From 257337f4fb2a7681ff769b202dd4f16ebb8e0725 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 25 Apr 2021 22:34:59 +0300 Subject: [PATCH 001/132] [WIP] Refactor optimization --- .../kscience/kmath/functions/integrate.kt | 4 +- .../kmath/functions/matrixIntegration.kt | 4 +- .../kmath/commons/integration/CMIntegrator.kt | 13 +- .../integration/GaussRuleIntegrator.kt | 4 +- .../commons/optimization/CMOptimization.kt | 145 ++-- .../kmath/commons/optimization/cmFit.kt | 20 +- .../commons/optimization/OptimizeTest.kt | 4 +- .../kmath/data/XYErrorColumnarData.kt | 33 + .../kscience/kmath/data/XYZColumnarData.kt | 2 +- .../expressions/DifferentiableExpression.kt | 2 +- .../kmath/expressions/SymbolIndexer.kt | 10 + .../space/kscience/kmath/linear/symmetric.kt | 34 + .../space/kscience/kmath/misc/Featured.kt | 37 + .../kmath/structures/BufferAccessor2D.kt | 2 +- .../kmath/structures/DoubleBufferField.kt | 10 +- .../space/kscience/kmath/real/RealVector.kt | 11 +- .../kmath/integration/GaussIntegrator.kt | 12 +- .../kscience/kmath/integration/Integrand.kt | 7 +- .../kscience/kmath/integration/Integrator.kt | 2 +- .../integration/MultivariateIntegrand.kt | 18 +- .../kmath/integration/UnivariateIntegrand.kt | 24 +- .../kmath/integration/GaussIntegralTest.kt | 4 +- .../optimization/FunctionOptimization.kt | 163 ++-- .../NoDerivFunctionOptimization.kt | 74 -- .../kmath/optimization/Optimization.kt | 49 -- .../kmath/optimization/OptimizationProblem.kt | 46 ++ .../kscience/kmath/optimization/XYFit.kt | 2 +- .../minuit/AnalyticalGradientCalculator.kt | 61 ++ .../optimization/minuit/CombinedMinimizer.kt | 32 + .../minuit/CombinedMinimumBuilder.kt | 57 ++ .../optimization/minuit/ContoursError.kt | 150 ++++ .../minuit/DavidonErrorUpdator.kt | 45 ++ .../optimization/minuit/FunctionGradient.kt | 72 ++ .../optimization/minuit/FunctionMinimum.kt | 259 ++++++ .../optimization/minuit/GradientCalculator.kt | 41 + .../minuit/HessianGradientCalculator.kt | 137 ++++ .../minuit/InitialGradientCalculator.kt | 116 +++ .../kmath/optimization/minuit/MINOSResult.kt | 70 ++ .../kmath/optimization/minuit/MINUITFitter.kt | 205 +++++ .../kmath/optimization/minuit/MINUITPlugin.kt | 86 ++ .../kmath/optimization/minuit/MINUITUtils.kt | 121 +++ .../optimization/minuit/MinimumBuilder.kt | 43 + .../kmath/optimization/minuit/MinimumError.kt | 155 ++++ .../minuit/MinimumErrorUpdator.kt | 33 + .../optimization/minuit/MinimumParameters.kt | 70 ++ .../kmath/optimization/minuit/MinimumSeed.kt | 64 ++ .../minuit/MinimumSeedGenerator.kt | 37 + .../kmath/optimization/minuit/MinimumState.kt | 104 +++ .../kmath/optimization/minuit/MinosError.kt | 219 +++++ .../optimization/minuit/MinuitParameter.kt | 314 ++++++++ .../minuit/MnAlgebraicSymMatrix.kt | 458 +++++++++++ .../optimization/minuit/MnApplication.kt | 554 +++++++++++++ .../kmath/optimization/minuit/MnContours.kt | 283 +++++++ .../minuit/MnCovarianceSqueeze.kt | 113 +++ .../kmath/optimization/minuit/MnCross.kt | 99 +++ .../kmath/optimization/minuit/MnEigen.kt | 50 ++ .../kmath/optimization/minuit/MnFcn.kt | 50 ++ .../optimization/minuit/MnFunctionCross.kt | 369 +++++++++ .../minuit/MnGlobalCorrelationCoeff.kt | 79 ++ .../kmath/optimization/minuit/MnHesse.kt | 371 +++++++++ .../kmath/optimization/minuit/MnLineSearch.kt | 204 +++++ .../optimization/minuit/MnMachinePrecision.kt | 71 ++ .../kmath/optimization/minuit/MnMigrad.kt | 136 ++++ .../kmath/optimization/minuit/MnMinimize.kt | 133 +++ .../kmath/optimization/minuit/MnMinos.kt | 379 +++++++++ .../kmath/optimization/minuit/MnParabola.kt | 55 ++ .../optimization/minuit/MnParabolaFactory.kt | 58 ++ .../optimization/minuit/MnParabolaPoint.kt | 30 + .../optimization/minuit/MnParameterScan.kt | 113 +++ .../kmath/optimization/minuit/MnPlot.kt | 438 ++++++++++ .../kmath/optimization/minuit/MnPosDef.kt | 89 +++ .../kmath/optimization/minuit/MnPrint.kt | 387 +++++++++ .../kmath/optimization/minuit/MnScan.kt | 181 +++++ .../optimization/minuit/MnSeedGenerator.kt | 107 +++ .../kmath/optimization/minuit/MnSimplex.kt | 138 ++++ .../kmath/optimization/minuit/MnStrategy.kt | 310 +++++++ .../optimization/minuit/MnUserCovariance.kt | 147 ++++ .../kmath/optimization/minuit/MnUserFcn.kt | 30 + .../minuit/MnUserParameterState.kt | 756 ++++++++++++++++++ .../optimization/minuit/MnUserParameters.kt | 402 ++++++++++ .../minuit/MnUserTransformation.kt | 390 +++++++++ .../kmath/optimization/minuit/MnUtils.kt | 147 ++++ .../minuit/ModularFunctionMinimizer.kt | 72 ++ .../minuit/NegativeG2LineSearch.kt | 80 ++ .../minuit/Numerical2PGradientCalculator.kt | 122 +++ .../kmath/optimization/minuit/Range.kt | 32 + .../kmath/optimization/minuit/ScanBuilder.kt | 58 ++ .../optimization/minuit/ScanMinimizer.kt | 36 + .../optimization/minuit/SimplexBuilder.kt | 179 +++++ .../optimization/minuit/SimplexMinimizer.kt | 43 + .../optimization/minuit/SimplexParameters.kt | 85 ++ .../minuit/SimplexSeedGenerator.kt | 52 ++ .../minuit/SinParameterTransformation.kt | 48 ++ .../minuit/SqrtLowParameterTransformation.kt | 43 + .../minuit/SqrtUpParameterTransformation.kt | 43 + .../minuit/VariableMetricBuilder.kt | 137 ++++ .../minuit/VariableMetricEDMEstimator.kt | 31 + .../minuit/VariableMetricMinimizer.kt | 43 + .../kmath/optimization/minuit/package-info.kt | 17 + .../kscience/kmath/optimization/qow/QowFit.kt | 380 +++++++++ 100 files changed, 11509 insertions(+), 346 deletions(-) create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/symmetric.kt create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt delete mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt delete mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/AnalyticalGradientCalculator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimizer.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimumBuilder.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ContoursError.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/DavidonErrorUpdator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionGradient.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionMinimum.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/GradientCalculator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/HessianGradientCalculator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/InitialGradientCalculator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINOSResult.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITFitter.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITPlugin.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITUtils.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumBuilder.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumError.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumErrorUpdator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumParameters.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeed.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeedGenerator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumState.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinosError.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinuitParameter.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnAlgebraicSymMatrix.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnApplication.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnContours.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCovarianceSqueeze.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCross.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnEigen.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFcn.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFunctionCross.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnGlobalCorrelationCoeff.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnHesse.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnLineSearch.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMachinePrecision.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMigrad.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinimize.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinos.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabola.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaFactory.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaPoint.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParameterScan.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPlot.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPosDef.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPrint.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnScan.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSeedGenerator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSimplex.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnStrategy.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserCovariance.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserFcn.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameterState.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameters.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserTransformation.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUtils.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ModularFunctionMinimizer.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/NegativeG2LineSearch.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Numerical2PGradientCalculator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Range.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanBuilder.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanMinimizer.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexBuilder.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexMinimizer.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexParameters.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexSeedGenerator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SinParameterTransformation.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtLowParameterTransformation.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtUpParameterTransformation.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricBuilder.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricEDMEstimator.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricMinimizer.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/package-info.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt index 6990e8c8f..7cdf7bef6 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt @@ -5,7 +5,7 @@ package space.kscience.kmath.functions -import space.kscience.kmath.integration.integrate +import space.kscience.kmath.integration.process import space.kscience.kmath.integration.value import space.kscience.kmath.operations.DoubleField import kotlin.math.pow @@ -15,7 +15,7 @@ fun main() { val function: UnivariateFunction = { x -> 3 * x.pow(2) + 2 * x + 1 } //get the result of the integration - val result = DoubleField.integrate(0.0..10.0, function = function) + val result = DoubleField.process(0.0..10.0, function = function) //the value is nullable because in some cases the integration could not succeed println(result.value) diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt index 8020df8f6..206ba3054 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt @@ -5,7 +5,7 @@ package space.kscience.kmath.functions -import space.kscience.kmath.integration.integrate +import space.kscience.kmath.integration.process import space.kscience.kmath.integration.value import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.nd @@ -24,7 +24,7 @@ fun main(): Unit = DoubleField { val function: (Double) -> StructureND = { x: Double -> 3 * number(x).pow(2) + 2 * diagonal(x) + 1 } //get the result of the integration - val result = integrate(0.0..10.0, function = function) + val result = process(0.0..10.0, function = function) //the value is nullable because in some cases the integration could not succeed println(result.value) diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt index 92bf86128..9da35a7c0 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt @@ -24,7 +24,7 @@ public class CMIntegrator( public class MinIterations(public val value: Int) : IntegrandFeature public class MaxIterations(public val value: Int) : IntegrandFeature - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand { val integrator = integratorBuilder(integrand) val maxCalls = integrand.getFeature()?.maxCalls ?: defaultMaxCalls val remainingCalls = maxCalls - integrand.calls @@ -32,11 +32,12 @@ public class CMIntegrator( ?: error("Integration range is not provided") val res = integrator.integrate(remainingCalls, integrand.function, range.start, range.endInclusive) - return integrand + - IntegrandValue(res) + - IntegrandAbsoluteAccuracy(integrator.absoluteAccuracy) + - IntegrandRelativeAccuracy(integrator.relativeAccuracy) + - IntegrandCallsPerformed(integrator.evaluations + integrand.calls) + return integrand.with( + IntegrandValue(res), + IntegrandAbsoluteAccuracy(integrator.absoluteAccuracy), + IntegrandRelativeAccuracy(integrator.relativeAccuracy), + IntegrandCallsPerformed(integrator.evaluations + integrand.calls) + ) } diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt index 1c9915563..1361b1079 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt @@ -16,7 +16,7 @@ public class GaussRuleIntegrator( private var type: GaussRule = GaussRule.LEGANDRE, ) : UnivariateIntegrator { - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand { val range = integrand.getFeature()?.range ?: error("Integration range is not provided") val integrator: GaussIntegrator = getIntegrator(range) @@ -76,7 +76,7 @@ public class GaussRuleIntegrator( numPoints: Int = 100, type: GaussRule = GaussRule.LEGANDRE, function: (Double) -> Double, - ): Double = GaussRuleIntegrator(numPoints, type).integrate( + ): Double = GaussRuleIntegrator(numPoints, type).process( UnivariateIntegrand(function, IntegrationRange(range)) ).value!! } diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt index cfb8c39be..db9ba6f21 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt @@ -14,10 +14,7 @@ import org.apache.commons.math3.optim.nonlinear.scalar.gradient.NonLinearConjuga import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.AbstractSimplex import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.NelderMeadSimplex import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.SimplexOptimizer -import space.kscience.kmath.expressions.DifferentiableExpression -import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.expressions.SymbolIndexer -import space.kscience.kmath.expressions.derivative +import space.kscience.kmath.expressions.* import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.optimization.* @@ -26,94 +23,98 @@ import kotlin.reflect.KClass public operator fun PointValuePair.component1(): DoubleArray = point public operator fun PointValuePair.component2(): Double = value +public class CMOptimizerFactory(public val optimizerBuilder: () -> MultivariateOptimizer) : OptimizationFeature +//public class CMOptimizerData(public val ) + @OptIn(UnstableKMathAPI::class) -public class CMOptimization( - override val symbols: List, -) : FunctionOptimization, NoDerivFunctionOptimization, SymbolIndexer, OptimizationFeature { +public class CMOptimization : Optimizer> { - private val optimizationData: HashMap, OptimizationData> = HashMap() - private var optimizerBuilder: (() -> MultivariateOptimizer)? = null - public var convergenceChecker: ConvergenceChecker = SimpleValueChecker( - DEFAULT_RELATIVE_TOLERANCE, - DEFAULT_ABSOLUTE_TOLERANCE, - DEFAULT_MAX_ITER - ) + override suspend fun process( + problem: FunctionOptimization + ): FunctionOptimization = withSymbols(problem.parameters){ + val cmOptimizer: MultivariateOptimizer = + problem.getFeature()?.optimizerBuilder?.invoke() ?: SimplexOptimizer() - override var maximize: Boolean - get() = optimizationData[GoalType::class] == GoalType.MAXIMIZE - set(value) { - optimizationData[GoalType::class] = if (value) GoalType.MAXIMIZE else GoalType.MINIMIZE + val convergenceChecker: ConvergenceChecker = SimpleValueChecker( + DEFAULT_RELATIVE_TOLERANCE, + DEFAULT_ABSOLUTE_TOLERANCE, + DEFAULT_MAX_ITER + ) + + val optimizationData: HashMap, OptimizationData> = HashMap() + + fun addOptimizationData(data: OptimizationData) { + optimizationData[data::class] = data } - - public fun addOptimizationData(data: OptimizationData) { - optimizationData[data::class] = data - } - - init { addOptimizationData(MaxEval.unlimited()) - } + addOptimizationData(InitialGuess(problem.initialGuess.toDoubleArray())) - public fun exportOptimizationData(): List = optimizationData.values.toList() + fun exportOptimizationData(): List = optimizationData.values.toList() - public override fun initialGuess(map: Map): Unit { - addOptimizationData(InitialGuess(map.toDoubleArray())) - } - public override fun function(expression: Expression): Unit { - val objectiveFunction = ObjectiveFunction { - val args = it.toMap() - expression(args) + /** + * Register no-deriv function instead of differentiable function + */ + /** + * Register no-deriv function instead of differentiable function + */ + fun noDerivFunction(expression: Expression): Unit { + val objectiveFunction = ObjectiveFunction { + val args = problem.initialGuess + it.toMap() + expression(args) + } + addOptimizationData(objectiveFunction) } - addOptimizationData(objectiveFunction) - } - public override fun diffFunction(expression: DifferentiableExpression>) { - function(expression) - val gradientFunction = ObjectiveFunctionGradient { - val args = it.toMap() - DoubleArray(symbols.size) { index -> - expression.derivative(symbols[index])(args) + public override fun function(expression: DifferentiableExpression>) { + noDerivFunction(expression) + val gradientFunction = ObjectiveFunctionGradient { + val args = startingPoint + it.toMap() + DoubleArray(symbols.size) { index -> + expression.derivative(symbols[index])(args) + } + } + addOptimizationData(gradientFunction) + if (optimizerBuilder == null) { + optimizerBuilder = { + NonLinearConjugateGradientOptimizer( + NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES, + convergenceChecker + ) + } } } - addOptimizationData(gradientFunction) - if (optimizerBuilder == null) { - optimizerBuilder = { - NonLinearConjugateGradientOptimizer( - NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES, - convergenceChecker - ) + + public fun simplex(simplex: AbstractSimplex) { + addOptimizationData(simplex) + //Set optimization builder to simplex if it is not present + if (optimizerBuilder == null) { + optimizerBuilder = { SimplexOptimizer(convergenceChecker) } } } - } - public fun simplex(simplex: AbstractSimplex) { - addOptimizationData(simplex) - //Set optimization builder to simplex if it is not present - if (optimizerBuilder == null) { - optimizerBuilder = { SimplexOptimizer(convergenceChecker) } + public fun simplexSteps(steps: Map) { + simplex(NelderMeadSimplex(steps.toDoubleArray())) } - } - public fun simplexSteps(steps: Map) { - simplex(NelderMeadSimplex(steps.toDoubleArray())) - } + public fun goal(goalType: GoalType) { + addOptimizationData(goalType) + } - public fun goal(goalType: GoalType) { - addOptimizationData(goalType) - } + public fun optimizer(block: () -> MultivariateOptimizer) { + optimizerBuilder = block + } - public fun optimizer(block: () -> MultivariateOptimizer) { - optimizerBuilder = block - } + override fun update(result: OptimizationResult) { + initialGuess(result.point) + } - override fun update(result: OptimizationResult) { - initialGuess(result.point) - } - - override fun optimize(): OptimizationResult { - val optimizer = optimizerBuilder?.invoke() ?: error("Optimizer not defined") - val (point, value) = optimizer.optimize(*optimizationData.values.toTypedArray()) - return OptimizationResult(point.toMap(), value, setOf(this)) + override suspend fun optimize(): OptimizationResult { + val optimizer = optimizerBuilder?.invoke() ?: error("Optimizer not defined") + val (point, value) = optimizer.optimize(*optimizationData.values.toTypedArray()) + return OptimizationResult(point.toMap(), value) + } + return@withSymbols TODO() } public companion object : OptimizationProblemFactory { diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt index 13b5c73f4..12d924063 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt @@ -10,10 +10,7 @@ import space.kscience.kmath.commons.expressions.DerivativeStructureField import space.kscience.kmath.expressions.DifferentiableExpression import space.kscience.kmath.expressions.Expression import space.kscience.kmath.misc.Symbol -import space.kscience.kmath.optimization.FunctionOptimization -import space.kscience.kmath.optimization.OptimizationResult -import space.kscience.kmath.optimization.noDerivOptimizeWith -import space.kscience.kmath.optimization.optimizeWith +import space.kscience.kmath.optimization.* import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.asBuffer @@ -46,20 +43,25 @@ public fun FunctionOptimization.Companion.chiSquared( /** * Optimize expression without derivatives */ -public fun Expression.optimize( +public suspend fun Expression.optimize( vararg symbols: Symbol, configuration: CMOptimization.() -> Unit, -): OptimizationResult = noDerivOptimizeWith(CMOptimization, symbols = symbols, configuration) +): OptimizationResult { + require(symbols.isNotEmpty()) { "Must provide a list of symbols for optimization" } + val problem = CMOptimization(symbols.toList(), configuration) + problem.noDerivFunction(this) + return problem.optimize() +} /** * Optimize differentiable expression */ -public fun DifferentiableExpression>.optimize( +public suspend fun DifferentiableExpression>.optimize( vararg symbols: Symbol, configuration: CMOptimization.() -> Unit, ): OptimizationResult = optimizeWith(CMOptimization, symbols = symbols, configuration) -public fun DifferentiableExpression>.minimize( +public suspend fun DifferentiableExpression>.minimize( vararg startPoint: Pair, configuration: CMOptimization.() -> Unit = {}, ): OptimizationResult { @@ -67,7 +69,7 @@ public fun DifferentiableExpression>.minimize( return optimize(*symbols){ maximize = false initialGuess(startPoint.toMap()) - diffFunction(this@minimize) + function(this@minimize) configuration() } } \ No newline at end of file diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt index 716cd1b0f..9b92eaac5 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt @@ -24,7 +24,7 @@ internal class OptimizeTest { } @Test - fun testGradientOptimization() { + fun testGradientOptimization() = runBlocking{ val result = normal.optimize(x, y) { initialGuess(x to 1.0, y to 1.0) //no need to select optimizer. Gradient optimizer is used by default because gradients are provided by function @@ -34,7 +34,7 @@ internal class OptimizeTest { } @Test - fun testSimplexOptimization() { + fun testSimplexOptimization() = runBlocking{ val result = normal.optimize(x, y) { initialGuess(x to 1.0, y to 1.0) simplexSteps(x to 2.0, y to 0.5) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt new file mode 100644 index 000000000..ea98e88b1 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt @@ -0,0 +1,33 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.data + +import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.misc.Symbol.Companion.z +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.misc.symbol +import space.kscience.kmath.structures.Buffer + + +/** + * A [ColumnarData] with additional [Companion.yErr] column for an [Symbol.y] error + * Inherits [XYColumnarData]. + */ +@UnstableKMathAPI +public interface XYErrorColumnarData : XYColumnarData { + public val yErr: Buffer + + override fun get(symbol: Symbol): Buffer = when (symbol) { + Symbol.x -> x + Symbol.y -> y + Companion.yErr -> yErr + else -> error("A column for symbol $symbol not found") + } + + public companion object{ + public val yErr: Symbol by symbol + } +} \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt index d76a44e9e..2ae7233ec 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt @@ -10,7 +10,7 @@ import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.structures.Buffer /** - * A [XYColumnarData] with guaranteed [x], [y] and [z] columns designated by corresponding symbols. + * A [ColumnarData] with guaranteed [x], [y] and [z] columns designated by corresponding symbols. * Inherits [XYColumnarData]. */ @UnstableKMathAPI diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt index dbc1431b3..f2346f483 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt @@ -51,6 +51,6 @@ public abstract class FirstDerivativeExpression> : Differen /** * A factory that converts an expression in autodiff variables to a [DifferentiableExpression] */ -public fun interface AutoDiffProcessor, out R : Expression> { +public fun interface AutoDiffProcessor, out R : Expression> { public fun process(function: A.() -> I): DifferentiableExpression } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt index 738156975..ea72c5b9e 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt @@ -10,6 +10,7 @@ import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.Structure2D import space.kscience.kmath.structures.BufferFactory +import space.kscience.kmath.structures.DoubleBuffer import kotlin.jvm.JvmInline /** @@ -46,6 +47,11 @@ public interface SymbolIndexer { return symbols.indices.associate { symbols[it] to get(it) } } + public fun Point.toMap(): Map { + require(size == symbols.size) { "The input array size for indexer should be ${symbols.size} but $size found" } + return symbols.indices.associate { symbols[it] to get(it) } + } + public operator fun Structure2D.get(rowSymbol: Symbol, columnSymbol: Symbol): T = get(indexOf(rowSymbol), indexOf(columnSymbol)) @@ -55,6 +61,10 @@ public interface SymbolIndexer { public fun Map.toPoint(bufferFactory: BufferFactory): Point = bufferFactory(symbols.size) { getValue(symbols[it]) } + public fun Map.toPoint(): DoubleBuffer = + DoubleBuffer(symbols.size) { getValue(symbols[it]) } + + public fun Map.toDoubleArray(): DoubleArray = DoubleArray(symbols.size) { getValue(symbols[it]) } } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/symmetric.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/symmetric.kt new file mode 100644 index 000000000..04d9a9897 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/symmetric.kt @@ -0,0 +1,34 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.linear + +import space.kscience.kmath.structures.BufferAccessor2D +import space.kscience.kmath.structures.MutableBuffer + +public object SymmetricMatrixFeature : MatrixFeature + +/** + * Naive implementation of a symmetric matrix builder, that adds a [SymmetricMatrixFeature] tag. The resulting matrix contains + * full `size^2` number of elements, but caches elements during calls to save [builder] calls. [builder] is always called in the + * upper triangle region meaning that `i <= j` + */ +public fun > LS.buildSymmetricMatrix( + size: Int, + builder: (i: Int, j: Int) -> T, +): Matrix = BufferAccessor2D(size, size, MutableBuffer.Companion::boxing).run { + val cache = factory(size * size) { null } + buildMatrix(size, size) { i, j -> + val cached = cache[i, j] + if (cached == null) { + val value = if (i <= j) builder(i, j) else builder(j, i) + cache[i, j] = value + cache[j, i] = value + value + } else { + cached + } + } + SymmetricMatrixFeature +} \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt new file mode 100644 index 000000000..157ff980b --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt @@ -0,0 +1,37 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.misc + +import kotlin.reflect.KClass + +/** + * A entity that contains a set of features defined by their types + */ +public interface Featured { + public fun getFeature(type: KClass): T? +} + +/** + * A container for a set of features + */ +public class FeatureSet private constructor(public val features: Map, Any>) : Featured { + @Suppress("UNCHECKED_CAST") + override fun getFeature(type: KClass): T? = features[type] as? T + + public inline fun getFeature(): T? = getFeature(T::class) + + public fun with(feature: T, type: KClass = feature::class): FeatureSet = + FeatureSet(features + (type to feature)) + + public fun with(other: FeatureSet): FeatureSet = FeatureSet(features + other.features) + + public fun with(vararg otherFeatures: F): FeatureSet = + FeatureSet(features + otherFeatures.associateBy { it::class }) + + public companion object { + public fun of(vararg features: F): FeatureSet = FeatureSet(features.associateBy { it::class }) + } +} diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt index 352c75956..d29c54d46 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt @@ -13,7 +13,7 @@ import space.kscience.kmath.nd.as2D /** * A context that allows to operate on a [MutableBuffer] as on 2d array */ -internal class BufferAccessor2D( +internal class BufferAccessor2D( public val rowNum: Int, public val colNum: Int, val factory: MutableBufferFactory, diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt index 34b5e373b..e438995dd 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt @@ -5,8 +5,10 @@ package space.kscience.kmath.structures +import space.kscience.kmath.linear.Point import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.ExtendedFieldOperations +import space.kscience.kmath.operations.Norm import kotlin.math.* /** @@ -161,12 +163,16 @@ public object DoubleBufferFieldOperations : ExtendedFieldOperations, Double> { + override fun norm(arg: Point): Double = sqrt(arg.fold(0.0) { acc: Double, d: Double -> acc + d.pow(2) }) +} + /** * [ExtendedField] over [DoubleBuffer]. * * @property size the size of buffers to operate on. */ -public class DoubleBufferField(public val size: Int) : ExtendedField> { +public class DoubleBufferField(public val size: Int) : ExtendedField>, Norm, Double> { public override val zero: Buffer by lazy { DoubleBuffer(size) { 0.0 } } public override val one: Buffer by lazy { DoubleBuffer(size) { 1.0 } } @@ -274,4 +280,6 @@ public class DoubleBufferField(public val size: Int) : ExtendedField): Double = DoubleL2Norm.norm(arg) } diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt index d3867ea89..dbf81b133 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt @@ -8,11 +8,8 @@ package space.kscience.kmath.real import space.kscience.kmath.linear.Point import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.Norm -import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.* import space.kscience.kmath.structures.MutableBuffer.Companion.double -import space.kscience.kmath.structures.asBuffer -import space.kscience.kmath.structures.fold -import space.kscience.kmath.structures.indices import kotlin.math.pow import kotlin.math.sqrt @@ -105,8 +102,4 @@ public fun DoubleVector.sum(): Double { return res } -public object VectorL2Norm : Norm { - override fun norm(arg: DoubleVector): Double = sqrt(arg.fold(0.0) { acc: Double, d: Double -> acc + d.pow(2) }) -} - -public val DoubleVector.norm: Double get() = VectorL2Norm.norm(this) \ No newline at end of file +public val DoubleVector.norm: Double get() = DoubleL2Norm.norm(this) \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt index ae82a40be..e3a9e5a4a 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt @@ -50,7 +50,7 @@ public class GaussIntegrator( } } - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand = with(algebra) { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand = with(algebra) { val f = integrand.function val (points, weights) = buildRule(integrand) var res = zero @@ -63,7 +63,7 @@ public class GaussIntegrator( c = t - res - y res = t } - return integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + points.size) + return integrand.with(IntegrandValue(res),IntegrandCallsPerformed(integrand.calls + points.size)) } public companion object { @@ -80,17 +80,17 @@ public class GaussIntegrator( * * [UnivariateIntegrandRanges] - Set of ranges and number of points per range. Defaults to given [IntegrationRange] and [IntegrandMaxCalls] */ @UnstableKMathAPI -public fun Field.integrate( +public fun Field.process( vararg features: IntegrandFeature, function: (Double) -> T, -): UnivariateIntegrand = GaussIntegrator(this).integrate(UnivariateIntegrand(function, *features)) +): UnivariateIntegrand = GaussIntegrator(this).process(UnivariateIntegrand(function, *features)) /** * Use [GaussIntegrator.Companion.integrate] to integrate the function in the current algebra with given [range] and [numPoints] */ @UnstableKMathAPI -public fun Field.integrate( +public fun Field.process( range: ClosedRange, order: Int = 10, intervals: Int = 10, @@ -104,7 +104,7 @@ public fun Field.integrate( val ranges = UnivariateIntegrandRanges( (0 until intervals).map { i -> (rangeSize * i)..(rangeSize * (i + 1)) to order } ) - return GaussIntegrator(this).integrate( + return GaussIntegrator(this).process( UnivariateIntegrand( function, IntegrationRange(range), diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt index 1ff8e422e..1f45e825b 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt @@ -5,12 +5,15 @@ package space.kscience.kmath.integration +import space.kscience.kmath.misc.FeatureSet +import space.kscience.kmath.misc.Featured import kotlin.reflect.KClass public interface IntegrandFeature -public interface Integrand { - public fun getFeature(type: KClass): T? +public interface Integrand: Featured{ + public val features: FeatureSet + override fun getFeature(type: KClass): T? = features.getFeature(type) } public inline fun Integrand.getFeature(): T? = getFeature(T::class) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrator.kt index abe6ea5ff..1cf15b42f 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrator.kt @@ -12,5 +12,5 @@ public interface Integrator { /** * Runs one integration pass and return a new [Integrand] with a new set of features. */ - public fun integrate(integrand: I): I + public fun process(integrand: I): I } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt index 12d0ef0a6..b9c1589c0 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt @@ -6,27 +6,21 @@ package space.kscience.kmath.integration import space.kscience.kmath.linear.Point +import space.kscience.kmath.misc.FeatureSet import kotlin.reflect.KClass public class MultivariateIntegrand internal constructor( - private val features: Map, IntegrandFeature>, + override val features: FeatureSet, public val function: (Point) -> T, -) : Integrand { +) : Integrand - @Suppress("UNCHECKED_CAST") - override fun getFeature(type: KClass): T? = features[type] as? T - - public operator fun plus(pair: Pair, F>): MultivariateIntegrand = - MultivariateIntegrand(features + pair, function) - - public operator fun plus(feature: F): MultivariateIntegrand = - plus(feature::class to feature) -} +public fun MultivariateIntegrand.with(vararg newFeatures: IntegrandFeature): MultivariateIntegrand = + MultivariateIntegrand(features.with(*newFeatures), function) @Suppress("FunctionName") public fun MultivariateIntegrand( vararg features: IntegrandFeature, function: (Point) -> T, -): MultivariateIntegrand = MultivariateIntegrand(features.associateBy { it::class }, function) +): MultivariateIntegrand = MultivariateIntegrand(FeatureSet.of(*features), function) public val MultivariateIntegrand.value: T? get() = getFeature>()?.value diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index bcd5005c4..3fc5b4599 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -5,30 +5,24 @@ package space.kscience.kmath.integration +import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.UnstableKMathAPI import kotlin.jvm.JvmInline -import kotlin.reflect.KClass + public class UnivariateIntegrand internal constructor( - private val features: Map, IntegrandFeature>, + override val features: FeatureSet, public val function: (Double) -> T, -) : Integrand { +) : Integrand - @Suppress("UNCHECKED_CAST") - override fun getFeature(type: KClass): T? = features[type] as? T - - public operator fun plus(pair: Pair, F>): UnivariateIntegrand = - UnivariateIntegrand(features + pair, function) - - public operator fun plus(feature: F): UnivariateIntegrand = - plus(feature::class to feature) -} +public fun UnivariateIntegrand.with(vararg newFeatures: IntegrandFeature): UnivariateIntegrand = + UnivariateIntegrand(features.with(*newFeatures), function) @Suppress("FunctionName") public fun UnivariateIntegrand( function: (Double) -> T, vararg features: IntegrandFeature, -): UnivariateIntegrand = UnivariateIntegrand(features.associateBy { it::class }, function) +): UnivariateIntegrand = UnivariateIntegrand(FeatureSet.of(*features), function) public typealias UnivariateIntegrator = Integrator> @@ -46,7 +40,7 @@ public fun UnivariateIntegrator.integrate( range: ClosedRange, vararg features: IntegrandFeature, function: (Double) -> Double, -): Double = integrate( +): Double = process( UnivariateIntegrand(function, IntegrationRange(range), *features) ).value ?: error("Unexpected: no value after integration.") @@ -65,7 +59,7 @@ public fun UnivariateIntegrator.integrate( featureBuilder() add(IntegrationRange(range)) } - return integrate( + return process( UnivariateIntegrand(function, *features.toTypedArray()) ).value ?: error("Unexpected: no value after integration.") } diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt index 195711452..d1e452454 100644 --- a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt @@ -16,7 +16,7 @@ import kotlin.test.assertEquals class GaussIntegralTest { @Test fun gaussSin() { - val res = DoubleField.integrate(0.0..2 * PI) { x -> + val res = DoubleField.process(0.0..2 * PI) { x -> sin(x) } assertEquals(0.0, res.value!!, 1e-2) @@ -24,7 +24,7 @@ class GaussIntegralTest { @Test fun gaussUniform() { - val res = DoubleField.integrate(0.0..100.0) { x -> + val res = DoubleField.process(0.0..100.0) { x -> if(x in 30.0..50.0){ 1.0 } else { diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index 38f3038c2..12ccea1d8 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -9,86 +9,97 @@ import space.kscience.kmath.expressions.AutoDiffProcessor import space.kscience.kmath.expressions.DifferentiableExpression import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.ExpressionAlgebra +import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.Symbol import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.indices -/** - * A likelihood function optimization problem with provided derivatives - */ -public interface FunctionOptimization : Optimization { - /** - * The optimization direction. If true search for function maximum, if false, search for the minimum - */ - public var maximize: Boolean - /** - * Define the initial guess for the optimization problem - */ - public fun initialGuess(map: Map) +public class FunctionOptimization( + override val features: FeatureSet, + public val expression: DifferentiableExpression>, + public val initialGuess: Map, + public val parameters: Collection, + public val maximize: Boolean, +) : OptimizationProblem - /** - * Set a differentiable expression as objective function as function and gradient provider - */ - public fun diffFunction(expression: DifferentiableExpression>) - - public companion object { - /** - * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation - */ - public fun chiSquared( - autoDiff: AutoDiffProcessor>, - x: Buffer, - y: Buffer, - yErr: Buffer, - model: A.(I) -> I, - ): DifferentiableExpression> where A : ExtendedField, A : ExpressionAlgebra { - require(x.size == y.size) { "X and y buffers should be of the same size" } - require(y.size == yErr.size) { "Y and yErr buffer should of the same size" } - - return autoDiff.process { - var sum = zero - - x.indices.forEach { - val xValue = const(x[it]) - val yValue = const(y[it]) - val yErrValue = const(yErr[it]) - val modelValue = model(xValue) - sum += ((yValue - modelValue) / yErrValue).pow(2) - } - - sum - } - } - } -} - -/** - * Define a chi-squared-based objective function - */ -public fun FunctionOptimization.chiSquared( - autoDiff: AutoDiffProcessor>, - x: Buffer, - y: Buffer, - yErr: Buffer, - model: A.(I) -> I, -) where A : ExtendedField, A : ExpressionAlgebra { - val chiSquared = FunctionOptimization.chiSquared(autoDiff, x, y, yErr, model) - diffFunction(chiSquared) - maximize = false -} - -/** - * Optimize differentiable expression using specific [OptimizationProblemFactory] - */ -public fun > DifferentiableExpression>.optimizeWith( - factory: OptimizationProblemFactory, - vararg symbols: Symbol, - configuration: F.() -> Unit, -): OptimizationResult { - require(symbols.isNotEmpty()) { "Must provide a list of symbols for optimization" } - val problem = factory(symbols.toList(), configuration) - problem.diffFunction(this) - return problem.optimize() -} +// +///** +// * A likelihood function optimization problem with provided derivatives +// */ +//public interface FunctionOptimizationBuilder { +// /** +// * The optimization direction. If true search for function maximum, if false, search for the minimum +// */ +// public var maximize: Boolean +// +// /** +// * Define the initial guess for the optimization problem +// */ +// public fun initialGuess(map: Map) +// +// /** +// * Set a differentiable expression as objective function as function and gradient provider +// */ +// public fun function(expression: DifferentiableExpression>) +// +// public companion object { +// /** +// * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation +// */ +// public fun chiSquared( +// autoDiff: AutoDiffProcessor>, +// x: Buffer, +// y: Buffer, +// yErr: Buffer, +// model: A.(I) -> I, +// ): DifferentiableExpression> where A : ExtendedField, A : ExpressionAlgebra { +// require(x.size == y.size) { "X and y buffers should be of the same size" } +// require(y.size == yErr.size) { "Y and yErr buffer should of the same size" } +// +// return autoDiff.process { +// var sum = zero +// +// x.indices.forEach { +// val xValue = const(x[it]) +// val yValue = const(y[it]) +// val yErrValue = const(yErr[it]) +// val modelValue = model(xValue) +// sum += ((yValue - modelValue) / yErrValue).pow(2) +// } +// +// sum +// } +// } +// } +//} +// +///** +// * Define a chi-squared-based objective function +// */ +//public fun FunctionOptimization.chiSquared( +// autoDiff: AutoDiffProcessor>, +// x: Buffer, +// y: Buffer, +// yErr: Buffer, +// model: A.(I) -> I, +//) where A : ExtendedField, A : ExpressionAlgebra { +// val chiSquared = FunctionOptimization.chiSquared(autoDiff, x, y, yErr, model) +// function(chiSquared) +// maximize = false +//} +// +///** +// * Optimize differentiable expression using specific [OptimizationProblemFactory] +// */ +//public suspend fun > DifferentiableExpression>.optimizeWith( +// factory: OptimizationProblemFactory, +// vararg symbols: Symbol, +// configuration: F.() -> Unit, +//): OptimizationResult { +// require(symbols.isNotEmpty()) { "Must provide a list of symbols for optimization" } +// val problem = factory(symbols.toList(), configuration) +// problem.function(this) +// return problem.optimize() +//} diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt deleted file mode 100644 index 67a21bf2a..000000000 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt +++ /dev/null @@ -1,74 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.optimization - -import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.misc.Symbol -import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.indices -import kotlin.math.pow - -/** - * A likelihood function optimization problem - */ -public interface NoDerivFunctionOptimization : Optimization { - /** - * The optimization direction. If true search for function maximum, if false, search for the minimum - */ - public var maximize: Boolean - - /** - * Define the initial guess for the optimization problem - */ - public fun initialGuess(map: Map) - - /** - * Set an objective function expression - */ - public fun function(expression: Expression) - - public companion object { - /** - * Generate a chi squared expression from given x-y-sigma model represented by an expression. Does not provide derivatives - */ - public fun chiSquared( - x: Buffer, - y: Buffer, - yErr: Buffer, - model: Expression, - xSymbol: Symbol = Symbol.x, - ): Expression { - require(x.size == y.size) { "X and y buffers should be of the same size" } - require(y.size == yErr.size) { "Y and yErr buffer should of the same size" } - - return Expression { arguments -> - x.indices.sumOf { - val xValue = x[it] - val yValue = y[it] - val yErrValue = yErr[it] - val modifiedArgs = arguments + (xSymbol to xValue) - val modelValue = model(modifiedArgs) - ((yValue - modelValue) / yErrValue).pow(2) - } - } - } - } -} - - -/** - * Optimize expression without derivatives using specific [OptimizationProblemFactory] - */ -public fun > Expression.noDerivOptimizeWith( - factory: OptimizationProblemFactory, - vararg symbols: Symbol, - configuration: F.() -> Unit, -): OptimizationResult { - require(symbols.isNotEmpty()) { "Must provide a list of symbols for optimization" } - val problem = factory(symbols.toList(), configuration) - problem.function(this) - return problem.optimize() -} diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt deleted file mode 100644 index 3b9868815..000000000 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt +++ /dev/null @@ -1,49 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.optimization - -import space.kscience.kmath.misc.Symbol - -public interface OptimizationFeature - -public class OptimizationResult( - public val point: Map, - public val value: T, - public val features: Set = emptySet(), -) { - override fun toString(): String { - return "OptimizationResult(point=$point, value=$value)" - } -} - -public operator fun OptimizationResult.plus( - feature: OptimizationFeature, -): OptimizationResult = OptimizationResult(point, value, features + feature) - -/** - * An optimization problem builder over [T] variables - */ -public interface Optimization { - - /** - * Update the problem from previous optimization run - */ - public fun update(result: OptimizationResult) - - /** - * Make an optimization run - */ - public fun optimize(): OptimizationResult -} - -public fun interface OptimizationProblemFactory> { - public fun build(symbols: List): P -} - -public operator fun > OptimizationProblemFactory.invoke( - symbols: List, - block: P.() -> Unit, -): P = build(symbols).apply(block) diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt new file mode 100644 index 000000000..9a5420be6 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt @@ -0,0 +1,46 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.optimization + +import space.kscience.kmath.misc.FeatureSet +import space.kscience.kmath.misc.Featured +import kotlin.reflect.KClass + +public interface OptimizationFeature + +public interface OptimizationProblem : Featured { + public val features: FeatureSet + override fun getFeature(type: KClass): T? = features.getFeature(type) +} + +public inline fun OptimizationProblem.getFeature(): T? = getFeature(T::class) + +//public class OptimizationResult( +// public val point: Map, +// public val value: T, +// public val features: Set = emptySet(), +//) { +// override fun toString(): String { +// return "OptimizationResult(point=$point, value=$value)" +// } +//} +// +//public operator fun OptimizationResult.plus( +// feature: OptimizationFeature, +//): OptimizationResult = OptimizationResult(point, value, features + feature) +//public fun interface OptimizationProblemFactory> { +// public fun build(symbols: List): P +//} +// +//public operator fun > OptimizationProblemFactory.invoke( +// symbols: List, +// block: P.() -> Unit, +//): P = build(symbols).apply(block) + +public interface Optimizer

{ + public suspend fun process(problem: P): P +} + diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt index f5cfa05e6..e4998c665 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt @@ -16,7 +16,7 @@ import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.Field @UnstableKMathAPI -public interface XYFit : Optimization { +public interface XYFit : OptimizationProblem { public val algebra: Field diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/AnalyticalGradientCalculator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/AnalyticalGradientCalculator.kt new file mode 100644 index 000000000..912fa22eb --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/AnalyticalGradientCalculator.kt @@ -0,0 +1,61 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction + +/** + * + * @version $Id$ + */ +internal class AnalyticalGradientCalculator(fcn: MultiFunction?, state: MnUserTransformation, checkGradient: Boolean) : + GradientCalculator { + private val function: MultiFunction? + private val theCheckGradient: Boolean + private val theTransformation: MnUserTransformation + fun checkGradient(): Boolean { + return theCheckGradient + } + + /** {@inheritDoc} */ + fun gradient(par: MinimumParameters): FunctionGradient { +// double[] grad = theGradCalc.gradientValue(theTransformation.andThen(par.vec()).data()); + val point: DoubleArray = theTransformation.transform(par.vec()).toArray() + require(!(function.getDimension() !== theTransformation.parameters().size())) { "Invalid parameter size" } + val v: RealVector = ArrayRealVector(par.vec().getDimension()) + for (i in 0 until par.vec().getDimension()) { + val ext: Int = theTransformation.extOfInt(i) + if (theTransformation.parameter(ext).hasLimits()) { + val dd: Double = theTransformation.dInt2Ext(i, par.vec().getEntry(i)) + v.setEntry(i, dd * function.derivValue(ext, point)) + } else { + v.setEntry(i, function.derivValue(ext, point)) + } + } + return FunctionGradient(v) + } + + /** {@inheritDoc} */ + fun gradient(par: MinimumParameters, grad: FunctionGradient?): FunctionGradient { + return gradient(par) + } + + init { + function = fcn + theTransformation = state + theCheckGradient = checkGradient + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimizer.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimizer.kt new file mode 100644 index 000000000..9363492ad --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimizer.kt @@ -0,0 +1,32 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal class CombinedMinimizer : ModularFunctionMinimizer() { + private val theMinBuilder: CombinedMinimumBuilder = CombinedMinimumBuilder() + private val theMinSeedGen: MnSeedGenerator = MnSeedGenerator() + override fun builder(): MinimumBuilder { + return theMinBuilder + } + + override fun seedGenerator(): MinimumSeedGenerator { + return theMinSeedGen + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimumBuilder.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimumBuilder.kt new file mode 100644 index 000000000..a2f0a644a --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimumBuilder.kt @@ -0,0 +1,57 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import space.kscience.kmath.optimization.minuit.MINUITPlugin + +/** + * + * @version $Id$ + */ +internal class CombinedMinimumBuilder : MinimumBuilder { + private val theSimplexMinimizer: SimplexMinimizer = SimplexMinimizer() + private val theVMMinimizer: VariableMetricMinimizer = VariableMetricMinimizer() + + /** {@inheritDoc} */ + override fun minimum( + fcn: MnFcn?, + gc: GradientCalculator?, + seed: MinimumSeed?, + strategy: MnStrategy?, + maxfcn: Int, + toler: Double + ): FunctionMinimum { + val min: FunctionMinimum = theVMMinimizer.minimize(fcn!!, gc, seed, strategy, maxfcn, toler) + if (!min.isValid()) { + MINUITPlugin.logStatic("CombinedMinimumBuilder: migrad method fails, will try with simplex method first.") + val str = MnStrategy(2) + val min1: FunctionMinimum = theSimplexMinimizer.minimize(fcn, gc, seed, str, maxfcn, toler) + if (!min1.isValid()) { + MINUITPlugin.logStatic("CombinedMinimumBuilder: both migrad and simplex method fail.") + return min1 + } + val seed1: MinimumSeed = theVMMinimizer.seedGenerator().generate(fcn, gc, min1.userState(), str) + val min2: FunctionMinimum = theVMMinimizer.minimize(fcn, gc, seed1, str, maxfcn, toler) + if (!min2.isValid()) { + MINUITPlugin.logStatic("CombinedMinimumBuilder: both migrad and method fails also at 2nd attempt.") + MINUITPlugin.logStatic("CombinedMinimumBuilder: return simplex minimum.") + return min1 + } + return min2 + } + return min + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ContoursError.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ContoursError.kt new file mode 100644 index 000000000..214d94c80 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ContoursError.kt @@ -0,0 +1,150 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * ContoursError class. + * + * @author Darksnake + * @version $Id$ + */ +class ContoursError internal constructor( + private val theParX: Int, + private val theParY: Int, + points: List, + xmnos: MinosError, + ymnos: MinosError, + nfcn: Int +) { + private val theNFcn: Int + private val thePoints: List = points + private val theXMinos: MinosError + private val theYMinos: MinosError + + /** + * + * nfcn. + * + * @return a int. + */ + fun nfcn(): Int { + return theNFcn + } + + /** + * + * points. + * + * @return a [List] object. + */ + fun points(): List { + return thePoints + } + + /** + * {@inheritDoc} + */ + override fun toString(): String { + return MnPrint.toString(this) + } + + /** + * + * xMinosError. + * + * @return a [hep.dataforge.MINUIT.MinosError] object. + */ + fun xMinosError(): MinosError { + return theXMinos + } + + /** + * + * xRange. + * + * @return + */ + fun xRange(): Range { + return theXMinos.range() + } + + /** + * + * xmin. + * + * @return a double. + */ + fun xmin(): Double { + return theXMinos.min() + } + + /** + * + * xpar. + * + * @return a int. + */ + fun xpar(): Int { + return theParX + } + + /** + * + * yMinosError. + * + * @return a [hep.dataforge.MINUIT.MinosError] object. + */ + fun yMinosError(): MinosError { + return theYMinos + } + + /** + * + * yRange. + * + * @return + */ + fun yRange(): Range { + return theYMinos.range() + } + + /** + * + * ymin. + * + * @return a double. + */ + fun ymin(): Double { + return theYMinos.min() + } + + /** + * + * ypar. + * + * @return a int. + */ + fun ypar(): Int { + return theParY + } + + init { + theXMinos = xmnos + theYMinos = ymnos + theNFcn = nfcn + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/DavidonErrorUpdator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/DavidonErrorUpdator.kt new file mode 100644 index 000000000..9eb2443e4 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/DavidonErrorUpdator.kt @@ -0,0 +1,45 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.RealVector +import ru.inr.mass.minuit.* + +/** + * + * @version $Id$ + */ +internal class DavidonErrorUpdator : MinimumErrorUpdator { + /** {@inheritDoc} */ + fun update(s0: MinimumState, p1: MinimumParameters, g1: FunctionGradient): MinimumError { + val V0: MnAlgebraicSymMatrix = s0.error().invHessian() + val dx: RealVector = MnUtils.sub(p1.vec(), s0.vec()) + val dg: RealVector = MnUtils.sub(g1.getGradient(), s0.gradient().getGradient()) + val delgam: Double = MnUtils.innerProduct(dx, dg) + val gvg: Double = MnUtils.similarity(dg, V0) + val vg: RealVector = MnUtils.mul(V0, dg) + var Vupd: MnAlgebraicSymMatrix = + MnUtils.sub(MnUtils.div(MnUtils.outerProduct(dx), delgam), MnUtils.div(MnUtils.outerProduct(vg), gvg)) + if (delgam > gvg) { + Vupd = MnUtils.add(Vupd, + MnUtils.mul(MnUtils.outerProduct(MnUtils.sub(MnUtils.div(dx, delgam), MnUtils.div(vg, gvg))), gvg)) + } + val sum_upd: Double = MnUtils.absoluteSumOfElements(Vupd) + Vupd = MnUtils.add(Vupd, V0) + val dcov: Double = 0.5 * (s0.error().dcovar() + sum_upd / MnUtils.absoluteSumOfElements(Vupd)) + return MinimumError(Vupd, dcov) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionGradient.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionGradient.kt new file mode 100644 index 000000000..a0866d916 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionGradient.kt @@ -0,0 +1,72 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector + +/** + * + * @version $Id$ + */ +class FunctionGradient { + private var theAnalytical = false + private var theG2ndDerivative: RealVector + private var theGStepSize: RealVector + private var theGradient: RealVector + private var theValid = false + + constructor(n: Int) { + theGradient = ArrayRealVector(n) + theG2ndDerivative = ArrayRealVector(n) + theGStepSize = ArrayRealVector(n) + } + + constructor(grd: RealVector) { + theGradient = grd + theG2ndDerivative = ArrayRealVector(grd.getDimension()) + theGStepSize = ArrayRealVector(grd.getDimension()) + theValid = true + theAnalytical = true + } + + constructor(grd: RealVector, g2: RealVector, gstep: RealVector) { + theGradient = grd + theG2ndDerivative = g2 + theGStepSize = gstep + theValid = true + theAnalytical = false + } + + fun getGradient(): RealVector { + return theGradient + } + + fun getGradientDerivative(): RealVector { + return theG2ndDerivative + } + + fun getStep(): RealVector { + return theGStepSize + } + + fun isAnalytical(): Boolean { + return theAnalytical + } + + fun isValid(): Boolean { + return theValid + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionMinimum.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionMinimum.kt new file mode 100644 index 000000000..56908f00d --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionMinimum.kt @@ -0,0 +1,259 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.minuit.* + +/** + * Result of the minimization. + * + * + * The FunctionMinimum is the output of the minimizers and contains the + * minimization result. The methods + * + * * userState(), + * * userParameters() and + * * userCovariance() + * + * are provided. These can be used as new input to a new minimization after some + * manipulation. The parameters and/or the FunctionMinimum can be printed using + * the toString() method or the MnPrint class. + * + * @author Darksnake + */ +class FunctionMinimum { + private var theAboveMaxEdm = false + private var theErrorDef: Double + private var theReachedCallLimit = false + private var theSeed: MinimumSeed + private var theStates: MutableList + private var theUserState: MnUserParameterState + + internal constructor(seed: MinimumSeed, up: Double) { + theSeed = seed + theStates = ArrayList() + theStates.add(MinimumState(seed.parameters(), + seed.error(), + seed.gradient(), + seed.parameters().fval(), + seed.nfcn())) + theErrorDef = up + theUserState = MnUserParameterState() + } + + internal constructor(seed: MinimumSeed, states: MutableList, up: Double) { + theSeed = seed + theStates = states + theErrorDef = up + theUserState = MnUserParameterState() + } + + internal constructor(seed: MinimumSeed, states: MutableList, up: Double, x: MnReachedCallLimit?) { + theSeed = seed + theStates = states + theErrorDef = up + theReachedCallLimit = true + theUserState = MnUserParameterState() + } + + internal constructor(seed: MinimumSeed, states: MutableList, up: Double, x: MnAboveMaxEdm?) { + theSeed = seed + theStates = states + theErrorDef = up + theAboveMaxEdm = true + theReachedCallLimit = false + theUserState = MnUserParameterState() + } + + // why not + fun add(state: MinimumState) { + theStates.add(state) + } + + /** + * returns the expected vertical distance to the minimum (EDM) + * + * @return a double. + */ + fun edm(): Double { + return lastState().edm() + } + + fun error(): MinimumError { + return lastState().error() + } + + /** + * + * + * errorDef. + * + * @return a double. + */ + fun errorDef(): Double { + return theErrorDef + } + + /** + * Returns the function value at the minimum. + * + * @return a double. + */ + fun fval(): Double { + return lastState().fval() + } + + fun grad(): FunctionGradient { + return lastState().gradient() + } + + fun hasAccurateCovar(): Boolean { + return state().error().isAccurate() + } + + fun hasCovariance(): Boolean { + return state().error().isAvailable() + } + + fun hasMadePosDefCovar(): Boolean { + return state().error().isMadePosDef() + } + + fun hasPosDefCovar(): Boolean { + return state().error().isPosDef() + } + + fun hasReachedCallLimit(): Boolean { + return theReachedCallLimit + } + + fun hasValidCovariance(): Boolean { + return state().error().isValid() + } + + fun hasValidParameters(): Boolean { + return state().parameters().isValid() + } + + fun hesseFailed(): Boolean { + return state().error().hesseFailed() + } + + fun isAboveMaxEdm(): Boolean { + return theAboveMaxEdm + } + + /** + * In general, if this returns true, the minimizer did find a + * minimum without running into troubles. However, in some cases a minimum + * cannot be found, then the return value will be false. + * Reasons for the minimization to fail are + * + * * the number of allowed function calls has been exhausted + * * the minimizer could not improve the values of the parameters (and + * knowing that it has not converged yet) + * * a problem with the calculation of the covariance matrix + * + * Additional methods for the analysis of the state at the minimum are + * provided. + * + * @return a boolean. + */ + fun isValid(): Boolean { + return state().isValid() && !isAboveMaxEdm() && !hasReachedCallLimit() + } + + private fun lastState(): MinimumState { + return theStates[theStates.size - 1] + } + // forward interface of last state + /** + * returns the total number of function calls during the minimization. + * + * @return a int. + */ + fun nfcn(): Int { + return lastState().nfcn() + } + + fun parameters(): MinimumParameters { + return lastState().parameters() + } + + fun seed(): MinimumSeed { + return theSeed + } + + fun state(): MinimumState { + return lastState() + } + + fun states(): List { + return theStates + } + + /** + * {@inheritDoc} + * + * @return + */ + override fun toString(): String { + return MnPrint.toString(this) + } + + /** + * + * + * userCovariance. + * + * @return a [hep.dataforge.MINUIT.MnUserCovariance] object. + */ + fun userCovariance(): MnUserCovariance { + if (!theUserState.isValid()) { + theUserState = MnUserParameterState(state(), errorDef(), seed().trafo()) + } + return theUserState.covariance() + } + + /** + * + * + * userParameters. + * + * @return a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + fun userParameters(): MnUserParameters { + if (!theUserState.isValid()) { + theUserState = MnUserParameterState(state(), errorDef(), seed().trafo()) + } + return theUserState.parameters() + } + + /** + * user representation of state at minimum + * + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun userState(): MnUserParameterState { + if (!theUserState.isValid()) { + theUserState = MnUserParameterState(state(), errorDef(), seed().trafo()) + } + return theUserState + } + + internal class MnAboveMaxEdm + internal class MnReachedCallLimit +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/GradientCalculator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/GradientCalculator.kt new file mode 100644 index 000000000..379de1b6d --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/GradientCalculator.kt @@ -0,0 +1,41 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +interface GradientCalculator { + /** + * + * gradient. + * + * @param par a [hep.dataforge.MINUIT.MinimumParameters] object. + * @return a [hep.dataforge.MINUIT.FunctionGradient] object. + */ + fun gradient(par: MinimumParameters?): FunctionGradient + + /** + * + * gradient. + * + * @param par a [hep.dataforge.MINUIT.MinimumParameters] object. + * @param grad a [hep.dataforge.MINUIT.FunctionGradient] object. + * @return a [hep.dataforge.MINUIT.FunctionGradient] object. + */ + fun gradient(par: MinimumParameters?, grad: FunctionGradient?): FunctionGradient +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/HessianGradientCalculator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/HessianGradientCalculator.kt new file mode 100644 index 000000000..150d192f9 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/HessianGradientCalculator.kt @@ -0,0 +1,137 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector +import ru.inr.mass.minuit.* + +/** + * + * @version $Id$ + */ +internal class HessianGradientCalculator(fcn: MnFcn, par: MnUserTransformation, stra: MnStrategy) : GradientCalculator { + private val theFcn: MnFcn = fcn + private val theStrategy: MnStrategy + private val theTransformation: MnUserTransformation + fun deltaGradient(par: MinimumParameters, gradient: FunctionGradient): Pair { + require(par.isValid()) { "parameters are invalid" } + val x: RealVector = par.vec().copy() + val grd: RealVector = gradient.getGradient().copy() + val g2: RealVector = gradient.getGradientDerivative() + val gstep: RealVector = gradient.getStep() + val fcnmin: Double = par.fval() + // std::cout<<"fval: "< optstp) { + d = optstp + } + if (d < dmin) { + d = dmin + } + var chgold = 10000.0 + var dgmin = 0.0 + var grdold = 0.0 + var grdnew = 0.0 + for (j in 0 until ncycle()) { + x.setEntry(i, xtf + d) + val fs1: Double = theFcn.value(x) + x.setEntry(i, xtf - d) + val fs2: Double = theFcn.value(x) + x.setEntry(i, xtf) + // double sag = 0.5*(fs1+fs2-2.*fcnmin); + grdold = grd.getEntry(i) + grdnew = (fs1 - fs2) / (2.0 * d) + dgmin = precision().eps() * (abs(fs1) + abs(fs2)) / d + if (abs(grdnew) < precision().eps()) { + break + } + val change: Double = abs((grdold - grdnew) / grdnew) + if (change > chgold && j > 1) { + break + } + chgold = change + grd.setEntry(i, grdnew) + if (change < 0.05) { + break + } + if (abs(grdold - grdnew) < dgmin) { + break + } + if (d < dmin) { + break + } + d *= 0.2 + } + dgrd.setEntry(i, max(dgmin, abs(grdold - grdnew))) + } + return Pair(FunctionGradient(grd, g2, gstep), dgrd) + } + + fun fcn(): MnFcn { + return theFcn + } + + fun gradTolerance(): Double { + return strategy().gradientTolerance() + } + + /** {@inheritDoc} */ + fun gradient(par: MinimumParameters): FunctionGradient { + val gc = InitialGradientCalculator(theFcn, theTransformation, theStrategy) + val gra: FunctionGradient = gc.gradient(par) + return gradient(par, gra) + } + + /** {@inheritDoc} */ + fun gradient(par: MinimumParameters, gradient: FunctionGradient): FunctionGradient { + return deltaGradient(par, gradient).getFirst() + } + + fun ncycle(): Int { + return strategy().hessianGradientNCycles() + } + + fun precision(): MnMachinePrecision { + return theTransformation.precision() + } + + fun stepTolerance(): Double { + return strategy().gradientStepTolerance() + } + + fun strategy(): MnStrategy { + return theStrategy + } + + fun trafo(): MnUserTransformation { + return theTransformation + } + + init { + theTransformation = par + theStrategy = stra + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/InitialGradientCalculator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/InitialGradientCalculator.kt new file mode 100644 index 000000000..794556414 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/InitialGradientCalculator.kt @@ -0,0 +1,116 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector +import ru.inr.mass.minuit.* + +/** + * Calculating derivatives via finite differences + * @version $Id$ + */ +internal class InitialGradientCalculator(fcn: MnFcn, par: MnUserTransformation, stra: MnStrategy) { + private val theFcn: MnFcn = fcn + private val theStrategy: MnStrategy + private val theTransformation: MnUserTransformation + fun fcn(): MnFcn { + return theFcn + } + + fun gradTolerance(): Double { + return strategy().gradientTolerance() + } + + fun gradient(par: MinimumParameters): FunctionGradient { + require(par.isValid()) { "Parameters are invalid" } + val n: Int = trafo().variableParameters() + require(n == par.vec().getDimension()) { "Parameters have invalid size" } + val gr: RealVector = ArrayRealVector(n) + val gr2: RealVector = ArrayRealVector(n) + val gst: RealVector = ArrayRealVector(n) + + // initial starting values + for (i in 0 until n) { + val exOfIn: Int = trafo().extOfInt(i) + val `var`: Double = par.vec().getEntry(i) //parameter value + val werr: Double = trafo().parameter(exOfIn).error() //parameter error + val sav: Double = trafo().int2ext(i, `var`) //value after transformation + var sav2 = sav + werr //value after transfomation + error + if (trafo().parameter(exOfIn).hasLimits()) { + if (trafo().parameter(exOfIn).hasUpperLimit() + && sav2 > trafo().parameter(exOfIn).upperLimit() + ) { + sav2 = trafo().parameter(exOfIn).upperLimit() + } + } + var var2: Double = trafo().ext2int(exOfIn, sav2) + val vplu = var2 - `var` + sav2 = sav - werr + if (trafo().parameter(exOfIn).hasLimits()) { + if (trafo().parameter(exOfIn).hasLowerLimit() + && sav2 < trafo().parameter(exOfIn).lowerLimit() + ) { + sav2 = trafo().parameter(exOfIn).lowerLimit() + } + } + var2 = trafo().ext2int(exOfIn, sav2) + val vmin = var2 - `var` + val dirin: Double = 0.5 * (abs(vplu) + abs(vmin)) + val g2: Double = 2.0 * theFcn.errorDef() / (dirin * dirin) + val gsmin: Double = 8.0 * precision().eps2() * (abs(`var`) + precision().eps2()) + var gstep: Double = max(gsmin, 0.1 * dirin) + val grd = g2 * dirin + if (trafo().parameter(exOfIn).hasLimits()) { + if (gstep > 0.5) { + gstep = 0.5 + } + } + gr.setEntry(i, grd) + gr2.setEntry(i, g2) + gst.setEntry(i, gstep) + } + return FunctionGradient(gr, gr2, gst) + } + + fun gradient(par: MinimumParameters, gra: FunctionGradient?): FunctionGradient { + return gradient(par) + } + + fun ncycle(): Int { + return strategy().gradientNCycles() + } + + fun precision(): MnMachinePrecision { + return theTransformation.precision() + } + + fun stepTolerance(): Double { + return strategy().gradientStepTolerance() + } + + fun strategy(): MnStrategy { + return theStrategy + } + + fun trafo(): MnUserTransformation { + return theTransformation + } + + init { + theTransformation = par + theStrategy = stra + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINOSResult.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINOSResult.kt new file mode 100644 index 000000000..c33994648 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINOSResult.kt @@ -0,0 +1,70 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package space.kscience.kmath.optimization.minuit + + +/** + * Контейнер для несимметричных оценок и доверительных интервалов + * + * @author Darksnake + * @version $Id: $Id + */ +class MINOSResult +/** + * + * Constructor for MINOSResult. + * + * @param list an array of [String] objects. + */(private val names: Array, private val errl: DoubleArray?, private val errp: DoubleArray?) : + IntervalEstimate { + fun getNames(): NameList { + return NameList(names) + } + + fun getInterval(parName: String?): Pair { + val index: Int = getNames().getNumberByName(parName) + return Pair(ValueFactory.of(errl!![index]), ValueFactory.of(errp!![index])) + } + + val cL: Double + get() = 0.68 + + /** {@inheritDoc} */ + fun print(out: PrintWriter) { + if (errl != null || errp != null) { + out.println() + out.println("Assymetrical errors:") + out.println() + out.println("Name\tLower\tUpper") + for (i in 0 until getNames().size()) { + out.print(getNames().get(i)) + out.print("\t") + if (errl != null) { + out.print(errl[i]) + } else { + out.print("---") + } + out.print("\t") + if (errp != null) { + out.print(errp[i]) + } else { + out.print("---") + } + out.println() + } + } + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITFitter.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITFitter.kt new file mode 100644 index 000000000..a26321249 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITFitter.kt @@ -0,0 +1,205 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ +package space.kscience.kmath.optimization.minuit + +import ru.inr.mass.minuit.* + +/** + * + * + * MINUITFitter class. + * + * @author Darksnake + * @version $Id: $Id + */ +class MINUITFitter : Fitter { + fun run(state: FitState, parentLog: History?, meta: Meta): FitResult { + val log = Chronicle("MINUIT", parentLog) + val action: String = meta.getString("action", TASK_RUN) + log.report("MINUIT fit engine started action '{}'", action) + return when (action) { + TASK_COVARIANCE -> runHesse(state, log, meta) + TASK_SINGLE, TASK_RUN -> runFit(state, log, meta) + else -> throw IllegalArgumentException("Unknown task") + } + } + + @NotNull + fun getName(): String { + return MINUIT_ENGINE_NAME + } + + /** + * + * + * runHesse. + * + * @param state a [hep.dataforge.stat.fit.FitState] object. + * @param log + * @return a [FitResult] object. + */ + fun runHesse(state: FitState, log: History, meta: Meta?): FitResult { + val strategy: Int + strategy = Global.INSTANCE.getInt("MINUIT_STRATEGY", 2) + log.report("Generating errors using MnHesse 2-nd order gradient calculator.") + val fcn: MultiFunction + val fitPars: Array = Fitter.Companion.getFitPars(state, meta) + val pars: ParamSet = state.getParameters() + fcn = MINUITUtils.getFcn(state, pars, fitPars) + val hesse = MnHesse(strategy) + val mnState: MnUserParameterState = hesse.calculate(fcn, MINUITUtils.getFitParameters(pars, fitPars)) + val allPars: ParamSet = pars.copy() + for (fitPar in fitPars) { + allPars.setParValue(fitPar, mnState.value(fitPar)) + allPars.setParError(fitPar, mnState.error(fitPar)) + } + val newState: FitState.Builder = state.edit() + newState.setPars(allPars) + if (mnState.hasCovariance()) { + val mnCov: MnUserCovariance = mnState.covariance() + var j: Int + val cov = Array(mnState.variableParameters()) { DoubleArray(mnState.variableParameters()) } + for (i in 0 until mnState.variableParameters()) { + j = 0 + while (j < mnState.variableParameters()) { + cov[i][j] = mnCov.get(i, j) + j++ + } + } + newState.setCovariance(NamedMatrix(fitPars, cov), true) + } + return FitResult.build(newState.build(), fitPars) + } + + fun runFit(state: FitState, log: History, meta: Meta): FitResult { + val minuit: MnApplication + log.report("Starting fit using Minuit.") + val strategy: Int + strategy = Global.INSTANCE.getInt("MINUIT_STRATEGY", 2) + var force: Boolean + force = Global.INSTANCE.getBoolean("FORCE_DERIVS", false) + val fitPars: Array = Fitter.Companion.getFitPars(state, meta) + for (fitPar in fitPars) { + if (!state.modelProvidesDerivs(fitPar)) { + force = true + log.reportError("Model does not provide derivatives for parameter '{}'", fitPar) + } + } + if (force) { + log.report("Using MINUIT gradient calculator.") + } + val fcn: MultiFunction + val pars: ParamSet = state.getParameters().copy() + fcn = MINUITUtils.getFcn(state, pars, fitPars) + val method: String = meta.getString("method", MINUIT_MIGRAD) + when (method) { + MINUIT_MINOS, MINUIT_MINIMIZE -> minuit = + MnMinimize(fcn, MINUITUtils.getFitParameters(pars, fitPars), strategy) + MINUIT_SIMPLEX -> minuit = MnSimplex(fcn, MINUITUtils.getFitParameters(pars, fitPars), strategy) + else -> minuit = MnMigrad(fcn, MINUITUtils.getFitParameters(pars, fitPars), strategy) + } + if (force) { + minuit.setUseAnalyticalDerivatives(false) + log.report("Forced to use MINUIT internal derivative calculator!") + } + +// minuit.setUseAnalyticalDerivatives(true); + val minimum: FunctionMinimum + val maxSteps: Int = meta.getInt("iterations", -1) + val tolerance: Double = meta.getDouble("tolerance", -1) + minimum = if (maxSteps > 0) { + if (tolerance > 0) { + minuit.minimize(maxSteps, tolerance) + } else { + minuit.minimize(maxSteps) + } + } else { + minuit.minimize() + } + if (!minimum.isValid()) { + log.report("Minimization failed!") + } + log.report("MINUIT run completed in {} function calls.", minimum.nfcn()) + + /* + * Генерация результата + */ + val allPars: ParamSet = pars.copy() + for (fitPar in fitPars) { + allPars.setParValue(fitPar, minimum.userParameters().value(fitPar)) + allPars.setParError(fitPar, minimum.userParameters().error(fitPar)) + } + val newState: FitState.Builder = state.edit() + newState.setPars(allPars) + var valid: Boolean = minimum.isValid() + if (minimum.userCovariance().nrow() > 0) { + var j: Int + val cov = Array(minuit.variableParameters()) { DoubleArray(minuit.variableParameters()) } + if (cov[0].length == 1) { + cov[0][0] = minimum.userParameters().error(0) * minimum.userParameters().error(0) + } else { + for (i in 0 until minuit.variableParameters()) { + j = 0 + while (j < minuit.variableParameters()) { + cov[i][j] = minimum.userCovariance().get(i, j) + j++ + } + } + } + newState.setCovariance(NamedMatrix(fitPars, cov), true) + } + if (method == MINUIT_MINOS) { + log.report("Starting MINOS procedure for precise error estimation.") + val minos = MnMinos(fcn, minimum, strategy) + var mnError: MinosError + val errl = DoubleArray(fitPars.size) + val errp = DoubleArray(fitPars.size) + for (i in fitPars.indices) { + mnError = minos.minos(i) + if (mnError.isValid()) { + errl[i] = mnError.lower() + errp[i] = mnError.upper() + } else { + valid = false + } + } + val minosErrors = MINOSResult(fitPars, errl, errp) + newState.setInterval(minosErrors) + } + return FitResult.build(newState.build(), valid, fitPars) + } + + companion object { + /** + * Constant `MINUIT_MIGRAD="MIGRAD"` + */ + const val MINUIT_MIGRAD = "MIGRAD" + + /** + * Constant `MINUIT_MINIMIZE="MINIMIZE"` + */ + const val MINUIT_MINIMIZE = "MINIMIZE" + + /** + * Constant `MINUIT_SIMPLEX="SIMPLEX"` + */ + const val MINUIT_SIMPLEX = "SIMPLEX" + + /** + * Constant `MINUIT_MINOS="MINOS"` + */ + const val MINUIT_MINOS = "MINOS" //MINOS errors + + /** + * Constant `MINUIT_HESSE="HESSE"` + */ + const val MINUIT_HESSE = "HESSE" //HESSE errors + + /** + * Constant `MINUIT_ENGINE_NAME="MINUIT"` + */ + const val MINUIT_ENGINE_NAME = "MINUIT" + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITPlugin.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITPlugin.kt new file mode 100644 index 000000000..7eaefd9d2 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITPlugin.kt @@ -0,0 +1,86 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ +package space.kscience.kmath.optimization.minuit + +import hep.dataforge.context.* + +/** + * Мэнеджер для MINUITа. Пока не играет никакой активной роли кроме ведения + * внутреннего лога. + * + * @author Darksnake + * @version $Id: $Id + */ +@PluginDef(group = "hep.dataforge", + name = "MINUIT", + dependsOn = ["hep.dataforge:fitting"], + info = "The MINUIT fitter engine for DataForge fitting") +class MINUITPlugin : BasicPlugin() { + fun attach(@NotNull context: Context?) { + super.attach(context) + clearStaticLog() + } + + @Provides(Fitter.FITTER_TARGET) + fun getFitter(fitterName: String): Fitter? { + return if (fitterName == "MINUIT") { + MINUITFitter() + } else { + null + } + } + + @ProvidesNames(Fitter.FITTER_TARGET) + fun listFitters(): List { + return listOf("MINUIT") + } + + fun detach() { + clearStaticLog() + super.detach() + } + + class Factory : PluginFactory() { + fun build(meta: Meta?): Plugin { + return MINUITPlugin() + } + + fun getType(): java.lang.Class { + return MINUITPlugin::class.java + } + } + + companion object { + /** + * Constant `staticLog` + */ + private val staticLog: Chronicle? = Chronicle("MINUIT-STATIC", Global.INSTANCE.getHistory()) + + /** + * + * + * clearStaticLog. + */ + fun clearStaticLog() { + staticLog.clear() + } + + /** + * + * + * logStatic. + * + * @param str a [String] object. + * @param pars a [Object] object. + */ + fun logStatic(str: String?, vararg pars: Any?) { + checkNotNull(staticLog) { "MINUIT log is not initialized." } + staticLog.report(str, pars) + LoggerFactory.getLogger("MINUIT").info(String.format(str, *pars)) + // Out.out.printf(str,pars); +// Out.out.println(); + } + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITUtils.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITUtils.kt new file mode 100644 index 000000000..44c70cb42 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITUtils.kt @@ -0,0 +1,121 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ +package space.kscience.kmath.optimization.minuit + +import hep.dataforge.MINUIT.FunctionMinimum + +internal object MINUITUtils { + fun getFcn(source: FitState, allPar: ParamSet, fitPars: Array): MultiFunction { + return MnFunc(source, allPar, fitPars) + } + + fun getFitParameters(set: ParamSet, fitPars: Array): MnUserParameters { + val pars = MnUserParameters() + var i: Int + var par: Param + i = 0 + while (i < fitPars.size) { + par = set.getByName(fitPars[i]) + pars.add(fitPars[i], par.getValue(), par.getErr()) + if (par.getLowerBound() > Double.NEGATIVE_INFINITY && par.getUpperBound() < Double.POSITIVE_INFINITY) { + pars.setLimits(i, par.getLowerBound(), par.getUpperBound()) + } else if (par.getLowerBound() > Double.NEGATIVE_INFINITY) { + pars.setLowerLimit(i, par.getLowerBound()) + } else if (par.getUpperBound() < Double.POSITIVE_INFINITY) { + pars.setUpperLimit(i, par.getUpperBound()) + } + i++ + } + return pars + } + + fun getValueSet(allPar: ParamSet, names: Array, values: DoubleArray): ParamSet { + assert(values.size == names.size) + assert(allPar.getNames().contains(names)) + val vector: ParamSet = allPar.copy() + for (i in values.indices) { + vector.setParValue(names[i], values[i]) + } + return vector + } + + fun isValidArray(ar: DoubleArray): Boolean { + for (i in ar.indices) { + if (java.lang.Double.isNaN(ar[i])) { + return false + } + } + return true + } + + /** + * + * + * printMINUITResult. + * + * @param out a [PrintWriter] object. + * @param minimum a [hep.dataforge.MINUIT.FunctionMinimum] object. + */ + fun printMINUITResult(out: PrintWriter, minimum: FunctionMinimum?) { + out.println() + out.println("***MINUIT INTERNAL FIT INFORMATION***") + out.println() + MnPrint.print(out, minimum) + out.println() + out.println("***END OF MINUIT INTERNAL FIT INFORMATION***") + out.println() + } + + internal class MnFunc(source: FitState, allPar: ParamSet, fitPars: Array) : MultiFunction { + var source: FitState + var allPar: ParamSet + var fitPars: Array + fun value(doubles: DoubleArray): Double { + assert(isValidArray(doubles)) + assert(doubles.size == fitPars.size) + return -2 * source.getLogProb(getValueSet(allPar, fitPars, doubles)) + // source.getChi2(getValueSet(allPar, fitPars, doubles)); + } + + @Throws(NotDefinedException::class) + fun derivValue(n: Int, doubles: DoubleArray): Double { + assert(isValidArray(doubles)) + assert(doubles.size == getDimension()) + val set: ParamSet = getValueSet(allPar, fitPars, doubles) + +// double res; +// double d, s, deriv; +// +// res = 0; +// for (int i = 0; i < source.getDataNum(); i++) { +// d = source.getDis(i, set); +// s = source.getDispersion(i, set); +// if (source.modelProvidesDerivs(fitPars[n])) { +// deriv = source.getDisDeriv(fitPars[n], i, set); +// } else { +// throw new NotDefinedException(); +// // Такого не должно быть, поскольку мы где-то наверху должы были проверить, что производные все есть. +// } +// res += 2 * d * deriv / s; +// } + return -2 * source.getLogProbDeriv(fitPars[n], set) + } + + fun getDimension(): Int { + return fitPars.size + } + + fun providesDeriv(n: Int): Boolean { + return source.modelProvidesDerivs(fitPars[n]) + } + + init { + this.source = source + this.allPar = allPar + this.fitPars = fitPars + assert(source.getModel().getNames().contains(fitPars)) + } + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumBuilder.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumBuilder.kt new file mode 100644 index 000000000..eadeeb91d --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumBuilder.kt @@ -0,0 +1,43 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +interface MinimumBuilder { + /** + * + * minimum. + * + * @param fcn a [hep.dataforge.MINUIT.MnFcn] object. + * @param gc a [hep.dataforge.MINUIT.GradientCalculator] object. + * @param seed a [hep.dataforge.MINUIT.MinimumSeed] object. + * @param strategy a [hep.dataforge.MINUIT.MnStrategy] object. + * @param maxfcn a int. + * @param toler a double. + * @return a [hep.dataforge.MINUIT.FunctionMinimum] object. + */ + fun minimum( + fcn: MnFcn?, + gc: GradientCalculator?, + seed: MinimumSeed?, + strategy: MnStrategy?, + maxfcn: Int, + toler: Double + ): FunctionMinimum +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumError.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumError.kt new file mode 100644 index 000000000..6993b9e6d --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumError.kt @@ -0,0 +1,155 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import space.kscience.kmath.optimization.minuit.MINUITPlugin + +/** + * MinimumError keeps the inverse 2nd derivative (inverse Hessian) used for + * calculating the parameter step size (-V*g) and for the covariance update + * (ErrorUpdator). The covariance matrix is equal to twice the inverse Hessian. + * + * @version $Id$ + */ +class MinimumError { + private var theAvailable = false + private var theDCovar: Double + private var theHesseFailed = false + private var theInvertFailed = false + private var theMadePosDef = false + private var theMatrix: MnAlgebraicSymMatrix + private var thePosDef = false + private var theValid = false + + constructor(n: Int) { + theMatrix = MnAlgebraicSymMatrix(n) + theDCovar = 1.0 + } + + constructor(mat: MnAlgebraicSymMatrix, dcov: Double) { + theMatrix = mat + theDCovar = dcov + theValid = true + thePosDef = true + theAvailable = true + } + + constructor(mat: MnAlgebraicSymMatrix, x: MnHesseFailed?) { + theMatrix = mat + theDCovar = 1.0 + theValid = false + thePosDef = false + theMadePosDef = false + theHesseFailed = true + theInvertFailed = false + theAvailable = true + } + + constructor(mat: MnAlgebraicSymMatrix, x: MnMadePosDef?) { + theMatrix = mat + theDCovar = 1.0 + theValid = false + thePosDef = false + theMadePosDef = true + theHesseFailed = false + theInvertFailed = false + theAvailable = true + } + + constructor(mat: MnAlgebraicSymMatrix, x: MnInvertFailed?) { + theMatrix = mat + theDCovar = 1.0 + theValid = false + thePosDef = true + theMadePosDef = false + theHesseFailed = false + theInvertFailed = true + theAvailable = true + } + + constructor(mat: MnAlgebraicSymMatrix, x: MnNotPosDef?) { + theMatrix = mat + theDCovar = 1.0 + theValid = false + thePosDef = false + theMadePosDef = false + theHesseFailed = false + theInvertFailed = false + theAvailable = true + } + + fun dcovar(): Double { + return theDCovar + } + + fun hesseFailed(): Boolean { + return theHesseFailed + } + + fun hessian(): MnAlgebraicSymMatrix { + return try { + val tmp: MnAlgebraicSymMatrix = theMatrix.copy() + tmp.invert() + tmp + } catch (x: SingularMatrixException) { + MINUITPlugin.logStatic("BasicMinimumError inversion fails; return diagonal matrix.") + val tmp = MnAlgebraicSymMatrix(theMatrix.nrow()) + var i = 0 + while (i < theMatrix.nrow()) { + tmp[i, i] = 1.0 / theMatrix[i, i] + i++ + } + tmp + } + } + + fun invHessian(): MnAlgebraicSymMatrix { + return theMatrix + } + + fun invertFailed(): Boolean { + return theInvertFailed + } + + fun isAccurate(): Boolean { + return theDCovar < 0.1 + } + + fun isAvailable(): Boolean { + return theAvailable + } + + fun isMadePosDef(): Boolean { + return theMadePosDef + } + + fun isPosDef(): Boolean { + return thePosDef + } + + fun isValid(): Boolean { + return theValid + } + + fun matrix(): MnAlgebraicSymMatrix { + return MnUtils.mul(theMatrix, 2) + } + + internal class MnHesseFailed + internal class MnInvertFailed + internal class MnMadePosDef + internal class MnNotPosDef +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumErrorUpdator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumErrorUpdator.kt new file mode 100644 index 000000000..6022aa5b7 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumErrorUpdator.kt @@ -0,0 +1,33 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal interface MinimumErrorUpdator { + /** + * + * update. + * + * @param state a [hep.dataforge.MINUIT.MinimumState] object. + * @param par a [hep.dataforge.MINUIT.MinimumParameters] object. + * @param grad a [hep.dataforge.MINUIT.FunctionGradient] object. + * @return a [hep.dataforge.MINUIT.MinimumError] object. + */ + fun update(state: MinimumState?, par: MinimumParameters?, grad: FunctionGradient?): MinimumError? +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumParameters.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumParameters.kt new file mode 100644 index 000000000..bed13ea0b --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumParameters.kt @@ -0,0 +1,70 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector + +/** + * + * @version $Id$ + */ +class MinimumParameters { + private var theFVal = 0.0 + private var theHasStep = false + private var theParameters: RealVector + private var theStepSize: RealVector + private var theValid = false + + constructor(n: Int) { + theParameters = ArrayRealVector(n) + theStepSize = ArrayRealVector(n) + } + + constructor(avec: RealVector, fval: Double) { + theParameters = avec + theStepSize = ArrayRealVector(avec.getDimension()) + theFVal = fval + theValid = true + } + + constructor(avec: RealVector, dirin: RealVector, fval: Double) { + theParameters = avec + theStepSize = dirin + theFVal = fval + theValid = true + theHasStep = true + } + + fun dirin(): RealVector { + return theStepSize + } + + fun fval(): Double { + return theFVal + } + + fun hasStepSize(): Boolean { + return theHasStep + } + + fun isValid(): Boolean { + return theValid + } + + fun vec(): RealVector { + return theParameters + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeed.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeed.kt new file mode 100644 index 000000000..aef672bb7 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeed.kt @@ -0,0 +1,64 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +class MinimumSeed(state: MinimumState, trafo: MnUserTransformation) { + private val theState: MinimumState = state + private val theTrafo: MnUserTransformation = trafo + private val theValid: Boolean = true + val edm: Double get() = state().edm() + + fun error(): MinimumError { + return state().error() + } + + fun fval(): Double { + return state().fval() + } + + fun gradient(): FunctionGradient { + return state().gradient() + } + + fun isValid(): Boolean { + return theValid + } + + fun nfcn(): Int { + return state().nfcn() + } + + fun parameters(): MinimumParameters { + return state().parameters() + } + + fun precision(): MnMachinePrecision { + return theTrafo.precision() + } + + fun state(): MinimumState { + return theState + } + + fun trafo(): MnUserTransformation { + return theTrafo + } + +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeedGenerator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeedGenerator.kt new file mode 100644 index 000000000..bd04c1a45 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeedGenerator.kt @@ -0,0 +1,37 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * base class for seed generators (starting values); the seed generator prepares + * initial starting values from the input (MnUserParameterState) for the + * minimization; + * + * @version $Id$ + */ +interface MinimumSeedGenerator { + /** + * + * generate. + * + * @param fcn a [hep.dataforge.MINUIT.MnFcn] object. + * @param calc a [hep.dataforge.MINUIT.GradientCalculator] object. + * @param user a [hep.dataforge.MINUIT.MnUserParameterState] object. + * @param stra a [hep.dataforge.MINUIT.MnStrategy] object. + * @return a [hep.dataforge.MINUIT.MinimumSeed] object. + */ + fun generate(fcn: MnFcn?, calc: GradientCalculator?, user: MnUserParameterState?, stra: MnStrategy?): MinimumSeed +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumState.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumState.kt new file mode 100644 index 000000000..9f63e0e1f --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumState.kt @@ -0,0 +1,104 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.RealVector + +/** + * MinimumState keeps the information (position, gradient, 2nd deriv, etc) after + * one minimization step (usually in MinimumBuilder). + * + * @version $Id$ + */ +class MinimumState { + private var theEDM = 0.0 + private var theError: MinimumError + private var theGradient: FunctionGradient + private var theNFcn = 0 + private var theParameters: MinimumParameters + + constructor(n: Int) { + theParameters = MinimumParameters(n) + theError = MinimumError(n) + theGradient = FunctionGradient(n) + } + + constructor(states: MinimumParameters, err: MinimumError, grad: FunctionGradient, edm: Double, nfcn: Int) { + theParameters = states + theError = err + theGradient = grad + theEDM = edm + theNFcn = nfcn + } + + constructor(states: MinimumParameters, edm: Double, nfcn: Int) { + theParameters = states + theError = MinimumError(states.vec().getDimension()) + theGradient = FunctionGradient(states.vec().getDimension()) + theEDM = edm + theNFcn = nfcn + } + + fun edm(): Double { + return theEDM + } + + fun error(): MinimumError { + return theError + } + + fun fval(): Double { + return theParameters.fval() + } + + fun gradient(): FunctionGradient { + return theGradient + } + + fun hasCovariance(): Boolean { + return theError.isAvailable() + } + + fun hasParameters(): Boolean { + return theParameters.isValid() + } + + fun isValid(): Boolean { + return if (hasParameters() && hasCovariance()) { + parameters().isValid() && error().isValid() + } else if (hasParameters()) { + parameters().isValid() + } else { + false + } + } + + fun nfcn(): Int { + return theNFcn + } + + fun parameters(): MinimumParameters { + return theParameters + } + + fun size(): Int { + return theParameters.vec().getDimension() + } + + fun vec(): RealVector { + return theParameters.vec() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinosError.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinosError.kt new file mode 100644 index 000000000..c7cf10523 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinosError.kt @@ -0,0 +1,219 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * MinosError class. + * + * @author Darksnake + * @version $Id$ + */ +class MinosError { + private var theLower: MnCross + private var theMinValue = 0.0 + private var theParameter = 0 + private var theUpper: MnCross + + internal constructor() { + theUpper = MnCross() + theLower = MnCross() + } + + internal constructor(par: Int, min: Double, low: MnCross, up: MnCross) { + theParameter = par + theMinValue = min + theUpper = up + theLower = low + } + + /** + * + * atLowerLimit. + * + * @return a boolean. + */ + fun atLowerLimit(): Boolean { + return theLower.atLimit() + } + + /** + * + * atLowerMaxFcn. + * + * @return a boolean. + */ + fun atLowerMaxFcn(): Boolean { + return theLower.atMaxFcn() + } + + /** + * + * atUpperLimit. + * + * @return a boolean. + */ + fun atUpperLimit(): Boolean { + return theUpper.atLimit() + } + + /** + * + * atUpperMaxFcn. + * + * @return a boolean. + */ + fun atUpperMaxFcn(): Boolean { + return theUpper.atMaxFcn() + } + + /** + * + * isValid. + * + * @return a boolean. + */ + fun isValid(): Boolean { + return theLower.isValid() && theUpper.isValid() + } + + /** + * + * lower. + * + * @return a double. + */ + fun lower(): Double { + return -1.0 * lowerState().error(parameter()) * (1.0 + theLower.value()) + } + + /** + * + * lowerNewMin. + * + * @return a boolean. + */ + fun lowerNewMin(): Boolean { + return theLower.newMinimum() + } + + /** + * + * lowerState. + * + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun lowerState(): MnUserParameterState { + return theLower.state() + } + + /** + * + * lowerValid. + * + * @return a boolean. + */ + fun lowerValid(): Boolean { + return theLower.isValid() + } + + /** + * + * min. + * + * @return a double. + */ + fun min(): Double { + return theMinValue + } + + /** + * + * nfcn. + * + * @return a int. + */ + fun nfcn(): Int { + return theUpper.nfcn() + theLower.nfcn() + } + + /** + * + * parameter. + * + * @return a int. + */ + fun parameter(): Int { + return theParameter + } + + /** + * + * range. + * + * @return + */ + fun range(): Range { + return Range(lower(), upper()) + } + + /** + * {@inheritDoc} + */ + override fun toString(): String { + return MnPrint.toString(this) + } + + /** + * + * upper. + * + * @return a double. + */ + fun upper(): Double { + return upperState().error(parameter()) * (1.0 + theUpper.value()) + } + + /** + * + * upperNewMin. + * + * @return a boolean. + */ + fun upperNewMin(): Boolean { + return theUpper.newMinimum() + } + + /** + * + * upperState. + * + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun upperState(): MnUserParameterState { + return theUpper.state() + } + + /** + * + * upperValid. + * + * @return a boolean. + */ + fun upperValid(): Boolean { + return theUpper.isValid() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinuitParameter.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinuitParameter.kt new file mode 100644 index 000000000..ff6834df4 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinuitParameter.kt @@ -0,0 +1,314 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +class MinuitParameter { + private var theConst = false + private var theError = 0.0 + private var theFix = false + private var theLoLimValid = false + private var theLoLimit = 0.0 + private var theName: String + private var theNum: Int + private var theUpLimValid = false + private var theUpLimit = 0.0 + private var theValue: Double + + /** + * constructor for constant parameter + * + * @param num a int. + * @param name a [String] object. + * @param val a double. + */ + constructor(num: Int, name: String, `val`: Double) { + theNum = num + theValue = `val` + theConst = true + theName = name + } + + /** + * constructor for standard parameter + * + * @param num a int. + * @param name a [String] object. + * @param val a double. + * @param err a double. + */ + constructor(num: Int, name: String, `val`: Double, err: Double) { + theNum = num + theValue = `val` + theError = err + theName = name + } + + /** + * constructor for limited parameter + * + * @param num a int. + * @param name a [String] object. + * @param val a double. + * @param err a double. + * @param min a double. + * @param max a double. + */ + constructor(num: Int, name: String, `val`: Double, err: Double, min: Double, max: Double) { + theNum = num + theValue = `val` + theError = err + theLoLimit = min + theUpLimit = max + theLoLimValid = true + theUpLimValid = true + require(min != max) { "min == max" } + if (min > max) { + theLoLimit = max + theUpLimit = min + } + theName = name + } + + private constructor(other: MinuitParameter) { + theNum = other.theNum + theName = other.theName + theValue = other.theValue + theError = other.theError + theConst = other.theConst + theFix = other.theFix + theLoLimit = other.theLoLimit + theUpLimit = other.theUpLimit + theLoLimValid = other.theLoLimValid + theUpLimValid = other.theUpLimValid + } + + /** + * + * copy. + * + * @return a [hep.dataforge.MINUIT.MinuitParameter] object. + */ + fun copy(): MinuitParameter { + return MinuitParameter(this) + } + + /** + * + * error. + * + * @return a double. + */ + fun error(): Double { + return theError + } + + /** + * + * fix. + */ + fun fix() { + theFix = true + } + + /** + * + * hasLimits. + * + * @return a boolean. + */ + fun hasLimits(): Boolean { + return theLoLimValid || theUpLimValid + } + + /** + * + * hasLowerLimit. + * + * @return a boolean. + */ + fun hasLowerLimit(): Boolean { + return theLoLimValid + } + + /** + * + * hasUpperLimit. + * + * @return a boolean. + */ + fun hasUpperLimit(): Boolean { + return theUpLimValid + } + //state of parameter (fixed/const/limited) + /** + * + * isConst. + * + * @return a boolean. + */ + fun isConst(): Boolean { + return theConst + } + + /** + * + * isFixed. + * + * @return a boolean. + */ + fun isFixed(): Boolean { + return theFix + } + + /** + * + * lowerLimit. + * + * @return a double. + */ + fun lowerLimit(): Double { + return theLoLimit + } + + /** + * + * name. + * + * @return a [String] object. + */ + fun name(): String { + return theName + } + //access methods + /** + * + * number. + * + * @return a int. + */ + fun number(): Int { + return theNum + } + + /** + * + * release. + */ + fun release() { + theFix = false + } + + /** + * + * removeLimits. + */ + fun removeLimits() { + theLoLimit = 0.0 + theUpLimit = 0.0 + theLoLimValid = false + theUpLimValid = false + } + + /** + * + * setError. + * + * @param err a double. + */ + fun setError(err: Double) { + theError = err + theConst = false + } + + /** + * + * setLimits. + * + * @param low a double. + * @param up a double. + */ + fun setLimits(low: Double, up: Double) { + require(low != up) { "min == max" } + theLoLimit = low + theUpLimit = up + theLoLimValid = true + theUpLimValid = true + if (low > up) { + theLoLimit = up + theUpLimit = low + } + } + + /** + * + * setLowerLimit. + * + * @param low a double. + */ + fun setLowerLimit(low: Double) { + theLoLimit = low + theUpLimit = 0.0 + theLoLimValid = true + theUpLimValid = false + } + + /** + * + * setUpperLimit. + * + * @param up a double. + */ + fun setUpperLimit(up: Double) { + theLoLimit = 0.0 + theUpLimit = up + theLoLimValid = false + theUpLimValid = true + } + //interaction + /** + * + * setValue. + * + * @param val a double. + */ + fun setValue(`val`: Double) { + theValue = `val` + } + + /** + * + * upperLimit. + * + * @return a double. + */ + fun upperLimit(): Double { + return theUpLimit + } + + /** + * + * value. + * + * @return a double. + */ + fun value(): Double { + return theValue + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnAlgebraicSymMatrix.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnAlgebraicSymMatrix.kt new file mode 100644 index 000000000..4b75858e1 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnAlgebraicSymMatrix.kt @@ -0,0 +1,458 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector + +/** + * + * @version $Id$ + */ +class MnAlgebraicSymMatrix(n: Int) { + private val theData: DoubleArray + private val theNRow: Int + private val theSize: Int + + /** + * + * copy. + * + * @return a [hep.dataforge.MINUIT.MnAlgebraicSymMatrix] object. + */ + fun copy(): MnAlgebraicSymMatrix { + val copy = MnAlgebraicSymMatrix(theNRow) + java.lang.System.arraycopy(theData, 0, copy.theData, 0, theSize) + return copy + } + + fun data(): DoubleArray { + return theData + } + + fun eigenvalues(): ArrayRealVector { + val nrow = theNRow + val tmp = DoubleArray((nrow + 1) * (nrow + 1)) + val work = DoubleArray(1 + 2 * nrow) + for (i in 0 until nrow) { + for (j in 0..i) { + tmp[1 + i + (1 + j) * nrow] = get(i, j) + tmp[(1 + i) * nrow + (1 + j)] = get(i, j) + } + } + val info = mneigen(tmp, nrow, nrow, work.size, work, 1e-6) + if (info != 0) { + throw EigenvaluesException() + } + val result = ArrayRealVector(nrow) + for (i in 0 until nrow) { + result.setEntry(i, work[1 + i]) + } + return result + } + + operator fun get(row: Int, col: Int): Double { + if (row >= theNRow || col >= theNRow) { + throw ArrayIndexOutOfBoundsException() + } + return theData[theIndex(row, col)] + } + + @Throws(SingularMatrixException::class) + fun invert() { + if (theSize == 1) { + val tmp = theData[0] + if (tmp <= 0.0) { + throw SingularMatrixException() + } + theData[0] = 1.0 / tmp + } else { + val nrow = theNRow + val s = DoubleArray(nrow) + val q = DoubleArray(nrow) + val pp = DoubleArray(nrow) + for (i in 0 until nrow) { + val si = theData[theIndex(i, i)] + if (si < 0.0) { + throw SingularMatrixException() + } + s[i] = 1.0 / sqrt(si) + } + for (i in 0 until nrow) { + for (j in i until nrow) { + theData[theIndex(i, j)] *= s[i] * s[j] + } + } + for (i in 0 until nrow) { + var k = i + if (theData[theIndex(k, k)] == 0.0) { + throw SingularMatrixException() + } + q[k] = 1.0 / theData[theIndex(k, k)] + pp[k] = 1.0 + theData[theIndex(k, k)] = 0.0 + val kp1 = k + 1 + if (k != 0) { + for (j in 0 until k) { + val index = theIndex(j, k) + pp[j] = theData[index] + q[j] = theData[index] * q[k] + theData[index] = 0.0 + } + } + if (k != nrow - 1) { + for (j in kp1 until nrow) { + val index = theIndex(k, j) + pp[j] = theData[index] + q[j] = -theData[index] * q[k] + theData[index] = 0.0 + } + } + for (j in 0 until nrow) { + k = j + while (k < nrow) { + theData[theIndex(j, k)] += pp[j] * q[k] + k++ + } + } + } + for (j in 0 until nrow) { + for (k in j until nrow) { + theData[theIndex(j, k)] *= s[j] * s[k] + } + } + } + } + + fun ncol(): Int { + return nrow() + } + + fun nrow(): Int { + return theNRow + } + + operator fun set(row: Int, col: Int, value: Double) { + if (row >= theNRow || col >= theNRow) { + throw ArrayIndexOutOfBoundsException() + } + theData[theIndex(row, col)] = value + } + + fun size(): Int { + return theSize + } + + private fun theIndex(row: Int, col: Int): Int { + return if (row > col) { + col + row * (row + 1) / 2 + } else { + row + col * (col + 1) / 2 + } + } + + /** {@inheritDoc} */ + override fun toString(): String { + return MnPrint.toString(this) + } /* mneig_ */ + + private inner class EigenvaluesException : RuntimeException() + companion object { + private fun mneigen(a: DoubleArray, ndima: Int, n: Int, mits: Int, work: DoubleArray, precis: Double): Int { + + /* System generated locals */ + var i__2: Int + var i__3: Int + + /* Local variables */ + var b: Double + var c__: Double + var f: Double + var h__: Double + var i__: Int + var j: Int + var k: Int + var l: Int + var m = 0 + var r__: Double + var s: Double + var i0: Int + var i1: Int + var j1: Int + var m1: Int + var hh: Double + var gl: Double + var pr: Double + var pt: Double + + /* PRECIS is the machine precision EPSMAC */ + /* Parameter adjustments */ + val a_dim1: Int = ndima + val a_offset: Int = 1 + a_dim1 * 1 + + /* Function Body */ + var ifault = 1 + i__ = n + var i__1: Int = n + i1 = 2 + while (i1 <= i__1) { + l = i__ - 2 + f = a[i__ + (i__ - 1) * a_dim1] + gl = 0.0 + if (l >= 1) { + i__2 = l + k = 1 + while (k <= i__2) { + + /* Computing 2nd power */ + val r__1 = a[i__ + k * a_dim1] + gl += r__1 * r__1 + ++k + } + } + /* Computing 2nd power */h__ = gl + f * f + if (gl <= 1e-35) { + work[i__] = 0.0 + work[n + i__] = f + } else { + ++l + gl = sqrt(h__) + if (f >= 0.0) { + gl = -gl + } + work[n + i__] = gl + h__ -= f * gl + a[i__ + (i__ - 1) * a_dim1] = f - gl + f = 0.0 + i__2 = l + j = 1 + while (j <= i__2) { + a[j + i__ * a_dim1] = a[i__ + j * a_dim1] / h__ + gl = 0.0 + i__3 = j + k = 1 + while (k <= i__3) { + gl += a[j + k * a_dim1] * a[i__ + k * a_dim1] + ++k + } + if (j < l) { + j1 = j + 1 + i__3 = l + k = j1 + while (k <= i__3) { + gl += a[k + j * a_dim1] * a[i__ + k * a_dim1] + ++k + } + } + work[n + j] = gl / h__ + f += gl * a[j + i__ * a_dim1] + ++j + } + hh = f / (h__ + h__) + i__2 = l + j = 1 + while (j <= i__2) { + f = a[i__ + j * a_dim1] + gl = work[n + j] - hh * f + work[n + j] = gl + i__3 = j + k = 1 + while (k <= i__3) { + a[j + k * a_dim1] = a[j + k * a_dim1] - f * work[n + k] - (gl + * a[i__ + k * a_dim1]) + ++k + } + ++j + } + work[i__] = h__ + } + --i__ + ++i1 + } + work[1] = 0.0 + work[n + 1] = 0.0 + i__1 = n + i__ = 1 + while (i__ <= i__1) { + l = i__ - 1 + if (work[i__] != 0.0 && l != 0) { + i__3 = l + j = 1 + while (j <= i__3) { + gl = 0.0 + i__2 = l + k = 1 + while (k <= i__2) { + gl += a[i__ + k * a_dim1] * a[k + j * a_dim1] + ++k + } + i__2 = l + k = 1 + while (k <= i__2) { + a[k + j * a_dim1] -= gl * a[k + i__ * a_dim1] + ++k + } + ++j + } + } + work[i__] = a[i__ + i__ * a_dim1] + a[i__ + i__ * a_dim1] = 1.0 + if (l != 0) { + i__2 = l + j = 1 + while (j <= i__2) { + a[i__ + j * a_dim1] = 0.0 + a[j + i__ * a_dim1] = 0.0 + ++j + } + } + ++i__ + } + val n1: Int = n - 1 + i__1 = n + i__ = 2 + while (i__ <= i__1) { + i0 = n + i__ - 1 + work[i0] = work[i0 + 1] + ++i__ + } + work[n + n] = 0.0 + b = 0.0 + f = 0.0 + i__1 = n + l = 1 + while (l <= i__1) { + j = 0 + h__ = precis * (abs(work[l]) + abs(work[n + l])) + if (b < h__) { + b = h__ + } + i__2 = n + m1 = l + while (m1 <= i__2) { + m = m1 + if (abs(work[n + m]) <= b) { + break + } + ++m1 + } + if (m != l) { + while (true) { + if (j == mits) { + return ifault + } + ++j + pt = (work[l + 1] - work[l]) / (work[n + l] * 2.0) + r__ = sqrt(pt * pt + 1.0) + pr = pt + r__ + if (pt < 0.0) { + pr = pt - r__ + } + h__ = work[l] - work[n + l] / pr + i__2 = n + i__ = l + while (i__ <= i__2) { + work[i__] -= h__ + ++i__ + } + f += h__ + pt = work[m] + c__ = 1.0 + s = 0.0 + m1 = m - 1 + i__ = m + i__2 = m1 + i1 = l + while (i1 <= i__2) { + j = i__ + --i__ + gl = c__ * work[n + i__] + h__ = c__ * pt + if (abs(pt) < abs(work[n + i__])) { + c__ = pt / work[n + i__] + r__ = sqrt(c__ * c__ + 1.0) + work[n + j] = s * work[n + i__] * r__ + s = 1.0 / r__ + c__ /= r__ + } else { + c__ = work[n + i__] / pt + r__ = sqrt(c__ * c__ + 1.0) + work[n + j] = s * pt * r__ + s = c__ / r__ + c__ = 1.0 / r__ + } + pt = c__ * work[i__] - s * gl + work[j] = h__ + s * (c__ * gl + s * work[i__]) + i__3 = n + k = 1 + while (k <= i__3) { + h__ = a[k + j * a_dim1] + a[k + j * a_dim1] = s * a[k + i__ * a_dim1] + c__ * h__ + a[k + i__ * a_dim1] = c__ * a[k + i__ * a_dim1] - s * h__ + ++k + } + ++i1 + } + work[n + l] = s * pt + work[l] = c__ * pt + if (abs(work[n + l]) <= b) { + break + } + } + } + work[l] += f + ++l + } + i__1 = n1 + i__ = 1 + while (i__ <= i__1) { + k = i__ + pt = work[i__] + i1 = i__ + 1 + i__3 = n + j = i1 + while (j <= i__3) { + if (work[j] < pt) { + k = j + pt = work[j] + } + ++j + } + if (k != i__) { + work[k] = work[i__] + work[i__] = pt + i__3 = n + j = 1 + while (j <= i__3) { + pt = a[j + i__ * a_dim1] + a[j + i__ * a_dim1] = a[j + k * a_dim1] + a[j + k * a_dim1] = pt + ++j + } + } + ++i__ + } + ifault = 0 + return ifault + } /* mneig_ */ + } + + init { + require(n >= 0) { "Invalid matrix size: $n" } + theSize = n * (n + 1) / 2 + theNRow = n + theData = DoubleArray(theSize) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnApplication.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnApplication.kt new file mode 100644 index 000000000..025eea4ae --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnApplication.kt @@ -0,0 +1,554 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction +import ru.inr.mass.minuit.* + +/** + * Base class for minimizers. + * + * @version $Id$ + * @author Darksnake + */ +abstract class MnApplication { + /* package protected */ + var checkAnalyticalDerivatives: Boolean + + /* package protected */ /* package protected */ + var theErrorDef = 1.0 /* package protected */ + var theFCN: MultiFunction? + + /* package protected */ /* package protected */ + var theNumCall /* package protected */ = 0 + var theState: MnUserParameterState + + /* package protected */ + var theStrategy: MnStrategy + + /* package protected */ + var useAnalyticalDerivatives: Boolean + + /* package protected */ + internal constructor(fcn: MultiFunction?, state: MnUserParameterState, stra: MnStrategy) { + theFCN = fcn + theState = state + theStrategy = stra + checkAnalyticalDerivatives = true + useAnalyticalDerivatives = true + } + + internal constructor(fcn: MultiFunction?, state: MnUserParameterState, stra: MnStrategy, nfcn: Int) { + theFCN = fcn + theState = state + theStrategy = stra + theNumCall = nfcn + checkAnalyticalDerivatives = true + useAnalyticalDerivatives = true + } + + /** + * + * MultiFunction. + * + * @return a [MultiFunction] object. + */ + fun MultiFunction(): MultiFunction? { + return theFCN + } + + /** + * add free parameter + * + * @param err a double. + * @param val a double. + * @param name a [String] object. + */ + fun add(name: String, `val`: Double, err: Double) { + theState.add(name, `val`, err) + } + + /** + * add limited parameter + * + * @param up a double. + * @param low a double. + * @param name a [String] object. + * @param val a double. + * @param err a double. + */ + fun add(name: String, `val`: Double, err: Double, low: Double, up: Double) { + theState.add(name, `val`, err, low, up) + } + + /** + * add const parameter + * + * @param name a [String] object. + * @param val a double. + */ + fun add(name: String, `val`: Double) { + theState.add(name, `val`) + } + + /** + * + * checkAnalyticalDerivatives. + * + * @return a boolean. + */ + fun checkAnalyticalDerivatives(): Boolean { + return checkAnalyticalDerivatives + } + + /** + * + * covariance. + * + * @return a [hep.dataforge.MINUIT.MnUserCovariance] object. + */ + fun covariance(): MnUserCovariance { + return theState.covariance() + } + + /** + * + * error. + * + * @param index a int. + * @return a double. + */ + fun error(index: Int): Double { + return theState.error(index) + } + + /** + * + * error. + * + * @param name a [String] object. + * @return a double. + */ + fun error(name: String?): Double { + return theState.error(name) + } + + /** + * + * errorDef. + * + * @return a double. + */ + fun errorDef(): Double { + return theErrorDef + } + + /** + * + * errors. + * + * @return an array of double. + */ + fun errors(): DoubleArray { + return theState.errors() + } + + fun ext2int(i: Int, value: Double): Double { + return theState.ext2int(i, value) + } + + fun extOfInt(i: Int): Int { + return theState.extOfInt(i) + } + //interaction via external number of parameter + /** + * + * fix. + * + * @param index a int. + */ + fun fix(index: Int) { + theState.fix(index) + } + //interaction via name of parameter + /** + * + * fix. + * + * @param name a [String] object. + */ + fun fix(name: String?) { + theState.fix(name) + } + + /** + * convert name into external number of parameter + * + * @param name a [String] object. + * @return a int. + */ + fun index(name: String?): Int { + return theState.index(name) + } + + // transformation internal <-> external + fun int2ext(i: Int, value: Double): Double { + return theState.int2ext(i, value) + } + + fun intOfExt(i: Int): Int { + return theState.intOfExt(i) + } + + /** + * + * minimize. + * + * @return a [hep.dataforge.MINUIT.FunctionMinimum] object. + */ + fun minimize(): FunctionMinimum { + return minimize(DEFAULT_MAXFCN) + } + + /** + * + * minimize. + * + * @param maxfcn a int. + * @return a [hep.dataforge.MINUIT.FunctionMinimum] object. + */ + fun minimize(maxfcn: Int): FunctionMinimum { + return minimize(maxfcn, DEFAULT_TOLER) + } + + /** + * Causes minimization of the FCN and returns the result in form of a + * FunctionMinimum. + * + * @param maxfcn specifies the (approximate) maximum number of function + * calls after which the calculation will be stopped even if it has not yet + * converged. + * @param toler specifies the required tolerance on the function value at + * the minimum. The default tolerance value is 0.1, and the minimization + * will stop when the estimated vertical distance to the minimum (EDM) is + * less than 0:001*tolerance*errorDef + * @return a [hep.dataforge.MINUIT.FunctionMinimum] object. + */ + fun minimize(maxfcn: Int, toler: Double): FunctionMinimum { + var maxfcn = maxfcn + check(theState.isValid()) { "Invalid state" } + val npar = variableParameters() + if (maxfcn == 0) { + maxfcn = 200 + 100 * npar + 5 * npar * npar + } + val min: FunctionMinimum = minimizer().minimize(theFCN, + theState, + theStrategy, + maxfcn, + toler, + theErrorDef, + useAnalyticalDerivatives, + checkAnalyticalDerivatives) + theNumCall += min.nfcn() + theState = min.userState() + return min + } + + abstract fun minimizer(): ModularFunctionMinimizer + + // facade: forward interface of MnUserParameters and MnUserTransformation + fun minuitParameters(): List { + return theState.minuitParameters() + } + + /** + * convert external number into name of parameter + * + * @param index a int. + * @return a [String] object. + */ + fun name(index: Int): String { + return theState.name(index) + } + + /** + * + * numOfCalls. + * + * @return a int. + */ + fun numOfCalls(): Int { + return theNumCall + } + + /** + * access to single parameter + * @param i + * @return + */ + fun parameter(i: Int): MinuitParameter { + return theState.parameter(i) + } + + /** + * + * parameters. + * + * @return a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + fun parameters(): MnUserParameters { + return theState.parameters() + } + + /** + * access to parameters and errors in column-wise representation + * + * @return an array of double. + */ + fun params(): DoubleArray { + return theState.params() + } + + /** + * + * precision. + * + * @return a [hep.dataforge.MINUIT.MnMachinePrecision] object. + */ + fun precision(): MnMachinePrecision { + return theState.precision() + } + + /** + * + * release. + * + * @param index a int. + */ + fun release(index: Int) { + theState.release(index) + } + + /** + * + * release. + * + * @param name a [String] object. + */ + fun release(name: String?) { + theState.release(name) + } + + /** + * + * removeLimits. + * + * @param index a int. + */ + fun removeLimits(index: Int) { + theState.removeLimits(index) + } + + /** + * + * removeLimits. + * + * @param name a [String] object. + */ + fun removeLimits(name: String?) { + theState.removeLimits(name) + } + + /** + * Minuit does a check of the user gradient at the beginning, if this is not + * wanted the set this to "false". + * + * @param check a boolean. + */ + fun setCheckAnalyticalDerivatives(check: Boolean) { + checkAnalyticalDerivatives = check + } + + /** + * + * setError. + * + * @param index a int. + * @param err a double. + */ + fun setError(index: Int, err: Double) { + theState.setError(index, err) + } + + /** + * + * setError. + * + * @param name a [String] object. + * @param err a double. + */ + fun setError(name: String?, err: Double) { + theState.setError(name, err) + } + + /** + * errorDef() is the error definition of the function. E.g. is 1 if function + * is Chi2 and 0.5 if function is -logLikelihood. If the user wants instead + * the 2-sigma errors, errorDef() = 4, as Chi2(x+n*sigma) = Chi2(x) + n*n. + * + * @param errorDef a double. + */ + fun setErrorDef(errorDef: Double) { + theErrorDef = errorDef + } + + /** + * + * setLimits. + * + * @param index a int. + * @param low a double. + * @param up a double. + */ + fun setLimits(index: Int, low: Double, up: Double) { + theState.setLimits(index, low, up) + } + + /** + * + * setLimits. + * + * @param name a [String] object. + * @param low a double. + * @param up a double. + */ + fun setLimits(name: String?, low: Double, up: Double) { + theState.setLimits(name, low, up) + } + + /** + * + * setPrecision. + * + * @param prec a double. + */ + fun setPrecision(prec: Double) { + theState.setPrecision(prec) + } + + /** + * By default if the function to be minimized implements MultiFunction then + * the analytical gradient provided by the function will be used. Set this + * to + * false to disable this behaviour and force numerical + * calculation of the gradient. + * + * @param use a boolean. + */ + fun setUseAnalyticalDerivatives(use: Boolean) { + useAnalyticalDerivatives = use + } + + /** + * + * setValue. + * + * @param index a int. + * @param val a double. + */ + fun setValue(index: Int, `val`: Double) { + theState.setValue(index, `val`) + } + + /** + * + * setValue. + * + * @param name a [String] object. + * @param val a double. + */ + fun setValue(name: String?, `val`: Double) { + theState.setValue(name, `val`) + } + + /** + * + * state. + * + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun state(): MnUserParameterState { + return theState + } + + /** + * + * strategy. + * + * @return a [hep.dataforge.MINUIT.MnStrategy] object. + */ + fun strategy(): MnStrategy { + return theStrategy + } + + /** + * + * useAnalyticalDerivaties. + * + * @return a boolean. + */ + fun useAnalyticalDerivaties(): Boolean { + return useAnalyticalDerivatives + } + + /** + * + * value. + * + * @param index a int. + * @return a double. + */ + fun value(index: Int): Double { + return theState.value(index) + } + + /** + * + * value. + * + * @param name a [String] object. + * @return a double. + */ + fun value(name: String?): Double { + return theState.value(name) + } + + /** + * + * variableParameters. + * + * @return a int. + */ + fun variableParameters(): Int { + return theState.variableParameters() + } + + companion object { + var DEFAULT_MAXFCN = 0 + var DEFAULT_STRATEGY = 1 + var DEFAULT_TOLER = 0.1 + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnContours.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnContours.kt new file mode 100644 index 000000000..1b700f4e2 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnContours.kt @@ -0,0 +1,283 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction +import ru.inr.mass.minuit.* + +/** + * API class for Contours error analysis (2-dim errors). Minimization has to be + * done before and minimum must be valid. Possibility to ask only for the points + * or the points and associated Minos errors. + * + * @version $Id$ + * @author Darksnake + */ +class MnContours(fcn: MultiFunction?, min: FunctionMinimum?, stra: MnStrategy?) { + private var theFCN: MultiFunction? = null + private var theMinimum: FunctionMinimum? = null + private var theStrategy: MnStrategy? = null + + /** + * construct from FCN + minimum + * + * @param fcn a [MultiFunction] object. + * @param min a [hep.dataforge.MINUIT.FunctionMinimum] object. + */ + constructor(fcn: MultiFunction?, min: FunctionMinimum?) : this(fcn, min, MnApplication.DEFAULT_STRATEGY) + + /** + * construct from FCN + minimum + strategy + * + * @param stra a int. + * @param min a [hep.dataforge.MINUIT.FunctionMinimum] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, min: FunctionMinimum?, stra: Int) : this(fcn, min, MnStrategy(stra)) + + /** + * + * contour. + * + * @param px a int. + * @param py a int. + * @return a [hep.dataforge.MINUIT.ContoursError] object. + */ + fun contour(px: Int, py: Int): ContoursError { + return contour(px, py, 1.0) + } + + /** + * + * contour. + * + * @param px a int. + * @param py a int. + * @param errDef a double. + * @return a [hep.dataforge.MINUIT.ContoursError] object. + */ + fun contour(px: Int, py: Int, errDef: Double): ContoursError { + return contour(px, py, errDef, 20) + } + + /** + * Causes a CONTOURS error analysis and returns the result in form of + * ContoursError. As a by-product ContoursError keeps the MinosError + * information of parameters parx and pary. The result ContoursError can be + * easily printed using MnPrint or toString(). + * + * @param npoints a int. + * @param px a int. + * @param py a int. + * @param errDef a double. + * @return a [hep.dataforge.MINUIT.ContoursError] object. + */ + fun contour(px: Int, py: Int, errDef: Double, npoints: Int): ContoursError { + var errDef = errDef + errDef *= theMinimum!!.errorDef() + assert(npoints > 3) + val maxcalls: Int = 100 * (npoints + 5) * (theMinimum!!.userState().variableParameters() + 1) + var nfcn = 0 + val result: MutableList = java.util.ArrayList(npoints) + val states: List = java.util.ArrayList() + val toler = 0.05 + + //get first four points + val minos = MnMinos(theFCN, theMinimum, theStrategy) + val valx: Double = theMinimum!!.userState().value(px) + val valy: Double = theMinimum!!.userState().value(py) + val mex: MinosError = minos.minos(px, errDef) + nfcn += mex.nfcn() + if (!mex.isValid()) { + MINUITPlugin.logStatic("MnContours is unable to find first two points.") + return ContoursError(px, py, result, mex, mex, nfcn) + } + val ex: Range = mex.range() + val mey: MinosError = minos.minos(py, errDef) + nfcn += mey.nfcn() + if (!mey.isValid()) { + MINUITPlugin.logStatic("MnContours is unable to find second two points.") + return ContoursError(px, py, result, mex, mey, nfcn) + } + val ey: Range = mey.range() + val migrad = MnMigrad(theFCN, + theMinimum!!.userState().copy(), + MnStrategy(max(0, theStrategy!!.strategy() - 1))) + migrad.fix(px) + migrad.setValue(px, valx + ex.getSecond()) + val exy_up: FunctionMinimum = migrad.minimize() + nfcn += exy_up.nfcn() + if (!exy_up.isValid()) { + MINUITPlugin.logStatic("MnContours is unable to find upper y value for x parameter $px.") + return ContoursError(px, py, result, mex, mey, nfcn) + } + migrad.setValue(px, valx + ex.getFirst()) + val exy_lo: FunctionMinimum = migrad.minimize() + nfcn += exy_lo.nfcn() + if (!exy_lo.isValid()) { + MINUITPlugin.logStatic("MnContours is unable to find lower y value for x parameter $px.") + return ContoursError(px, py, result, mex, mey, nfcn) + } + val migrad1 = MnMigrad(theFCN, + theMinimum!!.userState().copy(), + MnStrategy(max(0, theStrategy!!.strategy() - 1))) + migrad1.fix(py) + migrad1.setValue(py, valy + ey.getSecond()) + val eyx_up: FunctionMinimum = migrad1.minimize() + nfcn += eyx_up.nfcn() + if (!eyx_up.isValid()) { + MINUITPlugin.logStatic("MnContours is unable to find upper x value for y parameter $py.") + return ContoursError(px, py, result, mex, mey, nfcn) + } + migrad1.setValue(py, valy + ey.getFirst()) + val eyx_lo: FunctionMinimum = migrad1.minimize() + nfcn += eyx_lo.nfcn() + if (!eyx_lo.isValid()) { + MINUITPlugin.logStatic("MnContours is unable to find lower x value for y parameter $py.") + return ContoursError(px, py, result, mex, mey, nfcn) + } + val scalx: Double = 1.0 / (ex.getSecond() - ex.getFirst()) + val scaly: Double = 1.0 / (ey.getSecond() - ey.getFirst()) + result.add(Range(valx + ex.getFirst(), exy_lo.userState().value(py))) + result.add(Range(eyx_lo.userState().value(px), valy + ey.getFirst())) + result.add(Range(valx + ex.getSecond(), exy_up.userState().value(py))) + result.add(Range(eyx_up.userState().value(px), valy + ey.getSecond())) + val upar: MnUserParameterState = theMinimum!!.userState().copy() + upar.fix(px) + upar.fix(py) + val par = intArrayOf(px, py) + val cross = MnFunctionCross(theFCN, upar, theMinimum!!.fval(), theStrategy, errDef) + for (i in 4 until npoints) { + var idist1: Range = result[result.size - 1] + var idist2: Range = result[0] + var pos2 = 0 + val distx: Double = idist1.getFirst() - idist2.getFirst() + val disty: Double = idist1.getSecond() - idist2.getSecond() + var bigdis = scalx * scalx * distx * distx + scaly * scaly * disty * disty + for (j in 0 until result.size - 1) { + val ipair: Range = result[j] + val distx2: Double = ipair.getFirst() - result[j + 1].getFirst() + val disty2: Double = ipair.getSecond() - result[j + 1].getSecond() + val dist = scalx * scalx * distx2 * distx2 + scaly * scaly * disty2 * disty2 + if (dist > bigdis) { + bigdis = dist + idist1 = ipair + idist2 = result[j + 1] + pos2 = j + 1 + } + } + val a1 = 0.5 + val a2 = 0.5 + var sca = 1.0 + while (true) { + if (nfcn > maxcalls) { + MINUITPlugin.logStatic("MnContours: maximum number of function calls exhausted.") + return ContoursError(px, py, result, mex, mey, nfcn) + } + val xmidcr: Double = a1 * idist1.getFirst() + a2 * idist2.getFirst() + val ymidcr: Double = a1 * idist1.getSecond() + a2 * idist2.getSecond() + val xdir: Double = idist2.getSecond() - idist1.getSecond() + val ydir: Double = idist1.getFirst() - idist2.getFirst() + val scalfac: Double = + sca * max(abs(xdir * scalx), abs(ydir * scaly)) + val xdircr = xdir / scalfac + val ydircr = ydir / scalfac + val pmid = doubleArrayOf(xmidcr, ymidcr) + val pdir = doubleArrayOf(xdircr, ydircr) + val opt: MnCross = cross.cross(par, pmid, pdir, toler, maxcalls) + nfcn += opt.nfcn() + if (opt.isValid()) { + val aopt: Double = opt.value() + if (pos2 == 0) { + result.add(Range(xmidcr + aopt * xdircr, ymidcr + aopt * ydircr)) + } else { + result.add(pos2, Range(xmidcr + aopt * xdircr, ymidcr + aopt * ydircr)) + } + break + } + if (sca < 0.0) { + MINUITPlugin.logStatic("MnContours is unable to find point " + (i + 1) + " on contour.") + MINUITPlugin.logStatic("MnContours finds only $i points.") + return ContoursError(px, py, result, mex, mey, nfcn) + } + sca = -1.0 + } + } + return ContoursError(px, py, result, mex, mey, nfcn) + } + + /** + * + * points. + * + * @param px a int. + * @param py a int. + * @return a [List] object. + */ + fun points(px: Int, py: Int): List { + return points(px, py, 1.0) + } + + /** + * + * points. + * + * @param px a int. + * @param py a int. + * @param errDef a double. + * @return a [List] object. + */ + fun points(px: Int, py: Int, errDef: Double): List { + return points(px, py, errDef, 20) + } + + /** + * Calculates one function contour of FCN with respect to parameters parx + * and pary. The return value is a list of (x,y) points. FCN minimized + * always with respect to all other n - 2 variable parameters (if any). + * MINUITPlugin will try to find n points on the contour (default 20). To + * calculate more than one contour, the user needs to set the error + * definition in its FCN to the appropriate value for the desired confidence + * level and call this method for each contour. + * + * @param npoints a int. + * @param px a int. + * @param py a int. + * @param errDef a double. + * @return a [List] object. + */ + fun points(px: Int, py: Int, errDef: Double, npoints: Int): List { + val cont: ContoursError = contour(px, py, errDef, npoints) + return cont.points() + } + + fun strategy(): MnStrategy? { + return theStrategy + } + + /** + * construct from FCN + minimum + strategy + * + * @param stra a [hep.dataforge.MINUIT.MnStrategy] object. + * @param min a [hep.dataforge.MINUIT.FunctionMinimum] object. + * @param fcn a [MultiFunction] object. + */ + init { + theFCN = fcn + theMinimum = min + theStrategy = stra + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCovarianceSqueeze.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCovarianceSqueeze.kt new file mode 100644 index 000000000..7614a93b0 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCovarianceSqueeze.kt @@ -0,0 +1,113 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import space.kscience.kmath.optimization.minuit.MINUITPlugin + +/** + * + * @version $Id$ + */ +internal object MnCovarianceSqueeze { + fun squeeze(cov: MnUserCovariance, n: Int): MnUserCovariance { + assert(cov.nrow() > 0) + assert(n < cov.nrow()) + val hess = MnAlgebraicSymMatrix(cov.nrow()) + for (i in 0 until cov.nrow()) { + for (j in i until cov.nrow()) { + hess[i, j] = cov[i, j] + } + } + try { + hess.invert() + } catch (x: SingularMatrixException) { + MINUITPlugin.logStatic("MnUserCovariance inversion failed; return diagonal matrix;") + val result = MnUserCovariance(cov.nrow() - 1) + var i = 0 + var j = 0 + while (i < cov.nrow()) { + if (i == n) { + i++ + continue + } + result[j, j] = cov[i, i] + j++ + i++ + } + return result + } + val squeezed: MnAlgebraicSymMatrix = squeeze(hess, n) + try { + squeezed.invert() + } catch (x: SingularMatrixException) { + MINUITPlugin.logStatic("MnUserCovariance back-inversion failed; return diagonal matrix;") + val result = MnUserCovariance(squeezed.nrow()) + var i = 0 + while (i < squeezed.nrow()) { + result[i, i] = 1.0 / squeezed[i, i] + i++ + } + return result + } + return MnUserCovariance(squeezed.data(), squeezed.nrow()) + } + + fun squeeze(err: MinimumError, n: Int): MinimumError { + val hess: MnAlgebraicSymMatrix = err.hessian() + val squeezed: MnAlgebraicSymMatrix = squeeze(hess, n) + try { + squeezed.invert() + } catch (x: SingularMatrixException) { + MINUITPlugin.logStatic("MnCovarianceSqueeze: MinimumError inversion fails; return diagonal matrix.") + val tmp = MnAlgebraicSymMatrix(squeezed.nrow()) + var i = 0 + while (i < squeezed.nrow()) { + tmp[i, i] = 1.0 / squeezed[i, i] + i++ + } + return MinimumError(tmp, MnInvertFailed()) + } + return MinimumError(squeezed, err.dcovar()) + } + + fun squeeze(hess: MnAlgebraicSymMatrix, n: Int): MnAlgebraicSymMatrix { + assert(hess.nrow() > 0) + assert(n < hess.nrow()) + val hs = MnAlgebraicSymMatrix(hess.nrow() - 1) + var i = 0 + var j = 0 + while (i < hess.nrow()) { + if (i == n) { + i++ + continue + } + var k = i + var l = j + while (k < hess.nrow()) { + if (k == n) { + k++ + continue + } + hs[j, l] = hess[i, k] + l++ + k++ + } + j++ + i++ + } + return hs + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCross.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCross.kt new file mode 100644 index 000000000..f1487b106 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCross.kt @@ -0,0 +1,99 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * MnCross class. + * + * @version $Id$ + * @author Darksnake + */ +class MnCross { + private var theLimset = false + private var theMaxFcn = false + private var theNFcn = 0 + private var theNewMin = false + private var theState: MnUserParameterState + private var theValid = false + private var theValue = 0.0 + + internal constructor() { + theState = MnUserParameterState() + } + + internal constructor(nfcn: Int) { + theState = MnUserParameterState() + theNFcn = nfcn + } + + internal constructor(value: Double, state: MnUserParameterState, nfcn: Int) { + theValue = value + theState = state + theNFcn = nfcn + theValid = true + } + + internal constructor(state: MnUserParameterState, nfcn: Int, x: CrossParLimit?) { + theState = state + theNFcn = nfcn + theLimset = true + } + + internal constructor(state: MnUserParameterState, nfcn: Int, x: CrossFcnLimit?) { + theState = state + theNFcn = nfcn + theMaxFcn = true + } + + internal constructor(state: MnUserParameterState, nfcn: Int, x: CrossNewMin?) { + theState = state + theNFcn = nfcn + theNewMin = true + } + + fun atLimit(): Boolean { + return theLimset + } + + fun atMaxFcn(): Boolean { + return theMaxFcn + } + + fun isValid(): Boolean { + return theValid + } + + fun newMinimum(): Boolean { + return theNewMin + } + + fun nfcn(): Int { + return theNFcn + } + + fun state(): MnUserParameterState { + return theState + } + + fun value(): Double { + return theValue + } + + internal class CrossFcnLimit + internal class CrossNewMin + internal class CrossParLimit +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnEigen.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnEigen.kt new file mode 100644 index 000000000..d7aade0c9 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnEigen.kt @@ -0,0 +1,50 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.RealVector + +/** + * Calculates and the eigenvalues of the user covariance matrix + * MnUserCovariance. + * + * @version $Id$ + * @author Darksnake + */ +object MnEigen { + /* Calculate eigenvalues of the covariance matrix. + * Will perform the calculation of the eigenvalues of the covariance matrix + * and return the result in the form of a double array. + * The eigenvalues are ordered from the smallest to the largest eigenvalue. + */ + /** + * + * eigenvalues. + * + * @param covar a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @return an array of double. + */ + fun eigenvalues(covar: MnUserCovariance): DoubleArray { + val cov = MnAlgebraicSymMatrix(covar.nrow()) + for (i in 0 until covar.nrow()) { + for (j in i until covar.nrow()) { + cov[i, j] = covar[i, j] + } + } + val eigen: RealVector = cov.eigenvalues() + return eigen.toArray() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFcn.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFcn.kt new file mode 100644 index 000000000..b11f71035 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFcn.kt @@ -0,0 +1,50 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction + +/** + * Функция, которая помнит количество вызовов себя и ErrorDef + * @version $Id$ + */ +class MnFcn(fcn: MultiFunction?, errorDef: Double) { + private val theErrorDef: Double + private val theFCN: MultiFunction? + protected var theNumCall: Int + fun errorDef(): Double { + return theErrorDef + } + + fun fcn(): MultiFunction? { + return theFCN + } + + fun numOfCalls(): Int { + return theNumCall + } + + fun value(v: RealVector): Double { + theNumCall++ + return theFCN.value(v.toArray()) + } + + init { + theFCN = fcn + theNumCall = 0 + theErrorDef = errorDef + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFunctionCross.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFunctionCross.kt new file mode 100644 index 000000000..a05590e53 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFunctionCross.kt @@ -0,0 +1,369 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction +import ru.inr.mass.minuit.* +import kotlin.math.* + +/** + * + * @version $Id$ + */ +internal class MnFunctionCross( + fcn: MultiFunction?, + state: MnUserParameterState, + fval: Double, + stra: MnStrategy?, + errorDef: Double +) { + private val theErrorDef: Double + private val theFCN: MultiFunction? + private val theFval: Double + private val theState: MnUserParameterState + private val theStrategy: MnStrategy? + fun cross(par: IntArray, pmid: DoubleArray, pdir: DoubleArray, tlr: Double, maxcalls: Int): MnCross { + val npar = par.size + var nfcn = 0 + val prec: MnMachinePrecision = theState.precision() + val tlf = tlr * theErrorDef + var tla = tlr + val maxitr = 15 + var ipt = 0 + val aminsv = theFval + val aim = aminsv + theErrorDef + var aopt = 0.0 + var limset = false + val alsb = DoubleArray(3) + val flsb = DoubleArray(3) + val up = theErrorDef + var aulim = 100.0 + for (i in par.indices) { + val kex = par[i] + if (theState.parameter(kex).hasLimits()) { + val zmid = pmid[i] + val zdir = pdir[i] + if (abs(zdir) < theState.precision().eps()) { + continue + } + if (zdir > 0.0 && theState.parameter(kex).hasUpperLimit()) { + val zlim: Double = theState.parameter(kex).upperLimit() + aulim = min(aulim, (zlim - zmid) / zdir) + } else if (zdir < 0.0 && theState.parameter(kex).hasLowerLimit()) { + val zlim: Double = theState.parameter(kex).lowerLimit() + aulim = min(aulim, (zlim - zmid) / zdir) + } + } + } + if (aulim < aopt + tla) { + limset = true + } + val migrad = MnMigrad(theFCN, theState, MnStrategy(max(0, theStrategy!!.strategy() - 1))) + for (i in 0 until npar) { + migrad.setValue(par[i], pmid[i]) + } + val min0: FunctionMinimum = migrad.minimize(maxcalls, tlr) + nfcn += min0.nfcn() + if (min0.hasReachedCallLimit()) { + return MnCross(min0.userState(), nfcn, MnCross.CrossFcnLimit()) + } + if (!min0.isValid()) { + return MnCross(nfcn) + } + if (limset && min0.fval() < aim) { + return MnCross(min0.userState(), nfcn, MnCross.CrossParLimit()) + } + ipt++ + alsb[0] = 0.0 + flsb[0] = min0.fval() + flsb[0] = max(flsb[0], aminsv + 0.1 * up) + aopt = sqrt(up / (flsb[0] - aminsv)) - 1.0 + if (abs(flsb[0] - aim) < tlf) { + return MnCross(aopt, min0.userState(), nfcn) + } + if (aopt > 1.0) { + aopt = 1.0 + } + if (aopt < -0.5) { + aopt = -0.5 + } + limset = false + if (aopt > aulim) { + aopt = aulim + limset = true + } + for (i in 0 until npar) { + migrad.setValue(par[i], pmid[i] + aopt * pdir[i]) + } + var min1: FunctionMinimum = migrad.minimize(maxcalls, tlr) + nfcn += min1.nfcn() + if (min1.hasReachedCallLimit()) { + return MnCross(min1.userState(), nfcn, MnCross.CrossFcnLimit()) + } + if (!min1.isValid()) { + return MnCross(nfcn) + } + if (limset && min1.fval() < aim) { + return MnCross(min1.userState(), nfcn, MnCross.CrossParLimit()) + } + ipt++ + alsb[1] = aopt + flsb[1] = min1.fval() + var dfda = (flsb[1] - flsb[0]) / (alsb[1] - alsb[0]) + var ecarmn = 0.0 + var ecarmx = 0.0 + var ibest = 0 + var iworst = 0 + var noless = 0 + var min2: FunctionMinimum? = null + L300@ while (true) { + if (dfda < 0.0) { + val maxlk = maxitr - ipt + for (it in 0 until maxlk) { + alsb[0] = alsb[1] + flsb[0] = flsb[1] + aopt = alsb[0] + 0.2 * it + limset = false + if (aopt > aulim) { + aopt = aulim + limset = true + } + for (i in 0 until npar) { + migrad.setValue(par[i], pmid[i] + aopt * pdir[i]) + } + min1 = migrad.minimize(maxcalls, tlr) + nfcn += min1.nfcn() + if (min1.hasReachedCallLimit()) { + return MnCross(min1.userState(), nfcn, MnCross.CrossFcnLimit()) + } + if (!min1.isValid()) { + return MnCross(nfcn) + } + if (limset && min1.fval() < aim) { + return MnCross(min1.userState(), nfcn, MnCross.CrossParLimit()) + } + ipt++ + alsb[1] = aopt + flsb[1] = min1.fval() + dfda = (flsb[1] - flsb[0]) / (alsb[1] - alsb[0]) + if (dfda > 0.0) { + break + } + } + if (ipt > maxitr) { + return MnCross(nfcn) + } + } + L460@ while (true) { + aopt = alsb[1] + (aim - flsb[1]) / dfda + val fdist: Double = + min(abs(aim - flsb[0]), abs(aim - flsb[1])) + val adist: Double = + min(abs(aopt - alsb[0]), abs(aopt - alsb[1])) + tla = tlr + if (abs(aopt) > 1.0) { + tla = tlr * abs(aopt) + } + if (adist < tla && fdist < tlf) { + return MnCross(aopt, min1.userState(), nfcn) + } + if (ipt > maxitr) { + return MnCross(nfcn) + } + val bmin: Double = min(alsb[0], alsb[1]) - 1.0 + if (aopt < bmin) { + aopt = bmin + } + val bmax: Double = max(alsb[0], alsb[1]) + 1.0 + if (aopt > bmax) { + aopt = bmax + } + limset = false + if (aopt > aulim) { + aopt = aulim + limset = true + } + for (i in 0 until npar) { + migrad.setValue(par[i], pmid[i] + aopt * pdir[i]) + } + min2 = migrad.minimize(maxcalls, tlr) + nfcn += min2.nfcn() + if (min2.hasReachedCallLimit()) { + return MnCross(min2.userState(), nfcn, CrossFcnLimit()) + } + if (!min2.isValid()) { + return MnCross(nfcn) + } + if (limset && min2.fval() < aim) { + return MnCross(min2.userState(), nfcn, MnCross.CrossParLimit()) + } + ipt++ + alsb[2] = aopt + flsb[2] = min2.fval() + ecarmn = abs(flsb[2] - aim) + ecarmx = 0.0 + ibest = 2 + iworst = 0 + noless = 0 + for (i in 0..2) { + val ecart: Double = abs(flsb[i] - aim) + if (ecart > ecarmx) { + ecarmx = ecart + iworst = i + } + if (ecart < ecarmn) { + ecarmn = ecart + ibest = i + } + if (flsb[i] < aim) { + noless++ + } + } + if (noless == 1 || noless == 2) { + break@L300 + } + if (noless == 0 && ibest != 2) { + return MnCross(nfcn) + } + if (noless == 3 && ibest != 2) { + alsb[1] = alsb[2] + flsb[1] = flsb[2] + continue@L300 + } + flsb[iworst] = flsb[2] + alsb[iworst] = alsb[2] + dfda = (flsb[1] - flsb[0]) / (alsb[1] - alsb[0]) + } + } + do { + val parbol: MnParabola = MnParabolaFactory.create(MnParabolaPoint(alsb[0], flsb[0]), + MnParabolaPoint(alsb[1], flsb[1]), + MnParabolaPoint( + alsb[2], flsb[2])) + val coeff1: Double = parbol.c() + val coeff2: Double = parbol.b() + val coeff3: Double = parbol.a() + val determ = coeff2 * coeff2 - 4.0 * coeff3 * (coeff1 - aim) + if (determ < prec.eps()) { + return MnCross(nfcn) + } + val rt: Double = sqrt(determ) + val x1 = (-coeff2 + rt) / (2.0 * coeff3) + val x2 = (-coeff2 - rt) / (2.0 * coeff3) + val s1 = coeff2 + 2.0 * x1 * coeff3 + val s2 = coeff2 + 2.0 * x2 * coeff3 + if (s1 * s2 > 0.0) { + MINUITPlugin.logStatic("MnFunctionCross problem 1") + } + aopt = x1 + var slope = s1 + if (s2 > 0.0) { + aopt = x2 + slope = s2 + } + tla = tlr + if (abs(aopt) > 1.0) { + tla = tlr * abs(aopt) + } + if (abs(aopt - alsb[ibest]) < tla && abs(flsb[ibest] - aim) < tlf) { + return MnCross(aopt, min2!!.userState(), nfcn) + } + var ileft = 3 + var iright = 3 + var iout = 3 + ibest = 0 + ecarmx = 0.0 + ecarmn = abs(aim - flsb[0]) + for (i in 0..2) { + val ecart: Double = abs(flsb[i] - aim) + if (ecart < ecarmn) { + ecarmn = ecart + ibest = i + } + if (ecart > ecarmx) { + ecarmx = ecart + } + if (flsb[i] > aim) { + if (iright == 3) { + iright = i + } else if (flsb[i] > flsb[iright]) { + iout = i + } else { + iout = iright + iright = i + } + } else if (ileft == 3) { + ileft = i + } else if (flsb[i] < flsb[ileft]) { + iout = i + } else { + iout = ileft + ileft = i + } + } + if (ecarmx > 10.0 * abs(flsb[iout] - aim)) { + aopt = 0.5 * (aopt + 0.5 * (alsb[iright] + alsb[ileft])) + } + var smalla = 0.1 * tla + if (slope * smalla > tlf) { + smalla = tlf / slope + } + val aleft = alsb[ileft] + smalla + val aright = alsb[iright] - smalla + if (aopt < aleft) { + aopt = aleft + } + if (aopt > aright) { + aopt = aright + } + if (aleft > aright) { + aopt = 0.5 * (aleft + aright) + } + limset = false + if (aopt > aulim) { + aopt = aulim + limset = true + } + for (i in 0 until npar) { + migrad.setValue(par[i], pmid[i] + aopt * pdir[i]) + } + min2 = migrad.minimize(maxcalls, tlr) + nfcn += min2.nfcn() + if (min2.hasReachedCallLimit()) { + return MnCross(min2.userState(), nfcn, CrossFcnLimit()) + } + if (!min2.isValid()) { + return MnCross(nfcn) + } + if (limset && min2.fval() < aim) { + return MnCross(min2.userState(), nfcn, CrossParLimit()) + } + ipt++ + alsb[iout] = aopt + flsb[iout] = min2.fval() + ibest = iout + } while (ipt < maxitr) + return MnCross(nfcn) + } + + init { + theFCN = fcn + theState = state + theFval = fval + theStrategy = stra + theErrorDef = errorDef + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnGlobalCorrelationCoeff.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnGlobalCorrelationCoeff.kt new file mode 100644 index 000000000..939dd7fa0 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnGlobalCorrelationCoeff.kt @@ -0,0 +1,79 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.SingularMatrixException + +/** + * + * MnGlobalCorrelationCoeff class. + * + * @version $Id$ + * @author Darksnake + */ +class MnGlobalCorrelationCoeff { + private var theGlobalCC: DoubleArray + private var theValid = false + + internal constructor() { + theGlobalCC = DoubleArray(0) + } + + internal constructor(cov: MnAlgebraicSymMatrix) { + try { + val inv: MnAlgebraicSymMatrix = cov.copy() + inv.invert() + theGlobalCC = DoubleArray(cov.nrow()) + for (i in 0 until cov.nrow()) { + val denom: Double = inv[i, i] * cov[i, i] + if (denom < 1.0 && denom > 0.0) { + theGlobalCC[i] = 0 + } else { + theGlobalCC[i] = sqrt(1.0 - 1.0 / denom) + } + } + theValid = true + } catch (x: SingularMatrixException) { + theValid = false + theGlobalCC = DoubleArray(0) + } + } + + /** + * + * globalCC. + * + * @return an array of double. + */ + fun globalCC(): DoubleArray { + return theGlobalCC + } + + /** + * + * isValid. + * + * @return a boolean. + */ + fun isValid(): Boolean { + return theValid + } + + /** {@inheritDoc} */ + override fun toString(): String { + return MnPrint.toString(this) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnHesse.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnHesse.kt new file mode 100644 index 000000000..3bb6c4551 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnHesse.kt @@ -0,0 +1,371 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction +import ru.inr.mass.minuit.* + +/** + * With MnHesse the user can instructs MINUITPlugin to calculate, by finite + * differences, the Hessian or error matrix. That is, it calculates the full + * matrix of second derivatives of the function with respect to the currently + * variable parameters, and inverts it. + * + * @version $Id$ + * @author Darksnake + */ +class MnHesse { + private var theStrategy: MnStrategy + + /** + * default constructor with default strategy + */ + constructor() { + theStrategy = MnStrategy(1) + } + + /** + * constructor with user-defined strategy level + * + * @param stra a int. + */ + constructor(stra: Int) { + theStrategy = MnStrategy(stra) + } + + /** + * conctructor with specific strategy + * + * @param stra a [hep.dataforge.MINUIT.MnStrategy] object. + */ + constructor(stra: MnStrategy) { + theStrategy = stra + } + /// + /// low-level API + /// + /** + * + * calculate. + * + * @param fcn a [MultiFunction] object. + * @param par an array of double. + * @param err an array of double. + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun calculate(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray): MnUserParameterState { + return calculate(fcn, par, err, 0) + } + + /** + * FCN + parameters + errors + * + * @param maxcalls a int. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + * @param err an array of double. + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun calculate(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray, maxcalls: Int): MnUserParameterState { + return calculate(fcn, MnUserParameterState(par, err), maxcalls) + } + + /** + * + * calculate. + * + * @param fcn a [MultiFunction] object. + * @param par an array of double. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun calculate(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance): MnUserParameterState { + return calculate(fcn, par, cov, 0) + } + + /** + * FCN + parameters + MnUserCovariance + * + * @param maxcalls a int. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun calculate(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance, maxcalls: Int): MnUserParameterState { + return calculate(fcn, MnUserParameterState(par, cov), maxcalls) + } + /// + /// high-level API + /// + /** + * + * calculate. + * + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun calculate(fcn: MultiFunction?, par: MnUserParameters): MnUserParameterState { + return calculate(fcn, par, 0) + } + + /** + * FCN + MnUserParameters + * + * @param maxcalls a int. + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun calculate(fcn: MultiFunction?, par: MnUserParameters, maxcalls: Int): MnUserParameterState { + return calculate(fcn, MnUserParameterState(par), maxcalls) + } + + /** + * + * calculate. + * + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun calculate(fcn: MultiFunction?, par: MnUserParameters, cov: MnUserCovariance?): MnUserParameterState { + return calculate(fcn, par, 0) + } + + /** + * FCN + MnUserParameters + MnUserCovariance + * + * @param maxcalls a int. + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun calculate( + fcn: MultiFunction?, + par: MnUserParameters, + cov: MnUserCovariance, + maxcalls: Int + ): MnUserParameterState { + return calculate(fcn, MnUserParameterState(par, cov), maxcalls) + } + + /** + * FCN + MnUserParameterState + * + * @param maxcalls a int. + * @param fcn a [MultiFunction] object. + * @param state a [hep.dataforge.MINUIT.MnUserParameterState] object. + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun calculate(fcn: MultiFunction?, state: MnUserParameterState, maxcalls: Int): MnUserParameterState { + val errDef = 1.0 // FixMe! + val n: Int = state.variableParameters() + val mfcn = MnUserFcn(fcn, errDef, state.getTransformation()) + val x: RealVector = ArrayRealVector(n) + for (i in 0 until n) { + x.setEntry(i, state.intParameters()[i]) + } + val amin: Double = mfcn.value(x) + val gc = Numerical2PGradientCalculator(mfcn, state.getTransformation(), theStrategy) + val par = MinimumParameters(x, amin) + val gra: FunctionGradient = gc.gradient(par) + val tmp: MinimumState = calculate(mfcn, + MinimumState(par, MinimumError(MnAlgebraicSymMatrix(n), 1.0), gra, state.edm(), state.nfcn()), + state.getTransformation(), + maxcalls) + return MnUserParameterState(tmp, errDef, state.getTransformation()) + } + + /// + /// internal interface + /// + fun calculate(mfcn: MnFcn, st: MinimumState, trafo: MnUserTransformation, maxcalls: Int): MinimumState { + var maxcalls = maxcalls + val prec: MnMachinePrecision = trafo.precision() + // make sure starting at the right place + val amin: Double = mfcn.value(st.vec()) + val aimsag: Double = sqrt(prec.eps2()) * (abs(amin) + mfcn.errorDef()) + + // diagonal elements first + val n: Int = st.parameters().vec().getDimension() + if (maxcalls == 0) { + maxcalls = 200 + 100 * n + 5 * n * n + } + var vhmat = MnAlgebraicSymMatrix(n) + var g2: RealVector = st.gradient().getGradientDerivative().copy() + var gst: RealVector = st.gradient().getStep().copy() + var grd: RealVector = st.gradient().getGradient().copy() + var dirin: RealVector = st.gradient().getStep().copy() + val yy: RealVector = ArrayRealVector(n) + if (st.gradient().isAnalytical()) { + val igc = InitialGradientCalculator(mfcn, trafo, theStrategy) + val tmp: FunctionGradient = igc.gradient(st.parameters()) + gst = tmp.getStep().copy() + dirin = tmp.getStep().copy() + g2 = tmp.getGradientDerivative().copy() + } + return try { + val x: RealVector = st.parameters().vec().copy() + for (i in 0 until n) { + val xtf: Double = x.getEntry(i) + val dmin: Double = 8.0 * prec.eps2() * (abs(xtf) + prec.eps2()) + var d: Double = abs(gst.getEntry(i)) + if (d < dmin) { + d = dmin + } + for (icyc in 0 until ncycles()) { + var sag = 0.0 + var fs1 = 0.0 + var fs2 = 0.0 + var multpy = 0 + while (multpy < 5) { + x.setEntry(i, xtf + d) + fs1 = mfcn.value(x) + x.setEntry(i, xtf - d) + fs2 = mfcn.value(x) + x.setEntry(i, xtf) + sag = 0.5 * (fs1 + fs2 - 2.0 * amin) + if (sag > prec.eps2()) { + break + } + if (trafo.parameter(i).hasLimits()) { + if (d > 0.5) { + throw MnHesseFailedException("MnHesse: 2nd derivative zero for parameter") + } + d *= 10.0 + if (d > 0.5) { + d = 0.51 + } + multpy++ + continue + } + d *= 10.0 + multpy++ + } + if (multpy >= 5) { + throw MnHesseFailedException("MnHesse: 2nd derivative zero for parameter") + } + val g2bfor: Double = g2.getEntry(i) + g2.setEntry(i, 2.0 * sag / (d * d)) + grd.setEntry(i, (fs1 - fs2) / (2.0 * d)) + gst.setEntry(i, d) + dirin.setEntry(i, d) + yy.setEntry(i, fs1) + val dlast = d + d = sqrt(2.0 * aimsag / abs(g2.getEntry(i))) + if (trafo.parameter(i).hasLimits()) { + d = min(0.5, d) + } + if (d < dmin) { + d = dmin + } + + // see if converged + if (abs((d - dlast) / d) < tolerstp()) { + break + } + if (abs((g2.getEntry(i) - g2bfor) / g2.getEntry(i)) < tolerg2()) { + break + } + d = min(d, 10.0 * dlast) + d = max(d, 0.1 * dlast) + } + vhmat[i, i] = g2.getEntry(i) + if (mfcn.numOfCalls() - st.nfcn() > maxcalls) { + throw MnHesseFailedException("MnHesse: maximum number of allowed function calls exhausted.") + } + } + if (theStrategy.strategy() > 0) { + // refine first derivative + val hgc = HessianGradientCalculator(mfcn, trafo, theStrategy) + val gr: FunctionGradient = hgc.gradient(st.parameters(), FunctionGradient(grd, g2, gst)) + grd = gr.getGradient() + } + + //off-diagonal elements + for (i in 0 until n) { + x.setEntry(i, x.getEntry(i) + dirin.getEntry(i)) + for (j in i + 1 until n) { + x.setEntry(j, x.getEntry(j) + dirin.getEntry(j)) + val fs1: Double = mfcn.value(x) + val elem: Double = + (fs1 + amin - yy.getEntry(i) - yy.getEntry(j)) / (dirin.getEntry(i) * dirin.getEntry(j)) + vhmat[i, j] = elem + x.setEntry(j, x.getEntry(j) - dirin.getEntry(j)) + } + x.setEntry(i, x.getEntry(i) - dirin.getEntry(i)) + } + + //verify if matrix pos-def (still 2nd derivative) + val tmp: MinimumError = MnPosDef.test(MinimumError(vhmat, 1.0), prec) + vhmat = tmp.invHessian() + try { + vhmat.invert() + } catch (xx: SingularMatrixException) { + throw MnHesseFailedException("MnHesse: matrix inversion fails!") + } + val gr = FunctionGradient(grd, g2, gst) + if (tmp.isMadePosDef()) { + MINUITPlugin.logStatic("MnHesse: matrix is invalid!") + MINUITPlugin.logStatic("MnHesse: matrix is not pos. def.!") + MINUITPlugin.logStatic("MnHesse: matrix was forced pos. def.") + return MinimumState(st.parameters(), + MinimumError(vhmat, MnMadePosDef()), + gr, + st.edm(), + mfcn.numOfCalls()) + } + + //calculate edm + val err = MinimumError(vhmat, 0.0) + val edm: Double = VariableMetricEDMEstimator().estimate(gr, err) + MinimumState(st.parameters(), err, gr, edm, mfcn.numOfCalls()) + } catch (x: MnHesseFailedException) { + MINUITPlugin.logStatic(x.message) + MINUITPlugin.logStatic("MnHesse fails and will return diagonal matrix ") + var j = 0 + while (j < n) { + val tmp = if (g2.getEntry(j) < prec.eps2()) 1.0 else 1.0 / g2.getEntry(j) + vhmat[j, j] = if (tmp < prec.eps2()) 1.0 else tmp + j++ + } + MinimumState(st.parameters(), + MinimumError(vhmat, MnHesseFailed()), + st.gradient(), + st.edm(), + st.nfcn() + mfcn.numOfCalls()) + } + } + + /// forward interface of MnStrategy + fun ncycles(): Int { + return theStrategy.hessianNCycles() + } + + fun tolerg2(): Double { + return theStrategy.hessianG2Tolerance() + } + + fun tolerstp(): Double { + return theStrategy.hessianStepTolerance() + } + + private inner class MnHesseFailedException(message: String?) : java.lang.Exception(message) +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnLineSearch.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnLineSearch.kt new file mode 100644 index 000000000..7b1171d3c --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnLineSearch.kt @@ -0,0 +1,204 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.RealVector +import ru.inr.mass.minuit.* + +/** + * + * @version $Id$ + */ +internal object MnLineSearch { + fun search( + fcn: MnFcn, + st: MinimumParameters, + step: RealVector, + gdel: Double, + prec: MnMachinePrecision + ): MnParabolaPoint { + var overal = 1000.0 + var undral = -100.0 + val toler = 0.05 + var slamin = 0.0 + val slambg = 5.0 + val alpha = 2.0 + val maxiter = 12 + var niter = 0 + for (i in 0 until step.getDimension()) { + if (abs(step.getEntry(i)) < prec.eps()) { + continue + } + val ratio: Double = abs(st.vec().getEntry(i) / step.getEntry(i)) + if (abs(slamin) < prec.eps()) { + slamin = ratio + } + if (ratio < slamin) { + slamin = ratio + } + } + if (abs(slamin) < prec.eps()) { + slamin = prec.eps() + } + slamin *= prec.eps2() + val F0: Double = st.fval() + val F1: Double = fcn.value(MnUtils.add(st.vec(), step)) + var fvmin: Double = st.fval() + var xvmin = 0.0 + if (F1 < F0) { + fvmin = F1 + xvmin = 1.0 + } + var toler8 = toler + var slamax = slambg + var flast = F1 + var slam = 1.0 + var iterate = false + var p0 = MnParabolaPoint(0.0, F0) + var p1 = MnParabolaPoint(slam, flast) + var F2 = 0.0 + do { + // cut toler8 as function goes up + iterate = false + val pb: MnParabola = MnParabolaFactory.create(p0, gdel, p1) + var denom = 2.0 * (flast - F0 - gdel * slam) / (slam * slam) + if (abs(denom) < prec.eps()) { + denom = -0.1 * gdel + slam = 1.0 + } + if (abs(denom) > prec.eps()) { + slam = -gdel / denom + } + if (slam < 0.0) { + slam = slamax + } + if (slam > slamax) { + slam = slamax + } + if (slam < toler8) { + slam = toler8 + } + if (slam < slamin) { + return MnParabolaPoint(xvmin, fvmin) + } + if (abs(slam - 1.0) < toler8 && p1.y() < p0.y()) { + return MnParabolaPoint(xvmin, fvmin) + } + if (abs(slam - 1.0) < toler8) { + slam = 1.0 + toler8 + } + F2 = fcn.value(MnUtils.add(st.vec(), MnUtils.mul(step, slam))) + if (F2 < fvmin) { + fvmin = F2 + xvmin = slam + } + if (p0.y() - prec.eps() < fvmin && fvmin < p0.y() + prec.eps()) { + iterate = true + flast = F2 + toler8 = toler * slam + overal = slam - toler8 + slamax = overal + p1 = MnParabolaPoint(slam, flast) + niter++ + } + } while (iterate && niter < maxiter) + if (niter >= maxiter) { + // exhausted max number of iterations + return MnParabolaPoint(xvmin, fvmin) + } + var p2 = MnParabolaPoint(slam, F2) + do { + slamax = max(slamax, alpha * abs(xvmin)) + val pb: MnParabola = MnParabolaFactory.create(p0, p1, p2) + if (pb.a() < prec.eps2()) { + val slopem: Double = 2.0 * pb.a() * xvmin + pb.b() + slam = if (slopem < 0.0) { + xvmin + slamax + } else { + xvmin - slamax + } + } else { + slam = pb.min() + if (slam > xvmin + slamax) { + slam = xvmin + slamax + } + if (slam < xvmin - slamax) { + slam = xvmin - slamax + } + } + if (slam > 0.0) { + if (slam > overal) { + slam = overal + } + } else { + if (slam < undral) { + slam = undral + } + } + var F3 = 0.0 + do { + iterate = false + val toler9: Double = max(toler8, abs(toler8 * slam)) + // min. of parabola at one point + if (abs(p0.x() - slam) < toler9 || abs(p1.x() - slam) < toler9 || abs( + p2.x() - slam) < toler9 + ) { + return MnParabolaPoint(xvmin, fvmin) + } + F3 = fcn.value(MnUtils.add(st.vec(), MnUtils.mul(step, slam))) + // if latest point worse than all three previous, cut step + if (F3 > p0.y() && F3 > p1.y() && F3 > p2.y()) { + if (slam > xvmin) { + overal = min(overal, slam - toler8) + } + if (slam < xvmin) { + undral = max(undral, slam + toler8) + } + slam = 0.5 * (slam + xvmin) + iterate = true + niter++ + } + } while (iterate && niter < maxiter) + if (niter >= maxiter) { + // exhausted max number of iterations + return MnParabolaPoint(xvmin, fvmin) + } + + // find worst previous point out of three and replace + val p3 = MnParabolaPoint(slam, F3) + if (p0.y() > p1.y() && p0.y() > p2.y()) { + p0 = p3 + } else if (p1.y() > p0.y() && p1.y() > p2.y()) { + p1 = p3 + } else { + p2 = p3 + } + if (F3 < fvmin) { + fvmin = F3 + xvmin = slam + } else { + if (slam > xvmin) { + overal = min(overal, slam - toler8) + } + if (slam < xvmin) { + undral = max(undral, slam + toler8) + } + } + niter++ + } while (niter < maxiter) + return MnParabolaPoint(xvmin, fvmin) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMachinePrecision.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMachinePrecision.kt new file mode 100644 index 000000000..161ee0c0a --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMachinePrecision.kt @@ -0,0 +1,71 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * Determines the relative floating point arithmetic precision. The + * setPrecision() method can be used to override Minuit's own determination, + * when the user knows that the {FCN} function value is not calculated to the + * nominal machine accuracy. + * + * @version $Id$ + * @author Darksnake + */ +class MnMachinePrecision internal constructor() { + private var theEpsMa2 = 0.0 + private var theEpsMac = 0.0 + + /** + * eps returns the smallest possible number so that 1.+eps > 1. + * @return + */ + fun eps(): Double { + return theEpsMac + } + + /** + * eps2 returns 2*sqrt(eps) + * @return + */ + fun eps2(): Double { + return theEpsMa2 + } + + /** + * override Minuit's own determination + * + * @param prec a double. + */ + fun setPrecision(prec: Double) { + theEpsMac = prec + theEpsMa2 = 2.0 * sqrt(theEpsMac) + } + + init { + setPrecision(4.0E-7) + var epstry = 0.5 + val one = 1.0 + for (i in 0..99) { + epstry *= 0.5 + val epsp1 = one + epstry + val epsbak = epsp1 - one + if (epsbak < epstry) { + setPrecision(8.0 * epstry) + break + } + } + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMigrad.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMigrad.kt new file mode 100644 index 000000000..22616a1a6 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMigrad.kt @@ -0,0 +1,136 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction + +/** + * MnMigrad provides minimization of the function by the method of MIGRAD, the + * most efficient and complete single method, recommended for general functions, + * and the functionality for parameters interaction. It also retains the result + * from the last minimization in case the user may want to do subsequent + * minimization steps with parameter interactions in between the minimization + * requests. The minimization produces as a by-product the error matrix of the + * parameters, which is usually reliable unless warning messages are produced. + * + * @version $Id$ + * @author Darksnake + */ +class MnMigrad +/** + * construct from MultiFunction + MnUserParameterState + MnStrategy + * + * @param str a [hep.dataforge.MINUIT.MnStrategy] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameterState] object. + * @param fcn a [MultiFunction] object. + */ + (fcn: MultiFunction?, par: MnUserParameterState, str: MnStrategy) : MnApplication(fcn, par, str) { + private val theMinimizer: VariableMetricMinimizer = VariableMetricMinimizer() + + /** + * construct from MultiFunction + double[] for parameters and errors + * with default strategy + * + * @param err an array of double. + * @param par an array of double. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray) : this(fcn, par, err, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + double[] for parameters and errors + * + * @param stra a int. + * @param err an array of double. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray, stra: Int) : this(fcn, + MnUserParameterState(par, err), + MnStrategy(stra)) + + /** + * construct from MultiFunction + double[] for parameters and + * MnUserCovariance with default strategy + * + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param par an array of double. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance) : this(fcn, par, cov, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + double[] for parameters and + * MnUserCovariance + * + * @param stra a int. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance, stra: Int) : this(fcn, + MnUserParameterState(par, cov), + MnStrategy(stra)) + + /** + * construct from MultiFunction + MnUserParameters with default + * strategy + * + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters) : this(fcn, par, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + MnUserParameters + * + * @param stra a int. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, stra: Int) : this(fcn, + MnUserParameterState(par), + MnStrategy(stra)) + + /** + * construct from MultiFunction + MnUserParameters + MnUserCovariance + * with default strategy + * + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, cov: MnUserCovariance) : this(fcn, + par, + cov, + DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + MnUserParameters + MnUserCovariance + * + * @param stra a int. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, cov: MnUserCovariance, stra: Int) : this(fcn, + MnUserParameterState(par, cov), + MnStrategy(stra)) + + override fun minimizer(): ModularFunctionMinimizer { + return theMinimizer + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinimize.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinimize.kt new file mode 100644 index 000000000..ea14a5453 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinimize.kt @@ -0,0 +1,133 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction + +/** + * Causes minimization of the function by the method of MIGRAD, as does the + * MnMigrad class, but switches to the SIMPLEX method if MIGRAD fails to + * converge. Constructor arguments, methods arguments and names of methods are + * the same as for MnMigrad or MnSimplex. + * + * @version $Id$ + * @author Darksnake + */ +class MnMinimize +/** + * construct from MultiFunction + MnUserParameterState + MnStrategy + * + * @param str a [hep.dataforge.MINUIT.MnStrategy] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameterState] object. + * @param fcn a [MultiFunction] object. + */ + (fcn: MultiFunction?, par: MnUserParameterState, str: MnStrategy) : MnApplication(fcn, par, str) { + private val theMinimizer: CombinedMinimizer = CombinedMinimizer() + + /** + * construct from MultiFunction + double[] for parameters and errors + * with default strategy + * + * @param err an array of double. + * @param par an array of double. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray) : this(fcn, par, err, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + double[] for parameters and errors + * + * @param stra a int. + * @param err an array of double. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray, stra: Int) : this(fcn, + MnUserParameterState(par, err), + MnStrategy(stra)) + + /** + * construct from MultiFunction + double[] for parameters and + * MnUserCovariance with default strategy + * + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param par an array of double. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance) : this(fcn, par, cov, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + double[] for parameters and + * MnUserCovariance + * + * @param stra a int. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance, stra: Int) : this(fcn, + MnUserParameterState(par, cov), + MnStrategy(stra)) + + /** + * construct from MultiFunction + MnUserParameters with default + * strategy + * + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters) : this(fcn, par, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + MnUserParameters + * + * @param stra a int. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, stra: Int) : this(fcn, + MnUserParameterState(par), + MnStrategy(stra)) + + /** + * construct from MultiFunction + MnUserParameters + MnUserCovariance + * with default strategy + * + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, cov: MnUserCovariance) : this(fcn, + par, + cov, + DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + MnUserParameters + MnUserCovariance + * + * @param stra a int. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, cov: MnUserCovariance, stra: Int) : this(fcn, + MnUserParameterState(par, cov), + MnStrategy(stra)) + + override fun minimizer(): ModularFunctionMinimizer { + return theMinimizer + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinos.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinos.kt new file mode 100644 index 000000000..d49379b3b --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinos.kt @@ -0,0 +1,379 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction +import ru.inr.mass.minuit.* +import kotlin.jvm.JvmOverloads + +/** + * API class for Minos error analysis (asymmetric errors). Minimization has to + * be done before and minimum must be valid; possibility to ask only for one + * side of the Minos error; + * + * @version $Id$ + * @author Darksnake + */ +class MnMinos(fcn: MultiFunction?, min: FunctionMinimum?, stra: MnStrategy?) { + private var theFCN: MultiFunction? = null + private var theMinimum: FunctionMinimum? = null + private var theStrategy: MnStrategy? = null + + /** + * construct from FCN + minimum + * + * @param fcn a [MultiFunction] object. + * @param min a [hep.dataforge.MINUIT.FunctionMinimum] object. + */ + constructor(fcn: MultiFunction?, min: FunctionMinimum?) : this(fcn, min, MnApplication.DEFAULT_STRATEGY) + + /** + * construct from FCN + minimum + strategy + * + * @param stra a int. + * @param min a [hep.dataforge.MINUIT.FunctionMinimum] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, min: FunctionMinimum?, stra: Int) : this(fcn, min, MnStrategy(stra)) + // public MnMinos(MultiFunction fcn, MnUserParameterState state, double errDef, MnStrategy stra) { + // theFCN = fcn; + // theStrategy = stra; + // + // MinimumState minState = null; + // + // MnUserTransformation transformation = state.getTransformation(); + // + // MinimumSeed seed = new MinimumSeed(minState, transformation); + // + // theMinimum = new FunctionMinimum(seed,errDef); + // } + /** + * + * loval. + * + * @param par a int. + * @return a [hep.dataforge.MINUIT.MnCross] object. + */ + fun loval(par: Int): MnCross { + return loval(par, 1.0) + } + + /** + * + * loval. + * + * @param par a int. + * @param errDef a double. + * @return a [hep.dataforge.MINUIT.MnCross] object. + */ + fun loval(par: Int, errDef: Double): MnCross { + return loval(par, errDef, MnApplication.DEFAULT_MAXFCN) + } + + /** + * + * loval. + * + * @param par a int. + * @param errDef a double. + * @param maxcalls a int. + * @return a [hep.dataforge.MINUIT.MnCross] object. + */ + fun loval(par: Int, errDef: Double, maxcalls: Int): MnCross { + var errDef = errDef + var maxcalls = maxcalls + errDef *= theMinimum!!.errorDef() + assert(theMinimum!!.isValid()) + assert(!theMinimum!!.userState().parameter(par).isFixed()) + assert(!theMinimum!!.userState().parameter(par).isConst()) + if (maxcalls == 0) { + val nvar: Int = theMinimum!!.userState().variableParameters() + maxcalls = 2 * (nvar + 1) * (200 + 100 * nvar + 5 * nvar * nvar) + } + val para = intArrayOf(par) + val upar: MnUserParameterState = theMinimum!!.userState().copy() + val err: Double = upar.error(par) + val `val`: Double = upar.value(par) - err + val xmid = doubleArrayOf(`val`) + val xdir = doubleArrayOf(-err) + val ind: Int = upar.intOfExt(par) + val m: MnAlgebraicSymMatrix = theMinimum!!.error().matrix() + val xunit: Double = sqrt(errDef / err) + for (i in 0 until m.nrow()) { + if (i == ind) { + continue + } + val xdev: Double = xunit * m[ind, i] + val ext: Int = upar.extOfInt(i) + upar.setValue(ext, upar.value(ext) - xdev) + } + upar.fix(par) + upar.setValue(par, `val`) + val toler = 0.1 + val cross = MnFunctionCross(theFCN, upar, theMinimum!!.fval(), theStrategy, errDef) + val aopt: MnCross = cross.cross(para, xmid, xdir, toler, maxcalls) + if (aopt.atLimit()) { + MINUITPlugin.logStatic("MnMinos parameter $par is at lower limit.") + } + if (aopt.atMaxFcn()) { + MINUITPlugin.logStatic("MnMinos maximum number of function calls exceeded for parameter $par") + } + if (aopt.newMinimum()) { + MINUITPlugin.logStatic("MnMinos new minimum found while looking for parameter $par") + } + if (!aopt.isValid()) { + MINUITPlugin.logStatic("MnMinos could not find lower value for parameter $par.") + } + return aopt + } + /** + * calculate one side (negative or positive error) of the parameter + * + * @param maxcalls a int. + * @param par a int. + * @param errDef a double. + * @return a double. + */ + /** + * + * lower. + * + * @param par a int. + * @param errDef a double. + * @return a double. + */ + /** + * + * lower. + * + * @param par a int. + * @return a double. + */ + @JvmOverloads + fun lower(par: Int, errDef: Double = 1.0, maxcalls: Int = MnApplication.DEFAULT_MAXFCN): Double { + val upar: MnUserParameterState = theMinimum!!.userState() + val err: Double = theMinimum!!.userState().error(par) + val aopt: MnCross = loval(par, errDef, maxcalls) + return if (aopt.isValid()) -1.0 * err * (1.0 + aopt.value()) else if (aopt.atLimit()) upar.parameter(par) + .lowerLimit() else upar.value(par) + } + + /** + * + * minos. + * + * @param par a int. + * @return a [hep.dataforge.MINUIT.MinosError] object. + */ + fun minos(par: Int): MinosError { + return minos(par, 1.0) + } + + /** + * + * minos. + * + * @param par a int. + * @param errDef a double. + * @return a [hep.dataforge.MINUIT.MinosError] object. + */ + fun minos(par: Int, errDef: Double): MinosError { + return minos(par, errDef, MnApplication.DEFAULT_MAXFCN) + } + + /** + * Causes a MINOS error analysis to be performed on the parameter whose + * number is specified. MINOS errors may be expensive to calculate, but are + * very reliable since they take account of non-linearities in the problem + * as well as parameter correlations, and are in general asymmetric. + * + * @param maxcalls Specifies the (approximate) maximum number of function + * calls per parameter requested, after which the calculation will be + * stopped for that parameter. + * @param errDef a double. + * @param par a int. + * @return a [hep.dataforge.MINUIT.MinosError] object. + */ + fun minos(par: Int, errDef: Double, maxcalls: Int): MinosError { + assert(theMinimum!!.isValid()) + assert(!theMinimum!!.userState().parameter(par).isFixed()) + assert(!theMinimum!!.userState().parameter(par).isConst()) + val up: MnCross = upval(par, errDef, maxcalls) + val lo: MnCross = loval(par, errDef, maxcalls) + return MinosError(par, theMinimum!!.userState().value(par), lo, up) + } + + /** + * + * range. + * + * @param par a int. + * @return + */ + fun range(par: Int): Range { + return range(par, 1.0) + } + + /** + * + * range. + * + * @param par a int. + * @param errDef a double. + * @return + */ + fun range(par: Int, errDef: Double): Range { + return range(par, errDef, MnApplication.DEFAULT_MAXFCN) + } + + /** + * Causes a MINOS error analysis for external parameter n. + * + * @param maxcalls a int. + * @param errDef a double. + * @return The lower and upper bounds of parameter + * @param par a int. + */ + fun range(par: Int, errDef: Double, maxcalls: Int): Range { + val mnerr: MinosError = minos(par, errDef, maxcalls) + return mnerr.range() + } + /** + * + * upper. + * + * @param par a int. + * @param errDef a double. + * @param maxcalls a int. + * @return a double. + */ + /** + * + * upper. + * + * @param par a int. + * @param errDef a double. + * @return a double. + */ + /** + * + * upper. + * + * @param par a int. + * @return a double. + */ + @JvmOverloads + fun upper(par: Int, errDef: Double = 1.0, maxcalls: Int = MnApplication.DEFAULT_MAXFCN): Double { + val upar: MnUserParameterState = theMinimum!!.userState() + val err: Double = theMinimum!!.userState().error(par) + val aopt: MnCross = upval(par, errDef, maxcalls) + return if (aopt.isValid()) err * (1.0 + aopt.value()) else if (aopt.atLimit()) upar.parameter(par) + .upperLimit() else upar.value(par) + } + + /** + * + * upval. + * + * @param par a int. + * @return a [hep.dataforge.MINUIT.MnCross] object. + */ + fun upval(par: Int): MnCross { + return upval(par, 1.0) + } + + /** + * + * upval. + * + * @param par a int. + * @param errDef a double. + * @return a [hep.dataforge.MINUIT.MnCross] object. + */ + fun upval(par: Int, errDef: Double): MnCross { + return upval(par, errDef, MnApplication.DEFAULT_MAXFCN) + } + + /** + * + * upval. + * + * @param par a int. + * @param errDef a double. + * @param maxcalls a int. + * @return a [hep.dataforge.MINUIT.MnCross] object. + */ + fun upval(par: Int, errDef: Double, maxcalls: Int): MnCross { + var errDef = errDef + var maxcalls = maxcalls + errDef *= theMinimum!!.errorDef() + assert(theMinimum!!.isValid()) + assert(!theMinimum!!.userState().parameter(par).isFixed()) + assert(!theMinimum!!.userState().parameter(par).isConst()) + if (maxcalls == 0) { + val nvar: Int = theMinimum!!.userState().variableParameters() + maxcalls = 2 * (nvar + 1) * (200 + 100 * nvar + 5 * nvar * nvar) + } + val para = intArrayOf(par) + val upar: MnUserParameterState = theMinimum!!.userState().copy() + val err: Double = upar.error(par) + val `val`: Double = upar.value(par) + err + val xmid = doubleArrayOf(`val`) + val xdir = doubleArrayOf(err) + val ind: Int = upar.intOfExt(par) + val m: MnAlgebraicSymMatrix = theMinimum!!.error().matrix() + val xunit: Double = sqrt(errDef / err) + for (i in 0 until m.nrow()) { + if (i == ind) { + continue + } + val xdev: Double = xunit * m[ind, i] + val ext: Int = upar.extOfInt(i) + upar.setValue(ext, upar.value(ext) + xdev) + } + upar.fix(par) + upar.setValue(par, `val`) + val toler = 0.1 + val cross = MnFunctionCross(theFCN, upar, theMinimum!!.fval(), theStrategy, errDef) + val aopt: MnCross = cross.cross(para, xmid, xdir, toler, maxcalls) + if (aopt.atLimit()) { + MINUITPlugin.logStatic("MnMinos parameter $par is at upper limit.") + } + if (aopt.atMaxFcn()) { + MINUITPlugin.logStatic("MnMinos maximum number of function calls exceeded for parameter $par") + } + if (aopt.newMinimum()) { + MINUITPlugin.logStatic("MnMinos new minimum found while looking for parameter $par") + } + if (!aopt.isValid()) { + MINUITPlugin.logStatic("MnMinos could not find upper value for parameter $par.") + } + return aopt + } + + /** + * construct from FCN + minimum + strategy + * + * @param stra a [hep.dataforge.MINUIT.MnStrategy] object. + * @param min a [hep.dataforge.MINUIT.FunctionMinimum] object. + * @param fcn a [MultiFunction] object. + */ + init { + theFCN = fcn + theMinimum = min + theStrategy = stra + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabola.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabola.kt new file mode 100644 index 000000000..a0a56dedd --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabola.kt @@ -0,0 +1,55 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * parabola = a*xx + b*x + c + * + * @version $Id$ + */ +internal class MnParabola(private val theA: Double, private val theB: Double, private val theC: Double) { + fun a(): Double { + return theA + } + + fun b(): Double { + return theB + } + + fun c(): Double { + return theC + } + + fun min(): Double { + return -theB / (2.0 * theA) + } + + fun x_neg(y: Double): Double { + return -sqrt(y / theA + min() * min() - theC / theA) + min() + } + + fun x_pos(y: Double): Double { + return sqrt(y / theA + min() * min() - theC / theA) + min() + } + + fun y(x: Double): Double { + return theA * x * x + theB * x + theC + } + + fun ymin(): Double { + return -theB * theB / (4.0 * theA) + theC + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaFactory.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaFactory.kt new file mode 100644 index 000000000..f45d2b9c9 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaFactory.kt @@ -0,0 +1,58 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal object MnParabolaFactory { + fun create(p1: MnParabolaPoint, p2: MnParabolaPoint, p3: MnParabolaPoint): MnParabola { + var x1: Double = p1.x() + var x2: Double = p2.x() + var x3: Double = p3.x() + val dx12 = x1 - x2 + val dx13 = x1 - x3 + val dx23 = x2 - x3 + val xm = (x1 + x2 + x3) / 3.0 + x1 -= xm + x2 -= xm + x3 -= xm + val y1: Double = p1.y() + val y2: Double = p2.y() + val y3: Double = p3.y() + val a = y1 / (dx12 * dx13) - y2 / (dx12 * dx23) + y3 / (dx13 * dx23) + var b = -y1 * (x2 + x3) / (dx12 * dx13) + y2 * (x1 + x3) / (dx12 * dx23) - y3 * (x1 + x2) / (dx13 * dx23) + var c = y1 - a * x1 * x1 - b * x1 + c += xm * (xm * a - b) + b -= 2.0 * xm * a + return MnParabola(a, b, c) + } + + fun create(p1: MnParabolaPoint, dxdy1: Double, p2: MnParabolaPoint): MnParabola { + val x1: Double = p1.x() + val xx1 = x1 * x1 + val x2: Double = p2.x() + val xx2 = x2 * x2 + val y1: Double = p1.y() + val y12: Double = p1.y() - p2.y() + val det = xx1 - xx2 - 2.0 * x1 * (x1 - x2) + val a = -(y12 + (x2 - x1) * dxdy1) / det + val b = -(-2.0 * x1 * y12 + (xx1 - xx2) * dxdy1) / det + val c = y1 - a * xx1 - b * x1 + return MnParabola(a, b, c) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaPoint.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaPoint.kt new file mode 100644 index 000000000..858e010e6 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaPoint.kt @@ -0,0 +1,30 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal class MnParabolaPoint(private val theX: Double, private val theY: Double) { + fun x(): Double { + return theX + } + + fun y(): Double { + return theY + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParameterScan.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParameterScan.kt new file mode 100644 index 000000000..7791c20e8 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParameterScan.kt @@ -0,0 +1,113 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction + +/** + * Scans the values of FCN as a function of one parameter and retains the best + * function and parameter values found + * + * @version $Id$ + */ +internal class MnParameterScan { + private var theAmin: Double + private var theFCN: MultiFunction? + private var theParameters: MnUserParameters + + constructor(fcn: MultiFunction, par: MnUserParameters) { + theFCN = fcn + theParameters = par + theAmin = fcn.value(par.params()) + } + + constructor(fcn: MultiFunction?, par: MnUserParameters, fval: Double) { + theFCN = fcn + theParameters = par + theAmin = fval + } + + fun fval(): Double { + return theAmin + } + + fun parameters(): MnUserParameters { + return theParameters + } + + fun scan(par: Int): List { + return scan(par, 41) + } + + fun scan(par: Int, maxsteps: Int): List { + return scan(par, maxsteps, 0.0, 0.0) + } + + /** + * returns pairs of (x,y) points, x=parameter value, y=function value of FCN + * @param high + * @return + */ + fun scan(par: Int, maxsteps: Int, low: Double, high: Double): List { + var maxsteps = maxsteps + var low = low + var high = high + if (maxsteps > 101) { + maxsteps = 101 + } + val result: MutableList = java.util.ArrayList(maxsteps + 1) + val params: DoubleArray = theParameters.params() + result.add(Range(params[par], theAmin)) + if (low > high) { + return result + } + if (maxsteps < 2) { + return result + } + if (low == 0.0 && high == 0.0) { + low = params[par] - 2.0 * theParameters.error(par) + high = params[par] + 2.0 * theParameters.error(par) + } + if (low == 0.0 && high == 0.0 && theParameters.parameter(par).hasLimits()) { + if (theParameters.parameter(par).hasLowerLimit()) { + low = theParameters.parameter(par).lowerLimit() + } + if (theParameters.parameter(par).hasUpperLimit()) { + high = theParameters.parameter(par).upperLimit() + } + } + if (theParameters.parameter(par).hasLimits()) { + if (theParameters.parameter(par).hasLowerLimit()) { + low = max(low, theParameters.parameter(par).lowerLimit()) + } + if (theParameters.parameter(par).hasUpperLimit()) { + high = min(high, theParameters.parameter(par).upperLimit()) + } + } + val x0 = low + val stp = (high - low) / (maxsteps - 1.0) + for (i in 0 until maxsteps) { + params[par] = x0 + i.toDouble() * stp + val fval: Double = theFCN.value(params) + if (fval < theAmin) { + theParameters.setValue(par, params[par]) + theAmin = fval + } + result.add(Range(params[par], fval)) + } + return result + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPlot.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPlot.kt new file mode 100644 index 000000000..656dd8d35 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPlot.kt @@ -0,0 +1,438 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import java.lang.StringBuffer +import kotlin.jvm.JvmOverloads + +/** + * MnPlot produces a text-screen graphical output of (x,y) points. E.g. from + * Scan or Contours. + * + * @version $Id$ + * @author Darksnake + */ +class MnPlot @JvmOverloads constructor(private val thePageWidth: Int = 80, private val thePageLength: Int = 30) { + private var bh = 0.0 + private var bl = 0.0 + private var bwid = 0.0 + private var nb = 0 + fun length(): Int { + return thePageLength + } + + private fun mnbins(a1: Double, a2: Double, naa: Int) { + + //*-*-*-*-*-*-*-*-*-*-*Compute reasonable histogram intervals*-*-*-*-*-*-*-*-* + //*-* ====================================== + //*-* Function TO DETERMINE REASONABLE HISTOGRAM INTERVALS + //*-* GIVEN ABSOLUTE UPPER AND LOWER BOUNDS A1 AND A2 + //*-* AND DESIRED MAXIMUM NUMBER OF BINS NAA + //*-* PROGRAM MAKES REASONABLE BINNING FROM BL TO BH OF WIDTH BWID + //*-* F. JAMES, AUGUST, 1974 , stolen for Minuit, 1988 + //*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-* + + /* Local variables */ + var awid: Double + var ah: Double + var sigfig: Double + var sigrnd: Double + var alb: Double + var kwid: Int + var lwid: Int + var na = 0 + var log_: Int + val al: Double = if (a1 < a2) a1 else a2 + ah = if (a1 > a2) a1 else a2 + if (al == ah) { + ah = al + 1 + } + + //*-*- IF NAA .EQ. -1 , PROGRAM USES BWID INPUT FROM CALLING ROUTINE + var skip = naa == -1 && bwid > 0 + if (!skip) { + na = naa - 1 + if (na < 1) { + na = 1 + } + } + while (true) { + if (!skip) { + //*-*- GET NOMINAL BIN WIDTH IN EXPON FORM + awid = (ah - al) / na.toDouble() + log_ = log10(awid) + if (awid <= 1) { + --log_ + } + sigfig = awid * pow(10.0, -log_.toDouble()) + //*-*- ROUND MANTISSA UP TO 2, 2.5, 5, OR 10 + if (sigfig <= 2) { + sigrnd = 2.0 + } else if (sigfig <= 2.5) { + sigrnd = 2.5 + } else if (sigfig <= 5) { + sigrnd = 5.0 + } else { + sigrnd = 1.0 + ++log_ + } + bwid = sigrnd * pow(10.0, log_.toDouble()) + } + alb = al / bwid + lwid = alb.toInt() + if (alb < 0) { + --lwid + } + bl = bwid * lwid.toDouble() + alb = ah / bwid + 1 + kwid = alb.toInt() + if (alb < 0) { + --kwid + } + bh = bwid * kwid.toDouble() + nb = kwid - lwid + if (naa <= 5) { + if (naa == -1) { + return + } + //*-*- REQUEST FOR ONE BIN IS DIFFICULT CASE + if (naa > 1 || nb == 1) { + return + } + bwid *= 2.0 + nb = 1 + return + } + if (nb shl 1 != naa) { + return + } + ++na + skip = false + continue + } + } + + private fun mnplot(xpt: DoubleArray, ypt: DoubleArray, chpt: StringBuffer, nxypt: Int, npagwd: Int, npagln: Int) { + //*-*-*-*Plots points in array xypt onto one page with labelled axes*-*-*-*-* + //*-* =========================================================== + //*-* NXYPT is the number of points to be plotted + //*-* XPT(I) = x-coord. of ith point + //*-* YPT(I) = y-coord. of ith point + //*-* CHPT(I) = character to be plotted at this position + //*-* the input point arrays XPT, YPT, CHPT are destroyed. + //*-* + //*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-* + + /* Local variables */ + var xmin: Double + var xmax: Double + var ymax: Double + var savx: Double + var savy: Double + var yprt: Double + var xbest: Double + var ybest: Double + val xvalus = DoubleArray(12) + val any: Double + val iten: Int + var j: Int + var k: Int + var maxnx: Int + var maxny: Int + var iquit: Int + var ni: Int + var linodd: Int + var ibk: Int + var isp1: Int + var ks: Int + var ix: Int + var overpr: Boolean + val cline = StringBuffer(npagwd) + for (ii in 0 until npagwd) { + cline.append(' ') + } + var chsav: Char + val chbest: Char + + /* Function Body */ + //*-* Computing MIN + maxnx = if (npagwd - 20 < 100) npagwd - 20 else 100 + if (maxnx < 10) { + maxnx = 10 + } + maxny = npagln + if (maxny < 10) { + maxny = 10 + } + if (nxypt <= 1) { + return + } + xbest = xpt[0] + ybest = ypt[0] + chbest = chpt.get(0) + //*-*- order the points by decreasing y + val km1: Int = nxypt - 1 + var i: Int = 1 + while (i <= km1) { + iquit = 0 + ni = nxypt - i + j = 1 + while (j <= ni) { + if (ypt[j - 1] > ypt[j]) { + ++j + continue + } + savx = xpt[j - 1] + xpt[j - 1] = xpt[j] + xpt[j] = savx + savy = ypt[j - 1] + ypt[j - 1] = ypt[j] + ypt[j] = savy + chsav = chpt.get(j - 1) + chpt.setCharAt(j - 1, chpt.get(j)) + chpt.setCharAt(j, chsav) + iquit = 1 + ++j + } + if (iquit == 0) { + break + } + ++i + } + //*-*- find extreme values + xmax = xpt[0] + xmin = xmax + i = 1 + while (i <= nxypt) { + if (xpt[i - 1] > xmax) { + xmax = xpt[i - 1] + } + if (xpt[i - 1] < xmin) { + xmin = xpt[i - 1] + } + ++i + } + val dxx: Double = (xmax - xmin) * .001 + xmax += dxx + xmin -= dxx + mnbins(xmin, xmax, maxnx) + xmin = bl + xmax = bh + var nx: Int = nb + val bwidx: Double = bwid + ymax = ypt[0] + var ymin: Double = ypt[nxypt - 1] + if (ymax == ymin) { + ymax = ymin + 1 + } + val dyy: Double = (ymax - ymin) * .001 + ymax += dyy + ymin -= dyy + mnbins(ymin, ymax, maxny) + ymin = bl + ymax = bh + var ny: Int = nb + val bwidy: Double = bwid + any = ny.toDouble() + //*-*- if first point is blank, it is an 'origin' + if (chbest != ' ') { + xbest = (xmax + xmin) * .5 + ybest = (ymax + ymin) * .5 + } + //*-*- find scale constants + val ax: Double = 1 / bwidx + val ay: Double = 1 / bwidy + val bx: Double = -ax * xmin + 2 + val by: Double = -ay * ymin - 2 + //*-*- convert points to grid positions + i = 1 + while (i <= nxypt) { + xpt[i - 1] = ax * xpt[i - 1] + bx + ypt[i - 1] = any - ay * ypt[i - 1] - by + ++i + } + val nxbest: Int = (ax * xbest + bx).toInt() + val nybest: Int = (any - ay * ybest - by).toInt() + //*-*- print the points + ny += 2 + nx += 2 + isp1 = 1 + linodd = 1 + overpr = false + i = 1 + while (i <= ny) { + ibk = 1 + while (ibk <= nx) { + cline.setCharAt(ibk - 1, ' ') + ++ibk + } + // cline.setCharAt(nx,'\0'); + // cline.setCharAt(nx+1,'\0'); + cline.setCharAt(0, '.') + cline.setCharAt(nx - 1, '.') + cline.setCharAt(nxbest - 1, '.') + if (i == 1 || i == nybest || i == ny) { + j = 1 + while (j <= nx) { + cline.setCharAt(j - 1, '.') + ++j + } + } + yprt = ymax - (i - 1.0) * bwidy + var isplset = false + if (isp1 <= nxypt) { + //*-*- find the points to be plotted on this line + k = isp1 + while (k <= nxypt) { + ks = ypt[k - 1].toInt() + if (ks > i) { + isp1 = k + isplset = true + break + } + ix = xpt[k - 1].toInt() + if (cline.get(ix - 1) != '.' && cline.get(ix - 1) != ' ') { + if (cline.get(ix - 1) == chpt.get(k - 1)) { + ++k + continue + } + overpr = true + //*-*- OVERPR is true if one or more positions contains more than + //*-*- one point + cline.setCharAt(ix - 1, '&') + ++k + continue + } + cline.setCharAt(ix - 1, chpt.get(k - 1)) + ++k + } + if (!isplset) { + isp1 = nxypt + 1 + } + } + if (linodd != 1 && i != ny) { + linodd = 1 + java.lang.System.out.printf(" %s", cline.substring(0, 60)) + } else { + java.lang.System.out.printf(" %14.7g ..%s", yprt, cline.substring(0, 60)) + linodd = 0 + } + println() + ++i + } + //*-*- print labels on x-axis every ten columns + ibk = 1 + while (ibk <= nx) { + cline.setCharAt(ibk - 1, ' ') + if (ibk % 10 == 1) { + cline.setCharAt(ibk - 1, '/') + } + ++ibk + } + java.lang.System.out.printf(" %s", cline) + java.lang.System.out.printf("\n") + ibk = 1 + while (ibk <= 12) { + xvalus[ibk - 1] = xmin + (ibk - 1.0) * 10 * bwidx + ++ibk + } + java.lang.System.out.printf(" ") + iten = (nx + 9) / 10 + ibk = 1 + while (ibk <= iten) { + java.lang.System.out.printf(" %9.4g", xvalus[ibk - 1]) + ++ibk + } + java.lang.System.out.printf("\n") + if (overpr) { + val chmess = " Overprint character is &" + java.lang.System.out.printf(" ONE COLUMN=%13.7g%s", bwidx, chmess) + } else { + val chmess = " " + java.lang.System.out.printf(" ONE COLUMN=%13.7g%s", bwidx, chmess) + } + println() + } + + /** + * + * plot. + * + * @param points a [List] object. + */ + fun plot(points: List) { + val x = DoubleArray(points.size) + val y = DoubleArray(points.size) + val chpt = StringBuffer(points.size) + for ((i, ipoint) in points.withIndex()) { + x[i] = ipoint.getFirst() + y[i] = ipoint.getSecond() + chpt.append('*') + } + mnplot(x, y, chpt, points.size, width(), length()) + } + + /** + * + * plot. + * + * @param xmin a double. + * @param ymin a double. + * @param points a [List] object. + */ + fun plot(xmin: Double, ymin: Double, points: List) { + val x = DoubleArray(points.size + 2) + x[0] = xmin + x[1] = xmin + val y = DoubleArray(points.size + 2) + y[0] = ymin + y[1] = ymin + val chpt = StringBuffer(points.size + 2) + chpt.append(' ') + chpt.append('X') + var i = 2 + for (ipoint in points) { + x[i] = ipoint.getFirst() + y[i] = ipoint.getSecond() + chpt.append('*') + i++ + } + mnplot(x, y, chpt, points.size + 2, width(), length()) + } + + fun width(): Int { + return thePageWidth + } + /** + * + * Constructor for MnPlot. + * + * @param thePageWidth a int. + * @param thePageLength a int. + */ + /** + * + * Constructor for MnPlot. + */ + init { + if (thePageWidth > 120) { + thePageWidth = 120 + } + if (thePageLength > 56) { + thePageLength = 56 + } + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPosDef.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPosDef.kt new file mode 100644 index 000000000..f94e387d9 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPosDef.kt @@ -0,0 +1,89 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import space.kscience.kmath.optimization.minuit.MINUITPlugin + +/** + * + * @version $Id$ + */ +internal object MnPosDef { + fun test(st: MinimumState, prec: MnMachinePrecision): MinimumState { + val err: MinimumError = test(st.error(), prec) + return MinimumState(st.parameters(), err, st.gradient(), st.edm(), st.nfcn()) + } + + fun test(e: MinimumError, prec: MnMachinePrecision): MinimumError { + val err: MnAlgebraicSymMatrix = e.invHessian().copy() + if (err.size() === 1 && err[0, 0] < prec.eps()) { + err[0, 0] = 1.0 + return MinimumError(err, MnMadePosDef()) + } + if (err.size() === 1 && err[0, 0] > prec.eps()) { + return e + } + // std::cout<<"MnPosDef init matrix= "< 0.0) { + os.printf(" limited || %10g", ipar.value()) + if (abs(ipar.value() - ipar.lowerLimit()) < par.precision().eps2()) { + os.print("* ") + atLoLim = true + } + if (abs(ipar.value() - ipar.upperLimit()) < par.precision().eps2()) { + os.print("**") + atHiLim = true + } + os.printf(" || %10g\n", ipar.error()) + } else { + os.printf(" free || %10g || no\n", ipar.value()) + } + } else { + if (ipar.error() > 0.0) { + os.printf(" free || %10g || %10g\n", ipar.value(), ipar.error()) + } else { + os.printf(" free || %10g || no\n", ipar.value()) + } + } + } + os.println() + if (atLoLim) { + os.print("* parameter is at lower limit") + } + if (atHiLim) { + os.print("** parameter is at upper limit") + } + os.println() + } + + /** + * + * print. + * + * @param os a [PrintWriter] object. + * @param matrix a [hep.dataforge.MINUIT.MnUserCovariance] object. + */ + fun print(os: PrintWriter, matrix: MnUserCovariance) { + os.println() + os.println("MnUserCovariance: ") + run { + os.println() + val n: Int = matrix.nrow() + for (i in 0 until n) { + for (j in 0 until n) { + os.printf("%10g ", matrix[i, j]) + } + os.println() + } + } + os.println() + os.println("MnUserCovariance parameter correlations: ") + run { + os.println() + val n: Int = matrix.nrow() + for (i in 0 until n) { + val di: Double = matrix[i, i] + for (j in 0 until n) { + val dj: Double = matrix[j, j] + os.printf("%g ", matrix[i, j] / sqrt(abs(di * dj))) + } + os.println() + } + } + } + + /** + * + * print. + * + * @param os a [PrintWriter] object. + * @param coeff a [hep.dataforge.MINUIT.MnGlobalCorrelationCoeff] object. + */ + fun print(os: PrintWriter, coeff: MnGlobalCorrelationCoeff) { + os.println() + os.println("MnGlobalCorrelationCoeff: ") + run { + os.println() + for (i in 0 until coeff.globalCC().length) { + os.printf("%g\n", coeff.globalCC()[i]) + } + } + } + + /** + * + * print. + * + * @param os a [PrintWriter] object. + * @param state a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun print(os: PrintWriter, state: MnUserParameterState) { + os.println() + if (!state.isValid()) { + os.println() + os.println("WARNING: MnUserParameterState is not valid.") + os.println() + } + os.println("# of function calls: " + state.nfcn()) + os.println("function value: " + state.fval()) + os.println("expected distance to the minimum (edm): " + state.edm()) + os.println("external parameters: " + state.parameters()) + if (state.hasCovariance()) { + os.println("covariance matrix: " + state.covariance()) + } + if (state.hasGlobalCC()) { + os.println("global correlation coefficients : " + state.globalCC()) + } + if (!state.isValid()) { + os.println("WARNING: MnUserParameterState is not valid.") + } + os.println() + } + + /** + * + * print. + * + * @param os a [PrintWriter] object. + * @param me a [hep.dataforge.MINUIT.MinosError] object. + */ + fun print(os: PrintWriter, me: MinosError) { + os.println() + os.printf("Minos # of function calls: %d\n", me.nfcn()) + if (!me.isValid()) { + os.println("Minos error is not valid.") + } + if (!me.lowerValid()) { + os.println("lower Minos error is not valid.") + } + if (!me.upperValid()) { + os.println("upper Minos error is not valid.") + } + if (me.atLowerLimit()) { + os.println("Minos error is lower limit of parameter " + me.parameter()) + } + if (me.atUpperLimit()) { + os.println("Minos error is upper limit of parameter " + me.parameter()) + } + if (me.atLowerMaxFcn()) { + os.println("Minos number of function calls for lower error exhausted.") + } + if (me.atUpperMaxFcn()) { + os.println("Minos number of function calls for upper error exhausted.") + } + if (me.lowerNewMin()) { + os.println("Minos found a new minimum in negative direction.") + os.println(me.lowerState()) + } + if (me.upperNewMin()) { + os.println("Minos found a new minimum in positive direction.") + os.println(me.upperState()) + } + os.println("# ext. || name || value@min || negative || positive ") + os.printf("%4d||%10s||%10g||%10g||%10g\n", + me.parameter(), + me.lowerState().name(me.parameter()), + me.min(), + me.lower(), + me.upper()) + os.println() + } + + /** + * + * print. + * + * @param os a [PrintWriter] object. + * @param ce a [hep.dataforge.MINUIT.ContoursError] object. + */ + fun print(os: PrintWriter, ce: ContoursError) { + os.println() + os.println("Contours # of function calls: " + ce.nfcn()) + os.println("MinosError in x: ") + os.println(ce.xMinosError()) + os.println("MinosError in y: ") + os.println(ce.yMinosError()) + val plot = MnPlot() + plot.plot(ce.xmin(), ce.ymin(), ce.points()) + for ((i, ipoint) in ce.points().withIndex()) { + os.printf("%d %10g %10g\n", i, ipoint.getFirst(), ipoint.getSecond()) + } + os.println() + } + + fun toString(x: RealVector): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, x) } + return writer.toString() + } + + fun toString(x: MnAlgebraicSymMatrix?): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, x) } + return writer.toString() + } + + fun toString(min: FunctionMinimum?): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, min) } + return writer.toString() + } + + fun toString(x: MinimumState?): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, x) } + return writer.toString() + } + + fun toString(x: MnUserParameters?): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, x) } + return writer.toString() + } + + fun toString(x: MnUserCovariance?): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, x) } + return writer.toString() + } + + fun toString(x: MnGlobalCorrelationCoeff?): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, x) } + return writer.toString() + } + + fun toString(x: MnUserParameterState?): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, x) } + return writer.toString() + } + + fun toString(x: MinosError?): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, x) } + return writer.toString() + } + + fun toString(x: ContoursError?): String { + val writer: java.io.StringWriter = java.io.StringWriter() + PrintWriter(writer).use { pw -> print(pw, x) } + return writer.toString() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnScan.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnScan.kt new file mode 100644 index 000000000..63e565b4f --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnScan.kt @@ -0,0 +1,181 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction +import ru.inr.mass.minuit.* + +/** + * MnScan scans the value of the user function by varying one parameter. It is + * sometimes useful for debugging the user function or finding a reasonable + * starting point. + * construct from MultiFunction + MnUserParameterState + MnStrategy + * + * @param str a [hep.dataforge.MINUIT.MnStrategy] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameterState] object. + * @param fcn a [MultiFunction] object. + * @version $Id$ + * @author Darksnake + */ +class MnScan(fcn: MultiFunction?, par: MnUserParameterState, str: MnStrategy) : MnApplication(fcn, par, str) { + private val theMinimizer: ScanMinimizer = ScanMinimizer() + + /** + * construct from MultiFunction + double[] for parameters and errors + * with default strategy + * + * @param err an array of double. + * @param par an array of double. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray) : this(fcn, par, err, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + double[] for parameters and errors + * + * @param stra a int. + * @param err an array of double. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray, stra: Int) : this(fcn, + MnUserParameterState(par, err), + MnStrategy(stra)) + + /** + * construct from MultiFunction + double[] for parameters and + * MnUserCovariance with default strategy + * + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param par an array of double. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance) : this(fcn, par, cov, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + double[] for parameters and + * MnUserCovariance + * + * @param stra a int. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance, stra: Int) : this(fcn, + MnUserParameterState(par, cov), + MnStrategy(stra)) + + /** + * construct from MultiFunction + MnUserParameters with default + * strategy + * + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters) : this(fcn, par, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + MnUserParameters + * + * @param stra a int. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, stra: Int) : this(fcn, + MnUserParameterState(par), + MnStrategy(stra)) + + /** + * construct from MultiFunction + MnUserParameters + MnUserCovariance + * with default strategy + * + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, cov: MnUserCovariance) : this(fcn, + par, + cov, + DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + MnUserParameters + MnUserCovariance + * + * @param stra a int. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, cov: MnUserCovariance, stra: Int) : this(fcn, + MnUserParameterState(par, cov), + MnStrategy(stra)) + + override fun minimizer(): ModularFunctionMinimizer { + return theMinimizer + } + + /** + * + * scan. + * + * @param par a int. + * @return a [List] object. + */ + fun scan(par: Int): List { + return scan(par, 41) + } + + /** + * + * scan. + * + * @param par a int. + * @param maxsteps a int. + * @return a [List] object. + */ + fun scan(par: Int, maxsteps: Int): List { + return scan(par, maxsteps, 0.0, 0.0) + } + + /** + * Scans the value of the user function by varying parameter number par, + * leaving all other parameters fixed at the current value. If par is not + * specified, all variable parameters are scanned in sequence. The number of + * points npoints in the scan is 40 by default, and cannot exceed 100. The + * range of the scan is by default 2 standard deviations on each side of the + * current best value, but can be specified as from low to high. After each + * scan, if a new minimum is found, the best parameter values are retained + * as start values for future scans or minimizations. The curve resulting + * from each scan can be plotted on the output terminal using MnPlot in + * order to show the approximate behaviour of the function. + * + * @param high a double. + * @param par a int. + * @param maxsteps a int. + * @param low a double. + * @return a [List] object. + */ + fun scan(par: Int, maxsteps: Int, low: Double, high: Double): List { + val scan = MnParameterScan(theFCN, theState.parameters()) + var amin: Double = scan.fval() + val result: List = scan.scan(par, maxsteps, low, high) + if (scan.fval() < amin) { + theState.setValue(par, scan.parameters().value(par)) + amin = scan.fval() + } + return result + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSeedGenerator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSeedGenerator.kt new file mode 100644 index 000000000..cc3f9547e --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSeedGenerator.kt @@ -0,0 +1,107 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import space.kscience.kmath.optimization.minuit.MINUITPlugin +import ru.inr.mass.minuit.* + +/** + * + * @version $Id$ + */ +internal class MnSeedGenerator : MinimumSeedGenerator { + /** {@inheritDoc} */ + fun generate(fcn: MnFcn, gc: GradientCalculator, st: MnUserParameterState, stra: MnStrategy): MinimumSeed { + val n: Int = st.variableParameters() + val prec: MnMachinePrecision = st.precision() + + // initial starting values + val x: RealVector = ArrayRealVector(n) + for (i in 0 until n) { + x.setEntry(i, st.intParameters()[i]) + } + val fcnmin: Double = fcn.value(x) + val pa = MinimumParameters(x, fcnmin) + val dgrad: FunctionGradient + if (gc is AnalyticalGradientCalculator) { + val igc = InitialGradientCalculator(fcn, st.getTransformation(), stra) + val tmp: FunctionGradient = igc.gradient(pa) + val grd: FunctionGradient = gc.gradient(pa) + dgrad = FunctionGradient(grd.getGradient(), tmp.getGradientDerivative(), tmp.getStep()) + if (gc.checkGradient()) { + val good = true + val hgc = HessianGradientCalculator(fcn, st.getTransformation(), MnStrategy(2)) + val hgrd: Pair = hgc.deltaGradient(pa, dgrad) + for (i in 0 until n) { + val provided: Double = grd.getGradient().getEntry(i) + val calculated: Double = hgrd.getFirst().getGradient().getEntry(i) + val delta: Double = hgrd.getSecond().getEntry(i) + if (abs(calculated - provided) > delta) { + MINUITPlugin.logStatic("" + + "gradient discrepancy of external parameter \"%d\" " + + "(internal parameter \"%d\") too large. Expected: \"%f\", provided: \"%f\"", + st.getTransformation().extOfInt(i), i, provided, calculated) + +// +// MINUITPlugin.logStatic("gradient discrepancy of external parameter " +// + st.getTransformation().extOfInt(i) +// + " (internal parameter " + i + ") too large."); +// good = false; + } + } + if (!good) { + MINUITPlugin.logStatic("Minuit does not accept user specified gradient.") + // assert(good); + } + } + } else { + dgrad = gc.gradient(pa) + } + val mat = MnAlgebraicSymMatrix(n) + var dcovar = 1.0 + if (st.hasCovariance()) { + for (i in 0 until n) { + for (j in i until n) { + mat[i, j] = st.intCovariance()[i, j] + } + } + dcovar = 0.0 + } else { + for (i in 0 until n) { + mat[i, i] = if (abs(dgrad.getGradientDerivative() + .getEntry(i)) > prec.eps2() + ) 1.0 / dgrad.getGradientDerivative().getEntry(i) else 1.0 + } + } + val err = MinimumError(mat, dcovar) + val edm: Double = VariableMetricEDMEstimator().estimate(dgrad, err) + var state = MinimumState(pa, err, dgrad, edm, fcn.numOfCalls()) + if (NegativeG2LineSearch.hasNegativeG2(dgrad, prec)) { + state = if (gc is AnalyticalGradientCalculator) { + val ngc = Numerical2PGradientCalculator(fcn, st.getTransformation(), stra) + NegativeG2LineSearch.search(fcn, state, ngc, prec) + } else { + NegativeG2LineSearch.search(fcn, state, gc, prec) + } + } + if (stra.strategy() === 2 && !st.hasCovariance()) { + //calculate full 2nd derivative + val tmp: MinimumState = MnHesse(stra).calculate(fcn, state, st.getTransformation(), 0) + return MinimumSeed(tmp, st.getTransformation()) + } + return MinimumSeed(state, st.getTransformation()) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSimplex.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSimplex.kt new file mode 100644 index 000000000..b00745f26 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSimplex.kt @@ -0,0 +1,138 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction +import ru.inr.mass.minuit.* + +/** + * SIMPLEX is a function minimization method using the simplex method of Nelder + * and Mead. MnSimplex provides minimization of the function by the method of + * SIMPLEX and the functionality for parameters interaction. It also retains the + * result from the last minimization in case the user may want to do subsequent + * minimization steps with parameter interactions in between the minimization + * requests. As SIMPLEX is a stepping method it does not produce a covariance + * matrix. + * + * @version $Id$ + * @author Darksnake + */ +class MnSimplex +/** + * construct from MultiFunction + MnUserParameterState + MnStrategy + * + * @param str a [hep.dataforge.MINUIT.MnStrategy] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameterState] object. + * @param fcn a [MultiFunction] object. + */ + (fcn: MultiFunction?, par: MnUserParameterState, str: MnStrategy) : MnApplication(fcn, par, str) { + private val theMinimizer: SimplexMinimizer = SimplexMinimizer() + + /** + * construct from MultiFunction + double[] for parameters and errors + * with default strategy + * + * @param err an array of double. + * @param par an array of double. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray) : this(fcn, par, err, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + double[] for parameters and errors + * + * @param stra a int. + * @param err an array of double. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, err: DoubleArray, stra: Int) : this(fcn, + MnUserParameterState(par, err), + MnStrategy(stra)) + + /** + * construct from MultiFunction + double[] for parameters and + * MnUserCovariance with default strategy + * + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param par an array of double. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance) : this(fcn, par, cov, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + double[] for parameters and + * MnUserCovariance + * + * @param stra a int. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param fcn a [MultiFunction] object. + * @param par an array of double. + */ + constructor(fcn: MultiFunction?, par: DoubleArray, cov: MnUserCovariance, stra: Int) : this(fcn, + MnUserParameterState(par, cov), + MnStrategy(stra)) + + /** + * construct from MultiFunction + MnUserParameters with default + * strategy + * + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters) : this(fcn, par, DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + MnUserParameters + * + * @param stra a int. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, stra: Int) : this(fcn, + MnUserParameterState(par), + MnStrategy(stra)) + + /** + * construct from MultiFunction + MnUserParameters + MnUserCovariance + * with default strategy + * + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + * @param fcn a [MultiFunction] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, cov: MnUserCovariance) : this(fcn, + par, + cov, + DEFAULT_STRATEGY) + + /** + * construct from MultiFunction + MnUserParameters + MnUserCovariance + * + * @param stra a int. + * @param cov a [hep.dataforge.MINUIT.MnUserCovariance] object. + * @param fcn a [MultiFunction] object. + * @param par a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + constructor(fcn: MultiFunction?, par: MnUserParameters, cov: MnUserCovariance, stra: Int) : this(fcn, + MnUserParameterState(par, cov), + MnStrategy(stra)) + + /** {@inheritDoc} */ + override fun minimizer(): ModularFunctionMinimizer { + return theMinimizer + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnStrategy.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnStrategy.kt new file mode 100644 index 000000000..31b894665 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnStrategy.kt @@ -0,0 +1,310 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * API class for defining three levels of strategies: low (0), medium (1), high + * (2). + * + * + * At many places in the analysis of the FCN (the user provided function), + * MINUIT must decide whether to be safe and waste a few function calls + * in order to know where it is, or to be fast and attempt to get the + * requested results with the fewest possible calls at a certain risk of not + * obtaining the precision desired by the user. In order to allow the user to + * infuence these decisions, the MnStrategy class allows the user to control + * different settings. MnStrategy can be instantiated with three different + * minimization quality levels for low (0), medium (1) and high (2) quality. + * Default settings for iteration cycles and tolerances are initialized then. + * + * + * The default setting is set for medium quality. Value 0 (low) indicates to + * MINUIT that it should economize function calls; it is intended for cases + * where there are many variable parameters and/or the function takes a long + * time to calculate and/or the user is not interested in very precise values + * for parameter errors. On the other hand, value 2 (high) indicates that MINUIT + * is allowed to waste function calls in order to be sure that all values are + * precise; it is it is intended for cases where the function is evaluated in a + * relatively short time and/or where the parameter errors must be calculated + * reliably. + * + * In addition all constants set in MnStrategy can be changed individually by + * the user, e.g. the number of iteration cycles in the numerical gradient. + * + * + * + * + * Acts on: Migrad (behavioural), Minos (lowers strategy by 1 for Minos-own + * minimization), Hesse (iterations), Numerical2PDerivative (iterations) + * + * @author Darksnake + * @version $Id$ + */ +class MnStrategy { + private var theGradNCyc = 0 + private var theGradTlr = 0.0 + private var theGradTlrStp = 0.0 + private var theHessGradNCyc = 0 + + //default strategy + private var theHessNCyc = 0 + private var theHessTlrG2 = 0.0 + private var theHessTlrStp = 0.0 + private var theStrategy = 0 + + /** + * Creates a MnStrategy object with the default strategy (medium) + */ + constructor() { + setMediumStrategy() + } + //user defined strategy (0, 1, >=2) + /** + * Creates a MnStrategy object with the user specified strategy. + * + * @param stra The use defined strategy, 0=low, 1 medium, 2=high. + */ + constructor(stra: Int) { + if (stra == 0) { + setLowStrategy() + } else if (stra == 1) { + setMediumStrategy() + } else { + setHighStrategy() + } + } + + /** + * + * gradientNCycles. + * + * @return a int. + */ + fun gradientNCycles(): Int { + return theGradNCyc + } + + /** + * + * gradientStepTolerance. + * + * @return a double. + */ + fun gradientStepTolerance(): Double { + return theGradTlrStp + } + + /** + * + * gradientTolerance. + * + * @return a double. + */ + fun gradientTolerance(): Double { + return theGradTlr + } + + /** + * + * hessianG2Tolerance. + * + * @return a double. + */ + fun hessianG2Tolerance(): Double { + return theHessTlrG2 + } + + /** + * + * hessianGradientNCycles. + * + * @return a int. + */ + fun hessianGradientNCycles(): Int { + return theHessGradNCyc + } + + /** + * + * hessianNCycles. + * + * @return a int. + */ + fun hessianNCycles(): Int { + return theHessNCyc + } + + /** + * + * hessianStepTolerance. + * + * @return a double. + */ + fun hessianStepTolerance(): Double { + return theHessTlrStp + } + + /** + * + * isHigh. + * + * @return a boolean. + */ + fun isHigh(): Boolean { + return theStrategy >= 2 + } + + /** + * + * isLow. + * + * @return a boolean. + */ + fun isLow(): Boolean { + return theStrategy <= 0 + } + + /** + * + * isMedium. + * + * @return a boolean. + */ + fun isMedium(): Boolean { + return theStrategy == 1 + } + + /** + * + * setGradientNCycles. + * + * @param n a int. + */ + fun setGradientNCycles(n: Int) { + theGradNCyc = n + } + + /** + * + * setGradientStepTolerance. + * + * @param stp a double. + */ + fun setGradientStepTolerance(stp: Double) { + theGradTlrStp = stp + } + + /** + * + * setGradientTolerance. + * + * @param toler a double. + */ + fun setGradientTolerance(toler: Double) { + theGradTlr = toler + } + + /** + * + * setHessianG2Tolerance. + * + * @param toler a double. + */ + fun setHessianG2Tolerance(toler: Double) { + theHessTlrG2 = toler + } + + /** + * + * setHessianGradientNCycles. + * + * @param n a int. + */ + fun setHessianGradientNCycles(n: Int) { + theHessGradNCyc = n + } + + /** + * + * setHessianNCycles. + * + * @param n a int. + */ + fun setHessianNCycles(n: Int) { + theHessNCyc = n + } + + /** + * + * setHessianStepTolerance. + * + * @param stp a double. + */ + fun setHessianStepTolerance(stp: Double) { + theHessTlrStp = stp + } + + fun setHighStrategy() { + theStrategy = 2 + setGradientNCycles(5) + setGradientStepTolerance(0.1) + setGradientTolerance(0.02) + setHessianNCycles(7) + setHessianStepTolerance(0.1) + setHessianG2Tolerance(0.02) + setHessianGradientNCycles(6) + } + + /** + * + * setLowStrategy. + */ + fun setLowStrategy() { + theStrategy = 0 + setGradientNCycles(2) + setGradientStepTolerance(0.5) + setGradientTolerance(0.1) + setHessianNCycles(3) + setHessianStepTolerance(0.5) + setHessianG2Tolerance(0.1) + setHessianGradientNCycles(1) + } + + /** + * + * setMediumStrategy. + */ + fun setMediumStrategy() { + theStrategy = 1 + setGradientNCycles(3) + setGradientStepTolerance(0.3) + setGradientTolerance(0.05) + setHessianNCycles(5) + setHessianStepTolerance(0.3) + setHessianG2Tolerance(0.05) + setHessianGradientNCycles(2) + } + + /** + * + * strategy. + * + * @return a int. + */ + fun strategy(): Int { + return theStrategy + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserCovariance.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserCovariance.kt new file mode 100644 index 000000000..297588f8e --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserCovariance.kt @@ -0,0 +1,147 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * MnUserCovariance is the external covariance matrix designed for the + * interaction of the user. The result of the minimization (internal covariance + * matrix) is converted into the user representable format. It can also be used + * as input prior to the minimization. The size of the covariance matrix is + * according to the number of variable parameters (free and limited). + * + * @version $Id$ + * @author Darksnake + */ +class MnUserCovariance { + private var theData: DoubleArray + private var theNRow: Int + + private constructor(other: MnUserCovariance) { + theData = other.theData.clone() + theNRow = other.theNRow + } + + internal constructor() { + theData = DoubleArray(0) + theNRow = 0 + } + + /* + * covariance matrix is stored in upper triangular packed storage format, + * e.g. the elements in the array are arranged like + * {a(0,0), a(0,1), a(1,1), a(0,2), a(1,2), a(2,2), ...}, + * the size is nrow*(nrow+1)/2. + */ + internal constructor(data: DoubleArray, nrow: Int) { + require(data.size == nrow * (nrow + 1) / 2) { "Inconsistent arguments" } + theData = data + theNRow = nrow + } + + /** + * + * Constructor for MnUserCovariance. + * + * @param nrow a int. + */ + constructor(nrow: Int) { + theData = DoubleArray(nrow * (nrow + 1) / 2) + theNRow = nrow + } + + /** + * + * copy. + * + * @return a [hep.dataforge.MINUIT.MnUserCovariance] object. + */ + fun copy(): MnUserCovariance { + return MnUserCovariance(this) + } + + fun data(): DoubleArray { + return theData + } + + /** + * + * get. + * + * @param row a int. + * @param col a int. + * @return a double. + */ + operator fun get(row: Int, col: Int): Double { + require(!(row >= theNRow || col >= theNRow)) + return if (row > col) { + theData[col + row * (row + 1) / 2] + } else { + theData[row + col * (col + 1) / 2] + } + } + + /** + * + * ncol. + * + * @return a int. + */ + fun ncol(): Int { + return theNRow + } + + /** + * + * nrow. + * + * @return a int. + */ + fun nrow(): Int { + return theNRow + } + + fun scale(f: Double) { + for (i in theData.indices) { + theData[i] *= f + } + } + + /** + * + * set. + * + * @param row a int. + * @param col a int. + * @param value a double. + */ + operator fun set(row: Int, col: Int, value: Double) { + require(!(row >= theNRow || col >= theNRow)) + if (row > col) { + theData[col + row * (row + 1) / 2] = value + } else { + theData[row + col * (col + 1) / 2] = value + } + } + + fun size(): Int { + return theData.size + } + + /** {@inheritDoc} */ + override fun toString(): String { + return MnPrint.toString(this) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserFcn.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserFcn.kt new file mode 100644 index 000000000..8198a41ab --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserFcn.kt @@ -0,0 +1,30 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction + +/** + * + * @version $Id$ + */ +internal class MnUserFcn(fcn: MultiFunction?, errDef: Double, trafo: MnUserTransformation) : MnFcn(fcn, errDef) { + private val theTransform: MnUserTransformation = trafo + override fun value(v: RealVector): Double { + return super.value(theTransform.transform(v)) + } + +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameterState.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameterState.kt new file mode 100644 index 000000000..e80dd60a1 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameterState.kt @@ -0,0 +1,756 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.minuit.* + +/** + * The class MnUserParameterState contains the MnUserParameters and the + * MnUserCovariance. It can be created on input by the user, or by MINUIT itself + * as user representable format of the result of the minimization. + * + * @version $Id$ + * @author Darksnake + */ +class MnUserParameterState { + private var theCovariance: MnUserCovariance + private var theCovarianceValid = false + private var theEDM = 0.0 + private var theFVal = 0.0 + private var theGCCValid = false + private var theGlobalCC: MnGlobalCorrelationCoeff? = null + private var theIntCovariance: MnUserCovariance + private var theIntParameters: MutableList + private var theNFcn = 0 + private var theParameters: MnUserParameters + private var theValid: Boolean + + internal constructor() { + theValid = false + theCovarianceValid = false + theParameters = MnUserParameters() + theCovariance = MnUserCovariance() + theIntParameters = java.util.ArrayList() + theIntCovariance = MnUserCovariance() + } + + private constructor(other: MnUserParameterState) { + theValid = other.theValid + theCovarianceValid = other.theCovarianceValid + theGCCValid = other.theGCCValid + theFVal = other.theFVal + theEDM = other.theEDM + theNFcn = other.theNFcn + theParameters = other.theParameters.copy() + theCovariance = other.theCovariance + theGlobalCC = other.theGlobalCC + theIntParameters = java.util.ArrayList(other.theIntParameters) + theIntCovariance = other.theIntCovariance.copy() + } + + /** + * construct from user parameters (before minimization) + * @param par + * @param err + */ + internal constructor(par: DoubleArray, err: DoubleArray) { + theValid = true + theParameters = MnUserParameters(par, err) + theCovariance = MnUserCovariance() + theGlobalCC = MnGlobalCorrelationCoeff() + theIntParameters = java.util.ArrayList(par.size) + for (i in par.indices) { + theIntParameters.add(par[i]) + } + theIntCovariance = MnUserCovariance() + } + + internal constructor(par: MnUserParameters) { + theValid = true + theParameters = par + theCovariance = MnUserCovariance() + theGlobalCC = MnGlobalCorrelationCoeff() + theIntParameters = java.util.ArrayList(par.variableParameters()) + theIntCovariance = MnUserCovariance() + val i = 0 + for (ipar in par.parameters()) { + if (ipar.isConst() || ipar.isFixed()) { + continue + } + if (ipar.hasLimits()) { + theIntParameters.add(ext2int(ipar.number(), ipar.value())) + } else { + theIntParameters.add(ipar.value()) + } + } + } + + /** + * construct from user parameters + covariance (before minimization) + * @param nrow + * @param cov + */ + internal constructor(par: DoubleArray, cov: DoubleArray, nrow: Int) { + theValid = true + theCovarianceValid = true + theCovariance = MnUserCovariance(cov, nrow) + theGlobalCC = MnGlobalCorrelationCoeff() + theIntParameters = java.util.ArrayList(par.size) + theIntCovariance = MnUserCovariance(cov, nrow) + val err = DoubleArray(par.size) + for (i in par.indices) { + assert(theCovariance[i, i] > 0.0) + err[i] = sqrt(theCovariance[i, i]) + theIntParameters.add(par[i]) + } + theParameters = MnUserParameters(par, err) + assert(theCovariance.nrow() === variableParameters()) + } + + internal constructor(par: DoubleArray, cov: MnUserCovariance) { + theValid = true + theCovarianceValid = true + theCovariance = cov + theGlobalCC = MnGlobalCorrelationCoeff() + theIntParameters = java.util.ArrayList(par.size) + theIntCovariance = cov.copy() + require(!(theCovariance.nrow() !== variableParameters())) { "Bad covariance size" } + val err = DoubleArray(par.size) + for (i in par.indices) { + require(theCovariance[i, i] > 0.0) { "Bad covariance" } + err[i] = sqrt(theCovariance[i, i]) + theIntParameters.add(par[i]) + } + theParameters = MnUserParameters(par, err) + } + + internal constructor(par: MnUserParameters, cov: MnUserCovariance) { + theValid = true + theCovarianceValid = true + theParameters = par + theCovariance = cov + theGlobalCC = MnGlobalCorrelationCoeff() + theIntParameters = java.util.ArrayList() + theIntCovariance = cov.copy() + theIntCovariance.scale(0.5) + val i = 0 + for (ipar in par.parameters()) { + if (ipar.isConst() || ipar.isFixed()) { + continue + } + if (ipar.hasLimits()) { + theIntParameters.add(ext2int(ipar.number(), ipar.value())) + } else { + theIntParameters.add(ipar.value()) + } + } + assert(theCovariance.nrow() === variableParameters()) + } + + /** + * construct from internal parameters (after minimization) + * @param trafo + * @param up + */ + internal constructor(st: MinimumState, up: Double, trafo: MnUserTransformation) { + theValid = st.isValid() + theCovarianceValid = false + theGCCValid = false + theFVal = st.fval() + theEDM = st.edm() + theNFcn = st.nfcn() + theParameters = MnUserParameters() + theCovariance = MnUserCovariance() + theGlobalCC = MnGlobalCorrelationCoeff() + theIntParameters = java.util.ArrayList() + theIntCovariance = MnUserCovariance() + for (ipar in trafo.parameters()) { + if (ipar.isConst()) { + add(ipar.name(), ipar.value()) + } else if (ipar.isFixed()) { + add(ipar.name(), ipar.value(), ipar.error()) + if (ipar.hasLimits()) { + if (ipar.hasLowerLimit() && ipar.hasUpperLimit()) { + setLimits(ipar.name(), ipar.lowerLimit(), ipar.upperLimit()) + } else if (ipar.hasLowerLimit() && !ipar.hasUpperLimit()) { + setLowerLimit(ipar.name(), ipar.lowerLimit()) + } else { + setUpperLimit(ipar.name(), ipar.upperLimit()) + } + } + fix(ipar.name()) + } else if (ipar.hasLimits()) { + val i: Int = trafo.intOfExt(ipar.number()) + val err: Double = if (st.hasCovariance()) sqrt(2.0 * up * st.error().invHessian()[i, i]) else st.parameters().dirin().getEntry(i) + add(ipar.name(), + trafo.int2ext(i, st.vec().getEntry(i)), + trafo.int2extError(i, st.vec().getEntry(i), err)) + if (ipar.hasLowerLimit() && ipar.hasUpperLimit()) { + setLimits(ipar.name(), ipar.lowerLimit(), ipar.upperLimit()) + } else if (ipar.hasLowerLimit() && !ipar.hasUpperLimit()) { + setLowerLimit(ipar.name(), ipar.lowerLimit()) + } else { + setUpperLimit(ipar.name(), ipar.upperLimit()) + } + } else { + val i: Int = trafo.intOfExt(ipar.number()) + val err: Double = if (st.hasCovariance()) sqrt(2.0 * up * st.error().invHessian()[i, i]) else st.parameters().dirin().getEntry(i) + add(ipar.name(), st.vec().getEntry(i), err) + } + } + theCovarianceValid = st.error().isValid() + if (theCovarianceValid) { + theCovariance = trafo.int2extCovariance(st.vec(), st.error().invHessian()) + theIntCovariance = MnUserCovariance(st.error().invHessian().data().clone(), st.error().invHessian().nrow()) + theCovariance.scale(2.0 * up) + theGlobalCC = MnGlobalCorrelationCoeff(st.error().invHessian()) + theGCCValid = true + assert(theCovariance.nrow() === variableParameters()) + } + } + + /** + * add free parameter name, value, error + * + * @param err a double. + * @param val a double. + * @param name a [String] object. + */ + fun add(name: String, `val`: Double, err: Double) { + theParameters.add(name, `val`, err) + theIntParameters.add(`val`) + theCovarianceValid = false + theGCCValid = false + theValid = true + } + + /** + * add limited parameter name, value, lower bound, upper bound + * + * @param name a [String] object. + * @param val a double. + * @param low a double. + * @param err a double. + * @param up a double. + */ + fun add(name: String, `val`: Double, err: Double, low: Double, up: Double) { + theParameters.add(name, `val`, err, low, up) + theCovarianceValid = false + theIntParameters.add(ext2int(index(name), `val`)) + theGCCValid = false + theValid = true + } + + /** + * add const parameter name, value + * + * @param name a [String] object. + * @param val a double. + */ + fun add(name: String, `val`: Double) { + theParameters.add(name, `val`) + theValid = true + } + + /** + * + * copy. + * + * @return a [hep.dataforge.MINUIT.MnUserParameterState] object. + */ + fun copy(): MnUserParameterState { + return MnUserParameterState(this) + } + + /** + * Covariance matrix in the external representation + * + * @return a [hep.dataforge.MINUIT.MnUserCovariance] object. + */ + fun covariance(): MnUserCovariance { + return theCovariance + } + + /** + * Returns the expected vertival distance to the minimum (EDM) + * + * @return a double. + */ + fun edm(): Double { + return theEDM + } + + /** + * + * error. + * + * @param index a int. + * @return a double. + */ + fun error(index: Int): Double { + return theParameters.error(index) + } + + /** + * + * error. + * + * @param name a [String] object. + * @return a double. + */ + fun error(name: String?): Double { + return error(index(name)) + } + + /** + * + * errors. + * + * @return an array of double. + */ + fun errors(): DoubleArray { + return theParameters.errors() + } + + fun ext2int(i: Int, `val`: Double): Double { + return theParameters.trafo().ext2int(i, `val`) + } + + /** + * + * extOfInt. + * + * @param internal a int. + * @return a int. + */ + fun extOfInt(internal: Int): Int { + return theParameters.trafo().extOfInt(internal) + } + /// interaction via external number of parameter + /** + * + * fix. + * + * @param e a int. + */ + fun fix(e: Int) { + val i = intOfExt(e) + if (theCovarianceValid) { + theCovariance = MnCovarianceSqueeze.squeeze(theCovariance, i) + theIntCovariance = MnCovarianceSqueeze.squeeze(theIntCovariance, i) + } + theIntParameters.removeAt(i) + theParameters.fix(e) + theGCCValid = false + } + /// interaction via name of parameter + /** + * + * fix. + * + * @param name a [String] object. + */ + fun fix(name: String?) { + fix(index(name)) + } + + /** + * returns the function value at the minimum + * + * @return a double. + */ + fun fval(): Double { + return theFVal + } + + /** + * transformation internal <-> external + * @return + */ + fun getTransformation(): MnUserTransformation { + return theParameters.trafo() + } + + fun globalCC(): MnGlobalCorrelationCoeff? { + return theGlobalCC + } + + /** + * Returns + * true if the the state has a valid covariance, + * false otherwise. + * + * @return a boolean. + */ + fun hasCovariance(): Boolean { + return theCovarianceValid + } + + /** + * + * hasGlobalCC. + * + * @return a boolean. + */ + fun hasGlobalCC(): Boolean { + return theGCCValid + } + + /** + * convert name into external number of parameter + * + * @param name a [String] object. + * @return a int. + */ + fun index(name: String?): Int { + return theParameters.index(name) + } + + // transformation internal <-> external + fun int2ext(i: Int, `val`: Double): Double { + return theParameters.trafo().int2ext(i, `val`) + } + + fun intCovariance(): MnUserCovariance { + return theIntCovariance + } + + fun intOfExt(ext: Int): Int { + return theParameters.trafo().intOfExt(ext) + } + + /** + * Minuit internal representation + * @return + */ + fun intParameters(): List { + return theIntParameters + } + + /** + * Returns + * true if the the state is valid, + * false if not + * + * @return a boolean. + */ + fun isValid(): Boolean { + return theValid + } + + // facade: forward interface of MnUserParameters and MnUserTransformation + fun minuitParameters(): List { + return theParameters.parameters() + } + + /** + * convert external number into name of parameter + * + * @param index a int. + * @return a [String] object. + */ + fun name(index: Int): String { + return theParameters.name(index) + } + + /** + * Returns the number of function calls during the minimization. + * + * @return a int. + */ + fun nfcn(): Int { + return theNFcn + } + + fun parameter(i: Int): MinuitParameter { + return theParameters.parameter(i) + } + + //user external representation + fun parameters(): MnUserParameters { + return theParameters + } + + /** + * access to parameters and errors in column-wise representation + * + * @return an array of double. + */ + fun params(): DoubleArray { + return theParameters.params() + } + + /** + * + * precision. + * + * @return a [hep.dataforge.MINUIT.MnMachinePrecision] object. + */ + fun precision(): MnMachinePrecision { + return theParameters.precision() + } + + /** + * + * release. + * + * @param e a int. + */ + fun release(e: Int) { + theParameters.release(e) + theCovarianceValid = false + theGCCValid = false + val i = intOfExt(e) + if (parameter(e).hasLimits()) { + theIntParameters.add(i, ext2int(e, parameter(e).value())) + } else { + theIntParameters.add(i, parameter(e).value()) + } + } + + /** + * + * release. + * + * @param name a [String] object. + */ + fun release(name: String?) { + release(index(name)) + } + + /** + * + * removeLimits. + * + * @param e a int. + */ + fun removeLimits(e: Int) { + theParameters.removeLimits(e) + theCovarianceValid = false + theGCCValid = false + if (!parameter(e).isFixed() && !parameter(e).isConst()) { + theIntParameters[intOfExt(e)] = value(e) + } + } + + /** + * + * removeLimits. + * + * @param name a [String] object. + */ + fun removeLimits(name: String?) { + removeLimits(index(name)) + } + + /** + * + * setError. + * + * @param e a int. + * @param err a double. + * @param err a double. + */ + fun setError(e: Int, err: Double) { + theParameters.setError(e, err) + } + + /** + * + * setError. + * + * @param name a [String] object. + * @param err a double. + */ + fun setError(name: String?, err: Double) { + setError(index(name), err) + } + + /** + * + * setLimits. + * + * @param e a int. + * @param low a double. + * @param up a double. + */ + fun setLimits(e: Int, low: Double, up: Double) { + theParameters.setLimits(e, low, up) + theCovarianceValid = false + theGCCValid = false + if (!parameter(e).isFixed() && !parameter(e).isConst()) { + val i = intOfExt(e) + if (low < theIntParameters[i] && theIntParameters[i] < up) { + theIntParameters[i] = ext2int(e, theIntParameters[i]) + } else { + theIntParameters[i] = ext2int(e, 0.5 * (low + up)) + } + } + } + + /** + * + * setLimits. + * + * @param name a [String] object. + * @param low a double. + * @param up a double. + */ + fun setLimits(name: String?, low: Double, up: Double) { + setLimits(index(name), low, up) + } + + /** + * + * setLowerLimit. + * + * @param e a int. + * @param low a double. + */ + fun setLowerLimit(e: Int, low: Double) { + theParameters.setLowerLimit(e, low) + theCovarianceValid = false + theGCCValid = false + if (!parameter(e).isFixed() && !parameter(e).isConst()) { + val i = intOfExt(e) + if (low < theIntParameters[i]) { + theIntParameters[i] = ext2int(e, theIntParameters[i]) + } else { + theIntParameters[i] = ext2int(e, low + 0.5 * abs(low + 1.0)) + } + } + } + + /** + * + * setLowerLimit. + * + * @param name a [String] object. + * @param low a double. + */ + fun setLowerLimit(name: String?, low: Double) { + setLowerLimit(index(name), low) + } + + /** + * + * setPrecision. + * + * @param eps a double. + */ + fun setPrecision(eps: Double) { + theParameters.setPrecision(eps) + } + + /** + * + * setUpperLimit. + * + * @param e a int. + * @param up a double. + */ + fun setUpperLimit(e: Int, up: Double) { + theParameters.setUpperLimit(e, up) + theCovarianceValid = false + theGCCValid = false + if (!parameter(e).isFixed() && !parameter(e).isConst()) { + val i = intOfExt(e) + if (theIntParameters[i] < up) { + theIntParameters[i] = ext2int(e, theIntParameters[i]) + } else { + theIntParameters[i] = ext2int(e, up - 0.5 * abs(up + 1.0)) + } + } + } + + /** + * + * setUpperLimit. + * + * @param name a [String] object. + * @param up a double. + */ + fun setUpperLimit(name: String?, up: Double) { + setUpperLimit(index(name), up) + } + + /** + * + * setValue. + * + * @param e a int. + * @param val a double. + */ + fun setValue(e: Int, `val`: Double) { + theParameters.setValue(e, `val`) + if (!parameter(e).isFixed() && !parameter(e).isConst()) { + val i = intOfExt(e) + if (parameter(e).hasLimits()) { + theIntParameters[i] = ext2int(e, `val`) + } else { + theIntParameters[i] = `val` + } + } + } + + /** + * + * setValue. + * + * @param name a [String] object. + * @param val a double. + */ + fun setValue(name: String?, `val`: Double) { + setValue(index(name), `val`) + } + + /** {@inheritDoc} */ + override fun toString(): String { + return MnPrint.toString(this) + } + + /** + * + * value. + * + * @param index a int. + * @return a double. + */ + fun value(index: Int): Double { + return theParameters.value(index) + } + + /** + * + * value. + * + * @param name a [String] object. + * @return a double. + */ + fun value(name: String?): Double { + return value(index(name)) + } + + /** + * + * variableParameters. + * + * @return a int. + */ + fun variableParameters(): Int { + return theParameters.variableParameters() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameters.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameters.kt new file mode 100644 index 000000000..9bac54b25 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameters.kt @@ -0,0 +1,402 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * API class for the user interaction with the parameters. Serves as input to + * the minimizer as well as output from it; users can interact: fix/release + * parameters, set values and errors, etc.; parameters can be accessed via their + * parameter number or via their user-specified name. + * + * @version $Id$ + * @author Darksnake + */ +class MnUserParameters { + private var theTransformation: MnUserTransformation + + /** + * Creates a new instance of MnUserParameters + */ + constructor() { + theTransformation = MnUserTransformation() + } + + /** + * + * Constructor for MnUserParameters. + * + * @param par an array of double. + * @param err an array of double. + */ + constructor(par: DoubleArray, err: DoubleArray) { + theTransformation = MnUserTransformation(par, err) + } + + private constructor(other: MnUserParameters) { + theTransformation = other.theTransformation.copy() + } + + /** + * Add free parameter name, value, error + * + * + * When adding parameters, MINUIT assigns indices to each parameter which + * will be the same as in the double[] in the + * MultiFunction.valueOf(). That means the first parameter the user + * adds gets index 0, the second index 1, and so on. When calculating the + * function value inside FCN, MINUIT will call + * MultiFunction.valueOf() with the elements at their respective + * positions. + * + * @param err a double. + * @param val a double. + * @param name a [String] object. + */ + fun add(name: String, `val`: Double, err: Double) { + theTransformation.add(name, `val`, err) + } + + /** + * Add limited parameter name, value, lower bound, upper bound + * + * @param up a double. + * @param low a double. + * @param name a [String] object. + * @param val a double. + * @param err a double. + */ + fun add(name: String, `val`: Double, err: Double, low: Double, up: Double) { + theTransformation.add(name, `val`, err, low, up) + } + + /** + * Add const parameter name, value + * + * @param name a [String] object. + * @param val a double. + */ + fun add(name: String, `val`: Double) { + theTransformation.add(name, `val`) + } + + /** + * + * copy. + * + * @return a [hep.dataforge.MINUIT.MnUserParameters] object. + */ + fun copy(): MnUserParameters { + return MnUserParameters(this) + } + + /** + * + * error. + * + * @param index a int. + * @return a double. + */ + fun error(index: Int): Double { + return theTransformation.error(index) + } + + /** + * + * error. + * + * @param name a [String] object. + * @return a double. + */ + fun error(name: String?): Double { + return theTransformation.error(name) + } + + fun errors(): DoubleArray { + return theTransformation.errors() + } + /// interaction via external number of parameter + /** + * Fixes the specified parameter (so that the minimizer will no longer vary + * it) + * + * @param index a int. + */ + fun fix(index: Int) { + theTransformation.fix(index) + } + /// interaction via name of parameter + /** + * Fixes the specified parameter (so that the minimizer will no longer vary + * it) + * + * @param name a [String] object. + */ + fun fix(name: String?) { + theTransformation.fix(name) + } + + /** + * convert name into external number of parameter + * @param name + * @return + */ + fun index(name: String?): Int { + return theTransformation.index(name) + } + + /** + * convert external number into name of parameter + * @param index + * @return + */ + fun name(index: Int): String { + return theTransformation.name(index) + } + + /** + * access to single parameter + * @param index + * @return + */ + fun parameter(index: Int): MinuitParameter { + return theTransformation.parameter(index) + } + + /** + * access to parameters (row-wise) + * @return + */ + fun parameters(): List { + return theTransformation.parameters() + } + + /** + * access to parameters and errors in column-wise representation + * @return + */ + fun params(): DoubleArray { + return theTransformation.params() + } + + /** + * + * precision. + * + * @return a [hep.dataforge.MINUIT.MnMachinePrecision] object. + */ + fun precision(): MnMachinePrecision { + return theTransformation.precision() + } + + /** + * Releases the specified parameter (so that the minimizer can vary it) + * + * @param index a int. + */ + fun release(index: Int) { + theTransformation.release(index) + } + + /** + * Releases the specified parameter (so that the minimizer can vary it) + * + * @param name a [String] object. + */ + fun release(name: String?) { + theTransformation.release(name) + } + + /** + * + * removeLimits. + * + * @param index a int. + */ + fun removeLimits(index: Int) { + theTransformation.removeLimits(index) + } + + /** + * + * removeLimits. + * + * @param name a [String] object. + */ + fun removeLimits(name: String?) { + theTransformation.removeLimits(name) + } + + /** + * + * setError. + * + * @param index a int. + * @param err a double. + */ + fun setError(index: Int, err: Double) { + theTransformation.setError(index, err) + } + + /** + * + * setError. + * + * @param name a [String] object. + * @param err a double. + */ + fun setError(name: String?, err: Double) { + theTransformation.setError(name, err) + } + + /** + * Set the lower and upper bound on the specified variable. + * + * @param up a double. + * @param low a double. + * @param index a int. + */ + fun setLimits(index: Int, low: Double, up: Double) { + theTransformation.setLimits(index, low, up) + } + + /** + * Set the lower and upper bound on the specified variable. + * + * @param up a double. + * @param low a double. + * @param name a [String] object. + */ + fun setLimits(name: String?, low: Double, up: Double) { + theTransformation.setLimits(name, low, up) + } + + /** + * + * setLowerLimit. + * + * @param index a int. + * @param low a double. + */ + fun setLowerLimit(index: Int, low: Double) { + theTransformation.setLowerLimit(index, low) + } + + /** + * + * setLowerLimit. + * + * @param name a [String] object. + * @param low a double. + */ + fun setLowerLimit(name: String?, low: Double) { + theTransformation.setLowerLimit(name, low) + } + + /** + * + * setPrecision. + * + * @param eps a double. + */ + fun setPrecision(eps: Double) { + theTransformation.setPrecision(eps) + } + + /** + * + * setUpperLimit. + * + * @param index a int. + * @param up a double. + */ + fun setUpperLimit(index: Int, up: Double) { + theTransformation.setUpperLimit(index, up) + } + + /** + * + * setUpperLimit. + * + * @param name a [String] object. + * @param up a double. + */ + fun setUpperLimit(name: String?, up: Double) { + theTransformation.setUpperLimit(name, up) + } + + /** + * Set the value of parameter. The parameter in question may be variable, + * fixed, or constant, but must be defined. + * + * @param index a int. + * @param val a double. + */ + fun setValue(index: Int, `val`: Double) { + theTransformation.setValue(index, `val`) + } + + /** + * Set the value of parameter. The parameter in question may be variable, + * fixed, or constant, but must be defined. + * + * @param name a [String] object. + * @param val a double. + */ + fun setValue(name: String?, `val`: Double) { + theTransformation.setValue(name, `val`) + } + + /** {@inheritDoc} */ + override fun toString(): String { + return MnPrint.toString(this) + } + + fun trafo(): MnUserTransformation { + return theTransformation + } + + /** + * + * value. + * + * @param index a int. + * @return a double. + */ + fun value(index: Int): Double { + return theTransformation.value(index) + } + + /** + * + * value. + * + * @param name a [String] object. + * @return a double. + */ + fun value(name: String?): Double { + return theTransformation.value(name) + } + + /** + * + * variableParameters. + * + * @return a int. + */ + fun variableParameters(): Int { + return theTransformation.variableParameters() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserTransformation.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserTransformation.kt new file mode 100644 index 000000000..1066ac2da --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserTransformation.kt @@ -0,0 +1,390 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector + +/** + * knows how to andThen between user specified parameters (external) and + * internal parameters used for minimization + * + * Жуткий октопус, который занимается преобразованием внешних параметров во внутренние + * TODO по возможности отказаться от использования этого монстра + * @version $Id$ + */ +class MnUserTransformation { + private val nameMap: MutableMap = HashMap() + private var theCache: MutableList + private var theExtOfInt: MutableList + private var theParameters: MutableList + private var thePrecision: MnMachinePrecision + + constructor() { + thePrecision = MnMachinePrecision() + theParameters = java.util.ArrayList() + theExtOfInt = java.util.ArrayList() + theCache = java.util.ArrayList(0) + } + + private constructor(other: MnUserTransformation) { + thePrecision = other.thePrecision + theParameters = java.util.ArrayList(other.theParameters.size) + for (par in other.theParameters) { + theParameters.add(par.copy()) + } + theExtOfInt = java.util.ArrayList(other.theExtOfInt) + theCache = java.util.ArrayList(other.theCache) + } + + constructor(par: DoubleArray, err: DoubleArray) { + thePrecision = MnMachinePrecision() + theParameters = java.util.ArrayList(par.size) + theExtOfInt = java.util.ArrayList(par.size) + theCache = java.util.ArrayList(par.size) + for (i in par.indices) { + add("p$i", par[i], err[i]) + } + } + + /** + * add free parameter + * @param err + * @param val + */ + fun add(name: String, `val`: Double, err: Double) { + require(!nameMap.containsKey(name)) { "duplicate name: $name" } + nameMap[name] = theParameters.size + theExtOfInt.add(theParameters.size) + theCache.add(`val`) + theParameters.add(MinuitParameter(theParameters.size, name, `val`, err)) + } + + /** + * add limited parameter + * @param up + * @param low + */ + fun add(name: String, `val`: Double, err: Double, low: Double, up: Double) { + require(!nameMap.containsKey(name)) { "duplicate name: $name" } + nameMap[name] = theParameters.size + theExtOfInt.add(theParameters.size) + theCache.add(`val`) + theParameters.add(MinuitParameter(theParameters.size, name, `val`, err, low, up)) + } + + /** + * add parameter + * @param name + * @param val + */ + fun add(name: String, `val`: Double) { + require(!nameMap.containsKey(name)) { "duplicate name: $name" } + nameMap[name] = theParameters.size + theCache.add(`val`) + theParameters.add(MinuitParameter(theParameters.size, name, `val`)) + } + + /** + * + * copy. + * + * @return a [hep.dataforge.MINUIT.MnUserTransformation] object. + */ + fun copy(): MnUserTransformation { + return MnUserTransformation(this) + } + + fun dInt2Ext(i: Int, `val`: Double): Double { + var dd = 1.0 + val parm: MinuitParameter = theParameters[theExtOfInt[i]] + if (parm.hasLimits()) { + dd = if (parm.hasUpperLimit() && parm.hasLowerLimit()) { + theDoubleLimTrafo.dInt2Ext(`val`, + parm.upperLimit(), + parm.lowerLimit()) + } else if (parm.hasUpperLimit() && !parm.hasLowerLimit()) { + theUpperLimTrafo.dInt2Ext(`val`, parm.upperLimit()) + } else { + theLowerLimTrafo.dInt2Ext(`val`, parm.lowerLimit()) + } + } + return dd + } + + fun error(index: Int): Double { + return theParameters[index].error() + } + + fun error(name: String?): Double { + return error(index(name)) + } + + fun errors(): DoubleArray { + val result = DoubleArray(theParameters.size) + var i = 0 + for (parameter in theParameters) { + result[i++] = parameter.error() + } + return result + } + + fun ext2int(i: Int, `val`: Double): Double { + val parm: MinuitParameter = theParameters[i] + return if (parm.hasLimits()) { + if (parm.hasUpperLimit() && parm.hasLowerLimit()) { + theDoubleLimTrafo.ext2int(`val`, + parm.upperLimit(), + parm.lowerLimit(), + precision()) + } else if (parm.hasUpperLimit() && !parm.hasLowerLimit()) { + theUpperLimTrafo.ext2int(`val`, + parm.upperLimit(), + precision()) + } else { + theLowerLimTrafo.ext2int(`val`, + parm.lowerLimit(), + precision()) + } + } else `val` + } + + fun extOfInt(internal: Int): Int { + return theExtOfInt[internal] + } + + /** + * interaction via external number of parameter + * @param index + */ + fun fix(index: Int) { + val iind = intOfExt(index) + theExtOfInt.removeAt(iind) + theParameters[index].fix() + } + + /** + * interaction via name of parameter + * @param name + */ + fun fix(name: String?) { + fix(index(name)) + } + + /** + * convert name into external number of parameter + * @param name + * @return + */ + fun index(name: String?): Int { + return nameMap[name]!! + } + + fun int2ext(i: Int, `val`: Double): Double { + val parm: MinuitParameter = theParameters[theExtOfInt[i]] + return if (parm.hasLimits()) { + if (parm.hasUpperLimit() && parm.hasLowerLimit()) { + theDoubleLimTrafo.int2ext(`val`, + parm.upperLimit(), + parm.lowerLimit()) + } else if (parm.hasUpperLimit() && !parm.hasLowerLimit()) { + theUpperLimTrafo.int2ext(`val`, parm.upperLimit()) + } else { + theLowerLimTrafo.int2ext(`val`, parm.lowerLimit()) + } + } else `val` + } + + fun int2extCovariance(vec: RealVector, cov: MnAlgebraicSymMatrix): MnUserCovariance { + val result = MnUserCovariance(cov.nrow()) + for (i in 0 until vec.getDimension()) { + var dxdi = 1.0 + if (theParameters[theExtOfInt[i]].hasLimits()) { + dxdi = dInt2Ext(i, vec.getEntry(i)) + } + for (j in i until vec.getDimension()) { + var dxdj = 1.0 + if (theParameters[theExtOfInt[j]].hasLimits()) { + dxdj = dInt2Ext(j, vec.getEntry(j)) + } + result[i, j] = dxdi * cov[i, j] * dxdj + } + } + return result + } + + fun int2extError(i: Int, `val`: Double, err: Double): Double { + var dx = err + val parm: MinuitParameter = theParameters[theExtOfInt[i]] + if (parm.hasLimits()) { + val ui = int2ext(i, `val`) + var du1 = int2ext(i, `val` + dx) - ui + val du2 = int2ext(i, `val` - dx) - ui + if (parm.hasUpperLimit() && parm.hasLowerLimit()) { + if (dx > 1.0) { + du1 = parm.upperLimit() - parm.lowerLimit() + } + dx = 0.5 * (abs(du1) + abs(du2)) + } else { + dx = 0.5 * (abs(du1) + abs(du2)) + } + } + return dx + } + + fun intOfExt(ext: Int): Int { + for (iind in theExtOfInt.indices) { + if (ext == theExtOfInt[iind]) { + return iind + } + } + throw IllegalArgumentException("ext=$ext") + } + + /** + * convert external number into name of parameter + * @param index + * @return + */ + fun name(index: Int): String { + return theParameters[index].name() + } + + /** + * access to single parameter + * @param index + * @return + */ + fun parameter(index: Int): MinuitParameter { + return theParameters[index] + } + + fun parameters(): List { + return theParameters + } + + //access to parameters and errors in column-wise representation + fun params(): DoubleArray { + val result = DoubleArray(theParameters.size) + var i = 0 + for (parameter in theParameters) { + result[i++] = parameter.value() + } + return result + } + + fun precision(): MnMachinePrecision { + return thePrecision + } + + fun release(index: Int) { + require(!theExtOfInt.contains(index)) { "index=$index" } + theExtOfInt.add(index) + Collections.sort(theExtOfInt) + theParameters[index].release() + } + + fun release(name: String?) { + release(index(name)) + } + + fun removeLimits(index: Int) { + theParameters[index].removeLimits() + } + + fun removeLimits(name: String?) { + removeLimits(index(name)) + } + + fun setError(index: Int, err: Double) { + theParameters[index].setError(err) + } + + fun setError(name: String?, err: Double) { + setError(index(name), err) + } + + fun setLimits(index: Int, low: Double, up: Double) { + theParameters[index].setLimits(low, up) + } + + fun setLimits(name: String?, low: Double, up: Double) { + setLimits(index(name), low, up) + } + + fun setLowerLimit(index: Int, low: Double) { + theParameters[index].setLowerLimit(low) + } + + fun setLowerLimit(name: String?, low: Double) { + setLowerLimit(index(name), low) + } + + fun setPrecision(eps: Double) { + thePrecision.setPrecision(eps) + } + + fun setUpperLimit(index: Int, up: Double) { + theParameters[index].setUpperLimit(up) + } + + fun setUpperLimit(name: String?, up: Double) { + setUpperLimit(index(name), up) + } + + fun setValue(index: Int, `val`: Double) { + theParameters[index].setValue(`val`) + theCache[index] = `val` + } + + fun setValue(name: String?, `val`: Double) { + setValue(index(name), `val`) + } + + fun transform(pstates: RealVector): ArrayRealVector { + // FixMe: Worry about efficiency here + val result = ArrayRealVector(theCache.size) + for (i in 0 until result.getDimension()) { + result.setEntry(i, theCache[i]) + } + for (i in 0 until pstates.getDimension()) { + if (theParameters[theExtOfInt[i]].hasLimits()) { + result.setEntry(theExtOfInt[i], int2ext(i, pstates.getEntry(i))) + } else { + result.setEntry(theExtOfInt[i], pstates.getEntry(i)) + } + } + return result + } + + //forwarded interface + fun value(index: Int): Double { + return theParameters[index].value() + } + + fun value(name: String?): Double { + return value(index(name)) + } + + fun variableParameters(): Int { + return theExtOfInt.size + } + + companion object { + private val theDoubleLimTrafo: SinParameterTransformation = SinParameterTransformation() + private val theLowerLimTrafo: SqrtLowParameterTransformation = SqrtLowParameterTransformation() + private val theUpperLimTrafo: SqrtUpParameterTransformation = SqrtUpParameterTransformation() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUtils.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUtils.kt new file mode 100644 index 000000000..d9f3e1bd5 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUtils.kt @@ -0,0 +1,147 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector + +/** + * Utilities for operating on vectors and matrices + * + * @version $Id$ + */ +internal object MnUtils { + fun absoluteSumOfElements(m: MnAlgebraicSymMatrix): Double { + val data: DoubleArray = m.data() + var result = 0.0 + for (i in data.indices) { + result += abs(data[i]) + } + return result + } + + fun add(v1: RealVector, v2: RealVector?): RealVector { + return v1.add(v2) + } + + fun add(m1: MnAlgebraicSymMatrix, m2: MnAlgebraicSymMatrix): MnAlgebraicSymMatrix { + require(!(m1.size() !== m2.size())) { "Incompatible matrices" } + val result: MnAlgebraicSymMatrix = m1.copy() + val a: DoubleArray = result.data() + val b: DoubleArray = m2.data() + for (i in a.indices) { + a[i] += b[i] + } + return result + } + + fun div(m: MnAlgebraicSymMatrix?, scale: Double): MnAlgebraicSymMatrix { + return mul(m, 1 / scale) + } + + fun div(m: RealVector?, scale: Double): RealVector { + return mul(m, 1 / scale) + } + + fun innerProduct(v1: RealVector, v2: RealVector): Double { + require(!(v1.getDimension() !== v2.getDimension())) { "Incompatible vectors" } + var total = 0.0 + for (i in 0 until v1.getDimension()) { + total += v1.getEntry(i) * v2.getEntry(i) + } + return total + } + + fun mul(v1: RealVector, scale: Double): RealVector { + return v1.mapMultiply(scale) + } + + fun mul(m1: MnAlgebraicSymMatrix, scale: Double): MnAlgebraicSymMatrix { + val result: MnAlgebraicSymMatrix = m1.copy() + val a: DoubleArray = result.data() + for (i in a.indices) { + a[i] *= scale + } + return result + } + + fun mul(m1: MnAlgebraicSymMatrix, v1: RealVector): ArrayRealVector { + require(!(m1.nrow() !== v1.getDimension())) { "Incompatible arguments" } + val result = ArrayRealVector(m1.nrow()) + for (i in 0 until result.getDimension()) { + var total = 0.0 + for (k in 0 until result.getDimension()) { + total += m1[i, k] * v1.getEntry(k) + } + result.setEntry(i, total) + } + return result + } + + fun mul(m1: MnAlgebraicSymMatrix, m2: MnAlgebraicSymMatrix): MnAlgebraicSymMatrix { + require(!(m1.size() !== m2.size())) { "Incompatible matrices" } + val n: Int = m1.nrow() + val result = MnAlgebraicSymMatrix(n) + for (i in 0 until n) { + for (j in 0..i) { + var total = 0.0 + for (k in 0 until n) { + total += m1[i, k] * m2[k, j] + } + result[i, j] = total + } + } + return result + } + + fun outerProduct(v2: RealVector): MnAlgebraicSymMatrix { + // Fixme: check this. I am assuming this is just an outer-product of vector + // with itself. + val n: Int = v2.getDimension() + val result = MnAlgebraicSymMatrix(n) + val data: DoubleArray = v2.toArray() + for (i in 0 until n) { + for (j in 0..i) { + result[i, j] = data[i] * data[j] + } + } + return result + } + + fun similarity(avec: RealVector, mat: MnAlgebraicSymMatrix): Double { + val n: Int = avec.getDimension() + val tmp: RealVector = mul(mat, avec) + var result = 0.0 + for (i in 0 until n) { + result += tmp.getEntry(i) * avec.getEntry(i) + } + return result + } + + fun sub(v1: RealVector, v2: RealVector?): RealVector { + return v1.subtract(v2) + } + + fun sub(m1: MnAlgebraicSymMatrix, m2: MnAlgebraicSymMatrix): MnAlgebraicSymMatrix { + require(!(m1.size() !== m2.size())) { "Incompatible matrices" } + val result: MnAlgebraicSymMatrix = m1.copy() + val a: DoubleArray = result.data() + val b: DoubleArray = m2.data() + for (i in a.indices) { + a[i] -= b[i] + } + return result + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ModularFunctionMinimizer.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ModularFunctionMinimizer.kt new file mode 100644 index 000000000..f234bcd48 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ModularFunctionMinimizer.kt @@ -0,0 +1,72 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import ru.inr.mass.maths.MultiFunction +import ru.inr.mass.minuit.* + +/** + * + * @version $Id$ + */ +abstract class ModularFunctionMinimizer { + abstract fun builder(): MinimumBuilder + fun minimize( + fcn: MultiFunction?, + st: MnUserParameterState, + strategy: MnStrategy, + maxfcn: Int, + toler: Double, + errorDef: Double, + useAnalyticalGradient: Boolean, + checkGradient: Boolean + ): FunctionMinimum { + var maxfcn = maxfcn + val mfcn = MnUserFcn(fcn, errorDef, st.getTransformation()) + val gc: GradientCalculator + var providesAllDerivs = true + /* + * Проверяем в явном виде, что все аналитические производные присутствуют + * TODO сделать возможность того, что часть производных задается аналитически, а часть численно + */for (i in 0 until fcn.getDimension()) { + if (!fcn.providesDeriv(i)) providesAllDerivs = false + } + gc = if (providesAllDerivs && useAnalyticalGradient) { + AnalyticalGradientCalculator(fcn, st.getTransformation(), checkGradient) + } else { + Numerical2PGradientCalculator(mfcn, st.getTransformation(), strategy) + } + val npar: Int = st.variableParameters() + if (maxfcn == 0) { + maxfcn = 200 + 100 * npar + 5 * npar * npar + } + val mnseeds: MinimumSeed = seedGenerator().generate(mfcn, gc, st, strategy) + return minimize(mfcn, gc, mnseeds, strategy, maxfcn, toler) + } + + fun minimize( + mfcn: MnFcn, + gc: GradientCalculator?, + seed: MinimumSeed?, + strategy: MnStrategy?, + maxfcn: Int, + toler: Double + ): FunctionMinimum { + return builder().minimum(mfcn, gc, seed, strategy, maxfcn, toler * mfcn.errorDef()) + } + + abstract fun seedGenerator(): MinimumSeedGenerator +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/NegativeG2LineSearch.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/NegativeG2LineSearch.kt new file mode 100644 index 000000000..2e9ce5813 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/NegativeG2LineSearch.kt @@ -0,0 +1,80 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector +import ru.inr.mass.minuit.* + +/** + * In case that one of the components of the second derivative g2 calculated by + * the numerical gradient calculator is negative, a 1dim line search in the + * direction of that component is done in order to find a better position where + * g2 is again positive. + * + * @version $Id$ + */ +internal object NegativeG2LineSearch { + fun hasNegativeG2(grad: FunctionGradient, prec: MnMachinePrecision): Boolean { + for (i in 0 until grad.getGradient().getDimension()) { + if (grad.getGradientDerivative().getEntry(i) < prec.eps2()) { + return true + } + } + return false + } + + fun search(fcn: MnFcn, st: MinimumState, gc: GradientCalculator, prec: MnMachinePrecision): MinimumState { + val negG2 = hasNegativeG2(st.gradient(), prec) + if (!negG2) { + return st + } + val n: Int = st.parameters().vec().getDimension() + var dgrad: FunctionGradient = st.gradient() + var pa: MinimumParameters = st.parameters() + var iterate = false + var iter = 0 + do { + iterate = false + for (i in 0 until n) { + if (dgrad.getGradientDerivative().getEntry(i) < prec.eps2()) { + // do line search if second derivative negative + var step: RealVector = ArrayRealVector(n) + step.setEntry(i, dgrad.getStep().getEntry(i) * dgrad.getGradient().getEntry(i)) + if (abs(dgrad.getGradient().getEntry(i)) > prec.eps2()) { + step.setEntry(i, + step.getEntry(i) * (-1.0 / abs(dgrad.getGradient().getEntry(i)))) + } + val gdel: Double = step.getEntry(i) * dgrad.getGradient().getEntry(i) + val pp: MnParabolaPoint = MnLineSearch.search(fcn, pa, step, gdel, prec) + step = MnUtils.mul(step, pp.x()) + pa = MinimumParameters(MnUtils.add(pa.vec(), step), pp.y()) + dgrad = gc.gradient(pa, dgrad) + iterate = true + break + } + } + } while (iter++ < 2 * n && iterate) + val mat = MnAlgebraicSymMatrix(n) + for (i in 0 until n) { + mat[i, i] = if (abs(dgrad.getGradientDerivative() + .getEntry(i)) > prec.eps2() + ) 1.0 / dgrad.getGradientDerivative().getEntry(i) else 1.0 + } + val err = MinimumError(mat, 1.0) + val edm: Double = VariableMetricEDMEstimator().estimate(dgrad, err) + return MinimumState(pa, err, dgrad, edm, fcn.numOfCalls()) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Numerical2PGradientCalculator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Numerical2PGradientCalculator.kt new file mode 100644 index 000000000..efa1d57af --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Numerical2PGradientCalculator.kt @@ -0,0 +1,122 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.RealVector +import ru.inr.mass.minuit.* + +/** + * + * @version $Id$ + */ +internal class Numerical2PGradientCalculator(fcn: MnFcn, par: MnUserTransformation, stra: MnStrategy) : + GradientCalculator { + private val theFcn: MnFcn = fcn + private val theStrategy: MnStrategy + private val theTransformation: MnUserTransformation + fun fcn(): MnFcn { + return theFcn + } + + fun gradTolerance(): Double { + return strategy().gradientTolerance() + } + + /** {@inheritDoc} */ + fun gradient(par: MinimumParameters): FunctionGradient { + val gc = InitialGradientCalculator(theFcn, theTransformation, theStrategy) + val gra: FunctionGradient = gc.gradient(par) + return gradient(par, gra) + } + + /** {@inheritDoc} */ + fun gradient(par: MinimumParameters, gradient: FunctionGradient): FunctionGradient { + require(par.isValid()) { "Parameters are invalid" } + val x: RealVector = par.vec().copy() + val fcnmin: Double = par.fval() + val dfmin: Double = 8.0 * precision().eps2() * (abs(fcnmin) + theFcn.errorDef()) + val vrysml: Double = 8.0 * precision().eps() * precision().eps() + val n: Int = x.getDimension() + val grd: RealVector = gradient.getGradient().copy() + val g2: RealVector = gradient.getGradientDerivative().copy() + val gstep: RealVector = gradient.getStep().copy() + for (i in 0 until n) { + val xtf: Double = x.getEntry(i) + val epspri: Double = precision().eps2() + abs(grd.getEntry(i) * precision().eps2()) + var stepb4 = 0.0 + for (j in 0 until ncycle()) { + val optstp: Double = sqrt(dfmin / (abs(g2.getEntry(i)) + epspri)) + var step: Double = max(optstp, abs(0.1 * gstep.getEntry(i))) + if (trafo().parameter(trafo().extOfInt(i)).hasLimits()) { + if (step > 0.5) { + step = 0.5 + } + } + val stpmax: Double = 10.0 * abs(gstep.getEntry(i)) + if (step > stpmax) { + step = stpmax + } + val stpmin: Double = + max(vrysml, 8.0 * abs(precision().eps2() * x.getEntry(i))) + if (step < stpmin) { + step = stpmin + } + if (abs((step - stepb4) / step) < stepTolerance()) { + break + } + gstep.setEntry(i, step) + stepb4 = step + x.setEntry(i, xtf + step) + val fs1: Double = theFcn.value(x) + x.setEntry(i, xtf - step) + val fs2: Double = theFcn.value(x) + x.setEntry(i, xtf) + val grdb4: Double = grd.getEntry(i) + grd.setEntry(i, 0.5 * (fs1 - fs2) / step) + g2.setEntry(i, (fs1 + fs2 - 2.0 * fcnmin) / step / step) + if (abs(grdb4 - grd.getEntry(i)) / (abs(grd.getEntry(i)) + dfmin / step) < gradTolerance()) { + break + } + } + } + return FunctionGradient(grd, g2, gstep) + } + + fun ncycle(): Int { + return strategy().gradientNCycles() + } + + fun precision(): MnMachinePrecision { + return theTransformation.precision() + } + + fun stepTolerance(): Double { + return strategy().gradientStepTolerance() + } + + fun strategy(): MnStrategy { + return theStrategy + } + + fun trafo(): MnUserTransformation { + return theTransformation + } + + init { + theTransformation = par + theStrategy = stra + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Range.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Range.kt new file mode 100644 index 000000000..ebeedf7e8 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Range.kt @@ -0,0 +1,32 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * A class representing a pair of double (x,y) or (lower,upper) + * + * @version $Id$ + * @author Darksnake + */ +class Range +/** + * + * Constructor for Range. + * + * @param k a double. + * @param v a double. + */ + (k: Double, v: Double) : Pair(k, v) \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanBuilder.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanBuilder.kt new file mode 100644 index 000000000..b7e773924 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanBuilder.kt @@ -0,0 +1,58 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector +import ru.inr.mass.minuit.* + +/** + * Performs a minimization using the simplex method of Nelder and Mead (ref. + * Comp. J. 7, 308 (1965)). + * + * @version $Id$ + */ +internal class ScanBuilder : MinimumBuilder { + /** {@inheritDoc} */ + fun minimum( + mfcn: MnFcn, + gc: GradientCalculator?, + seed: MinimumSeed, + stra: MnStrategy?, + maxfcn: Int, + toler: Double + ): FunctionMinimum { + val x: RealVector = seed.parameters().vec().copy() + val upst = MnUserParameterState(seed.state(), mfcn.errorDef(), seed.trafo()) + val scan = MnParameterScan(mfcn.fcn(), upst.parameters(), seed.fval()) + var amin: Double = scan.fval() + val n: Int = seed.trafo().variableParameters() + val dirin: RealVector = ArrayRealVector(n) + for (i in 0 until n) { + val ext: Int = seed.trafo().extOfInt(i) + scan.scan(ext) + if (scan.fval() < amin) { + amin = scan.fval() + x.setEntry(i, seed.trafo().ext2int(ext, scan.parameters().value(ext))) + } + dirin.setEntry(i, sqrt(2.0 * mfcn.errorDef() * seed.error().invHessian()[i, i])) + } + val mp = MinimumParameters(x, dirin, amin) + val st = MinimumState(mp, 0.0, mfcn.numOfCalls()) + val states: MutableList = java.util.ArrayList(1) + states.add(st) + return FunctionMinimum(seed, states, mfcn.errorDef()) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanMinimizer.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanMinimizer.kt new file mode 100644 index 000000000..e39a49c0d --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanMinimizer.kt @@ -0,0 +1,36 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal class ScanMinimizer : ModularFunctionMinimizer() { + private val theBuilder: ScanBuilder + private val theSeedGenerator: SimplexSeedGenerator = SimplexSeedGenerator() + override fun builder(): MinimumBuilder { + return theBuilder + } + + override fun seedGenerator(): MinimumSeedGenerator { + return theSeedGenerator + } + + init { + theBuilder = ScanBuilder() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexBuilder.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexBuilder.kt new file mode 100644 index 000000000..8441a4177 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexBuilder.kt @@ -0,0 +1,179 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import space.kscience.kmath.optimization.minuit.MINUITPlugin +import ru.inr.mass.minuit.* + +/** + * + * @version $Id$ + */ +internal class SimplexBuilder : MinimumBuilder { + /** {@inheritDoc} */ + fun minimum( + mfcn: MnFcn, + gc: GradientCalculator?, + seed: MinimumSeed, + strategy: MnStrategy?, + maxfcn: Int, + minedm: Double + ): FunctionMinimum { + val prec: MnMachinePrecision = seed.precision() + val x: RealVector = seed.parameters().vec().copy() + val step: RealVector = MnUtils.mul(seed.gradient().getStep(), 10.0) + val n: Int = x.getDimension() + val wg = 1.0 / n + val alpha = 1.0 + val beta = 0.5 + val gamma = 2.0 + val rhomin = 4.0 + val rhomax = 8.0 + val rho1 = 1.0 + alpha + val rho2 = 1.0 + alpha * gamma + val simpl: MutableList> = java.util.ArrayList>(n + 1) + simpl.add(Pair(seed.fval(), x.copy())) + var jl = 0 + var jh = 0 + var amin: Double = seed.fval() + var aming: Double = seed.fval() + for (i in 0 until n) { + val dmin: Double = 8.0 * prec.eps2() * (abs(x.getEntry(i)) + prec.eps2()) + if (step.getEntry(i) < dmin) { + step.setEntry(i, dmin) + } + x.setEntry(i, x.getEntry(i) + step.getEntry(i)) + val tmp: Double = mfcn.value(x) + if (tmp < amin) { + amin = tmp + jl = i + 1 + } + if (tmp > aming) { + aming = tmp + jh = i + 1 + } + simpl.add(Pair(tmp, x.copy())) + x.setEntry(i, x.getEntry(i) - step.getEntry(i)) + } + val simplex = SimplexParameters(simpl, jh, jl) + do { + amin = simplex[jl].getFirst() + jl = simplex.jl() + jh = simplex.jh() + var pbar: RealVector = ArrayRealVector(n) + for (i in 0 until n + 1) { + if (i == jh) { + continue + } + pbar = MnUtils.add(pbar, MnUtils.mul(simplex[i].getSecond(), wg)) + } + val pstar: RealVector = + MnUtils.sub(MnUtils.mul(pbar, 1.0 + alpha), MnUtils.mul(simplex[jh].getSecond(), alpha)) + val ystar: Double = mfcn.value(pstar) + if (ystar > amin) { + if (ystar < simplex[jh].getFirst()) { + simplex.update(ystar, pstar) + if (jh != simplex.jh()) { + continue + } + } + val pstst: RealVector = + MnUtils.add(MnUtils.mul(simplex[jh].getSecond(), beta), MnUtils.mul(pbar, 1.0 - beta)) + val ystst: Double = mfcn.value(pstst) + if (ystst > simplex[jh].getFirst()) { + break + } + simplex.update(ystst, pstst) + continue + } + var pstst: RealVector = MnUtils.add(MnUtils.mul(pstar, gamma), MnUtils.mul(pbar, 1.0 - gamma)) + var ystst: Double = mfcn.value(pstst) + val y1: Double = (ystar - simplex[jh].getFirst()) * rho2 + val y2: Double = (ystst - simplex[jh].getFirst()) * rho1 + var rho = 0.5 * (rho2 * y1 - rho1 * y2) / (y1 - y2) + if (rho < rhomin) { + if (ystst < simplex[jl].getFirst()) { + simplex.update(ystst, pstst) + } else { + simplex.update(ystar, pstar) + } + continue + } + if (rho > rhomax) { + rho = rhomax + } + val prho: RealVector = + MnUtils.add(MnUtils.mul(pbar, rho), MnUtils.mul(simplex[jh].getSecond(), 1.0 - rho)) + val yrho: Double = mfcn.value(prho) + if (yrho < simplex[jl].getFirst() && yrho < ystst) { + simplex.update(yrho, prho) + continue + } + if (ystst < simplex[jl].getFirst()) { + simplex.update(ystst, pstst) + continue + } + if (yrho > simplex[jl].getFirst()) { + if (ystst < simplex[jl].getFirst()) { + simplex.update(ystst, pstst) + } else { + simplex.update(ystar, pstar) + } + continue + } + if (ystar > simplex[jh].getFirst()) { + pstst = MnUtils.add(MnUtils.mul(simplex[jh].getSecond(), beta), MnUtils.mul(pbar, 1 - beta)) + ystst = mfcn.value(pstst) + if (ystst > simplex[jh].getFirst()) { + break + } + simplex.update(ystst, pstst) + } + } while (simplex.edm() > minedm && mfcn.numOfCalls() < maxfcn) + amin = simplex[jl].getFirst() + jl = simplex.jl() + jh = simplex.jh() + var pbar: RealVector = ArrayRealVector(n) + for (i in 0 until n + 1) { + if (i == jh) { + continue + } + pbar = MnUtils.add(pbar, MnUtils.mul(simplex[i].getSecond(), wg)) + } + var ybar: Double = mfcn.value(pbar) + if (ybar < amin) { + simplex.update(ybar, pbar) + } else { + pbar = simplex[jl].getSecond() + ybar = simplex[jl].getFirst() + } + var dirin: RealVector = simplex.dirin() + // scale to sigmas on parameters werr^2 = dirin^2 * (up/edm) + dirin = MnUtils.mul(dirin, sqrt(mfcn.errorDef() / simplex.edm())) + val st = MinimumState(MinimumParameters(pbar, dirin, ybar), simplex.edm(), mfcn.numOfCalls()) + val states: MutableList = java.util.ArrayList(1) + states.add(st) + if (mfcn.numOfCalls() > maxfcn) { + MINUITPlugin.logStatic("Simplex did not converge, #fcn calls exhausted.") + return FunctionMinimum(seed, states, mfcn.errorDef(), MnReachedCallLimit()) + } + if (simplex.edm() > minedm) { + MINUITPlugin.logStatic("Simplex did not converge, edm > minedm.") + return FunctionMinimum(seed, states, mfcn.errorDef(), MnAboveMaxEdm()) + } + return FunctionMinimum(seed, states, mfcn.errorDef()) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexMinimizer.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexMinimizer.kt new file mode 100644 index 000000000..f4bbcc320 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexMinimizer.kt @@ -0,0 +1,43 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal class SimplexMinimizer : ModularFunctionMinimizer() { + private val theBuilder: SimplexBuilder + private val theSeedGenerator: SimplexSeedGenerator = SimplexSeedGenerator() + + /** {@inheritDoc} */ + override fun builder(): MinimumBuilder { + return theBuilder + } + + /** {@inheritDoc} */ + override fun seedGenerator(): MinimumSeedGenerator { + return theSeedGenerator + } + + /** + * + * Constructor for SimplexMinimizer. + */ + init { + theBuilder = SimplexBuilder() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexParameters.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexParameters.kt new file mode 100644 index 000000000..fef6e2010 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexParameters.kt @@ -0,0 +1,85 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector + +/** + * + * @version $Id$ + */ +internal class SimplexParameters(simpl: MutableList>, jh: Int, jl: Int) { + private var theJHigh: Int + private var theJLow: Int + private val theSimplexParameters: MutableList> + fun dirin(): ArrayRealVector { + val dirin = ArrayRealVector(theSimplexParameters.size - 1) + for (i in 0 until theSimplexParameters.size - 1) { + var pbig: Double = theSimplexParameters[0].getSecond().getEntry(i) + var plit = pbig + for (theSimplexParameter in theSimplexParameters) { + if (theSimplexParameter.getSecond().getEntry(i) < plit) { + plit = theSimplexParameter.getSecond().getEntry(i) + } + if (theSimplexParameter.getSecond().getEntry(i) > pbig) { + pbig = theSimplexParameter.getSecond().getEntry(i) + } + } + dirin.setEntry(i, pbig - plit) + } + return dirin + } + + fun edm(): Double { + return theSimplexParameters[jh()].getFirst() - theSimplexParameters[jl()].getFirst() + } + + operator fun get(i: Int): Pair { + return theSimplexParameters[i] + } + + fun jh(): Int { + return theJHigh + } + + fun jl(): Int { + return theJLow + } + + fun simplex(): List> { + return theSimplexParameters + } + + fun update(y: Double, p: RealVector?) { + theSimplexParameters.set(jh(), Pair(y, p)) + if (y < theSimplexParameters[jl()].getFirst()) { + theJLow = jh() + } + var jh = 0 + for (i in 1 until theSimplexParameters.size) { + if (theSimplexParameters[i].getFirst() > theSimplexParameters[jh].getFirst()) { + jh = i + } + } + theJHigh = jh + } + + init { + theSimplexParameters = simpl + theJHigh = jh + theJLow = jl + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexSeedGenerator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexSeedGenerator.kt new file mode 100644 index 000000000..e5025ff3d --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexSeedGenerator.kt @@ -0,0 +1,52 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import org.apache.commons.math3.linear.ArrayRealVector +import ru.inr.mass.minuit.* + +/** + * + * @version $Id$ + */ +internal class SimplexSeedGenerator : MinimumSeedGenerator { + /** {@inheritDoc} */ + fun generate(fcn: MnFcn, gc: GradientCalculator?, st: MnUserParameterState, stra: MnStrategy): MinimumSeed { + val n: Int = st.variableParameters() + val prec: MnMachinePrecision = st.precision() + + // initial starting values + val x: RealVector = ArrayRealVector(n) + for (i in 0 until n) { + x.setEntry(i, st.intParameters()[i]) + } + val fcnmin: Double = fcn.value(x) + val pa = MinimumParameters(x, fcnmin) + val igc = InitialGradientCalculator(fcn, st.getTransformation(), stra) + val dgrad: FunctionGradient = igc.gradient(pa) + val mat = MnAlgebraicSymMatrix(n) + val dcovar = 1.0 + for (i in 0 until n) { + mat[i, i] = if (abs(dgrad.getGradientDerivative() + .getEntry(i)) > prec.eps2() + ) 1.0 / dgrad.getGradientDerivative().getEntry(i) else 1.0 + } + val err = MinimumError(mat, dcovar) + val edm: Double = VariableMetricEDMEstimator().estimate(dgrad, err) + val state = MinimumState(pa, err, dgrad, edm, fcn.numOfCalls()) + return MinimumSeed(state, st.getTransformation()) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SinParameterTransformation.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SinParameterTransformation.kt new file mode 100644 index 000000000..821addef7 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SinParameterTransformation.kt @@ -0,0 +1,48 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal class SinParameterTransformation { + fun dInt2Ext(value: Double, upper: Double, lower: Double): Double { + return 0.5 * abs((upper - lower) * cos(value)) + } + + fun ext2int(value: Double, upper: Double, lower: Double, prec: MnMachinePrecision): Double { + val piby2: Double = 2.0 * atan(1.0) + val distnn: Double = 8.0 * sqrt(prec.eps2()) + val vlimhi = piby2 - distnn + val vlimlo = -piby2 + distnn + val yy = 2.0 * (value - lower) / (upper - lower) - 1.0 + val yy2 = yy * yy + return if (yy2 > 1.0 - prec.eps2()) { + if (yy < 0.0) { + vlimlo + } else { + vlimhi + } + } else { + asin(yy) + } + } + + fun int2ext(value: Double, upper: Double, lower: Double): Double { + return lower + 0.5 * (upper - lower) * (sin(value) + 1.0) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtLowParameterTransformation.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtLowParameterTransformation.kt new file mode 100644 index 000000000..444b63847 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtLowParameterTransformation.kt @@ -0,0 +1,43 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal class SqrtLowParameterTransformation { + // derivative of transformation from internal to external + fun dInt2Ext(value: Double, lower: Double): Double { + return value / sqrt(value * value + 1.0) + } + + // transformation from external to internal + fun ext2int(value: Double, lower: Double, prec: MnMachinePrecision): Double { + val yy = value - lower + 1.0 + val yy2 = yy * yy + return if (yy2 < 1.0 + prec.eps2()) { + 8 * sqrt(prec.eps2()) + } else { + sqrt(yy2 - 1) + } + } + + // transformation from internal to external + fun int2ext(value: Double, lower: Double): Double { + return lower - 1.0 + sqrt(value * value + 1.0) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtUpParameterTransformation.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtUpParameterTransformation.kt new file mode 100644 index 000000000..5774848bd --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtUpParameterTransformation.kt @@ -0,0 +1,43 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal class SqrtUpParameterTransformation { + // derivative of transformation from internal to external + fun dInt2Ext(value: Double, upper: Double): Double { + return -value / sqrt(value * value + 1.0) + } + + // transformation from external to internal + fun ext2int(value: Double, upper: Double, prec: MnMachinePrecision): Double { + val yy = upper - value + 1.0 + val yy2 = yy * yy + return if (yy2 < 1.0 + prec.eps2()) { + 8 * sqrt(prec.eps2()) + } else { + sqrt(yy2 - 1) + } + } + + // transformation from internal to external + fun int2ext(value: Double, upper: Double): Double { + return upper + 1.0 - sqrt(value * value + 1.0) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricBuilder.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricBuilder.kt new file mode 100644 index 000000000..8362c5e7e --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricBuilder.kt @@ -0,0 +1,137 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +import space.kscience.kmath.optimization.minuit.MINUITPlugin +import ru.inr.mass.minuit.* + +/** + * + * @version $Id$ + */ +internal class VariableMetricBuilder : MinimumBuilder { + private val theErrorUpdator: DavidonErrorUpdator + private val theEstimator: VariableMetricEDMEstimator = VariableMetricEDMEstimator() + fun errorUpdator(): DavidonErrorUpdator { + return theErrorUpdator + } + + fun estimator(): VariableMetricEDMEstimator { + return theEstimator + } + + /** {@inheritDoc} */ + fun minimum( + fcn: MnFcn, + gc: GradientCalculator, + seed: MinimumSeed, + strategy: MnStrategy, + maxfcn: Int, + edmval: Double + ): FunctionMinimum { + val min: FunctionMinimum = minimum(fcn, gc, seed, maxfcn, edmval) + if (strategy.strategy() === 2 || strategy.strategy() === 1 && min.error().dcovar() > 0.05) { + val st: MinimumState = MnHesse(strategy).calculate(fcn, min.state(), min.seed().trafo(), 0) + min.add(st) + } + if (!min.isValid()) { + MINUITPlugin.logStatic("FunctionMinimum is invalid.") + } + return min + } + + fun minimum(fcn: MnFcn, gc: GradientCalculator, seed: MinimumSeed, maxfcn: Int, edmval: Double): FunctionMinimum { + var edmval = edmval + edmval *= 0.0001 + if (seed.parameters().vec().getDimension() === 0) { + return FunctionMinimum(seed, fcn.errorDef()) + } + val prec: MnMachinePrecision = seed.precision() + val result: MutableList = java.util.ArrayList(8) + var edm: Double = seed.state().edm() + if (edm < 0.0) { + MINUITPlugin.logStatic("VariableMetricBuilder: initial matrix not pos.def.") + if (seed.error().isPosDef()) { + throw RuntimeException("Something is wrong!") + } + return FunctionMinimum(seed, fcn.errorDef()) + } + result.add(seed.state()) + + // iterate until edm is small enough or max # of iterations reached + edm *= 1.0 + 3.0 * seed.error().dcovar() + var step: RealVector // = new ArrayRealVector(seed.gradient().getGradient().getDimension()); + do { + var s0: MinimumState = result[result.size - 1] + step = MnUtils.mul(MnUtils.mul(s0.error().invHessian(), s0.gradient().getGradient()), -1) + var gdel: Double = MnUtils.innerProduct(step, s0.gradient().getGradient()) + if (gdel > 0.0) { + MINUITPlugin.logStatic("VariableMetricBuilder: matrix not pos.def.") + MINUITPlugin.logStatic("gdel > 0: $gdel") + s0 = MnPosDef.test(s0, prec) + step = MnUtils.mul(MnUtils.mul(s0.error().invHessian(), s0.gradient().getGradient()), -1) + gdel = MnUtils.innerProduct(step, s0.gradient().getGradient()) + MINUITPlugin.logStatic("gdel: $gdel") + if (gdel > 0.0) { + result.add(s0) + return FunctionMinimum(seed, result, fcn.errorDef()) + } + } + val pp: MnParabolaPoint = MnLineSearch.search(fcn, s0.parameters(), step, gdel, prec) + if (abs(pp.y() - s0.fval()) < prec.eps()) { + MINUITPlugin.logStatic("VariableMetricBuilder: no improvement") + break //no improvement + } + val p = MinimumParameters(MnUtils.add(s0.vec(), MnUtils.mul(step, pp.x())), pp.y()) + val g: FunctionGradient = gc.gradient(p, s0.gradient()) + edm = estimator().estimate(g, s0.error()) + if (edm < 0.0) { + MINUITPlugin.logStatic("VariableMetricBuilder: matrix not pos.def.") + MINUITPlugin.logStatic("edm < 0") + s0 = MnPosDef.test(s0, prec) + edm = estimator().estimate(g, s0.error()) + if (edm < 0.0) { + result.add(s0) + return FunctionMinimum(seed, result, fcn.errorDef()) + } + } + val e: MinimumError = errorUpdator().update(s0, p, g) + result.add(MinimumState(p, e, g, edm, fcn.numOfCalls())) + // result[0] = MinimumState(p, e, g, edm, fcn.numOfCalls()); + edm *= 1.0 + 3.0 * e.dcovar() + } while (edm > edmval && fcn.numOfCalls() < maxfcn) + if (fcn.numOfCalls() >= maxfcn) { + MINUITPlugin.logStatic("VariableMetricBuilder: call limit exceeded.") + return FunctionMinimum(seed, result, fcn.errorDef(), MnReachedCallLimit()) + } + return if (edm > edmval) { + if (edm < abs(prec.eps2() * result[result.size - 1].fval())) { + MINUITPlugin.logStatic("VariableMetricBuilder: machine accuracy limits further improvement.") + FunctionMinimum(seed, result, fcn.errorDef()) + } else if (edm < 10.0 * edmval) { + FunctionMinimum(seed, result, fcn.errorDef()) + } else { + MINUITPlugin.logStatic("VariableMetricBuilder: finishes without convergence.") + MINUITPlugin.logStatic("VariableMetricBuilder: edm= $edm requested: $edmval") + FunctionMinimum(seed, result, fcn.errorDef(), MnAboveMaxEdm()) + } + } else FunctionMinimum(seed, result, fcn.errorDef()) + } + + init { + theErrorUpdator = DavidonErrorUpdator() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricEDMEstimator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricEDMEstimator.kt new file mode 100644 index 000000000..8fca4e6ee --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricEDMEstimator.kt @@ -0,0 +1,31 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @author tonyj + * @version $Id$ + */ +internal class VariableMetricEDMEstimator { + fun estimate(g: FunctionGradient, e: MinimumError): Double { + if (e.invHessian().size() === 1) { + return 0.5 * g.getGradient().getEntry(0) * g.getGradient().getEntry(0) * e.invHessian()[0, 0] + } + val rho: Double = MnUtils.similarity(g.getGradient(), e.invHessian()) + return 0.5 * rho + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricMinimizer.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricMinimizer.kt new file mode 100644 index 000000000..2a13a5fff --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricMinimizer.kt @@ -0,0 +1,43 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + +/** + * + * @version $Id$ + */ +internal class VariableMetricMinimizer : ModularFunctionMinimizer() { + private val theMinBuilder: VariableMetricBuilder + private val theMinSeedGen: MnSeedGenerator = MnSeedGenerator() + + /** {@inheritDoc} */ + override fun builder(): MinimumBuilder { + return theMinBuilder + } + + /** {@inheritDoc} */ + override fun seedGenerator(): MinimumSeedGenerator { + return theMinSeedGen + } + + /** + * + * Constructor for VariableMetricMinimizer. + */ + init { + theMinBuilder = VariableMetricBuilder() + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/package-info.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/package-info.kt new file mode 100644 index 000000000..22779da86 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/package-info.kt @@ -0,0 +1,17 @@ +/* + * Copyright 2015 Alexander Nozik. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package ru.inr.mass.minuit + diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt new file mode 100644 index 000000000..02fd12dbc --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt @@ -0,0 +1,380 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.optimization.qow + +import space.kscience.kmath.data.ColumnarData +import space.kscience.kmath.data.XYErrorColumnarData +import space.kscience.kmath.expressions.DifferentiableExpression +import space.kscience.kmath.expressions.Expression +import space.kscience.kmath.expressions.SymbolIndexer +import space.kscience.kmath.expressions.derivative +import space.kscience.kmath.linear.* +import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.Field +import space.kscience.kmath.optimization.OptimizationFeature +import space.kscience.kmath.optimization.OptimizationProblemFactory +import space.kscience.kmath.optimization.OptimizationResult +import space.kscience.kmath.optimization.XYFit +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.DoubleL2Norm +import kotlin.math.pow + + +private typealias ParamSet = Map + +public fun interface FitLogger { + public fun log(block: () -> String) +} + +@OptIn(UnstableKMathAPI::class) +public class QowFit( + override val symbols: List, + private val space: LinearSpace, + private val solver: LinearSolver, +) : XYFit, SymbolIndexer { + + private var logger: FitLogger? = null + + private var startingPoint: Map = TODO() + private var covariance: Matrix? = TODO() + private val prior: DifferentiableExpression>? = TODO() + private var data: XYErrorColumnarData = TODO() + private var model: DifferentiableExpression> = TODO() + + private val features = HashSet() + + override fun update(result: OptimizationResult) { + TODO("Not yet implemented") + } + + override val algebra: Field + get() = TODO("Not yet implemented") + + override fun data( + dataSet: ColumnarData, + xSymbol: Symbol, + ySymbol: Symbol, + xErrSymbol: Symbol?, + yErrSymbol: Symbol?, + ) { + TODO("Not yet implemented") + } + + override fun model(model: (Double) -> DifferentiableExpression) { + TODO("Not yet implemented") + } + + private var x: Symbol = Symbol.x + + /** + * The signed distance from the model to the [i]-th point of data. + */ + private fun distance(i: Int, parameters: Map): Double = + model(parameters + (x to data.x[i])) - data.y[i] + + + /** + * The derivative of [distance] + * TODO use expressions instead + */ + private fun distanceDerivative(symbol: Symbol, i: Int, parameters: Map): Double = + model.derivative(symbol)(parameters + (x to data.x[i])) + + /** + * The dispersion of [i]-th data point + */ + private fun getDispersion(i: Int, parameters: Map): Double = data.yErr[i].pow(2) + + private fun getCovariance(weight: QoWeight): Matrix = solver.inverse(getEqDerivValues(weight)) + + /** + * Теоретическая ковариация весовых функций. + * + * D(\phi)=E(\phi_k(\theta_0) \phi_l(\theta_0))= disDeriv_k * disDeriv_l /sigma^2 + */ + private fun covarF(weight: QoWeight): Matrix = space.buildSymmetricMatrix(symbols.size) { k, l -> + (0 until data.size).sumOf { i -> weight.derivs[k, i] * weight.derivs[l, i] / weight.dispersion[i] } + } + + /** + * Экспериментальная ковариация весов. Формула (22) из + * http://arxiv.org/abs/physics/0604127 + * + * @param source + * @param set + * @param fitPars + * @param weight + * @return + */ + private fun covarFExp(weight: QoWeight, theta: Map): Matrix = space.run { + /* + * Важно! Если не делать предварителього вычисления этих производных, то + * количество вызывов функции будет dim^2 вместо dim Первый индекс - + * номер точки, второй - номер переменной, по которой берется производная + */ + val eqvalues = buildMatrix(data.size, symbols.size) { i, l -> + distance(i, theta) * weight.derivs[l, i] / weight.dispersion[i] + } + + buildMatrix(symbols.size, symbols.size) { k, l -> + (0 until data.size).sumOf { i -> eqvalues[i, l] * eqvalues[i, k] } + } + } + + /** + * производные уравнений для метода Ньютона + * + * @param source + * @param set + * @param fitPars + * @param weight + * @return + */ + private fun getEqDerivValues( + weight: QoWeight, theta: Map = weight.theta, + ): Matrix = space.run { + val fitDim = symbols.size + //Возвращает производную k-того Eq по l-тому параметру + val res = Array(fitDim) { DoubleArray(fitDim) } + val sderiv = buildMatrix(data.size, symbols.size) { i, l -> + distanceDerivative(symbols[l], i, theta) + } + + buildMatrix(symbols.size, symbols.size) { k, l -> + val base = (0 until data.size).sumOf { i -> + require(weight.dispersion[i] > 0) + sderiv[i, l] * weight.derivs[k, i] / weight.dispersion[i] + } + prior?.let { prior -> + //Check if this one is correct + val pi = prior(theta) + val deriv1 = prior.derivative(symbols[k])(theta) + val deriv2 = prior.derivative(symbols[l])(theta) + base + deriv1 * deriv2 / pi / pi + } ?: base + } + } + + + /** + * Значения уравнений метода квазиоптимальных весов + * + * @param source + * @param set + * @param fitPars + * @param weight + * @return + */ + private fun getEqValues(weight: QoWeight, theta: Map = weight.theta): Point { + val distances = DoubleBuffer(data.size) { i -> distance(i, theta) } + + return DoubleBuffer(symbols.size) { k -> + val base = (0 until data.size).sumOf { i -> distances[i] * weight.derivs[k, i] / weight.dispersion[i] } + //Поправка на априорную вероятность + prior?.let { prior -> + base - prior.derivative(symbols[k])(theta) / prior(theta) + } ?: base + } + } + + + /** + * The state of QOW fitter + * Created by Alexander Nozik on 17-Oct-16. + */ + private inner class QoWeight( + val theta: Map, + ) { + + init { + require(data.size > 0) { "The state does not contain data" } + } + + /** + * Derivatives of the spectrum over parameters. First index in the point number, second one - index of parameter + */ + val derivs: Matrix by lazy { + space.buildMatrix(data.size, symbols.size) { i, k -> + distanceDerivative(symbols[k], i, theta) + } + } + + /** + * Array of dispersions in each point + */ + val dispersion: Point by lazy { + DoubleBuffer(data.size) { i -> getDispersion(i, theta) } + } + + } + + private fun newtonianStep( + weight: QoWeight, + par: Map, + eqvalues: Point, + ): Map = space.run { + val start = par.toPoint() + val invJacob = solver.inverse(getEqDerivValues(weight, par)) + + val step = invJacob.dot(eqvalues) + return par + (start - step).toMap() + } + + private fun newtonianRun( + weight: QoWeight, + maxSteps: Int = 100, + tolerance: Double = 0.0, + fast: Boolean = false, + ): ParamSet { + + var dis: Double//норма невязки + // Для удобства работаем всегда с полным набором параметров + var par = startingPoint + + logger?.log { "Starting newtonian iteration from: \n\t$par" } + + var eqvalues = getEqValues(weight, par)//значения функций + + dis = DoubleL2Norm.norm(eqvalues)// невязка + logger?.log { "Starting discrepancy is $dis" } + var i = 0 + var flag = false + while (!flag) { + i++ + logger?.log { "Starting step number $i" } + + val currentSolution = if (fast) { + //Берет значения матрицы в той точке, где считается вес + newtonianStep(weight, weight.theta, eqvalues) + } else { + //Берет значения матрицы в точке par + newtonianStep(weight, par, eqvalues) + } + // здесь должен стоять учет границ параметров + logger?.log { "Parameter values after step are: \n\t$currentSolution" } + + eqvalues = getEqValues(weight, currentSolution) + val currentDis = DoubleL2Norm.norm(eqvalues)// невязка после шага + + logger?.log { "The discrepancy after step is: $currentDis." } + + if (currentDis >= dis && i > 1) { + //дополнительно проверяем, чтобы был сделан хотя бы один шаг + flag = true + logger?.log { "The discrepancy does not decrease. Stopping iteration." } + } else { + par = currentSolution + dis = currentDis + } + if (i >= maxSteps) { + flag = true + logger?.log { "Maximum number of iterations reached. Stopping iteration." } + } + if (dis <= tolerance) { + flag = true + logger?.log { "Tolerance threshold is reached. Stopping iteration." } + } + } + + return par + } + + +// +// override fun run(state: FitState, parentLog: History?, meta: Meta): FitResult { +// val log = Chronicle("QOW", parentLog) +// val action = meta.getString(FIT_STAGE_TYPE, TASK_RUN) +// log.report("QOW fit engine started task '{}'", action) +// return when (action) { +// TASK_SINGLE -> makeRun(state, log, meta) +// TASK_COVARIANCE -> generateErrors(state, log, meta) +// TASK_RUN -> { +// var res = makeRun(state, log, meta) +// res = makeRun(res.optState().get(), log, meta) +// generateErrors(res.optState().get(), log, meta) +// } +// else -> throw IllegalArgumentException("Unknown task") +// } +// } + +// private fun makeRun(state: FitState, log: History, meta: Meta): FitResult { +// /*Инициализация объектов, задание исходных значений*/ +// log.report("Starting fit using quasioptimal weights method.") +// +// val fitPars = getFitPars(state, meta) +// +// val curWeight = QoWeight(state, fitPars, state.parameters) +// +// // вычисляем вес в allPar. Потом можно будет попробовать ручное задание веса +// log.report("The starting weight is: \n\t{}", +// MathUtils.toString(curWeight.theta)) +// +// //Стартовая точка такая же как и параметр веса +// /*Фитирование*/ +// val res = newtonianRun(state, curWeight, log, meta) +// +// /*Генерация результата*/ +// +// return FitResult.build(state.edit().setPars(res).build(), *fitPars) +// } + + /** + * generateErrors. + */ + private fun generateErrors(): Matrix { + logger?.log { """ + Starting errors estimation using quasioptimal weights method. The starting weight is: + ${curWeight.theta} + """.trimIndent()} + val curWeight = QoWeight(startingPoint) + + val covar = getCovariance(curWeight) + + val decomposition = EigenDecomposition(covar.matrix) + var valid = true + for (lambda in decomposition.realEigenvalues) { + if (lambda <= 0) { + log.report("The covariance matrix is not positive defined. Error estimation is not valid") + valid = false + } + } + } + + + override suspend fun optimize(): OptimizationResult { + val curWeight = QoWeight(startingPoint) + logger?.log { + """ + Starting fit using quasioptimal weights method. The starting weight is: + ${curWeight.theta} + """.trimIndent() + } + val res = newtonianRun(curWeight) + } + + + companion object : OptimizationProblemFactory { + override fun build(symbols: List): QowFit { + TODO("Not yet implemented") + } + + + /** + * Constant `QOW_ENGINE_NAME="QOW"` + */ + const val QOW_ENGINE_NAME = "QOW" + + /** + * Constant `QOW_METHOD_FAST="fast"` + */ + const val QOW_METHOD_FAST = "fast" + + + } +} + From 7b6361e59d48d2ee12edbda6f99af91b1e38f0a5 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 26 Apr 2021 15:02:19 +0300 Subject: [PATCH 002/132] [WIP] optimization refactor in process --- .../commons/optimization/CMOptimization.kt | 112 +++++---------- .../kmath/commons/optimization/cmFit.kt | 8 +- .../space/kscience/kmath/misc/Featured.kt | 4 +- .../space/kscience/kmath/misc/logging.kt | 14 ++ .../optimization/FunctionOptimization.kt | 130 +++++++----------- .../kmath/optimization/OptimizationProblem.kt | 6 + .../kscience/kmath/optimization/XYFit.kt | 34 ++++- .../kscience/kmath/optimization/qow/QowFit.kt | 4 - 8 files changed, 146 insertions(+), 166 deletions(-) create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/logging.kt diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt index db9ba6f21..6bde14627 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt @@ -11,10 +11,8 @@ import org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer import org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction import org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunctionGradient import org.apache.commons.math3.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer -import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.AbstractSimplex -import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.NelderMeadSimplex -import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.SimplexOptimizer -import space.kscience.kmath.expressions.* +import space.kscience.kmath.expressions.derivative +import space.kscience.kmath.expressions.withSymbols import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.optimization.* @@ -24,107 +22,73 @@ public operator fun PointValuePair.component1(): DoubleArray = point public operator fun PointValuePair.component2(): Double = value public class CMOptimizerFactory(public val optimizerBuilder: () -> MultivariateOptimizer) : OptimizationFeature -//public class CMOptimizerData(public val ) +public class CMOptimizerData(public val data: List) : OptimizationFeature { + public constructor(vararg data: OptimizationData) : this(data.toList()) +} @OptIn(UnstableKMathAPI::class) public class CMOptimization : Optimizer> { override suspend fun process( - problem: FunctionOptimization - ): FunctionOptimization = withSymbols(problem.parameters){ - val cmOptimizer: MultivariateOptimizer = - problem.getFeature()?.optimizerBuilder?.invoke() ?: SimplexOptimizer() - + problem: FunctionOptimization, + ): FunctionOptimization = withSymbols(problem.parameters) { val convergenceChecker: ConvergenceChecker = SimpleValueChecker( DEFAULT_RELATIVE_TOLERANCE, DEFAULT_ABSOLUTE_TOLERANCE, DEFAULT_MAX_ITER ) + val cmOptimizer: MultivariateOptimizer = problem.getFeature()?.optimizerBuilder?.invoke() + ?: NonLinearConjugateGradientOptimizer( + NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES, + convergenceChecker + ) + val optimizationData: HashMap, OptimizationData> = HashMap() fun addOptimizationData(data: OptimizationData) { optimizationData[data::class] = data } + addOptimizationData(MaxEval.unlimited()) addOptimizationData(InitialGuess(problem.initialGuess.toDoubleArray())) fun exportOptimizationData(): List = optimizationData.values.toList() - - /** - * Register no-deriv function instead of differentiable function - */ - /** - * Register no-deriv function instead of differentiable function - */ - fun noDerivFunction(expression: Expression): Unit { - val objectiveFunction = ObjectiveFunction { - val args = problem.initialGuess + it.toMap() - expression(args) - } - addOptimizationData(objectiveFunction) + val objectiveFunction = ObjectiveFunction { + val args = problem.initialGuess + it.toMap() + problem.expression(args) } + addOptimizationData(objectiveFunction) - public override fun function(expression: DifferentiableExpression>) { - noDerivFunction(expression) - val gradientFunction = ObjectiveFunctionGradient { - val args = startingPoint + it.toMap() - DoubleArray(symbols.size) { index -> - expression.derivative(symbols[index])(args) - } - } - addOptimizationData(gradientFunction) - if (optimizerBuilder == null) { - optimizerBuilder = { - NonLinearConjugateGradientOptimizer( - NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES, - convergenceChecker - ) + val gradientFunction = ObjectiveFunctionGradient { + val args = problem.initialGuess + it.toMap() + DoubleArray(symbols.size) { index -> + problem.expression.derivative(symbols[index])(args) + } + } + addOptimizationData(gradientFunction) + + val logger = problem.getFeature() + + for (feature in problem.features) { + when (feature) { + is CMOptimizerData -> feature.data.forEach { addOptimizationData(it) } + is FunctionOptimizationTarget -> when(feature){ + FunctionOptimizationTarget.MAXIMIZE -> addOptimizationData(GoalType.MAXIMIZE) + FunctionOptimizationTarget.MINIMIZE -> addOptimizationData(GoalType.MINIMIZE) } + else -> logger?.log { "The feature $feature is unused in optimization" } } } - public fun simplex(simplex: AbstractSimplex) { - addOptimizationData(simplex) - //Set optimization builder to simplex if it is not present - if (optimizerBuilder == null) { - optimizerBuilder = { SimplexOptimizer(convergenceChecker) } - } - } - - public fun simplexSteps(steps: Map) { - simplex(NelderMeadSimplex(steps.toDoubleArray())) - } - - public fun goal(goalType: GoalType) { - addOptimizationData(goalType) - } - - public fun optimizer(block: () -> MultivariateOptimizer) { - optimizerBuilder = block - } - - override fun update(result: OptimizationResult) { - initialGuess(result.point) - } - - override suspend fun optimize(): OptimizationResult { - val optimizer = optimizerBuilder?.invoke() ?: error("Optimizer not defined") - val (point, value) = optimizer.optimize(*optimizationData.values.toTypedArray()) - return OptimizationResult(point.toMap(), value) - } - return@withSymbols TODO() + val (point, value) = cmOptimizer.optimize(*optimizationData.values.toTypedArray()) + return problem.withFeatures(FunctionOptimizationResult(point.toMap(), value)) } - public companion object : OptimizationProblemFactory { + public companion object { public const val DEFAULT_RELATIVE_TOLERANCE: Double = 1e-4 public const val DEFAULT_ABSOLUTE_TOLERANCE: Double = 1e-4 public const val DEFAULT_MAX_ITER: Int = 1000 - - override fun build(symbols: List): CMOptimization = CMOptimization(symbols) } } - -public fun CMOptimization.initialGuess(vararg pairs: Pair): Unit = initialGuess(pairs.toMap()) -public fun CMOptimization.simplexSteps(vararg pairs: Pair): Unit = simplexSteps(pairs.toMap()) diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt index 12d924063..9c0089b3d 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt @@ -17,22 +17,22 @@ import space.kscience.kmath.structures.asBuffer /** * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation */ -public fun FunctionOptimization.Companion.chiSquared( +public fun FunctionOptimization.Companion.chiSquaredExpression( x: Buffer, y: Buffer, yErr: Buffer, model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure, -): DifferentiableExpression> = chiSquared(DerivativeStructureField, x, y, yErr, model) +): DifferentiableExpression> = chiSquaredExpression(DerivativeStructureField, x, y, yErr, model) /** * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation */ -public fun FunctionOptimization.Companion.chiSquared( +public fun FunctionOptimization.Companion.chiSquaredExpression( x: Iterable, y: Iterable, yErr: Iterable, model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure, -): DifferentiableExpression> = chiSquared( +): DifferentiableExpression> = chiSquaredExpression( DerivativeStructureField, x.toList().asBuffer(), y.toList().asBuffer(), diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt index 157ff980b..a94efc788 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt @@ -17,7 +17,7 @@ public interface Featured { /** * A container for a set of features */ -public class FeatureSet private constructor(public val features: Map, Any>) : Featured { +public class FeatureSet private constructor(public val features: Map, F>) : Featured { @Suppress("UNCHECKED_CAST") override fun getFeature(type: KClass): T? = features[type] as? T @@ -31,6 +31,8 @@ public class FeatureSet private constructor(public val features: Map = FeatureSet(features + otherFeatures.associateBy { it::class }) + public operator fun iterator(): Iterator = features.values.iterator() + public companion object { public fun of(vararg features: F): FeatureSet = FeatureSet(features.associateBy { it::class }) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/logging.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/logging.kt new file mode 100644 index 000000000..d13840841 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/logging.kt @@ -0,0 +1,14 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.misc + +public interface Loggable { + public fun log(tag: String = INFO, block: () -> String) + + public companion object { + public const val INFO: String = "INFO" + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index 12ccea1d8..db613e236 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -15,91 +15,57 @@ import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.indices +public class FunctionOptimizationResult(point: Map, public val value: T) : OptimizationResult(point) -public class FunctionOptimization( +public enum class FunctionOptimizationTarget : OptimizationFeature { + MAXIMIZE, + MINIMIZE +} + +public class FunctionOptimization( override val features: FeatureSet, public val expression: DifferentiableExpression>, public val initialGuess: Map, public val parameters: Collection, - public val maximize: Boolean, -) : OptimizationProblem +) : OptimizationProblem{ + public companion object{ + /** + * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation + */ + public fun chiSquaredExpression( + autoDiff: AutoDiffProcessor>, + x: Buffer, + y: Buffer, + yErr: Buffer, + model: A.(I) -> I, + ): DifferentiableExpression> where A : ExtendedField, A : ExpressionAlgebra { + require(x.size == y.size) { "X and y buffers should be of the same size" } + require(y.size == yErr.size) { "Y and yErr buffer should of the same size" } + + return autoDiff.process { + var sum = zero + + x.indices.forEach { + val xValue = const(x[it]) + val yValue = const(y[it]) + val yErrValue = const(yErr[it]) + val modelValue = model(xValue) + sum += ((yValue - modelValue) / yErrValue).pow(2) + } + + sum + } + } + } +} + + +public fun FunctionOptimization.withFeatures( + vararg newFeature: OptimizationFeature, +): FunctionOptimization = FunctionOptimization( + features.with(*newFeature), + expression, + initialGuess, + parameters +) -// -///** -// * A likelihood function optimization problem with provided derivatives -// */ -//public interface FunctionOptimizationBuilder { -// /** -// * The optimization direction. If true search for function maximum, if false, search for the minimum -// */ -// public var maximize: Boolean -// -// /** -// * Define the initial guess for the optimization problem -// */ -// public fun initialGuess(map: Map) -// -// /** -// * Set a differentiable expression as objective function as function and gradient provider -// */ -// public fun function(expression: DifferentiableExpression>) -// -// public companion object { -// /** -// * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation -// */ -// public fun chiSquared( -// autoDiff: AutoDiffProcessor>, -// x: Buffer, -// y: Buffer, -// yErr: Buffer, -// model: A.(I) -> I, -// ): DifferentiableExpression> where A : ExtendedField, A : ExpressionAlgebra { -// require(x.size == y.size) { "X and y buffers should be of the same size" } -// require(y.size == yErr.size) { "Y and yErr buffer should of the same size" } -// -// return autoDiff.process { -// var sum = zero -// -// x.indices.forEach { -// val xValue = const(x[it]) -// val yValue = const(y[it]) -// val yErrValue = const(yErr[it]) -// val modelValue = model(xValue) -// sum += ((yValue - modelValue) / yErrValue).pow(2) -// } -// -// sum -// } -// } -// } -//} -// -///** -// * Define a chi-squared-based objective function -// */ -//public fun FunctionOptimization.chiSquared( -// autoDiff: AutoDiffProcessor>, -// x: Buffer, -// y: Buffer, -// yErr: Buffer, -// model: A.(I) -> I, -//) where A : ExtendedField, A : ExpressionAlgebra { -// val chiSquared = FunctionOptimization.chiSquared(autoDiff, x, y, yErr, model) -// function(chiSquared) -// maximize = false -//} -// -///** -// * Optimize differentiable expression using specific [OptimizationProblemFactory] -// */ -//public suspend fun > DifferentiableExpression>.optimizeWith( -// factory: OptimizationProblemFactory, -// vararg symbols: Symbol, -// configuration: F.() -> Unit, -//): OptimizationResult { -// require(symbols.isNotEmpty()) { "Must provide a list of symbols for optimization" } -// val problem = factory(symbols.toList(), configuration) -// problem.function(this) -// return problem.optimize() -//} diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt index 9a5420be6..0d2e3cb83 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt @@ -7,6 +7,8 @@ package space.kscience.kmath.optimization import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.Featured +import space.kscience.kmath.misc.Loggable +import space.kscience.kmath.misc.Symbol import kotlin.reflect.KClass public interface OptimizationFeature @@ -18,6 +20,10 @@ public interface OptimizationProblem : Featured { public inline fun OptimizationProblem.getFeature(): T? = getFeature(T::class) +public open class OptimizationResult(public val point: Map) : OptimizationFeature + +public class OptimizationLog(private val loggable: Loggable) : Loggable by loggable, OptimizationFeature + //public class OptimizationResult( // public val point: Map, // public val value: T, diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt index e4998c665..f1b6ef38d 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt @@ -14,9 +14,11 @@ import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.Field +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.indices @UnstableKMathAPI -public interface XYFit : OptimizationProblem { +public interface XYFit : OptimizationProblem { public val algebra: Field @@ -42,4 +44,34 @@ public interface XYFit : OptimizationProblem { ): Unit where A : ExtendedField, A : ExpressionAlgebra = model { arg -> autoDiff.process { modelFunction(const(arg)) } } +} + +// +///** +// * Define a chi-squared-based objective function +// */ +//public fun FunctionOptimization.chiSquared( +// autoDiff: AutoDiffProcessor>, +// x: Buffer, +// y: Buffer, +// yErr: Buffer, +// model: A.(I) -> I, +//) where A : ExtendedField, A : ExpressionAlgebra { +// val chiSquared = FunctionOptimization.chiSquared(autoDiff, x, y, yErr, model) +// function(chiSquared) +// maximize = false +//} + +/** + * Optimize differentiable expression using specific [OptimizationProblemFactory] + */ +public suspend fun > DifferentiableExpression>.optimizeWith( + factory: OptimizationProblemFactory, + vararg symbols: Symbol, + configuration: F.() -> Unit, +): OptimizationResult { + require(symbols.isNotEmpty()) { "Must provide a list of symbols for optimization" } + val problem = factory(symbols.toList(), configuration) + problem.function(this) + return problem.optimize() } \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt index 02fd12dbc..d611adf50 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt @@ -27,10 +27,6 @@ import kotlin.math.pow private typealias ParamSet = Map -public fun interface FitLogger { - public fun log(block: () -> String) -} - @OptIn(UnstableKMathAPI::class) public class QowFit( override val symbols: List, From bbef697b7dc553281af826ece76373af469fab0e Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sun, 9 May 2021 18:10:06 +0700 Subject: [PATCH 003/132] Document and change retention for UnstableKMathAPI --- .../kotlin/space/kscience/kmath/misc/annotations.kt | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt index 206e4e000..7f53d96ce 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt @@ -5,5 +5,13 @@ package space.kscience.kmath.misc +/** + * Marks declarations that are still experimental in the KMath APIs, which means that the design of the corresponding + * declarations has open issues which may (or may not) lead to their changes in the future. Roughly speaking, there is + * a chance that those declarations will be deprecated in the near future or the semantics of their behavior may change + * in some way that may break some code. + */ +@MustBeDocumented +@Retention(value = AnnotationRetention.BINARY) @RequiresOptIn("This API is unstable and could change in future", RequiresOptIn.Level.WARNING) public annotation class UnstableKMathAPI From e2920ed68390bf29ee0854da85d69efd53c6a5a3 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sun, 9 May 2021 16:40:10 +0700 Subject: [PATCH 004/132] Promote kmath-kotlingrad to experimental alongside minor documentation and API changes --- CHANGELOG.md | 3 +- README.md | 9 +++-- kmath-kotlingrad/README.md | 34 +++++++++++++++++++ kmath-kotlingrad/build.gradle.kts | 20 +++++++++-- kmath-kotlingrad/docs/README-TEMPLATE.md | 7 ++++ .../kotlingrad/DifferentiableMstExpression.kt | 17 +++++----- .../kscience/kmath/kotlingrad/KMathNumber.kt | 25 +++++++++----- .../kmath/kotlingrad/ScalarsAdapters.kt | 26 +++++++------- .../kmath/kotlingrad/AdaptingTests.kt | 6 +--- 9 files changed, 106 insertions(+), 41 deletions(-) create mode 100644 kmath-kotlingrad/README.md create mode 100644 kmath-kotlingrad/docs/README-TEMPLATE.md diff --git a/CHANGELOG.md b/CHANGELOG.md index 286511327..4fba361d5 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -26,6 +26,7 @@ - Move MST to core - Separated benchmarks and examples - Rewritten EJML module without ejml-simple +- Stability of kmath-ast and kmath-kotilngrad promoted to EXPERIMENTAL. ### Deprecated @@ -35,7 +36,7 @@ - `contentEquals` from Buffer. It moved to the companion. - MSTExpression - Expression algebra builders -- Comples and Quaternion no longer are elements. +- Complex and Quaternion no longer are elements. ### Fixed - Ring inherits RingOperations, not GroupOperations diff --git a/README.md b/README.md index c8da21b64..3b4387c1b 100644 --- a/README.md +++ b/README.md @@ -207,9 +207,14 @@ One can still use generic algebras though.

* ### [kmath-kotlingrad](kmath-kotlingrad) -> +> Functions, integration and interpolation > -> **Maturity**: PROTOTYPE +> **Maturity**: EXPERIMENTAL +> +> **Features:** +> - [differentiable-mst-expression](kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : MST based DifferentiableExpression. +> - [differentiable-mst-expression](kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : Conversions between Kotlin∇'s SFun and MST +
* ### [kmath-memory](kmath-memory) diff --git a/kmath-kotlingrad/README.md b/kmath-kotlingrad/README.md new file mode 100644 index 000000000..686df3271 --- /dev/null +++ b/kmath-kotlingrad/README.md @@ -0,0 +1,34 @@ +# Module kmath-kotlingrad + +[Kotlin∇](https://github.com/breandan/kotlingrad) integration module. + + - [differentiable-mst-expression](src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : MST based DifferentiableExpression. + - [differentiable-mst-expression](src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : Conversions between Kotlin∇'s SFun and MST + + +## Artifact: + +The Maven coordinates of this project are `space.kscience:kmath-kotlingrad:0.3.0-dev-8`. + +**Gradle:** +```gradle +repositories { + maven { url 'https://repo.kotlin.link' } + mavenCentral() +} + +dependencies { + implementation 'space.kscience:kmath-kotlingrad:0.3.0-dev-8' +} +``` +**Gradle Kotlin DSL:** +```kotlin +repositories { + maven("https://repo.kotlin.link") + mavenCentral() +} + +dependencies { + implementation("space.kscience:kmath-kotlingrad:0.3.0-dev-8") +} +``` diff --git a/kmath-kotlingrad/build.gradle.kts b/kmath-kotlingrad/build.gradle.kts index ed5b5bcb4..0e8e49971 100644 --- a/kmath-kotlingrad/build.gradle.kts +++ b/kmath-kotlingrad/build.gradle.kts @@ -4,11 +4,27 @@ plugins { } dependencies { - api("com.github.breandan:kaliningraph:0.1.4") + api("com.github.breandan:kaliningraph:0.1.6") api("com.github.breandan:kotlingrad:0.4.5") api(project(":kmath-ast")) } readme { - maturity = ru.mipt.npm.gradle.Maturity.PROTOTYPE + description = "Functions, integration and interpolation" + maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL + propertyByTemplate("artifact", rootProject.file("docs/templates/ARTIFACT-TEMPLATE.md")) + + feature( + "differentiable-mst-expression", + "src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt", + ) { + "MST based DifferentiableExpression." + } + + feature( + "differentiable-mst-expression", + "src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt", + ) { + "Conversions between Kotlin∇'s SFun and MST" + } } diff --git a/kmath-kotlingrad/docs/README-TEMPLATE.md b/kmath-kotlingrad/docs/README-TEMPLATE.md new file mode 100644 index 000000000..ac38c849b --- /dev/null +++ b/kmath-kotlingrad/docs/README-TEMPLATE.md @@ -0,0 +1,7 @@ +# Module kmath-kotlingrad + +[Kotlin∇](https://www.htmlsymbols.xyz/unicode/U+2207) integration module. + +${features} + +${artifact} diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt index 222145d2d..8c6745c79 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.kotlingrad import edu.umontreal.kotlingrad.api.SFun +import edu.umontreal.kotlingrad.api.SVar import space.kscience.kmath.expressions.DifferentiableExpression import space.kscience.kmath.expressions.MST import space.kscience.kmath.expressions.MstAlgebra @@ -14,20 +15,20 @@ import space.kscience.kmath.misc.Symbol import space.kscience.kmath.operations.NumericAlgebra /** - * Represents wrapper of [MstExpression] implementing [DifferentiableExpression]. + * Represents [MST] based [DifferentiableExpression]. * - * The principle of this API is converting the [mst] to an [SFun], differentiating it with Kotlin∇, then converting - * [SFun] back to [MST]. + * The principle of this API is converting the [mst] to an [SFun], differentiating it with + * [Kotlin∇](https://github.com/breandan/kotlingrad), then converting [SFun] back to [MST]. * - * @param T the type of number. - * @param A the [NumericAlgebra] of [T]. - * @property expr the underlying [MstExpression]. + * @param T The type of number. + * @param A The [NumericAlgebra] of [T]. + * @property algebra The [A] instance. + * @property mst The [MST] node. */ public class DifferentiableMstExpression>( public val algebra: A, public val mst: MST, ) : DifferentiableExpression> { - public override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) public override fun derivativeOrNull(symbols: List): DifferentiableMstExpression = @@ -35,7 +36,7 @@ public class DifferentiableMstExpression>( algebra, symbols.map(Symbol::identity) .map(MstAlgebra::bindSymbol) - .map { it.toSVar>() } + .map>>(MST.Symbolic::toSVar) .fold(mst.toSFun(), SFun>::d) .toMst(), ) diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KMathNumber.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KMathNumber.kt index 0c3768dcc..9c9d07b81 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KMathNumber.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KMathNumber.kt @@ -5,19 +5,26 @@ package space.kscience.kmath.kotlingrad -import edu.umontreal.kotlingrad.api.RealNumber import edu.umontreal.kotlingrad.api.SConst import space.kscience.kmath.operations.NumericAlgebra /** - * Implements [RealNumber] by delegating its functionality to [NumericAlgebra]. + * Implements [SConst] by delegating its functionality to [NumericAlgebra]. * - * @param T the type of number. - * @param A the [NumericAlgebra] of [T]. - * @property algebra the algebra. - * @param value the value of this number. + * @param T The type of number. + * @param A The [NumericAlgebra] over [T]. + * @property algebra The algebra. + * @property value The value of this number. */ -public class KMathNumber(public val algebra: A, value: T) : - RealNumber, T>(value) where T : Number, A : NumericAlgebra { - public override fun wrap(number: Number): SConst> = SConst(algebra.number(number)) +public class KMathNumber(public val algebra: A, public override val value: T) : + SConst>(value) where T : Number, A : NumericAlgebra { + /** + * Returns a string representation of the [value]. + */ + public override fun toString(): String = value.toString() + + /** + * Wraps [Number] to [KMathNumber]. + */ + public override fun wrap(number: Number): KMathNumber = KMathNumber(algebra, algebra.number(number)) } diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt index f65d2948d..bee2c9e3e 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt @@ -15,16 +15,16 @@ import space.kscience.kmath.operations.* /** * Maps [SVar] to [MST.Symbolic] directly. * - * @receiver the variable. - * @return a node. + * @receiver The variable. + * @returnAa node. */ public fun > SVar.toMst(): MST.Symbolic = MstAlgebra.bindSymbol(name) /** * Maps [SVar] to [MST.Numeric] directly. * - * @receiver the constant. - * @return a node. + * @receiver The constant. + * @return A node. */ public fun > SConst.toMst(): MST.Numeric = MstAlgebra.number(doubleValue) @@ -49,8 +49,8 @@ public fun > SConst.toMst(): MST.Numeric = MstAlgebra.number(doub * - [VSumAll] is requested to be evaluated; * - [Derivative] is requested to be evaluated. * - * @receiver the scalar function. - * @return a node. + * @receiver The scalar function. + * @return A node. */ public fun > SFun.toMst(): MST = MstExtendedField { when (this@toMst) { @@ -74,17 +74,16 @@ public fun > SFun.toMst(): MST = MstExtendedField { /** * Maps [MST.Numeric] to [SConst] directly. * - * @receiver the node. - * @return a new constant. + * @receiver The node. + * @return A new constant. */ public fun > MST.Numeric.toSConst(): SConst = SConst(value) /** * Maps [MST.Symbolic] to [SVar] directly. * - * @receiver the node. - * @param proto the prototype instance. - * @return a new variable. + * @receiver The node. + * @return A new variable. */ internal fun > MST.Symbolic.toSVar(): SVar = SVar(value) @@ -98,9 +97,8 @@ internal fun > MST.Symbolic.toSVar(): SVar = SVar(value) * - [MST.Unary] -> [Negative], [Sine], [Cosine], [Tangent], [Power], [Log]; * - [MST.Binary] -> [Sum], [Prod], [Power]. * - * @receiver the node. - * @param proto the prototype instance. - * @return a scalar function. + * @receiver The node. + * @return A scalar function. */ public fun > MST.toSFun(): SFun = when (this) { is MST.Numeric -> toSConst() diff --git a/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt b/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt index 3ed73451d..85c964c58 100644 --- a/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt +++ b/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt @@ -10,7 +10,7 @@ import space.kscience.kmath.asm.compileToExpression import space.kscience.kmath.ast.parseMath import space.kscience.kmath.expressions.MstAlgebra import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.misc.symbol +import space.kscience.kmath.misc.Symbol.Companion.x import space.kscience.kmath.operations.DoubleField import kotlin.test.Test import kotlin.test.assertEquals @@ -65,8 +65,4 @@ internal class AdaptingTests { assertEquals(actualDerivative(x to 0.1), expectedDerivative(x to 0.1)) } - - private companion object { - private val x by symbol - } } From 1716b7f5d1d871610961419fd425c49730ea1a2f Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Mon, 10 May 2021 17:57:49 +0300 Subject: [PATCH 005/132] Fast power is added --- .../kscience/kmath/benchmarks/BigIntBenchmark.kt | 6 ++---- .../space/kscience/kmath/operations/Algebra.kt | 15 +++++++++++++++ .../kmath/operations/BigIntAlgebraTest.kt | 14 ++++++++++++++ 3 files changed, 31 insertions(+), 4 deletions(-) diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt index b9a10c774..33c659fca 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt @@ -15,15 +15,13 @@ import space.kscience.kmath.operations.BigIntField import space.kscience.kmath.operations.JBigIntegerField import space.kscience.kmath.operations.invoke -private fun BigInt.pow(power: Int): BigInt = modPow(BigIntField.number(power), BigInt.ONE) - @State(Scope.Benchmark) internal class BigIntBenchmark { val kmNumber = BigIntField.number(Int.MAX_VALUE) val jvmNumber = JBigIntegerField.number(Int.MAX_VALUE) - val largeKmNumber = BigIntField { number(11).pow(100_000) } + val largeKmNumber = BigIntField { number(11).pow(100_000UL) } val largeJvmNumber = JBigIntegerField { number(11).pow(100_000) } val bigExponent = 50_000 @@ -59,7 +57,7 @@ internal class BigIntBenchmark { @Benchmark fun kmPower(blackhole: Blackhole) = BigIntField { - blackhole.consume(kmNumber.pow(bigExponent)) + blackhole.consume(kmNumber.pow(bigExponent.toULong())) } @Benchmark diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index 0334e0466..49861b543 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -250,6 +250,21 @@ public interface Ring : Group, RingOperations { * neutral operation for multiplication */ public val one: T + + public fun T.pow(exponent: ULong): T = when { + this == zero && exponent > 0UL -> zero + this == one -> this + else -> powWithoutOptimization(exponent) + } + + private fun T.powWithoutOptimization(exponent: ULong): T = when (exponent) { + 0UL -> one + 1UL -> this + else -> { + val pre = powWithoutOptimization(exponent shr 1).let { it * it } + if (exponent and 1UL == 0UL) pre else pre * this + } + } } /** diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt index 5df89a385..05b73b49d 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.operations import space.kscience.kmath.testutils.RingVerifier +import kotlin.math.pow import kotlin.test.Test import kotlin.test.assertEquals @@ -21,6 +22,19 @@ internal class BigIntAlgebraTest { assertEquals(res, 1_000_000.toBigInt()) } + @Test + fun testKBigIntegerRingPow() { + BigIntField { + for (num in 0..5) + for (exponent in 0UL..10UL) + assertEquals( + num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), + num.toBigInt().pow(exponent), + "$num ^ $exponent" + ) + } + } + @Test fun testKBigIntegerRingSum_100_000_000__100_000_000() { BigIntField { From d17a3ac6eff3d6c62e99af7e030010846afd413b Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Mon, 10 May 2021 18:24:13 +0300 Subject: [PATCH 006/132] Further optimization of power is added --- .../kotlin/space/kscience/kmath/operations/Algebra.kt | 1 + .../kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index 49861b543..f7c021998 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -254,6 +254,7 @@ public interface Ring : Group, RingOperations { public fun T.pow(exponent: ULong): T = when { this == zero && exponent > 0UL -> zero this == one -> this + this == -one -> powWithoutOptimization(exponent % 2UL) else -> powWithoutOptimization(exponent) } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt index 05b73b49d..90cd29758 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt @@ -25,7 +25,7 @@ internal class BigIntAlgebraTest { @Test fun testKBigIntegerRingPow() { BigIntField { - for (num in 0..5) + for (num in -5..5) for (exponent in 0UL..10UL) assertEquals( num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), From 3ad7f32ada115b279e00edc49f5e9ba7e63a834d Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Mon, 10 May 2021 18:41:40 +0300 Subject: [PATCH 007/132] Incorrect BigInt equality fixed --- .../kotlin/space/kscience/kmath/operations/BigInt.kt | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index e74efa9ca..e81f1686d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -56,8 +56,7 @@ public class BigInt internal constructor( else -> sign * compareMagnitudes(magnitude, other.magnitude) } - public override fun equals(other: Any?): Boolean = - if (other is BigInt) compareTo(other) == 0 else error("Can't compare KBigInteger to a different type") + public override fun equals(other: Any?): Boolean = other is BigInt && compareTo(other) == 0 public override fun hashCode(): Int = magnitude.hashCode() + sign From 2da0648d73829396777066f970bf861e75410f01 Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Tue, 11 May 2021 01:40:45 +0300 Subject: [PATCH 008/132] Karatsuba added Incorrect equals fix test Incorrect overflow handling support --- .../space/kscience/kmath/operations/BigInt.kt | 46 +++++++++++++++---- .../kmath/operations/BigIntOperationsTest.kt | 25 +++++++++- 2 files changed, 61 insertions(+), 10 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index e81f1686d..c7079902b 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -86,20 +86,23 @@ public class BigInt internal constructor( public operator fun times(b: BigInt): BigInt = when { this.sign == 0.toByte() -> ZERO b.sign == 0.toByte() -> ZERO -// TODO: Karatsuba + b.magnitude.size == 1 -> this * b.magnitude[0] * b.sign.toInt() + this.magnitude.size == 1 -> b * this.magnitude[0] * this.sign.toInt() else -> BigInt((this.sign * b.sign).toByte(), multiplyMagnitudes(this.magnitude, b.magnitude)) } public operator fun times(other: UInt): BigInt = when { sign == 0.toByte() -> ZERO other == 0U -> ZERO + other == 1U -> this else -> BigInt(sign, multiplyMagnitudeByUInt(magnitude, other)) } - public operator fun times(other: Int): BigInt = if (other > 0) - this * kotlin.math.abs(other).toUInt() - else - -this * kotlin.math.abs(other).toUInt() + public operator fun times(other: Int): BigInt = when { + other > 0 -> this * kotlin.math.abs(other).toUInt() + other != Int.MIN_VALUE -> -this * kotlin.math.abs(other).toUInt() + else -> times(other.toBigInt()) + } public operator fun div(other: UInt): BigInt = BigInt(this.sign, divideMagnitudeByUInt(this.magnitude, other)) @@ -237,6 +240,7 @@ public class BigInt internal constructor( public const val BASE_SIZE: Int = 32 public val ZERO: BigInt = BigInt(0, uintArrayOf()) public val ONE: BigInt = BigInt(1, uintArrayOf(1u)) + private const val KARATSUBA_THRESHOLD = 80 private val hexMapping: HashMap = hashMapOf( 0U to "0", 1U to "1", 2U to "2", 3U to "3", @@ -317,7 +321,16 @@ public class BigInt internal constructor( return stripLeadingZeros(result) } - private fun multiplyMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude { + internal fun multiplyMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude = when { + mag1.size + mag2.size < KARATSUBA_THRESHOLD || mag1.isEmpty() || mag2.isEmpty() -> naiveMultiplyMagnitudes( + mag1, + mag2 + ) + // TODO implement Fourier + else -> karatsubaMultiplyMagnitudes(mag1, mag2) + } + + internal fun naiveMultiplyMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude { val resultLength = mag1.size + mag2.size val result = Magnitude(resultLength) @@ -336,6 +349,21 @@ public class BigInt internal constructor( return stripLeadingZeros(result) } + internal fun karatsubaMultiplyMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude { + //https://en.wikipedia.org/wiki/Karatsuba_algorithm + val halfSize = min(mag1.size, mag2.size) / 2 + val x0 = mag1.sliceArray(0 until halfSize).toBigInt(1) + val x1 = mag1.sliceArray(halfSize until mag1.size).toBigInt(1) + val y0 = mag2.sliceArray(0 until halfSize).toBigInt(1) + val y1 = mag2.sliceArray(halfSize until mag2.size).toBigInt(1) + + val z0 = x0 * y0 + val z2 = x1 * y1 + val z1 = (x0 + x1) * (y1 + y0) - z0 - z2 + + return (z2.shl(2 * halfSize * BASE_SIZE) + z1.shl(halfSize * BASE_SIZE) + z0).magnitude + } + private fun divideMagnitudeByUInt(mag: Magnitude, x: UInt): Magnitude { val resultLength = mag.size val result = Magnitude(resultLength) @@ -426,7 +454,7 @@ private val hexChToInt: MutableMap = hashMapOf( public fun String.parseBigInteger(): BigInt? { val sign: Int val sPositive: String - + //TODO substring = O(n). Can be replaced by some drop that is O(1) when { this[0] == '+' -> { sign = +1 @@ -446,8 +474,10 @@ public fun String.parseBigInteger(): BigInt? { var digitValue = BigInt.ONE val sPositiveUpper = sPositive.uppercase() - if (sPositiveUpper.startsWith("0X")) { // hex representation + if (sPositiveUpper.startsWith("0X")) { + // hex representation val sHex = sPositiveUpper.substring(2) + // TODO optimize O(n2) -> O(n) for (ch in sHex.reversed()) { if (ch == '_') continue diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntOperationsTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntOperationsTest.kt index ae34dbc04..9f35f7a69 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntOperationsTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntOperationsTest.kt @@ -5,8 +5,9 @@ package space.kscience.kmath.operations -import kotlin.test.Test -import kotlin.test.assertEquals +import kotlin.random.Random +import kotlin.random.nextUInt +import kotlin.test.* @kotlin.ExperimentalUnsignedTypes class BigIntOperationsTest { @@ -150,6 +151,18 @@ class BigIntOperationsTest { assertEquals(prod, res) } + @Test + fun testKaratsuba() { + val x = uintArrayOf(12U, 345U) + val y = uintArrayOf(6U, 789U) + assertContentEquals(BigInt.naiveMultiplyMagnitudes(x, y), BigInt.karatsubaMultiplyMagnitudes(x, y)) + repeat(1000) { + val x1 = UIntArray(Random.nextInt(100, 1000)) { Random.nextUInt() } + val y1 = UIntArray(Random.nextInt(100, 1000)) { Random.nextUInt() } + assertContentEquals(BigInt.naiveMultiplyMagnitudes(x1, y1), BigInt.karatsubaMultiplyMagnitudes(x1, y1)) + } + } + @Test fun test_shr_20() { val x = 20.toBigInt() @@ -383,4 +396,12 @@ class BigIntOperationsTest { return assertEquals(res, x % mod) } + + @Test + fun testNotEqualsOtherTypeInstanceButButNotFails() = assertFalse(0.toBigInt().equals("")) + + @Test + fun testIntAbsOverflow() { + assertEquals((-Int.MAX_VALUE.toLong().toBigInt() - 1.toBigInt()) * 2, 2.toBigInt() * Int.MIN_VALUE) + } } From 74d14970b9e50e808c8901b8d2850ecd29f79ba1 Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Wed, 12 May 2021 00:58:27 +0300 Subject: [PATCH 009/132] empty string parsing fixed --- .../space/kscience/kmath/operations/BigInt.kt | 7 +++++- .../kmath/operations/BigIntConversionsTest.kt | 22 +++++++++++++++++++ 2 files changed, 28 insertions(+), 1 deletion(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index c7079902b..00b9f9fc2 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -452,6 +452,7 @@ private val hexChToInt: MutableMap = hashMapOf( * Returns null if a valid number can not be read from a string */ public fun String.parseBigInteger(): BigInt? { + if (this.isEmpty()) return null val sign: Int val sPositive: String //TODO substring = O(n). Can be replaced by some drop that is O(1) @@ -473,15 +474,18 @@ public fun String.parseBigInteger(): BigInt? { var res = BigInt.ZERO var digitValue = BigInt.ONE val sPositiveUpper = sPositive.uppercase() + var isEmpty = true if (sPositiveUpper.startsWith("0X")) { // hex representation val sHex = sPositiveUpper.substring(2) + if (this.isEmpty()) return null // TODO optimize O(n2) -> O(n) for (ch in sHex.reversed()) { if (ch == '_') continue res += digitValue * (hexChToInt[ch] ?: return null) + isEmpty = false digitValue *= 16.toBigInt() } } else for (ch in sPositiveUpper.reversed()) { @@ -491,10 +495,11 @@ public fun String.parseBigInteger(): BigInt? { return null } res += digitValue * (ch.code - '0'.code) + isEmpty = false digitValue *= 10.toBigInt() } - return res * sign + return if (isEmpty) null else res * sign } public inline fun Buffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): Buffer = diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntConversionsTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntConversionsTest.kt index a2832e531..1feaae808 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntConversionsTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntConversionsTest.kt @@ -7,9 +7,31 @@ package space.kscience.kmath.operations import kotlin.test.Test import kotlin.test.assertEquals +import kotlin.test.assertNull @kotlin.ExperimentalUnsignedTypes class BigIntConversionsTest { + + @Test + fun emptyString() { + assertNull("".parseBigInteger()) + assertNull("+".parseBigInteger()) + assertNull("-".parseBigInteger()) + + assertNull("0x".parseBigInteger()) + assertNull("+0x".parseBigInteger()) + assertNull("-0x".parseBigInteger()) + + + assertNull("_".parseBigInteger()) + assertNull("+_".parseBigInteger()) + assertNull("-_".parseBigInteger()) + + assertNull("0x_".parseBigInteger()) + assertNull("+0x_".parseBigInteger()) + assertNull("-0x_".parseBigInteger()) + } + @Test fun testToString0x10() { val x = 0x10.toBigInt() From 9184bd55de46bcb16a5c33b8a02f604b592aff4a Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Wed, 12 May 2021 02:01:49 +0300 Subject: [PATCH 010/132] Parser optimization --- .../space/kscience/kmath/operations/BigInt.kt | 90 +++++++++++-------- 1 file changed, 55 insertions(+), 35 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 00b9f9fc2..ab05d079f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -441,11 +441,11 @@ public fun UIntArray.toBigInt(sign: Byte): BigInt { return BigInt(sign, copyOf()) } -private val hexChToInt: MutableMap = hashMapOf( - '0' to 0, '1' to 1, '2' to 2, '3' to 3, - '4' to 4, '5' to 5, '6' to 6, '7' to 7, - '8' to 8, '9' to 9, 'A' to 10, 'B' to 11, - 'C' to 12, 'D' to 13, 'E' to 14, 'F' to 15 +private val hexChToInt: MutableMap = hashMapOf( + '0' to 0U, '1' to 1U, '2' to 2U, '3' to 3U, + '4' to 4U, '5' to 5U, '6' to 6U, '7' to 7U, + '8' to 8U, '9' to 9U, 'A' to 10U, 'B' to 11U, + 'C' to 12U, 'D' to 13U, 'E' to 14U, 'F' to 15U ) /** @@ -454,52 +454,72 @@ private val hexChToInt: MutableMap = hashMapOf( public fun String.parseBigInteger(): BigInt? { if (this.isEmpty()) return null val sign: Int - val sPositive: String - //TODO substring = O(n). Can be replaced by some drop that is O(1) - when { - this[0] == '+' -> { + + val positivePartIndex = when (this[0]) { + '+' -> { sign = +1 - sPositive = this.substring(1) + 1 } - this[0] == '-' -> { + '-' -> { sign = -1 - sPositive = this.substring(1) + 1 } else -> { - sPositive = this sign = +1 + 0 } } - var res = BigInt.ZERO - var digitValue = BigInt.ONE - val sPositiveUpper = sPositive.uppercase() var isEmpty = true - if (sPositiveUpper.startsWith("0X")) { + return if (this.startsWith("0X", startIndex = positivePartIndex, ignoreCase = true)) { // hex representation - val sHex = sPositiveUpper.substring(2) - if (this.isEmpty()) return null - // TODO optimize O(n2) -> O(n) - for (ch in sHex.reversed()) { - if (ch == '_') continue - res += digitValue * (hexChToInt[ch] ?: return null) + val uInts = mutableListOf(0U) + var offset = 0 + fun addDigit(value: UInt) { + uInts[uInts.lastIndex] += value shl offset + offset += 4 + if (offset == 32) { + uInts.add(0U) + offset = 0 + } + } + + for (index in lastIndex downTo positivePartIndex + 2) { + when (val ch = this[index]) { + '_' -> continue + in '0'..'9' -> addDigit((ch - '0').toUInt()) + in 'A'..'F' -> addDigit((ch - 'A').toUInt() + 10U) + in 'a'..'f' -> addDigit((ch - 'a').toUInt() + 10U) + else -> return null + } isEmpty = false - digitValue *= 16.toBigInt() } - } else for (ch in sPositiveUpper.reversed()) { - // decimal representation - if (ch == '_') continue - if (ch !in '0'..'9') { - return null - } - res += digitValue * (ch.code - '0'.code) - isEmpty = false - digitValue *= 10.toBigInt() - } - return if (isEmpty) null else res * sign + while (uInts.isNotEmpty() && uInts.last() == 0U) + uInts.removeLast() + + if (isEmpty) null else BigInt(sign.toByte(), uInts.toUIntArray()) + } else { + // hex representation + var res = BigInt.ZERO + var digitValue = BigInt.ONE + for (index in lastIndex downTo positivePartIndex) { + val ch = this[index] + // decimal representation + if (ch == '_') continue + if (ch !in '0'..'9') { + return null + } + res += digitValue * (ch.code - '0'.code) + isEmpty = false + digitValue *= 10.toBigInt() + + } + + if (isEmpty) null else res * sign + } } public inline fun Buffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): Buffer = From b4e47494fcf6683d14d523aaaba34e33da592c3c Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Wed, 12 May 2021 04:42:17 +0300 Subject: [PATCH 011/132] Parsing of decimal values takes 9 immediately digits but not 1. --- .../kmath/benchmarks/BigIntBenchmark.kt | 25 ++++++++-- .../space/kscience/kmath/operations/BigInt.kt | 47 ++++++++++--------- .../kmath/operations/BigIntConversionsTest.kt | 8 +++- 3 files changed, 54 insertions(+), 26 deletions(-) diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt index 33c659fca..639eaacf3 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt @@ -10,10 +10,7 @@ import kotlinx.benchmark.Blackhole import org.openjdk.jmh.annotations.Benchmark import org.openjdk.jmh.annotations.Scope import org.openjdk.jmh.annotations.State -import space.kscience.kmath.operations.BigInt -import space.kscience.kmath.operations.BigIntField -import space.kscience.kmath.operations.JBigIntegerField -import space.kscience.kmath.operations.invoke +import space.kscience.kmath.operations.* @State(Scope.Benchmark) @@ -64,4 +61,24 @@ internal class BigIntBenchmark { fun jvmPower(blackhole: Blackhole) = JBigIntegerField { blackhole.consume(jvmNumber.pow(bigExponent)) } + + @Benchmark + fun kmParsing16(blackhole: Blackhole) = JBigIntegerField { + blackhole.consume("0x7f57ed8b89c29a3b9a85c7a5b84ca3929c7b7488593".parseBigInteger()) + } + + @Benchmark + fun kmParsing10(blackhole: Blackhole) = JBigIntegerField { + blackhole.consume("236656783929183747565738292847574838922010".parseBigInteger()) + } + + @Benchmark + fun jvmParsing10(blackhole: Blackhole) = JBigIntegerField { + blackhole.consume("236656783929183747565738292847574838922010".toBigInteger(10)) + } + + @Benchmark + fun jvmParsing16(blackhole: Blackhole) = JBigIntegerField { + blackhole.consume("7f57ed8b89c29a3b9a85c7a5b84ca3929c7b7488593".toBigInteger(16)) + } } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index ab05d079f..780a4591d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -441,13 +441,6 @@ public fun UIntArray.toBigInt(sign: Byte): BigInt { return BigInt(sign, copyOf()) } -private val hexChToInt: MutableMap = hashMapOf( - '0' to 0U, '1' to 1U, '2' to 2U, '3' to 3U, - '4' to 4U, '5' to 5U, '6' to 6U, '7' to 7U, - '8' to 8U, '9' to 9U, 'A' to 10U, 'B' to 11U, - 'C' to 12U, 'D' to 13U, 'E' to 14U, 'F' to 15U -) - /** * Returns null if a valid number can not be read from a string */ @@ -475,7 +468,7 @@ public fun String.parseBigInteger(): BigInt? { return if (this.startsWith("0X", startIndex = positivePartIndex, ignoreCase = true)) { // hex representation - val uInts = mutableListOf(0U) + val uInts = ArrayList(length).apply { add(0U) } var offset = 0 fun addDigit(value: UInt) { uInts[uInts.lastIndex] += value shl offset @@ -502,22 +495,34 @@ public fun String.parseBigInteger(): BigInt? { if (isEmpty) null else BigInt(sign.toByte(), uInts.toUIntArray()) } else { - // hex representation - var res = BigInt.ZERO - var digitValue = BigInt.ONE - for (index in lastIndex downTo positivePartIndex) { - val ch = this[index] - // decimal representation - if (ch == '_') continue - if (ch !in '0'..'9') { - return null - } - res += digitValue * (ch.code - '0'.code) - isEmpty = false - digitValue *= 10.toBigInt() + // decimal representation + val positivePart = buildList(length) { + for (index in positivePartIndex until length) + when (val a = this@parseBigInteger[index]) { + '_' -> continue + in '0'..'9' -> add(a) + else -> return null + } } + val offset = positivePart.size % 9 + isEmpty = offset == 0 + + fun parseUInt(fromIndex: Int, toIndex: Int): UInt? { + var res = 0U + for (i in fromIndex until toIndex) { + res = res * 10U + (positivePart[i].digitToIntOrNull()?.toUInt() ?: return null) + } + return res + } + + var res = parseUInt(0, offset)?.toBigInt() ?: return null + + for (index in offset..positivePart.lastIndex step 9) { + isEmpty = false + res = res * 1_000_000_000U + (parseUInt(index, index + 9) ?: return null).toBigInt() + } if (isEmpty) null else res * sign } } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntConversionsTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntConversionsTest.kt index 1feaae808..85f368f3e 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntConversionsTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntConversionsTest.kt @@ -13,7 +13,7 @@ import kotlin.test.assertNull class BigIntConversionsTest { @Test - fun emptyString() { + fun testEmptyString() { assertNull("".parseBigInteger()) assertNull("+".parseBigInteger()) assertNull("-".parseBigInteger()) @@ -38,6 +38,12 @@ class BigIntConversionsTest { assertEquals("0x10", x.toString()) } + @Test + fun testUnderscores() { + assertEquals("0x10", "0x_1_0_".parseBigInteger().toString()) + assertEquals("0xa", "_1_0_".parseBigInteger().toString()) + } + @Test fun testToString0x17ffffffd() { val x = 0x17ffffffdL.toBigInt() From ed86a31c50d7d6b3890342fb2652ffdba4630fb0 Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Wed, 12 May 2021 04:58:48 +0300 Subject: [PATCH 012/132] Placing pow outside the Ring interface. --- .../kscience/kmath/operations/Algebra.kt | 26 +++++++++---------- .../space/kscience/kmath/operations/BigInt.kt | 2 ++ 2 files changed, 15 insertions(+), 13 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index f7c021998..645e60c29 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -250,21 +250,21 @@ public interface Ring : Group, RingOperations { * neutral operation for multiplication */ public val one: T +} - public fun T.pow(exponent: ULong): T = when { - this == zero && exponent > 0UL -> zero - this == one -> this - this == -one -> powWithoutOptimization(exponent % 2UL) - else -> powWithoutOptimization(exponent) - } +public fun Ring.pow(base: T, exponent: ULong): T = when { + this == zero && exponent > 0UL -> zero + this == one -> base + this == -one -> powWithoutOptimization(base, exponent % 2UL) + else -> powWithoutOptimization(base, exponent) +} - private fun T.powWithoutOptimization(exponent: ULong): T = when (exponent) { - 0UL -> one - 1UL -> this - else -> { - val pre = powWithoutOptimization(exponent shr 1).let { it * it } - if (exponent and 1UL == 0UL) pre else pre * this - } +private fun Ring.powWithoutOptimization(base: T, exponent: ULong): T = when (exponent) { + 0UL -> one + 1UL -> base + else -> { + val pre = powWithoutOptimization(base, exponent shr 1).let { it * it } + if (exponent and 1UL == 0UL) pre else pre * base } } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 780a4591d..88c952928 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -98,6 +98,8 @@ public class BigInt internal constructor( else -> BigInt(sign, multiplyMagnitudeByUInt(magnitude, other)) } + public fun pow(other: ULong): BigInt = BigIntField { pow(this@BigInt, other) } + public operator fun times(other: Int): BigInt = when { other > 0 -> this * kotlin.math.abs(other).toUInt() other != Int.MIN_VALUE -> -this * kotlin.math.abs(other).toUInt() From ded01251d1e94af4edf315c3d5ad70dce6b06ee0 Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Wed, 12 May 2021 11:05:42 +0300 Subject: [PATCH 013/132] Karatsuba enhancement --- .../kotlin/space/kscience/kmath/operations/BigInt.kt | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 88c952928..be73e274a 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -324,10 +324,8 @@ public class BigInt internal constructor( } internal fun multiplyMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude = when { - mag1.size + mag2.size < KARATSUBA_THRESHOLD || mag1.isEmpty() || mag2.isEmpty() -> naiveMultiplyMagnitudes( - mag1, - mag2 - ) + mag1.size + mag2.size < KARATSUBA_THRESHOLD || mag1.isEmpty() || mag2.isEmpty() -> + naiveMultiplyMagnitudes(mag1, mag2) // TODO implement Fourier else -> karatsubaMultiplyMagnitudes(mag1, mag2) } @@ -361,7 +359,7 @@ public class BigInt internal constructor( val z0 = x0 * y0 val z2 = x1 * y1 - val z1 = (x0 + x1) * (y1 + y0) - z0 - z2 + val z1 = (x0 - x1) * (y1 - y0) + z0 + z2 return (z2.shl(2 * halfSize * BASE_SIZE) + z1.shl(halfSize * BASE_SIZE) + z0).magnitude } From 1e71f29d5e64a5c933630f892fab29cdfbd36e63 Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Wed, 12 May 2021 13:59:41 +0300 Subject: [PATCH 014/132] Large addition tests added --- .../space/kscience/kmath/benchmarks/BigIntBenchmark.kt | 10 ++++++++++ .../kotlin/space/kscience/kmath/operations/BigInt.kt | 2 +- 2 files changed, 11 insertions(+), 1 deletion(-) diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt index 639eaacf3..d3262379f 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt @@ -32,6 +32,16 @@ internal class BigIntBenchmark { blackhole.consume(jvmNumber + jvmNumber + jvmNumber) } + @Benchmark + fun kmAddLarge(blackhole: Blackhole) = BigIntField { + blackhole.consume(largeKmNumber + largeKmNumber + largeKmNumber) + } + + @Benchmark + fun jvmAddLarge(blackhole: Blackhole) = JBigIntegerField { + blackhole.consume(largeJvmNumber + largeJvmNumber + largeJvmNumber) + } + @Benchmark fun kmMultiply(blackhole: Blackhole) = BigIntField { blackhole.consume(kmNumber * kmNumber * kmNumber) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index be73e274a..605dfd265 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -281,7 +281,7 @@ public class BigInt internal constructor( } result[i] = (res and BASE).toUInt() - carry = (res shr BASE_SIZE) + carry = res shr BASE_SIZE } result[resultLength - 1] = carry.toUInt() From 8443fac4ae4df746f26a1dd444be1ef194d7baa5 Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Wed, 12 May 2021 14:10:32 +0300 Subject: [PATCH 015/132] UInt can be used in exponent (in pow) now. --- .../kotlin/space/kscience/kmath/operations/Algebra.kt | 2 ++ .../kotlin/space/kscience/kmath/operations/BigInt.kt | 1 + .../space/kscience/kmath/operations/BigIntAlgebraTest.kt | 8 +++++++- 3 files changed, 10 insertions(+), 1 deletion(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index 645e60c29..a23dc427c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -259,6 +259,8 @@ public fun Ring.pow(base: T, exponent: ULong): T = when { else -> powWithoutOptimization(base, exponent) } +public fun Ring.pow(base: T, exponent: UInt): T = pow(base, exponent.toULong()) + private fun Ring.powWithoutOptimization(base: T, exponent: ULong): T = when (exponent) { 0UL -> one 1UL -> base diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 605dfd265..45161149c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -99,6 +99,7 @@ public class BigInt internal constructor( } public fun pow(other: ULong): BigInt = BigIntField { pow(this@BigInt, other) } + public fun pow(other: UInt): BigInt = BigIntField { pow(this@BigInt, other) } public operator fun times(other: Int): BigInt = when { other > 0 -> this * kotlin.math.abs(other).toUInt() diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt index 90cd29758..abc88934c 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt @@ -26,12 +26,18 @@ internal class BigIntAlgebraTest { fun testKBigIntegerRingPow() { BigIntField { for (num in -5..5) - for (exponent in 0UL..10UL) + for (exponent in 0U..10U) { + assertEquals( + num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), + num.toBigInt().pow(exponent.toULong()), + "$num ^ $exponent" + ) assertEquals( num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), num.toBigInt().pow(exponent), "$num ^ $exponent" ) + } } } From e5f3ee75be375f457c342ab5fc02ff0f324c6490 Mon Sep 17 00:00:00 2001 From: Roland Grinis Date: Wed, 12 May 2021 19:40:10 +0100 Subject: [PATCH 016/132] tensors readme fix --- README.md | 7 ++++--- kmath-tensors/README.md | 8 ++++---- 2 files changed, 8 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 3b4387c1b..c3def902b 100644 --- a/README.md +++ b/README.md @@ -247,9 +247,10 @@ One can still use generic algebras though. > **Maturity**: PROTOTYPE > > **Features:** -> - [tensor algebra](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Basic linear algebra operations on tensors (plus, dot, etc.) -> - [tensor algebra with broadcasting](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting. -> - [linear algebra operations](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Advanced linear algebra operations like LU decomposition, SVD, etc. +> - [tensor algebra](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Interface for basic linear algebra operations on tensors (plus, dot, etc.) +> - [linear algebra operations](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Interface for advanced linear algebra operations like LU decomposition, SVD, etc. +> - [tensor algebra over Double](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt): Full implementation of operations for tensors over `Double`'s +> - [tensor algebra with broadcasting](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting for tensors over `Double`'s.
diff --git a/kmath-tensors/README.md b/kmath-tensors/README.md index 7ece44217..586bb8ac6 100644 --- a/kmath-tensors/README.md +++ b/kmath-tensors/README.md @@ -2,10 +2,10 @@ Common linear algebra operations on tensors. - - [tensor algebra](src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Basic linear algebra operations on tensors (plus, dot, etc.) - - [tensor algebra with broadcasting](src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting. - - [linear algebra operations](src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Advanced linear algebra operations like LU decomposition, SVD, etc. - + - [tensor algebra](src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Interface for basic linear algebra operations on tensors (plus, dot, etc.) + - [linear algebra operations](src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Interface for advanced linear algebra operations like LU decomposition, SVD, etc. + - [tensor algebra over Double](src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt): Full implementation of operations for tensors over `Double`'s + - [tensor algebra with broadcasting](src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting for tensors over `Double`'s. ## Artifact: From d721c4b5976072dae740243b2f1cefee5fcbe2b2 Mon Sep 17 00:00:00 2001 From: Roland Grinis Date: Wed, 12 May 2021 19:43:08 +0100 Subject: [PATCH 017/132] typo found --- README.md | 2 +- kmath-tensors/README.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index c3def902b..519472a69 100644 --- a/README.md +++ b/README.md @@ -249,7 +249,7 @@ One can still use generic algebras though. > **Features:** > - [tensor algebra](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Interface for basic linear algebra operations on tensors (plus, dot, etc.) > - [linear algebra operations](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Interface for advanced linear algebra operations like LU decomposition, SVD, etc. -> - [tensor algebra over Double](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt): Full implementation of operations for tensors over `Double`'s +> - [tensor algebra over Double](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt): Full implementation of operations for tensors over `Double`'s. > - [tensor algebra with broadcasting](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting for tensors over `Double`'s.
diff --git a/kmath-tensors/README.md b/kmath-tensors/README.md index 586bb8ac6..affdad665 100644 --- a/kmath-tensors/README.md +++ b/kmath-tensors/README.md @@ -4,7 +4,7 @@ Common linear algebra operations on tensors. - [tensor algebra](src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Interface for basic linear algebra operations on tensors (plus, dot, etc.) - [linear algebra operations](src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Interface for advanced linear algebra operations like LU decomposition, SVD, etc. - - [tensor algebra over Double](src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt): Full implementation of operations for tensors over `Double`'s + - [tensor algebra over Double](src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt): Full implementation of operations for tensors over `Double`'s. - [tensor algebra with broadcasting](src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting for tensors over `Double`'s. ## Artifact: From 97c4b817173637818f1b496580afc688af8825d2 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Thu, 13 May 2021 11:02:20 +0300 Subject: [PATCH 018/132] Introduce PerformancePitfall annotation --- CHANGELOG.md | 1 + LICENSE | 201 ------------------ .../space/kscience/kmath/data/ColumnarData.kt | 2 + .../kscience/kmath/data/XYColumnarData.kt | 2 + .../kmath/linear/BufferedLinearSpace.kt | 3 + .../space/kscience/kmath/misc/annotations.kt | 12 ++ .../space/kscience/kmath/nd/BufferND.kt | 2 + .../space/kscience/kmath/nd/Structure1D.kt | 21 +- .../space/kscience/kmath/nd/Structure2D.kt | 8 +- .../space/kscience/kmath/nd/StructureND.kt | 4 + .../kmath/linear/DoubleLUSolverTest.kt | 2 + .../space/kscience/kmath/linear/MatrixTest.kt | 2 + .../kmath/structures/NumberNDFieldTest.kt | 2 + .../kmath/structures/LazyStructureND.kt | 2 + .../kscience/kmath/ejml/EjmlMatrixTest.kt | 2 + .../space/kscience/kmath/real/RealMatrix.kt | 4 + .../kaceince/kmath/real/DoubleMatrixTest.kt | 2 + .../kscience/kmath/jupyter/KMathJupyter.kt | 4 +- .../kscience/kmath/nd4j/Nd4jArrayStructure.kt | 2 + .../kmath/tensors/core/BufferedTensor.kt | 6 +- .../kmath/viktor/ViktorStructureND.kt | 2 + 21 files changed, 75 insertions(+), 211 deletions(-) delete mode 100644 LICENSE diff --git a/CHANGELOG.md b/CHANGELOG.md index 4fba361d5..286be25e5 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -12,6 +12,7 @@ - Integration for any Field element - Extended operations for ND4J fields - Jupyter Notebook integration module (kmath-jupyter) +- `@PerformancePitfall` annotation to mark possibly slow API ### Changed - Exponential operations merged with hyperbolic functions diff --git a/LICENSE b/LICENSE deleted file mode 100644 index 261eeb9e9..000000000 --- a/LICENSE +++ /dev/null @@ -1,201 +0,0 @@ - Apache License - Version 2.0, January 2004 - http://www.apache.org/licenses/ - - TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION - - 1. 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The code, marked by this API is not necessary slow, but could cause + * slow-down in some cases. Refer to the documentation and benchmark it to be sure. + */ +@MustBeDocumented +@Retention(value = AnnotationRetention.BINARY) +@RequiresOptIn( + "Refer to the documentation to use this API in performance-critical code", + RequiresOptIn.Level.WARNING +) +public annotation class PerformancePitfall diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferND.kt index 1f608f478..425808aeb 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferND.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.nd +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.BufferFactory import space.kscience.kmath.structures.MutableBuffer @@ -32,6 +33,7 @@ public open class BufferND( override val shape: IntArray get() = strides.shape + @PerformancePitfall override fun elements(): Sequence> = strides.indices().map { it to this[it] } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt index 8ea6d0f02..cc0528793 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.nd +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.MutableBuffer import space.kscience.kmath.structures.asMutableBuffer @@ -46,6 +47,8 @@ private value class Structure1DWrapper(val structure: StructureND) : Struc override val size: Int get() = structure.shape[0] override operator fun get(index: Int): T = structure[index] + + @PerformancePitfall override fun elements(): Sequence> = structure.elements() } @@ -55,6 +58,8 @@ private value class Structure1DWrapper(val structure: StructureND) : Struc private class MutableStructure1DWrapper(val structure: MutableStructureND) : MutableStructure1D { override val shape: IntArray get() = structure.shape override val size: Int get() = structure.shape[0] + + @PerformancePitfall override fun elements(): Sequence> = structure.elements() override fun get(index: Int): T = structure[index] @@ -62,8 +67,8 @@ private class MutableStructure1DWrapper(val structure: MutableStructureND) structure[intArrayOf(index)] = value } - override fun copy(): MutableBuffer = - structure.elements().map { it.second }.toMutableList().asMutableBuffer() + @PerformancePitfall + override fun copy(): MutableBuffer = structure.elements().map { it.second }.toMutableList().asMutableBuffer() } @@ -75,8 +80,10 @@ private value class Buffer1DWrapper(val buffer: Buffer) : Structure1D { override val shape: IntArray get() = intArrayOf(buffer.size) override val size: Int get() = buffer.size - override fun elements(): Sequence> = - buffer.asSequence().mapIndexed { index, value -> intArrayOf(index) to value } + @PerformancePitfall + override fun elements(): Sequence> = buffer.asSequence().mapIndexed { index, value -> + intArrayOf(index) to value + } override operator fun get(index: Int): T = buffer[index] } @@ -85,8 +92,10 @@ internal class MutableBuffer1DWrapper(val buffer: MutableBuffer) : Mutable override val shape: IntArray get() = intArrayOf(buffer.size) override val size: Int get() = buffer.size - override fun elements(): Sequence> = - buffer.asSequence().mapIndexed { index, value -> intArrayOf(index) to value } + @PerformancePitfall + override fun elements(): Sequence> = buffer.asSequence().mapIndexed { index, value -> + intArrayOf(index) to value + } override operator fun get(index: Int): T = buffer[index] override fun set(index: Int, value: T) { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt index 28ae07a3c..8dce4ad6b 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt @@ -5,10 +5,11 @@ package space.kscience.kmath.nd +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.VirtualBuffer import space.kscience.kmath.structures.MutableListBuffer +import space.kscience.kmath.structures.VirtualBuffer import kotlin.jvm.JvmInline import kotlin.reflect.KClass @@ -33,12 +34,14 @@ public interface Structure2D : StructureND { /** * The buffer of rows of this structure. It gets elements from the structure dynamically. */ + @PerformancePitfall public val rows: List> get() = List(rowNum) { i -> VirtualBuffer(colNum) { j -> get(i, j) } } /** * The buffer of columns of this structure. It gets elements from the structure dynamically. */ + @PerformancePitfall public val columns: List> get() = List(colNum) { j -> VirtualBuffer(rowNum) { i -> get(i, j) } } @@ -80,12 +83,14 @@ public interface MutableStructure2D : Structure2D, MutableStructureND { /** * The buffer of rows of this structure. It gets elements from the structure dynamically. */ + @PerformancePitfall override val rows: List> get() = List(rowNum) { i -> MutableBuffer1DWrapper(MutableListBuffer(colNum) { j -> get(i, j) })} /** * The buffer of columns of this structure. It gets elements from the structure dynamically. */ + @PerformancePitfall override val columns: List> get() = List(colNum) { j -> MutableBuffer1DWrapper(MutableListBuffer(rowNum) { i -> get(i, j) }) } } @@ -105,6 +110,7 @@ private value class Structure2DWrapper(val structure: StructureND) : Struc @UnstableKMathAPI override fun getFeature(type: KClass): F? = structure.getFeature(type) + @PerformancePitfall override fun elements(): Sequence> = structure.elements() } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt index a3331d71a..b9f1a063a 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.nd +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.BufferFactory @@ -48,6 +49,7 @@ public interface StructureND { * * @return the lazy sequence of pairs of indices to values. */ + @PerformancePitfall public fun elements(): Sequence> /** @@ -61,6 +63,7 @@ public interface StructureND { /** * Indicates whether some [StructureND] is equal to another one. */ + @PerformancePitfall public fun contentEquals(st1: StructureND, st2: StructureND): Boolean { if (st1 === st2) return true @@ -169,6 +172,7 @@ public interface MutableStructureND : StructureND { /** * Transform a structure element-by element in place. */ +@OptIn(PerformancePitfall::class) public inline fun MutableStructureND.mapInPlace(action: (IntArray, T) -> T): Unit = elements().forEach { (index, oldValue) -> this[index] = action(index, oldValue) } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt index ebbbbe392..2d2a0952b 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt @@ -5,12 +5,14 @@ package space.kscience.kmath.linear +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureND import kotlin.test.Test import kotlin.test.assertEquals import kotlin.test.assertTrue +@OptIn(PerformancePitfall::class) fun assertMatrixEquals(expected: StructureND, actual: StructureND) { assertTrue { StructureND.contentEquals(expected, actual) } } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt index 250fa3433..170f9caf4 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.linear +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.as2D @@ -13,6 +14,7 @@ import kotlin.test.assertEquals import kotlin.test.assertTrue @UnstableKMathAPI +@OptIn(PerformancePitfall::class) @Suppress("UNUSED_VARIABLE") class MatrixTest { @Test diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt index 99743d879..57393fadd 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.structures import space.kscience.kmath.linear.LinearSpace +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.* import space.kscience.kmath.operations.Norm import space.kscience.kmath.operations.invoke @@ -74,6 +75,7 @@ class NumberNDFieldTest { } object L2Norm : Norm, Double> { + @OptIn(PerformancePitfall::class) override fun norm(arg: StructureND): Double = kotlin.math.sqrt(arg.elements().sumOf { it.second.toDouble() }) } diff --git a/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt b/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt index e2ecb4b2f..1cd16054a 100644 --- a/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt +++ b/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt @@ -7,6 +7,7 @@ package space.kscience.kmath.structures import kotlinx.coroutines.* import space.kscience.kmath.coroutines.Math +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.DefaultStrides import space.kscience.kmath.nd.StructureND @@ -24,6 +25,7 @@ public class LazyStructureND( public suspend fun await(index: IntArray): T = deferred(index).await() public override operator fun get(index: IntArray): T = runBlocking { deferred(index).await() } + @OptIn(PerformancePitfall::class) public override fun elements(): Sequence> { val strides = DefaultStrides(shape) val res = runBlocking { strides.indices().toList().map { index -> index to await(index) } } diff --git a/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt b/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt index 485c53c38..50675bdac 100644 --- a/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt +++ b/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt @@ -12,12 +12,14 @@ import org.ejml.dense.row.factory.DecompositionFactory_DDRM import space.kscience.kmath.linear.DeterminantFeature import space.kscience.kmath.linear.LupDecompositionFeature import space.kscience.kmath.linear.getFeature +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureND import kotlin.random.Random import kotlin.random.asJavaRandom import kotlin.test.* +@OptIn(PerformancePitfall::class) fun assertMatrixEquals(expected: StructureND, actual: StructureND) { assertTrue { StructureND.contentEquals(expected, actual) } } diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt index c4656dd8a..8023236ea 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt @@ -3,9 +3,13 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ +@file:OptIn(PerformancePitfall::class) +@file:Suppress("unused") + package space.kscience.kmath.real import space.kscience.kmath.linear.* +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.structures.Buffer diff --git a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt b/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt index 84e604b18..b3e129c2e 100644 --- a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt @@ -7,6 +7,7 @@ package kaceince.kmath.real import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.matrix +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureND import space.kscience.kmath.real.* @@ -15,6 +16,7 @@ import kotlin.test.Test import kotlin.test.assertEquals import kotlin.test.assertTrue +@OptIn(PerformancePitfall::class) fun assertMatrixEquals(expected: StructureND, actual: StructureND) { assertTrue { StructureND.contentEquals(expected, actual) } } diff --git a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt index 78b25af47..f3d553f2e 100644 --- a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt +++ b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt @@ -8,11 +8,12 @@ import org.jetbrains.kotlinx.jupyter.api.DisplayResult import org.jetbrains.kotlinx.jupyter.api.HTML import org.jetbrains.kotlinx.jupyter.api.annotations.JupyterLibrary import org.jetbrains.kotlinx.jupyter.api.libraries.JupyterIntegration -import space.kscience.kmath.expressions.MST import space.kscience.kmath.ast.rendering.FeaturedMathRendererWithPostProcess import space.kscience.kmath.ast.rendering.MathMLSyntaxRenderer import space.kscience.kmath.ast.rendering.renderWithStringBuilder import space.kscience.kmath.complex.Complex +import space.kscience.kmath.expressions.MST +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.Structure2D import space.kscience.kmath.operations.GroupOperations import space.kscience.kmath.operations.RingOperations @@ -55,6 +56,7 @@ internal class KMathJupyter : JupyterIntegration() { } } + @OptIn(PerformancePitfall::class) override fun Builder.onLoaded() { import( "space.kscience.kmath.ast.*", diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt index 79db86fcc..d37c91cb6 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.nd4j import org.nd4j.linalg.api.ndarray.INDArray +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.MutableStructureND import space.kscience.kmath.nd.StructureND @@ -24,6 +25,7 @@ public sealed class Nd4jArrayStructure : MutableStructureND { internal abstract fun elementsIterator(): Iterator> internal fun indicesIterator(): Iterator = ndArray.indicesIterator() + @PerformancePitfall public override fun elements(): Sequence> = Sequence(::elementsIterator) } diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt index 858532abc..315dc4505 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt @@ -1,7 +1,8 @@ package space.kscience.kmath.tensors.core +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.Strides -import space.kscience.kmath.structures.* +import space.kscience.kmath.structures.MutableBuffer import space.kscience.kmath.tensors.api.Tensor import space.kscience.kmath.tensors.core.internal.TensorLinearStructure @@ -32,7 +33,8 @@ public open class BufferedTensor internal constructor( mutableBuffer[bufferStart + linearStructure.offset(index)] = value } + @PerformancePitfall override fun elements(): Sequence> = linearStructure.indices().map { - it to this[it] + it to get(it) } } diff --git a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt index dc1b45f5d..b7abf4304 100644 --- a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt +++ b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.viktor import org.jetbrains.bio.viktor.F64Array +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.* import space.kscience.kmath.operations.DoubleField @@ -23,6 +24,7 @@ public class ViktorStructureND(public val f64Buffer: F64Array) : MutableStructur f64Buffer.set(*index, value = value) } + @PerformancePitfall public override fun elements(): Sequence> = DefaultStrides(shape).indices().map { it to get(it) } } From f5289abdc3e6c636ff2411f04141eddd4847a5f8 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Thu, 13 May 2021 11:09:49 +0300 Subject: [PATCH 019/132] Introduce PerformancePitfall annotation --- kmath-core/api/kmath-core.api | 3 +++ .../commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt | 2 ++ .../kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt | 4 +--- .../kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt | 4 +--- .../space/kscience/kmath/histogram/IndexedHistogramSpace.kt | 5 ++--- .../kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt | 2 ++ .../kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt | 4 +++- .../space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt | 2 ++ .../space/kscience/kmath/tensors/core/TestDoubleTensor.kt | 2 ++ 9 files changed, 18 insertions(+), 10 deletions(-) diff --git a/kmath-core/api/kmath-core.api b/kmath-core/api/kmath-core.api index 7dd459104..14bc70a2a 100644 --- a/kmath-core/api/kmath-core.api +++ b/kmath-core/api/kmath-core.api @@ -674,6 +674,9 @@ public final class space/kscience/kmath/misc/CumulativeKt { public static final fun cumulativeSumOfLong (Lkotlin/sequences/Sequence;)Lkotlin/sequences/Sequence; } +public abstract interface annotation class space/kscience/kmath/misc/PerformancePitfall : java/lang/annotation/Annotation { +} + public final class space/kscience/kmath/misc/StringSymbol : space/kscience/kmath/misc/Symbol { public static final synthetic fun box-impl (Ljava/lang/String;)Lspace/kscience/kmath/misc/StringSymbol; public static fun constructor-impl (Ljava/lang/String;)Ljava/lang/String; diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt index 8dce4ad6b..5b8183699 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt @@ -59,6 +59,7 @@ public interface Structure2D : StructureND { return get(index[0], index[1]) } + @PerformancePitfall override fun elements(): Sequence> = sequence { for (i in 0 until rowNum) for (j in 0 until colNum) yield(intArrayOf(i, j) to get(i, j)) @@ -134,6 +135,7 @@ private class MutableStructure2DWrapper(val structure: MutableStructureND) structure[intArrayOf(i, j)] = value } + @PerformancePitfall override fun elements(): Sequence> = structure.elements() override fun equals(other: Any?): Boolean = false diff --git a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt index 3604fda31..2a4837ee0 100644 --- a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt +++ b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt @@ -7,16 +7,14 @@ package space.kscience.kmath.geometry import space.kscience.kmath.linear.Point import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.GroupElement import space.kscience.kmath.operations.ScaleOperations import space.kscience.kmath.operations.invoke import kotlin.math.sqrt @OptIn(UnstableKMathAPI::class) -public interface Vector2D : Point, Vector, GroupElement { +public interface Vector2D : Point, Vector{ public val x: Double public val y: Double - public override val context: Euclidean2DSpace get() = Euclidean2DSpace public override val size: Int get() = 2 public override operator fun get(index: Int): Double = when (index) { diff --git a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt index 8643b2dbb..37e7d2cb2 100644 --- a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt +++ b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt @@ -7,17 +7,15 @@ package space.kscience.kmath.geometry import space.kscience.kmath.linear.Point import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.GroupElement import space.kscience.kmath.operations.ScaleOperations import space.kscience.kmath.operations.invoke import kotlin.math.sqrt @OptIn(UnstableKMathAPI::class) -public interface Vector3D : Point, Vector, GroupElement { +public interface Vector3D : Point, Vector { public val x: Double public val y: Double public val z: Double - public override val context: Euclidean3DSpace get() = Euclidean3DSpace public override val size: Int get() = 3 public override operator fun get(index: Int): Double = when (index) { diff --git a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt index 818d81ab0..e5f6830c5 100644 --- a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt +++ b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt @@ -12,7 +12,6 @@ import space.kscience.kmath.nd.FieldND import space.kscience.kmath.nd.Strides import space.kscience.kmath.nd.StructureND import space.kscience.kmath.operations.Group -import space.kscience.kmath.operations.GroupElement import space.kscience.kmath.operations.ScaleOperations import space.kscience.kmath.operations.invoke @@ -26,9 +25,9 @@ public data class DomainBin>( @OptIn(UnstableKMathAPI::class) public class IndexedHistogram, V : Any>( - override val context: IndexedHistogramSpace, + public val context: IndexedHistogramSpace, public val values: StructureND, -) : Histogram>, GroupElement, IndexedHistogramSpace> { +) : Histogram> { override fun get(point: Point): Bin? { val index = context.getIndex(point) ?: return null diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt index 0205f1c87..3cac44c47 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt @@ -10,6 +10,7 @@ import org.nd4j.linalg.api.ops.impl.scalar.Pow import org.nd4j.linalg.api.ops.impl.transforms.strict.* import org.nd4j.linalg.factory.Nd4j import org.nd4j.linalg.ops.transforms.Transforms +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.* import space.kscience.kmath.operations.* @@ -52,6 +53,7 @@ public interface Nd4jArrayAlgebra> : AlgebraND { return struct } + @PerformancePitfall public override fun StructureND.map(transform: C.(T) -> T): Nd4jArrayStructure { val newStruct = ndArray.dup().wrap() newStruct.elements().forEach { (idx, value) -> newStruct[idx] = elementContext.transform(value) } diff --git a/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt b/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt index b6c524cc6..c80a1d771 100644 --- a/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt +++ b/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.nd4j import org.nd4j.linalg.factory.Nd4j +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.StructureND import space.kscience.kmath.operations.invoke import kotlin.math.PI @@ -14,6 +15,7 @@ import kotlin.test.assertEquals import kotlin.test.assertTrue import kotlin.test.fail +@OptIn(PerformancePitfall::class) internal class Nd4jArrayAlgebraTest { @Test fun testProduce() { @@ -28,7 +30,7 @@ internal class Nd4jArrayAlgebraTest { @Test fun testMap() { - val res = with(IntNd4jArrayRing(intArrayOf(2, 2))) { one.map() { it + it * 2 } } + val res = with(IntNd4jArrayRing(intArrayOf(2, 2))) { one.map { it + it * 2 } } val expected = (Nd4j.create(2, 2) ?: fail()).asIntStructure() expected[intArrayOf(0, 0)] = 3 expected[intArrayOf(0, 1)] = 3 diff --git a/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt b/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt index d59e04194..bdfec2ba6 100644 --- a/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt +++ b/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.nd4j import org.nd4j.linalg.factory.Nd4j +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.get import kotlin.test.Test import kotlin.test.assertEquals @@ -13,6 +14,7 @@ import kotlin.test.assertNotEquals import kotlin.test.fail internal class Nd4jArrayStructureTest { + @OptIn(PerformancePitfall::class) @Test fun testElements() { val nd = Nd4j.create(doubleArrayOf(1.0, 2.0, 3.0))!! diff --git a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt index a6c6a7618..a176abdd4 100644 --- a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt +++ b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt @@ -1,5 +1,6 @@ package space.kscience.kmath.tensors.core +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.DefaultStrides import space.kscience.kmath.nd.MutableBufferND import space.kscience.kmath.nd.as1D @@ -24,6 +25,7 @@ internal class TestDoubleTensor { assertEquals(tensor.value(), value) } + @OptIn(PerformancePitfall::class) @Test fun testStrides() = DoubleTensorAlgebra { val tensor = fromArray(intArrayOf(2, 2), doubleArrayOf(3.5, 5.8, 58.4, 2.4)) From feb5743f58616af3c46917ce098c63778191e5db Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Thu, 13 May 2021 11:10:59 +0300 Subject: [PATCH 020/132] Change signature of one of integrate helpers --- .../kscience/kmath/commons/integration/IntegrationTest.kt | 6 +++--- .../space/kscience/kmath/integration/UnivariateIntegrand.kt | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt index 9d475d04d..97dc94d1d 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt @@ -19,16 +19,16 @@ internal class IntegrationTest { @Test fun simpson() { - val res = CMIntegrator.simpson().integrate(0.0..2 * PI, function) + val res = CMIntegrator.simpson().integrate(0.0..2 * PI, function = function) assertTrue { abs(res) < 1e-3 } } @Test fun customSimpson() { - val res = CMIntegrator.simpson().integrate(0.0..PI, function) { + val res = CMIntegrator.simpson().integrate(0.0..PI, { targetRelativeAccuracy = 1e-4 targetAbsoluteAccuracy = 1e-4 - } + }, function) assertTrue { abs(res - 2) < 1e-3 } assertTrue { abs(res - 2) > 1e-12 } } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index bcd5005c4..51ea57a33 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -57,8 +57,8 @@ public fun UnivariateIntegrator.integrate( @UnstableKMathAPI public fun UnivariateIntegrator.integrate( range: ClosedRange, + featureBuilder: MutableList.() -> Unit = {}, function: (Double) -> Double, - featureBuilder: (MutableList.() -> Unit) = {}, ): Double { //TODO use dedicated feature builder class instead or add extensions to MutableList val features = buildList { From 1e945389314cf8d3072f919f5c18afd9a4dcca4d Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Thu, 13 May 2021 13:11:20 +0300 Subject: [PATCH 021/132] Unstable API annotation added + inconsistent docs fix + unnecessary BigIntField usage removed --- .../kmath/benchmarks/BigIntBenchmark.kt | 5 +++- .../kscience/kmath/operations/Algebra.kt | 5 +++- .../space/kscience/kmath/operations/BigInt.kt | 3 ++ .../kmath/operations/OptionalOperations.kt | 2 +- .../kmath/operations/BigIntAlgebraTest.kt | 30 +++++++++---------- 5 files changed, 27 insertions(+), 18 deletions(-) diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt index d3262379f..21b097609 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt @@ -10,16 +10,19 @@ import kotlinx.benchmark.Blackhole import org.openjdk.jmh.annotations.Benchmark import org.openjdk.jmh.annotations.Scope import org.openjdk.jmh.annotations.State +import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.* +import java.math.BigInteger +@UnstableKMathAPI @State(Scope.Benchmark) internal class BigIntBenchmark { val kmNumber = BigIntField.number(Int.MAX_VALUE) val jvmNumber = JBigIntegerField.number(Int.MAX_VALUE) val largeKmNumber = BigIntField { number(11).pow(100_000UL) } - val largeJvmNumber = JBigIntegerField { number(11).pow(100_000) } + val largeJvmNumber: BigInteger = JBigIntegerField { number(11).pow(100_000) } val bigExponent = 50_000 @Benchmark diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index a23dc427c..8881ae93c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.operations import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.misc.UnstableKMathAPI /** * Stub for DSL the [Algebra] is. @@ -247,11 +248,12 @@ public interface RingOperations : GroupOperations { */ public interface Ring : Group, RingOperations { /** - * neutral operation for multiplication + * The neutral element of multiplication */ public val one: T } +@UnstableKMathAPI public fun Ring.pow(base: T, exponent: ULong): T = when { this == zero && exponent > 0UL -> zero this == one -> base @@ -259,6 +261,7 @@ public fun Ring.pow(base: T, exponent: ULong): T = when { else -> powWithoutOptimization(base, exponent) } +@UnstableKMathAPI public fun Ring.pow(base: T, exponent: UInt): T = pow(base, exponent.toULong()) private fun Ring.powWithoutOptimization(base: T, exponent: ULong): T = when (exponent) { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 45161149c..0dcbbe567 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -98,7 +98,10 @@ public class BigInt internal constructor( else -> BigInt(sign, multiplyMagnitudeByUInt(magnitude, other)) } + @UnstableKMathAPI public fun pow(other: ULong): BigInt = BigIntField { pow(this@BigInt, other) } + + @UnstableKMathAPI public fun pow(other: UInt): BigInt = BigIntField { pow(this@BigInt, other) } public operator fun times(other: Int): BigInt = when { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt index 8e3e6c777..7045c874e 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt @@ -147,7 +147,7 @@ public interface PowerOperations : Algebra { } /** - * Raises this element to the power [pow]. + * Raises this element to the power [power]. * * @receiver the base. * @param power the exponent. diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt index abc88934c..d3fca4351 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.operations +import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.testutils.RingVerifier import kotlin.math.pow import kotlin.test.Test @@ -22,23 +23,22 @@ internal class BigIntAlgebraTest { assertEquals(res, 1_000_000.toBigInt()) } + @UnstableKMathAPI @Test fun testKBigIntegerRingPow() { - BigIntField { - for (num in -5..5) - for (exponent in 0U..10U) { - assertEquals( - num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), - num.toBigInt().pow(exponent.toULong()), - "$num ^ $exponent" - ) - assertEquals( - num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), - num.toBigInt().pow(exponent), - "$num ^ $exponent" - ) - } - } + for (num in -5..5) + for (exponent in 0U..10U) { + assertEquals( + num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), + num.toBigInt().pow(exponent.toULong()), + "$num ^ $exponent" + ) + assertEquals( + num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), + num.toBigInt().pow(exponent), + "$num ^ $exponent" + ) + } } @Test From fcb960533823090eff6fae936ffa0058db65ff88 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Thu, 13 May 2021 22:59:35 +0700 Subject: [PATCH 022/132] Special rendering of Quaternion #330 --- .../space/kscience/kmath/complex/Complex.kt | 2 +- .../kscience/kmath/jupyter/KMathJupyter.kt | 24 ++++++++++++------- 2 files changed, 17 insertions(+), 9 deletions(-) diff --git a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt index 8e28337f6..a96d046c9 100644 --- a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt +++ b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt @@ -187,7 +187,7 @@ public data class Complex(val re: Double, val im: Double) { public constructor(re: Number, im: Number) : this(re.toDouble(), im.toDouble()) public constructor(re: Number) : this(re.toDouble(), 0.0) - public override fun toString(): String = "($re + i*$im)" + public override fun toString(): String = "($re + i * $im)" public companion object : MemorySpec { public override val objectSize: Int diff --git a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt index f3d553f2e..e3767e13c 100644 --- a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt +++ b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt @@ -12,18 +12,19 @@ import space.kscience.kmath.ast.rendering.FeaturedMathRendererWithPostProcess import space.kscience.kmath.ast.rendering.MathMLSyntaxRenderer import space.kscience.kmath.ast.rendering.renderWithStringBuilder import space.kscience.kmath.complex.Complex +import space.kscience.kmath.complex.Quaternion import space.kscience.kmath.expressions.MST +import space.kscience.kmath.expressions.MstRing import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.Structure2D -import space.kscience.kmath.operations.GroupOperations -import space.kscience.kmath.operations.RingOperations +import space.kscience.kmath.operations.invoke import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.asSequence /** * A function for conversion of number to MST for pretty print */ -public fun Number.toMst(): MST.Numeric = MST.Numeric(this) +public fun Number.toMst(): MST.Numeric = MST.Numeric(this) @JupyterLibrary internal class KMathJupyter : JupyterIntegration() { @@ -121,11 +122,18 @@ internal class KMathJupyter : JupyterIntegration() { } render { - MST.Binary( - operation = GroupOperations.PLUS_OPERATION, - left = MST.Numeric(it.re), - right = MST.Binary(RingOperations.TIMES_OPERATION, MST.Numeric(it.im), MST.Symbolic("i")), - ).toDisplayResult() + MstRing { + number(it.re) + number(it.im) * bindSymbol("i") + }.toDisplayResult() + } + + render { + MstRing { + number(it.w) + + number(it.x) * bindSymbol("i") + + number(it.x) * bindSymbol("j") + + number(it.x) * bindSymbol("k") + }.toDisplayResult() } } } From e110253d8f38171b91d4417c115713585e9faa29 Mon Sep 17 00:00:00 2001 From: Roland Grinis Date: Thu, 13 May 2021 19:26:18 +0100 Subject: [PATCH 023/132] remove cov from tensors API --- .../kmath/tensors/api/AnalyticTensorAlgebra.kt | 10 ---------- .../kscience/kmath/tensors/core/DoubleTensorAlgebra.kt | 10 +++++++++- 2 files changed, 9 insertions(+), 11 deletions(-) diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt index 1db986e77..e58af14db 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt @@ -67,16 +67,6 @@ public interface AnalyticTensorAlgebra : TensorPartialDivisionAlgebra { */ public fun Tensor.variance(dim: Int, keepDim: Boolean): Tensor - /** - * Returns the covariance matrix M of given vectors. - * - * M[i, j] contains covariance of i-th and j-th given vectors - * - * @param tensors the [List] of 1-dimensional tensors with same shape - * @return the covariance matrix - */ - public fun cov(tensors: List>): Tensor - //For information: https://pytorch.org/docs/stable/generated/torch.exp.html public fun Tensor.exp(): Tensor diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt index c1694644f..78989f1f3 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt @@ -629,7 +629,15 @@ public open class DoubleTensorAlgebra : return ((x - x.mean()) * (y - y.mean())).mean() * n / (n - 1) } - override fun cov(tensors: List>): DoubleTensor { + /** + * Returns the covariance matrix M of given vectors. + * + * M[i, j] contains covariance of i-th and j-th given vectors + * + * @param tensors the [List] of 1-dimensional tensors with same shape + * @return the covariance matrix + */ + public fun cov(tensors: List>): DoubleTensor { check(tensors.isNotEmpty()) { "List must have at least 1 element" } val n = tensors.size val m = tensors[0].shape[0] From c2047474016f8c7de92b83f741c7bb00630cc1a9 Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Thu, 13 May 2021 22:44:33 +0300 Subject: [PATCH 024/132] Reusing of existing power function --- .../kmath/benchmarks/BigIntBenchmark.kt | 4 +- .../kscience/kmath/operations/Algebra.kt | 20 ---------- .../space/kscience/kmath/operations/BigInt.kt | 6 +-- .../kmath/operations/algebraExtensions.kt | 39 ++++++++++++------- .../kmath/operations/BigIntAlgebraTest.kt | 8 +--- .../kmath/operations/DoubleFieldTest.kt | 12 ++++++ 6 files changed, 41 insertions(+), 48 deletions(-) diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt index 21b097609..749cd5e75 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt @@ -21,7 +21,7 @@ internal class BigIntBenchmark { val kmNumber = BigIntField.number(Int.MAX_VALUE) val jvmNumber = JBigIntegerField.number(Int.MAX_VALUE) - val largeKmNumber = BigIntField { number(11).pow(100_000UL) } + val largeKmNumber = BigIntField { number(11).pow(100_000U) } val largeJvmNumber: BigInteger = JBigIntegerField { number(11).pow(100_000) } val bigExponent = 50_000 @@ -67,7 +67,7 @@ internal class BigIntBenchmark { @Benchmark fun kmPower(blackhole: Blackhole) = BigIntField { - blackhole.consume(kmNumber.pow(bigExponent.toULong())) + blackhole.consume(kmNumber.pow(bigExponent.toUInt())) } @Benchmark diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index 8881ae93c..b444ed964 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -253,26 +253,6 @@ public interface Ring : Group, RingOperations { public val one: T } -@UnstableKMathAPI -public fun Ring.pow(base: T, exponent: ULong): T = when { - this == zero && exponent > 0UL -> zero - this == one -> base - this == -one -> powWithoutOptimization(base, exponent % 2UL) - else -> powWithoutOptimization(base, exponent) -} - -@UnstableKMathAPI -public fun Ring.pow(base: T, exponent: UInt): T = pow(base, exponent.toULong()) - -private fun Ring.powWithoutOptimization(base: T, exponent: ULong): T = when (exponent) { - 0UL -> one - 1UL -> base - else -> { - val pre = powWithoutOptimization(base, exponent shr 1).let { it * it } - if (exponent and 1UL == 0UL) pre else pre * base - } -} - /** * Represents field without without multiplicative and additive identities, i.e. algebraic structure with associative, binary, commutative operations * [add] and [multiply]; binary operation [divide] as multiplication of left operand by reciprocal of right one. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 0dcbbe567..924ef07f4 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -98,11 +98,7 @@ public class BigInt internal constructor( else -> BigInt(sign, multiplyMagnitudeByUInt(magnitude, other)) } - @UnstableKMathAPI - public fun pow(other: ULong): BigInt = BigIntField { pow(this@BigInt, other) } - - @UnstableKMathAPI - public fun pow(other: UInt): BigInt = BigIntField { pow(this@BigInt, other) } + public fun pow(exponent: UInt): BigInt = BigIntField.power(this@BigInt, exponent) public operator fun times(other: Int): BigInt = when { other > 0 -> this * kotlin.math.abs(other).toUInt() diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt index b8670553d..9691c9d17 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt @@ -97,34 +97,45 @@ public fun Sequence.averageWith(space: S): T where S : Ring, S : Sc //TODO optimized power operation /** - * Raises [arg] to the natural power [power]. + * Raises [arg] to the non-negative integer power [power]. + * + * Special case: 0 ^ 0 is 1. * * @receiver the algebra to provide multiplication. * @param arg the base. * @param power the exponent. * @return the base raised to the power. + * @author Evgeniy Zhelenskiy */ -public fun Ring.power(arg: T, power: Int): T { - require(power >= 0) { "The power can't be negative." } - require(power != 0 || arg != zero) { "The $zero raised to $power is not defined." } - if (power == 0) return one - var res = arg - repeat(power - 1) { res *= arg } - return res +public fun Ring.power(arg: T, power: UInt): T = when { + this == zero && power > 0U -> zero + this == one -> arg + this == -one -> powWithoutOptimization(arg, power % 2U) + else -> powWithoutOptimization(arg, power) } +private fun Ring.powWithoutOptimization(base: T, exponent: UInt): T = when (exponent) { + 0U -> one + 1U -> base + else -> { + val pre = powWithoutOptimization(base, exponent shr 1).let { it * it } + if (exponent and 1U == 0U) pre else pre * base + } +} + + /** * Raises [arg] to the integer power [power]. * + * Special case: 0 ^ 0 is 1. + * * @receiver the algebra to provide multiplication and division. * @param arg the base. * @param power the exponent. * @return the base raised to the power. - * @author Iaroslav Postovalov + * @author Iaroslav Postovalov, Evgeniy Zhelenskiy */ -public fun Field.power(arg: T, power: Int): T { - require(power != 0 || arg != zero) { "The $zero raised to $power is not defined." } - if (power == 0) return one - if (power < 0) return one / (this as Ring).power(arg, -power) - return (this as Ring).power(arg, power) +public fun Field.power(arg: T, power: Int): T = when { + power < 0 -> one / (this as Ring).power(arg, if (power == Int.MIN_VALUE) Int.MAX_VALUE.toUInt().inc() else (-power).toUInt()) + else -> (this as Ring).power(arg, power.toUInt()) } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt index d3fca4351..0527f5252 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntAlgebraTest.kt @@ -27,18 +27,12 @@ internal class BigIntAlgebraTest { @Test fun testKBigIntegerRingPow() { for (num in -5..5) - for (exponent in 0U..10U) { - assertEquals( - num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), - num.toBigInt().pow(exponent.toULong()), - "$num ^ $exponent" - ) + for (exponent in 0U..10U) assertEquals( num.toDouble().pow(exponent.toInt()).toLong().toBigInt(), num.toBigInt().pow(exponent), "$num ^ $exponent" ) - } } @Test diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/DoubleFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/DoubleFieldTest.kt index c482dc978..7e689d079 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/DoubleFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/DoubleFieldTest.kt @@ -18,4 +18,16 @@ internal class DoubleFieldTest { val sqrt = DoubleField { sqrt(25 * one) } assertEquals(5.0, sqrt) } + + @Test + fun testPow() = DoubleField { + val num = 5 * one + assertEquals(5.0, power(num, 1)) + assertEquals(25.0, power(num, 2)) + assertEquals(1.0, power(num, 0)) + assertEquals(0.2, power(num, -1)) + assertEquals(0.04, power(num, -2)) + assertEquals(0.0, power(num, Int.MIN_VALUE)) + assertEquals(1.0, power(zero, 0)) + } } From bdb9ce6a59bf34b4ff21945f42a05c070752fcf7 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 14 May 2021 09:10:05 +0300 Subject: [PATCH 025/132] fixes to power --- .../kscience/kmath/operations/algebraExtensions.kt | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt index 9691c9d17..338dc6a5c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt @@ -108,9 +108,9 @@ public fun Sequence.averageWith(space: S): T where S : Ring, S : Sc * @author Evgeniy Zhelenskiy */ public fun Ring.power(arg: T, power: UInt): T = when { - this == zero && power > 0U -> zero - this == one -> arg - this == -one -> powWithoutOptimization(arg, power % 2U) + arg == zero && power > 0U -> zero + arg == one -> arg + arg == -one -> powWithoutOptimization(arg, power % 2U) else -> powWithoutOptimization(arg, power) } @@ -135,7 +135,7 @@ private fun Ring.powWithoutOptimization(base: T, exponent: UInt): T = whe * @return the base raised to the power. * @author Iaroslav Postovalov, Evgeniy Zhelenskiy */ -public fun Field.power(arg: T, power: Int): T = when { - power < 0 -> one / (this as Ring).power(arg, if (power == Int.MIN_VALUE) Int.MAX_VALUE.toUInt().inc() else (-power).toUInt()) - else -> (this as Ring).power(arg, power.toUInt()) +public fun Field.power(arg: T, power: UInt): T = when { + power < 0 -> one / (this as Ring).power(arg, power) + else -> (this as Ring).power(arg, power) } From 1b60f71ed0efbba385c3e8b65ab4147deff013db Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 14 May 2021 09:14:48 +0300 Subject: [PATCH 026/132] Revert "fixes to power" This reverts commit bdb9ce6a --- .../kscience/kmath/operations/algebraExtensions.kt | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt index 338dc6a5c..9691c9d17 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt @@ -108,9 +108,9 @@ public fun Sequence.averageWith(space: S): T where S : Ring, S : Sc * @author Evgeniy Zhelenskiy */ public fun Ring.power(arg: T, power: UInt): T = when { - arg == zero && power > 0U -> zero - arg == one -> arg - arg == -one -> powWithoutOptimization(arg, power % 2U) + this == zero && power > 0U -> zero + this == one -> arg + this == -one -> powWithoutOptimization(arg, power % 2U) else -> powWithoutOptimization(arg, power) } @@ -135,7 +135,7 @@ private fun Ring.powWithoutOptimization(base: T, exponent: UInt): T = whe * @return the base raised to the power. * @author Iaroslav Postovalov, Evgeniy Zhelenskiy */ -public fun Field.power(arg: T, power: UInt): T = when { - power < 0 -> one / (this as Ring).power(arg, power) - else -> (this as Ring).power(arg, power) +public fun Field.power(arg: T, power: Int): T = when { + power < 0 -> one / (this as Ring).power(arg, if (power == Int.MIN_VALUE) Int.MAX_VALUE.toUInt().inc() else (-power).toUInt()) + else -> (this as Ring).power(arg, power.toUInt()) } From 1a615c503d4fd337474d761485ecdc285d681c83 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 14 May 2021 09:20:49 +0300 Subject: [PATCH 027/132] re-apply bigint fix --- .../space/kscience/kmath/operations/algebraExtensions.kt | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt index 9691c9d17..830c504f3 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt @@ -108,9 +108,9 @@ public fun Sequence.averageWith(space: S): T where S : Ring, S : Sc * @author Evgeniy Zhelenskiy */ public fun Ring.power(arg: T, power: UInt): T = when { - this == zero && power > 0U -> zero - this == one -> arg - this == -one -> powWithoutOptimization(arg, power % 2U) + arg == zero && power > 0U -> zero + arg == one -> arg + arg == -one -> powWithoutOptimization(arg, power % 2U) else -> powWithoutOptimization(arg, power) } From dc9ec54644c4d7b9675bfd9959ee2e1f84829152 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 14 May 2021 09:32:24 +0300 Subject: [PATCH 028/132] naming fix and doc update --- CHANGELOG.md | 1 + kmath-core/api/kmath-core.api | 3 ++- .../space/kscience/kmath/operations/BigInt.kt | 2 +- .../kmath/operations/algebraExtensions.kt | 22 +++++++++---------- .../kmath/operations/BigIntOperationsTest.kt | 14 +++++++----- .../kmath/operations/DoubleFieldTest.kt | 14 ++++++------ 6 files changed, 30 insertions(+), 26 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 286be25e5..732cc87a2 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -13,6 +13,7 @@ - Extended operations for ND4J fields - Jupyter Notebook integration module (kmath-jupyter) - `@PerformancePitfall` annotation to mark possibly slow API +- BigInt operation performance improvement and fixes by @zhelenskiy (#328) ### Changed - Exponential operations merged with hyperbolic functions diff --git a/kmath-core/api/kmath-core.api b/kmath-core/api/kmath-core.api index 14bc70a2a..7b09b668b 100644 --- a/kmath-core/api/kmath-core.api +++ b/kmath-core/api/kmath-core.api @@ -1020,7 +1020,7 @@ public final class space/kscience/kmath/operations/AlgebraExtensionsKt { public static final fun averageWith (Ljava/lang/Iterable;Lspace/kscience/kmath/operations/Ring;)Ljava/lang/Object; public static final fun averageWith (Lkotlin/sequences/Sequence;Lspace/kscience/kmath/operations/Ring;)Ljava/lang/Object; public static final fun power (Lspace/kscience/kmath/operations/Field;Ljava/lang/Object;I)Ljava/lang/Object; - public static final fun power (Lspace/kscience/kmath/operations/Ring;Ljava/lang/Object;I)Ljava/lang/Object; + public static final fun power-jXDDuk8 (Lspace/kscience/kmath/operations/Ring;Ljava/lang/Object;I)Ljava/lang/Object; public static final fun sum (Lspace/kscience/kmath/operations/Ring;Ljava/lang/Iterable;)Ljava/lang/Object; public static final fun sum (Lspace/kscience/kmath/operations/Ring;Lkotlin/sequences/Sequence;)Ljava/lang/Object; public static final fun sumWith (Ljava/lang/Iterable;Lspace/kscience/kmath/operations/Ring;)Ljava/lang/Object; @@ -1050,6 +1050,7 @@ public final class space/kscience/kmath/operations/BigInt : java/lang/Comparable public final fun modPow (Lspace/kscience/kmath/operations/BigInt;Lspace/kscience/kmath/operations/BigInt;)Lspace/kscience/kmath/operations/BigInt; public final fun or (Lspace/kscience/kmath/operations/BigInt;)Lspace/kscience/kmath/operations/BigInt; public final fun plus (Lspace/kscience/kmath/operations/BigInt;)Lspace/kscience/kmath/operations/BigInt; + public final fun pow-WZ4Q5Ns (I)Lspace/kscience/kmath/operations/BigInt; public final fun rem (I)I public final fun rem (Lspace/kscience/kmath/operations/BigInt;)Lspace/kscience/kmath/operations/BigInt; public final fun shl (I)Lspace/kscience/kmath/operations/BigInt; diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 924ef07f4..ac53c4d5e 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -98,7 +98,7 @@ public class BigInt internal constructor( else -> BigInt(sign, multiplyMagnitudeByUInt(magnitude, other)) } - public fun pow(exponent: UInt): BigInt = BigIntField.power(this@BigInt, exponent) + public fun pow(exponent: UInt): BigInt = BigIntField.power(this, exponent) public operator fun times(other: Int): BigInt = when { other > 0 -> this * kotlin.math.abs(other).toUInt() diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt index 830c504f3..422b1ae1a 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt @@ -97,21 +97,21 @@ public fun Sequence.averageWith(space: S): T where S : Ring, S : Sc //TODO optimized power operation /** - * Raises [arg] to the non-negative integer power [power]. + * Raises [arg] to the non-negative integer power [exponent]. * * Special case: 0 ^ 0 is 1. * * @receiver the algebra to provide multiplication. * @param arg the base. - * @param power the exponent. + * @param exponent the exponent. * @return the base raised to the power. * @author Evgeniy Zhelenskiy */ -public fun Ring.power(arg: T, power: UInt): T = when { - arg == zero && power > 0U -> zero +public fun Ring.power(arg: T, exponent: UInt): T = when { + arg == zero && exponent > 0U -> zero arg == one -> arg - arg == -one -> powWithoutOptimization(arg, power % 2U) - else -> powWithoutOptimization(arg, power) + arg == -one -> powWithoutOptimization(arg, exponent % 2U) + else -> powWithoutOptimization(arg, exponent) } private fun Ring.powWithoutOptimization(base: T, exponent: UInt): T = when (exponent) { @@ -125,17 +125,17 @@ private fun Ring.powWithoutOptimization(base: T, exponent: UInt): T = whe /** - * Raises [arg] to the integer power [power]. + * Raises [arg] to the integer power [exponent]. * * Special case: 0 ^ 0 is 1. * * @receiver the algebra to provide multiplication and division. * @param arg the base. - * @param power the exponent. + * @param exponent the exponent. * @return the base raised to the power. * @author Iaroslav Postovalov, Evgeniy Zhelenskiy */ -public fun Field.power(arg: T, power: Int): T = when { - power < 0 -> one / (this as Ring).power(arg, if (power == Int.MIN_VALUE) Int.MAX_VALUE.toUInt().inc() else (-power).toUInt()) - else -> (this as Ring).power(arg, power.toUInt()) +public fun Field.power(arg: T, exponent: Int): T = when { + exponent < 0 -> one / (this as Ring).power(arg, if (exponent == Int.MIN_VALUE) Int.MAX_VALUE.toUInt().inc() else (-exponent).toUInt()) + else -> (this as Ring).power(arg, exponent.toUInt()) } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntOperationsTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntOperationsTest.kt index 9f35f7a69..26d6af224 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntOperationsTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/BigIntOperationsTest.kt @@ -7,7 +7,10 @@ package space.kscience.kmath.operations import kotlin.random.Random import kotlin.random.nextUInt -import kotlin.test.* +import kotlin.test.Test +import kotlin.test.assertContentEquals +import kotlin.test.assertEquals +import kotlin.test.assertFalse @kotlin.ExperimentalUnsignedTypes class BigIntOperationsTest { @@ -153,14 +156,13 @@ class BigIntOperationsTest { @Test fun testKaratsuba() { + val random = Random(2222) val x = uintArrayOf(12U, 345U) val y = uintArrayOf(6U, 789U) assertContentEquals(BigInt.naiveMultiplyMagnitudes(x, y), BigInt.karatsubaMultiplyMagnitudes(x, y)) - repeat(1000) { - val x1 = UIntArray(Random.nextInt(100, 1000)) { Random.nextUInt() } - val y1 = UIntArray(Random.nextInt(100, 1000)) { Random.nextUInt() } - assertContentEquals(BigInt.naiveMultiplyMagnitudes(x1, y1), BigInt.karatsubaMultiplyMagnitudes(x1, y1)) - } + val x1 = UIntArray(Random.nextInt(100, 1000)) { random.nextUInt() } + val y1 = UIntArray(Random.nextInt(100, 1000)) { random.nextUInt() } + assertContentEquals(BigInt.naiveMultiplyMagnitudes(x1, y1), BigInt.karatsubaMultiplyMagnitudes(x1, y1)) } @Test diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/DoubleFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/DoubleFieldTest.kt index 7e689d079..76171fedd 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/DoubleFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/operations/DoubleFieldTest.kt @@ -22,12 +22,12 @@ internal class DoubleFieldTest { @Test fun testPow() = DoubleField { val num = 5 * one - assertEquals(5.0, power(num, 1)) - assertEquals(25.0, power(num, 2)) - assertEquals(1.0, power(num, 0)) - assertEquals(0.2, power(num, -1)) - assertEquals(0.04, power(num, -2)) - assertEquals(0.0, power(num, Int.MIN_VALUE)) - assertEquals(1.0, power(zero, 0)) + assertEquals(5.0, power(num, 1), 0.01) + assertEquals(25.0, power(num, 2), 0.01) + assertEquals(1.0, power(num, 0), 0.01) + assertEquals(0.2, power(num, -1), 0.01) + assertEquals(0.04, power(num, -2), 0.01) + assertEquals(0.0, power(num, Int.MIN_VALUE), 0.01) + assertEquals(1.0, power(zero, 0), 0.01) } } From cf555bc8ae6a233b33567fb4f95acfcdcb0379bb Mon Sep 17 00:00:00 2001 From: zhelenskiy Date: Fri, 14 May 2021 10:48:57 +0300 Subject: [PATCH 029/132] TODO removed as I already added what neeed --- .../kotlin/space/kscience/kmath/operations/algebraExtensions.kt | 2 -- 1 file changed, 2 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt index 422b1ae1a..7967aeadb 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt @@ -94,8 +94,6 @@ public fun Iterable.averageWith(space: S): T where S : Ring, S : Sc public fun Sequence.averageWith(space: S): T where S : Ring, S : ScaleOperations = space.average(this) -//TODO optimized power operation - /** * Raises [arg] to the non-negative integer power [exponent]. * From 6eb95f26eb68082fcc47462089fdee33a25eeb55 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 14 May 2021 12:11:37 +0300 Subject: [PATCH 030/132] Additional piecewise extension --- .../kotlin/space/kscience/kmath/functions/Piecewise.kt | 9 +++++++++ .../kscience/kmath/interpolation/SplineInterpolator.kt | 8 +++++--- 2 files changed, 14 insertions(+), 3 deletions(-) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt index 6d481e334..dae55502d 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt @@ -79,4 +79,13 @@ public class OrderedPiecewisePolynomial>(delimiter: T) : public fun , C : Ring> PiecewisePolynomial.value(ring: C, arg: T): T? = findPiece(arg)?.value(ring, arg) +/** + * Convert this polynomial to a function returning nullable value (null if argument is outside piecewise range). + */ public fun , C : Ring> PiecewisePolynomial.asFunction(ring: C): (T) -> T? = { value(ring, it) } + +/** + * Convert this polynomial to a function using [defaultValue] for arguments outside the piecewise range. + */ +public fun , C : Ring> PiecewisePolynomial.asFunction(ring: C, defaultValue: T): (T) -> T = + { value(ring, it) ?: defaultValue } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt index f00b66a4c..2d2ff6f26 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt @@ -42,9 +42,11 @@ public class SplineInterpolator>( val g = 2.0 * (points.x[i + 1] - points.x[i - 1]) - h[i - 1] * mu[i - 1] mu[i] = h[i] / g - z[i] = - (3.0 * (points.y[i + 1] * h[i - 1] - points.x[i] * (points.x[i + 1] - points.x[i - 1]) + points.y[i - 1] * h[i]) / (h[i - 1] * h[i]) - - h[i - 1] * z[i - 1]) / g + z[i] = (3.0 * (points.y[i + 1] * h[i - 1] + - points.x[i] * (points.x[i + 1] - points.x[i - 1]) + + points.y[i - 1] * h[i]) / (h[i - 1] * h[i]) + - h[i - 1] * z[i - 1] + ) / g } // cubic spline coefficients -- b is linear, c quadratic, d is cubic (original y's are constants) From fff737768764a4f1fecfe6ad165304be1e036e34 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 14 May 2021 12:42:27 +0300 Subject: [PATCH 031/132] ColumnarData returns nullable column --- CHANGELOG.md | 1 + .../kotlin/space/kscience/kmath/data/ColumnarData.kt | 2 +- .../kotlin/space/kscience/kmath/data/XYColumnarData.kt | 4 ++-- .../kotlin/space/kscience/kmath/data/XYZColumnarData.kt | 4 ++-- 4 files changed, 6 insertions(+), 5 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 732cc87a2..3a5bde44a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -29,6 +29,7 @@ - Separated benchmarks and examples - Rewritten EJML module without ejml-simple - Stability of kmath-ast and kmath-kotilngrad promoted to EXPERIMENTAL. +- ColumnarData returns nullable column ### Deprecated diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt index febf615a8..b1c7cacd3 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt @@ -19,7 +19,7 @@ import space.kscience.kmath.structures.Buffer public interface ColumnarData { public val size: Int - public operator fun get(symbol: Symbol): Buffer + public operator fun get(symbol: Symbol): Buffer? } /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt index 56bb59826..bbd679ce9 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt @@ -27,10 +27,10 @@ public interface XYColumnarData : ColumnarData { */ public val y: Buffer - override fun get(symbol: Symbol): Buffer = when (symbol) { + override fun get(symbol: Symbol): Buffer? = when (symbol) { Symbol.x -> x Symbol.y -> y - else -> error("A column for symbol $symbol not found") + else -> null } } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt index d76a44e9e..3972429a5 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt @@ -17,10 +17,10 @@ import space.kscience.kmath.structures.Buffer public interface XYZColumnarData : XYColumnarData { public val z: Buffer - override fun get(symbol: Symbol): Buffer = when (symbol) { + override fun get(symbol: Symbol): Buffer? = when (symbol) { Symbol.x -> x Symbol.y -> y Symbol.z -> z - else -> error("A column for symbol $symbol not found") + else -> null } } \ No newline at end of file From 42d130f69c866f0d2456cf0698c83dab2e1f6bc7 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 14 May 2021 15:59:17 +0300 Subject: [PATCH 032/132] Build tools update. Cleanup --- build.gradle.kts | 2 +- .../kmath/tensors/DataSetNormalization.kt | 44 +++--- .../tensors/LinearSystemSolvingWithLUP.kt | 134 +++++++++--------- .../kscience/kmath/tensors/NeuralNetwork.kt | 112 +++++++-------- .../space/kscience/kmath/tensors/PCA.kt | 96 ++++++------- .../space/kscience/kmath/data/ColumnarData.kt | 3 + settings.gradle.kts | 2 +- 7 files changed, 191 insertions(+), 202 deletions(-) diff --git a/build.gradle.kts b/build.gradle.kts index 406a46810..e14d303fc 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -15,7 +15,7 @@ allprojects { } group = "space.kscience" - version = "0.3.0-dev-8" + version = "0.3.0-dev-9" } subprojects { diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt index 6fbf16a91..74795cc68 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt @@ -11,36 +11,32 @@ import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra // Dataset normalization -fun main() { +fun main() = BroadcastDoubleTensorAlgebra { // work in context with broadcast methods + // take dataset of 5-element vectors from normal distribution + val dataset = randomNormal(intArrayOf(100, 5)) * 1.5 // all elements from N(0, 1.5) - // work in context with broadcast methods - BroadcastDoubleTensorAlgebra { - // take dataset of 5-element vectors from normal distribution - val dataset = randomNormal(intArrayOf(100, 5)) * 1.5 // all elements from N(0, 1.5) - - dataset += fromArray( - intArrayOf(5), - doubleArrayOf(0.0, 1.0, 1.5, 3.0, 5.0) // rows means - ) + dataset += fromArray( + intArrayOf(5), + doubleArrayOf(0.0, 1.0, 1.5, 3.0, 5.0) // rows means + ) - // find out mean and standard deviation of each column - val mean = dataset.mean(0, false) - val std = dataset.std(0, false) + // find out mean and standard deviation of each column + val mean = dataset.mean(0, false) + val std = dataset.std(0, false) - println("Mean:\n$mean") - println("Standard deviation:\n$std") + println("Mean:\n$mean") + println("Standard deviation:\n$std") - // also we can calculate other statistic as minimum and maximum of rows - println("Minimum:\n${dataset.min(0, false)}") - println("Maximum:\n${dataset.max(0, false)}") + // also we can calculate other statistic as minimum and maximum of rows + println("Minimum:\n${dataset.min(0, false)}") + println("Maximum:\n${dataset.max(0, false)}") - // now we can scale dataset with mean normalization - val datasetScaled = (dataset - mean) / std + // now we can scale dataset with mean normalization + val datasetScaled = (dataset - mean) / std - // find out mean and std of scaled dataset + // find out mean and std of scaled dataset - println("Mean of scaled:\n${datasetScaled.mean(0, false)}") - println("Mean of scaled:\n${datasetScaled.std(0, false)}") - } + println("Mean of scaled:\n${datasetScaled.mean(0, false)}") + println("Mean of scaled:\n${datasetScaled.std(0, false)}") } \ No newline at end of file diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt index 78370b517..6453ca44e 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt @@ -6,92 +6,88 @@ package space.kscience.kmath.tensors import space.kscience.kmath.operations.invoke -import space.kscience.kmath.tensors.core.DoubleTensor import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra +import space.kscience.kmath.tensors.core.DoubleTensor // solving linear system with LUP decomposition -fun main () { +fun main() = BroadcastDoubleTensorAlgebra {// work in context with linear operations - // work in context with linear operations - BroadcastDoubleTensorAlgebra { + // set true value of x + val trueX = fromArray( + intArrayOf(4), + doubleArrayOf(-2.0, 1.5, 6.8, -2.4) + ) - // set true value of x - val trueX = fromArray( - intArrayOf(4), - doubleArrayOf(-2.0, 1.5, 6.8, -2.4) + // and A matrix + val a = fromArray( + intArrayOf(4, 4), + doubleArrayOf( + 0.5, 10.5, 4.5, 1.0, + 8.5, 0.9, 12.8, 0.1, + 5.56, 9.19, 7.62, 5.45, + 1.0, 2.0, -3.0, -2.5 ) + ) - // and A matrix - val a = fromArray( - intArrayOf(4, 4), - doubleArrayOf( - 0.5, 10.5, 4.5, 1.0, - 8.5, 0.9, 12.8, 0.1, - 5.56, 9.19, 7.62, 5.45, - 1.0, 2.0, -3.0, -2.5 - ) - ) + // calculate y value + val b = a dot trueX - // calculate y value - val b = a dot trueX + // check out A and b + println("A:\n$a") + println("b:\n$b") - // check out A and b - println("A:\n$a") - println("b:\n$b") + // solve `Ax = b` system using LUP decomposition - // solve `Ax = b` system using LUP decomposition + // get P, L, U such that PA = LU + val (p, l, u) = a.lu() - // get P, L, U such that PA = LU - val (p, l, u) = a.lu() + // check that P is permutation matrix + println("P:\n$p") + // L is lower triangular matrix and U is upper triangular matrix + println("L:\n$l") + println("U:\n$u") + // and PA = LU + println("PA:\n${p dot a}") + println("LU:\n${l dot u}") - // check that P is permutation matrix - println("P:\n$p") - // L is lower triangular matrix and U is upper triangular matrix - println("L:\n$l") - println("U:\n$u") - // and PA = LU - println("PA:\n${p dot a}") - println("LU:\n${l dot u}") - - /* Ax = b; - PAx = Pb; - LUx = Pb; - let y = Ux, then - Ly = Pb -- this system can be easily solved, since the matrix L is lower triangular; - Ux = y can be solved the same way, since the matrix L is upper triangular - */ + /* Ax = b; + PAx = Pb; + LUx = Pb; + let y = Ux, then + Ly = Pb -- this system can be easily solved, since the matrix L is lower triangular; + Ux = y can be solved the same way, since the matrix L is upper triangular + */ - // this function returns solution x of a system lx = b, l should be lower triangular - fun solveLT(l: DoubleTensor, b: DoubleTensor): DoubleTensor { - val n = l.shape[0] - val x = zeros(intArrayOf(n)) - for (i in 0 until n){ - x[intArrayOf(i)] = (b[intArrayOf(i)] - l[i].dot(x).value()) / l[intArrayOf(i, i)] - } - return x - } - - val y = solveLT(l, p dot b) - - // solveLT(l, b) function can be easily adapted for upper triangular matrix by the permutation matrix revMat - // create it by placing ones on side diagonal - val revMat = u.zeroesLike() - val n = revMat.shape[0] + // this function returns solution x of a system lx = b, l should be lower triangular + fun solveLT(l: DoubleTensor, b: DoubleTensor): DoubleTensor { + val n = l.shape[0] + val x = zeros(intArrayOf(n)) for (i in 0 until n) { - revMat[intArrayOf(i, n - 1 - i)] = 1.0 + x[intArrayOf(i)] = (b[intArrayOf(i)] - l[i].dot(x).value()) / l[intArrayOf(i, i)] } - - // solution of system ux = b, u should be upper triangular - fun solveUT(u: DoubleTensor, b: DoubleTensor): DoubleTensor = revMat dot solveLT( - revMat dot u dot revMat, revMat dot b - ) - - val x = solveUT(u, y) - - println("True x:\n$trueX") - println("x founded with LU method:\n$x") + return x } + + val y = solveLT(l, p dot b) + + // solveLT(l, b) function can be easily adapted for upper triangular matrix by the permutation matrix revMat + // create it by placing ones on side diagonal + val revMat = u.zeroesLike() + val n = revMat.shape[0] + for (i in 0 until n) { + revMat[intArrayOf(i, n - 1 - i)] = 1.0 + } + + // solution of system ux = b, u should be upper triangular + fun solveUT(u: DoubleTensor, b: DoubleTensor): DoubleTensor = revMat dot solveLT( + revMat dot u dot revMat, revMat dot b + ) + + val x = solveUT(u, y) + + println("True x:\n$trueX") + println("x founded with LU method:\n$x") } \ No newline at end of file diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt index 5b3c2e1cd..b262bee02 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt @@ -25,7 +25,7 @@ interface Layer { // activation layer open class Activation( val activation: (DoubleTensor) -> DoubleTensor, - val activationDer: (DoubleTensor) -> DoubleTensor + val activationDer: (DoubleTensor) -> DoubleTensor, ) : Layer { override fun forward(input: DoubleTensor): DoubleTensor { return activation(input) @@ -62,7 +62,7 @@ class Sigmoid : Activation(::sigmoid, ::sigmoidDer) class Dense( private val inputUnits: Int, private val outputUnits: Int, - private val learningRate: Double = 0.1 + private val learningRate: Double = 0.1, ) : Layer { private val weights: DoubleTensor = DoubleTensorAlgebra { @@ -74,8 +74,8 @@ class Dense( private val bias: DoubleTensor = DoubleTensorAlgebra { zeros(intArrayOf(outputUnits)) } - override fun forward(input: DoubleTensor): DoubleTensor { - return BroadcastDoubleTensorAlgebra { (input dot weights) + bias } + override fun forward(input: DoubleTensor): DoubleTensor = BroadcastDoubleTensorAlgebra { + (input dot weights) + bias } override fun backward(input: DoubleTensor, outputError: DoubleTensor): DoubleTensor = DoubleTensorAlgebra { @@ -116,7 +116,7 @@ class NeuralNetwork(private val layers: List) { onesForAnswers[intArrayOf(index, label)] = 1.0 } - val softmaxValue = yPred.exp() / yPred.exp().sum(dim = 1, keepDim = true) + val softmaxValue = yPred.exp() / yPred.exp().sum(dim = 1, keepDim = true) (-onesForAnswers + softmaxValue) / (yPred.shape[0].toDouble()) } @@ -175,67 +175,65 @@ class NeuralNetwork(private val layers: List) { @OptIn(ExperimentalStdlibApi::class) -fun main() { - BroadcastDoubleTensorAlgebra { - val features = 5 - val sampleSize = 250 - val trainSize = 180 - //val testSize = sampleSize - trainSize +fun main() = BroadcastDoubleTensorAlgebra { + val features = 5 + val sampleSize = 250 + val trainSize = 180 + //val testSize = sampleSize - trainSize - // take sample of features from normal distribution - val x = randomNormal(intArrayOf(sampleSize, features), seed) * 2.5 + // take sample of features from normal distribution + val x = randomNormal(intArrayOf(sampleSize, features), seed) * 2.5 - x += fromArray( - intArrayOf(5), - doubleArrayOf(0.0, -1.0, -2.5, -3.0, 5.5) // rows means - ) + x += fromArray( + intArrayOf(5), + doubleArrayOf(0.0, -1.0, -2.5, -3.0, 5.5) // rows means + ) - // define class like '1' if the sum of features > 0 and '0' otherwise - val y = fromArray( - intArrayOf(sampleSize, 1), - DoubleArray(sampleSize) { i -> - if (x[i].sum() > 0.0) { - 1.0 - } else { - 0.0 - } + // define class like '1' if the sum of features > 0 and '0' otherwise + val y = fromArray( + intArrayOf(sampleSize, 1), + DoubleArray(sampleSize) { i -> + if (x[i].sum() > 0.0) { + 1.0 + } else { + 0.0 } - ) - - // split train ans test - val trainIndices = (0 until trainSize).toList().toIntArray() - val testIndices = (trainSize until sampleSize).toList().toIntArray() - - val xTrain = x.rowsByIndices(trainIndices) - val yTrain = y.rowsByIndices(trainIndices) - - val xTest = x.rowsByIndices(testIndices) - val yTest = y.rowsByIndices(testIndices) - - // build model - val layers = buildList { - add(Dense(features, 64)) - add(ReLU()) - add(Dense(64, 16)) - add(ReLU()) - add(Dense(16, 2)) - add(Sigmoid()) } - val model = NeuralNetwork(layers) + ) - // fit it with train data - model.fit(xTrain, yTrain, batchSize = 20, epochs = 10) + // split train ans test + val trainIndices = (0 until trainSize).toList().toIntArray() + val testIndices = (trainSize until sampleSize).toList().toIntArray() - // make prediction - val prediction = model.predict(xTest) + val xTrain = x.rowsByIndices(trainIndices) + val yTrain = y.rowsByIndices(trainIndices) - // process raw prediction via argMax - val predictionLabels = prediction.argMax(1, true) - - // find out accuracy - val acc = accuracy(yTest, predictionLabels) - println("Test accuracy:$acc") + val xTest = x.rowsByIndices(testIndices) + val yTest = y.rowsByIndices(testIndices) + // build model + val layers = buildList { + add(Dense(features, 64)) + add(ReLU()) + add(Dense(64, 16)) + add(ReLU()) + add(Dense(16, 2)) + add(Sigmoid()) } + val model = NeuralNetwork(layers) + + // fit it with train data + model.fit(xTrain, yTrain, batchSize = 20, epochs = 10) + + // make prediction + val prediction = model.predict(xTest) + + // process raw prediction via argMax + val predictionLabels = prediction.argMax(1, true) + + // find out accuracy + val acc = accuracy(yTest, predictionLabels) + println("Test accuracy:$acc") + } diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt index f8ac13d3f..e47b87177 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt @@ -11,68 +11,64 @@ import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra // simple PCA -fun main(){ +fun main() = BroadcastDoubleTensorAlgebra { // work in context with broadcast methods val seed = 100500L - // work in context with broadcast methods - BroadcastDoubleTensorAlgebra { + // assume x is range from 0 until 10 + val x = fromArray( + intArrayOf(10), + (0 until 10).toList().map { it.toDouble() }.toDoubleArray() + ) - // assume x is range from 0 until 10 - val x = fromArray( - intArrayOf(10), - (0 until 10).toList().map { it.toDouble() }.toDoubleArray() - ) + // take y dependent on x with noise + val y = 2.0 * x + (3.0 + x.randomNormalLike(seed) * 1.5) - // take y dependent on x with noise - val y = 2.0 * x + (3.0 + x.randomNormalLike(seed) * 1.5) + println("x:\n$x") + println("y:\n$y") - println("x:\n$x") - println("y:\n$y") + // stack them into single dataset + val dataset = stack(listOf(x, y)).transpose() - // stack them into single dataset - val dataset = stack(listOf(x, y)).transpose() + // normalize both x and y + val xMean = x.mean() + val yMean = y.mean() - // normalize both x and y - val xMean = x.mean() - val yMean = y.mean() + val xStd = x.std() + val yStd = y.std() - val xStd = x.std() - val yStd = y.std() + val xScaled = (x - xMean) / xStd + val yScaled = (y - yMean) / yStd - val xScaled = (x - xMean) / xStd - val yScaled = (y - yMean) / yStd + // save means ans standard deviations for further recovery + val mean = fromArray( + intArrayOf(2), + doubleArrayOf(xMean, yMean) + ) + println("Means:\n$mean") - // save means ans standard deviations for further recovery - val mean = fromArray( - intArrayOf(2), - doubleArrayOf(xMean, yMean) - ) - println("Means:\n$mean") + val std = fromArray( + intArrayOf(2), + doubleArrayOf(xStd, yStd) + ) + println("Standard deviations:\n$std") - val std = fromArray( - intArrayOf(2), - doubleArrayOf(xStd, yStd) - ) - println("Standard deviations:\n$std") + // calculate the covariance matrix of scaled x and y + val covMatrix = cov(listOf(xScaled, yScaled)) + println("Covariance matrix:\n$covMatrix") - // calculate the covariance matrix of scaled x and y - val covMatrix = cov(listOf(xScaled, yScaled)) - println("Covariance matrix:\n$covMatrix") + // and find out eigenvector of it + val (_, evecs) = covMatrix.symEig() + val v = evecs[0] + println("Eigenvector:\n$v") - // and find out eigenvector of it - val (_, evecs) = covMatrix.symEig() - val v = evecs[0] - println("Eigenvector:\n$v") + // reduce dimension of dataset + val datasetReduced = v dot stack(listOf(xScaled, yScaled)) + println("Reduced data:\n$datasetReduced") - // reduce dimension of dataset - val datasetReduced = v dot stack(listOf(xScaled, yScaled)) - println("Reduced data:\n$datasetReduced") - - // we can restore original data from reduced data. - // for example, find 7th element of dataset - val n = 7 - val restored = (datasetReduced[n] dot v.view(intArrayOf(1, 2))) * std + mean - println("Original value:\n${dataset[n]}") - println("Restored value:\n$restored") - } + // we can restore original data from reduced data. + // for example, find 7th element of dataset + val n = 7 + val restored = (datasetReduced[n] dot v.view(intArrayOf(1, 2))) * std + mean + println("Original value:\n${dataset[n]}") + println("Restored value:\n$restored") } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt index b1c7cacd3..f5193ecd2 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt @@ -19,6 +19,9 @@ import space.kscience.kmath.structures.Buffer public interface ColumnarData { public val size: Int + /** + * Provide a column by symbol or null if column with given symbol is not defined + */ public operator fun get(symbol: Symbol): Buffer? } diff --git a/settings.gradle.kts b/settings.gradle.kts index 27e74c902..7ebfe1f59 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -5,7 +5,7 @@ pluginManagement { maven("https://repo.kotlin.link") } - val toolsVersion = "0.9.6" + val toolsVersion = "0.9.7" val kotlinVersion = "1.5.0" plugins { From 6f39b38a7203d7b40d794d1682c1cf18d546defc Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 16 May 2021 13:59:37 +0300 Subject: [PATCH 033/132] Refactor integrator API. --- .../kscience/kmath/functions/integrate.kt | 4 +-- .../kmath/functions/matrixIntegration.kt | 4 +-- .../integration/GaussRuleIntegrator.kt | 2 +- .../kmath/integration/GaussIntegrator.kt | 20 +++++-------- .../kmath/integration/UnivariateIntegrand.kt | 28 +++++++++++-------- .../kmath/integration/GaussIntegralTest.kt | 4 +-- 6 files changed, 28 insertions(+), 34 deletions(-) diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt index 6990e8c8f..73770726b 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt @@ -5,8 +5,6 @@ package space.kscience.kmath.functions -import space.kscience.kmath.integration.integrate -import space.kscience.kmath.integration.value import space.kscience.kmath.operations.DoubleField import kotlin.math.pow @@ -18,5 +16,5 @@ fun main() { val result = DoubleField.integrate(0.0..10.0, function = function) //the value is nullable because in some cases the integration could not succeed - println(result.value) + println(result.valueOrNull) } \ No newline at end of file diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt index 8020df8f6..184672044 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt @@ -5,8 +5,6 @@ package space.kscience.kmath.functions -import space.kscience.kmath.integration.integrate -import space.kscience.kmath.integration.value import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.nd import space.kscience.kmath.operations.DoubleField @@ -27,6 +25,6 @@ fun main(): Unit = DoubleField { val result = integrate(0.0..10.0, function = function) //the value is nullable because in some cases the integration could not succeed - println(result.value) + println(result.valueOrNull) } } \ No newline at end of file diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt index 1c9915563..304fdec8f 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt @@ -78,6 +78,6 @@ public class GaussRuleIntegrator( function: (Double) -> Double, ): Double = GaussRuleIntegrator(numPoints, type).integrate( UnivariateIntegrand(function, IntegrationRange(range)) - ).value!! + ).valueOrNull!! } } \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt index ae82a40be..d6e716371 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt @@ -66,31 +66,25 @@ public class GaussIntegrator( return integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + points.size) } - public companion object { - - } + public companion object } /** - * Integrate [T]-valued univariate function using provided set of [IntegrandFeature] - * Following features are evaluated: + * Create a Gauss-Legendre integrator for this field + * Following integrand features are accepted: * * [GaussIntegratorRuleFactory] - A factory for computing the Gauss integration rule. By default uses [GaussLegendreRuleFactory] * * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. * * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. * * [UnivariateIntegrandRanges] - Set of ranges and number of points per range. Defaults to given [IntegrationRange] and [IntegrandMaxCalls] */ -@UnstableKMathAPI -public fun Field.integrate( - vararg features: IntegrandFeature, - function: (Double) -> T, -): UnivariateIntegrand = GaussIntegrator(this).integrate(UnivariateIntegrand(function, *features)) +public val Field.integrator: GaussIntegrator get() = GaussIntegrator(this) /** - * Use [GaussIntegrator.Companion.integrate] to integrate the function in the current algebra with given [range] and [numPoints] + * Use [integrate] to integrate the function in the current algebra with given [range] and [numPoints] */ @UnstableKMathAPI -public fun Field.integrate( +public fun GaussIntegrator.integrate( range: ClosedRange, order: Int = 10, intervals: Int = 10, @@ -104,7 +98,7 @@ public fun Field.integrate( val ranges = UnivariateIntegrandRanges( (0 until intervals).map { i -> (rangeSize * i)..(rangeSize * (i + 1)) to order } ) - return GaussIntegrator(this).integrate( + return integrate( UnivariateIntegrand( function, IntegrationRange(range), diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index 51ea57a33..3cafc9782 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -35,37 +35,41 @@ public typealias UnivariateIntegrator = Integrator> @JvmInline public value class IntegrationRange(public val range: ClosedRange) : IntegrandFeature -public val UnivariateIntegrand.value: T? get() = getFeature>()?.value +/** + * Value of the integrand if it is present or null + */ +public val UnivariateIntegrand.valueOrNull: T? get() = getFeature>()?.value + +/** + * Value of the integrand or error + */ +public val UnivariateIntegrand.value: T get() = valueOrNull ?: error("No value in the integrand") /** * A shortcut method to integrate a [function] in [range] with additional [features]. * The [function] is placed in the end position to allow passing a lambda. */ @UnstableKMathAPI -public fun UnivariateIntegrator.integrate( +public fun UnivariateIntegrator.integrate( range: ClosedRange, vararg features: IntegrandFeature, - function: (Double) -> Double, -): Double = integrate( - UnivariateIntegrand(function, IntegrationRange(range), *features) -).value ?: error("Unexpected: no value after integration.") + function: (Double) -> T, +): UnivariateIntegrand = integrate(UnivariateIntegrand(function, IntegrationRange(range), *features)) /** * A shortcut method to integrate a [function] in [range] with additional [features]. * The [function] is placed in the end position to allow passing a lambda. */ @UnstableKMathAPI -public fun UnivariateIntegrator.integrate( +public fun UnivariateIntegrator.integrate( range: ClosedRange, featureBuilder: MutableList.() -> Unit = {}, - function: (Double) -> Double, -): Double { + function: (Double) -> T, +): UnivariateIntegrand { //TODO use dedicated feature builder class instead or add extensions to MutableList val features = buildList { featureBuilder() add(IntegrationRange(range)) } - return integrate( - UnivariateIntegrand(function, *features.toTypedArray()) - ).value ?: error("Unexpected: no value after integration.") + return integrate(UnivariateIntegrand(function, *features.toTypedArray())) } diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt index 195711452..b611b3f65 100644 --- a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt @@ -19,7 +19,7 @@ class GaussIntegralTest { val res = DoubleField.integrate(0.0..2 * PI) { x -> sin(x) } - assertEquals(0.0, res.value!!, 1e-2) + assertEquals(0.0, res.valueOrNull!!, 1e-2) } @Test @@ -31,7 +31,7 @@ class GaussIntegralTest { 0.0 } } - assertEquals(20.0, res.value!!, 0.5) + assertEquals(20.0, res.valueOrNull!!, 0.5) } From d1e76175b79bec4e41822cccc596019975e84a89 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 16 May 2021 14:09:21 +0300 Subject: [PATCH 034/132] Refactor integrator API. --- .../kotlin/space/kscience/kmath/functions/integrate.kt | 7 +++++-- .../space/kscience/kmath/functions/matrixIntegration.kt | 7 +++++-- .../kscience/kmath/commons/integration/IntegrationTest.kt | 5 +++-- .../space/kscience/kmath/integration/GaussIntegrator.kt | 6 ++++-- .../space/kscience/kmath/integration/GaussIntegralTest.kt | 4 ++-- 5 files changed, 19 insertions(+), 10 deletions(-) diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt index 73770726b..8d5349bce 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt @@ -5,6 +5,9 @@ package space.kscience.kmath.functions +import space.kscience.kmath.integration.integrate +import space.kscience.kmath.integration.integrator +import space.kscience.kmath.integration.value import space.kscience.kmath.operations.DoubleField import kotlin.math.pow @@ -13,8 +16,8 @@ fun main() { val function: UnivariateFunction = { x -> 3 * x.pow(2) + 2 * x + 1 } //get the result of the integration - val result = DoubleField.integrate(0.0..10.0, function = function) + val result = DoubleField.integrator.integrate(0.0..10.0, function = function) //the value is nullable because in some cases the integration could not succeed - println(result.valueOrNull) + println(result.value) } \ No newline at end of file diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt index 184672044..601a0e3c4 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt @@ -5,6 +5,9 @@ package space.kscience.kmath.functions +import space.kscience.kmath.integration.integrate +import space.kscience.kmath.integration.integrator +import space.kscience.kmath.integration.value import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.nd import space.kscience.kmath.operations.DoubleField @@ -22,9 +25,9 @@ fun main(): Unit = DoubleField { val function: (Double) -> StructureND = { x: Double -> 3 * number(x).pow(2) + 2 * diagonal(x) + 1 } //get the result of the integration - val result = integrate(0.0..10.0, function = function) + val result = integrator.integrate(0.0..10.0, function = function) //the value is nullable because in some cases the integration could not succeed - println(result.valueOrNull) + println(result.value) } } \ No newline at end of file diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt index 97dc94d1d..c5573fef1 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt @@ -7,6 +7,7 @@ package space.kscience.kmath.commons.integration import org.junit.jupiter.api.Test import space.kscience.kmath.integration.integrate +import space.kscience.kmath.integration.value import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.DoubleField.sin import kotlin.math.PI @@ -19,7 +20,7 @@ internal class IntegrationTest { @Test fun simpson() { - val res = CMIntegrator.simpson().integrate(0.0..2 * PI, function = function) + val res = CMIntegrator.simpson().integrate(0.0..2 * PI, function = function).value assertTrue { abs(res) < 1e-3 } } @@ -28,7 +29,7 @@ internal class IntegrationTest { val res = CMIntegrator.simpson().integrate(0.0..PI, { targetRelativeAccuracy = 1e-4 targetAbsoluteAccuracy = 1e-4 - }, function) + }, function).value assertTrue { abs(res - 2) < 1e-3 } assertTrue { abs(res - 2) > 1e-12 } } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt index d6e716371..0038ca0f2 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt @@ -6,7 +6,9 @@ package space.kscience.kmath.integration import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.Field -import space.kscience.kmath.structures.* +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.asBuffer +import space.kscience.kmath.structures.indices /** * Set of univariate integration ranges. First components correspond to ranges themselves, second components to number of @@ -81,7 +83,7 @@ public val Field.integrator: GaussIntegrator get() = GaussIntegrat /** - * Use [integrate] to integrate the function in the current algebra with given [range] and [numPoints] + * Integrate using [intervals] segments with Gauss-Legendre rule of [order] order */ @UnstableKMathAPI public fun GaussIntegrator.integrate( diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt index b611b3f65..1f9f7aedf 100644 --- a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt @@ -16,7 +16,7 @@ import kotlin.test.assertEquals class GaussIntegralTest { @Test fun gaussSin() { - val res = DoubleField.integrate(0.0..2 * PI) { x -> + val res = DoubleField.integrator.integrate(0.0..2 * PI) { x -> sin(x) } assertEquals(0.0, res.valueOrNull!!, 1e-2) @@ -24,7 +24,7 @@ class GaussIntegralTest { @Test fun gaussUniform() { - val res = DoubleField.integrate(0.0..100.0) { x -> + val res = DoubleField.integrator.integrate(0.0..100.0) { x -> if(x in 30.0..50.0){ 1.0 } else { From f86a6130e037cb921713db925b310515338da184 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 16 May 2021 14:20:28 +0300 Subject: [PATCH 035/132] Add opt-in for examples --- examples/build.gradle.kts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/build.gradle.kts b/examples/build.gradle.kts index 1c7caf1b9..90bb935b9 100644 --- a/examples/build.gradle.kts +++ b/examples/build.gradle.kts @@ -57,7 +57,7 @@ kotlin.sourceSets.all { tasks.withType { kotlinOptions{ jvmTarget = "11" - freeCompilerArgs = freeCompilerArgs + "-Xjvm-default=all" + freeCompilerArgs = freeCompilerArgs + "-Xjvm-default=all" + "-Xopt-in=kotlin.RequiresOptIn" } } From eb3a8655fbf229db782be8345cd54413fe305d35 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sat, 15 May 2021 02:23:28 +0700 Subject: [PATCH 036/132] Code generation of EJML linear spaces --- buildSrc/build.gradle.kts | 5 + .../kmath/ejml/codegen/ejmlCodegen.kt | 415 ++++++++ .../kscience/kmath/linear/MatrixFeatures.kt | 17 + kmath-ejml/build.gradle.kts | 22 +- .../kscience/kmath/ejml/EjmlLinearSpace.kt | 223 +--- .../space/kscience/kmath/ejml/EjmlMatrix.kt | 10 - .../space/kscience/kmath/ejml/EjmlVector.kt | 14 +- .../space/kscience/kmath/ejml/_generated.kt | 995 ++++++++++++++++++ .../kscience/kmath/ejml/EjmlVectorTest.kt | 6 +- 9 files changed, 1457 insertions(+), 250 deletions(-) create mode 100644 buildSrc/build.gradle.kts create mode 100644 buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt create mode 100644 kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt diff --git a/buildSrc/build.gradle.kts b/buildSrc/build.gradle.kts new file mode 100644 index 000000000..7ca4df19d --- /dev/null +++ b/buildSrc/build.gradle.kts @@ -0,0 +1,5 @@ +plugins { + `kotlin-dsl` +} + +repositories.mavenCentral() diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt new file mode 100644 index 000000000..e4b157973 --- /dev/null +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt @@ -0,0 +1,415 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +@file:Suppress("KDocUnresolvedReference") + +package space.kscience.kmath.ejml.codegen + +import org.intellij.lang.annotations.Language +import java.io.File + +private fun Appendable.appendEjmlVector(type: String, ejmlMatrixType: String) { + @Language("kotlin") val text = """/** + * [EjmlVector] specialization for [$type]. + */ +public class Ejml${type}Vector(public override val origin: M) : EjmlVector<$type, M>(origin) { + init { + require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } + } + + public override operator fun get(index: Int): $type = origin[0, index] +}""" + appendLine(text) + appendLine() +} + +private fun Appendable.appendEjmlMatrix(type: String, ejmlMatrixType: String) { + val text = """/** + * [EjmlMatrix] specialization for [$type]. + */ +public class Ejml${type}Matrix(public override val origin: M) : EjmlMatrix<$type, M>(origin) { + public override operator fun get(i: Int, j: Int): $type = origin[i, j] +}""" + appendLine(text) + appendLine() +} + +private fun Appendable.appendEjmlLinearSpace( + type: String, + kmathAlgebra: String, + ejmlMatrixParentTypeMatrix: String, + ejmlMatrixType: String, + ejmlMatrixDenseType: String, + ops: String, + denseOps: String, + isDense: Boolean, +) { + @Language("kotlin") val text = """/** + * [EjmlLinearSpace] implementation based on [CommonOps_$ops], [DecompositionFactory_${ops}] operations and + * [${ejmlMatrixType}] matrices. + */ +public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, $ejmlMatrixType>() { + /** + * The [${kmathAlgebra}] reference. + */ + public override val elementAlgebra: $kmathAlgebra get() = $kmathAlgebra + + @Suppress("UNCHECKED_CAST") + public override fun Matrix<${type}>.toEjml(): Ejml${type}Matrix<${ejmlMatrixType}> = when { + this is Ejml${type}Matrix<*> && origin is $ejmlMatrixType -> this as Ejml${type}Matrix<${ejmlMatrixType}> + else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } + } + + @Suppress("UNCHECKED_CAST") + public override fun Point<${type}>.toEjml(): Ejml${type}Vector<${ejmlMatrixType}> = when { + this is Ejml${type}Vector<*> && origin is $ejmlMatrixType -> this as Ejml${type}Vector<${ejmlMatrixType}> + else -> Ejml${type}Vector(${ejmlMatrixType}(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } + }) + } + + public override fun buildMatrix( + rows: Int, + columns: Int, + initializer: ${kmathAlgebra}.(i: Int, j: Int) -> ${type}, + ): Ejml${type}Matrix<${ejmlMatrixType}> = ${ejmlMatrixType}(rows, columns).also { + (0 until rows).forEach { row -> + (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } + } + }.wrapMatrix() + + public override fun buildVector( + size: Int, + initializer: ${kmathAlgebra}.(Int) -> ${type}, + ): Ejml${type}Vector<${ejmlMatrixType}> = Ejml${type}Vector(${ejmlMatrixType}(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } + }) + + private fun T.wrapMatrix() = Ejml${type}Matrix(this) + private fun T.wrapVector() = Ejml${type}Vector(this) + + public override fun Matrix<${type}>.unaryMinus(): Matrix<${type}> = this * elementAlgebra { -one } + + public override fun Matrix<${type}>.dot(other: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { + val out = ${ejmlMatrixType}(1, 1) + CommonOps_${ops}.mult(toEjml().origin, other.toEjml().origin, out) + return out.wrapMatrix() + } + + public override fun Matrix<${type}>.dot(vector: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { + val out = ${ejmlMatrixType}(1, 1) + CommonOps_${ops}.mult(toEjml().origin, vector.toEjml().origin, out) + return out.wrapVector() + } + + public override operator fun Matrix<${type}>.minus(other: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { + val out = ${ejmlMatrixType}(1, 1) + + CommonOps_${ops}.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out,${ + if (isDense) "" else + """ + null, + null,""" + } + ) + + return out.wrapMatrix() + } + + public override operator fun Matrix<${type}>.times(value: ${type}): Ejml${type}Matrix<${ejmlMatrixType}> { + val res = ${ejmlMatrixType}(1, 1) + CommonOps_${ops}.scale(value, toEjml().origin, res) + return res.wrapMatrix() + } + + public override fun Point<${type}>.unaryMinus(): Ejml${type}Vector<${ejmlMatrixType}> { + val res = ${ejmlMatrixType}(1, 1) + CommonOps_${ops}.changeSign(toEjml().origin, res) + return res.wrapVector() + } + + public override fun Matrix<${type}>.plus(other: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { + val out = ${ejmlMatrixType}(1, 1) + + CommonOps_${ops}.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out,${ + if (isDense) "" else + """ + null, + null,""" + } + ) + + return out.wrapMatrix() + } + + public override fun Point<${type}>.plus(other: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { + val out = ${ejmlMatrixType}(1, 1) + + CommonOps_${ops}.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out,${ + if (isDense) "" else + """ + null, + null,""" + } + ) + + return out.wrapVector() + } + + public override fun Point<${type}>.minus(other: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { + val out = ${ejmlMatrixType}(1, 1) + + CommonOps_${ops}.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out,${ + if (isDense) "" else + """ + null, + null,""" + } + ) + + return out.wrapVector() + } + + public override fun ${type}.times(m: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> = m * this + + public override fun Point<${type}>.times(value: ${type}): Ejml${type}Vector<${ejmlMatrixType}> { + val res = ${ejmlMatrixType}(1, 1) + CommonOps_${ops}.scale(value, toEjml().origin, res) + return res.wrapVector() + } + + public override fun ${type}.times(v: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> = v * this + + @UnstableKMathAPI + public override fun getFeature(structure: Matrix<${type}>, type: KClass): F? { + structure.getFeature(type)?.let { return it } + val origin = structure.toEjml().origin + + return when (type) { + ${ + if (isDense) + """ InverseMatrixFeature::class -> object : InverseMatrixFeature<${type}> { + override val inverse: Matrix<${type}> by lazy { + val res = origin.copy() + CommonOps_${ops}.invert(res) + res.wrapMatrix() + } + } + + DeterminantFeature::class -> object : DeterminantFeature<${type}> { + override val determinant: $type by lazy { CommonOps_${ops}.det(origin) } + } + + SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature<${type}> { + private val svd by lazy { + DecompositionFactory_${ops}.svd(origin.numRows, origin.numCols, true, true, false) + .apply { decompose(origin.copy()) } + } + + override val u: Matrix<${type}> by lazy { svd.getU(null, false).wrapMatrix() } + override val s: Matrix<${type}> by lazy { svd.getW(null).wrapMatrix() } + override val v: Matrix<${type}> by lazy { svd.getV(null, false).wrapMatrix() } + override val singularValues: Point<${type}> by lazy { ${type}Buffer(svd.singularValues) } + } + + QRDecompositionFeature::class -> object : QRDecompositionFeature<${type}> { + private val qr by lazy { + DecompositionFactory_${ops}.qr().apply { decompose(origin.copy()) } + } + + override val q: Matrix<${type}> by lazy { + qr.getQ(null, false).wrapMatrix() + OrthogonalFeature + } + + override val r: Matrix<${type}> by lazy { qr.getR(null, false).wrapMatrix() + UFeature } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<${type}> { + override val l: Matrix<${type}> by lazy { + val cholesky = + DecompositionFactory_${ops}.chol(structure.rowNum, true).apply { decompose(origin.copy()) } + + cholesky.getT(null).wrapMatrix() + LFeature + } + } + + LupDecompositionFeature::class -> object : LupDecompositionFeature<${type}> { + private val lup by lazy { + DecompositionFactory_${ops}.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) } + } + + override val l: Matrix<${type}> by lazy { + lup.getLower(null).wrapMatrix() + LFeature + } + + override val u: Matrix<${type}> by lazy { + lup.getUpper(null).wrapMatrix() + UFeature + } + + override val p: Matrix<${type}> by lazy { lup.getRowPivot(null).wrapMatrix() } + }""" else """ QRDecompositionFeature::class -> object : QRDecompositionFeature<$type> { + private val qr by lazy { + DecompositionFactory_${ops}.qr(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val q: Matrix<${type}> by lazy { + qr.getQ(null, false).wrapMatrix() + OrthogonalFeature + } + + override val r: Matrix<${type}> by lazy { qr.getR(null, false).wrapMatrix() + UFeature } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<${type}> { + override val l: Matrix<${type}> by lazy { + val cholesky = + DecompositionFactory_${ops}.cholesky().apply { decompose(origin.copy()) } + + (cholesky.getT(null) as ${ejmlMatrixParentTypeMatrix}).wrapMatrix() + LFeature + } + } + + LUDecompositionFeature::class, DeterminantFeature::class, InverseMatrixFeature::class -> object : + LUDecompositionFeature<${type}>, DeterminantFeature<${type}>, InverseMatrixFeature<${type}> { + private val lu by lazy { + DecompositionFactory_${ops}.lu(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val l: Matrix<${type}> by lazy { + lu.getLower(null).wrapMatrix() + LFeature + } + + override val u: Matrix<${type}> by lazy { + lu.getUpper(null).wrapMatrix() + UFeature + } + + override val inverse: Matrix<${type}> by lazy { + var a = origin + val inverse = ${ejmlMatrixDenseType}(1, 1) + val solver = LinearSolverFactory_${ops}.lu(FillReducing.NONE) + if (solver.modifiesA()) a = a.copy() + val i = CommonOps_${denseOps}.identity(a.numRows) + solver.solve(i, inverse) + inverse.wrapMatrix() + } + + override val determinant: $type by lazy { elementAlgebra.number(lu.computeDeterminant().real) } + }""" + } + + else -> null + }?.let(type::cast) + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p matrix. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix<${type}>, b: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { + val res = ${ejmlMatrixType}(1, 1) + CommonOps_${ops}.solve(${ejmlMatrixType}(a.toEjml().origin), ${ejmlMatrixType}(b.toEjml().origin), res) + return res.wrapMatrix() + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p vector. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix<${type}>, b: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { + val res = ${ejmlMatrixType}(1, 1) + CommonOps_${ops}.solve(${ejmlMatrixType}(a.toEjml().origin), ${ejmlMatrixType}(b.toEjml().origin), res) + return Ejml${type}Vector(res) + } +}""" + appendLine(text) + appendLine() +} + + +/** + * Generates routine EJML classes. + */ +fun ejmlCodegen(outputFile: String): Unit = File(outputFile).run { + parentFile.mkdirs() + + writer().use { + it.appendLine("/*") + it.appendLine(" * Copyright 2018-2021 KMath contributors.") + it.appendLine(" * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.") + it.appendLine(" */") + it.appendLine() + it.appendLine("/* This file is generated with buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt */") + it.appendLine() + it.appendLine("package space.kscience.kmath.ejml") + it.appendLine() + it.appendLine("import org.ejml.data.*") + it.appendLine("import space.kscience.kmath.linear.*") + it.appendLine("import space.kscience.kmath.operations.*") + it.appendLine("import space.kscience.kmath.structures.*") + it.appendLine("import space.kscience.kmath.misc.*") + it.appendLine("import kotlin.reflect.*") + it.appendLine("import org.ejml.dense.row.*") + it.appendLine("import org.ejml.dense.row.factory.*") + it.appendLine("import org.ejml.sparse.*") + it.appendLine("import org.ejml.sparse.csc.*") + it.appendLine("import org.ejml.sparse.csc.factory.*") + it.appendLine("import space.kscience.kmath.nd.*") + it.appendLine("import space.kscience.kmath.linear.Matrix") + it.appendLine() + it.appendEjmlVector("Double", "DMatrix") + it.appendEjmlVector("Float", "FMatrix") + it.appendEjmlMatrix("Double", "DMatrix") + it.appendEjmlMatrix("Float", "FMatrix") + it.appendEjmlLinearSpace("Double", "DoubleField", "DMatrix", "DMatrixRMaj", "DMatrixRMaj", "DDRM", "DDRM", true) + it.appendEjmlLinearSpace("Float", "FloatField", "FMatrix", "FMatrixRMaj", "FMatrixRMaj", "FDRM", "FDRM", true) + + it.appendEjmlLinearSpace( + type = "Double", + kmathAlgebra = "DoubleField", + ejmlMatrixParentTypeMatrix = "DMatrix", + ejmlMatrixType = "DMatrixSparseCSC", + ejmlMatrixDenseType = "DMatrixRMaj", + ops = "DSCC", + denseOps = "DDRM", + isDense = false, + ) + + it.appendEjmlLinearSpace( + type = "Float", + kmathAlgebra = "FloatField", + ejmlMatrixParentTypeMatrix = "FMatrix", + ejmlMatrixType = "FMatrixSparseCSC", + ejmlMatrixDenseType = "FMatrixRMaj", + ops = "FSCC", + denseOps = "FDRM", + isDense = false, + ) + } +} diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt index 4a0ca7dfe..37c93d249 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt @@ -75,6 +75,23 @@ public object LFeature : MatrixFeature */ public object UFeature : MatrixFeature +/** + * Matrices with this feature support LU factorization: *a = [l] · [u]* where *a* is the owning matrix. + * + * @param T the type of matrices' items. + */ +public interface LUDecompositionFeature : MatrixFeature { + /** + * The lower triangular matrix in this decomposition. It may have [LFeature]. + */ + public val l: Matrix + + /** + * The upper triangular matrix in this decomposition. It may have [UFeature]. + */ + public val u: Matrix +} + /** * Matrices with this feature support LU factorization with partial pivoting: *[p] · a = [l] · [u]* where * *a* is the owning matrix. diff --git a/kmath-ejml/build.gradle.kts b/kmath-ejml/build.gradle.kts index c8e2ecd8b..5107cfb68 100644 --- a/kmath-ejml/build.gradle.kts +++ b/kmath-ejml/build.gradle.kts @@ -1,3 +1,5 @@ +import space.kscience.kmath.ejml.codegen.ejmlCodegen + plugins { kotlin("jvm") id("ru.mipt.npm.gradle.common") @@ -5,6 +7,9 @@ plugins { dependencies { api("org.ejml:ejml-ddense:0.40") + api("org.ejml:ejml-fdense:0.40") + api("org.ejml:ejml-dsparse:0.40") + api("org.ejml:ejml-fsparse:0.40") api(project(":kmath-core")) } @@ -14,19 +19,24 @@ readme { feature( id = "ejml-vector", - description = "Point implementations.", ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt" - ) + ) { "Point implementations." } feature( id = "ejml-matrix", - description = "Matrix implementation.", ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt" - ) + ) { "Matrix implementation." } feature( id = "ejml-linear-space", - description = "LinearSpace implementations.", ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt" - ) + ) { "LinearSpace implementations." } +} + +kotlin.sourceSets.main { + val codegen by tasks.creating { + ejmlCodegen(kotlin.srcDirs.first().absolutePath + "/space/kscience/kmath/ejml/_generated.kt") + } + + kotlin.srcDirs(files().builtBy(codegen)) } diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt index 71cae4829..f88e83369 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt @@ -5,19 +5,10 @@ package space.kscience.kmath.ejml -import org.ejml.data.DMatrix -import org.ejml.data.DMatrixD1 -import org.ejml.data.DMatrixRMaj -import org.ejml.dense.row.CommonOps_DDRM -import org.ejml.dense.row.factory.DecompositionFactory_DDRM -import space.kscience.kmath.linear.* -import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.nd.StructureFeature -import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.linear.LinearSpace +import space.kscience.kmath.linear.Matrix +import space.kscience.kmath.linear.Point import space.kscience.kmath.operations.Ring -import space.kscience.kmath.structures.DoubleBuffer -import kotlin.reflect.KClass -import kotlin.reflect.cast /** * [LinearSpace] implementation specialized for a certain EJML type. @@ -27,7 +18,7 @@ import kotlin.reflect.cast * @param M the EJML matrix type. * @author Iaroslav Postovalov */ -public abstract class EjmlLinearSpace, M : org.ejml.data.Matrix> : LinearSpace { +public abstract class EjmlLinearSpace, out M : org.ejml.data.Matrix> : LinearSpace { /** * Converts this matrix to EJML one. */ @@ -46,209 +37,3 @@ public abstract class EjmlLinearSpace, M : org.ejml.dat public abstract override fun buildVector(size: Int, initializer: A.(Int) -> T): EjmlVector } - -/** - * [EjmlLinearSpace] implementation based on [CommonOps_DDRM], [DecompositionFactory_DDRM] operations and - * [DMatrixRMaj] matrices. - * - * @author Iaroslav Postovalov - */ -public object EjmlLinearSpaceDDRM : EjmlLinearSpace() { - /** - * The [DoubleField] reference. - */ - public override val elementAlgebra: DoubleField get() = DoubleField - - @Suppress("UNCHECKED_CAST") - public override fun Matrix.toEjml(): EjmlDoubleMatrix = when { - this is EjmlDoubleMatrix<*> && origin is DMatrixRMaj -> this as EjmlDoubleMatrix - else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } - } - - @Suppress("UNCHECKED_CAST") - public override fun Point.toEjml(): EjmlDoubleVector = when { - this is EjmlDoubleVector<*> && origin is DMatrixRMaj -> this as EjmlDoubleVector - else -> EjmlDoubleVector(DMatrixRMaj(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } - }) - } - - public override fun buildMatrix( - rows: Int, - columns: Int, - initializer: DoubleField.(i: Int, j: Int) -> Double, - ): EjmlDoubleMatrix = EjmlDoubleMatrix(DMatrixRMaj(rows, columns).also { - (0 until rows).forEach { row -> - (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } - } - }) - - public override fun buildVector( - size: Int, - initializer: DoubleField.(Int) -> Double, - ): EjmlDoubleVector = EjmlDoubleVector(DMatrixRMaj(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } - }) - - private fun T.wrapMatrix() = EjmlDoubleMatrix(this) - private fun T.wrapVector() = EjmlDoubleVector(this) - - public override fun Matrix.unaryMinus(): Matrix = this * (-1.0) - - public override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { - val out = DMatrixRMaj(1, 1) - CommonOps_DDRM.mult(toEjml().origin, other.toEjml().origin, out) - return out.wrapMatrix() - } - - public override fun Matrix.dot(vector: Point): EjmlDoubleVector { - val out = DMatrixRMaj(1, 1) - CommonOps_DDRM.mult(toEjml().origin, vector.toEjml().origin, out) - return out.wrapVector() - } - - public override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { - val out = DMatrixRMaj(1, 1) - CommonOps_DDRM.subtract(toEjml().origin, other.toEjml().origin, out) - return out.wrapMatrix() - } - - public override operator fun Matrix.times(value: Double): EjmlDoubleMatrix { - val res = this.toEjml().origin.copy() - CommonOps_DDRM.scale(value, res) - return res.wrapMatrix() - } - - public override fun Point.unaryMinus(): EjmlDoubleVector { - val out = toEjml().origin.copy() - CommonOps_DDRM.changeSign(out) - return out.wrapVector() - } - - public override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { - val out = DMatrixRMaj(1, 1) - CommonOps_DDRM.add(toEjml().origin, other.toEjml().origin, out) - return out.wrapMatrix() - } - - public override fun Point.plus(other: Point): EjmlDoubleVector { - val out = DMatrixRMaj(1, 1) - CommonOps_DDRM.add(toEjml().origin, other.toEjml().origin, out) - return out.wrapVector() - } - - public override fun Point.minus(other: Point): EjmlDoubleVector { - val out = DMatrixRMaj(1, 1) - CommonOps_DDRM.subtract(toEjml().origin, other.toEjml().origin, out) - return out.wrapVector() - } - - public override fun Double.times(m: Matrix): EjmlDoubleMatrix = m * this - - public override fun Point.times(value: Double): EjmlDoubleVector { - val res = this.toEjml().origin.copy() - CommonOps_DDRM.scale(value, res) - return res.wrapVector() - } - - public override fun Double.times(v: Point): EjmlDoubleVector = v * this - - @UnstableKMathAPI - public override fun getFeature(structure: Matrix, type: KClass): F? { - // Return the feature if it is intrinsic to the structure - structure.getFeature(type)?.let { return it } - - val origin = structure.toEjml().origin - - return when (type) { - InverseMatrixFeature::class -> object : InverseMatrixFeature { - override val inverse: Matrix by lazy { - val res = origin.copy() - CommonOps_DDRM.invert(res) - EjmlDoubleMatrix(res) - } - } - - DeterminantFeature::class -> object : DeterminantFeature { - override val determinant: Double by lazy { CommonOps_DDRM.det(DMatrixRMaj(origin)) } - } - - SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature { - private val svd by lazy { - DecompositionFactory_DDRM.svd(origin.numRows, origin.numCols, true, true, false) - .apply { decompose(origin.copy()) } - } - - override val u: Matrix by lazy { EjmlDoubleMatrix(svd.getU(null, false)) } - override val s: Matrix by lazy { EjmlDoubleMatrix(svd.getW(null)) } - override val v: Matrix by lazy { EjmlDoubleMatrix(svd.getV(null, false)) } - override val singularValues: Point by lazy { DoubleBuffer(svd.singularValues) } - } - - QRDecompositionFeature::class -> object : QRDecompositionFeature { - private val qr by lazy { - DecompositionFactory_DDRM.qr().apply { decompose(origin.copy()) } - } - - override val q: Matrix by lazy { - EjmlDoubleMatrix(qr.getQ(null, false)) + OrthogonalFeature - } - - override val r: Matrix by lazy { EjmlDoubleMatrix(qr.getR(null, false)) + UFeature } - } - - CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { - override val l: Matrix by lazy { - val cholesky = - DecompositionFactory_DDRM.chol(structure.rowNum, true).apply { decompose(origin.copy()) } - - EjmlDoubleMatrix(cholesky.getT(null)) + LFeature - } - } - - LupDecompositionFeature::class -> object : LupDecompositionFeature { - private val lup by lazy { - DecompositionFactory_DDRM.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) } - } - - override val l: Matrix by lazy { - EjmlDoubleMatrix(lup.getLower(null)) + LFeature - } - - override val u: Matrix by lazy { - EjmlDoubleMatrix(lup.getUpper(null)) + UFeature - } - - override val p: Matrix by lazy { EjmlDoubleMatrix(lup.getRowPivot(null)) } - } - - else -> null - }?.let(type::cast) - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p matrix. - * @return the solution for 'x' that is n by p. - */ - public fun solve(a: Matrix, b: Matrix): EjmlDoubleMatrix { - val res = DMatrixRMaj(1, 1) - CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res) - return EjmlDoubleMatrix(res) - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p vector. - * @return the solution for 'x' that is n by p. - */ - public fun solve(a: Matrix, b: Point): EjmlDoubleVector { - val res = DMatrixRMaj(1, 1) - CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res) - return EjmlDoubleVector(res) - } -} diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt index 92c4d1cf0..fd43f295c 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt @@ -5,7 +5,6 @@ package space.kscience.kmath.ejml -import org.ejml.data.DMatrix import org.ejml.data.Matrix import space.kscience.kmath.nd.Structure2D @@ -21,12 +20,3 @@ public abstract class EjmlMatrix(public open val origin: M) : public override val rowNum: Int get() = origin.numRows public override val colNum: Int get() = origin.numCols } - -/** - * [EjmlMatrix] specialization for [Double]. - * - * @author Iaroslav Postovalov - */ -public class EjmlDoubleMatrix(public override val origin: M) : EjmlMatrix(origin) { - public override operator fun get(i: Int, j: Int): Double = origin[i, j] -} diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt index 81502d6d0..5d10d1fbb 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt @@ -5,7 +5,6 @@ package space.kscience.kmath.ejml -import org.ejml.data.DMatrixD1 import org.ejml.data.Matrix import space.kscience.kmath.linear.Point @@ -14,12 +13,12 @@ import space.kscience.kmath.linear.Point * * @param T the type of elements contained in the buffer. * @param M the type of EJML matrix. - * @property origin The underlying matrix. + * @property origin The underlying matrix, must have only one row. * @author Iaroslav Postovalov */ public abstract class EjmlVector(public open val origin: M) : Point { public override val size: Int - get() = origin.numRows + get() = origin.numCols public override operator fun iterator(): Iterator = object : Iterator { private var cursor: Int = 0 @@ -34,12 +33,3 @@ public abstract class EjmlVector(public open val origin: public override fun toString(): String = "EjmlVector(origin=$origin)" } - -/** - * [EjmlVector] specialization for [Double]. - * - * @author Iaroslav Postovalov - */ -public class EjmlDoubleVector(public override val origin: M) : EjmlVector(origin) { - public override operator fun get(index: Int): Double = origin[index] -} diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt new file mode 100644 index 000000000..139c55697 --- /dev/null +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt @@ -0,0 +1,995 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +/* This file is generated with buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt */ + +package space.kscience.kmath.ejml + +import org.ejml.data.* +import org.ejml.dense.row.CommonOps_DDRM +import org.ejml.dense.row.CommonOps_FDRM +import org.ejml.dense.row.factory.DecompositionFactory_DDRM +import org.ejml.dense.row.factory.DecompositionFactory_FDRM +import org.ejml.sparse.FillReducing +import org.ejml.sparse.csc.CommonOps_DSCC +import org.ejml.sparse.csc.CommonOps_FSCC +import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC +import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC +import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC +import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC +import space.kscience.kmath.linear.* +import space.kscience.kmath.linear.Matrix +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.nd.StructureFeature +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.FloatField +import space.kscience.kmath.operations.invoke +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.FloatBuffer +import kotlin.reflect.KClass +import kotlin.reflect.cast + +/** + * [EjmlVector] specialization for [Double]. + */ +public class EjmlDoubleVector(public override val origin: M) : EjmlVector(origin) { + init { + require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } + } + + public override operator fun get(index: Int): Double = origin[0, index] +} + +/** + * [EjmlVector] specialization for [Float]. + */ +public class EjmlFloatVector(public override val origin: M) : EjmlVector(origin) { + init { + require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } + } + + public override operator fun get(index: Int): Float = origin[0, index] +} + +/** + * [EjmlMatrix] specialization for [Double]. + */ +public class EjmlDoubleMatrix(public override val origin: M) : EjmlMatrix(origin) { + public override operator fun get(i: Int, j: Int): Double = origin[i, j] +} + +/** + * [EjmlMatrix] specialization for [Float]. + */ +public class EjmlFloatMatrix(public override val origin: M) : EjmlMatrix(origin) { + public override operator fun get(i: Int, j: Int): Float = origin[i, j] +} + +/** + * [EjmlLinearSpace] implementation based on [CommonOps_DDRM], [DecompositionFactory_DDRM] operations and + * [DMatrixRMaj] matrices. + */ +public object EjmlLinearSpaceDDRM : EjmlLinearSpace() { + /** + * The [DoubleField] reference. + */ + public override val elementAlgebra: DoubleField get() = DoubleField + + @Suppress("UNCHECKED_CAST") + public override fun Matrix.toEjml(): EjmlDoubleMatrix = when { + this is EjmlDoubleMatrix<*> && origin is DMatrixRMaj -> this as EjmlDoubleMatrix + else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } + } + + @Suppress("UNCHECKED_CAST") + public override fun Point.toEjml(): EjmlDoubleVector = when { + this is EjmlDoubleVector<*> && origin is DMatrixRMaj -> this as EjmlDoubleVector + else -> EjmlDoubleVector(DMatrixRMaj(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } + }) + } + + public override fun buildMatrix( + rows: Int, + columns: Int, + initializer: DoubleField.(i: Int, j: Int) -> Double, + ): EjmlDoubleMatrix = DMatrixRMaj(rows, columns).also { + (0 until rows).forEach { row -> + (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } + } + }.wrapMatrix() + + public override fun buildVector( + size: Int, + initializer: DoubleField.(Int) -> Double, + ): EjmlDoubleVector = EjmlDoubleVector(DMatrixRMaj(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } + }) + + private fun T.wrapMatrix() = EjmlDoubleMatrix(this) + private fun T.wrapVector() = EjmlDoubleVector(this) + + public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + + public override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixRMaj(1, 1) + CommonOps_DDRM.mult(toEjml().origin, other.toEjml().origin, out) + return out.wrapMatrix() + } + + public override fun Matrix.dot(vector: Point): EjmlDoubleVector { + val out = DMatrixRMaj(1, 1) + CommonOps_DDRM.mult(toEjml().origin, vector.toEjml().origin, out) + return out.wrapVector() + } + + public override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixRMaj(1, 1) + + CommonOps_DDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + ) + + return out.wrapMatrix() + } + + public override operator fun Matrix.times(value: Double): EjmlDoubleMatrix { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.scale(value, toEjml().origin, res) + return res.wrapMatrix() + } + + public override fun Point.unaryMinus(): EjmlDoubleVector { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.changeSign(toEjml().origin, res) + return res.wrapVector() + } + + public override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixRMaj(1, 1) + + CommonOps_DDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + ) + + return out.wrapMatrix() + } + + public override fun Point.plus(other: Point): EjmlDoubleVector { + val out = DMatrixRMaj(1, 1) + + CommonOps_DDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + ) + + return out.wrapVector() + } + + public override fun Point.minus(other: Point): EjmlDoubleVector { + val out = DMatrixRMaj(1, 1) + + CommonOps_DDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + ) + + return out.wrapVector() + } + + public override fun Double.times(m: Matrix): EjmlDoubleMatrix = m * this + + public override fun Point.times(value: Double): EjmlDoubleVector { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.scale(value, toEjml().origin, res) + return res.wrapVector() + } + + public override fun Double.times(v: Point): EjmlDoubleVector = v * this + + @UnstableKMathAPI + public override fun getFeature(structure: Matrix, type: KClass): F? { + structure.getFeature(type)?.let { return it } + val origin = structure.toEjml().origin + + return when (type) { + InverseMatrixFeature::class -> object : InverseMatrixFeature { + override val inverse: Matrix by lazy { + val res = origin.copy() + CommonOps_DDRM.invert(res) + res.wrapMatrix() + } + } + + DeterminantFeature::class -> object : DeterminantFeature { + override val determinant: Double by lazy { CommonOps_DDRM.det(origin) } + } + + SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature { + private val svd by lazy { + DecompositionFactory_DDRM.svd(origin.numRows, origin.numCols, true, true, false) + .apply { decompose(origin.copy()) } + } + + override val u: Matrix by lazy { svd.getU(null, false).wrapMatrix() } + override val s: Matrix by lazy { svd.getW(null).wrapMatrix() } + override val v: Matrix by lazy { svd.getV(null, false).wrapMatrix() } + override val singularValues: Point by lazy { DoubleBuffer(svd.singularValues) } + } + + QRDecompositionFeature::class -> object : QRDecompositionFeature { + private val qr by lazy { + DecompositionFactory_DDRM.qr().apply { decompose(origin.copy()) } + } + + override val q: Matrix by lazy { + qr.getQ(null, false).wrapMatrix() + OrthogonalFeature + } + + override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix() + UFeature } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { + override val l: Matrix by lazy { + val cholesky = + DecompositionFactory_DDRM.chol(structure.rowNum, true).apply { decompose(origin.copy()) } + + cholesky.getT(null).wrapMatrix() + LFeature + } + } + + LupDecompositionFeature::class -> object : LupDecompositionFeature { + private val lup by lazy { + DecompositionFactory_DDRM.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) } + } + + override val l: Matrix by lazy { + lup.getLower(null).wrapMatrix() + LFeature + } + + override val u: Matrix by lazy { + lup.getUpper(null).wrapMatrix() + UFeature + } + + override val p: Matrix by lazy { lup.getRowPivot(null).wrapMatrix() } + } + + else -> null + }?.let(type::cast) + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p matrix. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Matrix): EjmlDoubleMatrix { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res) + return res.wrapMatrix() + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p vector. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Point): EjmlDoubleVector { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res) + return EjmlDoubleVector(res) + } +} + +/** + * [EjmlLinearSpace] implementation based on [CommonOps_FDRM], [DecompositionFactory_FDRM] operations and + * [FMatrixRMaj] matrices. + */ +public object EjmlLinearSpaceFDRM : EjmlLinearSpace() { + /** + * The [FloatField] reference. + */ + public override val elementAlgebra: FloatField get() = FloatField + + @Suppress("UNCHECKED_CAST") + public override fun Matrix.toEjml(): EjmlFloatMatrix = when { + this is EjmlFloatMatrix<*> && origin is FMatrixRMaj -> this as EjmlFloatMatrix + else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } + } + + @Suppress("UNCHECKED_CAST") + public override fun Point.toEjml(): EjmlFloatVector = when { + this is EjmlFloatVector<*> && origin is FMatrixRMaj -> this as EjmlFloatVector + else -> EjmlFloatVector(FMatrixRMaj(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } + }) + } + + public override fun buildMatrix( + rows: Int, + columns: Int, + initializer: FloatField.(i: Int, j: Int) -> Float, + ): EjmlFloatMatrix = FMatrixRMaj(rows, columns).also { + (0 until rows).forEach { row -> + (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } + } + }.wrapMatrix() + + public override fun buildVector( + size: Int, + initializer: FloatField.(Int) -> Float, + ): EjmlFloatVector = EjmlFloatVector(FMatrixRMaj(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } + }) + + private fun T.wrapMatrix() = EjmlFloatMatrix(this) + private fun T.wrapVector() = EjmlFloatVector(this) + + public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + + public override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { + val out = FMatrixRMaj(1, 1) + CommonOps_FDRM.mult(toEjml().origin, other.toEjml().origin, out) + return out.wrapMatrix() + } + + public override fun Matrix.dot(vector: Point): EjmlFloatVector { + val out = FMatrixRMaj(1, 1) + CommonOps_FDRM.mult(toEjml().origin, vector.toEjml().origin, out) + return out.wrapVector() + } + + public override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { + val out = FMatrixRMaj(1, 1) + + CommonOps_FDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + ) + + return out.wrapMatrix() + } + + public override operator fun Matrix.times(value: Float): EjmlFloatMatrix { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.scale(value, toEjml().origin, res) + return res.wrapMatrix() + } + + public override fun Point.unaryMinus(): EjmlFloatVector { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.changeSign(toEjml().origin, res) + return res.wrapVector() + } + + public override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { + val out = FMatrixRMaj(1, 1) + + CommonOps_FDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + ) + + return out.wrapMatrix() + } + + public override fun Point.plus(other: Point): EjmlFloatVector { + val out = FMatrixRMaj(1, 1) + + CommonOps_FDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + ) + + return out.wrapVector() + } + + public override fun Point.minus(other: Point): EjmlFloatVector { + val out = FMatrixRMaj(1, 1) + + CommonOps_FDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + ) + + return out.wrapVector() + } + + public override fun Float.times(m: Matrix): EjmlFloatMatrix = m * this + + public override fun Point.times(value: Float): EjmlFloatVector { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.scale(value, toEjml().origin, res) + return res.wrapVector() + } + + public override fun Float.times(v: Point): EjmlFloatVector = v * this + + @UnstableKMathAPI + public override fun getFeature(structure: Matrix, type: KClass): F? { + structure.getFeature(type)?.let { return it } + val origin = structure.toEjml().origin + + return when (type) { + InverseMatrixFeature::class -> object : InverseMatrixFeature { + override val inverse: Matrix by lazy { + val res = origin.copy() + CommonOps_FDRM.invert(res) + res.wrapMatrix() + } + } + + DeterminantFeature::class -> object : DeterminantFeature { + override val determinant: Float by lazy { CommonOps_FDRM.det(origin) } + } + + SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature { + private val svd by lazy { + DecompositionFactory_FDRM.svd(origin.numRows, origin.numCols, true, true, false) + .apply { decompose(origin.copy()) } + } + + override val u: Matrix by lazy { svd.getU(null, false).wrapMatrix() } + override val s: Matrix by lazy { svd.getW(null).wrapMatrix() } + override val v: Matrix by lazy { svd.getV(null, false).wrapMatrix() } + override val singularValues: Point by lazy { FloatBuffer(svd.singularValues) } + } + + QRDecompositionFeature::class -> object : QRDecompositionFeature { + private val qr by lazy { + DecompositionFactory_FDRM.qr().apply { decompose(origin.copy()) } + } + + override val q: Matrix by lazy { + qr.getQ(null, false).wrapMatrix() + OrthogonalFeature + } + + override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix() + UFeature } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { + override val l: Matrix by lazy { + val cholesky = + DecompositionFactory_FDRM.chol(structure.rowNum, true).apply { decompose(origin.copy()) } + + cholesky.getT(null).wrapMatrix() + LFeature + } + } + + LupDecompositionFeature::class -> object : LupDecompositionFeature { + private val lup by lazy { + DecompositionFactory_FDRM.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) } + } + + override val l: Matrix by lazy { + lup.getLower(null).wrapMatrix() + LFeature + } + + override val u: Matrix by lazy { + lup.getUpper(null).wrapMatrix() + UFeature + } + + override val p: Matrix by lazy { lup.getRowPivot(null).wrapMatrix() } + } + + else -> null + }?.let(type::cast) + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p matrix. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Matrix): EjmlFloatMatrix { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.solve(FMatrixRMaj(a.toEjml().origin), FMatrixRMaj(b.toEjml().origin), res) + return res.wrapMatrix() + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p vector. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Point): EjmlFloatVector { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.solve(FMatrixRMaj(a.toEjml().origin), FMatrixRMaj(b.toEjml().origin), res) + return EjmlFloatVector(res) + } +} + +/** + * [EjmlLinearSpace] implementation based on [CommonOps_DSCC], [DecompositionFactory_DSCC] operations and + * [DMatrixSparseCSC] matrices. + */ +public object EjmlLinearSpaceDSCC : EjmlLinearSpace() { + /** + * The [DoubleField] reference. + */ + public override val elementAlgebra: DoubleField get() = DoubleField + + @Suppress("UNCHECKED_CAST") + public override fun Matrix.toEjml(): EjmlDoubleMatrix = when { + this is EjmlDoubleMatrix<*> && origin is DMatrixSparseCSC -> this as EjmlDoubleMatrix + else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } + } + + @Suppress("UNCHECKED_CAST") + public override fun Point.toEjml(): EjmlDoubleVector = when { + this is EjmlDoubleVector<*> && origin is DMatrixSparseCSC -> this as EjmlDoubleVector + else -> EjmlDoubleVector(DMatrixSparseCSC(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } + }) + } + + public override fun buildMatrix( + rows: Int, + columns: Int, + initializer: DoubleField.(i: Int, j: Int) -> Double, + ): EjmlDoubleMatrix = DMatrixSparseCSC(rows, columns).also { + (0 until rows).forEach { row -> + (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } + } + }.wrapMatrix() + + public override fun buildVector( + size: Int, + initializer: DoubleField.(Int) -> Double, + ): EjmlDoubleVector = EjmlDoubleVector(DMatrixSparseCSC(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } + }) + + private fun T.wrapMatrix() = EjmlDoubleMatrix(this) + private fun T.wrapVector() = EjmlDoubleVector(this) + + public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + + public override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.mult(toEjml().origin, other.toEjml().origin, out) + return out.wrapMatrix() + } + + public override fun Matrix.dot(vector: Point): EjmlDoubleVector { + val out = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.mult(toEjml().origin, vector.toEjml().origin, out) + return out.wrapVector() + } + + public override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixSparseCSC(1, 1) + + CommonOps_DSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapMatrix() + } + + public override operator fun Matrix.times(value: Double): EjmlDoubleMatrix { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.scale(value, toEjml().origin, res) + return res.wrapMatrix() + } + + public override fun Point.unaryMinus(): EjmlDoubleVector { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.changeSign(toEjml().origin, res) + return res.wrapVector() + } + + public override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixSparseCSC(1, 1) + + CommonOps_DSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapMatrix() + } + + public override fun Point.plus(other: Point): EjmlDoubleVector { + val out = DMatrixSparseCSC(1, 1) + + CommonOps_DSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapVector() + } + + public override fun Point.minus(other: Point): EjmlDoubleVector { + val out = DMatrixSparseCSC(1, 1) + + CommonOps_DSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapVector() + } + + public override fun Double.times(m: Matrix): EjmlDoubleMatrix = m * this + + public override fun Point.times(value: Double): EjmlDoubleVector { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.scale(value, toEjml().origin, res) + return res.wrapVector() + } + + public override fun Double.times(v: Point): EjmlDoubleVector = v * this + + @UnstableKMathAPI + public override fun getFeature(structure: Matrix, type: KClass): F? { + structure.getFeature(type)?.let { return it } + val origin = structure.toEjml().origin + + return when (type) { + QRDecompositionFeature::class -> object : QRDecompositionFeature { + private val qr by lazy { + DecompositionFactory_DSCC.qr(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val q: Matrix by lazy { + qr.getQ(null, false).wrapMatrix() + OrthogonalFeature + } + + override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix() + UFeature } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { + override val l: Matrix by lazy { + val cholesky = + DecompositionFactory_DSCC.cholesky().apply { decompose(origin.copy()) } + + (cholesky.getT(null) as DMatrix).wrapMatrix() + LFeature + } + } + + LUDecompositionFeature::class, DeterminantFeature::class, InverseMatrixFeature::class -> object : + LUDecompositionFeature, DeterminantFeature, InverseMatrixFeature { + private val lu by lazy { + DecompositionFactory_DSCC.lu(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val l: Matrix by lazy { + lu.getLower(null).wrapMatrix() + LFeature + } + + override val u: Matrix by lazy { + lu.getUpper(null).wrapMatrix() + UFeature + } + + override val inverse: Matrix by lazy { + var a = origin + val inverse = DMatrixRMaj(1, 1) + val solver = LinearSolverFactory_DSCC.lu(FillReducing.NONE) + if (solver.modifiesA()) a = a.copy() + val i = CommonOps_DDRM.identity(a.numRows) + solver.solve(i, inverse) + inverse.wrapMatrix() + } + + override val determinant: Double by lazy { elementAlgebra.number(lu.computeDeterminant().real) } + } + + else -> null + }?.let(type::cast) + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p matrix. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Matrix): EjmlDoubleMatrix { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.solve(DMatrixSparseCSC(a.toEjml().origin), DMatrixSparseCSC(b.toEjml().origin), res) + return res.wrapMatrix() + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p vector. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Point): EjmlDoubleVector { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.solve(DMatrixSparseCSC(a.toEjml().origin), DMatrixSparseCSC(b.toEjml().origin), res) + return EjmlDoubleVector(res) + } +} + +/** + * [EjmlLinearSpace] implementation based on [CommonOps_FSCC], [DecompositionFactory_FSCC] operations and + * [FMatrixSparseCSC] matrices. + */ +public object EjmlLinearSpaceFSCC : EjmlLinearSpace() { + /** + * The [FloatField] reference. + */ + public override val elementAlgebra: FloatField get() = FloatField + + @Suppress("UNCHECKED_CAST") + public override fun Matrix.toEjml(): EjmlFloatMatrix = when { + this is EjmlFloatMatrix<*> && origin is FMatrixSparseCSC -> this as EjmlFloatMatrix + else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } + } + + @Suppress("UNCHECKED_CAST") + public override fun Point.toEjml(): EjmlFloatVector = when { + this is EjmlFloatVector<*> && origin is FMatrixSparseCSC -> this as EjmlFloatVector + else -> EjmlFloatVector(FMatrixSparseCSC(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } + }) + } + + public override fun buildMatrix( + rows: Int, + columns: Int, + initializer: FloatField.(i: Int, j: Int) -> Float, + ): EjmlFloatMatrix = FMatrixSparseCSC(rows, columns).also { + (0 until rows).forEach { row -> + (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } + } + }.wrapMatrix() + + public override fun buildVector( + size: Int, + initializer: FloatField.(Int) -> Float, + ): EjmlFloatVector = EjmlFloatVector(FMatrixSparseCSC(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } + }) + + private fun T.wrapMatrix() = EjmlFloatMatrix(this) + private fun T.wrapVector() = EjmlFloatVector(this) + + public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + + public override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { + val out = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.mult(toEjml().origin, other.toEjml().origin, out) + return out.wrapMatrix() + } + + public override fun Matrix.dot(vector: Point): EjmlFloatVector { + val out = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.mult(toEjml().origin, vector.toEjml().origin, out) + return out.wrapVector() + } + + public override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { + val out = FMatrixSparseCSC(1, 1) + + CommonOps_FSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapMatrix() + } + + public override operator fun Matrix.times(value: Float): EjmlFloatMatrix { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.scale(value, toEjml().origin, res) + return res.wrapMatrix() + } + + public override fun Point.unaryMinus(): EjmlFloatVector { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.changeSign(toEjml().origin, res) + return res.wrapVector() + } + + public override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { + val out = FMatrixSparseCSC(1, 1) + + CommonOps_FSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapMatrix() + } + + public override fun Point.plus(other: Point): EjmlFloatVector { + val out = FMatrixSparseCSC(1, 1) + + CommonOps_FSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapVector() + } + + public override fun Point.minus(other: Point): EjmlFloatVector { + val out = FMatrixSparseCSC(1, 1) + + CommonOps_FSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapVector() + } + + public override fun Float.times(m: Matrix): EjmlFloatMatrix = m * this + + public override fun Point.times(value: Float): EjmlFloatVector { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.scale(value, toEjml().origin, res) + return res.wrapVector() + } + + public override fun Float.times(v: Point): EjmlFloatVector = v * this + + @UnstableKMathAPI + public override fun getFeature(structure: Matrix, type: KClass): F? { + structure.getFeature(type)?.let { return it } + val origin = structure.toEjml().origin + + return when (type) { + QRDecompositionFeature::class -> object : QRDecompositionFeature { + private val qr by lazy { + DecompositionFactory_FSCC.qr(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val q: Matrix by lazy { + qr.getQ(null, false).wrapMatrix() + OrthogonalFeature + } + + override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix() + UFeature } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { + override val l: Matrix by lazy { + val cholesky = + DecompositionFactory_FSCC.cholesky().apply { decompose(origin.copy()) } + + (cholesky.getT(null) as FMatrix).wrapMatrix() + LFeature + } + } + + LUDecompositionFeature::class, DeterminantFeature::class, InverseMatrixFeature::class -> object : + LUDecompositionFeature, DeterminantFeature, InverseMatrixFeature { + private val lu by lazy { + DecompositionFactory_FSCC.lu(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val l: Matrix by lazy { + lu.getLower(null).wrapMatrix() + LFeature + } + + override val u: Matrix by lazy { + lu.getUpper(null).wrapMatrix() + UFeature + } + + override val inverse: Matrix by lazy { + var a = origin + val inverse = FMatrixRMaj(1, 1) + val solver = LinearSolverFactory_FSCC.lu(FillReducing.NONE) + if (solver.modifiesA()) a = a.copy() + val i = CommonOps_FDRM.identity(a.numRows) + solver.solve(i, inverse) + inverse.wrapMatrix() + } + + override val determinant: Float by lazy { elementAlgebra.number(lu.computeDeterminant().real) } + } + + else -> null + }?.let(type::cast) + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p matrix. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Matrix): EjmlFloatMatrix { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.solve(FMatrixSparseCSC(a.toEjml().origin), FMatrixSparseCSC(b.toEjml().origin), res) + return res.wrapMatrix() + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p vector. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Point): EjmlFloatVector { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.solve(FMatrixSparseCSC(a.toEjml().origin), FMatrixSparseCSC(b.toEjml().origin), res) + return EjmlFloatVector(res) + } +} + diff --git a/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlVectorTest.kt b/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlVectorTest.kt index 9bf76033d..9592bfa6c 100644 --- a/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlVectorTest.kt +++ b/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlVectorTest.kt @@ -18,7 +18,7 @@ internal class EjmlVectorTest { private val randomMatrix: DMatrixRMaj get() { - val d = DMatrixRMaj(random.nextInt(2, 100), 1) + val d = DMatrixRMaj(1, random.nextInt(2, 100)) RandomMatrices_DDRM.fillUniform(d, random.asJavaRandom()) return d } @@ -27,7 +27,7 @@ internal class EjmlVectorTest { fun size() { val m = randomMatrix val w = EjmlDoubleVector(m) - assertEquals(m.numRows, w.size) + assertEquals(m.numCols, w.size) } @Test @@ -43,7 +43,7 @@ internal class EjmlVectorTest { val w = EjmlDoubleVector(m) assertEquals( - m.iterator(true, 0, 0, m.numRows - 1, 0).asSequence().toList(), + m.iterator(true, 0, 0, 0, m.numCols - 1).asSequence().toList(), w.iterator().asSequence().toList() ) } From 15d874fb06c355cfcd3e611b534ae32ba8682a2b Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 16 May 2021 19:53:21 +0300 Subject: [PATCH 037/132] Remove MST.Symbolic Replace it by Symbol LogicAlgebra --- CHANGELOG.md | 1 + .../ExpressionsInterpretersBenchmark.kt | 2 - .../space/kscience/kmath/ast/expressions.kt | 2 +- .../kscience/kmath/ast/kotlingradSupport.kt | 2 +- .../kmath/commons/fit/fitWithAutoDiff.kt | 2 +- .../kotlin/space/kscience/kmath/ast/parser.kt | 3 +- .../kscience/kmath/ast/rendering/features.kt | 8 +- .../TestCompilerConsistencyWithInterpreter.kt | 2 +- .../kmath/ast/TestCompilerOperations.kt | 12 +- .../kmath/ast/TestCompilerVariables.kt | 2 +- .../kotlin/space/kscience/kmath/ast/utils.kt | 2 +- .../space/kscience/kmath/estree/estree.kt | 9 +- .../kmath/estree/internal/ESTreeBuilder.kt | 7 +- .../kmath/wasm/internal/WasmBuilder.kt | 16 +-- .../kotlin/space/kscience/kmath/wasm/wasm.kt | 2 +- .../kscience/kmath/ast/TestExecutionTime.kt | 1 - .../kotlin/space/kscience/kmath/ast/utils.kt | 2 +- .../kscience/kmath/wasm/TestWasmSpecific.kt | 2 +- .../kotlin/space/kscience/kmath/asm/asm.kt | 9 +- .../kmath/asm/internal/mapIntrinsics.kt | 4 +- .../kotlin/space/kscience/kmath/ast/utils.kt | 2 +- .../DerivativeStructureExpression.kt | 1 - .../commons/optimization/CMOptimization.kt | 14 +- .../kmath/commons/optimization/cmFit.kt | 2 +- .../DerivativeStructureExpressionTest.kt | 6 +- .../commons/optimization/OptimizeTest.kt | 2 +- .../complex/ExpressionFieldForComplexTest.kt | 2 +- kmath-core/api/kmath-core.api | 130 +++++++++--------- .../space/kscience/kmath/data/ColumnarData.kt | 2 +- .../kscience/kmath/data/XYColumnarData.kt | 2 +- .../kscience/kmath/data/XYZColumnarData.kt | 2 +- .../expressions/DifferentiableExpression.kt | 3 - .../kscience/kmath/expressions/Expression.kt | 2 - .../FunctionalExpressionAlgebra.kt | 1 - .../space/kscience/kmath/expressions/MST.kt | 19 +-- .../kscience/kmath/expressions/MstAlgebra.kt | 42 ++++-- .../kmath/expressions/SimpleAutoDiff.kt | 1 - .../kmath/{misc => expressions}/Symbol.kt | 7 +- .../kmath/expressions/SymbolIndexer.kt | 1 - .../kscience/kmath/operations/Algebra.kt | 3 +- .../kscience/kmath/operations/LogicAlgebra.kt | 71 ++++++++++ .../kmath/expressions/ExpressionFieldTest.kt | 1 - .../kmath/expressions/InterpretTest.kt | 1 - .../kmath/expressions/SimpleAutoDiffTest.kt | 2 - .../kotlingrad/DifferentiableMstExpression.kt | 10 +- .../kmath/kotlingrad/ScalarsAdapters.kt | 11 +- .../kmath/kotlingrad/AdaptingTests.kt | 12 +- .../optimization/FunctionOptimization.kt | 6 +- .../NoDerivFunctionOptimization.kt | 2 +- .../kmath/optimization/Optimization.kt | 2 +- .../kscience/kmath/optimization/XYFit.kt | 6 +- 51 files changed, 254 insertions(+), 204 deletions(-) rename kmath-core/src/commonMain/kotlin/space/kscience/kmath/{misc => expressions}/Symbol.kt (91%) create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt diff --git a/CHANGELOG.md b/CHANGELOG.md index 3a5bde44a..e9a67a0ab 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -30,6 +30,7 @@ - Rewritten EJML module without ejml-simple - Stability of kmath-ast and kmath-kotilngrad promoted to EXPERIMENTAL. - ColumnarData returns nullable column +- Replaced MST.Symbolic by Symbol. Symbol now inherits MST ### Deprecated diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt index 942fba308..15cd14399 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt @@ -11,8 +11,6 @@ import kotlinx.benchmark.Scope import kotlinx.benchmark.State import space.kscience.kmath.asm.compileToExpression import space.kscience.kmath.expressions.* -import space.kscience.kmath.misc.Symbol -import space.kscience.kmath.misc.symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke diff --git a/examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt b/examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt index 918134e04..d5a82590f 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt @@ -6,8 +6,8 @@ package space.kscience.kmath.ast import space.kscience.kmath.expressions.MstField +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.interpret -import space.kscience.kmath.misc.Symbol.Companion.x import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke diff --git a/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt b/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt index 25f42f5a9..420b23f9f 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt @@ -8,8 +8,8 @@ package space.kscience.kmath.ast import space.kscience.kmath.asm.compileToExpression import space.kscience.kmath.expressions.derivative import space.kscience.kmath.expressions.invoke +import space.kscience.kmath.expressions.symbol import space.kscience.kmath.kotlingrad.toDiffExpression -import space.kscience.kmath.misc.symbol import space.kscience.kmath.operations.DoubleField /** diff --git a/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt b/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt index 028985260..5e64235e3 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt @@ -10,7 +10,7 @@ import kotlinx.html.h3 import space.kscience.kmath.commons.optimization.chiSquared import space.kscience.kmath.commons.optimization.minimize import space.kscience.kmath.distributions.NormalDistribution -import space.kscience.kmath.misc.symbol +import space.kscience.kmath.expressions.symbol import space.kscience.kmath.optimization.FunctionOptimization import space.kscience.kmath.optimization.OptimizationResult import space.kscience.kmath.real.DoubleVector diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt index 246625d29..5201fec38 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt @@ -17,6 +17,7 @@ import com.github.h0tk3y.betterParse.lexer.regexToken import com.github.h0tk3y.betterParse.parser.ParseResult import com.github.h0tk3y.betterParse.parser.Parser import space.kscience.kmath.expressions.MST +import space.kscience.kmath.expressions.StringSymbol import space.kscience.kmath.operations.FieldOperations import space.kscience.kmath.operations.GroupOperations import space.kscience.kmath.operations.PowerOperations @@ -42,7 +43,7 @@ public object ArithmeticsEvaluator : Grammar() { private val ws: Token by regexToken("\\s+".toRegex(), ignore = true) private val number: Parser by num use { MST.Numeric(text.toDouble()) } - private val singular: Parser by id use { MST.Symbolic(text) } + private val singular: Parser by id use { StringSymbol(text) } private val unaryFunction: Parser by (id and -lpar and parser(ArithmeticsEvaluator::subSumChain) and -rpar) .map { (id, term) -> MST.Unary(id.text, term) } diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt index ac716f9ff..863825799 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt @@ -7,6 +7,7 @@ package space.kscience.kmath.ast.rendering import space.kscience.kmath.ast.rendering.FeaturedMathRenderer.RenderFeature import space.kscience.kmath.expressions.MST +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.* import kotlin.reflect.KClass @@ -19,9 +20,8 @@ import kotlin.reflect.KClass @UnstableKMathAPI public object PrintSymbolic : RenderFeature { public override fun render(renderer: FeaturedMathRenderer, node: MST): SymbolSyntax? = - if (node !is MST.Symbolic) null - else - SymbolSyntax(string = node.value) + if (node !is Symbol) null + else SymbolSyntax(string = node.identity) } /** @@ -142,7 +142,7 @@ public class PrettyPrintIntegers(public val types: Set>) : Re @UnstableKMathAPI public class PrettyPrintPi(public val symbols: Set) : RenderFeature { public override fun render(renderer: FeaturedMathRenderer, node: MST): SpecialSymbolSyntax? = - if (node !is MST.Symbolic || node.value !in symbols) + if (node !is Symbol || node.identity !in symbols) null else SpecialSymbolSyntax(kind = SpecialSymbolSyntax.Kind.SMALL_PI) diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt index 0d018070c..6209661b3 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt @@ -7,8 +7,8 @@ package space.kscience.kmath.ast import space.kscience.kmath.expressions.MstField import space.kscience.kmath.expressions.MstRing +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.interpret -import space.kscience.kmath.misc.Symbol.Companion.x import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing import space.kscience.kmath.operations.bindSymbol diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt index 7d2af31c2..073a03f14 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt @@ -6,8 +6,8 @@ package space.kscience.kmath.ast import space.kscience.kmath.expressions.MstExtendedField +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.misc.Symbol.Companion.x import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke @@ -17,31 +17,31 @@ import kotlin.test.assertEquals internal class TestCompilerOperations { @Test fun testUnaryPlus() = runCompilerTest { - val expr = MstExtendedField { +bindSymbol(x) }.compileToExpression(DoubleField) + val expr = MstExtendedField { +x }.compileToExpression(DoubleField) assertEquals(2.0, expr(x to 2.0)) } @Test fun testUnaryMinus() = runCompilerTest { - val expr = MstExtendedField { -bindSymbol(x) }.compileToExpression(DoubleField) + val expr = MstExtendedField { -x }.compileToExpression(DoubleField) assertEquals(-2.0, expr(x to 2.0)) } @Test fun testAdd() = runCompilerTest { - val expr = MstExtendedField { bindSymbol(x) + bindSymbol(x) }.compileToExpression(DoubleField) + val expr = MstExtendedField { x + x }.compileToExpression(DoubleField) assertEquals(4.0, expr(x to 2.0)) } @Test fun testSine() = runCompilerTest { - val expr = MstExtendedField { sin(bindSymbol(x)) }.compileToExpression(DoubleField) + val expr = MstExtendedField { sin(x) }.compileToExpression(DoubleField) assertEquals(0.0, expr(x to 0.0)) } @Test fun testCosine() = runCompilerTest { - val expr = MstExtendedField { cos(bindSymbol(x)) }.compileToExpression(DoubleField) + val expr = MstExtendedField { cos(x) }.compileToExpression(DoubleField) assertEquals(1.0, expr(x to 0.0)) } diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt index ecf8ed367..dcc15b311 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt @@ -6,8 +6,8 @@ package space.kscience.kmath.ast import space.kscience.kmath.expressions.MstRing +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.misc.Symbol.Companion.x import space.kscience.kmath.operations.IntRing import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/utils.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/utils.kt index abeaed0f8..ec7436188 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/utils.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/utils.kt @@ -7,7 +7,7 @@ package space.kscience.kmath.ast import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.MST -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing diff --git a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt index 40468f5ab..0c15e994c 100644 --- a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt +++ b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt @@ -9,22 +9,23 @@ import space.kscience.kmath.estree.internal.ESTreeBuilder import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.MST import space.kscience.kmath.expressions.MST.* +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.expressions.invoke import space.kscience.kmath.internal.estree.BaseExpression -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.operations.Algebra import space.kscience.kmath.operations.NumericAlgebra +import space.kscience.kmath.operations.bindSymbolOrNull @PublishedApi internal fun MST.compileWith(algebra: Algebra): Expression { fun ESTreeBuilder.visit(node: MST): BaseExpression = when (node) { - is Symbolic -> { - val symbol = algebra.bindSymbolOrNull(node.value) + is Symbol -> { + val symbol = algebra.bindSymbolOrNull(node) if (symbol != null) constant(symbol) else - variable(node.value) + variable(node.identity) } is Numeric -> constant(node.value) diff --git a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/ESTreeBuilder.kt b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/ESTreeBuilder.kt index ac20484a4..4907d8225 100644 --- a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/ESTreeBuilder.kt +++ b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/ESTreeBuilder.kt @@ -6,14 +6,9 @@ package space.kscience.kmath.estree.internal import space.kscience.kmath.expressions.Expression +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.internal.astring.generate import space.kscience.kmath.internal.estree.* -import space.kscience.kmath.internal.estree.BaseExpression -import space.kscience.kmath.internal.estree.BlockStatement -import space.kscience.kmath.internal.estree.Program -import space.kscience.kmath.internal.estree.VariableDeclaration -import space.kscience.kmath.internal.estree.VariableDeclarator -import space.kscience.kmath.misc.Symbol internal class ESTreeBuilder(val bodyCallback: ESTreeBuilder.() -> BaseExpression) { private class GeneratedExpression(val executable: dynamic, val constants: Array) : Expression { diff --git a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt index 8fd3c9fb9..95ace1bad 100644 --- a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt +++ b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt @@ -8,9 +8,9 @@ package space.kscience.kmath.wasm.internal import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.MST import space.kscience.kmath.expressions.MST.* +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.internal.binaryen.* import space.kscience.kmath.internal.webassembly.Instance -import space.kscience.kmath.misc.StringSymbol import space.kscience.kmath.operations.* import space.kscience.kmath.internal.binaryen.Module as BinaryenModule import space.kscience.kmath.internal.webassembly.Module as WasmModule @@ -23,20 +23,20 @@ internal sealed class WasmBuilder( val algebra: Algebra, val target: MST, ) where T : Number { - val keys: MutableList = mutableListOf() + val keys: MutableList = mutableListOf() lateinit var ctx: BinaryenModule - open fun visitSymbolic(mst: Symbolic): ExpressionRef { + open fun visitSymbolic(mst: Symbol): ExpressionRef { try { - algebra.bindSymbol(mst.value) + algebra.bindSymbol(mst) } catch (ignored: Throwable) { null }?.let { return visitNumeric(Numeric(it)) } - var idx = keys.indexOf(mst.value) + var idx = keys.indexOf(mst) if (idx == -1) { - keys += mst.value + keys += mst idx = keys.lastIndex } @@ -54,7 +54,7 @@ internal sealed class WasmBuilder( open fun createModule(): BinaryenModule = js("new \$module\$binaryen.Module()") fun visit(mst: MST): ExpressionRef = when (mst) { - is Symbolic -> visitSymbolic(mst) + is Symbol -> visitSymbolic(mst) is Numeric -> visitNumeric(mst) is Unary -> when { @@ -96,7 +96,7 @@ internal sealed class WasmBuilder( }) val i = Instance(c, js("{}") as Any) - val symbols = keys.map(::StringSymbol) + val symbols = keys keys.clear() Expression { args -> diff --git a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/wasm.kt b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/wasm.kt index 394a0567e..6ea8f26c1 100644 --- a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/wasm.kt +++ b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/wasm.kt @@ -8,8 +8,8 @@ package space.kscience.kmath.wasm import space.kscience.kmath.estree.compileWith import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.MST +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing diff --git a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt index 01746ddb6..6cb378182 100644 --- a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt +++ b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt @@ -6,7 +6,6 @@ package space.kscience.kmath.ast import space.kscience.kmath.expressions.* -import space.kscience.kmath.misc.symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.bindSymbol diff --git a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt index 6b5b1b83d..93b7e9449 100644 --- a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt +++ b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt @@ -7,7 +7,7 @@ package space.kscience.kmath.ast import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.MST -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing import space.kscience.kmath.estree.compile as estreeCompile diff --git a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt index dd5452d04..abdf865c7 100644 --- a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt +++ b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt @@ -8,7 +8,7 @@ package space.kscience.kmath.wasm import space.kscience.kmath.expressions.MstExtendedField import space.kscience.kmath.expressions.MstRing import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.misc.symbol +import space.kscience.kmath.expressions.symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing import space.kscience.kmath.operations.bindSymbol diff --git a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt index dbce893d1..4147324ee 100644 --- a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt +++ b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt @@ -10,10 +10,11 @@ import space.kscience.kmath.asm.internal.buildName import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.MST import space.kscience.kmath.expressions.MST.* +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.operations.Algebra import space.kscience.kmath.operations.NumericAlgebra +import space.kscience.kmath.operations.bindSymbolOrNull /** * Compiles given MST to an Expression using AST compiler. @@ -26,13 +27,13 @@ import space.kscience.kmath.operations.NumericAlgebra @PublishedApi internal fun MST.compileWith(type: Class, algebra: Algebra): Expression { fun AsmBuilder.visit(node: MST): Unit = when (node) { - is Symbolic -> { - val symbol = algebra.bindSymbolOrNull(node.value) + is Symbol -> { + val symbol = algebra.bindSymbolOrNull(node) if (symbol != null) loadObjectConstant(symbol as Any) else - loadVariable(node.value) + loadVariable(node.identity) } is Numeric -> loadNumberConstant(node.value) diff --git a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt index dc8f19fb6..8f4daecf9 100644 --- a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt +++ b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt @@ -7,8 +7,8 @@ package space.kscience.kmath.asm.internal -import space.kscience.kmath.misc.StringSymbol -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.StringSymbol +import space.kscience.kmath.expressions.Symbol /** * Gets value with given [key] or throws [NoSuchElementException] whenever it is not present. diff --git a/kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt b/kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt index 607c5fdd6..d3b554efd 100644 --- a/kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt +++ b/kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt @@ -7,7 +7,7 @@ package space.kscience.kmath.ast import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.MST -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing import space.kscience.kmath.asm.compile as asmCompile diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt index 736685789..89e216601 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt @@ -7,7 +7,6 @@ package space.kscience.kmath.commons.expressions import org.apache.commons.math3.analysis.differentiation.DerivativeStructure import space.kscience.kmath.expressions.* -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.NumbersAddOperations diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt index cfb8c39be..bca00de46 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt @@ -14,13 +14,17 @@ import org.apache.commons.math3.optim.nonlinear.scalar.gradient.NonLinearConjuga import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.AbstractSimplex import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.NelderMeadSimplex import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.SimplexOptimizer -import space.kscience.kmath.expressions.DifferentiableExpression -import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.expressions.SymbolIndexer -import space.kscience.kmath.expressions.derivative -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.* import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.optimization.* +import kotlin.collections.HashMap +import kotlin.collections.List +import kotlin.collections.Map +import kotlin.collections.set +import kotlin.collections.setOf +import kotlin.collections.toList +import kotlin.collections.toMap +import kotlin.collections.toTypedArray import kotlin.reflect.KClass public operator fun PointValuePair.component1(): DoubleArray = point diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt index 13b5c73f4..a5a913623 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt @@ -9,7 +9,7 @@ import org.apache.commons.math3.analysis.differentiation.DerivativeStructure import space.kscience.kmath.commons.expressions.DerivativeStructureField import space.kscience.kmath.expressions.DifferentiableExpression import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.optimization.FunctionOptimization import space.kscience.kmath.optimization.OptimizationResult import space.kscience.kmath.optimization.noDerivOptimizeWith diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt index 879cd75b1..966675062 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt @@ -5,11 +5,7 @@ package space.kscience.kmath.commons.expressions -import space.kscience.kmath.expressions.binding -import space.kscience.kmath.expressions.derivative -import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.misc.Symbol -import space.kscience.kmath.misc.symbol +import space.kscience.kmath.expressions.* import kotlin.contracts.InvocationKind import kotlin.contracts.contract import kotlin.test.Test diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt index 716cd1b0f..15c9120ec 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt @@ -8,7 +8,7 @@ package space.kscience.kmath.commons.optimization import kotlinx.coroutines.runBlocking import space.kscience.kmath.commons.expressions.DerivativeStructureExpression import space.kscience.kmath.distributions.NormalDistribution -import space.kscience.kmath.misc.symbol +import space.kscience.kmath.expressions.symbol import space.kscience.kmath.optimization.FunctionOptimization import space.kscience.kmath.stat.RandomGenerator import kotlin.math.pow diff --git a/kmath-complex/src/commonTest/kotlin/space/kscience/kmath/complex/ExpressionFieldForComplexTest.kt b/kmath-complex/src/commonTest/kotlin/space/kscience/kmath/complex/ExpressionFieldForComplexTest.kt index e023fcb81..4279471d4 100644 --- a/kmath-complex/src/commonTest/kotlin/space/kscience/kmath/complex/ExpressionFieldForComplexTest.kt +++ b/kmath-complex/src/commonTest/kotlin/space/kscience/kmath/complex/ExpressionFieldForComplexTest.kt @@ -7,7 +7,7 @@ package space.kscience.kmath.complex import space.kscience.kmath.expressions.FunctionalExpressionField import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.misc.symbol +import space.kscience.kmath.expressions.symbol import space.kscience.kmath.operations.bindSymbol import kotlin.test.Test import kotlin.test.assertEquals diff --git a/kmath-core/api/kmath-core.api b/kmath-core/api/kmath-core.api index 7b09b668b..ead4b96b5 100644 --- a/kmath-core/api/kmath-core.api +++ b/kmath-core/api/kmath-core.api @@ -21,7 +21,7 @@ public class space/kscience/kmath/expressions/AutoDiffValue { public final class space/kscience/kmath/expressions/DerivationResult { public fun (Ljava/lang/Object;Ljava/util/Map;Lspace/kscience/kmath/operations/Field;)V - public final fun derivative (Lspace/kscience/kmath/misc/Symbol;)Ljava/lang/Object; + public final fun derivative (Lspace/kscience/kmath/expressions/Symbol;)Ljava/lang/Object; public final fun div ()Ljava/lang/Object; public final fun getContext ()Lspace/kscience/kmath/operations/Field; public final fun getValue ()Ljava/lang/Object; @@ -34,7 +34,7 @@ public abstract interface class space/kscience/kmath/expressions/DifferentiableE public final class space/kscience/kmath/expressions/DifferentiableExpressionKt { public static final fun derivative (Lspace/kscience/kmath/expressions/DifferentiableExpression;Ljava/lang/String;)Lspace/kscience/kmath/expressions/Expression; public static final fun derivative (Lspace/kscience/kmath/expressions/DifferentiableExpression;Ljava/util/List;)Lspace/kscience/kmath/expressions/Expression; - public static final fun derivative (Lspace/kscience/kmath/expressions/DifferentiableExpression;[Lspace/kscience/kmath/misc/Symbol;)Lspace/kscience/kmath/expressions/Expression; + public static final fun derivative (Lspace/kscience/kmath/expressions/DifferentiableExpression;[Lspace/kscience/kmath/expressions/Symbol;)Lspace/kscience/kmath/expressions/Expression; } public abstract interface class space/kscience/kmath/expressions/Expression { @@ -55,7 +55,7 @@ public final class space/kscience/kmath/expressions/ExpressionKt { public abstract class space/kscience/kmath/expressions/FirstDerivativeExpression : space/kscience/kmath/expressions/DifferentiableExpression { public fun ()V public final fun derivativeOrNull (Ljava/util/List;)Lspace/kscience/kmath/expressions/Expression; - public abstract fun derivativeOrNull (Lspace/kscience/kmath/misc/Symbol;)Lspace/kscience/kmath/expressions/Expression; + public abstract fun derivativeOrNull (Lspace/kscience/kmath/expressions/Symbol;)Lspace/kscience/kmath/expressions/Expression; } public abstract class space/kscience/kmath/expressions/FunctionalExpressionAlgebra : space/kscience/kmath/expressions/ExpressionAlgebra { @@ -146,7 +146,7 @@ public class space/kscience/kmath/expressions/FunctionalExpressionRing : space/k public fun unaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function1; } -public abstract class space/kscience/kmath/expressions/MST { +public abstract interface class space/kscience/kmath/expressions/MST { } public final class space/kscience/kmath/expressions/MST$Binary : space/kscience/kmath/expressions/MST { @@ -175,17 +175,6 @@ public final class space/kscience/kmath/expressions/MST$Numeric : space/kscience public fun toString ()Ljava/lang/String; } -public final class space/kscience/kmath/expressions/MST$Symbolic : space/kscience/kmath/expressions/MST { - public fun (Ljava/lang/String;)V - public final fun component1 ()Ljava/lang/String; - public final fun copy (Ljava/lang/String;)Lspace/kscience/kmath/expressions/MST$Symbolic; - public static synthetic fun copy$default (Lspace/kscience/kmath/expressions/MST$Symbolic;Ljava/lang/String;ILjava/lang/Object;)Lspace/kscience/kmath/expressions/MST$Symbolic; - public fun equals (Ljava/lang/Object;)Z - public final fun getValue ()Ljava/lang/String; - public fun hashCode ()I - public fun toString ()Ljava/lang/String; -} - public final class space/kscience/kmath/expressions/MST$Unary : space/kscience/kmath/expressions/MST { public fun (Ljava/lang/String;Lspace/kscience/kmath/expressions/MST;)V public final fun component1 ()Ljava/lang/String; @@ -206,18 +195,6 @@ public final class space/kscience/kmath/expressions/MSTKt { public static final fun toExpression (Lspace/kscience/kmath/expressions/MST;Lspace/kscience/kmath/operations/Algebra;)Lspace/kscience/kmath/expressions/Expression; } -public final class space/kscience/kmath/expressions/MstAlgebra : space/kscience/kmath/operations/NumericAlgebra { - public static final field INSTANCE Lspace/kscience/kmath/expressions/MstAlgebra; - public fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2; - public synthetic fun bindSymbol (Ljava/lang/String;)Ljava/lang/Object; - public fun bindSymbol (Ljava/lang/String;)Lspace/kscience/kmath/expressions/MST$Symbolic; - public synthetic fun bindSymbolOrNull (Ljava/lang/String;)Ljava/lang/Object; - public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/MST$Symbolic; - public synthetic fun number (Ljava/lang/Number;)Ljava/lang/Object; - public fun number (Ljava/lang/Number;)Lspace/kscience/kmath/expressions/MST$Numeric; - public fun unaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function1; -} - public final class space/kscience/kmath/expressions/MstExtendedField : space/kscience/kmath/operations/ExtendedField, space/kscience/kmath/operations/NumericAlgebra { public static final field INSTANCE Lspace/kscience/kmath/expressions/MstExtendedField; public synthetic fun acos (Ljava/lang/Object;)Ljava/lang/Object; @@ -236,7 +213,7 @@ public final class space/kscience/kmath/expressions/MstExtendedField : space/ksc public fun atanh (Lspace/kscience/kmath/expressions/MST;)Lspace/kscience/kmath/expressions/MST$Unary; public fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2; public synthetic fun bindSymbolOrNull (Ljava/lang/String;)Ljava/lang/Object; - public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/MST$Symbolic; + public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/Symbol; public synthetic fun cos (Ljava/lang/Object;)Ljava/lang/Object; public fun cos (Lspace/kscience/kmath/expressions/MST;)Lspace/kscience/kmath/expressions/MST$Unary; public synthetic fun cosh (Ljava/lang/Object;)Ljava/lang/Object; @@ -284,7 +261,7 @@ public final class space/kscience/kmath/expressions/MstField : space/kscience/km public fun add (Lspace/kscience/kmath/expressions/MST;Lspace/kscience/kmath/expressions/MST;)Lspace/kscience/kmath/expressions/MST$Binary; public fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2; public synthetic fun bindSymbolOrNull (Ljava/lang/String;)Ljava/lang/Object; - public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/MST$Symbolic; + public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/Symbol; public synthetic fun divide (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object; public fun divide (Lspace/kscience/kmath/expressions/MST;Lspace/kscience/kmath/expressions/MST;)Lspace/kscience/kmath/expressions/MST$Binary; public synthetic fun getOne ()Ljava/lang/Object; @@ -312,7 +289,7 @@ public final class space/kscience/kmath/expressions/MstGroup : space/kscience/km public fun add (Lspace/kscience/kmath/expressions/MST;Lspace/kscience/kmath/expressions/MST;)Lspace/kscience/kmath/expressions/MST$Binary; public fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2; public synthetic fun bindSymbolOrNull (Ljava/lang/String;)Ljava/lang/Object; - public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/MST$Symbolic; + public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/Symbol; public synthetic fun getZero ()Ljava/lang/Object; public fun getZero ()Lspace/kscience/kmath/expressions/MST$Numeric; public synthetic fun minus (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object; @@ -328,13 +305,25 @@ public final class space/kscience/kmath/expressions/MstGroup : space/kscience/km public fun unaryPlus (Lspace/kscience/kmath/expressions/MST;)Lspace/kscience/kmath/expressions/MST$Unary; } +public final class space/kscience/kmath/expressions/MstNumericAlgebra : space/kscience/kmath/operations/NumericAlgebra { + public static final field INSTANCE Lspace/kscience/kmath/expressions/MstNumericAlgebra; + public fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2; + public synthetic fun bindSymbol (Ljava/lang/String;)Ljava/lang/Object; + public fun bindSymbol (Ljava/lang/String;)Lspace/kscience/kmath/expressions/Symbol; + public synthetic fun bindSymbolOrNull (Ljava/lang/String;)Ljava/lang/Object; + public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/Symbol; + public synthetic fun number (Ljava/lang/Number;)Ljava/lang/Object; + public fun number (Ljava/lang/Number;)Lspace/kscience/kmath/expressions/MST$Numeric; + public fun unaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function1; +} + public final class space/kscience/kmath/expressions/MstRing : space/kscience/kmath/operations/NumbersAddOperations, space/kscience/kmath/operations/Ring, space/kscience/kmath/operations/ScaleOperations { public static final field INSTANCE Lspace/kscience/kmath/expressions/MstRing; public synthetic fun add (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object; public fun add (Lspace/kscience/kmath/expressions/MST;Lspace/kscience/kmath/expressions/MST;)Lspace/kscience/kmath/expressions/MST$Binary; public fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2; public synthetic fun bindSymbolOrNull (Ljava/lang/String;)Ljava/lang/Object; - public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/MST$Symbolic; + public fun bindSymbolOrNull (Ljava/lang/String;)Lspace/kscience/kmath/expressions/Symbol; public synthetic fun getOne ()Ljava/lang/Object; public fun getOne ()Lspace/kscience/kmath/expressions/MST$Numeric; public synthetic fun getZero ()Ljava/lang/Object; @@ -356,7 +345,7 @@ public final class space/kscience/kmath/expressions/MstRing : space/kscience/kma public final class space/kscience/kmath/expressions/SimpleAutoDiffExpression : space/kscience/kmath/expressions/FirstDerivativeExpression { public fun (Lspace/kscience/kmath/operations/Field;Lkotlin/jvm/functions/Function1;)V - public fun derivativeOrNull (Lspace/kscience/kmath/misc/Symbol;)Lspace/kscience/kmath/expressions/Expression; + public fun derivativeOrNull (Lspace/kscience/kmath/expressions/Symbol;)Lspace/kscience/kmath/expressions/Expression; public final fun getField ()Lspace/kscience/kmath/operations/Field; public final fun getFunction ()Lkotlin/jvm/functions/Function1; public fun invoke (Ljava/util/Map;)Ljava/lang/Object; @@ -445,7 +434,7 @@ public final class space/kscience/kmath/expressions/SimpleAutoDiffKt { public static final fun cos (Lspace/kscience/kmath/expressions/SimpleAutoDiffField;Lspace/kscience/kmath/expressions/AutoDiffValue;)Lspace/kscience/kmath/expressions/AutoDiffValue; public static final fun cosh (Lspace/kscience/kmath/expressions/SimpleAutoDiffField;Lspace/kscience/kmath/expressions/AutoDiffValue;)Lspace/kscience/kmath/expressions/AutoDiffValue; public static final fun exp (Lspace/kscience/kmath/expressions/SimpleAutoDiffField;Lspace/kscience/kmath/expressions/AutoDiffValue;)Lspace/kscience/kmath/expressions/AutoDiffValue; - public static final fun grad (Lspace/kscience/kmath/expressions/DerivationResult;[Lspace/kscience/kmath/misc/Symbol;)Lspace/kscience/kmath/structures/Buffer; + public static final fun grad (Lspace/kscience/kmath/expressions/DerivationResult;[Lspace/kscience/kmath/expressions/Symbol;)Lspace/kscience/kmath/structures/Buffer; public static final fun ln (Lspace/kscience/kmath/expressions/SimpleAutoDiffField;Lspace/kscience/kmath/expressions/AutoDiffValue;)Lspace/kscience/kmath/expressions/AutoDiffValue; public static final fun pow (Lspace/kscience/kmath/expressions/SimpleAutoDiffField;Lspace/kscience/kmath/expressions/AutoDiffValue;D)Lspace/kscience/kmath/expressions/AutoDiffValue; public static final fun pow (Lspace/kscience/kmath/expressions/SimpleAutoDiffField;Lspace/kscience/kmath/expressions/AutoDiffValue;I)Lspace/kscience/kmath/expressions/AutoDiffValue; @@ -461,9 +450,42 @@ public final class space/kscience/kmath/expressions/SimpleAutoDiffKt { public static final fun tanh (Lspace/kscience/kmath/expressions/SimpleAutoDiffField;Lspace/kscience/kmath/expressions/AutoDiffValue;)Lspace/kscience/kmath/expressions/AutoDiffValue; } +public final class space/kscience/kmath/expressions/StringSymbol : space/kscience/kmath/expressions/Symbol { + public static final synthetic fun box-impl (Ljava/lang/String;)Lspace/kscience/kmath/expressions/StringSymbol; + public static fun constructor-impl (Ljava/lang/String;)Ljava/lang/String; + public fun equals (Ljava/lang/Object;)Z + public static fun equals-impl (Ljava/lang/String;Ljava/lang/Object;)Z + public static final fun equals-impl0 (Ljava/lang/String;Ljava/lang/String;)Z + public fun getIdentity ()Ljava/lang/String; + public fun hashCode ()I + public static fun hashCode-impl (Ljava/lang/String;)I + public fun toString ()Ljava/lang/String; + public static fun toString-impl (Ljava/lang/String;)Ljava/lang/String; + public final synthetic fun unbox-impl ()Ljava/lang/String; +} + +public abstract interface class space/kscience/kmath/expressions/Symbol : space/kscience/kmath/expressions/MST { + public static final field Companion Lspace/kscience/kmath/expressions/Symbol$Companion; + public abstract fun getIdentity ()Ljava/lang/String; +} + +public final class space/kscience/kmath/expressions/Symbol$Companion { + public final fun getX-uKgCeAI ()Ljava/lang/String; + public final fun getY-uKgCeAI ()Ljava/lang/String; + public final fun getZ-uKgCeAI ()Ljava/lang/String; +} + public final class space/kscience/kmath/expressions/SymbolIndexerKt { } +public final class space/kscience/kmath/expressions/SymbolKt { + public static final fun get (Ljava/util/Map;Ljava/lang/String;)Ljava/lang/Object; + public static final fun get (Ljava/util/Map;Lspace/kscience/kmath/expressions/Symbol;)Ljava/lang/Object; + public static final fun getSymbol ()Lkotlin/properties/ReadOnlyProperty; + public static final fun set (Ljava/util/Map;Ljava/lang/String;Ljava/lang/Object;)V + public static final fun set (Ljava/util/Map;Lspace/kscience/kmath/expressions/Symbol;Ljava/lang/Object;)V +} + public final class space/kscience/kmath/linear/BufferedLinearSpace : space/kscience/kmath/linear/LinearSpace { public fun (Lspace/kscience/kmath/operations/Ring;Lkotlin/jvm/functions/Function2;)V public fun buildMatrix (IILkotlin/jvm/functions/Function3;)Lspace/kscience/kmath/nd/Structure2D; @@ -677,39 +699,6 @@ public final class space/kscience/kmath/misc/CumulativeKt { public abstract interface annotation class space/kscience/kmath/misc/PerformancePitfall : java/lang/annotation/Annotation { } -public final class space/kscience/kmath/misc/StringSymbol : space/kscience/kmath/misc/Symbol { - public static final synthetic fun box-impl (Ljava/lang/String;)Lspace/kscience/kmath/misc/StringSymbol; - public static fun constructor-impl (Ljava/lang/String;)Ljava/lang/String; - public fun equals (Ljava/lang/Object;)Z - public static fun equals-impl (Ljava/lang/String;Ljava/lang/Object;)Z - public static final fun equals-impl0 (Ljava/lang/String;Ljava/lang/String;)Z - public fun getIdentity ()Ljava/lang/String; - public fun hashCode ()I - public static fun hashCode-impl (Ljava/lang/String;)I - public fun toString ()Ljava/lang/String; - public static fun toString-impl (Ljava/lang/String;)Ljava/lang/String; - public final synthetic fun unbox-impl ()Ljava/lang/String; -} - -public abstract interface class space/kscience/kmath/misc/Symbol { - public static final field Companion Lspace/kscience/kmath/misc/Symbol$Companion; - public abstract fun getIdentity ()Ljava/lang/String; -} - -public final class space/kscience/kmath/misc/Symbol$Companion { - public final fun getX-tWtZOCg ()Ljava/lang/String; - public final fun getY-tWtZOCg ()Ljava/lang/String; - public final fun getZ-tWtZOCg ()Ljava/lang/String; -} - -public final class space/kscience/kmath/misc/SymbolKt { - public static final fun get (Ljava/util/Map;Ljava/lang/String;)Ljava/lang/Object; - public static final fun get (Ljava/util/Map;Lspace/kscience/kmath/misc/Symbol;)Ljava/lang/Object; - public static final fun getSymbol ()Lkotlin/properties/ReadOnlyProperty; - public static final fun set (Ljava/util/Map;Ljava/lang/String;Ljava/lang/Object;)V - public static final fun set (Ljava/util/Map;Lspace/kscience/kmath/misc/Symbol;Ljava/lang/Object;)V -} - public abstract interface annotation class space/kscience/kmath/misc/UnstableKMathAPI : java/lang/annotation/Annotation { } @@ -1028,8 +1017,8 @@ public final class space/kscience/kmath/operations/AlgebraExtensionsKt { } public final class space/kscience/kmath/operations/AlgebraKt { - public static final fun bindSymbol (Lspace/kscience/kmath/operations/Algebra;Lspace/kscience/kmath/misc/Symbol;)Ljava/lang/Object; - public static final fun bindSymbolOrNull (Lspace/kscience/kmath/operations/Algebra;Lspace/kscience/kmath/misc/Symbol;)Ljava/lang/Object; + public static final fun bindSymbol (Lspace/kscience/kmath/operations/Algebra;Lspace/kscience/kmath/expressions/Symbol;)Ljava/lang/Object; + public static final fun bindSymbolOrNull (Lspace/kscience/kmath/operations/Algebra;Lspace/kscience/kmath/expressions/Symbol;)Ljava/lang/Object; public static final fun invoke (Lspace/kscience/kmath/operations/Algebra;Lkotlin/jvm/functions/Function1;)Ljava/lang/Object; } @@ -1414,6 +1403,11 @@ public final class space/kscience/kmath/operations/JBigIntegerField : space/ksci public abstract interface annotation class space/kscience/kmath/operations/KMathContext : java/lang/annotation/Annotation { } +public final class space/kscience/kmath/operations/LogicAlgebra$Companion { + public final fun getFALSE ()Lspace/kscience/kmath/expressions/Symbol; + public final fun getTRUE ()Lspace/kscience/kmath/expressions/Symbol; +} + public final class space/kscience/kmath/operations/LongRing : space/kscience/kmath/operations/Norm, space/kscience/kmath/operations/NumericAlgebra, space/kscience/kmath/operations/Ring { public static final field INSTANCE Lspace/kscience/kmath/operations/LongRing; public fun add (JJ)Ljava/lang/Long; diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt index f5193ecd2..88c14d311 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt @@ -5,8 +5,8 @@ package space.kscience.kmath.data +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.misc.PerformancePitfall -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.Structure2D import space.kscience.kmath.structures.Buffer diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt index bbd679ce9..08bfd3ca3 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt @@ -5,8 +5,8 @@ package space.kscience.kmath.data +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.misc.PerformancePitfall -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.Structure2D import space.kscience.kmath.structures.Buffer diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt index 3972429a5..39a6b858c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt @@ -5,7 +5,7 @@ package space.kscience.kmath.data -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.structures.Buffer diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt index dbc1431b3..33d72afad 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt @@ -5,9 +5,6 @@ package space.kscience.kmath.expressions -import space.kscience.kmath.misc.StringSymbol -import space.kscience.kmath.misc.Symbol - /** * Represents expression which structure can be differentiated. * diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt index a9ab8648f..84e66918f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt @@ -5,8 +5,6 @@ package space.kscience.kmath.expressions -import space.kscience.kmath.misc.StringSymbol -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.operations.Algebra import kotlin.jvm.JvmName import kotlin.properties.ReadOnlyProperty diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt index 994d52a73..951ec9474 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt @@ -5,7 +5,6 @@ package space.kscience.kmath.expressions -import space.kscience.kmath.misc.StringSymbol import space.kscience.kmath.operations.* /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MST.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MST.kt index 67881d9af..0e046ae5c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MST.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MST.kt @@ -5,30 +5,23 @@ package space.kscience.kmath.expressions -import space.kscience.kmath.misc.StringSymbol -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.operations.Algebra import space.kscience.kmath.operations.NumericAlgebra +import space.kscience.kmath.operations.bindSymbol /** * A Mathematical Syntax Tree (MST) node for mathematical expressions. * * @author Alexander Nozik */ -public sealed class MST { - /** - * A node containing raw string. - * - * @property value the value of this node. - */ - public data class Symbolic(val value: String) : MST() +public sealed interface MST { /** * A node containing a numeric value or scalar. * * @property value the value of this number. */ - public data class Numeric(val value: Number) : MST() + public data class Numeric(val value: Number) : MST /** * A node containing an unary operation. @@ -36,7 +29,7 @@ public sealed class MST { * @property operation the identifier of operation. * @property value the argument of this operation. */ - public data class Unary(val operation: String, val value: MST) : MST() + public data class Unary(val operation: String, val value: MST) : MST /** * A node containing binary operation. @@ -45,7 +38,7 @@ public sealed class MST { * @property left the left operand. * @property right the right operand. */ - public data class Binary(val operation: String, val left: MST, val right: MST) : MST() + public data class Binary(val operation: String, val left: MST, val right: MST) : MST } // TODO add a function with named arguments @@ -62,7 +55,7 @@ public fun Algebra.evaluate(node: MST): T = when (node) { is MST.Numeric -> (this as? NumericAlgebra)?.number(node.value) ?: error("Numeric nodes are not supported by $this") - is MST.Symbolic -> bindSymbol(node.value) + is Symbol -> bindSymbol(node) is MST.Unary -> when { this is NumericAlgebra && node.value is MST.Numeric -> unaryOperationFunction(node.operation)(number(node.value.value)) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt index 53124b777..fb2e38449 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt @@ -11,10 +11,10 @@ import space.kscience.kmath.operations.* /** * [Algebra] over [MST] nodes. */ -public object MstAlgebra : NumericAlgebra { +public object MstNumericAlgebra : NumericAlgebra { public override fun number(value: Number): MST.Numeric = MST.Numeric(value) - public override fun bindSymbolOrNull(value: String): MST.Symbolic = MST.Symbolic(value) - override fun bindSymbol(value: String): MST.Symbolic = bindSymbolOrNull(value) + public override fun bindSymbolOrNull(value: String): Symbol = StringSymbol(value) + override fun bindSymbol(value: String): Symbol = bindSymbolOrNull(value) public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = { arg -> MST.Unary(operation, arg) } @@ -29,8 +29,8 @@ public object MstAlgebra : NumericAlgebra { public object MstGroup : Group, NumericAlgebra, ScaleOperations { public override val zero: MST.Numeric = number(0.0) - public override fun number(value: Number): MST.Numeric = MstAlgebra.number(value) - public override fun bindSymbolOrNull(value: String): MST.Symbolic = MstAlgebra.bindSymbolOrNull(value) + public override fun number(value: Number): MST.Numeric = MstNumericAlgebra.number(value) + public override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) public override fun add(a: MST, b: MST): MST.Binary = binaryOperationFunction(GroupOperations.PLUS_OPERATION)(a, b) public override operator fun MST.unaryPlus(): MST.Unary = unaryOperationFunction(GroupOperations.PLUS_OPERATION)(this) @@ -45,10 +45,10 @@ public object MstGroup : Group, NumericAlgebra, ScaleOperations { binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, number(value)) public override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = - MstAlgebra.binaryOperationFunction(operation) + MstNumericAlgebra.binaryOperationFunction(operation) public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = - MstAlgebra.unaryOperationFunction(operation) + MstNumericAlgebra.unaryOperationFunction(operation) } /** @@ -61,7 +61,7 @@ public object MstRing : Ring, NumbersAddOperations, ScaleOperations, NumbersAddOperations, ScaleOperations MST.Unary = - MstAlgebra.unaryOperationFunction(operation) + MstNumericAlgebra.unaryOperationFunction(operation) } /** @@ -90,7 +90,7 @@ public object MstField : Field, NumbersAddOperations, ScaleOperations< public override inline val zero: MST.Numeric get() = MstRing.zero public override inline val one: MST.Numeric get() = MstRing.one - public override fun bindSymbolOrNull(value: String): MST.Symbolic = MstAlgebra.bindSymbolOrNull(value) + public override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) public override fun number(value: Number): MST.Numeric = MstRing.number(value) public override fun add(a: MST, b: MST): MST.Binary = MstRing.add(a, b) @@ -120,7 +120,7 @@ public object MstExtendedField : ExtendedField, NumericAlgebra { public override inline val zero: MST.Numeric get() = MstField.zero public override inline val one: MST.Numeric get() = MstField.one - public override fun bindSymbolOrNull(value: String): MST.Symbolic = MstAlgebra.bindSymbolOrNull(value) + public override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) public override fun number(value: Number): MST.Numeric = MstRing.number(value) public override fun sin(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.SIN_OPERATION)(arg) public override fun cos(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.COS_OPERATION)(arg) @@ -158,3 +158,23 @@ public object MstExtendedField : ExtendedField, NumericAlgebra { public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = MstField.unaryOperationFunction(operation) } + +/** + * Logic algebra for [MST] + */ +@UnstableKMathAPI +public object MstLogicAlgebra : LogicAlgebra { + public override fun bindSymbolOrNull(value: String): MST = super.bindSymbolOrNull(value) ?: StringSymbol(value) + + override fun const(boolean: Boolean): Symbol = if (boolean) { + LogicAlgebra.TRUE + } else { + LogicAlgebra.FALSE + } + + override fun MST.not(): MST = MST.Unary(Boolean::not.name, this) + + override fun MST.and(other: MST): MST = MST.Binary(Boolean::and.name, this, other) + + override fun MST.or(other: MST): MST = MST.Binary(Boolean::or.name, this, other) +} diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt index 09a5faa12..254d60b3d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt @@ -6,7 +6,6 @@ package space.kscience.kmath.expressions import space.kscience.kmath.linear.Point -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.* import space.kscience.kmath.structures.asBuffer diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Symbol.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt similarity index 91% rename from kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Symbol.kt rename to kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt index b9fb6879a..10a9ca5a1 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Symbol.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt @@ -3,15 +3,16 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ -package space.kscience.kmath.misc +package space.kscience.kmath.expressions import kotlin.jvm.JvmInline import kotlin.properties.ReadOnlyProperty /** - * A marker interface for a symbol. A symbol mus have an identity + * A marker interface for a symbol. A symbol must have an identity. + * Ic */ -public interface Symbol { +public interface Symbol: MST { /** * Identity object for the symbol. Two symbols with the same identity are considered to be the same symbol. */ diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt index 738156975..06634704c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt @@ -6,7 +6,6 @@ package space.kscience.kmath.expressions import space.kscience.kmath.linear.Point -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.Structure2D import space.kscience.kmath.structures.BufferFactory diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index 9a52d17f4..09bda6508 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -5,8 +5,7 @@ package space.kscience.kmath.operations -import space.kscience.kmath.misc.Symbol -import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.expressions.Symbol /** * Stub for DSL the [Algebra] is. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt new file mode 100644 index 000000000..2bef3f407 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt @@ -0,0 +1,71 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.operations + +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.expressions.symbol +import space.kscience.kmath.misc.UnstableKMathAPI + +/** + * An algebra for generic boolean logic + */ +@UnstableKMathAPI +public interface LogicAlgebra : Algebra { + + /** + * Represent constant [Boolean] as [T] + */ + public fun const(boolean: Boolean): T + + override fun bindSymbolOrNull(value: String): T? = value.lowercase().toBooleanStrictOrNull()?.let(::const) + + override fun unaryOperation(operation: String, arg: T): T = when (operation) { + Boolean::not.name -> arg.not() + else -> super.unaryOperation(operation, arg) + } + + override fun binaryOperation(operation: String, left: T, right: T): T = when (operation) { + Boolean::and.name -> left.and(right) + Boolean::or.name -> left.or(right) + else -> super.binaryOperation(operation, left, right) + } + + /** + * Logic 'not' + */ + public operator fun T.not(): T + + /** + * Logic 'and' + */ + public infix fun T.and(other: T): T + + /** + * Logic 'or' + */ + public infix fun T.or(other: T): T + + public companion object { + public val TRUE: Symbol by symbol + public val FALSE: Symbol by symbol + } +} + +/** + * An implementation of [LogicAlgebra] for primitive booleans + */ +@UnstableKMathAPI +@Suppress("EXTENSION_SHADOWED_BY_MEMBER") +public object BooleanAlgebra : LogicAlgebra { + + override fun const(boolean: Boolean): Boolean = boolean + + override fun Boolean.not(): Boolean = !this + + override fun Boolean.and(other: Boolean): Boolean = this && other + + override fun Boolean.or(other: Boolean): Boolean = this || other +} \ No newline at end of file diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt index cf3a565bc..ace67db06 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt @@ -5,7 +5,6 @@ package space.kscience.kmath.expressions -import space.kscience.kmath.misc.symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke import kotlin.test.Test diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/InterpretTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/InterpretTest.kt index 980819364..0df9fe5cf 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/InterpretTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/InterpretTest.kt @@ -5,7 +5,6 @@ package space.kscience.kmath.expressions -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/SimpleAutoDiffTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/SimpleAutoDiffTest.kt index ab509650a..c6852cbbf 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/SimpleAutoDiffTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/SimpleAutoDiffTest.kt @@ -5,8 +5,6 @@ package space.kscience.kmath.expressions -import space.kscience.kmath.misc.Symbol -import space.kscience.kmath.misc.symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.structures.Buffer diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt index 8c6745c79..59d481d02 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt @@ -7,11 +7,7 @@ package space.kscience.kmath.kotlingrad import edu.umontreal.kotlingrad.api.SFun import edu.umontreal.kotlingrad.api.SVar -import space.kscience.kmath.expressions.DifferentiableExpression -import space.kscience.kmath.expressions.MST -import space.kscience.kmath.expressions.MstAlgebra -import space.kscience.kmath.expressions.interpret -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.NumericAlgebra /** @@ -35,8 +31,8 @@ public class DifferentiableMstExpression>( DifferentiableMstExpression( algebra, symbols.map(Symbol::identity) - .map(MstAlgebra::bindSymbol) - .map>>(MST.Symbolic::toSVar) + .map(MstNumericAlgebra::bindSymbol) + .map>>(Symbol::toSVar) .fold(mst.toSFun(), SFun>::d) .toMst(), ) diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt index bee2c9e3e..8e3c54035 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt @@ -7,9 +7,10 @@ package space.kscience.kmath.kotlingrad import edu.umontreal.kotlingrad.api.* import space.kscience.kmath.expressions.MST -import space.kscience.kmath.expressions.MstAlgebra import space.kscience.kmath.expressions.MstExtendedField import space.kscience.kmath.expressions.MstExtendedField.unaryMinus +import space.kscience.kmath.expressions.MstNumericAlgebra +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.operations.* /** @@ -18,7 +19,7 @@ import space.kscience.kmath.operations.* * @receiver The variable. * @returnAa node. */ -public fun > SVar.toMst(): MST.Symbolic = MstAlgebra.bindSymbol(name) +public fun > SVar.toMst(): Symbol = MstNumericAlgebra.bindSymbol(name) /** * Maps [SVar] to [MST.Numeric] directly. @@ -26,7 +27,7 @@ public fun > SVar.toMst(): MST.Symbolic = MstAlgebra.bindSymbol(n * @receiver The constant. * @return A node. */ -public fun > SConst.toMst(): MST.Numeric = MstAlgebra.number(doubleValue) +public fun > SConst.toMst(): MST.Numeric = MstNumericAlgebra.number(doubleValue) /** * Maps [SFun] objects to [MST]. Some unsupported operations like [Derivative] are bound and converted then. @@ -85,7 +86,7 @@ public fun > MST.Numeric.toSConst(): SConst = SConst(value) * @receiver The node. * @return A new variable. */ -internal fun > MST.Symbolic.toSVar(): SVar = SVar(value) +internal fun > Symbol.toSVar(): SVar = SVar(identity) /** * Maps [MST] objects to [SFun]. Unsupported operations throw [IllegalStateException]. @@ -102,7 +103,7 @@ internal fun > MST.Symbolic.toSVar(): SVar = SVar(value) */ public fun > MST.toSFun(): SFun = when (this) { is MST.Numeric -> toSConst() - is MST.Symbolic -> toSVar() + is Symbol -> toSVar() is MST.Unary -> when (operation) { GroupOperations.PLUS_OPERATION -> +value.toSFun() diff --git a/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt b/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt index 85c964c58..57fe2411c 100644 --- a/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt +++ b/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt @@ -8,9 +8,9 @@ package space.kscience.kmath.kotlingrad import edu.umontreal.kotlingrad.api.* import space.kscience.kmath.asm.compileToExpression import space.kscience.kmath.ast.parseMath -import space.kscience.kmath.expressions.MstAlgebra +import space.kscience.kmath.expressions.MstNumericAlgebra +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.misc.Symbol.Companion.x import space.kscience.kmath.operations.DoubleField import kotlin.test.Test import kotlin.test.assertEquals @@ -20,7 +20,7 @@ import kotlin.test.fail internal class AdaptingTests { @Test fun symbol() { - val c1 = MstAlgebra.bindSymbol(x.identity) + val c1 = MstNumericAlgebra.bindSymbol(x.identity) assertEquals(x.identity, c1.toSVar>().name) val c2 = "kitten".parseMath().toSFun>() if (c2 is SVar) assertTrue(c2.name == "kitten") else fail() @@ -28,7 +28,7 @@ internal class AdaptingTests { @Test fun number() { - val c1 = MstAlgebra.number(12354324) + val c1 = MstNumericAlgebra.number(12354324) assertTrue(c1.toSConst().doubleValue == 12354324.0) val c2 = "0.234".parseMath().toSFun>() if (c2 is SConst) assertTrue(c2.doubleValue == 0.234) else fail() @@ -46,7 +46,7 @@ internal class AdaptingTests { @Test fun simpleFunctionDerivative() { - val xSVar = MstAlgebra.bindSymbol(x.identity).toSVar>() + val xSVar = MstNumericAlgebra.bindSymbol(x.identity).toSVar>() val quadratic = "x^2-4*x-44".parseMath().toSFun>() val actualDerivative = quadratic.d(xSVar).toMst().compileToExpression(DoubleField) val expectedDerivative = "2*x-4".parseMath().compileToExpression(DoubleField) @@ -55,7 +55,7 @@ internal class AdaptingTests { @Test fun moreComplexDerivative() { - val xSVar = MstAlgebra.bindSymbol(x.identity).toSVar>() + val xSVar = MstNumericAlgebra.bindSymbol(x.identity).toSVar>() val composition = "-sqrt(sin(x^2)-cos(x)^2-16*x)".parseMath().toSFun>() val actualDerivative = composition.d(xSVar).toMst().compileToExpression(DoubleField) diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index 38f3038c2..4cf5aea84 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -5,11 +5,7 @@ package space.kscience.kmath.optimization -import space.kscience.kmath.expressions.AutoDiffProcessor -import space.kscience.kmath.expressions.DifferentiableExpression -import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.expressions.ExpressionAlgebra -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.indices diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt index 67a21bf2a..0f2167549 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt @@ -6,7 +6,7 @@ package space.kscience.kmath.optimization import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.indices import kotlin.math.pow diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt index 3b9868815..4a1676412 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt @@ -5,7 +5,7 @@ package space.kscience.kmath.optimization -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.Symbol public interface OptimizationFeature diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt index f5cfa05e6..633e9ae0e 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt @@ -6,11 +6,7 @@ package space.kscience.kmath.optimization import space.kscience.kmath.data.ColumnarData -import space.kscience.kmath.expressions.AutoDiffProcessor -import space.kscience.kmath.expressions.DifferentiableExpression -import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.expressions.ExpressionAlgebra -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.* import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.Field From 516444d1bc25cd810e685a00a7098f1ff38d97d6 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 16 May 2021 20:51:46 +0300 Subject: [PATCH 038/132] Fix and test --- .../space/kscience/kmath/expressions/MST.kt | 6 +++--- .../kscience/kmath/operations/Algebra.kt | 2 +- .../kscience/kmath/operations/LogicAlgebra.kt | 6 ++++++ .../kmath/expressions/ExpressionFieldTest.kt | 3 +-- .../kmath/expressions/InterpretTest.kt | 20 ++++++++++++++++--- 5 files changed, 28 insertions(+), 9 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MST.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MST.kt index 0e046ae5c..7533024a1 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MST.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MST.kt @@ -76,7 +76,7 @@ public fun Algebra.evaluate(node: MST): T = when (node) { } } -internal class InnerAlgebra(val algebra: Algebra, val arguments: Map) : NumericAlgebra { +internal class InnerAlgebra(val algebra: Algebra, val arguments: Map) : NumericAlgebra { override fun bindSymbolOrNull(value: String): T? = algebra.bindSymbolOrNull(value) ?: arguments[StringSymbol(value)] override fun unaryOperation(operation: String, arg: T): T = @@ -101,7 +101,7 @@ internal class InnerAlgebra(val algebra: Algebra, val arguments: Map /** * Interprets the [MST] node with this [Algebra] and optional [arguments] */ -public fun MST.interpret(algebra: Algebra, arguments: Map): T = +public fun MST.interpret(algebra: Algebra, arguments: Map): T = InnerAlgebra(algebra, arguments).evaluate(this) /** @@ -111,7 +111,7 @@ public fun MST.interpret(algebra: Algebra, arguments: Map MST.interpret(algebra: Algebra, vararg arguments: Pair): T = +public fun MST.interpret(algebra: Algebra, vararg arguments: Pair): T = interpret(algebra, mapOf(*arguments)) /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index 09bda6508..aa22b8c19 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -84,7 +84,7 @@ public interface Algebra { * @return an operation. */ public fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = - error("Binary operation $operation not defined in $this") + error("Binary operation '$operation; not defined in $this") /** * Dynamically invokes a binary operation with the certain name. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt index 2bef3f407..406967897 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt @@ -27,12 +27,18 @@ public interface LogicAlgebra : Algebra { else -> super.unaryOperation(operation, arg) } + override fun unaryOperationFunction(operation: String): (arg: T) -> T = { unaryOperation(operation, it) } + override fun binaryOperation(operation: String, left: T, right: T): T = when (operation) { Boolean::and.name -> left.and(right) Boolean::or.name -> left.or(right) else -> super.binaryOperation(operation, left, right) } + override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = { l, r -> + binaryOperation(operation, l, r) + } + /** * Logic 'not' */ diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt index ace67db06..4d1b00b3d 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt @@ -6,7 +6,6 @@ package space.kscience.kmath.expressions import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.operations.invoke import kotlin.test.Test import kotlin.test.assertEquals import kotlin.test.assertFails @@ -16,7 +15,7 @@ class ExpressionFieldTest { @Test fun testExpression() { - val expression = FunctionalExpressionField(DoubleField).invoke { + val expression = with(FunctionalExpressionField(DoubleField)) { val x by binding() x * x + 2 * x + one } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/InterpretTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/InterpretTest.kt index 0df9fe5cf..156334b2e 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/InterpretTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/InterpretTest.kt @@ -5,18 +5,32 @@ package space.kscience.kmath.expressions +import space.kscience.kmath.expressions.Symbol.Companion.x +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.BooleanAlgebra import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke import kotlin.test.Test +import kotlin.test.assertEquals + internal class InterpretTest { @Test fun interpretation() { val expr = MstField { - val x = bindSymbol(Symbol.x) x * 2.0 + number(2.0) / x - 16.0 }.toExpression(DoubleField) - expr(Symbol.x to 2.2) + assertEquals(-10.69, expr(x to 2.2), 0.02) + } + + @Test + @UnstableKMathAPI + fun booleanAlgebra() { + val expr = MstLogicAlgebra { + x and const(true) + }.toExpression(BooleanAlgebra) + + assertEquals(true, expr(x to true)) + assertEquals(false, expr(x to false)) } } From e6c6925209e73a766a913450fdd9c6af11ca8f06 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 16 May 2021 22:33:53 +0300 Subject: [PATCH 039/132] Fix integration borders --- .../space/kscience/kmath/integration/GaussIntegrator.kt | 2 +- .../space/kscience/kmath/integration/GaussIntegralTest.kt | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt index 0038ca0f2..fcf47040e 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt @@ -98,7 +98,7 @@ public fun GaussIntegrator.integrate( require(intervals > 0) { "Number of intervals must be positive" } val rangeSize = (range.endInclusive - range.start) / intervals val ranges = UnivariateIntegrandRanges( - (0 until intervals).map { i -> (rangeSize * i)..(rangeSize * (i + 1)) to order } + (0 until intervals).map { i -> (range.start + rangeSize * i)..(range.start + rangeSize * (i + 1)) to order } ) return integrate( UnivariateIntegrand( diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt index 1f9f7aedf..6195d0ac6 100644 --- a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt @@ -24,14 +24,14 @@ class GaussIntegralTest { @Test fun gaussUniform() { - val res = DoubleField.integrator.integrate(0.0..100.0) { x -> + val res = DoubleField.integrator.integrate(35.0..100.0) { x -> if(x in 30.0..50.0){ 1.0 } else { 0.0 } } - assertEquals(20.0, res.valueOrNull!!, 0.5) + assertEquals(15.0, res.valueOrNull!!, 0.5) } From 83b6d8fee0b4c899fe9246c3173325fc54aff48f Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 16 May 2021 22:39:44 +0300 Subject: [PATCH 040/132] dump api --- build.gradle.kts | 2 +- kmath-core/api/kmath-core.api | 5 +++++ 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/build.gradle.kts b/build.gradle.kts index e14d303fc..6e1aa76f4 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -15,7 +15,7 @@ allprojects { } group = "space.kscience" - version = "0.3.0-dev-9" + version = "0.3.0-dev-10" } subprojects { diff --git a/kmath-core/api/kmath-core.api b/kmath-core/api/kmath-core.api index 7b09b668b..456b5cfba 100644 --- a/kmath-core/api/kmath-core.api +++ b/kmath-core/api/kmath-core.api @@ -500,6 +500,11 @@ public final class space/kscience/kmath/linear/LFeature : space/kscience/kmath/l public static final field INSTANCE Lspace/kscience/kmath/linear/LFeature; } +public abstract interface class space/kscience/kmath/linear/LUDecompositionFeature : space/kscience/kmath/linear/MatrixFeature { + public abstract fun getL ()Lspace/kscience/kmath/nd/Structure2D; + public abstract fun getU ()Lspace/kscience/kmath/nd/Structure2D; +} + public abstract interface class space/kscience/kmath/linear/LinearSolver { public abstract fun inverse (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D; public abstract fun solve (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D; From dfac6aeb5ca83fdf85c8c8f355a61539df908e1a Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 17 May 2021 10:10:49 +0300 Subject: [PATCH 041/132] Update CHANGELOG.md Co-authored-by: Iaroslav Postovalov <38042667+CommanderTvis@users.noreply.github.com> --- CHANGELOG.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index e9a67a0ab..acdf9899b 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -30,7 +30,8 @@ - Rewritten EJML module without ejml-simple - Stability of kmath-ast and kmath-kotilngrad promoted to EXPERIMENTAL. - ColumnarData returns nullable column -- Replaced MST.Symbolic by Symbol. Symbol now inherits MST +- MST is made sealed interface +- Replaced MST.Symbolic by Symbol, Symbol now implements MST ### Deprecated From 72f4d7c7e602766dcf71e3abbc0a7545e2ccb70f Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 17 May 2021 10:10:54 +0300 Subject: [PATCH 042/132] Update kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt Co-authored-by: Iaroslav Postovalov <38042667+CommanderTvis@users.noreply.github.com> --- .../kotlin/space/kscience/kmath/operations/Algebra.kt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index aa22b8c19..3a1ec430e 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -84,7 +84,7 @@ public interface Algebra { * @return an operation. */ public fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = - error("Binary operation '$operation; not defined in $this") + error("Binary operation '$operation' not defined in $this") /** * Dynamically invokes a binary operation with the certain name. From 53a6d3543fcbc11baac514f171dcd1d7e16cd8bf Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 17 May 2021 16:53:12 +0300 Subject: [PATCH 043/132] [WIP] Interpolation fix --- examples/build.gradle.kts | 2 +- .../kscience/kmath/functions/interpolate.kt | 56 +++++++++++++++++++ .../space/kscience/kmath/ejml/_generated.kt | 30 ++++------ .../kscience/kmath/functions/Piecewise.kt | 10 ++-- .../kscience/kmath/functions/Polynomial.kt | 18 +++--- .../kmath/interpolation/SplineInterpolator.kt | 15 ++--- .../interpolation/SplineInterpolatorTest.kt | 35 ++++++++++++ 7 files changed, 120 insertions(+), 46 deletions(-) create mode 100644 examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt create mode 100644 kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/SplineInterpolatorTest.kt diff --git a/examples/build.gradle.kts b/examples/build.gradle.kts index 90bb935b9..d095db1ba 100644 --- a/examples/build.gradle.kts +++ b/examples/build.gradle.kts @@ -43,7 +43,7 @@ dependencies { implementation("org.slf4j:slf4j-simple:1.7.30") // plotting - implementation("space.kscience:plotlykt-server:0.4.0-dev-2") + implementation("space.kscience:plotlykt-server:0.4.0") } kotlin.sourceSets.all { diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt new file mode 100644 index 000000000..54120ac50 --- /dev/null +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt @@ -0,0 +1,56 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.functions + +import space.kscience.kmath.interpolation.SplineInterpolator +import space.kscience.kmath.interpolation.interpolatePolynomials +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.plotly.Plotly +import space.kscience.plotly.makeFile +import space.kscience.plotly.models.functionXY +import space.kscience.plotly.scatter +import kotlin.math.PI +import kotlin.math.sin + +fun main() { + val data = (0..10).map { + val x = it.toDouble() / 5 * PI + x to sin(x) + } + + val polynomial: PiecewisePolynomial = SplineInterpolator( + DoubleField, ::DoubleBuffer + ).interpolatePolynomials(data) + + val function = polynomial.asFunction(DoubleField, 0.0) + + val cmInterpolate = org.apache.commons.math3.analysis.interpolation.SplineInterpolator().interpolate( + data.map { it.first }.toDoubleArray(), + data.map { it.second }.toDoubleArray() + ) + + println(function(2.0)) + println(cmInterpolate.value(2.0)) + +// +// Plotly.plot { +// scatter { +// name = "interpolated" +// x.numbers = data.map { it.first } +// y.numbers = x.doubles.map { function(it) } +// } +// scatter { +// name = "original" +// functionXY(0.0..(2 * PI), 0.1) { sin(it) } +// } +// scatter { +// name = "cm" +// x.numbers = data.map { it.first } +// y.numbers = x.doubles.map { cmInterpolate.value(it) } +// } +// }.makeFile() +} \ No newline at end of file diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt index 139c55697..6f74ab24f 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt @@ -8,28 +8,18 @@ package space.kscience.kmath.ejml import org.ejml.data.* -import org.ejml.dense.row.CommonOps_DDRM -import org.ejml.dense.row.CommonOps_FDRM -import org.ejml.dense.row.factory.DecompositionFactory_DDRM -import org.ejml.dense.row.factory.DecompositionFactory_FDRM -import org.ejml.sparse.FillReducing -import org.ejml.sparse.csc.CommonOps_DSCC -import org.ejml.sparse.csc.CommonOps_FSCC -import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC -import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC -import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC -import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC import space.kscience.kmath.linear.* +import space.kscience.kmath.operations.* +import space.kscience.kmath.structures.* +import space.kscience.kmath.misc.* +import kotlin.reflect.* +import org.ejml.dense.row.* +import org.ejml.dense.row.factory.* +import org.ejml.sparse.* +import org.ejml.sparse.csc.* +import org.ejml.sparse.csc.factory.* +import space.kscience.kmath.nd.* import space.kscience.kmath.linear.Matrix -import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.nd.StructureFeature -import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.operations.FloatField -import space.kscience.kmath.operations.invoke -import space.kscience.kmath.structures.DoubleBuffer -import space.kscience.kmath.structures.FloatBuffer -import kotlin.reflect.KClass -import kotlin.reflect.cast /** * [EjmlVector] specialization for [Double]. diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt index dae55502d..6bb2a1656 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt @@ -26,12 +26,12 @@ public fun interface Piecewise { public fun interface PiecewisePolynomial : Piecewise> /** - * Basic [Piecewise] implementation where all the pieces are ordered by the [Comparable] type instances. + * A [Piecewise] builder where all the pieces are ordered by the [Comparable] type instances. * * @param T the comparable piece key type. + * @param delimiter the initial piecewise separator */ -public class OrderedPiecewisePolynomial>(delimiter: T) : - PiecewisePolynomial { +public class OrderedPiecewisePolynomial>(delimiter: T) : PiecewisePolynomial { private val delimiters: MutableList = arrayListOf(delimiter) private val pieces: MutableList> = arrayListOf() @@ -64,9 +64,7 @@ public class OrderedPiecewisePolynomial>(delimiter: T) : return null else { for (index in 1 until delimiters.size) - if (arg < delimiters[index]) - return pieces[index - 1] - + if (arg < delimiters[index]) return pieces[index - 1] error("Piece not found") } } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt index efae71b0e..325010f99 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt @@ -19,7 +19,9 @@ import kotlin.math.pow * * @param coefficients constant is the leftmost coefficient. */ -public class Polynomial(public val coefficients: List) +public class Polynomial(public val coefficients: List){ + override fun toString(): String = "Polynomial$coefficients" +} /** * Returns a [Polynomial] instance with given [coefficients]. @@ -34,19 +36,15 @@ public fun Polynomial.value(): Double = coefficients.reduceIndexed { ind /** * Evaluates the value of the given polynomial for given argument. + * https://en.wikipedia.org/wiki/Horner%27s_method */ public fun > Polynomial.value(ring: C, arg: T): T = ring { if (coefficients.isEmpty()) return@ring zero - var res = coefficients.first() - var powerArg = arg - - for (index in 1 until coefficients.size) { - res += coefficients[index] * powerArg - // recalculating power on each step to avoid power costs on long polynomials - powerArg *= arg + var result: T = coefficients.last() + for (j in coefficients.size - 2 downTo 0) { + result = (arg * result) + coefficients[j] } - - res + return result } /** diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt index 2d2ff6f26..fc341e019 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt @@ -34,19 +34,16 @@ public class SplineInterpolator>( // Number of intervals. The number of data points is n + 1. val n = points.size - 1 // Differences between knot points - val h = bufferFactory(points.size) { i -> points.x[i + 1] - points.x[i] } - val mu = bufferFactory(points.size - 1) { zero } - val z = bufferFactory(points.size) { zero } + val h = bufferFactory(n) { i -> points.x[i + 1] - points.x[i] } + val mu = bufferFactory(n) { zero } + val z = bufferFactory(n + 1) { zero } for (i in 1 until n) { val g = 2.0 * (points.x[i + 1] - points.x[i - 1]) - h[i - 1] * mu[i - 1] mu[i] = h[i] / g - - z[i] = (3.0 * (points.y[i + 1] * h[i - 1] - - points.x[i] * (points.x[i + 1] - points.x[i - 1]) - + points.y[i - 1] * h[i]) / (h[i - 1] * h[i]) - - h[i - 1] * z[i - 1] - ) / g + z[i] = + ((points.y[i + 1] * h[i - 1] - points.y[i] * (points.x[i + 1] - points.x[i - 1]) + points.y[i - 1] * h[i]) * 3.0 / + (h[i - 1] * h[i]) - h[i - 1] * z[i - 1]) / g } // cubic spline coefficients -- b is linear, c quadratic, d is cubic (original y's are constants) diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/SplineInterpolatorTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/SplineInterpolatorTest.kt new file mode 100644 index 000000000..c3bd8195a --- /dev/null +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/SplineInterpolatorTest.kt @@ -0,0 +1,35 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.interpolation + +import space.kscience.kmath.functions.PiecewisePolynomial +import space.kscience.kmath.functions.asFunction +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.structures.DoubleBuffer +import kotlin.math.PI +import kotlin.math.sin +import kotlin.test.Test +import kotlin.test.assertEquals + +internal class SplineInterpolatorTest { + @Test + fun testInterpolation() { + val data = (0..10).map { + val x = it.toDouble() / 5 * PI + x to sin(x) + } + + val polynomial: PiecewisePolynomial = SplineInterpolator( + DoubleField, ::DoubleBuffer + ).interpolatePolynomials(data) + + val function = polynomial.asFunction(DoubleField) + assertEquals(null, function(-1.0)) + assertEquals(sin(0.5), function(0.5)!!, 0.1) + assertEquals(sin(1.5), function(1.5)!!, 0.1) + assertEquals(sin(2.0), function(2.0)!!, 0.1) + } +} From d45d44f96d87596594b9f60935b742f2a407b6df Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 17 May 2021 21:55:32 +0300 Subject: [PATCH 044/132] Fix Interpolation --- .../kscience/kmath/functions/interpolate.kt | 35 +++++++++---------- .../space/kscience/kmath/ejml/_generated.kt | 30 ++++++++++------ .../kmath/interpolation/SplineInterpolator.kt | 19 ++++++++-- .../interpolation/SplineInterpolatorTest.kt | 15 ++++---- 4 files changed, 59 insertions(+), 40 deletions(-) diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt index 54120ac50..69ba80fb6 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt @@ -33,24 +33,21 @@ fun main() { data.map { it.second }.toDoubleArray() ) - println(function(2.0)) - println(cmInterpolate.value(2.0)) -// -// Plotly.plot { -// scatter { -// name = "interpolated" -// x.numbers = data.map { it.first } -// y.numbers = x.doubles.map { function(it) } -// } -// scatter { -// name = "original" -// functionXY(0.0..(2 * PI), 0.1) { sin(it) } -// } -// scatter { -// name = "cm" -// x.numbers = data.map { it.first } -// y.numbers = x.doubles.map { cmInterpolate.value(it) } -// } -// }.makeFile() + Plotly.plot { + scatter { + name = "interpolated" + x.numbers = data.map { it.first } + y.numbers = x.doubles.map { function(it) } + } + scatter { + name = "original" + functionXY(0.0..(2 * PI), 0.1) { sin(it) } + } + scatter { + name = "cm" + x.numbers = data.map { it.first } + y.numbers = x.doubles.map { cmInterpolate.value(it) } + } + }.makeFile() } \ No newline at end of file diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt index 6f74ab24f..139c55697 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt @@ -8,18 +8,28 @@ package space.kscience.kmath.ejml import org.ejml.data.* +import org.ejml.dense.row.CommonOps_DDRM +import org.ejml.dense.row.CommonOps_FDRM +import org.ejml.dense.row.factory.DecompositionFactory_DDRM +import org.ejml.dense.row.factory.DecompositionFactory_FDRM +import org.ejml.sparse.FillReducing +import org.ejml.sparse.csc.CommonOps_DSCC +import org.ejml.sparse.csc.CommonOps_FSCC +import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC +import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC +import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC +import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC import space.kscience.kmath.linear.* -import space.kscience.kmath.operations.* -import space.kscience.kmath.structures.* -import space.kscience.kmath.misc.* -import kotlin.reflect.* -import org.ejml.dense.row.* -import org.ejml.dense.row.factory.* -import org.ejml.sparse.* -import org.ejml.sparse.csc.* -import org.ejml.sparse.csc.factory.* -import space.kscience.kmath.nd.* import space.kscience.kmath.linear.Matrix +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.nd.StructureFeature +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.FloatField +import space.kscience.kmath.operations.invoke +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.FloatBuffer +import kotlin.reflect.KClass +import kotlin.reflect.cast /** * [EjmlVector] specialization for [Double]. diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt index fc341e019..c3d6ffae7 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt @@ -10,8 +10,10 @@ import space.kscience.kmath.functions.OrderedPiecewisePolynomial import space.kscience.kmath.functions.PiecewisePolynomial import space.kscience.kmath.functions.Polynomial import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Field import space.kscience.kmath.operations.invoke +import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.MutableBufferFactory /** @@ -56,10 +58,23 @@ public class SplineInterpolator>( val a = points.y[j] val b = (points.y[j + 1] - points.y[j]) / h[j] - h[j] * (cOld + 2.0 * c) / 3.0 val d = (cOld - c) / (3.0 * h[j]) - val polynomial = Polynomial(a, b, c, d) + val x0 = points.x[j] + val x02 = x0 * x0 + val x03 = x02 * x0 + //Shift coefficients to represent absolute polynomial instead of one with an offset + val polynomial = Polynomial( + a - b * x0 + c * x02 - d * x03, + b - 2*c*x0 + 3*d*x02, + c - 3*d*x0, + d + ) cOld = c - putLeft(points.x[j], polynomial) + putLeft(x0, polynomial) } } } + + public companion object { + public val double: SplineInterpolator = SplineInterpolator(DoubleField, ::DoubleBuffer) + } } diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/SplineInterpolatorTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/SplineInterpolatorTest.kt index c3bd8195a..3adaab2d1 100644 --- a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/SplineInterpolatorTest.kt +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/interpolation/SplineInterpolatorTest.kt @@ -8,7 +8,6 @@ package space.kscience.kmath.interpolation import space.kscience.kmath.functions.PiecewisePolynomial import space.kscience.kmath.functions.asFunction import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.structures.DoubleBuffer import kotlin.math.PI import kotlin.math.sin import kotlin.test.Test @@ -22,14 +21,12 @@ internal class SplineInterpolatorTest { x to sin(x) } - val polynomial: PiecewisePolynomial = SplineInterpolator( - DoubleField, ::DoubleBuffer - ).interpolatePolynomials(data) + val polynomial: PiecewisePolynomial = SplineInterpolator.double.interpolatePolynomials(data) - val function = polynomial.asFunction(DoubleField) - assertEquals(null, function(-1.0)) - assertEquals(sin(0.5), function(0.5)!!, 0.1) - assertEquals(sin(1.5), function(1.5)!!, 0.1) - assertEquals(sin(2.0), function(2.0)!!, 0.1) + val function = polynomial.asFunction(DoubleField, Double.NaN) + assertEquals(Double.NaN, function(-1.0)) + assertEquals(sin(0.5), function(0.5), 0.1) + assertEquals(sin(1.5), function(1.5), 0.1) + assertEquals(sin(2.0), function(2.0), 0.1) } } From 8b92db9923adfe334ae472a8d6d525802241113f Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Tue, 18 May 2021 10:07:55 +0300 Subject: [PATCH 045/132] bump version --- build.gradle.kts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/build.gradle.kts b/build.gradle.kts index 6e1aa76f4..93f5059ff 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -15,7 +15,7 @@ allprojects { } group = "space.kscience" - version = "0.3.0-dev-10" + version = "0.3.0-dev-11" } subprojects { From a67c112793fc2f86964e785182f83ee92aca568a Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Tue, 18 May 2021 10:22:33 +0300 Subject: [PATCH 046/132] add xor --- kmath-core/api/kmath-core.api | 5 +++++ .../kotlin/space/kscience/kmath/expressions/MstAlgebra.kt | 2 ++ .../space/kscience/kmath/operations/LogicAlgebra.kt | 8 ++++++++ 3 files changed, 15 insertions(+) diff --git a/kmath-core/api/kmath-core.api b/kmath-core/api/kmath-core.api index ead4b96b5..b424b59ff 100644 --- a/kmath-core/api/kmath-core.api +++ b/kmath-core/api/kmath-core.api @@ -522,6 +522,11 @@ public final class space/kscience/kmath/linear/LFeature : space/kscience/kmath/l public static final field INSTANCE Lspace/kscience/kmath/linear/LFeature; } +public abstract interface class space/kscience/kmath/linear/LUDecompositionFeature : space/kscience/kmath/linear/MatrixFeature { + public abstract fun getL ()Lspace/kscience/kmath/nd/Structure2D; + public abstract fun getU ()Lspace/kscience/kmath/nd/Structure2D; +} + public abstract interface class space/kscience/kmath/linear/LinearSolver { public abstract fun inverse (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D; public abstract fun solve (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D; diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt index fb2e38449..4729f19ea 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt @@ -177,4 +177,6 @@ public object MstLogicAlgebra : LogicAlgebra { override fun MST.and(other: MST): MST = MST.Binary(Boolean::and.name, this, other) override fun MST.or(other: MST): MST = MST.Binary(Boolean::or.name, this, other) + + override fun MST.xor(other: MST): MST = MST.Binary(Boolean::xor.name, this, other) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt index 406967897..9037525e1 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/LogicAlgebra.kt @@ -54,6 +54,12 @@ public interface LogicAlgebra : Algebra { */ public infix fun T.or(other: T): T + /** + * Logic 'xor' + */ + public infix fun T.xor(other: T): T + + public companion object { public val TRUE: Symbol by symbol public val FALSE: Symbol by symbol @@ -74,4 +80,6 @@ public object BooleanAlgebra : LogicAlgebra { override fun Boolean.and(other: Boolean): Boolean = this && other override fun Boolean.or(other: Boolean): Boolean = this || other + + override fun Boolean.xor(other: Boolean): Boolean = this xor other } \ No newline at end of file From b4dd4380c070e22a61691a1f7a5f0245b2ddb4b2 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Tue, 18 May 2021 18:02:13 +0700 Subject: [PATCH 047/132] Hard code specific imports in codegen --- .../kmath/ejml/codegen/ejmlCodegen.kt | 36 ++++++++++++------- 1 file changed, 23 insertions(+), 13 deletions(-) diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt index e4b157973..5da7d0f67 100644 --- a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt @@ -369,19 +369,29 @@ fun ejmlCodegen(outputFile: String): Unit = File(outputFile).run { it.appendLine() it.appendLine("package space.kscience.kmath.ejml") it.appendLine() - it.appendLine("import org.ejml.data.*") - it.appendLine("import space.kscience.kmath.linear.*") - it.appendLine("import space.kscience.kmath.operations.*") - it.appendLine("import space.kscience.kmath.structures.*") - it.appendLine("import space.kscience.kmath.misc.*") - it.appendLine("import kotlin.reflect.*") - it.appendLine("import org.ejml.dense.row.*") - it.appendLine("import org.ejml.dense.row.factory.*") - it.appendLine("import org.ejml.sparse.*") - it.appendLine("import org.ejml.sparse.csc.*") - it.appendLine("import org.ejml.sparse.csc.factory.*") - it.appendLine("import space.kscience.kmath.nd.*") - it.appendLine("import space.kscience.kmath.linear.Matrix") + it.appendLine("""import org.ejml.data.* +import org.ejml.dense.row.CommonOps_DDRM +import org.ejml.dense.row.CommonOps_FDRM +import org.ejml.dense.row.factory.DecompositionFactory_DDRM +import org.ejml.dense.row.factory.DecompositionFactory_FDRM +import org.ejml.sparse.FillReducing +import org.ejml.sparse.csc.CommonOps_DSCC +import org.ejml.sparse.csc.CommonOps_FSCC +import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC +import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC +import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC +import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC +import space.kscience.kmath.linear.* +import space.kscience.kmath.linear.Matrix +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.nd.StructureFeature +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.FloatField +import space.kscience.kmath.operations.invoke +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.FloatBuffer +import kotlin.reflect.KClass +import kotlin.reflect.cast""") it.appendLine() it.appendEjmlVector("Double", "DMatrix") it.appendEjmlVector("Float", "FMatrix") From 08982855426eefe6ba2cf0987b1da732abba0064 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Wed, 19 May 2021 12:58:01 +0300 Subject: [PATCH 048/132] Removed Any restriction on polynomials --- CHANGELOG.md | 1 + .../space/kscience/kmath/functions/integrate.kt | 4 ++-- .../kmath/functions/matrixIntegration.kt | 4 ++-- .../kscience/kmath/functions/Polynomial.kt | 14 ++++++++------ .../kmath/integration/GaussIntegrator.kt | 13 +++++++------ .../kmath/integration/SimpsonIntegrator.kt | 17 +++++++++++++++++ .../kmath/integration/UnivariateIntegrand.kt | 10 ++++++++++ .../kmath/integration/GaussIntegralTest.kt | 4 ++-- settings.gradle.kts | 2 +- 9 files changed, 50 insertions(+), 19 deletions(-) create mode 100644 kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt diff --git a/CHANGELOG.md b/CHANGELOG.md index acdf9899b..c5acd4660 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -32,6 +32,7 @@ - ColumnarData returns nullable column - MST is made sealed interface - Replaced MST.Symbolic by Symbol, Symbol now implements MST +- Removed Any restriction on polynomials ### Deprecated diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt index 8d5349bce..f60b1ab45 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt @@ -5,8 +5,8 @@ package space.kscience.kmath.functions +import space.kscience.kmath.integration.gaussIntegrator import space.kscience.kmath.integration.integrate -import space.kscience.kmath.integration.integrator import space.kscience.kmath.integration.value import space.kscience.kmath.operations.DoubleField import kotlin.math.pow @@ -16,7 +16,7 @@ fun main() { val function: UnivariateFunction = { x -> 3 * x.pow(2) + 2 * x + 1 } //get the result of the integration - val result = DoubleField.integrator.integrate(0.0..10.0, function = function) + val result = DoubleField.gaussIntegrator.integrate(0.0..10.0, function = function) //the value is nullable because in some cases the integration could not succeed println(result.value) diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt index 601a0e3c4..2619d3d74 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt @@ -5,8 +5,8 @@ package space.kscience.kmath.functions +import space.kscience.kmath.integration.gaussIntegrator import space.kscience.kmath.integration.integrate -import space.kscience.kmath.integration.integrator import space.kscience.kmath.integration.value import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.nd @@ -25,7 +25,7 @@ fun main(): Unit = DoubleField { val function: (Double) -> StructureND = { x: Double -> 3 * number(x).pow(2) + 2 * diagonal(x) + 1 } //get the result of the integration - val result = integrator.integrate(0.0..10.0, function = function) + val result = gaussIntegrator.integrate(0.0..10.0, function = function) //the value is nullable because in some cases the integration could not succeed println(result.value) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt index 325010f99..427a17385 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt @@ -19,7 +19,7 @@ import kotlin.math.pow * * @param coefficients constant is the leftmost coefficient. */ -public class Polynomial(public val coefficients: List){ +public class Polynomial(public val coefficients: List){ override fun toString(): String = "Polynomial$coefficients" } @@ -27,7 +27,7 @@ public class Polynomial(public val coefficients: List){ * Returns a [Polynomial] instance with given [coefficients]. */ @Suppress("FunctionName") -public fun Polynomial(vararg coefficients: T): Polynomial = Polynomial(coefficients.toList()) +public fun Polynomial(vararg coefficients: T): Polynomial = Polynomial(coefficients.toList()) /** * Evaluates the value of the given double polynomial for given double argument. @@ -38,7 +38,7 @@ public fun Polynomial.value(): Double = coefficients.reduceIndexed { ind * Evaluates the value of the given polynomial for given argument. * https://en.wikipedia.org/wiki/Horner%27s_method */ -public fun > Polynomial.value(ring: C, arg: T): T = ring { +public fun > Polynomial.value(ring: C, arg: T): T = ring { if (coefficients.isEmpty()) return@ring zero var result: T = coefficients.last() for (j in coefficients.size - 2 downTo 0) { @@ -50,7 +50,9 @@ public fun > Polynomial.value(ring: C, arg: T): T = ring /** * Represent the polynomial as a regular context-less function. */ -public fun > Polynomial.asFunction(ring: C): (T) -> T = { value(ring, it) } +public fun > Polynomial.asFunction(ring: C): (T) -> T = { value(ring, it) } + +//public fun /** * Space of polynomials. @@ -59,7 +61,7 @@ public fun > Polynomial.asFunction(ring: C): (T) -> T = * @param C the intersection of [Ring] of [T] and [ScaleOperations] of [T]. * @param ring the [C] instance. */ -public class PolynomialSpace( +public class PolynomialSpace( private val ring: C, ) : Group>, ScaleOperations> where C : Ring, C : ScaleOperations { public override val zero: Polynomial = Polynomial(emptyList()) @@ -87,7 +89,7 @@ public class PolynomialSpace( public operator fun Polynomial.invoke(arg: T): T = value(ring, arg) } -public inline fun C.polynomial(block: PolynomialSpace.() -> R): R where C : Ring, C : ScaleOperations { +public inline fun C.polynomial(block: PolynomialSpace.() -> R): R where C : Ring, C : ScaleOperations { contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } return PolynomialSpace(this).block() } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt index fcf47040e..26757ae68 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt @@ -20,6 +20,11 @@ public class UnivariateIntegrandRanges(public val ranges: List( public val algebra: Field, @@ -73,13 +78,9 @@ public class GaussIntegrator( /** * Create a Gauss-Legendre integrator for this field - * Following integrand features are accepted: - * * [GaussIntegratorRuleFactory] - A factory for computing the Gauss integration rule. By default uses [GaussLegendreRuleFactory] - * * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. - * * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. - * * [UnivariateIntegrandRanges] - Set of ranges and number of points per range. Defaults to given [IntegrationRange] and [IntegrandMaxCalls] + * @see [GaussIntegrator] */ -public val Field.integrator: GaussIntegrator get() = GaussIntegrator(this) +public val Field.gaussIntegrator: GaussIntegrator get() = GaussIntegrator(this) /** diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt new file mode 100644 index 000000000..526d4d35d --- /dev/null +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt @@ -0,0 +1,17 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.integration + +import space.kscience.kmath.operations.Ring + + +public class SimpsonIntegrator( + public val algebra: Ring, +) : UnivariateIntegrator { + override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + TODO("Not yet implemented") + } +} \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index 3cafc9782..c03cc8df0 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -45,6 +45,16 @@ public val UnivariateIntegrand.valueOrNull: T? get() = getFeature UnivariateIntegrand.value: T get() = valueOrNull ?: error("No value in the integrand") +/** + * A shortcut method to integrate a [function] with additional [features]. Range must be provided in features. + * The [function] is placed in the end position to allow passing a lambda. + */ +@UnstableKMathAPI +public fun UnivariateIntegrator.integrate( + vararg features: IntegrandFeature, + function: (Double) -> T, +): UnivariateIntegrand = integrate(UnivariateIntegrand(function, *features)) + /** * A shortcut method to integrate a [function] in [range] with additional [features]. * The [function] is placed in the end position to allow passing a lambda. diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt index 6195d0ac6..5c9241120 100644 --- a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt @@ -16,7 +16,7 @@ import kotlin.test.assertEquals class GaussIntegralTest { @Test fun gaussSin() { - val res = DoubleField.integrator.integrate(0.0..2 * PI) { x -> + val res = DoubleField.gaussIntegrator.integrate(0.0..2 * PI) { x -> sin(x) } assertEquals(0.0, res.valueOrNull!!, 1e-2) @@ -24,7 +24,7 @@ class GaussIntegralTest { @Test fun gaussUniform() { - val res = DoubleField.integrator.integrate(35.0..100.0) { x -> + val res = DoubleField.gaussIntegrator.integrate(35.0..100.0) { x -> if(x in 30.0..50.0){ 1.0 } else { diff --git a/settings.gradle.kts b/settings.gradle.kts index 7ebfe1f59..cc9eb4860 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -5,7 +5,7 @@ pluginManagement { maven("https://repo.kotlin.link") } - val toolsVersion = "0.9.7" + val toolsVersion = "0.9.8" val kotlinVersion = "1.5.0" plugins { From 8a07140f7c91e3ff0cf18cdc6ef95b9ac02e59da Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Wed, 19 May 2021 22:35:06 +0300 Subject: [PATCH 049/132] Minor piecewise rework --- .../kscience/kmath/functions/interpolate.kt | 2 + .../kscience/kmath/functions/Piecewise.kt | 34 +++++++++---- .../kscience/kmath/functions/Polynomial.kt | 48 +++++++++++++++---- .../kmath/interpolation/LinearInterpolator.kt | 3 +- .../kmath/interpolation/SplineInterpolator.kt | 3 +- .../kmath/functions/PolynomialTest.kt | 17 +++++++ .../kmath/histogram/TreeHistogramSpace.kt | 11 ++--- .../kmath/histogram/UnivariateHistogram.kt | 5 +- 8 files changed, 91 insertions(+), 32 deletions(-) create mode 100644 kmath-functions/src/commonTest/kotlin/space/kscience/kmath/functions/PolynomialTest.kt diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt index 69ba80fb6..b05c003a6 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt @@ -10,12 +10,14 @@ import space.kscience.kmath.interpolation.interpolatePolynomials import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.structures.DoubleBuffer import space.kscience.plotly.Plotly +import space.kscience.plotly.UnstablePlotlyAPI import space.kscience.plotly.makeFile import space.kscience.plotly.models.functionXY import space.kscience.plotly.scatter import kotlin.math.PI import kotlin.math.sin +@OptIn(UnstablePlotlyAPI::class) fun main() { val data = (0..10).map { val x = it.toDouble() / 5 * PI diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt index 6bb2a1656..dd9c571b0 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt @@ -22,8 +22,20 @@ public fun interface Piecewise { /** * Represents piecewise-defined function where all the sub-functions are polynomials. + * @param pieces An ordered list of range-polynomial pairs. The list does not in general guarantee that there are no "holes" in it. */ -public fun interface PiecewisePolynomial : Piecewise> +public class PiecewisePolynomial>( + public val pieces: List, Polynomial>>, +) : Piecewise> { + + public override fun findPiece(arg: T): Polynomial? { + return if (arg < pieces.first().first.start || arg >= pieces.last().first.endInclusive) + null + else { + pieces.firstOrNull { arg in it.first }?.second + } + } +} /** * A [Piecewise] builder where all the pieces are ordered by the [Comparable] type instances. @@ -31,7 +43,7 @@ public fun interface PiecewisePolynomial : Piecewise> * @param T the comparable piece key type. * @param delimiter the initial piecewise separator */ -public class OrderedPiecewisePolynomial>(delimiter: T) : PiecewisePolynomial { +public class PiecewiseBuilder>(delimiter: T) { private val delimiters: MutableList = arrayListOf(delimiter) private val pieces: MutableList> = arrayListOf() @@ -59,17 +71,19 @@ public class OrderedPiecewisePolynomial>(delimiter: T) : Piece pieces.add(0, piece) } - public override fun findPiece(arg: T): Polynomial? { - if (arg < delimiters.first() || arg >= delimiters.last()) - return null - else { - for (index in 1 until delimiters.size) - if (arg < delimiters[index]) return pieces[index - 1] - error("Piece not found") - } + public fun build(): PiecewisePolynomial { + return PiecewisePolynomial(delimiters.zipWithNext { l, r -> l..r }.zip(pieces)) } } +/** + * A builder for [PiecewisePolynomial] + */ +public fun > PiecewisePolynomial( + startingPoint: T, + builder: PiecewiseBuilder.() -> Unit, +): PiecewisePolynomial = PiecewiseBuilder(startingPoint).apply(builder).build() + /** * Return a value of polynomial function with given [ring] an given [arg] or null if argument is outside of piecewise * definition. diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt index 427a17385..4976befcb 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt @@ -5,10 +5,8 @@ package space.kscience.kmath.functions -import space.kscience.kmath.operations.Group -import space.kscience.kmath.operations.Ring -import space.kscience.kmath.operations.ScaleOperations -import space.kscience.kmath.operations.invoke +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.* import kotlin.contracts.InvocationKind import kotlin.contracts.contract import kotlin.math.max @@ -19,7 +17,7 @@ import kotlin.math.pow * * @param coefficients constant is the leftmost coefficient. */ -public class Polynomial(public val coefficients: List){ +public class Polynomial(public val coefficients: List) { override fun toString(): String = "Polynomial$coefficients" } @@ -32,7 +30,9 @@ public fun Polynomial(vararg coefficients: T): Polynomial = Polynomial(co /** * Evaluates the value of the given double polynomial for given double argument. */ -public fun Polynomial.value(): Double = coefficients.reduceIndexed { index, acc, d -> acc + d.pow(index) } +public fun Polynomial.value(arg: Double): Double = coefficients.reduceIndexed { index, acc, c -> + acc + c * arg.pow(index) +} /** * Evaluates the value of the given polynomial for given argument. @@ -50,9 +50,38 @@ public fun > Polynomial.value(ring: C, arg: T): T = ring { /** * Represent the polynomial as a regular context-less function. */ -public fun > Polynomial.asFunction(ring: C): (T) -> T = { value(ring, it) } +public fun > Polynomial.asFunction(ring: C): (T) -> T = { value(ring, it) } -//public fun +/** + * Create a polynomial witch represents differentiated version of this polynomial + */ +@UnstableKMathAPI +public fun Polynomial.differentiate( + algebra: A, +): Polynomial where A : Ring, A : NumericAlgebra = algebra { + Polynomial(coefficients.drop(1).mapIndexed { index, t -> number(index) * t }) +} + +/** + * Create a polynomial witch represents indefinite integral version of this polynomial + */ +@UnstableKMathAPI +public fun Polynomial.integrate( + algebra: A, +): Polynomial where A : Field, A : NumericAlgebra = algebra { + Polynomial(coefficients.mapIndexed { index, t -> t / number(index) }) +} + +/** + * Compute a definite integral of a given polynomial in a [range] + */ +@UnstableKMathAPI +public fun , A> Polynomial.integrate( + algebra: A, + range: ClosedRange, +): T where A : Field, A : NumericAlgebra = algebra { + value(algebra, range.endInclusive) - value(algebra, range.start) +} /** * Space of polynomials. @@ -87,6 +116,9 @@ public class PolynomialSpace( * Evaluates the polynomial for the given value [arg]. */ public operator fun Polynomial.invoke(arg: T): T = value(ring, arg) + + public fun Polynomial.asFunction(): (T) -> T = asFunction(ring) + } public inline fun C.polynomial(block: PolynomialSpace.() -> R): R where C : Ring, C : ScaleOperations { diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt index 3fbf6157e..24c049647 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt @@ -6,7 +6,6 @@ package space.kscience.kmath.interpolation import space.kscience.kmath.data.XYColumnarData -import space.kscience.kmath.functions.OrderedPiecewisePolynomial import space.kscience.kmath.functions.PiecewisePolynomial import space.kscience.kmath.functions.Polynomial import space.kscience.kmath.misc.UnstableKMathAPI @@ -28,7 +27,7 @@ public class LinearInterpolator>(public override val algebra: require(points.size > 0) { "Point array should not be empty" } insureSorted(points) - OrderedPiecewisePolynomial(points.x[0]).apply { + PiecewisePolynomial(points.x[0]) { for (i in 0 until points.size - 1) { val slope = (points.y[i + 1] - points.y[i]) / (points.x[i + 1] - points.x[i]) val const = points.y[i] - slope * points.x[i] diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt index c3d6ffae7..bf291c315 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt @@ -6,7 +6,6 @@ package space.kscience.kmath.interpolation import space.kscience.kmath.data.XYColumnarData -import space.kscience.kmath.functions.OrderedPiecewisePolynomial import space.kscience.kmath.functions.PiecewisePolynomial import space.kscience.kmath.functions.Polynomial import space.kscience.kmath.misc.UnstableKMathAPI @@ -50,7 +49,7 @@ public class SplineInterpolator>( // cubic spline coefficients -- b is linear, c quadratic, d is cubic (original y's are constants) - OrderedPiecewisePolynomial(points.x[points.size - 1]).apply { + PiecewisePolynomial(points.x[points.size - 1]) { var cOld = zero for (j in n - 1 downTo 0) { diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/functions/PolynomialTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/functions/PolynomialTest.kt new file mode 100644 index 000000000..05c16d17e --- /dev/null +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/functions/PolynomialTest.kt @@ -0,0 +1,17 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.functions + +import kotlin.test.Test +import kotlin.test.assertEquals + +class PolynomialTest { + @Test + fun testIntegration() { + val polynomial = Polynomial(1.0, -2.0, 1.0) + assertEquals(0.0, polynomial.value(1.0), 0.001) + } +} \ No newline at end of file diff --git a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt index 5a217f6c2..6ae8b5ee3 100644 --- a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt +++ b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt @@ -28,7 +28,6 @@ private fun > TreeMap.getBin(val @UnstableKMathAPI public class TreeHistogram( - override val context: TreeHistogramSpace, private val binMap: TreeMap, ) : UnivariateHistogram { override fun get(value: Double): UnivariateBin? = binMap.getBin(value) @@ -79,15 +78,15 @@ public class TreeHistogramSpace( val count = binCounter.counter.value resBins[key] = UnivariateBin(binCounter.domain, count, sqrt(count)) } - return TreeHistogram(this, resBins) + return TreeHistogram(resBins) } override fun add( a: UnivariateHistogram, b: UnivariateHistogram, ): UnivariateHistogram { - require(a.context == this) { "Histogram $a does not belong to this context" } - require(b.context == this) { "Histogram $b does not belong to this context" } +// require(a.context == this) { "Histogram $a does not belong to this context" } +// require(b.context == this) { "Histogram $b does not belong to this context" } val bins = TreeMap().apply { (a.bins.map { it.domain } union b.bins.map { it.domain }).forEach { def -> put(def.center, @@ -100,7 +99,7 @@ public class TreeHistogramSpace( ) } } - return TreeHistogram(this, bins) + return TreeHistogram(bins) } override fun scale(a: UnivariateHistogram, value: Double): UnivariateHistogram { @@ -116,7 +115,7 @@ public class TreeHistogramSpace( } } - return TreeHistogram(this, bins) + return TreeHistogram(bins) } override fun UnivariateHistogram.unaryMinus(): UnivariateHistogram = this * (-1) diff --git a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt index 645116ade..70125e22e 100644 --- a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt +++ b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt @@ -7,8 +7,6 @@ package space.kscience.kmath.histogram import space.kscience.kmath.domains.UnivariateDomain import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.Group -import space.kscience.kmath.operations.GroupElement import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.asSequence @@ -35,8 +33,7 @@ public class UnivariateBin( } @OptIn(UnstableKMathAPI::class) -public interface UnivariateHistogram : Histogram, - GroupElement> { +public interface UnivariateHistogram : Histogram{ public operator fun get(value: Double): UnivariateBin? public override operator fun get(point: Buffer): UnivariateBin? = get(point[0]) From d7a4228f5f5da85d425d6778080f8ab38488ee0e Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Thu, 20 May 2021 19:43:29 +0700 Subject: [PATCH 050/132] Add out variance to StructureND and some related types, make some unrelated changes --- CHANGELOG.md | 19 ++++++++++--------- README.md | 15 +++++++-------- docs/templates/README-TEMPLATE.md | 2 +- .../space/kscience/kmath/tensors/PCA.kt | 2 +- kmath-ast/README.md | 6 +++--- kmath-complex/README.md | 6 +++--- kmath-core/README.md | 6 +++--- .../kscience/kmath/linear/MatrixBuilder.kt | 2 +- .../kscience/kmath/linear/MatrixWrapper.kt | 13 ++++++------- .../kscience/kmath/linear/VirtualMatrix.kt | 2 +- .../space/kscience/kmath/nd/AlgebraND.kt | 8 ++++---- .../kscience/kmath/nd/BufferAlgebraND.kt | 2 +- .../space/kscience/kmath/nd/BufferND.kt | 2 +- .../space/kscience/kmath/nd/Structure1D.kt | 12 ++++++++---- .../space/kscience/kmath/nd/Structure2D.kt | 4 ++-- .../space/kscience/kmath/nd/StructureND.kt | 6 ++---- .../space/kscience/kmath/structures/Buffer.kt | 2 +- .../kmath/structures/FlaggedBuffer.kt | 2 +- .../kmath/expressions/SimpleAutoDiffTest.kt | 2 +- .../kmath/structures/LazyStructureND.kt | 2 +- kmath-ejml/README.md | 6 +++--- .../space/kscience/kmath/ejml/EjmlMatrix.kt | 2 +- kmath-for-real/README.md | 6 +++--- kmath-functions/README.md | 6 +++--- kmath-kotlingrad/README.md | 8 ++++---- kmath-memory/build.gradle.kts | 2 +- kmath-nd4j/README.md | 6 +++--- kmath-tensors/README.md | 14 +++++++------- 28 files changed, 83 insertions(+), 82 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index c5acd4660..274a403b1 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -20,19 +20,20 @@ - Space is replaced by Group. Space is reserved for vector spaces. - VectorSpace is now a vector space - Buffer factories for primitives moved to MutableBuffer.Companion -- NDStructure and NDAlgebra to StructureND and AlgebraND respectively -- Real -> Double +- Rename `NDStructure` and `NDAlgebra` to `StructureND` and `AlgebraND` respectively +- `Real` -> `Double` - DataSets are moved from functions to core - Redesign advanced Chain API -- Redesign MST. Remove MSTExpression. -- Move MST to core +- Redesign `MST`. Remove `MstExpression`. +- Move `MST` to core - Separated benchmarks and examples -- Rewritten EJML module without ejml-simple -- Stability of kmath-ast and kmath-kotilngrad promoted to EXPERIMENTAL. +- Rewrite `kmath-ejml` without `ejml-simple` artifact, support sparse matrices +- Promote stability of kmath-ast and kmath-kotlingrad to EXPERIMENTAL. - ColumnarData returns nullable column -- MST is made sealed interface -- Replaced MST.Symbolic by Symbol, Symbol now implements MST -- Removed Any restriction on polynomials +- `MST` is made sealed interface +- Replace `MST.Symbolic` by `Symbol`, `Symbol` now implements MST +- Remove Any restriction on polynomials +- Add `out` variance to type parameters of `StructureND` and its implementations where possible ### Deprecated diff --git a/README.md b/README.md index 519472a69..9117582ac 100644 --- a/README.md +++ b/README.md @@ -40,7 +40,7 @@ KMath is a modular library. Different modules provide different features with di * **PROTOTYPE**. On this level there are no compatibility guarantees. All methods and classes form those modules could break any moment. You can still use it, but be sure to fix the specific version. * **EXPERIMENTAL**. The general API is decided, but some changes could be made. Volatile API is marked with `@UnstableKmathAPI` or other stability warning annotations. -* **DEVELOPMENT**. API breaking genrally follows semantic versioning ideology. There could be changes in minor versions, but not in patch versions. API is protected with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool. +* **DEVELOPMENT**. API breaking generally follows semantic versioning ideology. There could be changes in minor versions, but not in patch versions. API is protected with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool. * **STABLE**. The API stabilized. Breaking changes are allowed only in major releases. @@ -213,7 +213,7 @@ One can still use generic algebras though. > > **Features:** > - [differentiable-mst-expression](kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : MST based DifferentiableExpression. -> - [differentiable-mst-expression](kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : Conversions between Kotlin∇'s SFun and MST +> - [differentiable-mst-expression](kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : Conversions between Kotlin∇'s SFun and MST
@@ -247,10 +247,9 @@ One can still use generic algebras though. > **Maturity**: PROTOTYPE > > **Features:** -> - [tensor algebra](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Interface for basic linear algebra operations on tensors (plus, dot, etc.) -> - [linear algebra operations](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Interface for advanced linear algebra operations like LU decomposition, SVD, etc. -> - [tensor algebra over Double](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt): Full implementation of operations for tensors over `Double`'s. -> - [tensor algebra with broadcasting](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting for tensors over `Double`'s. +> - [tensor algebra](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Basic linear algebra operations on tensors (plus, dot, etc.) +> - [tensor algebra with broadcasting](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting. +> - [linear algebra operations](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Advanced linear algebra operations like LU decomposition, SVD, etc.
@@ -294,8 +293,8 @@ repositories { } dependencies { - api("space.kscience:kmath-core:0.3.0-dev-8") - // api("space.kscience:kmath-core-jvm:0.3.0-dev-8") for jvm-specific version + api("space.kscience:kmath-core:0.3.0-dev-11") + // api("space.kscience:kmath-core-jvm:0.3.0-dev-11") for jvm-specific version } ``` diff --git a/docs/templates/README-TEMPLATE.md b/docs/templates/README-TEMPLATE.md index 99951b4d6..6bb1e9085 100644 --- a/docs/templates/README-TEMPLATE.md +++ b/docs/templates/README-TEMPLATE.md @@ -40,7 +40,7 @@ KMath is a modular library. Different modules provide different features with di * **PROTOTYPE**. On this level there are no compatibility guarantees. All methods and classes form those modules could break any moment. You can still use it, but be sure to fix the specific version. * **EXPERIMENTAL**. The general API is decided, but some changes could be made. Volatile API is marked with `@UnstableKmathAPI` or other stability warning annotations. -* **DEVELOPMENT**. API breaking genrally follows semantic versioning ideology. There could be changes in minor versions, but not in patch versions. API is protected with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool. +* **DEVELOPMENT**. API breaking generally follows semantic versioning ideology. There could be changes in minor versions, but not in patch versions. API is protected with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool. * **STABLE**. The API stabilized. Breaking changes are allowed only in major releases. diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt index e47b87177..411e048d7 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt @@ -11,7 +11,7 @@ import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra // simple PCA -fun main() = BroadcastDoubleTensorAlgebra { // work in context with broadcast methods +fun main(): Unit = BroadcastDoubleTensorAlgebra { // work in context with broadcast methods val seed = 100500L // assume x is range from 0 until 10 diff --git a/kmath-ast/README.md b/kmath-ast/README.md index 646ab4306..b0f2d59e5 100644 --- a/kmath-ast/README.md +++ b/kmath-ast/README.md @@ -10,7 +10,7 @@ Performance and visualization extensions to MST API. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-8`. +The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-11`. **Gradle:** ```gradle @@ -20,7 +20,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-ast:0.3.0-dev-8' + implementation 'space.kscience:kmath-ast:0.3.0-dev-11' } ``` **Gradle Kotlin DSL:** @@ -31,7 +31,7 @@ repositories { } dependencies { - implementation("space.kscience:kmath-ast:0.3.0-dev-8") + implementation("space.kscience:kmath-ast:0.3.0-dev-11") } ``` diff --git a/kmath-complex/README.md b/kmath-complex/README.md index ee5ad416f..04431cf6c 100644 --- a/kmath-complex/README.md +++ b/kmath-complex/README.md @@ -8,7 +8,7 @@ Complex and hypercomplex number systems in KMath. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-complex:0.3.0-dev-8`. +The Maven coordinates of this project are `space.kscience:kmath-complex:0.3.0-dev-11`. **Gradle:** ```gradle @@ -18,7 +18,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-complex:0.3.0-dev-8' + implementation 'space.kscience:kmath-complex:0.3.0-dev-11' } ``` **Gradle Kotlin DSL:** @@ -29,6 +29,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-complex:0.3.0-dev-8") + implementation("space.kscience:kmath-complex:0.3.0-dev-11") } ``` diff --git a/kmath-core/README.md b/kmath-core/README.md index 7283a18ce..700eaef38 100644 --- a/kmath-core/README.md +++ b/kmath-core/README.md @@ -15,7 +15,7 @@ performance calculations to code generation. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-core:0.3.0-dev-8`. +The Maven coordinates of this project are `space.kscience:kmath-core:0.3.0-dev-11`. **Gradle:** ```gradle @@ -25,7 +25,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-core:0.3.0-dev-8' + implementation 'space.kscience:kmath-core:0.3.0-dev-11' } ``` **Gradle Kotlin DSL:** @@ -36,6 +36,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-core:0.3.0-dev-8") + implementation("space.kscience:kmath-core:0.3.0-dev-11") } ``` diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixBuilder.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixBuilder.kt index e6115a1e5..72d22233a 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixBuilder.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixBuilder.kt @@ -8,7 +8,7 @@ package space.kscience.kmath.linear import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.Ring -public class MatrixBuilder>( +public class MatrixBuilder>( public val linearSpace: LinearSpace, public val rows: Int, public val columns: Int, diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt index 4d1180c17..16aadab3b 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt @@ -16,7 +16,7 @@ import kotlin.reflect.KClass * * @param T the type of items. */ -public class MatrixWrapper internal constructor( +public class MatrixWrapper internal constructor( public val origin: Matrix, public val features: Set, ) : Matrix by origin { @@ -26,12 +26,11 @@ public class MatrixWrapper internal constructor( */ @UnstableKMathAPI @Suppress("UNCHECKED_CAST") - override fun getFeature(type: KClass): F? = features.singleOrNull { type.isInstance(it) } as? F - ?: origin.getFeature(type) + public override fun getFeature(type: KClass): F? = + features.singleOrNull(type::isInstance) as? F + ?: origin.getFeature(type) - override fun toString(): String { - return "MatrixWrapper(matrix=$origin, features=$features)" - } + public override fun toString(): String = "MatrixWrapper(matrix=$origin, features=$features)" } /** @@ -82,7 +81,7 @@ public fun LinearSpace>.zero( elementAlgebra.zero } + ZeroFeature -public class TransposedFeature(public val original: Matrix) : MatrixFeature +public class TransposedFeature(public val original: Matrix) : MatrixFeature /** * Create a virtual transposed matrix without copying anything. `A.transpose().transpose() === A` diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt index e4c2b49f0..3751bd33b 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt @@ -10,7 +10,7 @@ package space.kscience.kmath.linear * * @property generator the function that provides elements. */ -public class VirtualMatrix( +public class VirtualMatrix( override val rowNum: Int, override val colNum: Int, public val generator: (i: Int, j: Int) -> T, diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt index 1b3cb9e0a..93187eb41 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt @@ -26,7 +26,7 @@ public class ShapeMismatchException(public val expected: IntArray, public val ac * @param C the type of the element context. * @param N the type of the structure. */ -public interface AlgebraND> { +public interface AlgebraND> { /** * The shape of ND-structures this algebra operates on. */ @@ -121,7 +121,7 @@ internal fun > AlgebraND.checkShape(element: StructureND * @param N the type of ND structure. * @param S the type of space of structure elements. */ -public interface GroupND> : Group>, AlgebraND { +public interface GroupND> : Group>, AlgebraND { /** * Element-wise addition. * @@ -189,7 +189,7 @@ public interface GroupND> : Group>, AlgebraND> : Ring>, GroupND { +public interface RingND> : Ring>, GroupND { /** * Element-wise multiplication. * @@ -230,7 +230,7 @@ public interface RingND> : Ring>, GroupND { * @param N the type of ND structure. * @param F the type field of structure elements. */ -public interface FieldND> : Field>, RingND, ScaleOperations> { +public interface FieldND> : Field>, RingND, ScaleOperations> { /** * Element-wise division. * diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt index 905a48d5c..2b82a36ae 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt @@ -11,7 +11,7 @@ import space.kscience.kmath.structures.BufferFactory import kotlin.contracts.InvocationKind import kotlin.contracts.contract -public interface BufferAlgebraND> : AlgebraND { +public interface BufferAlgebraND> : AlgebraND { public val strides: Strides public val bufferFactory: BufferFactory diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferND.kt index 425808aeb..904419302 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferND.kt @@ -18,7 +18,7 @@ import space.kscience.kmath.structures.MutableBufferFactory * @param strides The strides to access elements of [Buffer] by linear indices. * @param buffer The underlying buffer. */ -public open class BufferND( +public open class BufferND( public val strides: Strides, public val buffer: Buffer, ) : StructureND { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt index cc0528793..150ebf6fb 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt @@ -15,7 +15,7 @@ import kotlin.jvm.JvmInline /** * A structure that is guaranteed to be one-dimensional */ -public interface Structure1D : StructureND, Buffer { +public interface Structure1D : StructureND, Buffer { public override val dimension: Int get() = 1 public override operator fun get(index: IntArray): T { @@ -42,7 +42,7 @@ public interface MutableStructure1D : Structure1D, MutableStructureND, * A 1D wrapper for nd-structure */ @JvmInline -private value class Structure1DWrapper(val structure: StructureND) : Structure1D { +private value class Structure1DWrapper(val structure: StructureND) : Structure1D { override val shape: IntArray get() = structure.shape override val size: Int get() = structure.shape[0] @@ -68,7 +68,11 @@ private class MutableStructure1DWrapper(val structure: MutableStructureND) } @PerformancePitfall - override fun copy(): MutableBuffer = structure.elements().map { it.second }.toMutableList().asMutableBuffer() + override fun copy(): MutableBuffer = structure + .elements() + .map(Pair::second) + .toMutableList() + .asMutableBuffer() } @@ -76,7 +80,7 @@ private class MutableStructure1DWrapper(val structure: MutableStructureND) * A structure wrapper for buffer */ @JvmInline -private value class Buffer1DWrapper(val buffer: Buffer) : Structure1D { +private value class Buffer1DWrapper(val buffer: Buffer) : Structure1D { override val shape: IntArray get() = intArrayOf(buffer.size) override val size: Int get() = buffer.size diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt index 5b8183699..f353b6974 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt @@ -18,7 +18,7 @@ import kotlin.reflect.KClass * * @param T the type of items. */ -public interface Structure2D : StructureND { +public interface Structure2D : StructureND { /** * The number of rows in this structure. */ @@ -100,7 +100,7 @@ public interface MutableStructure2D : Structure2D, MutableStructureND { * A 2D wrapper for nd-structure */ @JvmInline -private value class Structure2DWrapper(val structure: StructureND) : Structure2D { +private value class Structure2DWrapper(val structure: StructureND) : Structure2D { override val shape: IntArray get() = structure.shape override val rowNum: Int get() = shape[0] diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt index b9f1a063a..7fc91e321 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt @@ -24,7 +24,7 @@ public interface StructureFeature * * @param T the type of items. */ -public interface StructureND { +public interface StructureND { /** * The shape of structure, i.e. non-empty sequence of non-negative integers that specify sizes of dimensions of * this structure. @@ -213,9 +213,7 @@ public interface Strides { /** * Iterate over ND indices in a natural order */ - public fun indices(): Sequence = (0 until linearSize).asSequence().map { - index(it) - } + public fun indices(): Sequence = (0 until linearSize).asSequence().map(::index) } /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt index be5dfb359..82f17b807 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt @@ -283,7 +283,7 @@ public value class ReadOnlyBuffer(public val buffer: MutableBuffer) : Buff * * @param T the type of elements provided by the buffer. */ -public class VirtualBuffer(override val size: Int, private val generator: (Int) -> T) : Buffer { +public class VirtualBuffer(override val size: Int, private val generator: (Int) -> T) : Buffer { override operator fun get(index: Int): T { if (index < 0 || index >= size) throw IndexOutOfBoundsException("Expected index from 0 to ${size - 1}, but found $index") return generator(index) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt index a63f452f5..0b16a3afc 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt @@ -37,7 +37,7 @@ public enum class ValueFlag(public val mask: Byte) { /** * A buffer with flagged values. */ -public interface FlaggedBuffer : Buffer { +public interface FlaggedBuffer : Buffer { public fun getFlag(index: Int): Byte } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/SimpleAutoDiffTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/SimpleAutoDiffTest.kt index c6852cbbf..201890933 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/SimpleAutoDiffTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/SimpleAutoDiffTest.kt @@ -17,7 +17,7 @@ import kotlin.test.Test import kotlin.test.assertEquals import kotlin.test.assertTrue -class SimpleAutoDiffTest { +internal class SimpleAutoDiffTest { fun dx( xBinding: Pair, diff --git a/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt b/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt index 1cd16054a..ded8c9c44 100644 --- a/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt +++ b/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt @@ -11,7 +11,7 @@ import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.DefaultStrides import space.kscience.kmath.nd.StructureND -public class LazyStructureND( +public class LazyStructureND( public val scope: CoroutineScope, public override val shape: IntArray, public val function: suspend (IntArray) -> T, diff --git a/kmath-ejml/README.md b/kmath-ejml/README.md index cb12ef98d..79a28b824 100644 --- a/kmath-ejml/README.md +++ b/kmath-ejml/README.md @@ -9,7 +9,7 @@ EJML based linear algebra implementation. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-ejml:0.3.0-dev-8`. +The Maven coordinates of this project are `space.kscience:kmath-ejml:0.3.0-dev-11`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-ejml:0.3.0-dev-8' + implementation 'space.kscience:kmath-ejml:0.3.0-dev-11' } ``` **Gradle Kotlin DSL:** @@ -30,6 +30,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-ejml:0.3.0-dev-8") + implementation("space.kscience:kmath-ejml:0.3.0-dev-11") } ``` diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt index fd43f295c..cec31eb7d 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt @@ -16,7 +16,7 @@ import space.kscience.kmath.nd.Structure2D * @property origin The underlying EJML matrix. * @author Iaroslav Postovalov */ -public abstract class EjmlMatrix(public open val origin: M) : Structure2D { +public abstract class EjmlMatrix(public open val origin: M) : Structure2D { public override val rowNum: Int get() = origin.numRows public override val colNum: Int get() = origin.numCols } diff --git a/kmath-for-real/README.md b/kmath-for-real/README.md index 8b3b8e9e0..5ca805093 100644 --- a/kmath-for-real/README.md +++ b/kmath-for-real/README.md @@ -9,7 +9,7 @@ Specialization of KMath APIs for Double numbers. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-for-real:0.3.0-dev-8`. +The Maven coordinates of this project are `space.kscience:kmath-for-real:0.3.0-dev-11`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-for-real:0.3.0-dev-8' + implementation 'space.kscience:kmath-for-real:0.3.0-dev-11' } ``` **Gradle Kotlin DSL:** @@ -30,6 +30,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-for-real:0.3.0-dev-8") + implementation("space.kscience:kmath-for-real:0.3.0-dev-11") } ``` diff --git a/kmath-functions/README.md b/kmath-functions/README.md index 4f592c845..2497f7102 100644 --- a/kmath-functions/README.md +++ b/kmath-functions/README.md @@ -11,7 +11,7 @@ Functions and interpolations. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-functions:0.3.0-dev-8`. +The Maven coordinates of this project are `space.kscience:kmath-functions:0.3.0-dev-11`. **Gradle:** ```gradle @@ -21,7 +21,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-functions:0.3.0-dev-8' + implementation 'space.kscience:kmath-functions:0.3.0-dev-11' } ``` **Gradle Kotlin DSL:** @@ -32,6 +32,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-functions:0.3.0-dev-8") + implementation("space.kscience:kmath-functions:0.3.0-dev-11") } ``` diff --git a/kmath-kotlingrad/README.md b/kmath-kotlingrad/README.md index 686df3271..4393cbf8c 100644 --- a/kmath-kotlingrad/README.md +++ b/kmath-kotlingrad/README.md @@ -1,6 +1,6 @@ # Module kmath-kotlingrad -[Kotlin∇](https://github.com/breandan/kotlingrad) integration module. +[Kotlin∇](https://www.htmlsymbols.xyz/unicode/U+2207) integration module. - [differentiable-mst-expression](src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : MST based DifferentiableExpression. - [differentiable-mst-expression](src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : Conversions between Kotlin∇'s SFun and MST @@ -8,7 +8,7 @@ ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-kotlingrad:0.3.0-dev-8`. +The Maven coordinates of this project are `space.kscience:kmath-kotlingrad:0.3.0-dev-11`. **Gradle:** ```gradle @@ -18,7 +18,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-kotlingrad:0.3.0-dev-8' + implementation 'space.kscience:kmath-kotlingrad:0.3.0-dev-11' } ``` **Gradle Kotlin DSL:** @@ -29,6 +29,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-kotlingrad:0.3.0-dev-8") + implementation("space.kscience:kmath-kotlingrad:0.3.0-dev-11") } ``` diff --git a/kmath-memory/build.gradle.kts b/kmath-memory/build.gradle.kts index 288c61a51..4478e5b80 100644 --- a/kmath-memory/build.gradle.kts +++ b/kmath-memory/build.gradle.kts @@ -7,6 +7,6 @@ plugins { readme { maturity = ru.mipt.npm.gradle.Maturity.DEVELOPMENT description = """ - An API and basic implementation for arranging objects in a continous memory block. + An API and basic implementation for arranging objects in a continuous memory block. """.trimIndent() } diff --git a/kmath-nd4j/README.md b/kmath-nd4j/README.md index 5f33c1db1..6408be13b 100644 --- a/kmath-nd4j/README.md +++ b/kmath-nd4j/README.md @@ -9,7 +9,7 @@ ND4J based implementations of KMath abstractions. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-nd4j:0.3.0-dev-8`. +The Maven coordinates of this project are `space.kscience:kmath-nd4j:0.3.0-dev-11`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-nd4j:0.3.0-dev-8' + implementation 'space.kscience:kmath-nd4j:0.3.0-dev-11' } ``` **Gradle Kotlin DSL:** @@ -30,7 +30,7 @@ repositories { } dependencies { - implementation("space.kscience:kmath-nd4j:0.3.0-dev-8") + implementation("space.kscience:kmath-nd4j:0.3.0-dev-11") } ``` diff --git a/kmath-tensors/README.md b/kmath-tensors/README.md index affdad665..75de2bf35 100644 --- a/kmath-tensors/README.md +++ b/kmath-tensors/README.md @@ -2,14 +2,14 @@ Common linear algebra operations on tensors. - - [tensor algebra](src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Interface for basic linear algebra operations on tensors (plus, dot, etc.) - - [linear algebra operations](src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Interface for advanced linear algebra operations like LU decomposition, SVD, etc. - - [tensor algebra over Double](src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt): Full implementation of operations for tensors over `Double`'s. - - [tensor algebra with broadcasting](src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting for tensors over `Double`'s. + - [tensor algebra](src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Basic linear algebra operations on tensors (plus, dot, etc.) + - [tensor algebra with broadcasting](src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting. + - [linear algebra operations](src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Advanced linear algebra operations like LU decomposition, SVD, etc. + ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-tensors:0.3.0-dev-8`. +The Maven coordinates of this project are `space.kscience:kmath-tensors:0.3.0-dev-11`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-tensors:0.3.0-dev-8' + implementation 'space.kscience:kmath-tensors:0.3.0-dev-11' } ``` **Gradle Kotlin DSL:** @@ -30,6 +30,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-tensors:0.3.0-dev-8") + implementation("space.kscience:kmath-tensors:0.3.0-dev-11") } ``` From 15a0258b7d860c861239d26d33528935ce98083c Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Fri, 14 May 2021 00:37:33 +0700 Subject: [PATCH 051/132] Nd4j based TensorAlgebra implementation, drop Nd4jArrayLongStructure --- .../space/kscience/kmath/nd/AlgebraND.kt | 1 - kmath-nd4j/build.gradle.kts | 20 +- .../kscience/kmath/nd4j/Nd4jArrayAlgebra.kt | 179 ++++++++---------- .../kscience/kmath/nd4j/Nd4jArrayIterator.kt | 6 - .../kscience/kmath/nd4j/Nd4jArrayStructure.kt | 15 +- .../kscience/kmath/nd4j/Nd4jTensorAlgebra.kt | 175 +++++++++++++++++ .../space/kscience/kmath/nd4j/arrays.kt | 1 - .../kmath/nd4j/Nd4jArrayAlgebraTest.kt | 2 +- .../kmath/nd4j/Nd4jArrayStructureTest.kt | 2 +- .../kmath/tensors/api/TensorAlgebra.kt | 22 +-- .../kmath/tensors/core/DoubleTensorAlgebra.kt | 23 +-- 11 files changed, 280 insertions(+), 166 deletions(-) create mode 100644 kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt index 93187eb41..35bbc44f6 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt @@ -227,7 +227,6 @@ public interface RingND> : Ring>, GroupND> : Field>, RingND, ScaleOperations> { diff --git a/kmath-nd4j/build.gradle.kts b/kmath-nd4j/build.gradle.kts index bc61060db..12ea5c130 100644 --- a/kmath-nd4j/build.gradle.kts +++ b/kmath-nd4j/build.gradle.kts @@ -4,7 +4,7 @@ plugins { } dependencies { - api(project(":kmath-core")) + api(project(":kmath-tensors")) api("org.nd4j:nd4j-api:1.0.0-beta7") testImplementation("org.nd4j:nd4j-native:1.0.0-beta7") testImplementation("org.nd4j:nd4j-native-platform:1.0.0-beta7") @@ -15,19 +15,7 @@ readme { description = "ND4J NDStructure implementation and according NDAlgebra classes" maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL propertyByTemplate("artifact", rootProject.file("docs/templates/ARTIFACT-TEMPLATE.md")) - - feature( - id = "nd4jarraystructure", - description = "NDStructure wrapper for INDArray" - ) - - feature( - id = "nd4jarrayrings", - description = "Rings over Nd4jArrayStructure of Int and Long" - ) - - feature( - id = "nd4jarrayfields", - description = "Fields over Nd4jArrayStructure of Float and Double" - ) + feature(id = "nd4jarraystructure") { "NDStructure wrapper for INDArray" } + feature(id = "nd4jarrayrings") { "Rings over Nd4jArrayStructure of Int and Long" } + feature(id = "nd4jarrayfields") { "Fields over Nd4jArrayStructure of Float and Double" } } diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt index 3cac44c47..e94bda12a 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt @@ -6,15 +6,14 @@ package space.kscience.kmath.nd4j import org.nd4j.linalg.api.ndarray.INDArray -import org.nd4j.linalg.api.ops.impl.scalar.Pow -import org.nd4j.linalg.api.ops.impl.transforms.strict.* +import org.nd4j.linalg.api.ops.impl.transforms.strict.ACosh +import org.nd4j.linalg.api.ops.impl.transforms.strict.ASinh import org.nd4j.linalg.factory.Nd4j import org.nd4j.linalg.ops.transforms.Transforms import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.* import space.kscience.kmath.operations.* -import space.kscience.kmath.structures.* internal fun AlgebraND<*, *>.checkShape(array: INDArray): INDArray { val arrayShape = array.shape().toIntArray() @@ -29,23 +28,16 @@ internal fun AlgebraND<*, *>.checkShape(array: INDArray): INDArray { * @param T the type of ND-structure element. * @param C the type of the element context. */ -public interface Nd4jArrayAlgebra> : AlgebraND { +public sealed interface Nd4jArrayAlgebra> : AlgebraND { /** - * Wraps [INDArray] to [N]. + * Wraps [INDArray] to [Nd4jArrayStructure]. */ public fun INDArray.wrap(): Nd4jArrayStructure + /** + * Unwraps to or acquires [INDArray] from [StructureND]. + */ public val StructureND.ndArray: INDArray - get() = when { - !shape.contentEquals(this@Nd4jArrayAlgebra.shape) -> throw ShapeMismatchException( - this@Nd4jArrayAlgebra.shape, - shape - ) - this is Nd4jArrayStructure -> ndArray //TODO check strides - else -> { - TODO() - } - } public override fun produce(initializer: C.(IntArray) -> T): Nd4jArrayStructure { val struct = Nd4j.create(*shape)!!.wrap() @@ -85,7 +77,7 @@ public interface Nd4jArrayAlgebra> : AlgebraND { * @param T the type of the element contained in ND structure. * @param S the type of space of structure elements. */ -public interface Nd4JArrayGroup> : GroupND, Nd4jArrayAlgebra { +public sealed interface Nd4jArrayGroup> : GroupND, Nd4jArrayAlgebra { public override val zero: Nd4jArrayStructure get() = Nd4j.zeros(*shape).wrap() @@ -110,7 +102,7 @@ public interface Nd4JArrayGroup> : GroupND, Nd4jArrayAlgebr * @param R the type of ring of structure elements. */ @OptIn(UnstableKMathAPI::class) -public interface Nd4jArrayRing> : RingND, Nd4JArrayGroup { +public sealed interface Nd4jArrayRing> : RingND, Nd4jArrayGroup { public override val one: Nd4jArrayStructure get() = Nd4j.ones(*shape).wrap() @@ -135,10 +127,7 @@ public interface Nd4jArrayRing> : RingND, Nd4JArrayGroup> = - ThreadLocal.withInitial { hashMapOf() } - - private val longNd4jArrayRingCache: ThreadLocal> = - ThreadLocal.withInitial { hashMapOf() } + ThreadLocal.withInitial(::HashMap) /** * Creates an [RingND] for [Int] values or pull it from cache if it was created previously. @@ -146,20 +135,13 @@ public interface Nd4jArrayRing> : RingND, Nd4JArrayGroup = intNd4jArrayRingCache.get().getOrPut(shape) { IntNd4jArrayRing(shape) } - /** - * Creates an [RingND] for [Long] values or pull it from cache if it was created previously. - */ - public fun long(vararg shape: Int): Nd4jArrayRing = - longNd4jArrayRingCache.get().getOrPut(shape) { LongNd4jArrayRing(shape) } - /** * Creates a most suitable implementation of [RingND] using reified class. */ @Suppress("UNCHECKED_CAST") - public inline fun auto(vararg shape: Int): Nd4jArrayRing> = when { - T::class == Int::class -> int(*shape) as Nd4jArrayRing> - T::class == Long::class -> long(*shape) as Nd4jArrayRing> - else -> throw UnsupportedOperationException("This factory method only supports Int and Long types.") + public inline fun auto(vararg shape: Int): Nd4jArrayRing> = when { + T::class == Int::class -> int(*shape) as Nd4jArrayRing> + else -> throw UnsupportedOperationException("This factory method only supports Long type.") } } } @@ -168,11 +150,9 @@ public interface Nd4jArrayRing> : RingND, Nd4JArrayGroup> : FieldND, Nd4jArrayRing { - +public sealed interface Nd4jArrayField> : FieldND, Nd4jArrayRing { public override fun divide(a: StructureND, b: StructureND): Nd4jArrayStructure = a.ndArray.div(b.ndArray).wrap() @@ -180,10 +160,10 @@ public interface Nd4jArrayField> : FieldND, Nd4jArrayRing< public companion object { private val floatNd4jArrayFieldCache: ThreadLocal> = - ThreadLocal.withInitial { hashMapOf() } + ThreadLocal.withInitial(::HashMap) private val doubleNd4JArrayFieldCache: ThreadLocal> = - ThreadLocal.withInitial { hashMapOf() } + ThreadLocal.withInitial(::HashMap) /** * Creates an [FieldND] for [Float] values or pull it from cache if it was created previously. @@ -198,26 +178,64 @@ public interface Nd4jArrayField> : FieldND, Nd4jArrayRing< doubleNd4JArrayFieldCache.get().getOrPut(shape) { DoubleNd4jArrayField(shape) } /** - * Creates a most suitable implementation of [RingND] using reified class. + * Creates a most suitable implementation of [FieldND] using reified class. */ @Suppress("UNCHECKED_CAST") - public inline fun auto(vararg shape: Int): Nd4jArrayField> = when { - T::class == Float::class -> float(*shape) as Nd4jArrayField> - T::class == Double::class -> real(*shape) as Nd4jArrayField> + public inline fun auto(vararg shape: Int): Nd4jArrayField> = when { + T::class == Float::class -> float(*shape) as Nd4jArrayField> + T::class == Double::class -> real(*shape) as Nd4jArrayField> else -> throw UnsupportedOperationException("This factory method only supports Float and Double types.") } } } +/** + * Represents intersection of [ExtendedField] and [Field] over [Nd4jArrayStructure]. + */ +public sealed interface Nd4jArrayExtendedField> : ExtendedField>, + Nd4jArrayField { + public override fun sin(arg: StructureND): StructureND = Transforms.sin(arg.ndArray).wrap() + public override fun cos(arg: StructureND): StructureND = Transforms.cos(arg.ndArray).wrap() + public override fun asin(arg: StructureND): StructureND = Transforms.asin(arg.ndArray).wrap() + public override fun acos(arg: StructureND): StructureND = Transforms.acos(arg.ndArray).wrap() + public override fun atan(arg: StructureND): StructureND = Transforms.atan(arg.ndArray).wrap() + + public override fun power(arg: StructureND, pow: Number): StructureND = + Transforms.pow(arg.ndArray, pow).wrap() + + public override fun exp(arg: StructureND): StructureND = Transforms.exp(arg.ndArray).wrap() + public override fun ln(arg: StructureND): StructureND = Transforms.log(arg.ndArray).wrap() + public override fun sqrt(arg: StructureND): StructureND = Transforms.sqrt(arg.ndArray).wrap() + public override fun sinh(arg: StructureND): StructureND = Transforms.sinh(arg.ndArray).wrap() + public override fun cosh(arg: StructureND): StructureND = Transforms.cosh(arg.ndArray).wrap() + public override fun tanh(arg: StructureND): StructureND = Transforms.tanh(arg.ndArray).wrap() + + public override fun asinh(arg: StructureND): StructureND = + Nd4j.getExecutioner().exec(ASinh(arg.ndArray, arg.ndArray.ulike())).wrap() + + public override fun acosh(arg: StructureND): StructureND = + Nd4j.getExecutioner().exec(ACosh(arg.ndArray, arg.ndArray.ulike())).wrap() + + public override fun atanh(arg: StructureND): StructureND = Transforms.atanh(arg.ndArray).wrap() +} + /** * Represents [FieldND] over [Nd4jArrayDoubleStructure]. */ -public class DoubleNd4jArrayField(public override val shape: IntArray) : Nd4jArrayField, - ExtendedField> { +public class DoubleNd4jArrayField(public override val shape: IntArray) : Nd4jArrayExtendedField { public override val elementContext: DoubleField get() = DoubleField public override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asDoubleStructure() + @OptIn(PerformancePitfall::class) + override val StructureND.ndArray: INDArray + get() = when (this) { + is Nd4jArrayStructure -> checkShape(ndArray) + else -> Nd4j.zeros(*shape).also { + elements().forEach { (idx, value) -> it.putScalar(idx, value) } + } + } + override fun scale(a: StructureND, value: Double): Nd4jArrayStructure { return a.ndArray.mul(value).wrap() } @@ -245,34 +263,25 @@ public class DoubleNd4jArrayField(public override val shape: IntArray) : Nd4jArr public override operator fun Double.minus(arg: StructureND): Nd4jArrayStructure { return arg.ndArray.rsub(this).wrap() } - - override fun sin(arg: StructureND): StructureND = Transforms.sin(arg.ndArray).wrap() - - override fun cos(arg: StructureND): StructureND = Transforms.cos(arg.ndArray).wrap() - - override fun asin(arg: StructureND): StructureND = Transforms.asin(arg.ndArray).wrap() - - override fun acos(arg: StructureND): StructureND = Transforms.acos(arg.ndArray).wrap() - - override fun atan(arg: StructureND): StructureND = Transforms.atan(arg.ndArray).wrap() - - override fun power(arg: StructureND, pow: Number): StructureND = - Transforms.pow(arg.ndArray,pow).wrap() - - override fun exp(arg: StructureND): StructureND = Transforms.exp(arg.ndArray).wrap() - - override fun ln(arg: StructureND): StructureND = Transforms.log(arg.ndArray).wrap() } /** * Represents [FieldND] over [Nd4jArrayStructure] of [Float]. */ -public class FloatNd4jArrayField(public override val shape: IntArray) : Nd4jArrayField, - ExtendedField> { +public class FloatNd4jArrayField(public override val shape: IntArray) : Nd4jArrayExtendedField { public override val elementContext: FloatField get() = FloatField public override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asFloatStructure() + @OptIn(PerformancePitfall::class) + public override val StructureND.ndArray: INDArray + get() = when (this) { + is Nd4jArrayStructure -> checkShape(ndArray) + else -> Nd4j.zeros(*shape).also { + elements().forEach { (idx, value) -> it.putScalar(idx, value) } + } + } + override fun scale(a: StructureND, value: Double): StructureND = a.ndArray.mul(value).wrap() @@ -293,23 +302,6 @@ public class FloatNd4jArrayField(public override val shape: IntArray) : Nd4jArra public override operator fun Float.minus(arg: StructureND): Nd4jArrayStructure = arg.ndArray.rsub(this).wrap() - - override fun sin(arg: StructureND): StructureND = Sin(arg.ndArray).z().wrap() - - override fun cos(arg: StructureND): StructureND = Cos(arg.ndArray).z().wrap() - - override fun asin(arg: StructureND): StructureND = ASin(arg.ndArray).z().wrap() - - override fun acos(arg: StructureND): StructureND = ACos(arg.ndArray).z().wrap() - - override fun atan(arg: StructureND): StructureND = ATan(arg.ndArray).z().wrap() - - override fun power(arg: StructureND, pow: Number): StructureND = - Pow(arg.ndArray, pow.toDouble()).z().wrap() - - override fun exp(arg: StructureND): StructureND = Exp(arg.ndArray).z().wrap() - - override fun ln(arg: StructureND): StructureND = Log(arg.ndArray).z().wrap() } /** @@ -321,6 +313,15 @@ public class IntNd4jArrayRing(public override val shape: IntArray) : Nd4jArrayRi public override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asIntStructure() + @OptIn(PerformancePitfall::class) + public override val StructureND.ndArray: INDArray + get() = when (this) { + is Nd4jArrayStructure -> checkShape(ndArray) + else -> Nd4j.zeros(*shape).also { + elements().forEach { (idx, value) -> it.putScalar(idx, value) } + } + } + public override operator fun StructureND.plus(arg: Int): Nd4jArrayStructure = ndArray.add(arg).wrap() @@ -333,25 +334,3 @@ public class IntNd4jArrayRing(public override val shape: IntArray) : Nd4jArrayRi public override operator fun Int.minus(arg: StructureND): Nd4jArrayStructure = arg.ndArray.rsub(this).wrap() } - -/** - * Represents [RingND] over [Nd4jArrayStructure] of [Long]. - */ -public class LongNd4jArrayRing(public override val shape: IntArray) : Nd4jArrayRing { - public override val elementContext: LongRing - get() = LongRing - - public override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asLongStructure() - - public override operator fun StructureND.plus(arg: Long): Nd4jArrayStructure = - ndArray.add(arg).wrap() - - public override operator fun StructureND.minus(arg: Long): Nd4jArrayStructure = - ndArray.sub(arg).wrap() - - public override operator fun StructureND.times(arg: Long): Nd4jArrayStructure = - ndArray.mul(arg).wrap() - - public override operator fun Long.minus(arg: StructureND): Nd4jArrayStructure = - arg.ndArray.rsub(this).wrap() -} diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayIterator.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayIterator.kt index 71887ca3c..140a212f8 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayIterator.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayIterator.kt @@ -48,12 +48,6 @@ private class Nd4jArrayDoubleIterator(iterateOver: INDArray) : Nd4jArrayIterator internal fun INDArray.realIterator(): Iterator> = Nd4jArrayDoubleIterator(this) -private class Nd4jArrayLongIterator(iterateOver: INDArray) : Nd4jArrayIteratorBase(iterateOver) { - override fun getSingle(indices: LongArray) = iterateOver.getLong(*indices) -} - -internal fun INDArray.longIterator(): Iterator> = Nd4jArrayLongIterator(this) - private class Nd4jArrayIntIterator(iterateOver: INDArray) : Nd4jArrayIteratorBase(iterateOver) { override fun getSingle(indices: LongArray) = iterateOver.getInt(*indices.toIntArray()) } diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt index d37c91cb6..ffddcef90 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt @@ -17,7 +17,8 @@ import space.kscience.kmath.nd.StructureND */ public sealed class Nd4jArrayStructure : MutableStructureND { /** - * The wrapped [INDArray]. + * The wrapped [INDArray]. Since KMath uses [Int] indexes, assuming that the size of [INDArray] is less or equal to + * [Int.MAX_VALUE]. */ public abstract val ndArray: INDArray @@ -25,6 +26,7 @@ public sealed class Nd4jArrayStructure : MutableStructureND { internal abstract fun elementsIterator(): Iterator> internal fun indicesIterator(): Iterator = ndArray.indicesIterator() + @PerformancePitfall public override fun elements(): Sequence> = Sequence(::elementsIterator) } @@ -40,17 +42,6 @@ private data class Nd4jArrayIntStructure(override val ndArray: INDArray) : Nd4jA */ public fun INDArray.asIntStructure(): Nd4jArrayStructure = Nd4jArrayIntStructure(this) -private data class Nd4jArrayLongStructure(override val ndArray: INDArray) : Nd4jArrayStructure() { - override fun elementsIterator(): Iterator> = ndArray.longIterator() - override fun get(index: IntArray): Long = ndArray.getLong(*index.toLongArray()) - override fun set(index: IntArray, value: Long): Unit = run { ndArray.putScalar(index, value.toDouble()) } -} - -/** - * Wraps this [INDArray] to [Nd4jArrayStructure]. - */ -public fun INDArray.asLongStructure(): Nd4jArrayStructure = Nd4jArrayLongStructure(this) - private data class Nd4jArrayDoubleStructure(override val ndArray: INDArray) : Nd4jArrayStructure() { override fun elementsIterator(): Iterator> = ndArray.realIterator() override fun get(index: IntArray): Double = ndArray.getDouble(*index) diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt new file mode 100644 index 000000000..456f7c2a9 --- /dev/null +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt @@ -0,0 +1,175 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.nd4j + +import org.nd4j.linalg.api.ndarray.INDArray +import org.nd4j.linalg.api.ops.impl.summarystats.Variance +import org.nd4j.linalg.api.ops.impl.transforms.strict.ACosh +import org.nd4j.linalg.api.ops.impl.transforms.strict.ASinh +import org.nd4j.linalg.factory.Nd4j +import org.nd4j.linalg.factory.ops.NDBase +import org.nd4j.linalg.ops.transforms.Transforms +import space.kscience.kmath.misc.PerformancePitfall +import space.kscience.kmath.nd.StructureND +import space.kscience.kmath.tensors.api.AnalyticTensorAlgebra +import space.kscience.kmath.tensors.api.Tensor +import space.kscience.kmath.tensors.api.TensorAlgebra +import space.kscience.kmath.tensors.core.DoubleTensorAlgebra + +/** + * ND4J based [TensorAlgebra] implementation. + */ +public sealed interface Nd4jTensorAlgebra : AnalyticTensorAlgebra { + /** + * Wraps [INDArray] to [Nd4jArrayStructure]. + */ + public fun INDArray.wrap(): Nd4jArrayStructure + + /** + * Unwraps to or acquires [INDArray] from [StructureND]. + */ + public val StructureND.ndArray: INDArray + + public override fun T.plus(other: Tensor): Tensor = other.ndArray.add(this).wrap() + public override fun Tensor.plus(value: T): Tensor = ndArray.add(value).wrap() + + public override fun Tensor.plus(other: Tensor): Tensor = ndArray.add(other.ndArray).wrap() + + public override fun Tensor.plusAssign(value: T) { + ndArray.addi(value) + } + + public override fun Tensor.plusAssign(other: Tensor) { + ndArray.addi(other.ndArray) + } + + public override fun T.minus(other: Tensor): Tensor = other.ndArray.rsub(this).wrap() + public override fun Tensor.minus(value: T): Tensor = ndArray.sub(value).wrap() + public override fun Tensor.minus(other: Tensor): Tensor = ndArray.sub(other.ndArray).wrap() + + public override fun Tensor.minusAssign(value: T) { + ndArray.rsubi(value) + } + + public override fun Tensor.minusAssign(other: Tensor) { + ndArray.subi(other.ndArray) + } + + public override fun T.times(other: Tensor): Tensor = other.ndArray.mul(this).wrap() + + public override fun Tensor.times(value: T): Tensor = + ndArray.mul(value).wrap() + + public override fun Tensor.times(other: Tensor): Tensor = ndArray.mul(other.ndArray).wrap() + + public override fun Tensor.timesAssign(value: T) { + ndArray.muli(value) + } + + public override fun Tensor.timesAssign(other: Tensor) { + ndArray.mmuli(other.ndArray) + } + + public override fun Tensor.unaryMinus(): Tensor = ndArray.neg().wrap() + public override fun Tensor.get(i: Int): Tensor = ndArray.slice(i.toLong()).wrap() + public override fun Tensor.transpose(i: Int, j: Int): Tensor = ndArray.swapAxes(i, j).wrap() + public override fun Tensor.dot(other: Tensor): Tensor = ndArray.mmul(other.ndArray).wrap() + + public override fun Tensor.min(dim: Int, keepDim: Boolean): Tensor = + ndArray.min(keepDim, dim).wrap() + + public override fun Tensor.sum(dim: Int, keepDim: Boolean): Tensor = + ndArray.sum(keepDim, dim).wrap() + + public override fun Tensor.max(dim: Int, keepDim: Boolean): Tensor = + ndArray.max(keepDim, dim).wrap() + + public override fun Tensor.view(shape: IntArray): Tensor = ndArray.reshape(shape).wrap() + public override fun Tensor.viewAs(other: Tensor): Tensor = view(other.shape) + + public override fun Tensor.argMax(dim: Int, keepDim: Boolean): Tensor = + ndBase.get().argmax(ndArray, keepDim, dim).wrap() + + public override fun Tensor.mean(dim: Int, keepDim: Boolean): Tensor = ndArray.mean(keepDim, dim).wrap() + + public override fun Tensor.exp(): Tensor = Transforms.exp(ndArray).wrap() + public override fun Tensor.ln(): Tensor = Transforms.log(ndArray).wrap() + public override fun Tensor.sqrt(): Tensor = Transforms.sqrt(ndArray).wrap() + public override fun Tensor.cos(): Tensor = Transforms.cos(ndArray).wrap() + public override fun Tensor.acos(): Tensor = Transforms.acos(ndArray).wrap() + public override fun Tensor.cosh(): Tensor = Transforms.cosh(ndArray).wrap() + + public override fun Tensor.acosh(): Tensor = + Nd4j.getExecutioner().exec(ACosh(ndArray, ndArray.ulike())).wrap() + + public override fun Tensor.sin(): Tensor = Transforms.sin(ndArray).wrap() + public override fun Tensor.asin(): Tensor = Transforms.asin(ndArray).wrap() + public override fun Tensor.sinh(): Tensor = Transforms.sinh(ndArray).wrap() + + public override fun Tensor.asinh(): Tensor = + Nd4j.getExecutioner().exec(ASinh(ndArray, ndArray.ulike())).wrap() + + public override fun Tensor.tan(): Tensor = Transforms.tan(ndArray).wrap() + public override fun Tensor.atan(): Tensor = Transforms.atan(ndArray).wrap() + public override fun Tensor.tanh(): Tensor = Transforms.tanh(ndArray).wrap() + public override fun Tensor.atanh(): Tensor = Transforms.atanh(ndArray).wrap() + public override fun Tensor.ceil(): Tensor = Transforms.ceil(ndArray).wrap() + public override fun Tensor.floor(): Tensor = Transforms.floor(ndArray).wrap() + public override fun Tensor.std(dim: Int, keepDim: Boolean): Tensor = ndArray.std(true, keepDim, dim).wrap() + public override fun T.div(other: Tensor): Tensor = other.ndArray.rdiv(this).wrap() + public override fun Tensor.div(value: T): Tensor = ndArray.div(value).wrap() + public override fun Tensor.div(other: Tensor): Tensor = ndArray.div(other.ndArray).wrap() + + public override fun Tensor.divAssign(value: T) { + ndArray.divi(value) + } + + public override fun Tensor.divAssign(other: Tensor) { + ndArray.divi(other.ndArray) + } + + public override fun Tensor.variance(dim: Int, keepDim: Boolean): Tensor = + Nd4j.getExecutioner().exec(Variance(ndArray, true, true, dim)).wrap() + + private companion object { + private val ndBase: ThreadLocal = ThreadLocal.withInitial(::NDBase) + } +} + +/** + * [Double] specialization of [Nd4jTensorAlgebra]. + */ +public object DoubleNd4jTensorAlgebra : Nd4jTensorAlgebra { + public override fun INDArray.wrap(): Nd4jArrayStructure = asDoubleStructure() + + @OptIn(PerformancePitfall::class) + public override val StructureND.ndArray: INDArray + get() = when (this) { + is Nd4jArrayStructure -> ndArray + else -> Nd4j.zeros(*shape).also { + elements().forEach { (idx, value) -> it.putScalar(idx, value) } + } + } + + public override fun Tensor.valueOrNull(): Double? = + if (shape contentEquals intArrayOf(1)) ndArray.getDouble(0) else null + + // TODO rewrite + @PerformancePitfall + public override fun diagonalEmbedding( + diagonalEntries: Tensor, + offset: Int, + dim1: Int, + dim2: Int, + ): Tensor = DoubleTensorAlgebra.diagonalEmbedding(diagonalEntries, offset, dim1, dim2) + + public override fun Tensor.sum(): Double = ndArray.sumNumber().toDouble() + public override fun Tensor.min(): Double = ndArray.minNumber().toDouble() + public override fun Tensor.max(): Double = ndArray.maxNumber().toDouble() + public override fun Tensor.mean(): Double = ndArray.meanNumber().toDouble() + public override fun Tensor.std(): Double = ndArray.stdNumber().toDouble() + public override fun Tensor.variance(): Double = ndArray.varNumber().toDouble() +} diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/arrays.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/arrays.kt index 6c414cc13..75a334ca7 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/arrays.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/arrays.kt @@ -5,5 +5,4 @@ package space.kscience.kmath.nd4j -internal fun IntArray.toLongArray(): LongArray = LongArray(size) { this[it].toLong() } internal fun LongArray.toIntArray(): IntArray = IntArray(size) { this[it].toInt() } diff --git a/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt b/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt index c80a1d771..40da22763 100644 --- a/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt +++ b/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt @@ -52,7 +52,7 @@ internal class Nd4jArrayAlgebraTest { @Test fun testSin() = DoubleNd4jArrayField(intArrayOf(2, 2)).invoke { - val initial = produce { (i, j) -> if (i == j) PI/2 else 0.0 } + val initial = produce { (i, j) -> if (i == j) PI / 2 else 0.0 } val transformed = sin(initial) val expected = produce { (i, j) -> if (i == j) 1.0 else 0.0 } diff --git a/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt b/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt index bdfec2ba6..30d01338f 100644 --- a/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt +++ b/kmath-nd4j/src/test/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt @@ -72,7 +72,7 @@ internal class Nd4jArrayStructureTest { @Test fun testSet() { val nd = Nd4j.rand(17, 12, 4, 8)!! - val struct = nd.asLongStructure() + val struct = nd.asIntStructure() struct[intArrayOf(1, 2, 3, 4)] = 777 assertEquals(777, struct[1, 2, 3, 4]) } diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt index 2eb18ada6..62b8ef046 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt @@ -13,7 +13,7 @@ import space.kscience.kmath.operations.Algebra * * @param T the type of items in the tensors. */ -public interface TensorAlgebra: Algebra> { +public interface TensorAlgebra : Algebra> { /** * Returns a single tensor value of unit dimension if tensor shape equals to [1]. @@ -27,7 +27,8 @@ public interface TensorAlgebra: Algebra> { * * @return the value of a scalar tensor. */ - public fun Tensor.value(): T + public fun Tensor.value(): T = + valueOrNull() ?: throw IllegalArgumentException("Inconsistent value for tensor of with $shape shape") /** * Each element of the tensor [other] is added to this value. @@ -60,15 +61,14 @@ public interface TensorAlgebra: Algebra> { * * @param value the number to be added to each element of this tensor. */ - public operator fun Tensor.plusAssign(value: T): Unit + public operator fun Tensor.plusAssign(value: T) /** * Each element of the tensor [other] is added to each element of this tensor. * * @param other tensor to be added. */ - public operator fun Tensor.plusAssign(other: Tensor): Unit - + public operator fun Tensor.plusAssign(other: Tensor) /** * Each element of the tensor [other] is subtracted from this value. @@ -101,14 +101,14 @@ public interface TensorAlgebra: Algebra> { * * @param value the number to be subtracted from each element of this tensor. */ - public operator fun Tensor.minusAssign(value: T): Unit + public operator fun Tensor.minusAssign(value: T) /** * Each element of the tensor [other] is subtracted from each element of this tensor. * * @param other tensor to be subtracted. */ - public operator fun Tensor.minusAssign(other: Tensor): Unit + public operator fun Tensor.minusAssign(other: Tensor) /** @@ -142,14 +142,14 @@ public interface TensorAlgebra: Algebra> { * * @param value the number to be multiplied by each element of this tensor. */ - public operator fun Tensor.timesAssign(value: T): Unit + public operator fun Tensor.timesAssign(value: T) /** * Each element of the tensor [other] is multiplied by each element of this tensor. * * @param other tensor to be multiplied. */ - public operator fun Tensor.timesAssign(other: Tensor): Unit + public operator fun Tensor.timesAssign(other: Tensor) /** * Numerical negative, element-wise. @@ -217,7 +217,7 @@ public interface TensorAlgebra: Algebra> { * a 1 is prepended to its dimension for the purpose of the batched matrix multiply and removed after. * If the second argument is 1-dimensional, a 1 is appended to its dimension for the purpose of the batched matrix * multiple and removed after. - * The non-matrix (i.e. batch) dimensions are broadcasted (and thus must be broadcastable). + * The non-matrix (i.e. batch) dimensions are broadcast (and thus must be broadcastable). * For example, if `input` is a (j × 1 × n × n) tensor and `other` is a * (k × n × n) tensor, out will be a (j × k × n × n) tensor. * @@ -255,7 +255,7 @@ public interface TensorAlgebra: Algebra> { diagonalEntries: Tensor, offset: Int = 0, dim1: Int = -2, - dim2: Int = -1 + dim2: Int = -1, ): Tensor /** diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt index 78989f1f3..1fd46bd57 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt @@ -9,20 +9,9 @@ import space.kscience.kmath.nd.as1D import space.kscience.kmath.nd.as2D import space.kscience.kmath.tensors.api.AnalyticTensorAlgebra import space.kscience.kmath.tensors.api.LinearOpsTensorAlgebra -import space.kscience.kmath.tensors.api.TensorPartialDivisionAlgebra import space.kscience.kmath.tensors.api.Tensor -import space.kscience.kmath.tensors.core.internal.dotHelper -import space.kscience.kmath.tensors.core.internal.getRandomNormals +import space.kscience.kmath.tensors.api.TensorPartialDivisionAlgebra import space.kscience.kmath.tensors.core.internal.* -import space.kscience.kmath.tensors.core.internal.broadcastOuterTensors -import space.kscience.kmath.tensors.core.internal.checkBufferShapeConsistency -import space.kscience.kmath.tensors.core.internal.checkEmptyDoubleBuffer -import space.kscience.kmath.tensors.core.internal.checkEmptyShape -import space.kscience.kmath.tensors.core.internal.checkShapesCompatible -import space.kscience.kmath.tensors.core.internal.checkSquareMatrix -import space.kscience.kmath.tensors.core.internal.checkTranspose -import space.kscience.kmath.tensors.core.internal.checkView -import space.kscience.kmath.tensors.core.internal.minusIndexFrom import kotlin.math.* /** @@ -38,8 +27,8 @@ public open class DoubleTensorAlgebra : override fun Tensor.valueOrNull(): Double? = if (tensor.shape contentEquals intArrayOf(1)) tensor.mutableBuffer.array()[tensor.bufferStart] else null - override fun Tensor.value(): Double = - valueOrNull() ?: throw IllegalArgumentException("Inconsistent value for tensor of with $shape shape") + override fun Tensor.value(): Double = valueOrNull() + ?: throw IllegalArgumentException("The tensor shape is $shape, but value method is allowed only for shape [1]") /** * Constructs a tensor with the specified shape and data. @@ -466,7 +455,7 @@ public open class DoubleTensorAlgebra : private fun Tensor.eq( other: Tensor, - eqFunction: (Double, Double) -> Boolean + eqFunction: (Double, Double) -> Boolean, ): Boolean { checkShapesCompatible(tensor, other) val n = tensor.numElements @@ -540,7 +529,7 @@ public open class DoubleTensorAlgebra : internal fun Tensor.foldDim( foldFunction: (DoubleArray) -> Double, dim: Int, - keepDim: Boolean + keepDim: Boolean, ): DoubleTensor { check(dim < dimension) { "Dimension $dim out of range $dimension" } val resShape = if (keepDim) { @@ -729,7 +718,7 @@ public open class DoubleTensorAlgebra : */ public fun luPivot( luTensor: Tensor, - pivotsTensor: Tensor + pivotsTensor: Tensor, ): Triple { checkSquareMatrix(luTensor.shape) check( From 485e90fcd0f3e66ea5a1566634041117b983ae84 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Thu, 20 May 2021 23:32:56 +0700 Subject: [PATCH 052/132] Rename DifferentiableMstExpression, fix #349 --- CHANGELOG.md | 1 + build.gradle.kts | 1 + kmath-kotlingrad/build.gradle.kts | 6 ++++-- ...tExpression.kt => KotlingradExpression.kt} | 20 +++++++++---------- ...{ScalarsAdapters.kt => scalarsAdapters.kt} | 12 ++++++++--- kmath-nd4j/build.gradle.kts | 3 ++- 6 files changed, 27 insertions(+), 16 deletions(-) rename kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/{DifferentiableMstExpression.kt => KotlingradExpression.kt} (68%) rename kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/{ScalarsAdapters.kt => scalarsAdapters.kt} (84%) diff --git a/CHANGELOG.md b/CHANGELOG.md index 274a403b1..9c6b14b95 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -34,6 +34,7 @@ - Replace `MST.Symbolic` by `Symbol`, `Symbol` now implements MST - Remove Any restriction on polynomials - Add `out` variance to type parameters of `StructureND` and its implementations where possible +- Rename `DifferentiableMstExpression` to `KotlingradExpression` ### Deprecated diff --git a/build.gradle.kts b/build.gradle.kts index 93f5059ff..d44833445 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -11,6 +11,7 @@ allprojects { isAllowInsecureProtocol = true } maven("https://maven.pkg.jetbrains.space/public/p/kotlinx-html/maven") + maven("https://oss.sonatype.org/content/repositories/snapshots") mavenCentral() } diff --git a/kmath-kotlingrad/build.gradle.kts b/kmath-kotlingrad/build.gradle.kts index 0e8e49971..01b42d7ba 100644 --- a/kmath-kotlingrad/build.gradle.kts +++ b/kmath-kotlingrad/build.gradle.kts @@ -3,14 +3,16 @@ plugins { id("ru.mipt.npm.gradle.common") } +description = "Kotlin∇ integration module" + dependencies { api("com.github.breandan:kaliningraph:0.1.6") api("com.github.breandan:kotlingrad:0.4.5") - api(project(":kmath-ast")) + api(project(":kmath-core")) + testImplementation(project(":kmath-ast")) } readme { - description = "Functions, integration and interpolation" maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL propertyByTemplate("artifact", rootProject.file("docs/templates/ARTIFACT-TEMPLATE.md")) diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt similarity index 68% rename from kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt rename to kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt index 59d481d02..72ecee4f1 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt @@ -11,24 +11,24 @@ import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.NumericAlgebra /** - * Represents [MST] based [DifferentiableExpression]. + * Represents [MST] based [DifferentiableExpression] relying on [Kotlin∇](https://github.com/breandan/kotlingrad). * - * The principle of this API is converting the [mst] to an [SFun], differentiating it with - * [Kotlin∇](https://github.com/breandan/kotlingrad), then converting [SFun] back to [MST]. + * The principle of this API is converting the [mst] to an [SFun], differentiating it with Kotlin∇, then converting + * [SFun] back to [MST]. * * @param T The type of number. * @param A The [NumericAlgebra] of [T]. * @property algebra The [A] instance. * @property mst The [MST] node. */ -public class DifferentiableMstExpression>( +public class KotlingradExpression>( public val algebra: A, public val mst: MST, -) : DifferentiableExpression> { +) : DifferentiableExpression> { public override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) - public override fun derivativeOrNull(symbols: List): DifferentiableMstExpression = - DifferentiableMstExpression( + public override fun derivativeOrNull(symbols: List): KotlingradExpression = + KotlingradExpression( algebra, symbols.map(Symbol::identity) .map(MstNumericAlgebra::bindSymbol) @@ -39,7 +39,7 @@ public class DifferentiableMstExpression>( } /** - * Wraps this [MST] into [DifferentiableMstExpression]. + * Wraps this [MST] into [KotlingradExpression]. */ -public fun > MST.toDiffExpression(algebra: A): DifferentiableMstExpression = - DifferentiableMstExpression(algebra, this) +public fun > MST.toDiffExpression(algebra: A): KotlingradExpression = + KotlingradExpression(algebra, this) diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/scalarsAdapters.kt similarity index 84% rename from kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt rename to kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/scalarsAdapters.kt index 8e3c54035..6c0b98c59 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/ScalarsAdapters.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/scalarsAdapters.kt @@ -14,7 +14,7 @@ import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.operations.* /** - * Maps [SVar] to [MST.Symbolic] directly. + * Maps [SVar] to [Symbol] directly. * * @receiver The variable. * @returnAa node. @@ -81,7 +81,7 @@ public fun > SFun.toMst(): MST = MstExtendedField { public fun > MST.Numeric.toSConst(): SConst = SConst(value) /** - * Maps [MST.Symbolic] to [SVar] directly. + * Maps [Symbol] to [SVar] directly. * * @receiver The node. * @return A new variable. @@ -94,7 +94,7 @@ internal fun > Symbol.toSVar(): SVar = SVar(identity) * Detailed mapping is: * * - [MST.Numeric] -> [SConst]; - * - [MST.Symbolic] -> [SVar]; + * - [Symbol] -> [SVar]; * - [MST.Unary] -> [Negative], [Sine], [Cosine], [Tangent], [Power], [Log]; * - [MST.Binary] -> [Sum], [Prod], [Power]. * @@ -114,6 +114,12 @@ public fun > MST.toSFun(): SFun = when (this) { PowerOperations.SQRT_OPERATION -> sqrt(value.toSFun()) ExponentialOperations.EXP_OPERATION -> exp(value.toSFun()) ExponentialOperations.LN_OPERATION -> value.toSFun().ln() + ExponentialOperations.SINH_OPERATION -> MstExtendedField { (exp(value) - exp(-value)) / 2.0 }.toSFun() + ExponentialOperations.COSH_OPERATION -> MstExtendedField { (exp(value) + exp(-value)) / 2.0 }.toSFun() + ExponentialOperations.TANH_OPERATION -> MstExtendedField { (exp(value) - exp(-value)) / (exp(-value) + exp(value)) }.toSFun() + ExponentialOperations.ASINH_OPERATION -> MstExtendedField { ln(sqrt(value * value + one) + value) }.toSFun() + ExponentialOperations.ACOSH_OPERATION -> MstExtendedField { ln(value + sqrt((value - one) * (value + one))) }.toSFun() + ExponentialOperations.ATANH_OPERATION -> MstExtendedField { (ln(value + one) - ln(one - value)) / 2.0 }.toSFun() else -> error("Unary operation $operation not defined in $this") } diff --git a/kmath-nd4j/build.gradle.kts b/kmath-nd4j/build.gradle.kts index 12ea5c130..abcc02962 100644 --- a/kmath-nd4j/build.gradle.kts +++ b/kmath-nd4j/build.gradle.kts @@ -3,6 +3,8 @@ plugins { id("ru.mipt.npm.gradle.common") } +description = "ND4J NDStructure implementation and according NDAlgebra classes" + dependencies { api(project(":kmath-tensors")) api("org.nd4j:nd4j-api:1.0.0-beta7") @@ -12,7 +14,6 @@ dependencies { } readme { - description = "ND4J NDStructure implementation and according NDAlgebra classes" maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL propertyByTemplate("artifact", rootProject.file("docs/templates/ARTIFACT-TEMPLATE.md")) feature(id = "nd4jarraystructure") { "NDStructure wrapper for INDArray" } From a722cf0cdb7810c5cf1bde7c076fcef28f0d7452 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Fri, 21 May 2021 15:47:35 +0700 Subject: [PATCH 053/132] Integration between MST and Symja IExpr --- CHANGELOG.md | 9 +- examples/build.gradle.kts | 2 +- .../kscience/kmath/ast/kotlingradSupport.kt | 20 ++-- .../space/kscience/kmath/ast/symjaSupport.kt | 27 ++++++ .../kmath/kotlingrad/KotlingradExpression.kt | 4 +- kmath-symja/build.gradle.kts | 21 ++++ .../kscience/kmath/symja/SymjaExpression.kt | 34 +++++++ .../space/kscience/kmath/symja/adapters.kt | 95 +++++++++++++++++++ settings.gradle.kts | 1 + 9 files changed, 195 insertions(+), 18 deletions(-) create mode 100644 examples/src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt create mode 100644 kmath-symja/build.gradle.kts create mode 100644 kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt create mode 100644 kmath-symja/src/main/kotlin/space/kscience/kmath/symja/adapters.kt diff --git a/CHANGELOG.md b/CHANGELOG.md index 9c6b14b95..2ff5dd623 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -2,18 +2,19 @@ ## [Unreleased] ### Added -- ScaleOperations interface -- Field extends ScaleOperations +- `ScaleOperations` interface +- `Field` extends `ScaleOperations` - Basic integration API - Basic MPP distributions and samplers -- bindSymbolOrNull +- `bindSymbolOrNull` - Blocking chains and Statistics - Multiplatform integration - Integration for any Field element - Extended operations for ND4J fields - Jupyter Notebook integration module (kmath-jupyter) - `@PerformancePitfall` annotation to mark possibly slow API -- BigInt operation performance improvement and fixes by @zhelenskiy (#328) +- `BigInt` operation performance improvement and fixes by @zhelenskiy (#328) +- Integration between `MST` and Symja `IExpr` ### Changed - Exponential operations merged with hyperbolic functions diff --git a/examples/build.gradle.kts b/examples/build.gradle.kts index d095db1ba..568bde153 100644 --- a/examples/build.gradle.kts +++ b/examples/build.gradle.kts @@ -26,7 +26,7 @@ dependencies { implementation(project(":kmath-ejml")) implementation(project(":kmath-nd4j")) implementation(project(":kmath-tensors")) - + implementation(project(":kmath-symja")) implementation(project(":kmath-for-real")) implementation("org.nd4j:nd4j-native:1.0.0-beta7") diff --git a/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt b/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt index 420b23f9f..6ceaa962a 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt @@ -5,25 +5,23 @@ package space.kscience.kmath.ast -import space.kscience.kmath.asm.compileToExpression import space.kscience.kmath.expressions.derivative import space.kscience.kmath.expressions.invoke -import space.kscience.kmath.expressions.symbol -import space.kscience.kmath.kotlingrad.toDiffExpression +import space.kscience.kmath.expressions.Symbol.Companion.x +import space.kscience.kmath.expressions.toExpression +import space.kscience.kmath.kotlingrad.toKotlingradExpression import space.kscience.kmath.operations.DoubleField /** * In this example, x^2-4*x-44 function is differentiated with Kotlin∇, and the autodiff result is compared with - * valid derivative. + * valid derivative in a certain point. */ fun main() { - val x by symbol - - val actualDerivative = "x^2-4*x-44".parseMath() - .toDiffExpression(DoubleField) + val actualDerivative = "x^2-4*x-44" + .parseMath() + .toKotlingradExpression(DoubleField) .derivative(x) - - val expectedDerivative = "2*x-4".parseMath().compileToExpression(DoubleField) - assert(actualDerivative(x to 123.0) == expectedDerivative(x to 123.0)) + val expectedDerivative = "2*x-4".parseMath().toExpression(DoubleField) + check(actualDerivative(x to 123.0) == expectedDerivative(x to 123.0)) } diff --git a/examples/src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt b/examples/src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt new file mode 100644 index 000000000..a9eca0500 --- /dev/null +++ b/examples/src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt @@ -0,0 +1,27 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.ast + +import space.kscience.kmath.expressions.Symbol.Companion.x +import space.kscience.kmath.expressions.derivative +import space.kscience.kmath.expressions.invoke +import space.kscience.kmath.expressions.toExpression +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.symja.toSymjaExpression + +/** + * In this example, x^2-4*x-44 function is differentiated with Symja, and the autodiff result is compared with + * valid derivative in a certain point. + */ +fun main() { + val actualDerivative = "x^2-4*x-44" + .parseMath() + .toSymjaExpression(DoubleField) + .derivative(x) + + val expectedDerivative = "2*x-4".parseMath().toExpression(DoubleField) + check(actualDerivative(x to 123.0) == expectedDerivative(x to 123.0)) +} diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt index 72ecee4f1..8312eaff3 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt @@ -39,7 +39,7 @@ public class KotlingradExpression>( } /** - * Wraps this [MST] into [KotlingradExpression]. + * Wraps this [MST] into [KotlingradExpression] in the context of [algebra]. */ -public fun > MST.toDiffExpression(algebra: A): KotlingradExpression = +public fun > MST.toKotlingradExpression(algebra: A): KotlingradExpression = KotlingradExpression(algebra, this) diff --git a/kmath-symja/build.gradle.kts b/kmath-symja/build.gradle.kts new file mode 100644 index 000000000..c06020bb6 --- /dev/null +++ b/kmath-symja/build.gradle.kts @@ -0,0 +1,21 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +plugins { + kotlin("jvm") + id("ru.mipt.npm.gradle.common") +} + +description = "Symja integration module" + +dependencies { + api("org.matheclipse:matheclipse-core:2.0.0-SNAPSHOT") + api(project(":kmath-core")) + testImplementation("org.slf4j:slf4j-simple:1.7.30") +} + +readme { + maturity = ru.mipt.npm.gradle.Maturity.PROTOTYPE +} diff --git a/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt new file mode 100644 index 000000000..301678916 --- /dev/null +++ b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt @@ -0,0 +1,34 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.symja + +import org.matheclipse.core.eval.ExprEvaluator +import org.matheclipse.core.expression.F +import space.kscience.kmath.expressions.DifferentiableExpression +import space.kscience.kmath.expressions.MST +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.expressions.interpret +import space.kscience.kmath.operations.NumericAlgebra + +public class SymjaExpression>( + public val algebra: A, + public val mst: MST, + public val evaluator: ExprEvaluator = DEFAULT_EVALUATOR, +) : DifferentiableExpression> { + public override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) + + public override fun derivativeOrNull(symbols: List): SymjaExpression = SymjaExpression( + algebra, + symbols.map(Symbol::toIExpr).fold(mst.toIExpr(), F::D).toMst(evaluator), + evaluator, + ) +} + +/** + * Wraps this [MST] into [SymjaExpression] in the context of [algebra]. + */ +public fun > MST.toSymjaExpression(algebra: A): SymjaExpression = + SymjaExpression(algebra, this) diff --git a/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/adapters.kt b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/adapters.kt new file mode 100644 index 000000000..95dd1ebbf --- /dev/null +++ b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/adapters.kt @@ -0,0 +1,95 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.symja + +import org.matheclipse.core.eval.ExprEvaluator +import org.matheclipse.core.expression.ComplexNum +import org.matheclipse.core.expression.F +import org.matheclipse.core.interfaces.IExpr +import org.matheclipse.core.interfaces.ISymbol +import space.kscience.kmath.expressions.MST +import space.kscience.kmath.expressions.MstExtendedField +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.operations.* + +internal val DEFAULT_EVALUATOR = ExprEvaluator(false, 100) + +/** + * Matches the given [IExpr] instance to appropriate [MST] node or evaluates it with [evaluator]. + */ +public fun IExpr.toMst(evaluator: ExprEvaluator = DEFAULT_EVALUATOR): MST = MstExtendedField { + when { + isPlus -> first().toMst(evaluator) + second().toMst(evaluator) + isSin -> sin(first().toMst(evaluator)) + isSinh -> sinh(first().toMst(evaluator)) + isCos -> cos(first().toMst(evaluator)) + isCosh -> cosh(first().toMst(evaluator)) + isTan -> tan(first().toMst(evaluator)) + isTanh -> tanh(first().toMst(evaluator)) + isArcSin -> asin(first().toMst(evaluator)) + isArcCos -> acos(first().toMst(evaluator)) + isArcTan -> atan(first().toMst(evaluator)) + isArcTanh -> atanh(first().toMst(evaluator)) + isE -> bindSymbol("e") + isPi -> bindSymbol("pi") + isTimes -> first().toMst(evaluator) * second().toMst(evaluator) + isOne -> one + isZero -> zero + isImaginaryUnit -> bindSymbol("i") + isMinusOne -> -one + this@toMst is ISymbol -> bindSymbol(symbolName) + isPower -> power(first().toMst(evaluator), evaluator.evalf(second())) + isExp -> exp(first().toMst(evaluator)) + isNumber -> number(evaluator.evalf(this@toMst)) + this@toMst === F.NIL -> error("NIL cannot be converted to MST") + else -> evaluator.eval(this@toMst.toString()).toMst(evaluator) + } +} + +/** + * Matches the given [MST] instance to appropriate [IExpr] node, only standard operations and symbols (which are + * present in, say, [MstExtendedField]) are supported. + */ +public fun MST.toIExpr(): IExpr = when (this) { + is MST.Numeric -> F.symjify(value) + + is Symbol -> when (identity) { + "e" -> F.E + "pi" -> F.Pi + "i" -> ComplexNum.I + else -> F.Dummy(identity) + } + + is MST.Unary -> when (operation) { + GroupOperations.PLUS_OPERATION -> value.toIExpr() + GroupOperations.MINUS_OPERATION -> F.Negate(value.toIExpr()) + TrigonometricOperations.SIN_OPERATION -> F.Sin(value.toIExpr()) + TrigonometricOperations.COS_OPERATION -> F.Cos(value.toIExpr()) + TrigonometricOperations.TAN_OPERATION -> F.Tan(value.toIExpr()) + TrigonometricOperations.ASIN_OPERATION -> F.ArcSin(value.toIExpr()) + TrigonometricOperations.ACOS_OPERATION -> F.ArcCos(value.toIExpr()) + TrigonometricOperations.ATAN_OPERATION -> F.ArcTan(value.toIExpr()) + ExponentialOperations.SINH_OPERATION -> F.Sinh(value.toIExpr()) + ExponentialOperations.COSH_OPERATION -> F.Cosh(value.toIExpr()) + ExponentialOperations.TANH_OPERATION -> F.Tanh(value.toIExpr()) + ExponentialOperations.ASINH_OPERATION -> F.ArcSinh(value.toIExpr()) + ExponentialOperations.ACOSH_OPERATION -> F.ArcCosh(value.toIExpr()) + ExponentialOperations.ATANH_OPERATION -> F.ArcTanh(value.toIExpr()) + PowerOperations.SQRT_OPERATION -> F.Sqrt(value.toIExpr()) + ExponentialOperations.EXP_OPERATION -> F.Exp(value.toIExpr()) + ExponentialOperations.LN_OPERATION -> F.Log(value.toIExpr()) + else -> error("Unary operation $operation not defined in $this") + } + + is MST.Binary -> when (operation) { + GroupOperations.PLUS_OPERATION -> left.toIExpr() + right.toIExpr() + GroupOperations.MINUS_OPERATION -> left.toIExpr() - right.toIExpr() + RingOperations.TIMES_OPERATION -> left.toIExpr() * right.toIExpr() + FieldOperations.DIV_OPERATION -> F.Divide(left.toIExpr(), right.toIExpr()) + PowerOperations.POW_OPERATION -> F.Power(left.toIExpr(), F.symjify((right as MST.Numeric).value)) + else -> error("Binary operation $operation not defined in $this") + } +} diff --git a/settings.gradle.kts b/settings.gradle.kts index cc9eb4860..d47aea2a7 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -42,6 +42,7 @@ include( ":kmath-kotlingrad", ":kmath-tensors", ":kmath-jupyter", + ":kmath-symja", ":examples", ":benchmarks" ) From 189449f40e2d84c314225f92cec3cf04c4565aa8 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Fri, 21 May 2021 20:08:17 +0700 Subject: [PATCH 054/132] Fix unresolved reference in generated type parameter --- .../space/kscience/kmath/asm/internal/AsmBuilder.kt | 4 ++-- .../kotlin/space/kscience/kmath/expressions/Symbol.kt | 8 ++++---- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt index 39ebf049d..a796ae2a5 100644 --- a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt +++ b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt @@ -342,8 +342,8 @@ internal class AsmBuilder( val MAP_INTRINSICS_TYPE: Type by lazy { getObjectType("space/kscience/kmath/asm/internal/MapIntrinsics") } /** - * ASM Type for [space.kscience.kmath.misc.Symbol]. + * ASM Type for [space.kscience.kmath.expressions.Symbol]. */ - val SYMBOL_TYPE: Type by lazy { getObjectType("space/kscience/kmath/misc/Symbol") } + val SYMBOL_TYPE: Type by lazy { getObjectType("space/kscience/kmath/expressions/Symbol") } } } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt index 10a9ca5a1..74dc7aedc 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt @@ -12,13 +12,13 @@ import kotlin.properties.ReadOnlyProperty * A marker interface for a symbol. A symbol must have an identity. * Ic */ -public interface Symbol: MST { +public interface Symbol : MST { /** * Identity object for the symbol. Two symbols with the same identity are considered to be the same symbol. */ public val identity: String - public companion object{ + public companion object { public val x: StringSymbol = StringSymbol("x") public val y: StringSymbol = StringSymbol("y") public val z: StringSymbol = StringSymbol("z") @@ -48,7 +48,7 @@ public operator fun Map.get(symbol: Symbol): T? = get(symbol.iden /** * Set a value of [String]-keyed map by a [Symbol] */ -public operator fun MutableMap.set(symbol: Symbol, value: T){ +public operator fun MutableMap.set(symbol: Symbol, value: T) { set(symbol.identity, value) } @@ -60,6 +60,6 @@ public operator fun Map.get(string: String): T? = get(StringSymbo /** * Set a value of [String]-keyed map by a [Symbol] */ -public operator fun MutableMap.set(string: String, value: T){ +public operator fun MutableMap.set(string: String, value: T) { set(StringSymbol(string), value) } \ No newline at end of file From 18509f1259ca5363ce3059e68bcc69a85f94c429 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 21 May 2021 23:14:07 +0300 Subject: [PATCH 055/132] Simpson integrator --- .../kscience/kmath/functions/interpolate.kt | 1 - ...Integrator.kt => CMGaussRuleIntegrator.kt} | 4 +- .../kmath/integration/SimpsonIntegrator.kt | 36 +++++++++++++++--- .../kmath/integration/SplineIntegrator.kt | 12 ++++++ .../kmath/integration/UnivariateIntegrand.kt | 2 +- .../kmath/integration/GaussIntegralTest.kt | 4 +- .../kmath/integration/SimpsonIntegralTest.kt | 38 +++++++++++++++++++ 7 files changed, 85 insertions(+), 12 deletions(-) rename kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/{GaussRuleIntegrator.kt => CMGaussRuleIntegrator.kt} (96%) create mode 100644 kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt create mode 100644 kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SimpsonIntegralTest.kt diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt index b05c003a6..8dbc7b7a4 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolate.kt @@ -35,7 +35,6 @@ fun main() { data.map { it.second }.toDoubleArray() ) - Plotly.plot { scatter { name = "interpolated" diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMGaussRuleIntegrator.kt similarity index 96% rename from kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt rename to kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMGaussRuleIntegrator.kt index 304fdec8f..4e174723d 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMGaussRuleIntegrator.kt @@ -11,7 +11,7 @@ import space.kscience.kmath.integration.* /** * A simple one-pass integrator based on Gauss rule */ -public class GaussRuleIntegrator( +public class CMGaussRuleIntegrator( private val numpoints: Int, private var type: GaussRule = GaussRule.LEGANDRE, ) : UnivariateIntegrator { @@ -76,7 +76,7 @@ public class GaussRuleIntegrator( numPoints: Int = 100, type: GaussRule = GaussRule.LEGANDRE, function: (Double) -> Double, - ): Double = GaussRuleIntegrator(numPoints, type).integrate( + ): Double = CMGaussRuleIntegrator(numPoints, type).integrate( UnivariateIntegrand(function, IntegrationRange(range)) ).valueOrNull!! } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt index 526d4d35d..7eca90f88 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt @@ -5,13 +5,37 @@ package space.kscience.kmath.integration -import space.kscience.kmath.operations.Ring - +import space.kscience.kmath.operations.Field +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.BufferFactory +/** + * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. + * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. + */ public class SimpsonIntegrator( - public val algebra: Ring, + public val algebra: Field, + public val bufferFactory: BufferFactory, ) : UnivariateIntegrator { - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { - TODO("Not yet implemented") + override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand = with(algebra) { + val numPoints = integrand.getFeature()?.maxCalls ?: 100 + require(numPoints >= 4) + val range = integrand.getFeature()?.range ?: 0.0..1.0 + val h: Double = (range.endInclusive - range.start) / (numPoints - 1) + val points: Buffer = bufferFactory(numPoints) { i -> + integrand.function(range.start + i * h) + }// equally distributed point + + fun simpson(index: Int) = h / 3 * (points[index - 1] + 4 * points[index] + points[index + 1]) + var res = zero + res += simpson(1) / 1.5 //border points with 1.5 factor + for (i in 2 until (points.size - 2)) { + res += simpson(i) / 2 + } + res += simpson(points.size - 2) / 1.5 //border points with 1.5 factor + return integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + points.size) } -} \ No newline at end of file +} + +public inline val Field.simpsonIntegrator: SimpsonIntegrator + get() = SimpsonIntegrator(this, Buffer.Companion::auto) \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt new file mode 100644 index 000000000..da5730497 --- /dev/null +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt @@ -0,0 +1,12 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.integration + +public class SplineIntegrator: UnivariateIntegrator { + override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + TODO("Not yet implemented") + } +} \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index c03cc8df0..d3d0220f6 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -9,7 +9,7 @@ import space.kscience.kmath.misc.UnstableKMathAPI import kotlin.jvm.JvmInline import kotlin.reflect.KClass -public class UnivariateIntegrand internal constructor( +public class UnivariateIntegrand internal constructor( private val features: Map, IntegrandFeature>, public val function: (Double) -> T, ) : Integrand { diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt index 5c9241120..9f48a15ea 100644 --- a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/GaussIntegralTest.kt @@ -19,7 +19,7 @@ class GaussIntegralTest { val res = DoubleField.gaussIntegrator.integrate(0.0..2 * PI) { x -> sin(x) } - assertEquals(0.0, res.valueOrNull!!, 1e-2) + assertEquals(0.0, res.value, 1e-2) } @Test @@ -31,7 +31,7 @@ class GaussIntegralTest { 0.0 } } - assertEquals(15.0, res.valueOrNull!!, 0.5) + assertEquals(15.0, res.value, 0.5) } diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SimpsonIntegralTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SimpsonIntegralTest.kt new file mode 100644 index 000000000..b0c0cd098 --- /dev/null +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SimpsonIntegralTest.kt @@ -0,0 +1,38 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.integration + +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.DoubleField +import kotlin.math.PI +import kotlin.math.sin +import kotlin.test.Test +import kotlin.test.assertEquals + +@OptIn(UnstableKMathAPI::class) +class SimpsonIntegralTest { + @Test + fun gaussSin() { + val res = DoubleField.simpsonIntegrator.integrate(0.0..2 * PI, IntegrandMaxCalls(5)) { x -> + sin(x) + } + assertEquals(0.0, res.value, 1e-2) + } + + @Test + fun gaussUniform() { + val res = DoubleField.simpsonIntegrator.integrate(35.0..100.0) { x -> + if(x in 30.0..50.0){ + 1.0 + } else { + 0.0 + } + } + assertEquals(15.0, res.value, 0.5) + } + + +} \ No newline at end of file From a24c8dcbce3256bb0f707fcf373cbaccbec1760a Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sat, 22 May 2021 20:08:49 +0300 Subject: [PATCH 056/132] Simpson and spline integration --- .../kmath/functions/interpolateSquare.kt | 45 +++++++++ .../kmath/operations/algebraExtensions.kt | 2 + .../kmath/structures/NumberNDFieldTest.kt | 4 +- .../kscience/kmath/functions/Polynomial.kt | 15 ++- .../kmath/integration/GaussIntegrator.kt | 8 +- .../kmath/integration/SimpsonIntegrator.kt | 45 ++++++--- .../kmath/integration/SplineIntegrator.kt | 98 ++++++++++++++++++- .../kmath/integration/UnivariateIntegrand.kt | 15 +++ .../kmath/interpolation/Interpolator.kt | 6 ++ .../kmath/integration/SimpsonIntegralTest.kt | 6 +- .../kmath/integration/SplineIntegralTest.kt | 48 +++++++++ settings.gradle.kts | 8 +- 12 files changed, 260 insertions(+), 40 deletions(-) create mode 100644 examples/src/main/kotlin/space/kscience/kmath/functions/interpolateSquare.kt create mode 100644 kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SplineIntegralTest.kt diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolateSquare.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolateSquare.kt new file mode 100644 index 000000000..33973c880 --- /dev/null +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolateSquare.kt @@ -0,0 +1,45 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.functions + +import space.kscience.kmath.interpolation.SplineInterpolator +import space.kscience.kmath.interpolation.interpolatePolynomials +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.real.step +import space.kscience.kmath.structures.map +import space.kscience.plotly.Plotly +import space.kscience.plotly.UnstablePlotlyAPI +import space.kscience.plotly.makeFile +import space.kscience.plotly.models.functionXY +import space.kscience.plotly.scatter + +@OptIn(UnstablePlotlyAPI::class) +fun main() { + val function: UnivariateFunction = { x -> + if (x in 30.0..50.0) { + 1.0 + } else { + 0.0 + } + } + val xs = 0.0..100.0 step 0.5 + val ys = xs.map(function) + + val polynomial: PiecewisePolynomial = SplineInterpolator.double.interpolatePolynomials(xs, ys) + + val polyFunction = polynomial.asFunction(DoubleField, 0.0) + + Plotly.plot { + scatter { + name = "interpolated" + functionXY(25.0..55.0, 0.1) { polyFunction(it) } + } + scatter { + name = "original" + functionXY(25.0..55.0, 0.1) { function(it) } + } + }.makeFile() +} \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt index 7967aeadb..d52be943a 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt @@ -16,6 +16,8 @@ public fun Ring.sum(data: Iterable): T = data.fold(zero) { left, right add(left, right) } +//TODO replace by sumOf with multi-receivers + /** * Returns the sum of all elements in the sequence in this [Ring]. * diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt index 57393fadd..fb51553f7 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt @@ -74,9 +74,9 @@ class NumberNDFieldTest { val division = array1.combine(array2, Double::div) } - object L2Norm : Norm, Double> { + object L2Norm : Norm, Double> { @OptIn(PerformancePitfall::class) - override fun norm(arg: StructureND): Double = + override fun norm(arg: StructureND): Double = kotlin.math.sqrt(arg.elements().sumOf { it.second.toDouble() }) } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt index 4976befcb..ba77d7b25 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt @@ -69,18 +69,23 @@ public fun Polynomial.differentiate( public fun Polynomial.integrate( algebra: A, ): Polynomial where A : Field, A : NumericAlgebra = algebra { - Polynomial(coefficients.mapIndexed { index, t -> t / number(index) }) + val integratedCoefficients = buildList(coefficients.size + 1) { + add(zero) + coefficients.forEachIndexed{ index, t -> add(t / (number(index) + one)) } + } + Polynomial(integratedCoefficients) } /** * Compute a definite integral of a given polynomial in a [range] */ @UnstableKMathAPI -public fun , A> Polynomial.integrate( - algebra: A, +public fun > Polynomial.integrate( + algebra: Field, range: ClosedRange, -): T where A : Field, A : NumericAlgebra = algebra { - value(algebra, range.endInclusive) - value(algebra, range.start) +): T = algebra { + val integral = integrate(algebra) + integral.value(algebra, range.endInclusive) - integral.value(algebra, range.start) } /** diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt index 26757ae68..283f97557 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt @@ -10,13 +10,7 @@ import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.asBuffer import space.kscience.kmath.structures.indices -/** - * Set of univariate integration ranges. First components correspond to ranges themselves, second components to number of - * integration nodes per range - */ -public class UnivariateIntegrandRanges(public val ranges: List, Int>>) : IntegrandFeature { - public constructor(vararg pairs: Pair, Int>) : this(pairs.toList()) -} + /** * A simple one-pass integrator based on Gauss rule diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt index 7eca90f88..56647bace 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt @@ -6,36 +6,53 @@ package space.kscience.kmath.integration import space.kscience.kmath.operations.Field -import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.BufferFactory +import space.kscience.kmath.operations.invoke +import space.kscience.kmath.operations.sum /** + * Use double pass Simpson rule integration with a fixed number of points. + * Requires [UnivariateIntegrandRanges] or [IntegrationRange] and [IntegrandMaxCalls] * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. */ public class SimpsonIntegrator( public val algebra: Field, - public val bufferFactory: BufferFactory, ) : UnivariateIntegrator { - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand = with(algebra) { - val numPoints = integrand.getFeature()?.maxCalls ?: 100 - require(numPoints >= 4) - val range = integrand.getFeature()?.range ?: 0.0..1.0 + + private fun integrateRange( + integrand: UnivariateIntegrand, range: ClosedRange, numPoints: Int, + ): T = algebra { val h: Double = (range.endInclusive - range.start) / (numPoints - 1) - val points: Buffer = bufferFactory(numPoints) { i -> + val values: List = List(numPoints) { i -> integrand.function(range.start + i * h) }// equally distributed point - fun simpson(index: Int) = h / 3 * (points[index - 1] + 4 * points[index] + points[index + 1]) + //TODO don't use list, reassign values instead + fun simpson(index: Int) = h / 3 * (values[index - 1] + 4 * values[index] + values[index + 1]) + var res = zero res += simpson(1) / 1.5 //border points with 1.5 factor - for (i in 2 until (points.size - 2)) { + for (i in 2 until (values.size - 2)) { + //each half-interval is computed twice, therefore /2 res += simpson(i) / 2 } - res += simpson(points.size - 2) / 1.5 //border points with 1.5 factor - return integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + points.size) + res += simpson(values.size - 2) / 1.5 //border points with 1.5 factor + return res + } + + override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + val ranges = integrand.getFeature() + return if (ranges != null) { + val res = algebra.sum(ranges.ranges.map { integrateRange(integrand, it.first, it.second) }) + integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + ranges.ranges.sumOf { it.second }) + } else { + val numPoints = integrand.getFeature()?.maxCalls ?: 100 + require(numPoints >= 4) { "Simpson integrator requires at least 4 nodes" } + val range = integrand.getFeature()?.range ?: 0.0..1.0 + val res = integrateRange(integrand, range, numPoints) + integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + numPoints) + } } } -public inline val Field.simpsonIntegrator: SimpsonIntegrator - get() = SimpsonIntegrator(this, Buffer.Companion::auto) \ No newline at end of file +public val Field.simpsonIntegrator: SimpsonIntegrator get() = SimpsonIntegrator(this) \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt index da5730497..23d7bdd8d 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt @@ -5,8 +5,98 @@ package space.kscience.kmath.integration -public class SplineIntegrator: UnivariateIntegrator { - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { - TODO("Not yet implemented") +import space.kscience.kmath.functions.PiecewisePolynomial +import space.kscience.kmath.functions.integrate +import space.kscience.kmath.interpolation.PolynomialInterpolator +import space.kscience.kmath.interpolation.SplineInterpolator +import space.kscience.kmath.interpolation.interpolatePolynomials +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.Field +import space.kscience.kmath.operations.invoke +import space.kscience.kmath.operations.sum +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.MutableBufferFactory +import space.kscience.kmath.structures.map + +/** + * Compute analytical indefinite integral of this [PiecewisePolynomial], keeping all intervals intact + */ +@UnstableKMathAPI +public fun > PiecewisePolynomial.integrate(algebra: Field): PiecewisePolynomial = + PiecewisePolynomial(pieces.map { it.first to it.second.integrate(algebra) }) + +/** + * Compute definite integral of given [PiecewisePolynomial] piece by piece in a given [range] + * Requires [UnivariateIntegrationNodes] or [IntegrationRange] and [IntegrandMaxCalls] + */ +@UnstableKMathAPI +public fun > PiecewisePolynomial.integrate( + algebra: Field, range: ClosedRange, +): T = algebra.sum( + pieces.map { (region, poly) -> + val intersectedRange = maxOf(range.start, region.start)..minOf(range.endInclusive, region.endInclusive) + //Check if polynomial range is not used + if (intersectedRange.start == intersectedRange.endInclusive) algebra.zero + else poly.integrate(algebra, intersectedRange) } -} \ No newline at end of file +) + +/** + * A generic spline-interpolation-based analytic integration + * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. + * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. + */ +@UnstableKMathAPI +public class SplineIntegrator>( + public val algebra: Field, + public val bufferFactory: MutableBufferFactory, +) : UnivariateIntegrator { + override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand = algebra { + val range = integrand.getFeature()?.range ?: 0.0..1.0 + + val interpolator: PolynomialInterpolator = SplineInterpolator(algebra, bufferFactory) + val nodes: Buffer = integrand.getFeature()?.nodes ?: run { + val numPoints = integrand.getFeature()?.maxCalls ?: 100 + val step = (range.endInclusive - range.start) / (numPoints - 1) + DoubleBuffer(numPoints) { i -> range.start + i * step } + } + + val values = nodes.map(bufferFactory) { integrand.function(it) } + val polynomials = interpolator.interpolatePolynomials( + nodes.map(bufferFactory) { number(it) }, + values + ) + val res = polynomials.integrate(algebra, number(range.start)..number(range.endInclusive)) + integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + nodes.size) + } +} + +/** + * A simplified double-based spline-interpolation-based analytic integration + * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. + * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. + */ +@UnstableKMathAPI +public object DoubleSplineIntegrator : UnivariateIntegrator { + override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + val range = integrand.getFeature()?.range ?: 0.0..1.0 + + val interpolator: PolynomialInterpolator = SplineInterpolator(DoubleField, ::DoubleBuffer) + val nodes: Buffer = integrand.getFeature()?.nodes ?: run { + val numPoints = integrand.getFeature()?.maxCalls ?: 100 + val step = (range.endInclusive - range.start) / (numPoints - 1) + DoubleBuffer(numPoints) { i -> range.start + i * step } + } + + val values = nodes.map { integrand.function(it) } + val polynomials = interpolator.interpolatePolynomials(nodes, values) + val res = polynomials.integrate(DoubleField, range) + return integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + nodes.size) + } +} + +@UnstableKMathAPI +public inline val DoubleField.splineIntegrator: UnivariateIntegrator + get() = DoubleSplineIntegrator \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index d3d0220f6..8c515065f 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -6,6 +6,8 @@ package space.kscience.kmath.integration import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.DoubleBuffer import kotlin.jvm.JvmInline import kotlin.reflect.KClass @@ -35,6 +37,19 @@ public typealias UnivariateIntegrator = Integrator> @JvmInline public value class IntegrationRange(public val range: ClosedRange) : IntegrandFeature +/** + * Set of univariate integration ranges. First components correspond to ranges themselves, second components to number of + * integration nodes per range + */ +public class UnivariateIntegrandRanges(public val ranges: List, Int>>) : IntegrandFeature { + public constructor(vararg pairs: Pair, Int>) : this(pairs.toList()) +} + +public class UnivariateIntegrationNodes(public val nodes: Buffer) : IntegrandFeature { + public constructor(vararg nodes: Double) : this(DoubleBuffer(nodes)) +} + + /** * Value of the integrand if it is present or null */ diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt index 08090a522..c9ec0d527 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt @@ -15,10 +15,16 @@ import space.kscience.kmath.operations.Ring import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.asBuffer +/** + * And interpolator for data with x column type [X], y column type [Y]. + */ public fun interface Interpolator { public fun interpolate(points: XYColumnarData): (X) -> Y } +/** + * And interpolator returning [PiecewisePolynomial] function + */ public interface PolynomialInterpolator> : Interpolator { public val algebra: Ring diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SimpsonIntegralTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SimpsonIntegralTest.kt index b0c0cd098..9f2d71554 100644 --- a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SimpsonIntegralTest.kt +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SimpsonIntegralTest.kt @@ -24,8 +24,8 @@ class SimpsonIntegralTest { @Test fun gaussUniform() { - val res = DoubleField.simpsonIntegrator.integrate(35.0..100.0) { x -> - if(x in 30.0..50.0){ + val res = DoubleField.simpsonIntegrator.integrate(35.0..100.0, IntegrandMaxCalls(20)) { x -> + if (x in 30.0..50.0) { 1.0 } else { 0.0 @@ -33,6 +33,4 @@ class SimpsonIntegralTest { } assertEquals(15.0, res.value, 0.5) } - - } \ No newline at end of file diff --git a/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SplineIntegralTest.kt b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SplineIntegralTest.kt new file mode 100644 index 000000000..afeba0be4 --- /dev/null +++ b/kmath-functions/src/commonTest/kotlin/space/kscience/kmath/integration/SplineIntegralTest.kt @@ -0,0 +1,48 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.integration + +import space.kscience.kmath.functions.Polynomial +import space.kscience.kmath.functions.integrate +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.DoubleField +import kotlin.math.PI +import kotlin.math.sin +import kotlin.test.Test +import kotlin.test.assertEquals + +@OptIn(UnstableKMathAPI::class) +class SplineIntegralTest { + + @Test + fun integratePolynomial(){ + val polynomial = Polynomial(1.0, 2.0, 3.0) + val integral = polynomial.integrate(DoubleField,1.0..2.0) + assertEquals(11.0, integral, 0.001) + } + + @Test + fun gaussSin() { + val res = DoubleField.splineIntegrator.integrate(0.0..2 * PI, IntegrandMaxCalls(5)) { x -> + sin(x) + } + assertEquals(0.0, res.value, 1e-2) + } + + @Test + fun gaussUniform() { + val res = DoubleField.splineIntegrator.integrate(35.0..100.0, IntegrandMaxCalls(20)) { x -> + if(x in 30.0..50.0){ + 1.0 + } else { + 0.0 + } + } + assertEquals(15.0, res.value, 0.5) + } + + +} \ No newline at end of file diff --git a/settings.gradle.kts b/settings.gradle.kts index cc9eb4860..065dd3ac4 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -1,11 +1,11 @@ pluginManagement { repositories { + maven("https://repo.kotlin.link") mavenCentral() gradlePluginPortal() - maven("https://repo.kotlin.link") } - val toolsVersion = "0.9.8" + val toolsVersion = "0.9.9" val kotlinVersion = "1.5.0" plugins { @@ -15,8 +15,8 @@ pluginManagement { kotlin("multiplatform") version kotlinVersion kotlin("jvm") version kotlinVersion kotlin("plugin.allopen") version kotlinVersion - id("org.jetbrains.kotlinx.benchmark") version "0.3.0" - kotlin("jupyter.api") version "0.9.1-61" + id("org.jetbrains.kotlinx.benchmark") version "0.3.1" + kotlin("jupyter.api") version "0.10.0-25" } } From ec7a971df71e4371c2720ffb77d2c3dafbd0c0bf Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sat, 22 May 2021 20:17:52 +0300 Subject: [PATCH 057/132] Separate double-based integrator for a Simpson rule --- build.gradle.kts | 3 +- .../kmath/integration/SimpsonIntegrator.kt | 51 ++++++++++++++++++- 2 files changed, 51 insertions(+), 3 deletions(-) diff --git a/build.gradle.kts b/build.gradle.kts index d44833445..ef9c60c55 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -10,13 +10,12 @@ allprojects { maven("http://logicrunch.research.it.uu.se/maven") { isAllowInsecureProtocol = true } - maven("https://maven.pkg.jetbrains.space/public/p/kotlinx-html/maven") maven("https://oss.sonatype.org/content/repositories/snapshots") mavenCentral() } group = "space.kscience" - version = "0.3.0-dev-11" + version = "0.3.0-dev-12" } subprojects { diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt index 56647bace..baa9d4af8 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt @@ -5,6 +5,8 @@ package space.kscience.kmath.integration +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Field import space.kscience.kmath.operations.invoke import space.kscience.kmath.operations.sum @@ -15,6 +17,7 @@ import space.kscience.kmath.operations.sum * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. */ +@UnstableKMathAPI public class SimpsonIntegrator( public val algebra: Field, ) : UnivariateIntegrator { @@ -55,4 +58,50 @@ public class SimpsonIntegrator( } } -public val Field.simpsonIntegrator: SimpsonIntegrator get() = SimpsonIntegrator(this) \ No newline at end of file +@UnstableKMathAPI +public val Field.simpsonIntegrator: SimpsonIntegrator get() = SimpsonIntegrator(this) + +/** + * Use double pass Simpson rule integration with a fixed number of points. + * Requires [UnivariateIntegrandRanges] or [IntegrationRange] and [IntegrandMaxCalls] + * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. + * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. + */ +public object DoubleSimpsonIntegrator : UnivariateIntegrator { + + private fun integrateRange( + integrand: UnivariateIntegrand, range: ClosedRange, numPoints: Int, + ): Double { + val h: Double = (range.endInclusive - range.start) / (numPoints - 1) + val values = DoubleArray(numPoints) { i -> + integrand.function(range.start + i * h) + }// equally distributed point + + fun simpson(index: Int) = h / 3 * (values[index - 1] + 4 * values[index] + values[index + 1]) + + var res = 0.0 + res += simpson(1) / 1.5 //border points with 1.5 factor + for (i in 2 until (values.size - 2)) { + //each half-interval is computed twice, therefore /2 + res += simpson(i) / 2 + } + res += simpson(values.size - 2) / 1.5 //border points with 1.5 factor + return res + } + + override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + val ranges = integrand.getFeature() + return if (ranges != null) { + val res = ranges.ranges.sumOf { integrateRange(integrand, it.first, it.second) } + integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + ranges.ranges.sumOf { it.second }) + } else { + val numPoints = integrand.getFeature()?.maxCalls ?: 100 + require(numPoints >= 4) { "Simpson integrator requires at least 4 nodes" } + val range = integrand.getFeature()?.range ?: 0.0..1.0 + val res = integrateRange(integrand, range, numPoints) + integrand + IntegrandValue(res) + IntegrandCallsPerformed(integrand.calls + numPoints) + } + } +} + +public val DoubleField.simpsonIntegrator: DoubleSimpsonIntegrator get() = DoubleSimpsonIntegrator \ No newline at end of file From 380c76fe40d2cdaeca9731aeb0d5b54b225ea37a Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 23 May 2021 20:01:07 +0300 Subject: [PATCH 058/132] Piecewise optimization --- build.gradle.kts | 2 +- .../space/kscience/kmath/misc/annotations.kt | 4 +- .../kscience/kmath/functions/Piecewise.kt | 49 ++++++++++++++----- 3 files changed, 42 insertions(+), 13 deletions(-) diff --git a/build.gradle.kts b/build.gradle.kts index ef9c60c55..4de6d8bad 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -15,7 +15,7 @@ allprojects { } group = "space.kscience" - version = "0.3.0-dev-12" + version = "0.3.0-dev-13" } subprojects { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt index 18718de97..e521e6237 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt @@ -26,4 +26,6 @@ public annotation class UnstableKMathAPI "Refer to the documentation to use this API in performance-critical code", RequiresOptIn.Level.WARNING ) -public annotation class PerformancePitfall +public annotation class PerformancePitfall( + val message: String = "Potential performance problem" +) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt index dd9c571b0..73fa57c7b 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.functions +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.operations.Ring /** @@ -24,17 +25,43 @@ public fun interface Piecewise { * Represents piecewise-defined function where all the sub-functions are polynomials. * @param pieces An ordered list of range-polynomial pairs. The list does not in general guarantee that there are no "holes" in it. */ -public class PiecewisePolynomial>( - public val pieces: List, Polynomial>>, -) : Piecewise> { +public interface PiecewisePolynomial> : Piecewise> { + public val pieces: Collection, Polynomial>> - public override fun findPiece(arg: T): Polynomial? { - return if (arg < pieces.first().first.start || arg >= pieces.last().first.endInclusive) - null - else { - pieces.firstOrNull { arg in it.first }?.second + public override fun findPiece(arg: T): Polynomial? +} + +/** + * A generic piecewise without constraints on how pieces are placed + */ +@PerformancePitfall("findPiece method of resulting piecewise is slow") +public fun > PiecewisePolynomial( + pieces: Collection, Polynomial>>, +): PiecewisePolynomial = object : PiecewisePolynomial { + override val pieces: Collection, Polynomial>> = pieces + + override fun findPiece(arg: T): Polynomial? = pieces.firstOrNull { arg in it.first }?.second +} + +/** + * An optimized piecewise which uses not separate pieces, but a range separated by delimiters. + * The pices search is logarithmic + */ +private class OrderedPiecewisePolynomial>( + override val pieces: List, Polynomial>>, +) : PiecewisePolynomial { + + override fun findPiece(arg: T): Polynomial? { + val index = pieces.binarySearch { (range, _) -> + when { + arg >= range.endInclusive -> -1 + arg < range.start -> +1 + else -> 0 + } } + return if (index < 0) null else pieces[index].second } + } /** @@ -71,9 +98,9 @@ public class PiecewiseBuilder>(delimiter: T) { pieces.add(0, piece) } - public fun build(): PiecewisePolynomial { - return PiecewisePolynomial(delimiters.zipWithNext { l, r -> l..r }.zip(pieces)) - } + public fun build(): PiecewisePolynomial = OrderedPiecewisePolynomial(delimiters.zipWithNext { l, r -> + l..r + }.zip(pieces)) } /** From 12805712d3a42092c7b4ca65c1fd2507acf2c0f3 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 24 May 2021 14:30:51 +0300 Subject: [PATCH 059/132] Integrand toString --- .../kmath/commons/integration/CMIntegrator.kt | 41 ++++++++----------- .../integration/GaussIntegratorRuleFactory.kt | 2 + .../kscience/kmath/integration/Integrand.kt | 29 ++++++++++--- .../integration/MultivariateIntegrand.kt | 8 ++-- .../kmath/integration/UnivariateIntegrand.kt | 29 +++++++++---- 5 files changed, 66 insertions(+), 43 deletions(-) diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt index 92bf86128..bcddccdc4 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt @@ -18,12 +18,6 @@ public class CMIntegrator( public val integratorBuilder: (Integrand) -> org.apache.commons.math3.analysis.integration.UnivariateIntegrator, ) : UnivariateIntegrator { - public class TargetRelativeAccuracy(public val value: Double) : IntegrandFeature - public class TargetAbsoluteAccuracy(public val value: Double) : IntegrandFeature - - public class MinIterations(public val value: Int) : IntegrandFeature - public class MaxIterations(public val value: Int) : IntegrandFeature - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { val integrator = integratorBuilder(integrand) val maxCalls = integrand.getFeature()?.maxCalls ?: defaultMaxCalls @@ -45,16 +39,15 @@ public class CMIntegrator( * Create a Simpson integrator based on [SimpsonIntegrator] */ public fun simpson(defaultMaxCalls: Int = 200): CMIntegrator = CMIntegrator(defaultMaxCalls) { integrand -> - val absoluteAccuracy = integrand.getFeature()?.value + val absoluteAccuracy = integrand.getFeature()?.accuracy ?: SimpsonIntegrator.DEFAULT_ABSOLUTE_ACCURACY - val relativeAccuracy = integrand.getFeature()?.value + val relativeAccuracy = integrand.getFeature()?.accuracy ?: SimpsonIntegrator.DEFAULT_ABSOLUTE_ACCURACY - val minIterations = integrand.getFeature()?.value - ?: SimpsonIntegrator.DEFAULT_MIN_ITERATIONS_COUNT - val maxIterations = integrand.getFeature()?.value - ?: SimpsonIntegrator.SIMPSON_MAX_ITERATIONS_COUNT + val iterations = integrand.getFeature()?.range + ?: SimpsonIntegrator.DEFAULT_MIN_ITERATIONS_COUNT..SimpsonIntegrator.SIMPSON_MAX_ITERATIONS_COUNT - SimpsonIntegrator(relativeAccuracy, absoluteAccuracy, minIterations, maxIterations) + + SimpsonIntegrator(relativeAccuracy, absoluteAccuracy, iterations.first, iterations.last) } /** @@ -62,21 +55,19 @@ public class CMIntegrator( */ public fun legandre(numPoints: Int, defaultMaxCalls: Int = numPoints * 5): CMIntegrator = CMIntegrator(defaultMaxCalls) { integrand -> - val absoluteAccuracy = integrand.getFeature()?.value + val absoluteAccuracy = integrand.getFeature()?.accuracy ?: IterativeLegendreGaussIntegrator.DEFAULT_ABSOLUTE_ACCURACY - val relativeAccuracy = integrand.getFeature()?.value + val relativeAccuracy = integrand.getFeature()?.accuracy ?: IterativeLegendreGaussIntegrator.DEFAULT_ABSOLUTE_ACCURACY - val minIterations = integrand.getFeature()?.value - ?: IterativeLegendreGaussIntegrator.DEFAULT_MIN_ITERATIONS_COUNT - val maxIterations = integrand.getFeature()?.value - ?: IterativeLegendreGaussIntegrator.DEFAULT_MAX_ITERATIONS_COUNT + val iterations = integrand.getFeature()?.range + ?: IterativeLegendreGaussIntegrator.DEFAULT_MIN_ITERATIONS_COUNT..IterativeLegendreGaussIntegrator.DEFAULT_MAX_ITERATIONS_COUNT IterativeLegendreGaussIntegrator( numPoints, relativeAccuracy, absoluteAccuracy, - minIterations, - maxIterations + iterations.first, + iterations.last ) } } @@ -84,14 +75,14 @@ public class CMIntegrator( @UnstableKMathAPI public var MutableList.targetAbsoluteAccuracy: Double? - get() = filterIsInstance().lastOrNull()?.value + get() = filterIsInstance().lastOrNull()?.accuracy set(value) { - value?.let { add(CMIntegrator.TargetAbsoluteAccuracy(value)) } + value?.let { add(IntegrandAbsoluteAccuracy(value)) } } @UnstableKMathAPI public var MutableList.targetRelativeAccuracy: Double? - get() = filterIsInstance().lastOrNull()?.value + get() = filterIsInstance().lastOrNull()?.accuracy set(value) { - value?.let { add(CMIntegrator.TargetRelativeAccuracy(value)) } + value?.let { add(IntegrandRelativeAccuracy(value)) } } \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt index 133f829e3..594ca9940 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt @@ -164,4 +164,6 @@ public object GaussLegendreRuleFactory : GaussIntegratorRuleFactory { } override fun build(numPoints: Int): Pair, Buffer> = getOrBuildRule(numPoints) + + override fun toString(): String = "GaussLegendreRule" } \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt index 1ff8e422e..f9c26e88b 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt @@ -7,22 +7,39 @@ package space.kscience.kmath.integration import kotlin.reflect.KClass -public interface IntegrandFeature +public interface IntegrandFeature { + override fun toString(): String +} public interface Integrand { + public val features: Set public fun getFeature(type: KClass): T? } public inline fun Integrand.getFeature(): T? = getFeature(T::class) -public class IntegrandValue(public val value: T) : IntegrandFeature +public class IntegrandValue(public val value: T) : IntegrandFeature { + override fun toString(): String = "Value($value)" +} -public class IntegrandRelativeAccuracy(public val accuracy: Double) : IntegrandFeature +public class IntegrandRelativeAccuracy(public val accuracy: Double) : IntegrandFeature { + override fun toString(): String = "TargetRelativeAccuracy($accuracy)" +} -public class IntegrandAbsoluteAccuracy(public val accuracy: Double) : IntegrandFeature +public class IntegrandAbsoluteAccuracy(public val accuracy: Double) : IntegrandFeature { + override fun toString(): String = "TargetAbsoluteAccuracy($accuracy)" +} -public class IntegrandCallsPerformed(public val calls: Int) : IntegrandFeature +public class IntegrandCallsPerformed(public val calls: Int) : IntegrandFeature { + override fun toString(): String = "Calls($calls)" +} public val Integrand.calls: Int get() = getFeature()?.calls ?: 0 -public class IntegrandMaxCalls(public val maxCalls: Int) : IntegrandFeature +public class IntegrandMaxCalls(public val maxCalls: Int) : IntegrandFeature { + override fun toString(): String = "MaxCalls($maxCalls)" +} + +public class IntegrandIterationsRange(public val range: IntRange) : IntegrandFeature { + override fun toString(): String = "Iterations(${range.first}..${range.last})" +} diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt index 12d0ef0a6..5ba411bf9 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt @@ -9,15 +9,17 @@ import space.kscience.kmath.linear.Point import kotlin.reflect.KClass public class MultivariateIntegrand internal constructor( - private val features: Map, IntegrandFeature>, + private val featureMap: Map, IntegrandFeature>, public val function: (Point) -> T, ) : Integrand { + override val features: Set get() = featureMap.values.toSet() + @Suppress("UNCHECKED_CAST") - override fun getFeature(type: KClass): T? = features[type] as? T + override fun getFeature(type: KClass): T? = featureMap[type] as? T public operator fun plus(pair: Pair, F>): MultivariateIntegrand = - MultivariateIntegrand(features + pair, function) + MultivariateIntegrand(featureMap + pair, function) public operator fun plus(feature: F): MultivariateIntegrand = plus(feature::class to feature) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index 8c515065f..e265f54e8 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -8,19 +8,20 @@ package space.kscience.kmath.integration import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer -import kotlin.jvm.JvmInline import kotlin.reflect.KClass public class UnivariateIntegrand internal constructor( - private val features: Map, IntegrandFeature>, + private val featureMap: Map, IntegrandFeature>, public val function: (Double) -> T, ) : Integrand { + override val features: Set get() = featureMap.values.toSet() + @Suppress("UNCHECKED_CAST") - override fun getFeature(type: KClass): T? = features[type] as? T + override fun getFeature(type: KClass): T? = featureMap[type] as? T public operator fun plus(pair: Pair, F>): UnivariateIntegrand = - UnivariateIntegrand(features + pair, function) + UnivariateIntegrand(featureMap + pair, function) public operator fun plus(feature: F): UnivariateIntegrand = plus(feature::class to feature) @@ -34,8 +35,9 @@ public fun UnivariateIntegrand( public typealias UnivariateIntegrator = Integrator> -@JvmInline -public value class IntegrationRange(public val range: ClosedRange) : IntegrandFeature +public class IntegrationRange(public val range: ClosedRange) : IntegrandFeature { + override fun toString(): String = "Range(${range.start}..${range.endInclusive})" +} /** * Set of univariate integration ranges. First components correspond to ranges themselves, second components to number of @@ -43,10 +45,19 @@ public value class IntegrationRange(public val range: ClosedRange) : Int */ public class UnivariateIntegrandRanges(public val ranges: List, Int>>) : IntegrandFeature { public constructor(vararg pairs: Pair, Int>) : this(pairs.toList()) + + override fun toString(): String { + val rangesString = ranges.joinToString(separator = ",") { (range, points) -> + "${range.start}..${range.endInclusive} : $points" + } + return "UnivariateRanges($rangesString)" + } } public class UnivariateIntegrationNodes(public val nodes: Buffer) : IntegrandFeature { public constructor(vararg nodes: Double) : this(DoubleBuffer(nodes)) + + override fun toString(): String = "UnivariateNodes($nodes)" } @@ -65,7 +76,7 @@ public val UnivariateIntegrand.value: T get() = valueOrNull ?: erro * The [function] is placed in the end position to allow passing a lambda. */ @UnstableKMathAPI -public fun UnivariateIntegrator.integrate( +public fun UnivariateIntegrator.integrate( vararg features: IntegrandFeature, function: (Double) -> T, ): UnivariateIntegrand = integrate(UnivariateIntegrand(function, *features)) @@ -75,7 +86,7 @@ public fun UnivariateIntegrator.integrate( * The [function] is placed in the end position to allow passing a lambda. */ @UnstableKMathAPI -public fun UnivariateIntegrator.integrate( +public fun UnivariateIntegrator.integrate( range: ClosedRange, vararg features: IntegrandFeature, function: (Double) -> T, @@ -86,7 +97,7 @@ public fun UnivariateIntegrator.integrate( * The [function] is placed in the end position to allow passing a lambda. */ @UnstableKMathAPI -public fun UnivariateIntegrator.integrate( +public fun UnivariateIntegrator.integrate( range: ClosedRange, featureBuilder: MutableList.() -> Unit = {}, function: (Double) -> T, From 88e94a7fd9cc64dbb4d892b21cedef237bfd0045 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 24 May 2021 17:02:12 +0300 Subject: [PATCH 060/132] [WIP] Optimization --- .../kmath/commons/fit/fitWithAutoDiff.kt | 1 - .../commons/optimization/CMOptimization.kt | 103 ++++++++++-------- .../kmath/commons/optimization/cmFit.kt | 2 +- .../kmath/data/XYErrorColumnarData.kt | 6 +- .../kmath/integration/GaussIntegrator.kt | 4 +- .../kscience/kmath/integration/Integrand.kt | 10 +- .../integration/MultivariateIntegrand.kt | 16 +-- .../kmath/integration/SimpsonIntegrator.kt | 4 +- .../kmath/integration/SplineIntegrator.kt | 4 +- .../kmath/integration/UnivariateIntegrand.kt | 23 ++-- .../optimization/FunctionOptimization.kt | 10 +- .../kmath/optimization/OptimizationProblem.kt | 43 +++----- .../kscience/kmath/optimization/XYFit.kt | 21 ++-- .../kmath/optimization/minuit/Range.kt | 32 ------ .../kscience/kmath/optimization/qow/QowFit.kt | 6 +- 15 files changed, 119 insertions(+), 166 deletions(-) delete mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Range.kt diff --git a/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt b/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt index 5e64235e3..5660c76e8 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt @@ -8,7 +8,6 @@ package space.kscience.kmath.commons.fit import kotlinx.html.br import kotlinx.html.h3 import space.kscience.kmath.commons.optimization.chiSquared -import space.kscience.kmath.commons.optimization.minimize import space.kscience.kmath.distributions.NormalDistribution import space.kscience.kmath.expressions.symbol import space.kscience.kmath.optimization.FunctionOptimization diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt index 6bde14627..282f1670d 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt @@ -13,7 +13,6 @@ import org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunctionGradient import org.apache.commons.math3.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer import space.kscience.kmath.expressions.derivative import space.kscience.kmath.expressions.withSymbols -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.optimization.* import kotlin.reflect.KClass @@ -21,9 +20,15 @@ import kotlin.reflect.KClass public operator fun PointValuePair.component1(): DoubleArray = point public operator fun PointValuePair.component2(): Double = value -public class CMOptimizerFactory(public val optimizerBuilder: () -> MultivariateOptimizer) : OptimizationFeature +public class CMOptimizer(public val optimizerBuilder: () -> MultivariateOptimizer): OptimizationFeature{ + override fun toString(): String = "CMOptimizer($optimizerBuilder)" +} + public class CMOptimizerData(public val data: List) : OptimizationFeature { public constructor(vararg data: OptimizationData) : this(data.toList()) + + override fun toString(): String = "CMOptimizerData($data)" + } @OptIn(UnstableKMathAPI::class) @@ -31,59 +36,69 @@ public class CMOptimization : Optimizer> { override suspend fun process( problem: FunctionOptimization, - ): FunctionOptimization = withSymbols(problem.parameters) { - val convergenceChecker: ConvergenceChecker = SimpleValueChecker( - DEFAULT_RELATIVE_TOLERANCE, - DEFAULT_ABSOLUTE_TOLERANCE, - DEFAULT_MAX_ITER - ) + ): FunctionOptimization { + val startPoint = problem.getFeature>()?.point + ?: error("Starting point not defined in $problem") - val cmOptimizer: MultivariateOptimizer = problem.getFeature()?.optimizerBuilder?.invoke() - ?: NonLinearConjugateGradientOptimizer( - NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES, - convergenceChecker + val parameters = problem.getFeature()?.symbols + ?: problem.getFeature>()?.point?.keys + ?:startPoint.keys + + + withSymbols(parameters) { + val convergenceChecker: ConvergenceChecker = SimpleValueChecker( + DEFAULT_RELATIVE_TOLERANCE, + DEFAULT_ABSOLUTE_TOLERANCE, + DEFAULT_MAX_ITER ) - val optimizationData: HashMap, OptimizationData> = HashMap() + val cmOptimizer: MultivariateOptimizer = problem.getFeature()?.optimizerBuilder?.invoke() + ?: NonLinearConjugateGradientOptimizer( + NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES, + convergenceChecker + ) - fun addOptimizationData(data: OptimizationData) { - optimizationData[data::class] = data - } + val optimizationData: HashMap, OptimizationData> = HashMap() - addOptimizationData(MaxEval.unlimited()) - addOptimizationData(InitialGuess(problem.initialGuess.toDoubleArray())) - - fun exportOptimizationData(): List = optimizationData.values.toList() - - val objectiveFunction = ObjectiveFunction { - val args = problem.initialGuess + it.toMap() - problem.expression(args) - } - addOptimizationData(objectiveFunction) - - val gradientFunction = ObjectiveFunctionGradient { - val args = problem.initialGuess + it.toMap() - DoubleArray(symbols.size) { index -> - problem.expression.derivative(symbols[index])(args) + fun addOptimizationData(data: OptimizationData) { + optimizationData[data::class] = data } - } - addOptimizationData(gradientFunction) - val logger = problem.getFeature() + addOptimizationData(MaxEval.unlimited()) + addOptimizationData(InitialGuess(startPoint.toDoubleArray())) - for (feature in problem.features) { - when (feature) { - is CMOptimizerData -> feature.data.forEach { addOptimizationData(it) } - is FunctionOptimizationTarget -> when(feature){ - FunctionOptimizationTarget.MAXIMIZE -> addOptimizationData(GoalType.MAXIMIZE) - FunctionOptimizationTarget.MINIMIZE -> addOptimizationData(GoalType.MINIMIZE) + fun exportOptimizationData(): List = optimizationData.values.toList() + + val objectiveFunction = ObjectiveFunction { + val args = startPoint + it.toMap() + problem.expression(args) + } + addOptimizationData(objectiveFunction) + + val gradientFunction = ObjectiveFunctionGradient { + val args = startPoint + it.toMap() + DoubleArray(symbols.size) { index -> + problem.expression.derivative(symbols[index])(args) } - else -> logger?.log { "The feature $feature is unused in optimization" } } - } + addOptimizationData(gradientFunction) - val (point, value) = cmOptimizer.optimize(*optimizationData.values.toTypedArray()) - return problem.withFeatures(FunctionOptimizationResult(point.toMap(), value)) + val logger = problem.getFeature() + + for (feature in problem.features) { + when (feature) { + is CMOptimizerData -> feature.data.forEach { addOptimizationData(it) } + is FunctionOptimizationTarget -> when (feature) { + FunctionOptimizationTarget.MAXIMIZE -> addOptimizationData(GoalType.MAXIMIZE) + FunctionOptimizationTarget.MINIMIZE -> addOptimizationData(GoalType.MINIMIZE) + } + else -> logger?.log { "The feature $feature is unused in optimization" } + } + } + + val (point, value) = cmOptimizer.optimize(*optimizationData.values.toTypedArray()) + return problem.withFeatures(OptimizationResult(point.toMap()), OptimizationValue(value)) + } } public companion object { diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt index 9c0089b3d..f1095ef73 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt @@ -9,7 +9,7 @@ import org.apache.commons.math3.analysis.differentiation.DerivativeStructure import space.kscience.kmath.commons.expressions.DerivativeStructureField import space.kscience.kmath.expressions.DifferentiableExpression import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.misc.Symbol +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.optimization.* import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.asBuffer diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt index ea98e88b1..7199de888 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt @@ -5,10 +5,10 @@ package space.kscience.kmath.data -import space.kscience.kmath.misc.Symbol -import space.kscience.kmath.misc.Symbol.Companion.z +import space.kscience.kmath.data.XYErrorColumnarData.Companion +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.expressions.symbol import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.misc.symbol import space.kscience.kmath.structures.Buffer diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt index 283f97557..f794b075f 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt @@ -51,7 +51,7 @@ public class GaussIntegrator( } } - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand = with(algebra) { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand = with(algebra) { val f = integrand.function val (points, weights) = buildRule(integrand) var res = zero @@ -95,7 +95,7 @@ public fun GaussIntegrator.integrate( val ranges = UnivariateIntegrandRanges( (0 until intervals).map { i -> (range.start + rangeSize * i)..(range.start + rangeSize * (i + 1)) to order } ) - return integrate( + return process( UnivariateIntegrand( function, IntegrationRange(range), diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt index f9c26e88b..dcf711c3b 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt @@ -5,18 +5,20 @@ package space.kscience.kmath.integration +import space.kscience.kmath.misc.FeatureSet +import space.kscience.kmath.misc.Featured import kotlin.reflect.KClass public interface IntegrandFeature { override fun toString(): String } -public interface Integrand { - public val features: Set - public fun getFeature(type: KClass): T? +public interface Integrand : Featured { + public val features: FeatureSet + override fun getFeature(type: KClass): T? = features.getFeature(type) } -public inline fun Integrand.getFeature(): T? = getFeature(T::class) +public inline fun Integrand.getFeature(): T? = getFeature(T::class) public class IntegrandValue(public val value: T) : IntegrandFeature { override fun toString(): String = "Value($value)" diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt index 5ba411bf9..96b81aaa6 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/MultivariateIntegrand.kt @@ -6,29 +6,21 @@ package space.kscience.kmath.integration import space.kscience.kmath.linear.Point -import kotlin.reflect.KClass +import space.kscience.kmath.misc.FeatureSet public class MultivariateIntegrand internal constructor( - private val featureMap: Map, IntegrandFeature>, + override val features: FeatureSet, public val function: (Point) -> T, ) : Integrand { - override val features: Set get() = featureMap.values.toSet() - - @Suppress("UNCHECKED_CAST") - override fun getFeature(type: KClass): T? = featureMap[type] as? T - - public operator fun plus(pair: Pair, F>): MultivariateIntegrand = - MultivariateIntegrand(featureMap + pair, function) - public operator fun plus(feature: F): MultivariateIntegrand = - plus(feature::class to feature) + MultivariateIntegrand(features.with(feature), function) } @Suppress("FunctionName") public fun MultivariateIntegrand( vararg features: IntegrandFeature, function: (Point) -> T, -): MultivariateIntegrand = MultivariateIntegrand(features.associateBy { it::class }, function) +): MultivariateIntegrand = MultivariateIntegrand(FeatureSet.of(*features), function) public val MultivariateIntegrand.value: T? get() = getFeature>()?.value diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt index baa9d4af8..77f01101a 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt @@ -43,7 +43,7 @@ public class SimpsonIntegrator( return res } - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand { val ranges = integrand.getFeature() return if (ranges != null) { val res = algebra.sum(ranges.ranges.map { integrateRange(integrand, it.first, it.second) }) @@ -89,7 +89,7 @@ public object DoubleSimpsonIntegrator : UnivariateIntegrator { return res } - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand { val ranges = integrand.getFeature() return if (ranges != null) { val res = ranges.ranges.sumOf { integrateRange(integrand, it.first, it.second) } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt index 23d7bdd8d..54fa29e83 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt @@ -53,7 +53,7 @@ public class SplineIntegrator>( public val algebra: Field, public val bufferFactory: MutableBufferFactory, ) : UnivariateIntegrator { - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand = algebra { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand = algebra { val range = integrand.getFeature()?.range ?: 0.0..1.0 val interpolator: PolynomialInterpolator = SplineInterpolator(algebra, bufferFactory) @@ -80,7 +80,7 @@ public class SplineIntegrator>( */ @UnstableKMathAPI public object DoubleSplineIntegrator : UnivariateIntegrator { - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand { val range = integrand.getFeature()?.range ?: 0.0..1.0 val interpolator: PolynomialInterpolator = SplineInterpolator(DoubleField, ::DoubleBuffer) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index e265f54e8..82fed30cd 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -5,33 +5,24 @@ package space.kscience.kmath.integration +import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer -import kotlin.reflect.KClass public class UnivariateIntegrand internal constructor( - private val featureMap: Map, IntegrandFeature>, + override val features: FeatureSet, public val function: (Double) -> T, ) : Integrand { - - override val features: Set get() = featureMap.values.toSet() - - @Suppress("UNCHECKED_CAST") - override fun getFeature(type: KClass): T? = featureMap[type] as? T - - public operator fun plus(pair: Pair, F>): UnivariateIntegrand = - UnivariateIntegrand(featureMap + pair, function) - public operator fun plus(feature: F): UnivariateIntegrand = - plus(feature::class to feature) + UnivariateIntegrand(features.with(feature), function) } @Suppress("FunctionName") public fun UnivariateIntegrand( function: (Double) -> T, vararg features: IntegrandFeature, -): UnivariateIntegrand = UnivariateIntegrand(features.associateBy { it::class }, function) +): UnivariateIntegrand = UnivariateIntegrand(FeatureSet.of(*features), function) public typealias UnivariateIntegrator = Integrator> @@ -79,7 +70,7 @@ public val UnivariateIntegrand.value: T get() = valueOrNull ?: erro public fun UnivariateIntegrator.integrate( vararg features: IntegrandFeature, function: (Double) -> T, -): UnivariateIntegrand = integrate(UnivariateIntegrand(function, *features)) +): UnivariateIntegrand = process(UnivariateIntegrand(function, *features)) /** * A shortcut method to integrate a [function] in [range] with additional [features]. @@ -90,7 +81,7 @@ public fun UnivariateIntegrator.integrate( range: ClosedRange, vararg features: IntegrandFeature, function: (Double) -> T, -): UnivariateIntegrand = integrate(UnivariateIntegrand(function, IntegrationRange(range), *features)) +): UnivariateIntegrand = process(UnivariateIntegrand(function, IntegrationRange(range), *features)) /** * A shortcut method to integrate a [function] in [range] with additional [features]. @@ -107,5 +98,5 @@ public fun UnivariateIntegrator.integrate( featureBuilder() add(IntegrationRange(range)) } - return integrate(UnivariateIntegrand(function, *features.toTypedArray())) + return process(UnivariateIntegrand(function, *features.toTypedArray())) } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index db613e236..e5edb17e0 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -10,12 +10,13 @@ import space.kscience.kmath.expressions.DifferentiableExpression import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.ExpressionAlgebra import space.kscience.kmath.misc.FeatureSet -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.indices -public class FunctionOptimizationResult(point: Map, public val value: T) : OptimizationResult(point) +public class OptimizationValue(public val value: T) : OptimizationFeature{ + override fun toString(): String = "Value($value)" +} public enum class FunctionOptimizationTarget : OptimizationFeature { MAXIMIZE, @@ -25,9 +26,8 @@ public enum class FunctionOptimizationTarget : OptimizationFeature { public class FunctionOptimization( override val features: FeatureSet, public val expression: DifferentiableExpression>, - public val initialGuess: Map, - public val parameters: Collection, ) : OptimizationProblem{ + public companion object{ /** * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation @@ -65,7 +65,5 @@ public fun FunctionOptimization.withFeatures( ): FunctionOptimization = FunctionOptimization( features.with(*newFeature), expression, - initialGuess, - parameters ) diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt index 0d2e3cb83..53b6af144 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt @@ -5,13 +5,15 @@ package space.kscience.kmath.optimization +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.Featured import space.kscience.kmath.misc.Loggable -import space.kscience.kmath.misc.Symbol import kotlin.reflect.KClass -public interface OptimizationFeature +public interface OptimizationFeature { + override fun toString(): String +} public interface OptimizationProblem : Featured { public val features: FeatureSet @@ -20,31 +22,22 @@ public interface OptimizationProblem : Featured { public inline fun OptimizationProblem.getFeature(): T? = getFeature(T::class) -public open class OptimizationResult(public val point: Map) : OptimizationFeature +public open class OptimizationStartPoint(public val point: Map) : OptimizationFeature { + override fun toString(): String = "StartPoint($point)" +} -public class OptimizationLog(private val loggable: Loggable) : Loggable by loggable, OptimizationFeature +public open class OptimizationResult(public val point: Map) : OptimizationFeature { + override fun toString(): String = "Result($point)" +} + +public class OptimizationLog(private val loggable: Loggable) : Loggable by loggable, OptimizationFeature { + override fun toString(): String = "Log($loggable)" +} + +public class OptimizationParameters(public val symbols: List): OptimizationFeature{ + override fun toString(): String = "Parameters($symbols)" +} -//public class OptimizationResult( -// public val point: Map, -// public val value: T, -// public val features: Set = emptySet(), -//) { -// override fun toString(): String { -// return "OptimizationResult(point=$point, value=$value)" -// } -//} -// -//public operator fun OptimizationResult.plus( -// feature: OptimizationFeature, -//): OptimizationResult = OptimizationResult(point, value, features + feature) -//public fun interface OptimizationProblemFactory> { -// public fun build(symbols: List): P -//} -// -//public operator fun > OptimizationProblemFactory.invoke( -// symbols: List, -// block: P.() -> Unit, -//): P = build(symbols).apply(block) public interface Optimizer

{ public suspend fun process(problem: P): P diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt index 637746a27..050f95a10 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt @@ -10,8 +10,6 @@ import space.kscience.kmath.expressions.* import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.Field -import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.indices @UnstableKMathAPI public interface XYFit : OptimizationProblem { @@ -59,15 +57,16 @@ public interface XYFit : OptimizationProblem { //} /** - * Optimize differentiable expression using specific [OptimizationProblemFactory] + * Optimize differentiable expression using specific [Optimizer] */ public suspend fun > DifferentiableExpression>.optimizeWith( - factory: OptimizationProblemFactory, - vararg symbols: Symbol, - configuration: F.() -> Unit, -): OptimizationResult { - require(symbols.isNotEmpty()) { "Must provide a list of symbols for optimization" } - val problem = factory(symbols.toList(), configuration) - problem.function(this) - return problem.optimize() + optimizer: Optimizer, + startingPoint: Map, + vararg features: OptimizationFeature +): OptimizationProblem { +// require(startingPoint.isNotEmpty()) { "Must provide a list of symbols for optimization" } +// val problem = factory(symbols.toList(), configuration) +// problem.function(this) +// return problem.optimize() + val problem = FunctionOptimization() } \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Range.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Range.kt deleted file mode 100644 index ebeedf7e8..000000000 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Range.kt +++ /dev/null @@ -1,32 +0,0 @@ -/* - * Copyright 2015 Alexander Nozik. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ -package ru.inr.mass.minuit - -/** - * A class representing a pair of double (x,y) or (lower,upper) - * - * @version $Id$ - * @author Darksnake - */ -class Range -/** - * - * Constructor for Range. - * - * @param k a double. - * @param v a double. - */ - (k: Double, v: Double) : Pair(k, v) \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt index d611adf50..2ae33d82f 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt @@ -7,12 +7,8 @@ package space.kscience.kmath.optimization.qow import space.kscience.kmath.data.ColumnarData import space.kscience.kmath.data.XYErrorColumnarData -import space.kscience.kmath.expressions.DifferentiableExpression -import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.expressions.SymbolIndexer -import space.kscience.kmath.expressions.derivative +import space.kscience.kmath.expressions.* import space.kscience.kmath.linear.* -import space.kscience.kmath.misc.Symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Field From c240fa4a9efb55116571622fa57a5c3332a1a166 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Tue, 25 May 2021 16:42:23 +0300 Subject: [PATCH 061/132] [WIP] optimization refactoring --- .../kscience/kmath/data/XYColumnarData.kt | 21 +++++ .../kscience/kmath/expressions/Symbol.kt | 16 +++- .../optimization/FunctionOptimization.kt | 17 +++- .../kmath/optimization/OptimizationProblem.kt | 1 + .../kscience/kmath/optimization/XYFit.kt | 72 --------------- .../kmath/optimization/XYOptimization.kt | 92 +++++++++++++++++++ .../kscience/kmath/optimization/qow/QowFit.kt | 4 +- 7 files changed, 141 insertions(+), 82 deletions(-) delete mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt index 08bfd3ca3..2dc82c02e 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt @@ -45,6 +45,27 @@ public fun XYColumnarData(x: Buffer, y: Buffer): XYColum } } +/** + * Represent a [ColumnarData] as an [XYColumnarData]. The presence or respective columns is checked on creation. + */ +@UnstableKMathAPI +public fun ColumnarData.asXYData( + xSymbol: Symbol, + ySymbol: Symbol, +): XYColumnarData = object : XYColumnarData { + init { + requireNotNull(this@asXYData[xSymbol]){"The column with name $xSymbol is not present in $this"} + requireNotNull(this@asXYData[ySymbol]){"The column with name $ySymbol is not present in $this"} + } + override val size: Int get() = this@asXYData.size + override val x: Buffer get() = this@asXYData[xSymbol]!! + override val y: Buffer get() = this@asXYData[ySymbol]!! + override fun get(symbol: Symbol): Buffer? = when (symbol) { + Symbol.x -> x + Symbol.y -> y + else -> this@asXYData.get(symbol) + } +} /** * A zero-copy method to represent a [Structure2D] as a two-column x-y data. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt index 74dc7aedc..4cbdbf55b 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Symbol.kt @@ -19,9 +19,12 @@ public interface Symbol : MST { public val identity: String public companion object { - public val x: StringSymbol = StringSymbol("x") - public val y: StringSymbol = StringSymbol("y") - public val z: StringSymbol = StringSymbol("z") + public val x: Symbol = Symbol("x") + public val xError: Symbol = Symbol("x.error") + public val y: Symbol = Symbol("y") + public val yError: Symbol = Symbol("y.error") + public val z: Symbol = Symbol("z") + public val zError: Symbol = Symbol("z.error") } } @@ -29,10 +32,15 @@ public interface Symbol : MST { * A [Symbol] with a [String] identity */ @JvmInline -public value class StringSymbol(override val identity: String) : Symbol { +internal value class StringSymbol(override val identity: String) : Symbol { override fun toString(): String = identity } +/** + * Create s Symbols with a string identity + */ +public fun Symbol(identity: String): Symbol = StringSymbol(identity) + /** * A delegate to create a symbol with a string identity in this scope */ diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index e5edb17e0..2c70da308 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -5,10 +5,7 @@ package space.kscience.kmath.optimization -import space.kscience.kmath.expressions.AutoDiffProcessor -import space.kscience.kmath.expressions.DifferentiableExpression -import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.expressions.ExpressionAlgebra +import space.kscience.kmath.expressions.* import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.structures.Buffer @@ -67,3 +64,15 @@ public fun FunctionOptimization.withFeatures( expression, ) +/** + * Optimize differentiable expression using specific [optimizer] form given [startingPoint] + */ +public suspend fun DifferentiableExpression>.optimizeWith( + optimizer: Optimizer>, + startingPoint: Map, + vararg features: OptimizationFeature, +): FunctionOptimization { + val problem = FunctionOptimization(FeatureSet.of(OptimizationStartPoint(startingPoint), *features), this) + return optimizer.process(problem) +} + diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt index 53b6af144..2594fa182 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt @@ -35,6 +35,7 @@ public class OptimizationLog(private val loggable: Loggable) : Loggable by logga } public class OptimizationParameters(public val symbols: List): OptimizationFeature{ + public constructor(vararg symbols: Symbol) : this(listOf(*symbols)) override fun toString(): String = "Parameters($symbols)" } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt deleted file mode 100644 index 050f95a10..000000000 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt +++ /dev/null @@ -1,72 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.optimization - -import space.kscience.kmath.data.ColumnarData -import space.kscience.kmath.expressions.* -import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.ExtendedField -import space.kscience.kmath.operations.Field - -@UnstableKMathAPI -public interface XYFit : OptimizationProblem { - - public val algebra: Field - - /** - * Set X-Y data for this fit optionally including x and y errors - */ - public fun data( - dataSet: ColumnarData, - xSymbol: Symbol, - ySymbol: Symbol, - xErrSymbol: Symbol? = null, - yErrSymbol: Symbol? = null, - ) - - public fun model(model: (T) -> DifferentiableExpression) - - /** - * Set the differentiable model for this fit - */ - public fun model( - autoDiff: AutoDiffProcessor>, - modelFunction: A.(I) -> I, - ): Unit where A : ExtendedField, A : ExpressionAlgebra = model { arg -> - autoDiff.process { modelFunction(const(arg)) } - } -} - -// -///** -// * Define a chi-squared-based objective function -// */ -//public fun FunctionOptimization.chiSquared( -// autoDiff: AutoDiffProcessor>, -// x: Buffer, -// y: Buffer, -// yErr: Buffer, -// model: A.(I) -> I, -//) where A : ExtendedField, A : ExpressionAlgebra { -// val chiSquared = FunctionOptimization.chiSquared(autoDiff, x, y, yErr, model) -// function(chiSquared) -// maximize = false -//} - -/** - * Optimize differentiable expression using specific [Optimizer] - */ -public suspend fun > DifferentiableExpression>.optimizeWith( - optimizer: Optimizer, - startingPoint: Map, - vararg features: OptimizationFeature -): OptimizationProblem { -// require(startingPoint.isNotEmpty()) { "Must provide a list of symbols for optimization" } -// val problem = factory(symbols.toList(), configuration) -// problem.function(this) -// return problem.optimize() - val problem = FunctionOptimization() -} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt new file mode 100644 index 000000000..dda95fcd7 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt @@ -0,0 +1,92 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ +@file:OptIn(UnstableKMathAPI::class) + +package space.kscience.kmath.optimization + +import space.kscience.kmath.data.XYColumnarData +import space.kscience.kmath.expressions.DifferentiableExpression +import space.kscience.kmath.expressions.Expression +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.misc.FeatureSet +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.Field +import space.kscience.kmath.operations.invoke + +public fun interface PointToCurveDistance { + public fun distance(problem: XYOptimization, index: Int): DifferentiableExpression> + + public companion object { + public fun byY( + algebra: Field, + ): PointToCurveDistance = PointToCurveDistance { problem, index -> + algebra { + val x = problem.data.x[index] + val y = problem.data.y[index] + + val model = problem.model(args + (Symbol.x to x)) + model - y + } + } + + +// val default = PointToCurveDistance{args, data, index -> +// +// } + } +} + + +public class XYOptimization( + override val features: FeatureSet, + public val data: XYColumnarData, + public val model: DifferentiableExpression>, +) : OptimizationProblem + +// +//@UnstableKMathAPI +//public interface XYFit : OptimizationProblem { +// +// public val algebra: Field +// +// /** +// * Set X-Y data for this fit optionally including x and y errors +// */ +// public fun data( +// dataSet: ColumnarData, +// xSymbol: Symbol, +// ySymbol: Symbol, +// xErrSymbol: Symbol? = null, +// yErrSymbol: Symbol? = null, +// ) +// +// public fun model(model: (T) -> DifferentiableExpression) +// +// /** +// * Set the differentiable model for this fit +// */ +// public fun model( +// autoDiff: AutoDiffProcessor>, +// modelFunction: A.(I) -> I, +// ): Unit where A : ExtendedField, A : ExpressionAlgebra = model { arg -> +// autoDiff.process { modelFunction(const(arg)) } +// } +//} + +// +///** +// * Define a chi-squared-based objective function +// */ +//public fun FunctionOptimization.chiSquared( +// autoDiff: AutoDiffProcessor>, +// x: Buffer, +// y: Buffer, +// yErr: Buffer, +// model: A.(I) -> I, +//) where A : ExtendedField, A : ExpressionAlgebra { +// val chiSquared = FunctionOptimization.chiSquared(autoDiff, x, y, yErr, model) +// function(chiSquared) +// maximize = false +//} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt index 2ae33d82f..c78aef401 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt @@ -15,7 +15,7 @@ import space.kscience.kmath.operations.Field import space.kscience.kmath.optimization.OptimizationFeature import space.kscience.kmath.optimization.OptimizationProblemFactory import space.kscience.kmath.optimization.OptimizationResult -import space.kscience.kmath.optimization.XYFit +import space.kscience.kmath.optimization.XYOptimization import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.DoubleL2Norm import kotlin.math.pow @@ -28,7 +28,7 @@ public class QowFit( override val symbols: List, private val space: LinearSpace, private val solver: LinearSolver, -) : XYFit, SymbolIndexer { +) : XYOptimization, SymbolIndexer { private var logger: FitLogger? = null From f2b7a08ad8018d508a1edc3c5af9894fb89bafd5 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Tue, 25 May 2021 16:53:53 +0300 Subject: [PATCH 062/132] Remove second generic from DifferentiableExpression --- CHANGELOG.md | 1 + .../DerivativeStructureExpression.kt | 4 +-- .../commons/optimization/CMOptimization.kt | 9 +---- .../kmath/commons/optimization/cmFit.kt | 8 ++--- .../expressions/DifferentiableExpression.kt | 34 ++++++++++++++----- .../kmath/expressions/SimpleAutoDiff.kt | 2 +- .../kmath/kotlingrad/KotlingradExpression.kt | 2 +- .../optimization/FunctionOptimization.kt | 6 ++-- .../kscience/kmath/optimization/XYFit.kt | 2 +- 9 files changed, 39 insertions(+), 29 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 9c6b14b95..524d2a1de 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -45,6 +45,7 @@ - MSTExpression - Expression algebra builders - Complex and Quaternion no longer are elements. +- Second generic from DifferentiableExpression ### Fixed - Ring inherits RingOperations, not GroupOperations diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt index 89e216601..361027968 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt @@ -106,7 +106,7 @@ public class DerivativeStructureField( public companion object : AutoDiffProcessor> { - public override fun process(function: DerivativeStructureField.() -> DerivativeStructure): DifferentiableExpression> = + public override fun process(function: DerivativeStructureField.() -> DerivativeStructure): DifferentiableExpression = DerivativeStructureExpression(function) } } @@ -116,7 +116,7 @@ public class DerivativeStructureField( */ public class DerivativeStructureExpression( public val function: DerivativeStructureField.() -> DerivativeStructure, -) : DifferentiableExpression> { +) : DifferentiableExpression { public override operator fun invoke(arguments: Map): Double = DerivativeStructureField(0, arguments).function().value diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt index bca00de46..400ee0310 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt @@ -17,14 +17,7 @@ import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.SimplexOptimizer import space.kscience.kmath.expressions.* import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.optimization.* -import kotlin.collections.HashMap -import kotlin.collections.List -import kotlin.collections.Map import kotlin.collections.set -import kotlin.collections.setOf -import kotlin.collections.toList -import kotlin.collections.toMap -import kotlin.collections.toTypedArray import kotlin.reflect.KClass public operator fun PointValuePair.component1(): DoubleArray = point @@ -71,7 +64,7 @@ public class CMOptimization( addOptimizationData(objectiveFunction) } - public override fun diffFunction(expression: DifferentiableExpression>) { + public override fun diffFunction(expression: DifferentiableExpression) { function(expression) val gradientFunction = ObjectiveFunctionGradient { val args = it.toMap() diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt index a5a913623..645c41291 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt @@ -25,7 +25,7 @@ public fun FunctionOptimization.Companion.chiSquared( y: Buffer, yErr: Buffer, model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure, -): DifferentiableExpression> = chiSquared(DerivativeStructureField, x, y, yErr, model) +): DifferentiableExpression = chiSquared(DerivativeStructureField, x, y, yErr, model) /** * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation @@ -35,7 +35,7 @@ public fun FunctionOptimization.Companion.chiSquared( y: Iterable, yErr: Iterable, model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure, -): DifferentiableExpression> = chiSquared( +): DifferentiableExpression = chiSquared( DerivativeStructureField, x.toList().asBuffer(), y.toList().asBuffer(), @@ -54,12 +54,12 @@ public fun Expression.optimize( /** * Optimize differentiable expression */ -public fun DifferentiableExpression>.optimize( +public fun DifferentiableExpression.optimize( vararg symbols: Symbol, configuration: CMOptimization.() -> Unit, ): OptimizationResult = optimizeWith(CMOptimization, symbols = symbols, configuration) -public fun DifferentiableExpression>.minimize( +public fun DifferentiableExpression.minimize( vararg startPoint: Pair, configuration: CMOptimization.() -> Unit = {}, ): OptimizationResult { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt index 33d72afad..1dcada6d3 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt @@ -11,35 +11,51 @@ package space.kscience.kmath.expressions * @param T the type this expression takes as argument and returns. * @param R the type of expression this expression can be differentiated to. */ -public interface DifferentiableExpression> : Expression { +public interface DifferentiableExpression : Expression { /** * Differentiates this expression by ordered collection of [symbols]. * * @param symbols the symbols. * @return the derivative or `null`. */ - public fun derivativeOrNull(symbols: List): R? + public fun derivativeOrNull(symbols: List): Expression? } -public fun > DifferentiableExpression.derivative(symbols: List): R = +public fun DifferentiableExpression.derivative(symbols: List): Expression = derivativeOrNull(symbols) ?: error("Derivative by symbols $symbols not provided") -public fun > DifferentiableExpression.derivative(vararg symbols: Symbol): R = +public fun DifferentiableExpression.derivative(vararg symbols: Symbol): Expression = derivative(symbols.toList()) -public fun > DifferentiableExpression.derivative(name: String): R = +public fun DifferentiableExpression.derivative(name: String): Expression = + derivative(StringSymbol(name)) + +/** + * A special type of [DifferentiableExpression] which returns typed expressions as derivatives + */ +public interface SpecialDifferentiableExpression>: DifferentiableExpression { + override fun derivativeOrNull(symbols: List): R? +} + +public fun > SpecialDifferentiableExpression.derivative(symbols: List): R = + derivativeOrNull(symbols) ?: error("Derivative by symbols $symbols not provided") + +public fun > SpecialDifferentiableExpression.derivative(vararg symbols: Symbol): R = + derivative(symbols.toList()) + +public fun > SpecialDifferentiableExpression.derivative(name: String): R = derivative(StringSymbol(name)) /** * A [DifferentiableExpression] that defines only first derivatives */ -public abstract class FirstDerivativeExpression> : DifferentiableExpression { +public abstract class FirstDerivativeExpression : DifferentiableExpression { /** * Returns first derivative of this expression by given [symbol]. */ - public abstract fun derivativeOrNull(symbol: Symbol): R? + public abstract fun derivativeOrNull(symbol: Symbol): Expression? - public final override fun derivativeOrNull(symbols: List): R? { + public final override fun derivativeOrNull(symbols: List): Expression? { val dSymbol = symbols.firstOrNull() ?: return null return derivativeOrNull(dSymbol) } @@ -49,5 +65,5 @@ public abstract class FirstDerivativeExpression> : Differen * A factory that converts an expression in autodiff variables to a [DifferentiableExpression] */ public fun interface AutoDiffProcessor, out R : Expression> { - public fun process(function: A.() -> I): DifferentiableExpression + public fun process(function: A.() -> I): DifferentiableExpression } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt index 254d60b3d..478b85620 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt @@ -232,7 +232,7 @@ public fun > F.simpleAutoDiff( public class SimpleAutoDiffExpression>( public val field: F, public val function: SimpleAutoDiffField.() -> AutoDiffValue, -) : FirstDerivativeExpression>() { +) : FirstDerivativeExpression() { public override operator fun invoke(arguments: Map): T { //val bindings = arguments.entries.map { it.key.bind(it.value) } return SimpleAutoDiffField(field, arguments).function().value diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt index 72ecee4f1..4294462c0 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt @@ -24,7 +24,7 @@ import space.kscience.kmath.operations.NumericAlgebra public class KotlingradExpression>( public val algebra: A, public val mst: MST, -) : DifferentiableExpression> { +) : SpecialDifferentiableExpression> { public override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) public override fun derivativeOrNull(symbols: List): KotlingradExpression = diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index 4cf5aea84..f54ba5723 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -27,7 +27,7 @@ public interface FunctionOptimization : Optimization { /** * Set a differentiable expression as objective function as function and gradient provider */ - public fun diffFunction(expression: DifferentiableExpression>) + public fun diffFunction(expression: DifferentiableExpression) public companion object { /** @@ -39,7 +39,7 @@ public interface FunctionOptimization : Optimization { y: Buffer, yErr: Buffer, model: A.(I) -> I, - ): DifferentiableExpression> where A : ExtendedField, A : ExpressionAlgebra { + ): DifferentiableExpression where A : ExtendedField, A : ExpressionAlgebra { require(x.size == y.size) { "X and y buffers should be of the same size" } require(y.size == yErr.size) { "Y and yErr buffer should of the same size" } @@ -78,7 +78,7 @@ public fun FunctionOptimization.chiSquared( /** * Optimize differentiable expression using specific [OptimizationProblemFactory] */ -public fun > DifferentiableExpression>.optimizeWith( +public fun > DifferentiableExpression.optimizeWith( factory: OptimizationProblemFactory, vararg symbols: Symbol, configuration: F.() -> Unit, diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt index 633e9ae0e..70d7fdf79 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt @@ -27,7 +27,7 @@ public interface XYFit : Optimization { yErrSymbol: Symbol? = null, ) - public fun model(model: (T) -> DifferentiableExpression) + public fun model(model: (T) -> DifferentiableExpression) /** * Set the differentiable model for this fit From c8621ee5b759cc364f94e1df3fbdf3262e6a7878 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Tue, 25 May 2021 21:11:57 +0300 Subject: [PATCH 063/132] [WIP] optimization refactoring --- .../commons/optimization/CMOptimization.kt | 2 +- .../optimization/FunctionOptimization.kt | 4 +- .../kmath/optimization/OptimizationProblem.kt | 4 -- .../kscience/kmath/optimization/Optimizer.kt | 10 +++ .../kmath/optimization/XYOptimization.kt | 62 +++++++++++++------ 5 files changed, 56 insertions(+), 26 deletions(-) create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt index 549683d60..2faee1f5d 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt @@ -35,7 +35,7 @@ public class CMOptimizerData(public val data: List) : Optimiza @OptIn(UnstableKMathAPI::class) public class CMOptimization : Optimizer> { - override suspend fun process( + override suspend fun optimize( problem: FunctionOptimization, ): FunctionOptimization { val startPoint = problem.getFeature>()?.point diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index ee75bfbd6..62288242a 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -67,12 +67,12 @@ public fun FunctionOptimization.withFeatures( /** * Optimize differentiable expression using specific [optimizer] form given [startingPoint] */ -public suspend fun DifferentiableExpression>.optimizeWith( +public suspend fun DifferentiableExpression.optimizeWith( optimizer: Optimizer>, startingPoint: Map, vararg features: OptimizationFeature, ): FunctionOptimization { val problem = FunctionOptimization(FeatureSet.of(OptimizationStartPoint(startingPoint), *features), this) - return optimizer.process(problem) + return optimizer.optimize(problem) } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt index 2594fa182..739ce8ca5 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt @@ -40,7 +40,3 @@ public class OptimizationParameters(public val symbols: List): Optimizat } -public interface Optimizer

{ - public suspend fun process(problem: P): P -} - diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt new file mode 100644 index 000000000..ad1a16007 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt @@ -0,0 +1,10 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.optimization + +public interface Optimizer

{ + public suspend fun optimize(problem: P): P +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt index dda95fcd7..7dc17f6d9 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt @@ -12,39 +12,63 @@ import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.Field -import space.kscience.kmath.operations.invoke +import kotlin.math.pow -public fun interface PointToCurveDistance { - public fun distance(problem: XYOptimization, index: Int): DifferentiableExpression> +public interface PointToCurveDistance : OptimizationFeature { + public fun distance(problem: XYOptimization, index: Int): DifferentiableExpression public companion object { - public fun byY( - algebra: Field, - ): PointToCurveDistance = PointToCurveDistance { problem, index -> - algebra { + public val byY: PointToCurveDistance = object : PointToCurveDistance { + override fun distance(problem: XYOptimization, index: Int): DifferentiableExpression { + val x = problem.data.x[index] val y = problem.data.y[index] - - val model = problem.model(args + (Symbol.x to x)) - model - y + return object : DifferentiableExpression { + override fun derivativeOrNull(symbols: List): Expression? = + problem.model.derivativeOrNull(symbols) + + override fun invoke(arguments: Map): Double = + problem.model(arguments + (Symbol.x to x)) - y + } } + + override fun toString(): String = "PointToCurveDistanceByY" + } - -// val default = PointToCurveDistance{args, data, index -> -// -// } } } - -public class XYOptimization( +public class XYOptimization( override val features: FeatureSet, - public val data: XYColumnarData, - public val model: DifferentiableExpression>, + public val data: XYColumnarData, + public val model: DifferentiableExpression, ) : OptimizationProblem + +public suspend fun Optimizer>.maximumLogLikelihood(problem: XYOptimization): XYOptimization { + val distanceBuilder = problem.getFeature() ?: PointToCurveDistance.byY + val likelihood: DifferentiableExpression = object : DifferentiableExpression { + override fun derivativeOrNull(symbols: List): Expression? { + TODO("Not yet implemented") + } + + override fun invoke(arguments: Map): Double { + var res = 0.0 + for (index in 0 until problem.data.size) { + val d = distanceBuilder.distance(problem, index).invoke(arguments) + val sigma: Double = TODO() + res -= (d / sigma).pow(2) + } + return res + } + + } + val functionOptimization = FunctionOptimization(problem.features, likelihood) + val result = optimize(functionOptimization) + return XYOptimization(result.features, problem.data, problem.model) +} + // //@UnstableKMathAPI //public interface XYFit : OptimizationProblem { From 65e05605533a033fff621b83a447c7a78a07cd58 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sat, 29 May 2021 15:50:16 +0700 Subject: [PATCH 064/132] Fix Symja build issues --- build.gradle.kts | 5 ++++- kmath-symja/build.gradle.kts | 9 ++++++++- .../space/kscience/kmath/symja/SymjaExpression.kt | 15 +++++++++++++-- 3 files changed, 25 insertions(+), 4 deletions(-) diff --git a/build.gradle.kts b/build.gradle.kts index 4de6d8bad..1826a2e7e 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -10,7 +10,9 @@ allprojects { maven("http://logicrunch.research.it.uu.se/maven") { isAllowInsecureProtocol = true } - maven("https://oss.sonatype.org/content/repositories/snapshots") + maven("https://oss.sonatype.org/content/repositories/snapshots") { + + } mavenCentral() } @@ -31,6 +33,7 @@ subprojects { externalDocumentationLink("http://ejml.org/javadoc/") externalDocumentationLink("https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/") externalDocumentationLink("https://deeplearning4j.org/api/latest/") + externalDocumentationLink("https://axelclk.bitbucket.io/symja/javadoc/") externalDocumentationLink("https://kotlin.github.io/kotlinx.coroutines/kotlinx-coroutines-core/") } } diff --git a/kmath-symja/build.gradle.kts b/kmath-symja/build.gradle.kts index c06020bb6..c67b42e3f 100644 --- a/kmath-symja/build.gradle.kts +++ b/kmath-symja/build.gradle.kts @@ -11,7 +11,14 @@ plugins { description = "Symja integration module" dependencies { - api("org.matheclipse:matheclipse-core:2.0.0-SNAPSHOT") + api("org.matheclipse:matheclipse-core:2.0.0-SNAPSHOT") { + // Incorrect transitive dependency org.apfloat:apfloat:1.10.0-SNAPSHOT + exclude("org.apfloat", "apfloat") + } + + // Replace for org.apfloat:apfloat:1.10.0-SNAPSHOT + api("org.apfloat:apfloat:1.10.0") + api(project(":kmath-core")) testImplementation("org.slf4j:slf4j-simple:1.7.30") } diff --git a/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt index 301678916..a6773c709 100644 --- a/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt +++ b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt @@ -7,17 +7,28 @@ package space.kscience.kmath.symja import org.matheclipse.core.eval.ExprEvaluator import org.matheclipse.core.expression.F -import space.kscience.kmath.expressions.DifferentiableExpression +import space.kscience.kmath.expressions.SpecialDifferentiableExpression import space.kscience.kmath.expressions.MST import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.expressions.interpret import space.kscience.kmath.operations.NumericAlgebra +/** + * Represents [MST] based [DifferentiableExpression] relying on [Symja](https://github.com/axkr/symja_android_library). + * + * The principle of this API is converting the [mst] to an [org.matheclipse.core.interfaces.IExpr], differentiating it + * with Symja's [F.D], then converting [org.matheclipse.core.interfaces.IExpr] back to [MST]. + * + * @param T The type of number. + * @param A The [NumericAlgebra] of [T]. + * @property algebra The [A] instance. + * @property mst The [MST] node. + */ public class SymjaExpression>( public val algebra: A, public val mst: MST, public val evaluator: ExprEvaluator = DEFAULT_EVALUATOR, -) : DifferentiableExpression> { +) : SpecialDifferentiableExpression> { public override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) public override fun derivativeOrNull(symbols: List): SymjaExpression = SymjaExpression( From 7f32348e7a1c1701288c35db3c0dd020baa6726b Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Wed, 2 Jun 2021 21:10:05 +0300 Subject: [PATCH 065/132] Slight adjustment to tensor internals --- .../kmath/tensors/core/DoubleTensorAlgebra.kt | 60 ++++++++----- .../kmath/tensors/core/internal/linUtils.kt | 87 ++++++++++--------- 2 files changed, 84 insertions(+), 63 deletions(-) diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt index 1fd46bd57..f854beb29 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt @@ -5,8 +5,10 @@ package space.kscience.kmath.tensors.core +import space.kscience.kmath.nd.MutableStructure2D import space.kscience.kmath.nd.as1D import space.kscience.kmath.nd.as2D +import space.kscience.kmath.structures.indices import space.kscience.kmath.tensors.api.AnalyticTensorAlgebra import space.kscience.kmath.tensors.api.LinearOpsTensorAlgebra import space.kscience.kmath.tensors.api.Tensor @@ -813,28 +815,32 @@ public open class DoubleTensorAlgebra : val sTensor = zeros(commonShape + intArrayOf(min(n, m))) val vTensor = zeros(commonShape + intArrayOf(min(n, m), m)) - tensor.matrixSequence() - .zip( - uTensor.matrixSequence() - .zip( - sTensor.vectorSequence() - .zip(vTensor.matrixSequence()) - ) - ).forEach { (matrix, USV) -> - val matrixSize = matrix.shape.reduce { acc, i -> acc * i } - val curMatrix = DoubleTensor( - matrix.shape, - matrix.mutableBuffer.array().slice(matrix.bufferStart until matrix.bufferStart + matrixSize) - .toDoubleArray() - ) - svdHelper(curMatrix, USV, m, n, epsilon) - } + val matrices = tensor.matrices + val uTensors = uTensor.matrices + val sTensorVectors = sTensor.vectors + val vTensors = vTensor.matrices + + for (index in matrices.indices) { + val matrix = matrices[index] + val usv = Triple( + uTensors[index], + sTensorVectors[index], + vTensors[index] + ) + val matrixSize = matrix.shape.reduce { acc, i -> acc * i } + val curMatrix = DoubleTensor( + matrix.shape, + matrix.mutableBuffer.array() + .slice(matrix.bufferStart until matrix.bufferStart + matrixSize) + .toDoubleArray() + ) + svdHelper(curMatrix, usv, m, n, epsilon) + } return Triple(uTensor.transpose(), sTensor, vTensor.transpose()) } - override fun Tensor.symEig(): Pair = - symEig(epsilon = 1e-15) + override fun Tensor.symEig(): Pair = symEig(epsilon = 1e-15) /** * Returns eigenvalues and eigenvectors of a real symmetric matrix input or a batch of real symmetric matrices, @@ -846,12 +852,26 @@ public open class DoubleTensorAlgebra : */ public fun Tensor.symEig(epsilon: Double): Pair { checkSymmetric(tensor, epsilon) + + fun MutableStructure2D.cleanSym(n: Int) { + for (i in 0 until n) { + for (j in 0 until n) { + if (i == j) { + this[i, j] = sign(this[i, j]) + } else { + this[i, j] = 0.0 + } + } + } + } + val (u, s, v) = tensor.svd(epsilon) val shp = s.shape + intArrayOf(1) val utv = u.transpose() dot v val n = s.shape.last() - for (matrix in utv.matrixSequence()) - cleanSymHelper(matrix.as2D(), n) + for (matrix in utv.matrixSequence()) { + matrix.as2D().cleanSym(n) + } val eig = (utv dot s.view(shp)).view(s.shape) return eig to v diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt index 7d3617547..0434bf96f 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt @@ -10,41 +10,54 @@ import space.kscience.kmath.nd.MutableStructure2D import space.kscience.kmath.nd.as1D import space.kscience.kmath.nd.as2D import space.kscience.kmath.operations.invoke -import space.kscience.kmath.tensors.core.* +import space.kscience.kmath.structures.VirtualBuffer +import space.kscience.kmath.structures.asSequence +import space.kscience.kmath.tensors.core.BufferedTensor +import space.kscience.kmath.tensors.core.DoubleTensor import space.kscience.kmath.tensors.core.DoubleTensorAlgebra -import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.valueOrNull +import space.kscience.kmath.tensors.core.IntTensor import kotlin.math.abs import kotlin.math.min -import kotlin.math.sign import kotlin.math.sqrt +internal val BufferedTensor.vectors: VirtualBuffer> + get() { + val n = shape.size + val vectorOffset = shape[n - 1] + val vectorShape = intArrayOf(shape.last()) -internal fun BufferedTensor.vectorSequence(): Sequence> = sequence { - val n = shape.size - val vectorOffset = shape[n - 1] - val vectorShape = intArrayOf(shape.last()) - for (offset in 0 until numElements step vectorOffset) { - val vector = BufferedTensor(vectorShape, mutableBuffer, bufferStart + offset) - yield(vector) + return VirtualBuffer(numElements / vectorOffset) { index -> + val offset = index * vectorOffset + BufferedTensor(vectorShape, mutableBuffer, bufferStart + offset) + } } -} -internal fun BufferedTensor.matrixSequence(): Sequence> = sequence { - val n = shape.size - check(n >= 2) { "Expected tensor with 2 or more dimensions, got size $n" } - val matrixOffset = shape[n - 1] * shape[n - 2] - val matrixShape = intArrayOf(shape[n - 2], shape[n - 1]) - for (offset in 0 until numElements step matrixOffset) { - val matrix = BufferedTensor(matrixShape, mutableBuffer, bufferStart + offset) - yield(matrix) + +internal fun BufferedTensor.vectorSequence(): Sequence> = vectors.asSequence() + +/** + * A random access alternative to [matrixSequence] + */ +internal val BufferedTensor.matrices: VirtualBuffer> + get() { + val n = shape.size + check(n >= 2) { "Expected tensor with 2 or more dimensions, got size $n" } + val matrixOffset = shape[n - 1] * shape[n - 2] + val matrixShape = intArrayOf(shape[n - 2], shape[n - 1]) + + return VirtualBuffer(numElements / matrixOffset) { index -> + val offset = index * matrixOffset + BufferedTensor(matrixShape, mutableBuffer, bufferStart + offset) + } } -} + +internal fun BufferedTensor.matrixSequence(): Sequence> = matrices.asSequence() internal fun dotHelper( a: MutableStructure2D, b: MutableStructure2D, res: MutableStructure2D, - l: Int, m: Int, n: Int + l: Int, m: Int, n: Int, ) { for (i in 0 until l) { for (j in 0 until n) { @@ -60,7 +73,7 @@ internal fun dotHelper( internal fun luHelper( lu: MutableStructure2D, pivots: MutableStructure1D, - epsilon: Double + epsilon: Double, ): Boolean { val m = lu.rowNum @@ -122,7 +135,7 @@ internal fun BufferedTensor.setUpPivots(): IntTensor { internal fun DoubleTensorAlgebra.computeLU( tensor: DoubleTensor, - epsilon: Double + epsilon: Double, ): Pair? { checkSquareMatrix(tensor.shape) @@ -139,7 +152,7 @@ internal fun DoubleTensorAlgebra.computeLU( internal fun pivInit( p: MutableStructure2D, pivot: MutableStructure1D, - n: Int + n: Int, ) { for (i in 0 until n) { p[i, pivot[i]] = 1.0 @@ -150,7 +163,7 @@ internal fun luPivotHelper( l: MutableStructure2D, u: MutableStructure2D, lu: MutableStructure2D, - n: Int + n: Int, ) { for (i in 0 until n) { for (j in 0 until n) { @@ -170,7 +183,7 @@ internal fun luPivotHelper( internal fun choleskyHelper( a: MutableStructure2D, l: MutableStructure2D, - n: Int + n: Int, ) { for (i in 0 until n) { for (j in 0 until i) { @@ -200,7 +213,7 @@ internal fun luMatrixDet(lu: MutableStructure2D, pivots: MutableStructur internal fun luMatrixInv( lu: MutableStructure2D, pivots: MutableStructure1D, - invMatrix: MutableStructure2D + invMatrix: MutableStructure2D, ) { val m = lu.shape[0] @@ -227,7 +240,7 @@ internal fun luMatrixInv( internal fun DoubleTensorAlgebra.qrHelper( matrix: DoubleTensor, q: DoubleTensor, - r: MutableStructure2D + r: MutableStructure2D, ) { checkSquareMatrix(matrix.shape) val n = matrix.shape[0] @@ -280,12 +293,11 @@ internal fun DoubleTensorAlgebra.svd1d(a: DoubleTensor, epsilon: Double = 1e-10) internal fun DoubleTensorAlgebra.svdHelper( matrix: DoubleTensor, - USV: Pair, Pair, BufferedTensor>>, - m: Int, n: Int, epsilon: Double + USV: Triple, BufferedTensor, BufferedTensor>, + m: Int, n: Int, epsilon: Double, ) { val res = ArrayList>(0) - val (matrixU, SV) = USV - val (matrixS, matrixV) = SV + val (matrixU, matrixS, matrixV) = USV for (k in 0 until min(n, m)) { var a = matrix.copy() @@ -329,14 +341,3 @@ internal fun DoubleTensorAlgebra.svdHelper( matrixV.mutableBuffer.array()[matrixV.bufferStart + i] = vBuffer[i] } } - -internal fun cleanSymHelper(matrix: MutableStructure2D, n: Int) { - for (i in 0 until n) - for (j in 0 until n) { - if (i == j) { - matrix[i, j] = sign(matrix[i, j]) - } else { - matrix[i, j] = 0.0 - } - } -} From 95c0b2d3f097dfaec47ab449004befce7e349472 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Tue, 8 Jun 2021 14:27:45 +0300 Subject: [PATCH 066/132] [WIP] optimization with QOW --- .gitignore | 2 + CHANGELOG.md | 3 + .../kscience/kmath/benchmarks/DotBenchmark.kt | 6 +- .../benchmarks/MatrixInverseBenchmark.kt | 4 +- .../kmath/ejml/codegen/ejmlCodegen.kt | 2 +- .../kscience/kmath/ast/kotlingradSupport.kt | 4 +- .../kotlin/space/kscience/kmath/ast/parser.kt | 4 +- .../kmath/asm/internal/mapIntrinsics.kt | 3 +- .../DerivativeStructureExpression.kt | 10 +- .../integration/CMGaussRuleIntegrator.kt | 6 +- .../kmath/commons/integration/CMIntegrator.kt | 2 +- .../kscience/kmath/commons/linear/CMMatrix.kt | 14 +- .../kscience/kmath/commons/linear/CMSolver.kt | 10 + .../{CMOptimization.kt => CMOptimizer.kt} | 66 +- .../kmath/commons/optimization/cmFit.kt | 75 -- .../commons/optimization/OptimizeTest.kt | 36 +- .../space/kscience/kmath/data/ColumnarData.kt | 3 + .../expressions/DifferentiableExpression.kt | 9 +- .../kscience/kmath/linear/LinearSolver.kt | 19 - .../kscience/kmath/linear/LinearSpace.kt | 30 +- .../kscience/kmath/linear/LupDecomposition.kt | 65 +- .../kscience/kmath/linear/MatrixBuilder.kt | 31 +- .../kscience/kmath/linear/MatrixWrapper.kt | 27 +- .../kscience/kmath/linear/VirtualMatrix.kt | 3 + .../space/kscience/kmath/linear/symmetric.kt | 34 - .../space/kscience/kmath/misc/Featured.kt | 27 +- .../space/kscience/kmath/misc/annotations.kt | 4 +- .../space/kscience/kmath/nd/StructureND.kt | 8 +- .../kmath/structures/BufferAccessor2D.kt | 18 +- .../kmath/linear/DoubleLUSolverTest.kt | 12 +- .../space/kscience/kmath/linear/MatrixTest.kt | 8 +- .../kmath/structures/NumberNDFieldTest.kt | 2 +- .../kscience/kmath/dimensions/Wrappers.kt | 2 +- .../space/kscience/kmath/ejml/_generated.kt | 995 ------------------ .../kscience/kmath/ejml/EjmlMatrixTest.kt | 6 +- .../space/kscience/kmath/real/RealMatrix.kt | 36 +- .../kotlin/space/kscience/kmath/real/dot.kt | 2 +- .../kaceince/kmath/real/DoubleMatrixTest.kt | 4 +- .../kaceince/kmath/real/DoubleVectorTest.kt | 2 +- .../kscience/kmath/integration/Integrand.kt | 5 +- .../kmath/kotlingrad/KotlingradExpression.kt | 31 +- .../optimization/FunctionOptimization.kt | 10 +- .../kmath/optimization/OptimizationBuilder.kt | 93 ++ .../kmath/optimization/OptimizationProblem.kt | 40 +- .../kscience/kmath/optimization/Optimizer.kt | 2 +- .../kmath/optimization/QowOptimizer.kt | 247 +++++ .../kmath/optimization/XYOptimization.kt | 115 +- .../kmath/optimization/qow => tmp}/QowFit.kt | 0 .../minuit/AnalyticalGradientCalculator.kt | 0 .../minuit/CombinedMinimizer.kt | 0 .../minuit/CombinedMinimumBuilder.kt | 1 + .../minuit/ContoursError.kt | 0 .../minuit/DavidonErrorUpdator.kt | 0 .../minuit/FunctionGradient.kt | 0 .../minuit/FunctionMinimum.kt | 1 + .../minuit/GradientCalculator.kt | 0 .../minuit/HessianGradientCalculator.kt | 0 .../minuit/InitialGradientCalculator.kt | 0 .../minuit/MINOSResult.kt | 0 .../minuit/MINUITFitter.kt | 0 .../minuit/MINUITPlugin.kt | 0 .../minuit/MINUITUtils.kt | 0 .../minuit/MinimumBuilder.kt | 2 + .../minuit/MinimumError.kt | 0 .../minuit/MinimumErrorUpdator.kt | 0 .../minuit/MinimumParameters.kt | 0 .../minuit/MinimumSeed.kt | 4 +- .../minuit/MinimumSeedGenerator.kt | 2 + .../minuit/MinimumState.kt | 0 .../optimization => tmp}/minuit/MinosError.kt | 0 .../minuit/MinuitParameter.kt | 0 .../minuit/MnAlgebraicSymMatrix.kt | 0 .../minuit/MnApplication.kt | 0 .../optimization => tmp}/minuit/MnContours.kt | 0 .../minuit/MnCovarianceSqueeze.kt | 0 .../optimization => tmp}/minuit/MnCross.kt | 0 .../optimization => tmp}/minuit/MnEigen.kt | 0 .../optimization => tmp}/minuit/MnFcn.kt | 0 .../minuit/MnFunctionCross.kt | 0 .../minuit/MnGlobalCorrelationCoeff.kt | 0 .../optimization => tmp}/minuit/MnHesse.kt | 0 .../minuit/MnLineSearch.kt | 0 .../minuit/MnMachinePrecision.kt | 0 .../optimization => tmp}/minuit/MnMigrad.kt | 0 .../optimization => tmp}/minuit/MnMinimize.kt | 0 .../optimization => tmp}/minuit/MnMinos.kt | 0 .../optimization => tmp}/minuit/MnParabola.kt | 0 .../minuit/MnParabolaFactory.kt | 0 .../minuit/MnParabolaPoint.kt | 0 .../minuit/MnParameterScan.kt | 0 .../optimization => tmp}/minuit/MnPlot.kt | 0 .../optimization => tmp}/minuit/MnPosDef.kt | 0 .../optimization => tmp}/minuit/MnPrint.kt | 0 .../optimization => tmp}/minuit/MnScan.kt | 0 .../minuit/MnSeedGenerator.kt | 1 + .../optimization => tmp}/minuit/MnSimplex.kt | 0 .../optimization => tmp}/minuit/MnStrategy.kt | 0 .../minuit/MnUserCovariance.kt | 0 .../optimization => tmp}/minuit/MnUserFcn.kt | 0 .../minuit/MnUserParameterState.kt | 0 .../minuit/MnUserParameters.kt | 0 .../minuit/MnUserTransformation.kt | 0 .../optimization => tmp}/minuit/MnUtils.kt | 0 .../minuit/ModularFunctionMinimizer.kt | 1 + .../minuit/NegativeG2LineSearch.kt | 0 .../minuit/Numerical2PGradientCalculator.kt | 0 .../minuit/ScanBuilder.kt | 1 + .../minuit/ScanMinimizer.kt | 0 .../minuit/SimplexBuilder.kt | 1 + .../minuit/SimplexMinimizer.kt | 0 .../minuit/SimplexParameters.kt | 0 .../minuit/SimplexSeedGenerator.kt | 1 + .../minuit/SinParameterTransformation.kt | 0 .../minuit/SqrtLowParameterTransformation.kt | 0 .../minuit/SqrtUpParameterTransformation.kt | 0 .../minuit/VariableMetricBuilder.kt | 1 + .../minuit/VariableMetricEDMEstimator.kt | 0 .../minuit/VariableMetricMinimizer.kt | 0 .../minuit/package-info.kt | 0 119 files changed, 804 insertions(+), 1349 deletions(-) rename kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/{CMOptimization.kt => CMOptimizer.kt} (63%) delete mode 100644 kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt delete mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/symmetric.kt delete mode 100644 kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt create mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization/qow => tmp}/QowFit.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/AnalyticalGradientCalculator.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/CombinedMinimizer.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/CombinedMinimumBuilder.kt (97%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/ContoursError.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/DavidonErrorUpdator.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/FunctionGradient.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/FunctionMinimum.kt (99%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/GradientCalculator.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/HessianGradientCalculator.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/InitialGradientCalculator.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MINOSResult.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MINUITFitter.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MINUITPlugin.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MINUITUtils.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MinimumBuilder.kt (95%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MinimumError.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MinimumErrorUpdator.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MinimumParameters.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MinimumSeed.kt (95%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MinimumSeedGenerator.kt (95%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MinimumState.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MinosError.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MinuitParameter.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnAlgebraicSymMatrix.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnApplication.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnContours.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnCovarianceSqueeze.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnCross.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnEigen.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnFcn.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnFunctionCross.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnGlobalCorrelationCoeff.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnHesse.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnLineSearch.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnMachinePrecision.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnMigrad.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnMinimize.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnMinos.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnParabola.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnParabolaFactory.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnParabolaPoint.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnParameterScan.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnPlot.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnPosDef.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnPrint.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnScan.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnSeedGenerator.kt (98%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnSimplex.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnStrategy.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnUserCovariance.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnUserFcn.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnUserParameterState.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnUserParameters.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnUserTransformation.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/MnUtils.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/ModularFunctionMinimizer.kt (97%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/NegativeG2LineSearch.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/Numerical2PGradientCalculator.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/ScanBuilder.kt (97%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/ScanMinimizer.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/SimplexBuilder.kt (99%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/SimplexMinimizer.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/SimplexParameters.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/SimplexSeedGenerator.kt (97%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/SinParameterTransformation.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/SqrtLowParameterTransformation.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/SqrtUpParameterTransformation.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/VariableMetricBuilder.kt (98%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/VariableMetricEDMEstimator.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/VariableMetricMinimizer.kt (100%) rename kmath-stat/src/commonMain/{kotlin/space/kscience/kmath/optimization => tmp}/minuit/package-info.kt (100%) diff --git a/.gitignore b/.gitignore index d6c4af4e3..c5903368f 100644 --- a/.gitignore +++ b/.gitignore @@ -18,3 +18,5 @@ out/ # Generated by javac -h and runtime *.class *.log + +/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt diff --git a/CHANGELOG.md b/CHANGELOG.md index 524d2a1de..e35153d81 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -14,6 +14,7 @@ - Jupyter Notebook integration module (kmath-jupyter) - `@PerformancePitfall` annotation to mark possibly slow API - BigInt operation performance improvement and fixes by @zhelenskiy (#328) +- Unified architecture for Integration and Optimization using features. ### Changed - Exponential operations merged with hyperbolic functions @@ -35,6 +36,8 @@ - Remove Any restriction on polynomials - Add `out` variance to type parameters of `StructureND` and its implementations where possible - Rename `DifferentiableMstExpression` to `KotlingradExpression` +- `FeatureSet` now accepts only `Feature`. It is possible to override keys and use interfaces. +- Use `Symbol` factory function instead of `StringSymbol` ### Deprecated diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt index 2c5a03a97..698f1a702 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt @@ -23,8 +23,8 @@ internal class DotBenchmark { const val dim = 1000 //creating invertible matrix - val matrix1 = LinearSpace.real.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } - val matrix2 = LinearSpace.real.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } + val matrix1 = LinearSpace.double.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } + val matrix2 = LinearSpace.double.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } val cmMatrix1 = CMLinearSpace { matrix1.toCM() } val cmMatrix2 = CMLinearSpace { matrix2.toCM() } @@ -63,7 +63,7 @@ internal class DotBenchmark { @Benchmark fun realDot(blackhole: Blackhole) { - LinearSpace.real { + LinearSpace.double { blackhole.consume(matrix1 dot matrix2) } } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt index 7bb32af28..ff67ccc84 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt @@ -25,7 +25,7 @@ internal class MatrixInverseBenchmark { private val random = Random(1224) private const val dim = 100 - private val space = LinearSpace.real + private val space = LinearSpace.double //creating invertible matrix private val u = space.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } @@ -35,7 +35,7 @@ internal class MatrixInverseBenchmark { @Benchmark fun kmathLupInversion(blackhole: Blackhole) { - blackhole.consume(LinearSpace.real.inverseWithLup(matrix)) + blackhole.consume(LinearSpace.double.inverseWithLup(matrix)) } @Benchmark diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt index 5da7d0f67..da1f45c1f 100644 --- a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt @@ -203,7 +203,7 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, public override fun ${type}.times(v: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> = v * this @UnstableKMathAPI - public override fun getFeature(structure: Matrix<${type}>, type: KClass): F? { + public override fun computeFeature(structure: Matrix<${type}>, type: KClass): F? { structure.getFeature(type)?.let { return it } val origin = structure.toEjml().origin diff --git a/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt b/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt index 420b23f9f..88fd312c7 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt @@ -9,7 +9,7 @@ import space.kscience.kmath.asm.compileToExpression import space.kscience.kmath.expressions.derivative import space.kscience.kmath.expressions.invoke import space.kscience.kmath.expressions.symbol -import space.kscience.kmath.kotlingrad.toDiffExpression +import space.kscience.kmath.kotlingrad.toKotlingradExpression import space.kscience.kmath.operations.DoubleField /** @@ -20,7 +20,7 @@ fun main() { val x by symbol val actualDerivative = "x^2-4*x-44".parseMath() - .toDiffExpression(DoubleField) + .toKotlingradExpression(DoubleField) .derivative(x) diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt index 5201fec38..bfba08bbd 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt @@ -17,7 +17,7 @@ import com.github.h0tk3y.betterParse.lexer.regexToken import com.github.h0tk3y.betterParse.parser.ParseResult import com.github.h0tk3y.betterParse.parser.Parser import space.kscience.kmath.expressions.MST -import space.kscience.kmath.expressions.StringSymbol +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.operations.FieldOperations import space.kscience.kmath.operations.GroupOperations import space.kscience.kmath.operations.PowerOperations @@ -43,7 +43,7 @@ public object ArithmeticsEvaluator : Grammar() { private val ws: Token by regexToken("\\s+".toRegex(), ignore = true) private val number: Parser by num use { MST.Numeric(text.toDouble()) } - private val singular: Parser by id use { StringSymbol(text) } + private val singular: Parser by id use { Symbol(text) } private val unaryFunction: Parser by (id and -lpar and parser(ArithmeticsEvaluator::subSumChain) and -rpar) .map { (id, term) -> MST.Unary(id.text, term) } diff --git a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt index 8f4daecf9..948e7eab9 100644 --- a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt +++ b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt @@ -7,7 +7,6 @@ package space.kscience.kmath.asm.internal -import space.kscience.kmath.expressions.StringSymbol import space.kscience.kmath.expressions.Symbol /** @@ -15,4 +14,4 @@ import space.kscience.kmath.expressions.Symbol * * @author Iaroslav Postovalov */ -internal fun Map.getOrFail(key: String): V = getValue(StringSymbol(key)) +internal fun Map.getOrFail(key: String): V = getValue(Symbol(key)) diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt index 361027968..a7ee9ff3f 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt @@ -103,12 +103,12 @@ public class DerivativeStructureField( public override operator fun DerivativeStructure.minus(b: Number): DerivativeStructure = subtract(b.toDouble()) public override operator fun Number.plus(b: DerivativeStructure): DerivativeStructure = b + this public override operator fun Number.minus(b: DerivativeStructure): DerivativeStructure = b - this +} - public companion object : - AutoDiffProcessor> { - public override fun process(function: DerivativeStructureField.() -> DerivativeStructure): DifferentiableExpression = - DerivativeStructureExpression(function) - } +public object DSProcessor : AutoDiffProcessor { + public override fun differentiate( + function: DerivativeStructureField.() -> DerivativeStructure, + ): DerivativeStructureExpression = DerivativeStructureExpression(function) } /** diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMGaussRuleIntegrator.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMGaussRuleIntegrator.kt index 4e174723d..e0a2f4931 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMGaussRuleIntegrator.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMGaussRuleIntegrator.kt @@ -16,7 +16,7 @@ public class CMGaussRuleIntegrator( private var type: GaussRule = GaussRule.LEGANDRE, ) : UnivariateIntegrator { - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand { val range = integrand.getFeature()?.range ?: error("Integration range is not provided") val integrator: GaussIntegrator = getIntegrator(range) @@ -76,8 +76,8 @@ public class CMGaussRuleIntegrator( numPoints: Int = 100, type: GaussRule = GaussRule.LEGANDRE, function: (Double) -> Double, - ): Double = CMGaussRuleIntegrator(numPoints, type).integrate( + ): Double = CMGaussRuleIntegrator(numPoints, type).process( UnivariateIntegrand(function, IntegrationRange(range)) - ).valueOrNull!! + ).value } } \ No newline at end of file diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt index bcddccdc4..257429fa7 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt @@ -18,7 +18,7 @@ public class CMIntegrator( public val integratorBuilder: (Integrand) -> org.apache.commons.math3.analysis.integration.UnivariateIntegrator, ) : UnivariateIntegrator { - override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { + override fun process(integrand: UnivariateIntegrand): UnivariateIntegrand { val integrator = integratorBuilder(integrand) val maxCalls = integrand.getFeature()?.maxCalls ?: defaultMaxCalls val remainingCalls = maxCalls - integrand.calls diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt index 11b097831..c6f1cd852 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt @@ -95,7 +95,7 @@ public object CMLinearSpace : LinearSpace { v * this @UnstableKMathAPI - override fun getFeature(structure: Matrix, type: KClass): F? { + override fun computeFeature(structure: Matrix, type: KClass): F? { //Return the feature if it is intrinsic to the structure structure.getFeature(type)?.let { return it } @@ -109,22 +109,22 @@ public object CMLinearSpace : LinearSpace { LupDecompositionFeature { private val lup by lazy { LUDecomposition(origin) } override val determinant: Double by lazy { lup.determinant } - override val l: Matrix by lazy { CMMatrix(lup.l) + LFeature } - override val u: Matrix by lazy { CMMatrix(lup.u) + UFeature } + override val l: Matrix by lazy> { CMMatrix(lup.l).withFeature(LFeature) } + override val u: Matrix by lazy> { CMMatrix(lup.u).withFeature(UFeature) } override val p: Matrix by lazy { CMMatrix(lup.p) } } CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { - override val l: Matrix by lazy { + override val l: Matrix by lazy> { val cholesky = CholeskyDecomposition(origin) - CMMatrix(cholesky.l) + LFeature + CMMatrix(cholesky.l).withFeature(LFeature) } } QRDecompositionFeature::class -> object : QRDecompositionFeature { private val qr by lazy { QRDecomposition(origin) } - override val q: Matrix by lazy { CMMatrix(qr.q) + OrthogonalFeature } - override val r: Matrix by lazy { CMMatrix(qr.r) + UFeature } + override val q: Matrix by lazy> { CMMatrix(qr.q).withFeature(OrthogonalFeature) } + override val r: Matrix by lazy> { CMMatrix(qr.r).withFeature(UFeature) } } SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature { diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt index ee602ca06..9085974ea 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.commons.linear import org.apache.commons.math3.linear.* +import space.kscience.kmath.linear.LinearSolver import space.kscience.kmath.linear.Matrix import space.kscience.kmath.linear.Point @@ -44,3 +45,12 @@ public fun CMLinearSpace.inverse( a: Matrix, decomposition: CMDecomposition = CMDecomposition.LUP, ): CMMatrix = solver(a, decomposition).inverse.wrap() + + +public fun CMLinearSpace.solver(decomposition: CMDecomposition): LinearSolver = object : LinearSolver { + override fun solve(a: Matrix, b: Matrix): Matrix = solve(a, b, decomposition) + + override fun solve(a: Matrix, b: Point): Point = solve(a, b, decomposition) + + override fun inverse(matrix: Matrix): Matrix = inverse(matrix, decomposition) +} \ No newline at end of file diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimizer.kt similarity index 63% rename from kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt rename to kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimizer.kt index 2faee1f5d..abf95daf6 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimizer.kt @@ -2,7 +2,7 @@ * Copyright 2018-2021 KMath contributors. * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ - +@file:OptIn(UnstableKMathAPI::class) package space.kscience.kmath.commons.optimization import org.apache.commons.math3.optim.* @@ -11,6 +11,10 @@ import org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer import org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction import org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunctionGradient import org.apache.commons.math3.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer +import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.NelderMeadSimplex +import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.SimplexOptimizer +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.expressions.SymbolIndexer import space.kscience.kmath.expressions.derivative import space.kscience.kmath.expressions.withSymbols import space.kscience.kmath.misc.UnstableKMathAPI @@ -21,29 +25,61 @@ import kotlin.reflect.KClass public operator fun PointValuePair.component1(): DoubleArray = point public operator fun PointValuePair.component2(): Double = value -public class CMOptimizer(public val optimizerBuilder: () -> MultivariateOptimizer): OptimizationFeature{ +public class CMOptimizerEngine(public val optimizerBuilder: () -> MultivariateOptimizer) : OptimizationFeature { override fun toString(): String = "CMOptimizer($optimizerBuilder)" } -public class CMOptimizerData(public val data: List) : OptimizationFeature { - public constructor(vararg data: OptimizationData) : this(data.toList()) +/** + * Specify a Commons-maths optimization engine + */ +public fun FunctionOptimizationBuilder.cmEngine(optimizerBuilder: () -> MultivariateOptimizer) { + addFeature(CMOptimizerEngine(optimizerBuilder)) +} + +public class CMOptimizerData(public val data: List OptimizationData>) : OptimizationFeature { + public constructor(vararg data: (SymbolIndexer.() -> OptimizationData)) : this(data.toList()) override fun toString(): String = "CMOptimizerData($data)" +} +/** + * Specify Commons-maths optimization data. + */ +public fun FunctionOptimizationBuilder.cmOptimizationData(data: SymbolIndexer.() -> OptimizationData) { + updateFeature { + val newData = (it?.data ?: emptyList()) + data + CMOptimizerData(newData) + } +} + +public fun FunctionOptimizationBuilder.simplexSteps(vararg steps: Pair) { + //TODO use convergence checker from features + cmEngine { SimplexOptimizer(CMOptimizer.defaultConvergenceChecker) } + cmOptimizationData { NelderMeadSimplex(mapOf(*steps).toDoubleArray()) } } @OptIn(UnstableKMathAPI::class) -public class CMOptimization : Optimizer> { +public object CMOptimizer : Optimizer> { + + public const val DEFAULT_RELATIVE_TOLERANCE: Double = 1e-4 + public const val DEFAULT_ABSOLUTE_TOLERANCE: Double = 1e-4 + public const val DEFAULT_MAX_ITER: Int = 1000 + + public val defaultConvergenceChecker: SimpleValueChecker = SimpleValueChecker( + DEFAULT_RELATIVE_TOLERANCE, + DEFAULT_ABSOLUTE_TOLERANCE, + DEFAULT_MAX_ITER + ) + override suspend fun optimize( problem: FunctionOptimization, ): FunctionOptimization { - val startPoint = problem.getFeature>()?.point - ?: error("Starting point not defined in $problem") + val startPoint = problem.startPoint val parameters = problem.getFeature()?.symbols ?: problem.getFeature>()?.point?.keys - ?:startPoint.keys + ?: startPoint.keys withSymbols(parameters) { @@ -53,7 +89,7 @@ public class CMOptimization : Optimizer> { DEFAULT_MAX_ITER ) - val cmOptimizer: MultivariateOptimizer = problem.getFeature()?.optimizerBuilder?.invoke() + val cmOptimizer: MultivariateOptimizer = problem.getFeature()?.optimizerBuilder?.invoke() ?: NonLinearConjugateGradientOptimizer( NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES, convergenceChecker @@ -68,7 +104,7 @@ public class CMOptimization : Optimizer> { addOptimizationData(MaxEval.unlimited()) addOptimizationData(InitialGuess(startPoint.toDoubleArray())) - fun exportOptimizationData(): List = optimizationData.values.toList() + //fun exportOptimizationData(): List = optimizationData.values.toList() val objectiveFunction = ObjectiveFunction { val args = startPoint + it.toMap() @@ -88,7 +124,9 @@ public class CMOptimization : Optimizer> { for (feature in problem.features) { when (feature) { - is CMOptimizerData -> feature.data.forEach { addOptimizationData(it) } + is CMOptimizerData -> feature.data.forEach { dataBuilder -> + addOptimizationData(dataBuilder()) + } is FunctionOptimizationTarget -> when (feature) { FunctionOptimizationTarget.MAXIMIZE -> addOptimizationData(GoalType.MAXIMIZE) FunctionOptimizationTarget.MINIMIZE -> addOptimizationData(GoalType.MINIMIZE) @@ -101,10 +139,4 @@ public class CMOptimization : Optimizer> { return problem.withFeatures(OptimizationResult(point.toMap()), OptimizationValue(value)) } } - - public companion object { - public const val DEFAULT_RELATIVE_TOLERANCE: Double = 1e-4 - public const val DEFAULT_ABSOLUTE_TOLERANCE: Double = 1e-4 - public const val DEFAULT_MAX_ITER: Int = 1000 - } } diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt deleted file mode 100644 index b1d7f5ca3..000000000 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt +++ /dev/null @@ -1,75 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.commons.optimization - -import org.apache.commons.math3.analysis.differentiation.DerivativeStructure -import space.kscience.kmath.commons.expressions.DerivativeStructureField -import space.kscience.kmath.expressions.DifferentiableExpression -import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.expressions.Symbol -import space.kscience.kmath.optimization.* -import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.asBuffer - -/** - * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation - */ -public fun FunctionOptimization.Companion.chiSquaredExpression( - x: Buffer, - y: Buffer, - yErr: Buffer, - model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure, -): DifferentiableExpression = chiSquaredExpression(DerivativeStructureField, x, y, yErr, model) - -/** - * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation - */ -public fun FunctionOptimization.Companion.chiSquaredExpression( - x: Iterable, - y: Iterable, - yErr: Iterable, - model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure, -): DifferentiableExpression = chiSquaredExpression( - DerivativeStructureField, - x.toList().asBuffer(), - y.toList().asBuffer(), - yErr.toList().asBuffer(), - model -) - -/** - * Optimize expression without derivatives - */ -public suspend fun Expression.optimize( - vararg symbols: Symbol, - configuration: CMOptimization.() -> Unit, -): OptimizationResult { - require(symbols.isNotEmpty()) { "Must provide a list of symbols for optimization" } - val problem = CMOptimization(symbols.toList(), configuration) - problem.noDerivFunction(this) - return problem.optimize() -} - -/** - * Optimize differentiable expression - */ -public suspend fun DifferentiableExpression.optimize( - vararg symbols: Symbol, - configuration: CMOptimization.() -> Unit, -): OptimizationResult = optimizeWith(CMOptimization, symbols = symbols, configuration) - -public suspend fun DifferentiableExpression.minimize( - vararg startPoint: Pair, - configuration: CMOptimization.() -> Unit = {}, -): OptimizationResult { - val symbols = startPoint.map { it.first }.toTypedArray() - return optimize(*symbols){ - maximize = false - initialGuess(startPoint.toMap()) - function(this@minimize) - configuration() - } -} \ No newline at end of file diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt index b47d7da24..97761cfa2 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt @@ -6,43 +6,38 @@ package space.kscience.kmath.commons.optimization import kotlinx.coroutines.runBlocking +import space.kscience.kmath.commons.expressions.DSProcessor import space.kscience.kmath.commons.expressions.DerivativeStructureExpression import space.kscience.kmath.distributions.NormalDistribution +import space.kscience.kmath.expressions.Symbol.Companion.x +import space.kscience.kmath.expressions.Symbol.Companion.y import space.kscience.kmath.expressions.symbol -import space.kscience.kmath.optimization.FunctionOptimization +import space.kscience.kmath.optimization.* import space.kscience.kmath.stat.RandomGenerator import kotlin.math.pow import kotlin.test.Test internal class OptimizeTest { - val x by symbol - val y by symbol - val normal = DerivativeStructureExpression { - exp(-bindSymbol(x).pow(2) / 2) + exp(-bindSymbol(y) - .pow(2) / 2) + exp(-bindSymbol(x).pow(2) / 2) + exp(-bindSymbol(y).pow(2) / 2) } @Test - fun testGradientOptimization() = runBlocking{ - val result = normal.optimize(x, y) { - initialGuess(x to 1.0, y to 1.0) - //no need to select optimizer. Gradient optimizer is used by default because gradients are provided by function - } - println(result.point) - println(result.value) + fun testGradientOptimization() = runBlocking { + val result = normal.optimizeWith(CMOptimizer, x to 1.0, y to 1.0) + println(result.resultPoint) + println(result.resultValue) } @Test - fun testSimplexOptimization() = runBlocking{ - val result = normal.optimize(x, y) { - initialGuess(x to 1.0, y to 1.0) + fun testSimplexOptimization() = runBlocking { + val result = normal.optimizeWith(CMOptimizer, x to 1.0, y to 1.0) { simplexSteps(x to 2.0, y to 0.5) //this sets simplex optimizer } - println(result.point) - println(result.value) + println(result.resultPoint) + println(result.resultValue) } @Test @@ -62,6 +57,11 @@ internal class OptimizeTest { val yErr = List(x.size) { sigma } + val model = DSProcessor.differentiate { x1 -> + val cWithDefault = bindSymbolOrNull(c) ?: one + bindSymbol(a) * x1.pow(2) + bindSymbol(b) * x1 + cWithDefault + } + val chi2 = FunctionOptimization.chiSquared(x, y, yErr) { x1 -> val cWithDefault = bindSymbolOrNull(c) ?: one bindSymbol(a) * x1.pow(2) + bindSymbol(b) * x1 + cWithDefault diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt index 88c14d311..e06b774fd 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/ColumnarData.kt @@ -25,6 +25,9 @@ public interface ColumnarData { public operator fun get(symbol: Symbol): Buffer? } +@UnstableKMathAPI +public val ColumnarData<*>.indices: IntRange get() = 0 until size + /** * A zero-copy method to represent a [Structure2D] as a two-column x-y data. * There could more than two columns in the structure. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt index 011dc26e2..1782ff406 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt @@ -5,6 +5,8 @@ package space.kscience.kmath.expressions +import space.kscience.kmath.operations.Algebra + /** * Represents expression which structure can be differentiated. * @@ -63,7 +65,10 @@ public abstract class FirstDerivativeExpression : DifferentiableExpression /** * A factory that converts an expression in autodiff variables to a [DifferentiableExpression] + * @param T type of the constants for the expression + * @param I type of the actual expression state + * @param A type of expression algebra */ -public fun interface AutoDiffProcessor, out R : Expression> { - public fun process(function: A.() -> I): DifferentiableExpression +public fun interface AutoDiffProcessor> { + public fun differentiate(function: A.() -> I): DifferentiableExpression } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSolver.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSolver.kt index 9c3ffd819..288fabbaf 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSolver.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSolver.kt @@ -5,8 +5,6 @@ package space.kscience.kmath.linear -import space.kscience.kmath.nd.as1D - /** * A group of methods to solve for *X* in equation *X = A -1 · B*, where *A* and *B* are matrices or * vectors. @@ -30,20 +28,3 @@ public interface LinearSolver { public fun inverse(matrix: Matrix): Matrix } -/** - * Convert matrix to vector if it is possible. - */ -public fun Matrix.asVector(): Point = - if (this.colNum == 1) - as1D() - else - error("Can't convert matrix with more than one column to vector") - -/** - * Creates an n × 1 [VirtualMatrix], where n is the size of the given buffer. - * - * @param T the type of elements contained in the buffer. - * @receiver a buffer. - * @return the new matrix. - */ -public fun Point.asMatrix(): VirtualMatrix = VirtualMatrix(size, 1) { i, _ -> get(i) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt index ec073ac48..94083f70d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt @@ -164,7 +164,7 @@ public interface LinearSpace> { public operator fun T.times(v: Point): Point = v * this /** - * Get a feature of the structure in this scope. Structure features take precedence other context features + * Compute a feature of the structure in this scope. Structure features take precedence other context features * * @param F the type of feature. * @param structure the structure. @@ -172,7 +172,7 @@ public interface LinearSpace> { * @return a feature object or `null` if it isn't present. */ @UnstableKMathAPI - public fun getFeature(structure: Matrix, type: KClass): F? = structure.getFeature(type) + public fun computeFeature(structure: Matrix, type: KClass): F? = structure.getFeature(type) public companion object { @@ -184,7 +184,7 @@ public interface LinearSpace> { bufferFactory: BufferFactory = Buffer.Companion::boxing, ): LinearSpace = BufferedLinearSpace(algebra, bufferFactory) - public val real: LinearSpace = buffered(DoubleField, ::DoubleBuffer) + public val double: LinearSpace = buffered(DoubleField, ::DoubleBuffer) /** * Automatic buffered matrix, unboxed if it is possible @@ -202,9 +202,27 @@ public interface LinearSpace> { * @return a feature object or `null` if it isn't present. */ @UnstableKMathAPI -public inline fun LinearSpace.getFeature(structure: Matrix): F? = - getFeature(structure, F::class) +public inline fun LinearSpace.computeFeature(structure: Matrix): F? = + computeFeature(structure, F::class) -public operator fun , R> LS.invoke(block: LS.() -> R): R = run(block) +public inline operator fun , R> LS.invoke(block: LS.() -> R): R = run(block) + +/** + * Convert matrix to vector if it is possible. + */ +public fun Matrix.asVector(): Point = + if (this.colNum == 1) + as1D() + else + error("Can't convert matrix with more than one column to vector") + +/** + * Creates an n × 1 [VirtualMatrix], where n is the size of the given buffer. + * + * @param T the type of elements contained in the buffer. + * @receiver a buffer. + * @return the new matrix. + */ +public fun Point.asMatrix(): VirtualMatrix = VirtualMatrix(size, 1) { i, _ -> get(i) } \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt index f3653d394..3b6208468 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.linear +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.getFeature import space.kscience.kmath.operations.* @@ -34,7 +35,7 @@ public class LupDecomposition( j == i -> elementContext.one else -> elementContext.zero } - } + LFeature + }.withFeature(LFeature) /** @@ -44,7 +45,7 @@ public class LupDecomposition( */ override val u: Matrix = VirtualMatrix(lu.shape[0], lu.shape[1]) { i, j -> if (j >= i) lu[i, j] else elementContext.zero - } + UFeature + }.withFeature(UFeature) /** * Returns the P rows permutation matrix. @@ -82,7 +83,7 @@ public fun > LinearSpace>.lup( val m = matrix.colNum val pivot = IntArray(matrix.rowNum) - //TODO just waits for KEEP-176 + //TODO just waits for multi-receivers BufferAccessor2D(matrix.rowNum, matrix.colNum, factory).run { elementAlgebra { val lu = create(matrix) @@ -156,10 +157,13 @@ public inline fun > LinearSpace>.lup( noinline checkSingular: (T) -> Boolean, ): LupDecomposition = lup(MutableBuffer.Companion::auto, matrix, checkSingular) -public fun LinearSpace.lup(matrix: Matrix): LupDecomposition = - lup(::DoubleBuffer, matrix) { it < 1e-11 } +public fun LinearSpace.lup( + matrix: Matrix, + singularityThreshold: Double = 1e-11, +): LupDecomposition = + lup(::DoubleBuffer, matrix) { it < singularityThreshold } -public fun LupDecomposition.solveWithLup( +internal fun LupDecomposition.solve( factory: MutableBufferFactory, matrix: Matrix, ): Matrix { @@ -207,41 +211,24 @@ public fun LupDecomposition.solveWithLup( } } -public inline fun LupDecomposition.solveWithLup(matrix: Matrix): Matrix = - solveWithLup(MutableBuffer.Companion::auto, matrix) - /** - * Solves a system of linear equations *ax = b** using LUP decomposition. + * Produce a generic solver based on LUP decomposition */ +@PerformancePitfall() @OptIn(UnstableKMathAPI::class) -public inline fun > LinearSpace>.solveWithLup( - a: Matrix, - b: Matrix, - noinline bufferFactory: MutableBufferFactory = MutableBuffer.Companion::auto, - noinline checkSingular: (T) -> Boolean, -): Matrix { - // Use existing decomposition if it is provided by matrix - val decomposition = a.getFeature() ?: lup(bufferFactory, a, checkSingular) - return decomposition.solveWithLup(bufferFactory, b) +public fun , F : Field> LinearSpace.lupSolver( + bufferFactory: MutableBufferFactory, + singularityCheck: (T) -> Boolean, +): LinearSolver = object : LinearSolver { + override fun solve(a: Matrix, b: Matrix): Matrix { + // Use existing decomposition if it is provided by matrix + val decomposition = a.getFeature() ?: lup(bufferFactory, a, singularityCheck) + return decomposition.solve(bufferFactory, b) + } + + override fun inverse(matrix: Matrix): Matrix = solve(matrix, one(matrix.rowNum, matrix.colNum)) } -public inline fun > LinearSpace>.inverseWithLup( - matrix: Matrix, - noinline bufferFactory: MutableBufferFactory = MutableBuffer.Companion::auto, - noinline checkSingular: (T) -> Boolean, -): Matrix = solveWithLup(matrix, one(matrix.rowNum, matrix.colNum), bufferFactory, checkSingular) - - -@OptIn(UnstableKMathAPI::class) -public fun LinearSpace.solveWithLup(a: Matrix, b: Matrix): Matrix { - // Use existing decomposition if it is provided by matrix - val bufferFactory: MutableBufferFactory = ::DoubleBuffer - val decomposition: LupDecomposition = a.getFeature() ?: lup(bufferFactory, a) { it < 1e-11 } - return decomposition.solveWithLup(bufferFactory, b) -} - -/** - * Inverses a square matrix using LUP decomposition. Non square matrix will throw a error. - */ -public fun LinearSpace.inverseWithLup(matrix: Matrix): Matrix = - solveWithLup(matrix, one(matrix.rowNum, matrix.colNum)) \ No newline at end of file +@PerformancePitfall +public fun LinearSpace.lupSolver(singularityThreshold: Double = 1e-11): LinearSolver = + lupSolver(::DoubleBuffer) { it < singularityThreshold } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixBuilder.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixBuilder.kt index 72d22233a..029612bc5 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixBuilder.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixBuilder.kt @@ -7,6 +7,8 @@ package space.kscience.kmath.linear import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.Ring +import space.kscience.kmath.structures.BufferAccessor2D +import space.kscience.kmath.structures.MutableBuffer public class MatrixBuilder>( public val linearSpace: LinearSpace, @@ -45,4 +47,31 @@ public inline fun LinearSpace>.column( crossinline builder: (Int) -> T, ): Matrix = buildMatrix(size, 1) { i, _ -> builder(i) } -public fun LinearSpace>.column(vararg values: T): Matrix = column(values.size, values::get) \ No newline at end of file +public fun LinearSpace>.column(vararg values: T): Matrix = column(values.size, values::get) + +public object SymmetricMatrixFeature : MatrixFeature + +/** + * Naive implementation of a symmetric matrix builder, that adds a [SymmetricMatrixFeature] tag. The resulting matrix contains + * full `size^2` number of elements, but caches elements during calls to save [builder] calls. [builder] is always called in the + * upper triangle region meaning that `i <= j` + */ +public fun > MatrixBuilder.symmetric( + builder: (i: Int, j: Int) -> T, +): Matrix { + require(columns == rows) { "In order to build symmetric matrix, number of rows $rows should be equal to number of columns $columns" } + return with(BufferAccessor2D(rows, rows, MutableBuffer.Companion::boxing)) { + val cache = factory(rows * rows) { null } + linearSpace.buildMatrix(rows, rows) { i, j -> + val cached = cache[i, j] + if (cached == null) { + val value = if (i <= j) builder(i, j) else builder(j, i) + cache[i, j] = value + cache[j, i] = value + value + } else { + cached + } + }.withFeature(SymmetricMatrixFeature) + } +} \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt index 16aadab3b..df62c6fc0 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.linear +import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureFeature import space.kscience.kmath.nd.getFeature @@ -18,7 +19,7 @@ import kotlin.reflect.KClass */ public class MatrixWrapper internal constructor( public val origin: Matrix, - public val features: Set, + public val features: FeatureSet, ) : Matrix by origin { /** @@ -27,8 +28,7 @@ public class MatrixWrapper internal constructor( @UnstableKMathAPI @Suppress("UNCHECKED_CAST") public override fun getFeature(type: KClass): F? = - features.singleOrNull(type::isInstance) as? F - ?: origin.getFeature(type) + features.getFeature(type) ?: origin.getFeature(type) public override fun toString(): String = "MatrixWrapper(matrix=$origin, features=$features)" } @@ -44,20 +44,23 @@ public val Matrix.origin: Matrix /** * Add a single feature to a [Matrix] */ -public operator fun Matrix.plus(newFeature: MatrixFeature): MatrixWrapper = if (this is MatrixWrapper) { - MatrixWrapper(origin, features + newFeature) +public fun Matrix.withFeature(newFeature: MatrixFeature): MatrixWrapper = if (this is MatrixWrapper) { + MatrixWrapper(origin, features.with(newFeature)) } else { - MatrixWrapper(this, setOf(newFeature)) + MatrixWrapper(this, FeatureSet.of(newFeature)) } +@Deprecated("To be replaced by withFeature") +public operator fun Matrix.plus(newFeature: MatrixFeature): MatrixWrapper = withFeature(newFeature) + /** * Add a collection of features to a [Matrix] */ -public operator fun Matrix.plus(newFeatures: Collection): MatrixWrapper = +public fun Matrix.withFeatures(newFeatures: Iterable): MatrixWrapper = if (this is MatrixWrapper) { - MatrixWrapper(origin, features + newFeatures) + MatrixWrapper(origin, features.with(newFeatures)) } else { - MatrixWrapper(this, newFeatures.toSet()) + MatrixWrapper(this, FeatureSet.of(newFeatures)) } /** @@ -68,7 +71,7 @@ public fun LinearSpace>.one( columns: Int, ): Matrix = VirtualMatrix(rows, columns) { i, j -> if (i == j) elementAlgebra.one else elementAlgebra.zero -} + UnitFeature +}.withFeature(UnitFeature) /** @@ -79,7 +82,7 @@ public fun LinearSpace>.zero( columns: Int, ): Matrix = VirtualMatrix(rows, columns) { _, _ -> elementAlgebra.zero -} + ZeroFeature +}.withFeature(ZeroFeature) public class TransposedFeature(public val original: Matrix) : MatrixFeature @@ -90,4 +93,4 @@ public class TransposedFeature(public val original: Matrix) : Ma public fun Matrix.transpose(): Matrix = getFeature>()?.original ?: VirtualMatrix( colNum, rowNum, -) { i, j -> get(j, i) } + TransposedFeature(this) \ No newline at end of file +) { i, j -> get(j, i) }.withFeature(TransposedFeature(this)) \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt index 3751bd33b..fb2b1e547 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt @@ -20,3 +20,6 @@ public class VirtualMatrix( override operator fun get(i: Int, j: Int): T = generator(i, j) } + +public fun MatrixBuilder.virtual(generator: (i: Int, j: Int) -> T): VirtualMatrix = + VirtualMatrix(rows, columns, generator) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/symmetric.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/symmetric.kt deleted file mode 100644 index 04d9a9897..000000000 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/symmetric.kt +++ /dev/null @@ -1,34 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.linear - -import space.kscience.kmath.structures.BufferAccessor2D -import space.kscience.kmath.structures.MutableBuffer - -public object SymmetricMatrixFeature : MatrixFeature - -/** - * Naive implementation of a symmetric matrix builder, that adds a [SymmetricMatrixFeature] tag. The resulting matrix contains - * full `size^2` number of elements, but caches elements during calls to save [builder] calls. [builder] is always called in the - * upper triangle region meaning that `i <= j` - */ -public fun > LS.buildSymmetricMatrix( - size: Int, - builder: (i: Int, j: Int) -> T, -): Matrix = BufferAccessor2D(size, size, MutableBuffer.Companion::boxing).run { - val cache = factory(size * size) { null } - buildMatrix(size, size) { i, j -> - val cached = cache[i, j] - if (cached == null) { - val value = if (i <= j) builder(i, j) else builder(j, i) - cache[i, j] = value - cache[j, i] = value - value - } else { - cached - } - } + SymmetricMatrixFeature -} \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt index a94efc788..648b6376f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt @@ -11,29 +11,44 @@ import kotlin.reflect.KClass * A entity that contains a set of features defined by their types */ public interface Featured { - public fun getFeature(type: KClass): T? + public fun getFeature(type: FeatureKey): T? +} + +public typealias FeatureKey = KClass + +public interface Feature> { + + /** + * A key used for extraction + */ + @Suppress("UNCHECKED_CAST") + public val key: FeatureKey get() = this::class as FeatureKey } /** * A container for a set of features */ -public class FeatureSet private constructor(public val features: Map, F>) : Featured { +public class FeatureSet> private constructor(public val features: Map, F>) : Featured { @Suppress("UNCHECKED_CAST") - override fun getFeature(type: KClass): T? = features[type] as? T + override fun getFeature(type: FeatureKey): T? = features[type] as? T public inline fun getFeature(): T? = getFeature(T::class) - public fun with(feature: T, type: KClass = feature::class): FeatureSet = + public fun with(feature: T, type: FeatureKey = feature.key): FeatureSet = FeatureSet(features + (type to feature)) public fun with(other: FeatureSet): FeatureSet = FeatureSet(features + other.features) public fun with(vararg otherFeatures: F): FeatureSet = - FeatureSet(features + otherFeatures.associateBy { it::class }) + FeatureSet(features + otherFeatures.associateBy { it.key }) + + public fun with(otherFeatures: Iterable): FeatureSet = + FeatureSet(features + otherFeatures.associateBy { it.key }) public operator fun iterator(): Iterator = features.values.iterator() public companion object { - public fun of(vararg features: F): FeatureSet = FeatureSet(features.associateBy { it::class }) + public fun > of(vararg features: F): FeatureSet = FeatureSet(features.associateBy { it.key }) + public fun > of(features: Iterable): FeatureSet = FeatureSet(features.associateBy { it.key }) } } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt index e521e6237..39b2779eb 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt @@ -12,7 +12,7 @@ package space.kscience.kmath.misc * in some way that may break some code. */ @MustBeDocumented -@Retention(value = AnnotationRetention.BINARY) +@Retention(value = AnnotationRetention.SOURCE) @RequiresOptIn("This API is unstable and could change in future", RequiresOptIn.Level.WARNING) public annotation class UnstableKMathAPI @@ -21,7 +21,7 @@ public annotation class UnstableKMathAPI * slow-down in some cases. Refer to the documentation and benchmark it to be sure. */ @MustBeDocumented -@Retention(value = AnnotationRetention.BINARY) +@Retention(value = AnnotationRetention.SOURCE) @RequiresOptIn( "Refer to the documentation to use this API in performance-critical code", RequiresOptIn.Level.WARNING diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt index 7fc91e321..4962dcb7d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt @@ -5,6 +5,8 @@ package space.kscience.kmath.nd +import space.kscience.kmath.misc.Feature +import space.kscience.kmath.misc.Featured import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.structures.Buffer @@ -13,7 +15,7 @@ import kotlin.jvm.JvmName import kotlin.native.concurrent.ThreadLocal import kotlin.reflect.KClass -public interface StructureFeature +public interface StructureFeature : Feature /** * Represents n-dimensional structure, i.e. multidimensional container of items of the same type and size. The number @@ -24,7 +26,7 @@ public interface StructureFeature * * @param T the type of items. */ -public interface StructureND { +public interface StructureND : Featured { /** * The shape of structure, i.e. non-empty sequence of non-negative integers that specify sizes of dimensions of * this structure. @@ -57,7 +59,7 @@ public interface StructureND { * If the feature is not present, null is returned. */ @UnstableKMathAPI - public fun getFeature(type: KClass): F? = null + override fun getFeature(type: KClass): F? = null public companion object { /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt index d29c54d46..a96253939 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt @@ -14,30 +14,30 @@ import space.kscience.kmath.nd.as2D * A context that allows to operate on a [MutableBuffer] as on 2d array */ internal class BufferAccessor2D( - public val rowNum: Int, - public val colNum: Int, + val rowNum: Int, + val colNum: Int, val factory: MutableBufferFactory, ) { - public operator fun Buffer.get(i: Int, j: Int): T = get(i * colNum + j) + operator fun Buffer.get(i: Int, j: Int): T = get(i * colNum + j) - public operator fun MutableBuffer.set(i: Int, j: Int, value: T) { + operator fun MutableBuffer.set(i: Int, j: Int, value: T) { set(i * colNum + j, value) } - public inline fun create(crossinline init: (i: Int, j: Int) -> T): MutableBuffer = + inline fun create(crossinline init: (i: Int, j: Int) -> T): MutableBuffer = factory(rowNum * colNum) { offset -> init(offset / colNum, offset % colNum) } - public fun create(mat: Structure2D): MutableBuffer = create { i, j -> mat[i, j] } + fun create(mat: Structure2D): MutableBuffer = create { i, j -> mat[i, j] } //TODO optimize wrapper - public fun MutableBuffer.collect(): Structure2D = StructureND.buffered( + fun MutableBuffer.collect(): Structure2D = StructureND.buffered( DefaultStrides(intArrayOf(rowNum, colNum)), factory ) { (i, j) -> get(i, j) }.as2D() - public inner class Row(public val buffer: MutableBuffer, public val rowIndex: Int) : MutableBuffer { + inner class Row(val buffer: MutableBuffer, val rowIndex: Int) : MutableBuffer { override val size: Int get() = colNum override operator fun get(index: Int): T = buffer[rowIndex, index] @@ -54,5 +54,5 @@ internal class BufferAccessor2D( /** * Get row */ - public fun MutableBuffer.row(i: Int): Row = Row(this, i) + fun MutableBuffer.row(i: Int): Row = Row(this, i) } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt index 2d2a0952b..3be473e54 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt @@ -22,14 +22,14 @@ class DoubleLUSolverTest { @Test fun testInvertOne() { - val matrix = LinearSpace.real.one(2, 2) - val inverted = LinearSpace.real.inverseWithLup(matrix) + val matrix = LinearSpace.double.one(2, 2) + val inverted = LinearSpace.double.lupSolver().inverse(matrix) assertMatrixEquals(matrix, inverted) } @Test fun testDecomposition() { - LinearSpace.real.run { + LinearSpace.double.run { val matrix = matrix(2, 2)( 3.0, 1.0, 2.0, 3.0 @@ -46,14 +46,14 @@ class DoubleLUSolverTest { @Test fun testInvert() { - val matrix = LinearSpace.real.matrix(2, 2)( + val matrix = LinearSpace.double.matrix(2, 2)( 3.0, 1.0, 1.0, 3.0 ) - val inverted = LinearSpace.real.inverseWithLup(matrix) + val inverted = LinearSpace.double.lupSolver().inverse(matrix) - val expected = LinearSpace.real.matrix(2, 2)( + val expected = LinearSpace.double.matrix(2, 2)( 0.375, -0.125, -0.125, 0.375 ) diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt index 170f9caf4..feae07c1e 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt @@ -19,14 +19,14 @@ import kotlin.test.assertTrue class MatrixTest { @Test fun testTranspose() { - val matrix = LinearSpace.real.one(3, 3) + val matrix = LinearSpace.double.one(3, 3) val transposed = matrix.transpose() assertTrue { StructureND.contentEquals(matrix, transposed) } } @Test fun testBuilder() { - val matrix = LinearSpace.real.matrix(2, 3)( + val matrix = LinearSpace.double.matrix(2, 3)( 1.0, 0.0, 0.0, 0.0, 1.0, 2.0 ) @@ -48,7 +48,7 @@ class MatrixTest { infix fun Matrix.pow(power: Int): Matrix { var res = this repeat(power - 1) { - res = LinearSpace.real.run { res dot this@pow } + res = LinearSpace.double.run { res dot this@pow } } return res } @@ -61,7 +61,7 @@ class MatrixTest { val firstMatrix = StructureND.auto(2, 3) { (i, j) -> (i + j).toDouble() }.as2D() val secondMatrix = StructureND.auto(3, 2) { (i, j) -> (i + j).toDouble() }.as2D() - LinearSpace.real.run { + LinearSpace.double.run { // val firstMatrix = produce(2, 3) { i, j -> (i + j).toDouble() } // val secondMatrix = produce(3, 2) { i, j -> (i + j).toDouble() } val result = firstMatrix dot secondMatrix diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt index fb51553f7..8a03115b5 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt @@ -40,7 +40,7 @@ class NumberNDFieldTest { @Test fun testGeneration() { - val array = LinearSpace.real.buildMatrix(3, 3) { i, j -> + val array = LinearSpace.double.buildMatrix(3, 3) { i, j -> (i * 10 + j).toDouble() } diff --git a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt index 2ebcc454d..91ab6a5d6 100644 --- a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt +++ b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt @@ -151,7 +151,7 @@ public value class DMatrixContext>(public val context: context.run { (this@transpose as Matrix).transpose() }.coerce() public companion object { - public val real: DMatrixContext = DMatrixContext(LinearSpace.real) + public val real: DMatrixContext = DMatrixContext(LinearSpace.double) } } diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt deleted file mode 100644 index 139c55697..000000000 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt +++ /dev/null @@ -1,995 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -/* This file is generated with buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt */ - -package space.kscience.kmath.ejml - -import org.ejml.data.* -import org.ejml.dense.row.CommonOps_DDRM -import org.ejml.dense.row.CommonOps_FDRM -import org.ejml.dense.row.factory.DecompositionFactory_DDRM -import org.ejml.dense.row.factory.DecompositionFactory_FDRM -import org.ejml.sparse.FillReducing -import org.ejml.sparse.csc.CommonOps_DSCC -import org.ejml.sparse.csc.CommonOps_FSCC -import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC -import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC -import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC -import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC -import space.kscience.kmath.linear.* -import space.kscience.kmath.linear.Matrix -import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.nd.StructureFeature -import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.operations.FloatField -import space.kscience.kmath.operations.invoke -import space.kscience.kmath.structures.DoubleBuffer -import space.kscience.kmath.structures.FloatBuffer -import kotlin.reflect.KClass -import kotlin.reflect.cast - -/** - * [EjmlVector] specialization for [Double]. - */ -public class EjmlDoubleVector(public override val origin: M) : EjmlVector(origin) { - init { - require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } - } - - public override operator fun get(index: Int): Double = origin[0, index] -} - -/** - * [EjmlVector] specialization for [Float]. - */ -public class EjmlFloatVector(public override val origin: M) : EjmlVector(origin) { - init { - require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } - } - - public override operator fun get(index: Int): Float = origin[0, index] -} - -/** - * [EjmlMatrix] specialization for [Double]. - */ -public class EjmlDoubleMatrix(public override val origin: M) : EjmlMatrix(origin) { - public override operator fun get(i: Int, j: Int): Double = origin[i, j] -} - -/** - * [EjmlMatrix] specialization for [Float]. - */ -public class EjmlFloatMatrix(public override val origin: M) : EjmlMatrix(origin) { - public override operator fun get(i: Int, j: Int): Float = origin[i, j] -} - -/** - * [EjmlLinearSpace] implementation based on [CommonOps_DDRM], [DecompositionFactory_DDRM] operations and - * [DMatrixRMaj] matrices. - */ -public object EjmlLinearSpaceDDRM : EjmlLinearSpace() { - /** - * The [DoubleField] reference. - */ - public override val elementAlgebra: DoubleField get() = DoubleField - - @Suppress("UNCHECKED_CAST") - public override fun Matrix.toEjml(): EjmlDoubleMatrix = when { - this is EjmlDoubleMatrix<*> && origin is DMatrixRMaj -> this as EjmlDoubleMatrix - else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } - } - - @Suppress("UNCHECKED_CAST") - public override fun Point.toEjml(): EjmlDoubleVector = when { - this is EjmlDoubleVector<*> && origin is DMatrixRMaj -> this as EjmlDoubleVector - else -> EjmlDoubleVector(DMatrixRMaj(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } - }) - } - - public override fun buildMatrix( - rows: Int, - columns: Int, - initializer: DoubleField.(i: Int, j: Int) -> Double, - ): EjmlDoubleMatrix = DMatrixRMaj(rows, columns).also { - (0 until rows).forEach { row -> - (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } - } - }.wrapMatrix() - - public override fun buildVector( - size: Int, - initializer: DoubleField.(Int) -> Double, - ): EjmlDoubleVector = EjmlDoubleVector(DMatrixRMaj(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } - }) - - private fun T.wrapMatrix() = EjmlDoubleMatrix(this) - private fun T.wrapVector() = EjmlDoubleVector(this) - - public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } - - public override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { - val out = DMatrixRMaj(1, 1) - CommonOps_DDRM.mult(toEjml().origin, other.toEjml().origin, out) - return out.wrapMatrix() - } - - public override fun Matrix.dot(vector: Point): EjmlDoubleVector { - val out = DMatrixRMaj(1, 1) - CommonOps_DDRM.mult(toEjml().origin, vector.toEjml().origin, out) - return out.wrapVector() - } - - public override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { - val out = DMatrixRMaj(1, 1) - - CommonOps_DDRM.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra { -one }, - other.toEjml().origin, - out, - ) - - return out.wrapMatrix() - } - - public override operator fun Matrix.times(value: Double): EjmlDoubleMatrix { - val res = DMatrixRMaj(1, 1) - CommonOps_DDRM.scale(value, toEjml().origin, res) - return res.wrapMatrix() - } - - public override fun Point.unaryMinus(): EjmlDoubleVector { - val res = DMatrixRMaj(1, 1) - CommonOps_DDRM.changeSign(toEjml().origin, res) - return res.wrapVector() - } - - public override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { - val out = DMatrixRMaj(1, 1) - - CommonOps_DDRM.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra.one, - other.toEjml().origin, - out, - ) - - return out.wrapMatrix() - } - - public override fun Point.plus(other: Point): EjmlDoubleVector { - val out = DMatrixRMaj(1, 1) - - CommonOps_DDRM.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra.one, - other.toEjml().origin, - out, - ) - - return out.wrapVector() - } - - public override fun Point.minus(other: Point): EjmlDoubleVector { - val out = DMatrixRMaj(1, 1) - - CommonOps_DDRM.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra { -one }, - other.toEjml().origin, - out, - ) - - return out.wrapVector() - } - - public override fun Double.times(m: Matrix): EjmlDoubleMatrix = m * this - - public override fun Point.times(value: Double): EjmlDoubleVector { - val res = DMatrixRMaj(1, 1) - CommonOps_DDRM.scale(value, toEjml().origin, res) - return res.wrapVector() - } - - public override fun Double.times(v: Point): EjmlDoubleVector = v * this - - @UnstableKMathAPI - public override fun getFeature(structure: Matrix, type: KClass): F? { - structure.getFeature(type)?.let { return it } - val origin = structure.toEjml().origin - - return when (type) { - InverseMatrixFeature::class -> object : InverseMatrixFeature { - override val inverse: Matrix by lazy { - val res = origin.copy() - CommonOps_DDRM.invert(res) - res.wrapMatrix() - } - } - - DeterminantFeature::class -> object : DeterminantFeature { - override val determinant: Double by lazy { CommonOps_DDRM.det(origin) } - } - - SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature { - private val svd by lazy { - DecompositionFactory_DDRM.svd(origin.numRows, origin.numCols, true, true, false) - .apply { decompose(origin.copy()) } - } - - override val u: Matrix by lazy { svd.getU(null, false).wrapMatrix() } - override val s: Matrix by lazy { svd.getW(null).wrapMatrix() } - override val v: Matrix by lazy { svd.getV(null, false).wrapMatrix() } - override val singularValues: Point by lazy { DoubleBuffer(svd.singularValues) } - } - - QRDecompositionFeature::class -> object : QRDecompositionFeature { - private val qr by lazy { - DecompositionFactory_DDRM.qr().apply { decompose(origin.copy()) } - } - - override val q: Matrix by lazy { - qr.getQ(null, false).wrapMatrix() + OrthogonalFeature - } - - override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix() + UFeature } - } - - CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { - override val l: Matrix by lazy { - val cholesky = - DecompositionFactory_DDRM.chol(structure.rowNum, true).apply { decompose(origin.copy()) } - - cholesky.getT(null).wrapMatrix() + LFeature - } - } - - LupDecompositionFeature::class -> object : LupDecompositionFeature { - private val lup by lazy { - DecompositionFactory_DDRM.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) } - } - - override val l: Matrix by lazy { - lup.getLower(null).wrapMatrix() + LFeature - } - - override val u: Matrix by lazy { - lup.getUpper(null).wrapMatrix() + UFeature - } - - override val p: Matrix by lazy { lup.getRowPivot(null).wrapMatrix() } - } - - else -> null - }?.let(type::cast) - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p matrix. - * @return the solution for *x* that is n by p. - */ - public fun solve(a: Matrix, b: Matrix): EjmlDoubleMatrix { - val res = DMatrixRMaj(1, 1) - CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res) - return res.wrapMatrix() - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p vector. - * @return the solution for *x* that is n by p. - */ - public fun solve(a: Matrix, b: Point): EjmlDoubleVector { - val res = DMatrixRMaj(1, 1) - CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res) - return EjmlDoubleVector(res) - } -} - -/** - * [EjmlLinearSpace] implementation based on [CommonOps_FDRM], [DecompositionFactory_FDRM] operations and - * [FMatrixRMaj] matrices. - */ -public object EjmlLinearSpaceFDRM : EjmlLinearSpace() { - /** - * The [FloatField] reference. - */ - public override val elementAlgebra: FloatField get() = FloatField - - @Suppress("UNCHECKED_CAST") - public override fun Matrix.toEjml(): EjmlFloatMatrix = when { - this is EjmlFloatMatrix<*> && origin is FMatrixRMaj -> this as EjmlFloatMatrix - else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } - } - - @Suppress("UNCHECKED_CAST") - public override fun Point.toEjml(): EjmlFloatVector = when { - this is EjmlFloatVector<*> && origin is FMatrixRMaj -> this as EjmlFloatVector - else -> EjmlFloatVector(FMatrixRMaj(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } - }) - } - - public override fun buildMatrix( - rows: Int, - columns: Int, - initializer: FloatField.(i: Int, j: Int) -> Float, - ): EjmlFloatMatrix = FMatrixRMaj(rows, columns).also { - (0 until rows).forEach { row -> - (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } - } - }.wrapMatrix() - - public override fun buildVector( - size: Int, - initializer: FloatField.(Int) -> Float, - ): EjmlFloatVector = EjmlFloatVector(FMatrixRMaj(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } - }) - - private fun T.wrapMatrix() = EjmlFloatMatrix(this) - private fun T.wrapVector() = EjmlFloatVector(this) - - public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } - - public override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { - val out = FMatrixRMaj(1, 1) - CommonOps_FDRM.mult(toEjml().origin, other.toEjml().origin, out) - return out.wrapMatrix() - } - - public override fun Matrix.dot(vector: Point): EjmlFloatVector { - val out = FMatrixRMaj(1, 1) - CommonOps_FDRM.mult(toEjml().origin, vector.toEjml().origin, out) - return out.wrapVector() - } - - public override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { - val out = FMatrixRMaj(1, 1) - - CommonOps_FDRM.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra { -one }, - other.toEjml().origin, - out, - ) - - return out.wrapMatrix() - } - - public override operator fun Matrix.times(value: Float): EjmlFloatMatrix { - val res = FMatrixRMaj(1, 1) - CommonOps_FDRM.scale(value, toEjml().origin, res) - return res.wrapMatrix() - } - - public override fun Point.unaryMinus(): EjmlFloatVector { - val res = FMatrixRMaj(1, 1) - CommonOps_FDRM.changeSign(toEjml().origin, res) - return res.wrapVector() - } - - public override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { - val out = FMatrixRMaj(1, 1) - - CommonOps_FDRM.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra.one, - other.toEjml().origin, - out, - ) - - return out.wrapMatrix() - } - - public override fun Point.plus(other: Point): EjmlFloatVector { - val out = FMatrixRMaj(1, 1) - - CommonOps_FDRM.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra.one, - other.toEjml().origin, - out, - ) - - return out.wrapVector() - } - - public override fun Point.minus(other: Point): EjmlFloatVector { - val out = FMatrixRMaj(1, 1) - - CommonOps_FDRM.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra { -one }, - other.toEjml().origin, - out, - ) - - return out.wrapVector() - } - - public override fun Float.times(m: Matrix): EjmlFloatMatrix = m * this - - public override fun Point.times(value: Float): EjmlFloatVector { - val res = FMatrixRMaj(1, 1) - CommonOps_FDRM.scale(value, toEjml().origin, res) - return res.wrapVector() - } - - public override fun Float.times(v: Point): EjmlFloatVector = v * this - - @UnstableKMathAPI - public override fun getFeature(structure: Matrix, type: KClass): F? { - structure.getFeature(type)?.let { return it } - val origin = structure.toEjml().origin - - return when (type) { - InverseMatrixFeature::class -> object : InverseMatrixFeature { - override val inverse: Matrix by lazy { - val res = origin.copy() - CommonOps_FDRM.invert(res) - res.wrapMatrix() - } - } - - DeterminantFeature::class -> object : DeterminantFeature { - override val determinant: Float by lazy { CommonOps_FDRM.det(origin) } - } - - SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature { - private val svd by lazy { - DecompositionFactory_FDRM.svd(origin.numRows, origin.numCols, true, true, false) - .apply { decompose(origin.copy()) } - } - - override val u: Matrix by lazy { svd.getU(null, false).wrapMatrix() } - override val s: Matrix by lazy { svd.getW(null).wrapMatrix() } - override val v: Matrix by lazy { svd.getV(null, false).wrapMatrix() } - override val singularValues: Point by lazy { FloatBuffer(svd.singularValues) } - } - - QRDecompositionFeature::class -> object : QRDecompositionFeature { - private val qr by lazy { - DecompositionFactory_FDRM.qr().apply { decompose(origin.copy()) } - } - - override val q: Matrix by lazy { - qr.getQ(null, false).wrapMatrix() + OrthogonalFeature - } - - override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix() + UFeature } - } - - CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { - override val l: Matrix by lazy { - val cholesky = - DecompositionFactory_FDRM.chol(structure.rowNum, true).apply { decompose(origin.copy()) } - - cholesky.getT(null).wrapMatrix() + LFeature - } - } - - LupDecompositionFeature::class -> object : LupDecompositionFeature { - private val lup by lazy { - DecompositionFactory_FDRM.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) } - } - - override val l: Matrix by lazy { - lup.getLower(null).wrapMatrix() + LFeature - } - - override val u: Matrix by lazy { - lup.getUpper(null).wrapMatrix() + UFeature - } - - override val p: Matrix by lazy { lup.getRowPivot(null).wrapMatrix() } - } - - else -> null - }?.let(type::cast) - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p matrix. - * @return the solution for *x* that is n by p. - */ - public fun solve(a: Matrix, b: Matrix): EjmlFloatMatrix { - val res = FMatrixRMaj(1, 1) - CommonOps_FDRM.solve(FMatrixRMaj(a.toEjml().origin), FMatrixRMaj(b.toEjml().origin), res) - return res.wrapMatrix() - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p vector. - * @return the solution for *x* that is n by p. - */ - public fun solve(a: Matrix, b: Point): EjmlFloatVector { - val res = FMatrixRMaj(1, 1) - CommonOps_FDRM.solve(FMatrixRMaj(a.toEjml().origin), FMatrixRMaj(b.toEjml().origin), res) - return EjmlFloatVector(res) - } -} - -/** - * [EjmlLinearSpace] implementation based on [CommonOps_DSCC], [DecompositionFactory_DSCC] operations and - * [DMatrixSparseCSC] matrices. - */ -public object EjmlLinearSpaceDSCC : EjmlLinearSpace() { - /** - * The [DoubleField] reference. - */ - public override val elementAlgebra: DoubleField get() = DoubleField - - @Suppress("UNCHECKED_CAST") - public override fun Matrix.toEjml(): EjmlDoubleMatrix = when { - this is EjmlDoubleMatrix<*> && origin is DMatrixSparseCSC -> this as EjmlDoubleMatrix - else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } - } - - @Suppress("UNCHECKED_CAST") - public override fun Point.toEjml(): EjmlDoubleVector = when { - this is EjmlDoubleVector<*> && origin is DMatrixSparseCSC -> this as EjmlDoubleVector - else -> EjmlDoubleVector(DMatrixSparseCSC(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } - }) - } - - public override fun buildMatrix( - rows: Int, - columns: Int, - initializer: DoubleField.(i: Int, j: Int) -> Double, - ): EjmlDoubleMatrix = DMatrixSparseCSC(rows, columns).also { - (0 until rows).forEach { row -> - (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } - } - }.wrapMatrix() - - public override fun buildVector( - size: Int, - initializer: DoubleField.(Int) -> Double, - ): EjmlDoubleVector = EjmlDoubleVector(DMatrixSparseCSC(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } - }) - - private fun T.wrapMatrix() = EjmlDoubleMatrix(this) - private fun T.wrapVector() = EjmlDoubleVector(this) - - public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } - - public override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { - val out = DMatrixSparseCSC(1, 1) - CommonOps_DSCC.mult(toEjml().origin, other.toEjml().origin, out) - return out.wrapMatrix() - } - - public override fun Matrix.dot(vector: Point): EjmlDoubleVector { - val out = DMatrixSparseCSC(1, 1) - CommonOps_DSCC.mult(toEjml().origin, vector.toEjml().origin, out) - return out.wrapVector() - } - - public override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { - val out = DMatrixSparseCSC(1, 1) - - CommonOps_DSCC.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra { -one }, - other.toEjml().origin, - out, - null, - null, - ) - - return out.wrapMatrix() - } - - public override operator fun Matrix.times(value: Double): EjmlDoubleMatrix { - val res = DMatrixSparseCSC(1, 1) - CommonOps_DSCC.scale(value, toEjml().origin, res) - return res.wrapMatrix() - } - - public override fun Point.unaryMinus(): EjmlDoubleVector { - val res = DMatrixSparseCSC(1, 1) - CommonOps_DSCC.changeSign(toEjml().origin, res) - return res.wrapVector() - } - - public override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { - val out = DMatrixSparseCSC(1, 1) - - CommonOps_DSCC.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra.one, - other.toEjml().origin, - out, - null, - null, - ) - - return out.wrapMatrix() - } - - public override fun Point.plus(other: Point): EjmlDoubleVector { - val out = DMatrixSparseCSC(1, 1) - - CommonOps_DSCC.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra.one, - other.toEjml().origin, - out, - null, - null, - ) - - return out.wrapVector() - } - - public override fun Point.minus(other: Point): EjmlDoubleVector { - val out = DMatrixSparseCSC(1, 1) - - CommonOps_DSCC.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra { -one }, - other.toEjml().origin, - out, - null, - null, - ) - - return out.wrapVector() - } - - public override fun Double.times(m: Matrix): EjmlDoubleMatrix = m * this - - public override fun Point.times(value: Double): EjmlDoubleVector { - val res = DMatrixSparseCSC(1, 1) - CommonOps_DSCC.scale(value, toEjml().origin, res) - return res.wrapVector() - } - - public override fun Double.times(v: Point): EjmlDoubleVector = v * this - - @UnstableKMathAPI - public override fun getFeature(structure: Matrix, type: KClass): F? { - structure.getFeature(type)?.let { return it } - val origin = structure.toEjml().origin - - return when (type) { - QRDecompositionFeature::class -> object : QRDecompositionFeature { - private val qr by lazy { - DecompositionFactory_DSCC.qr(FillReducing.NONE).apply { decompose(origin.copy()) } - } - - override val q: Matrix by lazy { - qr.getQ(null, false).wrapMatrix() + OrthogonalFeature - } - - override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix() + UFeature } - } - - CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { - override val l: Matrix by lazy { - val cholesky = - DecompositionFactory_DSCC.cholesky().apply { decompose(origin.copy()) } - - (cholesky.getT(null) as DMatrix).wrapMatrix() + LFeature - } - } - - LUDecompositionFeature::class, DeterminantFeature::class, InverseMatrixFeature::class -> object : - LUDecompositionFeature, DeterminantFeature, InverseMatrixFeature { - private val lu by lazy { - DecompositionFactory_DSCC.lu(FillReducing.NONE).apply { decompose(origin.copy()) } - } - - override val l: Matrix by lazy { - lu.getLower(null).wrapMatrix() + LFeature - } - - override val u: Matrix by lazy { - lu.getUpper(null).wrapMatrix() + UFeature - } - - override val inverse: Matrix by lazy { - var a = origin - val inverse = DMatrixRMaj(1, 1) - val solver = LinearSolverFactory_DSCC.lu(FillReducing.NONE) - if (solver.modifiesA()) a = a.copy() - val i = CommonOps_DDRM.identity(a.numRows) - solver.solve(i, inverse) - inverse.wrapMatrix() - } - - override val determinant: Double by lazy { elementAlgebra.number(lu.computeDeterminant().real) } - } - - else -> null - }?.let(type::cast) - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p matrix. - * @return the solution for *x* that is n by p. - */ - public fun solve(a: Matrix, b: Matrix): EjmlDoubleMatrix { - val res = DMatrixSparseCSC(1, 1) - CommonOps_DSCC.solve(DMatrixSparseCSC(a.toEjml().origin), DMatrixSparseCSC(b.toEjml().origin), res) - return res.wrapMatrix() - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p vector. - * @return the solution for *x* that is n by p. - */ - public fun solve(a: Matrix, b: Point): EjmlDoubleVector { - val res = DMatrixSparseCSC(1, 1) - CommonOps_DSCC.solve(DMatrixSparseCSC(a.toEjml().origin), DMatrixSparseCSC(b.toEjml().origin), res) - return EjmlDoubleVector(res) - } -} - -/** - * [EjmlLinearSpace] implementation based on [CommonOps_FSCC], [DecompositionFactory_FSCC] operations and - * [FMatrixSparseCSC] matrices. - */ -public object EjmlLinearSpaceFSCC : EjmlLinearSpace() { - /** - * The [FloatField] reference. - */ - public override val elementAlgebra: FloatField get() = FloatField - - @Suppress("UNCHECKED_CAST") - public override fun Matrix.toEjml(): EjmlFloatMatrix = when { - this is EjmlFloatMatrix<*> && origin is FMatrixSparseCSC -> this as EjmlFloatMatrix - else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } - } - - @Suppress("UNCHECKED_CAST") - public override fun Point.toEjml(): EjmlFloatVector = when { - this is EjmlFloatVector<*> && origin is FMatrixSparseCSC -> this as EjmlFloatVector - else -> EjmlFloatVector(FMatrixSparseCSC(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } - }) - } - - public override fun buildMatrix( - rows: Int, - columns: Int, - initializer: FloatField.(i: Int, j: Int) -> Float, - ): EjmlFloatMatrix = FMatrixSparseCSC(rows, columns).also { - (0 until rows).forEach { row -> - (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } - } - }.wrapMatrix() - - public override fun buildVector( - size: Int, - initializer: FloatField.(Int) -> Float, - ): EjmlFloatVector = EjmlFloatVector(FMatrixSparseCSC(size, 1).also { - (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } - }) - - private fun T.wrapMatrix() = EjmlFloatMatrix(this) - private fun T.wrapVector() = EjmlFloatVector(this) - - public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } - - public override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { - val out = FMatrixSparseCSC(1, 1) - CommonOps_FSCC.mult(toEjml().origin, other.toEjml().origin, out) - return out.wrapMatrix() - } - - public override fun Matrix.dot(vector: Point): EjmlFloatVector { - val out = FMatrixSparseCSC(1, 1) - CommonOps_FSCC.mult(toEjml().origin, vector.toEjml().origin, out) - return out.wrapVector() - } - - public override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { - val out = FMatrixSparseCSC(1, 1) - - CommonOps_FSCC.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra { -one }, - other.toEjml().origin, - out, - null, - null, - ) - - return out.wrapMatrix() - } - - public override operator fun Matrix.times(value: Float): EjmlFloatMatrix { - val res = FMatrixSparseCSC(1, 1) - CommonOps_FSCC.scale(value, toEjml().origin, res) - return res.wrapMatrix() - } - - public override fun Point.unaryMinus(): EjmlFloatVector { - val res = FMatrixSparseCSC(1, 1) - CommonOps_FSCC.changeSign(toEjml().origin, res) - return res.wrapVector() - } - - public override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { - val out = FMatrixSparseCSC(1, 1) - - CommonOps_FSCC.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra.one, - other.toEjml().origin, - out, - null, - null, - ) - - return out.wrapMatrix() - } - - public override fun Point.plus(other: Point): EjmlFloatVector { - val out = FMatrixSparseCSC(1, 1) - - CommonOps_FSCC.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra.one, - other.toEjml().origin, - out, - null, - null, - ) - - return out.wrapVector() - } - - public override fun Point.minus(other: Point): EjmlFloatVector { - val out = FMatrixSparseCSC(1, 1) - - CommonOps_FSCC.add( - elementAlgebra.one, - toEjml().origin, - elementAlgebra { -one }, - other.toEjml().origin, - out, - null, - null, - ) - - return out.wrapVector() - } - - public override fun Float.times(m: Matrix): EjmlFloatMatrix = m * this - - public override fun Point.times(value: Float): EjmlFloatVector { - val res = FMatrixSparseCSC(1, 1) - CommonOps_FSCC.scale(value, toEjml().origin, res) - return res.wrapVector() - } - - public override fun Float.times(v: Point): EjmlFloatVector = v * this - - @UnstableKMathAPI - public override fun getFeature(structure: Matrix, type: KClass): F? { - structure.getFeature(type)?.let { return it } - val origin = structure.toEjml().origin - - return when (type) { - QRDecompositionFeature::class -> object : QRDecompositionFeature { - private val qr by lazy { - DecompositionFactory_FSCC.qr(FillReducing.NONE).apply { decompose(origin.copy()) } - } - - override val q: Matrix by lazy { - qr.getQ(null, false).wrapMatrix() + OrthogonalFeature - } - - override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix() + UFeature } - } - - CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { - override val l: Matrix by lazy { - val cholesky = - DecompositionFactory_FSCC.cholesky().apply { decompose(origin.copy()) } - - (cholesky.getT(null) as FMatrix).wrapMatrix() + LFeature - } - } - - LUDecompositionFeature::class, DeterminantFeature::class, InverseMatrixFeature::class -> object : - LUDecompositionFeature, DeterminantFeature, InverseMatrixFeature { - private val lu by lazy { - DecompositionFactory_FSCC.lu(FillReducing.NONE).apply { decompose(origin.copy()) } - } - - override val l: Matrix by lazy { - lu.getLower(null).wrapMatrix() + LFeature - } - - override val u: Matrix by lazy { - lu.getUpper(null).wrapMatrix() + UFeature - } - - override val inverse: Matrix by lazy { - var a = origin - val inverse = FMatrixRMaj(1, 1) - val solver = LinearSolverFactory_FSCC.lu(FillReducing.NONE) - if (solver.modifiesA()) a = a.copy() - val i = CommonOps_FDRM.identity(a.numRows) - solver.solve(i, inverse) - inverse.wrapMatrix() - } - - override val determinant: Float by lazy { elementAlgebra.number(lu.computeDeterminant().real) } - } - - else -> null - }?.let(type::cast) - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p matrix. - * @return the solution for *x* that is n by p. - */ - public fun solve(a: Matrix, b: Matrix): EjmlFloatMatrix { - val res = FMatrixSparseCSC(1, 1) - CommonOps_FSCC.solve(FMatrixSparseCSC(a.toEjml().origin), FMatrixSparseCSC(b.toEjml().origin), res) - return res.wrapMatrix() - } - - /** - * Solves for *x* in the following equation: *x = [a] -1 · [b]*. - * - * @param a the base matrix. - * @param b n by p vector. - * @return the solution for *x* that is n by p. - */ - public fun solve(a: Matrix, b: Point): EjmlFloatVector { - val res = FMatrixSparseCSC(1, 1) - CommonOps_FSCC.solve(FMatrixSparseCSC(a.toEjml().origin), FMatrixSparseCSC(b.toEjml().origin), res) - return EjmlFloatVector(res) - } -} - diff --git a/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt b/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt index 50675bdac..6055ae1d8 100644 --- a/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt +++ b/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt @@ -11,7 +11,7 @@ import org.ejml.dense.row.RandomMatrices_DDRM import org.ejml.dense.row.factory.DecompositionFactory_DDRM import space.kscience.kmath.linear.DeterminantFeature import space.kscience.kmath.linear.LupDecompositionFeature -import space.kscience.kmath.linear.getFeature +import space.kscience.kmath.linear.computeFeature import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureND @@ -59,9 +59,9 @@ internal class EjmlMatrixTest { fun features() { val m = randomMatrix val w = EjmlDoubleMatrix(m) - val det: DeterminantFeature = EjmlLinearSpaceDDRM.getFeature(w) ?: fail() + val det: DeterminantFeature = EjmlLinearSpaceDDRM.computeFeature(w) ?: fail() assertEquals(CommonOps_DDRM.det(m), det.determinant) - val lup: LupDecompositionFeature = EjmlLinearSpaceDDRM.getFeature(w) ?: fail() + val lup: LupDecompositionFeature = EjmlLinearSpaceDDRM.computeFeature(w) ?: fail() val ludecompositionF64 = DecompositionFactory_DDRM.lu(m.numRows, m.numCols) .also { it.decompose(m.copy()) } diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt index 8023236ea..38e5b4beb 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt @@ -32,18 +32,18 @@ import kotlin.math.pow public typealias RealMatrix = Matrix public fun realMatrix(rowNum: Int, colNum: Int, initializer: DoubleField.(i: Int, j: Int) -> Double): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, colNum, initializer) + LinearSpace.double.buildMatrix(rowNum, colNum, initializer) @OptIn(UnstableKMathAPI::class) public fun realMatrix(rowNum: Int, colNum: Int): MatrixBuilder = - LinearSpace.real.matrix(rowNum, colNum) + LinearSpace.double.matrix(rowNum, colNum) public fun Array.toMatrix(): RealMatrix { - return LinearSpace.real.buildMatrix(size, this[0].size) { row, col -> this@toMatrix[row][col] } + return LinearSpace.double.buildMatrix(size, this[0].size) { row, col -> this@toMatrix[row][col] } } public fun Sequence.toMatrix(): RealMatrix = toList().let { - LinearSpace.real.buildMatrix(it.size, it[0].size) { row, col -> it[row][col] } + LinearSpace.double.buildMatrix(it.size, it[0].size) { row, col -> it[row][col] } } public fun RealMatrix.repeatStackVertical(n: Int): RealMatrix = @@ -56,37 +56,37 @@ public fun RealMatrix.repeatStackVertical(n: Int): RealMatrix = */ public operator fun RealMatrix.times(double: Double): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> + LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> get(row, col) * double } public operator fun RealMatrix.plus(double: Double): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> + LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> get(row, col) + double } public operator fun RealMatrix.minus(double: Double): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> + LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> get(row, col) - double } public operator fun RealMatrix.div(double: Double): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> + LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> get(row, col) / double } public operator fun Double.times(matrix: RealMatrix): RealMatrix = - LinearSpace.real.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> + LinearSpace.double.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> this@times * matrix[row, col] } public operator fun Double.plus(matrix: RealMatrix): RealMatrix = - LinearSpace.real.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> + LinearSpace.double.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> this@plus + matrix[row, col] } public operator fun Double.minus(matrix: RealMatrix): RealMatrix = - LinearSpace.real.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> + LinearSpace.double.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> this@minus - matrix[row, col] } @@ -101,20 +101,20 @@ public operator fun Double.minus(matrix: RealMatrix): RealMatrix = @UnstableKMathAPI public operator fun RealMatrix.times(other: RealMatrix): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> this@times[row, col] * other[row, col] } + LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> this@times[row, col] * other[row, col] } public operator fun RealMatrix.plus(other: RealMatrix): RealMatrix = - LinearSpace.real.run { this@plus + other } + LinearSpace.double.run { this@plus + other } public operator fun RealMatrix.minus(other: RealMatrix): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> this@minus[row, col] - other[row, col] } + LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> this@minus[row, col] - other[row, col] } /* * Operations on columns */ public inline fun RealMatrix.appendColumn(crossinline mapper: (Buffer) -> Double): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, colNum + 1) { row, col -> + LinearSpace.double.buildMatrix(rowNum, colNum + 1) { row, col -> if (col < colNum) get(row, col) else @@ -122,7 +122,7 @@ public inline fun RealMatrix.appendColumn(crossinline mapper: (Buffer) - } public fun RealMatrix.extractColumns(columnRange: IntRange): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, columnRange.count()) { row, col -> + LinearSpace.double.buildMatrix(rowNum, columnRange.count()) { row, col -> this@extractColumns[row, columnRange.first + col] } @@ -155,14 +155,14 @@ public fun RealMatrix.max(): Double? = elements().map { (_, value) -> value }.ma public fun RealMatrix.average(): Double = elements().map { (_, value) -> value }.average() public inline fun RealMatrix.map(crossinline transform: (Double) -> Double): RealMatrix = - LinearSpace.real.buildMatrix(rowNum, colNum) { i, j -> + LinearSpace.double.buildMatrix(rowNum, colNum) { i, j -> transform(get(i, j)) } /** * Inverse a square real matrix using LUP decomposition */ -public fun RealMatrix.inverseWithLup(): RealMatrix = LinearSpace.real.inverseWithLup(this) +public fun RealMatrix.inverseWithLup(): RealMatrix = LinearSpace.double.lupSolver().inverse(this) //extended operations diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt index b79e5030c..395c94838 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt @@ -12,6 +12,6 @@ import space.kscience.kmath.linear.Matrix /** * Optimized dot product for real matrices */ -public infix fun Matrix.dot(other: Matrix): Matrix = LinearSpace.real.run { +public infix fun Matrix.dot(other: Matrix): Matrix = LinearSpace.double.run { this@dot dot other } \ No newline at end of file diff --git a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt b/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt index b3e129c2e..5a80ee677 100644 --- a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt @@ -65,7 +65,7 @@ internal class DoubleMatrixTest { 4.0, 6.0, 2.0 ) val matrix2 = (matrix1 * 2.5 + 1.0 - 2.0) / 2.0 - val expectedResult = LinearSpace.real.matrix(2, 3)( + val expectedResult = LinearSpace.double.matrix(2, 3)( 0.75, -0.5, 3.25, 4.5, 7.0, 2.0 ) @@ -160,7 +160,7 @@ internal class DoubleMatrixTest { @Test fun testAllElementOperations() { - val matrix1 = LinearSpace.real.matrix(2, 4)( + val matrix1 = LinearSpace.double.matrix(2, 4)( -1.0, 0.0, 3.0, 15.0, 4.0, -6.0, 7.0, -11.0 ) diff --git a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleVectorTest.kt b/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleVectorTest.kt index 9de54381c..ec7b536ba 100644 --- a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleVectorTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleVectorTest.kt @@ -35,7 +35,7 @@ internal class DoubleVectorTest { val vector2 = DoubleBuffer(5) { 5 - it.toDouble() } val matrix1 = vector1.asMatrix() val matrix2 = vector2.asMatrix().transpose() - val product = LinearSpace.real.run { matrix1 dot matrix2 } + val product = LinearSpace.double.run { matrix1 dot matrix2 } assertEquals(5.0, product[1, 0]) assertEquals(6.0, product[2, 2]) } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt index dcf711c3b..f90159c81 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt @@ -5,11 +5,12 @@ package space.kscience.kmath.integration +import space.kscience.kmath.misc.Feature import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.Featured import kotlin.reflect.KClass -public interface IntegrandFeature { +public interface IntegrandFeature : Feature { override fun toString(): String } @@ -18,7 +19,7 @@ public interface Integrand : Featured { override fun getFeature(type: KClass): T? = features.getFeature(type) } -public inline fun Integrand.getFeature(): T? = getFeature(T::class) +public inline fun Integrand.getFeature(): T? = getFeature(T::class) public class IntegrandValue(public val value: T) : IntegrandFeature { override fun toString(): String = "Value($value)" diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt index 4294462c0..a59c301cf 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt @@ -27,19 +27,30 @@ public class KotlingradExpression>( ) : SpecialDifferentiableExpression> { public override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) - public override fun derivativeOrNull(symbols: List): KotlingradExpression = - KotlingradExpression( - algebra, - symbols.map(Symbol::identity) - .map(MstNumericAlgebra::bindSymbol) - .map>>(Symbol::toSVar) - .fold(mst.toSFun(), SFun>::d) - .toMst(), - ) + public override fun derivativeOrNull( + symbols: List, + ): KotlingradExpression = KotlingradExpression( + algebra, + symbols.map(Symbol::identity) + .map(MstNumericAlgebra::bindSymbol) + .map>>(Symbol::toSVar) + .fold(mst.toSFun(), SFun>::d) + .toMst(), + ) +} + +/** + * A diff processor using [MST] to Kotlingrad converter + */ +public class KotlingradProcessor>( + public val algebra: A, +) : AutoDiffProcessor { + override fun differentiate(function: MstExtendedField.() -> MST): DifferentiableExpression = + MstExtendedField.function().toKotlingradExpression(algebra) } /** * Wraps this [MST] into [KotlingradExpression]. */ -public fun > MST.toDiffExpression(algebra: A): KotlingradExpression = +public fun > MST.toKotlingradExpression(algebra: A): KotlingradExpression = KotlingradExpression(algebra, this) diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index 62288242a..4d4f99b71 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -23,7 +23,7 @@ public enum class FunctionOptimizationTarget : OptimizationFeature { public class FunctionOptimization( override val features: FeatureSet, public val expression: DifferentiableExpression, -) : OptimizationProblem{ +) : OptimizationProblem{ public companion object{ /** @@ -56,7 +56,6 @@ public class FunctionOptimization( } } - public fun FunctionOptimization.withFeatures( vararg newFeature: OptimizationFeature, ): FunctionOptimization = FunctionOptimization( @@ -68,7 +67,7 @@ public fun FunctionOptimization.withFeatures( * Optimize differentiable expression using specific [optimizer] form given [startingPoint] */ public suspend fun DifferentiableExpression.optimizeWith( - optimizer: Optimizer>, + optimizer: Optimizer>, startingPoint: Map, vararg features: OptimizationFeature, ): FunctionOptimization { @@ -76,3 +75,8 @@ public suspend fun DifferentiableExpression.optimizeWith( return optimizer.optimize(problem) } +public val FunctionOptimization.resultValueOrNull:T? + get() = getFeature>()?.point?.let { expression(it) } + +public val FunctionOptimization.resultValue: T + get() = resultValueOrNull ?: error("Result is not present in $this") \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt new file mode 100644 index 000000000..7d52ae26e --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt @@ -0,0 +1,93 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.optimization + +import space.kscience.kmath.data.XYColumnarData +import space.kscience.kmath.expressions.DifferentiableExpression +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.misc.FeatureSet + +public abstract class OptimizationBuilder> { + public val features: ArrayList = ArrayList() + + public fun addFeature(feature: OptimizationFeature) { + features.add(feature) + } + + public inline fun updateFeature(update: (T?) -> T) { + val existing = features.find { it.key == T::class } as? T + val new = update(existing) + if (existing != null) { + features.remove(existing) + } + addFeature(new) + } + + public abstract fun build(): R +} + +public fun OptimizationBuilder.startAt(startingPoint: Map) { + addFeature(OptimizationStartPoint(startingPoint)) +} + +public class FunctionOptimizationBuilder( + private val expression: DifferentiableExpression, +) : OptimizationBuilder>() { + override fun build(): FunctionOptimization = FunctionOptimization(FeatureSet.of(features), expression) +} + +public fun FunctionOptimization( + expression: DifferentiableExpression, + builder: FunctionOptimizationBuilder.() -> Unit, +): FunctionOptimization = FunctionOptimizationBuilder(expression).apply(builder).build() + +public suspend fun DifferentiableExpression.optimizeWith( + optimizer: Optimizer>, + startingPoint: Map, + builder: FunctionOptimizationBuilder.() -> Unit = {}, +): FunctionOptimization { + val problem = FunctionOptimization(this) { + startAt(startingPoint) + builder() + } + return optimizer.optimize(problem) +} + +public suspend fun DifferentiableExpression.optimizeWith( + optimizer: Optimizer>, + vararg startingPoint: Pair, + builder: FunctionOptimizationBuilder.() -> Unit = {}, +): FunctionOptimization { + val problem = FunctionOptimization(this) { + startAt(mapOf(*startingPoint)) + builder() + } + return optimizer.optimize(problem) +} + + +public class XYOptimizationBuilder( + public val data: XYColumnarData, + public val model: DifferentiableExpression, +) : OptimizationBuilder() { + + public var pointToCurveDistance: PointToCurveDistance = PointToCurveDistance.byY + public var pointWeight: PointWeight = PointWeight.byYSigma + + override fun build(): XYOptimization = XYOptimization( + FeatureSet.of(features), + data, + model, + pointToCurveDistance, + pointWeight + ) +} + +public fun XYOptimization( + data: XYColumnarData, + model: DifferentiableExpression, + builder: XYOptimizationBuilder.() -> Unit, +): XYOptimization = XYOptimizationBuilder(data, model).apply(builder).build() \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt index 739ce8ca5..b42be4035 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt @@ -5,37 +5,61 @@ package space.kscience.kmath.optimization +import space.kscience.kmath.expressions.DifferentiableExpression import space.kscience.kmath.expressions.Symbol -import space.kscience.kmath.misc.FeatureSet -import space.kscience.kmath.misc.Featured -import space.kscience.kmath.misc.Loggable +import space.kscience.kmath.linear.Matrix +import space.kscience.kmath.misc.* import kotlin.reflect.KClass -public interface OptimizationFeature { +public interface OptimizationFeature : Feature { + // enforce toString override override fun toString(): String } -public interface OptimizationProblem : Featured { +public interface OptimizationProblem : Featured { public val features: FeatureSet - override fun getFeature(type: KClass): T? = features.getFeature(type) + override fun getFeature(type: KClass): F? = features.getFeature(type) } -public inline fun OptimizationProblem.getFeature(): T? = getFeature(T::class) +public inline fun OptimizationProblem<*>.getFeature(): F? = getFeature(F::class) public open class OptimizationStartPoint(public val point: Map) : OptimizationFeature { override fun toString(): String = "StartPoint($point)" } + +public interface OptimizationPrior : OptimizationFeature, DifferentiableExpression { + override val key: FeatureKey get() = OptimizationPrior::class +} + +public class OptimizationCovariance(public val covariance: Matrix) : OptimizationFeature { + override fun toString(): String = "Covariance($covariance)" +} + +/** + * Get the starting point for optimization. Throws error if not defined. + */ +public val OptimizationProblem.startPoint: Map + get() = getFeature>()?.point + ?: error("Starting point not defined in $this") + public open class OptimizationResult(public val point: Map) : OptimizationFeature { override fun toString(): String = "Result($point)" } +public val OptimizationProblem.resultPointOrNull: Map? + get() = getFeature>()?.point + +public val OptimizationProblem.resultPoint: Map + get() = resultPointOrNull ?: error("Result is not present in $this") + public class OptimizationLog(private val loggable: Loggable) : Loggable by loggable, OptimizationFeature { override fun toString(): String = "Log($loggable)" } -public class OptimizationParameters(public val symbols: List): OptimizationFeature{ +public class OptimizationParameters(public val symbols: List) : OptimizationFeature { public constructor(vararg symbols: Symbol) : this(listOf(*symbols)) + override fun toString(): String = "Parameters($symbols)" } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt index ad1a16007..78385a99b 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt @@ -5,6 +5,6 @@ package space.kscience.kmath.optimization -public interface Optimizer

{ +public interface Optimizer> { public suspend fun optimize(problem: P): P } \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt new file mode 100644 index 000000000..acfc7e445 --- /dev/null +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt @@ -0,0 +1,247 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.optimization + +import space.kscience.kmath.expressions.DifferentiableExpression +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.expressions.SymbolIndexer +import space.kscience.kmath.expressions.derivative +import space.kscience.kmath.linear.* +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.DoubleL2Norm + + +/** + * An optimizer based onf Fyodor Tkachev's quasi-optimal weights method. + * See [the article](http://arxiv.org/abs/physics/0604127). + */ +@UnstableKMathAPI +public class QowOptimizer : Optimizer { + + private val linearSpace: LinearSpace = LinearSpace.double + private val solver: LinearSolver = linearSpace.lupSolver() + + @OptIn(UnstableKMathAPI::class) + private inner class QoWeight( + val problem: XYOptimization, + val parameters: Map, + ) : Map by parameters, SymbolIndexer { + override val symbols: List = parameters.keys.toList() + + val data get() = problem.data + + /** + * Derivatives of the spectrum over parameters. First index in the point number, second one - index of parameter + */ + val derivs: Matrix by lazy { + linearSpace.buildMatrix(problem.data.size, symbols.size) { i, k -> + problem.distance(i).derivative(symbols[k])(parameters) + } + } + + /** + * Array of dispersions in each point + */ + val dispersion: Point by lazy { + DoubleBuffer(problem.data.size) { i -> + problem.weight(i).invoke(parameters) + } + } + + val prior: DifferentiableExpression? get() = problem.getFeature>() + } + + /** + * The signed distance from the model to the [i]-th point of data. + */ + private fun QoWeight.distance(i: Int, parameters: Map): Double = problem.distance(i)(parameters) + + + /** + * The derivative of [distance] + */ + private fun QoWeight.distanceDerivative(symbol: Symbol, i: Int, parameters: Map): Double = + problem.distance(i).derivative(symbol)(parameters) + + /** + * Теоретическая ковариация весовых функций. + * + * D(\phi)=E(\phi_k(\theta_0) \phi_l(\theta_0))= disDeriv_k * disDeriv_l /sigma^2 + */ + private fun QoWeight.covarF(): Matrix = + linearSpace.matrix(size, size).symmetric { k, l -> + (0 until data.size).sumOf { i -> derivs[k, i] * derivs[l, i] / dispersion[i] } + } + + /** + * Экспериментальная ковариация весов. Формула (22) из + * http://arxiv.org/abs/physics/0604127 + */ + private fun QoWeight.covarFExp(theta: Map): Matrix = + with(linearSpace) { + /* + * Важно! Если не делать предварителього вычисления этих производных, то + * количество вызывов функции будет dim^2 вместо dim Первый индекс - + * номер точки, второй - номер переменной, по которой берется производная + */ + val eqvalues = linearSpace.buildMatrix(data.size, size) { i, l -> + distance(i, theta) * derivs[l, i] / dispersion[i] + } + + buildMatrix(size, size) { k, l -> + (0 until data.size).sumOf { i -> eqvalues[i, l] * eqvalues[i, k] } + } + } + + /** + * Equation derivatives for Newton run + */ + private fun QoWeight.getEqDerivValues( + theta: Map = parameters, + ): Matrix = with(linearSpace) { + val fitDim = size + //Возвращает производную k-того Eq по l-тому параметру + //val res = Array(fitDim) { DoubleArray(fitDim) } + val sderiv = buildMatrix(data.size, size) { i, l -> + distanceDerivative(symbols[l], i, theta) + } + + buildMatrix(size, size) { k, l -> + val base = (0 until data.size).sumOf { i -> + require(dispersion[i] > 0) + sderiv[i, l] * derivs[k, i] / dispersion[i] + } + prior?.let { prior -> + //Check if this one is correct + val pi = prior(theta) + val deriv1 = prior.derivative(symbols[k])(theta) + val deriv2 = prior.derivative(symbols[l])(theta) + base + deriv1 * deriv2 / pi / pi + } ?: base + } + } + + + /** + * Значения уравнений метода квазиоптимальных весов + */ + private fun QoWeight.getEqValues(theta: Map = this): Point { + val distances = DoubleBuffer(data.size) { i -> distance(i, theta) } + + return DoubleBuffer(size) { k -> + val base = (0 until data.size).sumOf { i -> distances[i] * derivs[k, i] / dispersion[i] } + //Поправка на априорную вероятность + prior?.let { prior -> + base - prior.derivative(symbols[k])(theta) / prior(theta) + } ?: base + } + } + + + private fun QoWeight.newtonianStep( + theta: Map, + eqvalues: Point, + ): QoWeight = linearSpace { + with(this@newtonianStep) { + val start = theta.toPoint() + val invJacob = solver.inverse(this@newtonianStep.getEqDerivValues(theta)) + + val step = invJacob.dot(eqvalues) + return QoWeight(problem, theta + (start - step).toMap()) + } + } + + private fun QoWeight.newtonianRun( + maxSteps: Int = 100, + tolerance: Double = 0.0, + fast: Boolean = false, + ): QoWeight { + + val logger = problem.getFeature() + + var dis: Double//норма невязки + // Для удобства работаем всегда с полным набором параметров + var par = problem.startPoint + + logger?.log { "Starting newtonian iteration from: \n\t$par" } + + var eqvalues = getEqValues(par)//значения функций + + dis = DoubleL2Norm.norm(eqvalues)// невязка + logger?.log { "Starting discrepancy is $dis" } + var i = 0 + var flag = false + while (!flag) { + i++ + logger?.log { "Starting step number $i" } + + val currentSolution = if (fast) { + //Берет значения матрицы в той точке, где считается вес + newtonianStep(this, eqvalues) + } else { + //Берет значения матрицы в точке par + newtonianStep(par, eqvalues) + } + // здесь должен стоять учет границ параметров + logger?.log { "Parameter values after step are: \n\t$currentSolution" } + + eqvalues = getEqValues(currentSolution) + val currentDis = DoubleL2Norm.norm(eqvalues)// невязка после шага + + logger?.log { "The discrepancy after step is: $currentDis." } + + if (currentDis >= dis && i > 1) { + //дополнительно проверяем, чтобы был сделан хотя бы один шаг + flag = true + logger?.log { "The discrepancy does not decrease. Stopping iteration." } + } else { + par = currentSolution + dis = currentDis + } + if (i >= maxSteps) { + flag = true + logger?.log { "Maximum number of iterations reached. Stopping iteration." } + } + if (dis <= tolerance) { + flag = true + logger?.log { "Tolerance threshold is reached. Stopping iteration." } + } + } + + return QoWeight(problem, par) + } + + private fun QoWeight.covariance(): Matrix { + val logger = problem.getFeature() + + logger?.log { + """ + Starting errors estimation using quasioptimal weights method. The starting weight is: + ${problem.startPoint} + """.trimIndent() + } + + val covar = solver.inverse(getEqDerivValues()) + //TODO fix eigenvalues check +// val decomposition = EigenDecomposition(covar.matrix) +// var valid = true +// for (lambda in decomposition.realEigenvalues) { +// if (lambda <= 0) { +// logger?.log { "The covariance matrix is not positive defined. Error estimation is not valid" } +// valid = false +// } +// } + return covar + } + + override suspend fun optimize(problem: XYOptimization): XYOptimization { + val initialWeight = QoWeight(problem, problem.startPoint) + val res = initialWeight.newtonianRun() + return res.problem.withFeature(OptimizationResult(res.parameters)) + } +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt index 7dc17f6d9..68c0c77eb 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt @@ -7,13 +7,21 @@ package space.kscience.kmath.optimization import space.kscience.kmath.data.XYColumnarData +import space.kscience.kmath.data.indices import space.kscience.kmath.expressions.DifferentiableExpression import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.expressions.derivative import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.UnstableKMathAPI +import kotlin.math.PI +import kotlin.math.ln import kotlin.math.pow +import kotlin.math.sqrt +/** + * Specify the way to compute distance from point to the curve as DifferentiableExpression + */ public interface PointToCurveDistance : OptimizationFeature { public fun distance(problem: XYOptimization, index: Int): DifferentiableExpression @@ -33,42 +41,107 @@ public interface PointToCurveDistance : OptimizationFeature { } override fun toString(): String = "PointToCurveDistanceByY" - } - } } +/** + * Compute a wight of the point. The more the weight, the more impact this point will have on the fit. + * By default uses Dispersion^-1 + */ +public interface PointWeight : OptimizationFeature { + public fun weight(problem: XYOptimization, index: Int): DifferentiableExpression + + public companion object { + public fun bySigma(sigmaSymbol: Symbol): PointWeight = object : PointWeight { + override fun weight(problem: XYOptimization, index: Int): DifferentiableExpression = + object : DifferentiableExpression { + override fun invoke(arguments: Map): Double { + return problem.data[sigmaSymbol]?.get(index)?.pow(-2) ?: 1.0 + } + + override fun derivativeOrNull(symbols: List): Expression = Expression { 0.0 } + } + + override fun toString(): String = "PointWeightBySigma($sigmaSymbol)" + + } + + public val byYSigma: PointWeight = bySigma(Symbol.yError) + } +} + +/** + * An optimization for XY data. + */ public class XYOptimization( override val features: FeatureSet, public val data: XYColumnarData, public val model: DifferentiableExpression, -) : OptimizationProblem + internal val pointToCurveDistance: PointToCurveDistance = PointToCurveDistance.byY, + internal val pointWeight: PointWeight = PointWeight.byYSigma, +) : OptimizationProblem { + public fun distance(index: Int): DifferentiableExpression = pointToCurveDistance.distance(this, index) + public fun weight(index: Int): DifferentiableExpression = pointWeight.weight(this, index) +} -public suspend fun Optimizer>.maximumLogLikelihood(problem: XYOptimization): XYOptimization { - val distanceBuilder = problem.getFeature() ?: PointToCurveDistance.byY - val likelihood: DifferentiableExpression = object : DifferentiableExpression { - override fun derivativeOrNull(symbols: List): Expression? { - TODO("Not yet implemented") +public fun XYOptimization.withFeature(vararg features: OptimizationFeature): XYOptimization { + return XYOptimization(this.features.with(*features), data, model, pointToCurveDistance, pointWeight) +} + +private val oneOver2Pi = 1.0 / sqrt(2 * PI) + +internal fun XYOptimization.likelihood(): DifferentiableExpression = object : DifferentiableExpression { + override fun derivativeOrNull(symbols: List): Expression = Expression { arguments -> + data.indices.sumOf { index -> + + val d = distance(index)(arguments) + val weight = weight(index)(arguments) + val weightDerivative = weight(index)(arguments) + + // -1 / (sqrt(2 PI) * sigma) + 2 (x-mu)/ 2 sigma^2 * d mu/ d theta - (x-mu)^2 / 2 * d w/ d theta + return@sumOf -oneOver2Pi * sqrt(weight) + //offset derivative + d * model.derivative(symbols)(arguments) * weight - //model derivative + d.pow(2) * weightDerivative / 2 //weight derivative } - - override fun invoke(arguments: Map): Double { - var res = 0.0 - for (index in 0 until problem.data.size) { - val d = distanceBuilder.distance(problem, index).invoke(arguments) - val sigma: Double = TODO() - res -= (d / sigma).pow(2) - } - return res - } - } - val functionOptimization = FunctionOptimization(problem.features, likelihood) - val result = optimize(functionOptimization) + + override fun invoke(arguments: Map): Double { + return data.indices.sumOf { index -> + val d = distance(index)(arguments) + val weight = weight(index)(arguments) + //1/sqrt(2 PI sigma^2) - (x-mu)^2/ (2 * sigma^2) + oneOver2Pi * ln(weight) - d.pow(2) * weight + } / 2 + } + +} + +/** + * Optimize given XY (least squares) [problem] using this function [Optimizer]. + * The problem is treated as maximum likelihood problem and is done via maximizing logarithmic likelihood, respecting + * possible weight dependency on the model and parameters. + */ +public suspend fun Optimizer>.maximumLogLikelihood(problem: XYOptimization): XYOptimization { + val functionOptimization = FunctionOptimization(problem.features, problem.likelihood()) + val result = optimize(functionOptimization.withFeatures(FunctionOptimizationTarget.MAXIMIZE)) return XYOptimization(result.features, problem.data, problem.model) } +public suspend fun Optimizer>.maximumLogLikelihood( + data: XYColumnarData, + model: DifferentiableExpression, + builder: XYOptimizationBuilder.() -> Unit, +): XYOptimization = maximumLogLikelihood(XYOptimization(data, model, builder)) + +//public suspend fun XYColumnarData.fitWith( +// optimizer: XYOptimization, +// problemBuilder: XYOptimizationBuilder.() -> Unit = {}, +// +//) + + // //@UnstableKMathAPI //public interface XYFit : OptimizationProblem { diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt b/kmath-stat/src/commonMain/tmp/QowFit.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/qow/QowFit.kt rename to kmath-stat/src/commonMain/tmp/QowFit.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/AnalyticalGradientCalculator.kt b/kmath-stat/src/commonMain/tmp/minuit/AnalyticalGradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/AnalyticalGradientCalculator.kt rename to kmath-stat/src/commonMain/tmp/minuit/AnalyticalGradientCalculator.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimizer.kt b/kmath-stat/src/commonMain/tmp/minuit/CombinedMinimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimizer.kt rename to kmath-stat/src/commonMain/tmp/minuit/CombinedMinimizer.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimumBuilder.kt b/kmath-stat/src/commonMain/tmp/minuit/CombinedMinimumBuilder.kt similarity index 97% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimumBuilder.kt rename to kmath-stat/src/commonMain/tmp/minuit/CombinedMinimumBuilder.kt index a2f0a644a..8c5452575 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/CombinedMinimumBuilder.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/CombinedMinimumBuilder.kt @@ -16,6 +16,7 @@ package ru.inr.mass.minuit import space.kscience.kmath.optimization.minuit.MINUITPlugin +import space.kscience.kmath.optimization.minuit.MinimumSeed /** * diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ContoursError.kt b/kmath-stat/src/commonMain/tmp/minuit/ContoursError.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ContoursError.kt rename to kmath-stat/src/commonMain/tmp/minuit/ContoursError.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/DavidonErrorUpdator.kt b/kmath-stat/src/commonMain/tmp/minuit/DavidonErrorUpdator.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/DavidonErrorUpdator.kt rename to kmath-stat/src/commonMain/tmp/minuit/DavidonErrorUpdator.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionGradient.kt b/kmath-stat/src/commonMain/tmp/minuit/FunctionGradient.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionGradient.kt rename to kmath-stat/src/commonMain/tmp/minuit/FunctionGradient.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionMinimum.kt b/kmath-stat/src/commonMain/tmp/minuit/FunctionMinimum.kt similarity index 99% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionMinimum.kt rename to kmath-stat/src/commonMain/tmp/minuit/FunctionMinimum.kt index 56908f00d..e43523291 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/FunctionMinimum.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/FunctionMinimum.kt @@ -16,6 +16,7 @@ package ru.inr.mass.minuit import ru.inr.mass.minuit.* +import space.kscience.kmath.optimization.minuit.MinimumSeed /** * Result of the minimization. diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/GradientCalculator.kt b/kmath-stat/src/commonMain/tmp/minuit/GradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/GradientCalculator.kt rename to kmath-stat/src/commonMain/tmp/minuit/GradientCalculator.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/HessianGradientCalculator.kt b/kmath-stat/src/commonMain/tmp/minuit/HessianGradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/HessianGradientCalculator.kt rename to kmath-stat/src/commonMain/tmp/minuit/HessianGradientCalculator.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/InitialGradientCalculator.kt b/kmath-stat/src/commonMain/tmp/minuit/InitialGradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/InitialGradientCalculator.kt rename to kmath-stat/src/commonMain/tmp/minuit/InitialGradientCalculator.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINOSResult.kt b/kmath-stat/src/commonMain/tmp/minuit/MINOSResult.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINOSResult.kt rename to kmath-stat/src/commonMain/tmp/minuit/MINOSResult.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITFitter.kt b/kmath-stat/src/commonMain/tmp/minuit/MINUITFitter.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITFitter.kt rename to kmath-stat/src/commonMain/tmp/minuit/MINUITFitter.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITPlugin.kt b/kmath-stat/src/commonMain/tmp/minuit/MINUITPlugin.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITPlugin.kt rename to kmath-stat/src/commonMain/tmp/minuit/MINUITPlugin.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITUtils.kt b/kmath-stat/src/commonMain/tmp/minuit/MINUITUtils.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MINUITUtils.kt rename to kmath-stat/src/commonMain/tmp/minuit/MINUITUtils.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumBuilder.kt b/kmath-stat/src/commonMain/tmp/minuit/MinimumBuilder.kt similarity index 95% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumBuilder.kt rename to kmath-stat/src/commonMain/tmp/minuit/MinimumBuilder.kt index eadeeb91d..7d918c339 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumBuilder.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/MinimumBuilder.kt @@ -15,6 +15,8 @@ */ package ru.inr.mass.minuit +import space.kscience.kmath.optimization.minuit.MinimumSeed + /** * * @version $Id$ diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumError.kt b/kmath-stat/src/commonMain/tmp/minuit/MinimumError.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumError.kt rename to kmath-stat/src/commonMain/tmp/minuit/MinimumError.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumErrorUpdator.kt b/kmath-stat/src/commonMain/tmp/minuit/MinimumErrorUpdator.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumErrorUpdator.kt rename to kmath-stat/src/commonMain/tmp/minuit/MinimumErrorUpdator.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumParameters.kt b/kmath-stat/src/commonMain/tmp/minuit/MinimumParameters.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumParameters.kt rename to kmath-stat/src/commonMain/tmp/minuit/MinimumParameters.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeed.kt b/kmath-stat/src/commonMain/tmp/minuit/MinimumSeed.kt similarity index 95% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeed.kt rename to kmath-stat/src/commonMain/tmp/minuit/MinimumSeed.kt index aef672bb7..53a78da75 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeed.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/MinimumSeed.kt @@ -13,7 +13,9 @@ * See the License for the specific language governing permissions and * limitations under the License. */ -package ru.inr.mass.minuit +package space.kscience.kmath.optimization.minuit + +import ru.inr.mass.minuit.* /** * diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeedGenerator.kt b/kmath-stat/src/commonMain/tmp/minuit/MinimumSeedGenerator.kt similarity index 95% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeedGenerator.kt rename to kmath-stat/src/commonMain/tmp/minuit/MinimumSeedGenerator.kt index bd04c1a45..e152559b5 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumSeedGenerator.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/MinimumSeedGenerator.kt @@ -15,6 +15,8 @@ */ package ru.inr.mass.minuit +import space.kscience.kmath.optimization.minuit.MinimumSeed + /** * base class for seed generators (starting values); the seed generator prepares * initial starting values from the input (MnUserParameterState) for the diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumState.kt b/kmath-stat/src/commonMain/tmp/minuit/MinimumState.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinimumState.kt rename to kmath-stat/src/commonMain/tmp/minuit/MinimumState.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinosError.kt b/kmath-stat/src/commonMain/tmp/minuit/MinosError.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinosError.kt rename to kmath-stat/src/commonMain/tmp/minuit/MinosError.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinuitParameter.kt b/kmath-stat/src/commonMain/tmp/minuit/MinuitParameter.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MinuitParameter.kt rename to kmath-stat/src/commonMain/tmp/minuit/MinuitParameter.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnAlgebraicSymMatrix.kt b/kmath-stat/src/commonMain/tmp/minuit/MnAlgebraicSymMatrix.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnAlgebraicSymMatrix.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnAlgebraicSymMatrix.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnApplication.kt b/kmath-stat/src/commonMain/tmp/minuit/MnApplication.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnApplication.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnApplication.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnContours.kt b/kmath-stat/src/commonMain/tmp/minuit/MnContours.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnContours.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnContours.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCovarianceSqueeze.kt b/kmath-stat/src/commonMain/tmp/minuit/MnCovarianceSqueeze.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCovarianceSqueeze.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnCovarianceSqueeze.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCross.kt b/kmath-stat/src/commonMain/tmp/minuit/MnCross.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnCross.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnCross.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnEigen.kt b/kmath-stat/src/commonMain/tmp/minuit/MnEigen.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnEigen.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnEigen.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFcn.kt b/kmath-stat/src/commonMain/tmp/minuit/MnFcn.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFcn.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnFcn.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFunctionCross.kt b/kmath-stat/src/commonMain/tmp/minuit/MnFunctionCross.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnFunctionCross.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnFunctionCross.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnGlobalCorrelationCoeff.kt b/kmath-stat/src/commonMain/tmp/minuit/MnGlobalCorrelationCoeff.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnGlobalCorrelationCoeff.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnGlobalCorrelationCoeff.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnHesse.kt b/kmath-stat/src/commonMain/tmp/minuit/MnHesse.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnHesse.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnHesse.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnLineSearch.kt b/kmath-stat/src/commonMain/tmp/minuit/MnLineSearch.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnLineSearch.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnLineSearch.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMachinePrecision.kt b/kmath-stat/src/commonMain/tmp/minuit/MnMachinePrecision.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMachinePrecision.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnMachinePrecision.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMigrad.kt b/kmath-stat/src/commonMain/tmp/minuit/MnMigrad.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMigrad.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnMigrad.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinimize.kt b/kmath-stat/src/commonMain/tmp/minuit/MnMinimize.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinimize.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnMinimize.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinos.kt b/kmath-stat/src/commonMain/tmp/minuit/MnMinos.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnMinos.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnMinos.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabola.kt b/kmath-stat/src/commonMain/tmp/minuit/MnParabola.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabola.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnParabola.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaFactory.kt b/kmath-stat/src/commonMain/tmp/minuit/MnParabolaFactory.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaFactory.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnParabolaFactory.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaPoint.kt b/kmath-stat/src/commonMain/tmp/minuit/MnParabolaPoint.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParabolaPoint.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnParabolaPoint.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParameterScan.kt b/kmath-stat/src/commonMain/tmp/minuit/MnParameterScan.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnParameterScan.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnParameterScan.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPlot.kt b/kmath-stat/src/commonMain/tmp/minuit/MnPlot.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPlot.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnPlot.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPosDef.kt b/kmath-stat/src/commonMain/tmp/minuit/MnPosDef.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPosDef.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnPosDef.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPrint.kt b/kmath-stat/src/commonMain/tmp/minuit/MnPrint.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnPrint.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnPrint.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnScan.kt b/kmath-stat/src/commonMain/tmp/minuit/MnScan.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnScan.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnScan.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSeedGenerator.kt b/kmath-stat/src/commonMain/tmp/minuit/MnSeedGenerator.kt similarity index 98% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSeedGenerator.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnSeedGenerator.kt index cc3f9547e..a42edf4f1 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSeedGenerator.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/MnSeedGenerator.kt @@ -17,6 +17,7 @@ package ru.inr.mass.minuit import space.kscience.kmath.optimization.minuit.MINUITPlugin import ru.inr.mass.minuit.* +import space.kscience.kmath.optimization.minuit.MinimumSeed /** * diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSimplex.kt b/kmath-stat/src/commonMain/tmp/minuit/MnSimplex.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnSimplex.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnSimplex.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnStrategy.kt b/kmath-stat/src/commonMain/tmp/minuit/MnStrategy.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnStrategy.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnStrategy.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserCovariance.kt b/kmath-stat/src/commonMain/tmp/minuit/MnUserCovariance.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserCovariance.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnUserCovariance.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserFcn.kt b/kmath-stat/src/commonMain/tmp/minuit/MnUserFcn.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserFcn.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnUserFcn.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameterState.kt b/kmath-stat/src/commonMain/tmp/minuit/MnUserParameterState.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameterState.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnUserParameterState.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameters.kt b/kmath-stat/src/commonMain/tmp/minuit/MnUserParameters.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserParameters.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnUserParameters.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserTransformation.kt b/kmath-stat/src/commonMain/tmp/minuit/MnUserTransformation.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUserTransformation.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnUserTransformation.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUtils.kt b/kmath-stat/src/commonMain/tmp/minuit/MnUtils.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/MnUtils.kt rename to kmath-stat/src/commonMain/tmp/minuit/MnUtils.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ModularFunctionMinimizer.kt b/kmath-stat/src/commonMain/tmp/minuit/ModularFunctionMinimizer.kt similarity index 97% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ModularFunctionMinimizer.kt rename to kmath-stat/src/commonMain/tmp/minuit/ModularFunctionMinimizer.kt index f234bcd48..84130d24f 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ModularFunctionMinimizer.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/ModularFunctionMinimizer.kt @@ -17,6 +17,7 @@ package ru.inr.mass.minuit import ru.inr.mass.maths.MultiFunction import ru.inr.mass.minuit.* +import space.kscience.kmath.optimization.minuit.MinimumSeed /** * diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/NegativeG2LineSearch.kt b/kmath-stat/src/commonMain/tmp/minuit/NegativeG2LineSearch.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/NegativeG2LineSearch.kt rename to kmath-stat/src/commonMain/tmp/minuit/NegativeG2LineSearch.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Numerical2PGradientCalculator.kt b/kmath-stat/src/commonMain/tmp/minuit/Numerical2PGradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/Numerical2PGradientCalculator.kt rename to kmath-stat/src/commonMain/tmp/minuit/Numerical2PGradientCalculator.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanBuilder.kt b/kmath-stat/src/commonMain/tmp/minuit/ScanBuilder.kt similarity index 97% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanBuilder.kt rename to kmath-stat/src/commonMain/tmp/minuit/ScanBuilder.kt index b7e773924..57f910a26 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanBuilder.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/ScanBuilder.kt @@ -17,6 +17,7 @@ package ru.inr.mass.minuit import org.apache.commons.math3.linear.ArrayRealVector import ru.inr.mass.minuit.* +import space.kscience.kmath.optimization.minuit.MinimumSeed /** * Performs a minimization using the simplex method of Nelder and Mead (ref. diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanMinimizer.kt b/kmath-stat/src/commonMain/tmp/minuit/ScanMinimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/ScanMinimizer.kt rename to kmath-stat/src/commonMain/tmp/minuit/ScanMinimizer.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexBuilder.kt b/kmath-stat/src/commonMain/tmp/minuit/SimplexBuilder.kt similarity index 99% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexBuilder.kt rename to kmath-stat/src/commonMain/tmp/minuit/SimplexBuilder.kt index 8441a4177..0b10155ff 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexBuilder.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/SimplexBuilder.kt @@ -17,6 +17,7 @@ package ru.inr.mass.minuit import space.kscience.kmath.optimization.minuit.MINUITPlugin import ru.inr.mass.minuit.* +import space.kscience.kmath.optimization.minuit.MinimumSeed /** * diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexMinimizer.kt b/kmath-stat/src/commonMain/tmp/minuit/SimplexMinimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexMinimizer.kt rename to kmath-stat/src/commonMain/tmp/minuit/SimplexMinimizer.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexParameters.kt b/kmath-stat/src/commonMain/tmp/minuit/SimplexParameters.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexParameters.kt rename to kmath-stat/src/commonMain/tmp/minuit/SimplexParameters.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexSeedGenerator.kt b/kmath-stat/src/commonMain/tmp/minuit/SimplexSeedGenerator.kt similarity index 97% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexSeedGenerator.kt rename to kmath-stat/src/commonMain/tmp/minuit/SimplexSeedGenerator.kt index e5025ff3d..577545fc3 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SimplexSeedGenerator.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/SimplexSeedGenerator.kt @@ -17,6 +17,7 @@ package ru.inr.mass.minuit import org.apache.commons.math3.linear.ArrayRealVector import ru.inr.mass.minuit.* +import space.kscience.kmath.optimization.minuit.MinimumSeed /** * diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SinParameterTransformation.kt b/kmath-stat/src/commonMain/tmp/minuit/SinParameterTransformation.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SinParameterTransformation.kt rename to kmath-stat/src/commonMain/tmp/minuit/SinParameterTransformation.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtLowParameterTransformation.kt b/kmath-stat/src/commonMain/tmp/minuit/SqrtLowParameterTransformation.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtLowParameterTransformation.kt rename to kmath-stat/src/commonMain/tmp/minuit/SqrtLowParameterTransformation.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtUpParameterTransformation.kt b/kmath-stat/src/commonMain/tmp/minuit/SqrtUpParameterTransformation.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/SqrtUpParameterTransformation.kt rename to kmath-stat/src/commonMain/tmp/minuit/SqrtUpParameterTransformation.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricBuilder.kt b/kmath-stat/src/commonMain/tmp/minuit/VariableMetricBuilder.kt similarity index 98% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricBuilder.kt rename to kmath-stat/src/commonMain/tmp/minuit/VariableMetricBuilder.kt index 8362c5e7e..edc6783b6 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricBuilder.kt +++ b/kmath-stat/src/commonMain/tmp/minuit/VariableMetricBuilder.kt @@ -17,6 +17,7 @@ package ru.inr.mass.minuit import space.kscience.kmath.optimization.minuit.MINUITPlugin import ru.inr.mass.minuit.* +import space.kscience.kmath.optimization.minuit.MinimumSeed /** * diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricEDMEstimator.kt b/kmath-stat/src/commonMain/tmp/minuit/VariableMetricEDMEstimator.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricEDMEstimator.kt rename to kmath-stat/src/commonMain/tmp/minuit/VariableMetricEDMEstimator.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricMinimizer.kt b/kmath-stat/src/commonMain/tmp/minuit/VariableMetricMinimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/VariableMetricMinimizer.kt rename to kmath-stat/src/commonMain/tmp/minuit/VariableMetricMinimizer.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/package-info.kt b/kmath-stat/src/commonMain/tmp/minuit/package-info.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/minuit/package-info.kt rename to kmath-stat/src/commonMain/tmp/minuit/package-info.kt From 7d0eff74f6b48f26d16343f5a0c4e9d38fe73e68 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Tue, 8 Jun 2021 20:39:47 +0700 Subject: [PATCH 067/132] Fix shield README.md, fix build --- README.md | 2 +- docs/templates/README-TEMPLATE.md | 2 +- kmath-symja/build.gradle.kts | 18 ++++++++++++++++-- 3 files changed, 18 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 9117582ac..dfb9cba9c 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ [![DOI](https://zenodo.org/badge/129486382.svg)](https://zenodo.org/badge/latestdoi/129486382) ![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg) [![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22) -[![Space](https://img.shields.io/maven-metadata/v?label=Space&metadataUrl=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fkscience%2Fkmath%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/) +[![Space](https://img.shields.io/maven-metadata/v?label=Space&metadataUrl=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fspace%2Fkscience%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/) # KMath diff --git a/docs/templates/README-TEMPLATE.md b/docs/templates/README-TEMPLATE.md index 6bb1e9085..c981cb0bd 100644 --- a/docs/templates/README-TEMPLATE.md +++ b/docs/templates/README-TEMPLATE.md @@ -2,7 +2,7 @@ [![DOI](https://zenodo.org/badge/129486382.svg)](https://zenodo.org/badge/latestdoi/129486382) ![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg) [![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22) -[![Space](https://img.shields.io/maven-metadata/v?label=Space&metadataUrl=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fkscience%2Fkmath%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/) +[![Space](https://img.shields.io/maven-metadata/v?label=Space&metadataUrl=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fspace%2Fkscience%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/) # KMath diff --git a/kmath-symja/build.gradle.kts b/kmath-symja/build.gradle.kts index c67b42e3f..f305c03b8 100644 --- a/kmath-symja/build.gradle.kts +++ b/kmath-symja/build.gradle.kts @@ -12,12 +12,26 @@ description = "Symja integration module" dependencies { api("org.matheclipse:matheclipse-core:2.0.0-SNAPSHOT") { - // Incorrect transitive dependency org.apfloat:apfloat:1.10.0-SNAPSHOT + // Incorrect transitive dependencies exclude("org.apfloat", "apfloat") + exclude("org.hipparchus", "hipparchus-clustering") + exclude("org.hipparchus", "hipparchus-core") + exclude("org.hipparchus", "hipparchus-fft") + exclude("org.hipparchus", "hipparchus-fitting") + exclude("org.hipparchus", "hipparchus-ode") + exclude("org.hipparchus", "hipparchus-optim") + exclude("org.hipparchus", "hipparchus-stat") } - // Replace for org.apfloat:apfloat:1.10.0-SNAPSHOT + // Replaces for incorrect transitive dependencies api("org.apfloat:apfloat:1.10.0") + api("org.hipparchus:hipparchus-clustering:1.8") + api("org.hipparchus:hipparchus-core:1.8") + api("org.hipparchus:hipparchus-fft:1.8") + api("org.hipparchus:hipparchus-fitting:1.8") + api("org.hipparchus:hipparchus-ode:1.8") + api("org.hipparchus:hipparchus-optim:1.8") + api("org.hipparchus:hipparchus-stat:1.8") api(project(":kmath-core")) testImplementation("org.slf4j:slf4j-simple:1.7.30") From c0ab082d240d64f3476707912ba4aea31ecae6bc Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Tue, 8 Jun 2021 20:53:33 +0700 Subject: [PATCH 068/132] Run build workflow for PRs --- .github/workflows/build.yml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 9a9f04621..98f4d2ec2 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -1,6 +1,9 @@ name: Gradle build -on: [ push ] +on: + push: + pull_request: + types: [opened, edited] jobs: build: From 7b736a7c81391493c48eea54bdb4f263c01b1cb7 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Wed, 9 Jun 2021 21:40:47 +0700 Subject: [PATCH 069/132] Fix README.md again --- README.md | 18 ++++++++++++------ docs/templates/README-TEMPLATE.md | 2 +- kmath-ast/README.md | 6 +++--- kmath-complex/README.md | 6 +++--- kmath-core/README.md | 6 +++--- kmath-ejml/README.md | 6 +++--- kmath-for-real/README.md | 6 +++--- kmath-functions/README.md | 6 +++--- kmath-kotlingrad/README.md | 6 +++--- kmath-nd4j/README.md | 6 +++--- kmath-tensors/README.md | 6 +++--- 11 files changed, 40 insertions(+), 34 deletions(-) diff --git a/README.md b/README.md index dfb9cba9c..7c6f7ea2b 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ [![DOI](https://zenodo.org/badge/129486382.svg)](https://zenodo.org/badge/latestdoi/129486382) ![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg) [![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22) -[![Space](https://img.shields.io/maven-metadata/v?label=Space&metadataUrl=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fspace%2Fkscience%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/) +[![Space](https://img.shields.io/badge/dynamic/xml?color=orange&label=Space&query=//metadata/versioning/latest&url=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fspace%2Fkscience%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/) # KMath @@ -207,7 +207,7 @@ One can still use generic algebras though.

* ### [kmath-kotlingrad](kmath-kotlingrad) -> Functions, integration and interpolation +> > > **Maturity**: EXPERIMENTAL > @@ -218,13 +218,13 @@ One can still use generic algebras though.
* ### [kmath-memory](kmath-memory) -> An API and basic implementation for arranging objects in a continous memory block. +> An API and basic implementation for arranging objects in a continuous memory block. > > **Maturity**: DEVELOPMENT
* ### [kmath-nd4j](kmath-nd4j) -> ND4J NDStructure implementation and according NDAlgebra classes +> > > **Maturity**: EXPERIMENTAL > @@ -241,6 +241,12 @@ One can still use generic algebras though. > **Maturity**: EXPERIMENTAL
+* ### [kmath-symja](kmath-symja) +> +> +> **Maturity**: PROTOTYPE +
+ * ### [kmath-tensors](kmath-tensors) > > @@ -293,8 +299,8 @@ repositories { } dependencies { - api("space.kscience:kmath-core:0.3.0-dev-11") - // api("space.kscience:kmath-core-jvm:0.3.0-dev-11") for jvm-specific version + api("space.kscience:kmath-core:0.3.0-dev-13") + // api("space.kscience:kmath-core-jvm:0.3.0-dev-13") for jvm-specific version } ``` diff --git a/docs/templates/README-TEMPLATE.md b/docs/templates/README-TEMPLATE.md index c981cb0bd..bad11a31a 100644 --- a/docs/templates/README-TEMPLATE.md +++ b/docs/templates/README-TEMPLATE.md @@ -2,7 +2,7 @@ [![DOI](https://zenodo.org/badge/129486382.svg)](https://zenodo.org/badge/latestdoi/129486382) ![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg) [![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22) -[![Space](https://img.shields.io/maven-metadata/v?label=Space&metadataUrl=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fspace%2Fkscience%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/) +[![Space](https://img.shields.io/badge/dynamic/xml?color=orange&label=Space&query=//metadata/versioning/latest&url=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fspace%2Fkscience%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/) # KMath diff --git a/kmath-ast/README.md b/kmath-ast/README.md index b0f2d59e5..2f6b21094 100644 --- a/kmath-ast/README.md +++ b/kmath-ast/README.md @@ -10,7 +10,7 @@ Performance and visualization extensions to MST API. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-13`. **Gradle:** ```gradle @@ -20,7 +20,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-ast:0.3.0-dev-11' + implementation 'space.kscience:kmath-ast:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -31,7 +31,7 @@ repositories { } dependencies { - implementation("space.kscience:kmath-ast:0.3.0-dev-11") + implementation("space.kscience:kmath-ast:0.3.0-dev-13") } ``` diff --git a/kmath-complex/README.md b/kmath-complex/README.md index 04431cf6c..18a83756d 100644 --- a/kmath-complex/README.md +++ b/kmath-complex/README.md @@ -8,7 +8,7 @@ Complex and hypercomplex number systems in KMath. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-complex:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-complex:0.3.0-dev-13`. **Gradle:** ```gradle @@ -18,7 +18,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-complex:0.3.0-dev-11' + implementation 'space.kscience:kmath-complex:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -29,6 +29,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-complex:0.3.0-dev-11") + implementation("space.kscience:kmath-complex:0.3.0-dev-13") } ``` diff --git a/kmath-core/README.md b/kmath-core/README.md index 700eaef38..6ca8c8ef8 100644 --- a/kmath-core/README.md +++ b/kmath-core/README.md @@ -15,7 +15,7 @@ performance calculations to code generation. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-core:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-core:0.3.0-dev-13`. **Gradle:** ```gradle @@ -25,7 +25,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-core:0.3.0-dev-11' + implementation 'space.kscience:kmath-core:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -36,6 +36,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-core:0.3.0-dev-11") + implementation("space.kscience:kmath-core:0.3.0-dev-13") } ``` diff --git a/kmath-ejml/README.md b/kmath-ejml/README.md index 79a28b824..10e7bd606 100644 --- a/kmath-ejml/README.md +++ b/kmath-ejml/README.md @@ -9,7 +9,7 @@ EJML based linear algebra implementation. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-ejml:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-ejml:0.3.0-dev-13`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-ejml:0.3.0-dev-11' + implementation 'space.kscience:kmath-ejml:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -30,6 +30,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-ejml:0.3.0-dev-11") + implementation("space.kscience:kmath-ejml:0.3.0-dev-13") } ``` diff --git a/kmath-for-real/README.md b/kmath-for-real/README.md index 5ca805093..6339782dd 100644 --- a/kmath-for-real/README.md +++ b/kmath-for-real/README.md @@ -9,7 +9,7 @@ Specialization of KMath APIs for Double numbers. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-for-real:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-for-real:0.3.0-dev-13`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-for-real:0.3.0-dev-11' + implementation 'space.kscience:kmath-for-real:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -30,6 +30,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-for-real:0.3.0-dev-11") + implementation("space.kscience:kmath-for-real:0.3.0-dev-13") } ``` diff --git a/kmath-functions/README.md b/kmath-functions/README.md index 2497f7102..77f55528a 100644 --- a/kmath-functions/README.md +++ b/kmath-functions/README.md @@ -11,7 +11,7 @@ Functions and interpolations. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-functions:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-functions:0.3.0-dev-13`. **Gradle:** ```gradle @@ -21,7 +21,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-functions:0.3.0-dev-11' + implementation 'space.kscience:kmath-functions:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -32,6 +32,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-functions:0.3.0-dev-11") + implementation("space.kscience:kmath-functions:0.3.0-dev-13") } ``` diff --git a/kmath-kotlingrad/README.md b/kmath-kotlingrad/README.md index 4393cbf8c..31c7bb819 100644 --- a/kmath-kotlingrad/README.md +++ b/kmath-kotlingrad/README.md @@ -8,7 +8,7 @@ ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-kotlingrad:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-kotlingrad:0.3.0-dev-13`. **Gradle:** ```gradle @@ -18,7 +18,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-kotlingrad:0.3.0-dev-11' + implementation 'space.kscience:kmath-kotlingrad:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -29,6 +29,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-kotlingrad:0.3.0-dev-11") + implementation("space.kscience:kmath-kotlingrad:0.3.0-dev-13") } ``` diff --git a/kmath-nd4j/README.md b/kmath-nd4j/README.md index 6408be13b..1c945f06a 100644 --- a/kmath-nd4j/README.md +++ b/kmath-nd4j/README.md @@ -9,7 +9,7 @@ ND4J based implementations of KMath abstractions. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-nd4j:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-nd4j:0.3.0-dev-13`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-nd4j:0.3.0-dev-11' + implementation 'space.kscience:kmath-nd4j:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -30,7 +30,7 @@ repositories { } dependencies { - implementation("space.kscience:kmath-nd4j:0.3.0-dev-11") + implementation("space.kscience:kmath-nd4j:0.3.0-dev-13") } ``` diff --git a/kmath-tensors/README.md b/kmath-tensors/README.md index 75de2bf35..dd21a9f2f 100644 --- a/kmath-tensors/README.md +++ b/kmath-tensors/README.md @@ -9,7 +9,7 @@ Common linear algebra operations on tensors. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-tensors:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-tensors:0.3.0-dev-13`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-tensors:0.3.0-dev-11' + implementation 'space.kscience:kmath-tensors:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -30,6 +30,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-tensors:0.3.0-dev-11") + implementation("space.kscience:kmath-tensors:0.3.0-dev-13") } ``` From 46bf66c8ee28f6c3fa1645e19001b878cef60b7e Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Wed, 26 May 2021 20:24:29 +0700 Subject: [PATCH 070/132] Add justCalculate benchmark, some minor refactorings --- .../ExpressionsInterpretersBenchmark.kt | 46 ++++++++++++++--- .../space/kscience/kmath/ast/expressions.kt | 2 - kmath-ast/README.md | 15 +++--- kmath-ast/docs/README-TEMPLATE.md | 9 ++-- .../TestCompilerConsistencyWithInterpreter.kt | 4 +- .../kmath/ast/TestCompilerOperations.kt | 6 +-- .../kmath/ast/TestCompilerVariables.kt | 4 +- .../kmath/wasm/internal/WasmBuilder.kt | 6 +-- .../kscience/kmath/ast/TestExecutionTime.kt | 51 +++++++++++++++++-- .../kscience/kmath/wasm/TestWasmSpecific.kt | 4 +- .../kmath/asm/internal/codegenUtils.kt | 2 +- .../kmath/kotlingrad/AdaptingTests.kt | 7 ++- 12 files changed, 113 insertions(+), 43 deletions(-) diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt index 15cd14399..0294f924b 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt @@ -14,22 +14,51 @@ import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke +import kotlin.math.sin import kotlin.random.Random @State(Scope.Benchmark) internal class ExpressionsInterpretersBenchmark { + /** + * Benchmark case for [Expression] created with [expressionInExtendedField]. + */ @Benchmark fun functionalExpression(blackhole: Blackhole) = invokeAndSum(functional, blackhole) + /** + * Benchmark case for [Expression] created with [toExpression]. + */ @Benchmark fun mstExpression(blackhole: Blackhole) = invokeAndSum(mst, blackhole) + /** + * Benchmark case for [Expression] created with [compileToExpression]. + */ @Benchmark fun asmExpression(blackhole: Blackhole) = invokeAndSum(asm, blackhole) + /** + * Benchmark case for [Expression] implemented manually with `kotlin.math` functions. + */ @Benchmark fun rawExpression(blackhole: Blackhole) = invokeAndSum(raw, blackhole) + /** + * Benchmark case for direct computation w/o [Expression]. + */ + @Benchmark + fun justCalculate(blackhole: Blackhole) { + val random = Random(0) + var sum = 0.0 + + repeat(times) { + val x = random.nextDouble() + sum += x * 2.0 + 2.0 / x - 16.0 / sin(x) + } + + blackhole.consume(sum) + } + private fun invokeAndSum(expr: Expression, blackhole: Blackhole) { val random = Random(0) var sum = 0.0 @@ -42,23 +71,24 @@ internal class ExpressionsInterpretersBenchmark { } private companion object { - private val x: Symbol by symbol - private val algebra: DoubleField = DoubleField + private val x by symbol + private val algebra = DoubleField private const val times = 1_000_000 - private val functional: Expression = DoubleField.expressionInExtendedField { + private val functional = DoubleField.expressionInExtendedField { bindSymbol(x) * number(2.0) + number(2.0) / bindSymbol(x) - number(16.0) / sin(bindSymbol(x)) } private val node = MstExtendedField { - bindSymbol(x) * 2.0 + number(2.0) / bindSymbol(x) - number(16.0) / sin(bindSymbol(x)) + x * 2.0 + number(2.0) / x - number(16.0) / sin(x) } - private val mst: Expression = node.toExpression(DoubleField) - private val asm: Expression = node.compileToExpression(DoubleField) + private val mst = node.toExpression(DoubleField) + private val asm = node.compileToExpression(DoubleField) - private val raw: Expression = Expression { args -> - args.getValue(x) * 2.0 + 2.0 / args.getValue(x) - 16.0 / kotlin.math.sin(args.getValue(x)) + private val raw = Expression { args -> + val x = args[x]!! + x * 2.0 + 2.0 / x - 16.0 / sin(x) } } } diff --git a/examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt b/examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt index d5a82590f..96c9856cf 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt @@ -9,12 +9,10 @@ import space.kscience.kmath.expressions.MstField import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.interpret import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke fun main() { val expr = MstField { - val x = bindSymbol(x) x * 2.0 + number(2.0) / x - 16.0 } diff --git a/kmath-ast/README.md b/kmath-ast/README.md index b0f2d59e5..026c5a625 100644 --- a/kmath-ast/README.md +++ b/kmath-ast/README.md @@ -10,7 +10,7 @@ Performance and visualization extensions to MST API. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-11`. +The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-13`. **Gradle:** ```gradle @@ -20,7 +20,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-ast:0.3.0-dev-11' + implementation 'space.kscience:kmath-ast:0.3.0-dev-13' } ``` **Gradle Kotlin DSL:** @@ -31,7 +31,7 @@ repositories { } dependencies { - implementation("space.kscience:kmath-ast:0.3.0-dev-11") + implementation("space.kscience:kmath-ast:0.3.0-dev-13") } ``` @@ -45,11 +45,12 @@ special implementation of `Expression` with implemented `invoke` function. For example, the following builder: ```kotlin +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.* import space.kscience.kmath.asm.* -MstField { bindSymbol("x") + 2 }.compileToExpression(DoubleField) +MstField { x + 2 }.compileToExpression(DoubleField) ``` ... leads to generation of bytecode, which can be decompiled to the following Java class: @@ -89,11 +90,12 @@ public final class AsmCompiledExpression_45045_0 implements Expression { A similar feature is also available on JS. ```kotlin +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.* import space.kscience.kmath.estree.* -MstField { bindSymbol("x") + 2 }.compileToExpression(DoubleField) +MstField { x + 2 }.compileToExpression(DoubleField) ``` The code above returns expression implemented with such a JS function: @@ -108,11 +110,12 @@ JS also supports very experimental expression optimization with [WebAssembly](ht Currently, only expressions inside `DoubleField` and `IntRing` are supported. ```kotlin +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.* import space.kscience.kmath.wasm.* -MstField { bindSymbol("x") + 2 }.compileToExpression(DoubleField) +MstField { x + 2 }.compileToExpression(DoubleField) ``` An example of emitted Wasm IR in the form of WAT: diff --git a/kmath-ast/docs/README-TEMPLATE.md b/kmath-ast/docs/README-TEMPLATE.md index 80ea31642..b90f8ff08 100644 --- a/kmath-ast/docs/README-TEMPLATE.md +++ b/kmath-ast/docs/README-TEMPLATE.md @@ -16,11 +16,12 @@ special implementation of `Expression` with implemented `invoke` function. For example, the following builder: ```kotlin +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.* import space.kscience.kmath.asm.* -MstField { bindSymbol("x") + 2 }.compileToExpression(DoubleField) +MstField { x + 2 }.compileToExpression(DoubleField) ``` ... leads to generation of bytecode, which can be decompiled to the following Java class: @@ -60,11 +61,12 @@ public final class AsmCompiledExpression_45045_0 implements Expression { A similar feature is also available on JS. ```kotlin +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.* import space.kscience.kmath.estree.* -MstField { bindSymbol("x") + 2 }.compileToExpression(DoubleField) +MstField { x + 2 }.compileToExpression(DoubleField) ``` The code above returns expression implemented with such a JS function: @@ -79,11 +81,12 @@ JS also supports very experimental expression optimization with [WebAssembly](ht Currently, only expressions inside `DoubleField` and `IntRing` are supported. ```kotlin +import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.* import space.kscience.kmath.wasm.* -MstField { bindSymbol("x") + 2 }.compileToExpression(DoubleField) +MstField { x + 2 }.compileToExpression(DoubleField) ``` An example of emitted Wasm IR in the form of WAT: diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt index 6209661b3..3116466e6 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt @@ -22,7 +22,7 @@ internal class TestCompilerConsistencyWithInterpreter { val mst = MstRing { binaryOperationFunction("+")( unaryOperationFunction("+")( - (bindSymbol(x) - (2.toByte() + (scale( + (x - (2.toByte() + (scale( add(number(1), number(1)), 2.0, ) + 1.toByte()))) * 3.0 - 1.toByte() @@ -42,7 +42,7 @@ internal class TestCompilerConsistencyWithInterpreter { fun doubleField() = runCompilerTest { val mst = MstField { +(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")( - (3.0 - (bindSymbol(x) + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0 + (3.0 - (x + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0 + number(1), number(1) / 2 + number(2.0) * one, ) + zero diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt index 073a03f14..f869efd62 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt @@ -47,19 +47,19 @@ internal class TestCompilerOperations { @Test fun testSubtract() = runCompilerTest { - val expr = MstExtendedField { bindSymbol(x) - bindSymbol(x) }.compileToExpression(DoubleField) + val expr = MstExtendedField { x - x }.compileToExpression(DoubleField) assertEquals(0.0, expr(x to 2.0)) } @Test fun testDivide() = runCompilerTest { - val expr = MstExtendedField { bindSymbol(x) / bindSymbol(x) }.compileToExpression(DoubleField) + val expr = MstExtendedField { x / x }.compileToExpression(DoubleField) assertEquals(1.0, expr(x to 2.0)) } @Test fun testPower() = runCompilerTest { - val expr = MstExtendedField { bindSymbol(x) pow 2 }.compileToExpression(DoubleField) + val expr = MstExtendedField { x pow 2 }.compileToExpression(DoubleField) assertEquals(4.0, expr(x to 2.0)) } } diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt index dcc15b311..bed5bc7fa 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt @@ -18,13 +18,13 @@ import kotlin.test.assertFailsWith internal class TestCompilerVariables { @Test fun testVariable() = runCompilerTest { - val expr = MstRing { bindSymbol(x) }.compileToExpression(IntRing) + val expr = MstRing { x }.compileToExpression(IntRing) assertEquals(1, expr(x to 1)) } @Test fun testUndefinedVariableFails() = runCompilerTest { - val expr = MstRing { bindSymbol(x) }.compileToExpression(IntRing) + val expr = MstRing { x }.compileToExpression(IntRing) assertFailsWith { expr() } } } diff --git a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt index 95ace1bad..c89ad83c4 100644 --- a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt +++ b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt @@ -27,11 +27,7 @@ internal sealed class WasmBuilder( lateinit var ctx: BinaryenModule open fun visitSymbolic(mst: Symbol): ExpressionRef { - try { - algebra.bindSymbol(mst) - } catch (ignored: Throwable) { - null - }?.let { return visitNumeric(Numeric(it)) } + algebra.bindSymbolOrNull(mst)?.let { return visitNumeric(Numeric(it)) } var idx = keys.indexOf(mst) diff --git a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt index 6cb378182..d0e8128b4 100644 --- a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt +++ b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt @@ -7,7 +7,6 @@ package space.kscience.kmath.ast import space.kscience.kmath.expressions.* import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke import kotlin.math.sin @@ -17,18 +16,19 @@ import kotlin.time.measureTime import space.kscience.kmath.estree.compileToExpression as estreeCompileToExpression import space.kscience.kmath.wasm.compileToExpression as wasmCompileToExpression +// TODO move to benchmarks when https://github.com/Kotlin/kotlinx-benchmark/pull/38 or similar feature is merged internal class TestExecutionTime { private companion object { private const val times = 1_000_000 private val x by symbol - private val algebra: ExtendedField = DoubleField + private val algebra = DoubleField private val functional = DoubleField.expressionInExtendedField { bindSymbol(x) * const(2.0) + const(2.0) / bindSymbol(x) - const(16.0) / sin(bindSymbol(x)) } private val node = MstExtendedField { - bindSymbol(x) * number(2.0) + number(2.0) / bindSymbol(x) - number(16.0) / sin(bindSymbol(x)) + x * number(2.0) + number(2.0) / x - number(16.0) / sin(x) } private val mst = node.toExpression(DoubleField) @@ -43,7 +43,13 @@ internal class TestExecutionTime { // }; private val raw = Expression { args -> - args.getValue(x) * 2.0 + 2.0 / args.getValue(x) - 16.0 / sin(args.getValue(x)) + val x = args[x]!! + x * 2.0 + 2.0 / x - 16.0 / sin(x) + } + + private val justCalculate = { args: dynamic -> + val x = args[x].unsafeCast() + x * 2.0 + 2.0 / x - 16.0 / sin(x) } } @@ -51,21 +57,56 @@ internal class TestExecutionTime { println(name) val rng = Random(0) var sum = 0.0 - measureTime { repeat(times) { sum += expr(x to rng.nextDouble()) } }.also(::println) + measureTime { + repeat(times) { sum += expr(x to rng.nextDouble()) } + }.also(::println) } + /** + * [Expression] created with [expressionInExtendedField]. + */ @Test fun functionalExpression() = invokeAndSum("functional", functional) + /** + * [Expression] created with [mstExpression]. + */ @Test fun mstExpression() = invokeAndSum("mst", mst) + /** + * [Expression] created with [wasmCompileToExpression]. + */ @Test fun wasmExpression() = invokeAndSum("wasm", wasm) + /** + * [Expression] created with [estreeCompileToExpression]. + */ @Test fun estreeExpression() = invokeAndSum("estree", wasm) + /** + * [Expression] implemented manually with `kotlin.math`. + */ @Test fun rawExpression() = invokeAndSum("raw", raw) + + /** + * Direct computation w/o [Expression]. + */ + @Test + fun justCalculateExpression() { + println("justCalculate") + val rng = Random(0) + var sum = 0.0 + measureTime { + repeat(times) { + val arg = rng.nextDouble() + val o = js("{}") + o["x"] = arg + sum += justCalculate(o) + } + }.also(::println) + } } diff --git a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt index abdf865c7..45776c191 100644 --- a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt +++ b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt @@ -31,7 +31,7 @@ internal class TestWasmSpecific { @Test fun argsPassing() { - val res = MstExtendedField { bindSymbol(y) + bindSymbol(x).pow(10) }.compile( + val res = MstExtendedField { y + x.pow(10) }.compile( DoubleField, x to 2.0, y to 100000000.0, @@ -42,7 +42,7 @@ internal class TestWasmSpecific { @Test fun powFunction() { - val expr = MstExtendedField { bindSymbol(x).pow(1.0 / 6.0) }.compileToExpression(DoubleField) + val expr = MstExtendedField { x.pow(1.0 / 6.0) }.compileToExpression(DoubleField) assertEquals(0.9730585187140817, expr(x to 0.8488554755054833)) } diff --git a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt index cfac59847..a84248f63 100644 --- a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt +++ b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt @@ -63,7 +63,7 @@ internal fun MethodVisitor.label(): Label = Label().also(::visitLabel) * @author Iaroslav Postovalov */ internal tailrec fun buildName(mst: MST, collision: Int = 0): String { - val name = "kscience.kmath.asm.generated.AsmCompiledExpression_${mst.hashCode()}_$collision" + val name = "space.kscience.kmath.asm.generated.AsmCompiledExpression_${mst.hashCode()}_$collision" try { Class.forName(name) diff --git a/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt b/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt index 57fe2411c..9378adfea 100644 --- a/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt +++ b/kmath-kotlingrad/src/test/kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt @@ -20,8 +20,7 @@ import kotlin.test.fail internal class AdaptingTests { @Test fun symbol() { - val c1 = MstNumericAlgebra.bindSymbol(x.identity) - assertEquals(x.identity, c1.toSVar>().name) + assertEquals(x.identity, x.toSVar>().name) val c2 = "kitten".parseMath().toSFun>() if (c2 is SVar) assertTrue(c2.name == "kitten") else fail() } @@ -46,7 +45,7 @@ internal class AdaptingTests { @Test fun simpleFunctionDerivative() { - val xSVar = MstNumericAlgebra.bindSymbol(x.identity).toSVar>() + val xSVar = x.toSVar>() val quadratic = "x^2-4*x-44".parseMath().toSFun>() val actualDerivative = quadratic.d(xSVar).toMst().compileToExpression(DoubleField) val expectedDerivative = "2*x-4".parseMath().compileToExpression(DoubleField) @@ -55,7 +54,7 @@ internal class AdaptingTests { @Test fun moreComplexDerivative() { - val xSVar = MstNumericAlgebra.bindSymbol(x.identity).toSVar>() + val xSVar = x.toSVar>() val composition = "-sqrt(sin(x^2)-cos(x)^2-16*x)".parseMath().toSFun>() val actualDerivative = composition.d(xSVar).toMst().compileToExpression(DoubleField) From 2dff15c5aa2afe2ce99edfe8ae0fe4dc1db64087 Mon Sep 17 00:00:00 2001 From: therealansh Date: Thu, 3 Jun 2021 01:14:19 +0530 Subject: [PATCH 071/132] integrate: Jafama + KMath --- kmath-jafama/build.gradle.kts | 21 + .../kscience/kmath/jafama/CmnFastMath.java | 2112 ++++++++++++ .../kscience/kmath/jafama/DoubleWrapper.java | 13 + .../space/kscience/kmath/jafama/FastMath.java | 2986 ++++++++++++++++ .../kscience/kmath/jafama/IntWrapper.java | 13 + .../kscience/kmath/jafama/KMathJafama.kt | 102 + .../kscience/kmath/jafama/NumbersUtils.java | 2647 +++++++++++++++ .../kscience/kmath/jafama/StrictFastMath.java | 2998 +++++++++++++++++ settings.gradle.kts | 1 + 9 files changed, 10893 insertions(+) create mode 100644 kmath-jafama/build.gradle.kts create mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/CmnFastMath.java create mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/DoubleWrapper.java create mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/FastMath.java create mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/IntWrapper.java create mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt create mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/NumbersUtils.java create mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/StrictFastMath.java diff --git a/kmath-jafama/build.gradle.kts b/kmath-jafama/build.gradle.kts new file mode 100644 index 000000000..22d50f89c --- /dev/null +++ b/kmath-jafama/build.gradle.kts @@ -0,0 +1,21 @@ +plugins { + id("ru.mipt.npm.gradle.jvm") +} + +dependencies { + api(project(":kmath-ast")) + api(project(":kmath-complex")) + api(project(":kmath-for-real")) +} + +kscience{ + useHtml() +} + +readme { + maturity = ru.mipt.npm.gradle.Maturity.PROTOTYPE +} + +kotlin.sourceSets.all { + languageSettings.useExperimentalAnnotation("space.kscience.kmath.misc.UnstableKMathAPI") +} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/CmnFastMath.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/CmnFastMath.java new file mode 100644 index 000000000..0abc5d95d --- /dev/null +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/CmnFastMath.java @@ -0,0 +1,2112 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.jafama; + +/** + * Stuffs for FastMath and StrictFastMath. + */ +abstract class CmnFastMath { + + /* + * For trigonometric functions, use of look-up tables and Taylor-Lagrange formula + * with 4 derivatives (more take longer to compute and don't add much accuracy, + * less require larger tables (which use more memory, take more time to initialize, + * and are slower to access (at least on the machine they were developed on))). + * + * For angles reduction of cos/sin/tan functions: + * - for small values, instead of reducing angles, and then computing the best index + * for look-up tables, we compute this index right away, and use it for reduction, + * - for large values, treatments derived from fdlibm package are used, as done in + * java.lang.Math. They are faster but still "slow", so if you work with + * large numbers and need speed over accuracy for them, you might want to use + * normalizeXXXFast treatments before your function, or modify cos/sin/tan + * so that they call the fast normalization treatments instead of the accurate ones. + * NB: If an angle is huge (like PI*1e20), in double precision format its last digits + * are zeros, which most likely is not the case for the intended value, and doing + * an accurate reduction on a very inaccurate value is most likely pointless. + * But it gives some sort of coherence that could be needed in some cases. + * + * Multiplication on double appears to be about as fast (or not much slower) than call + * to [], and regrouping some doubles in a private class, to use + * index only once, does not seem to speed things up, so: + * - for uniformly tabulated values, to retrieve the parameter corresponding to + * an index, we recompute it rather than using an array to store it, + * - for cos/sin, we recompute derivatives divided by (multiplied by inverse of) + * factorial each time, rather than storing them in arrays. + * + * Lengths of look-up tables are usually of the form 2^n+1, for their values to be + * of the form ( * k/2^n, k in 0 .. 2^n), so that particular values + * (PI/2, etc.) are "exactly" computed, as well as for other reasons. + * + * Tables are put in specific inner classes, to be lazily initialized. + * Always doing strict tables initialization, even if StrictFastMath delegates + * to StrictMath and doesn't use tables, which makes tables initialization a bit + * slower but code simpler. + * Using redefined pure Java treatments during tables initialization, + * instead of Math or StrictMath ones (even asin(double)), can be very slow, + * because class loading is likely not to be optimized. + * + * Most math treatments I could find on the web, including "fast" ones, + * usually take care of special cases (NaN, etc.) at the beginning, and + * then deal with the general case, which adds a useless overhead for the + * general (and common) case. In this class, special cases are only dealt + * with when needed, and if the general case does not already handle them. + */ + + /* + * Regarding strictfp-ness: + * + * Switching from/to strictfp has some overhead, so we try to only + * strictfp-ize when needed (or when clueless). + * Compile-time constants are computed in a FP-strict way, so no need + * to make this whole class strictfp. + */ + + //-------------------------------------------------------------------------- + // CONFIGURATION + //-------------------------------------------------------------------------- + + /* + * FastMath + */ + + static final boolean FM_USE_JDK_MATH = getBooleanProperty("jafama.usejdk", false); + + /** + * Used for both FastMath.log(double) and FastMath.log10(double). + */ + static final boolean FM_USE_REDEFINED_LOG = getBooleanProperty("jafama.fastlog", false); + + static final boolean FM_USE_REDEFINED_SQRT = getBooleanProperty("jafama.fastsqrt", false); + + /** + * Set it to true if FastMath.sqrt(double) is slow + * (more tables, but less calls to FastMath.sqrt(double)). + */ + static final boolean FM_USE_POWTABS_FOR_ASIN = false; + + /* + * StrictFastMath + */ + + static final boolean SFM_USE_JDK_MATH = getBooleanProperty("jafama.strict.usejdk", false); + + /** + * Used for both StrictFastMath.log(double) and StrictFastMath.log10(double). + * True by default because the StrictMath implementations can be slow. + */ + static final boolean SFM_USE_REDEFINED_LOG = getBooleanProperty("jafama.strict.fastlog", true); + + static final boolean SFM_USE_REDEFINED_SQRT = getBooleanProperty("jafama.strict.fastsqrt", false); + + /** + * Set it to true if StrictFastMath.sqrt(double) is slow + * (more tables, but less calls to StrictFastMath.sqrt(double)). + */ + static final boolean SFM_USE_POWTABS_FOR_ASIN = false; + + /* + * Common to FastMath and StrictFastMath. + */ + + /** + * Using two pow tab can just make things barely faster, + * and could relatively hurt in case of cache-misses, + * especially for methods that otherwise wouldn't rely + * on any tab, so we don't use it. + */ + static final boolean USE_TWO_POW_TAB = false; + + /** + * Because on some architectures, some casts can be slow, + * especially for large values. + * Might make things a bit slower for latest architectures, + * but not as much as it makes them faster for older ones. + */ + static final boolean ANTI_SLOW_CASTS = true; + + /** + * If some methods get JIT-optimized, they might crash + * if they contain "(var == xxx)" with var being NaN + * (can happen with Java 6u29). + * + * The crash does not happen if we replace "==" with "<" or ">". + * + * Only the code that has been observed to trigger the bug + * has been modified. + */ + static final boolean ANTI_JIT_OPTIM_CRASH_ON_NAN = true; + + //-------------------------------------------------------------------------- + // GENERAL CONSTANTS + //-------------------------------------------------------------------------- + + /** + * Closest double approximation of e. + */ + public static final double E = Math.E; + + /** + * Closest double approximation of pi, which is inferior to mathematical pi: + * pi ~= 3.14159265358979323846... + * PI ~= 3.141592653589793 + */ + public static final double PI = Math.PI; + + /** + * High double approximation of pi, which is further from pi + * than the low approximation PI: + * pi ~= 3.14159265358979323846... + * PI ~= 3.141592653589793 + * PI_SUP ~= 3.1415926535897936 + */ + public static final double PI_SUP = Double.longBitsToDouble(Double.doubleToRawLongBits(Math.PI)+1); + + static final double ONE_DIV_F2 = 1/2.0; + static final double ONE_DIV_F3 = 1/6.0; + static final double ONE_DIV_F4 = 1/24.0; + + static final float TWO_POW_23_F = (float)NumbersUtils.twoPow(23); + + static final double TWO_POW_24 = NumbersUtils.twoPow(24); + private static final double TWO_POW_N24 = NumbersUtils.twoPow(-24); + + static final double TWO_POW_26 = NumbersUtils.twoPow(26); + static final double TWO_POW_N26 = NumbersUtils.twoPow(-26); + + // First double value (from zero) such as (value+-1/value == value). + static final double TWO_POW_27 = NumbersUtils.twoPow(27); + static final double TWO_POW_N27 = NumbersUtils.twoPow(-27); + + static final double TWO_POW_N28 = NumbersUtils.twoPow(-28); + + static final double TWO_POW_52 = NumbersUtils.twoPow(52); + + static final double TWO_POW_N55 = NumbersUtils.twoPow(-55); + + static final double TWO_POW_66 = NumbersUtils.twoPow(66); + + static final double TWO_POW_512 = NumbersUtils.twoPow(512); + static final double TWO_POW_N512 = NumbersUtils.twoPow(-512); + + /** + * Double.MIN_NORMAL since Java 6. + */ + static final double DOUBLE_MIN_NORMAL = Double.longBitsToDouble(0x0010000000000000L); // 2.2250738585072014E-308 + + // Not storing float/double mantissa size in constants, + // for 23 and 52 are shorter to read and more + // bitwise-explicit than some constant's name. + + static final int MIN_DOUBLE_EXPONENT = -1074; + static final int MIN_DOUBLE_NORMAL_EXPONENT = -1022; + static final int MAX_DOUBLE_EXPONENT = 1023; + + static final int MIN_FLOAT_NORMAL_EXPONENT = -126; + static final int MAX_FLOAT_EXPONENT = 127; + + private static final double SQRT_2 = StrictMath.sqrt(2.0); + + static final double LOG_2 = StrictMath.log(2.0); + static final double LOG_TWO_POW_27 = StrictMath.log(TWO_POW_27); + static final double LOG_DOUBLE_MAX_VALUE = StrictMath.log(Double.MAX_VALUE); + + static final double INV_LOG_10 = 1.0/StrictMath.log(10.0); + + static final double DOUBLE_BEFORE_60 = Double.longBitsToDouble(Double.doubleToRawLongBits(60.0)-1); + + //-------------------------------------------------------------------------- + // CONSTANTS FOR NORMALIZATIONS + //-------------------------------------------------------------------------- + + /** + * Table of constants for 1/(PI/2), 282 Hex digits (enough for normalizing doubles). + * 1/(PI/2) approximation = sum of TWO_OVER_PI_TAB[i]*2^(-24*(i+1)). + * + * double and not int, to avoid int-to-double cast during computations. + */ + private static final double TWO_OVER_PI_TAB[] = { + 0xA2F983, 0x6E4E44, 0x1529FC, 0x2757D1, 0xF534DD, 0xC0DB62, + 0x95993C, 0x439041, 0xFE5163, 0xABDEBB, 0xC561B7, 0x246E3A, + 0x424DD2, 0xe00649, 0x2EEA09, 0xD1921C, 0xFE1DEB, 0x1CB129, + 0xA73EE8, 0x8235F5, 0x2EBB44, 0x84E99C, 0x7026B4, 0x5F7E41, + 0x3991d6, 0x398353, 0x39F49C, 0x845F8B, 0xBDF928, 0x3B1FF8, + 0x97FFDE, 0x05980F, 0xEF2F11, 0x8B5A0A, 0x6D1F6D, 0x367ECF, + 0x27CB09, 0xB74F46, 0x3F669E, 0x5FEA2D, 0x7527BA, 0xC7EBE5, + 0xF17B3D, 0x0739F7, 0x8A5292, 0xEA6BFB, 0x5FB11F, 0x8D5D08, + 0x560330, 0x46FC7B, 0x6BABF0, 0xCFBC20, 0x9AF436, 0x1DA9E3, + 0x91615E, 0xE61B08, 0x659985, 0x5F14A0, 0x68408D, 0xFFD880, + 0x4D7327, 0x310606, 0x1556CA, 0x73A8C9, 0x60E27B, 0xC08C6B}; + + /* + * Constants for PI/2. Only the 23 most significant bits of each mantissa are used. + * 2*PI approximation = sum of TWOPI_TAB. + */ + private static final double PIO2_TAB0 = Double.longBitsToDouble(0x3FF921FB40000000L); + private static final double PIO2_TAB1 = Double.longBitsToDouble(0x3E74442D00000000L); + private static final double PIO2_TAB2 = Double.longBitsToDouble(0x3CF8469880000000L); + private static final double PIO2_TAB3 = Double.longBitsToDouble(0x3B78CC5160000000L); + private static final double PIO2_TAB4 = Double.longBitsToDouble(0x39F01B8380000000L); + private static final double PIO2_TAB5 = Double.longBitsToDouble(0x387A252040000000L); + + static final double PIO2_INV = Double.longBitsToDouble(0x3FE45F306DC9C883L); // 6.36619772367581382433e-01 53 bits of 2/pi + static final double PIO2_HI = Double.longBitsToDouble(0x3FF921FB54400000L); // 1.57079632673412561417e+00 first 33 bits of pi/2 + static final double PIO2_LO = Double.longBitsToDouble(0x3DD0B4611A626331L); // 6.07710050650619224932e-11 pi/2 - PIO2_HI + static final double PI_INV = PIO2_INV/2; + static final double PI_HI = 2*PIO2_HI; + static final double PI_LO = 2*PIO2_LO; + static final double TWOPI_INV = PIO2_INV/4; + static final double TWOPI_HI = 4*PIO2_HI; + static final double TWOPI_LO = 4*PIO2_LO; + + /** + * Bit = 0 where quadrant is encoded in remainder bits. + */ + private static final long QUADRANT_BITS_0_MASK = 0xCFFFFFFFFFFFFFFFL; + + /** + * Remainder bits where quadrant is encoded, 0 elsewhere. + */ + private static final long QUADRANT_PLACE_BITS = 0x3000000000000000L; + + /** + * fdlibm uses 2^19*PI/2 here. + * With 2^18*PI/2 we would be more accurate, for example when normalizing + * 822245.903631403, which is close to 2^19*PI/2, but we are still in + * our accuracy tolerance with fdlibm's value (but not 2^20*PI/2) so we + * stick to it, to help being faster than (Strict)Math for values in + * [2^18*PI/2,2^19*PI/2]. + * + * For tests, can use a smaller value, for heavy remainder + * not to only be used with huge values. + */ + static final double NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2 = StrictMath.pow(2.0,19.0)*(Math.PI/2); + + /** + * 2*Math.PI, normalized into [-PI,PI], as returned by + * StrictMath.asin(StrictMath.sin(2*Math.PI)) + * (asin behaves as identity for this). + * + * NB: NumbersUtils.minus2PI(2*Math.PI) returns -2.449293598153844E-16, + * which is different due to not using an accurate enough definition of PI. + */ + static final double TWO_MATH_PI_IN_MINUS_PI_PI = -2.4492935982947064E-16; + + //-------------------------------------------------------------------------- + // CONSTANTS AND TABLES FOR SIN AND COS + //-------------------------------------------------------------------------- + + static final int SIN_COS_TABS_SIZE = (1<>9) / SIN_COS_INDEXER) * 0.99; + + //-------------------------------------------------------------------------- + // CONSTANTS AND TABLES FOR TAN + //-------------------------------------------------------------------------- + + // We use the following formula: + // 1) tan(-x) = -tan(x) + // 2) tan(x) = 1/tan(PI/2-x) + // ---> we only have to compute tan(x) on [0,A] with PI/4<=A= 45deg, and supposed to be >= 51.4deg, as fdlibm code is not + * supposed to work with values inferior to that (51.4deg is about + * (PI/2-Double.longBitsToDouble(0x3FE5942800000000L))). + */ + static final double TAN_MAX_VALUE_FOR_TABS = StrictMath.toRadians(77.0); + + static final int TAN_TABS_SIZE = (int)((TAN_MAX_VALUE_FOR_TABS/(Math.PI/2)) * (TAN_VIRTUAL_TABS_SIZE-1)) + 1; + static final double TAN_DELTA_HI = PIO2_HI/(TAN_VIRTUAL_TABS_SIZE-1); + static final double TAN_DELTA_LO = PIO2_LO/(TAN_VIRTUAL_TABS_SIZE-1); + static final double TAN_INDEXER = 1/(TAN_DELTA_HI+TAN_DELTA_LO); + + static final class MyTTan { + static final double[] tanTab = new double[TAN_TABS_SIZE]; + static final double[] tanDer1DivF1Tab = new double[TAN_TABS_SIZE]; + static final double[] tanDer2DivF2Tab = new double[TAN_TABS_SIZE]; + static final double[] tanDer3DivF3Tab = new double[TAN_TABS_SIZE]; + static final double[] tanDer4DivF4Tab = new double[TAN_TABS_SIZE]; + static { + init(); + } + private static strictfp void init() { + for (int i=0;i>9) / TAN_INDEXER) * 0.99); + + //-------------------------------------------------------------------------- + // CONSTANTS AND TABLES FOR ACOS, ASIN + //-------------------------------------------------------------------------- + + // We use the following formula: + // 1) acos(x) = PI/2 - asin(x) + // 2) asin(-x) = -asin(x) + // ---> we only have to compute asin(x) on [0,1]. + // For values not close to +-1, we use look-up tables; + // for values near +-1, we use code derived from fdlibm. + + /** + * Supposed to be >= sin(77.2deg), as fdlibm code is supposed to work with values > 0.975, + * but seems to work well enough as long as value >= sin(25deg). + */ + static final double ASIN_MAX_VALUE_FOR_TABS = StrictMath.sin(StrictMath.toRadians(73.0)); + + static final int ASIN_TABS_SIZE = (1< we only have to compute atan(x) on [0,+Infinity[. + // For values corresponding to angles not close to +-PI/2, we use look-up tables; + // for values corresponding to angles near +-PI/2, we use code derived from fdlibm. + + /** + * Supposed to be >= tan(67.7deg), as fdlibm code is supposed to work with values > 2.4375. + */ + static final double ATAN_MAX_VALUE_FOR_TABS = StrictMath.tan(StrictMath.toRadians(74.0)); + + static final int ATAN_TABS_SIZE = (1<>SQRT_LO_BITS)); + for (int i=1;i>CBRT_LO_BITS)); + for (int i=1;i= MIN_DOUBLE_EXPONENT) { + if (power <= MAX_DOUBLE_EXPONENT) { // Normal or subnormal. + return MyTTwoPow.twoPowTab[power-MIN_DOUBLE_EXPONENT]; + } else { // Overflow. + return Double.POSITIVE_INFINITY; + } + } else { // Underflow. + return 0.0; + } + } else { + return NumbersUtils.twoPow(power); + } + } + + /** + * @param value An int value. + * @return value*value. + */ + public static int pow2(int value) { + return value*value; + } + + /** + * @param value A long value. + * @return value*value. + */ + public static long pow2(long value) { + return value*value; + } + + /** + * @param value An int value. + * @return value*value*value. + */ + public static int pow3(int value) { + return value*value*value; + } + + /** + * @param value A long value. + * @return value*value*value. + */ + public static long pow3(long value) { + return value*value*value; + } + + /* + * absolute values + */ + + /** + * @param value An int value. + * @return The absolute value, except if value is Integer.MIN_VALUE, for which it returns Integer.MIN_VALUE. + */ + public static int abs(int value) { + if (FM_USE_JDK_MATH || SFM_USE_JDK_MATH) { + return Math.abs(value); + } + return NumbersUtils.abs(value); + } + + /** + * @param value A long value. + * @return The absolute value, except if value is Long.MIN_VALUE, for which it returns Long.MIN_VALUE. + */ + public static long abs(long value) { + if (FM_USE_JDK_MATH || SFM_USE_JDK_MATH) { + return Math.abs(value); + } + return NumbersUtils.abs(value); + } + + /* + * close values + */ + + /** + * @param value A long value. + * @return The specified value as int. + * @throws ArithmeticException if the specified value is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int toIntExact(long value) { + return NumbersUtils.asInt(value); + } + + /** + * @param value A long value. + * @return The closest int value in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int toInt(long value) { + return NumbersUtils.toInt(value); + } + + /* + * ranges + */ + + /** + * @param min An int value. + * @param max An int value. + * @param value An int value. + * @return minValue if value < minValue, maxValue if value > maxValue, value otherwise. + */ + public static int toRange(int min, int max, int value) { + return NumbersUtils.toRange(min, max, value); + } + + /** + * @param min A long value. + * @param max A long value. + * @param value A long value. + * @return min if value < min, max if value > max, value otherwise. + */ + public static long toRange(long min, long max, long value) { + return NumbersUtils.toRange(min, max, value); + } + + /* + * unary operators (increment,decrement,negate) + */ + + /** + * @param value An int value. + * @return The argument incremented by one. + * @throws ArithmeticException if the mathematical result + * is not in int range. + */ + public static int incrementExact(int value) { + if (value == Integer.MAX_VALUE) { + throw new ArithmeticException("integer overflow"); + } + return value + 1; + } + + /** + * @param value A long value. + * @return The argument incremented by one. + * @throws ArithmeticException if the mathematical result + * is not in long range. + */ + public static long incrementExact(long value) { + if (value == Long.MAX_VALUE) { + throw new ArithmeticException("long overflow"); + } + return value + 1L; + } + + /** + * @param value An int value. + * @return The argument incremented by one, or the argument + * if the mathematical result is not in int range. + */ + public static int incrementBounded(int value) { + if (value == Integer.MAX_VALUE) { + return value; + } + return value + 1; + } + + /** + * @param value A long value. + * @return The argument incremented by one, or the argument + * if the mathematical result is not in long range. + */ + public static long incrementBounded(long value) { + if (value == Long.MAX_VALUE) { + return value; + } + return value + 1L; + } + + /** + * @param value An int value. + * @return The argument decremented by one. + * @throws ArithmeticException if the mathematical result + * is not in int range. + */ + public static int decrementExact(int value) { + if (value == Integer.MIN_VALUE) { + throw new ArithmeticException("integer overflow"); + } + return value - 1; + } + + /** + * @param value A long value. + * @return The argument decremented by one. + * @throws ArithmeticException if the mathematical result + * is not in long range. + */ + public static long decrementExact(long value) { + if (value == Long.MIN_VALUE) { + throw new ArithmeticException("long overflow"); + } + return value - 1L; + } + + /** + * @param value An int value. + * @return The argument decremented by one, or the argument + * if the mathematical result is not in int range. + */ + public static int decrementBounded(int value) { + if (value == Integer.MIN_VALUE) { + return value; + } + return value - 1; + } + + /** + * @param value A long value. + * @return The argument decremented by one, or the argument + * if the mathematical result is not in long range. + */ + public static long decrementBounded(long value) { + if (value == Long.MIN_VALUE) { + return value; + } + return value - 1L; + } + + /** + * @param value An int value. + * @return The argument negated. + * @throws ArithmeticException if the mathematical result + * is not in int range. + */ + public static int negateExact(int value) { + if (value == Integer.MIN_VALUE) { + throw new ArithmeticException("integer overflow"); + } + return -value; + } + + /** + * @param value A long value. + * @return The argument negated. + * @throws ArithmeticException if the mathematical result + * is not in long range. + */ + public static long negateExact(long value) { + if (value == Long.MIN_VALUE) { + throw new ArithmeticException("long overflow"); + } + return -value; + } + + /** + * @param value An int value. + * @return The argument negated, or Integer.MAX_VALUE + * if the argument is Integer.MIN_VALUE. + */ + public static int negateBounded(int value) { + if (value == Integer.MIN_VALUE) { + return Integer.MAX_VALUE; + } + return -value; + } + + /** + * @param value A long value. + * @return The argument negated, or Long.MAX_VALUE + * if the argument is Long.MIN_VALUE. + */ + public static long negateBounded(long value) { + if (value == Long.MIN_VALUE) { + return Long.MAX_VALUE; + } + return -value; + } + + /* + * binary operators (+,-,*) + */ + + /** + * @param a An int value. + * @param b An int value. + * @return The mathematical result of a+b. + * @throws ArithmeticException if the mathematical result of a+b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int addExact(int a, int b) { + return NumbersUtils.plusExact(a, b); + } + + /** + * @param a A long value. + * @param b A long value. + * @return The mathematical result of a+b. + * @throws ArithmeticException if the mathematical result of a+b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. + */ + public static long addExact(long a, long b) { + return NumbersUtils.plusExact(a, b); + } + + /** + * @param a An int value. + * @param b An int value. + * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a+b. + */ + public static int addBounded(int a, int b) { + return NumbersUtils.plusBounded(a, b); + } + + /** + * @param a A long value. + * @param b A long value. + * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a+b. + */ + public static long addBounded(long a, long b) { + return NumbersUtils.plusBounded(a, b); + } + + /** + * @param a An int value. + * @param b An int value. + * @return The mathematical result of a-b. + * @throws ArithmeticException if the mathematical result of a-b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int subtractExact(int a, int b) { + return NumbersUtils.minusExact(a, b); + } + + /** + * @param a A long value. + * @param b A long value. + * @return The mathematical result of a-b. + * @throws ArithmeticException if the mathematical result of a-b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. + */ + public static long subtractExact(long a, long b) { + return NumbersUtils.minusExact(a, b); + } + + /** + * @param a An int value. + * @param b An int value. + * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a-b. + */ + public static int subtractBounded(int a, int b) { + return NumbersUtils.minusBounded(a, b); + } + + /** + * @param a A long value. + * @param b A long value. + * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a-b. + */ + public static long subtractBounded(long a, long b) { + return NumbersUtils.minusBounded(a, b); + } + + /** + * @param a An int value. + * @param b An int value. + * @return The mathematical result of a*b. + * @throws ArithmeticException if the mathematical result of a*b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int multiplyExact(int a, int b) { + return NumbersUtils.timesExact(a, b); + } + + /** + * @param a A long value. + * @param b An int value. + * @return The mathematical result of a*b. + * @throws ArithmeticException if the mathematical result of a*b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. + */ + public static long multiplyExact(long a, int b) { + return NumbersUtils.timesExact(a, (long) b); + } + + /** + * @param a A long value. + * @param b A long value. + * @return The mathematical result of a*b. + * @throws ArithmeticException if the mathematical result of a*b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. + */ + public static long multiplyExact(long a, long b) { + return NumbersUtils.timesExact(a, b); + } + + /** + * @param a An int value. + * @param b An int value. + * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a*b. + */ + public static int multiplyBounded(int a, int b) { + return NumbersUtils.timesBounded(a, b); + } + + /** + * @param a A long value. + * @param b An int value. + * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a*b. + */ + public static long multiplyBounded(long a, int b) { + return NumbersUtils.timesBounded(a, (long) b); + } + + /** + * @param a A long value. + * @param b A long value. + * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a*b. + */ + public static long multiplyBounded(long a, long b) { + return NumbersUtils.timesBounded(a, b); + } + + /** + * @param x An int value. + * @param y An int value. + * @return The mathematical product as a long. + */ + public static long multiplyFull(int x, int y) { + return ((long) x) * ((long) y); + } + + /** + * @param x A long value. + * @param y A long value. + * @return The most significant 64 bits of the 128-bit product of two 64-bit factors. + */ + public static long multiplyHigh(long x, long y) { + if ((x|y) < 0) { + // Use technique from section 8-2 of Henry S. Warren, Jr., + // Hacker's Delight (2nd ed.) (Addison Wesley, 2013), 173-174. + long x1 = (x >> 32); + long y1 = (y >> 32); + long x2 = (x & 0xFFFFFFFFL); + long y2 = (y & 0xFFFFFFFFL); + long z2 = x2 * y2; + long t = x1 * y2 + (z2 >>> 32); + long z1 = (t & 0xFFFFFFFFL) + x2 * y1; + long z0 = (t >> 32); + return x1 * y1 + z0 + (z1 >> 32); + } else { + // Use Karatsuba technique with two base 2^32 digits. + long x1 = (x >>> 32); + long y1 = (y >>> 32); + long x2 = (x & 0xFFFFFFFFL); + long y2 = (y & 0xFFFFFFFFL); + long A = x1 * y1; + long B = x2 * y2; + long C = (x1 + x2) * (y1 + y2); + long K = C - A - B; + return (((B >>> 32) + K) >>> 32) + A; + } + } + + /* + * binary operators (/,%) + */ + + /** + * Returns the largest int <= dividend/divisor. + * + * Unlike "/" operator, which rounds towards 0, this division + * rounds towards -Infinity (which give different result + * when the exact result is negative). + * + * @param x The dividend. + * @param y The divisor. + * @return The largest int <= dividend/divisor, unless dividend is + * Integer.MIN_VALUE and divisor is -1, in which case + * Integer.MIN_VALUE is returned. + * @throws ArithmeticException if the divisor is zero. + */ + public static int floorDiv(int x, int y) { + int r = x / y; + // If the signs are different and modulo not zero, rounding down. + if (((x ^ y) < 0) && ((r * y) != x)) { + r--; + } + return r; + } + + /** + * Returns the largest long <= dividend/divisor. + * + * Unlike "/" operator, which rounds towards 0, this division + * rounds towards -Infinity (which give different result + * when the exact result is negative). + * + * @param x The dividend. + * @param y The divisor. + * @return The largest long <= dividend/divisor, unless dividend is + * Long.MIN_VALUE and divisor is -1, in which case + * Long.MIN_VALUE is returned. + * @throws ArithmeticException if the divisor is zero. + */ + public static long floorDiv(long x, int y) { + return floorDiv(x, (long) y); + } + + /** + * Returns the largest long <= dividend/divisor. + * + * Unlike "/" operator, which rounds towards 0, this division + * rounds towards -Infinity (which give different result + * when the exact result is negative). + * + * @param x The dividend. + * @param y The divisor. + * @return The largest long <= dividend/divisor, unless dividend is + * Long.MIN_VALUE and divisor is -1, in which case + * Long.MIN_VALUE is returned. + * @throws ArithmeticException if the divisor is zero. + */ + public static long floorDiv(long x, long y) { + long r = x / y; + // If the signs are different and modulo not zero, rounding down. + if (((x ^ y) < 0) && ((r * y) != x)) { + r--; + } + return r; + } + + /** + * Returns the floor modulus, which is "x - floorDiv(x,y) * y", + * has the same sign as y, and is in ]-abs(y),abs(y)[. + * + * The relationship between floorMod and floorDiv is the same + * than between "%" and "/". + * + * @param x The dividend. + * @param y The divisor. + * @return The floor modulus, i.e. "x - (floorDiv(x, y) * y)". + * @throws ArithmeticException if the divisor is zero. + */ + public static int floorMod(int x, int y) { + return x - floorDiv(x, y) * y; + } + + /** + * Returns the floor modulus, which is "x - floorDiv(x,y) * y", + * has the same sign as y, and is in ]-abs(y),abs(y)[. + * + * The relationship between floorMod and floorDiv is the same + * than between "%" and "/". + * + * @param x The dividend. + * @param y The divisor. + * @return The floor modulus, i.e. "x - (floorDiv(x, y) * y)". + * @throws ArithmeticException if the divisor is zero. + */ + public static int floorMod(long x, int y) { + // No overflow so can cast. + return (int) (x - floorDiv(x,y) * y); + } + + /** + * Returns the floor modulus, which is "x - floorDiv(x,y) * y", + * has the same sign as y, and is in ]-abs(y),abs(y)[. + * + * The relationship between floorMod and floorDiv is the same + * than between "%" and "/". + * + * @param x The dividend. + * @param y The divisor. + * @return The floor modulus, i.e. "x - (floorDiv(x, y) * y)". + * @throws ArithmeticException if the divisor is zero. + */ + public static long floorMod(long x, long y) { + return x - floorDiv(x, y) * y; + } + + /* + * Non-redefined Math public values and treatments. + */ + + public static int min(int a, int b) { + return Math.min(a,b); + } + + public static long min(long a, long b) { + return Math.min(a,b); + } + + public static int max(int a, int b) { + return Math.max(a,b); + } + + public static long max(long a, long b) { + return Math.max(a,b); + } + + //-------------------------------------------------------------------------- + // PACKAGE-PRIVATE METHODS + //-------------------------------------------------------------------------- + + /** + * @param power Must be in normal values range. + */ + static double twoPowNormal(int power) { + if (USE_TWO_POW_TAB) { + return MyTTwoPow.twoPowTab[power-MIN_DOUBLE_EXPONENT]; + } else { + return Double.longBitsToDouble(((long)(power+MAX_DOUBLE_EXPONENT))<<52); + } + } + + /** + * @param power Must be in normal or subnormal values range. + */ + static double twoPowNormalOrSubnormal(int power) { + if (USE_TWO_POW_TAB) { + return MyTTwoPow.twoPowTab[power-MIN_DOUBLE_EXPONENT]; + } else { + if (power <= -MAX_DOUBLE_EXPONENT) { // Not normal. + return Double.longBitsToDouble(0x0008000000000000L>>(-(power+MAX_DOUBLE_EXPONENT))); + } else { // Normal. + return Double.longBitsToDouble(((long)(power+MAX_DOUBLE_EXPONENT))<<52); + } + } + } + + static double atan2_pinf_yyy(double y) { + if (y == Double.POSITIVE_INFINITY) { + return Math.PI/4; + } else if (y == Double.NEGATIVE_INFINITY) { + return -Math.PI/4; + } else if (y > 0.0) { + return 0.0; + } else if (y < 0.0) { + return -0.0; + } else { + return Double.NaN; + } + } + + static double atan2_ninf_yyy(double y) { + if (y == Double.POSITIVE_INFINITY) { + return 3*Math.PI/4; + } else if (y == Double.NEGATIVE_INFINITY) { + return -3*Math.PI/4; + } else if (y > 0.0) { + return Math.PI; + } else if (y < 0.0) { + return -Math.PI; + } else { + return Double.NaN; + } + } + + static double atan2_yyy_zeroOrNaN(double y, double x) { + if (x == 0.0) { + if (y == 0.0) { + if (signFromBit_antiCyclic(x) < 0) { + // x is -0.0 + return signFromBit_antiCyclic(y) * Math.PI; + } else { + // +-0.0 + return y; + } + } + if (y > 0.0) { + return Math.PI/2; + } else if (y < 0.0) { + return -Math.PI/2; + } else { + return Double.NaN; + } + } else { + return Double.NaN; + } + } + + /** + * At least one of the arguments must be NaN. + */ + static double hypot_NaN(double xAbs, double yAbs) { + if ((xAbs == Double.POSITIVE_INFINITY) || (yAbs == Double.POSITIVE_INFINITY)) { + return Double.POSITIVE_INFINITY; + } else { + return Double.NaN; + } + } + + /** + * At least one of the arguments must be NaN. + */ + static double hypot_NaN(double xAbs, double yAbs, double zAbs) { + if ((xAbs == Double.POSITIVE_INFINITY) || (yAbs == Double.POSITIVE_INFINITY) || (zAbs == Double.POSITIVE_INFINITY)) { + return Double.POSITIVE_INFINITY; + } else { + return Double.NaN; + } + } + + /* + * + */ + + /** + * @param remainder Must have 1 for 2nd and 3rd exponent bits, which is the + * case for heavyRemPiO2 remainders (their absolute values are >= + * Double.longBitsToDouble(0x3000000000000000L) + * = 1.727233711018889E-77, and even if they were not, turning these + * bits from 0 to 1 on decoding would not change the absolute error + * much), and also works for +-Infinity or NaN encoding. + * @param quadrant Must be in [0,3]. + * @return Bits holding remainder, and quadrant instead of + * reamainder's 2nd and 3rd exponent bits. + */ + static long encodeRemainderAndQuadrant(double remainder, int quadrant) { + final long bits = Double.doubleToRawLongBits(remainder); + return (bits&QUADRANT_BITS_0_MASK)|(((long)quadrant)<<60); + } + + static double decodeRemainder(long bits) { + return Double.longBitsToDouble((bits&QUADRANT_BITS_0_MASK)|QUADRANT_PLACE_BITS); + } + + static int decodeQuadrant(long bits) { + return ((int)(bits>>60))&3; + } + + /* + * JDK-based remainders. + * Since a strict one for (% (PI/2)) is needed for heavyRemainderPiO2, + * we need it in this class. + * Then, for homogeneity, we put them all in this class. + * Then, to avoid code duplication for these slow-anyway methods, + * we just stick with strict versions, for both FastMath and StrictFastMath. + */ + + /** + * @param angle Angle, in radians. + * @return Remainder of (angle % (2*PI)), in [-PI,PI]. + */ + static strictfp double jdkRemainderTwoPi(double angle) { + final double sin = StrictMath.sin(angle); + final double cos = StrictMath.cos(angle); + return StrictMath.atan2(sin, cos); + } + + /** + * @param angle Angle, in radians. + * @return Remainder of (angle % PI), in [-PI/2,PI/2]. + */ + static strictfp double jdkRemainderPi(double angle) { + final double sin = StrictMath.sin(angle); + final double cos = StrictMath.cos(angle); + /* + * Making sure atan2's result ends up in [-PI/2,PI/2], + * i.e. has maximum accuracy. + */ + return StrictMath.atan2(sin, Math.abs(cos)); + } + + /** + * @param angle Angle, in radians. + * @return Bits of double corresponding to remainder of (angle % (PI/2)), + * in [-PI/4,PI/4], with quadrant encoded in exponent bits. + */ + static strictfp long jdkRemainderPiO2(double angle, boolean negateRem) { + final double sin = StrictMath.sin(angle); + final double cos = StrictMath.cos(angle); + + /* + * Computing quadrant first, and then computing + * atan2, to make sure its result ends up in [-PI/4,PI/4], + * i.e. has maximum accuracy. + */ + + final int q; + final double sinForAtan2; + final double cosForAtan2; + if (cos >= (SQRT_2/2)) { + // [-PI/4,PI/4] + q = 0; + sinForAtan2 = sin; + cosForAtan2 = cos; + } else if (cos <= -(SQRT_2/2)) { + // [3*PI/4,5*PI/4] + q = 2; + sinForAtan2 = -sin; + cosForAtan2 = -cos; + } else if (sin > 0.0) { + // [PI/4,3*PI/4] + q = 1; + sinForAtan2 = -cos; + cosForAtan2 = sin; + } else { + // [5*PI/4,7*PI/4] + q = 3; + sinForAtan2 = cos; + cosForAtan2 = -sin; + } + + double fw = StrictMath.atan2(sinForAtan2, cosForAtan2); + + return encodeRemainderAndQuadrant(negateRem ? -fw : fw, q); + } + + /* + * Our remainders implementations. + */ + + /** + * @param angle Angle, in radians. Must not be NaN nor +-Infinity. + * @return Remainder of (angle % (2*PI)), in [-PI,PI]. + */ + static strictfp double heavyRemainderTwoPi(double angle) { + final long remAndQuad = heavyRemainderPiO2(angle, false); + final double rem = decodeRemainder(remAndQuad); + final int q = decodeQuadrant(remAndQuad); + if (q == 0) { + return rem; + } else if (q == 1) { + return (rem + PIO2_LO) + PIO2_HI; + } else if (q == 2) { + if (rem < 0.0) { + return (rem + PI_LO) + PI_HI; + } else { + return (rem - PI_LO) - PI_HI; + } + } else { + return (rem - PIO2_LO) - PIO2_HI; + } + } + + /** + * @param angle Angle, in radians. Must not be NaN nor +-Infinity. + * @return Remainder of (angle % PI), in [-PI/2,PI/2]. + */ + static strictfp double heavyRemainderPi(double angle) { + final long remAndQuad = heavyRemainderPiO2(angle, false); + final double rem = decodeRemainder(remAndQuad); + final int q = decodeQuadrant(remAndQuad); + if ((q&1) != 0) { + // q is 1 or 3 + if (rem < 0.0) { + return (rem + PIO2_LO) + PIO2_HI; + } else { + return (rem - PIO2_LO) - PIO2_HI; + } + } + return rem; + } + + /** + * Remainder using an accurate definition of PI. + * Derived from a fdlibm treatment called __kernel_rem_pio2. + * + * Not defining a non-strictfp version for FastMath, to avoid duplicating + * its long and messy code, and because it's slow anyway, and should be + * rarely used when speed matters. + * + * @param angle Angle, in radians. Must not be NaN nor +-Infinity. + * @param negateRem True if remainder must be negated before encoded into returned long. + * @return Bits of double corresponding to remainder of (angle % (PI/2)), + * in [-PI/4,PI/4], with quadrant encoded in exponent bits. + */ + static strictfp long heavyRemainderPiO2(double angle, boolean negateRem) { + + /* + * fdlibm treatments unrolled, to avoid garbage and be OOME-free, + * corresponding to: + * 1) initial jk = 4 (precision = 3 = 64 bits (extended)), + * which is more accurate than using precision = 2 + * (53 bits, double), even though we work with doubles + * and use strictfp! + * 2) max lengths of 8 for f[], 6 for q[], fq[] and iq[]. + * 3) at most one recomputation (one goto). + * These limitations were experimentally found to + * be sufficient for billions of random doubles + * of random magnitudes. + * For the rare cases that our unrolled treatments can't handle, + * we fall back to a JDK-based implementation. + */ + + int n,i,j,ih; + double fw; + + /* + * Turning angle into 24-bits integer chunks. + * Done outside __kernel_rem_pio2, but we factor it inside our method. + */ + + // Reworking exponent to have a value < 2^24. + final long lx = Double.doubleToRawLongBits(angle); + final long exp = ((lx>>52)&0x7FF) - (1023+23); + double z = Double.longBitsToDouble(lx - (exp<<52)); + + double x0 = (double)(int)z; + z = (z-x0)*TWO_POW_24; + double x1 = (double)(int)z; + z = (z-x1)*TWO_POW_24; + double x2 = (double)(int)z; + + final int e0 = (int)exp; + // in [1,3] + final int nx = (x2 == 0.0) ? ((x1 == 0.0) ? 1 : 2) : 3; + + /* + * + */ + + double f0,f1,f2,f3,f4,f5,f6,f7; + double q0,q1,q2,q3,q4,q5; + int iq0,iq1,iq2,iq3,iq4,iq5; + + int jk = 4; + + int jx = nx-1; + int jv = Math.max(0,(e0-3)/24); + // In fdlibm, this is q0, but we prefer to use q0 for q[0]. + int qZero = e0-24*(jv+1); + + j = jv-jx; + if (jx == 0) { + f6 = 0.0; + f5 = 0.0; + f4 = (j >= -4) ? TWO_OVER_PI_TAB[j+4] : 0.0; + f3 = (j >= -3) ? TWO_OVER_PI_TAB[j+3] : 0.0; + f2 = (j >= -2) ? TWO_OVER_PI_TAB[j+2] : 0.0; + f1 = (j >= -1) ? TWO_OVER_PI_TAB[j+1] : 0.0; + f0 = (j >= 0) ? TWO_OVER_PI_TAB[j] : 0.0; + + q0 = x0*f0; + q1 = x0*f1; + q2 = x0*f2; + q3 = x0*f3; + q4 = x0*f4; + } else if (jx == 1) { + f6 = 0.0; + f5 = (j >= -5) ? TWO_OVER_PI_TAB[j+5] : 0.0; + f4 = (j >= -4) ? TWO_OVER_PI_TAB[j+4] : 0.0; + f3 = (j >= -3) ? TWO_OVER_PI_TAB[j+3] : 0.0; + f2 = (j >= -2) ? TWO_OVER_PI_TAB[j+2] : 0.0; + f1 = (j >= -1) ? TWO_OVER_PI_TAB[j+1] : 0.0; + f0 = (j >= 0) ? TWO_OVER_PI_TAB[j] : 0.0; + + q0 = x0*f1 + x1*f0; + q1 = x0*f2 + x1*f1; + q2 = x0*f3 + x1*f2; + q3 = x0*f4 + x1*f3; + q4 = x0*f5 + x1*f4; + } else { // jx == 2 + f6 = (j >= -6) ? TWO_OVER_PI_TAB[j+6] : 0.0; + f5 = (j >= -5) ? TWO_OVER_PI_TAB[j+5] : 0.0; + f4 = (j >= -4) ? TWO_OVER_PI_TAB[j+4] : 0.0; + f3 = (j >= -3) ? TWO_OVER_PI_TAB[j+3] : 0.0; + f2 = (j >= -2) ? TWO_OVER_PI_TAB[j+2] : 0.0; + f1 = (j >= -1) ? TWO_OVER_PI_TAB[j+1] : 0.0; + f0 = (j >= 0) ? TWO_OVER_PI_TAB[j] : 0.0; + + q0 = x0*f2 + x1*f1 + x2*f0; + q1 = x0*f3 + x1*f2 + x2*f1; + q2 = x0*f4 + x1*f3 + x2*f2; + q3 = x0*f5 + x1*f4 + x2*f3; + q4 = x0*f6 + x1*f5 + x2*f4; + } + + double twoPowQZero = twoPowNormal(qZero); + + int jz = jk; + + /* + * Unrolling of first round. + */ + + z = q4; + fw = (double)(int)(TWO_POW_N24*z); + iq0 = (int)(z-TWO_POW_24*fw); + z = q3+fw; + fw = (double)(int)(TWO_POW_N24*z); + iq1 = (int)(z-TWO_POW_24*fw); + z = q2+fw; + fw = (double)(int)(TWO_POW_N24*z); + iq2 = (int)(z-TWO_POW_24*fw); + z = q1+fw; + fw = (double)(int)(TWO_POW_N24*z); + iq3 = (int)(z-TWO_POW_24*fw); + z = q0+fw; + iq4 = 0; + iq5 = 0; + + z = (z*twoPowQZero) % 8.0; + n = (int)z; + z -= (double)n; + + ih = 0; + if (qZero > 0) { + // Parentheses against code formatter bug. + i = (iq3>>(24-qZero)); + n += i; + iq3 -= i<<(24-qZero); + ih = iq3>>(23-qZero); + } else if (qZero == 0) { + ih = iq3>>23; + } else if (z >= 0.5) { + ih = 2; + } + + if (ih > 0) { + n += 1; + // carry = 1 is common case, + // so using it as initial value. + int carry = 1; + if (iq0 != 0) { + iq0 = 0x1000000 - iq0; + iq1 = 0xFFFFFF - iq1; + iq2 = 0xFFFFFF - iq2; + iq3 = 0xFFFFFF - iq3; + } else if (iq1 != 0) { + iq1 = 0x1000000 - iq1; + iq2 = 0xFFFFFF - iq2; + iq3 = 0xFFFFFF - iq3; + } else if (iq2 != 0) { + iq2 = 0x1000000 - iq2; + iq3 = 0xFFFFFF - iq3; + } else if (iq3 != 0) { + iq3 = 0x1000000 - iq3; + } else { + carry = 0; + } + if (qZero > 0) { + if (qZero == 1) { + iq3 &= 0x7FFFFF; + } else if (qZero == 2) { + iq3 &= 0x3FFFFF; + } + } + if (ih == 2) { + z = 1.0 - z; + if (carry != 0) { + z -= twoPowQZero; + } + } + } + + if (z == 0.0) { + if (iq3 == 0) { + // With random values of random magnitude, + // probability for this to happen seems lower than 1e-6. + // jz would be more than just incremented by one, + // which our unrolling doesn't support. + return jdkRemainderPiO2(angle, negateRem); + } + if (jx == 0) { + f5 = TWO_OVER_PI_TAB[jv+5]; + q5 = x0*f5; + } else if (jx == 1) { + f6 = TWO_OVER_PI_TAB[jv+5]; + q5 = x0*f6 + x1*f5; + } else { // jx == 2 + f7 = TWO_OVER_PI_TAB[jv+5]; + q5 = x0*f7 + x1*f6 + x2*f5; + } + + jz++; + + /* + * Unrolling of second round. + */ + + z = q5; + fw = (double)(int)(TWO_POW_N24*z); + iq0 = (int)(z-TWO_POW_24*fw); + z = q4+fw; + fw = (double)(int)(TWO_POW_N24*z); + iq1 = (int)(z-TWO_POW_24*fw); + z = q3+fw; + fw = (double)(int)(TWO_POW_N24*z); + iq2 = (int)(z-TWO_POW_24*fw); + z = q2+fw; + fw = (double)(int)(TWO_POW_N24*z); + iq3 = (int)(z-TWO_POW_24*fw); + z = q1+fw; + fw = (double)(int)(TWO_POW_N24*z); + iq4 = (int)(z-TWO_POW_24*fw); + z = q0+fw; + iq5 = 0; + + z = (z*twoPowQZero) % 8.0; + n = (int)z; + z -= (double)n; + + ih = 0; + if (qZero > 0) { + // Parentheses against code formatter bug. + i = (iq4>>(24-qZero)); + n += i; + iq4 -= i<<(24-qZero); + ih = iq4>>(23-qZero); + } else if (qZero == 0) { + ih = iq4>>23; + } else if (z >= 0.5) { + ih = 2; + } + + if (ih > 0) { + n += 1; + // carry = 1 is common case, + // so using it as initial value. + int carry = 1; + if (iq0 != 0) { + iq0 = 0x1000000 - iq0; + iq1 = 0xFFFFFF - iq1; + iq2 = 0xFFFFFF - iq2; + iq3 = 0xFFFFFF - iq3; + iq4 = 0xFFFFFF - iq4; + } else if (iq1 != 0) { + iq1 = 0x1000000 - iq1; + iq2 = 0xFFFFFF - iq2; + iq3 = 0xFFFFFF - iq3; + iq4 = 0xFFFFFF - iq4; + } else if (iq2 != 0) { + iq2 = 0x1000000 - iq2; + iq3 = 0xFFFFFF - iq3; + iq4 = 0xFFFFFF - iq4; + } else if (iq3 != 0) { + iq3 = 0x1000000 - iq3; + iq4 = 0xFFFFFF - iq4; + } else if (iq4 != 0) { + iq4 = 0x1000000 - iq4; + } else { + carry = 0; + } + if (qZero > 0) { + if (qZero == 1) { + iq4 &= 0x7FFFFF; + } else if (qZero == 2) { + iq4 &= 0x3FFFFF; + } + } + if (ih == 2) { + z = 1.0 - z; + if (carry != 0) { + z -= twoPowQZero; + } + } + } + + if (z == 0.0) { + if (iq4 == 0) { + // Case not encountered in tests, but still handling it. + // Would require a third loop unrolling. + return jdkRemainderPiO2(angle, negateRem); + } else { + // z == 0.0, and iq4 != 0, + // so we remove 24 from qZero only once, + // but since we no longer use qZero, + // we just bother to multiply its 2-power + // by 2^-24. + jz--; + twoPowQZero *= TWO_POW_N24; + } + } else { + // z != 0.0 at end of second round. + } + } else { + // z != 0.0 at end of first round. + } + + /* + * After loop. + */ + + if (z != 0.0) { + z /= twoPowQZero; + if (z >= TWO_POW_24) { + fw = (double)(int)(TWO_POW_N24*z); + if (jz == jk) { + iq4 = (int)(z-TWO_POW_24*fw); + jz++; // jz to 5 + // Not using qZero anymore so not updating it. + twoPowQZero *= TWO_POW_24; + iq5 = (int)fw; + } else { // jz == jk+1 == 5 + // Case not encountered in tests, but still handling it. + // Would require use of iq6, with jz = 6. + return jdkRemainderPiO2(angle, negateRem); + } + } else { + if (jz == jk) { + iq4 = (int)z; + } else { // jz == jk+1 == 5 + // Case not encountered in tests, but still handling it. + iq5 = (int)z; + } + } + } + + fw = twoPowQZero; + + if (jz == 5) { + q5 = fw*(double)iq5; + fw *= TWO_POW_N24; + } else { + q5 = 0.0; + } + q4 = fw*(double)iq4; + fw *= TWO_POW_N24; + q3 = fw*(double)iq3; + fw *= TWO_POW_N24; + q2 = fw*(double)iq2; + fw *= TWO_POW_N24; + q1 = fw*(double)iq1; + fw *= TWO_POW_N24; + q0 = fw*(double)iq0; + + /* + * We just use HI part of the result. + */ + + fw = PIO2_TAB0*q5; + fw += PIO2_TAB0*q4 + PIO2_TAB1*q5; + fw += PIO2_TAB0*q3 + PIO2_TAB1*q4 + PIO2_TAB2*q5; + fw += PIO2_TAB0*q2 + PIO2_TAB1*q3 + PIO2_TAB2*q4 + PIO2_TAB3*q5; + fw += PIO2_TAB0*q1 + PIO2_TAB1*q2 + PIO2_TAB2*q3 + PIO2_TAB3*q4 + PIO2_TAB4*q5; + fw += PIO2_TAB0*q0 + PIO2_TAB1*q1 + PIO2_TAB2*q2 + PIO2_TAB3*q3 + PIO2_TAB4*q4 + PIO2_TAB5*q5; + + if ((ih != 0) ^ negateRem) { + fw = -fw; + } + + return encodeRemainderAndQuadrant(fw, n&3); + } + + //-------------------------------------------------------------------------- + // PRIVATE METHODS + //-------------------------------------------------------------------------- + + /** + * Redefined here, to avoid cyclic dependency with (Strict)FastMath. + * + * @param value A double value. + * @return -1 if sign bit is 1, 1 if sign bit is 0. + */ + private static long signFromBit_antiCyclic(double value) { + // Returning a long, to avoid useless cast into int. + return ((Double.doubleToRawLongBits(value)>>62)|1); + } + + private static boolean getBooleanProperty( + final String key, + boolean defaultValue) { + final String tmp = System.getProperty(key); + if (tmp != null) { + return Boolean.parseBoolean(tmp); + } else { + return defaultValue; + } + } + + /** + * Use look-up tables size power through this method, + * to make sure is it small in case java.lang.Math + * is directly used. + */ + private static int getTabSizePower(int tabSizePower) { + return (FM_USE_JDK_MATH && SFM_USE_JDK_MATH) ? Math.min(2, tabSizePower) : tabSizePower; + } +} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/DoubleWrapper.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/DoubleWrapper.java new file mode 100644 index 000000000..e7adc8d59 --- /dev/null +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/DoubleWrapper.java @@ -0,0 +1,13 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ +package space.kscience.kmath.jafama; + +public class DoubleWrapper { + public double value; + @Override + public String toString() { + return Double.toString(this.value); + } +} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/FastMath.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/FastMath.java new file mode 100644 index 000000000..a83c01f7b --- /dev/null +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/FastMath.java @@ -0,0 +1,2986 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.jafama; + +/** + * Faster (hopefully) versions of java.lang.Math methods, plus additional ones. + * Cf. README.txt for more info. + */ +public final class FastMath extends CmnFastMath { + + //-------------------------------------------------------------------------- + // CONFIGURATION + //-------------------------------------------------------------------------- + + private static final boolean USE_JDK_MATH = FM_USE_JDK_MATH; + + private static final boolean USE_REDEFINED_LOG = FM_USE_REDEFINED_LOG; + + private static final boolean USE_REDEFINED_SQRT = FM_USE_REDEFINED_SQRT; + + private static final boolean USE_POWTABS_FOR_ASIN = FM_USE_POWTABS_FOR_ASIN; + + //-------------------------------------------------------------------------- + // PUBLIC METHODS + //-------------------------------------------------------------------------- + + /* + * trigonometry + */ + + /** + * @param angle Angle in radians. + * @return Angle sine. + */ + public static double sin(double angle) { + if (USE_JDK_MATH) { + return Math.sin(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { + if (false) { + // Can give very bad relative error near PI (mod 2*PI). + angle = remainderTwoPi(angle); + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } else { + final long remAndQuad = remainderPiO2(angle); + angle = decodeRemainder(remAndQuad); + final double sin; + final int q = decodeQuadrant(remAndQuad); + if (q == 0) { + sin = sin(angle); + } else if (q == 1) { + sin = cos(angle); + } else if (q == 2) { + sin = -sin(angle); + } else { + sin = -cos(angle); + } + return (negateResult ? -sin : sin); + } + } + // index: possibly outside tables range. + int index = (int)(angle * SIN_COS_INDEXER + 0.5); + double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; + // Making sure index is within tables range. + // Last value of each table is the same than first, + // so we ignore it (tabs size minus one) for modulo. + index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) + double indexSin = MyTSinCos.sinTab[index]; + double indexCos = MyTSinCos.cosTab[index]; + double result = indexSin + delta * (indexCos + delta * (-indexSin * ONE_DIV_F2 + delta * (-indexCos * ONE_DIV_F3 + delta * indexSin * ONE_DIV_F4))); + return negateResult ? -result : result; + } + + /** + * Quick sin, with accuracy of about 1.6e-3 (PI/) + * for |angle| < 6588395.0 (Integer.MAX_VALUE * (2*PI/) - 2) + * (- 2 due to removing PI/2 before using cosine tab), + * and no accuracy at all for larger values. + * + * @param angle Angle in radians. + * @return Angle sine. + */ + public static double sinQuick(double angle) { + if (USE_JDK_MATH) { + return Math.sin(angle); + } + return MyTSinCos.cosTab[((int)(Math.abs(angle-Math.PI/2) * SIN_COS_INDEXER + 0.5)) & (SIN_COS_TABS_SIZE-2)]; + } + + /** + * @param angle Angle in radians. + * @return Angle cosine. + */ + public static double cos(double angle) { + if (USE_JDK_MATH) { + return Math.cos(angle); + } + angle = Math.abs(angle); + if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { + if (false) { + // Can give very bad relative error near PI (mod 2*PI). + angle = remainderTwoPi(angle); + if (angle < 0.0) { + angle = -angle; + } + } else { + final long remAndQuad = remainderPiO2(angle); + angle = decodeRemainder(remAndQuad); + final double cos; + final int q = decodeQuadrant(remAndQuad); + if (q == 0) { + cos = cos(angle); + } else if (q == 1) { + cos = -sin(angle); + } else if (q == 2) { + cos = -cos(angle); + } else { + cos = sin(angle); + } + return cos; + } + } + // index: possibly outside tables range. + int index = (int)(angle * SIN_COS_INDEXER + 0.5); + double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; + // Making sure index is within tables range. + // Last value of each table is the same than first, + // so we ignore it (tabs size minus one) for modulo. + index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) + double indexCos = MyTSinCos.cosTab[index]; + double indexSin = MyTSinCos.sinTab[index]; + return indexCos + delta * (-indexSin + delta * (-indexCos * ONE_DIV_F2 + delta * (indexSin * ONE_DIV_F3 + delta * indexCos * ONE_DIV_F4))); + } + + /** + * Quick cos, with accuracy of about 1.6e-3 (PI/) + * for |angle| < 6588397.0 (Integer.MAX_VALUE * (2*PI/)), + * and no accuracy at all for larger values. + * + * @param angle Angle in radians. + * @return Angle cosine. + */ + public static double cosQuick(double angle) { + if (USE_JDK_MATH) { + return Math.cos(angle); + } + return MyTSinCos.cosTab[((int)(Math.abs(angle) * SIN_COS_INDEXER + 0.5)) & (SIN_COS_TABS_SIZE-2)]; + } + + /** + * Computes sine and cosine together. + * + * @param angle Angle in radians. + * @param cosine (out) Angle cosine. + * @return Angle sine. + */ + public static double sinAndCos(double angle, DoubleWrapper cosine) { + if (USE_JDK_MATH) { + cosine.value = Math.cos(angle); + return Math.sin(angle); + } + // Using the same algorithm than sin(double) method, + // and computing also cosine at the end. + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { + if (false) { + // Can give very bad relative error near PI (mod 2*PI). + angle = remainderTwoPi(angle); + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } else { + final long remAndQuad = remainderPiO2(angle); + angle = decodeRemainder(remAndQuad); + final double sin; + final int q = decodeQuadrant(remAndQuad); + if (q == 0) { + sin = sin(angle); + cosine.value = cos(angle); + } else if (q == 1) { + sin = cos(angle); + cosine.value = -sin(angle); + } else if (q == 2) { + sin = -sin(angle); + cosine.value = -cos(angle); + } else { + sin = -cos(angle); + cosine.value = sin(angle); + } + return (negateResult ? -sin : sin); + } + } + int index = (int)(angle * SIN_COS_INDEXER + 0.5); + double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; + index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) + double indexSin = MyTSinCos.sinTab[index]; + double indexCos = MyTSinCos.cosTab[index]; + // Could factor some multiplications (delta * factorials), but then is less accurate. + cosine.value = indexCos + delta * (-indexSin + delta * (-indexCos * ONE_DIV_F2 + delta * (indexSin * ONE_DIV_F3 + delta * indexCos * ONE_DIV_F4))); + double result = indexSin + delta * (indexCos + delta * (-indexSin * ONE_DIV_F2 + delta * (-indexCos * ONE_DIV_F3 + delta * indexSin * ONE_DIV_F4))); + return negateResult ? -result : result; + } + + /** + * Can have very bad relative error near +-PI/2, + * but of the same magnitude than the relative delta between + * StrictMath.tan(PI/2) and StrictMath.tan(nextDown(PI/2)). + * + * @param angle Angle in radians. + * @return Angle tangent. + */ + public static double tan(double angle) { + if (USE_JDK_MATH) { + return Math.tan(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle > TAN_MAX_VALUE_FOR_INT_MODULO) { + angle = remainderPi(angle); + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } + // index: possibly outside tables range. + int index = (int)(angle * TAN_INDEXER + 0.5); + double delta = (angle - index * TAN_DELTA_HI) - index * TAN_DELTA_LO; + // Making sure index is within tables range. + // index modulo PI, i.e. 2*(virtual tab size minus one). + index &= (2*(TAN_VIRTUAL_TABS_SIZE-1)-1); // index % (2*(TAN_VIRTUAL_TABS_SIZE-1)) + // Here, index is in [0,2*(TAN_VIRTUAL_TABS_SIZE-1)-1], i.e. indicates an angle in [0,PI[. + if (index > (TAN_VIRTUAL_TABS_SIZE-1)) { + index = (2*(TAN_VIRTUAL_TABS_SIZE-1)) - index; + delta = -delta; + negateResult = !negateResult; + } + double result; + if (index < TAN_TABS_SIZE) { + result = MyTTan.tanTab[index] + + delta * (MyTTan.tanDer1DivF1Tab[index] + + delta * (MyTTan.tanDer2DivF2Tab[index] + + delta * (MyTTan.tanDer3DivF3Tab[index] + + delta * MyTTan.tanDer4DivF4Tab[index]))); + } else { // angle in ]TAN_MAX_VALUE_FOR_TABS,TAN_MAX_VALUE_FOR_INT_MODULO], or angle is NaN + // Using tan(angle) == 1/tan(PI/2-angle) formula: changing angle (index and delta), and inverting. + index = (TAN_VIRTUAL_TABS_SIZE-1) - index; + result = 1/(MyTTan.tanTab[index] + - delta * (MyTTan.tanDer1DivF1Tab[index] + - delta * (MyTTan.tanDer2DivF2Tab[index] + - delta * (MyTTan.tanDer3DivF3Tab[index] + - delta * MyTTan.tanDer4DivF4Tab[index])))); + } + return negateResult ? -result : result; + } + + /** + * @param value Value in [-1,1]. + * @return Value arcsine, in radians, in [-PI/2,PI/2]. + */ + public static double asin(double value) { + if (USE_JDK_MATH) { + return Math.asin(value); + } + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + if (value <= ASIN_MAX_VALUE_FOR_TABS) { + int index = (int)(value * ASIN_INDEXER + 0.5); + double delta = value - index * ASIN_DELTA; + double result = MyTAsin.asinTab[index] + + delta * (MyTAsin.asinDer1DivF1Tab[index] + + delta * (MyTAsin.asinDer2DivF2Tab[index] + + delta * (MyTAsin.asinDer3DivF3Tab[index] + + delta * MyTAsin.asinDer4DivF4Tab[index]))); + return negateResult ? -result : result; + } else if (USE_POWTABS_FOR_ASIN && (value <= ASIN_MAX_VALUE_FOR_POWTABS)) { + int index = (int)(powFast(value * ASIN_POWTABS_ONE_DIV_MAX_VALUE, ASIN_POWTABS_POWER) * ASIN_POWTABS_SIZE_MINUS_ONE + 0.5); + double delta = value - MyTAsinPow.asinParamPowTab[index]; + double result = MyTAsinPow.asinPowTab[index] + + delta * (MyTAsinPow.asinDer1DivF1PowTab[index] + + delta * (MyTAsinPow.asinDer2DivF2PowTab[index] + + delta * (MyTAsinPow.asinDer3DivF3PowTab[index] + + delta * MyTAsinPow.asinDer4DivF4PowTab[index]))); + return negateResult ? -result : result; + } else { // value > ASIN_MAX_VALUE_FOR_TABS, or value is NaN + // This part is derived from fdlibm. + if (value < 1.0) { + double t = (1.0 - value)*0.5; + double p = t*(ASIN_PS0+t*(ASIN_PS1+t*(ASIN_PS2+t*(ASIN_PS3+t*(ASIN_PS4+t*ASIN_PS5))))); + double q = 1.0+t*(ASIN_QS1+t*(ASIN_QS2+t*(ASIN_QS3+t*ASIN_QS4))); + double s = sqrt(t); + double z = s+s*(p/q); + double result = ASIN_PIO2_HI-((z+z)-ASIN_PIO2_LO); + return negateResult ? -result : result; + } else { // value >= 1.0, or value is NaN + if (value == 1.0) { + return negateResult ? -Math.PI/2 : Math.PI/2; + } else { + return Double.NaN; + } + } + } + } + + /** + * If value is not NaN and is outside [-1,1] range, closest value in this range is used. + * + * @param value Value in [-1,1]. + * @return Value arcsine, in radians, in [-PI/2,PI/2]. + */ + public static double asinInRange(double value) { + if (value <= -1.0) { + return -Math.PI/2; + } else if (value >= 1.0) { + return Math.PI/2; + } else { + return asin(value); + } + } + + /** + * @param value Value in [-1,1]. + * @return Value arccosine, in radians, in [0,PI]. + */ + public static double acos(double value) { + if (USE_JDK_MATH) { + return Math.acos(value); + } + return Math.PI/2 - asin(value); + } + + /** + * If value is not NaN and is outside [-1,1] range, + * closest value in this range is used. + * + * @param value Value in [-1,1]. + * @return Value arccosine, in radians, in [0,PI]. + */ + public static double acosInRange(double value) { + if (value <= -1.0) { + return Math.PI; + } else if (value >= 1.0) { + return 0.0; + } else { + return acos(value); + } + } + + /** + * @param value A double value. + * @return Value arctangent, in radians, in [-PI/2,PI/2]. + */ + public static double atan(double value) { + if (USE_JDK_MATH) { + return Math.atan(value); + } + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + if (value == 1.0) { + // We want "exact" result for 1.0. + return negateResult ? -Math.PI/4 : Math.PI/4; + } else if (value <= ATAN_MAX_VALUE_FOR_TABS) { + int index = (int)(value * ATAN_INDEXER + 0.5); + double delta = value - index * ATAN_DELTA; + double result = MyTAtan.atanTab[index] + + delta * (MyTAtan.atanDer1DivF1Tab[index] + + delta * (MyTAtan.atanDer2DivF2Tab[index] + + delta * (MyTAtan.atanDer3DivF3Tab[index] + + delta * MyTAtan.atanDer4DivF4Tab[index]))); + return negateResult ? -result : result; + } else { // value > ATAN_MAX_VALUE_FOR_TABS, or value is NaN + // This part is derived from fdlibm. + if (value < TWO_POW_66) { + double x = -1/value; + double x2 = x*x; + double x4 = x2*x2; + double s1 = x2*(ATAN_AT0+x4*(ATAN_AT2+x4*(ATAN_AT4+x4*(ATAN_AT6+x4*(ATAN_AT8+x4*ATAN_AT10))))); + double s2 = x4*(ATAN_AT1+x4*(ATAN_AT3+x4*(ATAN_AT5+x4*(ATAN_AT7+x4*ATAN_AT9)))); + double result = ATAN_HI3-((x*(s1+s2)-ATAN_LO3)-x); + return negateResult ? -result : result; + } else { // value >= 2^66, or value is NaN + if (value != value) { + return Double.NaN; + } else { + return negateResult ? -Math.PI/2 : Math.PI/2; + } + } + } + } + + /** + * For special values for which multiple conventions could be adopted, + * behaves like Math.atan2(double,double). + * + * @param y Coordinate on y axis. + * @param x Coordinate on x axis. + * @return Angle from x axis positive side to (x,y) position, in radians, in [-PI,PI]. + * Angle measure is positive when going from x axis to y axis (positive sides). + */ + public static double atan2(double y, double x) { + if (USE_JDK_MATH) { + return Math.atan2(y,x); + } + /* + * Using sub-methods, to make method lighter for general case, + * and to avoid JIT-optimization crash on NaN. + */ + if (x > 0.0) { + if (y == 0.0) { + // +-0.0 + return y; + } + if (x == Double.POSITIVE_INFINITY) { + return atan2_pinf_yyy(y); + } else { + return atan(y/x); + } + } else if (x < 0.0) { + if (y == 0.0) { + return signFromBit(y) * Math.PI; + } + if (x == Double.NEGATIVE_INFINITY) { + return atan2_ninf_yyy(y); + } else if (y > 0.0) { + return Math.PI/2 - atan(x/y); + } else if (y < 0.0) { + return -Math.PI/2 - atan(x/y); + } else { + return Double.NaN; + } + } else { + return atan2_yyy_zeroOrNaN(y, x); + } + } + + /** + * Gives same result as Math.toRadians for some particular values + * like 90.0, 180.0 or 360.0, but is faster (no division). + * + * @param angdeg Angle value in degrees. + * @return Angle value in radians. + */ + public static double toRadians(double angdeg) { + if (USE_JDK_MATH) { + return Math.toRadians(angdeg); + } + return angdeg * (Math.PI/180); + } + + /** + * Gives same result as Math.toDegrees for some particular values + * like Math.PI/2, Math.PI or 2*Math.PI, but is faster (no division). + * + * @param angrad Angle value in radians. + * @return Angle value in degrees. + */ + public static double toDegrees(double angrad) { + if (USE_JDK_MATH) { + return Math.toDegrees(angrad); + } + return angrad * (180/Math.PI); + } + + /** + * @param sign Sign of the angle: true for positive, false for negative. + * @param degrees Degrees, in [0,180]. + * @param minutes Minutes, in [0,59]. + * @param seconds Seconds, in [0.0,60.0[. + * @return Angle in radians. + */ + public static double toRadians(boolean sign, int degrees, int minutes, double seconds) { + return toRadians(toDegrees(sign, degrees, minutes, seconds)); + } + + /** + * @param sign Sign of the angle: true for positive, false for negative. + * @param degrees Degrees, in [0,180]. + * @param minutes Minutes, in [0,59]. + * @param seconds Seconds, in [0.0,60.0[. + * @return Angle in degrees. + */ + public static double toDegrees(boolean sign, int degrees, int minutes, double seconds) { + double signFactor = sign ? 1.0 : -1.0; + return signFactor * (degrees + (1.0/60)*(minutes + (1.0/60)*seconds)); + } + + /** + * @param angrad Angle in radians. + * @param degrees (out) Degrees, in [0,180]. + * @param minutes (out) Minutes, in [0,59]. + * @param seconds (out) Seconds, in [0.0,60.0[. + * @return true if the resulting angle in [-180deg,180deg] is positive, false if it is negative. + */ + public static boolean toDMS(double angrad, IntWrapper degrees, IntWrapper minutes, DoubleWrapper seconds) { + // Computing longitude DMS. + double tmp = toDegrees(normalizeMinusPiPi(angrad)); + boolean isNeg = (tmp < 0.0); + if (isNeg) { + tmp = -tmp; + } + degrees.value = (int)tmp; + tmp = (tmp-degrees.value)*60.0; + minutes.value = (int)tmp; + seconds.value = Math.min((tmp-minutes.value)*60.0,DOUBLE_BEFORE_60); + return !isNeg; + } + + /** + * NB: Since 2*Math.PI < 2*PI, a span of 2*Math.PI does not mean full angular range. + * ex.: isInClockwiseDomain(0.0, 2*Math.PI, -1e-20) returns false. + * ---> For full angular range, use a span > 2*Math.PI, like 2*PI_SUP constant of this class. + * + * @param startAngRad An angle, in radians. + * @param angSpanRad An angular span, >= 0.0, in radians. + * @param angRad An angle, in radians. + * @return true if angRad is in the clockwise angular domain going from startAngRad, over angSpanRad, + * extremities included, false otherwise. + */ + public static boolean isInClockwiseDomain(double startAngRad, double angSpanRad, double angRad) { + if (Math.abs(angRad) < -TWO_MATH_PI_IN_MINUS_PI_PI) { + // special case for angular values of small magnitude + if (angSpanRad <= 2*Math.PI) { + if (angSpanRad < 0.0) { + // empty domain + return false; + } + // angSpanRad is in [0,2*PI] + startAngRad = normalizeMinusPiPi(startAngRad); + double endAngRad = normalizeMinusPiPi(startAngRad + angSpanRad); + if (startAngRad <= endAngRad) { + return (angRad >= startAngRad) && (angRad <= endAngRad); + } else { + return (angRad >= startAngRad) || (angRad <= endAngRad); + } + } else { // angSpanRad > 2*Math.PI, or is NaN + return (angSpanRad == angSpanRad); + } + } else { + // general case + return (normalizeZeroTwoPi(angRad - startAngRad) <= angSpanRad); + } + } + + /* + * hyperbolic trigonometry + */ + + /** + * Some properties of sinh(x) = (exp(x)-exp(-x))/2: + * 1) defined on ]-Infinity,+Infinity[ + * 2) result in ]-Infinity,+Infinity[ + * 3) sinh(x) = -sinh(-x) (implies sinh(0) = 0) + * 4) sinh(epsilon) ~= epsilon + * 5) lim(sinh(x),x->+Infinity) = +Infinity + * (y increasing exponentially faster than x) + * 6) reaches +Infinity (double overflow) for x >= 710.475860073944, + * i.e. a bit further than exp(x) + * + * @param value A double value. + * @return Value hyperbolic sine. + */ + public static double sinh(double value) { + if (USE_JDK_MATH) { + return Math.sinh(value); + } + // sinh(x) = (exp(x)-exp(-x))/2 + double h; + if (value < 0.0) { + value = -value; + h = -0.5; + } else { + h = 0.5; + } + if (value < 22.0) { + if (value < TWO_POW_N28) { + return (h < 0.0) ? -value : value; + } else { + // sinh(x) + // = (exp(x)-exp(-x))/2 + // = (exp(x)-1/exp(x))/2 + // = (expm1(x) + 1 - 1/(expm1(x)+1))/2 + // = (expm1(x) + (expm1(x)+1)/(expm1(x)+1) - 1/(expm1(x)+1))/2 + // = (expm1(x) + expm1(x)/(expm1(x)+1))/2 + double t = expm1(value); + // Might be more accurate, if value < 1: return h*((t+t)-t*t/(t+1.0)). + return h * (t + t/(t+1.0)); + } + } else if (value < LOG_DOUBLE_MAX_VALUE) { + return h * exp(value); + } else { + double t = exp(value*0.5); + return (h*t)*t; + } + } + + /** + * Some properties of cosh(x) = (exp(x)+exp(-x))/2: + * 1) defined on ]-Infinity,+Infinity[ + * 2) result in [1,+Infinity[ + * 3) cosh(0) = 1 + * 4) cosh(x) = cosh(-x) + * 5) lim(cosh(x),x->+Infinity) = +Infinity + * (y increasing exponentially faster than x) + * 6) reaches +Infinity (double overflow) for x >= 710.475860073944, + * i.e. a bit further than exp(x) + * + * @param value A double value. + * @return Value hyperbolic cosine. + */ + public static double cosh(double value) { + if (USE_JDK_MATH) { + return Math.cosh(value); + } + // cosh(x) = (exp(x)+exp(-x))/2 + if (value < 0.0) { + value = -value; + } + if (value < LOG_TWO_POW_27) { + if (value < TWO_POW_N27) { + // cosh(x) + // = (exp(x)+exp(-x))/2 + // = ((1+x+x^2/2!+...) + (1-x+x^2/2!-...))/2 + // = 1+x^2/2!+x^4/4!+... + // For value of x small in magnitude, the sum of the terms does not add to 1. + return 1; + } else { + // cosh(x) + // = (exp(x)+exp(-x))/2 + // = (exp(x)+1/exp(x))/2 + double t = exp(value); + return 0.5 * (t+1/t); + } + } else if (value < LOG_DOUBLE_MAX_VALUE) { + return 0.5 * exp(value); + } else { + double t = exp(value*0.5); + return (0.5*t)*t; + } + } + + /** + * Much more accurate than cosh(value)-1, + * for arguments (and results) close to zero. + * + * coshm1(-0.0) = -0.0, for homogeneity with + * acosh1p(-0.0) = -0.0. + * + * @param value A double value. + * @return Value hyperbolic cosine, minus 1. + */ + public static double coshm1(double value) { + // cosh(x)-1 = (exp(x)+exp(-x))/2 - 1 + if (value < 0.0) { + value = -value; + } + if (value < LOG_TWO_POW_27) { + if (value < TWO_POW_N27) { + if (value == 0.0) { + // +-0.0 + return value; + } + // Using (expm1(x)+expm1(-x))/2 + // is not accurate for tiny values, + // for expm1 results are of higher + // magnitude than the result and + // of different signs, such as their + // sum is not accurate. + // cosh(x) - 1 + // = (exp(x)+exp(-x))/2 - 1 + // = ((1+x+x^2/2!+...) + (1-x+x^2/2!-...))/2 - 1 + // = x^2/2!+x^4/4!+... + // ~= x^2 * (1/2 + x^2 * 1/24) + // = x^2 * 0.5 (since x < 2^-27) + return 0.5 * value*value; + } else { + // cosh(x) - 1 + // = (exp(x)+exp(-x))/2 - 1 + // = (exp(x)-1+exp(-x)-1)/2 + // = (expm1(x)+expm1(-x))/2 + return 0.5 * (expm1(value)+expm1(-value)); + } + } else if (value < LOG_DOUBLE_MAX_VALUE) { + return 0.5 * exp(value) - 1.0; + } else { + // No need to subtract 1 from result. + double t = exp(value*0.5); + return (0.5*t)*t; + } + } + + /** + * Computes hyperbolic sine and hyperbolic cosine together. + * + * @param value A double value. + * @param hcosine (out) Value hyperbolic cosine. + * @return Value hyperbolic sine. + */ + public static double sinhAndCosh(double value, DoubleWrapper hcosine) { + if (USE_JDK_MATH) { + hcosine.value = Math.cosh(value); + return Math.sinh(value); + } + // Mixup of sinh and cosh treatments: if you modify them, + // you might want to also modify this. + double h; + if (value < 0.0) { + value = -value; + h = -0.5; + } else { + h = 0.5; + } + final double hsine; + // LOG_TWO_POW_27 = 18.714973875118524 + if (value < LOG_TWO_POW_27) { // test from cosh + // sinh + if (value < TWO_POW_N28) { + hsine = (h < 0.0) ? -value : value; + } else { + double t = expm1(value); + hsine = h * (t + t/(t+1.0)); + } + // cosh + if (value < TWO_POW_N27) { + hcosine.value = 1; + } else { + double t = exp(value); + hcosine.value = 0.5 * (t+1/t); + } + } else if (value < 22.0) { // test from sinh + // Here, value is in [18.714973875118524,22.0[. + double t = expm1(value); + hsine = h * (t + t/(t+1.0)); + hcosine.value = 0.5 * (t+1.0); + } else { + if (value < LOG_DOUBLE_MAX_VALUE) { + hsine = h * exp(value); + } else { + double t = exp(value*0.5); + hsine = (h*t)*t; + } + hcosine.value = Math.abs(hsine); + } + return hsine; + } + + /** + * Some properties of tanh(x) = sinh(x)/cosh(x) = (exp(2*x)-1)/(exp(2*x)+1): + * 1) defined on ]-Infinity,+Infinity[ + * 2) result in ]-1,1[ + * 3) tanh(x) = -tanh(-x) (implies tanh(0) = 0) + * 4) tanh(epsilon) ~= epsilon + * 5) lim(tanh(x),x->+Infinity) = 1 + * 6) reaches 1 (double loss of precision) for x = 19.061547465398498 + * + * @param value A double value. + * @return Value hyperbolic tangent. + */ + public static double tanh(double value) { + if (USE_JDK_MATH) { + return Math.tanh(value); + } + // tanh(x) = sinh(x)/cosh(x) + // = (exp(x)-exp(-x))/(exp(x)+exp(-x)) + // = (exp(2*x)-1)/(exp(2*x)+1) + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + double z; + if (value < TANH_1_THRESHOLD) { + if (value < TWO_POW_N55) { + return negateResult ? -value*(1.0-value) : value*(1.0+value); + } else if (value >= 1) { + z = 1.0-2.0/(expm1(value+value)+2.0); + } else { + double t = expm1(-(value+value)); + z = -t/(t+2.0); + } + } else { + z = (value != value) ? Double.NaN : 1.0; + } + return negateResult ? -z : z; + } + + /** + * Some properties of asinh(x) = log(x + sqrt(x^2 + 1)) + * 1) defined on ]-Infinity,+Infinity[ + * 2) result in ]-Infinity,+Infinity[ + * 3) asinh(x) = -asinh(-x) (implies asinh(0) = 0) + * 4) asinh(epsilon) ~= epsilon + * 5) lim(asinh(x),x->+Infinity) = +Infinity + * (y increasing logarithmically slower than x) + * + * @param value A double value. + * @return Value hyperbolic arcsine. + */ + public static double asinh(double value) { + // asinh(x) = log(x + sqrt(x^2 + 1)) + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + double result; + // (about) smallest possible for + // non-log1p case to be accurate. + if (value < ASINH_LOG1P_THRESHOLD) { + // Around this range, FDLIBM uses + // log1p(value+value*value/(1+sqrt(value*value+1))), + // but it's slower, so we don't use it. + /* + * If x is close to zero, log argument is close to 1, + * so to avoid precision loss we use log1p(double), + * with + * (1+x)^p = 1 + p * x + (p*(p-1))/2! * x^2 + (p*(p-1)*(p-2))/3! * x^3 + ... + * (1+x)^p = 1 + p * x * (1 + (p-1)/2 * x * (1 + (p-2)/3 * x + ...) + * (1+x)^0.5 = 1 + 0.5 * x * (1 + (0.5-1)/2 * x * (1 + (0.5-2)/3 * x + ...) + * (1+x^2)^0.5 = 1 + 0.5 * x^2 * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...) + * x + (1+x^2)^0.5 = 1 + x * (1 + 0.5 * x * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...)) + * so + * asinh(x) = log1p(x * (1 + 0.5 * x * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...))) + */ + final double x = value; + final double x2 = x*x; + // Enough terms for good accuracy, + // given our threshold. + final double argLog1p = (x * + (1 + 0.5 * x + * (1 + (0.5-1)/2 * x2 + * (1 + (0.5-2)/3 * x2 + * (1 + (0.5-3)/4 * x2 + * (1 + (0.5-4)/5 * x2 + )))))); + result = log1p(argLog1p); + } else if (value < ASINH_ACOSH_SQRT_ELISION_THRESHOLD) { + // Around this range, FDLIBM uses + // log(2*value+1/(value+sqrt(value*value+1))), + // but it involves an additional division + // so we don't use it. + result = log(value + sqrt(value*value + 1.0)); + } else { + // log(2*value) would overflow for value > Double.MAX_VALUE/2, + // so we compute otherwise. + result = LOG_2 + log(value); + } + return negateResult ? -result : result; + } + + /** + * Some properties of acosh(x) = log(x + sqrt(x^2 - 1)): + * 1) defined on [1,+Infinity[ + * 2) result in ]0,+Infinity[ (by convention, since cosh(x) = cosh(-x)) + * 3) acosh(1) = 0 + * 4) acosh(1+epsilon) ~= log(1 + sqrt(2*epsilon)) ~= sqrt(2*epsilon) + * 5) lim(acosh(x),x->+Infinity) = +Infinity + * (y increasing logarithmically slower than x) + * + * @param value A double value. + * @return Value hyperbolic arccosine. + */ + public static double acosh(double value) { + if (!(value > 1.0)) { + // NaN, or value <= 1 + if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { + return (value < 1.0) ? Double.NaN : value - 1.0; + } else { + return (value == 1.0) ? 0.0 : Double.NaN; + } + } + double result; + if (value < ASINH_ACOSH_SQRT_ELISION_THRESHOLD) { + // Around this range, FDLIBM uses + // log(2*value-1/(value+sqrt(value*value-1))), + // but it involves an additional division + // so we don't use it. + result = log(value + sqrt(value*value - 1.0)); + } else { + // log(2*value) would overflow for value > Double.MAX_VALUE/2, + // so we compute otherwise. + result = LOG_2 + log(value); + } + return result; + } + + /** + * Much more accurate than acosh(1+value), + * for arguments (and results) close to zero. + * + * acosh1p(-0.0) = -0.0, for homogeneity with + * sqrt(-0.0) = -0.0, which looks about the same + * near 0. + * + * @param value A double value. + * @return Hyperbolic arccosine of (1+value). + */ + public static double acosh1p(double value) { + if (!(value > 0.0)) { + // NaN, or value <= 0. + // If value is -0.0, returning -0.0. + if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { + return (value < 0.0) ? Double.NaN : value; + } else { + return (value == 0.0) ? value : Double.NaN; + } + } + double result; + if (value < (ASINH_ACOSH_SQRT_ELISION_THRESHOLD-1)) { + // acosh(1+x) + // = log((1+x) + sqrt((1+x)^2 - 1)) + // = log(1 + x + sqrt(1 + 2*x + x^2 - 1)) + // = log1p(x + sqrt(2*x + x^2)) + // = log1p(x + sqrt(x * (2 + x)) + result = log1p(value + sqrt(value * (2 + value))); + } else { + result = LOG_2 + log(1+value); + } + return result; + } + + /** + * Some properties of atanh(x) = log((1+x)/(1-x))/2: + * 1) defined on ]-1,1[ + * 2) result in ]-Infinity,+Infinity[ + * 3) atanh(-1) = -Infinity (by continuity) + * 4) atanh(1) = +Infinity (by continuity) + * 5) atanh(epsilon) ~= epsilon + * 6) lim(atanh(x),x->1) = +Infinity + * + * @param value A double value. + * @return Value hyperbolic arctangent. + */ + public static double atanh(double value) { + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + double result; + if (!(value < 1.0)) { + // NaN, or value >= 1 + if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { + result = (value > 1.0) ? Double.NaN : Double.POSITIVE_INFINITY + value; + } else { + result = (value == 1.0) ? Double.POSITIVE_INFINITY : Double.NaN; + } + } else { + // For value < 0.5, FDLIBM uses + // 0.5 * log1p((value+value) + (value+value)*value/(1-value)), + // instead, but this is good enough for us. + // atanh(x) + // = log((1+x)/(1-x))/2 + // = log((1-x+2x)/(1-x))/2 + // = log1p(2x/(1-x))/2 + result = 0.5 * log1p((value+value)/(1.0-value)); + } + return negateResult ? -result : result; + } + + /* + * exponentials + */ + + /** + * @param value A double value. + * @return e^value. + */ + public static double exp(double value) { + if (USE_JDK_MATH) { + return Math.exp(value); + } + // exp(x) = exp([x])*exp(y) + // with [x] the integer part of x, and y = x-[x] + // ===> + // We find an approximation of y, called z. + // ===> + // exp(x) = exp([x])*(exp(z)*exp(epsilon)) + // with epsilon = y - z + // ===> + // We have exp([x]) and exp(z) pre-computed in tables, we "just" have to compute exp(epsilon). + // + // We use the same indexing (cast to int) to compute x integer part and the + // table index corresponding to z, to avoid two int casts. + // Also, to optimize index multiplication and division, we use powers of two, + // so that we can do it with bits shifts. + + if (value > EXP_OVERFLOW_LIMIT) { + return Double.POSITIVE_INFINITY; + } else if (!(value >= EXP_UNDERFLOW_LIMIT)) { + return (value != value) ? Double.NaN : 0.0; + } + + final int indexes = (int)(value*EXP_LO_INDEXING); + + final int valueInt; + if (indexes >= 0) { + valueInt = (indexes>>EXP_LO_INDEXING_DIV_SHIFT); + } else { + valueInt = -((-indexes)>>EXP_LO_INDEXING_DIV_SHIFT); + } + final double hiTerm = MyTExp.expHiTab[valueInt-(int)EXP_UNDERFLOW_LIMIT]; + + final int zIndex = indexes - (valueInt< 0.0) { + if (value == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } + + // For normal values not close to 1.0, we use the following formula: + // log(value) + // = log(2^exponent*1.mantissa) + // = log(2^exponent) + log(1.mantissa) + // = exponent * log(2) + log(1.mantissa) + // = exponent * log(2) + log(1.mantissaApprox) + log(1.mantissa/1.mantissaApprox) + // = exponent * log(2) + log(1.mantissaApprox) + log(1+epsilon) + // = exponent * log(2) + log(1.mantissaApprox) + epsilon-epsilon^2/2+epsilon^3/3-epsilon^4/4+... + // with: + // 1.mantissaApprox <= 1.mantissa, + // log(1.mantissaApprox) in table, + // epsilon = (1.mantissa/1.mantissaApprox)-1 + // + // To avoid bad relative error for small results, + // values close to 1.0 are treated aside, with the formula: + // log(x) = z*(2+z^2*((2.0/3)+z^2*((2.0/5))+z^2*((2.0/7))+...))) + // with z=(x-1)/(x+1) + + double h; + if (value > 0.95) { + if (value < 1.14) { + double z = (value-1.0)/(value+1.0); + double z2 = z*z; + return z*(2+z2*((2.0/3)+z2*((2.0/5)+z2*((2.0/7)+z2*((2.0/9)+z2*((2.0/11))))))); + } + h = 0.0; + } else if (value < DOUBLE_MIN_NORMAL) { + // Ensuring value is normal. + value *= TWO_POW_52; + // log(x*2^52) + // = log(x)-ln(2^52) + // = log(x)-52*ln(2) + h = -52*LOG_2; + } else { + h = 0.0; + } + + int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); + int valueExp = (valueBitsHi>>20)-MAX_DOUBLE_EXPONENT; + // Getting the first LOG_BITS bits of the mantissa. + int xIndex = ((valueBitsHi<<12)>>>(32-LOG_BITS)); + + // 1.mantissa/1.mantissaApprox - 1 + double z = (value * twoPowNormalOrSubnormal(-valueExp)) * MyTLog.logXInvTab[xIndex] - 1; + + z *= (1-z*((1.0/2)-z*((1.0/3)))); + + return h + valueExp * LOG_2 + (MyTLog.logXLogTab[xIndex] + z); + + } else if (value == 0.0) { + return Double.NEGATIVE_INFINITY; + } else { // value < 0.0, or value is NaN + return Double.NaN; + } + } + + /** + * Quick log, with a max relative error of about 1.9e-3 + * for values in ]Double.MIN_NORMAL,+Infinity[, and + * worse accuracy outside this range. + * + * @param value A double value, in ]0,+Infinity[ (strictly positive and finite). + * @return Value logarithm (base e). + */ + public static double logQuick(double value) { + if (USE_JDK_MATH) { + return Math.log(value); + } + /* + * Inverse of Schraudolph's method for exp, is very inaccurate near 1, + * and not that fast (even using floats), especially with added if's + * to deal with values near 1, so we don't use it, and use a simplified + * version of our log's redefined algorithm. + */ + + // Simplified version of log's redefined algorithm: + // log(value) ~= exponent * log(2) + log(1.mantissaApprox) + + double h; + if (value > 0.87) { + if (value < 1.16) { + return 2.0 * (value-1.0)/(value+1.0); + } + h = 0.0; + } else if (value < DOUBLE_MIN_NORMAL) { + value *= TWO_POW_52; + h = -52*LOG_2; + } else { + h = 0.0; + } + + int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); + int valueExp = (valueBitsHi>>20)-MAX_DOUBLE_EXPONENT; + int xIndex = ((valueBitsHi<<12)>>>(32-LOG_BITS)); + + return h + valueExp * LOG_2 + MyTLog.logXLogTab[xIndex]; + } + + /** + * @param value A double value. + * @return Value logarithm (base 10). + */ + public static double log10(double value) { + if (USE_JDK_MATH || (!USE_REDEFINED_LOG)) { + return Math.log10(value); + } + // INV_LOG_10 is < 1, but there is no risk of log(double) + // overflow (positive or negative) while the end result shouldn't, + // since log(Double.MIN_VALUE) and log(Double.MAX_VALUE) have + // magnitudes of just a few hundreds. + return log(value) * INV_LOG_10; + } + + /** + * Much more accurate than log(1+value), + * for arguments (and results) close to zero. + * + * @param value A double value. + * @return Logarithm (base e) of (1+value). + */ + public static double log1p(double value) { + if (USE_JDK_MATH) { + return Math.log1p(value); + } + if (false) { + // This also works. Simpler but a bit slower. + if (value == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } + double valuePlusOne = 1+value; + if (valuePlusOne == 1.0) { + return value; + } else { + return log(valuePlusOne)*(value/(valuePlusOne-1.0)); + } + } + if (value > -1.0) { + if (value == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } + + // ln'(x) = 1/x + // so + // log(x+epsilon) ~= log(x) + epsilon/x + // + // Let u be 1+value rounded: + // 1+value = u+epsilon + // + // log(1+value) + // = log(u+epsilon) + // ~= log(u) + epsilon/value + // We compute log(u) as done in log(double), and then add the corrective term. + + double valuePlusOne = 1.0+value; + if (valuePlusOne == 1.0) { + return value; + } else if (Math.abs(value) < 0.15) { + double z = value/(value+2.0); + double z2 = z*z; + return z*(2+z2*((2.0/3)+z2*((2.0/5)+z2*((2.0/7)+z2*((2.0/9)+z2*((2.0/11))))))); + } + + int valuePlusOneBitsHi = (int)(Double.doubleToRawLongBits(valuePlusOne)>>32) & 0x7FFFFFFF; + int valuePlusOneExp = (valuePlusOneBitsHi>>20)-MAX_DOUBLE_EXPONENT; + // Getting the first LOG_BITS bits of the mantissa. + int xIndex = ((valuePlusOneBitsHi<<12)>>>(32-LOG_BITS)); + + // 1.mantissa/1.mantissaApprox - 1 + double z = (valuePlusOne * twoPowNormalOrSubnormal(-valuePlusOneExp)) * MyTLog.logXInvTab[xIndex] - 1; + + z *= (1-z*((1.0/2)-z*(1.0/3))); + + // Adding epsilon/valuePlusOne to z, + // with + // epsilon = value - (valuePlusOne-1) + // (valuePlusOne + epsilon ~= 1+value (not rounded)) + + return valuePlusOneExp * LOG_2 + MyTLog.logXLogTab[xIndex] + (z + (value - (valuePlusOne-1))/valuePlusOne); + } else if (value == -1.0) { + return Double.NEGATIVE_INFINITY; + } else { // value < -1.0, or value is NaN + return Double.NaN; + } + } + + /* + * powers + */ + + /** + * 1e-13ish accuracy or better on whole double range. + * + * @param value A double value. + * @param power A power. + * @return value^power. + */ + public static double pow(double value, double power) { + if (USE_JDK_MATH) { + return Math.pow(value,power); + } + if (power == 0.0) { + return 1.0; + } else if (power == 1.0) { + return value; + } + if (value <= 0.0) { + // powerInfo: 0 if not integer, 1 if even integer, -1 if odd integer + int powerInfo; + if (Math.abs(power) >= (TWO_POW_52*2)) { + // The binary digit just before comma is outside mantissa, + // thus it is always 0: power is an even integer. + powerInfo = 1; + } else { + // If power's magnitude permits, we cast into int instead of into long, + // as it is faster. + if (Math.abs(power) <= (double)Integer.MAX_VALUE) { + int powerAsInt = (int)power; + if (power == (double)powerAsInt) { + powerInfo = ((powerAsInt & 1) == 0) ? 1 : -1; + } else { // power is not an integer (and not NaN, due to test against Integer.MAX_VALUE) + powerInfo = 0; + } + } else { + long powerAsLong = (long)power; + if (power == (double)powerAsLong) { + powerInfo = ((powerAsLong & 1) == 0) ? 1 : -1; + } else { // power is not an integer, or is NaN + if (power != power) { + return Double.NaN; + } + powerInfo = 0; + } + } + } + + if (value == 0.0) { + if (power < 0.0) { + return (powerInfo < 0) ? 1/value : Double.POSITIVE_INFINITY; + } else { // power > 0.0 (0 and NaN cases already treated) + return (powerInfo < 0) ? value : 0.0; + } + } else { // value < 0.0 + if (value == Double.NEGATIVE_INFINITY) { + if (powerInfo < 0) { // power odd integer + return (power < 0.0) ? -0.0 : Double.NEGATIVE_INFINITY; + } else { // power even integer, or not an integer + return (power < 0.0) ? 0.0 : Double.POSITIVE_INFINITY; + } + } else { + return (powerInfo == 0) ? Double.NaN : powerInfo * exp(power*log(-value)); + } + } + } else { // value > 0.0, or value is NaN + return exp(power*log(value)); + } + } + + /** + * Quick pow, with a max relative error of about 1e-2 + * for value >= Double.MIN_NORMAL and 1e-10 < |value^power| < 1e10, + * of about 6e-2 for value >= Double.MIN_NORMAL and 1e-40 < |value^power| < 1e40, + * and worse accuracy otherwise. + * + * @param value A double value, in ]0,+Infinity[ (strictly positive and finite). + * @param power A double value. + * @return value^power. + */ + public static double powQuick(double value, double power) { + if (USE_JDK_MATH) { + return Math.pow(value,power); + } + return exp(power*logQuick(value)); + } + + /** + * This treatment is somehow accurate for low values of |power|, + * and for |power*getExponent(value)| < 1023 or so (to stay away + * from double extreme magnitudes (large and small)). + * + * @param value A double value. + * @param power A power. + * @return value^power. + */ + public static double powFast(double value, int power) { + if (USE_JDK_MATH) { + return Math.pow(value,power); + } + if (power < 3) { + if (power < 0) { + // Opposite of Integer.MIN_VALUE does not exist as int. + if (power == Integer.MIN_VALUE) { + // Integer.MAX_VALUE = -(power+1) + return 1.0/(powFast(value,Integer.MAX_VALUE) * value); + } else { + return 1.0/powFast(value,-power); + } + } else { + // Here, power is in [0,2]. + if (power == 2) { // Most common case first. + return value * value; + } else if (power == 0) { + return 1.0; + } else { // power == 1 + return value; + } + } + } else { // power >= 4 + double oddRemains = 1.0; + // If power <= 5, faster to finish outside the loop. + while (power > 5) { + // Test if power is odd. + if ((power & 1) != 0) { + oddRemains *= value; + } + value *= value; + power >>= 1; // power = power / 2 + } + // Here, power is in [3,5]. + if (power == 3) { + return oddRemains * value * value * value; + } else { // power in [4,5]. + double v2 = value * value; + if (power == 4) { + return oddRemains * v2 * v2; + } else { // power == 5 + return oddRemains * v2 * v2 * value; + } + } + } + } + + /** + * @param value A float value. + * @return value*value. + */ + public static float pow2(float value) { + return value*value; + } + + /** + * @param value A double value. + * @return value*value. + */ + public static double pow2(double value) { + return value*value; + } + + /** + * @param value A float value. + * @return value*value*value. + */ + public static float pow3(float value) { + return value*value*value; + } + + /** + * @param value A double value. + * @return value*value*value. + */ + public static double pow3(double value) { + return value*value*value; + } + + /* + * roots + */ + + /** + * @param value A double value. + * @return Value square root. + */ + public static double sqrt(double value) { + if (USE_JDK_MATH || (!USE_REDEFINED_SQRT)) { + return Math.sqrt(value); + } + // See cbrt for comments, sqrt uses the same ideas. + + if (!(value > 0.0)) { // value <= 0.0, or value is NaN + if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { + return (value < 0.0) ? Double.NaN : value; + } else { + return (value == 0.0) ? value : Double.NaN; + } + } else if (value == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } + + double h; + if (value < DOUBLE_MIN_NORMAL) { + value *= TWO_POW_52; + h = 2*TWO_POW_N26; + } else { + h = 2.0; + } + + int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); + int valueExponentIndex = (valueBitsHi>>20)+(-MAX_DOUBLE_EXPONENT-MIN_DOUBLE_EXPONENT); + int xIndex = ((valueBitsHi<<12)>>>(32-SQRT_LO_BITS)); + + double result = MyTSqrt.sqrtXSqrtHiTab[valueExponentIndex] * MyTSqrt.sqrtXSqrtLoTab[xIndex]; + double slope = MyTSqrt.sqrtSlopeHiTab[valueExponentIndex] * MyTSqrt.sqrtSlopeLoTab[xIndex]; + value *= 0.25; + + result += (value - result * result) * slope; + result += (value - result * result) * slope; + return h*(result + (value - result * result) * slope); + } + + /** + * Quick sqrt, with with a max relative error of about 3.41e-2 + * for values in [Double.MIN_NORMAL,Double.MAX_VALUE], and worse + * accuracy outside this range. + * + * @param value A double value. + * @return Value square root. + */ + public static double sqrtQuick(double value) { + if (USE_JDK_MATH) { + return Math.sqrt(value); + } + final long bits = Double.doubleToRawLongBits(value); + /* + * Constant determined empirically, using a random-based metaheuristic. + * Should be possible to find a better one. + */ + return Double.longBitsToDouble((bits+4606859074900000000L)>>>1); + } + + /** + * Quick inverse of square root, with a max relative error of about 3.44e-2 + * for values in [Double.MIN_NORMAL,Double.MAX_VALUE], and worse accuracy + * outside this range. + * + * This implementation uses zero step of Newton's method. + * Here are the max relative errors on [Double.MIN_NORMAL,Double.MAX_VALUE] + * depending on number of steps, if you want to copy-paste this code + * and use your own number: + * n=0: about 3.44e-2 + * n=1: about 1.75e-3 + * n=2: about 4.6e-6 + * n=3: about 3.17e-11 + * n=4: about 3.92e-16 + * n=5: about 3.03e-16 + * + * @param value A double value. + * @return Inverse of value square root. + */ + public static double invSqrtQuick(double value) { + if (USE_JDK_MATH) { + return 1/Math.sqrt(value); + } + /* + * http://en.wikipedia.org/wiki/Fast_inverse_square_root + */ + if (false) { + // With one Newton step (much slower than + // 1/Math.sqrt(double) if not optimized). + final double halfInitial = value * 0.5; + long bits = Double.doubleToRawLongBits(value); + // If n=0, 6910474759270000000L might be better (3.38e-2 max relative error). + bits = 0x5FE6EB50C7B537A9L - (bits>>1); + value = Double.longBitsToDouble(bits); + value = value * (1.5 - halfInitial * value * value); // Newton step, can repeat. + return value; + } else { + return Double.longBitsToDouble(0x5FE6EB50C7B537A9L - (Double.doubleToRawLongBits(value)>>1)); + } + } + + /** + * @param value A double value. + * @return Value cubic root. + */ + public static double cbrt(double value) { + if (USE_JDK_MATH) { + return Math.cbrt(value); + } + double h; + if (value < 0.0) { + if (value == Double.NEGATIVE_INFINITY) { + return Double.NEGATIVE_INFINITY; + } + value = -value; + // Making sure value is normal. + if (value < DOUBLE_MIN_NORMAL) { + value *= (TWO_POW_52*TWO_POW_26); + // h = * / + h = -2*TWO_POW_N26; + } else { + h = -2.0; + } + } else { + if (!(value < Double.POSITIVE_INFINITY)) { // value is +Infinity, or value is NaN + return value; + } + // Making sure value is normal. + if (value < DOUBLE_MIN_NORMAL) { + if (value == 0.0) { + // cbrt(0.0) = 0.0, cbrt(-0.0) = -0.0 + return value; + } + value *= (TWO_POW_52*TWO_POW_26); + h = 2*TWO_POW_N26; + } else { + h = 2.0; + } + } + + // Normal value is (2^ * ). + // First member cubic root is computed, and multiplied with an approximation + // of the cubic root of the second member, to end up with a good guess of + // the result before using Newton's (or Archimedes's) method. + // To compute the cubic root approximation, we use the formula "cbrt(value) = cbrt(x) * cbrt(value/x)", + // choosing x as close to value as possible but inferior to it, so that cbrt(value/x) is close to 1 + // (we could iterate on this method, using value/x as new value for each iteration, + // but finishing with Newton's method is faster). + + // Shift and cast into an int, which overall is faster than working with a long. + int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); + int valueExponentIndex = (valueBitsHi>>20)+(-MAX_DOUBLE_EXPONENT-MIN_DOUBLE_EXPONENT); + // Getting the first CBRT_LO_BITS bits of the mantissa. + int xIndex = ((valueBitsHi<<12)>>>(32-CBRT_LO_BITS)); + double result = MyTCbrt.cbrtXCbrtHiTab[valueExponentIndex] * MyTCbrt.cbrtXCbrtLoTab[xIndex]; + double slope = MyTCbrt.cbrtSlopeHiTab[valueExponentIndex] * MyTCbrt.cbrtSlopeLoTab[xIndex]; + + // Lowering values to avoid overflows when using Newton's method + // (we will then just have to return twice the result). + // result^3 = value + // (result/2)^3 = value/8 + value *= 0.125; + // No need to divide result here, as division is factorized in result computation tables. + // result *= 0.5; + + // Newton's method, looking for y = x^(1/p): + // y(n) = y(n-1) + (x-y(n-1)^p) * slope(y(n-1)) + // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(x(n-1)^(1/p-1)) + // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(x(n-1)^((1-p)/p)) + // with x(n-1)=y(n-1)^p, i.e.: + // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(y(n-1)^(1-p)) + // + // For p=3: + // y(n) = y(n-1) + (x-y(n-1)^3) * (1/(3*y(n-1)^2)) + + // To save time, we don't recompute the slope between Newton's method steps, + // as initial slope is good enough for a few iterations. + // + // NB: slope = 1/(3*trueResult*trueResult) + // As we have result = trueResult/2 (to avoid overflows), we have: + // slope = 4/(3*result*result) + // = (4/3)*resultInv*resultInv + // with newResultInv = 1/newResult + // = 1/(oldResult+resultDelta) + // = (oldResultInv)*1/(1+resultDelta/oldResult) + // = (oldResultInv)*1/(1+resultDelta*oldResultInv) + // ~= (oldResultInv)*(1-resultDelta*oldResultInv) + // ===> Successive slopes could be computed without division, if needed, + // by computing resultInv (instead of slope right away) and retrieving + // slopes from it. + + result += (value - result * result * result) * slope; + result += (value - result * result * result) * slope; + return h*(result + (value - result * result * result) * slope); + } + + /** + * @return sqrt(x^2+y^2) without intermediate overflow or underflow. + */ + public static double hypot(double x, double y) { + if (USE_JDK_MATH) { + return Math.hypot(x,y); + } + x = Math.abs(x); + y = Math.abs(y); + // Ensuring x <= y. + if (y < x) { + double a = x; + x = y; + y = a; + } else if (!(y >= x)) { // Testing if we have some NaN. + return hypot_NaN(x, y); + } + + if (y-x == y) { + // x too small to subtract from y. + return y; + } else { + double factor; + if (y > HYPOT_MAX_MAG) { + // y is too large: scaling down. + x *= (1/HYPOT_FACTOR); + y *= (1/HYPOT_FACTOR); + factor = HYPOT_FACTOR; + } else if (x < (1/HYPOT_MAX_MAG)) { + // x is too small: scaling up. + x *= HYPOT_FACTOR; + y *= HYPOT_FACTOR; + factor = (1/HYPOT_FACTOR); + } else { + factor = 1.0; + } + return factor * sqrt(x*x+y*y); + } + } + + /** + * @return sqrt(x^2+y^2+z^2) without intermediate overflow or underflow. + */ + public static double hypot(double x, double y, double z) { + if (USE_JDK_MATH) { + // No simple JDK equivalent. + } + x = Math.abs(x); + y = Math.abs(y); + z = Math.abs(z); + /* + * Considering that z magnitude is the most likely to be the smaller, + * hence ensuring z <= y <= x, and not x <= y <= z, for less swaps. + */ + // Ensuring z <= y. + if (z > y) { + // y < z: swapping y and z + double a = z; + z = y; + y = a; + } else if (!(z <= y)) { // Testing if y or z is NaN. + return hypot_NaN(x, y, z); + } + // Ensuring y <= x. + if (z > x) { + // x < z <= y: moving x + double oldZ = z; + z = x; + double oldY = y; + y = oldZ; + x = oldY; + } else if (y > x) { + // z <= x < y: swapping x and y + double a = y; + y = x; + x = a; + } else if (x != x) { // Testing if x is NaN. + return hypot_NaN(x, y, z); + } + + if (x-y == x) { + // y, hence z, too small to subtract from x. + return x; + } else if (y-z == y) { + // z too small to subtract from y, hence x. + double factor; + if (x > HYPOT_MAX_MAG) { + // x is too large: scaling down. + x *= (1/HYPOT_FACTOR); + y *= (1/HYPOT_FACTOR); + factor = HYPOT_FACTOR; + } else if (y < (1/HYPOT_MAX_MAG)) { + // y is too small: scaling up. + x *= HYPOT_FACTOR; + y *= HYPOT_FACTOR; + factor = (1/HYPOT_FACTOR); + } else { + factor = 1.0; + } + return factor * sqrt(x*x+y*y); + } else { + double factor; + if (x > HYPOT_MAX_MAG) { + // x is too large: scaling down. + x *= (1/HYPOT_FACTOR); + y *= (1/HYPOT_FACTOR); + z *= (1/HYPOT_FACTOR); + factor = HYPOT_FACTOR; + } else if (z < (1/HYPOT_MAX_MAG)) { + // z is too small: scaling up. + x *= HYPOT_FACTOR; + y *= HYPOT_FACTOR; + z *= HYPOT_FACTOR; + factor = (1/HYPOT_FACTOR); + } else { + factor = 1.0; + } + // Adding smaller magnitudes together first. + return factor * sqrt(x*x+(y*y+z*z)); + } + } + + /* + * close values + */ + + /** + * @param value A float value. + * @return Floor of value. + */ + public static float floor(float value) { + final int exponent = getExponent(value); + if (exponent < 0) { + // abs(value) < 1. + if (value < 0.0f) { + return -1.0f; + } else { + // 0.0f, or -0.0f if value is -0.0f + return 0.0f * value; + } + } else if (exponent < 23) { + // A bit faster than using casts. + final int bits = Float.floatToRawIntBits(value); + final int anteCommaBits = bits & (0xFF800000>>exponent); + if ((value < 0.0f) && (anteCommaBits != bits)) { + return Float.intBitsToFloat(anteCommaBits) - 1.0f; + } else { + return Float.intBitsToFloat(anteCommaBits); + } + } else { + // +-Infinity, NaN, or a mathematical integer. + return value; + } + } + + /** + * @param value A double value. + * @return Floor of value. + */ + public static double floor(double value) { + if (USE_JDK_MATH) { + return Math.floor(value); + } + if (ANTI_SLOW_CASTS) { + double valueAbs = Math.abs(value); + if (valueAbs <= (double)Integer.MAX_VALUE) { + if (value > 0.0) { + return (double)(int)value; + } else if (value < 0.0) { + double anteCommaDigits = (double)(int)value; + if (value != anteCommaDigits) { + return anteCommaDigits - 1.0; + } else { + return anteCommaDigits; + } + } else { // value is +-0.0 (not NaN due to test against Integer.MAX_VALUE) + return value; + } + } else if (valueAbs < TWO_POW_52) { + // We split the value in two: + // high part, which is a mathematical integer, + // and the rest, for which we can get rid of the + // post comma digits by casting into an int. + double highPart = ((int)(value * TWO_POW_N26)) * TWO_POW_26; + if (value > 0.0) { + return highPart + (double)((int)(value - highPart)); + } else { + double anteCommaDigits = highPart + (double)((int)(value - highPart)); + if (value != anteCommaDigits) { + return anteCommaDigits - 1.0; + } else { + return anteCommaDigits; + } + } + } else { // abs(value) >= 2^52, or value is NaN + return value; + } + } else { + final int exponent = getExponent(value); + if (exponent < 0) { + // abs(value) < 1. + if (value < 0.0) { + return -1.0; + } else { + // 0.0, or -0.0 if value is -0.0 + return 0.0 * value; + } + } else if (exponent < 52) { + // A bit faster than working on bits. + final long matIntPart = (long)value; + final double matIntToValue = value-(double)matIntPart; + if (matIntToValue >= 0.0) { + return (double)matIntPart; + } else { + return (double)(matIntPart - 1); + } + } else { + // +-Infinity, NaN, or a mathematical integer. + return value; + } + } + } + + /** + * @param value A float value. + * @return Ceiling of value. + */ + public static float ceil(float value) { + return -floor(-value); + } + + /** + * @param value A double value. + * @return Ceiling of value. + */ + public static double ceil(double value) { + if (USE_JDK_MATH) { + return Math.ceil(value); + } + return -floor(-value); + } + + /** + * Might have different semantics than Math.round(float), + * see bugs 6430675 and 8010430. + * + * @param value A double value. + * @return Value rounded to nearest int, choosing superior int in case two + * are equally close (i.e. rounding-up). + */ + public static int round(float value) { + /* + * Not delegating to JDK, because we want delegation to provide + * at least as good results, and some supported JDK versions + * have bugged round() methods. + */ + // Algorithm by Dmitry Nadezhin (but replaced an if by a multiply) + // (http://mail.openjdk.java.net/pipermail/core-libs-dev/2013-August/020247.html). + final int bits = Float.floatToRawIntBits(value); + final int biasedExp = ((bits>>23)&0xFF); + // Shift to get rid of bits past comma except first one: will need to + // 1-shift to the right to end up with correct magnitude. + final int shift = (23 - 1 + MAX_FLOAT_EXPONENT) - biasedExp; + if ((shift & -32) == 0) { + int bitsSignum = (((bits >> 31) << 1) + 1); + // shift in [0,31], so unbiased exp in [-9,22]. + int extendedMantissa = (0x00800000 | (bits & 0x007FFFFF)) * bitsSignum; + // If value is positive and first bit past comma is 0, rounding + // to lower integer, else to upper one, which is what "+1" and + // then ">>1" do. + return ((extendedMantissa >> shift) + 1) >> 1; + } else { + // +-Infinity, NaN, or a mathematical integer, or tiny. + if (false && ANTI_SLOW_CASTS) { // not worth it + if (Math.abs(value) >= -(float)Integer.MIN_VALUE) { + // +-Infinity or a mathematical integer (mostly) out of int range. + return (value < 0.0) ? Integer.MIN_VALUE : Integer.MAX_VALUE; + } + // NaN or a mathematical integer (mostly) in int range. + } + return (int)value; + } + } + + /** + * Might have different semantics than Math.round(double), + * see bugs 6430675 and 8010430. + * + * @param value A double value. + * @return Value rounded to nearest long, choosing superior long in case two + * are equally close (i.e. rounding-up). + */ + public static long round(double value) { + /* + * Not delegating to JDK, because we want delegation to provide + * at least as good results, and some supported JDK versions + * have bugged round() methods. + */ + final long bits = Double.doubleToRawLongBits(value); + final int biasedExp = (((int)(bits>>52))&0x7FF); + // Shift to get rid of bits past comma except first one: will need to + // 1-shift to the right to end up with correct magnitude. + final int shift = (52 - 1 + MAX_DOUBLE_EXPONENT) - biasedExp; + if ((shift & -64) == 0) { + long bitsSignum = (((bits >> 63) << 1) + 1); + // shift in [0,63], so unbiased exp in [-12,51]. + long extendedMantissa = (0x0010000000000000L | (bits & 0x000FFFFFFFFFFFFFL)) * bitsSignum; + // If value is positive and first bit past comma is 0, rounding + // to lower integer, else to upper one, which is what "+1" and + // then ">>1" do. + return ((extendedMantissa >> shift) + 1L) >> 1; + } else { + // +-Infinity, NaN, or a mathematical integer, or tiny. + if (ANTI_SLOW_CASTS) { + if (Math.abs(value) >= -(double)Long.MIN_VALUE) { + // +-Infinity or a mathematical integer (mostly) out of long range. + return (value < 0.0) ? Long.MIN_VALUE : Long.MAX_VALUE; + } + // NaN or a mathematical integer (mostly) in long range. + } + return (long)value; + } + } + + /** + * @param value A float value. + * @return Value rounded to nearest int, choosing even int in case two + * are equally close. + */ + public static int roundEven(float value) { + final int sign = signFromBit(value); + value = Math.abs(value); + if (ANTI_SLOW_CASTS) { + if (value < TWO_POW_23_F) { + // Getting rid of post-comma bits. + value = ((value + TWO_POW_23_F) - TWO_POW_23_F); + return sign * (int)value; + } else if (value < (float)Integer.MAX_VALUE) { // "<=" doesn't work, because of float precision + // value is in [-Integer.MAX_VALUE,Integer.MAX_VALUE] + return sign * (int)value; + } + } else { + if (value < TWO_POW_23_F) { + // Getting rid of post-comma bits. + value = ((value + TWO_POW_23_F) - TWO_POW_23_F); + } + } + return (int)(sign * value); + } + + /** + * @param value A double value. + * @return Value rounded to nearest long, choosing even long in case two + * are equally close. + */ + public static long roundEven(double value) { + final int sign = (int)signFromBit(value); + value = Math.abs(value); + if (value < TWO_POW_52) { + // Getting rid of post-comma bits. + value = ((value + TWO_POW_52) - TWO_POW_52); + } + if (ANTI_SLOW_CASTS) { + if (value <= (double)Integer.MAX_VALUE) { + // value is in [-Integer.MAX_VALUE,Integer.MAX_VALUE] + return sign * (int)value; + } + } + return (long)(sign * value); + } + + /** + * @param value A float value. + * @return The float mathematical integer closest to the specified value, + * choosing even one if two are equally close, or respectively + * NaN, +-Infinity or +-0.0f if the value is any of these. + */ + public static float rint(float value) { + final int sign = signFromBit(value); + value = Math.abs(value); + if (value < TWO_POW_23_F) { + // Getting rid of post-comma bits. + value = ((TWO_POW_23_F + value ) - TWO_POW_23_F); + } + // Restoring original sign. + return sign * value; + } + + /** + * @param value A double value. + * @return The double mathematical integer closest to the specified value, + * choosing even one if two are equally close, or respectively + * NaN, +-Infinity or +-0.0 if the value is any of these. + */ + public static double rint(double value) { + if (USE_JDK_MATH) { + return Math.rint(value); + } + final int sign = (int)signFromBit(value); + value = Math.abs(value); + if (value < TWO_POW_52) { + // Getting rid of post-comma bits. + value = ((TWO_POW_52 + value ) - TWO_POW_52); + } + // Restoring original sign. + return sign * value; + } + + /* + * close int values + * + * Never delegating to JDK for these methods, for we should always + * be faster and exact, and JDK doesn't exactly have such methods. + */ + + /** + * @param value A double value. + * @return Floor of value as int, or closest int if floor is out + * of int range, or 0 if value is NaN. + */ + public static int floorToInt(double value) { + int valueInt = (int) value; + if (value < 0.0) { + if (value == (double) valueInt) { + return valueInt; + } else { + if (valueInt == Integer.MIN_VALUE) { + return valueInt; + } else { + return valueInt - 1; + } + } + } else { // >= 0 or NaN. + return valueInt; + } + } + + /** + * @param value A double value. + * @return Ceiling of value as int, or closest int if ceiling is out + * of int range, or 0 if value is NaN. + */ + public static int ceilToInt(double value) { + int valueInt = (int) value; + if (value > 0.0) { + if (value == (double) valueInt) { + return valueInt; + } else { + if (valueInt == Integer.MAX_VALUE) { + return valueInt; + } else { + return valueInt + 1; + } + } + } else { // <= 0 or NaN. + return valueInt; + } + } + + /** + * @param value A double value. + * @return Value rounded to nearest int, choosing superior int in case two + * are equally close (i.e. rounding-up). + */ + public static int roundToInt(double value) { + /* + * We don't gain much by reimplementing rounding, except for + * pathologically large values, which should not be a common case + * when dealing with ints, so we just use round(double). + */ + return NumbersUtils.toInt(round(value)); + } + + /** + * @param value A double value. + * @return Value rounded to nearest int, choosing even int in case two + * are equally close. + */ + public static int roundEvenToInt(double value) { + final int sign = (int)signFromBit(value); + value = Math.abs(value); + /* + * Applying the post-comma bits removal logic even if value is out + * of int range, to avoid a test, for it doesn't mess up the result, + * and we want to optimize for the case of values in int range. + */ + value = ((value + TWO_POW_52) - TWO_POW_52); + return (int)(sign * value); + } + + /* + * ranges + */ + + /** + * @param min A float value. + * @param max A float value. + * @param value A float value. + * @return min if value < min, max if value > max, value otherwise. + */ + public static float toRange(float min, float max, float value) { + return NumbersUtils.toRange(min, max, value); + } + + /** + * @param min A double value. + * @param max A double value. + * @param value A double value. + * @return min if value < min, max if value > max, value otherwise. + */ + public static double toRange(double min, double max, double value) { + return NumbersUtils.toRange(min, max, value); + } + + /* + * binary operators (/,%) + */ + + /** + * Returns dividend - divisor * n, where n is the mathematical integer + * closest to dividend/divisor. + * If dividend/divisor is equally close to surrounding integers, + * we choose n to be the integer of smallest magnitude, which makes + * this treatment differ from Math.IEEEremainder(double,double), + * where n is chosen to be the even integer. + * Note that the choice of n is not done considering the double + * approximation of dividend/divisor, because it could cause + * result to be outside [-|divisor|/2,|divisor|/2] range. + * The practical effect is that if multiple results would be possible, + * we always choose the result that is the closest to (and has the same + * sign as) the dividend. + * Ex. : + * - for (-3.0,2.0), this method returns -1.0, + * whereas Math.IEEEremainder returns 1.0. + * - for (-5.0,2.0), both this method and Math.IEEEremainder return -1.0. + * + * If the remainder is zero, its sign is the same as the sign of the first argument. + * If either argument is NaN, or the first argument is infinite, + * or the second argument is positive zero or negative zero, + * then the result is NaN. + * If the first argument is finite and the second argument is + * infinite, then the result is the same as the first argument. + * + * NB: + * - Modulo operator (%) returns a value in ]-|divisor|,|divisor|[, + * which sign is the same as dividend. + * - As for modulo operator, the sign of the divisor has no effect on the result. + * - On some architecture, % operator has been observed to return NaN + * for some subnormal values of divisor, when dividend exponent is 1023, + * which impacts the correctness of this method. + * + * @param dividend Dividend. + * @param divisor Divisor. + * @return Remainder of dividend/divisor, i.e. a value in [-|divisor|/2,|divisor|/2]. + */ + public static double remainder(double dividend, double divisor) { + if (Double.isInfinite(divisor)) { + if (Double.isInfinite(dividend)) { + return Double.NaN; + } else { + return dividend; + } + } + double value = dividend % divisor; + if (Math.abs(value+value) > Math.abs(divisor)) { + return value + ((value > 0.0) ? -Math.abs(divisor) : Math.abs(divisor)); + } else { + return value; + } + } + + /** + * @param angle Angle in radians. + * @return The same angle, in radians, but in [-PI,PI]. + */ + public static double normalizeMinusPiPi(double angle) { + // Not modifying values in output range. + if ((angle >= -Math.PI) && (angle <= Math.PI)) { + return angle; + } + return remainderTwoPi(angle); + } + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return The same angle, in radians, but in [-PI,PI]. + */ + public static double normalizeMinusPiPiFast(double angle) { + // Not modifying values in output range. + if ((angle >= -Math.PI) && (angle <= Math.PI)) { + return angle; + } + return remainderTwoPiFast(angle); + } + + /** + * @param angle Angle in radians. + * @return The same angle, in radians, but in [0,2*PI]. + */ + public static double normalizeZeroTwoPi(double angle) { + // Not modifying values in output range. + if ((angle >= 0.0) && (angle <= 2*Math.PI)) { + return angle; + } + angle = remainderTwoPi(angle); + if (angle < 0.0) { + // LO then HI is theoretically better (when starting near 0). + return (angle + TWOPI_LO) + TWOPI_HI; + } else { + return angle; + } + } + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return The same angle, in radians, but in [0,2*PI]. + */ + public static double normalizeZeroTwoPiFast(double angle) { + // Not modifying values in output range. + if ((angle >= 0.0) && (angle <= 2*Math.PI)) { + return angle; + } + angle = remainderTwoPiFast(angle); + if (angle < 0.0) { + // LO then HI is theoretically better (when starting near 0). + return (angle + TWOPI_LO) + TWOPI_HI; + } else { + return angle; + } + } + + /** + * @param angle Angle in radians. + * @return Angle value modulo PI, in radians, in [-PI/2,PI/2]. + */ + public static double normalizeMinusHalfPiHalfPi(double angle) { + // Not modifying values in output range. + if ((angle >= -Math.PI/2) && (angle <= Math.PI/2)) { + return angle; + } + return remainderPi(angle); + } + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return Angle value modulo PI, in radians, in [-PI/2,PI/2]. + */ + public static double normalizeMinusHalfPiHalfPiFast(double angle) { + // Not modifying values in output range. + if ((angle >= -Math.PI/2) && (angle <= Math.PI/2)) { + return angle; + } + return remainderPiFast(angle); + } + + /* + * floating points utils + */ + + /** + * @param value A float value. + * @return true if the specified value is NaN or +-Infinity, false otherwise. + */ + public static boolean isNaNOrInfinite(float value) { + return NumbersUtils.isNaNOrInfinite(value); + } + + /** + * @param value A double value. + * @return true if the specified value is NaN or +-Infinity, false otherwise. + */ + public static boolean isNaNOrInfinite(double value) { + return NumbersUtils.isNaNOrInfinite(value); + } + + /** + * @param value A float value. + * @return Value unbiased exponent. + */ + public static int getExponent(float value) { + return ((Float.floatToRawIntBits(value)>>23)&0xFF)-MAX_FLOAT_EXPONENT; + } + + /** + * @param value A double value. + * @return Value unbiased exponent. + */ + public static int getExponent(double value) { + return (((int)(Double.doubleToRawLongBits(value)>>52))&0x7FF)-MAX_DOUBLE_EXPONENT; + } + + /** + * @param value A float value. + * @return -1.0f if the specified value is < 0, 1.0f if it is > 0, + * and the value itself if it is NaN or +-0.0f. + */ + public static float signum(float value) { + if (USE_JDK_MATH) { + return Math.signum(value); + } + if ((value == 0.0f) || (value != value)) { + return value; + } + return (float)signFromBit(value); + } + + /** + * @param value A double value. + * @return -1.0 if the specified value is < 0, 1.0 if it is > 0, + * and the value itself if it is NaN or +-0.0. + */ + public static double signum(double value) { + if (USE_JDK_MATH) { + return Math.signum(value); + } + if ((value == 0.0) || (value != value)) { + return value; + } + if (ANTI_SLOW_CASTS) { + return (double)(int)signFromBit(value); + } else { + return (double)signFromBit(value); + } + } + + /** + * @param value A float value. + * @return -1 if sign bit is 1, 1 if sign bit is 0. + */ + public static int signFromBit(float value) { + return ((Float.floatToRawIntBits(value)>>30)|1); + } + + /** + * @param value A double value. + * @return -1 if sign bit is 1, 1 if sign bit is 0. + */ + public static long signFromBit(double value) { + // Returning a long, to avoid useless cast into int. + return ((Double.doubleToRawLongBits(value)>>62)|1); + } + + /** + * A sign of NaN can be interpreted as positive or negative. + * + * @param magnitude A float value. + * @param sign A float value. + * @return A value with the magnitude of the first argument, and the sign + * of the second argument. + */ + public static float copySign(float magnitude, float sign) { + return Float.intBitsToFloat( + (Float.floatToRawIntBits(sign) & Integer.MIN_VALUE) + | (Float.floatToRawIntBits(magnitude) & Integer.MAX_VALUE)); + } + + /** + * A sign of NaN can be interpreted as positive or negative. + * + * @param magnitude A double value. + * @param sign A double value. + * @return A value with the magnitude of the first argument, and the sign + * of the second argument. + */ + public static double copySign(double magnitude, double sign) { + return Double.longBitsToDouble( + (Double.doubleToRawLongBits(sign) & Long.MIN_VALUE) + | (Double.doubleToRawLongBits(magnitude) & Long.MAX_VALUE)); + } + + /** + * The ULP (Unit in the Last Place) is the distance to the next value larger + * in magnitude. + * + * @param value A float value. + * @return The size of an ulp of the specified value, or Float.MIN_VALUE + * if it is +-0.0f, or +Infinity if it is +-Infinity, or NaN + * if it is NaN. + */ + public static float ulp(float value) { + if (USE_JDK_MATH) { + return Math.ulp(value); + } + /* + * Look-up table not really worth it in micro-benchmark, + * so should be worse with cache-misses. + */ + final int exponent = getExponent(value); + if (exponent >= (MIN_FLOAT_NORMAL_EXPONENT+23)) { + if (exponent == MAX_FLOAT_EXPONENT+1) { + // NaN or +-Infinity + return Math.abs(value); + } + // normal: returning 2^(exponent-23) + return Float.intBitsToFloat((exponent+(MAX_FLOAT_EXPONENT-23))<<23); + } else { + if (exponent == MIN_FLOAT_NORMAL_EXPONENT-1) { + // +-0.0f or subnormal + return Float.MIN_VALUE; + } + // subnormal result + return Float.intBitsToFloat(1<<(exponent-MIN_FLOAT_NORMAL_EXPONENT)); + } + } + + /** + * The ULP (Unit in the Last Place) is the distance to the next value larger + * in magnitude. + * + * @param value A double value. + * @return The size of an ulp of the specified value, or Double.MIN_VALUE + * if it is +-0.0, or +Infinity if it is +-Infinity, or NaN + * if it is NaN. + */ + public static double ulp(double value) { + if (USE_JDK_MATH) { + return Math.ulp(value); + } + /* + * Look-up table not really worth it in micro-benchmark, + * so should be worse with cache-misses. + */ + final int exponent = getExponent(value); + if (exponent >= (MIN_DOUBLE_NORMAL_EXPONENT+52)) { + if (exponent == MAX_DOUBLE_EXPONENT+1) { + // NaN or +-Infinity + return Math.abs(value); + } + // normal: returning 2^(exponent-52) + return Double.longBitsToDouble((exponent+(MAX_DOUBLE_EXPONENT-52L))<<52); + } else { + if (exponent == MIN_DOUBLE_NORMAL_EXPONENT-1) { + // +-0.0f or subnormal + return Double.MIN_VALUE; + } + // subnormal result + return Double.longBitsToDouble(1L<<(exponent-MIN_DOUBLE_NORMAL_EXPONENT)); + } + } + + /** + * If both arguments are +-0.0(f), (float)direction is returned. + * + * If both arguments are +Infinity or -Infinity, + * respectively +Infinity or -Infinity is returned. + * + * @param start A float value. + * @param direction A double value. + * @return The float adjacent to start towards direction, considering that + * +(-)Float.MIN_VALUE is adjacent to +(-)0.0f, and that + * +(-)Float.MAX_VALUE is adjacent to +(-)Infinity, + * or NaN if any argument is NaN. + */ + public static float nextAfter(float start, double direction) { + if (direction < start) { + // Going towards -Infinity. + if (start == 0.0f) { + // +-0.0f + return -Float.MIN_VALUE; + } + final int bits = Float.floatToRawIntBits(start); + return Float.intBitsToFloat(bits + ((bits > 0) ? -1 : 1)); + } else if (direction > start) { + // Going towards +Infinity. + // +0.0f to get rid of eventual -0.0f + final int bits = Float.floatToRawIntBits(start + 0.0f); + return Float.intBitsToFloat(bits + (bits >= 0 ? 1 : -1)); + } else if (start == direction) { + return (float)direction; + } else { + // Returning a NaN derived from the input NaN(s). + return start + (float)direction; + } + } + + /** + * If both arguments are +-0.0, direction is returned. + * + * If both arguments are +Infinity or -Infinity, + * respectively +Infinity or -Infinity is returned. + * + * @param start A double value. + * @param direction A double value. + * @return The double adjacent to start towards direction, considering that + * +(-)Double.MIN_VALUE is adjacent to +(-)0.0, and that + * +(-)Double.MAX_VALUE is adjacent to +(-)Infinity, + * or NaN if any argument is NaN. + */ + public static double nextAfter(double start, double direction) { + if (direction < start) { + // Going towards -Infinity. + if (start == 0.0) { + // +-0.0 + return -Double.MIN_VALUE; + } + final long bits = Double.doubleToRawLongBits(start); + return Double.longBitsToDouble(bits + ((bits > 0) ? -1 : 1)); + } else if (direction > start) { + // Going towards +Infinity. + // +0.0 to get rid of eventual -0.0 + final long bits = Double.doubleToRawLongBits(start + 0.0f); + return Double.longBitsToDouble(bits + (bits >= 0 ? 1 : -1)); + } else if (start == direction) { + return direction; + } else { + // Returning a NaN derived from the input NaN(s). + return start + direction; + } + } + + /** + * Semantically equivalent to nextAfter(start,Double.NEGATIVE_INFINITY). + */ + public static float nextDown(float start) { + if (start > Float.NEGATIVE_INFINITY) { + if (start == 0.0f) { + // +-0.0f + return -Float.MIN_VALUE; + } + final int bits = Float.floatToRawIntBits(start); + return Float.intBitsToFloat(bits + ((bits > 0) ? -1 : 1)); + } else if (start == Float.NEGATIVE_INFINITY) { + return Float.NEGATIVE_INFINITY; + } else { + // NaN + return start; + } + } + + /** + * Semantically equivalent to nextAfter(start,Double.NEGATIVE_INFINITY). + */ + public static double nextDown(double start) { + if (start > Double.NEGATIVE_INFINITY) { + if (start == 0.0) { + // +-0.0 + return -Double.MIN_VALUE; + } + final long bits = Double.doubleToRawLongBits(start); + return Double.longBitsToDouble(bits + ((bits > 0) ? -1 : 1)); + } else if (start == Double.NEGATIVE_INFINITY) { + return Double.NEGATIVE_INFINITY; + } else { + // NaN + return start; + } + } + + /** + * Semantically equivalent to nextAfter(start,Double.POSITIVE_INFINITY). + */ + public static float nextUp(float start) { + if (start < Float.POSITIVE_INFINITY) { + // +0.0f to get rid of eventual -0.0f + final int bits = Float.floatToRawIntBits(start + 0.0f); + return Float.intBitsToFloat(bits + (bits >= 0 ? 1 : -1)); + } else if (start == Float.POSITIVE_INFINITY) { + return Float.POSITIVE_INFINITY; + } else { + // NaN + return start; + } + } + + /** + * Semantically equivalent to nextAfter(start,Double.POSITIVE_INFINITY). + */ + public static double nextUp(double start) { + if (start < Double.POSITIVE_INFINITY) { + // +0.0 to get rid of eventual -0.0 + final long bits = Double.doubleToRawLongBits(start + 0.0); + return Double.longBitsToDouble(bits + (bits >= 0 ? 1 : -1)); + } else if (start == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } else { + // NaN + return start; + } + } + + /** + * Precision may be lost if the result is subnormal. + * + * @param value A float value. + * @param scaleFactor An int value. + * @return value * 2^scaleFactor, or a value equivalent to the specified + * one if it is NaN, +-Infinity or +-0.0f. + */ + public static float scalb(float value, int scaleFactor) { + // Large enough to imply overflow or underflow for + // a finite non-zero value. + final int MAX_SCALE = 2*MAX_FLOAT_EXPONENT+23+1; + + // Making sure scaling factor is in a reasonable range. + scaleFactor = Math.max(Math.min(scaleFactor, MAX_SCALE), -MAX_SCALE); + + return (float)(((double)value) * twoPowNormal(scaleFactor)); + } + + /** + * Precision may be lost if the result is subnormal. + * + * @param value A double value. + * @param scaleFactor An int value. + * @return value * 2^scaleFactor, or a value equivalent to the specified + * one if it is NaN, +-Infinity or +-0.0. + */ + public static double scalb(double value, int scaleFactor) { + if ((scaleFactor > -MAX_DOUBLE_EXPONENT) && (scaleFactor <= MAX_DOUBLE_EXPONENT)) { + // Quick case (as done in apache FastMath). + return value * twoPowNormal(scaleFactor); + } + + // Large enough to imply overflow or underflow for + // a finite non-zero value. + final int MAX_SCALE = 2*MAX_DOUBLE_EXPONENT+52+1; + + // Making sure scaling factor is in a reasonable range. + final int exponentAdjust; + final int scaleIncrement; + final double exponentDelta; + if (scaleFactor < 0) { + scaleFactor = Math.max(scaleFactor, -MAX_SCALE); + scaleIncrement = -512; + exponentDelta = TWO_POW_N512; + } else { + scaleFactor = Math.min(scaleFactor, MAX_SCALE); + scaleIncrement = 512; + exponentDelta = TWO_POW_512; + } + + // Calculating (scaleFactor % +-512), 512 = 2^9, using + // technique from "Hacker's Delight" section 10-2. + final int t = ((scaleFactor >> (9-1)) >>> (32-9)); + exponentAdjust = ((scaleFactor + t) & (512-1)) - t; + + value *= twoPowNormal(exponentAdjust); + scaleFactor -= exponentAdjust; + + while (scaleFactor != 0) { + value *= exponentDelta; + scaleFactor -= scaleIncrement; + } + + return value; + } + + /* + * Non-redefined Math public values and treatments. + */ + + public static float abs(float a) { + return Math.abs(a); + } + + public static double abs(double a) { + return Math.abs(a); + } + + public static float min(float a, float b) { + return Math.min(a,b); + } + + public static double min(double a, double b) { + return Math.min(a,b); + } + + public static float max(float a, float b) { + return Math.max(a,b); + } + + public static double max(double a, double b) { + return Math.max(a,b); + } + + public static double IEEEremainder(double f1, double f2) { + return Math.IEEEremainder(f1,f2); + } + + public static double random() { + return Math.random(); + } + + //-------------------------------------------------------------------------- + // PRIVATE METHODS + //-------------------------------------------------------------------------- + + /** + * Non-instantiable. + */ + private FastMath() { + } + + /* + * Remainders (accurate). + */ + + /** + * @param angle Angle in radians. + * @return Remainder of (angle % (2*PI)), in [-PI,PI]. + */ + private static double remainderTwoPi(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderTwoPi(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle <= (4*NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2)) { + double fn = (double)(int)(angle*TWOPI_INV+0.5); + angle = (angle - fn*TWOPI_HI) - fn*TWOPI_LO; + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI) { + angle = (angle + TWOPI_HI) + TWOPI_LO; + } else if (angle > Math.PI) { + angle = (angle - TWOPI_HI) - TWOPI_LO; + } + return negateResult ? -angle : angle; + } else if (angle < Double.POSITIVE_INFINITY) { + angle = heavyRemainderTwoPi(angle); + return negateResult ? -angle : angle; + } else { // angle is +Infinity or NaN + return Double.NaN; + } + } + + /** + * @param angle Angle in radians. + * @return Remainder of (angle % PI), in [-PI/2,PI/2]. + */ + private static double remainderPi(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderPi(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle <= (2*NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2)) { + double fn = (double)(int)(angle*PI_INV+0.5); + angle = (angle - fn*PI_HI) - fn*PI_LO; + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI/2) { + angle = (angle + PI_HI) + PI_LO; + } else if (angle > Math.PI/2) { + angle = (angle - PI_HI) - PI_LO; + } + return negateResult ? -angle : angle; + } else if (angle < Double.POSITIVE_INFINITY) { + angle = heavyRemainderPi(angle); + return negateResult ? -angle : angle; + } else { // angle is +Infinity or NaN + return Double.NaN; + } + } + + /** + * @param angle Angle in radians. + * @return Bits of double corresponding to remainder of (angle % (PI/2)), + * in [-PI/4,PI/4], with quadrant encoded in exponent bits. + */ + private static long remainderPiO2(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderPiO2(angle, false); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle <= NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2) { + int n = (int)(angle*PIO2_INV+0.5); + double fn = (double)n; + angle = (angle - fn*PIO2_HI) - fn*PIO2_LO; + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI/4) { + angle = (angle + PIO2_HI) + PIO2_LO; + n--; + } else if (angle > Math.PI/4) { + angle = (angle - PIO2_HI) - PIO2_LO; + n++; + } + if (negateResult) { + angle = -angle; + } + return encodeRemainderAndQuadrant(angle, n&3); + } else if (angle < Double.POSITIVE_INFINITY) { + return heavyRemainderPiO2(angle, negateResult); + } else { // angle is +Infinity or NaN + return encodeRemainderAndQuadrant(Double.NaN, 0); + } + } + + /* + * Remainders (fast). + */ + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return Remainder of (angle % (2*PI)), in [-PI,PI]. + */ + private static double remainderTwoPiFast(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderTwoPi(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + // - We don't bother with values higher than (2*PI*(2^52)), + // since they are spaced by 2*PI or more from each other. + // - For large values, we don't use % because it might be very slow, + // and we split computation in two, because cast from double to int + // with large numbers might be very slow also. + if (angle <= TWO_POW_26*(2*Math.PI)) { + // ok + } else if (angle <= TWO_POW_52*(2*Math.PI)) { + // Computing remainder of angle modulo TWO_POW_26*(2*PI). + double fn = (double)(int)(angle*(TWOPI_INV/TWO_POW_26)+0.5); + angle = (angle - fn*(TWOPI_HI*TWO_POW_26)) - fn*(TWOPI_LO*TWO_POW_26); + // Here, angle is in [-TWO_POW_26*PI,TWO_POW_26*PI], or so. + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } else if (angle < Double.POSITIVE_INFINITY) { + return 0.0; + } else { // angle is +Infinity or NaN + return Double.NaN; + } + + // Computing remainder of angle modulo 2*PI. + double fn = (double)(int)(angle*TWOPI_INV+0.5); + angle = (angle - fn*TWOPI_HI) - fn*TWOPI_LO; + + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI) { + angle = (angle + TWOPI_HI) + TWOPI_LO; + } else if (angle > Math.PI) { + angle = (angle - TWOPI_HI) - TWOPI_LO; + } + return negateResult ? -angle : angle; + } + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return Remainder of (angle % PI), in [-PI/2,PI/2]. + */ + private static double remainderPiFast(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderPi(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + // - We don't bother with values higher than (PI*(2^52)), + // since they are spaced by PI or more from each other. + // - For large values, we don't use % because it might be very slow, + // and we split computation in two, because cast from double to int + // with large numbers might be very slow also. + if (angle <= TWO_POW_26*Math.PI) { + // ok + } else if (angle <= TWO_POW_52*Math.PI) { + // Computing remainder of angle modulo TWO_POW_26*PI. + double fn = (double)(int)(angle*(PI_INV/TWO_POW_26)+0.5); + angle = (angle - fn*(PI_HI*TWO_POW_26)) - fn*(PI_LO*TWO_POW_26); + // Here, angle is in [-TWO_POW_26*PI/2,TWO_POW_26*PI/2], or so. + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } else if (angle < Double.POSITIVE_INFINITY) { + return 0.0; + } else { // angle is +Infinity or NaN + return Double.NaN; + } + + // Computing remainder of angle modulo PI. + double fn = (double)(int)(angle*PI_INV+0.5); + angle = (angle - fn*PI_HI) - fn*PI_LO; + + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI/2) { + angle = (angle + PI_HI) + PI_LO; + } else if (angle > Math.PI/2) { + angle = (angle - PI_HI) - PI_LO; + } + return negateResult ? -angle : angle; + } +} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/IntWrapper.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/IntWrapper.java new file mode 100644 index 000000000..812e5a22d --- /dev/null +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/IntWrapper.java @@ -0,0 +1,13 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ +package space.kscience.kmath.jafama; + +public class IntWrapper { + public int value; + @Override + public String toString() { + return Integer.toString(this.value); + } +} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt new file mode 100644 index 000000000..2b6cc3a5a --- /dev/null +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt @@ -0,0 +1,102 @@ +package space.kscience.kmath.jafama + +import space.kscience.kmath.operations.* + +/** + * Advanced Number-like semifield that implements basic operations. + */ +public interface ExtendedFieldOperations : + FieldOperations, + TrigonometricOperations, + PowerOperations, + ExponentialOperations { + public override fun tan(arg: T): T = sin(arg) / cos(arg) + public override fun tanh(arg: T): T = sinh(arg) / cosh(arg) + + public override fun unaryOperationFunction(operation: String): (arg: T) -> T = when (operation) { + TrigonometricOperations.COS_OPERATION -> ::cos + TrigonometricOperations.SIN_OPERATION -> ::sin + TrigonometricOperations.TAN_OPERATION -> ::tan + TrigonometricOperations.ACOS_OPERATION -> ::acos + TrigonometricOperations.ASIN_OPERATION -> ::asin + TrigonometricOperations.ATAN_OPERATION -> ::atan + PowerOperations.SQRT_OPERATION -> ::sqrt + ExponentialOperations.EXP_OPERATION -> ::exp + ExponentialOperations.LN_OPERATION -> ::ln + ExponentialOperations.COSH_OPERATION -> ::cosh + ExponentialOperations.SINH_OPERATION -> ::sinh + ExponentialOperations.TANH_OPERATION -> ::tanh + ExponentialOperations.ACOSH_OPERATION -> ::acosh + ExponentialOperations.ASINH_OPERATION -> ::asinh + ExponentialOperations.ATANH_OPERATION -> ::atanh + else -> super.unaryOperationFunction(operation) + } +} + +/** + * Advanced Number-like field that implements basic operations. + */ +public interface ExtendedField : ExtendedFieldOperations, Field, NumericAlgebra, ScaleOperations { + public override fun sinh(arg: T): T = (exp(arg) - exp(-arg)) / 2.0 + public override fun cosh(arg: T): T = (exp(arg) + exp(-arg)) / 2.0 + public override fun tanh(arg: T): T = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg)) + public override fun asinh(arg: T): T = ln(sqrt(arg * arg + one) + arg) + public override fun acosh(arg: T): T = ln(arg + sqrt((arg - one) * (arg + one))) + public override fun atanh(arg: T): T = (ln(arg + one) - ln(one - arg)) / 2.0 + + public override fun rightSideNumberOperationFunction(operation: String): (left: T, right: Number) -> T = + when (operation) { + PowerOperations.POW_OPERATION -> ::power + else -> super.rightSideNumberOperationFunction(operation) + } +} + +/** + * A field for [Double] without boxing. Does not produce appropriate field element. + */ +@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") +public object DoubleField : ExtendedField, Norm, ScaleOperations { + public override inline val zero: Double get() = 0.0 + public override inline val one: Double get() = 1.0 + + public override fun number(value: Number): Double = value.toDouble() + + public override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = + when (operation) { + PowerOperations.POW_OPERATION -> ::power + else -> super.binaryOperationFunction(operation) + } + + public override inline fun add(a: Double, b: Double): Double = a + b + + public override inline fun multiply(a: Double, b: Double): Double = a * b + public override inline fun divide(a: Double, b: Double): Double = a / b + + public override fun scale(a: Double, value: Double): Double = a * value + + public override inline fun sin(arg: Double): Double = FastMath.sin(arg) + public override inline fun cos(arg: Double): Double = FastMath.cos(arg) + public override inline fun tan(arg: Double): Double = FastMath.tan(arg) + public override inline fun acos(arg: Double): Double = FastMath.acos(arg) + public override inline fun asin(arg: Double): Double = FastMath.asin(arg) + public override inline fun atan(arg: Double): Double = FastMath.atan(arg) + + public override inline fun sinh(arg: Double): Double = FastMath.sinh(arg) + public override inline fun cosh(arg: Double): Double = FastMath.cosh(arg) + public override inline fun tanh(arg: Double): Double = FastMath.tanh(arg) + public override inline fun asinh(arg: Double): Double = FastMath.asinh(arg) + public override inline fun acosh(arg: Double): Double = FastMath.acosh(arg) + public override inline fun atanh(arg: Double): Double = FastMath.atanh(arg) + + public override inline fun power(arg: Double, pow: Number): Double = FastMath.pow(arg, pow.toDouble()) + public override inline fun exp(arg: Double): Double = FastMath.exp(arg) + public override inline fun ln(arg: Double): Double = FastMath.log(arg) + + public override inline fun norm(arg: Double): Double = FastMath.abs(arg) + + public override inline fun Double.unaryMinus(): Double = -this + public override inline fun Double.plus(b: Double): Double = this + b + public override inline fun Double.minus(b: Double): Double = this - b + public override inline fun Double.times(b: Double): Double = this * b + public override inline fun Double.div(b: Double): Double = this / b +} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/NumbersUtils.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/NumbersUtils.java new file mode 100644 index 000000000..6fdd9dea5 --- /dev/null +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/NumbersUtils.java @@ -0,0 +1,2647 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ +package space.kscience.kmath.jafama; + +/** + * Class containing various basic utility methods to deal with numbers. + * This class is meant to be light (no big look-up tables or such). + * + * Check methods return boolean if success, + * for it allows to use them in assertions. + * + * toString methods use capital letters, unlike JDK's toStrings, for it is more + * readable (especially, "l" and "1" can easily be confused with one another). + * + * Some methods have an int version additionally to the long version, + * even though long version could be used instead, for performance reasons, + * either for the methods themselves (if they do computations with ints + * instead of longs), or to be used in an int use case (like methods + * checking whether or not a signed int can fit in such number of bits). + */ +public final class NumbersUtils { + + //-------------------------------------------------------------------------- + // MEMBERS + //-------------------------------------------------------------------------- + + /** + * Double.MIN_NORMAL since Java 6. + */ + public static final double DOUBLE_MIN_NORMAL = Double.longBitsToDouble(0x0010000000000000L); // 2.2250738585072014E-308 + + /** + * Float.MIN_NORMAL since Java 6. + */ + public static final float FLOAT_MIN_NORMAL = Float.intBitsToFloat(0x00800000); // 1.17549435E-38f + + private static final int MIN_DOUBLE_EXPONENT = -1074; + private static final int MAX_DOUBLE_EXPONENT = 1023; + + /** + * All possible upper case chars for representing a number as a String. + */ + private final static char[] CHAR_BY_DIGIT; + static { + final char minDecimal = '0'; + final char maxDecimal = '9'; + final int n1 = maxDecimal - minDecimal + 1; + final char minLetter = 'A'; + final char maxLetter = 'Z'; + final int n2 = maxLetter - minLetter + 1; + CHAR_BY_DIGIT = new char[n1+n2]; + int i=0; + for (char c=minDecimal;c<=maxDecimal;c++) { + CHAR_BY_DIGIT[i++] = c; + } + for (char c=minLetter;c<=maxLetter;c++) { + CHAR_BY_DIGIT[i++] = c; + } + } + + /** + * For power-of-two radixes only. + */ + private static final int[] DIV_SHIFT_BY_RADIX; + static { + DIV_SHIFT_BY_RADIX = new int[32+1]; + int shift=1; + for (int radix=2;radix<=32;radix*=2) { + DIV_SHIFT_BY_RADIX[radix] = shift++; + } + } + + private final static int[] MAX_NBR_OF_NEG_INT_DIGITS_BY_RADIX = new int[Character.MAX_RADIX+1]; + private final static int[] MAX_NBR_OF_NEG_LONG_DIGITS_BY_RADIX = new int[Character.MAX_RADIX+1]; + static { + for (int radix=Character.MIN_RADIX;radix<=Character.MAX_RADIX;radix++) { + /* + * Brutal but works. + * -1 for the sign. + */ + MAX_NBR_OF_NEG_INT_DIGITS_BY_RADIX[radix] = Integer.toString(Integer.MIN_VALUE, radix).length()-1; + MAX_NBR_OF_NEG_LONG_DIGITS_BY_RADIX[radix] = Long.toString(Long.MIN_VALUE, radix).length()-1; + } + } + + static final double NO_CSN_MIN_BOUND_INCL = 1e-3; + static final double NO_CSN_MAX_BOUND_EXCL = 1e7; + + private static final double PIO2_HI = Double.longBitsToDouble(0x3FF921FB54400000L); // 1.57079632673412561417e+00 first 33 bits of pi/2 + private static final double PIO2_LO = Double.longBitsToDouble(0x3DD0B4611A626331L); // 6.07710050650619224932e-11 pi/2 - PIO2_HI + private static final double PI_HI = 2*PIO2_HI; + private static final double PI_LO = 2*PIO2_LO; + private static final double TWOPI_HI = 4*PIO2_HI; + private static final double TWOPI_LO = 4*PIO2_LO; + + //-------------------------------------------------------------------------- + // PUBLIC METHODS + //-------------------------------------------------------------------------- + + /** + * @return True if the specified values are equal or both NaN, false otherwise. + */ + public static boolean equal(float a, float b) { + // Only does one test if a == b. + return (a == b) ? true : ((a != a) && (b != b)); + } + + /** + * @return True if the specified values are equal or both NaN, false otherwise. + */ + public static boolean equal(double a, double b) { + // Only does one test if a == b. + return (a == b) ? true : ((a != a) && (b != b)); + } + + /** + * @return True if the specified value is a mathematical integer, + * false otherwise (which includes NaN and +-Infinity). + */ + public static boolean isMathematicalInteger(float value) { + // Doing magnitude test first, for cast + // might be very slow for huge values. + // It also helps be faster for huge values, + // for which the test with cast always fail. + value = Math.abs(value); + return ((value >= (float)(1<<23) + && (value != Float.POSITIVE_INFINITY))) + || (value == (float)(int)value); + } + + /** + * @return True if the specified value is a mathematical integer, + * false otherwise (which includes NaN and +-Infinity). + */ + public static boolean isMathematicalInteger(double value) { + // Doing magnitude test first, for cast + // might be very slow for huge values. + // It also helps be faster for huge values, + // for which the test with cast always fail. + value = Math.abs(value); + return ((value >= (double)(1L<<52)) + && (value != Double.POSITIVE_INFINITY)) + || (value == (double)(long)value); + } + + /** + * @param value A float value. + * @return True if the specified value is equidistant from two adjacent + * mathematical integers, false otherwise (which includes NaN + * and +-Infinity). + */ + public static boolean isEquidistant(float value) { + if (false) { + // Also works, but slower. + final int bits = Float.floatToRawIntBits(value); + final int exponent = ((bits>>23)&0xFF)-127; + final int nbrOfPostCommaBits = 23 - exponent; + if ((nbrOfPostCommaBits <= 0) || (nbrOfPostCommaBits >= 25)) { + // No mantissa bit after comma, or all mantissa bits + // (including implicit 1) are at least one bit away from it. + //System.out.println("can't be"); + return false; + } + final int mantissa = 0x00800000|(bits&0x007FFFFF); + final int postCommaMask = ~((-1)<>52))&0x7FF)-1023; + final int nbrOfPostCommaBits = 52 - exponent; + if ((nbrOfPostCommaBits <= 0) || (nbrOfPostCommaBits >= 54)) { + // No mantissa bit after comma, or all mantissa bits + // (including implicit 1) are at least one bit away from it. + return false; + } + final long mantissa = 0x0010000000000000L|(bits&0x000FFFFFFFFFFFFFL); + final long postCommaMask = ~((-1L)< value is NaN or +-Infinity + return !(value-value == 0.0f); + } + + /** + * @param value A double value. + * @return True if the specified value is NaN or +-Infinity, false otherwise. + */ + public static boolean isNaNOrInfinite(double value) { + // value-value is not equal to 0.0 (and is NaN) <-> value is NaN or +-Infinity + return !(value-value == 0.0); + } + + /** + * @param value A float value. + * @return -1 if sign bit is 1, 1 if sign bit is 0. + */ + public static int signFromBit(float value) { + return ((Float.floatToRawIntBits(value)>>30)|1); + } + + /** + * @param value A double value. + * @return -1 if sign bit is 1, 1 if sign bit is 0. + */ + public static long signFromBit(double value) { + // Returning a long, to avoid useless cast into int. + return ((Double.doubleToRawLongBits(value)>>62)|1); + } + + /* + * min/max ranges + */ + + /** + * @return True if the specified value is in the specified range (inclusive), false otherwise. + */ + public static boolean isInRange(int min, int max, int a) { + return (min <= a) && (a <= max); + } + + /** + * @return True if the specified value is in the specified range (inclusive), false otherwise. + */ + public static boolean isInRange(long min, long max, long a) { + return (min <= a) && (a <= max); + } + + /** + * Returns false if any value is NaN. + * + * @return True if the specified value is in the specified range (inclusive), false otherwise. + */ + public static boolean isInRange(float min, float max, float a) { + return (min <= a) && (a <= max); + } + + /** + * Returns false if any value is NaN. + * + * @return True if the specified value is in the specified range (inclusive), false otherwise. + */ + public static boolean isInRange(double min, double max, double a) { + return (min <= a) && (a <= max); + } + + /* + * + */ + + /** + * @return True if does not throw. + * @throws IllegalArgumentException if the specified value is not in the specified range (inclusive). + */ + public static boolean checkIsInRange(int min, int max, int a) { + if (!isInRange(min, max, a)) { + throw new IllegalArgumentException(a+" not in ["+min+","+max+"]"); + } + return true; + } + + /** + * @return True if does not throw. + * @throws IllegalArgumentException if the specified value is not in the specified range (inclusive). + */ + public static boolean checkIsInRange(long min, long max, long a) { + if (!isInRange(min, max, a)) { + throw new IllegalArgumentException(a+" not in ["+min+","+max+"]"); + } + return true; + } + + /** + * @return True if does not throw. + * @throws IllegalArgumentException if the specified value is not in the specified range (inclusive) + * or any parameter is NaN. + */ + public static boolean checkIsInRange(float min, float max, float a) { + if (!isInRange(min, max, a)) { + throw new IllegalArgumentException(a+" not in ["+min+","+max+"]"); + } + return true; + } + + /** + * @return True if does not throw. + * @throws IllegalArgumentException if the specified value is not in the specified range (inclusive) + * or any parameter is NaN. + */ + public static boolean checkIsInRange(double min, double max, double a) { + if (!isInRange(min, max, a)) { + throw new IllegalArgumentException(a+" not in ["+min+","+max+"]"); + } + return true; + } + + /* + * + */ + + /** + * @param min A value. + * @param max A value. + * @param a A value. + * @return min if a <= min, else max if a >= max, else a. + */ + public static int toRange(int min, int max, int a) { + if (a <= min) { + return min; + } else if (a >= max) { + return max; + } else { + return a; + } + } + + /** + * @param min A value. + * @param max A value. + * @param a A value. + * @return min if a <= min, else max if a >= max, else a. + */ + public static long toRange(long min, long max, long a) { + if (a <= min) { + return min; + } else if (a >= max) { + return max; + } else { + return a; + } + } + + /** + * @param min A value. + * @param max A value. + * @param a A value. + * @return min if a <= min, else max if a >= max, else a. + */ + public static float toRange(float min, float max, float a) { + if (a <= min) { + return min; + } else if (a >= max) { + return max; + } else { + return a; + } + } + + /** + * @param min A value. + * @param max A value. + * @param a A value. + * @return min if a <= min, else max if a >= max, else a. + */ + public static double toRange(double min, double max, double a) { + if (a <= min) { + return min; + } else if (a >= max) { + return max; + } else { + return a; + } + } + + /* + * bitwise ranges + */ + + /** + * @param bitSize A number of bits, in [1,32]. + * @return True if the specified value fits as a signed integer + * over the specified number of bits, false otherwise. + * @throws IllegalArgumentException if the specified number of bits is not in [1,32]. + */ + public static boolean isInRangeSigned(int a, int bitSize) { + checkBitSizeForSignedInt(bitSize); + return (minSignedIntForBitSize_noCheck(bitSize) <= a) && (a <= maxSignedIntForBitSize_noCheck(bitSize)); + } + + /** + * @param bitSize A number of bits, in [1,64]. + * @return True if the specified value fits as a signed integer + * over the specified number of bits, false otherwise. + * @throws IllegalArgumentException if the specified number of bits is not in [1,64]. + */ + public static boolean isInRangeSigned(long a, int bitSize) { + checkBitSizeForSignedLong(bitSize); + return (minSignedLongForBitSize_noCheck(bitSize) <= a) && (a <= maxSignedLongForBitSize_noCheck(bitSize)); + } + + /** + * @param bitSize A number of bits, in [1,31]. + * @return True if the specified value fits as an unsigned integer + * over the specified number of bits, false otherwise. + * @throws IllegalArgumentException if the specified number of bits is not in [1,31]. + */ + public static boolean isInRangeUnsigned(int a, int bitSize) { + return isInRange(0, maxUnsignedIntForBitSize(bitSize), a); + } + + /** + * @param bitSize A number of bits, in [1,63]. + * @return True if the specified value fits as an unsigned integer + * over the specified number of bits, false otherwise. + * @throws IllegalArgumentException if the specified number of bits is not in [1,63]. + */ + public static boolean isInRangeUnsigned(long a, int bitSize) { + return isInRange(0, maxUnsignedLongForBitSize(bitSize), a); + } + + /* + * + */ + + /** + * @param bitSize A number of bits, in [1,32]. + * @return True if does not throw. + * @throws IllegalArgumentException if the specified value does not fit + * as a signed integer over the specified number of bits. + */ + public static boolean checkIsInRangeSigned(int a, int bitSize) { + if (!isInRangeSigned(a, bitSize)) { + throw new IllegalArgumentException(a+" does not fit as a signed value over "+bitSize+" bits"); + } + return true; + } + + /** + * @param bitSize A number of bits, in [1,64]. + * @return True if does not throw. + * @throws IllegalArgumentException if the specified value does not fit + * as a signed integer over the specified number of bits. + */ + public static boolean checkIsInRangeSigned(long a, int bitSize) { + if (!isInRangeSigned(a, bitSize)) { + throw new IllegalArgumentException(a+" does not fit as a signed value over "+bitSize+" bits"); + } + return true; + } + + /** + * @param bitSize A number of bits, in [1,31]. + * @return True if does not throw. + * @throws IllegalArgumentException if the specified value does not fit + * as an unsigned integer over the specified number of bits. + */ + public static boolean checkIsInRangeUnsigned(int a, int bitSize) { + if (!isInRangeUnsigned(a, bitSize)) { + throw new IllegalArgumentException(a+" does not fit as an unsigned value over "+bitSize+" bits"); + } + return true; + } + + /** + * @param bitSize A number of bits, in [1,63]. + * @return True if does not throw. + * @throws IllegalArgumentException if the specified value does not fit + * as an unsigned integer over the specified number of bits. + */ + public static boolean checkIsInRangeUnsigned(long a, int bitSize) { + if (!isInRangeUnsigned(a, bitSize)) { + throw new IllegalArgumentException(a+" does not fit as an unsigned value over "+bitSize+" bits"); + } + return true; + } + + /* + * masks (int) + */ + + /** + * @param bitSize A number of bits, in [0,32]. + * @return Mask with the specified number of left bits set with 0, + * and other bits set with 1. + */ + public static int intMaskMSBits0(int bitSize) { + checkIsInRange(0, 32, bitSize); + // Shifting in two times, for >>> doesn't work for full bit size (<< as well). + final int halfish = (bitSize>>1); + return ((-1)>>>halfish)>>>(bitSize-halfish); + } + + /** + * @param bitSize A number of bits, in [0,32]. + * @return Mask with the specified number of left bits set with 1, + * and other bits set with 0. + */ + public static int intMaskMSBits1(int bitSize) { + return ~intMaskMSBits0(bitSize); + } + + /** + * @param bitSize A number of bits, in [0,32]. + * @return Mask with the specified number of right bits set with 0, + * and other bits set with 1. + */ + public static int intMaskLSBits0(int bitSize) { + return ~intMaskMSBits0(32-bitSize); + } + + /** + * @param bitSize A number of bits, in [0,32]. + * @return Mask with the specified number of right bits set with 1, + * and other bits set with 0. + */ + public static int intMaskLSBits1(int bitSize) { + return intMaskMSBits0(32-bitSize); + } + + /* + * masks (long) + */ + + /** + * @param bitSize A number of bits, in [0,64]. + * @return Mask with the specified number of left bits set with 0, + * and other bits set with 1. + */ + public static long longMaskMSBits0(int bitSize) { + checkIsInRange(0, 64, bitSize); + // Shifting in two times, for >>> doesn't work for full bit size (<< as well). + final int halfish = (bitSize>>1); + return ((-1L)>>>halfish)>>>(bitSize-halfish); + } + + /** + * @param bitSize A number of bits, in [0,64]. + * @return Mask with the specified number of left bits set with 1, + * and other bits set with 0. + */ + public static long longMaskMSBits1(int bitSize) { + return ~longMaskMSBits0(bitSize); + } + + /** + * @param bitSize A number of bits, in [0,64]. + * @return Mask with the specified number of right bits set with 0, + * and other bits set with 1. + */ + public static long longMaskLSBits0(int bitSize) { + return ~longMaskMSBits0(64-bitSize); + } + + /** + * @param bitSize A number of bits, in [0,64]. + * @return Mask with the specified number of right bits set with 1, + * and other bits set with 0. + */ + public static long longMaskLSBits1(int bitSize) { + return longMaskMSBits0(64-bitSize); + } + + /* + * signed/unsigned + */ + + /** + * @return Unsigned value corresponding to bits of the specified byte. + */ + public static short byteAsUnsigned(byte value) { + return (short)(((short)value) & 0xFF); + } + + /** + * @return Unsigned value corresponding to bits of the specified short. + */ + public static int shortAsUnsigned(short value) { + return ((int)value) & 0xFFFF; + } + + /** + * @return Unsigned value corresponding to bits of the specified int. + */ + public static long intAsUnsigned(int value) { + return ((long)value) & 0xFFFFFFFF; + } + + /* + * bitwise ranges + */ + + /** + * @return True if a signed int value can be read over the specified number of bits, + * i.e. if it is in [1,32], false otherwise. + */ + public static boolean isValidBitSizeForSignedInt(int bitSize) { + return (bitSize > 0) && (bitSize <= 32); + } + + /** + * @return True if a signed long value can be read over the specified number of bits, + * i.e. if it is in [1,64], false otherwise. + */ + public static boolean isValidBitSizeForSignedLong(int bitSize) { + return (bitSize > 0) && (bitSize <= 64); + } + + /** + * @return True if an unsigned int value can be read over the specified number of bits, + * i.e. if it is in [1,31], false otherwise. + */ + public static boolean isValidBitSizeForUnsignedInt(int bitSize) { + return (bitSize > 0) && (bitSize < 32); + } + + /** + * @return True if an unsigned long value can be read over the specified number of bits, + * i.e. if it is in [1,63], false otherwise. + */ + public static boolean isValidBitSizeForUnsignedLong(int bitSize) { + return (bitSize > 0) && (bitSize < 64); + } + + /* + * + */ + + /** + * @return True if does not throw. + * @throws IllegalArgumentException if a signed int value can't be read over the + * specified number of bits, i.e. if it is not in [1,32]. + */ + public static boolean checkBitSizeForSignedInt(int bitSize) { + if (!isValidBitSizeForSignedInt(bitSize)) { + throw new IllegalArgumentException("bit size ["+bitSize+"] must be in [1,32] for signed int values"); + } + return true; + } + + /** + * @return True if does not throw. + * @throws IllegalArgumentException if a signed long value can't be read over the + * specified number of bits, i.e. if it is not in [1,64]. + */ + public static boolean checkBitSizeForSignedLong(int bitSize) { + if (!isValidBitSizeForSignedLong(bitSize)) { + throw new IllegalArgumentException("bit size ["+bitSize+"] must be in [1,64] for signed long values"); + } + return true; + } + + /** + * @return True if does not throw. + * @throws IllegalArgumentException if an unsigned int value can't be read over the + * specified number of bits, i.e. if it is not in [1,31]. + */ + public static boolean checkBitSizeForUnsignedInt(int bitSize) { + if (!isValidBitSizeForUnsignedInt(bitSize)) { + throw new IllegalArgumentException("bit size ["+bitSize+"] must be in [1,31] for unsigned int values"); + } + return true; + } + + /** + * @return True if does not throw. + * @throws IllegalArgumentException if an unsigned long value can't be read over the + * specified number of bits, i.e. if it is not in [1,63]. + */ + public static boolean checkBitSizeForUnsignedLong(int bitSize) { + if (!isValidBitSizeForUnsignedLong(bitSize)) { + throw new IllegalArgumentException("bit size ["+bitSize+"] must be in [1,63] for unsigned long values"); + } + return true; + } + + /* + * + */ + + /** + * @param bitSize A number of bits in [1,32]. + * @return The min signed int value that can be stored over the specified number of bits. + * @throws IllegalArgumentException if the specified number of bits is out of range. + */ + public static int minSignedIntForBitSize(int bitSize) { + checkBitSizeForSignedInt(bitSize); + return minSignedIntForBitSize_noCheck(bitSize); + } + + /** + * @param bitSize A number of bits in [1,64]. + * @return The min signed long value that can be stored over the specified number of bits. + * @throws IllegalArgumentException if the specified number of bits is out of range. + */ + public static long minSignedLongForBitSize(int bitSize) { + checkBitSizeForSignedLong(bitSize); + return minSignedLongForBitSize_noCheck(bitSize); + } + + /** + * @param bitSize A number of bits in [1,32]. + * @return The max signed int value that can be stored over the specified number of bits. + * @throws IllegalArgumentException if the specified number of bits is out of range. + */ + public static int maxSignedIntForBitSize(int bitSize) { + checkBitSizeForSignedInt(bitSize); + return maxSignedIntForBitSize_noCheck(bitSize); + } + + /** + * @param bitSize A number of bits in [1,64]. + * @return The max signed long value that can be stored over the specified number of bits. + * @throws IllegalArgumentException if the specified number of bits is out of range. + */ + public static long maxSignedLongForBitSize(int bitSize) { + checkBitSizeForSignedLong(bitSize); + return maxSignedLongForBitSize_noCheck(bitSize); + } + + /** + * @param bitSize A number of bits in [1,31]. + * @return The max unsigned int value that can be stored over the specified number of bits. + * @throws IllegalArgumentException if the specified number of bits is out of range. + */ + public static int maxUnsignedIntForBitSize(int bitSize) { + checkBitSizeForUnsignedInt(bitSize); + // i.e. (1<>(31-bitSize)); + } + + /** + * @param bitSize A number of bits in [1,63]. + * @return The max unsigned long value that can be stored over the specified number of bits. + * @throws IllegalArgumentException if the specified number of bits is out of range. + */ + public static long maxUnsignedLongForBitSize(int bitSize) { + checkBitSizeForUnsignedLong(bitSize); + // i.e. (1L<>(63-bitSize)); + } + + /* + * + */ + + /** + * @return The number of bits required to store the specified value as a signed integer, + * i.e. a result in [1,32]. + */ + public static int bitSizeForSignedValue(int value) { + if (value > 0) { + return 33-Integer.numberOfLeadingZeros(value); + } else if (value == 0) { + return 1; + } else { + // Works for Integer.MIN_VALUE as well. + return 33-Integer.numberOfLeadingZeros(-value-1); + } + } + + /** + * @return The number of bits required to store the specified value as a signed integer, + * i.e. a result in [1,64]. + */ + public static int bitSizeForSignedValue(long value) { + if (value > 0) { + return 65-Long.numberOfLeadingZeros(value); + } else if (value == 0) { + return 1; + } else { + // Works for Long.MIN_VALUE as well. + return 65-Long.numberOfLeadingZeros(-value-1); + } + } + + /** + * @param value An integer value in [0,Integer.MAX_VALUE]. + * @return The number of bits required to store the specified value as an unsigned integer, + * i.e. a result in [1,31]. + * @throws IllegalArgumentException if the specified value is < 0. + */ + public static int bitSizeForUnsignedValue(int value) { + if (value > 0) { + return 32-Integer.numberOfLeadingZeros(value); + } else { + if (value == 0) { + return 1; + } else { + throw new IllegalArgumentException("unsigned value ["+value+"] must be >= 0"); + } + } + } + + /** + * @param value An integer value in [0,Long.MAX_VALUE]. + * @return The number of bits required to store the specified value as an unsigned integer, + * i.e. a result in [1,63]. + * @throws IllegalArgumentException if the specified value is < 0. + */ + public static int bitSizeForUnsignedValue(long value) { + if (value > 0) { + return 64-Long.numberOfLeadingZeros(value); + } else { + if (value == 0) { + return 1; + } else { + throw new IllegalArgumentException("unsigned value ["+value+"] must be >= 0"); + } + } + } + + /* + * integer functions + */ + + /** + * @return 1 if the specified value is > 0, 0 if it is 0, -1 otherwise. + */ + public static int signum(int a) { + return (a < 0) ? -1 : ((a == 0) ? 0 : 1); + } + + /** + * @return 1 if the specified value is > 0, 0 if it is 0, -1 otherwise. + */ + public static int signum(long a) { + return (a < 0) ? -1 : ((a == 0) ? 0 : 1); + } + + /** + * @return True if the specified value is even, false otherwise. + */ + public static boolean isEven(int a) { + return ((a&1) == 0); + } + + /** + * @return True if the specified value is even, false otherwise. + */ + public static boolean isEven(long a) { + // faster to work on ints + return isEven((int)a); + } + + /** + * @return True if the specified value is odd, false otherwise. + */ + public static boolean isOdd(int a) { + return ((a&1) != 0); + } + + /** + * @return True if the specified value is odd, false otherwise. + */ + public static boolean isOdd(long a) { + // faster to work on ints + return isOdd((int)a); + } + + /** + * @return True if the specified values are both even or both odd, false otherwise. + */ + public static boolean haveSameEvenness(int a, int b) { + return (((a^b)&1) == 0); + } + + /** + * @return True if the specified values are both even or both odd, false otherwise. + */ + public static boolean haveSameEvenness(long a, long b) { + // faster to work on ints + return haveSameEvenness((int)a, (int)b); + } + + /** + * @return True if the specified values are both >= 0 or both < 0, false otherwise. + */ + public static boolean haveSameSign(int a, int b) { + return ((a^b) >= 0); + } + + /** + * @return True if the specified values are both >= 0 or both < 0, false otherwise. + */ + public static boolean haveSameSign(long a, long b) { + return ((a^b) >= 0); + } + + /** + * @return True if the specified value is a power of two, + * i.e. a value of the form 2^k, with k >= 0. + */ + public static boolean isPowerOfTwo(int a) { + if (a <= 0) { + return false; + } + if (false) { + // also works + return (a & -a) == a; + } + return (a & (a-1)) == 0; + } + + /** + * @return True if the specified value is a power of two, + * i.e. a value of the form 2^k, with k >= 0. + */ + public static boolean isPowerOfTwo(long a) { + if (a <= 0) { + return false; + } + if (false) { + // also works + return (a & -a) == a; + } + return (a & (a-1)) == 0; + } + + /** + * @return True if the specified value is a signed power of two, + * i.e. a value of the form +-2^k, with k >= 0. + */ + public static boolean isSignedPowerOfTwo(int a) { + if (a > 0) { + return (a & (a-1)) == 0; + } else { + if (a == -a) { + // a is 0 or Integer.MIN_VALUE + return (a != 0); + } + return ((-a) & (-a-1)) == 0; + } + } + + /** + * @return True if the specified value is a signed power of two, + * i.e. a value of the form +-2^k, with k >= 0. + */ + public static boolean isSignedPowerOfTwo(long a) { + if (a > 0) { + return (a & (a-1)) == 0; + } else { + if (a == -a) { + // a is 0 or Long.MIN_VALUE + return (a != 0); + } + return ((-a) & (-a-1)) == 0; + } + } + + /** + * @param a A value in [1,Integer.MAX_VALUE]. + * @return The highest power of two <= a. + */ + public static int floorPowerOfTwo(int a) { + if (a <= 0) { + throw new IllegalArgumentException("a ["+a+"] must be > 0"); + } + return Integer.highestOneBit(a); + } + + /** + * @param a A value in [1,Long.MAX_VALUE]. + * @return The highest power of two <= a. + */ + public static long floorPowerOfTwo(long a) { + if (a <= 0) { + throw new IllegalArgumentException("a ["+a+"] must be > 0"); + } + // Faster than copying int method + // (less computations on long). + return 1L << (63 - Long.numberOfLeadingZeros(a)); + } + + /** + * @param a A value in [0,2^30]. + * @return The lowest power of two >= a. + */ + public static int ceilingPowerOfTwo(int a) { + checkIsInRange(0, (1<<30), a); + return (a >= 2) ? Integer.highestOneBit((a-1)<<1) : 1; + } + + /** + * @param a A value in [0,2^62]. + * @return The lowest power of two >= a. + */ + public static long ceilingPowerOfTwo(long a) { + checkIsInRange(0L, (1L<<62), a); + // Faster than copying int method + // (less computations on long). + return 1L << (64 - Long.numberOfLeadingZeros(a - 1)); + } + + /** + * @return Mean without overflow, rounded to the lowest value (i.e. mathematical floor((a+b)/2), using floating point division). + */ + public static int meanLow(int a, int b) { + return (a & b) + ((a ^ b) >> 1); + } + + /** + * @return Mean without overflow, rounded to the lowest value (i.e. mathematical floor((a+b)/2), using floating point division). + */ + public static long meanLow(long a, long b) { + return (a & b) + ((a ^ b) >> 1); + } + + /** + * @return Mean without overflow, rounded to the value of smallest magnitude (i.e. mathematical (a+b)/2, using integer division). + */ + public static int meanSml(int a, int b) { + int result = meanLow(a,b); + if (!haveSameEvenness(a, b)) { + // inexact + if (((a&b) < 0) || (((a|b) < 0) && (a+b < 0))) { + // both < 0, or only one is < 0 and it has the largest magnitude + result++; + } + } + return result; + } + + /** + * @return Mean without overflow, rounded to the value of smallest magnitude (i.e. mathematical (a+b)/2, using integer division). + */ + public static long meanSml(long a, long b) { + long result = meanLow(a,b); + if (!haveSameEvenness(a, b)) { + // inexact + if (((a&b) < 0) || (((a|b) < 0) && (a+b < 0))) { + // both < 0, or only one is < 0 and it has the largest magnitude + result++; + } + } + return result; + } + + /** + * Useful because a positive int value could not represent half the width + * of full int range width, which is mathematically Integer.MAX_VALUE+1. + * + * @return Minus half the range width (inclusive, and rounded to the value of smaller magnitude) + * between the specified bounds. + * @throws IllegalArgumentException if min > max. + */ + public static int negHalfWidth(int min, int max) { + if (min > max) { + throw new IllegalArgumentException("min ["+min+"] must be <= max ["+max+"]"); + } + int mean = meanLow(min, max); + return min - mean - ((min^max)&1); + } + + /** + * Useful because a positive long value could not represent half the width + * of full long range width, which is mathematically Long.MAX_VALUE+1. + * + * @return Minus half the range width (inclusive, and rounded to the value of smaller magnitude) + * between the specified bounds. + * @throws IllegalArgumentException if min > max. + */ + public static long negHalfWidth(long min, long max) { + if (min > max) { + throw new IllegalArgumentException("min ["+min+"] must be <= max ["+max+"]"); + } + long mean = meanLow(min, max); + return min - mean - ((min^max)&1); + } + + /** + * This treatment being designed for optimization, the fact that spot + * is a signed power of two is not checked. + * + * @param value A value. + * @param spot A signed power of two (i.e. a value of the form +-2^k, k >= 0). + * @return value % spot, i.e. a value in ]-|spot|,|spot|[. + */ + public static int moduloSignedPowerOfTwo(int value, int spot) { + if (spot == Integer.MIN_VALUE) { + return (value != Integer.MIN_VALUE) ? value : 0; + } else { + int s = (value>>31); + return ((((value+s) ^ s) & (abs(spot)-1)) + s) ^ s; + } + } + + /** + * This treatment being designed for optimization, the fact that spot + * is a signed power of two is not checked. + * + * @param value A value. + * @param spot A signed power of two (i.e. a value of the form +-2^k, k >= 0). + * @return value % spot, i.e. a value in ]-|spot|,|spot|[. + */ + public static long moduloSignedPowerOfTwo(long value, long spot) { + if (spot == Long.MIN_VALUE) { + return (value != Long.MIN_VALUE) ? value : 0; + } else { + long s = (value>>63); + return ((((value+s) ^ s) & (abs(spot)-1)) + s) ^ s; + } + } + + /** + * @param value An integer value > 0. + * @return The integer part of the logarithm, in base 2, of the specified value, + * i.e. a result in [0,30] + * @throws IllegalArgumentException if the specified value is <= 0. + */ + public static int log2(int value) { + if (value <= 0) { + throw new IllegalArgumentException("value ["+value+"] must be > 0"); + } + return 31-Integer.numberOfLeadingZeros(value); + } + + /** + * @param value An integer value > 0. + * @return The integer part of the logarithm, in base 2, of the specified value, + * i.e. a result in [0,62] + * @throws IllegalArgumentException if the specified value is <= 0. + */ + public static int log2(long value) { + if (value <= 0) { + throw new IllegalArgumentException("value ["+value+"] must be > 0"); + } + return 63-Long.numberOfLeadingZeros(value); + } + + /** + * Possibly faster than java.lang.Math.abs(int). + * + * @return The absolute value, except if value is Integer.MIN_VALUE, for which it returns Integer.MIN_VALUE. + */ + public static int abs(int a) { + return (a^(a>>31))-(a>>31); + } + + /** + * Possibly faster than java.lang.Math.abs(long). + * + * @return The absolute value, except if value is Long.MIN_VALUE, for which it returns Long.MIN_VALUE. + */ + public static long abs(long a) { + return (a^(a>>63))-(a>>63); + } + + /** + * @return The negative of the absolute value (always exact). + */ + public static int absNeg(int a) { + return (a>>31)-(a^(a>>31)); + } + + /** + * @return The negative of the absolute value (always exact). + */ + public static long absNeg(long a) { + return (a>>63)-(a^(a>>63)); + } + + /** + * If the specified value is in int range, the returned value is identical. + * + * @return An int hash of the specified value. + */ + public static int intHash(long a) { + if (false) { + // also works + int hash = ((int)(a>>32)) ^ ((int)a); + if (a < 0) { + hash = -hash-1; + } + return hash; + } + int hash = ((int)(a>>32)) + ((int)a); + if (a < 0) { + hash++; + } + return hash; + } + + /** + * @param a An int value. + * @return The specified value as byte. + * @throws ArithmeticException if the specified value is not in [Byte.MIN_VALUE,Byte.MAX_VALUE] range. + */ + public static byte asByte(int a) { + if (a != (byte)a) { + throw new ArithmeticException("overflow: "+a); + } + return (byte)a; + } + + /** + * @param a A long value. + * @return The specified value as int. + * @throws ArithmeticException if the specified value is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int asInt(long a) { + if (a != (int)a) { + throw new ArithmeticException("overflow: "+a); + } + return (int)a; + } + + /** + * @param a A long value. + * @return The closest int value in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int toInt(long a) { + if (a != (int)a) { + return (a < 0) ? Integer.MIN_VALUE : Integer.MAX_VALUE; + } + return (int)a; + } + + /** + * @param a An int value. + * @param b An int value. + * @return The mathematical result of a+b. + * @throws ArithmeticException if the mathematical result of a+b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int plusExact(int a, int b) { + final int sum = a + b; + // HD 2-12 Overflow iff both arguments + // have the opposite sign of the result. + if (((a ^ sum) & (b ^ sum)) < 0) { + throw new ArithmeticException("overflow: "+a+"+"+b); + } + return sum; + } + + /** + * @param a A long value. + * @param b A long value. + * @return The mathematical result of a+b. + * @throws ArithmeticException if the mathematical result of a+b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. + */ + public static long plusExact(long a, long b) { + final long sum = a + b; + // HD 2-12 Overflow iff both arguments + // have the opposite sign of the result. + if (((a ^ sum) & (b ^ sum)) < 0) { + throw new ArithmeticException("overflow: "+a+"+"+b); + } + return sum; + } + + /** + * @param a An int value. + * @param b An int value. + * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a+b. + */ + public static int plusBounded(int a, int b) { + return toInt(((long)a) + ((long)b)); + } + + /** + * @param a A long value. + * @param b A long value. + * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a+b. + */ + public static long plusBounded(long a, long b) { + final long sum = a + b; + if (((a ^ sum) & (b ^ sum)) < 0) { + return (sum >= 0) ? Long.MIN_VALUE : Long.MAX_VALUE; + } + return sum; + } + + /** + * @param a An int value. + * @param b An int value. + * @return The mathematical result of a-b. + * @throws ArithmeticException if the mathematical result of a-b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int minusExact(int a, int b) { + final int diff = a - b; + // HD 2-12 Overflow iff the arguments have different signs and + // the sign of the result is different than the sign of "a". + if (((a ^ b) & (a ^ diff)) < 0) { + throw new ArithmeticException("integer overflow"); + } + return diff; + } + + /** + * @param a A long value. + * @param b A long value. + * @return The mathematical result of a-b. + * @throws ArithmeticException if the mathematical result of a-b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. + */ + public static long minusExact(long a, long b) { + final long diff = a - b; + // HD 2-12 Overflow iff the arguments have different signs and + // the sign of the result is different than the sign of "a". + if (((a ^ b) & (a ^ diff)) < 0) { + throw new ArithmeticException("integer overflow"); + } + return diff; + } + + /** + * @param a An int value. + * @param b An int value. + * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a-b. + */ + public static int minusBounded(int a, int b) { + return toInt(((long)a) - ((long)b)); + } + + /** + * @param a A long value. + * @param b A long value. + * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a-b. + */ + public static long minusBounded(long a, long b) { + final long diff = a - b; + if (((a ^ b) & (a ^ diff)) < 0) { + return (diff >= 0) ? Long.MIN_VALUE : Long.MAX_VALUE; + } + return diff; + } + + /** + * @param a An int value. + * @param b An int value. + * @return The mathematical result of a*b. + * @throws ArithmeticException if the mathematical result of a*b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. + */ + public static int timesExact(int a, int b) { + final long prod = a * (long)b; + if (prod != (int)prod) { + throw new ArithmeticException("overflow: "+a+"*"+b); + } + return (int)prod; + } + + /** + * @param a A long value. + * @param b A long value. + * @return The mathematical result of a*b. + * @throws ArithmeticException if the mathematical result of a*b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. + */ + public static long timesExact(long a, long b) { + final long prod = a * b; + final long absA = abs(a); + final long absB = abs(b); + if (((absA|absB)>>>31) != 0) { + // Some bits greater than 2^31 that might cause overflow + // Check the result using the divide operator + // and check for the special case of Long.MIN_VALUE * -1 + if (((b != 0) && (prod/b != a)) || + ((a == Long.MIN_VALUE) && (b == -1))) { + throw new ArithmeticException("overflow: "+a+"*"+b); + } + } + return prod; + } + + /** + * @param a An int value. + * @param b An int value. + * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a*b. + */ + public static int timesBounded(int a, int b) { + return (int)(a * (double)b); + } + + /** + * @param a A long value. + * @param b A long value. + * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a*b. + */ + public static long timesBounded(long a, long b) { + final long prod = a * b; + final long absA = abs(a); + final long absB = abs(b); + if (((absA|absB)>>>31) != 0) { + // Some bits greater than 2^31 that might cause overflow + // Check the result using the divide operator + // and check for the special case of Long.MIN_VALUE * -1 + if (((b != 0) && (prod/b != a)) || + ((a == Long.MIN_VALUE) && (b == -1))) { + return ((a^b) >= 0) ? Long.MAX_VALUE : Long.MIN_VALUE; + } + } + return prod; + } + + /* + * powers + */ + + /** + * Returns the exact result, provided it's in double range, + * i.e. if power is in [-1074,1023]. + * + * @param power An int power. + * @return 2^power as a double, or +-Infinity in case of overflow. + */ + public static double twoPow(int power) { + if (power <= -MAX_DOUBLE_EXPONENT) { // Not normal. + if (power >= MIN_DOUBLE_EXPONENT) { // Subnormal. + return Double.longBitsToDouble(0x0008000000000000L>>(-(power+MAX_DOUBLE_EXPONENT))); + } else { // Underflow. + return 0.0; + } + } else if (power > MAX_DOUBLE_EXPONENT) { // Overflow. + return Double.POSITIVE_INFINITY; + } else { // Normal. + return Double.longBitsToDouble(((long)(power+MAX_DOUBLE_EXPONENT))<<52); + } + } + + /** + * @param power An int power. + * @return 2^power as an int. + * @throws ArithmeticException if the mathematical result + * is not in int range, i.e. if power is not in [0,30]. + */ + public static int twoPowAsIntExact(int power) { + if ((power < 0) || (power > 30)) { + throw new ArithmeticException("integer overflow"); + } + return 1 << power; + } + + /** + * @param power An int power. + * @return 2^power as an int, or the closest power of two in int range + * in case of overflow, i.e. if power is not in [0,30]. + */ + public static int twoPowAsIntBounded(int power) { + power = toRange(0, 30, power); + return 1 << power; + } + + /** + * @param power An int power. + * @return 2^power as a long. + * @throws ArithmeticException if the mathematical result + * is not in long range, i.e. if power is not in [0,62]. + */ + public static long twoPowAsLongExact(int power) { + if ((power < 0) || (power > 62)) { + throw new ArithmeticException("long overflow"); + } + return 1L << power; + } + + /** + * @param power An int power. + * @return 2^power as a long, or the closest power of two in long range + * in case of overflow, i.e. if power is not in [0,62]. + */ + public static long twoPowAsLongBounded(int power) { + power = toRange(0, 62, power); + return 1L << power; + } + + /** + * @param a A value. + * @return a*a. + */ + public static int pow2(int a) { + return a*a; + } + + /** + * @param a A value. + * @return a*a. + */ + public static long pow2(long a) { + return a*a; + } + + /** + * @param a A value. + * @return a*a. + */ + public static float pow2(float a) { + return a*a; + } + + /** + * Strict version. + * + * @param a A value. + * @return a*a. + */ + public static strictfp float pow2_strict(float a) { + return a*a; + } + + /** + * @param a A value. + * @return a*a. + */ + public static double pow2(double a) { + return a*a; + } + + /** + * Strict version. + * + * @param a A value. + * @return a*a. + */ + public static strictfp double pow2_strict(double a) { + return a*a; + } + + /** + * @param a A value. + * @return a*a*a. + */ + public static int pow3(int a) { + return a*a*a; + } + + /** + * @param a A value. + * @return a*a*a. + */ + public static long pow3(long a) { + return a*a*a; + } + + /** + * @param a A value. + * @return a*a*a. + */ + public static float pow3(float a) { + return a*a*a; + } + + /** + * Strict version. + * + * @param a A value. + * @return a*a*a. + */ + public static strictfp float pow3_strict(float a) { + return a*a*a; + } + + /** + * @param a A value. + * @return a*a*a. + */ + public static double pow3(double a) { + return a*a*a; + } + + /** + * Strict version. + * + * @param a A value. + * @return a*a*a. + */ + public static strictfp double pow3_strict(double a) { + return a*a*a; + } + + /* + * Accurate +-m*PI/n. + */ + + /** + * @param angRad An angle, in radians. + * @return angRad + 2*PI, accurately computed. + */ + public static double plus2PI(double angRad) { + if (angRad > -Math.PI) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad + TWOPI_LO) + TWOPI_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad + TWOPI_HI) + TWOPI_LO; + } + } + + /** + * Strict version. + * + * @param angRad An angle, in radians. + * @return angRad + 2*PI, accurately computed. + */ + public static strictfp double plus2PI_strict(double angRad) { + if (angRad > -Math.PI) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad + TWOPI_LO) + TWOPI_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad + TWOPI_HI) + TWOPI_LO; + } + } + + /** + * @param angRad An angle, in radians. + * @return angRad - 2*PI, accurately computed. + */ + public static double minus2PI(double angRad) { + if (angRad < Math.PI) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad - TWOPI_LO) - TWOPI_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad - TWOPI_HI) - TWOPI_LO; + } + } + + /** + * Strict version. + * + * @param angRad An angle, in radians. + * @return angRad - 2*PI, accurately computed. + */ + public static strictfp double minus2PI_strict(double angRad) { + if (angRad < Math.PI) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad - TWOPI_LO) - TWOPI_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad - TWOPI_HI) - TWOPI_LO; + } + } + + /** + * @param angRad An angle, in radians. + * @return angRad + PI, accurately computed. + */ + public static double plusPI(double angRad) { + if (angRad > -Math.PI/2) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad + PI_LO) + PI_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad + PI_HI) + PI_LO; + } + } + + /** + * Strict version. + * + * @param angRad An angle, in radians. + * @return angRad + PI, accurately computed. + */ + public static strictfp double plusPI_strict(double angRad) { + if (angRad > -Math.PI/2) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad + PI_LO) + PI_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad + PI_HI) + PI_LO; + } + } + + /** + * @param angRad An angle, in radians. + * @return angRad - PI, accurately computed. + */ + public static double minusPI(double angRad) { + if (angRad < Math.PI/2) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad - PI_LO) - PI_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad - PI_HI) - PI_LO; + } + } + + /** + * Strict version. + * + * @param angRad An angle, in radians. + * @return angRad - PI, accurately computed. + */ + public static strictfp double minusPI_strict(double angRad) { + if (angRad < Math.PI/2) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad - PI_LO) - PI_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad - PI_HI) - PI_LO; + } + } + + /** + * @param angRad An angle, in radians. + * @return angRad + PI/2, accurately computed. + */ + public static double plusPIO2(double angRad) { + if (angRad > -Math.PI/4) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad + PIO2_LO) + PIO2_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad + PIO2_HI) + PIO2_LO; + } + } + + /** + * Strict version. + * + * @param angRad An angle, in radians. + * @return angRad + PI/2, accurately computed. + */ + public static strictfp double plusPIO2_strict(double angRad) { + if (angRad > -Math.PI/4) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad + PIO2_LO) + PIO2_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad + PIO2_HI) + PIO2_LO; + } + } + + /** + * @param angRad An angle, in radians. + * @return angRad - PI/2, accurately computed. + */ + public static double minusPIO2(double angRad) { + if (angRad < Math.PI/4) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad - PIO2_LO) - PIO2_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad - PIO2_HI) - PIO2_LO; + } + } + + /** + * Strict version. + * + * @param angRad An angle, in radians. + * @return angRad - PI/2, accurately computed. + */ + public static strictfp double minusPIO2_strict(double angRad) { + if (angRad < Math.PI/4) { + // LO then HI, for better accuracy (if starting near 0). + return (angRad - PIO2_LO) - PIO2_HI; + } else { + // HI then LO, for better accuracy (if ending near 0). + return (angRad - PIO2_HI) - PIO2_LO; + } + } + + /* + * toString (radix) + */ + + /** + * @param radix Radix to be checked. + * @return True if does not throw. + * @throws IllegalArgumentException if the specified radix is not in [2,36]. + */ + public static boolean checkRadix(int radix) { + if (!isInRange(Character.MIN_RADIX, Character.MAX_RADIX, radix)) { + throw new IllegalArgumentException("radix ["+radix+"] must be in ["+Character.MIN_RADIX+","+Character.MAX_RADIX+"]"); + } + return true; + } + + /** + * @param radix A radix in [2,36]. + * @return Number of characters (minus sign included) + * to represent the specified value in the specified radix. + */ + public static int computeNbrOfChars(int value, int radix) { + if (value < 0) { + // 1 for sign + return 1 + computeNbrOfDigits_negValue(value, radix); + } else { + return computeNbrOfDigits_negValue(-value, radix); + } + } + + /** + * @param radix A radix in [2,36]. + * @return Number of characters (minus sign included) + * to represent the specified value in the specified radix. + */ + public static int computeNbrOfChars(long value, int radix) { + if (value < 0) { + // 1 for sign + return 1 + computeNbrOfDigits_negValue(value, radix); + } else { + return computeNbrOfDigits_negValue(-value, radix); + } + } + + /** + * @param radix A radix in [2,36]. + * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. + * @return Number of characters (minus sign included) + * to represent the specified value in the specified radix. + */ + public static int computeNbrOfChars(int value, int radix, int paddingUpTo) { + if (value < 0) { + // 1 for sign + return 1 + Math.max(paddingUpTo, computeNbrOfDigits_negValue(value, radix)); + } else { + return Math.max(paddingUpTo, computeNbrOfDigits_negValue(-value, radix)); + } + } + + /** + * @param radix A radix in [2,36]. + * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. + * @return Number of characters (minus sign included) + * to represent the specified value in the specified radix. + */ + public static int computeNbrOfChars(long value, int radix, int paddingUpTo) { + if (value < 0) { + // 1 for sign + return 1 + Math.max(paddingUpTo, computeNbrOfDigits_negValue(value, radix)); + } else { + return Math.max(paddingUpTo, computeNbrOfDigits_negValue(-value, radix)); + } + } + + /** + * @param radix A radix in [2,36]. + * @return Number of digits of the specified value in the specified radix. + */ + public static int computeNbrOfDigits(int value, int radix) { + return computeNbrOfDigits_negValue(-abs(value), radix); + } + + /** + * @param radix A radix in [2,36]. + * @return Number of digits of the specified value in the specified radix. + */ + public static int computeNbrOfDigits(long value, int radix) { + return computeNbrOfDigits_negValue(-abs(value), radix); + } + + /** + * @param radix A radix in [2,36]. + * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. + * @return Number of digits of the specified value in the specified radix, + * including the specified padding. + */ + public static int computeNbrOfDigits(int value, int radix, int paddingUpTo) { + return Math.max(paddingUpTo,computeNbrOfDigits(value, radix)); + } + + /** + * @param radix A radix in [2,36]. + * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. + * @return Number of digits of the specified value in the specified radix, + * including the specified padding. + */ + public static int computeNbrOfDigits(long value, int radix, int paddingUpTo) { + return Math.max(paddingUpTo,computeNbrOfDigits(value, radix)); + } + + /** + * This method just delegates to Integer.toString(int), + * but is defined here to complete the API. + * + * @return String representation of the specified value in base 10. + */ + public static String toString(int value) { + return Integer.toString(value); + } + + /** + * This method just delegates to Long.toString(long), + * but is defined here to complete the API. + * + * @return String representation of the specified value in base 10. + */ + public static String toString(long value) { + return Long.toString(value); + } + + /** + * @param radix A radix in [2,36]. + * @return String representation of the specified value in the specified radix. + * @throws IllegalArgumentException if the specified radix is out of range. + */ + public static String toString(int value, int radix) { + return toString(value, radix, 0); + } + + /** + * @param radix A radix in [2,36]. + * @return String representation of the specified value in the specified radix. + * @throws IllegalArgumentException if the specified radix is out of range. + */ + public static String toString(long value, int radix) { + return toString(value, radix, 0); + } + + /** + * @param radix A radix in [2,36]. + * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. + * @return String representation of the specified value in the specified radix. + * @throws IllegalArgumentException if the specified radix is out of range. + */ + public static String toString(int value, int radix, int paddingUpTo) { + // Only one test if radix+paddingUpTo != 10. + if ((radix+paddingUpTo == 10) && (paddingUpTo == 0)) { + // Using JDK's optimized algorithm. + return Integer.toString(value); + } + + int negValue; + final int signSize; + final boolean negative = (value < 0); + if (negative) { + negValue = value; + signSize = 1; + } else { + negValue = -value; + signSize = 0; + } + // Faster if we just use max possible number of characters (33), + // but we prefer to take care of garbage's memory footprint. + // Checks radix. + final int nbrOfChars = signSize + Math.max(paddingUpTo, computeNbrOfDigits_negValue(negValue, radix)); + + final char[] chars = new char[nbrOfChars]; + + int charPos = nbrOfChars; + + final boolean radixIsPowerOfTwo = ((radix & (radix-1)) == 0); + // Not allowing Integer.MIN_VALUE so it can be negated. + if (radixIsPowerOfTwo && (negValue != Integer.MIN_VALUE)) { + final int mask = radix-1; + final int divShift = DIV_SHIFT_BY_RADIX[radix]; + while (negValue <= -radix) { + chars[--charPos] = CHAR_BY_DIGIT[(int)((-negValue) & mask)]; + negValue = -((-negValue) >> divShift); + } + } else { + while (negValue <= -radix) { + chars[--charPos] = CHAR_BY_DIGIT[(int)(-(negValue % radix))]; + negValue /= radix; + } + } + chars[--charPos] = CHAR_BY_DIGIT[(int)(-negValue)]; + + while (charPos > signSize) { + chars[--charPos] = '0'; + } + + if (negative) { + chars[0] = '-'; + } + + return new String(chars); + } + + /** + * @param radix A radix in [2,36]. + * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. + * @return String representation of the specified value in the specified radix. + * @throws IllegalArgumentException if the specified radix is out of range. + */ + public static String toString(long value, int radix, int paddingUpTo) { + // Only one test if radix+paddingUpTo != 10. + if ((radix+paddingUpTo == 10) && (paddingUpTo == 0)) { + // Using JDK's optimized algorithm. + return Long.toString(value); + } + + long negValue; + final int signSize; + final boolean negative = (value < 0); + if (negative) { + negValue = value; + signSize = 1; + } else { + negValue = -value; + signSize = 0; + } + // Checks radix. + final int nbrOfChars = signSize + Math.max(paddingUpTo, computeNbrOfDigits_negValue(negValue, radix)); + + final char[] chars = new char[nbrOfChars]; + + int charPos = nbrOfChars; + + final boolean radixIsPowerOfTwo = ((radix & (radix-1)) == 0); + // Not allowing Long.MIN_VALUE so it can be negated. + if (radixIsPowerOfTwo && (negValue != Long.MIN_VALUE)) { + final int mask = radix-1; + final int divShift = DIV_SHIFT_BY_RADIX[radix]; + while (negValue <= -radix) { + chars[--charPos] = CHAR_BY_DIGIT[(int)((-negValue) & mask)]; + negValue = -((-negValue) >> divShift); + } + } else { + while (negValue <= -radix) { + chars[--charPos] = CHAR_BY_DIGIT[(int)(-(negValue % radix))]; + negValue /= radix; + } + } + chars[--charPos] = CHAR_BY_DIGIT[(int)(-negValue)]; + + while (charPos > signSize) { + chars[--charPos] = '0'; + } + + if (negative) { + chars[0] = '-'; + } + + return new String(chars); + } + + /* + * toString (bits) + */ + + /** + * @param firstBitPos First bit position (inclusive). + * @param lastBitPosExcl Last bit position (exclusive). + * @return True if does not throw. + * @throws IllegalArgumentException if the specified bit range does not fit in a byte. + */ + public static boolean checkBitPositionsByte(int firstBitPos, int lastBitPosExcl) { + return checkBitPositions(firstBitPos, lastBitPosExcl, 8); + } + + /** + * @param firstBitPos First bit position (inclusive). + * @param lastBitPosExcl Last bit position (exclusive). + * @return True if does not throw. + * @throws IllegalArgumentException if the specified bit range does not fit in a short. + */ + public static boolean checkBitPositionsShort(int firstBitPos, int lastBitPosExcl) { + return checkBitPositions(firstBitPos, lastBitPosExcl, 16); + } + + /** + * @param firstBitPos First bit position (inclusive). + * @param lastBitPosExcl Last bit position (exclusive). + * @return True if does not throw. + * @throws IllegalArgumentException if the specified bit range does not fit in an int. + */ + public static boolean checkBitPositionsInt(int firstBitPos, int lastBitPosExcl) { + return checkBitPositions(firstBitPos, lastBitPosExcl, 32); + } + + /** + * @param firstBitPos First bit position (inclusive). + * @param lastBitPosExcl Last bit position (exclusive). + * @return True if does not throw. + * @throws IllegalArgumentException if the specified bit range does not fit in a long. + */ + public static boolean checkBitPositionsLong(int firstBitPos, int lastBitPosExcl) { + return checkBitPositions(firstBitPos, lastBitPosExcl, 64); + } + + /** + * @return String representation of specified bits, in big endian. + */ + public static String toStringBits(byte bits) { + final char[] chars = new char[8]; + int bitIndex = 8; + while (--bitIndex >= 0) { + chars[7-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + } + return new String(chars); + } + + /** + * @return String representation of specified bits, in big endian. + */ + public static String toStringBits(short bits) { + final char[] chars = new char[16]; + int bitIndex = 16; + while (--bitIndex >= 0) { + chars[15-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + } + return new String(chars); + } + + /** + * @return String representation of specified bits, in big endian. + */ + public static String toStringBits(int bits) { + final char[] chars = new char[32]; + int bitIndex = 32; + while (--bitIndex >= 0) { + chars[31-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + } + return new String(chars); + } + + /** + * @return String representation of specified bits, in big endian. + */ + public static String toStringBits(long bits) { + final char[] chars = new char[64]; + int bitIndex = 64; + while (--bitIndex >= 0) { + chars[63-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + } + return new String(chars); + } + + /** + * @param firstBitPos First bit position (inclusive). + * @param lastBitPosExcl Last bit position (exclusive). + * @param bigEndian True for bits to be added in big endian order (MSBit to LSBit) + * false for little endian order. + * @param padding True if underscores must be added instead of out-of-range bits, + * false to just add characters corresponding to in-range bits. + * @return String representation of specified bits. + */ + public static String toStringBits( + byte bits, + int firstBitPos, + int lastBitPosExcl, + boolean bigEndian, + boolean padding) { + checkBitPositionsByte(firstBitPos, lastBitPosExcl); + return toStringBits_0_32_bitPosAlreadyChecked(8,bits, firstBitPos, lastBitPosExcl, bigEndian, padding); + } + + /** + * @param firstBitPos First bit position (inclusive). + * @param lastBitPosExcl Last bit position (exclusive). + * @param bigEndian True for bits to be added in big endian order (MSBit to LSBit) + * false for little endian order. + * @param padding True if underscores must be added instead of out-of-range bits, + * false to just add characters corresponding to in-range bits. + * @return String representation of specified bits. + */ + public static String toStringBits( + short bits, + int firstBitPos, + int lastBitPosExcl, + boolean bigEndian, + boolean padding) { + checkBitPositionsShort(firstBitPos, lastBitPosExcl); + return toStringBits_0_32_bitPosAlreadyChecked(16,bits, firstBitPos, lastBitPosExcl, bigEndian, padding); + } + + /** + * @param firstBitPos First bit position (inclusive). + * @param lastBitPosExcl Last bit position (exclusive). + * @param bigEndian True for bits to be added in big endian order (MSBit to LSBit) + * false for little endian order. + * @param padding True if underscores must be added instead of out-of-range bits, + * false to just add characters corresponding to in-range bits. + * @return String representation of specified bits. + */ + public static String toStringBits( + int bits, + int firstBitPos, + int lastBitPosExcl, + boolean bigEndian, + boolean padding) { + checkBitPositionsInt(firstBitPos, lastBitPosExcl); + return toStringBits_0_32_bitPosAlreadyChecked(32,bits, firstBitPos, lastBitPosExcl, bigEndian, padding); + } + + /** + * @param firstBitPos First bit position (inclusive). + * @param lastBitPosExcl Last bit position (exclusive). + * @param bigEndian True for bits to be added in big endian order (MSBit to LSBit) + * false for little endian order. + * @param padding True if underscores must be added instead of out-of-range bits, + * false to just add characters corresponding to in-range bits. + * @return String representation of specified bits. + */ + public static String toStringBits( + long bits, + int firstBitPos, + int lastBitPosExcl, + boolean bigEndian, + boolean padding) { + checkBitPositionsLong(firstBitPos, lastBitPosExcl); + final int bitSize = 64; + final int bitSizeM1 = bitSize-1; + final int lastBitPos = lastBitPosExcl-1; + if (padding) { + final int nbrOfChars = bitSize; + final char[] chars = new char[nbrOfChars]; + int bitIndex = bitSizeM1; + if (bigEndian) { + final int firstBitIndex = bitSizeM1-lastBitPos; + final int lastBitIndex = bitSizeM1-firstBitPos; + while (bitIndex > lastBitIndex) { + chars[bitSizeM1-bitIndex] = '_'; + --bitIndex; + } + while (bitIndex >= firstBitIndex) { + chars[bitSizeM1-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + --bitIndex; + } + while (bitIndex >= 0) { + chars[bitSizeM1-bitIndex] = '_'; + --bitIndex; + } + } else { + while (bitIndex > lastBitPos) { + chars[bitIndex] = '_'; + --bitIndex; + } + while (bitIndex >= firstBitPos) { + chars[bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + --bitIndex; + } + while (bitIndex >= 0) { + chars[bitIndex] = '_'; + --bitIndex; + } + } + return new String(chars); + } else { + final int nbrOfChars = (lastBitPosExcl - firstBitPos); + final char[] chars = new char[nbrOfChars]; + if (bigEndian) { + final int firstBitIndex = bitSizeM1-lastBitPos; + final int lastBitIndex = bitSizeM1-firstBitPos; + int bitIndex = lastBitIndex; + while (bitIndex >= firstBitIndex) { + chars[lastBitIndex-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + --bitIndex; + } + } else { + int bitIndex = lastBitPos; + while (bitIndex >= firstBitPos) { + chars[bitIndex-firstBitPos] = (char)('0'+((bits>>bitIndex)&1)); + --bitIndex; + } + } + return new String(chars); + } + } + + /* + * toString (floating points) + * + * toStringCSN(double) and toStringNoCSN(double) + * could be made faster, by using directly internals + * of Double.toString(double), but this would require + * copy-paste of much tricky code from JDK, and + * the overhead of our little rework is relatively + * negligible. + */ + + /** + * @param value A double value. + * @return String representing the specified value, + * using "computerized scientific notation", + * which Double.toString(double) uses for non-infinite + * values, when |value| < 1e-3 or |value| >= 1e7. + */ + public static String toStringCSN(double value) { + // Quick case (also to get rid of +-0.0, + // for which Double.toString(double) doesn't use CSN). + if (value == 0.0) { + if (Double.doubleToRawLongBits(value) < 0) { + return "-0.0E0"; + } else { + return "0.0E0"; + } + } + + final double abs = Math.abs(value); + if ((abs >= NO_CSN_MIN_BOUND_INCL) && (abs < NO_CSN_MAX_BOUND_EXCL)) { + final boolean neg = (value < 0.0); + + final String rawAbs = Double.toString(abs); + if (abs >= 1.0) { + /* + * 0123456 + * 12.3456 ===> 1.23456E1 + * 123.0 ===> 1.23E2 + */ + final int dotIndex = rawAbs.indexOf((int)'.'); + final int powerOfTen = dotIndex-1; + final StringBuilder sb = new StringBuilder(); + if (neg) { + sb.append('-'); + } + // Adding unit-or-above digits, with dot after first one. + sb.append(rawAbs.charAt(0)); + sb.append('.'); + sb.append(rawAbs,1,dotIndex); + if ((value != (int)value) || (abs < 10.0)) { + // Adding below-unit digits (possibly just 0 if abs < 10.0, + // to end up for example with "3.0E0" instead of "3.E0"). + sb.append(rawAbs,dotIndex+1,rawAbs.length()); + } + sb.append('E'); + sb.append(CHAR_BY_DIGIT[powerOfTen]); + return sb.toString(); + } else { + /* + * 012345678 + * 0.0123456 ===> 1.23456E-2 + * 0.01 ===> 1.0E-2 + */ + int nonZeroIndex = 1; + while (rawAbs.charAt(++nonZeroIndex) == '0') { + } + // Negative. + final int powerOfTen = 1-nonZeroIndex; + final int nbrOfSignificantDigitsPastDot = (rawAbs.length() - (nonZeroIndex+1)); + final StringBuilder sb = new StringBuilder(); + if (neg) { + sb.append('-'); + } + sb.append(rawAbs.charAt(nonZeroIndex)); + sb.append('.'); + if (nbrOfSignificantDigitsPastDot > 0) { + // If bug 4428022 make rawAbs being something like "0.0010", + // we add the last '0' here after the dot, which is fine. + sb.append(rawAbs,nonZeroIndex+1,rawAbs.length()); + } else { + sb.append('0'); + } + sb.append("E-"); + sb.append(CHAR_BY_DIGIT[-powerOfTen]); + return sb.toString(); + } + } else { + return Double.toString(value); + } + } + + /** + * @param value A double value. + * @return String representing the specified value, + * not in "computerized scientific notation", + * which Double.toString(double) uses for non-infinite + * values, when |value| < 1e-3 or |value| >= 1e7. + */ + public static String toStringNoCSN(double value) { + // Quick case. + // Should also work with long instead of int, + // but less obvious (due to roundings...), + // and we just want to speed up the more common + // case of "small" integer values. + final int intValue = (int)value; + if (value == intValue) { + if (value == 0.0) { + if (Double.doubleToRawLongBits(value) < 0) { + return "-0.0"; + } else { + return "0.0"; + } + } else { + return Integer.toString(intValue)+".0"; + } + } + + final String raw = Double.toString(value); + final double abs = Math.abs(value); + if (abs >= NO_CSN_MAX_BOUND_EXCL) { + if (abs == Double.POSITIVE_INFINITY) { + return raw; + } + /* + * 0123456789 + * 1.234567E5 ===> 123456.7 + * 1.23456E5 ===> 123456.0 (adding 0) + * 1.23E5 ===> 123000.0 + * 1.0E5 ===> 100000.0 + */ + // "." close to start, so using indexOf. + final int dotIndex = raw.indexOf((int)'.'); + // "E" close to end, so using lastIndexOf. + final int eIndex = raw.lastIndexOf((int)'E'); + final int powerOfTen = Integer.parseInt(raw.substring(eIndex+1)); + final int nbrOfSignificantLoDigits = (eIndex - dotIndex - 1); + final int nbrOfZerosToAddBeforeDot = (powerOfTen - nbrOfSignificantLoDigits); + + int start; + int end; + + final StringBuilder sb = new StringBuilder(); + sb.append(raw,0,dotIndex); + if (nbrOfZerosToAddBeforeDot >= 0) { + // Can copy all digits that were between '.' and 'E'. + sb.append(raw,dotIndex+1,eIndex); + for (int i=0;i 0.0001234 + * 1.0E-4 ===> 0.0001 + */ + // "." close to start, so using indexOf. + final int dotIndex = raw.indexOf((int)'.'); + // "E" close to end, so using lastIndexOf. + final int eIndex = raw.lastIndexOf((int)'E'); + // Negative. + final int powerOfTen = Integer.parseInt(raw.substring(eIndex+1)); + final int nbrOfZerosToAddAfterDot = (-powerOfTen-1); + + final StringBuilder sb = new StringBuilder(); + if (value < 0.0) { + sb.append("-0."); + } else { + sb.append("0."); + } + for (int i=0;i>(32-bitSize)); + } + + private static long minSignedLongForBitSize_noCheck(int bitSize) { + // i.e. (-1L<<(bitSize-1)) + return (Long.MIN_VALUE>>(64-bitSize)); + } + + private static int maxSignedIntForBitSize_noCheck(int bitSize) { + // i.e. (1<<(bitSize-1))-1 + return (Integer.MAX_VALUE>>(32-bitSize)); + } + + private static long maxSignedLongForBitSize_noCheck(int bitSize) { + // i.e. (1L<<(bitSize-1))-1 + return (Long.MAX_VALUE>>(64-bitSize)); + } + + /* + * + */ + + /** + * @throws IllegalArgumentException if the specified radix is out of range. + */ + private static int computeNbrOfDigits_negValue(int negValue, int radix) { + checkRadix(radix); + final int maxNbrOfDigits = MAX_NBR_OF_NEG_INT_DIGITS_BY_RADIX[radix]; + int p = radix; + for (int i=1;i -p) { + return i; + } + p *= radix; + } + return maxNbrOfDigits; + } + + /** + * @throws IllegalArgumentException if the specified radix is out of range. + */ + private static int computeNbrOfDigits_negValue(long negValue, int radix) { + checkRadix(radix); + final int maxNbrOfDigits = MAX_NBR_OF_NEG_LONG_DIGITS_BY_RADIX[radix]; + long p = radix; + for (int i=1;i -p) { + return i; + } + p *= radix; + } + return maxNbrOfDigits; + } + + /* + * + */ + + private static boolean checkBitPositions(int firstBitPos, int lastBitPosExcl, int bitSize) { + if ((firstBitPos < 0) || (firstBitPos > lastBitPosExcl) || (lastBitPosExcl > bitSize)) { + throw new IllegalArgumentException( + "bit positions (first="+firstBitPos+",lastExcl="+lastBitPosExcl + +") must verify 0 <= first <= lastExcl <= "+bitSize); + } + return true; + } + + /** + * Common method for byte, short and int. + * Could be a bit faster to have specific methods for byte and short, + * but not much, and that would also make more messy (byte-)code. + * + * @param bitSize Must be in [0,32]. + */ + private static String toStringBits_0_32_bitPosAlreadyChecked( + int bitSize, + int bits, + int firstBitPos, + int lastBitPosExcl, + boolean bigEndian, + boolean padding) { + final int bitSizeM1 = bitSize-1; + final int lastBitPos = lastBitPosExcl-1; + if (padding) { + final int nbrOfChars = bitSize; + final char[] chars = new char[nbrOfChars]; + int bitIndex = bitSizeM1; + if (bigEndian) { + final int firstBitIndex = bitSizeM1-lastBitPos; + final int lastBitIndex = bitSizeM1-firstBitPos; + while (bitIndex > lastBitIndex) { + chars[bitSizeM1-bitIndex] = '_'; + --bitIndex; + } + while (bitIndex >= firstBitIndex) { + chars[bitSizeM1-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + --bitIndex; + } + while (bitIndex >= 0) { + chars[bitSizeM1-bitIndex] = '_'; + --bitIndex; + } + } else { + while (bitIndex > lastBitPos) { + chars[bitIndex] = '_'; + --bitIndex; + } + while (bitIndex >= firstBitPos) { + chars[bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + --bitIndex; + } + while (bitIndex >= 0) { + chars[bitIndex] = '_'; + --bitIndex; + } + } + return new String(chars); + } else { + final int nbrOfChars = (lastBitPosExcl - firstBitPos); + final char[] chars = new char[nbrOfChars]; + if (bigEndian) { + final int firstBitIndex = bitSizeM1-lastBitPos; + final int lastBitIndex = bitSizeM1-firstBitPos; + int bitIndex = lastBitIndex; + while (bitIndex >= firstBitIndex) { + chars[lastBitIndex-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); + --bitIndex; + } + } else { + int bitIndex = lastBitPos; + while (bitIndex >= firstBitPos) { + chars[bitIndex-firstBitPos] = (char)('0'+((bits>>bitIndex)&1)); + --bitIndex; + } + } + return new String(chars); + } + } +} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/StrictFastMath.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/StrictFastMath.java new file mode 100644 index 000000000..a61ac9772 --- /dev/null +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/StrictFastMath.java @@ -0,0 +1,2998 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.jafama; + +/** + * Strict versions of FastMath methods. + * Cf. README.txt for more info. + */ +public final strictfp class StrictFastMath extends CmnFastMath { + + /* + * We use strictfp for the whole class: + * - for simplicity, + * - to reduce strictfp/non-strictfp switching, which can add overhead, + * when these treatments are used from within strictfp code, + * - to make sure that we only use and return non-extended values, + * else if strictfp gets added later to some treatments they might then + * behave differently due to no longer being inlinable into FP-wide + * expressions, + * - to make sure we don't mistakenly not use it. + */ + + //-------------------------------------------------------------------------- + // CONFIGURATION + //-------------------------------------------------------------------------- + + private static final boolean USE_JDK_MATH = SFM_USE_JDK_MATH; + + private static final boolean USE_REDEFINED_LOG = SFM_USE_REDEFINED_LOG; + + private static final boolean USE_REDEFINED_SQRT = SFM_USE_REDEFINED_SQRT; + + private static final boolean USE_POWTABS_FOR_ASIN = SFM_USE_POWTABS_FOR_ASIN; + + //-------------------------------------------------------------------------- + // PUBLIC METHODS + //-------------------------------------------------------------------------- + + /* + * trigonometry + */ + + /** + * @param angle Angle in radians. + * @return Angle sine. + */ + public static double sin(double angle) { + if (USE_JDK_MATH) { + return StrictMath.sin(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { + if (false) { + // Can give very bad relative error near PI (mod 2*PI). + angle = remainderTwoPi(angle); + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } else { + final long remAndQuad = remainderPiO2(angle); + angle = decodeRemainder(remAndQuad); + final double sin; + final int q = decodeQuadrant(remAndQuad); + if (q == 0) { + sin = sin(angle); + } else if (q == 1) { + sin = cos(angle); + } else if (q == 2) { + sin = -sin(angle); + } else { + sin = -cos(angle); + } + return (negateResult ? -sin : sin); + } + } + // index: possibly outside tables range. + int index = (int)(angle * SIN_COS_INDEXER + 0.5); + double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; + // Making sure index is within tables range. + // Last value of each table is the same than first, + // so we ignore it (tabs size minus one) for modulo. + index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) + double indexSin = MyTSinCos.sinTab[index]; + double indexCos = MyTSinCos.cosTab[index]; + double result = indexSin + delta * (indexCos + delta * (-indexSin * ONE_DIV_F2 + delta * (-indexCos * ONE_DIV_F3 + delta * indexSin * ONE_DIV_F4))); + return negateResult ? -result : result; + } + + /** + * Quick sin, with accuracy of about 1.6e-3 (PI/) + * for |angle| < 6588395.0 (Integer.MAX_VALUE * (2*PI/) - 2) + * (- 2 due to removing PI/2 before using cosine tab), + * and no accuracy at all for larger values. + * + * @param angle Angle in radians. + * @return Angle sine. + */ + public static double sinQuick(double angle) { + if (USE_JDK_MATH) { + return StrictMath.sin(angle); + } + return MyTSinCos.cosTab[((int)(Math.abs(angle-Math.PI/2) * SIN_COS_INDEXER + 0.5)) & (SIN_COS_TABS_SIZE-2)]; + } + + /** + * @param angle Angle in radians. + * @return Angle cosine. + */ + public static double cos(double angle) { + if (USE_JDK_MATH) { + return StrictMath.cos(angle); + } + angle = Math.abs(angle); + if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { + if (false) { + // Can give very bad relative error near PI (mod 2*PI). + angle = remainderTwoPi(angle); + if (angle < 0.0) { + angle = -angle; + } + } else { + final long remAndQuad = remainderPiO2(angle); + angle = decodeRemainder(remAndQuad); + final double cos; + final int q = decodeQuadrant(remAndQuad); + if (q == 0) { + cos = cos(angle); + } else if (q == 1) { + cos = -sin(angle); + } else if (q == 2) { + cos = -cos(angle); + } else { + cos = sin(angle); + } + return cos; + } + } + // index: possibly outside tables range. + int index = (int)(angle * SIN_COS_INDEXER + 0.5); + double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; + // Making sure index is within tables range. + // Last value of each table is the same than first, + // so we ignore it (tabs size minus one) for modulo. + index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) + double indexCos = MyTSinCos.cosTab[index]; + double indexSin = MyTSinCos.sinTab[index]; + return indexCos + delta * (-indexSin + delta * (-indexCos * ONE_DIV_F2 + delta * (indexSin * ONE_DIV_F3 + delta * indexCos * ONE_DIV_F4))); + } + + /** + * Quick cos, with accuracy of about 1.6e-3 (PI/) + * for |angle| < 6588397.0 (Integer.MAX_VALUE * (2*PI/)), + * and no accuracy at all for larger values. + * + * @param angle Angle in radians. + * @return Angle cosine. + */ + public static double cosQuick(double angle) { + if (USE_JDK_MATH) { + return StrictMath.cos(angle); + } + return MyTSinCos.cosTab[((int)(Math.abs(angle) * SIN_COS_INDEXER + 0.5)) & (SIN_COS_TABS_SIZE-2)]; + } + + /** + * Computes sine and cosine together. + * + * @param angle Angle in radians. + * @param cosine (out) Angle cosine. + * @return Angle sine. + */ + public static double sinAndCos(double angle, DoubleWrapper cosine) { + if (USE_JDK_MATH) { + cosine.value = StrictMath.cos(angle); + return StrictMath.sin(angle); + } + // Using the same algorithm than sin(double) method, + // and computing also cosine at the end. + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { + if (false) { + // Can give very bad relative error near PI (mod 2*PI). + angle = remainderTwoPi(angle); + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } else { + final long remAndQuad = remainderPiO2(angle); + angle = decodeRemainder(remAndQuad); + final double sin; + final int q = decodeQuadrant(remAndQuad); + if (q == 0) { + sin = sin(angle); + cosine.value = cos(angle); + } else if (q == 1) { + sin = cos(angle); + cosine.value = -sin(angle); + } else if (q == 2) { + sin = -sin(angle); + cosine.value = -cos(angle); + } else { + sin = -cos(angle); + cosine.value = sin(angle); + } + return (negateResult ? -sin : sin); + } + } + int index = (int)(angle * SIN_COS_INDEXER + 0.5); + double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; + index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) + double indexSin = MyTSinCos.sinTab[index]; + double indexCos = MyTSinCos.cosTab[index]; + // Could factor some multiplications (delta * factorials), but then is less accurate. + cosine.value = indexCos + delta * (-indexSin + delta * (-indexCos * ONE_DIV_F2 + delta * (indexSin * ONE_DIV_F3 + delta * indexCos * ONE_DIV_F4))); + double result = indexSin + delta * (indexCos + delta * (-indexSin * ONE_DIV_F2 + delta * (-indexCos * ONE_DIV_F3 + delta * indexSin * ONE_DIV_F4))); + return negateResult ? -result : result; + } + + /** + * Can have very bad relative error near +-PI/2, + * but of the same magnitude than the relative delta between + * StrictMath.tan(PI/2) and StrictMath.tan(nextDown(PI/2)). + * + * @param angle Angle in radians. + * @return Angle tangent. + */ + public static double tan(double angle) { + if (USE_JDK_MATH) { + return StrictMath.tan(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle > TAN_MAX_VALUE_FOR_INT_MODULO) { + angle = remainderPi(angle); + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } + // index: possibly outside tables range. + int index = (int)(angle * TAN_INDEXER + 0.5); + double delta = (angle - index * TAN_DELTA_HI) - index * TAN_DELTA_LO; + // Making sure index is within tables range. + // index modulo PI, i.e. 2*(virtual tab size minus one). + index &= (2*(TAN_VIRTUAL_TABS_SIZE-1)-1); // index % (2*(TAN_VIRTUAL_TABS_SIZE-1)) + // Here, index is in [0,2*(TAN_VIRTUAL_TABS_SIZE-1)-1], i.e. indicates an angle in [0,PI[. + if (index > (TAN_VIRTUAL_TABS_SIZE-1)) { + index = (2*(TAN_VIRTUAL_TABS_SIZE-1)) - index; + delta = -delta; + negateResult = !negateResult; + } + double result; + if (index < TAN_TABS_SIZE) { + result = MyTTan.tanTab[index] + + delta * (MyTTan.tanDer1DivF1Tab[index] + + delta * (MyTTan.tanDer2DivF2Tab[index] + + delta * (MyTTan.tanDer3DivF3Tab[index] + + delta * MyTTan.tanDer4DivF4Tab[index]))); + } else { // angle in ]TAN_MAX_VALUE_FOR_TABS,TAN_MAX_VALUE_FOR_INT_MODULO], or angle is NaN + // Using tan(angle) == 1/tan(PI/2-angle) formula: changing angle (index and delta), and inverting. + index = (TAN_VIRTUAL_TABS_SIZE-1) - index; + result = 1/(MyTTan.tanTab[index] + - delta * (MyTTan.tanDer1DivF1Tab[index] + - delta * (MyTTan.tanDer2DivF2Tab[index] + - delta * (MyTTan.tanDer3DivF3Tab[index] + - delta * MyTTan.tanDer4DivF4Tab[index])))); + } + return negateResult ? -result : result; + } + + /** + * @param value Value in [-1,1]. + * @return Value arcsine, in radians, in [-PI/2,PI/2]. + */ + public static double asin(double value) { + if (USE_JDK_MATH) { + return StrictMath.asin(value); + } + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + if (value <= ASIN_MAX_VALUE_FOR_TABS) { + int index = (int)(value * ASIN_INDEXER + 0.5); + double delta = value - index * ASIN_DELTA; + double result = MyTAsin.asinTab[index] + + delta * (MyTAsin.asinDer1DivF1Tab[index] + + delta * (MyTAsin.asinDer2DivF2Tab[index] + + delta * (MyTAsin.asinDer3DivF3Tab[index] + + delta * MyTAsin.asinDer4DivF4Tab[index]))); + return negateResult ? -result : result; + } else if (USE_POWTABS_FOR_ASIN && (value <= ASIN_MAX_VALUE_FOR_POWTABS)) { + int index = (int)(powFast(value * ASIN_POWTABS_ONE_DIV_MAX_VALUE, ASIN_POWTABS_POWER) * ASIN_POWTABS_SIZE_MINUS_ONE + 0.5); + double delta = value - MyTAsinPow.asinParamPowTab[index]; + double result = MyTAsinPow.asinPowTab[index] + + delta * (MyTAsinPow.asinDer1DivF1PowTab[index] + + delta * (MyTAsinPow.asinDer2DivF2PowTab[index] + + delta * (MyTAsinPow.asinDer3DivF3PowTab[index] + + delta * MyTAsinPow.asinDer4DivF4PowTab[index]))); + return negateResult ? -result : result; + } else { // value > ASIN_MAX_VALUE_FOR_TABS, or value is NaN + // This part is derived from fdlibm. + if (value < 1.0) { + double t = (1.0 - value)*0.5; + double p = t*(ASIN_PS0+t*(ASIN_PS1+t*(ASIN_PS2+t*(ASIN_PS3+t*(ASIN_PS4+t*ASIN_PS5))))); + double q = 1.0+t*(ASIN_QS1+t*(ASIN_QS2+t*(ASIN_QS3+t*ASIN_QS4))); + double s = sqrt(t); + double z = s+s*(p/q); + double result = ASIN_PIO2_HI-((z+z)-ASIN_PIO2_LO); + return negateResult ? -result : result; + } else { // value >= 1.0, or value is NaN + if (value == 1.0) { + return negateResult ? -Math.PI/2 : Math.PI/2; + } else { + return Double.NaN; + } + } + } + } + + /** + * If value is not NaN and is outside [-1,1] range, closest value in this range is used. + * + * @param value Value in [-1,1]. + * @return Value arcsine, in radians, in [-PI/2,PI/2]. + */ + public static double asinInRange(double value) { + if (value <= -1.0) { + return -Math.PI/2; + } else if (value >= 1.0) { + return Math.PI/2; + } else { + return asin(value); + } + } + + /** + * @param value Value in [-1,1]. + * @return Value arccosine, in radians, in [0,PI]. + */ + public static double acos(double value) { + if (USE_JDK_MATH) { + return StrictMath.acos(value); + } + return Math.PI/2 - asin(value); + } + + /** + * If value is not NaN and is outside [-1,1] range, + * closest value in this range is used. + * + * @param value Value in [-1,1]. + * @return Value arccosine, in radians, in [0,PI]. + */ + public static double acosInRange(double value) { + if (value <= -1.0) { + return Math.PI; + } else if (value >= 1.0) { + return 0.0; + } else { + return acos(value); + } + } + + /** + * @param value A double value. + * @return Value arctangent, in radians, in [-PI/2,PI/2]. + */ + public static double atan(double value) { + if (USE_JDK_MATH) { + return StrictMath.atan(value); + } + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + if (value == 1.0) { + // We want "exact" result for 1.0. + return negateResult ? -Math.PI/4 : Math.PI/4; + } else if (value <= ATAN_MAX_VALUE_FOR_TABS) { + int index = (int)(value * ATAN_INDEXER + 0.5); + double delta = value - index * ATAN_DELTA; + double result = MyTAtan.atanTab[index] + + delta * (MyTAtan.atanDer1DivF1Tab[index] + + delta * (MyTAtan.atanDer2DivF2Tab[index] + + delta * (MyTAtan.atanDer3DivF3Tab[index] + + delta * MyTAtan.atanDer4DivF4Tab[index]))); + return negateResult ? -result : result; + } else { // value > ATAN_MAX_VALUE_FOR_TABS, or value is NaN + // This part is derived from fdlibm. + if (value < TWO_POW_66) { + double x = -1/value; + double x2 = x*x; + double x4 = x2*x2; + double s1 = x2*(ATAN_AT0+x4*(ATAN_AT2+x4*(ATAN_AT4+x4*(ATAN_AT6+x4*(ATAN_AT8+x4*ATAN_AT10))))); + double s2 = x4*(ATAN_AT1+x4*(ATAN_AT3+x4*(ATAN_AT5+x4*(ATAN_AT7+x4*ATAN_AT9)))); + double result = ATAN_HI3-((x*(s1+s2)-ATAN_LO3)-x); + return negateResult ? -result : result; + } else { // value >= 2^66, or value is NaN + if (value != value) { + return Double.NaN; + } else { + return negateResult ? -Math.PI/2 : Math.PI/2; + } + } + } + } + + /** + * For special values for which multiple conventions could be adopted, + * behaves like StrictMath.atan2(double,double). + * + * @param y Coordinate on y axis. + * @param x Coordinate on x axis. + * @return Angle from x axis positive side to (x,y) position, in radians, in [-PI,PI]. + * Angle measure is positive when going from x axis to y axis (positive sides). + */ + public static double atan2(double y, double x) { + if (USE_JDK_MATH) { + return StrictMath.atan2(y,x); + } + /* + * Using sub-methods, to make method lighter for general case, + * and to avoid JIT-optimization crash on NaN. + */ + if (x > 0.0) { + if (y == 0.0) { + // +-0.0 + return y; + } + if (x == Double.POSITIVE_INFINITY) { + return atan2_pinf_yyy(y); + } else { + return atan(y/x); + } + } else if (x < 0.0) { + if (y == 0.0) { + return signFromBit(y) * Math.PI; + } + if (x == Double.NEGATIVE_INFINITY) { + return atan2_ninf_yyy(y); + } else if (y > 0.0) { + return Math.PI/2 - atan(x/y); + } else if (y < 0.0) { + return -Math.PI/2 - atan(x/y); + } else { + return Double.NaN; + } + } else { + return atan2_yyy_zeroOrNaN(y, x); + } + } + + /** + * Gives same result as StrictMath.toRadians for some particular values + * like 90.0, 180.0 or 360.0, but is faster (no division). + * + * @param angdeg Angle value in degrees. + * @return Angle value in radians. + */ + public static double toRadians(double angdeg) { + if (USE_JDK_MATH) { + return StrictMath.toRadians(angdeg); + } + return angdeg * (Math.PI/180); + } + + /** + * Gives same result as StrictMath.toDegrees for some particular values + * like Math.PI/2, Math.PI or 2*Math.PI, but is faster (no division). + * + * @param angrad Angle value in radians. + * @return Angle value in degrees. + */ + public static double toDegrees(double angrad) { + if (USE_JDK_MATH) { + return StrictMath.toDegrees(angrad); + } + return angrad * (180/Math.PI); + } + + /** + * @param sign Sign of the angle: true for positive, false for negative. + * @param degrees Degrees, in [0,180]. + * @param minutes Minutes, in [0,59]. + * @param seconds Seconds, in [0.0,60.0[. + * @return Angle in radians. + */ + public static double toRadians(boolean sign, int degrees, int minutes, double seconds) { + return toRadians(toDegrees(sign, degrees, minutes, seconds)); + } + + /** + * @param sign Sign of the angle: true for positive, false for negative. + * @param degrees Degrees, in [0,180]. + * @param minutes Minutes, in [0,59]. + * @param seconds Seconds, in [0.0,60.0[. + * @return Angle in degrees. + */ + public static double toDegrees(boolean sign, int degrees, int minutes, double seconds) { + double signFactor = sign ? 1.0 : -1.0; + return signFactor * (degrees + (1.0/60)*(minutes + (1.0/60)*seconds)); + } + + /** + * @param angrad Angle in radians. + * @param degrees (out) Degrees, in [0,180]. + * @param minutes (out) Minutes, in [0,59]. + * @param seconds (out) Seconds, in [0.0,60.0[. + * @return true if the resulting angle in [-180deg,180deg] is positive, false if it is negative. + */ + public static boolean toDMS(double angrad, IntWrapper degrees, IntWrapper minutes, DoubleWrapper seconds) { + // Computing longitude DMS. + double tmp = toDegrees(normalizeMinusPiPi(angrad)); + boolean isNeg = (tmp < 0.0); + if (isNeg) { + tmp = -tmp; + } + degrees.value = (int)tmp; + tmp = (tmp-degrees.value)*60.0; + minutes.value = (int)tmp; + seconds.value = Math.min((tmp-minutes.value)*60.0,DOUBLE_BEFORE_60); + return !isNeg; + } + + /** + * NB: Since 2*Math.PI < 2*PI, a span of 2*Math.PI does not mean full angular range. + * ex.: isInClockwiseDomain(0.0, 2*Math.PI, -1e-20) returns false. + * ---> For full angular range, use a span > 2*Math.PI, like 2*PI_SUP constant of this class. + * + * @param startAngRad An angle, in radians. + * @param angSpanRad An angular span, >= 0.0, in radians. + * @param angRad An angle, in radians. + * @return true if angRad is in the clockwise angular domain going from startAngRad, over angSpanRad, + * extremities included, false otherwise. + */ + public static boolean isInClockwiseDomain(double startAngRad, double angSpanRad, double angRad) { + if (Math.abs(angRad) < -TWO_MATH_PI_IN_MINUS_PI_PI) { + // special case for angular values of small magnitude + if (angSpanRad <= 2*Math.PI) { + if (angSpanRad < 0.0) { + // empty domain + return false; + } + // angSpanRad is in [0,2*PI] + startAngRad = normalizeMinusPiPi(startAngRad); + double endAngRad = normalizeMinusPiPi(startAngRad + angSpanRad); + if (startAngRad <= endAngRad) { + return (angRad >= startAngRad) && (angRad <= endAngRad); + } else { + return (angRad >= startAngRad) || (angRad <= endAngRad); + } + } else { // angSpanRad > 2*Math.PI, or is NaN + return (angSpanRad == angSpanRad); + } + } else { + // general case + return (normalizeZeroTwoPi(angRad - startAngRad) <= angSpanRad); + } + } + + /* + * hyperbolic trigonometry + */ + + /** + * Some properties of sinh(x) = (exp(x)-exp(-x))/2: + * 1) defined on ]-Infinity,+Infinity[ + * 2) result in ]-Infinity,+Infinity[ + * 3) sinh(x) = -sinh(-x) (implies sinh(0) = 0) + * 4) sinh(epsilon) ~= epsilon + * 5) lim(sinh(x),x->+Infinity) = +Infinity + * (y increasing exponentially faster than x) + * 6) reaches +Infinity (double overflow) for x >= 710.475860073944, + * i.e. a bit further than exp(x) + * + * @param value A double value. + * @return Value hyperbolic sine. + */ + public static double sinh(double value) { + if (USE_JDK_MATH) { + return StrictMath.sinh(value); + } + // sinh(x) = (exp(x)-exp(-x))/2 + double h; + if (value < 0.0) { + value = -value; + h = -0.5; + } else { + h = 0.5; + } + if (value < 22.0) { + if (value < TWO_POW_N28) { + return (h < 0.0) ? -value : value; + } else { + // sinh(x) + // = (exp(x)-exp(-x))/2 + // = (exp(x)-1/exp(x))/2 + // = (expm1(x) + 1 - 1/(expm1(x)+1))/2 + // = (expm1(x) + (expm1(x)+1)/(expm1(x)+1) - 1/(expm1(x)+1))/2 + // = (expm1(x) + expm1(x)/(expm1(x)+1))/2 + double t = expm1(value); + // Might be more accurate, if value < 1: return h*((t+t)-t*t/(t+1.0)). + return h * (t + t/(t+1.0)); + } + } else if (value < LOG_DOUBLE_MAX_VALUE) { + return h * exp(value); + } else { + double t = exp(value*0.5); + return (h*t)*t; + } + } + + /** + * Some properties of cosh(x) = (exp(x)+exp(-x))/2: + * 1) defined on ]-Infinity,+Infinity[ + * 2) result in [1,+Infinity[ + * 3) cosh(0) = 1 + * 4) cosh(x) = cosh(-x) + * 5) lim(cosh(x),x->+Infinity) = +Infinity + * (y increasing exponentially faster than x) + * 6) reaches +Infinity (double overflow) for x >= 710.475860073944, + * i.e. a bit further than exp(x) + * + * @param value A double value. + * @return Value hyperbolic cosine. + */ + public static double cosh(double value) { + if (USE_JDK_MATH) { + return StrictMath.cosh(value); + } + // cosh(x) = (exp(x)+exp(-x))/2 + if (value < 0.0) { + value = -value; + } + if (value < LOG_TWO_POW_27) { + if (value < TWO_POW_N27) { + // cosh(x) + // = (exp(x)+exp(-x))/2 + // = ((1+x+x^2/2!+...) + (1-x+x^2/2!-...))/2 + // = 1+x^2/2!+x^4/4!+... + // For value of x small in magnitude, the sum of the terms does not add to 1. + return 1; + } else { + // cosh(x) + // = (exp(x)+exp(-x))/2 + // = (exp(x)+1/exp(x))/2 + double t = exp(value); + return 0.5 * (t+1/t); + } + } else if (value < LOG_DOUBLE_MAX_VALUE) { + return 0.5 * exp(value); + } else { + double t = exp(value*0.5); + return (0.5*t)*t; + } + } + + /** + * Much more accurate than cosh(value)-1, + * for arguments (and results) close to zero. + * + * coshm1(-0.0) = -0.0, for homogeneity with + * acosh1p(-0.0) = -0.0. + * + * @param value A double value. + * @return Value hyperbolic cosine, minus 1. + */ + public static double coshm1(double value) { + // cosh(x)-1 = (exp(x)+exp(-x))/2 - 1 + if (value < 0.0) { + value = -value; + } + if (value < LOG_TWO_POW_27) { + if (value < TWO_POW_N27) { + if (value == 0.0) { + // +-0.0 + return value; + } + // Using (expm1(x)+expm1(-x))/2 + // is not accurate for tiny values, + // for expm1 results are of higher + // magnitude than the result and + // of different signs, such as their + // sum is not accurate. + // cosh(x) - 1 + // = (exp(x)+exp(-x))/2 - 1 + // = ((1+x+x^2/2!+...) + (1-x+x^2/2!-...))/2 - 1 + // = x^2/2!+x^4/4!+... + // ~= x^2 * (1/2 + x^2 * 1/24) + // = x^2 * 0.5 (since x < 2^-27) + return 0.5 * value*value; + } else { + // cosh(x) - 1 + // = (exp(x)+exp(-x))/2 - 1 + // = (exp(x)-1+exp(-x)-1)/2 + // = (expm1(x)+expm1(-x))/2 + return 0.5 * (expm1(value)+expm1(-value)); + } + } else if (value < LOG_DOUBLE_MAX_VALUE) { + return 0.5 * exp(value) - 1.0; + } else { + // No need to subtract 1 from result. + double t = exp(value*0.5); + return (0.5*t)*t; + } + } + + /** + * Computes hyperbolic sine and hyperbolic cosine together. + * + * @param value A double value. + * @param hcosine (out) Value hyperbolic cosine. + * @return Value hyperbolic sine. + */ + public static double sinhAndCosh(double value, DoubleWrapper hcosine) { + if (USE_JDK_MATH) { + hcosine.value = StrictMath.cosh(value); + return StrictMath.sinh(value); + } + // Mixup of sinh and cosh treatments: if you modify them, + // you might want to also modify this. + double h; + if (value < 0.0) { + value = -value; + h = -0.5; + } else { + h = 0.5; + } + final double hsine; + // LOG_TWO_POW_27 = 18.714973875118524 + if (value < LOG_TWO_POW_27) { // test from cosh + // sinh + if (value < TWO_POW_N28) { + hsine = (h < 0.0) ? -value : value; + } else { + double t = expm1(value); + hsine = h * (t + t/(t+1.0)); + } + // cosh + if (value < TWO_POW_N27) { + hcosine.value = 1; + } else { + double t = exp(value); + hcosine.value = 0.5 * (t+1/t); + } + } else if (value < 22.0) { // test from sinh + // Here, value is in [18.714973875118524,22.0[. + double t = expm1(value); + hsine = h * (t + t/(t+1.0)); + hcosine.value = 0.5 * (t+1.0); + } else { + if (value < LOG_DOUBLE_MAX_VALUE) { + hsine = h * exp(value); + } else { + double t = exp(value*0.5); + hsine = (h*t)*t; + } + hcosine.value = Math.abs(hsine); + } + return hsine; + } + + /** + * Some properties of tanh(x) = sinh(x)/cosh(x) = (exp(2*x)-1)/(exp(2*x)+1): + * 1) defined on ]-Infinity,+Infinity[ + * 2) result in ]-1,1[ + * 3) tanh(x) = -tanh(-x) (implies tanh(0) = 0) + * 4) tanh(epsilon) ~= epsilon + * 5) lim(tanh(x),x->+Infinity) = 1 + * 6) reaches 1 (double loss of precision) for x = 19.061547465398498 + * + * @param value A double value. + * @return Value hyperbolic tangent. + */ + public static double tanh(double value) { + if (USE_JDK_MATH) { + return StrictMath.tanh(value); + } + // tanh(x) = sinh(x)/cosh(x) + // = (exp(x)-exp(-x))/(exp(x)+exp(-x)) + // = (exp(2*x)-1)/(exp(2*x)+1) + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + double z; + if (value < TANH_1_THRESHOLD) { + if (value < TWO_POW_N55) { + return negateResult ? -value*(1.0-value) : value*(1.0+value); + } else if (value >= 1) { + z = 1.0-2.0/(expm1(value+value)+2.0); + } else { + double t = expm1(-(value+value)); + z = -t/(t+2.0); + } + } else { + z = (value != value) ? Double.NaN : 1.0; + } + return negateResult ? -z : z; + } + + /** + * Some properties of asinh(x) = log(x + sqrt(x^2 + 1)) + * 1) defined on ]-Infinity,+Infinity[ + * 2) result in ]-Infinity,+Infinity[ + * 3) asinh(x) = -asinh(-x) (implies asinh(0) = 0) + * 4) asinh(epsilon) ~= epsilon + * 5) lim(asinh(x),x->+Infinity) = +Infinity + * (y increasing logarithmically slower than x) + * + * @param value A double value. + * @return Value hyperbolic arcsine. + */ + public static double asinh(double value) { + // asinh(x) = log(x + sqrt(x^2 + 1)) + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + double result; + // (about) smallest possible for + // non-log1p case to be accurate. + if (value < ASINH_LOG1P_THRESHOLD) { + // Around this range, FDLIBM uses + // log1p(value+value*value/(1+sqrt(value*value+1))), + // but it's slower, so we don't use it. + /* + * If x is close to zero, log argument is close to 1, + * so to avoid precision loss we use log1p(double), + * with + * (1+x)^p = 1 + p * x + (p*(p-1))/2! * x^2 + (p*(p-1)*(p-2))/3! * x^3 + ... + * (1+x)^p = 1 + p * x * (1 + (p-1)/2 * x * (1 + (p-2)/3 * x + ...) + * (1+x)^0.5 = 1 + 0.5 * x * (1 + (0.5-1)/2 * x * (1 + (0.5-2)/3 * x + ...) + * (1+x^2)^0.5 = 1 + 0.5 * x^2 * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...) + * x + (1+x^2)^0.5 = 1 + x * (1 + 0.5 * x * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...)) + * so + * asinh(x) = log1p(x * (1 + 0.5 * x * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...))) + */ + final double x = value; + final double x2 = x*x; + // Enough terms for good accuracy, + // given our threshold. + final double argLog1p = (x * + (1 + 0.5 * x + * (1 + (0.5-1)/2 * x2 + * (1 + (0.5-2)/3 * x2 + * (1 + (0.5-3)/4 * x2 + * (1 + (0.5-4)/5 * x2 + )))))); + result = log1p(argLog1p); + } else if (value < ASINH_ACOSH_SQRT_ELISION_THRESHOLD) { + // Around this range, FDLIBM uses + // log(2*value+1/(value+sqrt(value*value+1))), + // but it involves an additional division + // so we don't use it. + result = log(value + sqrt(value*value + 1.0)); + } else { + // log(2*value) would overflow for value > Double.MAX_VALUE/2, + // so we compute otherwise. + result = LOG_2 + log(value); + } + return negateResult ? -result : result; + } + + /** + * Some properties of acosh(x) = log(x + sqrt(x^2 - 1)): + * 1) defined on [1,+Infinity[ + * 2) result in ]0,+Infinity[ (by convention, since cosh(x) = cosh(-x)) + * 3) acosh(1) = 0 + * 4) acosh(1+epsilon) ~= log(1 + sqrt(2*epsilon)) ~= sqrt(2*epsilon) + * 5) lim(acosh(x),x->+Infinity) = +Infinity + * (y increasing logarithmically slower than x) + * + * @param value A double value. + * @return Value hyperbolic arccosine. + */ + public static double acosh(double value) { + if (!(value > 1.0)) { + // NaN, or value <= 1 + if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { + return (value < 1.0) ? Double.NaN : value - 1.0; + } else { + return (value == 1.0) ? 0.0 : Double.NaN; + } + } + double result; + if (value < ASINH_ACOSH_SQRT_ELISION_THRESHOLD) { + // Around this range, FDLIBM uses + // log(2*value-1/(value+sqrt(value*value-1))), + // but it involves an additional division + // so we don't use it. + result = log(value + sqrt(value*value - 1.0)); + } else { + // log(2*value) would overflow for value > Double.MAX_VALUE/2, + // so we compute otherwise. + result = LOG_2 + log(value); + } + return result; + } + + /** + * Much more accurate than acosh(1+value), + * for arguments (and results) close to zero. + * + * acosh1p(-0.0) = -0.0, for homogeneity with + * sqrt(-0.0) = -0.0, which looks about the same + * near 0. + * + * @param value A double value. + * @return Hyperbolic arccosine of (1+value). + */ + public static double acosh1p(double value) { + if (!(value > 0.0)) { + // NaN, or value <= 0. + // If value is -0.0, returning -0.0. + if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { + return (value < 0.0) ? Double.NaN : value; + } else { + return (value == 0.0) ? value : Double.NaN; + } + } + double result; + if (value < (ASINH_ACOSH_SQRT_ELISION_THRESHOLD-1)) { + // acosh(1+x) + // = log((1+x) + sqrt((1+x)^2 - 1)) + // = log(1 + x + sqrt(1 + 2*x + x^2 - 1)) + // = log1p(x + sqrt(2*x + x^2)) + // = log1p(x + sqrt(x * (2 + x)) + result = log1p(value + sqrt(value * (2 + value))); + } else { + result = LOG_2 + log(1+value); + } + return result; + } + + /** + * Some properties of atanh(x) = log((1+x)/(1-x))/2: + * 1) defined on ]-1,1[ + * 2) result in ]-Infinity,+Infinity[ + * 3) atanh(-1) = -Infinity (by continuity) + * 4) atanh(1) = +Infinity (by continuity) + * 5) atanh(epsilon) ~= epsilon + * 6) lim(atanh(x),x->1) = +Infinity + * + * @param value A double value. + * @return Value hyperbolic arctangent. + */ + public static double atanh(double value) { + boolean negateResult = false; + if (value < 0.0) { + value = -value; + negateResult = true; + } + double result; + if (!(value < 1.0)) { + // NaN, or value >= 1 + if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { + result = (value > 1.0) ? Double.NaN : Double.POSITIVE_INFINITY + value; + } else { + result = (value == 1.0) ? Double.POSITIVE_INFINITY : Double.NaN; + } + } else { + // For value < 0.5, FDLIBM uses + // 0.5 * log1p((value+value) + (value+value)*value/(1-value)), + // instead, but this is good enough for us. + // atanh(x) + // = log((1+x)/(1-x))/2 + // = log((1-x+2x)/(1-x))/2 + // = log1p(2x/(1-x))/2 + result = 0.5 * log1p((value+value)/(1.0-value)); + } + return negateResult ? -result : result; + } + + /* + * exponentials + */ + + /** + * @param value A double value. + * @return e^value. + */ + public static double exp(double value) { + if (USE_JDK_MATH) { + return StrictMath.exp(value); + } + // exp(x) = exp([x])*exp(y) + // with [x] the integer part of x, and y = x-[x] + // ===> + // We find an approximation of y, called z. + // ===> + // exp(x) = exp([x])*(exp(z)*exp(epsilon)) + // with epsilon = y - z + // ===> + // We have exp([x]) and exp(z) pre-computed in tables, we "just" have to compute exp(epsilon). + // + // We use the same indexing (cast to int) to compute x integer part and the + // table index corresponding to z, to avoid two int casts. + // Also, to optimize index multiplication and division, we use powers of two, + // so that we can do it with bits shifts. + + if (value > EXP_OVERFLOW_LIMIT) { + return Double.POSITIVE_INFINITY; + } else if (!(value >= EXP_UNDERFLOW_LIMIT)) { + return (value != value) ? Double.NaN : 0.0; + } + + final int indexes = (int)(value*EXP_LO_INDEXING); + + final int valueInt; + if (indexes >= 0) { + valueInt = (indexes>>EXP_LO_INDEXING_DIV_SHIFT); + } else { + valueInt = -((-indexes)>>EXP_LO_INDEXING_DIV_SHIFT); + } + final double hiTerm = MyTExp.expHiTab[valueInt-(int)EXP_UNDERFLOW_LIMIT]; + + final int zIndex = indexes - (valueInt< 0.0) { + if (value == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } + + // For normal values not close to 1.0, we use the following formula: + // log(value) + // = log(2^exponent*1.mantissa) + // = log(2^exponent) + log(1.mantissa) + // = exponent * log(2) + log(1.mantissa) + // = exponent * log(2) + log(1.mantissaApprox) + log(1.mantissa/1.mantissaApprox) + // = exponent * log(2) + log(1.mantissaApprox) + log(1+epsilon) + // = exponent * log(2) + log(1.mantissaApprox) + epsilon-epsilon^2/2+epsilon^3/3-epsilon^4/4+... + // with: + // 1.mantissaApprox <= 1.mantissa, + // log(1.mantissaApprox) in table, + // epsilon = (1.mantissa/1.mantissaApprox)-1 + // + // To avoid bad relative error for small results, + // values close to 1.0 are treated aside, with the formula: + // log(x) = z*(2+z^2*((2.0/3)+z^2*((2.0/5))+z^2*((2.0/7))+...))) + // with z=(x-1)/(x+1) + + double h; + if (value > 0.95) { + if (value < 1.14) { + double z = (value-1.0)/(value+1.0); + double z2 = z*z; + return z*(2+z2*((2.0/3)+z2*((2.0/5)+z2*((2.0/7)+z2*((2.0/9)+z2*((2.0/11))))))); + } + h = 0.0; + } else if (value < DOUBLE_MIN_NORMAL) { + // Ensuring value is normal. + value *= TWO_POW_52; + // log(x*2^52) + // = log(x)-ln(2^52) + // = log(x)-52*ln(2) + h = -52*LOG_2; + } else { + h = 0.0; + } + + int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); + int valueExp = (valueBitsHi>>20)-MAX_DOUBLE_EXPONENT; + // Getting the first LOG_BITS bits of the mantissa. + int xIndex = ((valueBitsHi<<12)>>>(32-LOG_BITS)); + + // 1.mantissa/1.mantissaApprox - 1 + double z = (value * twoPowNormalOrSubnormal(-valueExp)) * MyTLog.logXInvTab[xIndex] - 1; + + z *= (1-z*((1.0/2)-z*((1.0/3)))); + + return h + valueExp * LOG_2 + (MyTLog.logXLogTab[xIndex] + z); + + } else if (value == 0.0) { + return Double.NEGATIVE_INFINITY; + } else { // value < 0.0, or value is NaN + return Double.NaN; + } + } + + /** + * Quick log, with a max relative error of about 1.9e-3 + * for values in ]Double.MIN_NORMAL,+Infinity[, and + * worse accuracy outside this range. + * + * @param value A double value, in ]0,+Infinity[ (strictly positive and finite). + * @return Value logarithm (base e). + */ + public static double logQuick(double value) { + if (USE_JDK_MATH) { + return StrictMath.log(value); + } + /* + * Inverse of Schraudolph's method for exp, is very inaccurate near 1, + * and not that fast (even using floats), especially with added if's + * to deal with values near 1, so we don't use it, and use a simplified + * version of our log's redefined algorithm. + */ + + // Simplified version of log's redefined algorithm: + // log(value) ~= exponent * log(2) + log(1.mantissaApprox) + + double h; + if (value > 0.87) { + if (value < 1.16) { + return 2.0 * (value-1.0)/(value+1.0); + } + h = 0.0; + } else if (value < DOUBLE_MIN_NORMAL) { + value *= TWO_POW_52; + h = -52*LOG_2; + } else { + h = 0.0; + } + + int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); + int valueExp = (valueBitsHi>>20)-MAX_DOUBLE_EXPONENT; + int xIndex = ((valueBitsHi<<12)>>>(32-LOG_BITS)); + + return h + valueExp * LOG_2 + MyTLog.logXLogTab[xIndex]; + } + + /** + * @param value A double value. + * @return Value logarithm (base 10). + */ + public static double log10(double value) { + if (USE_JDK_MATH || (!USE_REDEFINED_LOG)) { + return StrictMath.log10(value); + } + // INV_LOG_10 is < 1, but there is no risk of log(double) + // overflow (positive or negative) while the end result shouldn't, + // since log(Double.MIN_VALUE) and log(Double.MAX_VALUE) have + // magnitudes of just a few hundreds. + return log(value) * INV_LOG_10; + } + + /** + * Much more accurate than log(1+value), + * for arguments (and results) close to zero. + * + * @param value A double value. + * @return Logarithm (base e) of (1+value). + */ + public static double log1p(double value) { + if (USE_JDK_MATH) { + return StrictMath.log1p(value); + } + if (false) { + // This also works. Simpler but a bit slower. + if (value == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } + double valuePlusOne = 1+value; + if (valuePlusOne == 1.0) { + return value; + } else { + return log(valuePlusOne)*(value/(valuePlusOne-1.0)); + } + } + if (value > -1.0) { + if (value == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } + + // ln'(x) = 1/x + // so + // log(x+epsilon) ~= log(x) + epsilon/x + // + // Let u be 1+value rounded: + // 1+value = u+epsilon + // + // log(1+value) + // = log(u+epsilon) + // ~= log(u) + epsilon/value + // We compute log(u) as done in log(double), and then add the corrective term. + + double valuePlusOne = 1.0+value; + if (valuePlusOne == 1.0) { + return value; + } else if (Math.abs(value) < 0.15) { + double z = value/(value+2.0); + double z2 = z*z; + return z*(2+z2*((2.0/3)+z2*((2.0/5)+z2*((2.0/7)+z2*((2.0/9)+z2*((2.0/11))))))); + } + + int valuePlusOneBitsHi = (int)(Double.doubleToRawLongBits(valuePlusOne)>>32) & 0x7FFFFFFF; + int valuePlusOneExp = (valuePlusOneBitsHi>>20)-MAX_DOUBLE_EXPONENT; + // Getting the first LOG_BITS bits of the mantissa. + int xIndex = ((valuePlusOneBitsHi<<12)>>>(32-LOG_BITS)); + + // 1.mantissa/1.mantissaApprox - 1 + double z = (valuePlusOne * twoPowNormalOrSubnormal(-valuePlusOneExp)) * MyTLog.logXInvTab[xIndex] - 1; + + z *= (1-z*((1.0/2)-z*(1.0/3))); + + // Adding epsilon/valuePlusOne to z, + // with + // epsilon = value - (valuePlusOne-1) + // (valuePlusOne + epsilon ~= 1+value (not rounded)) + + return valuePlusOneExp * LOG_2 + MyTLog.logXLogTab[xIndex] + (z + (value - (valuePlusOne-1))/valuePlusOne); + } else if (value == -1.0) { + return Double.NEGATIVE_INFINITY; + } else { // value < -1.0, or value is NaN + return Double.NaN; + } + } + + /* + * powers + */ + + /** + * 1e-13ish accuracy or better on whole double range. + * + * @param value A double value. + * @param power A power. + * @return value^power. + */ + public static double pow(double value, double power) { + if (USE_JDK_MATH) { + return StrictMath.pow(value,power); + } + if (power == 0.0) { + return 1.0; + } else if (power == 1.0) { + return value; + } + if (value <= 0.0) { + // powerInfo: 0 if not integer, 1 if even integer, -1 if odd integer + int powerInfo; + if (Math.abs(power) >= (TWO_POW_52*2)) { + // The binary digit just before comma is outside mantissa, + // thus it is always 0: power is an even integer. + powerInfo = 1; + } else { + // If power's magnitude permits, we cast into int instead of into long, + // as it is faster. + if (Math.abs(power) <= (double)Integer.MAX_VALUE) { + int powerAsInt = (int)power; + if (power == (double)powerAsInt) { + powerInfo = ((powerAsInt & 1) == 0) ? 1 : -1; + } else { // power is not an integer (and not NaN, due to test against Integer.MAX_VALUE) + powerInfo = 0; + } + } else { + long powerAsLong = (long)power; + if (power == (double)powerAsLong) { + powerInfo = ((powerAsLong & 1) == 0) ? 1 : -1; + } else { // power is not an integer, or is NaN + if (power != power) { + return Double.NaN; + } + powerInfo = 0; + } + } + } + + if (value == 0.0) { + if (power < 0.0) { + return (powerInfo < 0) ? 1/value : Double.POSITIVE_INFINITY; + } else { // power > 0.0 (0 and NaN cases already treated) + return (powerInfo < 0) ? value : 0.0; + } + } else { // value < 0.0 + if (value == Double.NEGATIVE_INFINITY) { + if (powerInfo < 0) { // power odd integer + return (power < 0.0) ? -0.0 : Double.NEGATIVE_INFINITY; + } else { // power even integer, or not an integer + return (power < 0.0) ? 0.0 : Double.POSITIVE_INFINITY; + } + } else { + return (powerInfo == 0) ? Double.NaN : powerInfo * exp(power*log(-value)); + } + } + } else { // value > 0.0, or value is NaN + return exp(power*log(value)); + } + } + + /** + * Quick pow, with a max relative error of about 1e-2 + * for value >= Double.MIN_NORMAL and 1e-10 < |value^power| < 1e10, + * of about 6e-2 for value >= Double.MIN_NORMAL and 1e-40 < |value^power| < 1e40, + * and worse accuracy otherwise. + * + * @param value A double value, in ]0,+Infinity[ (strictly positive and finite). + * @param power A double value. + * @return value^power. + */ + public static double powQuick(double value, double power) { + if (USE_JDK_MATH) { + return StrictMath.pow(value,power); + } + return exp(power*logQuick(value)); + } + + /** + * This treatment is somehow accurate for low values of |power|, + * and for |power*getExponent(value)| < 1023 or so (to stay away + * from double extreme magnitudes (large and small)). + * + * @param value A double value. + * @param power A power. + * @return value^power. + */ + public static double powFast(double value, int power) { + if (USE_JDK_MATH) { + return StrictMath.pow(value,power); + } + if (power < 3) { + if (power < 0) { + // Opposite of Integer.MIN_VALUE does not exist as int. + if (power == Integer.MIN_VALUE) { + // Integer.MAX_VALUE = -(power+1) + return 1.0/(powFast(value,Integer.MAX_VALUE) * value); + } else { + return 1.0/powFast(value,-power); + } + } else { + // Here, power is in [0,2]. + if (power == 2) { // Most common case first. + return value * value; + } else if (power == 0) { + return 1.0; + } else { // power == 1 + return value; + } + } + } else { // power >= 4 + double oddRemains = 1.0; + // If power <= 5, faster to finish outside the loop. + while (power > 5) { + // Test if power is odd. + if ((power & 1) != 0) { + oddRemains *= value; + } + value *= value; + power >>= 1; // power = power / 2 + } + // Here, power is in [3,5]. + if (power == 3) { + return oddRemains * value * value * value; + } else { // power in [4,5]. + double v2 = value * value; + if (power == 4) { + return oddRemains * v2 * v2; + } else { // power == 5 + return oddRemains * v2 * v2 * value; + } + } + } + } + + /** + * @param value A float value. + * @return value*value. + */ + public static float pow2(float value) { + return value*value; + } + + /** + * @param value A double value. + * @return value*value. + */ + public static double pow2(double value) { + return value*value; + } + + /** + * @param value A float value. + * @return value*value*value. + */ + public static float pow3(float value) { + return value*value*value; + } + + /** + * @param value A double value. + * @return value*value*value. + */ + public static double pow3(double value) { + return value*value*value; + } + + /* + * roots + */ + + /** + * @param value A double value. + * @return Value square root. + */ + public static double sqrt(double value) { + if (USE_JDK_MATH || (!USE_REDEFINED_SQRT)) { + return StrictMath.sqrt(value); + } + // See cbrt for comments, sqrt uses the same ideas. + + if (!(value > 0.0)) { // value <= 0.0, or value is NaN + if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { + return (value < 0.0) ? Double.NaN : value; + } else { + return (value == 0.0) ? value : Double.NaN; + } + } else if (value == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } + + double h; + if (value < DOUBLE_MIN_NORMAL) { + value *= TWO_POW_52; + h = 2*TWO_POW_N26; + } else { + h = 2.0; + } + + int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); + int valueExponentIndex = (valueBitsHi>>20)+(-MAX_DOUBLE_EXPONENT-MIN_DOUBLE_EXPONENT); + int xIndex = ((valueBitsHi<<12)>>>(32-SQRT_LO_BITS)); + + double result = MyTSqrt.sqrtXSqrtHiTab[valueExponentIndex] * MyTSqrt.sqrtXSqrtLoTab[xIndex]; + double slope = MyTSqrt.sqrtSlopeHiTab[valueExponentIndex] * MyTSqrt.sqrtSlopeLoTab[xIndex]; + value *= 0.25; + + result += (value - result * result) * slope; + result += (value - result * result) * slope; + return h*(result + (value - result * result) * slope); + } + + /** + * Quick sqrt, with with a max relative error of about 3.41e-2 + * for values in [Double.MIN_NORMAL,Double.MAX_VALUE], and worse + * accuracy outside this range. + * + * @param value A double value. + * @return Value square root. + */ + public static double sqrtQuick(double value) { + if (USE_JDK_MATH) { + return StrictMath.sqrt(value); + } + final long bits = Double.doubleToRawLongBits(value); + /* + * Constant determined empirically, using a random-based metaheuristic. + * Should be possible to find a better one. + */ + return Double.longBitsToDouble((bits+4606859074900000000L)>>>1); + } + + /** + * Quick inverse of square root, with a max relative error of about 3.44e-2 + * for values in [Double.MIN_NORMAL,Double.MAX_VALUE], and worse accuracy + * outside this range. + * + * This implementation uses zero step of Newton's method. + * Here are the max relative errors on [Double.MIN_NORMAL,Double.MAX_VALUE] + * depending on number of steps, if you want to copy-paste this code + * and use your own number: + * n=0: about 3.44e-2 + * n=1: about 1.75e-3 + * n=2: about 4.6e-6 + * n=3: about 3.17e-11 + * n=4: about 3.92e-16 + * n=5: about 3.03e-16 + * + * @param value A double value. + * @return Inverse of value square root. + */ + public static double invSqrtQuick(double value) { + if (USE_JDK_MATH) { + return 1/StrictMath.sqrt(value); + } + /* + * http://en.wikipedia.org/wiki/Fast_inverse_square_root + */ + if (false) { + // With one Newton step (much slower than + // 1/Math.sqrt(double) if not optimized). + final double halfInitial = value * 0.5; + long bits = Double.doubleToRawLongBits(value); + // If n=0, 6910474759270000000L might be better (3.38e-2 max relative error). + bits = 0x5FE6EB50C7B537A9L - (bits>>1); + value = Double.longBitsToDouble(bits); + value = value * (1.5 - halfInitial * value * value); // Newton step, can repeat. + return value; + } else { + return Double.longBitsToDouble(0x5FE6EB50C7B537A9L - (Double.doubleToRawLongBits(value)>>1)); + } + } + + /** + * @param value A double value. + * @return Value cubic root. + */ + public static double cbrt(double value) { + if (USE_JDK_MATH) { + return StrictMath.cbrt(value); + } + double h; + if (value < 0.0) { + if (value == Double.NEGATIVE_INFINITY) { + return Double.NEGATIVE_INFINITY; + } + value = -value; + // Making sure value is normal. + if (value < DOUBLE_MIN_NORMAL) { + value *= (TWO_POW_52*TWO_POW_26); + // h = * / + h = -2*TWO_POW_N26; + } else { + h = -2.0; + } + } else { + if (!(value < Double.POSITIVE_INFINITY)) { // value is +Infinity, or value is NaN + return value; + } + // Making sure value is normal. + if (value < DOUBLE_MIN_NORMAL) { + if (value == 0.0) { + // cbrt(0.0) = 0.0, cbrt(-0.0) = -0.0 + return value; + } + value *= (TWO_POW_52*TWO_POW_26); + h = 2*TWO_POW_N26; + } else { + h = 2.0; + } + } + + // Normal value is (2^ * ). + // First member cubic root is computed, and multiplied with an approximation + // of the cubic root of the second member, to end up with a good guess of + // the result before using Newton's (or Archimedes's) method. + // To compute the cubic root approximation, we use the formula "cbrt(value) = cbrt(x) * cbrt(value/x)", + // choosing x as close to value as possible but inferior to it, so that cbrt(value/x) is close to 1 + // (we could iterate on this method, using value/x as new value for each iteration, + // but finishing with Newton's method is faster). + + // Shift and cast into an int, which overall is faster than working with a long. + int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); + int valueExponentIndex = (valueBitsHi>>20)+(-MAX_DOUBLE_EXPONENT-MIN_DOUBLE_EXPONENT); + // Getting the first CBRT_LO_BITS bits of the mantissa. + int xIndex = ((valueBitsHi<<12)>>>(32-CBRT_LO_BITS)); + double result = MyTCbrt.cbrtXCbrtHiTab[valueExponentIndex] * MyTCbrt.cbrtXCbrtLoTab[xIndex]; + double slope = MyTCbrt.cbrtSlopeHiTab[valueExponentIndex] * MyTCbrt.cbrtSlopeLoTab[xIndex]; + + // Lowering values to avoid overflows when using Newton's method + // (we will then just have to return twice the result). + // result^3 = value + // (result/2)^3 = value/8 + value *= 0.125; + // No need to divide result here, as division is factorized in result computation tables. + // result *= 0.5; + + // Newton's method, looking for y = x^(1/p): + // y(n) = y(n-1) + (x-y(n-1)^p) * slope(y(n-1)) + // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(x(n-1)^(1/p-1)) + // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(x(n-1)^((1-p)/p)) + // with x(n-1)=y(n-1)^p, i.e.: + // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(y(n-1)^(1-p)) + // + // For p=3: + // y(n) = y(n-1) + (x-y(n-1)^3) * (1/(3*y(n-1)^2)) + + // To save time, we don't recompute the slope between Newton's method steps, + // as initial slope is good enough for a few iterations. + // + // NB: slope = 1/(3*trueResult*trueResult) + // As we have result = trueResult/2 (to avoid overflows), we have: + // slope = 4/(3*result*result) + // = (4/3)*resultInv*resultInv + // with newResultInv = 1/newResult + // = 1/(oldResult+resultDelta) + // = (oldResultInv)*1/(1+resultDelta/oldResult) + // = (oldResultInv)*1/(1+resultDelta*oldResultInv) + // ~= (oldResultInv)*(1-resultDelta*oldResultInv) + // ===> Successive slopes could be computed without division, if needed, + // by computing resultInv (instead of slope right away) and retrieving + // slopes from it. + + result += (value - result * result * result) * slope; + result += (value - result * result * result) * slope; + return h*(result + (value - result * result * result) * slope); + } + + /** + * @return sqrt(x^2+y^2) without intermediate overflow or underflow. + */ + public static double hypot(double x, double y) { + if (USE_JDK_MATH) { + return StrictMath.hypot(x,y); + } + x = Math.abs(x); + y = Math.abs(y); + // Ensuring x <= y. + if (y < x) { + double a = x; + x = y; + y = a; + } else if (!(y >= x)) { // Testing if we have some NaN. + return hypot_NaN(x, y); + } + + if (y-x == y) { + // x too small to subtract from y. + return y; + } else { + double factor; + if (y > HYPOT_MAX_MAG) { + // y is too large: scaling down. + x *= (1/HYPOT_FACTOR); + y *= (1/HYPOT_FACTOR); + factor = HYPOT_FACTOR; + } else if (x < (1/HYPOT_MAX_MAG)) { + // x is too small: scaling up. + x *= HYPOT_FACTOR; + y *= HYPOT_FACTOR; + factor = (1/HYPOT_FACTOR); + } else { + factor = 1.0; + } + return factor * sqrt(x*x+y*y); + } + } + + /** + * @return sqrt(x^2+y^2+z^2) without intermediate overflow or underflow. + */ + public static double hypot(double x, double y, double z) { + if (USE_JDK_MATH) { + // No simple JDK equivalent. + } + x = Math.abs(x); + y = Math.abs(y); + z = Math.abs(z); + /* + * Considering that z magnitude is the most likely to be the smaller, + * hence ensuring z <= y <= x, and not x <= y <= z, for less swaps. + */ + // Ensuring z <= y. + if (z > y) { + // y < z: swapping y and z + double a = z; + z = y; + y = a; + } else if (!(z <= y)) { // Testing if y or z is NaN. + return hypot_NaN(x, y, z); + } + // Ensuring y <= x. + if (z > x) { + // x < z <= y: moving x + double oldZ = z; + z = x; + double oldY = y; + y = oldZ; + x = oldY; + } else if (y > x) { + // z <= x < y: swapping x and y + double a = y; + y = x; + x = a; + } else if (x != x) { // Testing if x is NaN. + return hypot_NaN(x, y, z); + } + + if (x-y == x) { + // y, hence z, too small to subtract from x. + return x; + } else if (y-z == y) { + // z too small to subtract from y, hence x. + double factor; + if (x > HYPOT_MAX_MAG) { + // x is too large: scaling down. + x *= (1/HYPOT_FACTOR); + y *= (1/HYPOT_FACTOR); + factor = HYPOT_FACTOR; + } else if (y < (1/HYPOT_MAX_MAG)) { + // y is too small: scaling up. + x *= HYPOT_FACTOR; + y *= HYPOT_FACTOR; + factor = (1/HYPOT_FACTOR); + } else { + factor = 1.0; + } + return factor * sqrt(x*x+y*y); + } else { + double factor; + if (x > HYPOT_MAX_MAG) { + // x is too large: scaling down. + x *= (1/HYPOT_FACTOR); + y *= (1/HYPOT_FACTOR); + z *= (1/HYPOT_FACTOR); + factor = HYPOT_FACTOR; + } else if (z < (1/HYPOT_MAX_MAG)) { + // z is too small: scaling up. + x *= HYPOT_FACTOR; + y *= HYPOT_FACTOR; + z *= HYPOT_FACTOR; + factor = (1/HYPOT_FACTOR); + } else { + factor = 1.0; + } + // Adding smaller magnitudes together first. + return factor * sqrt(x*x+(y*y+z*z)); + } + } + + /* + * close values + */ + + /** + * @param value A float value. + * @return Floor of value. + */ + public static float floor(float value) { + final int exponent = getExponent(value); + if (exponent < 0) { + // abs(value) < 1. + if (value < 0.0f) { + return -1.0f; + } else { + // 0.0f, or -0.0f if value is -0.0f + return 0.0f * value; + } + } else if (exponent < 23) { + // A bit faster than using casts. + final int bits = Float.floatToRawIntBits(value); + final int anteCommaBits = bits & (0xFF800000>>exponent); + if ((value < 0.0f) && (anteCommaBits != bits)) { + return Float.intBitsToFloat(anteCommaBits) - 1.0f; + } else { + return Float.intBitsToFloat(anteCommaBits); + } + } else { + // +-Infinity, NaN, or a mathematical integer. + return value; + } + } + + /** + * @param value A double value. + * @return Floor of value. + */ + public static double floor(double value) { + if (USE_JDK_MATH) { + return StrictMath.floor(value); + } + if (ANTI_SLOW_CASTS) { + double valueAbs = Math.abs(value); + if (valueAbs <= (double)Integer.MAX_VALUE) { + if (value > 0.0) { + return (double)(int)value; + } else if (value < 0.0) { + double anteCommaDigits = (double)(int)value; + if (value != anteCommaDigits) { + return anteCommaDigits - 1.0; + } else { + return anteCommaDigits; + } + } else { // value is +-0.0 (not NaN due to test against Integer.MAX_VALUE) + return value; + } + } else if (valueAbs < TWO_POW_52) { + // We split the value in two: + // high part, which is a mathematical integer, + // and the rest, for which we can get rid of the + // post comma digits by casting into an int. + double highPart = ((int)(value * TWO_POW_N26)) * TWO_POW_26; + if (value > 0.0) { + return highPart + (double)((int)(value - highPart)); + } else { + double anteCommaDigits = highPart + (double)((int)(value - highPart)); + if (value != anteCommaDigits) { + return anteCommaDigits - 1.0; + } else { + return anteCommaDigits; + } + } + } else { // abs(value) >= 2^52, or value is NaN + return value; + } + } else { + final int exponent = getExponent(value); + if (exponent < 0) { + // abs(value) < 1. + if (value < 0.0) { + return -1.0; + } else { + // 0.0, or -0.0 if value is -0.0 + return 0.0 * value; + } + } else if (exponent < 52) { + // A bit faster than working on bits. + final long matIntPart = (long)value; + final double matIntToValue = value-(double)matIntPart; + if (matIntToValue >= 0.0) { + return (double)matIntPart; + } else { + return (double)(matIntPart - 1); + } + } else { + // +-Infinity, NaN, or a mathematical integer. + return value; + } + } + } + + /** + * @param value A float value. + * @return Ceiling of value. + */ + public static float ceil(float value) { + return -floor(-value); + } + + /** + * @param value A double value. + * @return Ceiling of value. + */ + public static double ceil(double value) { + if (USE_JDK_MATH) { + return StrictMath.ceil(value); + } + return -floor(-value); + } + + /** + * Might have different semantics than StrictMath.round(float), + * see bugs 6430675 and 8010430. + * + * @param value A double value. + * @return Value rounded to nearest int, choosing superior int in case two + * are equally close (i.e. rounding-up). + */ + public static int round(float value) { + /* + * Not delegating to JDK, because we want delegation to provide + * at least as good results, and some supported JDK versions + * have bugged round() methods. + */ + // Algorithm by Dmitry Nadezhin (but replaced an if by a multiply) + // (http://mail.openjdk.java.net/pipermail/core-libs-dev/2013-August/020247.html). + final int bits = Float.floatToRawIntBits(value); + final int biasedExp = ((bits>>23)&0xFF); + // Shift to get rid of bits past comma except first one: will need to + // 1-shift to the right to end up with correct magnitude. + final int shift = (23 - 1 + MAX_FLOAT_EXPONENT) - biasedExp; + if ((shift & -32) == 0) { + int bitsSignum = (((bits >> 31) << 1) + 1); + // shift in [0,31], so unbiased exp in [-9,22]. + int extendedMantissa = (0x00800000 | (bits & 0x007FFFFF)) * bitsSignum; + // If value is positive and first bit past comma is 0, rounding + // to lower integer, else to upper one, which is what "+1" and + // then ">>1" do. + return ((extendedMantissa >> shift) + 1) >> 1; + } else { + // +-Infinity, NaN, or a mathematical integer, or tiny. + if (false && ANTI_SLOW_CASTS) { // not worth it + if (Math.abs(value) >= -(float)Integer.MIN_VALUE) { + // +-Infinity or a mathematical integer (mostly) out of int range. + return (value < 0.0) ? Integer.MIN_VALUE : Integer.MAX_VALUE; + } + // NaN or a mathematical integer (mostly) in int range. + } + return (int)value; + } + } + + /** + * Might have different semantics than StrictMath.round(double), + * see bugs 6430675 and 8010430. + * + * @param value A double value. + * @return Value rounded to nearest long, choosing superior long in case two + * are equally close (i.e. rounding-up). + */ + public static long round(double value) { + /* + * Not delegating to JDK, because we want delegation to provide + * at least as good results, and some supported JDK versions + * have bugged round() methods. + */ + final long bits = Double.doubleToRawLongBits(value); + final int biasedExp = (((int)(bits>>52))&0x7FF); + // Shift to get rid of bits past comma except first one: will need to + // 1-shift to the right to end up with correct magnitude. + final int shift = (52 - 1 + MAX_DOUBLE_EXPONENT) - biasedExp; + if ((shift & -64) == 0) { + long bitsSignum = (((bits >> 63) << 1) + 1); + // shift in [0,63], so unbiased exp in [-12,51]. + long extendedMantissa = (0x0010000000000000L | (bits & 0x000FFFFFFFFFFFFFL)) * bitsSignum; + // If value is positive and first bit past comma is 0, rounding + // to lower integer, else to upper one, which is what "+1" and + // then ">>1" do. + return ((extendedMantissa >> shift) + 1L) >> 1; + } else { + // +-Infinity, NaN, or a mathematical integer, or tiny. + if (ANTI_SLOW_CASTS) { + if (Math.abs(value) >= -(double)Long.MIN_VALUE) { + // +-Infinity or a mathematical integer (mostly) out of long range. + return (value < 0.0) ? Long.MIN_VALUE : Long.MAX_VALUE; + } + // NaN or a mathematical integer (mostly) in long range. + } + return (long)value; + } + } + + /** + * @param value A float value. + * @return Value rounded to nearest int, choosing even int in case two + * are equally close. + */ + public static int roundEven(float value) { + final int sign = signFromBit(value); + value = Math.abs(value); + if (ANTI_SLOW_CASTS) { + if (value < TWO_POW_23_F) { + // Getting rid of post-comma bits. + value = ((value + TWO_POW_23_F) - TWO_POW_23_F); + return sign * (int)value; + } else if (value < (float)Integer.MAX_VALUE) { // "<=" doesn't work, because of float precision + // value is in [-Integer.MAX_VALUE,Integer.MAX_VALUE] + return sign * (int)value; + } + } else { + if (value < TWO_POW_23_F) { + // Getting rid of post-comma bits. + value = ((value + TWO_POW_23_F) - TWO_POW_23_F); + } + } + return (int)(sign * value); + } + + /** + * @param value A double value. + * @return Value rounded to nearest long, choosing even long in case two + * are equally close. + */ + public static long roundEven(double value) { + final int sign = (int)signFromBit(value); + value = Math.abs(value); + if (value < TWO_POW_52) { + // Getting rid of post-comma bits. + value = ((value + TWO_POW_52) - TWO_POW_52); + } + if (ANTI_SLOW_CASTS) { + if (value <= (double)Integer.MAX_VALUE) { + // value is in [-Integer.MAX_VALUE,Integer.MAX_VALUE] + return sign * (int)value; + } + } + return (long)(sign * value); + } + + /** + * @param value A float value. + * @return The float mathematical integer closest to the specified value, + * choosing even one if two are equally close, or respectively + * NaN, +-Infinity or +-0.0f if the value is any of these. + */ + public static float rint(float value) { + final int sign = signFromBit(value); + value = Math.abs(value); + if (value < TWO_POW_23_F) { + // Getting rid of post-comma bits. + value = ((TWO_POW_23_F + value ) - TWO_POW_23_F); + } + // Restoring original sign. + return sign * value; + } + + /** + * @param value A double value. + * @return The double mathematical integer closest to the specified value, + * choosing even one if two are equally close, or respectively + * NaN, +-Infinity or +-0.0 if the value is any of these. + */ + public static double rint(double value) { + if (USE_JDK_MATH) { + return StrictMath.rint(value); + } + final int sign = (int)signFromBit(value); + value = Math.abs(value); + if (value < TWO_POW_52) { + // Getting rid of post-comma bits. + value = ((TWO_POW_52 + value ) - TWO_POW_52); + } + // Restoring original sign. + return sign * value; + } + + /* + * close int values + * + * Never delegating to JDK for these methods, for we should always + * be faster and exact, and JDK doesn't exactly have such methods. + */ + + /** + * @param value A double value. + * @return Floor of value as int, or closest int if floor is out + * of int range, or 0 if value is NaN. + */ + public static int floorToInt(double value) { + int valueInt = (int) value; + if (value < 0.0) { + if (value == (double) valueInt) { + return valueInt; + } else { + if (valueInt == Integer.MIN_VALUE) { + return valueInt; + } else { + return valueInt - 1; + } + } + } else { // >= 0 or NaN. + return valueInt; + } + } + + /** + * @param value A double value. + * @return Ceiling of value as int, or closest int if ceiling is out + * of int range, or 0 if value is NaN. + */ + public static int ceilToInt(double value) { + int valueInt = (int) value; + if (value > 0.0) { + if (value == (double) valueInt) { + return valueInt; + } else { + if (valueInt == Integer.MAX_VALUE) { + return valueInt; + } else { + return valueInt + 1; + } + } + } else { // <= 0 or NaN. + return valueInt; + } + } + + /** + * @param value A double value. + * @return Value rounded to nearest int, choosing superior int in case two + * are equally close (i.e. rounding-up). + */ + public static int roundToInt(double value) { + /* + * We don't gain much by reimplementing rounding, except for + * pathologically large values, which should not be a common case + * when dealing with ints, so we just use round(double). + */ + return NumbersUtils.toInt(round(value)); + } + + /** + * @param value A double value. + * @return Value rounded to nearest int, choosing even int in case two + * are equally close. + */ + public static int roundEvenToInt(double value) { + final int sign = (int)signFromBit(value); + value = Math.abs(value); + /* + * Applying the post-comma bits removal logic even if value is out + * of int range, to avoid a test, for it doesn't mess up the result, + * and we want to optimize for the case of values in int range. + */ + value = ((value + TWO_POW_52) - TWO_POW_52); + return (int)(sign * value); + } + + /* + * ranges + */ + + /** + * @param min A float value. + * @param max A float value. + * @param value A float value. + * @return min if value < min, max if value > max, value otherwise. + */ + public static float toRange(float min, float max, float value) { + return NumbersUtils.toRange(min, max, value); + } + + /** + * @param min A double value. + * @param max A double value. + * @param value A double value. + * @return min if value < min, max if value > max, value otherwise. + */ + public static double toRange(double min, double max, double value) { + return NumbersUtils.toRange(min, max, value); + } + + /* + * binary operators (/,%) + */ + + /** + * Returns dividend - divisor * n, where n is the mathematical integer + * closest to dividend/divisor. + * If dividend/divisor is equally close to surrounding integers, + * we choose n to be the integer of smallest magnitude, which makes + * this treatment differ from StrictMath.IEEEremainder(double,double), + * where n is chosen to be the even integer. + * Note that the choice of n is not done considering the double + * approximation of dividend/divisor, because it could cause + * result to be outside [-|divisor|/2,|divisor|/2] range. + * The practical effect is that if multiple results would be possible, + * we always choose the result that is the closest to (and has the same + * sign as) the dividend. + * Ex. : + * - for (-3.0,2.0), this method returns -1.0, + * whereas StrictMath.IEEEremainder returns 1.0. + * - for (-5.0,2.0), both this method and StrictMath.IEEEremainder return -1.0. + * + * If the remainder is zero, its sign is the same as the sign of the first argument. + * If either argument is NaN, or the first argument is infinite, + * or the second argument is positive zero or negative zero, + * then the result is NaN. + * If the first argument is finite and the second argument is + * infinite, then the result is the same as the first argument. + * + * NB: + * - Modulo operator (%) returns a value in ]-|divisor|,|divisor|[, + * which sign is the same as dividend. + * - As for modulo operator, the sign of the divisor has no effect on the result. + * - On some architecture, % operator has been observed to return NaN + * for some subnormal values of divisor, when dividend exponent is 1023, + * which impacts the correctness of this method. + * + * @param dividend Dividend. + * @param divisor Divisor. + * @return Remainder of dividend/divisor, i.e. a value in [-|divisor|/2,|divisor|/2]. + */ + public static double remainder(double dividend, double divisor) { + if (Double.isInfinite(divisor)) { + if (Double.isInfinite(dividend)) { + return Double.NaN; + } else { + return dividend; + } + } + double value = dividend % divisor; + if (Math.abs(value+value) > Math.abs(divisor)) { + return value + ((value > 0.0) ? -Math.abs(divisor) : Math.abs(divisor)); + } else { + return value; + } + } + + /** + * @param angle Angle in radians. + * @return The same angle, in radians, but in [-PI,PI]. + */ + public static double normalizeMinusPiPi(double angle) { + // Not modifying values in output range. + if ((angle >= -Math.PI) && (angle <= Math.PI)) { + return angle; + } + return remainderTwoPi(angle); + } + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return The same angle, in radians, but in [-PI,PI]. + */ + public static double normalizeMinusPiPiFast(double angle) { + // Not modifying values in output range. + if ((angle >= -Math.PI) && (angle <= Math.PI)) { + return angle; + } + return remainderTwoPiFast(angle); + } + + /** + * @param angle Angle in radians. + * @return The same angle, in radians, but in [0,2*PI]. + */ + public static double normalizeZeroTwoPi(double angle) { + // Not modifying values in output range. + if ((angle >= 0.0) && (angle <= 2*Math.PI)) { + return angle; + } + angle = remainderTwoPi(angle); + if (angle < 0.0) { + // LO then HI is theoretically better (when starting near 0). + return (angle + TWOPI_LO) + TWOPI_HI; + } else { + return angle; + } + } + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return The same angle, in radians, but in [0,2*PI]. + */ + public static double normalizeZeroTwoPiFast(double angle) { + // Not modifying values in output range. + if ((angle >= 0.0) && (angle <= 2*Math.PI)) { + return angle; + } + angle = remainderTwoPiFast(angle); + if (angle < 0.0) { + // LO then HI is theoretically better (when starting near 0). + return (angle + TWOPI_LO) + TWOPI_HI; + } else { + return angle; + } + } + + /** + * @param angle Angle in radians. + * @return Angle value modulo PI, in radians, in [-PI/2,PI/2]. + */ + public static double normalizeMinusHalfPiHalfPi(double angle) { + // Not modifying values in output range. + if ((angle >= -Math.PI/2) && (angle <= Math.PI/2)) { + return angle; + } + return remainderPi(angle); + } + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return Angle value modulo PI, in radians, in [-PI/2,PI/2]. + */ + public static double normalizeMinusHalfPiHalfPiFast(double angle) { + // Not modifying values in output range. + if ((angle >= -Math.PI/2) && (angle <= Math.PI/2)) { + return angle; + } + return remainderPiFast(angle); + } + + /* + * floating points utils + */ + + /** + * @param value A float value. + * @return true if the specified value is NaN or +-Infinity, false otherwise. + */ + public static boolean isNaNOrInfinite(float value) { + return NumbersUtils.isNaNOrInfinite(value); + } + + /** + * @param value A double value. + * @return true if the specified value is NaN or +-Infinity, false otherwise. + */ + public static boolean isNaNOrInfinite(double value) { + return NumbersUtils.isNaNOrInfinite(value); + } + + /** + * @param value A float value. + * @return Value unbiased exponent. + */ + public static int getExponent(float value) { + return ((Float.floatToRawIntBits(value)>>23)&0xFF)-MAX_FLOAT_EXPONENT; + } + + /** + * @param value A double value. + * @return Value unbiased exponent. + */ + public static int getExponent(double value) { + return (((int)(Double.doubleToRawLongBits(value)>>52))&0x7FF)-MAX_DOUBLE_EXPONENT; + } + + /** + * @param value A float value. + * @return -1.0f if the specified value is < 0, 1.0f if it is > 0, + * and the value itself if it is NaN or +-0.0f. + */ + public static float signum(float value) { + if (USE_JDK_MATH) { + return StrictMath.signum(value); + } + if ((value == 0.0f) || (value != value)) { + return value; + } + return (float)signFromBit(value); + } + + /** + * @param value A double value. + * @return -1.0 if the specified value is < 0, 1.0 if it is > 0, + * and the value itself if it is NaN or +-0.0. + */ + public static double signum(double value) { + if (USE_JDK_MATH) { + return StrictMath.signum(value); + } + if ((value == 0.0) || (value != value)) { + return value; + } + if (ANTI_SLOW_CASTS) { + return (double)(int)signFromBit(value); + } else { + return (double)signFromBit(value); + } + } + + /** + * @param value A float value. + * @return -1 if sign bit is 1, 1 if sign bit is 0. + */ + public static int signFromBit(float value) { + return ((Float.floatToRawIntBits(value)>>30)|1); + } + + /** + * @param value A double value. + * @return -1 if sign bit is 1, 1 if sign bit is 0. + */ + public static long signFromBit(double value) { + // Returning a long, to avoid useless cast into int. + return ((Double.doubleToRawLongBits(value)>>62)|1); + } + + /** + * A sign of NaN is interpreted as positive. + * + * @param magnitude A float value. + * @param sign A float value. + * @return A value with the magnitude of the first argument, and the sign + * of the second argument. + */ + public static float copySign(float magnitude, float sign) { + return Float.intBitsToFloat( + (Float.floatToRawIntBits((sign != sign) ? 1.0f : sign) & Integer.MIN_VALUE) + | (Float.floatToRawIntBits(magnitude) & Integer.MAX_VALUE)); + } + + /** + * A sign of NaN is interpreted as positive. + * + * @param magnitude A double value. + * @param sign A double value. + * @return A value with the magnitude of the first argument, and the sign + * of the second argument. + */ + public static double copySign(double magnitude, double sign) { + return Double.longBitsToDouble( + (Double.doubleToRawLongBits((sign != sign) ? 1.0 : sign) & Long.MIN_VALUE) + | (Double.doubleToRawLongBits(magnitude) & Long.MAX_VALUE)); + } + + /** + * The ULP (Unit in the Last Place) is the distance to the next value larger + * in magnitude. + * + * @param value A float value. + * @return The size of an ulp of the specified value, or Float.MIN_VALUE + * if it is +-0.0f, or +Infinity if it is +-Infinity, or NaN + * if it is NaN. + */ + public static float ulp(float value) { + if (USE_JDK_MATH) { + return StrictMath.ulp(value); + } + /* + * Look-up table not really worth it in micro-benchmark, + * so should be worse with cache-misses. + */ + final int exponent = getExponent(value); + if (exponent >= (MIN_FLOAT_NORMAL_EXPONENT+23)) { + if (exponent == MAX_FLOAT_EXPONENT+1) { + // NaN or +-Infinity + return Math.abs(value); + } + // normal: returning 2^(exponent-23) + return Float.intBitsToFloat((exponent+(MAX_FLOAT_EXPONENT-23))<<23); + } else { + if (exponent == MIN_FLOAT_NORMAL_EXPONENT-1) { + // +-0.0f or subnormal + return Float.MIN_VALUE; + } + // subnormal result + return Float.intBitsToFloat(1<<(exponent-MIN_FLOAT_NORMAL_EXPONENT)); + } + } + + /** + * The ULP (Unit in the Last Place) is the distance to the next value larger + * in magnitude. + * + * @param value A double value. + * @return The size of an ulp of the specified value, or Double.MIN_VALUE + * if it is +-0.0, or +Infinity if it is +-Infinity, or NaN + * if it is NaN. + */ + public static double ulp(double value) { + if (USE_JDK_MATH) { + return StrictMath.ulp(value); + } + /* + * Look-up table not really worth it in micro-benchmark, + * so should be worse with cache-misses. + */ + final int exponent = getExponent(value); + if (exponent >= (MIN_DOUBLE_NORMAL_EXPONENT+52)) { + if (exponent == MAX_DOUBLE_EXPONENT+1) { + // NaN or +-Infinity + return Math.abs(value); + } + // normal: returning 2^(exponent-52) + return Double.longBitsToDouble((exponent+(MAX_DOUBLE_EXPONENT-52L))<<52); + } else { + if (exponent == MIN_DOUBLE_NORMAL_EXPONENT-1) { + // +-0.0f or subnormal + return Double.MIN_VALUE; + } + // subnormal result + return Double.longBitsToDouble(1L<<(exponent-MIN_DOUBLE_NORMAL_EXPONENT)); + } + } + + /** + * If both arguments are +-0.0(f), (float)direction is returned. + * + * If both arguments are +Infinity or -Infinity, + * respectively +Infinity or -Infinity is returned. + * + * @param start A float value. + * @param direction A double value. + * @return The float adjacent to start towards direction, considering that + * +(-)Float.MIN_VALUE is adjacent to +(-)0.0f, and that + * +(-)Float.MAX_VALUE is adjacent to +(-)Infinity, + * or NaN if any argument is NaN. + */ + public static float nextAfter(float start, double direction) { + if (direction < start) { + // Going towards -Infinity. + if (start == 0.0f) { + // +-0.0f + return -Float.MIN_VALUE; + } + final int bits = Float.floatToRawIntBits(start); + return Float.intBitsToFloat(bits + ((bits > 0) ? -1 : 1)); + } else if (direction > start) { + // Going towards +Infinity. + // +0.0f to get rid of eventual -0.0f + final int bits = Float.floatToRawIntBits(start + 0.0f); + return Float.intBitsToFloat(bits + (bits >= 0 ? 1 : -1)); + } else if (start == direction) { + return (float)direction; + } else { + // Returning a NaN derived from the input NaN(s). + return start + (float)direction; + } + } + + /** + * If both arguments are +-0.0, direction is returned. + * + * If both arguments are +Infinity or -Infinity, + * respectively +Infinity or -Infinity is returned. + * + * @param start A double value. + * @param direction A double value. + * @return The double adjacent to start towards direction, considering that + * +(-)Double.MIN_VALUE is adjacent to +(-)0.0, and that + * +(-)Double.MAX_VALUE is adjacent to +(-)Infinity, + * or NaN if any argument is NaN. + */ + public static double nextAfter(double start, double direction) { + if (direction < start) { + // Going towards -Infinity. + if (start == 0.0) { + // +-0.0 + return -Double.MIN_VALUE; + } + final long bits = Double.doubleToRawLongBits(start); + return Double.longBitsToDouble(bits + ((bits > 0) ? -1 : 1)); + } else if (direction > start) { + // Going towards +Infinity. + // +0.0 to get rid of eventual -0.0 + final long bits = Double.doubleToRawLongBits(start + 0.0f); + return Double.longBitsToDouble(bits + (bits >= 0 ? 1 : -1)); + } else if (start == direction) { + return direction; + } else { + // Returning a NaN derived from the input NaN(s). + return start + direction; + } + } + + /** + * Semantically equivalent to nextAfter(start,Double.NEGATIVE_INFINITY). + */ + public static float nextDown(float start) { + if (start > Float.NEGATIVE_INFINITY) { + if (start == 0.0f) { + // +-0.0f + return -Float.MIN_VALUE; + } + final int bits = Float.floatToRawIntBits(start); + return Float.intBitsToFloat(bits + ((bits > 0) ? -1 : 1)); + } else if (start == Float.NEGATIVE_INFINITY) { + return Float.NEGATIVE_INFINITY; + } else { + // NaN + return start; + } + } + + /** + * Semantically equivalent to nextAfter(start,Double.NEGATIVE_INFINITY). + */ + public static double nextDown(double start) { + if (start > Double.NEGATIVE_INFINITY) { + if (start == 0.0) { + // +-0.0 + return -Double.MIN_VALUE; + } + final long bits = Double.doubleToRawLongBits(start); + return Double.longBitsToDouble(bits + ((bits > 0) ? -1 : 1)); + } else if (start == Double.NEGATIVE_INFINITY) { + return Double.NEGATIVE_INFINITY; + } else { + // NaN + return start; + } + } + + /** + * Semantically equivalent to nextAfter(start,Double.POSITIVE_INFINITY). + */ + public static float nextUp(float start) { + if (start < Float.POSITIVE_INFINITY) { + // +0.0f to get rid of eventual -0.0f + final int bits = Float.floatToRawIntBits(start + 0.0f); + return Float.intBitsToFloat(bits + (bits >= 0 ? 1 : -1)); + } else if (start == Float.POSITIVE_INFINITY) { + return Float.POSITIVE_INFINITY; + } else { + // NaN + return start; + } + } + + /** + * Semantically equivalent to nextAfter(start,Double.POSITIVE_INFINITY). + */ + public static double nextUp(double start) { + if (start < Double.POSITIVE_INFINITY) { + // +0.0 to get rid of eventual -0.0 + final long bits = Double.doubleToRawLongBits(start + 0.0); + return Double.longBitsToDouble(bits + (bits >= 0 ? 1 : -1)); + } else if (start == Double.POSITIVE_INFINITY) { + return Double.POSITIVE_INFINITY; + } else { + // NaN + return start; + } + } + + /** + * Precision may be lost if the result is subnormal. + * + * @param value A float value. + * @param scaleFactor An int value. + * @return value * 2^scaleFactor, or a value equivalent to the specified + * one if it is NaN, +-Infinity or +-0.0f. + */ + public static float scalb(float value, int scaleFactor) { + // Large enough to imply overflow or underflow for + // a finite non-zero value. + final int MAX_SCALE = 2*MAX_FLOAT_EXPONENT+23+1; + + // Making sure scaling factor is in a reasonable range. + scaleFactor = Math.max(Math.min(scaleFactor, MAX_SCALE), -MAX_SCALE); + + return (float)(((double)value) * twoPowNormal(scaleFactor)); + } + + /** + * Precision may be lost if the result is subnormal. + * + * @param value A double value. + * @param scaleFactor An int value. + * @return value * 2^scaleFactor, or a value equivalent to the specified + * one if it is NaN, +-Infinity or +-0.0. + */ + public static double scalb(double value, int scaleFactor) { + if ((scaleFactor > -MAX_DOUBLE_EXPONENT) && (scaleFactor <= MAX_DOUBLE_EXPONENT)) { + // Quick case (as done in apache FastMath). + return value * twoPowNormal(scaleFactor); + } + + // Large enough to imply overflow or underflow for + // a finite non-zero value. + final int MAX_SCALE = 2*MAX_DOUBLE_EXPONENT+52+1; + + // Making sure scaling factor is in a reasonable range. + final int exponentAdjust; + final int scaleIncrement; + final double exponentDelta; + if (scaleFactor < 0) { + scaleFactor = Math.max(scaleFactor, -MAX_SCALE); + scaleIncrement = -512; + exponentDelta = TWO_POW_N512; + } else { + scaleFactor = Math.min(scaleFactor, MAX_SCALE); + scaleIncrement = 512; + exponentDelta = TWO_POW_512; + } + + // Calculating (scaleFactor % +-512), 512 = 2^9, using + // technique from "Hacker's Delight" section 10-2. + final int t = ((scaleFactor >> (9-1)) >>> (32-9)); + exponentAdjust = ((scaleFactor + t) & (512-1)) - t; + + value *= twoPowNormal(exponentAdjust); + scaleFactor -= exponentAdjust; + + while (scaleFactor != 0) { + value *= exponentDelta; + scaleFactor -= scaleIncrement; + } + + return value; + } + + /* + * Non-redefined StrictMath public values and treatments. + */ + + public static float abs(float a) { + return StrictMath.abs(a); + } + + public static double abs(double a) { + return StrictMath.abs(a); + } + + public static float min(float a, float b) { + return StrictMath.min(a,b); + } + + public static double min(double a, double b) { + return StrictMath.min(a,b); + } + + public static float max(float a, float b) { + return StrictMath.max(a,b); + } + + public static double max(double a, double b) { + return StrictMath.max(a,b); + } + + public static double IEEEremainder(double f1, double f2) { + return StrictMath.IEEEremainder(f1,f2); + } + + public static double random() { + return StrictMath.random(); + } + + //-------------------------------------------------------------------------- + // PRIVATE METHODS + //-------------------------------------------------------------------------- + + /** + * Non-instantiable. + */ + private StrictFastMath() { + } + + /* + * Remainders (accurate). + */ + + /** + * @param angle Angle in radians. + * @return Remainder of (angle % (2*PI)), in [-PI,PI]. + */ + private static double remainderTwoPi(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderTwoPi(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle <= (4*NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2)) { + double fn = (double)(int)(angle*TWOPI_INV+0.5); + angle = (angle - fn*TWOPI_HI) - fn*TWOPI_LO; + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI) { + angle = (angle + TWOPI_HI) + TWOPI_LO; + } else if (angle > Math.PI) { + angle = (angle - TWOPI_HI) - TWOPI_LO; + } + return negateResult ? -angle : angle; + } else if (angle < Double.POSITIVE_INFINITY) { + angle = heavyRemainderTwoPi(angle); + return negateResult ? -angle : angle; + } else { // angle is +Infinity or NaN + return Double.NaN; + } + } + + /** + * @param angle Angle in radians. + * @return Remainder of (angle % PI), in [-PI/2,PI/2]. + */ + private static double remainderPi(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderPi(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle <= (2*NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2)) { + double fn = (double)(int)(angle*PI_INV+0.5); + angle = (angle - fn*PI_HI) - fn*PI_LO; + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI/2) { + angle = (angle + PI_HI) + PI_LO; + } else if (angle > Math.PI/2) { + angle = (angle - PI_HI) - PI_LO; + } + return negateResult ? -angle : angle; + } else if (angle < Double.POSITIVE_INFINITY) { + angle = heavyRemainderPi(angle); + return negateResult ? -angle : angle; + } else { // angle is +Infinity or NaN + return Double.NaN; + } + } + + /** + * @param angle Angle in radians. + * @return Bits of double corresponding to remainder of (angle % (PI/2)), + * in [-PI/4,PI/4], with quadrant encoded in exponent bits. + */ + private static long remainderPiO2(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderPiO2(angle, false); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + if (angle <= NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2) { + int n = (int)(angle*PIO2_INV+0.5); + double fn = (double)n; + angle = (angle - fn*PIO2_HI) - fn*PIO2_LO; + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI/4) { + angle = (angle + PIO2_HI) + PIO2_LO; + n--; + } else if (angle > Math.PI/4) { + angle = (angle - PIO2_HI) - PIO2_LO; + n++; + } + if (negateResult) { + angle = -angle; + } + return encodeRemainderAndQuadrant(angle, n&3); + } else if (angle < Double.POSITIVE_INFINITY) { + return heavyRemainderPiO2(angle, negateResult); + } else { // angle is +Infinity or NaN + return encodeRemainderAndQuadrant(Double.NaN, 0); + } + } + + /* + * Remainders (fast). + */ + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return Remainder of (angle % (2*PI)), in [-PI,PI]. + */ + private static double remainderTwoPiFast(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderTwoPi(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + // - We don't bother with values higher than (2*PI*(2^52)), + // since they are spaced by 2*PI or more from each other. + // - For large values, we don't use % because it might be very slow, + // and we split computation in two, because cast from double to int + // with large numbers might be very slow also. + if (angle <= TWO_POW_26*(2*Math.PI)) { + // ok + } else if (angle <= TWO_POW_52*(2*Math.PI)) { + // Computing remainder of angle modulo TWO_POW_26*(2*PI). + double fn = (double)(int)(angle*(TWOPI_INV/TWO_POW_26)+0.5); + angle = (angle - fn*(TWOPI_HI*TWO_POW_26)) - fn*(TWOPI_LO*TWO_POW_26); + // Here, angle is in [-TWO_POW_26*PI,TWO_POW_26*PI], or so. + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } else if (angle < Double.POSITIVE_INFINITY) { + return 0.0; + } else { // angle is +Infinity or NaN + return Double.NaN; + } + + // Computing remainder of angle modulo 2*PI. + double fn = (double)(int)(angle*TWOPI_INV+0.5); + angle = (angle - fn*TWOPI_HI) - fn*TWOPI_LO; + + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI) { + angle = (angle + TWOPI_HI) + TWOPI_LO; + } else if (angle > Math.PI) { + angle = (angle - TWOPI_HI) - TWOPI_LO; + } + return negateResult ? -angle : angle; + } + + /** + * Not accurate for large values. + * + * @param angle Angle in radians. + * @return Remainder of (angle % PI), in [-PI/2,PI/2]. + */ + private static double remainderPiFast(double angle) { + if (USE_JDK_MATH) { + return jdkRemainderPi(angle); + } + boolean negateResult = false; + if (angle < 0.0) { + angle = -angle; + negateResult = true; + } + // - We don't bother with values higher than (PI*(2^52)), + // since they are spaced by PI or more from each other. + // - For large values, we don't use % because it might be very slow, + // and we split computation in two, because cast from double to int + // with large numbers might be very slow also. + if (angle <= TWO_POW_26*Math.PI) { + // ok + } else if (angle <= TWO_POW_52*Math.PI) { + // Computing remainder of angle modulo TWO_POW_26*PI. + double fn = (double)(int)(angle*(PI_INV/TWO_POW_26)+0.5); + angle = (angle - fn*(PI_HI*TWO_POW_26)) - fn*(PI_LO*TWO_POW_26); + // Here, angle is in [-TWO_POW_26*PI/2,TWO_POW_26*PI/2], or so. + if (angle < 0.0) { + angle = -angle; + negateResult = !negateResult; + } + } else if (angle < Double.POSITIVE_INFINITY) { + return 0.0; + } else { // angle is +Infinity or NaN + return Double.NaN; + } + + // Computing remainder of angle modulo PI. + double fn = (double)(int)(angle*PI_INV+0.5); + angle = (angle - fn*PI_HI) - fn*PI_LO; + + // Ensuring range. + // HI/LO can help a bit, even though we are always far from 0. + if (angle < -Math.PI/2) { + angle = (angle + PI_HI) + PI_LO; + } else if (angle > Math.PI/2) { + angle = (angle - PI_HI) - PI_LO; + } + return negateResult ? -angle : angle; + } +} diff --git a/settings.gradle.kts b/settings.gradle.kts index 661afa67c..15a6a176c 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -43,6 +43,7 @@ include( ":kmath-tensors", ":kmath-jupyter", ":kmath-symja", + ":kmath-jafama", ":examples", ":benchmarks" ) From 6c815abd54a248cd1f95e02d580382e4b55377ba Mon Sep 17 00:00:00 2001 From: therealansh Date: Thu, 3 Jun 2021 01:37:23 +0530 Subject: [PATCH 072/132] chore: refactored and dependency add --- kmath-jafama/build.gradle.kts | 9 +- .../kscience/kmath/jafama/CmnFastMath.java | 2112 ------------ .../kscience/kmath/jafama/DoubleWrapper.java | 13 - .../space/kscience/kmath/jafama/FastMath.java | 2986 ---------------- .../kscience/kmath/jafama/IntWrapper.java | 13 - .../kscience/kmath/jafama/KMathJafama.kt | 3 +- .../kscience/kmath/jafama/NumbersUtils.java | 2647 --------------- .../kscience/kmath/jafama/StrictFastMath.java | 2998 ----------------- 8 files changed, 6 insertions(+), 10775 deletions(-) delete mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/CmnFastMath.java delete mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/DoubleWrapper.java delete mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/FastMath.java delete mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/IntWrapper.java delete mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/NumbersUtils.java delete mode 100644 kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/StrictFastMath.java diff --git a/kmath-jafama/build.gradle.kts b/kmath-jafama/build.gradle.kts index 22d50f89c..f31f2602f 100644 --- a/kmath-jafama/build.gradle.kts +++ b/kmath-jafama/build.gradle.kts @@ -3,13 +3,12 @@ plugins { } dependencies { - api(project(":kmath-ast")) - api(project(":kmath-complex")) - api(project(":kmath-for-real")) + api(project(":kmath-core")) + api("net.jafama:jafama:2.3.2") } -kscience{ - useHtml() +repositories { + mavenCentral() } readme { diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/CmnFastMath.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/CmnFastMath.java deleted file mode 100644 index 0abc5d95d..000000000 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/CmnFastMath.java +++ /dev/null @@ -1,2112 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.jafama; - -/** - * Stuffs for FastMath and StrictFastMath. - */ -abstract class CmnFastMath { - - /* - * For trigonometric functions, use of look-up tables and Taylor-Lagrange formula - * with 4 derivatives (more take longer to compute and don't add much accuracy, - * less require larger tables (which use more memory, take more time to initialize, - * and are slower to access (at least on the machine they were developed on))). - * - * For angles reduction of cos/sin/tan functions: - * - for small values, instead of reducing angles, and then computing the best index - * for look-up tables, we compute this index right away, and use it for reduction, - * - for large values, treatments derived from fdlibm package are used, as done in - * java.lang.Math. They are faster but still "slow", so if you work with - * large numbers and need speed over accuracy for them, you might want to use - * normalizeXXXFast treatments before your function, or modify cos/sin/tan - * so that they call the fast normalization treatments instead of the accurate ones. - * NB: If an angle is huge (like PI*1e20), in double precision format its last digits - * are zeros, which most likely is not the case for the intended value, and doing - * an accurate reduction on a very inaccurate value is most likely pointless. - * But it gives some sort of coherence that could be needed in some cases. - * - * Multiplication on double appears to be about as fast (or not much slower) than call - * to [], and regrouping some doubles in a private class, to use - * index only once, does not seem to speed things up, so: - * - for uniformly tabulated values, to retrieve the parameter corresponding to - * an index, we recompute it rather than using an array to store it, - * - for cos/sin, we recompute derivatives divided by (multiplied by inverse of) - * factorial each time, rather than storing them in arrays. - * - * Lengths of look-up tables are usually of the form 2^n+1, for their values to be - * of the form ( * k/2^n, k in 0 .. 2^n), so that particular values - * (PI/2, etc.) are "exactly" computed, as well as for other reasons. - * - * Tables are put in specific inner classes, to be lazily initialized. - * Always doing strict tables initialization, even if StrictFastMath delegates - * to StrictMath and doesn't use tables, which makes tables initialization a bit - * slower but code simpler. - * Using redefined pure Java treatments during tables initialization, - * instead of Math or StrictMath ones (even asin(double)), can be very slow, - * because class loading is likely not to be optimized. - * - * Most math treatments I could find on the web, including "fast" ones, - * usually take care of special cases (NaN, etc.) at the beginning, and - * then deal with the general case, which adds a useless overhead for the - * general (and common) case. In this class, special cases are only dealt - * with when needed, and if the general case does not already handle them. - */ - - /* - * Regarding strictfp-ness: - * - * Switching from/to strictfp has some overhead, so we try to only - * strictfp-ize when needed (or when clueless). - * Compile-time constants are computed in a FP-strict way, so no need - * to make this whole class strictfp. - */ - - //-------------------------------------------------------------------------- - // CONFIGURATION - //-------------------------------------------------------------------------- - - /* - * FastMath - */ - - static final boolean FM_USE_JDK_MATH = getBooleanProperty("jafama.usejdk", false); - - /** - * Used for both FastMath.log(double) and FastMath.log10(double). - */ - static final boolean FM_USE_REDEFINED_LOG = getBooleanProperty("jafama.fastlog", false); - - static final boolean FM_USE_REDEFINED_SQRT = getBooleanProperty("jafama.fastsqrt", false); - - /** - * Set it to true if FastMath.sqrt(double) is slow - * (more tables, but less calls to FastMath.sqrt(double)). - */ - static final boolean FM_USE_POWTABS_FOR_ASIN = false; - - /* - * StrictFastMath - */ - - static final boolean SFM_USE_JDK_MATH = getBooleanProperty("jafama.strict.usejdk", false); - - /** - * Used for both StrictFastMath.log(double) and StrictFastMath.log10(double). - * True by default because the StrictMath implementations can be slow. - */ - static final boolean SFM_USE_REDEFINED_LOG = getBooleanProperty("jafama.strict.fastlog", true); - - static final boolean SFM_USE_REDEFINED_SQRT = getBooleanProperty("jafama.strict.fastsqrt", false); - - /** - * Set it to true if StrictFastMath.sqrt(double) is slow - * (more tables, but less calls to StrictFastMath.sqrt(double)). - */ - static final boolean SFM_USE_POWTABS_FOR_ASIN = false; - - /* - * Common to FastMath and StrictFastMath. - */ - - /** - * Using two pow tab can just make things barely faster, - * and could relatively hurt in case of cache-misses, - * especially for methods that otherwise wouldn't rely - * on any tab, so we don't use it. - */ - static final boolean USE_TWO_POW_TAB = false; - - /** - * Because on some architectures, some casts can be slow, - * especially for large values. - * Might make things a bit slower for latest architectures, - * but not as much as it makes them faster for older ones. - */ - static final boolean ANTI_SLOW_CASTS = true; - - /** - * If some methods get JIT-optimized, they might crash - * if they contain "(var == xxx)" with var being NaN - * (can happen with Java 6u29). - * - * The crash does not happen if we replace "==" with "<" or ">". - * - * Only the code that has been observed to trigger the bug - * has been modified. - */ - static final boolean ANTI_JIT_OPTIM_CRASH_ON_NAN = true; - - //-------------------------------------------------------------------------- - // GENERAL CONSTANTS - //-------------------------------------------------------------------------- - - /** - * Closest double approximation of e. - */ - public static final double E = Math.E; - - /** - * Closest double approximation of pi, which is inferior to mathematical pi: - * pi ~= 3.14159265358979323846... - * PI ~= 3.141592653589793 - */ - public static final double PI = Math.PI; - - /** - * High double approximation of pi, which is further from pi - * than the low approximation PI: - * pi ~= 3.14159265358979323846... - * PI ~= 3.141592653589793 - * PI_SUP ~= 3.1415926535897936 - */ - public static final double PI_SUP = Double.longBitsToDouble(Double.doubleToRawLongBits(Math.PI)+1); - - static final double ONE_DIV_F2 = 1/2.0; - static final double ONE_DIV_F3 = 1/6.0; - static final double ONE_DIV_F4 = 1/24.0; - - static final float TWO_POW_23_F = (float)NumbersUtils.twoPow(23); - - static final double TWO_POW_24 = NumbersUtils.twoPow(24); - private static final double TWO_POW_N24 = NumbersUtils.twoPow(-24); - - static final double TWO_POW_26 = NumbersUtils.twoPow(26); - static final double TWO_POW_N26 = NumbersUtils.twoPow(-26); - - // First double value (from zero) such as (value+-1/value == value). - static final double TWO_POW_27 = NumbersUtils.twoPow(27); - static final double TWO_POW_N27 = NumbersUtils.twoPow(-27); - - static final double TWO_POW_N28 = NumbersUtils.twoPow(-28); - - static final double TWO_POW_52 = NumbersUtils.twoPow(52); - - static final double TWO_POW_N55 = NumbersUtils.twoPow(-55); - - static final double TWO_POW_66 = NumbersUtils.twoPow(66); - - static final double TWO_POW_512 = NumbersUtils.twoPow(512); - static final double TWO_POW_N512 = NumbersUtils.twoPow(-512); - - /** - * Double.MIN_NORMAL since Java 6. - */ - static final double DOUBLE_MIN_NORMAL = Double.longBitsToDouble(0x0010000000000000L); // 2.2250738585072014E-308 - - // Not storing float/double mantissa size in constants, - // for 23 and 52 are shorter to read and more - // bitwise-explicit than some constant's name. - - static final int MIN_DOUBLE_EXPONENT = -1074; - static final int MIN_DOUBLE_NORMAL_EXPONENT = -1022; - static final int MAX_DOUBLE_EXPONENT = 1023; - - static final int MIN_FLOAT_NORMAL_EXPONENT = -126; - static final int MAX_FLOAT_EXPONENT = 127; - - private static final double SQRT_2 = StrictMath.sqrt(2.0); - - static final double LOG_2 = StrictMath.log(2.0); - static final double LOG_TWO_POW_27 = StrictMath.log(TWO_POW_27); - static final double LOG_DOUBLE_MAX_VALUE = StrictMath.log(Double.MAX_VALUE); - - static final double INV_LOG_10 = 1.0/StrictMath.log(10.0); - - static final double DOUBLE_BEFORE_60 = Double.longBitsToDouble(Double.doubleToRawLongBits(60.0)-1); - - //-------------------------------------------------------------------------- - // CONSTANTS FOR NORMALIZATIONS - //-------------------------------------------------------------------------- - - /** - * Table of constants for 1/(PI/2), 282 Hex digits (enough for normalizing doubles). - * 1/(PI/2) approximation = sum of TWO_OVER_PI_TAB[i]*2^(-24*(i+1)). - * - * double and not int, to avoid int-to-double cast during computations. - */ - private static final double TWO_OVER_PI_TAB[] = { - 0xA2F983, 0x6E4E44, 0x1529FC, 0x2757D1, 0xF534DD, 0xC0DB62, - 0x95993C, 0x439041, 0xFE5163, 0xABDEBB, 0xC561B7, 0x246E3A, - 0x424DD2, 0xe00649, 0x2EEA09, 0xD1921C, 0xFE1DEB, 0x1CB129, - 0xA73EE8, 0x8235F5, 0x2EBB44, 0x84E99C, 0x7026B4, 0x5F7E41, - 0x3991d6, 0x398353, 0x39F49C, 0x845F8B, 0xBDF928, 0x3B1FF8, - 0x97FFDE, 0x05980F, 0xEF2F11, 0x8B5A0A, 0x6D1F6D, 0x367ECF, - 0x27CB09, 0xB74F46, 0x3F669E, 0x5FEA2D, 0x7527BA, 0xC7EBE5, - 0xF17B3D, 0x0739F7, 0x8A5292, 0xEA6BFB, 0x5FB11F, 0x8D5D08, - 0x560330, 0x46FC7B, 0x6BABF0, 0xCFBC20, 0x9AF436, 0x1DA9E3, - 0x91615E, 0xE61B08, 0x659985, 0x5F14A0, 0x68408D, 0xFFD880, - 0x4D7327, 0x310606, 0x1556CA, 0x73A8C9, 0x60E27B, 0xC08C6B}; - - /* - * Constants for PI/2. Only the 23 most significant bits of each mantissa are used. - * 2*PI approximation = sum of TWOPI_TAB. - */ - private static final double PIO2_TAB0 = Double.longBitsToDouble(0x3FF921FB40000000L); - private static final double PIO2_TAB1 = Double.longBitsToDouble(0x3E74442D00000000L); - private static final double PIO2_TAB2 = Double.longBitsToDouble(0x3CF8469880000000L); - private static final double PIO2_TAB3 = Double.longBitsToDouble(0x3B78CC5160000000L); - private static final double PIO2_TAB4 = Double.longBitsToDouble(0x39F01B8380000000L); - private static final double PIO2_TAB5 = Double.longBitsToDouble(0x387A252040000000L); - - static final double PIO2_INV = Double.longBitsToDouble(0x3FE45F306DC9C883L); // 6.36619772367581382433e-01 53 bits of 2/pi - static final double PIO2_HI = Double.longBitsToDouble(0x3FF921FB54400000L); // 1.57079632673412561417e+00 first 33 bits of pi/2 - static final double PIO2_LO = Double.longBitsToDouble(0x3DD0B4611A626331L); // 6.07710050650619224932e-11 pi/2 - PIO2_HI - static final double PI_INV = PIO2_INV/2; - static final double PI_HI = 2*PIO2_HI; - static final double PI_LO = 2*PIO2_LO; - static final double TWOPI_INV = PIO2_INV/4; - static final double TWOPI_HI = 4*PIO2_HI; - static final double TWOPI_LO = 4*PIO2_LO; - - /** - * Bit = 0 where quadrant is encoded in remainder bits. - */ - private static final long QUADRANT_BITS_0_MASK = 0xCFFFFFFFFFFFFFFFL; - - /** - * Remainder bits where quadrant is encoded, 0 elsewhere. - */ - private static final long QUADRANT_PLACE_BITS = 0x3000000000000000L; - - /** - * fdlibm uses 2^19*PI/2 here. - * With 2^18*PI/2 we would be more accurate, for example when normalizing - * 822245.903631403, which is close to 2^19*PI/2, but we are still in - * our accuracy tolerance with fdlibm's value (but not 2^20*PI/2) so we - * stick to it, to help being faster than (Strict)Math for values in - * [2^18*PI/2,2^19*PI/2]. - * - * For tests, can use a smaller value, for heavy remainder - * not to only be used with huge values. - */ - static final double NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2 = StrictMath.pow(2.0,19.0)*(Math.PI/2); - - /** - * 2*Math.PI, normalized into [-PI,PI], as returned by - * StrictMath.asin(StrictMath.sin(2*Math.PI)) - * (asin behaves as identity for this). - * - * NB: NumbersUtils.minus2PI(2*Math.PI) returns -2.449293598153844E-16, - * which is different due to not using an accurate enough definition of PI. - */ - static final double TWO_MATH_PI_IN_MINUS_PI_PI = -2.4492935982947064E-16; - - //-------------------------------------------------------------------------- - // CONSTANTS AND TABLES FOR SIN AND COS - //-------------------------------------------------------------------------- - - static final int SIN_COS_TABS_SIZE = (1<>9) / SIN_COS_INDEXER) * 0.99; - - //-------------------------------------------------------------------------- - // CONSTANTS AND TABLES FOR TAN - //-------------------------------------------------------------------------- - - // We use the following formula: - // 1) tan(-x) = -tan(x) - // 2) tan(x) = 1/tan(PI/2-x) - // ---> we only have to compute tan(x) on [0,A] with PI/4<=A= 45deg, and supposed to be >= 51.4deg, as fdlibm code is not - * supposed to work with values inferior to that (51.4deg is about - * (PI/2-Double.longBitsToDouble(0x3FE5942800000000L))). - */ - static final double TAN_MAX_VALUE_FOR_TABS = StrictMath.toRadians(77.0); - - static final int TAN_TABS_SIZE = (int)((TAN_MAX_VALUE_FOR_TABS/(Math.PI/2)) * (TAN_VIRTUAL_TABS_SIZE-1)) + 1; - static final double TAN_DELTA_HI = PIO2_HI/(TAN_VIRTUAL_TABS_SIZE-1); - static final double TAN_DELTA_LO = PIO2_LO/(TAN_VIRTUAL_TABS_SIZE-1); - static final double TAN_INDEXER = 1/(TAN_DELTA_HI+TAN_DELTA_LO); - - static final class MyTTan { - static final double[] tanTab = new double[TAN_TABS_SIZE]; - static final double[] tanDer1DivF1Tab = new double[TAN_TABS_SIZE]; - static final double[] tanDer2DivF2Tab = new double[TAN_TABS_SIZE]; - static final double[] tanDer3DivF3Tab = new double[TAN_TABS_SIZE]; - static final double[] tanDer4DivF4Tab = new double[TAN_TABS_SIZE]; - static { - init(); - } - private static strictfp void init() { - for (int i=0;i>9) / TAN_INDEXER) * 0.99); - - //-------------------------------------------------------------------------- - // CONSTANTS AND TABLES FOR ACOS, ASIN - //-------------------------------------------------------------------------- - - // We use the following formula: - // 1) acos(x) = PI/2 - asin(x) - // 2) asin(-x) = -asin(x) - // ---> we only have to compute asin(x) on [0,1]. - // For values not close to +-1, we use look-up tables; - // for values near +-1, we use code derived from fdlibm. - - /** - * Supposed to be >= sin(77.2deg), as fdlibm code is supposed to work with values > 0.975, - * but seems to work well enough as long as value >= sin(25deg). - */ - static final double ASIN_MAX_VALUE_FOR_TABS = StrictMath.sin(StrictMath.toRadians(73.0)); - - static final int ASIN_TABS_SIZE = (1< we only have to compute atan(x) on [0,+Infinity[. - // For values corresponding to angles not close to +-PI/2, we use look-up tables; - // for values corresponding to angles near +-PI/2, we use code derived from fdlibm. - - /** - * Supposed to be >= tan(67.7deg), as fdlibm code is supposed to work with values > 2.4375. - */ - static final double ATAN_MAX_VALUE_FOR_TABS = StrictMath.tan(StrictMath.toRadians(74.0)); - - static final int ATAN_TABS_SIZE = (1<>SQRT_LO_BITS)); - for (int i=1;i>CBRT_LO_BITS)); - for (int i=1;i= MIN_DOUBLE_EXPONENT) { - if (power <= MAX_DOUBLE_EXPONENT) { // Normal or subnormal. - return MyTTwoPow.twoPowTab[power-MIN_DOUBLE_EXPONENT]; - } else { // Overflow. - return Double.POSITIVE_INFINITY; - } - } else { // Underflow. - return 0.0; - } - } else { - return NumbersUtils.twoPow(power); - } - } - - /** - * @param value An int value. - * @return value*value. - */ - public static int pow2(int value) { - return value*value; - } - - /** - * @param value A long value. - * @return value*value. - */ - public static long pow2(long value) { - return value*value; - } - - /** - * @param value An int value. - * @return value*value*value. - */ - public static int pow3(int value) { - return value*value*value; - } - - /** - * @param value A long value. - * @return value*value*value. - */ - public static long pow3(long value) { - return value*value*value; - } - - /* - * absolute values - */ - - /** - * @param value An int value. - * @return The absolute value, except if value is Integer.MIN_VALUE, for which it returns Integer.MIN_VALUE. - */ - public static int abs(int value) { - if (FM_USE_JDK_MATH || SFM_USE_JDK_MATH) { - return Math.abs(value); - } - return NumbersUtils.abs(value); - } - - /** - * @param value A long value. - * @return The absolute value, except if value is Long.MIN_VALUE, for which it returns Long.MIN_VALUE. - */ - public static long abs(long value) { - if (FM_USE_JDK_MATH || SFM_USE_JDK_MATH) { - return Math.abs(value); - } - return NumbersUtils.abs(value); - } - - /* - * close values - */ - - /** - * @param value A long value. - * @return The specified value as int. - * @throws ArithmeticException if the specified value is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int toIntExact(long value) { - return NumbersUtils.asInt(value); - } - - /** - * @param value A long value. - * @return The closest int value in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int toInt(long value) { - return NumbersUtils.toInt(value); - } - - /* - * ranges - */ - - /** - * @param min An int value. - * @param max An int value. - * @param value An int value. - * @return minValue if value < minValue, maxValue if value > maxValue, value otherwise. - */ - public static int toRange(int min, int max, int value) { - return NumbersUtils.toRange(min, max, value); - } - - /** - * @param min A long value. - * @param max A long value. - * @param value A long value. - * @return min if value < min, max if value > max, value otherwise. - */ - public static long toRange(long min, long max, long value) { - return NumbersUtils.toRange(min, max, value); - } - - /* - * unary operators (increment,decrement,negate) - */ - - /** - * @param value An int value. - * @return The argument incremented by one. - * @throws ArithmeticException if the mathematical result - * is not in int range. - */ - public static int incrementExact(int value) { - if (value == Integer.MAX_VALUE) { - throw new ArithmeticException("integer overflow"); - } - return value + 1; - } - - /** - * @param value A long value. - * @return The argument incremented by one. - * @throws ArithmeticException if the mathematical result - * is not in long range. - */ - public static long incrementExact(long value) { - if (value == Long.MAX_VALUE) { - throw new ArithmeticException("long overflow"); - } - return value + 1L; - } - - /** - * @param value An int value. - * @return The argument incremented by one, or the argument - * if the mathematical result is not in int range. - */ - public static int incrementBounded(int value) { - if (value == Integer.MAX_VALUE) { - return value; - } - return value + 1; - } - - /** - * @param value A long value. - * @return The argument incremented by one, or the argument - * if the mathematical result is not in long range. - */ - public static long incrementBounded(long value) { - if (value == Long.MAX_VALUE) { - return value; - } - return value + 1L; - } - - /** - * @param value An int value. - * @return The argument decremented by one. - * @throws ArithmeticException if the mathematical result - * is not in int range. - */ - public static int decrementExact(int value) { - if (value == Integer.MIN_VALUE) { - throw new ArithmeticException("integer overflow"); - } - return value - 1; - } - - /** - * @param value A long value. - * @return The argument decremented by one. - * @throws ArithmeticException if the mathematical result - * is not in long range. - */ - public static long decrementExact(long value) { - if (value == Long.MIN_VALUE) { - throw new ArithmeticException("long overflow"); - } - return value - 1L; - } - - /** - * @param value An int value. - * @return The argument decremented by one, or the argument - * if the mathematical result is not in int range. - */ - public static int decrementBounded(int value) { - if (value == Integer.MIN_VALUE) { - return value; - } - return value - 1; - } - - /** - * @param value A long value. - * @return The argument decremented by one, or the argument - * if the mathematical result is not in long range. - */ - public static long decrementBounded(long value) { - if (value == Long.MIN_VALUE) { - return value; - } - return value - 1L; - } - - /** - * @param value An int value. - * @return The argument negated. - * @throws ArithmeticException if the mathematical result - * is not in int range. - */ - public static int negateExact(int value) { - if (value == Integer.MIN_VALUE) { - throw new ArithmeticException("integer overflow"); - } - return -value; - } - - /** - * @param value A long value. - * @return The argument negated. - * @throws ArithmeticException if the mathematical result - * is not in long range. - */ - public static long negateExact(long value) { - if (value == Long.MIN_VALUE) { - throw new ArithmeticException("long overflow"); - } - return -value; - } - - /** - * @param value An int value. - * @return The argument negated, or Integer.MAX_VALUE - * if the argument is Integer.MIN_VALUE. - */ - public static int negateBounded(int value) { - if (value == Integer.MIN_VALUE) { - return Integer.MAX_VALUE; - } - return -value; - } - - /** - * @param value A long value. - * @return The argument negated, or Long.MAX_VALUE - * if the argument is Long.MIN_VALUE. - */ - public static long negateBounded(long value) { - if (value == Long.MIN_VALUE) { - return Long.MAX_VALUE; - } - return -value; - } - - /* - * binary operators (+,-,*) - */ - - /** - * @param a An int value. - * @param b An int value. - * @return The mathematical result of a+b. - * @throws ArithmeticException if the mathematical result of a+b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int addExact(int a, int b) { - return NumbersUtils.plusExact(a, b); - } - - /** - * @param a A long value. - * @param b A long value. - * @return The mathematical result of a+b. - * @throws ArithmeticException if the mathematical result of a+b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. - */ - public static long addExact(long a, long b) { - return NumbersUtils.plusExact(a, b); - } - - /** - * @param a An int value. - * @param b An int value. - * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a+b. - */ - public static int addBounded(int a, int b) { - return NumbersUtils.plusBounded(a, b); - } - - /** - * @param a A long value. - * @param b A long value. - * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a+b. - */ - public static long addBounded(long a, long b) { - return NumbersUtils.plusBounded(a, b); - } - - /** - * @param a An int value. - * @param b An int value. - * @return The mathematical result of a-b. - * @throws ArithmeticException if the mathematical result of a-b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int subtractExact(int a, int b) { - return NumbersUtils.minusExact(a, b); - } - - /** - * @param a A long value. - * @param b A long value. - * @return The mathematical result of a-b. - * @throws ArithmeticException if the mathematical result of a-b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. - */ - public static long subtractExact(long a, long b) { - return NumbersUtils.minusExact(a, b); - } - - /** - * @param a An int value. - * @param b An int value. - * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a-b. - */ - public static int subtractBounded(int a, int b) { - return NumbersUtils.minusBounded(a, b); - } - - /** - * @param a A long value. - * @param b A long value. - * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a-b. - */ - public static long subtractBounded(long a, long b) { - return NumbersUtils.minusBounded(a, b); - } - - /** - * @param a An int value. - * @param b An int value. - * @return The mathematical result of a*b. - * @throws ArithmeticException if the mathematical result of a*b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int multiplyExact(int a, int b) { - return NumbersUtils.timesExact(a, b); - } - - /** - * @param a A long value. - * @param b An int value. - * @return The mathematical result of a*b. - * @throws ArithmeticException if the mathematical result of a*b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. - */ - public static long multiplyExact(long a, int b) { - return NumbersUtils.timesExact(a, (long) b); - } - - /** - * @param a A long value. - * @param b A long value. - * @return The mathematical result of a*b. - * @throws ArithmeticException if the mathematical result of a*b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. - */ - public static long multiplyExact(long a, long b) { - return NumbersUtils.timesExact(a, b); - } - - /** - * @param a An int value. - * @param b An int value. - * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a*b. - */ - public static int multiplyBounded(int a, int b) { - return NumbersUtils.timesBounded(a, b); - } - - /** - * @param a A long value. - * @param b An int value. - * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a*b. - */ - public static long multiplyBounded(long a, int b) { - return NumbersUtils.timesBounded(a, (long) b); - } - - /** - * @param a A long value. - * @param b A long value. - * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a*b. - */ - public static long multiplyBounded(long a, long b) { - return NumbersUtils.timesBounded(a, b); - } - - /** - * @param x An int value. - * @param y An int value. - * @return The mathematical product as a long. - */ - public static long multiplyFull(int x, int y) { - return ((long) x) * ((long) y); - } - - /** - * @param x A long value. - * @param y A long value. - * @return The most significant 64 bits of the 128-bit product of two 64-bit factors. - */ - public static long multiplyHigh(long x, long y) { - if ((x|y) < 0) { - // Use technique from section 8-2 of Henry S. Warren, Jr., - // Hacker's Delight (2nd ed.) (Addison Wesley, 2013), 173-174. - long x1 = (x >> 32); - long y1 = (y >> 32); - long x2 = (x & 0xFFFFFFFFL); - long y2 = (y & 0xFFFFFFFFL); - long z2 = x2 * y2; - long t = x1 * y2 + (z2 >>> 32); - long z1 = (t & 0xFFFFFFFFL) + x2 * y1; - long z0 = (t >> 32); - return x1 * y1 + z0 + (z1 >> 32); - } else { - // Use Karatsuba technique with two base 2^32 digits. - long x1 = (x >>> 32); - long y1 = (y >>> 32); - long x2 = (x & 0xFFFFFFFFL); - long y2 = (y & 0xFFFFFFFFL); - long A = x1 * y1; - long B = x2 * y2; - long C = (x1 + x2) * (y1 + y2); - long K = C - A - B; - return (((B >>> 32) + K) >>> 32) + A; - } - } - - /* - * binary operators (/,%) - */ - - /** - * Returns the largest int <= dividend/divisor. - * - * Unlike "/" operator, which rounds towards 0, this division - * rounds towards -Infinity (which give different result - * when the exact result is negative). - * - * @param x The dividend. - * @param y The divisor. - * @return The largest int <= dividend/divisor, unless dividend is - * Integer.MIN_VALUE and divisor is -1, in which case - * Integer.MIN_VALUE is returned. - * @throws ArithmeticException if the divisor is zero. - */ - public static int floorDiv(int x, int y) { - int r = x / y; - // If the signs are different and modulo not zero, rounding down. - if (((x ^ y) < 0) && ((r * y) != x)) { - r--; - } - return r; - } - - /** - * Returns the largest long <= dividend/divisor. - * - * Unlike "/" operator, which rounds towards 0, this division - * rounds towards -Infinity (which give different result - * when the exact result is negative). - * - * @param x The dividend. - * @param y The divisor. - * @return The largest long <= dividend/divisor, unless dividend is - * Long.MIN_VALUE and divisor is -1, in which case - * Long.MIN_VALUE is returned. - * @throws ArithmeticException if the divisor is zero. - */ - public static long floorDiv(long x, int y) { - return floorDiv(x, (long) y); - } - - /** - * Returns the largest long <= dividend/divisor. - * - * Unlike "/" operator, which rounds towards 0, this division - * rounds towards -Infinity (which give different result - * when the exact result is negative). - * - * @param x The dividend. - * @param y The divisor. - * @return The largest long <= dividend/divisor, unless dividend is - * Long.MIN_VALUE and divisor is -1, in which case - * Long.MIN_VALUE is returned. - * @throws ArithmeticException if the divisor is zero. - */ - public static long floorDiv(long x, long y) { - long r = x / y; - // If the signs are different and modulo not zero, rounding down. - if (((x ^ y) < 0) && ((r * y) != x)) { - r--; - } - return r; - } - - /** - * Returns the floor modulus, which is "x - floorDiv(x,y) * y", - * has the same sign as y, and is in ]-abs(y),abs(y)[. - * - * The relationship between floorMod and floorDiv is the same - * than between "%" and "/". - * - * @param x The dividend. - * @param y The divisor. - * @return The floor modulus, i.e. "x - (floorDiv(x, y) * y)". - * @throws ArithmeticException if the divisor is zero. - */ - public static int floorMod(int x, int y) { - return x - floorDiv(x, y) * y; - } - - /** - * Returns the floor modulus, which is "x - floorDiv(x,y) * y", - * has the same sign as y, and is in ]-abs(y),abs(y)[. - * - * The relationship between floorMod and floorDiv is the same - * than between "%" and "/". - * - * @param x The dividend. - * @param y The divisor. - * @return The floor modulus, i.e. "x - (floorDiv(x, y) * y)". - * @throws ArithmeticException if the divisor is zero. - */ - public static int floorMod(long x, int y) { - // No overflow so can cast. - return (int) (x - floorDiv(x,y) * y); - } - - /** - * Returns the floor modulus, which is "x - floorDiv(x,y) * y", - * has the same sign as y, and is in ]-abs(y),abs(y)[. - * - * The relationship between floorMod and floorDiv is the same - * than between "%" and "/". - * - * @param x The dividend. - * @param y The divisor. - * @return The floor modulus, i.e. "x - (floorDiv(x, y) * y)". - * @throws ArithmeticException if the divisor is zero. - */ - public static long floorMod(long x, long y) { - return x - floorDiv(x, y) * y; - } - - /* - * Non-redefined Math public values and treatments. - */ - - public static int min(int a, int b) { - return Math.min(a,b); - } - - public static long min(long a, long b) { - return Math.min(a,b); - } - - public static int max(int a, int b) { - return Math.max(a,b); - } - - public static long max(long a, long b) { - return Math.max(a,b); - } - - //-------------------------------------------------------------------------- - // PACKAGE-PRIVATE METHODS - //-------------------------------------------------------------------------- - - /** - * @param power Must be in normal values range. - */ - static double twoPowNormal(int power) { - if (USE_TWO_POW_TAB) { - return MyTTwoPow.twoPowTab[power-MIN_DOUBLE_EXPONENT]; - } else { - return Double.longBitsToDouble(((long)(power+MAX_DOUBLE_EXPONENT))<<52); - } - } - - /** - * @param power Must be in normal or subnormal values range. - */ - static double twoPowNormalOrSubnormal(int power) { - if (USE_TWO_POW_TAB) { - return MyTTwoPow.twoPowTab[power-MIN_DOUBLE_EXPONENT]; - } else { - if (power <= -MAX_DOUBLE_EXPONENT) { // Not normal. - return Double.longBitsToDouble(0x0008000000000000L>>(-(power+MAX_DOUBLE_EXPONENT))); - } else { // Normal. - return Double.longBitsToDouble(((long)(power+MAX_DOUBLE_EXPONENT))<<52); - } - } - } - - static double atan2_pinf_yyy(double y) { - if (y == Double.POSITIVE_INFINITY) { - return Math.PI/4; - } else if (y == Double.NEGATIVE_INFINITY) { - return -Math.PI/4; - } else if (y > 0.0) { - return 0.0; - } else if (y < 0.0) { - return -0.0; - } else { - return Double.NaN; - } - } - - static double atan2_ninf_yyy(double y) { - if (y == Double.POSITIVE_INFINITY) { - return 3*Math.PI/4; - } else if (y == Double.NEGATIVE_INFINITY) { - return -3*Math.PI/4; - } else if (y > 0.0) { - return Math.PI; - } else if (y < 0.0) { - return -Math.PI; - } else { - return Double.NaN; - } - } - - static double atan2_yyy_zeroOrNaN(double y, double x) { - if (x == 0.0) { - if (y == 0.0) { - if (signFromBit_antiCyclic(x) < 0) { - // x is -0.0 - return signFromBit_antiCyclic(y) * Math.PI; - } else { - // +-0.0 - return y; - } - } - if (y > 0.0) { - return Math.PI/2; - } else if (y < 0.0) { - return -Math.PI/2; - } else { - return Double.NaN; - } - } else { - return Double.NaN; - } - } - - /** - * At least one of the arguments must be NaN. - */ - static double hypot_NaN(double xAbs, double yAbs) { - if ((xAbs == Double.POSITIVE_INFINITY) || (yAbs == Double.POSITIVE_INFINITY)) { - return Double.POSITIVE_INFINITY; - } else { - return Double.NaN; - } - } - - /** - * At least one of the arguments must be NaN. - */ - static double hypot_NaN(double xAbs, double yAbs, double zAbs) { - if ((xAbs == Double.POSITIVE_INFINITY) || (yAbs == Double.POSITIVE_INFINITY) || (zAbs == Double.POSITIVE_INFINITY)) { - return Double.POSITIVE_INFINITY; - } else { - return Double.NaN; - } - } - - /* - * - */ - - /** - * @param remainder Must have 1 for 2nd and 3rd exponent bits, which is the - * case for heavyRemPiO2 remainders (their absolute values are >= - * Double.longBitsToDouble(0x3000000000000000L) - * = 1.727233711018889E-77, and even if they were not, turning these - * bits from 0 to 1 on decoding would not change the absolute error - * much), and also works for +-Infinity or NaN encoding. - * @param quadrant Must be in [0,3]. - * @return Bits holding remainder, and quadrant instead of - * reamainder's 2nd and 3rd exponent bits. - */ - static long encodeRemainderAndQuadrant(double remainder, int quadrant) { - final long bits = Double.doubleToRawLongBits(remainder); - return (bits&QUADRANT_BITS_0_MASK)|(((long)quadrant)<<60); - } - - static double decodeRemainder(long bits) { - return Double.longBitsToDouble((bits&QUADRANT_BITS_0_MASK)|QUADRANT_PLACE_BITS); - } - - static int decodeQuadrant(long bits) { - return ((int)(bits>>60))&3; - } - - /* - * JDK-based remainders. - * Since a strict one for (% (PI/2)) is needed for heavyRemainderPiO2, - * we need it in this class. - * Then, for homogeneity, we put them all in this class. - * Then, to avoid code duplication for these slow-anyway methods, - * we just stick with strict versions, for both FastMath and StrictFastMath. - */ - - /** - * @param angle Angle, in radians. - * @return Remainder of (angle % (2*PI)), in [-PI,PI]. - */ - static strictfp double jdkRemainderTwoPi(double angle) { - final double sin = StrictMath.sin(angle); - final double cos = StrictMath.cos(angle); - return StrictMath.atan2(sin, cos); - } - - /** - * @param angle Angle, in radians. - * @return Remainder of (angle % PI), in [-PI/2,PI/2]. - */ - static strictfp double jdkRemainderPi(double angle) { - final double sin = StrictMath.sin(angle); - final double cos = StrictMath.cos(angle); - /* - * Making sure atan2's result ends up in [-PI/2,PI/2], - * i.e. has maximum accuracy. - */ - return StrictMath.atan2(sin, Math.abs(cos)); - } - - /** - * @param angle Angle, in radians. - * @return Bits of double corresponding to remainder of (angle % (PI/2)), - * in [-PI/4,PI/4], with quadrant encoded in exponent bits. - */ - static strictfp long jdkRemainderPiO2(double angle, boolean negateRem) { - final double sin = StrictMath.sin(angle); - final double cos = StrictMath.cos(angle); - - /* - * Computing quadrant first, and then computing - * atan2, to make sure its result ends up in [-PI/4,PI/4], - * i.e. has maximum accuracy. - */ - - final int q; - final double sinForAtan2; - final double cosForAtan2; - if (cos >= (SQRT_2/2)) { - // [-PI/4,PI/4] - q = 0; - sinForAtan2 = sin; - cosForAtan2 = cos; - } else if (cos <= -(SQRT_2/2)) { - // [3*PI/4,5*PI/4] - q = 2; - sinForAtan2 = -sin; - cosForAtan2 = -cos; - } else if (sin > 0.0) { - // [PI/4,3*PI/4] - q = 1; - sinForAtan2 = -cos; - cosForAtan2 = sin; - } else { - // [5*PI/4,7*PI/4] - q = 3; - sinForAtan2 = cos; - cosForAtan2 = -sin; - } - - double fw = StrictMath.atan2(sinForAtan2, cosForAtan2); - - return encodeRemainderAndQuadrant(negateRem ? -fw : fw, q); - } - - /* - * Our remainders implementations. - */ - - /** - * @param angle Angle, in radians. Must not be NaN nor +-Infinity. - * @return Remainder of (angle % (2*PI)), in [-PI,PI]. - */ - static strictfp double heavyRemainderTwoPi(double angle) { - final long remAndQuad = heavyRemainderPiO2(angle, false); - final double rem = decodeRemainder(remAndQuad); - final int q = decodeQuadrant(remAndQuad); - if (q == 0) { - return rem; - } else if (q == 1) { - return (rem + PIO2_LO) + PIO2_HI; - } else if (q == 2) { - if (rem < 0.0) { - return (rem + PI_LO) + PI_HI; - } else { - return (rem - PI_LO) - PI_HI; - } - } else { - return (rem - PIO2_LO) - PIO2_HI; - } - } - - /** - * @param angle Angle, in radians. Must not be NaN nor +-Infinity. - * @return Remainder of (angle % PI), in [-PI/2,PI/2]. - */ - static strictfp double heavyRemainderPi(double angle) { - final long remAndQuad = heavyRemainderPiO2(angle, false); - final double rem = decodeRemainder(remAndQuad); - final int q = decodeQuadrant(remAndQuad); - if ((q&1) != 0) { - // q is 1 or 3 - if (rem < 0.0) { - return (rem + PIO2_LO) + PIO2_HI; - } else { - return (rem - PIO2_LO) - PIO2_HI; - } - } - return rem; - } - - /** - * Remainder using an accurate definition of PI. - * Derived from a fdlibm treatment called __kernel_rem_pio2. - * - * Not defining a non-strictfp version for FastMath, to avoid duplicating - * its long and messy code, and because it's slow anyway, and should be - * rarely used when speed matters. - * - * @param angle Angle, in radians. Must not be NaN nor +-Infinity. - * @param negateRem True if remainder must be negated before encoded into returned long. - * @return Bits of double corresponding to remainder of (angle % (PI/2)), - * in [-PI/4,PI/4], with quadrant encoded in exponent bits. - */ - static strictfp long heavyRemainderPiO2(double angle, boolean negateRem) { - - /* - * fdlibm treatments unrolled, to avoid garbage and be OOME-free, - * corresponding to: - * 1) initial jk = 4 (precision = 3 = 64 bits (extended)), - * which is more accurate than using precision = 2 - * (53 bits, double), even though we work with doubles - * and use strictfp! - * 2) max lengths of 8 for f[], 6 for q[], fq[] and iq[]. - * 3) at most one recomputation (one goto). - * These limitations were experimentally found to - * be sufficient for billions of random doubles - * of random magnitudes. - * For the rare cases that our unrolled treatments can't handle, - * we fall back to a JDK-based implementation. - */ - - int n,i,j,ih; - double fw; - - /* - * Turning angle into 24-bits integer chunks. - * Done outside __kernel_rem_pio2, but we factor it inside our method. - */ - - // Reworking exponent to have a value < 2^24. - final long lx = Double.doubleToRawLongBits(angle); - final long exp = ((lx>>52)&0x7FF) - (1023+23); - double z = Double.longBitsToDouble(lx - (exp<<52)); - - double x0 = (double)(int)z; - z = (z-x0)*TWO_POW_24; - double x1 = (double)(int)z; - z = (z-x1)*TWO_POW_24; - double x2 = (double)(int)z; - - final int e0 = (int)exp; - // in [1,3] - final int nx = (x2 == 0.0) ? ((x1 == 0.0) ? 1 : 2) : 3; - - /* - * - */ - - double f0,f1,f2,f3,f4,f5,f6,f7; - double q0,q1,q2,q3,q4,q5; - int iq0,iq1,iq2,iq3,iq4,iq5; - - int jk = 4; - - int jx = nx-1; - int jv = Math.max(0,(e0-3)/24); - // In fdlibm, this is q0, but we prefer to use q0 for q[0]. - int qZero = e0-24*(jv+1); - - j = jv-jx; - if (jx == 0) { - f6 = 0.0; - f5 = 0.0; - f4 = (j >= -4) ? TWO_OVER_PI_TAB[j+4] : 0.0; - f3 = (j >= -3) ? TWO_OVER_PI_TAB[j+3] : 0.0; - f2 = (j >= -2) ? TWO_OVER_PI_TAB[j+2] : 0.0; - f1 = (j >= -1) ? TWO_OVER_PI_TAB[j+1] : 0.0; - f0 = (j >= 0) ? TWO_OVER_PI_TAB[j] : 0.0; - - q0 = x0*f0; - q1 = x0*f1; - q2 = x0*f2; - q3 = x0*f3; - q4 = x0*f4; - } else if (jx == 1) { - f6 = 0.0; - f5 = (j >= -5) ? TWO_OVER_PI_TAB[j+5] : 0.0; - f4 = (j >= -4) ? TWO_OVER_PI_TAB[j+4] : 0.0; - f3 = (j >= -3) ? TWO_OVER_PI_TAB[j+3] : 0.0; - f2 = (j >= -2) ? TWO_OVER_PI_TAB[j+2] : 0.0; - f1 = (j >= -1) ? TWO_OVER_PI_TAB[j+1] : 0.0; - f0 = (j >= 0) ? TWO_OVER_PI_TAB[j] : 0.0; - - q0 = x0*f1 + x1*f0; - q1 = x0*f2 + x1*f1; - q2 = x0*f3 + x1*f2; - q3 = x0*f4 + x1*f3; - q4 = x0*f5 + x1*f4; - } else { // jx == 2 - f6 = (j >= -6) ? TWO_OVER_PI_TAB[j+6] : 0.0; - f5 = (j >= -5) ? TWO_OVER_PI_TAB[j+5] : 0.0; - f4 = (j >= -4) ? TWO_OVER_PI_TAB[j+4] : 0.0; - f3 = (j >= -3) ? TWO_OVER_PI_TAB[j+3] : 0.0; - f2 = (j >= -2) ? TWO_OVER_PI_TAB[j+2] : 0.0; - f1 = (j >= -1) ? TWO_OVER_PI_TAB[j+1] : 0.0; - f0 = (j >= 0) ? TWO_OVER_PI_TAB[j] : 0.0; - - q0 = x0*f2 + x1*f1 + x2*f0; - q1 = x0*f3 + x1*f2 + x2*f1; - q2 = x0*f4 + x1*f3 + x2*f2; - q3 = x0*f5 + x1*f4 + x2*f3; - q4 = x0*f6 + x1*f5 + x2*f4; - } - - double twoPowQZero = twoPowNormal(qZero); - - int jz = jk; - - /* - * Unrolling of first round. - */ - - z = q4; - fw = (double)(int)(TWO_POW_N24*z); - iq0 = (int)(z-TWO_POW_24*fw); - z = q3+fw; - fw = (double)(int)(TWO_POW_N24*z); - iq1 = (int)(z-TWO_POW_24*fw); - z = q2+fw; - fw = (double)(int)(TWO_POW_N24*z); - iq2 = (int)(z-TWO_POW_24*fw); - z = q1+fw; - fw = (double)(int)(TWO_POW_N24*z); - iq3 = (int)(z-TWO_POW_24*fw); - z = q0+fw; - iq4 = 0; - iq5 = 0; - - z = (z*twoPowQZero) % 8.0; - n = (int)z; - z -= (double)n; - - ih = 0; - if (qZero > 0) { - // Parentheses against code formatter bug. - i = (iq3>>(24-qZero)); - n += i; - iq3 -= i<<(24-qZero); - ih = iq3>>(23-qZero); - } else if (qZero == 0) { - ih = iq3>>23; - } else if (z >= 0.5) { - ih = 2; - } - - if (ih > 0) { - n += 1; - // carry = 1 is common case, - // so using it as initial value. - int carry = 1; - if (iq0 != 0) { - iq0 = 0x1000000 - iq0; - iq1 = 0xFFFFFF - iq1; - iq2 = 0xFFFFFF - iq2; - iq3 = 0xFFFFFF - iq3; - } else if (iq1 != 0) { - iq1 = 0x1000000 - iq1; - iq2 = 0xFFFFFF - iq2; - iq3 = 0xFFFFFF - iq3; - } else if (iq2 != 0) { - iq2 = 0x1000000 - iq2; - iq3 = 0xFFFFFF - iq3; - } else if (iq3 != 0) { - iq3 = 0x1000000 - iq3; - } else { - carry = 0; - } - if (qZero > 0) { - if (qZero == 1) { - iq3 &= 0x7FFFFF; - } else if (qZero == 2) { - iq3 &= 0x3FFFFF; - } - } - if (ih == 2) { - z = 1.0 - z; - if (carry != 0) { - z -= twoPowQZero; - } - } - } - - if (z == 0.0) { - if (iq3 == 0) { - // With random values of random magnitude, - // probability for this to happen seems lower than 1e-6. - // jz would be more than just incremented by one, - // which our unrolling doesn't support. - return jdkRemainderPiO2(angle, negateRem); - } - if (jx == 0) { - f5 = TWO_OVER_PI_TAB[jv+5]; - q5 = x0*f5; - } else if (jx == 1) { - f6 = TWO_OVER_PI_TAB[jv+5]; - q5 = x0*f6 + x1*f5; - } else { // jx == 2 - f7 = TWO_OVER_PI_TAB[jv+5]; - q5 = x0*f7 + x1*f6 + x2*f5; - } - - jz++; - - /* - * Unrolling of second round. - */ - - z = q5; - fw = (double)(int)(TWO_POW_N24*z); - iq0 = (int)(z-TWO_POW_24*fw); - z = q4+fw; - fw = (double)(int)(TWO_POW_N24*z); - iq1 = (int)(z-TWO_POW_24*fw); - z = q3+fw; - fw = (double)(int)(TWO_POW_N24*z); - iq2 = (int)(z-TWO_POW_24*fw); - z = q2+fw; - fw = (double)(int)(TWO_POW_N24*z); - iq3 = (int)(z-TWO_POW_24*fw); - z = q1+fw; - fw = (double)(int)(TWO_POW_N24*z); - iq4 = (int)(z-TWO_POW_24*fw); - z = q0+fw; - iq5 = 0; - - z = (z*twoPowQZero) % 8.0; - n = (int)z; - z -= (double)n; - - ih = 0; - if (qZero > 0) { - // Parentheses against code formatter bug. - i = (iq4>>(24-qZero)); - n += i; - iq4 -= i<<(24-qZero); - ih = iq4>>(23-qZero); - } else if (qZero == 0) { - ih = iq4>>23; - } else if (z >= 0.5) { - ih = 2; - } - - if (ih > 0) { - n += 1; - // carry = 1 is common case, - // so using it as initial value. - int carry = 1; - if (iq0 != 0) { - iq0 = 0x1000000 - iq0; - iq1 = 0xFFFFFF - iq1; - iq2 = 0xFFFFFF - iq2; - iq3 = 0xFFFFFF - iq3; - iq4 = 0xFFFFFF - iq4; - } else if (iq1 != 0) { - iq1 = 0x1000000 - iq1; - iq2 = 0xFFFFFF - iq2; - iq3 = 0xFFFFFF - iq3; - iq4 = 0xFFFFFF - iq4; - } else if (iq2 != 0) { - iq2 = 0x1000000 - iq2; - iq3 = 0xFFFFFF - iq3; - iq4 = 0xFFFFFF - iq4; - } else if (iq3 != 0) { - iq3 = 0x1000000 - iq3; - iq4 = 0xFFFFFF - iq4; - } else if (iq4 != 0) { - iq4 = 0x1000000 - iq4; - } else { - carry = 0; - } - if (qZero > 0) { - if (qZero == 1) { - iq4 &= 0x7FFFFF; - } else if (qZero == 2) { - iq4 &= 0x3FFFFF; - } - } - if (ih == 2) { - z = 1.0 - z; - if (carry != 0) { - z -= twoPowQZero; - } - } - } - - if (z == 0.0) { - if (iq4 == 0) { - // Case not encountered in tests, but still handling it. - // Would require a third loop unrolling. - return jdkRemainderPiO2(angle, negateRem); - } else { - // z == 0.0, and iq4 != 0, - // so we remove 24 from qZero only once, - // but since we no longer use qZero, - // we just bother to multiply its 2-power - // by 2^-24. - jz--; - twoPowQZero *= TWO_POW_N24; - } - } else { - // z != 0.0 at end of second round. - } - } else { - // z != 0.0 at end of first round. - } - - /* - * After loop. - */ - - if (z != 0.0) { - z /= twoPowQZero; - if (z >= TWO_POW_24) { - fw = (double)(int)(TWO_POW_N24*z); - if (jz == jk) { - iq4 = (int)(z-TWO_POW_24*fw); - jz++; // jz to 5 - // Not using qZero anymore so not updating it. - twoPowQZero *= TWO_POW_24; - iq5 = (int)fw; - } else { // jz == jk+1 == 5 - // Case not encountered in tests, but still handling it. - // Would require use of iq6, with jz = 6. - return jdkRemainderPiO2(angle, negateRem); - } - } else { - if (jz == jk) { - iq4 = (int)z; - } else { // jz == jk+1 == 5 - // Case not encountered in tests, but still handling it. - iq5 = (int)z; - } - } - } - - fw = twoPowQZero; - - if (jz == 5) { - q5 = fw*(double)iq5; - fw *= TWO_POW_N24; - } else { - q5 = 0.0; - } - q4 = fw*(double)iq4; - fw *= TWO_POW_N24; - q3 = fw*(double)iq3; - fw *= TWO_POW_N24; - q2 = fw*(double)iq2; - fw *= TWO_POW_N24; - q1 = fw*(double)iq1; - fw *= TWO_POW_N24; - q0 = fw*(double)iq0; - - /* - * We just use HI part of the result. - */ - - fw = PIO2_TAB0*q5; - fw += PIO2_TAB0*q4 + PIO2_TAB1*q5; - fw += PIO2_TAB0*q3 + PIO2_TAB1*q4 + PIO2_TAB2*q5; - fw += PIO2_TAB0*q2 + PIO2_TAB1*q3 + PIO2_TAB2*q4 + PIO2_TAB3*q5; - fw += PIO2_TAB0*q1 + PIO2_TAB1*q2 + PIO2_TAB2*q3 + PIO2_TAB3*q4 + PIO2_TAB4*q5; - fw += PIO2_TAB0*q0 + PIO2_TAB1*q1 + PIO2_TAB2*q2 + PIO2_TAB3*q3 + PIO2_TAB4*q4 + PIO2_TAB5*q5; - - if ((ih != 0) ^ negateRem) { - fw = -fw; - } - - return encodeRemainderAndQuadrant(fw, n&3); - } - - //-------------------------------------------------------------------------- - // PRIVATE METHODS - //-------------------------------------------------------------------------- - - /** - * Redefined here, to avoid cyclic dependency with (Strict)FastMath. - * - * @param value A double value. - * @return -1 if sign bit is 1, 1 if sign bit is 0. - */ - private static long signFromBit_antiCyclic(double value) { - // Returning a long, to avoid useless cast into int. - return ((Double.doubleToRawLongBits(value)>>62)|1); - } - - private static boolean getBooleanProperty( - final String key, - boolean defaultValue) { - final String tmp = System.getProperty(key); - if (tmp != null) { - return Boolean.parseBoolean(tmp); - } else { - return defaultValue; - } - } - - /** - * Use look-up tables size power through this method, - * to make sure is it small in case java.lang.Math - * is directly used. - */ - private static int getTabSizePower(int tabSizePower) { - return (FM_USE_JDK_MATH && SFM_USE_JDK_MATH) ? Math.min(2, tabSizePower) : tabSizePower; - } -} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/DoubleWrapper.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/DoubleWrapper.java deleted file mode 100644 index e7adc8d59..000000000 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/DoubleWrapper.java +++ /dev/null @@ -1,13 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ -package space.kscience.kmath.jafama; - -public class DoubleWrapper { - public double value; - @Override - public String toString() { - return Double.toString(this.value); - } -} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/FastMath.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/FastMath.java deleted file mode 100644 index a83c01f7b..000000000 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/FastMath.java +++ /dev/null @@ -1,2986 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.jafama; - -/** - * Faster (hopefully) versions of java.lang.Math methods, plus additional ones. - * Cf. README.txt for more info. - */ -public final class FastMath extends CmnFastMath { - - //-------------------------------------------------------------------------- - // CONFIGURATION - //-------------------------------------------------------------------------- - - private static final boolean USE_JDK_MATH = FM_USE_JDK_MATH; - - private static final boolean USE_REDEFINED_LOG = FM_USE_REDEFINED_LOG; - - private static final boolean USE_REDEFINED_SQRT = FM_USE_REDEFINED_SQRT; - - private static final boolean USE_POWTABS_FOR_ASIN = FM_USE_POWTABS_FOR_ASIN; - - //-------------------------------------------------------------------------- - // PUBLIC METHODS - //-------------------------------------------------------------------------- - - /* - * trigonometry - */ - - /** - * @param angle Angle in radians. - * @return Angle sine. - */ - public static double sin(double angle) { - if (USE_JDK_MATH) { - return Math.sin(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { - if (false) { - // Can give very bad relative error near PI (mod 2*PI). - angle = remainderTwoPi(angle); - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } else { - final long remAndQuad = remainderPiO2(angle); - angle = decodeRemainder(remAndQuad); - final double sin; - final int q = decodeQuadrant(remAndQuad); - if (q == 0) { - sin = sin(angle); - } else if (q == 1) { - sin = cos(angle); - } else if (q == 2) { - sin = -sin(angle); - } else { - sin = -cos(angle); - } - return (negateResult ? -sin : sin); - } - } - // index: possibly outside tables range. - int index = (int)(angle * SIN_COS_INDEXER + 0.5); - double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; - // Making sure index is within tables range. - // Last value of each table is the same than first, - // so we ignore it (tabs size minus one) for modulo. - index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) - double indexSin = MyTSinCos.sinTab[index]; - double indexCos = MyTSinCos.cosTab[index]; - double result = indexSin + delta * (indexCos + delta * (-indexSin * ONE_DIV_F2 + delta * (-indexCos * ONE_DIV_F3 + delta * indexSin * ONE_DIV_F4))); - return negateResult ? -result : result; - } - - /** - * Quick sin, with accuracy of about 1.6e-3 (PI/) - * for |angle| < 6588395.0 (Integer.MAX_VALUE * (2*PI/) - 2) - * (- 2 due to removing PI/2 before using cosine tab), - * and no accuracy at all for larger values. - * - * @param angle Angle in radians. - * @return Angle sine. - */ - public static double sinQuick(double angle) { - if (USE_JDK_MATH) { - return Math.sin(angle); - } - return MyTSinCos.cosTab[((int)(Math.abs(angle-Math.PI/2) * SIN_COS_INDEXER + 0.5)) & (SIN_COS_TABS_SIZE-2)]; - } - - /** - * @param angle Angle in radians. - * @return Angle cosine. - */ - public static double cos(double angle) { - if (USE_JDK_MATH) { - return Math.cos(angle); - } - angle = Math.abs(angle); - if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { - if (false) { - // Can give very bad relative error near PI (mod 2*PI). - angle = remainderTwoPi(angle); - if (angle < 0.0) { - angle = -angle; - } - } else { - final long remAndQuad = remainderPiO2(angle); - angle = decodeRemainder(remAndQuad); - final double cos; - final int q = decodeQuadrant(remAndQuad); - if (q == 0) { - cos = cos(angle); - } else if (q == 1) { - cos = -sin(angle); - } else if (q == 2) { - cos = -cos(angle); - } else { - cos = sin(angle); - } - return cos; - } - } - // index: possibly outside tables range. - int index = (int)(angle * SIN_COS_INDEXER + 0.5); - double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; - // Making sure index is within tables range. - // Last value of each table is the same than first, - // so we ignore it (tabs size minus one) for modulo. - index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) - double indexCos = MyTSinCos.cosTab[index]; - double indexSin = MyTSinCos.sinTab[index]; - return indexCos + delta * (-indexSin + delta * (-indexCos * ONE_DIV_F2 + delta * (indexSin * ONE_DIV_F3 + delta * indexCos * ONE_DIV_F4))); - } - - /** - * Quick cos, with accuracy of about 1.6e-3 (PI/) - * for |angle| < 6588397.0 (Integer.MAX_VALUE * (2*PI/)), - * and no accuracy at all for larger values. - * - * @param angle Angle in radians. - * @return Angle cosine. - */ - public static double cosQuick(double angle) { - if (USE_JDK_MATH) { - return Math.cos(angle); - } - return MyTSinCos.cosTab[((int)(Math.abs(angle) * SIN_COS_INDEXER + 0.5)) & (SIN_COS_TABS_SIZE-2)]; - } - - /** - * Computes sine and cosine together. - * - * @param angle Angle in radians. - * @param cosine (out) Angle cosine. - * @return Angle sine. - */ - public static double sinAndCos(double angle, DoubleWrapper cosine) { - if (USE_JDK_MATH) { - cosine.value = Math.cos(angle); - return Math.sin(angle); - } - // Using the same algorithm than sin(double) method, - // and computing also cosine at the end. - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { - if (false) { - // Can give very bad relative error near PI (mod 2*PI). - angle = remainderTwoPi(angle); - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } else { - final long remAndQuad = remainderPiO2(angle); - angle = decodeRemainder(remAndQuad); - final double sin; - final int q = decodeQuadrant(remAndQuad); - if (q == 0) { - sin = sin(angle); - cosine.value = cos(angle); - } else if (q == 1) { - sin = cos(angle); - cosine.value = -sin(angle); - } else if (q == 2) { - sin = -sin(angle); - cosine.value = -cos(angle); - } else { - sin = -cos(angle); - cosine.value = sin(angle); - } - return (negateResult ? -sin : sin); - } - } - int index = (int)(angle * SIN_COS_INDEXER + 0.5); - double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; - index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) - double indexSin = MyTSinCos.sinTab[index]; - double indexCos = MyTSinCos.cosTab[index]; - // Could factor some multiplications (delta * factorials), but then is less accurate. - cosine.value = indexCos + delta * (-indexSin + delta * (-indexCos * ONE_DIV_F2 + delta * (indexSin * ONE_DIV_F3 + delta * indexCos * ONE_DIV_F4))); - double result = indexSin + delta * (indexCos + delta * (-indexSin * ONE_DIV_F2 + delta * (-indexCos * ONE_DIV_F3 + delta * indexSin * ONE_DIV_F4))); - return negateResult ? -result : result; - } - - /** - * Can have very bad relative error near +-PI/2, - * but of the same magnitude than the relative delta between - * StrictMath.tan(PI/2) and StrictMath.tan(nextDown(PI/2)). - * - * @param angle Angle in radians. - * @return Angle tangent. - */ - public static double tan(double angle) { - if (USE_JDK_MATH) { - return Math.tan(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle > TAN_MAX_VALUE_FOR_INT_MODULO) { - angle = remainderPi(angle); - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } - // index: possibly outside tables range. - int index = (int)(angle * TAN_INDEXER + 0.5); - double delta = (angle - index * TAN_DELTA_HI) - index * TAN_DELTA_LO; - // Making sure index is within tables range. - // index modulo PI, i.e. 2*(virtual tab size minus one). - index &= (2*(TAN_VIRTUAL_TABS_SIZE-1)-1); // index % (2*(TAN_VIRTUAL_TABS_SIZE-1)) - // Here, index is in [0,2*(TAN_VIRTUAL_TABS_SIZE-1)-1], i.e. indicates an angle in [0,PI[. - if (index > (TAN_VIRTUAL_TABS_SIZE-1)) { - index = (2*(TAN_VIRTUAL_TABS_SIZE-1)) - index; - delta = -delta; - negateResult = !negateResult; - } - double result; - if (index < TAN_TABS_SIZE) { - result = MyTTan.tanTab[index] - + delta * (MyTTan.tanDer1DivF1Tab[index] - + delta * (MyTTan.tanDer2DivF2Tab[index] - + delta * (MyTTan.tanDer3DivF3Tab[index] - + delta * MyTTan.tanDer4DivF4Tab[index]))); - } else { // angle in ]TAN_MAX_VALUE_FOR_TABS,TAN_MAX_VALUE_FOR_INT_MODULO], or angle is NaN - // Using tan(angle) == 1/tan(PI/2-angle) formula: changing angle (index and delta), and inverting. - index = (TAN_VIRTUAL_TABS_SIZE-1) - index; - result = 1/(MyTTan.tanTab[index] - - delta * (MyTTan.tanDer1DivF1Tab[index] - - delta * (MyTTan.tanDer2DivF2Tab[index] - - delta * (MyTTan.tanDer3DivF3Tab[index] - - delta * MyTTan.tanDer4DivF4Tab[index])))); - } - return negateResult ? -result : result; - } - - /** - * @param value Value in [-1,1]. - * @return Value arcsine, in radians, in [-PI/2,PI/2]. - */ - public static double asin(double value) { - if (USE_JDK_MATH) { - return Math.asin(value); - } - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - if (value <= ASIN_MAX_VALUE_FOR_TABS) { - int index = (int)(value * ASIN_INDEXER + 0.5); - double delta = value - index * ASIN_DELTA; - double result = MyTAsin.asinTab[index] - + delta * (MyTAsin.asinDer1DivF1Tab[index] - + delta * (MyTAsin.asinDer2DivF2Tab[index] - + delta * (MyTAsin.asinDer3DivF3Tab[index] - + delta * MyTAsin.asinDer4DivF4Tab[index]))); - return negateResult ? -result : result; - } else if (USE_POWTABS_FOR_ASIN && (value <= ASIN_MAX_VALUE_FOR_POWTABS)) { - int index = (int)(powFast(value * ASIN_POWTABS_ONE_DIV_MAX_VALUE, ASIN_POWTABS_POWER) * ASIN_POWTABS_SIZE_MINUS_ONE + 0.5); - double delta = value - MyTAsinPow.asinParamPowTab[index]; - double result = MyTAsinPow.asinPowTab[index] - + delta * (MyTAsinPow.asinDer1DivF1PowTab[index] - + delta * (MyTAsinPow.asinDer2DivF2PowTab[index] - + delta * (MyTAsinPow.asinDer3DivF3PowTab[index] - + delta * MyTAsinPow.asinDer4DivF4PowTab[index]))); - return negateResult ? -result : result; - } else { // value > ASIN_MAX_VALUE_FOR_TABS, or value is NaN - // This part is derived from fdlibm. - if (value < 1.0) { - double t = (1.0 - value)*0.5; - double p = t*(ASIN_PS0+t*(ASIN_PS1+t*(ASIN_PS2+t*(ASIN_PS3+t*(ASIN_PS4+t*ASIN_PS5))))); - double q = 1.0+t*(ASIN_QS1+t*(ASIN_QS2+t*(ASIN_QS3+t*ASIN_QS4))); - double s = sqrt(t); - double z = s+s*(p/q); - double result = ASIN_PIO2_HI-((z+z)-ASIN_PIO2_LO); - return negateResult ? -result : result; - } else { // value >= 1.0, or value is NaN - if (value == 1.0) { - return negateResult ? -Math.PI/2 : Math.PI/2; - } else { - return Double.NaN; - } - } - } - } - - /** - * If value is not NaN and is outside [-1,1] range, closest value in this range is used. - * - * @param value Value in [-1,1]. - * @return Value arcsine, in radians, in [-PI/2,PI/2]. - */ - public static double asinInRange(double value) { - if (value <= -1.0) { - return -Math.PI/2; - } else if (value >= 1.0) { - return Math.PI/2; - } else { - return asin(value); - } - } - - /** - * @param value Value in [-1,1]. - * @return Value arccosine, in radians, in [0,PI]. - */ - public static double acos(double value) { - if (USE_JDK_MATH) { - return Math.acos(value); - } - return Math.PI/2 - asin(value); - } - - /** - * If value is not NaN and is outside [-1,1] range, - * closest value in this range is used. - * - * @param value Value in [-1,1]. - * @return Value arccosine, in radians, in [0,PI]. - */ - public static double acosInRange(double value) { - if (value <= -1.0) { - return Math.PI; - } else if (value >= 1.0) { - return 0.0; - } else { - return acos(value); - } - } - - /** - * @param value A double value. - * @return Value arctangent, in radians, in [-PI/2,PI/2]. - */ - public static double atan(double value) { - if (USE_JDK_MATH) { - return Math.atan(value); - } - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - if (value == 1.0) { - // We want "exact" result for 1.0. - return negateResult ? -Math.PI/4 : Math.PI/4; - } else if (value <= ATAN_MAX_VALUE_FOR_TABS) { - int index = (int)(value * ATAN_INDEXER + 0.5); - double delta = value - index * ATAN_DELTA; - double result = MyTAtan.atanTab[index] - + delta * (MyTAtan.atanDer1DivF1Tab[index] - + delta * (MyTAtan.atanDer2DivF2Tab[index] - + delta * (MyTAtan.atanDer3DivF3Tab[index] - + delta * MyTAtan.atanDer4DivF4Tab[index]))); - return negateResult ? -result : result; - } else { // value > ATAN_MAX_VALUE_FOR_TABS, or value is NaN - // This part is derived from fdlibm. - if (value < TWO_POW_66) { - double x = -1/value; - double x2 = x*x; - double x4 = x2*x2; - double s1 = x2*(ATAN_AT0+x4*(ATAN_AT2+x4*(ATAN_AT4+x4*(ATAN_AT6+x4*(ATAN_AT8+x4*ATAN_AT10))))); - double s2 = x4*(ATAN_AT1+x4*(ATAN_AT3+x4*(ATAN_AT5+x4*(ATAN_AT7+x4*ATAN_AT9)))); - double result = ATAN_HI3-((x*(s1+s2)-ATAN_LO3)-x); - return negateResult ? -result : result; - } else { // value >= 2^66, or value is NaN - if (value != value) { - return Double.NaN; - } else { - return negateResult ? -Math.PI/2 : Math.PI/2; - } - } - } - } - - /** - * For special values for which multiple conventions could be adopted, - * behaves like Math.atan2(double,double). - * - * @param y Coordinate on y axis. - * @param x Coordinate on x axis. - * @return Angle from x axis positive side to (x,y) position, in radians, in [-PI,PI]. - * Angle measure is positive when going from x axis to y axis (positive sides). - */ - public static double atan2(double y, double x) { - if (USE_JDK_MATH) { - return Math.atan2(y,x); - } - /* - * Using sub-methods, to make method lighter for general case, - * and to avoid JIT-optimization crash on NaN. - */ - if (x > 0.0) { - if (y == 0.0) { - // +-0.0 - return y; - } - if (x == Double.POSITIVE_INFINITY) { - return atan2_pinf_yyy(y); - } else { - return atan(y/x); - } - } else if (x < 0.0) { - if (y == 0.0) { - return signFromBit(y) * Math.PI; - } - if (x == Double.NEGATIVE_INFINITY) { - return atan2_ninf_yyy(y); - } else if (y > 0.0) { - return Math.PI/2 - atan(x/y); - } else if (y < 0.0) { - return -Math.PI/2 - atan(x/y); - } else { - return Double.NaN; - } - } else { - return atan2_yyy_zeroOrNaN(y, x); - } - } - - /** - * Gives same result as Math.toRadians for some particular values - * like 90.0, 180.0 or 360.0, but is faster (no division). - * - * @param angdeg Angle value in degrees. - * @return Angle value in radians. - */ - public static double toRadians(double angdeg) { - if (USE_JDK_MATH) { - return Math.toRadians(angdeg); - } - return angdeg * (Math.PI/180); - } - - /** - * Gives same result as Math.toDegrees for some particular values - * like Math.PI/2, Math.PI or 2*Math.PI, but is faster (no division). - * - * @param angrad Angle value in radians. - * @return Angle value in degrees. - */ - public static double toDegrees(double angrad) { - if (USE_JDK_MATH) { - return Math.toDegrees(angrad); - } - return angrad * (180/Math.PI); - } - - /** - * @param sign Sign of the angle: true for positive, false for negative. - * @param degrees Degrees, in [0,180]. - * @param minutes Minutes, in [0,59]. - * @param seconds Seconds, in [0.0,60.0[. - * @return Angle in radians. - */ - public static double toRadians(boolean sign, int degrees, int minutes, double seconds) { - return toRadians(toDegrees(sign, degrees, minutes, seconds)); - } - - /** - * @param sign Sign of the angle: true for positive, false for negative. - * @param degrees Degrees, in [0,180]. - * @param minutes Minutes, in [0,59]. - * @param seconds Seconds, in [0.0,60.0[. - * @return Angle in degrees. - */ - public static double toDegrees(boolean sign, int degrees, int minutes, double seconds) { - double signFactor = sign ? 1.0 : -1.0; - return signFactor * (degrees + (1.0/60)*(minutes + (1.0/60)*seconds)); - } - - /** - * @param angrad Angle in radians. - * @param degrees (out) Degrees, in [0,180]. - * @param minutes (out) Minutes, in [0,59]. - * @param seconds (out) Seconds, in [0.0,60.0[. - * @return true if the resulting angle in [-180deg,180deg] is positive, false if it is negative. - */ - public static boolean toDMS(double angrad, IntWrapper degrees, IntWrapper minutes, DoubleWrapper seconds) { - // Computing longitude DMS. - double tmp = toDegrees(normalizeMinusPiPi(angrad)); - boolean isNeg = (tmp < 0.0); - if (isNeg) { - tmp = -tmp; - } - degrees.value = (int)tmp; - tmp = (tmp-degrees.value)*60.0; - minutes.value = (int)tmp; - seconds.value = Math.min((tmp-minutes.value)*60.0,DOUBLE_BEFORE_60); - return !isNeg; - } - - /** - * NB: Since 2*Math.PI < 2*PI, a span of 2*Math.PI does not mean full angular range. - * ex.: isInClockwiseDomain(0.0, 2*Math.PI, -1e-20) returns false. - * ---> For full angular range, use a span > 2*Math.PI, like 2*PI_SUP constant of this class. - * - * @param startAngRad An angle, in radians. - * @param angSpanRad An angular span, >= 0.0, in radians. - * @param angRad An angle, in radians. - * @return true if angRad is in the clockwise angular domain going from startAngRad, over angSpanRad, - * extremities included, false otherwise. - */ - public static boolean isInClockwiseDomain(double startAngRad, double angSpanRad, double angRad) { - if (Math.abs(angRad) < -TWO_MATH_PI_IN_MINUS_PI_PI) { - // special case for angular values of small magnitude - if (angSpanRad <= 2*Math.PI) { - if (angSpanRad < 0.0) { - // empty domain - return false; - } - // angSpanRad is in [0,2*PI] - startAngRad = normalizeMinusPiPi(startAngRad); - double endAngRad = normalizeMinusPiPi(startAngRad + angSpanRad); - if (startAngRad <= endAngRad) { - return (angRad >= startAngRad) && (angRad <= endAngRad); - } else { - return (angRad >= startAngRad) || (angRad <= endAngRad); - } - } else { // angSpanRad > 2*Math.PI, or is NaN - return (angSpanRad == angSpanRad); - } - } else { - // general case - return (normalizeZeroTwoPi(angRad - startAngRad) <= angSpanRad); - } - } - - /* - * hyperbolic trigonometry - */ - - /** - * Some properties of sinh(x) = (exp(x)-exp(-x))/2: - * 1) defined on ]-Infinity,+Infinity[ - * 2) result in ]-Infinity,+Infinity[ - * 3) sinh(x) = -sinh(-x) (implies sinh(0) = 0) - * 4) sinh(epsilon) ~= epsilon - * 5) lim(sinh(x),x->+Infinity) = +Infinity - * (y increasing exponentially faster than x) - * 6) reaches +Infinity (double overflow) for x >= 710.475860073944, - * i.e. a bit further than exp(x) - * - * @param value A double value. - * @return Value hyperbolic sine. - */ - public static double sinh(double value) { - if (USE_JDK_MATH) { - return Math.sinh(value); - } - // sinh(x) = (exp(x)-exp(-x))/2 - double h; - if (value < 0.0) { - value = -value; - h = -0.5; - } else { - h = 0.5; - } - if (value < 22.0) { - if (value < TWO_POW_N28) { - return (h < 0.0) ? -value : value; - } else { - // sinh(x) - // = (exp(x)-exp(-x))/2 - // = (exp(x)-1/exp(x))/2 - // = (expm1(x) + 1 - 1/(expm1(x)+1))/2 - // = (expm1(x) + (expm1(x)+1)/(expm1(x)+1) - 1/(expm1(x)+1))/2 - // = (expm1(x) + expm1(x)/(expm1(x)+1))/2 - double t = expm1(value); - // Might be more accurate, if value < 1: return h*((t+t)-t*t/(t+1.0)). - return h * (t + t/(t+1.0)); - } - } else if (value < LOG_DOUBLE_MAX_VALUE) { - return h * exp(value); - } else { - double t = exp(value*0.5); - return (h*t)*t; - } - } - - /** - * Some properties of cosh(x) = (exp(x)+exp(-x))/2: - * 1) defined on ]-Infinity,+Infinity[ - * 2) result in [1,+Infinity[ - * 3) cosh(0) = 1 - * 4) cosh(x) = cosh(-x) - * 5) lim(cosh(x),x->+Infinity) = +Infinity - * (y increasing exponentially faster than x) - * 6) reaches +Infinity (double overflow) for x >= 710.475860073944, - * i.e. a bit further than exp(x) - * - * @param value A double value. - * @return Value hyperbolic cosine. - */ - public static double cosh(double value) { - if (USE_JDK_MATH) { - return Math.cosh(value); - } - // cosh(x) = (exp(x)+exp(-x))/2 - if (value < 0.0) { - value = -value; - } - if (value < LOG_TWO_POW_27) { - if (value < TWO_POW_N27) { - // cosh(x) - // = (exp(x)+exp(-x))/2 - // = ((1+x+x^2/2!+...) + (1-x+x^2/2!-...))/2 - // = 1+x^2/2!+x^4/4!+... - // For value of x small in magnitude, the sum of the terms does not add to 1. - return 1; - } else { - // cosh(x) - // = (exp(x)+exp(-x))/2 - // = (exp(x)+1/exp(x))/2 - double t = exp(value); - return 0.5 * (t+1/t); - } - } else if (value < LOG_DOUBLE_MAX_VALUE) { - return 0.5 * exp(value); - } else { - double t = exp(value*0.5); - return (0.5*t)*t; - } - } - - /** - * Much more accurate than cosh(value)-1, - * for arguments (and results) close to zero. - * - * coshm1(-0.0) = -0.0, for homogeneity with - * acosh1p(-0.0) = -0.0. - * - * @param value A double value. - * @return Value hyperbolic cosine, minus 1. - */ - public static double coshm1(double value) { - // cosh(x)-1 = (exp(x)+exp(-x))/2 - 1 - if (value < 0.0) { - value = -value; - } - if (value < LOG_TWO_POW_27) { - if (value < TWO_POW_N27) { - if (value == 0.0) { - // +-0.0 - return value; - } - // Using (expm1(x)+expm1(-x))/2 - // is not accurate for tiny values, - // for expm1 results are of higher - // magnitude than the result and - // of different signs, such as their - // sum is not accurate. - // cosh(x) - 1 - // = (exp(x)+exp(-x))/2 - 1 - // = ((1+x+x^2/2!+...) + (1-x+x^2/2!-...))/2 - 1 - // = x^2/2!+x^4/4!+... - // ~= x^2 * (1/2 + x^2 * 1/24) - // = x^2 * 0.5 (since x < 2^-27) - return 0.5 * value*value; - } else { - // cosh(x) - 1 - // = (exp(x)+exp(-x))/2 - 1 - // = (exp(x)-1+exp(-x)-1)/2 - // = (expm1(x)+expm1(-x))/2 - return 0.5 * (expm1(value)+expm1(-value)); - } - } else if (value < LOG_DOUBLE_MAX_VALUE) { - return 0.5 * exp(value) - 1.0; - } else { - // No need to subtract 1 from result. - double t = exp(value*0.5); - return (0.5*t)*t; - } - } - - /** - * Computes hyperbolic sine and hyperbolic cosine together. - * - * @param value A double value. - * @param hcosine (out) Value hyperbolic cosine. - * @return Value hyperbolic sine. - */ - public static double sinhAndCosh(double value, DoubleWrapper hcosine) { - if (USE_JDK_MATH) { - hcosine.value = Math.cosh(value); - return Math.sinh(value); - } - // Mixup of sinh and cosh treatments: if you modify them, - // you might want to also modify this. - double h; - if (value < 0.0) { - value = -value; - h = -0.5; - } else { - h = 0.5; - } - final double hsine; - // LOG_TWO_POW_27 = 18.714973875118524 - if (value < LOG_TWO_POW_27) { // test from cosh - // sinh - if (value < TWO_POW_N28) { - hsine = (h < 0.0) ? -value : value; - } else { - double t = expm1(value); - hsine = h * (t + t/(t+1.0)); - } - // cosh - if (value < TWO_POW_N27) { - hcosine.value = 1; - } else { - double t = exp(value); - hcosine.value = 0.5 * (t+1/t); - } - } else if (value < 22.0) { // test from sinh - // Here, value is in [18.714973875118524,22.0[. - double t = expm1(value); - hsine = h * (t + t/(t+1.0)); - hcosine.value = 0.5 * (t+1.0); - } else { - if (value < LOG_DOUBLE_MAX_VALUE) { - hsine = h * exp(value); - } else { - double t = exp(value*0.5); - hsine = (h*t)*t; - } - hcosine.value = Math.abs(hsine); - } - return hsine; - } - - /** - * Some properties of tanh(x) = sinh(x)/cosh(x) = (exp(2*x)-1)/(exp(2*x)+1): - * 1) defined on ]-Infinity,+Infinity[ - * 2) result in ]-1,1[ - * 3) tanh(x) = -tanh(-x) (implies tanh(0) = 0) - * 4) tanh(epsilon) ~= epsilon - * 5) lim(tanh(x),x->+Infinity) = 1 - * 6) reaches 1 (double loss of precision) for x = 19.061547465398498 - * - * @param value A double value. - * @return Value hyperbolic tangent. - */ - public static double tanh(double value) { - if (USE_JDK_MATH) { - return Math.tanh(value); - } - // tanh(x) = sinh(x)/cosh(x) - // = (exp(x)-exp(-x))/(exp(x)+exp(-x)) - // = (exp(2*x)-1)/(exp(2*x)+1) - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - double z; - if (value < TANH_1_THRESHOLD) { - if (value < TWO_POW_N55) { - return negateResult ? -value*(1.0-value) : value*(1.0+value); - } else if (value >= 1) { - z = 1.0-2.0/(expm1(value+value)+2.0); - } else { - double t = expm1(-(value+value)); - z = -t/(t+2.0); - } - } else { - z = (value != value) ? Double.NaN : 1.0; - } - return negateResult ? -z : z; - } - - /** - * Some properties of asinh(x) = log(x + sqrt(x^2 + 1)) - * 1) defined on ]-Infinity,+Infinity[ - * 2) result in ]-Infinity,+Infinity[ - * 3) asinh(x) = -asinh(-x) (implies asinh(0) = 0) - * 4) asinh(epsilon) ~= epsilon - * 5) lim(asinh(x),x->+Infinity) = +Infinity - * (y increasing logarithmically slower than x) - * - * @param value A double value. - * @return Value hyperbolic arcsine. - */ - public static double asinh(double value) { - // asinh(x) = log(x + sqrt(x^2 + 1)) - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - double result; - // (about) smallest possible for - // non-log1p case to be accurate. - if (value < ASINH_LOG1P_THRESHOLD) { - // Around this range, FDLIBM uses - // log1p(value+value*value/(1+sqrt(value*value+1))), - // but it's slower, so we don't use it. - /* - * If x is close to zero, log argument is close to 1, - * so to avoid precision loss we use log1p(double), - * with - * (1+x)^p = 1 + p * x + (p*(p-1))/2! * x^2 + (p*(p-1)*(p-2))/3! * x^3 + ... - * (1+x)^p = 1 + p * x * (1 + (p-1)/2 * x * (1 + (p-2)/3 * x + ...) - * (1+x)^0.5 = 1 + 0.5 * x * (1 + (0.5-1)/2 * x * (1 + (0.5-2)/3 * x + ...) - * (1+x^2)^0.5 = 1 + 0.5 * x^2 * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...) - * x + (1+x^2)^0.5 = 1 + x * (1 + 0.5 * x * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...)) - * so - * asinh(x) = log1p(x * (1 + 0.5 * x * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...))) - */ - final double x = value; - final double x2 = x*x; - // Enough terms for good accuracy, - // given our threshold. - final double argLog1p = (x * - (1 + 0.5 * x - * (1 + (0.5-1)/2 * x2 - * (1 + (0.5-2)/3 * x2 - * (1 + (0.5-3)/4 * x2 - * (1 + (0.5-4)/5 * x2 - )))))); - result = log1p(argLog1p); - } else if (value < ASINH_ACOSH_SQRT_ELISION_THRESHOLD) { - // Around this range, FDLIBM uses - // log(2*value+1/(value+sqrt(value*value+1))), - // but it involves an additional division - // so we don't use it. - result = log(value + sqrt(value*value + 1.0)); - } else { - // log(2*value) would overflow for value > Double.MAX_VALUE/2, - // so we compute otherwise. - result = LOG_2 + log(value); - } - return negateResult ? -result : result; - } - - /** - * Some properties of acosh(x) = log(x + sqrt(x^2 - 1)): - * 1) defined on [1,+Infinity[ - * 2) result in ]0,+Infinity[ (by convention, since cosh(x) = cosh(-x)) - * 3) acosh(1) = 0 - * 4) acosh(1+epsilon) ~= log(1 + sqrt(2*epsilon)) ~= sqrt(2*epsilon) - * 5) lim(acosh(x),x->+Infinity) = +Infinity - * (y increasing logarithmically slower than x) - * - * @param value A double value. - * @return Value hyperbolic arccosine. - */ - public static double acosh(double value) { - if (!(value > 1.0)) { - // NaN, or value <= 1 - if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { - return (value < 1.0) ? Double.NaN : value - 1.0; - } else { - return (value == 1.0) ? 0.0 : Double.NaN; - } - } - double result; - if (value < ASINH_ACOSH_SQRT_ELISION_THRESHOLD) { - // Around this range, FDLIBM uses - // log(2*value-1/(value+sqrt(value*value-1))), - // but it involves an additional division - // so we don't use it. - result = log(value + sqrt(value*value - 1.0)); - } else { - // log(2*value) would overflow for value > Double.MAX_VALUE/2, - // so we compute otherwise. - result = LOG_2 + log(value); - } - return result; - } - - /** - * Much more accurate than acosh(1+value), - * for arguments (and results) close to zero. - * - * acosh1p(-0.0) = -0.0, for homogeneity with - * sqrt(-0.0) = -0.0, which looks about the same - * near 0. - * - * @param value A double value. - * @return Hyperbolic arccosine of (1+value). - */ - public static double acosh1p(double value) { - if (!(value > 0.0)) { - // NaN, or value <= 0. - // If value is -0.0, returning -0.0. - if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { - return (value < 0.0) ? Double.NaN : value; - } else { - return (value == 0.0) ? value : Double.NaN; - } - } - double result; - if (value < (ASINH_ACOSH_SQRT_ELISION_THRESHOLD-1)) { - // acosh(1+x) - // = log((1+x) + sqrt((1+x)^2 - 1)) - // = log(1 + x + sqrt(1 + 2*x + x^2 - 1)) - // = log1p(x + sqrt(2*x + x^2)) - // = log1p(x + sqrt(x * (2 + x)) - result = log1p(value + sqrt(value * (2 + value))); - } else { - result = LOG_2 + log(1+value); - } - return result; - } - - /** - * Some properties of atanh(x) = log((1+x)/(1-x))/2: - * 1) defined on ]-1,1[ - * 2) result in ]-Infinity,+Infinity[ - * 3) atanh(-1) = -Infinity (by continuity) - * 4) atanh(1) = +Infinity (by continuity) - * 5) atanh(epsilon) ~= epsilon - * 6) lim(atanh(x),x->1) = +Infinity - * - * @param value A double value. - * @return Value hyperbolic arctangent. - */ - public static double atanh(double value) { - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - double result; - if (!(value < 1.0)) { - // NaN, or value >= 1 - if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { - result = (value > 1.0) ? Double.NaN : Double.POSITIVE_INFINITY + value; - } else { - result = (value == 1.0) ? Double.POSITIVE_INFINITY : Double.NaN; - } - } else { - // For value < 0.5, FDLIBM uses - // 0.5 * log1p((value+value) + (value+value)*value/(1-value)), - // instead, but this is good enough for us. - // atanh(x) - // = log((1+x)/(1-x))/2 - // = log((1-x+2x)/(1-x))/2 - // = log1p(2x/(1-x))/2 - result = 0.5 * log1p((value+value)/(1.0-value)); - } - return negateResult ? -result : result; - } - - /* - * exponentials - */ - - /** - * @param value A double value. - * @return e^value. - */ - public static double exp(double value) { - if (USE_JDK_MATH) { - return Math.exp(value); - } - // exp(x) = exp([x])*exp(y) - // with [x] the integer part of x, and y = x-[x] - // ===> - // We find an approximation of y, called z. - // ===> - // exp(x) = exp([x])*(exp(z)*exp(epsilon)) - // with epsilon = y - z - // ===> - // We have exp([x]) and exp(z) pre-computed in tables, we "just" have to compute exp(epsilon). - // - // We use the same indexing (cast to int) to compute x integer part and the - // table index corresponding to z, to avoid two int casts. - // Also, to optimize index multiplication and division, we use powers of two, - // so that we can do it with bits shifts. - - if (value > EXP_OVERFLOW_LIMIT) { - return Double.POSITIVE_INFINITY; - } else if (!(value >= EXP_UNDERFLOW_LIMIT)) { - return (value != value) ? Double.NaN : 0.0; - } - - final int indexes = (int)(value*EXP_LO_INDEXING); - - final int valueInt; - if (indexes >= 0) { - valueInt = (indexes>>EXP_LO_INDEXING_DIV_SHIFT); - } else { - valueInt = -((-indexes)>>EXP_LO_INDEXING_DIV_SHIFT); - } - final double hiTerm = MyTExp.expHiTab[valueInt-(int)EXP_UNDERFLOW_LIMIT]; - - final int zIndex = indexes - (valueInt< 0.0) { - if (value == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } - - // For normal values not close to 1.0, we use the following formula: - // log(value) - // = log(2^exponent*1.mantissa) - // = log(2^exponent) + log(1.mantissa) - // = exponent * log(2) + log(1.mantissa) - // = exponent * log(2) + log(1.mantissaApprox) + log(1.mantissa/1.mantissaApprox) - // = exponent * log(2) + log(1.mantissaApprox) + log(1+epsilon) - // = exponent * log(2) + log(1.mantissaApprox) + epsilon-epsilon^2/2+epsilon^3/3-epsilon^4/4+... - // with: - // 1.mantissaApprox <= 1.mantissa, - // log(1.mantissaApprox) in table, - // epsilon = (1.mantissa/1.mantissaApprox)-1 - // - // To avoid bad relative error for small results, - // values close to 1.0 are treated aside, with the formula: - // log(x) = z*(2+z^2*((2.0/3)+z^2*((2.0/5))+z^2*((2.0/7))+...))) - // with z=(x-1)/(x+1) - - double h; - if (value > 0.95) { - if (value < 1.14) { - double z = (value-1.0)/(value+1.0); - double z2 = z*z; - return z*(2+z2*((2.0/3)+z2*((2.0/5)+z2*((2.0/7)+z2*((2.0/9)+z2*((2.0/11))))))); - } - h = 0.0; - } else if (value < DOUBLE_MIN_NORMAL) { - // Ensuring value is normal. - value *= TWO_POW_52; - // log(x*2^52) - // = log(x)-ln(2^52) - // = log(x)-52*ln(2) - h = -52*LOG_2; - } else { - h = 0.0; - } - - int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); - int valueExp = (valueBitsHi>>20)-MAX_DOUBLE_EXPONENT; - // Getting the first LOG_BITS bits of the mantissa. - int xIndex = ((valueBitsHi<<12)>>>(32-LOG_BITS)); - - // 1.mantissa/1.mantissaApprox - 1 - double z = (value * twoPowNormalOrSubnormal(-valueExp)) * MyTLog.logXInvTab[xIndex] - 1; - - z *= (1-z*((1.0/2)-z*((1.0/3)))); - - return h + valueExp * LOG_2 + (MyTLog.logXLogTab[xIndex] + z); - - } else if (value == 0.0) { - return Double.NEGATIVE_INFINITY; - } else { // value < 0.0, or value is NaN - return Double.NaN; - } - } - - /** - * Quick log, with a max relative error of about 1.9e-3 - * for values in ]Double.MIN_NORMAL,+Infinity[, and - * worse accuracy outside this range. - * - * @param value A double value, in ]0,+Infinity[ (strictly positive and finite). - * @return Value logarithm (base e). - */ - public static double logQuick(double value) { - if (USE_JDK_MATH) { - return Math.log(value); - } - /* - * Inverse of Schraudolph's method for exp, is very inaccurate near 1, - * and not that fast (even using floats), especially with added if's - * to deal with values near 1, so we don't use it, and use a simplified - * version of our log's redefined algorithm. - */ - - // Simplified version of log's redefined algorithm: - // log(value) ~= exponent * log(2) + log(1.mantissaApprox) - - double h; - if (value > 0.87) { - if (value < 1.16) { - return 2.0 * (value-1.0)/(value+1.0); - } - h = 0.0; - } else if (value < DOUBLE_MIN_NORMAL) { - value *= TWO_POW_52; - h = -52*LOG_2; - } else { - h = 0.0; - } - - int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); - int valueExp = (valueBitsHi>>20)-MAX_DOUBLE_EXPONENT; - int xIndex = ((valueBitsHi<<12)>>>(32-LOG_BITS)); - - return h + valueExp * LOG_2 + MyTLog.logXLogTab[xIndex]; - } - - /** - * @param value A double value. - * @return Value logarithm (base 10). - */ - public static double log10(double value) { - if (USE_JDK_MATH || (!USE_REDEFINED_LOG)) { - return Math.log10(value); - } - // INV_LOG_10 is < 1, but there is no risk of log(double) - // overflow (positive or negative) while the end result shouldn't, - // since log(Double.MIN_VALUE) and log(Double.MAX_VALUE) have - // magnitudes of just a few hundreds. - return log(value) * INV_LOG_10; - } - - /** - * Much more accurate than log(1+value), - * for arguments (and results) close to zero. - * - * @param value A double value. - * @return Logarithm (base e) of (1+value). - */ - public static double log1p(double value) { - if (USE_JDK_MATH) { - return Math.log1p(value); - } - if (false) { - // This also works. Simpler but a bit slower. - if (value == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } - double valuePlusOne = 1+value; - if (valuePlusOne == 1.0) { - return value; - } else { - return log(valuePlusOne)*(value/(valuePlusOne-1.0)); - } - } - if (value > -1.0) { - if (value == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } - - // ln'(x) = 1/x - // so - // log(x+epsilon) ~= log(x) + epsilon/x - // - // Let u be 1+value rounded: - // 1+value = u+epsilon - // - // log(1+value) - // = log(u+epsilon) - // ~= log(u) + epsilon/value - // We compute log(u) as done in log(double), and then add the corrective term. - - double valuePlusOne = 1.0+value; - if (valuePlusOne == 1.0) { - return value; - } else if (Math.abs(value) < 0.15) { - double z = value/(value+2.0); - double z2 = z*z; - return z*(2+z2*((2.0/3)+z2*((2.0/5)+z2*((2.0/7)+z2*((2.0/9)+z2*((2.0/11))))))); - } - - int valuePlusOneBitsHi = (int)(Double.doubleToRawLongBits(valuePlusOne)>>32) & 0x7FFFFFFF; - int valuePlusOneExp = (valuePlusOneBitsHi>>20)-MAX_DOUBLE_EXPONENT; - // Getting the first LOG_BITS bits of the mantissa. - int xIndex = ((valuePlusOneBitsHi<<12)>>>(32-LOG_BITS)); - - // 1.mantissa/1.mantissaApprox - 1 - double z = (valuePlusOne * twoPowNormalOrSubnormal(-valuePlusOneExp)) * MyTLog.logXInvTab[xIndex] - 1; - - z *= (1-z*((1.0/2)-z*(1.0/3))); - - // Adding epsilon/valuePlusOne to z, - // with - // epsilon = value - (valuePlusOne-1) - // (valuePlusOne + epsilon ~= 1+value (not rounded)) - - return valuePlusOneExp * LOG_2 + MyTLog.logXLogTab[xIndex] + (z + (value - (valuePlusOne-1))/valuePlusOne); - } else if (value == -1.0) { - return Double.NEGATIVE_INFINITY; - } else { // value < -1.0, or value is NaN - return Double.NaN; - } - } - - /* - * powers - */ - - /** - * 1e-13ish accuracy or better on whole double range. - * - * @param value A double value. - * @param power A power. - * @return value^power. - */ - public static double pow(double value, double power) { - if (USE_JDK_MATH) { - return Math.pow(value,power); - } - if (power == 0.0) { - return 1.0; - } else if (power == 1.0) { - return value; - } - if (value <= 0.0) { - // powerInfo: 0 if not integer, 1 if even integer, -1 if odd integer - int powerInfo; - if (Math.abs(power) >= (TWO_POW_52*2)) { - // The binary digit just before comma is outside mantissa, - // thus it is always 0: power is an even integer. - powerInfo = 1; - } else { - // If power's magnitude permits, we cast into int instead of into long, - // as it is faster. - if (Math.abs(power) <= (double)Integer.MAX_VALUE) { - int powerAsInt = (int)power; - if (power == (double)powerAsInt) { - powerInfo = ((powerAsInt & 1) == 0) ? 1 : -1; - } else { // power is not an integer (and not NaN, due to test against Integer.MAX_VALUE) - powerInfo = 0; - } - } else { - long powerAsLong = (long)power; - if (power == (double)powerAsLong) { - powerInfo = ((powerAsLong & 1) == 0) ? 1 : -1; - } else { // power is not an integer, or is NaN - if (power != power) { - return Double.NaN; - } - powerInfo = 0; - } - } - } - - if (value == 0.0) { - if (power < 0.0) { - return (powerInfo < 0) ? 1/value : Double.POSITIVE_INFINITY; - } else { // power > 0.0 (0 and NaN cases already treated) - return (powerInfo < 0) ? value : 0.0; - } - } else { // value < 0.0 - if (value == Double.NEGATIVE_INFINITY) { - if (powerInfo < 0) { // power odd integer - return (power < 0.0) ? -0.0 : Double.NEGATIVE_INFINITY; - } else { // power even integer, or not an integer - return (power < 0.0) ? 0.0 : Double.POSITIVE_INFINITY; - } - } else { - return (powerInfo == 0) ? Double.NaN : powerInfo * exp(power*log(-value)); - } - } - } else { // value > 0.0, or value is NaN - return exp(power*log(value)); - } - } - - /** - * Quick pow, with a max relative error of about 1e-2 - * for value >= Double.MIN_NORMAL and 1e-10 < |value^power| < 1e10, - * of about 6e-2 for value >= Double.MIN_NORMAL and 1e-40 < |value^power| < 1e40, - * and worse accuracy otherwise. - * - * @param value A double value, in ]0,+Infinity[ (strictly positive and finite). - * @param power A double value. - * @return value^power. - */ - public static double powQuick(double value, double power) { - if (USE_JDK_MATH) { - return Math.pow(value,power); - } - return exp(power*logQuick(value)); - } - - /** - * This treatment is somehow accurate for low values of |power|, - * and for |power*getExponent(value)| < 1023 or so (to stay away - * from double extreme magnitudes (large and small)). - * - * @param value A double value. - * @param power A power. - * @return value^power. - */ - public static double powFast(double value, int power) { - if (USE_JDK_MATH) { - return Math.pow(value,power); - } - if (power < 3) { - if (power < 0) { - // Opposite of Integer.MIN_VALUE does not exist as int. - if (power == Integer.MIN_VALUE) { - // Integer.MAX_VALUE = -(power+1) - return 1.0/(powFast(value,Integer.MAX_VALUE) * value); - } else { - return 1.0/powFast(value,-power); - } - } else { - // Here, power is in [0,2]. - if (power == 2) { // Most common case first. - return value * value; - } else if (power == 0) { - return 1.0; - } else { // power == 1 - return value; - } - } - } else { // power >= 4 - double oddRemains = 1.0; - // If power <= 5, faster to finish outside the loop. - while (power > 5) { - // Test if power is odd. - if ((power & 1) != 0) { - oddRemains *= value; - } - value *= value; - power >>= 1; // power = power / 2 - } - // Here, power is in [3,5]. - if (power == 3) { - return oddRemains * value * value * value; - } else { // power in [4,5]. - double v2 = value * value; - if (power == 4) { - return oddRemains * v2 * v2; - } else { // power == 5 - return oddRemains * v2 * v2 * value; - } - } - } - } - - /** - * @param value A float value. - * @return value*value. - */ - public static float pow2(float value) { - return value*value; - } - - /** - * @param value A double value. - * @return value*value. - */ - public static double pow2(double value) { - return value*value; - } - - /** - * @param value A float value. - * @return value*value*value. - */ - public static float pow3(float value) { - return value*value*value; - } - - /** - * @param value A double value. - * @return value*value*value. - */ - public static double pow3(double value) { - return value*value*value; - } - - /* - * roots - */ - - /** - * @param value A double value. - * @return Value square root. - */ - public static double sqrt(double value) { - if (USE_JDK_MATH || (!USE_REDEFINED_SQRT)) { - return Math.sqrt(value); - } - // See cbrt for comments, sqrt uses the same ideas. - - if (!(value > 0.0)) { // value <= 0.0, or value is NaN - if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { - return (value < 0.0) ? Double.NaN : value; - } else { - return (value == 0.0) ? value : Double.NaN; - } - } else if (value == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } - - double h; - if (value < DOUBLE_MIN_NORMAL) { - value *= TWO_POW_52; - h = 2*TWO_POW_N26; - } else { - h = 2.0; - } - - int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); - int valueExponentIndex = (valueBitsHi>>20)+(-MAX_DOUBLE_EXPONENT-MIN_DOUBLE_EXPONENT); - int xIndex = ((valueBitsHi<<12)>>>(32-SQRT_LO_BITS)); - - double result = MyTSqrt.sqrtXSqrtHiTab[valueExponentIndex] * MyTSqrt.sqrtXSqrtLoTab[xIndex]; - double slope = MyTSqrt.sqrtSlopeHiTab[valueExponentIndex] * MyTSqrt.sqrtSlopeLoTab[xIndex]; - value *= 0.25; - - result += (value - result * result) * slope; - result += (value - result * result) * slope; - return h*(result + (value - result * result) * slope); - } - - /** - * Quick sqrt, with with a max relative error of about 3.41e-2 - * for values in [Double.MIN_NORMAL,Double.MAX_VALUE], and worse - * accuracy outside this range. - * - * @param value A double value. - * @return Value square root. - */ - public static double sqrtQuick(double value) { - if (USE_JDK_MATH) { - return Math.sqrt(value); - } - final long bits = Double.doubleToRawLongBits(value); - /* - * Constant determined empirically, using a random-based metaheuristic. - * Should be possible to find a better one. - */ - return Double.longBitsToDouble((bits+4606859074900000000L)>>>1); - } - - /** - * Quick inverse of square root, with a max relative error of about 3.44e-2 - * for values in [Double.MIN_NORMAL,Double.MAX_VALUE], and worse accuracy - * outside this range. - * - * This implementation uses zero step of Newton's method. - * Here are the max relative errors on [Double.MIN_NORMAL,Double.MAX_VALUE] - * depending on number of steps, if you want to copy-paste this code - * and use your own number: - * n=0: about 3.44e-2 - * n=1: about 1.75e-3 - * n=2: about 4.6e-6 - * n=3: about 3.17e-11 - * n=4: about 3.92e-16 - * n=5: about 3.03e-16 - * - * @param value A double value. - * @return Inverse of value square root. - */ - public static double invSqrtQuick(double value) { - if (USE_JDK_MATH) { - return 1/Math.sqrt(value); - } - /* - * http://en.wikipedia.org/wiki/Fast_inverse_square_root - */ - if (false) { - // With one Newton step (much slower than - // 1/Math.sqrt(double) if not optimized). - final double halfInitial = value * 0.5; - long bits = Double.doubleToRawLongBits(value); - // If n=0, 6910474759270000000L might be better (3.38e-2 max relative error). - bits = 0x5FE6EB50C7B537A9L - (bits>>1); - value = Double.longBitsToDouble(bits); - value = value * (1.5 - halfInitial * value * value); // Newton step, can repeat. - return value; - } else { - return Double.longBitsToDouble(0x5FE6EB50C7B537A9L - (Double.doubleToRawLongBits(value)>>1)); - } - } - - /** - * @param value A double value. - * @return Value cubic root. - */ - public static double cbrt(double value) { - if (USE_JDK_MATH) { - return Math.cbrt(value); - } - double h; - if (value < 0.0) { - if (value == Double.NEGATIVE_INFINITY) { - return Double.NEGATIVE_INFINITY; - } - value = -value; - // Making sure value is normal. - if (value < DOUBLE_MIN_NORMAL) { - value *= (TWO_POW_52*TWO_POW_26); - // h = * / - h = -2*TWO_POW_N26; - } else { - h = -2.0; - } - } else { - if (!(value < Double.POSITIVE_INFINITY)) { // value is +Infinity, or value is NaN - return value; - } - // Making sure value is normal. - if (value < DOUBLE_MIN_NORMAL) { - if (value == 0.0) { - // cbrt(0.0) = 0.0, cbrt(-0.0) = -0.0 - return value; - } - value *= (TWO_POW_52*TWO_POW_26); - h = 2*TWO_POW_N26; - } else { - h = 2.0; - } - } - - // Normal value is (2^ * ). - // First member cubic root is computed, and multiplied with an approximation - // of the cubic root of the second member, to end up with a good guess of - // the result before using Newton's (or Archimedes's) method. - // To compute the cubic root approximation, we use the formula "cbrt(value) = cbrt(x) * cbrt(value/x)", - // choosing x as close to value as possible but inferior to it, so that cbrt(value/x) is close to 1 - // (we could iterate on this method, using value/x as new value for each iteration, - // but finishing with Newton's method is faster). - - // Shift and cast into an int, which overall is faster than working with a long. - int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); - int valueExponentIndex = (valueBitsHi>>20)+(-MAX_DOUBLE_EXPONENT-MIN_DOUBLE_EXPONENT); - // Getting the first CBRT_LO_BITS bits of the mantissa. - int xIndex = ((valueBitsHi<<12)>>>(32-CBRT_LO_BITS)); - double result = MyTCbrt.cbrtXCbrtHiTab[valueExponentIndex] * MyTCbrt.cbrtXCbrtLoTab[xIndex]; - double slope = MyTCbrt.cbrtSlopeHiTab[valueExponentIndex] * MyTCbrt.cbrtSlopeLoTab[xIndex]; - - // Lowering values to avoid overflows when using Newton's method - // (we will then just have to return twice the result). - // result^3 = value - // (result/2)^3 = value/8 - value *= 0.125; - // No need to divide result here, as division is factorized in result computation tables. - // result *= 0.5; - - // Newton's method, looking for y = x^(1/p): - // y(n) = y(n-1) + (x-y(n-1)^p) * slope(y(n-1)) - // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(x(n-1)^(1/p-1)) - // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(x(n-1)^((1-p)/p)) - // with x(n-1)=y(n-1)^p, i.e.: - // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(y(n-1)^(1-p)) - // - // For p=3: - // y(n) = y(n-1) + (x-y(n-1)^3) * (1/(3*y(n-1)^2)) - - // To save time, we don't recompute the slope between Newton's method steps, - // as initial slope is good enough for a few iterations. - // - // NB: slope = 1/(3*trueResult*trueResult) - // As we have result = trueResult/2 (to avoid overflows), we have: - // slope = 4/(3*result*result) - // = (4/3)*resultInv*resultInv - // with newResultInv = 1/newResult - // = 1/(oldResult+resultDelta) - // = (oldResultInv)*1/(1+resultDelta/oldResult) - // = (oldResultInv)*1/(1+resultDelta*oldResultInv) - // ~= (oldResultInv)*(1-resultDelta*oldResultInv) - // ===> Successive slopes could be computed without division, if needed, - // by computing resultInv (instead of slope right away) and retrieving - // slopes from it. - - result += (value - result * result * result) * slope; - result += (value - result * result * result) * slope; - return h*(result + (value - result * result * result) * slope); - } - - /** - * @return sqrt(x^2+y^2) without intermediate overflow or underflow. - */ - public static double hypot(double x, double y) { - if (USE_JDK_MATH) { - return Math.hypot(x,y); - } - x = Math.abs(x); - y = Math.abs(y); - // Ensuring x <= y. - if (y < x) { - double a = x; - x = y; - y = a; - } else if (!(y >= x)) { // Testing if we have some NaN. - return hypot_NaN(x, y); - } - - if (y-x == y) { - // x too small to subtract from y. - return y; - } else { - double factor; - if (y > HYPOT_MAX_MAG) { - // y is too large: scaling down. - x *= (1/HYPOT_FACTOR); - y *= (1/HYPOT_FACTOR); - factor = HYPOT_FACTOR; - } else if (x < (1/HYPOT_MAX_MAG)) { - // x is too small: scaling up. - x *= HYPOT_FACTOR; - y *= HYPOT_FACTOR; - factor = (1/HYPOT_FACTOR); - } else { - factor = 1.0; - } - return factor * sqrt(x*x+y*y); - } - } - - /** - * @return sqrt(x^2+y^2+z^2) without intermediate overflow or underflow. - */ - public static double hypot(double x, double y, double z) { - if (USE_JDK_MATH) { - // No simple JDK equivalent. - } - x = Math.abs(x); - y = Math.abs(y); - z = Math.abs(z); - /* - * Considering that z magnitude is the most likely to be the smaller, - * hence ensuring z <= y <= x, and not x <= y <= z, for less swaps. - */ - // Ensuring z <= y. - if (z > y) { - // y < z: swapping y and z - double a = z; - z = y; - y = a; - } else if (!(z <= y)) { // Testing if y or z is NaN. - return hypot_NaN(x, y, z); - } - // Ensuring y <= x. - if (z > x) { - // x < z <= y: moving x - double oldZ = z; - z = x; - double oldY = y; - y = oldZ; - x = oldY; - } else if (y > x) { - // z <= x < y: swapping x and y - double a = y; - y = x; - x = a; - } else if (x != x) { // Testing if x is NaN. - return hypot_NaN(x, y, z); - } - - if (x-y == x) { - // y, hence z, too small to subtract from x. - return x; - } else if (y-z == y) { - // z too small to subtract from y, hence x. - double factor; - if (x > HYPOT_MAX_MAG) { - // x is too large: scaling down. - x *= (1/HYPOT_FACTOR); - y *= (1/HYPOT_FACTOR); - factor = HYPOT_FACTOR; - } else if (y < (1/HYPOT_MAX_MAG)) { - // y is too small: scaling up. - x *= HYPOT_FACTOR; - y *= HYPOT_FACTOR; - factor = (1/HYPOT_FACTOR); - } else { - factor = 1.0; - } - return factor * sqrt(x*x+y*y); - } else { - double factor; - if (x > HYPOT_MAX_MAG) { - // x is too large: scaling down. - x *= (1/HYPOT_FACTOR); - y *= (1/HYPOT_FACTOR); - z *= (1/HYPOT_FACTOR); - factor = HYPOT_FACTOR; - } else if (z < (1/HYPOT_MAX_MAG)) { - // z is too small: scaling up. - x *= HYPOT_FACTOR; - y *= HYPOT_FACTOR; - z *= HYPOT_FACTOR; - factor = (1/HYPOT_FACTOR); - } else { - factor = 1.0; - } - // Adding smaller magnitudes together first. - return factor * sqrt(x*x+(y*y+z*z)); - } - } - - /* - * close values - */ - - /** - * @param value A float value. - * @return Floor of value. - */ - public static float floor(float value) { - final int exponent = getExponent(value); - if (exponent < 0) { - // abs(value) < 1. - if (value < 0.0f) { - return -1.0f; - } else { - // 0.0f, or -0.0f if value is -0.0f - return 0.0f * value; - } - } else if (exponent < 23) { - // A bit faster than using casts. - final int bits = Float.floatToRawIntBits(value); - final int anteCommaBits = bits & (0xFF800000>>exponent); - if ((value < 0.0f) && (anteCommaBits != bits)) { - return Float.intBitsToFloat(anteCommaBits) - 1.0f; - } else { - return Float.intBitsToFloat(anteCommaBits); - } - } else { - // +-Infinity, NaN, or a mathematical integer. - return value; - } - } - - /** - * @param value A double value. - * @return Floor of value. - */ - public static double floor(double value) { - if (USE_JDK_MATH) { - return Math.floor(value); - } - if (ANTI_SLOW_CASTS) { - double valueAbs = Math.abs(value); - if (valueAbs <= (double)Integer.MAX_VALUE) { - if (value > 0.0) { - return (double)(int)value; - } else if (value < 0.0) { - double anteCommaDigits = (double)(int)value; - if (value != anteCommaDigits) { - return anteCommaDigits - 1.0; - } else { - return anteCommaDigits; - } - } else { // value is +-0.0 (not NaN due to test against Integer.MAX_VALUE) - return value; - } - } else if (valueAbs < TWO_POW_52) { - // We split the value in two: - // high part, which is a mathematical integer, - // and the rest, for which we can get rid of the - // post comma digits by casting into an int. - double highPart = ((int)(value * TWO_POW_N26)) * TWO_POW_26; - if (value > 0.0) { - return highPart + (double)((int)(value - highPart)); - } else { - double anteCommaDigits = highPart + (double)((int)(value - highPart)); - if (value != anteCommaDigits) { - return anteCommaDigits - 1.0; - } else { - return anteCommaDigits; - } - } - } else { // abs(value) >= 2^52, or value is NaN - return value; - } - } else { - final int exponent = getExponent(value); - if (exponent < 0) { - // abs(value) < 1. - if (value < 0.0) { - return -1.0; - } else { - // 0.0, or -0.0 if value is -0.0 - return 0.0 * value; - } - } else if (exponent < 52) { - // A bit faster than working on bits. - final long matIntPart = (long)value; - final double matIntToValue = value-(double)matIntPart; - if (matIntToValue >= 0.0) { - return (double)matIntPart; - } else { - return (double)(matIntPart - 1); - } - } else { - // +-Infinity, NaN, or a mathematical integer. - return value; - } - } - } - - /** - * @param value A float value. - * @return Ceiling of value. - */ - public static float ceil(float value) { - return -floor(-value); - } - - /** - * @param value A double value. - * @return Ceiling of value. - */ - public static double ceil(double value) { - if (USE_JDK_MATH) { - return Math.ceil(value); - } - return -floor(-value); - } - - /** - * Might have different semantics than Math.round(float), - * see bugs 6430675 and 8010430. - * - * @param value A double value. - * @return Value rounded to nearest int, choosing superior int in case two - * are equally close (i.e. rounding-up). - */ - public static int round(float value) { - /* - * Not delegating to JDK, because we want delegation to provide - * at least as good results, and some supported JDK versions - * have bugged round() methods. - */ - // Algorithm by Dmitry Nadezhin (but replaced an if by a multiply) - // (http://mail.openjdk.java.net/pipermail/core-libs-dev/2013-August/020247.html). - final int bits = Float.floatToRawIntBits(value); - final int biasedExp = ((bits>>23)&0xFF); - // Shift to get rid of bits past comma except first one: will need to - // 1-shift to the right to end up with correct magnitude. - final int shift = (23 - 1 + MAX_FLOAT_EXPONENT) - biasedExp; - if ((shift & -32) == 0) { - int bitsSignum = (((bits >> 31) << 1) + 1); - // shift in [0,31], so unbiased exp in [-9,22]. - int extendedMantissa = (0x00800000 | (bits & 0x007FFFFF)) * bitsSignum; - // If value is positive and first bit past comma is 0, rounding - // to lower integer, else to upper one, which is what "+1" and - // then ">>1" do. - return ((extendedMantissa >> shift) + 1) >> 1; - } else { - // +-Infinity, NaN, or a mathematical integer, or tiny. - if (false && ANTI_SLOW_CASTS) { // not worth it - if (Math.abs(value) >= -(float)Integer.MIN_VALUE) { - // +-Infinity or a mathematical integer (mostly) out of int range. - return (value < 0.0) ? Integer.MIN_VALUE : Integer.MAX_VALUE; - } - // NaN or a mathematical integer (mostly) in int range. - } - return (int)value; - } - } - - /** - * Might have different semantics than Math.round(double), - * see bugs 6430675 and 8010430. - * - * @param value A double value. - * @return Value rounded to nearest long, choosing superior long in case two - * are equally close (i.e. rounding-up). - */ - public static long round(double value) { - /* - * Not delegating to JDK, because we want delegation to provide - * at least as good results, and some supported JDK versions - * have bugged round() methods. - */ - final long bits = Double.doubleToRawLongBits(value); - final int biasedExp = (((int)(bits>>52))&0x7FF); - // Shift to get rid of bits past comma except first one: will need to - // 1-shift to the right to end up with correct magnitude. - final int shift = (52 - 1 + MAX_DOUBLE_EXPONENT) - biasedExp; - if ((shift & -64) == 0) { - long bitsSignum = (((bits >> 63) << 1) + 1); - // shift in [0,63], so unbiased exp in [-12,51]. - long extendedMantissa = (0x0010000000000000L | (bits & 0x000FFFFFFFFFFFFFL)) * bitsSignum; - // If value is positive and first bit past comma is 0, rounding - // to lower integer, else to upper one, which is what "+1" and - // then ">>1" do. - return ((extendedMantissa >> shift) + 1L) >> 1; - } else { - // +-Infinity, NaN, or a mathematical integer, or tiny. - if (ANTI_SLOW_CASTS) { - if (Math.abs(value) >= -(double)Long.MIN_VALUE) { - // +-Infinity or a mathematical integer (mostly) out of long range. - return (value < 0.0) ? Long.MIN_VALUE : Long.MAX_VALUE; - } - // NaN or a mathematical integer (mostly) in long range. - } - return (long)value; - } - } - - /** - * @param value A float value. - * @return Value rounded to nearest int, choosing even int in case two - * are equally close. - */ - public static int roundEven(float value) { - final int sign = signFromBit(value); - value = Math.abs(value); - if (ANTI_SLOW_CASTS) { - if (value < TWO_POW_23_F) { - // Getting rid of post-comma bits. - value = ((value + TWO_POW_23_F) - TWO_POW_23_F); - return sign * (int)value; - } else if (value < (float)Integer.MAX_VALUE) { // "<=" doesn't work, because of float precision - // value is in [-Integer.MAX_VALUE,Integer.MAX_VALUE] - return sign * (int)value; - } - } else { - if (value < TWO_POW_23_F) { - // Getting rid of post-comma bits. - value = ((value + TWO_POW_23_F) - TWO_POW_23_F); - } - } - return (int)(sign * value); - } - - /** - * @param value A double value. - * @return Value rounded to nearest long, choosing even long in case two - * are equally close. - */ - public static long roundEven(double value) { - final int sign = (int)signFromBit(value); - value = Math.abs(value); - if (value < TWO_POW_52) { - // Getting rid of post-comma bits. - value = ((value + TWO_POW_52) - TWO_POW_52); - } - if (ANTI_SLOW_CASTS) { - if (value <= (double)Integer.MAX_VALUE) { - // value is in [-Integer.MAX_VALUE,Integer.MAX_VALUE] - return sign * (int)value; - } - } - return (long)(sign * value); - } - - /** - * @param value A float value. - * @return The float mathematical integer closest to the specified value, - * choosing even one if two are equally close, or respectively - * NaN, +-Infinity or +-0.0f if the value is any of these. - */ - public static float rint(float value) { - final int sign = signFromBit(value); - value = Math.abs(value); - if (value < TWO_POW_23_F) { - // Getting rid of post-comma bits. - value = ((TWO_POW_23_F + value ) - TWO_POW_23_F); - } - // Restoring original sign. - return sign * value; - } - - /** - * @param value A double value. - * @return The double mathematical integer closest to the specified value, - * choosing even one if two are equally close, or respectively - * NaN, +-Infinity or +-0.0 if the value is any of these. - */ - public static double rint(double value) { - if (USE_JDK_MATH) { - return Math.rint(value); - } - final int sign = (int)signFromBit(value); - value = Math.abs(value); - if (value < TWO_POW_52) { - // Getting rid of post-comma bits. - value = ((TWO_POW_52 + value ) - TWO_POW_52); - } - // Restoring original sign. - return sign * value; - } - - /* - * close int values - * - * Never delegating to JDK for these methods, for we should always - * be faster and exact, and JDK doesn't exactly have such methods. - */ - - /** - * @param value A double value. - * @return Floor of value as int, or closest int if floor is out - * of int range, or 0 if value is NaN. - */ - public static int floorToInt(double value) { - int valueInt = (int) value; - if (value < 0.0) { - if (value == (double) valueInt) { - return valueInt; - } else { - if (valueInt == Integer.MIN_VALUE) { - return valueInt; - } else { - return valueInt - 1; - } - } - } else { // >= 0 or NaN. - return valueInt; - } - } - - /** - * @param value A double value. - * @return Ceiling of value as int, or closest int if ceiling is out - * of int range, or 0 if value is NaN. - */ - public static int ceilToInt(double value) { - int valueInt = (int) value; - if (value > 0.0) { - if (value == (double) valueInt) { - return valueInt; - } else { - if (valueInt == Integer.MAX_VALUE) { - return valueInt; - } else { - return valueInt + 1; - } - } - } else { // <= 0 or NaN. - return valueInt; - } - } - - /** - * @param value A double value. - * @return Value rounded to nearest int, choosing superior int in case two - * are equally close (i.e. rounding-up). - */ - public static int roundToInt(double value) { - /* - * We don't gain much by reimplementing rounding, except for - * pathologically large values, which should not be a common case - * when dealing with ints, so we just use round(double). - */ - return NumbersUtils.toInt(round(value)); - } - - /** - * @param value A double value. - * @return Value rounded to nearest int, choosing even int in case two - * are equally close. - */ - public static int roundEvenToInt(double value) { - final int sign = (int)signFromBit(value); - value = Math.abs(value); - /* - * Applying the post-comma bits removal logic even if value is out - * of int range, to avoid a test, for it doesn't mess up the result, - * and we want to optimize for the case of values in int range. - */ - value = ((value + TWO_POW_52) - TWO_POW_52); - return (int)(sign * value); - } - - /* - * ranges - */ - - /** - * @param min A float value. - * @param max A float value. - * @param value A float value. - * @return min if value < min, max if value > max, value otherwise. - */ - public static float toRange(float min, float max, float value) { - return NumbersUtils.toRange(min, max, value); - } - - /** - * @param min A double value. - * @param max A double value. - * @param value A double value. - * @return min if value < min, max if value > max, value otherwise. - */ - public static double toRange(double min, double max, double value) { - return NumbersUtils.toRange(min, max, value); - } - - /* - * binary operators (/,%) - */ - - /** - * Returns dividend - divisor * n, where n is the mathematical integer - * closest to dividend/divisor. - * If dividend/divisor is equally close to surrounding integers, - * we choose n to be the integer of smallest magnitude, which makes - * this treatment differ from Math.IEEEremainder(double,double), - * where n is chosen to be the even integer. - * Note that the choice of n is not done considering the double - * approximation of dividend/divisor, because it could cause - * result to be outside [-|divisor|/2,|divisor|/2] range. - * The practical effect is that if multiple results would be possible, - * we always choose the result that is the closest to (and has the same - * sign as) the dividend. - * Ex. : - * - for (-3.0,2.0), this method returns -1.0, - * whereas Math.IEEEremainder returns 1.0. - * - for (-5.0,2.0), both this method and Math.IEEEremainder return -1.0. - * - * If the remainder is zero, its sign is the same as the sign of the first argument. - * If either argument is NaN, or the first argument is infinite, - * or the second argument is positive zero or negative zero, - * then the result is NaN. - * If the first argument is finite and the second argument is - * infinite, then the result is the same as the first argument. - * - * NB: - * - Modulo operator (%) returns a value in ]-|divisor|,|divisor|[, - * which sign is the same as dividend. - * - As for modulo operator, the sign of the divisor has no effect on the result. - * - On some architecture, % operator has been observed to return NaN - * for some subnormal values of divisor, when dividend exponent is 1023, - * which impacts the correctness of this method. - * - * @param dividend Dividend. - * @param divisor Divisor. - * @return Remainder of dividend/divisor, i.e. a value in [-|divisor|/2,|divisor|/2]. - */ - public static double remainder(double dividend, double divisor) { - if (Double.isInfinite(divisor)) { - if (Double.isInfinite(dividend)) { - return Double.NaN; - } else { - return dividend; - } - } - double value = dividend % divisor; - if (Math.abs(value+value) > Math.abs(divisor)) { - return value + ((value > 0.0) ? -Math.abs(divisor) : Math.abs(divisor)); - } else { - return value; - } - } - - /** - * @param angle Angle in radians. - * @return The same angle, in radians, but in [-PI,PI]. - */ - public static double normalizeMinusPiPi(double angle) { - // Not modifying values in output range. - if ((angle >= -Math.PI) && (angle <= Math.PI)) { - return angle; - } - return remainderTwoPi(angle); - } - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return The same angle, in radians, but in [-PI,PI]. - */ - public static double normalizeMinusPiPiFast(double angle) { - // Not modifying values in output range. - if ((angle >= -Math.PI) && (angle <= Math.PI)) { - return angle; - } - return remainderTwoPiFast(angle); - } - - /** - * @param angle Angle in radians. - * @return The same angle, in radians, but in [0,2*PI]. - */ - public static double normalizeZeroTwoPi(double angle) { - // Not modifying values in output range. - if ((angle >= 0.0) && (angle <= 2*Math.PI)) { - return angle; - } - angle = remainderTwoPi(angle); - if (angle < 0.0) { - // LO then HI is theoretically better (when starting near 0). - return (angle + TWOPI_LO) + TWOPI_HI; - } else { - return angle; - } - } - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return The same angle, in radians, but in [0,2*PI]. - */ - public static double normalizeZeroTwoPiFast(double angle) { - // Not modifying values in output range. - if ((angle >= 0.0) && (angle <= 2*Math.PI)) { - return angle; - } - angle = remainderTwoPiFast(angle); - if (angle < 0.0) { - // LO then HI is theoretically better (when starting near 0). - return (angle + TWOPI_LO) + TWOPI_HI; - } else { - return angle; - } - } - - /** - * @param angle Angle in radians. - * @return Angle value modulo PI, in radians, in [-PI/2,PI/2]. - */ - public static double normalizeMinusHalfPiHalfPi(double angle) { - // Not modifying values in output range. - if ((angle >= -Math.PI/2) && (angle <= Math.PI/2)) { - return angle; - } - return remainderPi(angle); - } - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return Angle value modulo PI, in radians, in [-PI/2,PI/2]. - */ - public static double normalizeMinusHalfPiHalfPiFast(double angle) { - // Not modifying values in output range. - if ((angle >= -Math.PI/2) && (angle <= Math.PI/2)) { - return angle; - } - return remainderPiFast(angle); - } - - /* - * floating points utils - */ - - /** - * @param value A float value. - * @return true if the specified value is NaN or +-Infinity, false otherwise. - */ - public static boolean isNaNOrInfinite(float value) { - return NumbersUtils.isNaNOrInfinite(value); - } - - /** - * @param value A double value. - * @return true if the specified value is NaN or +-Infinity, false otherwise. - */ - public static boolean isNaNOrInfinite(double value) { - return NumbersUtils.isNaNOrInfinite(value); - } - - /** - * @param value A float value. - * @return Value unbiased exponent. - */ - public static int getExponent(float value) { - return ((Float.floatToRawIntBits(value)>>23)&0xFF)-MAX_FLOAT_EXPONENT; - } - - /** - * @param value A double value. - * @return Value unbiased exponent. - */ - public static int getExponent(double value) { - return (((int)(Double.doubleToRawLongBits(value)>>52))&0x7FF)-MAX_DOUBLE_EXPONENT; - } - - /** - * @param value A float value. - * @return -1.0f if the specified value is < 0, 1.0f if it is > 0, - * and the value itself if it is NaN or +-0.0f. - */ - public static float signum(float value) { - if (USE_JDK_MATH) { - return Math.signum(value); - } - if ((value == 0.0f) || (value != value)) { - return value; - } - return (float)signFromBit(value); - } - - /** - * @param value A double value. - * @return -1.0 if the specified value is < 0, 1.0 if it is > 0, - * and the value itself if it is NaN or +-0.0. - */ - public static double signum(double value) { - if (USE_JDK_MATH) { - return Math.signum(value); - } - if ((value == 0.0) || (value != value)) { - return value; - } - if (ANTI_SLOW_CASTS) { - return (double)(int)signFromBit(value); - } else { - return (double)signFromBit(value); - } - } - - /** - * @param value A float value. - * @return -1 if sign bit is 1, 1 if sign bit is 0. - */ - public static int signFromBit(float value) { - return ((Float.floatToRawIntBits(value)>>30)|1); - } - - /** - * @param value A double value. - * @return -1 if sign bit is 1, 1 if sign bit is 0. - */ - public static long signFromBit(double value) { - // Returning a long, to avoid useless cast into int. - return ((Double.doubleToRawLongBits(value)>>62)|1); - } - - /** - * A sign of NaN can be interpreted as positive or negative. - * - * @param magnitude A float value. - * @param sign A float value. - * @return A value with the magnitude of the first argument, and the sign - * of the second argument. - */ - public static float copySign(float magnitude, float sign) { - return Float.intBitsToFloat( - (Float.floatToRawIntBits(sign) & Integer.MIN_VALUE) - | (Float.floatToRawIntBits(magnitude) & Integer.MAX_VALUE)); - } - - /** - * A sign of NaN can be interpreted as positive or negative. - * - * @param magnitude A double value. - * @param sign A double value. - * @return A value with the magnitude of the first argument, and the sign - * of the second argument. - */ - public static double copySign(double magnitude, double sign) { - return Double.longBitsToDouble( - (Double.doubleToRawLongBits(sign) & Long.MIN_VALUE) - | (Double.doubleToRawLongBits(magnitude) & Long.MAX_VALUE)); - } - - /** - * The ULP (Unit in the Last Place) is the distance to the next value larger - * in magnitude. - * - * @param value A float value. - * @return The size of an ulp of the specified value, or Float.MIN_VALUE - * if it is +-0.0f, or +Infinity if it is +-Infinity, or NaN - * if it is NaN. - */ - public static float ulp(float value) { - if (USE_JDK_MATH) { - return Math.ulp(value); - } - /* - * Look-up table not really worth it in micro-benchmark, - * so should be worse with cache-misses. - */ - final int exponent = getExponent(value); - if (exponent >= (MIN_FLOAT_NORMAL_EXPONENT+23)) { - if (exponent == MAX_FLOAT_EXPONENT+1) { - // NaN or +-Infinity - return Math.abs(value); - } - // normal: returning 2^(exponent-23) - return Float.intBitsToFloat((exponent+(MAX_FLOAT_EXPONENT-23))<<23); - } else { - if (exponent == MIN_FLOAT_NORMAL_EXPONENT-1) { - // +-0.0f or subnormal - return Float.MIN_VALUE; - } - // subnormal result - return Float.intBitsToFloat(1<<(exponent-MIN_FLOAT_NORMAL_EXPONENT)); - } - } - - /** - * The ULP (Unit in the Last Place) is the distance to the next value larger - * in magnitude. - * - * @param value A double value. - * @return The size of an ulp of the specified value, or Double.MIN_VALUE - * if it is +-0.0, or +Infinity if it is +-Infinity, or NaN - * if it is NaN. - */ - public static double ulp(double value) { - if (USE_JDK_MATH) { - return Math.ulp(value); - } - /* - * Look-up table not really worth it in micro-benchmark, - * so should be worse with cache-misses. - */ - final int exponent = getExponent(value); - if (exponent >= (MIN_DOUBLE_NORMAL_EXPONENT+52)) { - if (exponent == MAX_DOUBLE_EXPONENT+1) { - // NaN or +-Infinity - return Math.abs(value); - } - // normal: returning 2^(exponent-52) - return Double.longBitsToDouble((exponent+(MAX_DOUBLE_EXPONENT-52L))<<52); - } else { - if (exponent == MIN_DOUBLE_NORMAL_EXPONENT-1) { - // +-0.0f or subnormal - return Double.MIN_VALUE; - } - // subnormal result - return Double.longBitsToDouble(1L<<(exponent-MIN_DOUBLE_NORMAL_EXPONENT)); - } - } - - /** - * If both arguments are +-0.0(f), (float)direction is returned. - * - * If both arguments are +Infinity or -Infinity, - * respectively +Infinity or -Infinity is returned. - * - * @param start A float value. - * @param direction A double value. - * @return The float adjacent to start towards direction, considering that - * +(-)Float.MIN_VALUE is adjacent to +(-)0.0f, and that - * +(-)Float.MAX_VALUE is adjacent to +(-)Infinity, - * or NaN if any argument is NaN. - */ - public static float nextAfter(float start, double direction) { - if (direction < start) { - // Going towards -Infinity. - if (start == 0.0f) { - // +-0.0f - return -Float.MIN_VALUE; - } - final int bits = Float.floatToRawIntBits(start); - return Float.intBitsToFloat(bits + ((bits > 0) ? -1 : 1)); - } else if (direction > start) { - // Going towards +Infinity. - // +0.0f to get rid of eventual -0.0f - final int bits = Float.floatToRawIntBits(start + 0.0f); - return Float.intBitsToFloat(bits + (bits >= 0 ? 1 : -1)); - } else if (start == direction) { - return (float)direction; - } else { - // Returning a NaN derived from the input NaN(s). - return start + (float)direction; - } - } - - /** - * If both arguments are +-0.0, direction is returned. - * - * If both arguments are +Infinity or -Infinity, - * respectively +Infinity or -Infinity is returned. - * - * @param start A double value. - * @param direction A double value. - * @return The double adjacent to start towards direction, considering that - * +(-)Double.MIN_VALUE is adjacent to +(-)0.0, and that - * +(-)Double.MAX_VALUE is adjacent to +(-)Infinity, - * or NaN if any argument is NaN. - */ - public static double nextAfter(double start, double direction) { - if (direction < start) { - // Going towards -Infinity. - if (start == 0.0) { - // +-0.0 - return -Double.MIN_VALUE; - } - final long bits = Double.doubleToRawLongBits(start); - return Double.longBitsToDouble(bits + ((bits > 0) ? -1 : 1)); - } else if (direction > start) { - // Going towards +Infinity. - // +0.0 to get rid of eventual -0.0 - final long bits = Double.doubleToRawLongBits(start + 0.0f); - return Double.longBitsToDouble(bits + (bits >= 0 ? 1 : -1)); - } else if (start == direction) { - return direction; - } else { - // Returning a NaN derived from the input NaN(s). - return start + direction; - } - } - - /** - * Semantically equivalent to nextAfter(start,Double.NEGATIVE_INFINITY). - */ - public static float nextDown(float start) { - if (start > Float.NEGATIVE_INFINITY) { - if (start == 0.0f) { - // +-0.0f - return -Float.MIN_VALUE; - } - final int bits = Float.floatToRawIntBits(start); - return Float.intBitsToFloat(bits + ((bits > 0) ? -1 : 1)); - } else if (start == Float.NEGATIVE_INFINITY) { - return Float.NEGATIVE_INFINITY; - } else { - // NaN - return start; - } - } - - /** - * Semantically equivalent to nextAfter(start,Double.NEGATIVE_INFINITY). - */ - public static double nextDown(double start) { - if (start > Double.NEGATIVE_INFINITY) { - if (start == 0.0) { - // +-0.0 - return -Double.MIN_VALUE; - } - final long bits = Double.doubleToRawLongBits(start); - return Double.longBitsToDouble(bits + ((bits > 0) ? -1 : 1)); - } else if (start == Double.NEGATIVE_INFINITY) { - return Double.NEGATIVE_INFINITY; - } else { - // NaN - return start; - } - } - - /** - * Semantically equivalent to nextAfter(start,Double.POSITIVE_INFINITY). - */ - public static float nextUp(float start) { - if (start < Float.POSITIVE_INFINITY) { - // +0.0f to get rid of eventual -0.0f - final int bits = Float.floatToRawIntBits(start + 0.0f); - return Float.intBitsToFloat(bits + (bits >= 0 ? 1 : -1)); - } else if (start == Float.POSITIVE_INFINITY) { - return Float.POSITIVE_INFINITY; - } else { - // NaN - return start; - } - } - - /** - * Semantically equivalent to nextAfter(start,Double.POSITIVE_INFINITY). - */ - public static double nextUp(double start) { - if (start < Double.POSITIVE_INFINITY) { - // +0.0 to get rid of eventual -0.0 - final long bits = Double.doubleToRawLongBits(start + 0.0); - return Double.longBitsToDouble(bits + (bits >= 0 ? 1 : -1)); - } else if (start == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } else { - // NaN - return start; - } - } - - /** - * Precision may be lost if the result is subnormal. - * - * @param value A float value. - * @param scaleFactor An int value. - * @return value * 2^scaleFactor, or a value equivalent to the specified - * one if it is NaN, +-Infinity or +-0.0f. - */ - public static float scalb(float value, int scaleFactor) { - // Large enough to imply overflow or underflow for - // a finite non-zero value. - final int MAX_SCALE = 2*MAX_FLOAT_EXPONENT+23+1; - - // Making sure scaling factor is in a reasonable range. - scaleFactor = Math.max(Math.min(scaleFactor, MAX_SCALE), -MAX_SCALE); - - return (float)(((double)value) * twoPowNormal(scaleFactor)); - } - - /** - * Precision may be lost if the result is subnormal. - * - * @param value A double value. - * @param scaleFactor An int value. - * @return value * 2^scaleFactor, or a value equivalent to the specified - * one if it is NaN, +-Infinity or +-0.0. - */ - public static double scalb(double value, int scaleFactor) { - if ((scaleFactor > -MAX_DOUBLE_EXPONENT) && (scaleFactor <= MAX_DOUBLE_EXPONENT)) { - // Quick case (as done in apache FastMath). - return value * twoPowNormal(scaleFactor); - } - - // Large enough to imply overflow or underflow for - // a finite non-zero value. - final int MAX_SCALE = 2*MAX_DOUBLE_EXPONENT+52+1; - - // Making sure scaling factor is in a reasonable range. - final int exponentAdjust; - final int scaleIncrement; - final double exponentDelta; - if (scaleFactor < 0) { - scaleFactor = Math.max(scaleFactor, -MAX_SCALE); - scaleIncrement = -512; - exponentDelta = TWO_POW_N512; - } else { - scaleFactor = Math.min(scaleFactor, MAX_SCALE); - scaleIncrement = 512; - exponentDelta = TWO_POW_512; - } - - // Calculating (scaleFactor % +-512), 512 = 2^9, using - // technique from "Hacker's Delight" section 10-2. - final int t = ((scaleFactor >> (9-1)) >>> (32-9)); - exponentAdjust = ((scaleFactor + t) & (512-1)) - t; - - value *= twoPowNormal(exponentAdjust); - scaleFactor -= exponentAdjust; - - while (scaleFactor != 0) { - value *= exponentDelta; - scaleFactor -= scaleIncrement; - } - - return value; - } - - /* - * Non-redefined Math public values and treatments. - */ - - public static float abs(float a) { - return Math.abs(a); - } - - public static double abs(double a) { - return Math.abs(a); - } - - public static float min(float a, float b) { - return Math.min(a,b); - } - - public static double min(double a, double b) { - return Math.min(a,b); - } - - public static float max(float a, float b) { - return Math.max(a,b); - } - - public static double max(double a, double b) { - return Math.max(a,b); - } - - public static double IEEEremainder(double f1, double f2) { - return Math.IEEEremainder(f1,f2); - } - - public static double random() { - return Math.random(); - } - - //-------------------------------------------------------------------------- - // PRIVATE METHODS - //-------------------------------------------------------------------------- - - /** - * Non-instantiable. - */ - private FastMath() { - } - - /* - * Remainders (accurate). - */ - - /** - * @param angle Angle in radians. - * @return Remainder of (angle % (2*PI)), in [-PI,PI]. - */ - private static double remainderTwoPi(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderTwoPi(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle <= (4*NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2)) { - double fn = (double)(int)(angle*TWOPI_INV+0.5); - angle = (angle - fn*TWOPI_HI) - fn*TWOPI_LO; - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI) { - angle = (angle + TWOPI_HI) + TWOPI_LO; - } else if (angle > Math.PI) { - angle = (angle - TWOPI_HI) - TWOPI_LO; - } - return negateResult ? -angle : angle; - } else if (angle < Double.POSITIVE_INFINITY) { - angle = heavyRemainderTwoPi(angle); - return negateResult ? -angle : angle; - } else { // angle is +Infinity or NaN - return Double.NaN; - } - } - - /** - * @param angle Angle in radians. - * @return Remainder of (angle % PI), in [-PI/2,PI/2]. - */ - private static double remainderPi(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderPi(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle <= (2*NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2)) { - double fn = (double)(int)(angle*PI_INV+0.5); - angle = (angle - fn*PI_HI) - fn*PI_LO; - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI/2) { - angle = (angle + PI_HI) + PI_LO; - } else if (angle > Math.PI/2) { - angle = (angle - PI_HI) - PI_LO; - } - return negateResult ? -angle : angle; - } else if (angle < Double.POSITIVE_INFINITY) { - angle = heavyRemainderPi(angle); - return negateResult ? -angle : angle; - } else { // angle is +Infinity or NaN - return Double.NaN; - } - } - - /** - * @param angle Angle in radians. - * @return Bits of double corresponding to remainder of (angle % (PI/2)), - * in [-PI/4,PI/4], with quadrant encoded in exponent bits. - */ - private static long remainderPiO2(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderPiO2(angle, false); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle <= NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2) { - int n = (int)(angle*PIO2_INV+0.5); - double fn = (double)n; - angle = (angle - fn*PIO2_HI) - fn*PIO2_LO; - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI/4) { - angle = (angle + PIO2_HI) + PIO2_LO; - n--; - } else if (angle > Math.PI/4) { - angle = (angle - PIO2_HI) - PIO2_LO; - n++; - } - if (negateResult) { - angle = -angle; - } - return encodeRemainderAndQuadrant(angle, n&3); - } else if (angle < Double.POSITIVE_INFINITY) { - return heavyRemainderPiO2(angle, negateResult); - } else { // angle is +Infinity or NaN - return encodeRemainderAndQuadrant(Double.NaN, 0); - } - } - - /* - * Remainders (fast). - */ - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return Remainder of (angle % (2*PI)), in [-PI,PI]. - */ - private static double remainderTwoPiFast(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderTwoPi(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - // - We don't bother with values higher than (2*PI*(2^52)), - // since they are spaced by 2*PI or more from each other. - // - For large values, we don't use % because it might be very slow, - // and we split computation in two, because cast from double to int - // with large numbers might be very slow also. - if (angle <= TWO_POW_26*(2*Math.PI)) { - // ok - } else if (angle <= TWO_POW_52*(2*Math.PI)) { - // Computing remainder of angle modulo TWO_POW_26*(2*PI). - double fn = (double)(int)(angle*(TWOPI_INV/TWO_POW_26)+0.5); - angle = (angle - fn*(TWOPI_HI*TWO_POW_26)) - fn*(TWOPI_LO*TWO_POW_26); - // Here, angle is in [-TWO_POW_26*PI,TWO_POW_26*PI], or so. - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } else if (angle < Double.POSITIVE_INFINITY) { - return 0.0; - } else { // angle is +Infinity or NaN - return Double.NaN; - } - - // Computing remainder of angle modulo 2*PI. - double fn = (double)(int)(angle*TWOPI_INV+0.5); - angle = (angle - fn*TWOPI_HI) - fn*TWOPI_LO; - - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI) { - angle = (angle + TWOPI_HI) + TWOPI_LO; - } else if (angle > Math.PI) { - angle = (angle - TWOPI_HI) - TWOPI_LO; - } - return negateResult ? -angle : angle; - } - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return Remainder of (angle % PI), in [-PI/2,PI/2]. - */ - private static double remainderPiFast(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderPi(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - // - We don't bother with values higher than (PI*(2^52)), - // since they are spaced by PI or more from each other. - // - For large values, we don't use % because it might be very slow, - // and we split computation in two, because cast from double to int - // with large numbers might be very slow also. - if (angle <= TWO_POW_26*Math.PI) { - // ok - } else if (angle <= TWO_POW_52*Math.PI) { - // Computing remainder of angle modulo TWO_POW_26*PI. - double fn = (double)(int)(angle*(PI_INV/TWO_POW_26)+0.5); - angle = (angle - fn*(PI_HI*TWO_POW_26)) - fn*(PI_LO*TWO_POW_26); - // Here, angle is in [-TWO_POW_26*PI/2,TWO_POW_26*PI/2], or so. - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } else if (angle < Double.POSITIVE_INFINITY) { - return 0.0; - } else { // angle is +Infinity or NaN - return Double.NaN; - } - - // Computing remainder of angle modulo PI. - double fn = (double)(int)(angle*PI_INV+0.5); - angle = (angle - fn*PI_HI) - fn*PI_LO; - - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI/2) { - angle = (angle + PI_HI) + PI_LO; - } else if (angle > Math.PI/2) { - angle = (angle - PI_HI) - PI_LO; - } - return negateResult ? -angle : angle; - } -} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/IntWrapper.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/IntWrapper.java deleted file mode 100644 index 812e5a22d..000000000 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/IntWrapper.java +++ /dev/null @@ -1,13 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ -package space.kscience.kmath.jafama; - -public class IntWrapper { - public int value; - @Override - public String toString() { - return Integer.toString(this.value); - } -} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt index 2b6cc3a5a..2557004e9 100644 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt @@ -1,6 +1,7 @@ package space.kscience.kmath.jafama import space.kscience.kmath.operations.* +import net.jafama.* /** * Advanced Number-like semifield that implements basic operations. @@ -55,7 +56,7 @@ public interface ExtendedField : ExtendedFieldOperations, Field, Numeri * A field for [Double] without boxing. Does not produce appropriate field element. */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") -public object DoubleField : ExtendedField, Norm, ScaleOperations { +public object JafamaDoubleField : ExtendedField, Norm, ScaleOperations { public override inline val zero: Double get() = 0.0 public override inline val one: Double get() = 1.0 diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/NumbersUtils.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/NumbersUtils.java deleted file mode 100644 index 6fdd9dea5..000000000 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/NumbersUtils.java +++ /dev/null @@ -1,2647 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ -package space.kscience.kmath.jafama; - -/** - * Class containing various basic utility methods to deal with numbers. - * This class is meant to be light (no big look-up tables or such). - * - * Check methods return boolean if success, - * for it allows to use them in assertions. - * - * toString methods use capital letters, unlike JDK's toStrings, for it is more - * readable (especially, "l" and "1" can easily be confused with one another). - * - * Some methods have an int version additionally to the long version, - * even though long version could be used instead, for performance reasons, - * either for the methods themselves (if they do computations with ints - * instead of longs), or to be used in an int use case (like methods - * checking whether or not a signed int can fit in such number of bits). - */ -public final class NumbersUtils { - - //-------------------------------------------------------------------------- - // MEMBERS - //-------------------------------------------------------------------------- - - /** - * Double.MIN_NORMAL since Java 6. - */ - public static final double DOUBLE_MIN_NORMAL = Double.longBitsToDouble(0x0010000000000000L); // 2.2250738585072014E-308 - - /** - * Float.MIN_NORMAL since Java 6. - */ - public static final float FLOAT_MIN_NORMAL = Float.intBitsToFloat(0x00800000); // 1.17549435E-38f - - private static final int MIN_DOUBLE_EXPONENT = -1074; - private static final int MAX_DOUBLE_EXPONENT = 1023; - - /** - * All possible upper case chars for representing a number as a String. - */ - private final static char[] CHAR_BY_DIGIT; - static { - final char minDecimal = '0'; - final char maxDecimal = '9'; - final int n1 = maxDecimal - minDecimal + 1; - final char minLetter = 'A'; - final char maxLetter = 'Z'; - final int n2 = maxLetter - minLetter + 1; - CHAR_BY_DIGIT = new char[n1+n2]; - int i=0; - for (char c=minDecimal;c<=maxDecimal;c++) { - CHAR_BY_DIGIT[i++] = c; - } - for (char c=minLetter;c<=maxLetter;c++) { - CHAR_BY_DIGIT[i++] = c; - } - } - - /** - * For power-of-two radixes only. - */ - private static final int[] DIV_SHIFT_BY_RADIX; - static { - DIV_SHIFT_BY_RADIX = new int[32+1]; - int shift=1; - for (int radix=2;radix<=32;radix*=2) { - DIV_SHIFT_BY_RADIX[radix] = shift++; - } - } - - private final static int[] MAX_NBR_OF_NEG_INT_DIGITS_BY_RADIX = new int[Character.MAX_RADIX+1]; - private final static int[] MAX_NBR_OF_NEG_LONG_DIGITS_BY_RADIX = new int[Character.MAX_RADIX+1]; - static { - for (int radix=Character.MIN_RADIX;radix<=Character.MAX_RADIX;radix++) { - /* - * Brutal but works. - * -1 for the sign. - */ - MAX_NBR_OF_NEG_INT_DIGITS_BY_RADIX[radix] = Integer.toString(Integer.MIN_VALUE, radix).length()-1; - MAX_NBR_OF_NEG_LONG_DIGITS_BY_RADIX[radix] = Long.toString(Long.MIN_VALUE, radix).length()-1; - } - } - - static final double NO_CSN_MIN_BOUND_INCL = 1e-3; - static final double NO_CSN_MAX_BOUND_EXCL = 1e7; - - private static final double PIO2_HI = Double.longBitsToDouble(0x3FF921FB54400000L); // 1.57079632673412561417e+00 first 33 bits of pi/2 - private static final double PIO2_LO = Double.longBitsToDouble(0x3DD0B4611A626331L); // 6.07710050650619224932e-11 pi/2 - PIO2_HI - private static final double PI_HI = 2*PIO2_HI; - private static final double PI_LO = 2*PIO2_LO; - private static final double TWOPI_HI = 4*PIO2_HI; - private static final double TWOPI_LO = 4*PIO2_LO; - - //-------------------------------------------------------------------------- - // PUBLIC METHODS - //-------------------------------------------------------------------------- - - /** - * @return True if the specified values are equal or both NaN, false otherwise. - */ - public static boolean equal(float a, float b) { - // Only does one test if a == b. - return (a == b) ? true : ((a != a) && (b != b)); - } - - /** - * @return True if the specified values are equal or both NaN, false otherwise. - */ - public static boolean equal(double a, double b) { - // Only does one test if a == b. - return (a == b) ? true : ((a != a) && (b != b)); - } - - /** - * @return True if the specified value is a mathematical integer, - * false otherwise (which includes NaN and +-Infinity). - */ - public static boolean isMathematicalInteger(float value) { - // Doing magnitude test first, for cast - // might be very slow for huge values. - // It also helps be faster for huge values, - // for which the test with cast always fail. - value = Math.abs(value); - return ((value >= (float)(1<<23) - && (value != Float.POSITIVE_INFINITY))) - || (value == (float)(int)value); - } - - /** - * @return True if the specified value is a mathematical integer, - * false otherwise (which includes NaN and +-Infinity). - */ - public static boolean isMathematicalInteger(double value) { - // Doing magnitude test first, for cast - // might be very slow for huge values. - // It also helps be faster for huge values, - // for which the test with cast always fail. - value = Math.abs(value); - return ((value >= (double)(1L<<52)) - && (value != Double.POSITIVE_INFINITY)) - || (value == (double)(long)value); - } - - /** - * @param value A float value. - * @return True if the specified value is equidistant from two adjacent - * mathematical integers, false otherwise (which includes NaN - * and +-Infinity). - */ - public static boolean isEquidistant(float value) { - if (false) { - // Also works, but slower. - final int bits = Float.floatToRawIntBits(value); - final int exponent = ((bits>>23)&0xFF)-127; - final int nbrOfPostCommaBits = 23 - exponent; - if ((nbrOfPostCommaBits <= 0) || (nbrOfPostCommaBits >= 25)) { - // No mantissa bit after comma, or all mantissa bits - // (including implicit 1) are at least one bit away from it. - //System.out.println("can't be"); - return false; - } - final int mantissa = 0x00800000|(bits&0x007FFFFF); - final int postCommaMask = ~((-1)<>52))&0x7FF)-1023; - final int nbrOfPostCommaBits = 52 - exponent; - if ((nbrOfPostCommaBits <= 0) || (nbrOfPostCommaBits >= 54)) { - // No mantissa bit after comma, or all mantissa bits - // (including implicit 1) are at least one bit away from it. - return false; - } - final long mantissa = 0x0010000000000000L|(bits&0x000FFFFFFFFFFFFFL); - final long postCommaMask = ~((-1L)< value is NaN or +-Infinity - return !(value-value == 0.0f); - } - - /** - * @param value A double value. - * @return True if the specified value is NaN or +-Infinity, false otherwise. - */ - public static boolean isNaNOrInfinite(double value) { - // value-value is not equal to 0.0 (and is NaN) <-> value is NaN or +-Infinity - return !(value-value == 0.0); - } - - /** - * @param value A float value. - * @return -1 if sign bit is 1, 1 if sign bit is 0. - */ - public static int signFromBit(float value) { - return ((Float.floatToRawIntBits(value)>>30)|1); - } - - /** - * @param value A double value. - * @return -1 if sign bit is 1, 1 if sign bit is 0. - */ - public static long signFromBit(double value) { - // Returning a long, to avoid useless cast into int. - return ((Double.doubleToRawLongBits(value)>>62)|1); - } - - /* - * min/max ranges - */ - - /** - * @return True if the specified value is in the specified range (inclusive), false otherwise. - */ - public static boolean isInRange(int min, int max, int a) { - return (min <= a) && (a <= max); - } - - /** - * @return True if the specified value is in the specified range (inclusive), false otherwise. - */ - public static boolean isInRange(long min, long max, long a) { - return (min <= a) && (a <= max); - } - - /** - * Returns false if any value is NaN. - * - * @return True if the specified value is in the specified range (inclusive), false otherwise. - */ - public static boolean isInRange(float min, float max, float a) { - return (min <= a) && (a <= max); - } - - /** - * Returns false if any value is NaN. - * - * @return True if the specified value is in the specified range (inclusive), false otherwise. - */ - public static boolean isInRange(double min, double max, double a) { - return (min <= a) && (a <= max); - } - - /* - * - */ - - /** - * @return True if does not throw. - * @throws IllegalArgumentException if the specified value is not in the specified range (inclusive). - */ - public static boolean checkIsInRange(int min, int max, int a) { - if (!isInRange(min, max, a)) { - throw new IllegalArgumentException(a+" not in ["+min+","+max+"]"); - } - return true; - } - - /** - * @return True if does not throw. - * @throws IllegalArgumentException if the specified value is not in the specified range (inclusive). - */ - public static boolean checkIsInRange(long min, long max, long a) { - if (!isInRange(min, max, a)) { - throw new IllegalArgumentException(a+" not in ["+min+","+max+"]"); - } - return true; - } - - /** - * @return True if does not throw. - * @throws IllegalArgumentException if the specified value is not in the specified range (inclusive) - * or any parameter is NaN. - */ - public static boolean checkIsInRange(float min, float max, float a) { - if (!isInRange(min, max, a)) { - throw new IllegalArgumentException(a+" not in ["+min+","+max+"]"); - } - return true; - } - - /** - * @return True if does not throw. - * @throws IllegalArgumentException if the specified value is not in the specified range (inclusive) - * or any parameter is NaN. - */ - public static boolean checkIsInRange(double min, double max, double a) { - if (!isInRange(min, max, a)) { - throw new IllegalArgumentException(a+" not in ["+min+","+max+"]"); - } - return true; - } - - /* - * - */ - - /** - * @param min A value. - * @param max A value. - * @param a A value. - * @return min if a <= min, else max if a >= max, else a. - */ - public static int toRange(int min, int max, int a) { - if (a <= min) { - return min; - } else if (a >= max) { - return max; - } else { - return a; - } - } - - /** - * @param min A value. - * @param max A value. - * @param a A value. - * @return min if a <= min, else max if a >= max, else a. - */ - public static long toRange(long min, long max, long a) { - if (a <= min) { - return min; - } else if (a >= max) { - return max; - } else { - return a; - } - } - - /** - * @param min A value. - * @param max A value. - * @param a A value. - * @return min if a <= min, else max if a >= max, else a. - */ - public static float toRange(float min, float max, float a) { - if (a <= min) { - return min; - } else if (a >= max) { - return max; - } else { - return a; - } - } - - /** - * @param min A value. - * @param max A value. - * @param a A value. - * @return min if a <= min, else max if a >= max, else a. - */ - public static double toRange(double min, double max, double a) { - if (a <= min) { - return min; - } else if (a >= max) { - return max; - } else { - return a; - } - } - - /* - * bitwise ranges - */ - - /** - * @param bitSize A number of bits, in [1,32]. - * @return True if the specified value fits as a signed integer - * over the specified number of bits, false otherwise. - * @throws IllegalArgumentException if the specified number of bits is not in [1,32]. - */ - public static boolean isInRangeSigned(int a, int bitSize) { - checkBitSizeForSignedInt(bitSize); - return (minSignedIntForBitSize_noCheck(bitSize) <= a) && (a <= maxSignedIntForBitSize_noCheck(bitSize)); - } - - /** - * @param bitSize A number of bits, in [1,64]. - * @return True if the specified value fits as a signed integer - * over the specified number of bits, false otherwise. - * @throws IllegalArgumentException if the specified number of bits is not in [1,64]. - */ - public static boolean isInRangeSigned(long a, int bitSize) { - checkBitSizeForSignedLong(bitSize); - return (minSignedLongForBitSize_noCheck(bitSize) <= a) && (a <= maxSignedLongForBitSize_noCheck(bitSize)); - } - - /** - * @param bitSize A number of bits, in [1,31]. - * @return True if the specified value fits as an unsigned integer - * over the specified number of bits, false otherwise. - * @throws IllegalArgumentException if the specified number of bits is not in [1,31]. - */ - public static boolean isInRangeUnsigned(int a, int bitSize) { - return isInRange(0, maxUnsignedIntForBitSize(bitSize), a); - } - - /** - * @param bitSize A number of bits, in [1,63]. - * @return True if the specified value fits as an unsigned integer - * over the specified number of bits, false otherwise. - * @throws IllegalArgumentException if the specified number of bits is not in [1,63]. - */ - public static boolean isInRangeUnsigned(long a, int bitSize) { - return isInRange(0, maxUnsignedLongForBitSize(bitSize), a); - } - - /* - * - */ - - /** - * @param bitSize A number of bits, in [1,32]. - * @return True if does not throw. - * @throws IllegalArgumentException if the specified value does not fit - * as a signed integer over the specified number of bits. - */ - public static boolean checkIsInRangeSigned(int a, int bitSize) { - if (!isInRangeSigned(a, bitSize)) { - throw new IllegalArgumentException(a+" does not fit as a signed value over "+bitSize+" bits"); - } - return true; - } - - /** - * @param bitSize A number of bits, in [1,64]. - * @return True if does not throw. - * @throws IllegalArgumentException if the specified value does not fit - * as a signed integer over the specified number of bits. - */ - public static boolean checkIsInRangeSigned(long a, int bitSize) { - if (!isInRangeSigned(a, bitSize)) { - throw new IllegalArgumentException(a+" does not fit as a signed value over "+bitSize+" bits"); - } - return true; - } - - /** - * @param bitSize A number of bits, in [1,31]. - * @return True if does not throw. - * @throws IllegalArgumentException if the specified value does not fit - * as an unsigned integer over the specified number of bits. - */ - public static boolean checkIsInRangeUnsigned(int a, int bitSize) { - if (!isInRangeUnsigned(a, bitSize)) { - throw new IllegalArgumentException(a+" does not fit as an unsigned value over "+bitSize+" bits"); - } - return true; - } - - /** - * @param bitSize A number of bits, in [1,63]. - * @return True if does not throw. - * @throws IllegalArgumentException if the specified value does not fit - * as an unsigned integer over the specified number of bits. - */ - public static boolean checkIsInRangeUnsigned(long a, int bitSize) { - if (!isInRangeUnsigned(a, bitSize)) { - throw new IllegalArgumentException(a+" does not fit as an unsigned value over "+bitSize+" bits"); - } - return true; - } - - /* - * masks (int) - */ - - /** - * @param bitSize A number of bits, in [0,32]. - * @return Mask with the specified number of left bits set with 0, - * and other bits set with 1. - */ - public static int intMaskMSBits0(int bitSize) { - checkIsInRange(0, 32, bitSize); - // Shifting in two times, for >>> doesn't work for full bit size (<< as well). - final int halfish = (bitSize>>1); - return ((-1)>>>halfish)>>>(bitSize-halfish); - } - - /** - * @param bitSize A number of bits, in [0,32]. - * @return Mask with the specified number of left bits set with 1, - * and other bits set with 0. - */ - public static int intMaskMSBits1(int bitSize) { - return ~intMaskMSBits0(bitSize); - } - - /** - * @param bitSize A number of bits, in [0,32]. - * @return Mask with the specified number of right bits set with 0, - * and other bits set with 1. - */ - public static int intMaskLSBits0(int bitSize) { - return ~intMaskMSBits0(32-bitSize); - } - - /** - * @param bitSize A number of bits, in [0,32]. - * @return Mask with the specified number of right bits set with 1, - * and other bits set with 0. - */ - public static int intMaskLSBits1(int bitSize) { - return intMaskMSBits0(32-bitSize); - } - - /* - * masks (long) - */ - - /** - * @param bitSize A number of bits, in [0,64]. - * @return Mask with the specified number of left bits set with 0, - * and other bits set with 1. - */ - public static long longMaskMSBits0(int bitSize) { - checkIsInRange(0, 64, bitSize); - // Shifting in two times, for >>> doesn't work for full bit size (<< as well). - final int halfish = (bitSize>>1); - return ((-1L)>>>halfish)>>>(bitSize-halfish); - } - - /** - * @param bitSize A number of bits, in [0,64]. - * @return Mask with the specified number of left bits set with 1, - * and other bits set with 0. - */ - public static long longMaskMSBits1(int bitSize) { - return ~longMaskMSBits0(bitSize); - } - - /** - * @param bitSize A number of bits, in [0,64]. - * @return Mask with the specified number of right bits set with 0, - * and other bits set with 1. - */ - public static long longMaskLSBits0(int bitSize) { - return ~longMaskMSBits0(64-bitSize); - } - - /** - * @param bitSize A number of bits, in [0,64]. - * @return Mask with the specified number of right bits set with 1, - * and other bits set with 0. - */ - public static long longMaskLSBits1(int bitSize) { - return longMaskMSBits0(64-bitSize); - } - - /* - * signed/unsigned - */ - - /** - * @return Unsigned value corresponding to bits of the specified byte. - */ - public static short byteAsUnsigned(byte value) { - return (short)(((short)value) & 0xFF); - } - - /** - * @return Unsigned value corresponding to bits of the specified short. - */ - public static int shortAsUnsigned(short value) { - return ((int)value) & 0xFFFF; - } - - /** - * @return Unsigned value corresponding to bits of the specified int. - */ - public static long intAsUnsigned(int value) { - return ((long)value) & 0xFFFFFFFF; - } - - /* - * bitwise ranges - */ - - /** - * @return True if a signed int value can be read over the specified number of bits, - * i.e. if it is in [1,32], false otherwise. - */ - public static boolean isValidBitSizeForSignedInt(int bitSize) { - return (bitSize > 0) && (bitSize <= 32); - } - - /** - * @return True if a signed long value can be read over the specified number of bits, - * i.e. if it is in [1,64], false otherwise. - */ - public static boolean isValidBitSizeForSignedLong(int bitSize) { - return (bitSize > 0) && (bitSize <= 64); - } - - /** - * @return True if an unsigned int value can be read over the specified number of bits, - * i.e. if it is in [1,31], false otherwise. - */ - public static boolean isValidBitSizeForUnsignedInt(int bitSize) { - return (bitSize > 0) && (bitSize < 32); - } - - /** - * @return True if an unsigned long value can be read over the specified number of bits, - * i.e. if it is in [1,63], false otherwise. - */ - public static boolean isValidBitSizeForUnsignedLong(int bitSize) { - return (bitSize > 0) && (bitSize < 64); - } - - /* - * - */ - - /** - * @return True if does not throw. - * @throws IllegalArgumentException if a signed int value can't be read over the - * specified number of bits, i.e. if it is not in [1,32]. - */ - public static boolean checkBitSizeForSignedInt(int bitSize) { - if (!isValidBitSizeForSignedInt(bitSize)) { - throw new IllegalArgumentException("bit size ["+bitSize+"] must be in [1,32] for signed int values"); - } - return true; - } - - /** - * @return True if does not throw. - * @throws IllegalArgumentException if a signed long value can't be read over the - * specified number of bits, i.e. if it is not in [1,64]. - */ - public static boolean checkBitSizeForSignedLong(int bitSize) { - if (!isValidBitSizeForSignedLong(bitSize)) { - throw new IllegalArgumentException("bit size ["+bitSize+"] must be in [1,64] for signed long values"); - } - return true; - } - - /** - * @return True if does not throw. - * @throws IllegalArgumentException if an unsigned int value can't be read over the - * specified number of bits, i.e. if it is not in [1,31]. - */ - public static boolean checkBitSizeForUnsignedInt(int bitSize) { - if (!isValidBitSizeForUnsignedInt(bitSize)) { - throw new IllegalArgumentException("bit size ["+bitSize+"] must be in [1,31] for unsigned int values"); - } - return true; - } - - /** - * @return True if does not throw. - * @throws IllegalArgumentException if an unsigned long value can't be read over the - * specified number of bits, i.e. if it is not in [1,63]. - */ - public static boolean checkBitSizeForUnsignedLong(int bitSize) { - if (!isValidBitSizeForUnsignedLong(bitSize)) { - throw new IllegalArgumentException("bit size ["+bitSize+"] must be in [1,63] for unsigned long values"); - } - return true; - } - - /* - * - */ - - /** - * @param bitSize A number of bits in [1,32]. - * @return The min signed int value that can be stored over the specified number of bits. - * @throws IllegalArgumentException if the specified number of bits is out of range. - */ - public static int minSignedIntForBitSize(int bitSize) { - checkBitSizeForSignedInt(bitSize); - return minSignedIntForBitSize_noCheck(bitSize); - } - - /** - * @param bitSize A number of bits in [1,64]. - * @return The min signed long value that can be stored over the specified number of bits. - * @throws IllegalArgumentException if the specified number of bits is out of range. - */ - public static long minSignedLongForBitSize(int bitSize) { - checkBitSizeForSignedLong(bitSize); - return minSignedLongForBitSize_noCheck(bitSize); - } - - /** - * @param bitSize A number of bits in [1,32]. - * @return The max signed int value that can be stored over the specified number of bits. - * @throws IllegalArgumentException if the specified number of bits is out of range. - */ - public static int maxSignedIntForBitSize(int bitSize) { - checkBitSizeForSignedInt(bitSize); - return maxSignedIntForBitSize_noCheck(bitSize); - } - - /** - * @param bitSize A number of bits in [1,64]. - * @return The max signed long value that can be stored over the specified number of bits. - * @throws IllegalArgumentException if the specified number of bits is out of range. - */ - public static long maxSignedLongForBitSize(int bitSize) { - checkBitSizeForSignedLong(bitSize); - return maxSignedLongForBitSize_noCheck(bitSize); - } - - /** - * @param bitSize A number of bits in [1,31]. - * @return The max unsigned int value that can be stored over the specified number of bits. - * @throws IllegalArgumentException if the specified number of bits is out of range. - */ - public static int maxUnsignedIntForBitSize(int bitSize) { - checkBitSizeForUnsignedInt(bitSize); - // i.e. (1<>(31-bitSize)); - } - - /** - * @param bitSize A number of bits in [1,63]. - * @return The max unsigned long value that can be stored over the specified number of bits. - * @throws IllegalArgumentException if the specified number of bits is out of range. - */ - public static long maxUnsignedLongForBitSize(int bitSize) { - checkBitSizeForUnsignedLong(bitSize); - // i.e. (1L<>(63-bitSize)); - } - - /* - * - */ - - /** - * @return The number of bits required to store the specified value as a signed integer, - * i.e. a result in [1,32]. - */ - public static int bitSizeForSignedValue(int value) { - if (value > 0) { - return 33-Integer.numberOfLeadingZeros(value); - } else if (value == 0) { - return 1; - } else { - // Works for Integer.MIN_VALUE as well. - return 33-Integer.numberOfLeadingZeros(-value-1); - } - } - - /** - * @return The number of bits required to store the specified value as a signed integer, - * i.e. a result in [1,64]. - */ - public static int bitSizeForSignedValue(long value) { - if (value > 0) { - return 65-Long.numberOfLeadingZeros(value); - } else if (value == 0) { - return 1; - } else { - // Works for Long.MIN_VALUE as well. - return 65-Long.numberOfLeadingZeros(-value-1); - } - } - - /** - * @param value An integer value in [0,Integer.MAX_VALUE]. - * @return The number of bits required to store the specified value as an unsigned integer, - * i.e. a result in [1,31]. - * @throws IllegalArgumentException if the specified value is < 0. - */ - public static int bitSizeForUnsignedValue(int value) { - if (value > 0) { - return 32-Integer.numberOfLeadingZeros(value); - } else { - if (value == 0) { - return 1; - } else { - throw new IllegalArgumentException("unsigned value ["+value+"] must be >= 0"); - } - } - } - - /** - * @param value An integer value in [0,Long.MAX_VALUE]. - * @return The number of bits required to store the specified value as an unsigned integer, - * i.e. a result in [1,63]. - * @throws IllegalArgumentException if the specified value is < 0. - */ - public static int bitSizeForUnsignedValue(long value) { - if (value > 0) { - return 64-Long.numberOfLeadingZeros(value); - } else { - if (value == 0) { - return 1; - } else { - throw new IllegalArgumentException("unsigned value ["+value+"] must be >= 0"); - } - } - } - - /* - * integer functions - */ - - /** - * @return 1 if the specified value is > 0, 0 if it is 0, -1 otherwise. - */ - public static int signum(int a) { - return (a < 0) ? -1 : ((a == 0) ? 0 : 1); - } - - /** - * @return 1 if the specified value is > 0, 0 if it is 0, -1 otherwise. - */ - public static int signum(long a) { - return (a < 0) ? -1 : ((a == 0) ? 0 : 1); - } - - /** - * @return True if the specified value is even, false otherwise. - */ - public static boolean isEven(int a) { - return ((a&1) == 0); - } - - /** - * @return True if the specified value is even, false otherwise. - */ - public static boolean isEven(long a) { - // faster to work on ints - return isEven((int)a); - } - - /** - * @return True if the specified value is odd, false otherwise. - */ - public static boolean isOdd(int a) { - return ((a&1) != 0); - } - - /** - * @return True if the specified value is odd, false otherwise. - */ - public static boolean isOdd(long a) { - // faster to work on ints - return isOdd((int)a); - } - - /** - * @return True if the specified values are both even or both odd, false otherwise. - */ - public static boolean haveSameEvenness(int a, int b) { - return (((a^b)&1) == 0); - } - - /** - * @return True if the specified values are both even or both odd, false otherwise. - */ - public static boolean haveSameEvenness(long a, long b) { - // faster to work on ints - return haveSameEvenness((int)a, (int)b); - } - - /** - * @return True if the specified values are both >= 0 or both < 0, false otherwise. - */ - public static boolean haveSameSign(int a, int b) { - return ((a^b) >= 0); - } - - /** - * @return True if the specified values are both >= 0 or both < 0, false otherwise. - */ - public static boolean haveSameSign(long a, long b) { - return ((a^b) >= 0); - } - - /** - * @return True if the specified value is a power of two, - * i.e. a value of the form 2^k, with k >= 0. - */ - public static boolean isPowerOfTwo(int a) { - if (a <= 0) { - return false; - } - if (false) { - // also works - return (a & -a) == a; - } - return (a & (a-1)) == 0; - } - - /** - * @return True if the specified value is a power of two, - * i.e. a value of the form 2^k, with k >= 0. - */ - public static boolean isPowerOfTwo(long a) { - if (a <= 0) { - return false; - } - if (false) { - // also works - return (a & -a) == a; - } - return (a & (a-1)) == 0; - } - - /** - * @return True if the specified value is a signed power of two, - * i.e. a value of the form +-2^k, with k >= 0. - */ - public static boolean isSignedPowerOfTwo(int a) { - if (a > 0) { - return (a & (a-1)) == 0; - } else { - if (a == -a) { - // a is 0 or Integer.MIN_VALUE - return (a != 0); - } - return ((-a) & (-a-1)) == 0; - } - } - - /** - * @return True if the specified value is a signed power of two, - * i.e. a value of the form +-2^k, with k >= 0. - */ - public static boolean isSignedPowerOfTwo(long a) { - if (a > 0) { - return (a & (a-1)) == 0; - } else { - if (a == -a) { - // a is 0 or Long.MIN_VALUE - return (a != 0); - } - return ((-a) & (-a-1)) == 0; - } - } - - /** - * @param a A value in [1,Integer.MAX_VALUE]. - * @return The highest power of two <= a. - */ - public static int floorPowerOfTwo(int a) { - if (a <= 0) { - throw new IllegalArgumentException("a ["+a+"] must be > 0"); - } - return Integer.highestOneBit(a); - } - - /** - * @param a A value in [1,Long.MAX_VALUE]. - * @return The highest power of two <= a. - */ - public static long floorPowerOfTwo(long a) { - if (a <= 0) { - throw new IllegalArgumentException("a ["+a+"] must be > 0"); - } - // Faster than copying int method - // (less computations on long). - return 1L << (63 - Long.numberOfLeadingZeros(a)); - } - - /** - * @param a A value in [0,2^30]. - * @return The lowest power of two >= a. - */ - public static int ceilingPowerOfTwo(int a) { - checkIsInRange(0, (1<<30), a); - return (a >= 2) ? Integer.highestOneBit((a-1)<<1) : 1; - } - - /** - * @param a A value in [0,2^62]. - * @return The lowest power of two >= a. - */ - public static long ceilingPowerOfTwo(long a) { - checkIsInRange(0L, (1L<<62), a); - // Faster than copying int method - // (less computations on long). - return 1L << (64 - Long.numberOfLeadingZeros(a - 1)); - } - - /** - * @return Mean without overflow, rounded to the lowest value (i.e. mathematical floor((a+b)/2), using floating point division). - */ - public static int meanLow(int a, int b) { - return (a & b) + ((a ^ b) >> 1); - } - - /** - * @return Mean without overflow, rounded to the lowest value (i.e. mathematical floor((a+b)/2), using floating point division). - */ - public static long meanLow(long a, long b) { - return (a & b) + ((a ^ b) >> 1); - } - - /** - * @return Mean without overflow, rounded to the value of smallest magnitude (i.e. mathematical (a+b)/2, using integer division). - */ - public static int meanSml(int a, int b) { - int result = meanLow(a,b); - if (!haveSameEvenness(a, b)) { - // inexact - if (((a&b) < 0) || (((a|b) < 0) && (a+b < 0))) { - // both < 0, or only one is < 0 and it has the largest magnitude - result++; - } - } - return result; - } - - /** - * @return Mean without overflow, rounded to the value of smallest magnitude (i.e. mathematical (a+b)/2, using integer division). - */ - public static long meanSml(long a, long b) { - long result = meanLow(a,b); - if (!haveSameEvenness(a, b)) { - // inexact - if (((a&b) < 0) || (((a|b) < 0) && (a+b < 0))) { - // both < 0, or only one is < 0 and it has the largest magnitude - result++; - } - } - return result; - } - - /** - * Useful because a positive int value could not represent half the width - * of full int range width, which is mathematically Integer.MAX_VALUE+1. - * - * @return Minus half the range width (inclusive, and rounded to the value of smaller magnitude) - * between the specified bounds. - * @throws IllegalArgumentException if min > max. - */ - public static int negHalfWidth(int min, int max) { - if (min > max) { - throw new IllegalArgumentException("min ["+min+"] must be <= max ["+max+"]"); - } - int mean = meanLow(min, max); - return min - mean - ((min^max)&1); - } - - /** - * Useful because a positive long value could not represent half the width - * of full long range width, which is mathematically Long.MAX_VALUE+1. - * - * @return Minus half the range width (inclusive, and rounded to the value of smaller magnitude) - * between the specified bounds. - * @throws IllegalArgumentException if min > max. - */ - public static long negHalfWidth(long min, long max) { - if (min > max) { - throw new IllegalArgumentException("min ["+min+"] must be <= max ["+max+"]"); - } - long mean = meanLow(min, max); - return min - mean - ((min^max)&1); - } - - /** - * This treatment being designed for optimization, the fact that spot - * is a signed power of two is not checked. - * - * @param value A value. - * @param spot A signed power of two (i.e. a value of the form +-2^k, k >= 0). - * @return value % spot, i.e. a value in ]-|spot|,|spot|[. - */ - public static int moduloSignedPowerOfTwo(int value, int spot) { - if (spot == Integer.MIN_VALUE) { - return (value != Integer.MIN_VALUE) ? value : 0; - } else { - int s = (value>>31); - return ((((value+s) ^ s) & (abs(spot)-1)) + s) ^ s; - } - } - - /** - * This treatment being designed for optimization, the fact that spot - * is a signed power of two is not checked. - * - * @param value A value. - * @param spot A signed power of two (i.e. a value of the form +-2^k, k >= 0). - * @return value % spot, i.e. a value in ]-|spot|,|spot|[. - */ - public static long moduloSignedPowerOfTwo(long value, long spot) { - if (spot == Long.MIN_VALUE) { - return (value != Long.MIN_VALUE) ? value : 0; - } else { - long s = (value>>63); - return ((((value+s) ^ s) & (abs(spot)-1)) + s) ^ s; - } - } - - /** - * @param value An integer value > 0. - * @return The integer part of the logarithm, in base 2, of the specified value, - * i.e. a result in [0,30] - * @throws IllegalArgumentException if the specified value is <= 0. - */ - public static int log2(int value) { - if (value <= 0) { - throw new IllegalArgumentException("value ["+value+"] must be > 0"); - } - return 31-Integer.numberOfLeadingZeros(value); - } - - /** - * @param value An integer value > 0. - * @return The integer part of the logarithm, in base 2, of the specified value, - * i.e. a result in [0,62] - * @throws IllegalArgumentException if the specified value is <= 0. - */ - public static int log2(long value) { - if (value <= 0) { - throw new IllegalArgumentException("value ["+value+"] must be > 0"); - } - return 63-Long.numberOfLeadingZeros(value); - } - - /** - * Possibly faster than java.lang.Math.abs(int). - * - * @return The absolute value, except if value is Integer.MIN_VALUE, for which it returns Integer.MIN_VALUE. - */ - public static int abs(int a) { - return (a^(a>>31))-(a>>31); - } - - /** - * Possibly faster than java.lang.Math.abs(long). - * - * @return The absolute value, except if value is Long.MIN_VALUE, for which it returns Long.MIN_VALUE. - */ - public static long abs(long a) { - return (a^(a>>63))-(a>>63); - } - - /** - * @return The negative of the absolute value (always exact). - */ - public static int absNeg(int a) { - return (a>>31)-(a^(a>>31)); - } - - /** - * @return The negative of the absolute value (always exact). - */ - public static long absNeg(long a) { - return (a>>63)-(a^(a>>63)); - } - - /** - * If the specified value is in int range, the returned value is identical. - * - * @return An int hash of the specified value. - */ - public static int intHash(long a) { - if (false) { - // also works - int hash = ((int)(a>>32)) ^ ((int)a); - if (a < 0) { - hash = -hash-1; - } - return hash; - } - int hash = ((int)(a>>32)) + ((int)a); - if (a < 0) { - hash++; - } - return hash; - } - - /** - * @param a An int value. - * @return The specified value as byte. - * @throws ArithmeticException if the specified value is not in [Byte.MIN_VALUE,Byte.MAX_VALUE] range. - */ - public static byte asByte(int a) { - if (a != (byte)a) { - throw new ArithmeticException("overflow: "+a); - } - return (byte)a; - } - - /** - * @param a A long value. - * @return The specified value as int. - * @throws ArithmeticException if the specified value is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int asInt(long a) { - if (a != (int)a) { - throw new ArithmeticException("overflow: "+a); - } - return (int)a; - } - - /** - * @param a A long value. - * @return The closest int value in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int toInt(long a) { - if (a != (int)a) { - return (a < 0) ? Integer.MIN_VALUE : Integer.MAX_VALUE; - } - return (int)a; - } - - /** - * @param a An int value. - * @param b An int value. - * @return The mathematical result of a+b. - * @throws ArithmeticException if the mathematical result of a+b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int plusExact(int a, int b) { - final int sum = a + b; - // HD 2-12 Overflow iff both arguments - // have the opposite sign of the result. - if (((a ^ sum) & (b ^ sum)) < 0) { - throw new ArithmeticException("overflow: "+a+"+"+b); - } - return sum; - } - - /** - * @param a A long value. - * @param b A long value. - * @return The mathematical result of a+b. - * @throws ArithmeticException if the mathematical result of a+b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. - */ - public static long plusExact(long a, long b) { - final long sum = a + b; - // HD 2-12 Overflow iff both arguments - // have the opposite sign of the result. - if (((a ^ sum) & (b ^ sum)) < 0) { - throw new ArithmeticException("overflow: "+a+"+"+b); - } - return sum; - } - - /** - * @param a An int value. - * @param b An int value. - * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a+b. - */ - public static int plusBounded(int a, int b) { - return toInt(((long)a) + ((long)b)); - } - - /** - * @param a A long value. - * @param b A long value. - * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a+b. - */ - public static long plusBounded(long a, long b) { - final long sum = a + b; - if (((a ^ sum) & (b ^ sum)) < 0) { - return (sum >= 0) ? Long.MIN_VALUE : Long.MAX_VALUE; - } - return sum; - } - - /** - * @param a An int value. - * @param b An int value. - * @return The mathematical result of a-b. - * @throws ArithmeticException if the mathematical result of a-b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int minusExact(int a, int b) { - final int diff = a - b; - // HD 2-12 Overflow iff the arguments have different signs and - // the sign of the result is different than the sign of "a". - if (((a ^ b) & (a ^ diff)) < 0) { - throw new ArithmeticException("integer overflow"); - } - return diff; - } - - /** - * @param a A long value. - * @param b A long value. - * @return The mathematical result of a-b. - * @throws ArithmeticException if the mathematical result of a-b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. - */ - public static long minusExact(long a, long b) { - final long diff = a - b; - // HD 2-12 Overflow iff the arguments have different signs and - // the sign of the result is different than the sign of "a". - if (((a ^ b) & (a ^ diff)) < 0) { - throw new ArithmeticException("integer overflow"); - } - return diff; - } - - /** - * @param a An int value. - * @param b An int value. - * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a-b. - */ - public static int minusBounded(int a, int b) { - return toInt(((long)a) - ((long)b)); - } - - /** - * @param a A long value. - * @param b A long value. - * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a-b. - */ - public static long minusBounded(long a, long b) { - final long diff = a - b; - if (((a ^ b) & (a ^ diff)) < 0) { - return (diff >= 0) ? Long.MIN_VALUE : Long.MAX_VALUE; - } - return diff; - } - - /** - * @param a An int value. - * @param b An int value. - * @return The mathematical result of a*b. - * @throws ArithmeticException if the mathematical result of a*b is not in [Integer.MIN_VALUE,Integer.MAX_VALUE] range. - */ - public static int timesExact(int a, int b) { - final long prod = a * (long)b; - if (prod != (int)prod) { - throw new ArithmeticException("overflow: "+a+"*"+b); - } - return (int)prod; - } - - /** - * @param a A long value. - * @param b A long value. - * @return The mathematical result of a*b. - * @throws ArithmeticException if the mathematical result of a*b is not in [Long.MIN_VALUE,Long.MAX_VALUE] range. - */ - public static long timesExact(long a, long b) { - final long prod = a * b; - final long absA = abs(a); - final long absB = abs(b); - if (((absA|absB)>>>31) != 0) { - // Some bits greater than 2^31 that might cause overflow - // Check the result using the divide operator - // and check for the special case of Long.MIN_VALUE * -1 - if (((b != 0) && (prod/b != a)) || - ((a == Long.MIN_VALUE) && (b == -1))) { - throw new ArithmeticException("overflow: "+a+"*"+b); - } - } - return prod; - } - - /** - * @param a An int value. - * @param b An int value. - * @return The int value of [Integer.MIN_VALUE,Integer.MAX_VALUE] range which is the closest to mathematical result of a*b. - */ - public static int timesBounded(int a, int b) { - return (int)(a * (double)b); - } - - /** - * @param a A long value. - * @param b A long value. - * @return The long value of [Long.MIN_VALUE,Long.MAX_VALUE] range which is the closest to mathematical result of a*b. - */ - public static long timesBounded(long a, long b) { - final long prod = a * b; - final long absA = abs(a); - final long absB = abs(b); - if (((absA|absB)>>>31) != 0) { - // Some bits greater than 2^31 that might cause overflow - // Check the result using the divide operator - // and check for the special case of Long.MIN_VALUE * -1 - if (((b != 0) && (prod/b != a)) || - ((a == Long.MIN_VALUE) && (b == -1))) { - return ((a^b) >= 0) ? Long.MAX_VALUE : Long.MIN_VALUE; - } - } - return prod; - } - - /* - * powers - */ - - /** - * Returns the exact result, provided it's in double range, - * i.e. if power is in [-1074,1023]. - * - * @param power An int power. - * @return 2^power as a double, or +-Infinity in case of overflow. - */ - public static double twoPow(int power) { - if (power <= -MAX_DOUBLE_EXPONENT) { // Not normal. - if (power >= MIN_DOUBLE_EXPONENT) { // Subnormal. - return Double.longBitsToDouble(0x0008000000000000L>>(-(power+MAX_DOUBLE_EXPONENT))); - } else { // Underflow. - return 0.0; - } - } else if (power > MAX_DOUBLE_EXPONENT) { // Overflow. - return Double.POSITIVE_INFINITY; - } else { // Normal. - return Double.longBitsToDouble(((long)(power+MAX_DOUBLE_EXPONENT))<<52); - } - } - - /** - * @param power An int power. - * @return 2^power as an int. - * @throws ArithmeticException if the mathematical result - * is not in int range, i.e. if power is not in [0,30]. - */ - public static int twoPowAsIntExact(int power) { - if ((power < 0) || (power > 30)) { - throw new ArithmeticException("integer overflow"); - } - return 1 << power; - } - - /** - * @param power An int power. - * @return 2^power as an int, or the closest power of two in int range - * in case of overflow, i.e. if power is not in [0,30]. - */ - public static int twoPowAsIntBounded(int power) { - power = toRange(0, 30, power); - return 1 << power; - } - - /** - * @param power An int power. - * @return 2^power as a long. - * @throws ArithmeticException if the mathematical result - * is not in long range, i.e. if power is not in [0,62]. - */ - public static long twoPowAsLongExact(int power) { - if ((power < 0) || (power > 62)) { - throw new ArithmeticException("long overflow"); - } - return 1L << power; - } - - /** - * @param power An int power. - * @return 2^power as a long, or the closest power of two in long range - * in case of overflow, i.e. if power is not in [0,62]. - */ - public static long twoPowAsLongBounded(int power) { - power = toRange(0, 62, power); - return 1L << power; - } - - /** - * @param a A value. - * @return a*a. - */ - public static int pow2(int a) { - return a*a; - } - - /** - * @param a A value. - * @return a*a. - */ - public static long pow2(long a) { - return a*a; - } - - /** - * @param a A value. - * @return a*a. - */ - public static float pow2(float a) { - return a*a; - } - - /** - * Strict version. - * - * @param a A value. - * @return a*a. - */ - public static strictfp float pow2_strict(float a) { - return a*a; - } - - /** - * @param a A value. - * @return a*a. - */ - public static double pow2(double a) { - return a*a; - } - - /** - * Strict version. - * - * @param a A value. - * @return a*a. - */ - public static strictfp double pow2_strict(double a) { - return a*a; - } - - /** - * @param a A value. - * @return a*a*a. - */ - public static int pow3(int a) { - return a*a*a; - } - - /** - * @param a A value. - * @return a*a*a. - */ - public static long pow3(long a) { - return a*a*a; - } - - /** - * @param a A value. - * @return a*a*a. - */ - public static float pow3(float a) { - return a*a*a; - } - - /** - * Strict version. - * - * @param a A value. - * @return a*a*a. - */ - public static strictfp float pow3_strict(float a) { - return a*a*a; - } - - /** - * @param a A value. - * @return a*a*a. - */ - public static double pow3(double a) { - return a*a*a; - } - - /** - * Strict version. - * - * @param a A value. - * @return a*a*a. - */ - public static strictfp double pow3_strict(double a) { - return a*a*a; - } - - /* - * Accurate +-m*PI/n. - */ - - /** - * @param angRad An angle, in radians. - * @return angRad + 2*PI, accurately computed. - */ - public static double plus2PI(double angRad) { - if (angRad > -Math.PI) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad + TWOPI_LO) + TWOPI_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad + TWOPI_HI) + TWOPI_LO; - } - } - - /** - * Strict version. - * - * @param angRad An angle, in radians. - * @return angRad + 2*PI, accurately computed. - */ - public static strictfp double plus2PI_strict(double angRad) { - if (angRad > -Math.PI) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad + TWOPI_LO) + TWOPI_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad + TWOPI_HI) + TWOPI_LO; - } - } - - /** - * @param angRad An angle, in radians. - * @return angRad - 2*PI, accurately computed. - */ - public static double minus2PI(double angRad) { - if (angRad < Math.PI) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad - TWOPI_LO) - TWOPI_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad - TWOPI_HI) - TWOPI_LO; - } - } - - /** - * Strict version. - * - * @param angRad An angle, in radians. - * @return angRad - 2*PI, accurately computed. - */ - public static strictfp double minus2PI_strict(double angRad) { - if (angRad < Math.PI) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad - TWOPI_LO) - TWOPI_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad - TWOPI_HI) - TWOPI_LO; - } - } - - /** - * @param angRad An angle, in radians. - * @return angRad + PI, accurately computed. - */ - public static double plusPI(double angRad) { - if (angRad > -Math.PI/2) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad + PI_LO) + PI_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad + PI_HI) + PI_LO; - } - } - - /** - * Strict version. - * - * @param angRad An angle, in radians. - * @return angRad + PI, accurately computed. - */ - public static strictfp double plusPI_strict(double angRad) { - if (angRad > -Math.PI/2) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad + PI_LO) + PI_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad + PI_HI) + PI_LO; - } - } - - /** - * @param angRad An angle, in radians. - * @return angRad - PI, accurately computed. - */ - public static double minusPI(double angRad) { - if (angRad < Math.PI/2) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad - PI_LO) - PI_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad - PI_HI) - PI_LO; - } - } - - /** - * Strict version. - * - * @param angRad An angle, in radians. - * @return angRad - PI, accurately computed. - */ - public static strictfp double minusPI_strict(double angRad) { - if (angRad < Math.PI/2) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad - PI_LO) - PI_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad - PI_HI) - PI_LO; - } - } - - /** - * @param angRad An angle, in radians. - * @return angRad + PI/2, accurately computed. - */ - public static double plusPIO2(double angRad) { - if (angRad > -Math.PI/4) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad + PIO2_LO) + PIO2_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad + PIO2_HI) + PIO2_LO; - } - } - - /** - * Strict version. - * - * @param angRad An angle, in radians. - * @return angRad + PI/2, accurately computed. - */ - public static strictfp double plusPIO2_strict(double angRad) { - if (angRad > -Math.PI/4) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad + PIO2_LO) + PIO2_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad + PIO2_HI) + PIO2_LO; - } - } - - /** - * @param angRad An angle, in radians. - * @return angRad - PI/2, accurately computed. - */ - public static double minusPIO2(double angRad) { - if (angRad < Math.PI/4) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad - PIO2_LO) - PIO2_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad - PIO2_HI) - PIO2_LO; - } - } - - /** - * Strict version. - * - * @param angRad An angle, in radians. - * @return angRad - PI/2, accurately computed. - */ - public static strictfp double minusPIO2_strict(double angRad) { - if (angRad < Math.PI/4) { - // LO then HI, for better accuracy (if starting near 0). - return (angRad - PIO2_LO) - PIO2_HI; - } else { - // HI then LO, for better accuracy (if ending near 0). - return (angRad - PIO2_HI) - PIO2_LO; - } - } - - /* - * toString (radix) - */ - - /** - * @param radix Radix to be checked. - * @return True if does not throw. - * @throws IllegalArgumentException if the specified radix is not in [2,36]. - */ - public static boolean checkRadix(int radix) { - if (!isInRange(Character.MIN_RADIX, Character.MAX_RADIX, radix)) { - throw new IllegalArgumentException("radix ["+radix+"] must be in ["+Character.MIN_RADIX+","+Character.MAX_RADIX+"]"); - } - return true; - } - - /** - * @param radix A radix in [2,36]. - * @return Number of characters (minus sign included) - * to represent the specified value in the specified radix. - */ - public static int computeNbrOfChars(int value, int radix) { - if (value < 0) { - // 1 for sign - return 1 + computeNbrOfDigits_negValue(value, radix); - } else { - return computeNbrOfDigits_negValue(-value, radix); - } - } - - /** - * @param radix A radix in [2,36]. - * @return Number of characters (minus sign included) - * to represent the specified value in the specified radix. - */ - public static int computeNbrOfChars(long value, int radix) { - if (value < 0) { - // 1 for sign - return 1 + computeNbrOfDigits_negValue(value, radix); - } else { - return computeNbrOfDigits_negValue(-value, radix); - } - } - - /** - * @param radix A radix in [2,36]. - * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. - * @return Number of characters (minus sign included) - * to represent the specified value in the specified radix. - */ - public static int computeNbrOfChars(int value, int radix, int paddingUpTo) { - if (value < 0) { - // 1 for sign - return 1 + Math.max(paddingUpTo, computeNbrOfDigits_negValue(value, radix)); - } else { - return Math.max(paddingUpTo, computeNbrOfDigits_negValue(-value, radix)); - } - } - - /** - * @param radix A radix in [2,36]. - * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. - * @return Number of characters (minus sign included) - * to represent the specified value in the specified radix. - */ - public static int computeNbrOfChars(long value, int radix, int paddingUpTo) { - if (value < 0) { - // 1 for sign - return 1 + Math.max(paddingUpTo, computeNbrOfDigits_negValue(value, radix)); - } else { - return Math.max(paddingUpTo, computeNbrOfDigits_negValue(-value, radix)); - } - } - - /** - * @param radix A radix in [2,36]. - * @return Number of digits of the specified value in the specified radix. - */ - public static int computeNbrOfDigits(int value, int radix) { - return computeNbrOfDigits_negValue(-abs(value), radix); - } - - /** - * @param radix A radix in [2,36]. - * @return Number of digits of the specified value in the specified radix. - */ - public static int computeNbrOfDigits(long value, int radix) { - return computeNbrOfDigits_negValue(-abs(value), radix); - } - - /** - * @param radix A radix in [2,36]. - * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. - * @return Number of digits of the specified value in the specified radix, - * including the specified padding. - */ - public static int computeNbrOfDigits(int value, int radix, int paddingUpTo) { - return Math.max(paddingUpTo,computeNbrOfDigits(value, radix)); - } - - /** - * @param radix A radix in [2,36]. - * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. - * @return Number of digits of the specified value in the specified radix, - * including the specified padding. - */ - public static int computeNbrOfDigits(long value, int radix, int paddingUpTo) { - return Math.max(paddingUpTo,computeNbrOfDigits(value, radix)); - } - - /** - * This method just delegates to Integer.toString(int), - * but is defined here to complete the API. - * - * @return String representation of the specified value in base 10. - */ - public static String toString(int value) { - return Integer.toString(value); - } - - /** - * This method just delegates to Long.toString(long), - * but is defined here to complete the API. - * - * @return String representation of the specified value in base 10. - */ - public static String toString(long value) { - return Long.toString(value); - } - - /** - * @param radix A radix in [2,36]. - * @return String representation of the specified value in the specified radix. - * @throws IllegalArgumentException if the specified radix is out of range. - */ - public static String toString(int value, int radix) { - return toString(value, radix, 0); - } - - /** - * @param radix A radix in [2,36]. - * @return String representation of the specified value in the specified radix. - * @throws IllegalArgumentException if the specified radix is out of range. - */ - public static String toString(long value, int radix) { - return toString(value, radix, 0); - } - - /** - * @param radix A radix in [2,36]. - * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. - * @return String representation of the specified value in the specified radix. - * @throws IllegalArgumentException if the specified radix is out of range. - */ - public static String toString(int value, int radix, int paddingUpTo) { - // Only one test if radix+paddingUpTo != 10. - if ((radix+paddingUpTo == 10) && (paddingUpTo == 0)) { - // Using JDK's optimized algorithm. - return Integer.toString(value); - } - - int negValue; - final int signSize; - final boolean negative = (value < 0); - if (negative) { - negValue = value; - signSize = 1; - } else { - negValue = -value; - signSize = 0; - } - // Faster if we just use max possible number of characters (33), - // but we prefer to take care of garbage's memory footprint. - // Checks radix. - final int nbrOfChars = signSize + Math.max(paddingUpTo, computeNbrOfDigits_negValue(negValue, radix)); - - final char[] chars = new char[nbrOfChars]; - - int charPos = nbrOfChars; - - final boolean radixIsPowerOfTwo = ((radix & (radix-1)) == 0); - // Not allowing Integer.MIN_VALUE so it can be negated. - if (radixIsPowerOfTwo && (negValue != Integer.MIN_VALUE)) { - final int mask = radix-1; - final int divShift = DIV_SHIFT_BY_RADIX[radix]; - while (negValue <= -radix) { - chars[--charPos] = CHAR_BY_DIGIT[(int)((-negValue) & mask)]; - negValue = -((-negValue) >> divShift); - } - } else { - while (negValue <= -radix) { - chars[--charPos] = CHAR_BY_DIGIT[(int)(-(negValue % radix))]; - negValue /= radix; - } - } - chars[--charPos] = CHAR_BY_DIGIT[(int)(-negValue)]; - - while (charPos > signSize) { - chars[--charPos] = '0'; - } - - if (negative) { - chars[0] = '-'; - } - - return new String(chars); - } - - /** - * @param radix A radix in [2,36]. - * @param paddingUpTo Number of digits (sign excluded) up to which left-padding with zeros is done. - * @return String representation of the specified value in the specified radix. - * @throws IllegalArgumentException if the specified radix is out of range. - */ - public static String toString(long value, int radix, int paddingUpTo) { - // Only one test if radix+paddingUpTo != 10. - if ((radix+paddingUpTo == 10) && (paddingUpTo == 0)) { - // Using JDK's optimized algorithm. - return Long.toString(value); - } - - long negValue; - final int signSize; - final boolean negative = (value < 0); - if (negative) { - negValue = value; - signSize = 1; - } else { - negValue = -value; - signSize = 0; - } - // Checks radix. - final int nbrOfChars = signSize + Math.max(paddingUpTo, computeNbrOfDigits_negValue(negValue, radix)); - - final char[] chars = new char[nbrOfChars]; - - int charPos = nbrOfChars; - - final boolean radixIsPowerOfTwo = ((radix & (radix-1)) == 0); - // Not allowing Long.MIN_VALUE so it can be negated. - if (radixIsPowerOfTwo && (negValue != Long.MIN_VALUE)) { - final int mask = radix-1; - final int divShift = DIV_SHIFT_BY_RADIX[radix]; - while (negValue <= -radix) { - chars[--charPos] = CHAR_BY_DIGIT[(int)((-negValue) & mask)]; - negValue = -((-negValue) >> divShift); - } - } else { - while (negValue <= -radix) { - chars[--charPos] = CHAR_BY_DIGIT[(int)(-(negValue % radix))]; - negValue /= radix; - } - } - chars[--charPos] = CHAR_BY_DIGIT[(int)(-negValue)]; - - while (charPos > signSize) { - chars[--charPos] = '0'; - } - - if (negative) { - chars[0] = '-'; - } - - return new String(chars); - } - - /* - * toString (bits) - */ - - /** - * @param firstBitPos First bit position (inclusive). - * @param lastBitPosExcl Last bit position (exclusive). - * @return True if does not throw. - * @throws IllegalArgumentException if the specified bit range does not fit in a byte. - */ - public static boolean checkBitPositionsByte(int firstBitPos, int lastBitPosExcl) { - return checkBitPositions(firstBitPos, lastBitPosExcl, 8); - } - - /** - * @param firstBitPos First bit position (inclusive). - * @param lastBitPosExcl Last bit position (exclusive). - * @return True if does not throw. - * @throws IllegalArgumentException if the specified bit range does not fit in a short. - */ - public static boolean checkBitPositionsShort(int firstBitPos, int lastBitPosExcl) { - return checkBitPositions(firstBitPos, lastBitPosExcl, 16); - } - - /** - * @param firstBitPos First bit position (inclusive). - * @param lastBitPosExcl Last bit position (exclusive). - * @return True if does not throw. - * @throws IllegalArgumentException if the specified bit range does not fit in an int. - */ - public static boolean checkBitPositionsInt(int firstBitPos, int lastBitPosExcl) { - return checkBitPositions(firstBitPos, lastBitPosExcl, 32); - } - - /** - * @param firstBitPos First bit position (inclusive). - * @param lastBitPosExcl Last bit position (exclusive). - * @return True if does not throw. - * @throws IllegalArgumentException if the specified bit range does not fit in a long. - */ - public static boolean checkBitPositionsLong(int firstBitPos, int lastBitPosExcl) { - return checkBitPositions(firstBitPos, lastBitPosExcl, 64); - } - - /** - * @return String representation of specified bits, in big endian. - */ - public static String toStringBits(byte bits) { - final char[] chars = new char[8]; - int bitIndex = 8; - while (--bitIndex >= 0) { - chars[7-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - } - return new String(chars); - } - - /** - * @return String representation of specified bits, in big endian. - */ - public static String toStringBits(short bits) { - final char[] chars = new char[16]; - int bitIndex = 16; - while (--bitIndex >= 0) { - chars[15-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - } - return new String(chars); - } - - /** - * @return String representation of specified bits, in big endian. - */ - public static String toStringBits(int bits) { - final char[] chars = new char[32]; - int bitIndex = 32; - while (--bitIndex >= 0) { - chars[31-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - } - return new String(chars); - } - - /** - * @return String representation of specified bits, in big endian. - */ - public static String toStringBits(long bits) { - final char[] chars = new char[64]; - int bitIndex = 64; - while (--bitIndex >= 0) { - chars[63-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - } - return new String(chars); - } - - /** - * @param firstBitPos First bit position (inclusive). - * @param lastBitPosExcl Last bit position (exclusive). - * @param bigEndian True for bits to be added in big endian order (MSBit to LSBit) - * false for little endian order. - * @param padding True if underscores must be added instead of out-of-range bits, - * false to just add characters corresponding to in-range bits. - * @return String representation of specified bits. - */ - public static String toStringBits( - byte bits, - int firstBitPos, - int lastBitPosExcl, - boolean bigEndian, - boolean padding) { - checkBitPositionsByte(firstBitPos, lastBitPosExcl); - return toStringBits_0_32_bitPosAlreadyChecked(8,bits, firstBitPos, lastBitPosExcl, bigEndian, padding); - } - - /** - * @param firstBitPos First bit position (inclusive). - * @param lastBitPosExcl Last bit position (exclusive). - * @param bigEndian True for bits to be added in big endian order (MSBit to LSBit) - * false for little endian order. - * @param padding True if underscores must be added instead of out-of-range bits, - * false to just add characters corresponding to in-range bits. - * @return String representation of specified bits. - */ - public static String toStringBits( - short bits, - int firstBitPos, - int lastBitPosExcl, - boolean bigEndian, - boolean padding) { - checkBitPositionsShort(firstBitPos, lastBitPosExcl); - return toStringBits_0_32_bitPosAlreadyChecked(16,bits, firstBitPos, lastBitPosExcl, bigEndian, padding); - } - - /** - * @param firstBitPos First bit position (inclusive). - * @param lastBitPosExcl Last bit position (exclusive). - * @param bigEndian True for bits to be added in big endian order (MSBit to LSBit) - * false for little endian order. - * @param padding True if underscores must be added instead of out-of-range bits, - * false to just add characters corresponding to in-range bits. - * @return String representation of specified bits. - */ - public static String toStringBits( - int bits, - int firstBitPos, - int lastBitPosExcl, - boolean bigEndian, - boolean padding) { - checkBitPositionsInt(firstBitPos, lastBitPosExcl); - return toStringBits_0_32_bitPosAlreadyChecked(32,bits, firstBitPos, lastBitPosExcl, bigEndian, padding); - } - - /** - * @param firstBitPos First bit position (inclusive). - * @param lastBitPosExcl Last bit position (exclusive). - * @param bigEndian True for bits to be added in big endian order (MSBit to LSBit) - * false for little endian order. - * @param padding True if underscores must be added instead of out-of-range bits, - * false to just add characters corresponding to in-range bits. - * @return String representation of specified bits. - */ - public static String toStringBits( - long bits, - int firstBitPos, - int lastBitPosExcl, - boolean bigEndian, - boolean padding) { - checkBitPositionsLong(firstBitPos, lastBitPosExcl); - final int bitSize = 64; - final int bitSizeM1 = bitSize-1; - final int lastBitPos = lastBitPosExcl-1; - if (padding) { - final int nbrOfChars = bitSize; - final char[] chars = new char[nbrOfChars]; - int bitIndex = bitSizeM1; - if (bigEndian) { - final int firstBitIndex = bitSizeM1-lastBitPos; - final int lastBitIndex = bitSizeM1-firstBitPos; - while (bitIndex > lastBitIndex) { - chars[bitSizeM1-bitIndex] = '_'; - --bitIndex; - } - while (bitIndex >= firstBitIndex) { - chars[bitSizeM1-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - --bitIndex; - } - while (bitIndex >= 0) { - chars[bitSizeM1-bitIndex] = '_'; - --bitIndex; - } - } else { - while (bitIndex > lastBitPos) { - chars[bitIndex] = '_'; - --bitIndex; - } - while (bitIndex >= firstBitPos) { - chars[bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - --bitIndex; - } - while (bitIndex >= 0) { - chars[bitIndex] = '_'; - --bitIndex; - } - } - return new String(chars); - } else { - final int nbrOfChars = (lastBitPosExcl - firstBitPos); - final char[] chars = new char[nbrOfChars]; - if (bigEndian) { - final int firstBitIndex = bitSizeM1-lastBitPos; - final int lastBitIndex = bitSizeM1-firstBitPos; - int bitIndex = lastBitIndex; - while (bitIndex >= firstBitIndex) { - chars[lastBitIndex-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - --bitIndex; - } - } else { - int bitIndex = lastBitPos; - while (bitIndex >= firstBitPos) { - chars[bitIndex-firstBitPos] = (char)('0'+((bits>>bitIndex)&1)); - --bitIndex; - } - } - return new String(chars); - } - } - - /* - * toString (floating points) - * - * toStringCSN(double) and toStringNoCSN(double) - * could be made faster, by using directly internals - * of Double.toString(double), but this would require - * copy-paste of much tricky code from JDK, and - * the overhead of our little rework is relatively - * negligible. - */ - - /** - * @param value A double value. - * @return String representing the specified value, - * using "computerized scientific notation", - * which Double.toString(double) uses for non-infinite - * values, when |value| < 1e-3 or |value| >= 1e7. - */ - public static String toStringCSN(double value) { - // Quick case (also to get rid of +-0.0, - // for which Double.toString(double) doesn't use CSN). - if (value == 0.0) { - if (Double.doubleToRawLongBits(value) < 0) { - return "-0.0E0"; - } else { - return "0.0E0"; - } - } - - final double abs = Math.abs(value); - if ((abs >= NO_CSN_MIN_BOUND_INCL) && (abs < NO_CSN_MAX_BOUND_EXCL)) { - final boolean neg = (value < 0.0); - - final String rawAbs = Double.toString(abs); - if (abs >= 1.0) { - /* - * 0123456 - * 12.3456 ===> 1.23456E1 - * 123.0 ===> 1.23E2 - */ - final int dotIndex = rawAbs.indexOf((int)'.'); - final int powerOfTen = dotIndex-1; - final StringBuilder sb = new StringBuilder(); - if (neg) { - sb.append('-'); - } - // Adding unit-or-above digits, with dot after first one. - sb.append(rawAbs.charAt(0)); - sb.append('.'); - sb.append(rawAbs,1,dotIndex); - if ((value != (int)value) || (abs < 10.0)) { - // Adding below-unit digits (possibly just 0 if abs < 10.0, - // to end up for example with "3.0E0" instead of "3.E0"). - sb.append(rawAbs,dotIndex+1,rawAbs.length()); - } - sb.append('E'); - sb.append(CHAR_BY_DIGIT[powerOfTen]); - return sb.toString(); - } else { - /* - * 012345678 - * 0.0123456 ===> 1.23456E-2 - * 0.01 ===> 1.0E-2 - */ - int nonZeroIndex = 1; - while (rawAbs.charAt(++nonZeroIndex) == '0') { - } - // Negative. - final int powerOfTen = 1-nonZeroIndex; - final int nbrOfSignificantDigitsPastDot = (rawAbs.length() - (nonZeroIndex+1)); - final StringBuilder sb = new StringBuilder(); - if (neg) { - sb.append('-'); - } - sb.append(rawAbs.charAt(nonZeroIndex)); - sb.append('.'); - if (nbrOfSignificantDigitsPastDot > 0) { - // If bug 4428022 make rawAbs being something like "0.0010", - // we add the last '0' here after the dot, which is fine. - sb.append(rawAbs,nonZeroIndex+1,rawAbs.length()); - } else { - sb.append('0'); - } - sb.append("E-"); - sb.append(CHAR_BY_DIGIT[-powerOfTen]); - return sb.toString(); - } - } else { - return Double.toString(value); - } - } - - /** - * @param value A double value. - * @return String representing the specified value, - * not in "computerized scientific notation", - * which Double.toString(double) uses for non-infinite - * values, when |value| < 1e-3 or |value| >= 1e7. - */ - public static String toStringNoCSN(double value) { - // Quick case. - // Should also work with long instead of int, - // but less obvious (due to roundings...), - // and we just want to speed up the more common - // case of "small" integer values. - final int intValue = (int)value; - if (value == intValue) { - if (value == 0.0) { - if (Double.doubleToRawLongBits(value) < 0) { - return "-0.0"; - } else { - return "0.0"; - } - } else { - return Integer.toString(intValue)+".0"; - } - } - - final String raw = Double.toString(value); - final double abs = Math.abs(value); - if (abs >= NO_CSN_MAX_BOUND_EXCL) { - if (abs == Double.POSITIVE_INFINITY) { - return raw; - } - /* - * 0123456789 - * 1.234567E5 ===> 123456.7 - * 1.23456E5 ===> 123456.0 (adding 0) - * 1.23E5 ===> 123000.0 - * 1.0E5 ===> 100000.0 - */ - // "." close to start, so using indexOf. - final int dotIndex = raw.indexOf((int)'.'); - // "E" close to end, so using lastIndexOf. - final int eIndex = raw.lastIndexOf((int)'E'); - final int powerOfTen = Integer.parseInt(raw.substring(eIndex+1)); - final int nbrOfSignificantLoDigits = (eIndex - dotIndex - 1); - final int nbrOfZerosToAddBeforeDot = (powerOfTen - nbrOfSignificantLoDigits); - - int start; - int end; - - final StringBuilder sb = new StringBuilder(); - sb.append(raw,0,dotIndex); - if (nbrOfZerosToAddBeforeDot >= 0) { - // Can copy all digits that were between '.' and 'E'. - sb.append(raw,dotIndex+1,eIndex); - for (int i=0;i 0.0001234 - * 1.0E-4 ===> 0.0001 - */ - // "." close to start, so using indexOf. - final int dotIndex = raw.indexOf((int)'.'); - // "E" close to end, so using lastIndexOf. - final int eIndex = raw.lastIndexOf((int)'E'); - // Negative. - final int powerOfTen = Integer.parseInt(raw.substring(eIndex+1)); - final int nbrOfZerosToAddAfterDot = (-powerOfTen-1); - - final StringBuilder sb = new StringBuilder(); - if (value < 0.0) { - sb.append("-0."); - } else { - sb.append("0."); - } - for (int i=0;i>(32-bitSize)); - } - - private static long minSignedLongForBitSize_noCheck(int bitSize) { - // i.e. (-1L<<(bitSize-1)) - return (Long.MIN_VALUE>>(64-bitSize)); - } - - private static int maxSignedIntForBitSize_noCheck(int bitSize) { - // i.e. (1<<(bitSize-1))-1 - return (Integer.MAX_VALUE>>(32-bitSize)); - } - - private static long maxSignedLongForBitSize_noCheck(int bitSize) { - // i.e. (1L<<(bitSize-1))-1 - return (Long.MAX_VALUE>>(64-bitSize)); - } - - /* - * - */ - - /** - * @throws IllegalArgumentException if the specified radix is out of range. - */ - private static int computeNbrOfDigits_negValue(int negValue, int radix) { - checkRadix(radix); - final int maxNbrOfDigits = MAX_NBR_OF_NEG_INT_DIGITS_BY_RADIX[radix]; - int p = radix; - for (int i=1;i -p) { - return i; - } - p *= radix; - } - return maxNbrOfDigits; - } - - /** - * @throws IllegalArgumentException if the specified radix is out of range. - */ - private static int computeNbrOfDigits_negValue(long negValue, int radix) { - checkRadix(radix); - final int maxNbrOfDigits = MAX_NBR_OF_NEG_LONG_DIGITS_BY_RADIX[radix]; - long p = radix; - for (int i=1;i -p) { - return i; - } - p *= radix; - } - return maxNbrOfDigits; - } - - /* - * - */ - - private static boolean checkBitPositions(int firstBitPos, int lastBitPosExcl, int bitSize) { - if ((firstBitPos < 0) || (firstBitPos > lastBitPosExcl) || (lastBitPosExcl > bitSize)) { - throw new IllegalArgumentException( - "bit positions (first="+firstBitPos+",lastExcl="+lastBitPosExcl - +") must verify 0 <= first <= lastExcl <= "+bitSize); - } - return true; - } - - /** - * Common method for byte, short and int. - * Could be a bit faster to have specific methods for byte and short, - * but not much, and that would also make more messy (byte-)code. - * - * @param bitSize Must be in [0,32]. - */ - private static String toStringBits_0_32_bitPosAlreadyChecked( - int bitSize, - int bits, - int firstBitPos, - int lastBitPosExcl, - boolean bigEndian, - boolean padding) { - final int bitSizeM1 = bitSize-1; - final int lastBitPos = lastBitPosExcl-1; - if (padding) { - final int nbrOfChars = bitSize; - final char[] chars = new char[nbrOfChars]; - int bitIndex = bitSizeM1; - if (bigEndian) { - final int firstBitIndex = bitSizeM1-lastBitPos; - final int lastBitIndex = bitSizeM1-firstBitPos; - while (bitIndex > lastBitIndex) { - chars[bitSizeM1-bitIndex] = '_'; - --bitIndex; - } - while (bitIndex >= firstBitIndex) { - chars[bitSizeM1-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - --bitIndex; - } - while (bitIndex >= 0) { - chars[bitSizeM1-bitIndex] = '_'; - --bitIndex; - } - } else { - while (bitIndex > lastBitPos) { - chars[bitIndex] = '_'; - --bitIndex; - } - while (bitIndex >= firstBitPos) { - chars[bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - --bitIndex; - } - while (bitIndex >= 0) { - chars[bitIndex] = '_'; - --bitIndex; - } - } - return new String(chars); - } else { - final int nbrOfChars = (lastBitPosExcl - firstBitPos); - final char[] chars = new char[nbrOfChars]; - if (bigEndian) { - final int firstBitIndex = bitSizeM1-lastBitPos; - final int lastBitIndex = bitSizeM1-firstBitPos; - int bitIndex = lastBitIndex; - while (bitIndex >= firstBitIndex) { - chars[lastBitIndex-bitIndex] = (char)('0'+((bits>>bitIndex)&1)); - --bitIndex; - } - } else { - int bitIndex = lastBitPos; - while (bitIndex >= firstBitPos) { - chars[bitIndex-firstBitPos] = (char)('0'+((bits>>bitIndex)&1)); - --bitIndex; - } - } - return new String(chars); - } - } -} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/StrictFastMath.java b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/StrictFastMath.java deleted file mode 100644 index a61ac9772..000000000 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/StrictFastMath.java +++ /dev/null @@ -1,2998 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.jafama; - -/** - * Strict versions of FastMath methods. - * Cf. README.txt for more info. - */ -public final strictfp class StrictFastMath extends CmnFastMath { - - /* - * We use strictfp for the whole class: - * - for simplicity, - * - to reduce strictfp/non-strictfp switching, which can add overhead, - * when these treatments are used from within strictfp code, - * - to make sure that we only use and return non-extended values, - * else if strictfp gets added later to some treatments they might then - * behave differently due to no longer being inlinable into FP-wide - * expressions, - * - to make sure we don't mistakenly not use it. - */ - - //-------------------------------------------------------------------------- - // CONFIGURATION - //-------------------------------------------------------------------------- - - private static final boolean USE_JDK_MATH = SFM_USE_JDK_MATH; - - private static final boolean USE_REDEFINED_LOG = SFM_USE_REDEFINED_LOG; - - private static final boolean USE_REDEFINED_SQRT = SFM_USE_REDEFINED_SQRT; - - private static final boolean USE_POWTABS_FOR_ASIN = SFM_USE_POWTABS_FOR_ASIN; - - //-------------------------------------------------------------------------- - // PUBLIC METHODS - //-------------------------------------------------------------------------- - - /* - * trigonometry - */ - - /** - * @param angle Angle in radians. - * @return Angle sine. - */ - public static double sin(double angle) { - if (USE_JDK_MATH) { - return StrictMath.sin(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { - if (false) { - // Can give very bad relative error near PI (mod 2*PI). - angle = remainderTwoPi(angle); - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } else { - final long remAndQuad = remainderPiO2(angle); - angle = decodeRemainder(remAndQuad); - final double sin; - final int q = decodeQuadrant(remAndQuad); - if (q == 0) { - sin = sin(angle); - } else if (q == 1) { - sin = cos(angle); - } else if (q == 2) { - sin = -sin(angle); - } else { - sin = -cos(angle); - } - return (negateResult ? -sin : sin); - } - } - // index: possibly outside tables range. - int index = (int)(angle * SIN_COS_INDEXER + 0.5); - double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; - // Making sure index is within tables range. - // Last value of each table is the same than first, - // so we ignore it (tabs size minus one) for modulo. - index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) - double indexSin = MyTSinCos.sinTab[index]; - double indexCos = MyTSinCos.cosTab[index]; - double result = indexSin + delta * (indexCos + delta * (-indexSin * ONE_DIV_F2 + delta * (-indexCos * ONE_DIV_F3 + delta * indexSin * ONE_DIV_F4))); - return negateResult ? -result : result; - } - - /** - * Quick sin, with accuracy of about 1.6e-3 (PI/) - * for |angle| < 6588395.0 (Integer.MAX_VALUE * (2*PI/) - 2) - * (- 2 due to removing PI/2 before using cosine tab), - * and no accuracy at all for larger values. - * - * @param angle Angle in radians. - * @return Angle sine. - */ - public static double sinQuick(double angle) { - if (USE_JDK_MATH) { - return StrictMath.sin(angle); - } - return MyTSinCos.cosTab[((int)(Math.abs(angle-Math.PI/2) * SIN_COS_INDEXER + 0.5)) & (SIN_COS_TABS_SIZE-2)]; - } - - /** - * @param angle Angle in radians. - * @return Angle cosine. - */ - public static double cos(double angle) { - if (USE_JDK_MATH) { - return StrictMath.cos(angle); - } - angle = Math.abs(angle); - if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { - if (false) { - // Can give very bad relative error near PI (mod 2*PI). - angle = remainderTwoPi(angle); - if (angle < 0.0) { - angle = -angle; - } - } else { - final long remAndQuad = remainderPiO2(angle); - angle = decodeRemainder(remAndQuad); - final double cos; - final int q = decodeQuadrant(remAndQuad); - if (q == 0) { - cos = cos(angle); - } else if (q == 1) { - cos = -sin(angle); - } else if (q == 2) { - cos = -cos(angle); - } else { - cos = sin(angle); - } - return cos; - } - } - // index: possibly outside tables range. - int index = (int)(angle * SIN_COS_INDEXER + 0.5); - double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; - // Making sure index is within tables range. - // Last value of each table is the same than first, - // so we ignore it (tabs size minus one) for modulo. - index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) - double indexCos = MyTSinCos.cosTab[index]; - double indexSin = MyTSinCos.sinTab[index]; - return indexCos + delta * (-indexSin + delta * (-indexCos * ONE_DIV_F2 + delta * (indexSin * ONE_DIV_F3 + delta * indexCos * ONE_DIV_F4))); - } - - /** - * Quick cos, with accuracy of about 1.6e-3 (PI/) - * for |angle| < 6588397.0 (Integer.MAX_VALUE * (2*PI/)), - * and no accuracy at all for larger values. - * - * @param angle Angle in radians. - * @return Angle cosine. - */ - public static double cosQuick(double angle) { - if (USE_JDK_MATH) { - return StrictMath.cos(angle); - } - return MyTSinCos.cosTab[((int)(Math.abs(angle) * SIN_COS_INDEXER + 0.5)) & (SIN_COS_TABS_SIZE-2)]; - } - - /** - * Computes sine and cosine together. - * - * @param angle Angle in radians. - * @param cosine (out) Angle cosine. - * @return Angle sine. - */ - public static double sinAndCos(double angle, DoubleWrapper cosine) { - if (USE_JDK_MATH) { - cosine.value = StrictMath.cos(angle); - return StrictMath.sin(angle); - } - // Using the same algorithm than sin(double) method, - // and computing also cosine at the end. - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle > SIN_COS_MAX_VALUE_FOR_INT_MODULO) { - if (false) { - // Can give very bad relative error near PI (mod 2*PI). - angle = remainderTwoPi(angle); - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } else { - final long remAndQuad = remainderPiO2(angle); - angle = decodeRemainder(remAndQuad); - final double sin; - final int q = decodeQuadrant(remAndQuad); - if (q == 0) { - sin = sin(angle); - cosine.value = cos(angle); - } else if (q == 1) { - sin = cos(angle); - cosine.value = -sin(angle); - } else if (q == 2) { - sin = -sin(angle); - cosine.value = -cos(angle); - } else { - sin = -cos(angle); - cosine.value = sin(angle); - } - return (negateResult ? -sin : sin); - } - } - int index = (int)(angle * SIN_COS_INDEXER + 0.5); - double delta = (angle - index * SIN_COS_DELTA_HI) - index * SIN_COS_DELTA_LO; - index &= (SIN_COS_TABS_SIZE-2); // index % (SIN_COS_TABS_SIZE-1) - double indexSin = MyTSinCos.sinTab[index]; - double indexCos = MyTSinCos.cosTab[index]; - // Could factor some multiplications (delta * factorials), but then is less accurate. - cosine.value = indexCos + delta * (-indexSin + delta * (-indexCos * ONE_DIV_F2 + delta * (indexSin * ONE_DIV_F3 + delta * indexCos * ONE_DIV_F4))); - double result = indexSin + delta * (indexCos + delta * (-indexSin * ONE_DIV_F2 + delta * (-indexCos * ONE_DIV_F3 + delta * indexSin * ONE_DIV_F4))); - return negateResult ? -result : result; - } - - /** - * Can have very bad relative error near +-PI/2, - * but of the same magnitude than the relative delta between - * StrictMath.tan(PI/2) and StrictMath.tan(nextDown(PI/2)). - * - * @param angle Angle in radians. - * @return Angle tangent. - */ - public static double tan(double angle) { - if (USE_JDK_MATH) { - return StrictMath.tan(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle > TAN_MAX_VALUE_FOR_INT_MODULO) { - angle = remainderPi(angle); - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } - // index: possibly outside tables range. - int index = (int)(angle * TAN_INDEXER + 0.5); - double delta = (angle - index * TAN_DELTA_HI) - index * TAN_DELTA_LO; - // Making sure index is within tables range. - // index modulo PI, i.e. 2*(virtual tab size minus one). - index &= (2*(TAN_VIRTUAL_TABS_SIZE-1)-1); // index % (2*(TAN_VIRTUAL_TABS_SIZE-1)) - // Here, index is in [0,2*(TAN_VIRTUAL_TABS_SIZE-1)-1], i.e. indicates an angle in [0,PI[. - if (index > (TAN_VIRTUAL_TABS_SIZE-1)) { - index = (2*(TAN_VIRTUAL_TABS_SIZE-1)) - index; - delta = -delta; - negateResult = !negateResult; - } - double result; - if (index < TAN_TABS_SIZE) { - result = MyTTan.tanTab[index] - + delta * (MyTTan.tanDer1DivF1Tab[index] - + delta * (MyTTan.tanDer2DivF2Tab[index] - + delta * (MyTTan.tanDer3DivF3Tab[index] - + delta * MyTTan.tanDer4DivF4Tab[index]))); - } else { // angle in ]TAN_MAX_VALUE_FOR_TABS,TAN_MAX_VALUE_FOR_INT_MODULO], or angle is NaN - // Using tan(angle) == 1/tan(PI/2-angle) formula: changing angle (index and delta), and inverting. - index = (TAN_VIRTUAL_TABS_SIZE-1) - index; - result = 1/(MyTTan.tanTab[index] - - delta * (MyTTan.tanDer1DivF1Tab[index] - - delta * (MyTTan.tanDer2DivF2Tab[index] - - delta * (MyTTan.tanDer3DivF3Tab[index] - - delta * MyTTan.tanDer4DivF4Tab[index])))); - } - return negateResult ? -result : result; - } - - /** - * @param value Value in [-1,1]. - * @return Value arcsine, in radians, in [-PI/2,PI/2]. - */ - public static double asin(double value) { - if (USE_JDK_MATH) { - return StrictMath.asin(value); - } - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - if (value <= ASIN_MAX_VALUE_FOR_TABS) { - int index = (int)(value * ASIN_INDEXER + 0.5); - double delta = value - index * ASIN_DELTA; - double result = MyTAsin.asinTab[index] - + delta * (MyTAsin.asinDer1DivF1Tab[index] - + delta * (MyTAsin.asinDer2DivF2Tab[index] - + delta * (MyTAsin.asinDer3DivF3Tab[index] - + delta * MyTAsin.asinDer4DivF4Tab[index]))); - return negateResult ? -result : result; - } else if (USE_POWTABS_FOR_ASIN && (value <= ASIN_MAX_VALUE_FOR_POWTABS)) { - int index = (int)(powFast(value * ASIN_POWTABS_ONE_DIV_MAX_VALUE, ASIN_POWTABS_POWER) * ASIN_POWTABS_SIZE_MINUS_ONE + 0.5); - double delta = value - MyTAsinPow.asinParamPowTab[index]; - double result = MyTAsinPow.asinPowTab[index] - + delta * (MyTAsinPow.asinDer1DivF1PowTab[index] - + delta * (MyTAsinPow.asinDer2DivF2PowTab[index] - + delta * (MyTAsinPow.asinDer3DivF3PowTab[index] - + delta * MyTAsinPow.asinDer4DivF4PowTab[index]))); - return negateResult ? -result : result; - } else { // value > ASIN_MAX_VALUE_FOR_TABS, or value is NaN - // This part is derived from fdlibm. - if (value < 1.0) { - double t = (1.0 - value)*0.5; - double p = t*(ASIN_PS0+t*(ASIN_PS1+t*(ASIN_PS2+t*(ASIN_PS3+t*(ASIN_PS4+t*ASIN_PS5))))); - double q = 1.0+t*(ASIN_QS1+t*(ASIN_QS2+t*(ASIN_QS3+t*ASIN_QS4))); - double s = sqrt(t); - double z = s+s*(p/q); - double result = ASIN_PIO2_HI-((z+z)-ASIN_PIO2_LO); - return negateResult ? -result : result; - } else { // value >= 1.0, or value is NaN - if (value == 1.0) { - return negateResult ? -Math.PI/2 : Math.PI/2; - } else { - return Double.NaN; - } - } - } - } - - /** - * If value is not NaN and is outside [-1,1] range, closest value in this range is used. - * - * @param value Value in [-1,1]. - * @return Value arcsine, in radians, in [-PI/2,PI/2]. - */ - public static double asinInRange(double value) { - if (value <= -1.0) { - return -Math.PI/2; - } else if (value >= 1.0) { - return Math.PI/2; - } else { - return asin(value); - } - } - - /** - * @param value Value in [-1,1]. - * @return Value arccosine, in radians, in [0,PI]. - */ - public static double acos(double value) { - if (USE_JDK_MATH) { - return StrictMath.acos(value); - } - return Math.PI/2 - asin(value); - } - - /** - * If value is not NaN and is outside [-1,1] range, - * closest value in this range is used. - * - * @param value Value in [-1,1]. - * @return Value arccosine, in radians, in [0,PI]. - */ - public static double acosInRange(double value) { - if (value <= -1.0) { - return Math.PI; - } else if (value >= 1.0) { - return 0.0; - } else { - return acos(value); - } - } - - /** - * @param value A double value. - * @return Value arctangent, in radians, in [-PI/2,PI/2]. - */ - public static double atan(double value) { - if (USE_JDK_MATH) { - return StrictMath.atan(value); - } - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - if (value == 1.0) { - // We want "exact" result for 1.0. - return negateResult ? -Math.PI/4 : Math.PI/4; - } else if (value <= ATAN_MAX_VALUE_FOR_TABS) { - int index = (int)(value * ATAN_INDEXER + 0.5); - double delta = value - index * ATAN_DELTA; - double result = MyTAtan.atanTab[index] - + delta * (MyTAtan.atanDer1DivF1Tab[index] - + delta * (MyTAtan.atanDer2DivF2Tab[index] - + delta * (MyTAtan.atanDer3DivF3Tab[index] - + delta * MyTAtan.atanDer4DivF4Tab[index]))); - return negateResult ? -result : result; - } else { // value > ATAN_MAX_VALUE_FOR_TABS, or value is NaN - // This part is derived from fdlibm. - if (value < TWO_POW_66) { - double x = -1/value; - double x2 = x*x; - double x4 = x2*x2; - double s1 = x2*(ATAN_AT0+x4*(ATAN_AT2+x4*(ATAN_AT4+x4*(ATAN_AT6+x4*(ATAN_AT8+x4*ATAN_AT10))))); - double s2 = x4*(ATAN_AT1+x4*(ATAN_AT3+x4*(ATAN_AT5+x4*(ATAN_AT7+x4*ATAN_AT9)))); - double result = ATAN_HI3-((x*(s1+s2)-ATAN_LO3)-x); - return negateResult ? -result : result; - } else { // value >= 2^66, or value is NaN - if (value != value) { - return Double.NaN; - } else { - return negateResult ? -Math.PI/2 : Math.PI/2; - } - } - } - } - - /** - * For special values for which multiple conventions could be adopted, - * behaves like StrictMath.atan2(double,double). - * - * @param y Coordinate on y axis. - * @param x Coordinate on x axis. - * @return Angle from x axis positive side to (x,y) position, in radians, in [-PI,PI]. - * Angle measure is positive when going from x axis to y axis (positive sides). - */ - public static double atan2(double y, double x) { - if (USE_JDK_MATH) { - return StrictMath.atan2(y,x); - } - /* - * Using sub-methods, to make method lighter for general case, - * and to avoid JIT-optimization crash on NaN. - */ - if (x > 0.0) { - if (y == 0.0) { - // +-0.0 - return y; - } - if (x == Double.POSITIVE_INFINITY) { - return atan2_pinf_yyy(y); - } else { - return atan(y/x); - } - } else if (x < 0.0) { - if (y == 0.0) { - return signFromBit(y) * Math.PI; - } - if (x == Double.NEGATIVE_INFINITY) { - return atan2_ninf_yyy(y); - } else if (y > 0.0) { - return Math.PI/2 - atan(x/y); - } else if (y < 0.0) { - return -Math.PI/2 - atan(x/y); - } else { - return Double.NaN; - } - } else { - return atan2_yyy_zeroOrNaN(y, x); - } - } - - /** - * Gives same result as StrictMath.toRadians for some particular values - * like 90.0, 180.0 or 360.0, but is faster (no division). - * - * @param angdeg Angle value in degrees. - * @return Angle value in radians. - */ - public static double toRadians(double angdeg) { - if (USE_JDK_MATH) { - return StrictMath.toRadians(angdeg); - } - return angdeg * (Math.PI/180); - } - - /** - * Gives same result as StrictMath.toDegrees for some particular values - * like Math.PI/2, Math.PI or 2*Math.PI, but is faster (no division). - * - * @param angrad Angle value in radians. - * @return Angle value in degrees. - */ - public static double toDegrees(double angrad) { - if (USE_JDK_MATH) { - return StrictMath.toDegrees(angrad); - } - return angrad * (180/Math.PI); - } - - /** - * @param sign Sign of the angle: true for positive, false for negative. - * @param degrees Degrees, in [0,180]. - * @param minutes Minutes, in [0,59]. - * @param seconds Seconds, in [0.0,60.0[. - * @return Angle in radians. - */ - public static double toRadians(boolean sign, int degrees, int minutes, double seconds) { - return toRadians(toDegrees(sign, degrees, minutes, seconds)); - } - - /** - * @param sign Sign of the angle: true for positive, false for negative. - * @param degrees Degrees, in [0,180]. - * @param minutes Minutes, in [0,59]. - * @param seconds Seconds, in [0.0,60.0[. - * @return Angle in degrees. - */ - public static double toDegrees(boolean sign, int degrees, int minutes, double seconds) { - double signFactor = sign ? 1.0 : -1.0; - return signFactor * (degrees + (1.0/60)*(minutes + (1.0/60)*seconds)); - } - - /** - * @param angrad Angle in radians. - * @param degrees (out) Degrees, in [0,180]. - * @param minutes (out) Minutes, in [0,59]. - * @param seconds (out) Seconds, in [0.0,60.0[. - * @return true if the resulting angle in [-180deg,180deg] is positive, false if it is negative. - */ - public static boolean toDMS(double angrad, IntWrapper degrees, IntWrapper minutes, DoubleWrapper seconds) { - // Computing longitude DMS. - double tmp = toDegrees(normalizeMinusPiPi(angrad)); - boolean isNeg = (tmp < 0.0); - if (isNeg) { - tmp = -tmp; - } - degrees.value = (int)tmp; - tmp = (tmp-degrees.value)*60.0; - minutes.value = (int)tmp; - seconds.value = Math.min((tmp-minutes.value)*60.0,DOUBLE_BEFORE_60); - return !isNeg; - } - - /** - * NB: Since 2*Math.PI < 2*PI, a span of 2*Math.PI does not mean full angular range. - * ex.: isInClockwiseDomain(0.0, 2*Math.PI, -1e-20) returns false. - * ---> For full angular range, use a span > 2*Math.PI, like 2*PI_SUP constant of this class. - * - * @param startAngRad An angle, in radians. - * @param angSpanRad An angular span, >= 0.0, in radians. - * @param angRad An angle, in radians. - * @return true if angRad is in the clockwise angular domain going from startAngRad, over angSpanRad, - * extremities included, false otherwise. - */ - public static boolean isInClockwiseDomain(double startAngRad, double angSpanRad, double angRad) { - if (Math.abs(angRad) < -TWO_MATH_PI_IN_MINUS_PI_PI) { - // special case for angular values of small magnitude - if (angSpanRad <= 2*Math.PI) { - if (angSpanRad < 0.0) { - // empty domain - return false; - } - // angSpanRad is in [0,2*PI] - startAngRad = normalizeMinusPiPi(startAngRad); - double endAngRad = normalizeMinusPiPi(startAngRad + angSpanRad); - if (startAngRad <= endAngRad) { - return (angRad >= startAngRad) && (angRad <= endAngRad); - } else { - return (angRad >= startAngRad) || (angRad <= endAngRad); - } - } else { // angSpanRad > 2*Math.PI, or is NaN - return (angSpanRad == angSpanRad); - } - } else { - // general case - return (normalizeZeroTwoPi(angRad - startAngRad) <= angSpanRad); - } - } - - /* - * hyperbolic trigonometry - */ - - /** - * Some properties of sinh(x) = (exp(x)-exp(-x))/2: - * 1) defined on ]-Infinity,+Infinity[ - * 2) result in ]-Infinity,+Infinity[ - * 3) sinh(x) = -sinh(-x) (implies sinh(0) = 0) - * 4) sinh(epsilon) ~= epsilon - * 5) lim(sinh(x),x->+Infinity) = +Infinity - * (y increasing exponentially faster than x) - * 6) reaches +Infinity (double overflow) for x >= 710.475860073944, - * i.e. a bit further than exp(x) - * - * @param value A double value. - * @return Value hyperbolic sine. - */ - public static double sinh(double value) { - if (USE_JDK_MATH) { - return StrictMath.sinh(value); - } - // sinh(x) = (exp(x)-exp(-x))/2 - double h; - if (value < 0.0) { - value = -value; - h = -0.5; - } else { - h = 0.5; - } - if (value < 22.0) { - if (value < TWO_POW_N28) { - return (h < 0.0) ? -value : value; - } else { - // sinh(x) - // = (exp(x)-exp(-x))/2 - // = (exp(x)-1/exp(x))/2 - // = (expm1(x) + 1 - 1/(expm1(x)+1))/2 - // = (expm1(x) + (expm1(x)+1)/(expm1(x)+1) - 1/(expm1(x)+1))/2 - // = (expm1(x) + expm1(x)/(expm1(x)+1))/2 - double t = expm1(value); - // Might be more accurate, if value < 1: return h*((t+t)-t*t/(t+1.0)). - return h * (t + t/(t+1.0)); - } - } else if (value < LOG_DOUBLE_MAX_VALUE) { - return h * exp(value); - } else { - double t = exp(value*0.5); - return (h*t)*t; - } - } - - /** - * Some properties of cosh(x) = (exp(x)+exp(-x))/2: - * 1) defined on ]-Infinity,+Infinity[ - * 2) result in [1,+Infinity[ - * 3) cosh(0) = 1 - * 4) cosh(x) = cosh(-x) - * 5) lim(cosh(x),x->+Infinity) = +Infinity - * (y increasing exponentially faster than x) - * 6) reaches +Infinity (double overflow) for x >= 710.475860073944, - * i.e. a bit further than exp(x) - * - * @param value A double value. - * @return Value hyperbolic cosine. - */ - public static double cosh(double value) { - if (USE_JDK_MATH) { - return StrictMath.cosh(value); - } - // cosh(x) = (exp(x)+exp(-x))/2 - if (value < 0.0) { - value = -value; - } - if (value < LOG_TWO_POW_27) { - if (value < TWO_POW_N27) { - // cosh(x) - // = (exp(x)+exp(-x))/2 - // = ((1+x+x^2/2!+...) + (1-x+x^2/2!-...))/2 - // = 1+x^2/2!+x^4/4!+... - // For value of x small in magnitude, the sum of the terms does not add to 1. - return 1; - } else { - // cosh(x) - // = (exp(x)+exp(-x))/2 - // = (exp(x)+1/exp(x))/2 - double t = exp(value); - return 0.5 * (t+1/t); - } - } else if (value < LOG_DOUBLE_MAX_VALUE) { - return 0.5 * exp(value); - } else { - double t = exp(value*0.5); - return (0.5*t)*t; - } - } - - /** - * Much more accurate than cosh(value)-1, - * for arguments (and results) close to zero. - * - * coshm1(-0.0) = -0.0, for homogeneity with - * acosh1p(-0.0) = -0.0. - * - * @param value A double value. - * @return Value hyperbolic cosine, minus 1. - */ - public static double coshm1(double value) { - // cosh(x)-1 = (exp(x)+exp(-x))/2 - 1 - if (value < 0.0) { - value = -value; - } - if (value < LOG_TWO_POW_27) { - if (value < TWO_POW_N27) { - if (value == 0.0) { - // +-0.0 - return value; - } - // Using (expm1(x)+expm1(-x))/2 - // is not accurate for tiny values, - // for expm1 results are of higher - // magnitude than the result and - // of different signs, such as their - // sum is not accurate. - // cosh(x) - 1 - // = (exp(x)+exp(-x))/2 - 1 - // = ((1+x+x^2/2!+...) + (1-x+x^2/2!-...))/2 - 1 - // = x^2/2!+x^4/4!+... - // ~= x^2 * (1/2 + x^2 * 1/24) - // = x^2 * 0.5 (since x < 2^-27) - return 0.5 * value*value; - } else { - // cosh(x) - 1 - // = (exp(x)+exp(-x))/2 - 1 - // = (exp(x)-1+exp(-x)-1)/2 - // = (expm1(x)+expm1(-x))/2 - return 0.5 * (expm1(value)+expm1(-value)); - } - } else if (value < LOG_DOUBLE_MAX_VALUE) { - return 0.5 * exp(value) - 1.0; - } else { - // No need to subtract 1 from result. - double t = exp(value*0.5); - return (0.5*t)*t; - } - } - - /** - * Computes hyperbolic sine and hyperbolic cosine together. - * - * @param value A double value. - * @param hcosine (out) Value hyperbolic cosine. - * @return Value hyperbolic sine. - */ - public static double sinhAndCosh(double value, DoubleWrapper hcosine) { - if (USE_JDK_MATH) { - hcosine.value = StrictMath.cosh(value); - return StrictMath.sinh(value); - } - // Mixup of sinh and cosh treatments: if you modify them, - // you might want to also modify this. - double h; - if (value < 0.0) { - value = -value; - h = -0.5; - } else { - h = 0.5; - } - final double hsine; - // LOG_TWO_POW_27 = 18.714973875118524 - if (value < LOG_TWO_POW_27) { // test from cosh - // sinh - if (value < TWO_POW_N28) { - hsine = (h < 0.0) ? -value : value; - } else { - double t = expm1(value); - hsine = h * (t + t/(t+1.0)); - } - // cosh - if (value < TWO_POW_N27) { - hcosine.value = 1; - } else { - double t = exp(value); - hcosine.value = 0.5 * (t+1/t); - } - } else if (value < 22.0) { // test from sinh - // Here, value is in [18.714973875118524,22.0[. - double t = expm1(value); - hsine = h * (t + t/(t+1.0)); - hcosine.value = 0.5 * (t+1.0); - } else { - if (value < LOG_DOUBLE_MAX_VALUE) { - hsine = h * exp(value); - } else { - double t = exp(value*0.5); - hsine = (h*t)*t; - } - hcosine.value = Math.abs(hsine); - } - return hsine; - } - - /** - * Some properties of tanh(x) = sinh(x)/cosh(x) = (exp(2*x)-1)/(exp(2*x)+1): - * 1) defined on ]-Infinity,+Infinity[ - * 2) result in ]-1,1[ - * 3) tanh(x) = -tanh(-x) (implies tanh(0) = 0) - * 4) tanh(epsilon) ~= epsilon - * 5) lim(tanh(x),x->+Infinity) = 1 - * 6) reaches 1 (double loss of precision) for x = 19.061547465398498 - * - * @param value A double value. - * @return Value hyperbolic tangent. - */ - public static double tanh(double value) { - if (USE_JDK_MATH) { - return StrictMath.tanh(value); - } - // tanh(x) = sinh(x)/cosh(x) - // = (exp(x)-exp(-x))/(exp(x)+exp(-x)) - // = (exp(2*x)-1)/(exp(2*x)+1) - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - double z; - if (value < TANH_1_THRESHOLD) { - if (value < TWO_POW_N55) { - return negateResult ? -value*(1.0-value) : value*(1.0+value); - } else if (value >= 1) { - z = 1.0-2.0/(expm1(value+value)+2.0); - } else { - double t = expm1(-(value+value)); - z = -t/(t+2.0); - } - } else { - z = (value != value) ? Double.NaN : 1.0; - } - return negateResult ? -z : z; - } - - /** - * Some properties of asinh(x) = log(x + sqrt(x^2 + 1)) - * 1) defined on ]-Infinity,+Infinity[ - * 2) result in ]-Infinity,+Infinity[ - * 3) asinh(x) = -asinh(-x) (implies asinh(0) = 0) - * 4) asinh(epsilon) ~= epsilon - * 5) lim(asinh(x),x->+Infinity) = +Infinity - * (y increasing logarithmically slower than x) - * - * @param value A double value. - * @return Value hyperbolic arcsine. - */ - public static double asinh(double value) { - // asinh(x) = log(x + sqrt(x^2 + 1)) - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - double result; - // (about) smallest possible for - // non-log1p case to be accurate. - if (value < ASINH_LOG1P_THRESHOLD) { - // Around this range, FDLIBM uses - // log1p(value+value*value/(1+sqrt(value*value+1))), - // but it's slower, so we don't use it. - /* - * If x is close to zero, log argument is close to 1, - * so to avoid precision loss we use log1p(double), - * with - * (1+x)^p = 1 + p * x + (p*(p-1))/2! * x^2 + (p*(p-1)*(p-2))/3! * x^3 + ... - * (1+x)^p = 1 + p * x * (1 + (p-1)/2 * x * (1 + (p-2)/3 * x + ...) - * (1+x)^0.5 = 1 + 0.5 * x * (1 + (0.5-1)/2 * x * (1 + (0.5-2)/3 * x + ...) - * (1+x^2)^0.5 = 1 + 0.5 * x^2 * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...) - * x + (1+x^2)^0.5 = 1 + x * (1 + 0.5 * x * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...)) - * so - * asinh(x) = log1p(x * (1 + 0.5 * x * (1 + (0.5-1)/2 * x^2 * (1 + (0.5-2)/3 * x^2 + ...))) - */ - final double x = value; - final double x2 = x*x; - // Enough terms for good accuracy, - // given our threshold. - final double argLog1p = (x * - (1 + 0.5 * x - * (1 + (0.5-1)/2 * x2 - * (1 + (0.5-2)/3 * x2 - * (1 + (0.5-3)/4 * x2 - * (1 + (0.5-4)/5 * x2 - )))))); - result = log1p(argLog1p); - } else if (value < ASINH_ACOSH_SQRT_ELISION_THRESHOLD) { - // Around this range, FDLIBM uses - // log(2*value+1/(value+sqrt(value*value+1))), - // but it involves an additional division - // so we don't use it. - result = log(value + sqrt(value*value + 1.0)); - } else { - // log(2*value) would overflow for value > Double.MAX_VALUE/2, - // so we compute otherwise. - result = LOG_2 + log(value); - } - return negateResult ? -result : result; - } - - /** - * Some properties of acosh(x) = log(x + sqrt(x^2 - 1)): - * 1) defined on [1,+Infinity[ - * 2) result in ]0,+Infinity[ (by convention, since cosh(x) = cosh(-x)) - * 3) acosh(1) = 0 - * 4) acosh(1+epsilon) ~= log(1 + sqrt(2*epsilon)) ~= sqrt(2*epsilon) - * 5) lim(acosh(x),x->+Infinity) = +Infinity - * (y increasing logarithmically slower than x) - * - * @param value A double value. - * @return Value hyperbolic arccosine. - */ - public static double acosh(double value) { - if (!(value > 1.0)) { - // NaN, or value <= 1 - if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { - return (value < 1.0) ? Double.NaN : value - 1.0; - } else { - return (value == 1.0) ? 0.0 : Double.NaN; - } - } - double result; - if (value < ASINH_ACOSH_SQRT_ELISION_THRESHOLD) { - // Around this range, FDLIBM uses - // log(2*value-1/(value+sqrt(value*value-1))), - // but it involves an additional division - // so we don't use it. - result = log(value + sqrt(value*value - 1.0)); - } else { - // log(2*value) would overflow for value > Double.MAX_VALUE/2, - // so we compute otherwise. - result = LOG_2 + log(value); - } - return result; - } - - /** - * Much more accurate than acosh(1+value), - * for arguments (and results) close to zero. - * - * acosh1p(-0.0) = -0.0, for homogeneity with - * sqrt(-0.0) = -0.0, which looks about the same - * near 0. - * - * @param value A double value. - * @return Hyperbolic arccosine of (1+value). - */ - public static double acosh1p(double value) { - if (!(value > 0.0)) { - // NaN, or value <= 0. - // If value is -0.0, returning -0.0. - if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { - return (value < 0.0) ? Double.NaN : value; - } else { - return (value == 0.0) ? value : Double.NaN; - } - } - double result; - if (value < (ASINH_ACOSH_SQRT_ELISION_THRESHOLD-1)) { - // acosh(1+x) - // = log((1+x) + sqrt((1+x)^2 - 1)) - // = log(1 + x + sqrt(1 + 2*x + x^2 - 1)) - // = log1p(x + sqrt(2*x + x^2)) - // = log1p(x + sqrt(x * (2 + x)) - result = log1p(value + sqrt(value * (2 + value))); - } else { - result = LOG_2 + log(1+value); - } - return result; - } - - /** - * Some properties of atanh(x) = log((1+x)/(1-x))/2: - * 1) defined on ]-1,1[ - * 2) result in ]-Infinity,+Infinity[ - * 3) atanh(-1) = -Infinity (by continuity) - * 4) atanh(1) = +Infinity (by continuity) - * 5) atanh(epsilon) ~= epsilon - * 6) lim(atanh(x),x->1) = +Infinity - * - * @param value A double value. - * @return Value hyperbolic arctangent. - */ - public static double atanh(double value) { - boolean negateResult = false; - if (value < 0.0) { - value = -value; - negateResult = true; - } - double result; - if (!(value < 1.0)) { - // NaN, or value >= 1 - if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { - result = (value > 1.0) ? Double.NaN : Double.POSITIVE_INFINITY + value; - } else { - result = (value == 1.0) ? Double.POSITIVE_INFINITY : Double.NaN; - } - } else { - // For value < 0.5, FDLIBM uses - // 0.5 * log1p((value+value) + (value+value)*value/(1-value)), - // instead, but this is good enough for us. - // atanh(x) - // = log((1+x)/(1-x))/2 - // = log((1-x+2x)/(1-x))/2 - // = log1p(2x/(1-x))/2 - result = 0.5 * log1p((value+value)/(1.0-value)); - } - return negateResult ? -result : result; - } - - /* - * exponentials - */ - - /** - * @param value A double value. - * @return e^value. - */ - public static double exp(double value) { - if (USE_JDK_MATH) { - return StrictMath.exp(value); - } - // exp(x) = exp([x])*exp(y) - // with [x] the integer part of x, and y = x-[x] - // ===> - // We find an approximation of y, called z. - // ===> - // exp(x) = exp([x])*(exp(z)*exp(epsilon)) - // with epsilon = y - z - // ===> - // We have exp([x]) and exp(z) pre-computed in tables, we "just" have to compute exp(epsilon). - // - // We use the same indexing (cast to int) to compute x integer part and the - // table index corresponding to z, to avoid two int casts. - // Also, to optimize index multiplication and division, we use powers of two, - // so that we can do it with bits shifts. - - if (value > EXP_OVERFLOW_LIMIT) { - return Double.POSITIVE_INFINITY; - } else if (!(value >= EXP_UNDERFLOW_LIMIT)) { - return (value != value) ? Double.NaN : 0.0; - } - - final int indexes = (int)(value*EXP_LO_INDEXING); - - final int valueInt; - if (indexes >= 0) { - valueInt = (indexes>>EXP_LO_INDEXING_DIV_SHIFT); - } else { - valueInt = -((-indexes)>>EXP_LO_INDEXING_DIV_SHIFT); - } - final double hiTerm = MyTExp.expHiTab[valueInt-(int)EXP_UNDERFLOW_LIMIT]; - - final int zIndex = indexes - (valueInt< 0.0) { - if (value == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } - - // For normal values not close to 1.0, we use the following formula: - // log(value) - // = log(2^exponent*1.mantissa) - // = log(2^exponent) + log(1.mantissa) - // = exponent * log(2) + log(1.mantissa) - // = exponent * log(2) + log(1.mantissaApprox) + log(1.mantissa/1.mantissaApprox) - // = exponent * log(2) + log(1.mantissaApprox) + log(1+epsilon) - // = exponent * log(2) + log(1.mantissaApprox) + epsilon-epsilon^2/2+epsilon^3/3-epsilon^4/4+... - // with: - // 1.mantissaApprox <= 1.mantissa, - // log(1.mantissaApprox) in table, - // epsilon = (1.mantissa/1.mantissaApprox)-1 - // - // To avoid bad relative error for small results, - // values close to 1.0 are treated aside, with the formula: - // log(x) = z*(2+z^2*((2.0/3)+z^2*((2.0/5))+z^2*((2.0/7))+...))) - // with z=(x-1)/(x+1) - - double h; - if (value > 0.95) { - if (value < 1.14) { - double z = (value-1.0)/(value+1.0); - double z2 = z*z; - return z*(2+z2*((2.0/3)+z2*((2.0/5)+z2*((2.0/7)+z2*((2.0/9)+z2*((2.0/11))))))); - } - h = 0.0; - } else if (value < DOUBLE_MIN_NORMAL) { - // Ensuring value is normal. - value *= TWO_POW_52; - // log(x*2^52) - // = log(x)-ln(2^52) - // = log(x)-52*ln(2) - h = -52*LOG_2; - } else { - h = 0.0; - } - - int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); - int valueExp = (valueBitsHi>>20)-MAX_DOUBLE_EXPONENT; - // Getting the first LOG_BITS bits of the mantissa. - int xIndex = ((valueBitsHi<<12)>>>(32-LOG_BITS)); - - // 1.mantissa/1.mantissaApprox - 1 - double z = (value * twoPowNormalOrSubnormal(-valueExp)) * MyTLog.logXInvTab[xIndex] - 1; - - z *= (1-z*((1.0/2)-z*((1.0/3)))); - - return h + valueExp * LOG_2 + (MyTLog.logXLogTab[xIndex] + z); - - } else if (value == 0.0) { - return Double.NEGATIVE_INFINITY; - } else { // value < 0.0, or value is NaN - return Double.NaN; - } - } - - /** - * Quick log, with a max relative error of about 1.9e-3 - * for values in ]Double.MIN_NORMAL,+Infinity[, and - * worse accuracy outside this range. - * - * @param value A double value, in ]0,+Infinity[ (strictly positive and finite). - * @return Value logarithm (base e). - */ - public static double logQuick(double value) { - if (USE_JDK_MATH) { - return StrictMath.log(value); - } - /* - * Inverse of Schraudolph's method for exp, is very inaccurate near 1, - * and not that fast (even using floats), especially with added if's - * to deal with values near 1, so we don't use it, and use a simplified - * version of our log's redefined algorithm. - */ - - // Simplified version of log's redefined algorithm: - // log(value) ~= exponent * log(2) + log(1.mantissaApprox) - - double h; - if (value > 0.87) { - if (value < 1.16) { - return 2.0 * (value-1.0)/(value+1.0); - } - h = 0.0; - } else if (value < DOUBLE_MIN_NORMAL) { - value *= TWO_POW_52; - h = -52*LOG_2; - } else { - h = 0.0; - } - - int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); - int valueExp = (valueBitsHi>>20)-MAX_DOUBLE_EXPONENT; - int xIndex = ((valueBitsHi<<12)>>>(32-LOG_BITS)); - - return h + valueExp * LOG_2 + MyTLog.logXLogTab[xIndex]; - } - - /** - * @param value A double value. - * @return Value logarithm (base 10). - */ - public static double log10(double value) { - if (USE_JDK_MATH || (!USE_REDEFINED_LOG)) { - return StrictMath.log10(value); - } - // INV_LOG_10 is < 1, but there is no risk of log(double) - // overflow (positive or negative) while the end result shouldn't, - // since log(Double.MIN_VALUE) and log(Double.MAX_VALUE) have - // magnitudes of just a few hundreds. - return log(value) * INV_LOG_10; - } - - /** - * Much more accurate than log(1+value), - * for arguments (and results) close to zero. - * - * @param value A double value. - * @return Logarithm (base e) of (1+value). - */ - public static double log1p(double value) { - if (USE_JDK_MATH) { - return StrictMath.log1p(value); - } - if (false) { - // This also works. Simpler but a bit slower. - if (value == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } - double valuePlusOne = 1+value; - if (valuePlusOne == 1.0) { - return value; - } else { - return log(valuePlusOne)*(value/(valuePlusOne-1.0)); - } - } - if (value > -1.0) { - if (value == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } - - // ln'(x) = 1/x - // so - // log(x+epsilon) ~= log(x) + epsilon/x - // - // Let u be 1+value rounded: - // 1+value = u+epsilon - // - // log(1+value) - // = log(u+epsilon) - // ~= log(u) + epsilon/value - // We compute log(u) as done in log(double), and then add the corrective term. - - double valuePlusOne = 1.0+value; - if (valuePlusOne == 1.0) { - return value; - } else if (Math.abs(value) < 0.15) { - double z = value/(value+2.0); - double z2 = z*z; - return z*(2+z2*((2.0/3)+z2*((2.0/5)+z2*((2.0/7)+z2*((2.0/9)+z2*((2.0/11))))))); - } - - int valuePlusOneBitsHi = (int)(Double.doubleToRawLongBits(valuePlusOne)>>32) & 0x7FFFFFFF; - int valuePlusOneExp = (valuePlusOneBitsHi>>20)-MAX_DOUBLE_EXPONENT; - // Getting the first LOG_BITS bits of the mantissa. - int xIndex = ((valuePlusOneBitsHi<<12)>>>(32-LOG_BITS)); - - // 1.mantissa/1.mantissaApprox - 1 - double z = (valuePlusOne * twoPowNormalOrSubnormal(-valuePlusOneExp)) * MyTLog.logXInvTab[xIndex] - 1; - - z *= (1-z*((1.0/2)-z*(1.0/3))); - - // Adding epsilon/valuePlusOne to z, - // with - // epsilon = value - (valuePlusOne-1) - // (valuePlusOne + epsilon ~= 1+value (not rounded)) - - return valuePlusOneExp * LOG_2 + MyTLog.logXLogTab[xIndex] + (z + (value - (valuePlusOne-1))/valuePlusOne); - } else if (value == -1.0) { - return Double.NEGATIVE_INFINITY; - } else { // value < -1.0, or value is NaN - return Double.NaN; - } - } - - /* - * powers - */ - - /** - * 1e-13ish accuracy or better on whole double range. - * - * @param value A double value. - * @param power A power. - * @return value^power. - */ - public static double pow(double value, double power) { - if (USE_JDK_MATH) { - return StrictMath.pow(value,power); - } - if (power == 0.0) { - return 1.0; - } else if (power == 1.0) { - return value; - } - if (value <= 0.0) { - // powerInfo: 0 if not integer, 1 if even integer, -1 if odd integer - int powerInfo; - if (Math.abs(power) >= (TWO_POW_52*2)) { - // The binary digit just before comma is outside mantissa, - // thus it is always 0: power is an even integer. - powerInfo = 1; - } else { - // If power's magnitude permits, we cast into int instead of into long, - // as it is faster. - if (Math.abs(power) <= (double)Integer.MAX_VALUE) { - int powerAsInt = (int)power; - if (power == (double)powerAsInt) { - powerInfo = ((powerAsInt & 1) == 0) ? 1 : -1; - } else { // power is not an integer (and not NaN, due to test against Integer.MAX_VALUE) - powerInfo = 0; - } - } else { - long powerAsLong = (long)power; - if (power == (double)powerAsLong) { - powerInfo = ((powerAsLong & 1) == 0) ? 1 : -1; - } else { // power is not an integer, or is NaN - if (power != power) { - return Double.NaN; - } - powerInfo = 0; - } - } - } - - if (value == 0.0) { - if (power < 0.0) { - return (powerInfo < 0) ? 1/value : Double.POSITIVE_INFINITY; - } else { // power > 0.0 (0 and NaN cases already treated) - return (powerInfo < 0) ? value : 0.0; - } - } else { // value < 0.0 - if (value == Double.NEGATIVE_INFINITY) { - if (powerInfo < 0) { // power odd integer - return (power < 0.0) ? -0.0 : Double.NEGATIVE_INFINITY; - } else { // power even integer, or not an integer - return (power < 0.0) ? 0.0 : Double.POSITIVE_INFINITY; - } - } else { - return (powerInfo == 0) ? Double.NaN : powerInfo * exp(power*log(-value)); - } - } - } else { // value > 0.0, or value is NaN - return exp(power*log(value)); - } - } - - /** - * Quick pow, with a max relative error of about 1e-2 - * for value >= Double.MIN_NORMAL and 1e-10 < |value^power| < 1e10, - * of about 6e-2 for value >= Double.MIN_NORMAL and 1e-40 < |value^power| < 1e40, - * and worse accuracy otherwise. - * - * @param value A double value, in ]0,+Infinity[ (strictly positive and finite). - * @param power A double value. - * @return value^power. - */ - public static double powQuick(double value, double power) { - if (USE_JDK_MATH) { - return StrictMath.pow(value,power); - } - return exp(power*logQuick(value)); - } - - /** - * This treatment is somehow accurate for low values of |power|, - * and for |power*getExponent(value)| < 1023 or so (to stay away - * from double extreme magnitudes (large and small)). - * - * @param value A double value. - * @param power A power. - * @return value^power. - */ - public static double powFast(double value, int power) { - if (USE_JDK_MATH) { - return StrictMath.pow(value,power); - } - if (power < 3) { - if (power < 0) { - // Opposite of Integer.MIN_VALUE does not exist as int. - if (power == Integer.MIN_VALUE) { - // Integer.MAX_VALUE = -(power+1) - return 1.0/(powFast(value,Integer.MAX_VALUE) * value); - } else { - return 1.0/powFast(value,-power); - } - } else { - // Here, power is in [0,2]. - if (power == 2) { // Most common case first. - return value * value; - } else if (power == 0) { - return 1.0; - } else { // power == 1 - return value; - } - } - } else { // power >= 4 - double oddRemains = 1.0; - // If power <= 5, faster to finish outside the loop. - while (power > 5) { - // Test if power is odd. - if ((power & 1) != 0) { - oddRemains *= value; - } - value *= value; - power >>= 1; // power = power / 2 - } - // Here, power is in [3,5]. - if (power == 3) { - return oddRemains * value * value * value; - } else { // power in [4,5]. - double v2 = value * value; - if (power == 4) { - return oddRemains * v2 * v2; - } else { // power == 5 - return oddRemains * v2 * v2 * value; - } - } - } - } - - /** - * @param value A float value. - * @return value*value. - */ - public static float pow2(float value) { - return value*value; - } - - /** - * @param value A double value. - * @return value*value. - */ - public static double pow2(double value) { - return value*value; - } - - /** - * @param value A float value. - * @return value*value*value. - */ - public static float pow3(float value) { - return value*value*value; - } - - /** - * @param value A double value. - * @return value*value*value. - */ - public static double pow3(double value) { - return value*value*value; - } - - /* - * roots - */ - - /** - * @param value A double value. - * @return Value square root. - */ - public static double sqrt(double value) { - if (USE_JDK_MATH || (!USE_REDEFINED_SQRT)) { - return StrictMath.sqrt(value); - } - // See cbrt for comments, sqrt uses the same ideas. - - if (!(value > 0.0)) { // value <= 0.0, or value is NaN - if (ANTI_JIT_OPTIM_CRASH_ON_NAN) { - return (value < 0.0) ? Double.NaN : value; - } else { - return (value == 0.0) ? value : Double.NaN; - } - } else if (value == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } - - double h; - if (value < DOUBLE_MIN_NORMAL) { - value *= TWO_POW_52; - h = 2*TWO_POW_N26; - } else { - h = 2.0; - } - - int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); - int valueExponentIndex = (valueBitsHi>>20)+(-MAX_DOUBLE_EXPONENT-MIN_DOUBLE_EXPONENT); - int xIndex = ((valueBitsHi<<12)>>>(32-SQRT_LO_BITS)); - - double result = MyTSqrt.sqrtXSqrtHiTab[valueExponentIndex] * MyTSqrt.sqrtXSqrtLoTab[xIndex]; - double slope = MyTSqrt.sqrtSlopeHiTab[valueExponentIndex] * MyTSqrt.sqrtSlopeLoTab[xIndex]; - value *= 0.25; - - result += (value - result * result) * slope; - result += (value - result * result) * slope; - return h*(result + (value - result * result) * slope); - } - - /** - * Quick sqrt, with with a max relative error of about 3.41e-2 - * for values in [Double.MIN_NORMAL,Double.MAX_VALUE], and worse - * accuracy outside this range. - * - * @param value A double value. - * @return Value square root. - */ - public static double sqrtQuick(double value) { - if (USE_JDK_MATH) { - return StrictMath.sqrt(value); - } - final long bits = Double.doubleToRawLongBits(value); - /* - * Constant determined empirically, using a random-based metaheuristic. - * Should be possible to find a better one. - */ - return Double.longBitsToDouble((bits+4606859074900000000L)>>>1); - } - - /** - * Quick inverse of square root, with a max relative error of about 3.44e-2 - * for values in [Double.MIN_NORMAL,Double.MAX_VALUE], and worse accuracy - * outside this range. - * - * This implementation uses zero step of Newton's method. - * Here are the max relative errors on [Double.MIN_NORMAL,Double.MAX_VALUE] - * depending on number of steps, if you want to copy-paste this code - * and use your own number: - * n=0: about 3.44e-2 - * n=1: about 1.75e-3 - * n=2: about 4.6e-6 - * n=3: about 3.17e-11 - * n=4: about 3.92e-16 - * n=5: about 3.03e-16 - * - * @param value A double value. - * @return Inverse of value square root. - */ - public static double invSqrtQuick(double value) { - if (USE_JDK_MATH) { - return 1/StrictMath.sqrt(value); - } - /* - * http://en.wikipedia.org/wiki/Fast_inverse_square_root - */ - if (false) { - // With one Newton step (much slower than - // 1/Math.sqrt(double) if not optimized). - final double halfInitial = value * 0.5; - long bits = Double.doubleToRawLongBits(value); - // If n=0, 6910474759270000000L might be better (3.38e-2 max relative error). - bits = 0x5FE6EB50C7B537A9L - (bits>>1); - value = Double.longBitsToDouble(bits); - value = value * (1.5 - halfInitial * value * value); // Newton step, can repeat. - return value; - } else { - return Double.longBitsToDouble(0x5FE6EB50C7B537A9L - (Double.doubleToRawLongBits(value)>>1)); - } - } - - /** - * @param value A double value. - * @return Value cubic root. - */ - public static double cbrt(double value) { - if (USE_JDK_MATH) { - return StrictMath.cbrt(value); - } - double h; - if (value < 0.0) { - if (value == Double.NEGATIVE_INFINITY) { - return Double.NEGATIVE_INFINITY; - } - value = -value; - // Making sure value is normal. - if (value < DOUBLE_MIN_NORMAL) { - value *= (TWO_POW_52*TWO_POW_26); - // h = * / - h = -2*TWO_POW_N26; - } else { - h = -2.0; - } - } else { - if (!(value < Double.POSITIVE_INFINITY)) { // value is +Infinity, or value is NaN - return value; - } - // Making sure value is normal. - if (value < DOUBLE_MIN_NORMAL) { - if (value == 0.0) { - // cbrt(0.0) = 0.0, cbrt(-0.0) = -0.0 - return value; - } - value *= (TWO_POW_52*TWO_POW_26); - h = 2*TWO_POW_N26; - } else { - h = 2.0; - } - } - - // Normal value is (2^ * ). - // First member cubic root is computed, and multiplied with an approximation - // of the cubic root of the second member, to end up with a good guess of - // the result before using Newton's (or Archimedes's) method. - // To compute the cubic root approximation, we use the formula "cbrt(value) = cbrt(x) * cbrt(value/x)", - // choosing x as close to value as possible but inferior to it, so that cbrt(value/x) is close to 1 - // (we could iterate on this method, using value/x as new value for each iteration, - // but finishing with Newton's method is faster). - - // Shift and cast into an int, which overall is faster than working with a long. - int valueBitsHi = (int)(Double.doubleToRawLongBits(value)>>32); - int valueExponentIndex = (valueBitsHi>>20)+(-MAX_DOUBLE_EXPONENT-MIN_DOUBLE_EXPONENT); - // Getting the first CBRT_LO_BITS bits of the mantissa. - int xIndex = ((valueBitsHi<<12)>>>(32-CBRT_LO_BITS)); - double result = MyTCbrt.cbrtXCbrtHiTab[valueExponentIndex] * MyTCbrt.cbrtXCbrtLoTab[xIndex]; - double slope = MyTCbrt.cbrtSlopeHiTab[valueExponentIndex] * MyTCbrt.cbrtSlopeLoTab[xIndex]; - - // Lowering values to avoid overflows when using Newton's method - // (we will then just have to return twice the result). - // result^3 = value - // (result/2)^3 = value/8 - value *= 0.125; - // No need to divide result here, as division is factorized in result computation tables. - // result *= 0.5; - - // Newton's method, looking for y = x^(1/p): - // y(n) = y(n-1) + (x-y(n-1)^p) * slope(y(n-1)) - // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(x(n-1)^(1/p-1)) - // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(x(n-1)^((1-p)/p)) - // with x(n-1)=y(n-1)^p, i.e.: - // y(n) = y(n-1) + (x-y(n-1)^p) * (1/p)*(y(n-1)^(1-p)) - // - // For p=3: - // y(n) = y(n-1) + (x-y(n-1)^3) * (1/(3*y(n-1)^2)) - - // To save time, we don't recompute the slope between Newton's method steps, - // as initial slope is good enough for a few iterations. - // - // NB: slope = 1/(3*trueResult*trueResult) - // As we have result = trueResult/2 (to avoid overflows), we have: - // slope = 4/(3*result*result) - // = (4/3)*resultInv*resultInv - // with newResultInv = 1/newResult - // = 1/(oldResult+resultDelta) - // = (oldResultInv)*1/(1+resultDelta/oldResult) - // = (oldResultInv)*1/(1+resultDelta*oldResultInv) - // ~= (oldResultInv)*(1-resultDelta*oldResultInv) - // ===> Successive slopes could be computed without division, if needed, - // by computing resultInv (instead of slope right away) and retrieving - // slopes from it. - - result += (value - result * result * result) * slope; - result += (value - result * result * result) * slope; - return h*(result + (value - result * result * result) * slope); - } - - /** - * @return sqrt(x^2+y^2) without intermediate overflow or underflow. - */ - public static double hypot(double x, double y) { - if (USE_JDK_MATH) { - return StrictMath.hypot(x,y); - } - x = Math.abs(x); - y = Math.abs(y); - // Ensuring x <= y. - if (y < x) { - double a = x; - x = y; - y = a; - } else if (!(y >= x)) { // Testing if we have some NaN. - return hypot_NaN(x, y); - } - - if (y-x == y) { - // x too small to subtract from y. - return y; - } else { - double factor; - if (y > HYPOT_MAX_MAG) { - // y is too large: scaling down. - x *= (1/HYPOT_FACTOR); - y *= (1/HYPOT_FACTOR); - factor = HYPOT_FACTOR; - } else if (x < (1/HYPOT_MAX_MAG)) { - // x is too small: scaling up. - x *= HYPOT_FACTOR; - y *= HYPOT_FACTOR; - factor = (1/HYPOT_FACTOR); - } else { - factor = 1.0; - } - return factor * sqrt(x*x+y*y); - } - } - - /** - * @return sqrt(x^2+y^2+z^2) without intermediate overflow or underflow. - */ - public static double hypot(double x, double y, double z) { - if (USE_JDK_MATH) { - // No simple JDK equivalent. - } - x = Math.abs(x); - y = Math.abs(y); - z = Math.abs(z); - /* - * Considering that z magnitude is the most likely to be the smaller, - * hence ensuring z <= y <= x, and not x <= y <= z, for less swaps. - */ - // Ensuring z <= y. - if (z > y) { - // y < z: swapping y and z - double a = z; - z = y; - y = a; - } else if (!(z <= y)) { // Testing if y or z is NaN. - return hypot_NaN(x, y, z); - } - // Ensuring y <= x. - if (z > x) { - // x < z <= y: moving x - double oldZ = z; - z = x; - double oldY = y; - y = oldZ; - x = oldY; - } else if (y > x) { - // z <= x < y: swapping x and y - double a = y; - y = x; - x = a; - } else if (x != x) { // Testing if x is NaN. - return hypot_NaN(x, y, z); - } - - if (x-y == x) { - // y, hence z, too small to subtract from x. - return x; - } else if (y-z == y) { - // z too small to subtract from y, hence x. - double factor; - if (x > HYPOT_MAX_MAG) { - // x is too large: scaling down. - x *= (1/HYPOT_FACTOR); - y *= (1/HYPOT_FACTOR); - factor = HYPOT_FACTOR; - } else if (y < (1/HYPOT_MAX_MAG)) { - // y is too small: scaling up. - x *= HYPOT_FACTOR; - y *= HYPOT_FACTOR; - factor = (1/HYPOT_FACTOR); - } else { - factor = 1.0; - } - return factor * sqrt(x*x+y*y); - } else { - double factor; - if (x > HYPOT_MAX_MAG) { - // x is too large: scaling down. - x *= (1/HYPOT_FACTOR); - y *= (1/HYPOT_FACTOR); - z *= (1/HYPOT_FACTOR); - factor = HYPOT_FACTOR; - } else if (z < (1/HYPOT_MAX_MAG)) { - // z is too small: scaling up. - x *= HYPOT_FACTOR; - y *= HYPOT_FACTOR; - z *= HYPOT_FACTOR; - factor = (1/HYPOT_FACTOR); - } else { - factor = 1.0; - } - // Adding smaller magnitudes together first. - return factor * sqrt(x*x+(y*y+z*z)); - } - } - - /* - * close values - */ - - /** - * @param value A float value. - * @return Floor of value. - */ - public static float floor(float value) { - final int exponent = getExponent(value); - if (exponent < 0) { - // abs(value) < 1. - if (value < 0.0f) { - return -1.0f; - } else { - // 0.0f, or -0.0f if value is -0.0f - return 0.0f * value; - } - } else if (exponent < 23) { - // A bit faster than using casts. - final int bits = Float.floatToRawIntBits(value); - final int anteCommaBits = bits & (0xFF800000>>exponent); - if ((value < 0.0f) && (anteCommaBits != bits)) { - return Float.intBitsToFloat(anteCommaBits) - 1.0f; - } else { - return Float.intBitsToFloat(anteCommaBits); - } - } else { - // +-Infinity, NaN, or a mathematical integer. - return value; - } - } - - /** - * @param value A double value. - * @return Floor of value. - */ - public static double floor(double value) { - if (USE_JDK_MATH) { - return StrictMath.floor(value); - } - if (ANTI_SLOW_CASTS) { - double valueAbs = Math.abs(value); - if (valueAbs <= (double)Integer.MAX_VALUE) { - if (value > 0.0) { - return (double)(int)value; - } else if (value < 0.0) { - double anteCommaDigits = (double)(int)value; - if (value != anteCommaDigits) { - return anteCommaDigits - 1.0; - } else { - return anteCommaDigits; - } - } else { // value is +-0.0 (not NaN due to test against Integer.MAX_VALUE) - return value; - } - } else if (valueAbs < TWO_POW_52) { - // We split the value in two: - // high part, which is a mathematical integer, - // and the rest, for which we can get rid of the - // post comma digits by casting into an int. - double highPart = ((int)(value * TWO_POW_N26)) * TWO_POW_26; - if (value > 0.0) { - return highPart + (double)((int)(value - highPart)); - } else { - double anteCommaDigits = highPart + (double)((int)(value - highPart)); - if (value != anteCommaDigits) { - return anteCommaDigits - 1.0; - } else { - return anteCommaDigits; - } - } - } else { // abs(value) >= 2^52, or value is NaN - return value; - } - } else { - final int exponent = getExponent(value); - if (exponent < 0) { - // abs(value) < 1. - if (value < 0.0) { - return -1.0; - } else { - // 0.0, or -0.0 if value is -0.0 - return 0.0 * value; - } - } else if (exponent < 52) { - // A bit faster than working on bits. - final long matIntPart = (long)value; - final double matIntToValue = value-(double)matIntPart; - if (matIntToValue >= 0.0) { - return (double)matIntPart; - } else { - return (double)(matIntPart - 1); - } - } else { - // +-Infinity, NaN, or a mathematical integer. - return value; - } - } - } - - /** - * @param value A float value. - * @return Ceiling of value. - */ - public static float ceil(float value) { - return -floor(-value); - } - - /** - * @param value A double value. - * @return Ceiling of value. - */ - public static double ceil(double value) { - if (USE_JDK_MATH) { - return StrictMath.ceil(value); - } - return -floor(-value); - } - - /** - * Might have different semantics than StrictMath.round(float), - * see bugs 6430675 and 8010430. - * - * @param value A double value. - * @return Value rounded to nearest int, choosing superior int in case two - * are equally close (i.e. rounding-up). - */ - public static int round(float value) { - /* - * Not delegating to JDK, because we want delegation to provide - * at least as good results, and some supported JDK versions - * have bugged round() methods. - */ - // Algorithm by Dmitry Nadezhin (but replaced an if by a multiply) - // (http://mail.openjdk.java.net/pipermail/core-libs-dev/2013-August/020247.html). - final int bits = Float.floatToRawIntBits(value); - final int biasedExp = ((bits>>23)&0xFF); - // Shift to get rid of bits past comma except first one: will need to - // 1-shift to the right to end up with correct magnitude. - final int shift = (23 - 1 + MAX_FLOAT_EXPONENT) - biasedExp; - if ((shift & -32) == 0) { - int bitsSignum = (((bits >> 31) << 1) + 1); - // shift in [0,31], so unbiased exp in [-9,22]. - int extendedMantissa = (0x00800000 | (bits & 0x007FFFFF)) * bitsSignum; - // If value is positive and first bit past comma is 0, rounding - // to lower integer, else to upper one, which is what "+1" and - // then ">>1" do. - return ((extendedMantissa >> shift) + 1) >> 1; - } else { - // +-Infinity, NaN, or a mathematical integer, or tiny. - if (false && ANTI_SLOW_CASTS) { // not worth it - if (Math.abs(value) >= -(float)Integer.MIN_VALUE) { - // +-Infinity or a mathematical integer (mostly) out of int range. - return (value < 0.0) ? Integer.MIN_VALUE : Integer.MAX_VALUE; - } - // NaN or a mathematical integer (mostly) in int range. - } - return (int)value; - } - } - - /** - * Might have different semantics than StrictMath.round(double), - * see bugs 6430675 and 8010430. - * - * @param value A double value. - * @return Value rounded to nearest long, choosing superior long in case two - * are equally close (i.e. rounding-up). - */ - public static long round(double value) { - /* - * Not delegating to JDK, because we want delegation to provide - * at least as good results, and some supported JDK versions - * have bugged round() methods. - */ - final long bits = Double.doubleToRawLongBits(value); - final int biasedExp = (((int)(bits>>52))&0x7FF); - // Shift to get rid of bits past comma except first one: will need to - // 1-shift to the right to end up with correct magnitude. - final int shift = (52 - 1 + MAX_DOUBLE_EXPONENT) - biasedExp; - if ((shift & -64) == 0) { - long bitsSignum = (((bits >> 63) << 1) + 1); - // shift in [0,63], so unbiased exp in [-12,51]. - long extendedMantissa = (0x0010000000000000L | (bits & 0x000FFFFFFFFFFFFFL)) * bitsSignum; - // If value is positive and first bit past comma is 0, rounding - // to lower integer, else to upper one, which is what "+1" and - // then ">>1" do. - return ((extendedMantissa >> shift) + 1L) >> 1; - } else { - // +-Infinity, NaN, or a mathematical integer, or tiny. - if (ANTI_SLOW_CASTS) { - if (Math.abs(value) >= -(double)Long.MIN_VALUE) { - // +-Infinity or a mathematical integer (mostly) out of long range. - return (value < 0.0) ? Long.MIN_VALUE : Long.MAX_VALUE; - } - // NaN or a mathematical integer (mostly) in long range. - } - return (long)value; - } - } - - /** - * @param value A float value. - * @return Value rounded to nearest int, choosing even int in case two - * are equally close. - */ - public static int roundEven(float value) { - final int sign = signFromBit(value); - value = Math.abs(value); - if (ANTI_SLOW_CASTS) { - if (value < TWO_POW_23_F) { - // Getting rid of post-comma bits. - value = ((value + TWO_POW_23_F) - TWO_POW_23_F); - return sign * (int)value; - } else if (value < (float)Integer.MAX_VALUE) { // "<=" doesn't work, because of float precision - // value is in [-Integer.MAX_VALUE,Integer.MAX_VALUE] - return sign * (int)value; - } - } else { - if (value < TWO_POW_23_F) { - // Getting rid of post-comma bits. - value = ((value + TWO_POW_23_F) - TWO_POW_23_F); - } - } - return (int)(sign * value); - } - - /** - * @param value A double value. - * @return Value rounded to nearest long, choosing even long in case two - * are equally close. - */ - public static long roundEven(double value) { - final int sign = (int)signFromBit(value); - value = Math.abs(value); - if (value < TWO_POW_52) { - // Getting rid of post-comma bits. - value = ((value + TWO_POW_52) - TWO_POW_52); - } - if (ANTI_SLOW_CASTS) { - if (value <= (double)Integer.MAX_VALUE) { - // value is in [-Integer.MAX_VALUE,Integer.MAX_VALUE] - return sign * (int)value; - } - } - return (long)(sign * value); - } - - /** - * @param value A float value. - * @return The float mathematical integer closest to the specified value, - * choosing even one if two are equally close, or respectively - * NaN, +-Infinity or +-0.0f if the value is any of these. - */ - public static float rint(float value) { - final int sign = signFromBit(value); - value = Math.abs(value); - if (value < TWO_POW_23_F) { - // Getting rid of post-comma bits. - value = ((TWO_POW_23_F + value ) - TWO_POW_23_F); - } - // Restoring original sign. - return sign * value; - } - - /** - * @param value A double value. - * @return The double mathematical integer closest to the specified value, - * choosing even one if two are equally close, or respectively - * NaN, +-Infinity or +-0.0 if the value is any of these. - */ - public static double rint(double value) { - if (USE_JDK_MATH) { - return StrictMath.rint(value); - } - final int sign = (int)signFromBit(value); - value = Math.abs(value); - if (value < TWO_POW_52) { - // Getting rid of post-comma bits. - value = ((TWO_POW_52 + value ) - TWO_POW_52); - } - // Restoring original sign. - return sign * value; - } - - /* - * close int values - * - * Never delegating to JDK for these methods, for we should always - * be faster and exact, and JDK doesn't exactly have such methods. - */ - - /** - * @param value A double value. - * @return Floor of value as int, or closest int if floor is out - * of int range, or 0 if value is NaN. - */ - public static int floorToInt(double value) { - int valueInt = (int) value; - if (value < 0.0) { - if (value == (double) valueInt) { - return valueInt; - } else { - if (valueInt == Integer.MIN_VALUE) { - return valueInt; - } else { - return valueInt - 1; - } - } - } else { // >= 0 or NaN. - return valueInt; - } - } - - /** - * @param value A double value. - * @return Ceiling of value as int, or closest int if ceiling is out - * of int range, or 0 if value is NaN. - */ - public static int ceilToInt(double value) { - int valueInt = (int) value; - if (value > 0.0) { - if (value == (double) valueInt) { - return valueInt; - } else { - if (valueInt == Integer.MAX_VALUE) { - return valueInt; - } else { - return valueInt + 1; - } - } - } else { // <= 0 or NaN. - return valueInt; - } - } - - /** - * @param value A double value. - * @return Value rounded to nearest int, choosing superior int in case two - * are equally close (i.e. rounding-up). - */ - public static int roundToInt(double value) { - /* - * We don't gain much by reimplementing rounding, except for - * pathologically large values, which should not be a common case - * when dealing with ints, so we just use round(double). - */ - return NumbersUtils.toInt(round(value)); - } - - /** - * @param value A double value. - * @return Value rounded to nearest int, choosing even int in case two - * are equally close. - */ - public static int roundEvenToInt(double value) { - final int sign = (int)signFromBit(value); - value = Math.abs(value); - /* - * Applying the post-comma bits removal logic even if value is out - * of int range, to avoid a test, for it doesn't mess up the result, - * and we want to optimize for the case of values in int range. - */ - value = ((value + TWO_POW_52) - TWO_POW_52); - return (int)(sign * value); - } - - /* - * ranges - */ - - /** - * @param min A float value. - * @param max A float value. - * @param value A float value. - * @return min if value < min, max if value > max, value otherwise. - */ - public static float toRange(float min, float max, float value) { - return NumbersUtils.toRange(min, max, value); - } - - /** - * @param min A double value. - * @param max A double value. - * @param value A double value. - * @return min if value < min, max if value > max, value otherwise. - */ - public static double toRange(double min, double max, double value) { - return NumbersUtils.toRange(min, max, value); - } - - /* - * binary operators (/,%) - */ - - /** - * Returns dividend - divisor * n, where n is the mathematical integer - * closest to dividend/divisor. - * If dividend/divisor is equally close to surrounding integers, - * we choose n to be the integer of smallest magnitude, which makes - * this treatment differ from StrictMath.IEEEremainder(double,double), - * where n is chosen to be the even integer. - * Note that the choice of n is not done considering the double - * approximation of dividend/divisor, because it could cause - * result to be outside [-|divisor|/2,|divisor|/2] range. - * The practical effect is that if multiple results would be possible, - * we always choose the result that is the closest to (and has the same - * sign as) the dividend. - * Ex. : - * - for (-3.0,2.0), this method returns -1.0, - * whereas StrictMath.IEEEremainder returns 1.0. - * - for (-5.0,2.0), both this method and StrictMath.IEEEremainder return -1.0. - * - * If the remainder is zero, its sign is the same as the sign of the first argument. - * If either argument is NaN, or the first argument is infinite, - * or the second argument is positive zero or negative zero, - * then the result is NaN. - * If the first argument is finite and the second argument is - * infinite, then the result is the same as the first argument. - * - * NB: - * - Modulo operator (%) returns a value in ]-|divisor|,|divisor|[, - * which sign is the same as dividend. - * - As for modulo operator, the sign of the divisor has no effect on the result. - * - On some architecture, % operator has been observed to return NaN - * for some subnormal values of divisor, when dividend exponent is 1023, - * which impacts the correctness of this method. - * - * @param dividend Dividend. - * @param divisor Divisor. - * @return Remainder of dividend/divisor, i.e. a value in [-|divisor|/2,|divisor|/2]. - */ - public static double remainder(double dividend, double divisor) { - if (Double.isInfinite(divisor)) { - if (Double.isInfinite(dividend)) { - return Double.NaN; - } else { - return dividend; - } - } - double value = dividend % divisor; - if (Math.abs(value+value) > Math.abs(divisor)) { - return value + ((value > 0.0) ? -Math.abs(divisor) : Math.abs(divisor)); - } else { - return value; - } - } - - /** - * @param angle Angle in radians. - * @return The same angle, in radians, but in [-PI,PI]. - */ - public static double normalizeMinusPiPi(double angle) { - // Not modifying values in output range. - if ((angle >= -Math.PI) && (angle <= Math.PI)) { - return angle; - } - return remainderTwoPi(angle); - } - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return The same angle, in radians, but in [-PI,PI]. - */ - public static double normalizeMinusPiPiFast(double angle) { - // Not modifying values in output range. - if ((angle >= -Math.PI) && (angle <= Math.PI)) { - return angle; - } - return remainderTwoPiFast(angle); - } - - /** - * @param angle Angle in radians. - * @return The same angle, in radians, but in [0,2*PI]. - */ - public static double normalizeZeroTwoPi(double angle) { - // Not modifying values in output range. - if ((angle >= 0.0) && (angle <= 2*Math.PI)) { - return angle; - } - angle = remainderTwoPi(angle); - if (angle < 0.0) { - // LO then HI is theoretically better (when starting near 0). - return (angle + TWOPI_LO) + TWOPI_HI; - } else { - return angle; - } - } - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return The same angle, in radians, but in [0,2*PI]. - */ - public static double normalizeZeroTwoPiFast(double angle) { - // Not modifying values in output range. - if ((angle >= 0.0) && (angle <= 2*Math.PI)) { - return angle; - } - angle = remainderTwoPiFast(angle); - if (angle < 0.0) { - // LO then HI is theoretically better (when starting near 0). - return (angle + TWOPI_LO) + TWOPI_HI; - } else { - return angle; - } - } - - /** - * @param angle Angle in radians. - * @return Angle value modulo PI, in radians, in [-PI/2,PI/2]. - */ - public static double normalizeMinusHalfPiHalfPi(double angle) { - // Not modifying values in output range. - if ((angle >= -Math.PI/2) && (angle <= Math.PI/2)) { - return angle; - } - return remainderPi(angle); - } - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return Angle value modulo PI, in radians, in [-PI/2,PI/2]. - */ - public static double normalizeMinusHalfPiHalfPiFast(double angle) { - // Not modifying values in output range. - if ((angle >= -Math.PI/2) && (angle <= Math.PI/2)) { - return angle; - } - return remainderPiFast(angle); - } - - /* - * floating points utils - */ - - /** - * @param value A float value. - * @return true if the specified value is NaN or +-Infinity, false otherwise. - */ - public static boolean isNaNOrInfinite(float value) { - return NumbersUtils.isNaNOrInfinite(value); - } - - /** - * @param value A double value. - * @return true if the specified value is NaN or +-Infinity, false otherwise. - */ - public static boolean isNaNOrInfinite(double value) { - return NumbersUtils.isNaNOrInfinite(value); - } - - /** - * @param value A float value. - * @return Value unbiased exponent. - */ - public static int getExponent(float value) { - return ((Float.floatToRawIntBits(value)>>23)&0xFF)-MAX_FLOAT_EXPONENT; - } - - /** - * @param value A double value. - * @return Value unbiased exponent. - */ - public static int getExponent(double value) { - return (((int)(Double.doubleToRawLongBits(value)>>52))&0x7FF)-MAX_DOUBLE_EXPONENT; - } - - /** - * @param value A float value. - * @return -1.0f if the specified value is < 0, 1.0f if it is > 0, - * and the value itself if it is NaN or +-0.0f. - */ - public static float signum(float value) { - if (USE_JDK_MATH) { - return StrictMath.signum(value); - } - if ((value == 0.0f) || (value != value)) { - return value; - } - return (float)signFromBit(value); - } - - /** - * @param value A double value. - * @return -1.0 if the specified value is < 0, 1.0 if it is > 0, - * and the value itself if it is NaN or +-0.0. - */ - public static double signum(double value) { - if (USE_JDK_MATH) { - return StrictMath.signum(value); - } - if ((value == 0.0) || (value != value)) { - return value; - } - if (ANTI_SLOW_CASTS) { - return (double)(int)signFromBit(value); - } else { - return (double)signFromBit(value); - } - } - - /** - * @param value A float value. - * @return -1 if sign bit is 1, 1 if sign bit is 0. - */ - public static int signFromBit(float value) { - return ((Float.floatToRawIntBits(value)>>30)|1); - } - - /** - * @param value A double value. - * @return -1 if sign bit is 1, 1 if sign bit is 0. - */ - public static long signFromBit(double value) { - // Returning a long, to avoid useless cast into int. - return ((Double.doubleToRawLongBits(value)>>62)|1); - } - - /** - * A sign of NaN is interpreted as positive. - * - * @param magnitude A float value. - * @param sign A float value. - * @return A value with the magnitude of the first argument, and the sign - * of the second argument. - */ - public static float copySign(float magnitude, float sign) { - return Float.intBitsToFloat( - (Float.floatToRawIntBits((sign != sign) ? 1.0f : sign) & Integer.MIN_VALUE) - | (Float.floatToRawIntBits(magnitude) & Integer.MAX_VALUE)); - } - - /** - * A sign of NaN is interpreted as positive. - * - * @param magnitude A double value. - * @param sign A double value. - * @return A value with the magnitude of the first argument, and the sign - * of the second argument. - */ - public static double copySign(double magnitude, double sign) { - return Double.longBitsToDouble( - (Double.doubleToRawLongBits((sign != sign) ? 1.0 : sign) & Long.MIN_VALUE) - | (Double.doubleToRawLongBits(magnitude) & Long.MAX_VALUE)); - } - - /** - * The ULP (Unit in the Last Place) is the distance to the next value larger - * in magnitude. - * - * @param value A float value. - * @return The size of an ulp of the specified value, or Float.MIN_VALUE - * if it is +-0.0f, or +Infinity if it is +-Infinity, or NaN - * if it is NaN. - */ - public static float ulp(float value) { - if (USE_JDK_MATH) { - return StrictMath.ulp(value); - } - /* - * Look-up table not really worth it in micro-benchmark, - * so should be worse with cache-misses. - */ - final int exponent = getExponent(value); - if (exponent >= (MIN_FLOAT_NORMAL_EXPONENT+23)) { - if (exponent == MAX_FLOAT_EXPONENT+1) { - // NaN or +-Infinity - return Math.abs(value); - } - // normal: returning 2^(exponent-23) - return Float.intBitsToFloat((exponent+(MAX_FLOAT_EXPONENT-23))<<23); - } else { - if (exponent == MIN_FLOAT_NORMAL_EXPONENT-1) { - // +-0.0f or subnormal - return Float.MIN_VALUE; - } - // subnormal result - return Float.intBitsToFloat(1<<(exponent-MIN_FLOAT_NORMAL_EXPONENT)); - } - } - - /** - * The ULP (Unit in the Last Place) is the distance to the next value larger - * in magnitude. - * - * @param value A double value. - * @return The size of an ulp of the specified value, or Double.MIN_VALUE - * if it is +-0.0, or +Infinity if it is +-Infinity, or NaN - * if it is NaN. - */ - public static double ulp(double value) { - if (USE_JDK_MATH) { - return StrictMath.ulp(value); - } - /* - * Look-up table not really worth it in micro-benchmark, - * so should be worse with cache-misses. - */ - final int exponent = getExponent(value); - if (exponent >= (MIN_DOUBLE_NORMAL_EXPONENT+52)) { - if (exponent == MAX_DOUBLE_EXPONENT+1) { - // NaN or +-Infinity - return Math.abs(value); - } - // normal: returning 2^(exponent-52) - return Double.longBitsToDouble((exponent+(MAX_DOUBLE_EXPONENT-52L))<<52); - } else { - if (exponent == MIN_DOUBLE_NORMAL_EXPONENT-1) { - // +-0.0f or subnormal - return Double.MIN_VALUE; - } - // subnormal result - return Double.longBitsToDouble(1L<<(exponent-MIN_DOUBLE_NORMAL_EXPONENT)); - } - } - - /** - * If both arguments are +-0.0(f), (float)direction is returned. - * - * If both arguments are +Infinity or -Infinity, - * respectively +Infinity or -Infinity is returned. - * - * @param start A float value. - * @param direction A double value. - * @return The float adjacent to start towards direction, considering that - * +(-)Float.MIN_VALUE is adjacent to +(-)0.0f, and that - * +(-)Float.MAX_VALUE is adjacent to +(-)Infinity, - * or NaN if any argument is NaN. - */ - public static float nextAfter(float start, double direction) { - if (direction < start) { - // Going towards -Infinity. - if (start == 0.0f) { - // +-0.0f - return -Float.MIN_VALUE; - } - final int bits = Float.floatToRawIntBits(start); - return Float.intBitsToFloat(bits + ((bits > 0) ? -1 : 1)); - } else if (direction > start) { - // Going towards +Infinity. - // +0.0f to get rid of eventual -0.0f - final int bits = Float.floatToRawIntBits(start + 0.0f); - return Float.intBitsToFloat(bits + (bits >= 0 ? 1 : -1)); - } else if (start == direction) { - return (float)direction; - } else { - // Returning a NaN derived from the input NaN(s). - return start + (float)direction; - } - } - - /** - * If both arguments are +-0.0, direction is returned. - * - * If both arguments are +Infinity or -Infinity, - * respectively +Infinity or -Infinity is returned. - * - * @param start A double value. - * @param direction A double value. - * @return The double adjacent to start towards direction, considering that - * +(-)Double.MIN_VALUE is adjacent to +(-)0.0, and that - * +(-)Double.MAX_VALUE is adjacent to +(-)Infinity, - * or NaN if any argument is NaN. - */ - public static double nextAfter(double start, double direction) { - if (direction < start) { - // Going towards -Infinity. - if (start == 0.0) { - // +-0.0 - return -Double.MIN_VALUE; - } - final long bits = Double.doubleToRawLongBits(start); - return Double.longBitsToDouble(bits + ((bits > 0) ? -1 : 1)); - } else if (direction > start) { - // Going towards +Infinity. - // +0.0 to get rid of eventual -0.0 - final long bits = Double.doubleToRawLongBits(start + 0.0f); - return Double.longBitsToDouble(bits + (bits >= 0 ? 1 : -1)); - } else if (start == direction) { - return direction; - } else { - // Returning a NaN derived from the input NaN(s). - return start + direction; - } - } - - /** - * Semantically equivalent to nextAfter(start,Double.NEGATIVE_INFINITY). - */ - public static float nextDown(float start) { - if (start > Float.NEGATIVE_INFINITY) { - if (start == 0.0f) { - // +-0.0f - return -Float.MIN_VALUE; - } - final int bits = Float.floatToRawIntBits(start); - return Float.intBitsToFloat(bits + ((bits > 0) ? -1 : 1)); - } else if (start == Float.NEGATIVE_INFINITY) { - return Float.NEGATIVE_INFINITY; - } else { - // NaN - return start; - } - } - - /** - * Semantically equivalent to nextAfter(start,Double.NEGATIVE_INFINITY). - */ - public static double nextDown(double start) { - if (start > Double.NEGATIVE_INFINITY) { - if (start == 0.0) { - // +-0.0 - return -Double.MIN_VALUE; - } - final long bits = Double.doubleToRawLongBits(start); - return Double.longBitsToDouble(bits + ((bits > 0) ? -1 : 1)); - } else if (start == Double.NEGATIVE_INFINITY) { - return Double.NEGATIVE_INFINITY; - } else { - // NaN - return start; - } - } - - /** - * Semantically equivalent to nextAfter(start,Double.POSITIVE_INFINITY). - */ - public static float nextUp(float start) { - if (start < Float.POSITIVE_INFINITY) { - // +0.0f to get rid of eventual -0.0f - final int bits = Float.floatToRawIntBits(start + 0.0f); - return Float.intBitsToFloat(bits + (bits >= 0 ? 1 : -1)); - } else if (start == Float.POSITIVE_INFINITY) { - return Float.POSITIVE_INFINITY; - } else { - // NaN - return start; - } - } - - /** - * Semantically equivalent to nextAfter(start,Double.POSITIVE_INFINITY). - */ - public static double nextUp(double start) { - if (start < Double.POSITIVE_INFINITY) { - // +0.0 to get rid of eventual -0.0 - final long bits = Double.doubleToRawLongBits(start + 0.0); - return Double.longBitsToDouble(bits + (bits >= 0 ? 1 : -1)); - } else if (start == Double.POSITIVE_INFINITY) { - return Double.POSITIVE_INFINITY; - } else { - // NaN - return start; - } - } - - /** - * Precision may be lost if the result is subnormal. - * - * @param value A float value. - * @param scaleFactor An int value. - * @return value * 2^scaleFactor, or a value equivalent to the specified - * one if it is NaN, +-Infinity or +-0.0f. - */ - public static float scalb(float value, int scaleFactor) { - // Large enough to imply overflow or underflow for - // a finite non-zero value. - final int MAX_SCALE = 2*MAX_FLOAT_EXPONENT+23+1; - - // Making sure scaling factor is in a reasonable range. - scaleFactor = Math.max(Math.min(scaleFactor, MAX_SCALE), -MAX_SCALE); - - return (float)(((double)value) * twoPowNormal(scaleFactor)); - } - - /** - * Precision may be lost if the result is subnormal. - * - * @param value A double value. - * @param scaleFactor An int value. - * @return value * 2^scaleFactor, or a value equivalent to the specified - * one if it is NaN, +-Infinity or +-0.0. - */ - public static double scalb(double value, int scaleFactor) { - if ((scaleFactor > -MAX_DOUBLE_EXPONENT) && (scaleFactor <= MAX_DOUBLE_EXPONENT)) { - // Quick case (as done in apache FastMath). - return value * twoPowNormal(scaleFactor); - } - - // Large enough to imply overflow or underflow for - // a finite non-zero value. - final int MAX_SCALE = 2*MAX_DOUBLE_EXPONENT+52+1; - - // Making sure scaling factor is in a reasonable range. - final int exponentAdjust; - final int scaleIncrement; - final double exponentDelta; - if (scaleFactor < 0) { - scaleFactor = Math.max(scaleFactor, -MAX_SCALE); - scaleIncrement = -512; - exponentDelta = TWO_POW_N512; - } else { - scaleFactor = Math.min(scaleFactor, MAX_SCALE); - scaleIncrement = 512; - exponentDelta = TWO_POW_512; - } - - // Calculating (scaleFactor % +-512), 512 = 2^9, using - // technique from "Hacker's Delight" section 10-2. - final int t = ((scaleFactor >> (9-1)) >>> (32-9)); - exponentAdjust = ((scaleFactor + t) & (512-1)) - t; - - value *= twoPowNormal(exponentAdjust); - scaleFactor -= exponentAdjust; - - while (scaleFactor != 0) { - value *= exponentDelta; - scaleFactor -= scaleIncrement; - } - - return value; - } - - /* - * Non-redefined StrictMath public values and treatments. - */ - - public static float abs(float a) { - return StrictMath.abs(a); - } - - public static double abs(double a) { - return StrictMath.abs(a); - } - - public static float min(float a, float b) { - return StrictMath.min(a,b); - } - - public static double min(double a, double b) { - return StrictMath.min(a,b); - } - - public static float max(float a, float b) { - return StrictMath.max(a,b); - } - - public static double max(double a, double b) { - return StrictMath.max(a,b); - } - - public static double IEEEremainder(double f1, double f2) { - return StrictMath.IEEEremainder(f1,f2); - } - - public static double random() { - return StrictMath.random(); - } - - //-------------------------------------------------------------------------- - // PRIVATE METHODS - //-------------------------------------------------------------------------- - - /** - * Non-instantiable. - */ - private StrictFastMath() { - } - - /* - * Remainders (accurate). - */ - - /** - * @param angle Angle in radians. - * @return Remainder of (angle % (2*PI)), in [-PI,PI]. - */ - private static double remainderTwoPi(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderTwoPi(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle <= (4*NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2)) { - double fn = (double)(int)(angle*TWOPI_INV+0.5); - angle = (angle - fn*TWOPI_HI) - fn*TWOPI_LO; - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI) { - angle = (angle + TWOPI_HI) + TWOPI_LO; - } else if (angle > Math.PI) { - angle = (angle - TWOPI_HI) - TWOPI_LO; - } - return negateResult ? -angle : angle; - } else if (angle < Double.POSITIVE_INFINITY) { - angle = heavyRemainderTwoPi(angle); - return negateResult ? -angle : angle; - } else { // angle is +Infinity or NaN - return Double.NaN; - } - } - - /** - * @param angle Angle in radians. - * @return Remainder of (angle % PI), in [-PI/2,PI/2]. - */ - private static double remainderPi(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderPi(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle <= (2*NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2)) { - double fn = (double)(int)(angle*PI_INV+0.5); - angle = (angle - fn*PI_HI) - fn*PI_LO; - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI/2) { - angle = (angle + PI_HI) + PI_LO; - } else if (angle > Math.PI/2) { - angle = (angle - PI_HI) - PI_LO; - } - return negateResult ? -angle : angle; - } else if (angle < Double.POSITIVE_INFINITY) { - angle = heavyRemainderPi(angle); - return negateResult ? -angle : angle; - } else { // angle is +Infinity or NaN - return Double.NaN; - } - } - - /** - * @param angle Angle in radians. - * @return Bits of double corresponding to remainder of (angle % (PI/2)), - * in [-PI/4,PI/4], with quadrant encoded in exponent bits. - */ - private static long remainderPiO2(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderPiO2(angle, false); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - if (angle <= NORMALIZE_ANGLE_MAX_MEDIUM_DOUBLE_PIO2) { - int n = (int)(angle*PIO2_INV+0.5); - double fn = (double)n; - angle = (angle - fn*PIO2_HI) - fn*PIO2_LO; - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI/4) { - angle = (angle + PIO2_HI) + PIO2_LO; - n--; - } else if (angle > Math.PI/4) { - angle = (angle - PIO2_HI) - PIO2_LO; - n++; - } - if (negateResult) { - angle = -angle; - } - return encodeRemainderAndQuadrant(angle, n&3); - } else if (angle < Double.POSITIVE_INFINITY) { - return heavyRemainderPiO2(angle, negateResult); - } else { // angle is +Infinity or NaN - return encodeRemainderAndQuadrant(Double.NaN, 0); - } - } - - /* - * Remainders (fast). - */ - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return Remainder of (angle % (2*PI)), in [-PI,PI]. - */ - private static double remainderTwoPiFast(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderTwoPi(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - // - We don't bother with values higher than (2*PI*(2^52)), - // since they are spaced by 2*PI or more from each other. - // - For large values, we don't use % because it might be very slow, - // and we split computation in two, because cast from double to int - // with large numbers might be very slow also. - if (angle <= TWO_POW_26*(2*Math.PI)) { - // ok - } else if (angle <= TWO_POW_52*(2*Math.PI)) { - // Computing remainder of angle modulo TWO_POW_26*(2*PI). - double fn = (double)(int)(angle*(TWOPI_INV/TWO_POW_26)+0.5); - angle = (angle - fn*(TWOPI_HI*TWO_POW_26)) - fn*(TWOPI_LO*TWO_POW_26); - // Here, angle is in [-TWO_POW_26*PI,TWO_POW_26*PI], or so. - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } else if (angle < Double.POSITIVE_INFINITY) { - return 0.0; - } else { // angle is +Infinity or NaN - return Double.NaN; - } - - // Computing remainder of angle modulo 2*PI. - double fn = (double)(int)(angle*TWOPI_INV+0.5); - angle = (angle - fn*TWOPI_HI) - fn*TWOPI_LO; - - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI) { - angle = (angle + TWOPI_HI) + TWOPI_LO; - } else if (angle > Math.PI) { - angle = (angle - TWOPI_HI) - TWOPI_LO; - } - return negateResult ? -angle : angle; - } - - /** - * Not accurate for large values. - * - * @param angle Angle in radians. - * @return Remainder of (angle % PI), in [-PI/2,PI/2]. - */ - private static double remainderPiFast(double angle) { - if (USE_JDK_MATH) { - return jdkRemainderPi(angle); - } - boolean negateResult = false; - if (angle < 0.0) { - angle = -angle; - negateResult = true; - } - // - We don't bother with values higher than (PI*(2^52)), - // since they are spaced by PI or more from each other. - // - For large values, we don't use % because it might be very slow, - // and we split computation in two, because cast from double to int - // with large numbers might be very slow also. - if (angle <= TWO_POW_26*Math.PI) { - // ok - } else if (angle <= TWO_POW_52*Math.PI) { - // Computing remainder of angle modulo TWO_POW_26*PI. - double fn = (double)(int)(angle*(PI_INV/TWO_POW_26)+0.5); - angle = (angle - fn*(PI_HI*TWO_POW_26)) - fn*(PI_LO*TWO_POW_26); - // Here, angle is in [-TWO_POW_26*PI/2,TWO_POW_26*PI/2], or so. - if (angle < 0.0) { - angle = -angle; - negateResult = !negateResult; - } - } else if (angle < Double.POSITIVE_INFINITY) { - return 0.0; - } else { // angle is +Infinity or NaN - return Double.NaN; - } - - // Computing remainder of angle modulo PI. - double fn = (double)(int)(angle*PI_INV+0.5); - angle = (angle - fn*PI_HI) - fn*PI_LO; - - // Ensuring range. - // HI/LO can help a bit, even though we are always far from 0. - if (angle < -Math.PI/2) { - angle = (angle + PI_HI) + PI_LO; - } else if (angle > Math.PI/2) { - angle = (angle - PI_HI) - PI_LO; - } - return negateResult ? -angle : angle; - } -} From abb3d9fe5024f31d72354a38efeb3582b9357f46 Mon Sep 17 00:00:00 2001 From: therealansh Date: Thu, 3 Jun 2021 10:17:13 +0530 Subject: [PATCH 073/132] add: Double using StrictMath --- .../kscience/kmath/jafama/KMathJafama.kt | 103 +++++++++--------- 1 file changed, 53 insertions(+), 50 deletions(-) diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt index 2557004e9..9d4341036 100644 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt @@ -4,56 +4,7 @@ import space.kscience.kmath.operations.* import net.jafama.* /** - * Advanced Number-like semifield that implements basic operations. - */ -public interface ExtendedFieldOperations : - FieldOperations, - TrigonometricOperations, - PowerOperations, - ExponentialOperations { - public override fun tan(arg: T): T = sin(arg) / cos(arg) - public override fun tanh(arg: T): T = sinh(arg) / cosh(arg) - - public override fun unaryOperationFunction(operation: String): (arg: T) -> T = when (operation) { - TrigonometricOperations.COS_OPERATION -> ::cos - TrigonometricOperations.SIN_OPERATION -> ::sin - TrigonometricOperations.TAN_OPERATION -> ::tan - TrigonometricOperations.ACOS_OPERATION -> ::acos - TrigonometricOperations.ASIN_OPERATION -> ::asin - TrigonometricOperations.ATAN_OPERATION -> ::atan - PowerOperations.SQRT_OPERATION -> ::sqrt - ExponentialOperations.EXP_OPERATION -> ::exp - ExponentialOperations.LN_OPERATION -> ::ln - ExponentialOperations.COSH_OPERATION -> ::cosh - ExponentialOperations.SINH_OPERATION -> ::sinh - ExponentialOperations.TANH_OPERATION -> ::tanh - ExponentialOperations.ACOSH_OPERATION -> ::acosh - ExponentialOperations.ASINH_OPERATION -> ::asinh - ExponentialOperations.ATANH_OPERATION -> ::atanh - else -> super.unaryOperationFunction(operation) - } -} - -/** - * Advanced Number-like field that implements basic operations. - */ -public interface ExtendedField : ExtendedFieldOperations, Field, NumericAlgebra, ScaleOperations { - public override fun sinh(arg: T): T = (exp(arg) - exp(-arg)) / 2.0 - public override fun cosh(arg: T): T = (exp(arg) + exp(-arg)) / 2.0 - public override fun tanh(arg: T): T = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg)) - public override fun asinh(arg: T): T = ln(sqrt(arg * arg + one) + arg) - public override fun acosh(arg: T): T = ln(arg + sqrt((arg - one) * (arg + one))) - public override fun atanh(arg: T): T = (ln(arg + one) - ln(one - arg)) / 2.0 - - public override fun rightSideNumberOperationFunction(operation: String): (left: T, right: Number) -> T = - when (operation) { - PowerOperations.POW_OPERATION -> ::power - else -> super.rightSideNumberOperationFunction(operation) - } -} - -/** - * A field for [Double] without boxing. Does not produce appropriate field element. + * A field for [Double] (using FastMath) without boxing. Does not produce appropriate field element. */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object JafamaDoubleField : ExtendedField, Norm, ScaleOperations { @@ -101,3 +52,55 @@ public object JafamaDoubleField : ExtendedField, Norm, S public override inline fun Double.times(b: Double): Double = this * b public override inline fun Double.div(b: Double): Double = this / b } + +/** + * A field for [Double] (using StrictMath) without boxing. Does not produce appropriate field element. + */ +@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") +public object StrictJafamaDoubleField : ExtendedField, Norm, ScaleOperations { + public override inline val zero: Double get() = 0.0 + public override inline val one: Double get() = 1.0 + + public override fun number(value: Number): Double = value.toDouble() + + public override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = + when (operation) { + PowerOperations.POW_OPERATION -> ::power + else -> super.binaryOperationFunction(operation) + } + + public override inline fun add(a: Double, b: Double): Double = a + b + + public override inline fun multiply(a: Double, b: Double): Double = a * b + public override inline fun divide(a: Double, b: Double): Double = a / b + + public override fun scale(a: Double, value: Double): Double = a * value + + public override inline fun sin(arg: Double): Double = StrictFastMath.sin(arg) + public override inline fun cos(arg: Double): Double = StrictFastMath.cos(arg) + public override inline fun tan(arg: Double): Double = StrictFastMath.tan(arg) + public override inline fun acos(arg: Double): Double = StrictFastMath.acos(arg) + public override inline fun asin(arg: Double): Double = StrictFastMath.asin(arg) + public override inline fun atan(arg: Double): Double = StrictFastMath.atan(arg) + + public override inline fun sinh(arg: Double): Double = StrictFastMath.sinh(arg) + public override inline fun cosh(arg: Double): Double = StrictFastMath.cosh(arg) + public override inline fun tanh(arg: Double): Double = StrictFastMath.tanh(arg) + public override inline fun asinh(arg: Double): Double = StrictFastMath.asinh(arg) + public override inline fun acosh(arg: Double): Double = StrictFastMath.acosh(arg) + public override inline fun atanh(arg: Double): Double = StrictFastMath.atanh(arg) + + public override inline fun power(arg: Double, pow: Number): Double = StrictFastMath.pow(arg, pow.toDouble()) + public override inline fun exp(arg: Double): Double = StrictFastMath.exp(arg) + public override inline fun ln(arg: Double): Double = StrictFastMath.log(arg) + + public override inline fun norm(arg: Double): Double = StrictFastMath.abs(arg) + + public override inline fun Double.unaryMinus(): Double = -this + public override inline fun Double.plus(b: Double): Double = this + b + public override inline fun Double.minus(b: Double): Double = this - b + public override inline fun Double.times(b: Double): Double = this * b + public override inline fun Double.div(b: Double): Double = this / b +} + + From 590910ac2dcb0028046442ad0b740328eaecd356 Mon Sep 17 00:00:00 2001 From: therealansh Date: Sat, 5 Jun 2021 11:14:02 +0530 Subject: [PATCH 074/132] add: example and Readme --- README.md | 6 +++++ examples/build.gradle.kts | 2 ++ .../kscience/kmath/jafama/KMathaJafamaDemo.kt | 17 +++++++++++++ kmath-jafama/README.md | 24 +++++++++++++++++++ 4 files changed, 49 insertions(+) create mode 100644 examples/src/main/kotlin/space/kscience/kmath/jafama/KMathaJafamaDemo.kt create mode 100644 kmath-jafama/README.md diff --git a/README.md b/README.md index 7c6f7ea2b..90ab524e2 100644 --- a/README.md +++ b/README.md @@ -200,6 +200,12 @@ One can still use generic algebras though. > **Maturity**: PROTOTYPE
+* ### [kmath-jafama](kmath-jafama) +> +> +> **Maturity**: PROTOTYPE +
+ * ### [kmath-jupyter](kmath-jupyter) > > diff --git a/examples/build.gradle.kts b/examples/build.gradle.kts index 568bde153..406b8f470 100644 --- a/examples/build.gradle.kts +++ b/examples/build.gradle.kts @@ -44,6 +44,8 @@ dependencies { implementation("org.slf4j:slf4j-simple:1.7.30") // plotting implementation("space.kscience:plotlykt-server:0.4.0") + //jafama + implementation(project(":kmath-jafama")) } kotlin.sourceSets.all { diff --git a/examples/src/main/kotlin/space/kscience/kmath/jafama/KMathaJafamaDemo.kt b/examples/src/main/kotlin/space/kscience/kmath/jafama/KMathaJafamaDemo.kt new file mode 100644 index 000000000..879aab08f --- /dev/null +++ b/examples/src/main/kotlin/space/kscience/kmath/jafama/KMathaJafamaDemo.kt @@ -0,0 +1,17 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.jafama + +import net.jafama.FastMath + + +fun main(){ + val a = JafamaDoubleField.number(2.0) + val b = StrictJafamaDoubleField.power(FastMath.E,a) + + println(JafamaDoubleField.add(b,a)) + println(StrictJafamaDoubleField.ln(b)) +} diff --git a/kmath-jafama/README.md b/kmath-jafama/README.md new file mode 100644 index 000000000..fab777bf4 --- /dev/null +++ b/kmath-jafama/README.md @@ -0,0 +1,24 @@ +# Module kmath-jafama + +Jafama based implementation of DoubleField of kmath-operations. + +- JafamaDoubleField : DoubleField implementation using FastMath +- StrictJafamaDoubleField - DoubleField implementation using StrictFastMath + +## Examples + +Different Operations on DoubleField + +```kotlin +package space.kscience.kmath.jafama + +import net.jafama.FastMath + + +fun main(){ + val a = JafamaDoubleField.number(2.0) + val b = StrictJafamaDoubleField.power(FastMath.E,a) + println(JafamaDoubleField.add(b,a)) + println(StrictJafamaDoubleField.ln(b)) +} +``` From 9a9ebc730453735c5b6c0364d9fdbed1e92b3bc3 Mon Sep 17 00:00:00 2001 From: therealansh Date: Tue, 8 Jun 2021 19:19:55 +0530 Subject: [PATCH 075/132] add: benchmarks for Jafama --- benchmarks/build.gradle.kts | 7 +- .../kmath/benchmarks/JafamaBenchmark.kt | 48 ++++++++ .../kscience/kmath/jafama/KMathJafama.kt | 104 +++++++++--------- 3 files changed, 106 insertions(+), 53 deletions(-) create mode 100644 benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt diff --git a/benchmarks/build.gradle.kts b/benchmarks/build.gradle.kts index 98ffc5a96..182c182d9 100644 --- a/benchmarks/build.gradle.kts +++ b/benchmarks/build.gradle.kts @@ -30,6 +30,7 @@ kotlin { implementation(project(":kmath-stat")) implementation(project(":kmath-dimensions")) implementation(project(":kmath-for-real")) + implementation(project(":kmath-jafama")) implementation("org.jetbrains.kotlinx:kotlinx-benchmark-runtime:0.3.0") } } @@ -42,7 +43,6 @@ kotlin { implementation(project(":kmath-kotlingrad")) implementation(project(":kmath-viktor")) implementation("org.nd4j:nd4j-native:1.0.0-beta7") - // uncomment if your system supports AVX2 // val os = System.getProperty("os.name") // @@ -95,6 +95,11 @@ benchmark { commonConfiguration() include("BigIntBenchmark") } + + configurations.register("jafamaDouble") { + commonConfiguration() + include("JafamaBenchmark") + } } // Fix kotlinx-benchmarks bug diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt new file mode 100644 index 000000000..c828de82b --- /dev/null +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt @@ -0,0 +1,48 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.benchmarks + +import kotlinx.benchmark.Blackhole +import org.openjdk.jmh.annotations.Benchmark +import org.openjdk.jmh.annotations.Scope +import org.openjdk.jmh.annotations.State +import space.kscience.kmath.jafama.JafamaDoubleField +import space.kscience.kmath.jafama.StrictJafamaDoubleField +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.invoke + + +@State(Scope.Benchmark) +internal class JafamaBenchmark { + @Benchmark + fun jafamaBench(blackhole: Blackhole) = invokeBenchmarks(jafama, blackhole) + + @Benchmark + fun coreBench(blackhole: Blackhole) = invokeBenchmarks(core,blackhole) + + @Benchmark + fun strictJafamaBench(blackhole: Blackhole) = invokeBenchmarks(strictJafama,blackhole) + + private fun invokeBenchmarks(expr: Double, blackhole: Blackhole) { + blackhole.consume(expr) + } + + private companion object { + private val x: Double = Double.MAX_VALUE + + private val jafama = JafamaDoubleField{ + x * power(x, 1_000_000) * exp(x) / cos(x) + } + + private val core = DoubleField { + x * power(x, 1_000_000) * exp(x) / cos(x) + } + + private val strictJafama = StrictJafamaDoubleField { + x * power(x, 1_000_000) * exp(x) / cos(x) + } + } +} diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt index 9d4341036..f37d8e7b3 100644 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt @@ -8,8 +8,8 @@ import net.jafama.* */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object JafamaDoubleField : ExtendedField, Norm, ScaleOperations { - public override inline val zero: Double get() = 0.0 - public override inline val one: Double get() = 1.0 + public override val zero: Double get() = 0.0 + public override val one: Double get() = 1.0 public override fun number(value: Number): Double = value.toDouble() @@ -19,38 +19,38 @@ public object JafamaDoubleField : ExtendedField, Norm, S else -> super.binaryOperationFunction(operation) } - public override inline fun add(a: Double, b: Double): Double = a + b + public override fun add(a: Double, b: Double): Double = a + b - public override inline fun multiply(a: Double, b: Double): Double = a * b - public override inline fun divide(a: Double, b: Double): Double = a / b + public override fun multiply(a: Double, b: Double): Double = a * b + public override fun divide(a: Double, b: Double): Double = a / b public override fun scale(a: Double, value: Double): Double = a * value - public override inline fun sin(arg: Double): Double = FastMath.sin(arg) - public override inline fun cos(arg: Double): Double = FastMath.cos(arg) - public override inline fun tan(arg: Double): Double = FastMath.tan(arg) - public override inline fun acos(arg: Double): Double = FastMath.acos(arg) - public override inline fun asin(arg: Double): Double = FastMath.asin(arg) - public override inline fun atan(arg: Double): Double = FastMath.atan(arg) + public override fun sin(arg: Double): Double = FastMath.sin(arg) + public override fun cos(arg: Double): Double = FastMath.cos(arg) + public override fun tan(arg: Double): Double = FastMath.tan(arg) + public override fun acos(arg: Double): Double = FastMath.acos(arg) + public override fun asin(arg: Double): Double = FastMath.asin(arg) + public override fun atan(arg: Double): Double = FastMath.atan(arg) - public override inline fun sinh(arg: Double): Double = FastMath.sinh(arg) - public override inline fun cosh(arg: Double): Double = FastMath.cosh(arg) - public override inline fun tanh(arg: Double): Double = FastMath.tanh(arg) - public override inline fun asinh(arg: Double): Double = FastMath.asinh(arg) - public override inline fun acosh(arg: Double): Double = FastMath.acosh(arg) - public override inline fun atanh(arg: Double): Double = FastMath.atanh(arg) + public override fun sinh(arg: Double): Double = FastMath.sinh(arg) + public override fun cosh(arg: Double): Double = FastMath.cosh(arg) + public override fun tanh(arg: Double): Double = FastMath.tanh(arg) + public override fun asinh(arg: Double): Double = FastMath.asinh(arg) + public override fun acosh(arg: Double): Double = FastMath.acosh(arg) + public override fun atanh(arg: Double): Double = FastMath.atanh(arg) - public override inline fun power(arg: Double, pow: Number): Double = FastMath.pow(arg, pow.toDouble()) - public override inline fun exp(arg: Double): Double = FastMath.exp(arg) - public override inline fun ln(arg: Double): Double = FastMath.log(arg) + public override fun power(arg: Double, pow: Number): Double = FastMath.pow(arg, pow.toDouble()) + public override fun exp(arg: Double): Double = FastMath.exp(arg) + public override fun ln(arg: Double): Double = FastMath.log(arg) - public override inline fun norm(arg: Double): Double = FastMath.abs(arg) + public override fun norm(arg: Double): Double = FastMath.abs(arg) - public override inline fun Double.unaryMinus(): Double = -this - public override inline fun Double.plus(b: Double): Double = this + b - public override inline fun Double.minus(b: Double): Double = this - b - public override inline fun Double.times(b: Double): Double = this * b - public override inline fun Double.div(b: Double): Double = this / b + public override fun Double.unaryMinus(): Double = -this + public override fun Double.plus(b: Double): Double = this + b + public override fun Double.minus(b: Double): Double = this - b + public override fun Double.times(b: Double): Double = this * b + public override fun Double.div(b: Double): Double = this / b } /** @@ -58,8 +58,8 @@ public object JafamaDoubleField : ExtendedField, Norm, S */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object StrictJafamaDoubleField : ExtendedField, Norm, ScaleOperations { - public override inline val zero: Double get() = 0.0 - public override inline val one: Double get() = 1.0 + public override val zero: Double get() = 0.0 + public override val one: Double get() = 1.0 public override fun number(value: Number): Double = value.toDouble() @@ -69,38 +69,38 @@ public object StrictJafamaDoubleField : ExtendedField, Norm super.binaryOperationFunction(operation) } - public override inline fun add(a: Double, b: Double): Double = a + b + public override fun add(a: Double, b: Double): Double = a + b - public override inline fun multiply(a: Double, b: Double): Double = a * b - public override inline fun divide(a: Double, b: Double): Double = a / b + public override fun multiply(a: Double, b: Double): Double = a * b + public override fun divide(a: Double, b: Double): Double = a / b public override fun scale(a: Double, value: Double): Double = a * value - public override inline fun sin(arg: Double): Double = StrictFastMath.sin(arg) - public override inline fun cos(arg: Double): Double = StrictFastMath.cos(arg) - public override inline fun tan(arg: Double): Double = StrictFastMath.tan(arg) - public override inline fun acos(arg: Double): Double = StrictFastMath.acos(arg) - public override inline fun asin(arg: Double): Double = StrictFastMath.asin(arg) - public override inline fun atan(arg: Double): Double = StrictFastMath.atan(arg) + public override fun sin(arg: Double): Double = StrictFastMath.sin(arg) + public override fun cos(arg: Double): Double = StrictFastMath.cos(arg) + public override fun tan(arg: Double): Double = StrictFastMath.tan(arg) + public override fun acos(arg: Double): Double = StrictFastMath.acos(arg) + public override fun asin(arg: Double): Double = StrictFastMath.asin(arg) + public override fun atan(arg: Double): Double = StrictFastMath.atan(arg) - public override inline fun sinh(arg: Double): Double = StrictFastMath.sinh(arg) - public override inline fun cosh(arg: Double): Double = StrictFastMath.cosh(arg) - public override inline fun tanh(arg: Double): Double = StrictFastMath.tanh(arg) - public override inline fun asinh(arg: Double): Double = StrictFastMath.asinh(arg) - public override inline fun acosh(arg: Double): Double = StrictFastMath.acosh(arg) - public override inline fun atanh(arg: Double): Double = StrictFastMath.atanh(arg) + public override fun sinh(arg: Double): Double = StrictFastMath.sinh(arg) + public override fun cosh(arg: Double): Double = StrictFastMath.cosh(arg) + public override fun tanh(arg: Double): Double = StrictFastMath.tanh(arg) + public override fun asinh(arg: Double): Double = StrictFastMath.asinh(arg) + public override fun acosh(arg: Double): Double = StrictFastMath.acosh(arg) + public override fun atanh(arg: Double): Double = StrictFastMath.atanh(arg) - public override inline fun power(arg: Double, pow: Number): Double = StrictFastMath.pow(arg, pow.toDouble()) - public override inline fun exp(arg: Double): Double = StrictFastMath.exp(arg) - public override inline fun ln(arg: Double): Double = StrictFastMath.log(arg) + public override fun power(arg: Double, pow: Number): Double = StrictFastMath.pow(arg, pow.toDouble()) + public override fun exp(arg: Double): Double = StrictFastMath.exp(arg) + public override fun ln(arg: Double): Double = StrictFastMath.log(arg) - public override inline fun norm(arg: Double): Double = StrictFastMath.abs(arg) + public override fun norm(arg: Double): Double = StrictFastMath.abs(arg) - public override inline fun Double.unaryMinus(): Double = -this - public override inline fun Double.plus(b: Double): Double = this + b - public override inline fun Double.minus(b: Double): Double = this - b - public override inline fun Double.times(b: Double): Double = this * b - public override inline fun Double.div(b: Double): Double = this / b + public override fun Double.unaryMinus(): Double = -this + public override fun Double.plus(b: Double): Double = this + b + public override fun Double.minus(b: Double): Double = this - b + public override fun Double.times(b: Double): Double = this * b + public override fun Double.div(b: Double): Double = this / b } From b99d0b96d82289a738326b7b4a71df6064734519 Mon Sep 17 00:00:00 2001 From: therealansh Date: Tue, 8 Jun 2021 19:28:34 +0530 Subject: [PATCH 076/132] add:benchmarks to readme --- kmath-jafama/README.md | 44 ++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 44 insertions(+) diff --git a/kmath-jafama/README.md b/kmath-jafama/README.md index fab777bf4..bc5655a1e 100644 --- a/kmath-jafama/README.md +++ b/kmath-jafama/README.md @@ -22,3 +22,47 @@ fun main(){ println(StrictJafamaDoubleField.ln(b)) } ``` + +## Benchmarks +Comparing Operations on DoubleField and JafamaDoubleField +```bash +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench + +Warm-up 1: 242556635.528 ops/s +Iteration 1: 236249893.335 ops/s +Iteration 2: 294526940.968 ops/s +Iteration 3: 295973752.533 ops/s +Iteration 4: 296467676.763 ops/s +Iteration 5: 295929441.421 ops/s + +283829541.004 ±(99.9%) 102456604.440 ops/s [Average] + (min, avg, max) = (236249893.335, 283829541.004, 296467676.763), stdev = 26607654.808 + CI (99.9%): [181372936.564, 386286145.444] (assumes normal distribution) + +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench + +Warm-up 1: 234737640.196 ops/s +Iteration 1: 231689614.905 ops/s +Iteration 2: 296629612.909 ops/s +Iteration 3: 297456237.453 ops/s +Iteration 4: 296754794.513 ops/s +Iteration 5: 293722557.848 ops/s + +283250563.526 ±(99.9%) 111125582.233 ops/s [Average] + (min, avg, max) = (231689614.905, 283250563.526, 297456237.453), stdev = 28858960.811 + CI (99.9%): [172124981.293, 394376145.759] (assumes normal distribution) + +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench + +Warm-up 1: 234895701.589 ops/s +Iteration 1: 236061284.195 ops/s +Iteration 2: 296894799.416 ops/s +Iteration 3: 286852020.677 ops/s +Iteration 4: 284021863.614 ops/s +Iteration 5: 284404358.656 ops/s + +277646865.312 ±(99.9%) 91748868.927 ops/s [Average] + (min, avg, max) = (236061284.195, 277646865.312, 296894799.416), stdev = 23826889.899 + CI (99.9%): [185897996.385, 369395734.239] (assumes normal distribution) + +``` From 03be37bb4f6843a8fb08b3c44256df4f6bbdb15f Mon Sep 17 00:00:00 2001 From: therealansh Date: Sat, 12 Jun 2021 10:00:36 +0530 Subject: [PATCH 077/132] add: kotlin math benchmarks --- .../kmath/benchmarks/JafamaBenchmark.kt | 8 +++ kmath-jafama/README.md | 68 +++++++++++-------- 2 files changed, 48 insertions(+), 28 deletions(-) diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt index c828de82b..e998054fb 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt @@ -13,6 +13,9 @@ import space.kscience.kmath.jafama.JafamaDoubleField import space.kscience.kmath.jafama.StrictJafamaDoubleField import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke +import kotlin.math.cos +import kotlin.math.exp +import kotlin.math.pow @State(Scope.Benchmark) @@ -26,6 +29,9 @@ internal class JafamaBenchmark { @Benchmark fun strictJafamaBench(blackhole: Blackhole) = invokeBenchmarks(strictJafama,blackhole) + @Benchmark + fun kotlinMathBench(blackhole: Blackhole) = invokeBenchmarks(kotlinMath, blackhole) + private fun invokeBenchmarks(expr: Double, blackhole: Blackhole) { blackhole.consume(expr) } @@ -37,6 +43,8 @@ internal class JafamaBenchmark { x * power(x, 1_000_000) * exp(x) / cos(x) } + private val kotlinMath = x * x.pow(1_000_000) * exp(x) / cos(x) + private val core = DoubleField { x * power(x, 1_000_000) * exp(x) / cos(x) } diff --git a/kmath-jafama/README.md b/kmath-jafama/README.md index bc5655a1e..d170f6591 100644 --- a/kmath-jafama/README.md +++ b/kmath-jafama/README.md @@ -28,41 +28,53 @@ Comparing Operations on DoubleField and JafamaDoubleField ```bash jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench -Warm-up 1: 242556635.528 ops/s -Iteration 1: 236249893.335 ops/s -Iteration 2: 294526940.968 ops/s -Iteration 3: 295973752.533 ops/s -Iteration 4: 296467676.763 ops/s -Iteration 5: 295929441.421 ops/s +Warm-up 1: 384414358.081 ops/s +Iteration 1: 374827571.951 ops/s +Iteration 2: 479335182.332 ops/s +Iteration 3: 475483069.577 ops/s +Iteration 4: 478235949.414 ops/s +Iteration 5: 472256385.114 ops/s -283829541.004 ±(99.9%) 102456604.440 ops/s [Average] - (min, avg, max) = (236249893.335, 283829541.004, 296467676.763), stdev = 26607654.808 - CI (99.9%): [181372936.564, 386286145.444] (assumes normal distribution) +456027631.678 ±(99.9%) 175106815.384 ops/s [Average] + (min, avg, max) = (374827571.951, 456027631.678, 479335182.332), stdev = 45474683.880 + CI (99.9%): [280920816.294, 631134447.061] (assumes normal distribution) jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench -Warm-up 1: 234737640.196 ops/s -Iteration 1: 231689614.905 ops/s -Iteration 2: 296629612.909 ops/s -Iteration 3: 297456237.453 ops/s -Iteration 4: 296754794.513 ops/s -Iteration 5: 293722557.848 ops/s +Warm-up 1: 359418665.041 ops/s +Iteration 1: 335704885.798 ops/s +Iteration 2: 427684801.542 ops/s +Iteration 3: 452193034.265 ops/s +Iteration 4: 433855064.931 ops/s +Iteration 5: 453863386.566 ops/s -283250563.526 ±(99.9%) 111125582.233 ops/s [Average] - (min, avg, max) = (231689614.905, 283250563.526, 297456237.453), stdev = 28858960.811 - CI (99.9%): [172124981.293, 394376145.759] (assumes normal distribution) +420660234.620 ±(99.9%) 188028426.875 ops/s [Average] + (min, avg, max) = (335704885.798, 420660234.620, 453863386.566), stdev = 48830385.349 + CI (99.9%): [232631807.746, 608688661.495] (assumes normal distribution) + +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.kotlinMathBench + +Warm-up 1: 371570418.113 ops/s +Iteration 1: 379281146.127 ops/s +Iteration 2: 465234403.109 ops/s +Iteration 3: 470621634.240 ops/s +Iteration 4: 467074553.006 ops/s +Iteration 5: 466424840.144 ops/s + +449727315.325 ±(99.9%) 151837475.500 ops/s [Average] + (min, avg, max) = (379281146.127, 449727315.325, 470621634.240), stdev = 39431710.207 + CI (99.9%): [297889839.825, 601564790.825] (assumes normal distribution) jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench -Warm-up 1: 234895701.589 ops/s -Iteration 1: 236061284.195 ops/s -Iteration 2: 296894799.416 ops/s -Iteration 3: 286852020.677 ops/s -Iteration 4: 284021863.614 ops/s -Iteration 5: 284404358.656 ops/s - -277646865.312 ±(99.9%) 91748868.927 ops/s [Average] - (min, avg, max) = (236061284.195, 277646865.312, 296894799.416), stdev = 23826889.899 - CI (99.9%): [185897996.385, 369395734.239] (assumes normal distribution) +Warm-up 1: 371241281.065 ops/s +Iteration 1: 374490259.387 ops/s +Iteration 2: 464995837.424 ops/s +Iteration 3: 469788706.385 ops/s +Iteration 4: 469528470.682 ops/s +Iteration 5: 456727921.978 ops/s +447106239.171 ±(99.9%) 157629035.980 ops/s [Average] + (min, avg, max) = (374490259.387, 447106239.171, 469788706.385), stdev = 40935760.071 + CI (99.9%): [289477203.192, 604735275.151] (assumes normal distribution) ``` From 4d6428a3082c4c1b775cc1e70e35b42032e5ad49 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Mon, 14 Jun 2021 21:51:06 +0700 Subject: [PATCH 078/132] Update Jafama module documentation with some minor code amendments --- README.md | 8 +- benchmarks/build.gradle.kts | 1 + .../kmath/benchmarks/JafamaBenchmark.kt | 45 ++--- kmath-ast/build.gradle.kts | 7 +- .../kmath/ast/TestCompilerOperations.kt | 1 - .../kscience/kmath/operations/numbers.kt | 6 +- kmath-functions/build.gradle.kts | 5 +- kmath-jafama/README.md | 178 ++++++++++++------ kmath-jafama/build.gradle.kts | 7 + kmath-jafama/docs/README-TEMPLATE.md | 118 ++++++++++++ .../kscience/kmath/jafama/KMathJafama.kt | 124 ++++++------ 11 files changed, 341 insertions(+), 159 deletions(-) create mode 100644 kmath-jafama/docs/README-TEMPLATE.md diff --git a/README.md b/README.md index 90ab524e2..015988cd3 100644 --- a/README.md +++ b/README.md @@ -175,7 +175,7 @@ One can still use generic algebras though.
* ### [kmath-functions](kmath-functions) -> Functions, integration and interpolation +> > > **Maturity**: EXPERIMENTAL > @@ -201,9 +201,13 @@ One can still use generic algebras though.
* ### [kmath-jafama](kmath-jafama) -> +> > > **Maturity**: PROTOTYPE +> +> **Features:** +> - [jafama-double](kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/) : Double ExtendedField implementations based on Jafama +
* ### [kmath-jupyter](kmath-jupyter) diff --git a/benchmarks/build.gradle.kts b/benchmarks/build.gradle.kts index 182c182d9..f171437d3 100644 --- a/benchmarks/build.gradle.kts +++ b/benchmarks/build.gradle.kts @@ -12,6 +12,7 @@ repositories { maven("https://repo.kotlin.link") maven("https://clojars.org/repo") maven("https://jitpack.io") + maven("http://logicrunch.research.it.uu.se/maven") { isAllowInsecureProtocol = true } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt index e998054fb..260eea2b6 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt @@ -13,44 +13,27 @@ import space.kscience.kmath.jafama.JafamaDoubleField import space.kscience.kmath.jafama.StrictJafamaDoubleField import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke -import kotlin.math.cos -import kotlin.math.exp -import kotlin.math.pow - +import kotlin.random.Random @State(Scope.Benchmark) internal class JafamaBenchmark { @Benchmark - fun jafamaBench(blackhole: Blackhole) = invokeBenchmarks(jafama, blackhole) - - @Benchmark - fun coreBench(blackhole: Blackhole) = invokeBenchmarks(core,blackhole) - - @Benchmark - fun strictJafamaBench(blackhole: Blackhole) = invokeBenchmarks(strictJafama,blackhole) - - @Benchmark - fun kotlinMathBench(blackhole: Blackhole) = invokeBenchmarks(kotlinMath, blackhole) - - private fun invokeBenchmarks(expr: Double, blackhole: Blackhole) { - blackhole.consume(expr) + fun jafamaBench(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> + JafamaDoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) } } - private companion object { - private val x: Double = Double.MAX_VALUE + @Benchmark + fun coreBench(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> + DoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) } + } - private val jafama = JafamaDoubleField{ - x * power(x, 1_000_000) * exp(x) / cos(x) - } + @Benchmark + fun strictJafamaBench(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> + StrictJafamaDoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) } + } - private val kotlinMath = x * x.pow(1_000_000) * exp(x) / cos(x) - - private val core = DoubleField { - x * power(x, 1_000_000) * exp(x) / cos(x) - } - - private val strictJafama = StrictJafamaDoubleField { - x * power(x, 1_000_000) * exp(x) / cos(x) - } + private inline fun invokeBenchmarks(blackhole: Blackhole, expr: (Double) -> Double) { + val rng = Random(0) + repeat(1000000) { blackhole.consume(expr(rng.nextDouble())) } } } diff --git a/kmath-ast/build.gradle.kts b/kmath-ast/build.gradle.kts index 508374d82..89647c9e9 100644 --- a/kmath-ast/build.gradle.kts +++ b/kmath-ast/build.gradle.kts @@ -37,10 +37,9 @@ kotlin.sourceSets { jsMain { dependencies { - implementation(npm("astring", "1.7.4")) - implementation(npm("binaryen", "100.0")) - implementation(npm("js-base64", "3.6.0")) - implementation(npm("webassembly", "0.11.0")) + implementation(npm("astring", "1.7.5")) + implementation(npm("binaryen", "101.0.0")) + implementation(npm("js-base64", "3.6.1")) } } diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt index f869efd62..929d17775 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerOperations.kt @@ -9,7 +9,6 @@ import space.kscience.kmath.expressions.MstExtendedField import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.invoke import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke import kotlin.test.Test import kotlin.test.assertEquals diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt index 0d6d9e98d..36c13d6ec 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt @@ -64,7 +64,7 @@ public object DoubleField : ExtendedField, Norm, ScaleOp public override inline val zero: Double get() = 0.0 public override inline val one: Double get() = 1.0 - public override fun number(value: Number): Double = value.toDouble() + public override inline fun number(value: Number): Double = value.toDouble() public override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = when (operation) { @@ -77,7 +77,7 @@ public object DoubleField : ExtendedField, Norm, ScaleOp public override inline fun multiply(a: Double, b: Double): Double = a * b public override inline fun divide(a: Double, b: Double): Double = a / b - public override fun scale(a: Double, value: Double): Double = a * value + public override inline fun scale(a: Double, value: Double): Double = a * value public override inline fun sin(arg: Double): Double = kotlin.math.sin(arg) public override inline fun cos(arg: Double): Double = kotlin.math.cos(arg) @@ -93,6 +93,7 @@ public object DoubleField : ExtendedField, Norm, ScaleOp public override inline fun acosh(arg: Double): Double = kotlin.math.acosh(arg) public override inline fun atanh(arg: Double): Double = kotlin.math.atanh(arg) + public override inline fun sqrt(arg: Double): Double = kotlin.math.sqrt(arg) public override inline fun power(arg: Double, pow: Number): Double = arg.kpow(pow.toDouble()) public override inline fun exp(arg: Double): Double = kotlin.math.exp(arg) public override inline fun ln(arg: Double): Double = kotlin.math.ln(arg) @@ -143,6 +144,7 @@ public object FloatField : ExtendedField, Norm { public override inline fun acosh(arg: Float): Float = kotlin.math.acosh(arg) public override inline fun atanh(arg: Float): Float = kotlin.math.atanh(arg) + public override inline fun sqrt(arg: Float): Float = kotlin.math.sqrt(arg) public override inline fun power(arg: Float, pow: Number): Float = arg.kpow(pow.toFloat()) public override inline fun exp(arg: Float): Float = kotlin.math.exp(arg) public override inline fun ln(arg: Float): Float = kotlin.math.ln(arg) diff --git a/kmath-functions/build.gradle.kts b/kmath-functions/build.gradle.kts index 622b8f8da..f77df3833 100644 --- a/kmath-functions/build.gradle.kts +++ b/kmath-functions/build.gradle.kts @@ -3,6 +3,8 @@ plugins { id("ru.mipt.npm.gradle.common") } +description = "Functions, integration and interpolation" + kotlin.sourceSets.commonMain { dependencies { api(project(":kmath-core")) @@ -10,7 +12,6 @@ kotlin.sourceSets.commonMain { } readme { - description = "Functions, integration and interpolation" maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL propertyByTemplate("artifact", rootProject.file("docs/templates/ARTIFACT-TEMPLATE.md")) @@ -29,4 +30,4 @@ readme { feature("integration") { "Univariate and multivariate quadratures" } -} \ No newline at end of file +} diff --git a/kmath-jafama/README.md b/kmath-jafama/README.md index d170f6591..9b439c5c2 100644 --- a/kmath-jafama/README.md +++ b/kmath-jafama/README.md @@ -1,80 +1,144 @@ # Module kmath-jafama -Jafama based implementation of DoubleField of kmath-operations. +Integration with [Jafama](https://github.com/jeffhain/jafama). -- JafamaDoubleField : DoubleField implementation using FastMath -- StrictJafamaDoubleField - DoubleField implementation using StrictFastMath + - [jafama-double](src/main/kotlin/space/kscience/kmath/jafama/) : Double ExtendedField implementations based on Jafama -## Examples -Different Operations on DoubleField +## Artifact: +The Maven coordinates of this project are `space.kscience:kmath-jafama:0.3.0-dev-13`. + +**Gradle:** +```gradle +repositories { + maven { url 'https://repo.kotlin.link' } + mavenCentral() +} + +dependencies { + implementation 'space.kscience:kmath-jafama:0.3.0-dev-13' +} +``` +**Gradle Kotlin DSL:** ```kotlin -package space.kscience.kmath.jafama +repositories { + maven("https://repo.kotlin.link") + mavenCentral() +} -import net.jafama.FastMath - - -fun main(){ - val a = JafamaDoubleField.number(2.0) - val b = StrictJafamaDoubleField.power(FastMath.E,a) - println(JafamaDoubleField.add(b,a)) - println(StrictJafamaDoubleField.ln(b)) +dependencies { + implementation("space.kscience:kmath-jafama:0.3.0-dev-13") } ``` -## Benchmarks -Comparing Operations on DoubleField and JafamaDoubleField -```bash +## Example usage + +All the `DoubleField` uses can be replaced with `JafamaDoubleField` or `StrictJafamaDoubleField`. + +```kotlin +import space.kscience.kmath.jafama.* +import space.kscience.kmath.operations.* + +fun main() { + val a = 2.0 + val b = StrictJafamaDoubleField { exp(a) } + println(JafamaDoubleField { b + a }) + println(StrictJafamaDoubleField { ln(b) }) +} +``` + +## Performance + +According to benchmarking data, on Hotspot Jafama functions are 20% faster than JDK math. On GraalVM, they are slower. + +
+Raw data: + +**Hotspot** + +``` jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench -Warm-up 1: 384414358.081 ops/s -Iteration 1: 374827571.951 ops/s -Iteration 2: 479335182.332 ops/s -Iteration 3: 475483069.577 ops/s -Iteration 4: 478235949.414 ops/s -Iteration 5: 472256385.114 ops/s +Warm-up 1: 11.447 ops/s +Iteration 1: 13.354 ops/s +Iteration 2: 14.237 ops/s +Iteration 3: 14.708 ops/s +Iteration 4: 14.629 ops/s +Iteration 5: 14.692 ops/s -456027631.678 ±(99.9%) 175106815.384 ops/s [Average] - (min, avg, max) = (374827571.951, 456027631.678, 479335182.332), stdev = 45474683.880 - CI (99.9%): [280920816.294, 631134447.061] (assumes normal distribution) +14.324 ±(99.9%) 2.217 ops/s [Average] + (min, avg, max) = (13.354, 14.324, 14.708), stdev = 0.576 + CI (99.9%): [12.107, 16.541] (assumes normal distribution) jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench -Warm-up 1: 359418665.041 ops/s -Iteration 1: 335704885.798 ops/s -Iteration 2: 427684801.542 ops/s -Iteration 3: 452193034.265 ops/s -Iteration 4: 433855064.931 ops/s -Iteration 5: 453863386.566 ops/s +Warm-up 1: 15.628 ops/s +Iteration 1: 15.991 ops/s +Iteration 2: 16.633 ops/s +Iteration 3: 16.583 ops/s +Iteration 4: 16.716 ops/s +Iteration 5: 16.762 ops/s -420660234.620 ±(99.9%) 188028426.875 ops/s [Average] - (min, avg, max) = (335704885.798, 420660234.620, 453863386.566), stdev = 48830385.349 - CI (99.9%): [232631807.746, 608688661.495] (assumes normal distribution) - -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.kotlinMathBench - -Warm-up 1: 371570418.113 ops/s -Iteration 1: 379281146.127 ops/s -Iteration 2: 465234403.109 ops/s -Iteration 3: 470621634.240 ops/s -Iteration 4: 467074553.006 ops/s -Iteration 5: 466424840.144 ops/s - -449727315.325 ±(99.9%) 151837475.500 ops/s [Average] - (min, avg, max) = (379281146.127, 449727315.325, 470621634.240), stdev = 39431710.207 - CI (99.9%): [297889839.825, 601564790.825] (assumes normal distribution) +16.537 ±(99.9%) 1.205 ops/s [Average] + (min, avg, max) = (15.991, 16.537, 16.762), stdev = 0.313 + CI (99.9%): [15.332, 17.743] (assumes normal distribution) jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench -Warm-up 1: 371241281.065 ops/s -Iteration 1: 374490259.387 ops/s -Iteration 2: 464995837.424 ops/s -Iteration 3: 469788706.385 ops/s -Iteration 4: 469528470.682 ops/s -Iteration 5: 456727921.978 ops/s +Warm-up 1: 13.378 ops/s +Iteration 1: 15.049 ops/s +Iteration 2: 14.468 ops/s +Iteration 3: 14.469 ops/s +Iteration 4: 14.753 ops/s +Iteration 5: 14.958 ops/s -447106239.171 ±(99.9%) 157629035.980 ops/s [Average] - (min, avg, max) = (374490259.387, 447106239.171, 469788706.385), stdev = 40935760.071 - CI (99.9%): [289477203.192, 604735275.151] (assumes normal distribution) +14.739 ±(99.9%) 1.038 ops/s [Average] + (min, avg, max) = (14.468, 14.739, 15.049), stdev = 0.269 + CI (99.9%): [13.701, 15.777] (assumes normal distribution) ``` + +**GraalVM** + +``` +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench + +Warm-up 1: 14.357 ops/s +Iteration 1: 14.768 ops/s +Iteration 2: 14.922 ops/s +Iteration 3: 14.966 ops/s +Iteration 4: 14.805 ops/s +Iteration 5: 14.520 ops/s + +14.796 ±(99.9%) 0.671 ops/s [Average] + (min, avg, max) = (14.520, 14.796, 14.966), stdev = 0.174 + CI (99.9%): [14.125, 15.468] (assumes normal distribution) + +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench + +Warm-up 1: 11.592 ops/s +Iteration 1: 12.174 ops/s +Iteration 2: 11.734 ops/s +Iteration 3: 11.939 ops/s +Iteration 4: 12.026 ops/s +Iteration 5: 12.221 ops/s + +12.019 ±(99.9%) 0.752 ops/s [Average] + (min, avg, max) = (11.734, 12.019, 12.221), stdev = 0.195 + CI (99.9%): [11.267, 12.771] (assumes normal distribution) + +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench + +Warm-up 1: 12.097 ops/s +Iteration 1: 13.072 ops/s +Iteration 2: 13.112 ops/s +Iteration 3: 13.103 ops/s +Iteration 4: 12.950 ops/s +Iteration 5: 13.011 ops/s + +13.049 ±(99.9%) 0.263 ops/s [Average] + (min, avg, max) = (12.950, 13.049, 13.112), stdev = 0.068 + CI (99.9%): [12.787, 13.312] (assumes normal distribution) +``` + +
diff --git a/kmath-jafama/build.gradle.kts b/kmath-jafama/build.gradle.kts index f31f2602f..9cf328d0b 100644 --- a/kmath-jafama/build.gradle.kts +++ b/kmath-jafama/build.gradle.kts @@ -2,6 +2,8 @@ plugins { id("ru.mipt.npm.gradle.jvm") } +description = "Jafama integration module" + dependencies { api(project(":kmath-core")) api("net.jafama:jafama:2.3.2") @@ -13,6 +15,11 @@ repositories { readme { maturity = ru.mipt.npm.gradle.Maturity.PROTOTYPE + propertyByTemplate("artifact", rootProject.file("docs/templates/ARTIFACT-TEMPLATE.md")) + + feature("jafama-double", "src/main/kotlin/space/kscience/kmath/jafama/") { + "Double ExtendedField implementations based on Jafama" + } } kotlin.sourceSets.all { diff --git a/kmath-jafama/docs/README-TEMPLATE.md b/kmath-jafama/docs/README-TEMPLATE.md new file mode 100644 index 000000000..fa58f7697 --- /dev/null +++ b/kmath-jafama/docs/README-TEMPLATE.md @@ -0,0 +1,118 @@ +# Module kmath-jafama + +Integration with [Jafama](https://github.com/jeffhain/jafama). + +${features} + +${artifact} + +## Example usage + +All the `DoubleField` uses can be replaced with `JafamaDoubleField` or `StrictJafamaDoubleField`. + +```kotlin +import space.kscience.kmath.jafama.* +import space.kscience.kmath.operations.* + +fun main() { + val a = 2.0 + val b = StrictJafamaDoubleField { exp(a) } + println(JafamaDoubleField { b + a }) + println(StrictJafamaDoubleField { ln(b) }) +} +``` + +## Performance + +According to benchmarking data, on Hotspot Jafama functions are 20% faster than JDK math. On GraalVM, they are slower. + +
+Raw data: + +**Hotspot** + +``` +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench + +Warm-up 1: 11.447 ops/s +Iteration 1: 13.354 ops/s +Iteration 2: 14.237 ops/s +Iteration 3: 14.708 ops/s +Iteration 4: 14.629 ops/s +Iteration 5: 14.692 ops/s + +14.324 ±(99.9%) 2.217 ops/s [Average] + (min, avg, max) = (13.354, 14.324, 14.708), stdev = 0.576 + CI (99.9%): [12.107, 16.541] (assumes normal distribution) + +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench + +Warm-up 1: 15.628 ops/s +Iteration 1: 15.991 ops/s +Iteration 2: 16.633 ops/s +Iteration 3: 16.583 ops/s +Iteration 4: 16.716 ops/s +Iteration 5: 16.762 ops/s + +16.537 ±(99.9%) 1.205 ops/s [Average] + (min, avg, max) = (15.991, 16.537, 16.762), stdev = 0.313 + CI (99.9%): [15.332, 17.743] (assumes normal distribution) + +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench + +Warm-up 1: 13.378 ops/s +Iteration 1: 15.049 ops/s +Iteration 2: 14.468 ops/s +Iteration 3: 14.469 ops/s +Iteration 4: 14.753 ops/s +Iteration 5: 14.958 ops/s + +14.739 ±(99.9%) 1.038 ops/s [Average] + (min, avg, max) = (14.468, 14.739, 15.049), stdev = 0.269 + CI (99.9%): [13.701, 15.777] (assumes normal distribution) +``` + +**GraalVM** + +``` +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench + +Warm-up 1: 14.357 ops/s +Iteration 1: 14.768 ops/s +Iteration 2: 14.922 ops/s +Iteration 3: 14.966 ops/s +Iteration 4: 14.805 ops/s +Iteration 5: 14.520 ops/s + +14.796 ±(99.9%) 0.671 ops/s [Average] + (min, avg, max) = (14.520, 14.796, 14.966), stdev = 0.174 + CI (99.9%): [14.125, 15.468] (assumes normal distribution) + +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench + +Warm-up 1: 11.592 ops/s +Iteration 1: 12.174 ops/s +Iteration 2: 11.734 ops/s +Iteration 3: 11.939 ops/s +Iteration 4: 12.026 ops/s +Iteration 5: 12.221 ops/s + +12.019 ±(99.9%) 0.752 ops/s [Average] + (min, avg, max) = (11.734, 12.019, 12.221), stdev = 0.195 + CI (99.9%): [11.267, 12.771] (assumes normal distribution) + +jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench + +Warm-up 1: 12.097 ops/s +Iteration 1: 13.072 ops/s +Iteration 2: 13.112 ops/s +Iteration 3: 13.103 ops/s +Iteration 4: 12.950 ops/s +Iteration 5: 13.011 ops/s + +13.049 ±(99.9%) 0.263 ops/s [Average] + (min, avg, max) = (12.950, 13.049, 13.112), stdev = 0.068 + CI (99.9%): [12.787, 13.312] (assumes normal distribution) +``` + +
diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt index f37d8e7b3..cf6f9471d 100644 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt @@ -1,17 +1,21 @@ package space.kscience.kmath.jafama -import space.kscience.kmath.operations.* -import net.jafama.* +import net.jafama.FastMath +import net.jafama.StrictFastMath +import space.kscience.kmath.operations.ExtendedField +import space.kscience.kmath.operations.Norm +import space.kscience.kmath.operations.PowerOperations +import space.kscience.kmath.operations.ScaleOperations /** * A field for [Double] (using FastMath) without boxing. Does not produce appropriate field element. */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object JafamaDoubleField : ExtendedField, Norm, ScaleOperations { - public override val zero: Double get() = 0.0 - public override val one: Double get() = 1.0 + public override inline val zero: Double get() = 0.0 + public override inline val one: Double get() = 1.0 - public override fun number(value: Number): Double = value.toDouble() + public override inline fun number(value: Number): Double = value.toDouble() public override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = when (operation) { @@ -19,38 +23,39 @@ public object JafamaDoubleField : ExtendedField, Norm, S else -> super.binaryOperationFunction(operation) } - public override fun add(a: Double, b: Double): Double = a + b + public override inline fun add(a: Double, b: Double): Double = a + b - public override fun multiply(a: Double, b: Double): Double = a * b - public override fun divide(a: Double, b: Double): Double = a / b + public override inline fun multiply(a: Double, b: Double): Double = a * b + public override inline fun divide(a: Double, b: Double): Double = a / b - public override fun scale(a: Double, value: Double): Double = a * value + public override inline fun scale(a: Double, value: Double): Double = a * value - public override fun sin(arg: Double): Double = FastMath.sin(arg) - public override fun cos(arg: Double): Double = FastMath.cos(arg) - public override fun tan(arg: Double): Double = FastMath.tan(arg) - public override fun acos(arg: Double): Double = FastMath.acos(arg) - public override fun asin(arg: Double): Double = FastMath.asin(arg) - public override fun atan(arg: Double): Double = FastMath.atan(arg) + public override inline fun sin(arg: Double): Double = FastMath.sin(arg) + public override inline fun cos(arg: Double): Double = FastMath.cos(arg) + public override inline fun tan(arg: Double): Double = FastMath.tan(arg) + public override inline fun acos(arg: Double): Double = FastMath.acos(arg) + public override inline fun asin(arg: Double): Double = FastMath.asin(arg) + public override inline fun atan(arg: Double): Double = FastMath.atan(arg) - public override fun sinh(arg: Double): Double = FastMath.sinh(arg) - public override fun cosh(arg: Double): Double = FastMath.cosh(arg) - public override fun tanh(arg: Double): Double = FastMath.tanh(arg) - public override fun asinh(arg: Double): Double = FastMath.asinh(arg) - public override fun acosh(arg: Double): Double = FastMath.acosh(arg) - public override fun atanh(arg: Double): Double = FastMath.atanh(arg) + public override inline fun sinh(arg: Double): Double = FastMath.sinh(arg) + public override inline fun cosh(arg: Double): Double = FastMath.cosh(arg) + public override inline fun tanh(arg: Double): Double = FastMath.tanh(arg) + public override inline fun asinh(arg: Double): Double = FastMath.asinh(arg) + public override inline fun acosh(arg: Double): Double = FastMath.acosh(arg) + public override inline fun atanh(arg: Double): Double = FastMath.atanh(arg) - public override fun power(arg: Double, pow: Number): Double = FastMath.pow(arg, pow.toDouble()) - public override fun exp(arg: Double): Double = FastMath.exp(arg) - public override fun ln(arg: Double): Double = FastMath.log(arg) + public override inline fun sqrt(arg: Double): Double = FastMath.sqrt(arg) + public override inline fun power(arg: Double, pow: Number): Double = FastMath.pow(arg, pow.toDouble()) + public override inline fun exp(arg: Double): Double = FastMath.exp(arg) + public override inline fun ln(arg: Double): Double = FastMath.log(arg) - public override fun norm(arg: Double): Double = FastMath.abs(arg) + public override inline fun norm(arg: Double): Double = FastMath.abs(arg) - public override fun Double.unaryMinus(): Double = -this - public override fun Double.plus(b: Double): Double = this + b - public override fun Double.minus(b: Double): Double = this - b - public override fun Double.times(b: Double): Double = this * b - public override fun Double.div(b: Double): Double = this / b + public override inline fun Double.unaryMinus(): Double = -this + public override inline fun Double.plus(b: Double): Double = this + b + public override inline fun Double.minus(b: Double): Double = this - b + public override inline fun Double.times(b: Double): Double = this * b + public override inline fun Double.div(b: Double): Double = this / b } /** @@ -58,10 +63,10 @@ public object JafamaDoubleField : ExtendedField, Norm, S */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object StrictJafamaDoubleField : ExtendedField, Norm, ScaleOperations { - public override val zero: Double get() = 0.0 - public override val one: Double get() = 1.0 + public override inline val zero: Double get() = 0.0 + public override inline val one: Double get() = 1.0 - public override fun number(value: Number): Double = value.toDouble() + public override inline fun number(value: Number): Double = value.toDouble() public override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = when (operation) { @@ -69,38 +74,37 @@ public object StrictJafamaDoubleField : ExtendedField, Norm super.binaryOperationFunction(operation) } - public override fun add(a: Double, b: Double): Double = a + b + public override inline fun add(a: Double, b: Double): Double = a + b - public override fun multiply(a: Double, b: Double): Double = a * b - public override fun divide(a: Double, b: Double): Double = a / b + public override inline fun multiply(a: Double, b: Double): Double = a * b + public override inline fun divide(a: Double, b: Double): Double = a / b - public override fun scale(a: Double, value: Double): Double = a * value + public override inline fun scale(a: Double, value: Double): Double = a * value - public override fun sin(arg: Double): Double = StrictFastMath.sin(arg) - public override fun cos(arg: Double): Double = StrictFastMath.cos(arg) - public override fun tan(arg: Double): Double = StrictFastMath.tan(arg) - public override fun acos(arg: Double): Double = StrictFastMath.acos(arg) - public override fun asin(arg: Double): Double = StrictFastMath.asin(arg) - public override fun atan(arg: Double): Double = StrictFastMath.atan(arg) + public override inline fun sin(arg: Double): Double = StrictFastMath.sin(arg) + public override inline fun cos(arg: Double): Double = StrictFastMath.cos(arg) + public override inline fun tan(arg: Double): Double = StrictFastMath.tan(arg) + public override inline fun acos(arg: Double): Double = StrictFastMath.acos(arg) + public override inline fun asin(arg: Double): Double = StrictFastMath.asin(arg) + public override inline fun atan(arg: Double): Double = StrictFastMath.atan(arg) - public override fun sinh(arg: Double): Double = StrictFastMath.sinh(arg) - public override fun cosh(arg: Double): Double = StrictFastMath.cosh(arg) - public override fun tanh(arg: Double): Double = StrictFastMath.tanh(arg) - public override fun asinh(arg: Double): Double = StrictFastMath.asinh(arg) - public override fun acosh(arg: Double): Double = StrictFastMath.acosh(arg) - public override fun atanh(arg: Double): Double = StrictFastMath.atanh(arg) + public override inline fun sinh(arg: Double): Double = StrictFastMath.sinh(arg) + public override inline fun cosh(arg: Double): Double = StrictFastMath.cosh(arg) + public override inline fun tanh(arg: Double): Double = StrictFastMath.tanh(arg) + public override inline fun asinh(arg: Double): Double = StrictFastMath.asinh(arg) + public override inline fun acosh(arg: Double): Double = StrictFastMath.acosh(arg) + public override inline fun atanh(arg: Double): Double = StrictFastMath.atanh(arg) - public override fun power(arg: Double, pow: Number): Double = StrictFastMath.pow(arg, pow.toDouble()) - public override fun exp(arg: Double): Double = StrictFastMath.exp(arg) - public override fun ln(arg: Double): Double = StrictFastMath.log(arg) + public override inline fun sqrt(arg: Double): Double = StrictFastMath.sqrt(arg) + public override inline fun power(arg: Double, pow: Number): Double = StrictFastMath.pow(arg, pow.toDouble()) + public override inline fun exp(arg: Double): Double = StrictFastMath.exp(arg) + public override inline fun ln(arg: Double): Double = StrictFastMath.log(arg) - public override fun norm(arg: Double): Double = StrictFastMath.abs(arg) + public override inline fun norm(arg: Double): Double = StrictFastMath.abs(arg) - public override fun Double.unaryMinus(): Double = -this - public override fun Double.plus(b: Double): Double = this + b - public override fun Double.minus(b: Double): Double = this - b - public override fun Double.times(b: Double): Double = this * b - public override fun Double.div(b: Double): Double = this / b + public override inline fun Double.unaryMinus(): Double = -this + public override inline fun Double.plus(b: Double): Double = this + b + public override inline fun Double.minus(b: Double): Double = this - b + public override inline fun Double.times(b: Double): Double = this * b + public override inline fun Double.div(b: Double): Double = this / b } - - From 45f158817551cf277688d42c3cdb8994f6401023 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Tue, 15 Jun 2021 13:18:40 +0700 Subject: [PATCH 079/132] Generated benchmarking reports --- benchmarks/build.gradle.kts | 8 +- .../kmath/benchmarks/JafamaBenchmark.kt | 6 +- buildSrc/build.gradle.kts | 16 ++- .../kscience/kmath/benchmarks/JmhReport.kt | 60 ++++++++++ .../benchmarks/addBenchmarkProperties.kt | 105 ++++++++++++++++++ kmath-ast/build.gradle.kts | 12 +- kmath-jafama/README.md | 97 +++------------- kmath-jafama/docs/README-TEMPLATE.md | 93 +--------------- settings.gradle.kts | 2 +- 9 files changed, 210 insertions(+), 189 deletions(-) create mode 100644 buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt create mode 100644 buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt diff --git a/benchmarks/build.gradle.kts b/benchmarks/build.gradle.kts index f171437d3..2198ac5d6 100644 --- a/benchmarks/build.gradle.kts +++ b/benchmarks/build.gradle.kts @@ -1,3 +1,7 @@ +@file:Suppress("UNUSED_VARIABLE") + +import space.kscience.kmath.benchmarks.addBenchmarkProperties + plugins { kotlin("multiplatform") kotlin("plugin.allopen") @@ -32,7 +36,7 @@ kotlin { implementation(project(":kmath-dimensions")) implementation(project(":kmath-for-real")) implementation(project(":kmath-jafama")) - implementation("org.jetbrains.kotlinx:kotlinx-benchmark-runtime:0.3.0") + implementation("org.jetbrains.kotlinx:kotlinx-benchmark-runtime:0.3.1") } } @@ -130,3 +134,5 @@ tasks.withType { readme { maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL } + +addBenchmarkProperties() diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt index 260eea2b6..24a730375 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt @@ -18,17 +18,17 @@ import kotlin.random.Random @State(Scope.Benchmark) internal class JafamaBenchmark { @Benchmark - fun jafamaBench(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> + fun jafama(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> JafamaDoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) } } @Benchmark - fun coreBench(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> + fun core(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> DoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) } } @Benchmark - fun strictJafamaBench(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> + fun strictJafama(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> StrictJafamaDoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) } } diff --git a/buildSrc/build.gradle.kts b/buildSrc/build.gradle.kts index 7ca4df19d..8ff1c4369 100644 --- a/buildSrc/build.gradle.kts +++ b/buildSrc/build.gradle.kts @@ -1,5 +1,19 @@ plugins { `kotlin-dsl` + kotlin("plugin.serialization") version "1.4.31" } -repositories.mavenCentral() +repositories { + gradlePluginPortal() + mavenCentral() +} + +dependencies { + api("org.jetbrains.kotlinx:kotlinx-serialization-json:1.1.0") + api("ru.mipt.npm:gradle-tools:0.9.10") + api("org.jetbrains.kotlinx:kotlinx-benchmark-plugin:0.3.1") +} + +kotlin.sourceSets.all { + languageSettings.useExperimentalAnnotation("kotlin.ExperimentalStdlibApi") +} diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt new file mode 100644 index 000000000..eaa0f59d8 --- /dev/null +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt @@ -0,0 +1,60 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.benchmarks + +import kotlinx.serialization.Serializable + +@Serializable +data class JmhReport( + val jmhVersion: String, + val benchmark: String, + val mode: String, + val threads: Int, + val forks: Int, + val jvm: String, + val jvmArgs: List, + val jdkVersion: String, + val vmName: String, + val vmVersion: String, + val warmupIterations: Int, + val warmupTime: String, + val warmupBatchSize: Int, + val measurementIterations: Int, + val measurementTime: String, + val measurementBatchSize: Int, + val params: Map = emptyMap(), + val primaryMetric: PrimaryMetric, + val secondaryMetrics: Map, +) { + interface Metric { + val score: Double + val scoreError: Double + val scoreConfidence: List + val scorePercentiles: Map + val scoreUnit: String + } + + @Serializable + data class PrimaryMetric( + override val score: Double, + override val scoreError: Double, + override val scoreConfidence: List, + override val scorePercentiles: Map, + override val scoreUnit: String, + val rawDataHistogram: List>>>? = null, + val rawData: List>? = null, + ) : Metric + + @Serializable + data class SecondaryMetric( + override val score: Double, + override val scoreError: Double, + override val scoreConfidence: List, + override val scorePercentiles: Map, + override val scoreUnit: String, + val rawData: List>, + ) : Metric +} diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt new file mode 100644 index 000000000..31d952157 --- /dev/null +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt @@ -0,0 +1,105 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.benchmarks + +import kotlinx.serialization.* +import org.gradle.api.Project +import java.time.* +import java.time.format.* +import java.time.temporal.ChronoField.* + +private val ISO_DATE_TIME: DateTimeFormatter = DateTimeFormatterBuilder().run { + parseCaseInsensitive() + appendValue(YEAR, 4, 10, SignStyle.EXCEEDS_PAD) + appendLiteral('-') + appendValue(MONTH_OF_YEAR, 2) + appendLiteral('-') + appendValue(DAY_OF_MONTH, 2) + appendLiteral('T') + appendValue(HOUR_OF_DAY, 2) + appendLiteral('.') + appendValue(MINUTE_OF_HOUR, 2) + optionalStart() + appendLiteral('.') + appendValue(SECOND_OF_MINUTE, 2) + optionalStart() + appendFraction(NANO_OF_SECOND, 0, 9, true) + optionalStart() + appendOffsetId() + optionalStart() + appendLiteral('[') + parseCaseSensitive() + appendZoneRegionId() + appendLiteral(']') + toFormatter() +} + +private fun noun(number: Number, singular: String, plural: String) = if (number.toLong() == 1L) singular else plural + +fun Project.addBenchmarkProperties() { + val benchmarksProject = this + rootProject.subprojects.forEach { p -> + p.extensions.findByType(ru.mipt.npm.gradle.KScienceReadmeExtension::class.java)?.run { + benchmarksProject.extensions.findByType(kotlinx.benchmark.gradle.BenchmarksExtension::class.java)?.configurations?.forEach { cfg -> + // TODO remove this hack when https://github.com/mipt-npm/gradle-tools/pull/15 is merged + @Suppress("UNCHECKED_CAST") + (javaClass.getDeclaredField("properties") + .also { + it.isAccessible = true + }[this] as MutableMap Any?>)["benchmark${cfg.name.replaceFirstChar(Char::uppercase)}"] = + { + val launches = benchmarksProject.buildDir.resolve("reports/benchmarks/${cfg.name}") + + val resDirectory = launches.listFiles()?.maxByOrNull { + LocalDateTime.parse(it.name, ISO_DATE_TIME).atZone(ZoneId.systemDefault()).toInstant() + } + + if (resDirectory == null) { + "> **Can't find appropriate benchmark data. Try generating readme files after running benchmarks**." + } else { + val reports = + kotlinx.serialization.json.Json.decodeFromString>( + resDirectory.resolve("jvm.json").readText() + ) + + buildString { + appendLine("
") + appendLine("") + appendLine("Report for benchmark configuration ${cfg.name}") + appendLine("") + appendLine() + val first = reports.first() + + appendLine("* Run on ${first.vmName} (build ${first.vmVersion}) with Java process:") + appendLine() + appendLine("```") + appendLine("${first.jvm} ${ + first.jvmArgs.joinToString(" ") + }") + appendLine("```") + + appendLine("* JMH ${first.jmhVersion} was used in `${first.mode}` mode with ${first.warmupIterations} warmup ${ + noun(first.warmupIterations, "iteration", "iterations") + } by ${first.warmupTime} and ${first.measurementIterations} measurement ${ + noun(first.measurementIterations, "iteration", "iterations") + } by ${first.measurementTime}.") + + appendLine() + appendLine("| Benchmark | Score |") + appendLine("|:---------:|:-----:|") + + reports.forEach { report -> + appendLine("|`${report.benchmark}`|${report.primaryMetric.score} ± ${report.primaryMetric.scoreError} ${report.primaryMetric.scoreUnit}|") + } + + appendLine("
") + } + } + } + } + } + } +} diff --git a/kmath-ast/build.gradle.kts b/kmath-ast/build.gradle.kts index 89647c9e9..8209a0dad 100644 --- a/kmath-ast/build.gradle.kts +++ b/kmath-ast/build.gradle.kts @@ -62,25 +62,21 @@ readme { feature( id = "expression-language", - description = "Expression language and its parser", ref = "src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt" - ) + ) { "Expression language and its parser" } feature( id = "mst-jvm-codegen", - description = "Dynamic MST to JVM bytecode compiler", ref = "src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt" - ) + ) { "Dynamic MST to JVM bytecode compiler" } feature( id = "mst-js-codegen", - description = "Dynamic MST to JS compiler", ref = "src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt" - ) + ) { "Dynamic MST to JS compiler" } feature( id = "rendering", - description = "Extendable MST rendering", ref = "src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt" - ) + ) { "Extendable MST rendering" } } diff --git a/kmath-jafama/README.md b/kmath-jafama/README.md index 9b439c5c2..ef8fcd352 100644 --- a/kmath-jafama/README.md +++ b/kmath-jafama/README.md @@ -50,95 +50,24 @@ fun main() { ## Performance -According to benchmarking data, on Hotspot Jafama functions are 20% faster than JDK math. On GraalVM, they are slower. +According to KMath benchmarks on GraalVM, Jafama functions are slower than JDK math; however, there are indications that on Hotspot Jafama is a bit faster.
-Raw data: + +Report for benchmark configuration jafamaDouble + -**Hotspot** +* Run on OpenJDK 64-Bit Server VM (build 11.0.11+8-jvmci-21.1-b05) with Java process: ``` -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench - -Warm-up 1: 11.447 ops/s -Iteration 1: 13.354 ops/s -Iteration 2: 14.237 ops/s -Iteration 3: 14.708 ops/s -Iteration 4: 14.629 ops/s -Iteration 5: 14.692 ops/s - -14.324 ±(99.9%) 2.217 ops/s [Average] - (min, avg, max) = (13.354, 14.324, 14.708), stdev = 0.576 - CI (99.9%): [12.107, 16.541] (assumes normal distribution) - -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench - -Warm-up 1: 15.628 ops/s -Iteration 1: 15.991 ops/s -Iteration 2: 16.633 ops/s -Iteration 3: 16.583 ops/s -Iteration 4: 16.716 ops/s -Iteration 5: 16.762 ops/s - -16.537 ±(99.9%) 1.205 ops/s [Average] - (min, avg, max) = (15.991, 16.537, 16.762), stdev = 0.313 - CI (99.9%): [15.332, 17.743] (assumes normal distribution) - -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench - -Warm-up 1: 13.378 ops/s -Iteration 1: 15.049 ops/s -Iteration 2: 14.468 ops/s -Iteration 3: 14.469 ops/s -Iteration 4: 14.753 ops/s -Iteration 5: 14.958 ops/s - -14.739 ±(99.9%) 1.038 ops/s [Average] - (min, avg, max) = (14.468, 14.739, 15.049), stdev = 0.269 - CI (99.9%): [13.701, 15.777] (assumes normal distribution) -``` - -**GraalVM** - -``` -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench - -Warm-up 1: 14.357 ops/s -Iteration 1: 14.768 ops/s -Iteration 2: 14.922 ops/s -Iteration 3: 14.966 ops/s -Iteration 4: 14.805 ops/s -Iteration 5: 14.520 ops/s - -14.796 ±(99.9%) 0.671 ops/s [Average] - (min, avg, max) = (14.520, 14.796, 14.966), stdev = 0.174 - CI (99.9%): [14.125, 15.468] (assumes normal distribution) - -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench - -Warm-up 1: 11.592 ops/s -Iteration 1: 12.174 ops/s -Iteration 2: 11.734 ops/s -Iteration 3: 11.939 ops/s -Iteration 4: 12.026 ops/s -Iteration 5: 12.221 ops/s - -12.019 ±(99.9%) 0.752 ops/s [Average] - (min, avg, max) = (11.734, 12.019, 12.221), stdev = 0.195 - CI (99.9%): [11.267, 12.771] (assumes normal distribution) - -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench - -Warm-up 1: 12.097 ops/s -Iteration 1: 13.072 ops/s -Iteration 2: 13.112 ops/s -Iteration 3: 13.103 ops/s -Iteration 4: 12.950 ops/s -Iteration 5: 13.011 ops/s - -13.049 ±(99.9%) 0.263 ops/s [Average] - (min, avg, max) = (12.950, 13.049, 13.112), stdev = 0.068 - CI (99.9%): [12.787, 13.312] (assumes normal distribution) +/home/commandertvis/graalvm-ce-java11/bin/java -XX:+UnlockExperimentalVMOptions -XX:+EnableJVMCIProduct -XX:-UnlockExperimentalVMOptions -XX:ThreadPriorityPolicy=1 -javaagent:/home/commandertvis/.gradle/caches/modules-2/files-2.1/org.jetbrains.kotlinx/kotlinx-coroutines-core-jvm/1.5.0/d8cebccdcddd029022aa8646a5a953ff88b13ac8/kotlinx-coroutines-core-jvm-1.5.0.jar -Dfile.encoding=UTF-8 -Duser.country=US -Duser.language=en -Duser.variant -ea ``` +* JMH 1.21 was used in `thrpt` mode with 1 warmup iteration by 1000 ms and 5 measurement iterations by 1000 ms. +| Benchmark | Score | +|:---------:|:-----:| +|`space.kscience.kmath.benchmarks.JafamaBenchmark.core`|14.296120859512893 ± 0.36462633435888736 ops/s| +|`space.kscience.kmath.benchmarks.JafamaBenchmark.jafama`|11.431566395649781 ± 2.570896777898243 ops/s| +|`space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafama`|11.746020495694117 ± 6.205909559197869 ops/s|
+ diff --git a/kmath-jafama/docs/README-TEMPLATE.md b/kmath-jafama/docs/README-TEMPLATE.md index fa58f7697..54348467b 100644 --- a/kmath-jafama/docs/README-TEMPLATE.md +++ b/kmath-jafama/docs/README-TEMPLATE.md @@ -24,95 +24,6 @@ fun main() { ## Performance -According to benchmarking data, on Hotspot Jafama functions are 20% faster than JDK math. On GraalVM, they are slower. +According to KMath benchmarks on GraalVM, Jafama functions are slower than JDK math; however, there are indications that on Hotspot Jafama is a bit faster. -
-Raw data: - -**Hotspot** - -``` -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench - -Warm-up 1: 11.447 ops/s -Iteration 1: 13.354 ops/s -Iteration 2: 14.237 ops/s -Iteration 3: 14.708 ops/s -Iteration 4: 14.629 ops/s -Iteration 5: 14.692 ops/s - -14.324 ±(99.9%) 2.217 ops/s [Average] - (min, avg, max) = (13.354, 14.324, 14.708), stdev = 0.576 - CI (99.9%): [12.107, 16.541] (assumes normal distribution) - -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench - -Warm-up 1: 15.628 ops/s -Iteration 1: 15.991 ops/s -Iteration 2: 16.633 ops/s -Iteration 3: 16.583 ops/s -Iteration 4: 16.716 ops/s -Iteration 5: 16.762 ops/s - -16.537 ±(99.9%) 1.205 ops/s [Average] - (min, avg, max) = (15.991, 16.537, 16.762), stdev = 0.313 - CI (99.9%): [15.332, 17.743] (assumes normal distribution) - -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench - -Warm-up 1: 13.378 ops/s -Iteration 1: 15.049 ops/s -Iteration 2: 14.468 ops/s -Iteration 3: 14.469 ops/s -Iteration 4: 14.753 ops/s -Iteration 5: 14.958 ops/s - -14.739 ±(99.9%) 1.038 ops/s [Average] - (min, avg, max) = (14.468, 14.739, 15.049), stdev = 0.269 - CI (99.9%): [13.701, 15.777] (assumes normal distribution) -``` - -**GraalVM** - -``` -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.coreBench - -Warm-up 1: 14.357 ops/s -Iteration 1: 14.768 ops/s -Iteration 2: 14.922 ops/s -Iteration 3: 14.966 ops/s -Iteration 4: 14.805 ops/s -Iteration 5: 14.520 ops/s - -14.796 ±(99.9%) 0.671 ops/s [Average] - (min, avg, max) = (14.520, 14.796, 14.966), stdev = 0.174 - CI (99.9%): [14.125, 15.468] (assumes normal distribution) - -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.jafamaBench - -Warm-up 1: 11.592 ops/s -Iteration 1: 12.174 ops/s -Iteration 2: 11.734 ops/s -Iteration 3: 11.939 ops/s -Iteration 4: 12.026 ops/s -Iteration 5: 12.221 ops/s - -12.019 ±(99.9%) 0.752 ops/s [Average] - (min, avg, max) = (11.734, 12.019, 12.221), stdev = 0.195 - CI (99.9%): [11.267, 12.771] (assumes normal distribution) - -jvm: space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafamaBench - -Warm-up 1: 12.097 ops/s -Iteration 1: 13.072 ops/s -Iteration 2: 13.112 ops/s -Iteration 3: 13.103 ops/s -Iteration 4: 12.950 ops/s -Iteration 5: 13.011 ops/s - -13.049 ±(99.9%) 0.263 ops/s [Average] - (min, avg, max) = (12.950, 13.049, 13.112), stdev = 0.068 - CI (99.9%): [12.787, 13.312] (assumes normal distribution) -``` - -
+${benchmarkJafamaDouble} diff --git a/settings.gradle.kts b/settings.gradle.kts index 15a6a176c..710017588 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -5,7 +5,7 @@ pluginManagement { gradlePluginPortal() } - val toolsVersion = "0.9.9" + val toolsVersion = "0.9.10" val kotlinVersion = "1.5.0" plugins { From 94c58b7749e5e4ea69d167cda4ea282fa3d9077f Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Tue, 15 Jun 2021 13:45:08 +0300 Subject: [PATCH 080/132] Fix Univariate histogram filling --- CHANGELOG.md | 1 + build.gradle.kts | 2 +- .../kmath/histogram/TreeHistogramSpace.kt | 89 ++++++++++--------- .../kmath/histogram/UnivariateHistogram.kt | 6 +- .../kmath/histogram/TreeHistogramTest.kt | 24 +++++ 5 files changed, 77 insertions(+), 45 deletions(-) create mode 100644 kmath-histograms/src/jvmTest/kotlin/space/kscience/kmath/histogram/TreeHistogramTest.kt diff --git a/CHANGELOG.md b/CHANGELOG.md index 7f7b6b529..12540821e 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -50,6 +50,7 @@ ### Fixed - Ring inherits RingOperations, not GroupOperations +- Univariate histogram filling ### Security diff --git a/build.gradle.kts b/build.gradle.kts index 86394d792..9978281f2 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -17,7 +17,7 @@ allprojects { } group = "space.kscience" - version = "0.3.0-dev-13" + version = "0.3.0-dev-14" } subprojects { diff --git a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt index 6ae8b5ee3..8d05df68a 100644 --- a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt +++ b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt @@ -35,51 +35,56 @@ public class TreeHistogram( override val bins: Collection get() = binMap.values } +@OptIn(UnstableKMathAPI::class) +private class TreeHistogramBuilder(val binFactory: (Double) -> UnivariateDomain) : UnivariateHistogramBuilder { + + private class BinCounter(val domain: UnivariateDomain, val counter: Counter = Counter.real()) : + ClosedFloatingPointRange by domain.range + + private val bins: TreeMap = TreeMap() + + fun get(value: Double): BinCounter? = bins.getBin(value) + + fun createBin(value: Double): BinCounter { + val binDefinition = binFactory(value) + val newBin = BinCounter(binDefinition) + synchronized(this) { bins[binDefinition.center] = newBin } + return newBin + } + + /** + * Thread safe put operation + */ + override fun putValue(at: Double, value: Double) { + (get(at) ?: createBin(at)).apply { + counter.add(value) + } + } + + override fun putValue(point: Buffer, value: Number) { + require(point.size == 1) { "Only points with single value could be used in univariate histogram" } + putValue(point[0], value.toDouble()) + } + + fun build(): TreeHistogram { + val map = bins.mapValuesTo(TreeMap()) { (_, binCounter) -> + val count = binCounter.counter.value + UnivariateBin(binCounter.domain, count, sqrt(count)) + } + return TreeHistogram(map) + } +} + /** * A space for univariate histograms with variable bin borders based on a tree map */ @UnstableKMathAPI public class TreeHistogramSpace( - public val binFactory: (Double) -> UnivariateDomain, + private val binFactory: (Double) -> UnivariateDomain, ) : Group, ScaleOperations { - private class BinCounter(val domain: UnivariateDomain, val counter: Counter = Counter.real()) : - ClosedFloatingPointRange by domain.range - - public fun produce(builder: UnivariateHistogramBuilder.() -> Unit): UnivariateHistogram { - val bins: TreeMap = TreeMap() - val hBuilder = object : UnivariateHistogramBuilder { - - fun get(value: Double): BinCounter? = bins.getBin(value) - - fun createBin(value: Double): BinCounter { - val binDefinition = binFactory(value) - val newBin = BinCounter(binDefinition) - synchronized(this) { bins[binDefinition.center] = newBin } - return newBin - } - - /** - * Thread safe put operation - */ - override fun putValue(at: Double, value: Double) { - (get(at) ?: createBin(at)).apply { - counter.add(value) - } - } - - override fun putValue(point: Buffer, value: Number) { - put(point[0], value.toDouble()) - } - } - hBuilder.apply(builder) - val resBins = TreeMap() - bins.forEach { (key, binCounter) -> - val count = binCounter.counter.value - resBins[key] = UnivariateBin(binCounter.domain, count, sqrt(count)) - } - return TreeHistogram(resBins) - } + public fun fill(block: UnivariateHistogramBuilder.() -> Unit): UnivariateHistogram = + TreeHistogramBuilder(binFactory).apply(block).build() override fun add( a: UnivariateHistogram, @@ -89,7 +94,8 @@ public class TreeHistogramSpace( // require(b.context == this) { "Histogram $b does not belong to this context" } val bins = TreeMap().apply { (a.bins.map { it.domain } union b.bins.map { it.domain }).forEach { def -> - put(def.center, + put( + def.center, UnivariateBin( def, value = (a[def.center]?.value ?: 0.0) + (b[def.center]?.value ?: 0.0), @@ -105,7 +111,8 @@ public class TreeHistogramSpace( override fun scale(a: UnivariateHistogram, value: Double): UnivariateHistogram { val bins = TreeMap().apply { a.bins.forEach { bin -> - put(bin.domain.center, + put( + bin.domain.center, UnivariateBin( bin.domain, value = bin.value * value.toDouble(), @@ -120,7 +127,7 @@ public class TreeHistogramSpace( override fun UnivariateHistogram.unaryMinus(): UnivariateHistogram = this * (-1) - override val zero: UnivariateHistogram = produce { } + override val zero: UnivariateHistogram by lazy { fill { } } public companion object { /** diff --git a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt index 70125e22e..0ad96ad46 100644 --- a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt +++ b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt @@ -13,7 +13,7 @@ import space.kscience.kmath.structures.asSequence @UnstableKMathAPI public val UnivariateDomain.center: Double - get() = (range.endInclusive - range.start) / 2 + get() = (range.endInclusive + range.start) / 2 /** * A univariate bin based an a range @@ -45,7 +45,7 @@ public interface UnivariateHistogram : Histogram{ binSize: Double, start: Double = 0.0, builder: UnivariateHistogramBuilder.() -> Unit, - ): UnivariateHistogram = TreeHistogramSpace.uniform(binSize, start).produce(builder) + ): UnivariateHistogram = TreeHistogramSpace.uniform(binSize, start).fill(builder) /** * Build and fill a histogram with custom borders. Returns a read-only histogram. @@ -53,7 +53,7 @@ public interface UnivariateHistogram : Histogram{ public fun custom( borders: DoubleArray, builder: UnivariateHistogramBuilder.() -> Unit, - ): UnivariateHistogram = TreeHistogramSpace.custom(borders).produce(builder) + ): UnivariateHistogram = TreeHistogramSpace.custom(borders).fill(builder) } } diff --git a/kmath-histograms/src/jvmTest/kotlin/space/kscience/kmath/histogram/TreeHistogramTest.kt b/kmath-histograms/src/jvmTest/kotlin/space/kscience/kmath/histogram/TreeHistogramTest.kt new file mode 100644 index 000000000..28a1b03cb --- /dev/null +++ b/kmath-histograms/src/jvmTest/kotlin/space/kscience/kmath/histogram/TreeHistogramTest.kt @@ -0,0 +1,24 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.histogram + +import org.junit.jupiter.api.Test +import kotlin.random.Random +import kotlin.test.assertTrue + +class TreeHistogramTest { + + @Test + fun normalFill() { + val histogram = UnivariateHistogram.uniform(0.1) { + repeat(100_000) { + putValue(Random.nextDouble()) + } + } + + assertTrue { histogram.bins.count() > 10 } + } +} \ No newline at end of file From 5d5f84ad55e65af19c8b4a8daa549ba306a9f722 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Tue, 15 Jun 2021 20:37:40 +0700 Subject: [PATCH 081/132] Some refactoring of AST rendering --- .../kmath/ast/rendering/MathRenderer.kt | 6 +- .../kscience/kmath/ast/rendering/features.kt | 41 +++++---- .../ast/rendering/{stages.kt => phases.kt} | 89 ++++++++++--------- 3 files changed, 68 insertions(+), 68 deletions(-) rename kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/{stages.kt => phases.kt} (76%) diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt index c33f95483..68d829724 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt @@ -54,7 +54,7 @@ public open class FeaturedMathRenderer(public val features: List) @UnstableKMathAPI public open class FeaturedMathRendererWithPostProcess( features: List, - public val stages: List, + public val stages: List, ) : FeaturedMathRenderer(features) { public override fun render(mst: MST): MathSyntax { val res = super.render(mst) @@ -65,7 +65,7 @@ public open class FeaturedMathRendererWithPostProcess( /** * Logical unit of [MathSyntax] post-processing. */ - public fun interface PostProcessStage { + public fun interface PostProcessPhase { /** * Performs the specified action over [MathSyntax]. */ @@ -102,7 +102,7 @@ public open class FeaturedMathRendererWithPostProcess( // Printing terminal nodes as string PrintNumeric, - PrintSymbolic, + PrintSymbol, ), listOf( BetterExponent, diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt index 863825799..a2f42d1bf 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt @@ -13,15 +13,14 @@ import space.kscience.kmath.operations.* import kotlin.reflect.KClass /** - * Prints any [MST.Symbolic] as a [SymbolSyntax] containing the [MST.Symbolic.value] of it. + * Prints any [Symbol] as a [SymbolSyntax] containing the [Symbol.value] of it. * * @author Iaroslav Postovalov */ @UnstableKMathAPI -public object PrintSymbolic : RenderFeature { - public override fun render(renderer: FeaturedMathRenderer, node: MST): SymbolSyntax? = - if (node !is Symbol) null - else SymbolSyntax(string = node.identity) +public val PrintSymbol: RenderFeature = RenderFeature { _, node -> + if (node !is Symbol) null + else SymbolSyntax(string = node.identity) } /** @@ -30,8 +29,8 @@ public object PrintSymbolic : RenderFeature { * @author Iaroslav Postovalov */ @UnstableKMathAPI -public object PrintNumeric : RenderFeature { - public override fun render(renderer: FeaturedMathRenderer, node: MST): NumberSyntax? = if (node !is MST.Numeric) +public val PrintNumeric: RenderFeature = RenderFeature { _, node -> + if (node !is MST.Numeric) null else NumberSyntax(string = node.value.toString()) @@ -141,7 +140,7 @@ public class PrettyPrintIntegers(public val types: Set>) : Re */ @UnstableKMathAPI public class PrettyPrintPi(public val symbols: Set) : RenderFeature { - public override fun render(renderer: FeaturedMathRenderer, node: MST): SpecialSymbolSyntax? = + public override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? = if (node !is Symbol || node.identity !in symbols) null else @@ -203,7 +202,7 @@ public abstract class Binary(public val operations: Collection?) : Rende */ @UnstableKMathAPI public class BinaryPlus(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): BinaryPlusSyntax = + public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = BinaryPlusSyntax( operation = node.operation, left = OperandSyntax(parent.render(node.left), true), @@ -225,7 +224,7 @@ public class BinaryPlus(operations: Collection?) : Binary(operations) { */ @UnstableKMathAPI public class BinaryMinus(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): BinaryMinusSyntax = + public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = BinaryMinusSyntax( operation = node.operation, left = OperandSyntax(operand = parent.render(node.left), parentheses = true), @@ -247,7 +246,7 @@ public class BinaryMinus(operations: Collection?) : Binary(operations) { */ @UnstableKMathAPI public class UnaryPlus(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): UnaryPlusSyntax = UnaryPlusSyntax( + public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryPlusSyntax( operation = node.operation, operand = OperandSyntax(operand = parent.render(node.value), parentheses = true), ) @@ -267,7 +266,7 @@ public class UnaryPlus(operations: Collection?) : Unary(operations) { */ @UnstableKMathAPI public class UnaryMinus(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): UnaryMinusSyntax = UnaryMinusSyntax( + public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryMinusSyntax( operation = node.operation, operand = OperandSyntax(operand = parent.render(node.value), parentheses = true), ) @@ -287,7 +286,7 @@ public class UnaryMinus(operations: Collection?) : Unary(operations) { */ @UnstableKMathAPI public class Fraction(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): FractionSyntax = FractionSyntax( + public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = FractionSyntax( operation = node.operation, left = OperandSyntax(operand = parent.render(node.left), parentheses = true), right = OperandSyntax(operand = parent.render(node.right), parentheses = true), @@ -309,7 +308,7 @@ public class Fraction(operations: Collection?) : Binary(operations) { */ @UnstableKMathAPI public class BinaryOperator(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): BinaryOperatorSyntax = + public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = BinaryOperatorSyntax( operation = node.operation, prefix = OperatorNameSyntax(name = node.operation), @@ -332,7 +331,7 @@ public class BinaryOperator(operations: Collection?) : Binary(operations */ @UnstableKMathAPI public class UnaryOperator(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): UnaryOperatorSyntax = + public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryOperatorSyntax( operation = node.operation, prefix = OperatorNameSyntax(node.operation), @@ -354,7 +353,7 @@ public class UnaryOperator(operations: Collection?) : Unary(operations) */ @UnstableKMathAPI public class Power(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): SuperscriptSyntax = + public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = SuperscriptSyntax( operation = node.operation, left = OperandSyntax(parent.render(node.left), true), @@ -374,7 +373,7 @@ public class Power(operations: Collection?) : Binary(operations) { */ @UnstableKMathAPI public class SquareRoot(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): RadicalSyntax = + public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = RadicalSyntax(operation = node.operation, operand = parent.render(node.value)) public companion object { @@ -392,7 +391,7 @@ public class SquareRoot(operations: Collection?) : Unary(operations) { */ @UnstableKMathAPI public class Exponent(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): ExponentSyntax = ExponentSyntax( + public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = ExponentSyntax( operation = node.operation, operand = OperandSyntax(operand = parent.render(node.value), parentheses = true), useOperatorForm = true, @@ -413,7 +412,7 @@ public class Exponent(operations: Collection?) : Unary(operations) { */ @UnstableKMathAPI public class Multiplication(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MultiplicationSyntax = + public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = MultiplicationSyntax( operation = node.operation, left = OperandSyntax(operand = parent.render(node.left), parentheses = true), @@ -436,7 +435,7 @@ public class Multiplication(operations: Collection?) : Binary(operations */ @UnstableKMathAPI public class InverseTrigonometricOperations(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): UnaryOperatorSyntax = + public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryOperatorSyntax( operation = node.operation, prefix = OperatorNameSyntax(name = node.operation.replaceFirst("a", "arc")), @@ -463,7 +462,7 @@ public class InverseTrigonometricOperations(operations: Collection?) : U */ @UnstableKMathAPI public class InverseHyperbolicOperations(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): UnaryOperatorSyntax = + public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryOperatorSyntax( operation = node.operation, prefix = OperatorNameSyntax(name = node.operation.replaceFirst("a", "ar")), diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/stages.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/phases.kt similarity index 76% rename from kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/stages.kt rename to kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/phases.kt index 1f31af853..6da4994a6 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/stages.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/phases.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.ast.rendering +import space.kscience.kmath.ast.rendering.FeaturedMathRendererWithPostProcess.PostProcessPhase import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.FieldOperations import space.kscience.kmath.operations.GroupOperations @@ -17,8 +18,8 @@ import space.kscience.kmath.operations.RingOperations * @author Iaroslav Postovalov */ @UnstableKMathAPI -public object BetterMultiplication : FeaturedMathRendererWithPostProcess.PostProcessStage { - public override fun perform(node: MathSyntax): Unit = when (node) { +public val BetterMultiplication: PostProcessPhase = PostProcessPhase { node -> + fun perform(node: MathSyntax): Unit = when (node) { is NumberSyntax -> Unit is SymbolSyntax -> Unit is OperatorNameSyntax -> Unit @@ -81,6 +82,8 @@ public object BetterMultiplication : FeaturedMathRendererWithPostProcess.PostPro perform(node.right) } } + + perform(node) } /** @@ -89,68 +92,68 @@ public object BetterMultiplication : FeaturedMathRendererWithPostProcess.PostPro * @author Iaroslav Postovalov */ @UnstableKMathAPI -public object BetterFraction : FeaturedMathRendererWithPostProcess.PostProcessStage { - private fun perform0(node: MathSyntax, infix: Boolean = false): Unit = when (node) { +public val BetterFraction: PostProcessPhase = PostProcessPhase { node -> + fun perform(node: MathSyntax, infix: Boolean = false): Unit = when (node) { is NumberSyntax -> Unit is SymbolSyntax -> Unit is OperatorNameSyntax -> Unit is SpecialSymbolSyntax -> Unit - is OperandSyntax -> perform0(node.operand, infix) + is OperandSyntax -> perform(node.operand, infix) is UnaryOperatorSyntax -> { - perform0(node.prefix, infix) - perform0(node.operand, infix) + perform(node.prefix, infix) + perform(node.operand, infix) } - is UnaryPlusSyntax -> perform0(node.operand, infix) - is UnaryMinusSyntax -> perform0(node.operand, infix) - is RadicalSyntax -> perform0(node.operand, infix) - is ExponentSyntax -> perform0(node.operand, infix) + is UnaryPlusSyntax -> perform(node.operand, infix) + is UnaryMinusSyntax -> perform(node.operand, infix) + is RadicalSyntax -> perform(node.operand, infix) + is ExponentSyntax -> perform(node.operand, infix) is SuperscriptSyntax -> { - perform0(node.left, true) - perform0(node.right, true) + perform(node.left, true) + perform(node.right, true) } is SubscriptSyntax -> { - perform0(node.left, true) - perform0(node.right, true) + perform(node.left, true) + perform(node.right, true) } is BinaryOperatorSyntax -> { - perform0(node.prefix, infix) - perform0(node.left, infix) - perform0(node.right, infix) + perform(node.prefix, infix) + perform(node.left, infix) + perform(node.right, infix) } is BinaryPlusSyntax -> { - perform0(node.left, infix) - perform0(node.right, infix) + perform(node.left, infix) + perform(node.right, infix) } is BinaryMinusSyntax -> { - perform0(node.left, infix) - perform0(node.right, infix) + perform(node.left, infix) + perform(node.right, infix) } is FractionSyntax -> { node.infix = infix - perform0(node.left, infix) - perform0(node.right, infix) + perform(node.left, infix) + perform(node.right, infix) } is RadicalWithIndexSyntax -> { - perform0(node.left, true) - perform0(node.right, true) + perform(node.left, true) + perform(node.right, true) } is MultiplicationSyntax -> { - perform0(node.left, infix) - perform0(node.right, infix) + perform(node.left, infix) + perform(node.right, infix) } } - public override fun perform(node: MathSyntax): Unit = perform0(node) + perform(node) } /** @@ -160,39 +163,37 @@ public object BetterFraction : FeaturedMathRendererWithPostProcess.PostProcessSt * @author Iaroslav Postovalov */ @UnstableKMathAPI -public object BetterExponent : FeaturedMathRendererWithPostProcess.PostProcessStage { - private fun perform0(node: MathSyntax): Boolean { +public val BetterExponent: PostProcessPhase = PostProcessPhase { node -> + fun perform(node: MathSyntax): Boolean { return when (node) { is NumberSyntax -> false is SymbolSyntax -> false is OperatorNameSyntax -> false is SpecialSymbolSyntax -> false - is OperandSyntax -> perform0(node.operand) - is UnaryOperatorSyntax -> perform0(node.prefix) || perform0(node.operand) - is UnaryPlusSyntax -> perform0(node.operand) - is UnaryMinusSyntax -> perform0(node.operand) + is OperandSyntax -> perform(node.operand) + is UnaryOperatorSyntax -> perform(node.prefix) || perform(node.operand) + is UnaryPlusSyntax -> perform(node.operand) + is UnaryMinusSyntax -> perform(node.operand) is RadicalSyntax -> true is ExponentSyntax -> { - val r = perform0(node.operand) + val r = perform(node.operand) node.useOperatorForm = r r } is SuperscriptSyntax -> true is SubscriptSyntax -> true - is BinaryOperatorSyntax -> perform0(node.prefix) || perform0(node.left) || perform0(node.right) - is BinaryPlusSyntax -> perform0(node.left) || perform0(node.right) - is BinaryMinusSyntax -> perform0(node.left) || perform0(node.right) + is BinaryOperatorSyntax -> perform(node.prefix) || perform(node.left) || perform(node.right) + is BinaryPlusSyntax -> perform(node.left) || perform(node.right) + is BinaryMinusSyntax -> perform(node.left) || perform(node.right) is FractionSyntax -> true is RadicalWithIndexSyntax -> true - is MultiplicationSyntax -> perform0(node.left) || perform0(node.right) + is MultiplicationSyntax -> perform(node.left) || perform(node.right) } } - public override fun perform(node: MathSyntax) { - perform0(node) - } + perform(node) } /** @@ -203,7 +204,7 @@ public object BetterExponent : FeaturedMathRendererWithPostProcess.PostProcessSt */ @UnstableKMathAPI public class SimplifyParentheses(public val precedenceFunction: (MathSyntax) -> Int) : - FeaturedMathRendererWithPostProcess.PostProcessStage { + PostProcessPhase { public override fun perform(node: MathSyntax): Unit = when (node) { is NumberSyntax -> Unit is SymbolSyntax -> Unit From 7feb87ff052b0a99b5790cf788814fbee46f08cc Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sat, 19 Jun 2021 20:52:26 +0700 Subject: [PATCH 082/132] Refactor benchmark report writer --- build.gradle.kts | 4 +- buildSrc/build.gradle.kts | 5 +- .../benchmarks/addBenchmarkProperties.kt | 89 +++++++++---------- settings.gradle.kts | 2 +- 4 files changed, 47 insertions(+), 53 deletions(-) diff --git a/build.gradle.kts b/build.gradle.kts index 9978281f2..93cd67d47 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -10,9 +10,7 @@ allprojects { maven("http://logicrunch.research.it.uu.se/maven") { isAllowInsecureProtocol = true } - maven("https://oss.sonatype.org/content/repositories/snapshots") { - - } + maven("https://oss.sonatype.org/content/repositories/snapshots") mavenCentral() } diff --git a/buildSrc/build.gradle.kts b/buildSrc/build.gradle.kts index 8ff1c4369..fe69b05c6 100644 --- a/buildSrc/build.gradle.kts +++ b/buildSrc/build.gradle.kts @@ -4,13 +4,14 @@ plugins { } repositories { - gradlePluginPortal() + maven("https://repo.kotlin.link") mavenCentral() + gradlePluginPortal() } dependencies { api("org.jetbrains.kotlinx:kotlinx-serialization-json:1.1.0") - api("ru.mipt.npm:gradle-tools:0.9.10") + api("ru.mipt.npm:gradle-tools:0.10.0") api("org.jetbrains.kotlinx:kotlinx-benchmark-plugin:0.3.1") } diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt index 31d952157..b55e1320e 100644 --- a/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt @@ -5,8 +5,11 @@ package space.kscience.kmath.benchmarks +import kotlinx.benchmark.gradle.BenchmarksExtension import kotlinx.serialization.* +import kotlinx.serialization.json.* import org.gradle.api.Project +import ru.mipt.npm.gradle.KScienceReadmeExtension import java.time.* import java.time.format.* import java.time.temporal.ChronoField.* @@ -42,63 +45,55 @@ private fun noun(number: Number, singular: String, plural: String) = if (number. fun Project.addBenchmarkProperties() { val benchmarksProject = this rootProject.subprojects.forEach { p -> - p.extensions.findByType(ru.mipt.npm.gradle.KScienceReadmeExtension::class.java)?.run { - benchmarksProject.extensions.findByType(kotlinx.benchmark.gradle.BenchmarksExtension::class.java)?.configurations?.forEach { cfg -> - // TODO remove this hack when https://github.com/mipt-npm/gradle-tools/pull/15 is merged - @Suppress("UNCHECKED_CAST") - (javaClass.getDeclaredField("properties") - .also { - it.isAccessible = true - }[this] as MutableMap Any?>)["benchmark${cfg.name.replaceFirstChar(Char::uppercase)}"] = - { - val launches = benchmarksProject.buildDir.resolve("reports/benchmarks/${cfg.name}") + p.extensions.findByType(KScienceReadmeExtension::class.java)?.run { + benchmarksProject.extensions.findByType(BenchmarksExtension::class.java)?.configurations?.forEach { cfg -> + property("benchmark${cfg.name.replaceFirstChar(Char::uppercase)}") { + val launches = benchmarksProject.buildDir.resolve("reports/benchmarks/${cfg.name}") - val resDirectory = launches.listFiles()?.maxByOrNull { - LocalDateTime.parse(it.name, ISO_DATE_TIME).atZone(ZoneId.systemDefault()).toInstant() - } + val resDirectory = launches.listFiles()?.maxByOrNull { + LocalDateTime.parse(it.name, ISO_DATE_TIME).atZone(ZoneId.systemDefault()).toInstant() + } - if (resDirectory == null) { - "> **Can't find appropriate benchmark data. Try generating readme files after running benchmarks**." - } else { - val reports = - kotlinx.serialization.json.Json.decodeFromString>( - resDirectory.resolve("jvm.json").readText() - ) + if (resDirectory == null) { + "> **Can't find appropriate benchmark data. Try generating readme files after running benchmarks**." + } else { + val reports = + Json.decodeFromString>(resDirectory.resolve("jvm.json").readText()) - buildString { - appendLine("
") - appendLine("") - appendLine("Report for benchmark configuration ${cfg.name}") - appendLine("") - appendLine() - val first = reports.first() + buildString { + appendLine("
") + appendLine("") + appendLine("Report for benchmark configuration ${cfg.name}") + appendLine("") + appendLine() + val first = reports.first() - appendLine("* Run on ${first.vmName} (build ${first.vmVersion}) with Java process:") - appendLine() - appendLine("```") - appendLine("${first.jvm} ${ - first.jvmArgs.joinToString(" ") - }") - appendLine("```") + appendLine("* Run on ${first.vmName} (build ${first.vmVersion}) with Java process:") + appendLine() + appendLine("```") + appendLine("${first.jvm} ${ + first.jvmArgs.joinToString(" ") + }") + appendLine("```") - appendLine("* JMH ${first.jmhVersion} was used in `${first.mode}` mode with ${first.warmupIterations} warmup ${ - noun(first.warmupIterations, "iteration", "iterations") - } by ${first.warmupTime} and ${first.measurementIterations} measurement ${ - noun(first.measurementIterations, "iteration", "iterations") - } by ${first.measurementTime}.") + appendLine("* JMH ${first.jmhVersion} was used in `${first.mode}` mode with ${first.warmupIterations} warmup ${ + noun(first.warmupIterations, "iteration", "iterations") + } by ${first.warmupTime} and ${first.measurementIterations} measurement ${ + noun(first.measurementIterations, "iteration", "iterations") + } by ${first.measurementTime}.") - appendLine() - appendLine("| Benchmark | Score |") - appendLine("|:---------:|:-----:|") + appendLine() + appendLine("| Benchmark | Score |") + appendLine("|:---------:|:-----:|") - reports.forEach { report -> - appendLine("|`${report.benchmark}`|${report.primaryMetric.score} ± ${report.primaryMetric.scoreError} ${report.primaryMetric.scoreUnit}|") - } - - appendLine("
") + reports.forEach { report -> + appendLine("|`${report.benchmark}`|${report.primaryMetric.score} ± ${report.primaryMetric.scoreError} ${report.primaryMetric.scoreUnit}|") } + + appendLine("
") } } + } } } } diff --git a/settings.gradle.kts b/settings.gradle.kts index 710017588..063c69280 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -5,7 +5,7 @@ pluginManagement { gradlePluginPortal() } - val toolsVersion = "0.9.10" + val toolsVersion = "0.10.0" val kotlinVersion = "1.5.0" plugins { From 9f513b355c767c2c0536c5e4d7ad8df7dc6c2691 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sun, 20 Jun 2021 01:16:08 +0700 Subject: [PATCH 083/132] Update CMRandomGeneratorWrapper --- .../kmath/commons/random/CMRandomGeneratorWrapper.kt | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt index 16a6967e2..4e2fbf980 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt @@ -5,7 +5,11 @@ package space.kscience.kmath.commons.random +import kotlinx.coroutines.runBlocking +import space.kscience.kmath.misc.PerformancePitfall +import space.kscience.kmath.samplers.GaussianSampler import space.kscience.kmath.stat.RandomGenerator +import space.kscience.kmath.stat.next public class CMRandomGeneratorWrapper( public val factory: (IntArray) -> RandomGenerator, @@ -33,7 +37,10 @@ public class CMRandomGeneratorWrapper( public override fun nextInt(): Int = generator.nextInt() public override fun nextInt(n: Int): Int = generator.nextInt(n) - public override fun nextGaussian(): Double = TODO() + + @PerformancePitfall + public override fun nextGaussian(): Double = runBlocking { GaussianSampler(0.0, 1.0).next(generator) } + public override fun nextDouble(): Double = generator.nextDouble() public override fun nextLong(): Long = generator.nextLong() } From 83fc4e28d825343860c724f9a16fcf0b86f5f56b Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sat, 3 Jul 2021 17:11:47 +0700 Subject: [PATCH 084/132] Generate README, bump versions of Kotlin, Gradle, ND4J, ASM --- README.md | 4 ++-- benchmarks/build.gradle.kts | 2 +- build.gradle.kts | 8 ++++++-- gradle/wrapper/gradle-wrapper.jar | Bin 59203 -> 59536 bytes gradle/wrapper/gradle-wrapper.properties | 2 +- gradlew | 2 +- kmath-ast/README.md | 6 +++--- kmath-ast/build.gradle.kts | 3 +-- kmath-complex/README.md | 6 +++--- kmath-core/README.md | 6 +++--- kmath-ejml/README.md | 6 +++--- kmath-for-real/README.md | 6 +++--- kmath-functions/README.md | 6 +++--- kmath-jafama/README.md | 12 ++++++------ kmath-kotlingrad/README.md | 6 +++--- kmath-nd4j/README.md | 6 +++--- kmath-nd4j/build.gradle.kts | 5 ++--- kmath-tensors/README.md | 6 +++--- settings.gradle.kts | 5 ++--- 19 files changed, 49 insertions(+), 48 deletions(-) diff --git a/README.md b/README.md index 015988cd3..7645256d9 100644 --- a/README.md +++ b/README.md @@ -309,8 +309,8 @@ repositories { } dependencies { - api("space.kscience:kmath-core:0.3.0-dev-13") - // api("space.kscience:kmath-core-jvm:0.3.0-dev-13") for jvm-specific version + api("space.kscience:kmath-core:0.3.0-dev-14") + // api("space.kscience:kmath-core-jvm:0.3.0-dev-14") for jvm-specific version } ``` diff --git a/benchmarks/build.gradle.kts b/benchmarks/build.gradle.kts index 2198ac5d6..d96c5a8b6 100644 --- a/benchmarks/build.gradle.kts +++ b/benchmarks/build.gradle.kts @@ -47,7 +47,7 @@ kotlin { implementation(project(":kmath-nd4j")) implementation(project(":kmath-kotlingrad")) implementation(project(":kmath-viktor")) - implementation("org.nd4j:nd4j-native:1.0.0-beta7") + implementation("org.nd4j:nd4j-native:1.0.0-M1") // uncomment if your system supports AVX2 // val os = System.getProperty("os.name") // diff --git a/build.gradle.kts b/build.gradle.kts index 93cd67d47..d0f6ced78 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -28,12 +28,16 @@ subprojects { dokkaSourceSets.all { val readmeFile = File(this@subprojects.projectDir, "README.md") if (readmeFile.exists()) includes.from(readmeFile.absolutePath) - externalDocumentationLink("http://ejml.org/javadoc/") + externalDocumentationLink("https://ejml.org/javadoc/") externalDocumentationLink("https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/") externalDocumentationLink("https://deeplearning4j.org/api/latest/") externalDocumentationLink("https://axelclk.bitbucket.io/symja/javadoc/") externalDocumentationLink("https://kotlin.github.io/kotlinx.coroutines/kotlinx-coroutines-core/") - externalDocumentationLink("https://breandan.net/kotlingrad/kotlingrad/", "https://breandan.net/kotlingrad/kotlingrad/kotlingrad/package-list") + + externalDocumentationLink( + "https://breandan.net/kotlingrad/kotlingrad/", + "https://breandan.net/kotlingrad/kotlingrad/kotlingrad/package-list", + ) } } } diff --git a/gradle/wrapper/gradle-wrapper.jar 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-distributionUrl=https\://services.gradle.org/distributions/gradle-7.0-bin.zip +distributionUrl=https\://services.gradle.org/distributions/gradle-7.1.1-bin.zip zipStoreBase=GRADLE_USER_HOME zipStorePath=wrapper/dists diff --git a/gradlew b/gradlew index 4f906e0c8..744e882ed 100755 --- a/gradlew +++ b/gradlew @@ -72,7 +72,7 @@ case "`uname`" in Darwin* ) darwin=true ;; - MINGW* ) + MSYS* | MINGW* ) msys=true ;; NONSTOP* ) diff --git a/kmath-ast/README.md b/kmath-ast/README.md index 026c5a625..c3c4c38a1 100644 --- a/kmath-ast/README.md +++ b/kmath-ast/README.md @@ -10,7 +10,7 @@ Performance and visualization extensions to MST API. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-14`. **Gradle:** ```gradle @@ -20,7 +20,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-ast:0.3.0-dev-13' + implementation 'space.kscience:kmath-ast:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -31,7 +31,7 @@ repositories { } dependencies { - implementation("space.kscience:kmath-ast:0.3.0-dev-13") + implementation("space.kscience:kmath-ast:0.3.0-dev-14") } ``` diff --git a/kmath-ast/build.gradle.kts b/kmath-ast/build.gradle.kts index 8209a0dad..9de7e9980 100644 --- a/kmath-ast/build.gradle.kts +++ b/kmath-ast/build.gradle.kts @@ -45,8 +45,7 @@ kotlin.sourceSets { jvmMain { dependencies { - implementation("org.ow2.asm:asm:9.1") - implementation("org.ow2.asm:asm-commons:9.1") + implementation("org.ow2.asm:asm-commons:9.2") } } } diff --git a/kmath-complex/README.md b/kmath-complex/README.md index 18a83756d..110529b72 100644 --- a/kmath-complex/README.md +++ b/kmath-complex/README.md @@ -8,7 +8,7 @@ Complex and hypercomplex number systems in KMath. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-complex:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-complex:0.3.0-dev-14`. **Gradle:** ```gradle @@ -18,7 +18,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-complex:0.3.0-dev-13' + implementation 'space.kscience:kmath-complex:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -29,6 +29,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-complex:0.3.0-dev-13") + implementation("space.kscience:kmath-complex:0.3.0-dev-14") } ``` diff --git a/kmath-core/README.md b/kmath-core/README.md index 6ca8c8ef8..a563552bb 100644 --- a/kmath-core/README.md +++ b/kmath-core/README.md @@ -15,7 +15,7 @@ performance calculations to code generation. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-core:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-core:0.3.0-dev-14`. **Gradle:** ```gradle @@ -25,7 +25,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-core:0.3.0-dev-13' + implementation 'space.kscience:kmath-core:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -36,6 +36,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-core:0.3.0-dev-13") + implementation("space.kscience:kmath-core:0.3.0-dev-14") } ``` diff --git a/kmath-ejml/README.md b/kmath-ejml/README.md index 10e7bd606..f88f53000 100644 --- a/kmath-ejml/README.md +++ b/kmath-ejml/README.md @@ -9,7 +9,7 @@ EJML based linear algebra implementation. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-ejml:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-ejml:0.3.0-dev-14`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-ejml:0.3.0-dev-13' + implementation 'space.kscience:kmath-ejml:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -30,6 +30,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-ejml:0.3.0-dev-13") + implementation("space.kscience:kmath-ejml:0.3.0-dev-14") } ``` diff --git a/kmath-for-real/README.md b/kmath-for-real/README.md index 6339782dd..d449b4540 100644 --- a/kmath-for-real/README.md +++ b/kmath-for-real/README.md @@ -9,7 +9,7 @@ Specialization of KMath APIs for Double numbers. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-for-real:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-for-real:0.3.0-dev-14`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-for-real:0.3.0-dev-13' + implementation 'space.kscience:kmath-for-real:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -30,6 +30,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-for-real:0.3.0-dev-13") + implementation("space.kscience:kmath-for-real:0.3.0-dev-14") } ``` diff --git a/kmath-functions/README.md b/kmath-functions/README.md index 77f55528a..d0beae2c8 100644 --- a/kmath-functions/README.md +++ b/kmath-functions/README.md @@ -11,7 +11,7 @@ Functions and interpolations. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-functions:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-functions:0.3.0-dev-14`. **Gradle:** ```gradle @@ -21,7 +21,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-functions:0.3.0-dev-13' + implementation 'space.kscience:kmath-functions:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -32,6 +32,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-functions:0.3.0-dev-13") + implementation("space.kscience:kmath-functions:0.3.0-dev-14") } ``` diff --git a/kmath-jafama/README.md b/kmath-jafama/README.md index ef8fcd352..71097771d 100644 --- a/kmath-jafama/README.md +++ b/kmath-jafama/README.md @@ -7,7 +7,7 @@ Integration with [Jafama](https://github.com/jeffhain/jafama). ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-jafama:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-jafama:0.3.0-dev-14`. **Gradle:** ```gradle @@ -17,7 +17,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-jafama:0.3.0-dev-13' + implementation 'space.kscience:kmath-jafama:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -28,7 +28,7 @@ repositories { } dependencies { - implementation("space.kscience:kmath-jafama:0.3.0-dev-13") + implementation("space.kscience:kmath-jafama:0.3.0-dev-14") } ``` @@ -66,8 +66,8 @@ Report for benchmark configuration jafamaDouble | Benchmark | Score | |:---------:|:-----:| -|`space.kscience.kmath.benchmarks.JafamaBenchmark.core`|14.296120859512893 ± 0.36462633435888736 ops/s| -|`space.kscience.kmath.benchmarks.JafamaBenchmark.jafama`|11.431566395649781 ± 2.570896777898243 ops/s| -|`space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafama`|11.746020495694117 ± 6.205909559197869 ops/s| +|`space.kscience.kmath.benchmarks.JafamaBenchmark.core`|14.35014650168397 ± 0.9200669832937576 ops/s| +|`space.kscience.kmath.benchmarks.JafamaBenchmark.jafama`|12.048429204455887 ± 1.2882929181842269 ops/s| +|`space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafama`|12.977653357239152 ± 1.4122819627470866 ops/s| diff --git a/kmath-kotlingrad/README.md b/kmath-kotlingrad/README.md index 31c7bb819..304a0639b 100644 --- a/kmath-kotlingrad/README.md +++ b/kmath-kotlingrad/README.md @@ -8,7 +8,7 @@ ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-kotlingrad:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-kotlingrad:0.3.0-dev-14`. **Gradle:** ```gradle @@ -18,7 +18,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-kotlingrad:0.3.0-dev-13' + implementation 'space.kscience:kmath-kotlingrad:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -29,6 +29,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-kotlingrad:0.3.0-dev-13") + implementation("space.kscience:kmath-kotlingrad:0.3.0-dev-14") } ``` diff --git a/kmath-nd4j/README.md b/kmath-nd4j/README.md index 1c945f06a..5cbb31d5a 100644 --- a/kmath-nd4j/README.md +++ b/kmath-nd4j/README.md @@ -9,7 +9,7 @@ ND4J based implementations of KMath abstractions. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-nd4j:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-nd4j:0.3.0-dev-14`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-nd4j:0.3.0-dev-13' + implementation 'space.kscience:kmath-nd4j:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -30,7 +30,7 @@ repositories { } dependencies { - implementation("space.kscience:kmath-nd4j:0.3.0-dev-13") + implementation("space.kscience:kmath-nd4j:0.3.0-dev-14") } ``` diff --git a/kmath-nd4j/build.gradle.kts b/kmath-nd4j/build.gradle.kts index abcc02962..6e890a937 100644 --- a/kmath-nd4j/build.gradle.kts +++ b/kmath-nd4j/build.gradle.kts @@ -7,9 +7,8 @@ description = "ND4J NDStructure implementation and according NDAlgebra classes" dependencies { api(project(":kmath-tensors")) - api("org.nd4j:nd4j-api:1.0.0-beta7") - testImplementation("org.nd4j:nd4j-native:1.0.0-beta7") - testImplementation("org.nd4j:nd4j-native-platform:1.0.0-beta7") + api("org.nd4j:nd4j-api:1.0.0-M1") + testImplementation("org.nd4j:nd4j-native-platform:1.0.0-M1") testImplementation("org.slf4j:slf4j-simple:1.7.30") } diff --git a/kmath-tensors/README.md b/kmath-tensors/README.md index dd21a9f2f..6b991d5df 100644 --- a/kmath-tensors/README.md +++ b/kmath-tensors/README.md @@ -9,7 +9,7 @@ Common linear algebra operations on tensors. ## Artifact: -The Maven coordinates of this project are `space.kscience:kmath-tensors:0.3.0-dev-13`. +The Maven coordinates of this project are `space.kscience:kmath-tensors:0.3.0-dev-14`. **Gradle:** ```gradle @@ -19,7 +19,7 @@ repositories { } dependencies { - implementation 'space.kscience:kmath-tensors:0.3.0-dev-13' + implementation 'space.kscience:kmath-tensors:0.3.0-dev-14' } ``` **Gradle Kotlin DSL:** @@ -30,6 +30,6 @@ repositories { } dependencies { - implementation("space.kscience:kmath-tensors:0.3.0-dev-13") + implementation("space.kscience:kmath-tensors:0.3.0-dev-14") } ``` diff --git a/settings.gradle.kts b/settings.gradle.kts index 063c69280..02b75cddc 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -6,7 +6,7 @@ pluginManagement { } val toolsVersion = "0.10.0" - val kotlinVersion = "1.5.0" + val kotlinVersion = "1.5.20" plugins { id("ru.mipt.npm.gradle.project") version toolsVersion @@ -17,7 +17,6 @@ pluginManagement { kotlin("plugin.allopen") version kotlinVersion id("org.jetbrains.kotlinx.benchmark") version "0.3.1" kotlin("jupyter.api") version "0.10.0-25" - } } @@ -45,5 +44,5 @@ include( ":kmath-symja", ":kmath-jafama", ":examples", - ":benchmarks" + ":benchmarks", ) From 3ba12f49993d03e9af6bd59b97186e72e78799f6 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 9 Jul 2021 14:11:26 +0300 Subject: [PATCH 085/132] Generic Buffer Algebra --- CHANGELOG.md | 1 + .../kscience/kmath/structures/buffers.kt | 22 +++ .../kmath/operations/BufferAlgebra.kt | 146 ++++++++++++++++++ .../kmath/structures/DoubleBufferField.kt | 4 + 4 files changed, 173 insertions(+) create mode 100644 examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BufferAlgebra.kt diff --git a/CHANGELOG.md b/CHANGELOG.md index e35153d81..8c4f5b547 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -40,6 +40,7 @@ - Use `Symbol` factory function instead of `StringSymbol` ### Deprecated +- Specialized `DoubleBufferAlgebra` ### Removed - Nearest in Domain. To be implemented in geometry package. diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt new file mode 100644 index 000000000..eabb16701 --- /dev/null +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt @@ -0,0 +1,22 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.structures + +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.bufferAlgebra +import space.kscience.kmath.operations.produce + +inline fun MutableBuffer.Companion.same( + n: Int, + value: R +): MutableBuffer = auto(n) { value } + + +fun main() { + with(DoubleField.bufferAlgebra(5)) { + println(number(2.0) + produce(1, 2, 3, 4, 5)) + } +} \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BufferAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BufferAlgebra.kt new file mode 100644 index 000000000..9f4d741fd --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BufferAlgebra.kt @@ -0,0 +1,146 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.operations + +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.BufferFactory +import space.kscience.kmath.structures.DoubleBuffer + +/** + * An algebra over [Buffer] + */ +@UnstableKMathAPI +public interface BufferAlgebra> : Algebra> { + public val bufferFactory: BufferFactory + public val elementAlgebra: A + + //TODO move to multi-receiver inline extension + public fun Buffer.map(block: (T) -> T): Buffer = bufferFactory(size) { block(get(it)) } + + public fun Buffer.zip(other: Buffer, block: (left: T, right: T) -> T): Buffer { + require(size == other.size) { "Incompatible buffer sizes. left: $size, right: ${other.size}" } + return bufferFactory(size) { block(this[it], other[it]) } + } + + override fun unaryOperationFunction(operation: String): (arg: Buffer) -> Buffer { + val operationFunction = elementAlgebra.unaryOperationFunction(operation) + return { arg -> bufferFactory(arg.size) { operationFunction(arg[it]) } } + } + + override fun binaryOperationFunction(operation: String): (left: Buffer, right: Buffer) -> Buffer { + val operationFunction = elementAlgebra.binaryOperationFunction(operation) + return { left, right -> + bufferFactory(left.size) { operationFunction(left[it], right[it]) } + } + } +} + +@UnstableKMathAPI +public fun > BufferAlgebra.sin(arg: Buffer): Buffer = + arg.map(elementAlgebra::sin) + +@UnstableKMathAPI +public fun > BufferAlgebra.cos(arg: Buffer): Buffer = + arg.map(elementAlgebra::cos) + +@UnstableKMathAPI +public fun > BufferAlgebra.tan(arg: Buffer): Buffer = + arg.map(elementAlgebra::tan) + +@UnstableKMathAPI +public fun > BufferAlgebra.asin(arg: Buffer): Buffer = + arg.map(elementAlgebra::asin) + +@UnstableKMathAPI +public fun > BufferAlgebra.acos(arg: Buffer): Buffer = + arg.map(elementAlgebra::acos) + +@UnstableKMathAPI +public fun > BufferAlgebra.atan(arg: Buffer): Buffer = + arg.map(elementAlgebra::atan) + +@UnstableKMathAPI +public fun > BufferAlgebra.exp(arg: Buffer): Buffer = + arg.map(elementAlgebra::exp) + +@UnstableKMathAPI +public fun > BufferAlgebra.ln(arg: Buffer): Buffer = + arg.map(elementAlgebra::ln) + +@UnstableKMathAPI +public fun > BufferAlgebra.sinh(arg: Buffer): Buffer = + arg.map(elementAlgebra::sinh) + +@UnstableKMathAPI +public fun > BufferAlgebra.cosh(arg: Buffer): Buffer = + arg.map(elementAlgebra::cosh) + +@UnstableKMathAPI +public fun > BufferAlgebra.tanh(arg: Buffer): Buffer = + arg.map(elementAlgebra::tanh) + +@UnstableKMathAPI +public fun > BufferAlgebra.asinh(arg: Buffer): Buffer = + arg.map(elementAlgebra::asinh) + +@UnstableKMathAPI +public fun > BufferAlgebra.acosh(arg: Buffer): Buffer = + arg.map(elementAlgebra::acosh) + +@UnstableKMathAPI +public fun > BufferAlgebra.atanh(arg: Buffer): Buffer = + arg.map(elementAlgebra::atanh) + +@UnstableKMathAPI +public fun > BufferAlgebra.pow(arg: Buffer, pow: Number): Buffer = + with(elementAlgebra) { arg.map { power(it, pow) } } + + +@UnstableKMathAPI +public class BufferField>( + override val bufferFactory: BufferFactory, + override val elementAlgebra: A, + public val size: Int +) : BufferAlgebra, Field> { + + public fun produce(vararg elements: T): Buffer { + require(elements.size == size) { "Expected $size elements but found ${elements.size}" } + return bufferFactory(size) { elements[it] } + } + + override val zero: Buffer = bufferFactory(size) { elementAlgebra.zero } + override val one: Buffer = bufferFactory(size) { elementAlgebra.one } + + + override fun add(a: Buffer, b: Buffer): Buffer = a.zip(b, elementAlgebra::add) + override fun multiply(a: Buffer, b: Buffer): Buffer = a.zip(b, elementAlgebra::multiply) + override fun divide(a: Buffer, b: Buffer): Buffer = a.zip(b, elementAlgebra::divide) + + override fun scale(a: Buffer, value: Double): Buffer = with(elementAlgebra) { a.map { scale(it, value) } } + override fun Buffer.unaryMinus(): Buffer = with(elementAlgebra) { map { -it } } + + override fun unaryOperationFunction(operation: String): (arg: Buffer) -> Buffer { + return super.unaryOperationFunction(operation) + } + + override fun binaryOperationFunction(operation: String): (left: Buffer, right: Buffer) -> Buffer { + return super.binaryOperationFunction(operation) + } +} + +//Double buffer specialization + +@UnstableKMathAPI +public fun BufferField.produce(vararg elements: Number): Buffer { + require(elements.size == size) { "Expected $size elements but found ${elements.size}" } + return bufferFactory(size) { elements[it].toDouble() } +} + +@UnstableKMathAPI +public fun DoubleField.bufferAlgebra(size: Int): BufferField = + BufferField(::DoubleBuffer, DoubleField, size) + diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt index e438995dd..c65a0a48a 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt @@ -6,6 +6,8 @@ package space.kscience.kmath.structures import space.kscience.kmath.linear.Point +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.ExtendedFieldOperations import space.kscience.kmath.operations.Norm @@ -14,6 +16,7 @@ import kotlin.math.* /** * [ExtendedFieldOperations] over [DoubleBuffer]. */ +@Deprecated("To be replaced by generic BufferAlgebra") public object DoubleBufferFieldOperations : ExtendedFieldOperations> { override fun Buffer.unaryMinus(): DoubleBuffer = if (this is DoubleBuffer) { DoubleBuffer(size) { -array[it] } @@ -172,6 +175,7 @@ public object DoubleL2Norm : Norm, Double> { * * @property size the size of buffers to operate on. */ +@Deprecated("To be replaced by generic BufferAlgebra") public class DoubleBufferField(public val size: Int) : ExtendedField>, Norm, Double> { public override val zero: Buffer by lazy { DoubleBuffer(size) { 0.0 } } public override val one: Buffer by lazy { DoubleBuffer(size) { 1.0 } } From 5d2eaaf68aeb0b4c5d455aa46e366436d61de77d Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Tue, 13 Jul 2021 00:21:46 +0700 Subject: [PATCH 086/132] Add contracts to some functions, fix multiple style issues --- .../kmath/benchmarks/JafamaBenchmark.kt | 13 +++--- .../benchmarks/MatrixInverseBenchmark.kt | 4 +- docs/nd-structure.md | 2 + .../space/kscience/kmath/ast/astRendering.kt | 2 +- .../kscience/kmath/ast/rendering/features.kt | 2 +- .../TestCompilerConsistencyWithInterpreter.kt | 1 - .../kmath/ast/TestCompilerVariables.kt | 1 - .../kscience/kmath/internal/estree/estree.kt | 2 + .../kotlin/space/kscience/kmath/ast/utils.kt | 3 ++ .../kscience/kmath/wasm/TestWasmSpecific.kt | 1 - .../kotlin/space/kscience/kmath/ast/utils.kt | 7 +++- .../DerivativeStructureExpression.kt | 2 +- .../commons/optimization/CMOptimization.kt | 4 +- .../commons/transform/Transformations.kt | 2 +- .../DerivativeStructureExpressionTest.kt | 2 +- .../kscience/kmath/complex/Quaternion.kt | 2 +- .../kscience/kmath/data/XYColumnarData.kt | 2 +- .../kscience/kmath/data/XYZColumnarData.kt | 4 +- .../space/kscience/kmath/domains/Domain.kt | 2 +- .../expressions/DifferentiableExpression.kt | 17 ++++---- .../FunctionalExpressionAlgebra.kt | 42 +++++++++++-------- .../kmath/expressions/SimpleAutoDiff.kt | 9 ++-- .../kmath/expressions/SymbolIndexer.kt | 14 +++++-- .../kmath/linear/BufferedLinearSpace.kt | 4 +- .../kscience/kmath/linear/LinearSpace.kt | 2 +- .../kscience/kmath/linear/MatrixFeatures.kt | 14 +++---- .../space/kscience/kmath/misc/cumulative.kt | 2 +- .../space/kscience/kmath/nd/AlgebraND.kt | 9 ++-- .../kscience/kmath/nd/BufferAlgebraND.kt | 6 +-- .../space/kscience/kmath/nd/ShortRingND.kt | 7 ++-- .../space/kscience/kmath/nd/StructureND.kt | 2 +- .../kmath/operations/AlgebraElements.kt | 2 +- .../space/kscience/kmath/operations/BigInt.kt | 2 +- .../kmath/structures/BufferAccessor2D.kt | 18 ++++---- .../kmath/structures/bufferOperation.kt | 4 +- .../kscience/kmath/linear/VectorSpaceTest.kt | 5 --- .../kscience/kmath/testutils/FieldVerifier.kt | 2 +- .../kscience/kmath/testutils/RingVerifier.kt | 2 +- .../kmath/chains/BlockingDoubleChain.kt | 2 +- .../kmath/coroutines/coroutinesExtra.kt | 15 ++++--- .../kscience/kmath/dimensions/Wrappers.kt | 10 ++--- .../kscience/dimensions/DMatrixContextTest.kt | 0 .../space/kscience/kmath/real/RealMatrix.kt | 2 +- .../kaceince/kmath/real/DoubleMatrixTest.kt | 2 +- .../kscience/kmath/functions/Piecewise.kt | 8 ++-- .../kscience/kmath/functions/Polynomial.kt | 4 +- .../kscience/kmath/integration/Integrand.kt | 2 +- .../kmath/integration/UnivariateIntegrand.kt | 2 +- .../kmath/interpolation/Interpolator.kt | 2 +- .../space/kscience/kmath/geometry/Line.kt | 2 +- .../kscience/kmath/histogram/Histogram.kt | 6 +-- .../kmath/histogram/IndexedHistogramSpace.kt | 2 +- .../kmath/histogram/TreeHistogramSpace.kt | 13 +++--- kmath-kotlingrad/build.gradle.kts | 6 +-- .../kscience/kmath/nd4j/Nd4jArrayIterator.kt | 2 +- .../kmath/optimization/Optimization.kt | 2 +- .../kmath/samplers/ConstantSampler.kt | 18 -------- .../space/kscience/kmath/stat/MCScope.kt | 14 +++++-- .../space/kscience/kmath/stat/Sampler.kt | 2 +- .../kscience/kmath/stat/SamplerAlgebra.kt | 6 +-- .../space/kscience/kmath/stat/Statistic.kt | 8 ++-- .../kscience/kmath/symja/SymjaExpression.kt | 3 +- kmath-tensors/README.md | 2 +- kmath-tensors/build.gradle.kts | 14 +++---- .../kmath/tensors/core/BufferedTensor.kt | 4 +- .../kmath/tensors/core/DoubleTensor.kt | 2 +- .../kmath/tensors/core/DoubleTensorAlgebra.kt | 20 ++++----- .../kmath/tensors/core/internal/linUtils.kt | 6 +-- .../tensors/core/internal/tensorCastsUtils.kt | 1 + .../kmath/tensors/core/internal/utils.kt | 1 + .../core/TestDoubleLinearOpsAlgebra.kt | 2 +- .../tensors/core/TestDoubleTensorAlgebra.kt | 2 +- .../kmath/viktor/ViktorStructureND.kt | 2 +- 73 files changed, 210 insertions(+), 200 deletions(-) delete mode 100644 kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/VectorSpaceTest.kt rename kmath-dimensions/src/commonTest/kotlin/{ => space}/kscience/dimensions/DMatrixContextTest.kt (100%) delete mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ConstantSampler.kt diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt index 24a730375..5d4eee7c0 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt @@ -13,6 +13,8 @@ import space.kscience.kmath.jafama.JafamaDoubleField import space.kscience.kmath.jafama.StrictJafamaDoubleField import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke +import kotlin.contracts.InvocationKind +import kotlin.contracts.contract import kotlin.random.Random @State(Scope.Benchmark) @@ -31,9 +33,10 @@ internal class JafamaBenchmark { fun strictJafama(blackhole: Blackhole) = invokeBenchmarks(blackhole) { x -> StrictJafamaDoubleField { x * power(x, 4) * exp(x) / cos(x) + sin(x) } } - - private inline fun invokeBenchmarks(blackhole: Blackhole, expr: (Double) -> Double) { - val rng = Random(0) - repeat(1000000) { blackhole.consume(expr(rng.nextDouble())) } - } +} + +private inline fun invokeBenchmarks(blackhole: Blackhole, expr: (Double) -> Double) { + contract { callsInPlace(expr, InvocationKind.AT_LEAST_ONCE) } + val rng = Random(0) + repeat(1000000) { blackhole.consume(expr(rng.nextDouble())) } } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt index 7bb32af28..e3179c05c 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt @@ -40,14 +40,14 @@ internal class MatrixInverseBenchmark { @Benchmark fun cmLUPInversion(blackhole: Blackhole) { - with(CMLinearSpace) { + CMLinearSpace { blackhole.consume(inverse(matrix)) } } @Benchmark fun ejmlInverse(blackhole: Blackhole) { - with(EjmlLinearSpaceDDRM) { + EjmlLinearSpaceDDRM { blackhole.consume(matrix.getFeature>()?.inverse) } } diff --git a/docs/nd-structure.md b/docs/nd-structure.md index ec9b4d521..ab214094e 100644 --- a/docs/nd-structure.md +++ b/docs/nd-structure.md @@ -115,6 +115,8 @@ via extension function. Usually it is bad idea to compare the direct numerical operation performance in different languages, but it hard to work completely without frame of reference. In this case, simple numpy code: ```python +import numpy as np + res = np.ones((1000,1000)) for i in range(1000): res = res + 1.0 diff --git a/examples/src/main/kotlin/space/kscience/kmath/ast/astRendering.kt b/examples/src/main/kotlin/space/kscience/kmath/ast/astRendering.kt index e16769464..c4f263f97 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/ast/astRendering.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/ast/astRendering.kt @@ -10,7 +10,7 @@ import space.kscience.kmath.ast.rendering.LatexSyntaxRenderer import space.kscience.kmath.ast.rendering.MathMLSyntaxRenderer import space.kscience.kmath.ast.rendering.renderWithStringBuilder -public fun main() { +fun main() { val mst = "exp(sqrt(x))-asin(2*x)/(2e10+x^3)/(-12)".parseMath() val syntax = FeaturedMathRendererWithPostProcess.Default.render(mst) println("MathSyntax:") diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt index a2f42d1bf..203cdf8b3 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt @@ -13,7 +13,7 @@ import space.kscience.kmath.operations.* import kotlin.reflect.KClass /** - * Prints any [Symbol] as a [SymbolSyntax] containing the [Symbol.value] of it. + * Prints any [Symbol] as a [SymbolSyntax] containing the [Symbol.identity] of it. * * @author Iaroslav Postovalov */ diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt index 3116466e6..1edb5923e 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerConsistencyWithInterpreter.kt @@ -11,7 +11,6 @@ import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.interpret import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing -import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke import kotlin.test.Test import kotlin.test.assertEquals diff --git a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt index bed5bc7fa..af1a2e338 100644 --- a/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt +++ b/kmath-ast/src/commonTest/kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt @@ -9,7 +9,6 @@ import space.kscience.kmath.expressions.MstRing import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.invoke import space.kscience.kmath.operations.IntRing -import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke import kotlin.test.Test import kotlin.test.assertEquals diff --git a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/internal/estree/estree.kt b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/internal/estree/estree.kt index e5254013e..b62b8c06c 100644 --- a/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/internal/estree/estree.kt +++ b/kmath-ast/src/jsMain/kotlin/space/kscience/kmath/internal/estree/estree.kt @@ -3,6 +3,8 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ +@file:Suppress("ClassName") + package space.kscience.kmath.internal.estree import kotlin.js.RegExp diff --git a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt index 93b7e9449..0d896c6f6 100644 --- a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt +++ b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt @@ -10,6 +10,8 @@ import space.kscience.kmath.expressions.MST import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing +import kotlin.contracts.InvocationKind +import kotlin.contracts.contract import space.kscience.kmath.estree.compile as estreeCompile import space.kscience.kmath.estree.compileToExpression as estreeCompileToExpression import space.kscience.kmath.wasm.compile as wasmCompile @@ -34,6 +36,7 @@ private object ESTreeCompilerTestContext : CompilerTestContext { } internal actual inline fun runCompilerTest(action: CompilerTestContext.() -> Unit) { + contract { callsInPlace(action, InvocationKind.AT_LEAST_ONCE) } action(WasmCompilerTestContext) action(ESTreeCompilerTestContext) } diff --git a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt index 45776c191..8ae5fcb36 100644 --- a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt +++ b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt @@ -11,7 +11,6 @@ import space.kscience.kmath.expressions.invoke import space.kscience.kmath.expressions.symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing -import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke import kotlin.test.Test import kotlin.test.assertEquals diff --git a/kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt b/kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt index d3b554efd..a7f0bb3fb 100644 --- a/kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt +++ b/kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt @@ -10,6 +10,8 @@ import space.kscience.kmath.expressions.MST import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.IntRing +import kotlin.contracts.InvocationKind +import kotlin.contracts.contract import space.kscience.kmath.asm.compile as asmCompile import space.kscience.kmath.asm.compileToExpression as asmCompileToExpression @@ -22,4 +24,7 @@ private object AsmCompilerTestContext : CompilerTestContext { asmCompile(algebra, arguments) } -internal actual inline fun runCompilerTest(action: CompilerTestContext.() -> Unit) = action(AsmCompilerTestContext) +internal actual inline fun runCompilerTest(action: CompilerTestContext.() -> Unit) { + contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } + action(AsmCompilerTestContext) +} diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt index 361027968..d0ab8b1e8 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt @@ -15,7 +15,7 @@ import space.kscience.kmath.operations.NumbersAddOperations * A field over commons-math [DerivativeStructure]. * * @property order The derivation order. - * @property bindings The map of bindings values. All bindings are considered free parameters + * @param bindings The map of bindings values. All bindings are considered free parameters */ @OptIn(UnstableKMathAPI::class) public class DerivativeStructureField( diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt index 400ee0310..a46f06568 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt @@ -52,11 +52,11 @@ public class CMOptimization( public fun exportOptimizationData(): List = optimizationData.values.toList() - public override fun initialGuess(map: Map): Unit { + public override fun initialGuess(map: Map) { addOptimizationData(InitialGuess(map.toDoubleArray())) } - public override fun function(expression: Expression): Unit { + public override fun function(expression: Expression) { val objectiveFunction = ObjectiveFunction { val args = it.toMap() expression(args) diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt index d29491d63..6fef12138 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt @@ -32,7 +32,7 @@ public object Transformations { /** * Create a virtual buffer on top of array */ - private fun Array.asBuffer() = VirtualBuffer(size) { + private fun Array.asBuffer() = VirtualBuffer(size) { val value = get(it) Complex(value.real, value.imaginary) } diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt index 966675062..0bf1d53f0 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt @@ -16,7 +16,7 @@ internal inline fun diff( order: Int, vararg parameters: Pair, block: DerivativeStructureField.() -> Unit, -): Unit { +) { contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } DerivativeStructureField(order, mapOf(*parameters)).run(block) } diff --git a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt index c59aabdcb..28aae7bb4 100644 --- a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt +++ b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt @@ -147,7 +147,7 @@ public object QuaternionField : Field, Norm, return if (arg.w > 0) Quaternion(ln(arg.w), 0, 0, 0) else { - val l = ComplexField { ComplexField.ln(arg.w.toComplex()) } + val l = ComplexField { ln(arg.w.toComplex()) } Quaternion(l.re, l.im, 0, 0) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt index 08bfd3ca3..920fcc021 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt @@ -16,7 +16,7 @@ import kotlin.math.max * The buffer of X values. */ @UnstableKMathAPI -public interface XYColumnarData : ColumnarData { +public interface XYColumnarData : ColumnarData { /** * The buffer of X values */ diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt index 39a6b858c..6050c311c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYZColumnarData.kt @@ -14,7 +14,7 @@ import space.kscience.kmath.structures.Buffer * Inherits [XYColumnarData]. */ @UnstableKMathAPI -public interface XYZColumnarData : XYColumnarData { +public interface XYZColumnarData : XYColumnarData { public val z: Buffer override fun get(symbol: Symbol): Buffer? = when (symbol) { @@ -23,4 +23,4 @@ public interface XYZColumnarData : XYColumna Symbol.z -> z else -> null } -} \ No newline at end of file +} diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/Domain.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/Domain.kt index e6e703cbf..b5a84cf6c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/Domain.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/Domain.kt @@ -12,7 +12,7 @@ import space.kscience.kmath.linear.Point * * @param T the type of element of this domain. */ -public interface Domain { +public interface Domain { /** * Checks if the specified point is contained in this domain. */ diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt index 1dcada6d3..ce1265b2f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt @@ -9,7 +9,6 @@ package space.kscience.kmath.expressions * Represents expression which structure can be differentiated. * * @param T the type this expression takes as argument and returns. - * @param R the type of expression this expression can be differentiated to. */ public interface DifferentiableExpression : Expression { /** @@ -24,16 +23,18 @@ public interface DifferentiableExpression : Expression { public fun DifferentiableExpression.derivative(symbols: List): Expression = derivativeOrNull(symbols) ?: error("Derivative by symbols $symbols not provided") -public fun DifferentiableExpression.derivative(vararg symbols: Symbol): Expression = +public fun DifferentiableExpression.derivative(vararg symbols: Symbol): Expression = derivative(symbols.toList()) -public fun DifferentiableExpression.derivative(name: String): Expression = +public fun DifferentiableExpression.derivative(name: String): Expression = derivative(StringSymbol(name)) /** - * A special type of [DifferentiableExpression] which returns typed expressions as derivatives + * A special type of [DifferentiableExpression] which returns typed expressions as derivatives. + * + * @param R the type of expression this expression can be differentiated to. */ -public interface SpecialDifferentiableExpression>: DifferentiableExpression { +public interface SpecialDifferentiableExpression> : DifferentiableExpression { override fun derivativeOrNull(symbols: List): R? } @@ -53,9 +54,9 @@ public abstract class FirstDerivativeExpression : DifferentiableExpression /** * Returns first derivative of this expression by given [symbol]. */ - public abstract fun derivativeOrNull(symbol: Symbol): Expression? + public abstract fun derivativeOrNull(symbol: Symbol): Expression? - public final override fun derivativeOrNull(symbols: List): Expression? { + public final override fun derivativeOrNull(symbols: List): Expression? { val dSymbol = symbols.firstOrNull() ?: return null return derivativeOrNull(dSymbol) } @@ -64,6 +65,6 @@ public abstract class FirstDerivativeExpression : DifferentiableExpression /** * A factory that converts an expression in autodiff variables to a [DifferentiableExpression] */ -public fun interface AutoDiffProcessor, out R : Expression> { +public fun interface AutoDiffProcessor, out R : Expression> { public fun process(function: A.() -> I): DifferentiableExpression } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt index 951ec9474..a10e29cf0 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt @@ -6,13 +6,15 @@ package space.kscience.kmath.expressions import space.kscience.kmath.operations.* +import kotlin.contracts.InvocationKind +import kotlin.contracts.contract /** * A context class for [Expression] construction. * * @param algebra The algebra to provide for Expressions built. */ -public abstract class FunctionalExpressionAlgebra>( +public abstract class FunctionalExpressionAlgebra>( public val algebra: A, ) : ExpressionAlgebra> { /** @@ -29,9 +31,6 @@ public abstract class FunctionalExpressionAlgebra>( ?: error("Symbol '$value' is not supported in $this") } - /** - * Builds an Expression of dynamic call of binary operation [operation] on [left] and [right]. - */ public override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = { left, right -> Expression { arguments -> @@ -39,9 +38,6 @@ public abstract class FunctionalExpressionAlgebra>( } } - /** - * Builds an Expression of dynamic call of unary operation with name [operation] on [arg]. - */ public override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = { arg -> Expression { arguments -> algebra.unaryOperationFunction(operation)(arg.invoke(arguments)) } } @@ -50,7 +46,7 @@ public abstract class FunctionalExpressionAlgebra>( /** * A context class for [Expression] construction for [Ring] algebras. */ -public open class FunctionalExpressionGroup>( +public open class FunctionalExpressionGroup>( algebra: A, ) : FunctionalExpressionAlgebra(algebra), Group> { public override val zero: Expression get() = const(algebra.zero) @@ -84,7 +80,7 @@ public open class FunctionalExpressionGroup>( } -public open class FunctionalExpressionRing>( +public open class FunctionalExpressionRing>( algebra: A, ) : FunctionalExpressionGroup(algebra), Ring> { public override val one: Expression get() = const(algebra.one) @@ -105,7 +101,7 @@ public open class FunctionalExpressionRing>( super.binaryOperationFunction(operation) } -public open class FunctionalExpressionField>( +public open class FunctionalExpressionField>( algebra: A, ) : FunctionalExpressionRing(algebra), Field>, ScaleOperations> { /** @@ -131,7 +127,7 @@ public open class FunctionalExpressionField>( super.bindSymbolOrNull(value) } -public open class FunctionalExpressionExtendedField>( +public open class FunctionalExpressionExtendedField>( algebra: A, ) : FunctionalExpressionField(algebra), ExtendedField> { public override fun number(value: Number): Expression = const(algebra.number(value)) @@ -172,14 +168,26 @@ public open class FunctionalExpressionExtendedField>( public override fun bindSymbol(value: String): Expression = super.bindSymbol(value) } -public inline fun > A.expressionInSpace(block: FunctionalExpressionGroup.() -> Expression): Expression = - FunctionalExpressionGroup(this).block() +public inline fun > A.expressionInGroup( + block: FunctionalExpressionGroup.() -> Expression, +): Expression { + contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } + return FunctionalExpressionGroup(this).block() +} -public inline fun > A.expressionInRing(block: FunctionalExpressionRing.() -> Expression): Expression = - FunctionalExpressionRing(this).block() +public inline fun > A.expressionInRing( + block: FunctionalExpressionRing.() -> Expression, +): Expression { + contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } + return FunctionalExpressionRing(this).block() +} -public inline fun > A.expressionInField(block: FunctionalExpressionField.() -> Expression): Expression = - FunctionalExpressionField(this).block() +public inline fun > A.expressionInField( + block: FunctionalExpressionField.() -> Expression, +): Expression { + contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } + return FunctionalExpressionField(this).block() +} public inline fun > A.expressionInExtendedField( block: FunctionalExpressionExtendedField.() -> Expression, diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt index 478b85620..960f6fd79 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt @@ -119,8 +119,6 @@ public open class SimpleAutoDiffField>( get() = getDerivative(this) set(value) = setDerivative(this, value) - public inline fun const(block: F.() -> T): AutoDiffValue = const(context.block()) - /** * Performs update of derivative after the rest of the formula in the back-pass. * @@ -194,6 +192,11 @@ public open class SimpleAutoDiffField>( } } +public inline fun > SimpleAutoDiffField.const(block: F.() -> T): AutoDiffValue { + contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } + return const(context.block()) +} + /** * Runs differentiation and establishes [SimpleAutoDiffField] context inside the block of code. @@ -208,7 +211,7 @@ public open class SimpleAutoDiffField>( * assertEquals(9.0, x.d) // dy/dx * ``` * - * @param body the action in [SimpleAutoDiffField] context returning [AutoDiffVariable] to differentiate with respect to. + * @param body the action in [SimpleAutoDiffField] context returning [AutoDiffValue] to differentiate with respect to. * @return the result of differentiation. */ public fun > F.simpleAutoDiff( diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt index 06634704c..c02bdad02 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SymbolIndexer.kt @@ -9,6 +9,8 @@ import space.kscience.kmath.linear.Point import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.Structure2D import space.kscience.kmath.structures.BufferFactory +import kotlin.contracts.InvocationKind +import kotlin.contracts.contract import kotlin.jvm.JvmInline /** @@ -65,9 +67,13 @@ public value class SimpleSymbolIndexer(override val symbols: List) : Sym * Execute the block with symbol indexer based on given symbol order */ @UnstableKMathAPI -public inline fun withSymbols(vararg symbols: Symbol, block: SymbolIndexer.() -> R): R = - with(SimpleSymbolIndexer(symbols.toList()), block) +public inline fun withSymbols(vararg symbols: Symbol, block: SymbolIndexer.() -> R): R { + contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } + return with(SimpleSymbolIndexer(symbols.toList()), block) +} @UnstableKMathAPI -public inline fun withSymbols(symbols: Collection, block: SymbolIndexer.() -> R): R = - with(SimpleSymbolIndexer(symbols.toList()), block) \ No newline at end of file +public inline fun withSymbols(symbols: Collection, block: SymbolIndexer.() -> R): R { + contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } + return with(SimpleSymbolIndexer(symbols.toList()), block) +} diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt index 9b4451a62..f1839077f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt @@ -15,7 +15,7 @@ import space.kscience.kmath.structures.VirtualBuffer import space.kscience.kmath.structures.indices -public class BufferedLinearSpace>( +public class BufferedLinearSpace>( override val elementAlgebra: A, private val bufferFactory: BufferFactory, ) : LinearSpace { @@ -88,4 +88,4 @@ public class BufferedLinearSpace>( override fun Matrix.times(value: T): Matrix = ndRing(rowNum, colNum).run { unwrap().map { it * value }.as2D() } -} \ No newline at end of file +} diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt index ec073ac48..badf2794e 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt @@ -32,7 +32,7 @@ public typealias Point = Buffer * Basic operations on matrices and vectors. Operates on [Matrix]. * * @param T the type of items in the matrices. - * @param M the type of operated matrices. + * @param A the type of ring over [T]. */ public interface LinearSpace> { public val elementAlgebra: A diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt index 37c93d249..e0d733a66 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt @@ -35,7 +35,7 @@ public object UnitFeature : DiagonalFeature * * @param T the type of matrices' items. */ -public interface InverseMatrixFeature : MatrixFeature { +public interface InverseMatrixFeature : MatrixFeature { /** * The inverse matrix of the matrix that owns this feature. */ @@ -47,7 +47,7 @@ public interface InverseMatrixFeature : MatrixFeature { * * @param T the type of matrices' items. */ -public interface DeterminantFeature : MatrixFeature { +public interface DeterminantFeature : MatrixFeature { /** * The determinant of the matrix that owns this feature. */ @@ -80,7 +80,7 @@ public object UFeature : MatrixFeature * * @param T the type of matrices' items. */ -public interface LUDecompositionFeature : MatrixFeature { +public interface LUDecompositionFeature : MatrixFeature { /** * The lower triangular matrix in this decomposition. It may have [LFeature]. */ @@ -98,7 +98,7 @@ public interface LUDecompositionFeature : MatrixFeature { * * @param T the type of matrices' items. */ -public interface LupDecompositionFeature : MatrixFeature { +public interface LupDecompositionFeature : MatrixFeature { /** * The lower triangular matrix in this decomposition. It may have [LFeature]. */ @@ -126,7 +126,7 @@ public object OrthogonalFeature : MatrixFeature * * @param T the type of matrices' items. */ -public interface QRDecompositionFeature : MatrixFeature { +public interface QRDecompositionFeature : MatrixFeature { /** * The orthogonal matrix in this decomposition. It may have [OrthogonalFeature]. */ @@ -144,7 +144,7 @@ public interface QRDecompositionFeature : MatrixFeature { * * @param T the type of matrices' items. */ -public interface CholeskyDecompositionFeature : MatrixFeature { +public interface CholeskyDecompositionFeature : MatrixFeature { /** * The triangular matrix in this decomposition. It may have either [UFeature] or [LFeature]. */ @@ -157,7 +157,7 @@ public interface CholeskyDecompositionFeature : MatrixFeature { * * @param T the type of matrices' items. */ -public interface SingularValueDecompositionFeature : MatrixFeature { +public interface SingularValueDecompositionFeature : MatrixFeature { /** * The matrix in this decomposition. It is unitary, and it consists from left singular vectors. */ diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/cumulative.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/cumulative.kt index 889eb4f22..ee7f1d8be 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/cumulative.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/cumulative.kt @@ -34,7 +34,7 @@ public inline fun Iterable.cumulative(initial: R, crossinline operatio public inline fun Sequence.cumulative(initial: R, crossinline operation: (R, T) -> R): Sequence = Sequence { this@cumulative.iterator().cumulative(initial, operation) } -public fun List.cumulative(initial: R, operation: (R, T) -> R): List = +public inline fun List.cumulative(initial: R, crossinline operation: (R, T) -> R): List = iterator().cumulative(initial, operation).asSequence().toList() //Cumulative sum diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt index 35bbc44f6..38985f216 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt @@ -24,7 +24,6 @@ public class ShapeMismatchException(public val expected: IntArray, public val ac * * @param T the type of ND-structure element. * @param C the type of the element context. - * @param N the type of the structure. */ public interface AlgebraND> { /** @@ -118,8 +117,7 @@ internal fun > AlgebraND.checkShape(element: StructureND * Space of [StructureND]. * * @param T the type of the element contained in ND structure. - * @param N the type of ND structure. - * @param S the type of space of structure elements. + * @param S the type of group over structure elements. */ public interface GroupND> : Group>, AlgebraND { /** @@ -186,8 +184,7 @@ public interface GroupND> : Group>, AlgebraND * Ring of [StructureND]. * * @param T the type of the element contained in ND structure. - * @param N the type of ND structure. - * @param R the type of ring of structure elements. + * @param R the type of ring over structure elements. */ public interface RingND> : Ring>, GroupND { /** @@ -227,7 +224,7 @@ public interface RingND> : Ring>, GroupND> : Field>, RingND, ScaleOperations> { /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt index 2b82a36ae..6eacf1ca5 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt @@ -57,7 +57,7 @@ public interface BufferAlgebraND> : AlgebraND { } } -public open class BufferedGroupND>( +public open class BufferedGroupND>( final override val shape: IntArray, final override val elementContext: A, final override val bufferFactory: BufferFactory, @@ -67,7 +67,7 @@ public open class BufferedGroupND>( override fun StructureND.unaryMinus(): StructureND = produce { -get(it) } } -public open class BufferedRingND>( +public open class BufferedRingND>( shape: IntArray, elementContext: R, bufferFactory: BufferFactory, @@ -75,7 +75,7 @@ public open class BufferedRingND>( override val one: BufferND by lazy { produce { one } } } -public open class BufferedFieldND>( +public open class BufferedFieldND>( shape: IntArray, elementContext: R, bufferFactory: BufferFactory, diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt index 720a06ace..1305558e5 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt @@ -31,11 +31,10 @@ public class ShortRingND( /** * Fast element production using function inlining. */ -public inline fun BufferedRingND.produceInline(crossinline initializer: ShortRing.(Int) -> Short): BufferND { - return BufferND(strides, ShortBuffer(ShortArray(strides.linearSize) { offset -> ShortRing.initializer(offset) })) -} +public inline fun BufferedRingND.produceInline(crossinline initializer: ShortRing.(Int) -> Short): BufferND = + BufferND(strides, ShortBuffer(ShortArray(strides.linearSize) { offset -> ShortRing.initializer(offset) })) public inline fun ShortRing.nd(vararg shape: Int, action: ShortRingND.() -> R): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } return ShortRingND(shape).run(action) -} \ No newline at end of file +} diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt index 7fc91e321..1ad8289bc 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt @@ -53,7 +53,7 @@ public interface StructureND { public fun elements(): Sequence> /** - * Feature is some additional strucure information which allows to access it special properties or hints. + * Feature is some additional structure information which allows to access it special properties or hints. * If the feature is not present, null is returned. */ @UnstableKMathAPI diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt index cc058d3fc..403a9c9b1 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt @@ -15,7 +15,7 @@ import space.kscience.kmath.misc.UnstableKMathAPI */ @UnstableKMathAPI @Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public interface AlgebraElement> { +public interface AlgebraElement> { /** * The context this element belongs to. */ diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index ac53c4d5e..c332b086e 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -445,7 +445,7 @@ public fun UIntArray.toBigInt(sign: Byte): BigInt { * Returns null if a valid number can not be read from a string */ public fun String.parseBigInteger(): BigInt? { - if (this.isEmpty()) return null + if (isEmpty()) return null val sign: Int val positivePartIndex = when (this[0]) { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt index 352c75956..03b3822c3 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt @@ -14,30 +14,30 @@ import space.kscience.kmath.nd.as2D * A context that allows to operate on a [MutableBuffer] as on 2d array */ internal class BufferAccessor2D( - public val rowNum: Int, - public val colNum: Int, + val rowNum: Int, + val colNum: Int, val factory: MutableBufferFactory, ) { - public operator fun Buffer.get(i: Int, j: Int): T = get(i * colNum + j) + operator fun Buffer.get(i: Int, j: Int): T = get(i * colNum + j) - public operator fun MutableBuffer.set(i: Int, j: Int, value: T) { + operator fun MutableBuffer.set(i: Int, j: Int, value: T) { set(i * colNum + j, value) } - public inline fun create(crossinline init: (i: Int, j: Int) -> T): MutableBuffer = + inline fun create(crossinline init: (i: Int, j: Int) -> T): MutableBuffer = factory(rowNum * colNum) { offset -> init(offset / colNum, offset % colNum) } - public fun create(mat: Structure2D): MutableBuffer = create { i, j -> mat[i, j] } + fun create(mat: Structure2D): MutableBuffer = create { i, j -> mat[i, j] } //TODO optimize wrapper - public fun MutableBuffer.collect(): Structure2D = StructureND.buffered( + fun MutableBuffer.collect(): Structure2D = StructureND.buffered( DefaultStrides(intArrayOf(rowNum, colNum)), factory ) { (i, j) -> get(i, j) }.as2D() - public inner class Row(public val buffer: MutableBuffer, public val rowIndex: Int) : MutableBuffer { + inner class Row(val buffer: MutableBuffer, val rowIndex: Int) : MutableBuffer { override val size: Int get() = colNum override operator fun get(index: Int): T = buffer[rowIndex, index] @@ -54,5 +54,5 @@ internal class BufferAccessor2D( /** * Get row */ - public fun MutableBuffer.row(i: Int): Row = Row(this, i) + fun MutableBuffer.row(i: Int): Row = Row(this, i) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferOperation.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferOperation.kt index 1b89e7838..3dad14ac5 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferOperation.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferOperation.kt @@ -67,9 +67,9 @@ public inline fun Buffer.map(block: (T) -> R): Buf * Create a new buffer from this one with the given mapping function. * Provided [bufferFactory] is used to construct the new buffer. */ -public fun Buffer.map( +public inline fun Buffer.map( bufferFactory: BufferFactory, - block: (T) -> R, + crossinline block: (T) -> R, ): Buffer = bufferFactory(size) { block(get(it)) } /** diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/VectorSpaceTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/VectorSpaceTest.kt deleted file mode 100644 index f2c7f1f90..000000000 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/VectorSpaceTest.kt +++ /dev/null @@ -1,5 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/testutils/FieldVerifier.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/testutils/FieldVerifier.kt index bd09ff449..20a7b6a72 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/testutils/FieldVerifier.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/testutils/FieldVerifier.kt @@ -10,7 +10,7 @@ import space.kscience.kmath.operations.invoke import kotlin.test.assertEquals import kotlin.test.assertNotEquals -internal class FieldVerifier>( +internal class FieldVerifier>( algebra: A, a: T, b: T, c: T, x: Number, ) : RingVerifier(algebra, a, b, c, x) { diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/testutils/RingVerifier.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/testutils/RingVerifier.kt index 885857f04..daf18834a 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/testutils/RingVerifier.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/testutils/RingVerifier.kt @@ -10,7 +10,7 @@ import space.kscience.kmath.operations.ScaleOperations import space.kscience.kmath.operations.invoke import kotlin.test.assertEquals -internal open class RingVerifier(algebra: A, a: T, b: T, c: T, x: Number) : +internal open class RingVerifier(algebra: A, a: T, b: T, c: T, x: Number) : SpaceVerifier(algebra, a, b, c, x) where A : Ring, A : ScaleOperations { override fun verify() { diff --git a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingDoubleChain.kt b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingDoubleChain.kt index 526250cf0..88456e124 100644 --- a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingDoubleChain.kt +++ b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingDoubleChain.kt @@ -29,4 +29,4 @@ public fun BlockingDoubleChain.map(transform: (Double) -> Double): BlockingDoubl } override suspend fun fork(): BlockingDoubleChain = this@map.fork().map(transform) -} \ No newline at end of file +} diff --git a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/coroutines/coroutinesExtra.kt b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/coroutines/coroutinesExtra.kt index 49f32f82f..1f17efe49 100644 --- a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/coroutines/coroutinesExtra.kt +++ b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/coroutines/coroutinesExtra.kt @@ -15,30 +15,33 @@ public val Dispatchers.Math: CoroutineDispatcher /** * An imitator of [Deferred] which holds a suspended function block and dispatcher */ -internal class LazyDeferred(val dispatcher: CoroutineDispatcher, val block: suspend CoroutineScope.() -> T) { +@PublishedApi +internal class LazyDeferred(val dispatcher: CoroutineDispatcher, val block: suspend CoroutineScope.() -> T) { private var deferred: Deferred? = null - internal fun start(scope: CoroutineScope) { + fun start(scope: CoroutineScope) { if (deferred == null) deferred = scope.async(dispatcher, block = block) } suspend fun await(): T = deferred?.await() ?: error("Coroutine not started") } -public class AsyncFlow internal constructor(internal val deferredFlow: Flow>) : Flow { +public class AsyncFlow @PublishedApi internal constructor( + @PublishedApi internal val deferredFlow: Flow>, +) : Flow { override suspend fun collect(collector: FlowCollector): Unit = deferredFlow.collect { collector.emit((it.await())) } } -public fun Flow.async( +public inline fun Flow.async( dispatcher: CoroutineDispatcher = Dispatchers.Default, - block: suspend CoroutineScope.(T) -> R, + crossinline block: suspend CoroutineScope.(T) -> R, ): AsyncFlow { val flow = map { LazyDeferred(dispatcher) { block(it) } } return AsyncFlow(flow) } -public fun AsyncFlow.map(action: (T) -> R): AsyncFlow = +public inline fun AsyncFlow.map(crossinline action: (T) -> R): AsyncFlow = AsyncFlow(deferredFlow.map { input -> //TODO add function composition LazyDeferred(input.dispatcher) { diff --git a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt index 2ebcc454d..a2ee14301 100644 --- a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt +++ b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt @@ -17,7 +17,7 @@ import kotlin.jvm.JvmInline /** * A matrix with compile-time controlled dimension */ -public interface DMatrix : Structure2D { +public interface DMatrix : Structure2D { public companion object { /** * Coerces a regular matrix to a matrix with type-safe dimensions and throws a error if coercion failed @@ -46,7 +46,7 @@ public interface DMatrix : Structure2D { * An inline wrapper for a Matrix */ @JvmInline -public value class DMatrixWrapper( +public value class DMatrixWrapper( private val structure: Structure2D, ) : DMatrix { override val shape: IntArray get() = structure.shape @@ -58,7 +58,7 @@ public value class DMatrixWrapper( /** * Dimension-safe point */ -public interface DPoint : Point { +public interface DPoint : Point { public companion object { public inline fun coerce(point: Point): DPoint { require(point.size == Dimension.dim().toInt()) { @@ -76,7 +76,7 @@ public interface DPoint : Point { * Dimension-safe point wrapper */ @JvmInline -public value class DPointWrapper(public val point: Point) : +public value class DPointWrapper(public val point: Point) : DPoint { override val size: Int get() = point.size @@ -111,7 +111,7 @@ public value class DMatrixContext>(public val context: ): DMatrix { val rows = Dimension.dim() val cols = Dimension.dim() - return context.buildMatrix(rows.toInt(), cols.toInt(), initializer).coerce() + return context.buildMatrix(rows.toInt(), cols.toInt(), initializer).coerce() } public inline fun point(noinline initializer: A.(Int) -> T): DPoint { diff --git a/kmath-dimensions/src/commonTest/kotlin/kscience/dimensions/DMatrixContextTest.kt b/kmath-dimensions/src/commonTest/kotlin/space/kscience/dimensions/DMatrixContextTest.kt similarity index 100% rename from kmath-dimensions/src/commonTest/kotlin/kscience/dimensions/DMatrixContextTest.kt rename to kmath-dimensions/src/commonTest/kotlin/space/kscience/dimensions/DMatrixContextTest.kt diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt index 8023236ea..091b5db3f 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt @@ -184,4 +184,4 @@ public fun tan(arg: RealMatrix): RealMatrix = arg.map { kotlin.math.tan(it) } public fun ln(arg: RealMatrix): RealMatrix = arg.map { kotlin.math.ln(it) } -public fun log10(arg: RealMatrix): RealMatrix = arg.map { kotlin.math.log10(it) } \ No newline at end of file +public fun log10(arg: RealMatrix): RealMatrix = arg.map { kotlin.math.log10(it) } diff --git a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt b/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt index b3e129c2e..a9c5f9e1a 100644 --- a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt @@ -32,7 +32,7 @@ internal class DoubleMatrixTest { @Test fun testSequenceToMatrix() { - val m = Sequence { + val m = Sequence { listOf( DoubleArray(10) { 10.0 }, DoubleArray(10) { 20.0 }, diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt index 73fa57c7b..5f35d0ab6 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt @@ -14,7 +14,7 @@ import space.kscience.kmath.operations.Ring * @param T the piece key type. * @param R the sub-function type. */ -public fun interface Piecewise { +public fun interface Piecewise { /** * Returns the appropriate sub-function for given piece key. */ @@ -23,7 +23,9 @@ public fun interface Piecewise { /** * Represents piecewise-defined function where all the sub-functions are polynomials. - * @param pieces An ordered list of range-polynomial pairs. The list does not in general guarantee that there are no "holes" in it. + * + * @property pieces An ordered list of range-polynomial pairs. The list does not in general guarantee that there are no + * "holes" in it. */ public interface PiecewisePolynomial> : Piecewise> { public val pieces: Collection, Polynomial>> @@ -45,7 +47,7 @@ public fun > PiecewisePolynomial( /** * An optimized piecewise which uses not separate pieces, but a range separated by delimiters. - * The pices search is logarithmic + * The pieces search is logarithmic */ private class OrderedPiecewisePolynomial>( override val pieces: List, Polynomial>>, diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt index ba77d7b25..f0c858b03 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt @@ -17,7 +17,7 @@ import kotlin.math.pow * * @param coefficients constant is the leftmost coefficient. */ -public class Polynomial(public val coefficients: List) { +public class Polynomial(public val coefficients: List) { override fun toString(): String = "Polynomial$coefficients" } @@ -69,7 +69,7 @@ public fun Polynomial.differentiate( public fun Polynomial.integrate( algebra: A, ): Polynomial where A : Field, A : NumericAlgebra = algebra { - val integratedCoefficients = buildList(coefficients.size + 1) { + val integratedCoefficients = buildList(coefficients.size + 1) { add(zero) coefficients.forEachIndexed{ index, t -> add(t / (number(index) + one)) } } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt index f9c26e88b..4f565a893 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrand.kt @@ -18,7 +18,7 @@ public interface Integrand { public inline fun Integrand.getFeature(): T? = getFeature(T::class) -public class IntegrandValue(public val value: T) : IntegrandFeature { +public class IntegrandValue(public val value: T) : IntegrandFeature { override fun toString(): String = "Value($value)" } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index e265f54e8..7f68284a7 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -93,7 +93,7 @@ public fun UnivariateIntegrator.integrate( ): UnivariateIntegrand = integrate(UnivariateIntegrand(function, IntegrationRange(range), *features)) /** - * A shortcut method to integrate a [function] in [range] with additional [features]. + * A shortcut method to integrate a [function] in [range] with additional features. * The [function] is placed in the end position to allow passing a lambda. */ @UnstableKMathAPI diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt index c9ec0d527..f4a0abd5d 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt @@ -18,7 +18,7 @@ import space.kscience.kmath.structures.asBuffer /** * And interpolator for data with x column type [X], y column type [Y]. */ -public fun interface Interpolator { +public fun interface Interpolator { public fun interpolate(points: XYColumnarData): (X) -> Y } diff --git a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Line.kt b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Line.kt index 5a6d23709..8c6ccb55e 100644 --- a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Line.kt +++ b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Line.kt @@ -5,7 +5,7 @@ package space.kscience.kmath.geometry -public data class Line(val base: V, val direction: V) +public data class Line(val base: V, val direction: V) public typealias Line2D = Line public typealias Line3D = Line diff --git a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt index fcb5e96dc..31da4f392 100644 --- a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt +++ b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt @@ -13,14 +13,14 @@ import space.kscience.kmath.structures.asBuffer /** * The binned data element. Could be a histogram bin with a number of counts or an artificial construct */ -public interface Bin : Domain { +public interface Bin : Domain { /** * The value of this bin. */ public val value: Number } -public interface Histogram> { +public interface Histogram> { /** * Find existing bin, corresponding to given coordinates */ @@ -34,7 +34,7 @@ public interface Histogram> { public val bins: Iterable } -public fun interface HistogramBuilder { +public fun interface HistogramBuilder { /** * Increment appropriate bin diff --git a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt index e5f6830c5..6d48d3738 100644 --- a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt +++ b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt @@ -18,7 +18,7 @@ import space.kscience.kmath.operations.invoke /** * A simple histogram bin based on domain */ -public data class DomainBin>( +public data class DomainBin>( public val domain: Domain, public override val value: Number, ) : Bin, Domain by domain diff --git a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt index 8d05df68a..daea4a82e 100644 --- a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt +++ b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/TreeHistogramSpace.kt @@ -36,9 +36,10 @@ public class TreeHistogram( } @OptIn(UnstableKMathAPI::class) -private class TreeHistogramBuilder(val binFactory: (Double) -> UnivariateDomain) : UnivariateHistogramBuilder { +@PublishedApi +internal class TreeHistogramBuilder(val binFactory: (Double) -> UnivariateDomain) : UnivariateHistogramBuilder { - private class BinCounter(val domain: UnivariateDomain, val counter: Counter = Counter.real()) : + internal class BinCounter(val domain: UnivariateDomain, val counter: Counter = Counter.real()) : ClosedFloatingPointRange by domain.range private val bins: TreeMap = TreeMap() @@ -80,10 +81,10 @@ private class TreeHistogramBuilder(val binFactory: (Double) -> UnivariateDomain) */ @UnstableKMathAPI public class TreeHistogramSpace( - private val binFactory: (Double) -> UnivariateDomain, + @PublishedApi internal val binFactory: (Double) -> UnivariateDomain, ) : Group, ScaleOperations { - public fun fill(block: UnivariateHistogramBuilder.() -> Unit): UnivariateHistogram = + public inline fun fill(block: UnivariateHistogramBuilder.() -> Unit): UnivariateHistogram = TreeHistogramBuilder(binFactory).apply(block).build() override fun add( @@ -115,8 +116,8 @@ public class TreeHistogramSpace( bin.domain.center, UnivariateBin( bin.domain, - value = bin.value * value.toDouble(), - standardDeviation = abs(bin.standardDeviation * value.toDouble()) + value = bin.value * value, + standardDeviation = abs(bin.standardDeviation * value) ) ) } diff --git a/kmath-kotlingrad/build.gradle.kts b/kmath-kotlingrad/build.gradle.kts index 01b42d7ba..d222ed7d6 100644 --- a/kmath-kotlingrad/build.gradle.kts +++ b/kmath-kotlingrad/build.gradle.kts @@ -18,14 +18,14 @@ readme { feature( "differentiable-mst-expression", - "src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt", + "src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt", ) { "MST based DifferentiableExpression." } feature( - "differentiable-mst-expression", - "src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt", + "scalars-adapters", + "src/main/kotlin/space/kscience/kmath/kotlingrad/scalarsAdapters.kt", ) { "Conversions between Kotlin∇'s SFun and MST" } diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayIterator.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayIterator.kt index 140a212f8..d4cad8996 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayIterator.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayIterator.kt @@ -25,7 +25,7 @@ private class Nd4jArrayIndicesIterator(private val iterateOver: INDArray) : Iter internal fun INDArray.indicesIterator(): Iterator = Nd4jArrayIndicesIterator(this) -private sealed class Nd4jArrayIteratorBase(protected val iterateOver: INDArray) : Iterator> { +private sealed class Nd4jArrayIteratorBase(protected val iterateOver: INDArray) : Iterator> { private var i: Int = 0 final override fun hasNext(): Boolean = i < iterateOver.length() diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt index 4a1676412..15ae494f6 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt @@ -9,7 +9,7 @@ import space.kscience.kmath.expressions.Symbol public interface OptimizationFeature -public class OptimizationResult( +public class OptimizationResult( public val point: Map, public val value: T, public val features: Set = emptySet(), diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ConstantSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ConstantSampler.kt deleted file mode 100644 index 0d38fe19b..000000000 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ConstantSampler.kt +++ /dev/null @@ -1,18 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.samplers - -import space.kscience.kmath.chains.BlockingBufferChain -import space.kscience.kmath.stat.RandomGenerator -import space.kscience.kmath.stat.Sampler -import space.kscience.kmath.structures.Buffer - -public class ConstantSampler(public val const: T) : Sampler { - override fun sample(generator: RandomGenerator): BlockingBufferChain = object : BlockingBufferChain { - override fun nextBufferBlocking(size: Int): Buffer = Buffer.boxing(size) { const } - override suspend fun fork(): BlockingBufferChain = this - } -} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/MCScope.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/MCScope.kt index 9e5c70a26..0e06fa162 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/MCScope.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/MCScope.kt @@ -6,6 +6,8 @@ package space.kscience.kmath.stat import kotlinx.coroutines.* +import kotlin.contracts.InvocationKind +import kotlin.contracts.contract import kotlin.coroutines.CoroutineContext import kotlin.coroutines.EmptyCoroutineContext import kotlin.coroutines.coroutineContext @@ -23,14 +25,18 @@ public class MCScope( /** * Launches a supervised Monte-Carlo scope */ -public suspend inline fun mcScope(generator: RandomGenerator, block: MCScope.() -> T): T = - MCScope(coroutineContext, generator).block() +public suspend inline fun mcScope(generator: RandomGenerator, block: MCScope.() -> T): T { + contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } + return MCScope(coroutineContext, generator).block() +} /** * Launch mc scope with a given seed */ -public suspend inline fun mcScope(seed: Long, block: MCScope.() -> T): T = - mcScope(RandomGenerator.default(seed), block) +public suspend inline fun mcScope(seed: Long, block: MCScope.() -> T): T { + contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) } + return mcScope(RandomGenerator.default(seed), block) +} /** * Specialized launch for [MCScope]. Behaves the same way as regular [CoroutineScope.launch], but also stores the generator fork. diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Sampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Sampler.kt index 51ae78d3d..4c11fdd65 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Sampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Sampler.kt @@ -12,7 +12,7 @@ import space.kscience.kmath.structures.* import kotlin.jvm.JvmName /** - * Sampler that generates chains of values of type [T] in a chain of type [C]. + * Sampler that generates chains of values of type [T]. */ public fun interface Sampler { /** diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt index b3d607ab0..27465eff4 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt @@ -18,7 +18,7 @@ import space.kscience.kmath.operations.invoke * * @property value the value to sample. */ -public class ConstantSampler(public val value: T) : Sampler { +public class ConstantSampler(public val value: T) : Sampler { public override fun sample(generator: RandomGenerator): Chain = ConstantChain(value) } @@ -27,7 +27,7 @@ public class ConstantSampler(public val value: T) : Sampler { * * @property chainBuilder the provider of [Chain]. */ -public class BasicSampler(public val chainBuilder: (RandomGenerator) -> Chain) : Sampler { +public class BasicSampler(public val chainBuilder: (RandomGenerator) -> Chain) : Sampler { public override fun sample(generator: RandomGenerator): Chain = chainBuilder(generator) } @@ -36,7 +36,7 @@ public class BasicSampler(public val chainBuilder: (RandomGenerator) -> * * @property algebra the space to provide addition and scalar multiplication for [T]. */ -public class SamplerSpace(public val algebra: S) : Group>, +public class SamplerSpace(public val algebra: S) : Group>, ScaleOperations> where S : Group, S : ScaleOperations { public override val zero: Sampler = ConstantSampler(algebra.zero) diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt index 1b05aa9cd..f29b7415c 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt @@ -18,14 +18,14 @@ import space.kscience.kmath.structures.Buffer /** * A function, that transforms a buffer of random quantities to some resulting value */ -public interface Statistic { +public interface Statistic { public suspend fun evaluate(data: Buffer): R } -public interface BlockingStatistic: Statistic{ +public interface BlockingStatistic : Statistic { public fun evaluateBlocking(data: Buffer): R - override suspend fun evaluate(data: Buffer): R = evaluateBlocking(data) + override suspend fun evaluate(data: Buffer): R = evaluateBlocking(data) } /** @@ -34,7 +34,7 @@ public interface BlockingStatistic: Statistic{ * @param I - intermediate block type * @param R - result type */ -public interface ComposableStatistic : Statistic { +public interface ComposableStatistic : Statistic { //compute statistic on a single block public suspend fun computeIntermediate(data: Buffer): I diff --git a/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt index a6773c709..88f0c941e 100644 --- a/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt +++ b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt @@ -14,7 +14,8 @@ import space.kscience.kmath.expressions.interpret import space.kscience.kmath.operations.NumericAlgebra /** - * Represents [MST] based [DifferentiableExpression] relying on [Symja](https://github.com/axkr/symja_android_library). + * Represents [MST] based [space.kscience.kmath.expressions.DifferentiableExpression] relying on + * [Symja](https://github.com/axkr/symja_android_library). * * The principle of this API is converting the [mst] to an [org.matheclipse.core.interfaces.IExpr], differentiating it * with Symja's [F.D], then converting [org.matheclipse.core.interfaces.IExpr] back to [MST]. diff --git a/kmath-tensors/README.md b/kmath-tensors/README.md index 6b991d5df..b19a55381 100644 --- a/kmath-tensors/README.md +++ b/kmath-tensors/README.md @@ -3,7 +3,7 @@ Common linear algebra operations on tensors. - [tensor algebra](src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Basic linear algebra operations on tensors (plus, dot, etc.) - - [tensor algebra with broadcasting](src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting. + - [tensor algebra with broadcasting](src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting. - [linear algebra operations](src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Advanced linear algebra operations like LU decomposition, SVD, etc. diff --git a/kmath-tensors/build.gradle.kts b/kmath-tensors/build.gradle.kts index b7f24dc6a..2eff2d821 100644 --- a/kmath-tensors/build.gradle.kts +++ b/kmath-tensors/build.gradle.kts @@ -24,20 +24,16 @@ readme { feature( id = "tensor algebra", - description = "Basic linear algebra operations on tensors (plus, dot, etc.)", ref = "src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt" - ) + ) { "Basic linear algebra operations on tensors (plus, dot, etc.)" } feature( id = "tensor algebra with broadcasting", - description = "Basic linear algebra operations implemented with broadcasting.", - ref = "src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt" - ) + ref = "src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt" + ) { "Basic linear algebra operations implemented with broadcasting." } feature( id = "linear algebra operations", - description = "Advanced linear algebra operations like LU decomposition, SVD, etc.", ref = "src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt" - ) - -} \ No newline at end of file + ) { "Advanced linear algebra operations like LU decomposition, SVD, etc." } +} diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt index 315dc4505..87ac2fdf6 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt @@ -11,8 +11,8 @@ import space.kscience.kmath.tensors.core.internal.TensorLinearStructure */ public open class BufferedTensor internal constructor( override val shape: IntArray, - internal val mutableBuffer: MutableBuffer, - internal val bufferStart: Int + @PublishedApi internal val mutableBuffer: MutableBuffer, + @PublishedApi internal val bufferStart: Int, ) : Tensor { /** diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensor.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensor.kt index 41df50cba..8e5116336 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensor.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensor.kt @@ -11,7 +11,7 @@ import space.kscience.kmath.tensors.core.internal.toPrettyString /** * Default [BufferedTensor] implementation for [Double] values */ -public class DoubleTensor internal constructor( +public class DoubleTensor @PublishedApi internal constructor( shape: IntArray, buffer: DoubleArray, offset: Int = 0 diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt index 1fd46bd57..d182558c5 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt @@ -426,13 +426,11 @@ public open class DoubleTensorAlgebra : * @param transform the function to be applied to each element of the tensor. * @return the resulting tensor after applying the function. */ - public fun Tensor.map(transform: (Double) -> Double): DoubleTensor { - return DoubleTensor( - tensor.shape, - tensor.mutableBuffer.array().map { transform(it) }.toDoubleArray(), - tensor.bufferStart - ) - } + public inline fun Tensor.map(transform: (Double) -> Double): DoubleTensor = DoubleTensor( + tensor.shape, + tensor.mutableBuffer.array().map { transform(it) }.toDoubleArray(), + tensor.bufferStart + ) /** * Compares element-wise two tensors with a specified precision. @@ -519,14 +517,12 @@ public open class DoubleTensorAlgebra : * @param indices the [IntArray] of 1-dimensional indices * @return tensor with rows corresponding to rows by [indices] */ - public fun Tensor.rowsByIndices(indices: IntArray): DoubleTensor { - return stack(indices.map { this[it] }) - } + public fun Tensor.rowsByIndices(indices: IntArray): DoubleTensor = stack(indices.map { this[it] }) - internal fun Tensor.fold(foldFunction: (DoubleArray) -> Double): Double = + internal inline fun Tensor.fold(foldFunction: (DoubleArray) -> Double): Double = foldFunction(tensor.toDoubleArray()) - internal fun Tensor.foldDim( + internal inline fun Tensor.foldDim( foldFunction: (DoubleArray) -> Double, dim: Int, keepDim: Boolean, diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt index 7d3617547..4c9c00552 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt @@ -10,15 +10,15 @@ import space.kscience.kmath.nd.MutableStructure2D import space.kscience.kmath.nd.as1D import space.kscience.kmath.nd.as2D import space.kscience.kmath.operations.invoke -import space.kscience.kmath.tensors.core.* +import space.kscience.kmath.tensors.core.BufferedTensor +import space.kscience.kmath.tensors.core.DoubleTensor import space.kscience.kmath.tensors.core.DoubleTensorAlgebra -import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.valueOrNull +import space.kscience.kmath.tensors.core.IntTensor import kotlin.math.abs import kotlin.math.min import kotlin.math.sign import kotlin.math.sqrt - internal fun BufferedTensor.vectorSequence(): Sequence> = sequence { val n = shape.size val vectorOffset = shape[n - 1] diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/tensorCastsUtils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/tensorCastsUtils.kt index d965b6bcd..77264ff92 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/tensorCastsUtils.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/tensorCastsUtils.kt @@ -31,6 +31,7 @@ internal fun Tensor.toBufferedTensor(): BufferedTensor = when (this) { else -> this.copyToBufferedTensor() } +@PublishedApi internal val Tensor.tensor: DoubleTensor get() = when (this) { is DoubleTensor -> this diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt index 0ffaf39e7..e337eeef9 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt @@ -24,6 +24,7 @@ internal fun Buffer.array(): IntArray = when (this) { /** * Returns a reference to [DoubleArray] containing all of the elements of this [Buffer] or copy the data. */ +@PublishedApi internal fun Buffer.array(): DoubleArray = when (this) { is DoubleBuffer -> array else -> this.toDoubleArray() diff --git a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt index 347bb683f..c525d5c83 100644 --- a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt +++ b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt @@ -183,7 +183,7 @@ internal class TestDoubleLinearOpsTensorAlgebra { } -private fun DoubleTensorAlgebra.testSVDFor(tensor: DoubleTensor, epsilon: Double = 1e-10): Unit { +private fun DoubleTensorAlgebra.testSVDFor(tensor: DoubleTensor, epsilon: Double = 1e-10) { val svd = tensor.svd() val tensorSVD = svd.first diff --git a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt index e7e898008..85c3e74e3 100644 --- a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt +++ b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt @@ -17,7 +17,7 @@ internal class TestDoubleTensorAlgebra { } @Test - fun TestDoubleDiv() = DoubleTensorAlgebra { + fun testDoubleDiv() = DoubleTensorAlgebra { val tensor = fromArray(intArrayOf(2), doubleArrayOf(2.0, 4.0)) val res = 2.0/tensor assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 0.5)) diff --git a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt index b7abf4304..915637e2c 100644 --- a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt +++ b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt @@ -92,7 +92,7 @@ public class ViktorFieldND(public override val shape: IntArray) : FieldND, value: Double): ViktorStructureND = - (a.f64Buffer * value.toDouble()).asStructure() + (a.f64Buffer * value).asStructure() public override inline fun StructureND.plus(b: StructureND): ViktorStructureND = (f64Buffer + b.f64Buffer).asStructure() From ef41c3f1680ce67788c128ea3105c0c77e90c0c1 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sat, 17 Jul 2021 01:12:14 +0700 Subject: [PATCH 087/132] Build infrastructure changes --- .github/workflows/build.yml | 7 +++-- .github/workflows/pages.yml | 25 ++++++++++-------- .github/workflows/publish.yml | 21 +++++---------- build.gradle.kts | 42 ++++++++++++++++++++---------- buildSrc/build.gradle.kts | 2 +- gradle.properties | 1 - kmath-core/README.md | 2 +- kmath-core/build.gradle.kts | 43 ++++++++++++------------------- kmath-coroutines/build.gradle.kts | 1 + kmath-ejml/build.gradle.kts | 8 +++--- kmath-for-real/build.gradle.kts | 1 + kmath-functions/build.gradle.kts | 1 + kmath-geometry/build.gradle.kts | 1 + kmath-histograms/build.gradle.kts | 1 + kmath-stat/build.gradle.kts | 1 + kmath-tensors/build.gradle.kts | 9 +++---- settings.gradle.kts | 6 ++--- 17 files changed, 87 insertions(+), 85 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 98f4d2ec2..2b611a46a 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -2,8 +2,10 @@ name: Gradle build on: push: + branches: + - dev + - master pull_request: - types: [opened, edited] jobs: build: @@ -21,9 +23,6 @@ jobs: graalvm: 21.1.0 java: java11 arch: amd64 - - name: Add msys to path - if: matrix.os == 'windows-latest' - run: SETX PATH "%PATH%;C:\msys64\mingw64\bin" - name: Cache gradle uses: actions/cache@v2 with: diff --git a/.github/workflows/pages.yml b/.github/workflows/pages.yml index 86fdac6a6..1836287c8 100644 --- a/.github/workflows/pages.yml +++ b/.github/workflows/pages.yml @@ -2,23 +2,26 @@ name: Dokka publication on: push: - branches: - - master + branches: [ master ] jobs: build: runs-on: ubuntu-20.04 steps: - - name: Checkout the repo - uses: actions/checkout@v2 - - name: Set up JDK 11 - uses: actions/setup-java@v1 + - uses: actions/checkout@v2 + - uses: DeLaGuardo/setup-graalvm@4.0 with: - java-version: 11 - - name: Build - run: ./gradlew dokkaHtmlMultiModule --no-daemon --no-parallel --stacktrace - - name: Deploy to GitHub Pages - uses: JamesIves/github-pages-deploy-action@4.1.0 + graalvm: 21.1.0 + java: java11 + arch: amd64 + - uses: actions/cache@v2 + with: + path: ~/.gradle/caches + key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }} + restore-keys: | + ${{ runner.os }}-gradle- + - run: ./gradlew dokkaHtmlMultiModule --no-daemon --no-parallel --stacktrace + - uses: JamesIves/github-pages-deploy-action@4.1.0 with: branch: gh-pages folder: build/dokka/htmlMultiModule diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index c5c110e89..d1698d79b 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -3,8 +3,7 @@ name: Gradle publish on: workflow_dispatch: release: - types: - - created + types: [ created ] jobs: publish: @@ -23,13 +22,12 @@ jobs: graalvm: 21.1.0 java: java11 arch: amd64 - - name: Add msys to path - if: matrix.os == 'windows-latest' - run: SETX PATH "%PATH%;C:\msys64\mingw64\bin" - name: Cache gradle uses: actions/cache@v2 with: - path: ~/.gradle/caches + path: | + ~/.gradle/caches + ~/.gradle/wrapper key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }} restore-keys: | ${{ runner.os }}-gradle- @@ -43,19 +41,12 @@ jobs: - name: Publish Windows Artifacts if: matrix.os == 'windows-latest' run: > - ./gradlew release --no-daemon - -Ppublishing.enabled=true - -Ppublishing.github.user=${{ secrets.PUBLISHING_GITHUB_USER }} - -Ppublishing.github.token=${{ secrets.PUBLISHING_GITHUB_TOKEN }} + ./gradlew release --no-daemon -Ppublishing.enabled=true -Ppublishing.space.user=${{ secrets.PUBLISHING_SPACE_USER }} -Ppublishing.space.token=${{ secrets.PUBLISHING_SPACE_TOKEN }} - name: Publish Mac Artifacts if: matrix.os == 'macOS-latest' run: > - ./gradlew release --no-daemon - -Ppublishing.enabled=true - -Ppublishing.platform=macosX64 - -Ppublishing.github.user=${{ secrets.PUBLISHING_GITHUB_USER }} - -Ppublishing.github.token=${{ secrets.PUBLISHING_GITHUB_TOKEN }} + ./gradlew release --no-daemon -Ppublishing.enabled=true -Ppublishing.platform=macosX64 -Ppublishing.space.user=${{ secrets.PUBLISHING_SPACE_USER }} -Ppublishing.space.token=${{ secrets.PUBLISHING_SPACE_TOKEN }} diff --git a/build.gradle.kts b/build.gradle.kts index d0f6ced78..6bb19cd35 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -1,3 +1,5 @@ +import java.net.URL + plugins { id("ru.mipt.npm.gradle.project") kotlin("jupyter.api") apply false @@ -7,9 +9,11 @@ allprojects { repositories { maven("https://clojars.org/repo") maven("https://jitpack.io") + maven("http://logicrunch.research.it.uu.se/maven") { isAllowInsecureProtocol = true } + maven("https://oss.sonatype.org/content/repositories/snapshots") mavenCentral() } @@ -23,16 +27,30 @@ subprojects { afterEvaluate { tasks.withType { - dependsOn(tasks.getByName("assemble")) + dependsOn(tasks["assemble"]) dokkaSourceSets.all { - val readmeFile = File(this@subprojects.projectDir, "README.md") - if (readmeFile.exists()) includes.from(readmeFile.absolutePath) - externalDocumentationLink("https://ejml.org/javadoc/") + val readmeFile = this@subprojects.projectDir.resolve("README.md") + if (readmeFile.exists()) includes.from(readmeFile) + val kotlinDirPath = "src/$name/kotlin" + val kotlinDir = file(kotlinDirPath) + + if (kotlinDir.exists()) sourceLink { + localDirectory.set(kotlinDir) + + remoteUrl.set( + URL("https://github.com/mipt-npm/${rootProject.name}/tree/master/${this@subprojects.name}/$kotlinDirPath") + ) + } + externalDocumentationLink("https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/") externalDocumentationLink("https://deeplearning4j.org/api/latest/") externalDocumentationLink("https://axelclk.bitbucket.io/symja/javadoc/") - externalDocumentationLink("https://kotlin.github.io/kotlinx.coroutines/kotlinx-coroutines-core/") + + externalDocumentationLink( + "https://kotlin.github.io/kotlinx.coroutines/kotlinx-coroutines-core/", + "https://kotlin.github.io/kotlinx.coroutines/package-list", + ) externalDocumentationLink( "https://breandan.net/kotlingrad/kotlingrad/", @@ -43,16 +61,12 @@ subprojects { } } -readme { - readmeTemplate = file("docs/templates/README-TEMPLATE.md") -} +readme.readmeTemplate = file("docs/templates/README-TEMPLATE.md") ksciencePublish { - github("kmath") - space() - sonatype() + vcs("https://github.com/mipt-npm/kmath") + space(publish = true) + sonatype(publish = true) } -apiValidation { - nonPublicMarkers.add("space.kscience.kmath.misc.UnstableKMathAPI") -} +apiValidation.nonPublicMarkers.add("space.kscience.kmath.misc.UnstableKMathAPI") diff --git a/buildSrc/build.gradle.kts b/buildSrc/build.gradle.kts index fe69b05c6..3427a6d61 100644 --- a/buildSrc/build.gradle.kts +++ b/buildSrc/build.gradle.kts @@ -11,7 +11,7 @@ repositories { dependencies { api("org.jetbrains.kotlinx:kotlinx-serialization-json:1.1.0") - api("ru.mipt.npm:gradle-tools:0.10.0") + api("ru.mipt.npm:gradle-tools:0.10.1") api("org.jetbrains.kotlinx:kotlinx-benchmark-plugin:0.3.1") } diff --git a/gradle.properties b/gradle.properties index 3aaade368..b97db1c54 100644 --- a/gradle.properties +++ b/gradle.properties @@ -7,7 +7,6 @@ kotlin.code.style=official kotlin.mpp.enableGranularSourceSetsMetadata=true kotlin.mpp.stability.nowarn=true kotlin.native.enableDependencyPropagation=false -kotlin.parallel.tasks.in.project=true org.gradle.configureondemand=true org.gradle.jvmargs=-XX:MaxMetaspaceSize=2G org.gradle.parallel=true diff --git a/kmath-core/README.md b/kmath-core/README.md index a563552bb..4ea493f44 100644 --- a/kmath-core/README.md +++ b/kmath-core/README.md @@ -10,7 +10,7 @@ The core interfaces of KMath. objects to the expression by providing a context. Expressions can be used for a wide variety of purposes from high performance calculations to code generation. - [domains](src/commonMain/kotlin/space/kscience/kmath/domains) : Domains - - [autodif](src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation + - [autodiff](src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation ## Artifact: diff --git a/kmath-core/build.gradle.kts b/kmath-core/build.gradle.kts index 92a5f419d..564d06f49 100644 --- a/kmath-core/build.gradle.kts +++ b/kmath-core/build.gradle.kts @@ -19,51 +19,42 @@ readme { feature( id = "algebras", - description = """ - Algebraic structures like rings, spaces and fields. - """.trimIndent(), - ref = "src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt" - ) + ref = "src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt", + ) { "Algebraic structures like rings, spaces and fields." } feature( id = "nd", - description = "Many-dimensional structures and operations on them.", - ref = "src/commonMain/kotlin/space/kscience/kmath/structures/StructureND.kt" - ) + ref = "src/commonMain/kotlin/space/kscience/kmath/structures/StructureND.kt", + ) { "Many-dimensional structures and operations on them." } feature( id = "linear", - description = """ - Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. Advanced linear algebra operations like matrix inversion and LU decomposition. - """.trimIndent(), - ref = "src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt" - ) + ref = "src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt", + ) { "Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. Advanced linear algebra operations like matrix inversion and LU decomposition." } feature( id = "buffers", - description = "One-dimensional structure", - ref = "src/commonMain/kotlin/space/kscience/kmath/structures/Buffers.kt" - ) + ref = "src/commonMain/kotlin/space/kscience/kmath/structures/Buffers.kt", + ) { "One-dimensional structure" } feature( id = "expressions", - description = """ + ref = "src/commonMain/kotlin/space/kscience/kmath/expressions" + ) { + """ By writing a single mathematical expression once, users will be able to apply different types of objects to the expression by providing a context. Expressions can be used for a wide variety of purposes from high performance calculations to code generation. - """.trimIndent(), - ref = "src/commonMain/kotlin/space/kscience/kmath/expressions" - ) + """.trimIndent() + } feature( id = "domains", - description = "Domains", - ref = "src/commonMain/kotlin/space/kscience/kmath/domains" - ) + ref = "src/commonMain/kotlin/space/kscience/kmath/domains", + ) { "Domains" } feature( - id = "autodif", - description = "Automatic differentiation", + id = "autodiff", ref = "src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt" - ) + ) { "Automatic differentiation" } } diff --git a/kmath-coroutines/build.gradle.kts b/kmath-coroutines/build.gradle.kts index 1546e7d96..317691ae5 100644 --- a/kmath-coroutines/build.gradle.kts +++ b/kmath-coroutines/build.gradle.kts @@ -1,6 +1,7 @@ plugins { kotlin("multiplatform") id("ru.mipt.npm.gradle.common") + id("ru.mipt.npm.gradle.native") } kotlin.sourceSets { diff --git a/kmath-ejml/build.gradle.kts b/kmath-ejml/build.gradle.kts index 5107cfb68..727d21e3a 100644 --- a/kmath-ejml/build.gradle.kts +++ b/kmath-ejml/build.gradle.kts @@ -6,10 +6,10 @@ plugins { } dependencies { - api("org.ejml:ejml-ddense:0.40") - api("org.ejml:ejml-fdense:0.40") - api("org.ejml:ejml-dsparse:0.40") - api("org.ejml:ejml-fsparse:0.40") + api("org.ejml:ejml-ddense:0.41") + api("org.ejml:ejml-fdense:0.41") + api("org.ejml:ejml-dsparse:0.41") + api("org.ejml:ejml-fsparse:0.41") api(project(":kmath-core")) } diff --git a/kmath-for-real/build.gradle.kts b/kmath-for-real/build.gradle.kts index f6d12decd..25fdefaba 100644 --- a/kmath-for-real/build.gradle.kts +++ b/kmath-for-real/build.gradle.kts @@ -1,6 +1,7 @@ plugins { kotlin("multiplatform") id("ru.mipt.npm.gradle.common") + id("ru.mipt.npm.gradle.native") } kotlin.sourceSets.commonMain { diff --git a/kmath-functions/build.gradle.kts b/kmath-functions/build.gradle.kts index f77df3833..fadbac091 100644 --- a/kmath-functions/build.gradle.kts +++ b/kmath-functions/build.gradle.kts @@ -1,6 +1,7 @@ plugins { kotlin("multiplatform") id("ru.mipt.npm.gradle.common") + id("ru.mipt.npm.gradle.native") } description = "Functions, integration and interpolation" diff --git a/kmath-geometry/build.gradle.kts b/kmath-geometry/build.gradle.kts index 9b6e593b2..7eb814683 100644 --- a/kmath-geometry/build.gradle.kts +++ b/kmath-geometry/build.gradle.kts @@ -1,6 +1,7 @@ plugins { kotlin("multiplatform") id("ru.mipt.npm.gradle.common") + id("ru.mipt.npm.gradle.native") } kotlin.sourceSets.commonMain { diff --git a/kmath-histograms/build.gradle.kts b/kmath-histograms/build.gradle.kts index 2167726c0..7e511faa0 100644 --- a/kmath-histograms/build.gradle.kts +++ b/kmath-histograms/build.gradle.kts @@ -1,6 +1,7 @@ plugins { kotlin("multiplatform") id("ru.mipt.npm.gradle.common") + id("ru.mipt.npm.gradle.native") } kscience { diff --git a/kmath-stat/build.gradle.kts b/kmath-stat/build.gradle.kts index e8f629f7a..e3e396b6f 100644 --- a/kmath-stat/build.gradle.kts +++ b/kmath-stat/build.gradle.kts @@ -1,6 +1,7 @@ plugins { kotlin("multiplatform") id("ru.mipt.npm.gradle.common") + id("ru.mipt.npm.gradle.native") } kscience { diff --git a/kmath-tensors/build.gradle.kts b/kmath-tensors/build.gradle.kts index 2eff2d821..d084878ea 100644 --- a/kmath-tensors/build.gradle.kts +++ b/kmath-tensors/build.gradle.kts @@ -1,11 +1,14 @@ plugins { - id("ru.mipt.npm.gradle.mpp") + kotlin("multiplatform") + id("ru.mipt.npm.gradle.common") + id("ru.mipt.npm.gradle.native") } kotlin.sourceSets { all { languageSettings.useExperimentalAnnotation("space.kscience.kmath.misc.UnstableKMathAPI") } + commonMain { dependencies { api(project(":kmath-core")) @@ -14,10 +17,6 @@ kotlin.sourceSets { } } -tasks.dokkaHtml { - dependsOn(tasks.build) -} - readme { maturity = ru.mipt.npm.gradle.Maturity.PROTOTYPE propertyByTemplate("artifact", rootProject.file("docs/templates/ARTIFACT-TEMPLATE.md")) diff --git a/settings.gradle.kts b/settings.gradle.kts index 02b75cddc..445f75c09 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -5,8 +5,8 @@ pluginManagement { gradlePluginPortal() } - val toolsVersion = "0.10.0" - val kotlinVersion = "1.5.20" + val toolsVersion = "0.10.1" + val kotlinVersion = "1.5.21" plugins { id("ru.mipt.npm.gradle.project") version toolsVersion @@ -16,7 +16,7 @@ pluginManagement { kotlin("jvm") version kotlinVersion kotlin("plugin.allopen") version kotlinVersion id("org.jetbrains.kotlinx.benchmark") version "0.3.1" - kotlin("jupyter.api") version "0.10.0-25" + kotlin("jupyter.api") version "0.10.0-131-1" } } From b1998ed1a90152027ab809686229365a8de8bdd9 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Mon, 19 Jul 2021 03:12:41 +0700 Subject: [PATCH 088/132] Replace public override with override --- .../kmath/ejml/codegen/ejmlCodegen.kt | 44 ++-- .../ast/rendering/LatexSyntaxRenderer.kt | 2 +- .../ast/rendering/MathMLSyntaxRenderer.kt | 2 +- .../kmath/ast/rendering/MathRenderer.kt | 4 +- .../kmath/ast/rendering/MathSyntax.kt | 68 +++--- .../kscience/kmath/ast/rendering/features.kt | 32 +-- .../kscience/kmath/ast/rendering/phases.kt | 2 +- .../DerivativeStructureExpression.kt | 74 +++--- .../kscience/kmath/commons/linear/CMMatrix.kt | 22 +- .../commons/optimization/CMOptimization.kt | 6 +- .../random/CMRandomGeneratorWrapper.kt | 22 +- .../space/kscience/kmath/complex/Complex.kt | 42 ++-- .../kscience/kmath/complex/ComplexFieldND.kt | 36 +-- .../kscience/kmath/complex/Quaternion.kt | 50 ++-- .../kmath/domains/HyperSquareDomain.kt | 10 +- .../kmath/domains/UnconstrainedDomain.kt | 10 +- .../kmath/domains/UnivariateDomain.kt | 10 +- .../FunctionalExpressionAlgebra.kt | 64 ++--- .../kscience/kmath/expressions/MstAlgebra.kt | 138 +++++------ .../kmath/expressions/SimpleAutoDiff.kt | 60 ++--- .../kscience/kmath/linear/MatrixWrapper.kt | 4 +- .../space/kscience/kmath/nd/AlgebraND.kt | 8 +- .../space/kscience/kmath/nd/DoubleFieldND.kt | 48 ++-- .../space/kscience/kmath/nd/Structure1D.kt | 8 +- .../space/kscience/kmath/nd/Structure2D.kt | 2 +- .../kscience/kmath/operations/Algebra.kt | 10 +- .../space/kscience/kmath/operations/BigInt.kt | 6 +- .../kmath/operations/NumericAlgebra.kt | 2 +- .../kscience/kmath/operations/numbers.kt | 220 +++++++++--------- .../kmath/structures/DoubleBufferField.kt | 82 +++---- .../kscience/kmath/structures/MemoryBuffer.kt | 4 +- .../kscience/kmath/structures/ShortBuffer.kt | 10 +- .../kscience/kmath/operations/BigNumbers.kt | 36 +-- .../kscience/kmath/chains/BlockingChain.kt | 4 +- .../kmath/chains/BlockingDoubleChain.kt | 2 +- .../space/kscience/kmath/chains/Chain.kt | 16 +- .../kscience/kmath/streaming/RingBuffer.kt | 6 +- .../kmath/structures/LazyStructureND.kt | 6 +- .../space/kscience/kmath/ejml/EjmlMatrix.kt | 4 +- .../space/kscience/kmath/ejml/EjmlVector.kt | 6 +- .../space/kscience/kmath/ejml/_generated.kt | 160 ++++++------- .../kscience/kmath/functions/Piecewise.kt | 2 +- .../kscience/kmath/functions/Polynomial.kt | 6 +- .../kmath/interpolation/LinearInterpolator.kt | 4 +- .../kmath/interpolation/SplineInterpolator.kt | 4 +- .../kmath/geometry/Euclidean2DSpace.kt | 16 +- .../kmath/geometry/Euclidean3DSpace.kt | 16 +- .../kmath/histogram/IndexedHistogramSpace.kt | 2 +- .../kmath/histogram/UnivariateHistogram.kt | 6 +- .../kscience/kmath/jafama/KMathJafama.kt | 120 +++++----- .../kscience/kmath/kotlingrad/KMathNumber.kt | 6 +- .../kmath/kotlingrad/KotlingradExpression.kt | 4 +- .../kscience/kmath/nd4j/Nd4jArrayAlgebra.kt | 112 ++++----- .../kscience/kmath/nd4j/Nd4jArrayStructure.kt | 4 +- .../kscience/kmath/nd4j/Nd4jTensorAlgebra.kt | 120 +++++----- .../kmath/distributions/Distribution.kt | 2 +- .../kmath/distributions/NormalDistribution.kt | 6 +- .../AhrensDieterExponentialSampler.kt | 2 +- .../AhrensDieterMarsagliaTsangGammaSampler.kt | 4 +- .../samplers/AliasMethodDiscreteSampler.kt | 4 +- .../kmath/samplers/GaussianSampler.kt | 2 +- .../samplers/KempSmallMeanPoissonSampler.kt | 4 +- .../kscience/kmath/samplers/PoissonSampler.kt | 8 +- .../kotlin/space/kscience/kmath/stat/Mean.kt | 6 +- .../space/kscience/kmath/stat/Median.kt | 2 +- .../space/kscience/kmath/stat/RandomChain.kt | 2 +- .../kscience/kmath/stat/RandomGenerator.kt | 18 +- .../kscience/kmath/stat/SamplerAlgebra.kt | 12 +- .../space/kscience/kmath/stat/Statistic.kt | 2 +- .../kmath/stat/RandomSourceGenerator.kt | 34 +-- .../kscience/kmath/symja/SymjaExpression.kt | 4 +- .../kscience/kmath/viktor/ViktorBuffer.kt | 10 +- .../kmath/viktor/ViktorStructureND.kt | 58 ++--- 73 files changed, 972 insertions(+), 972 deletions(-) diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt index 5da7d0f67..a0d40c1ee 100644 --- a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt @@ -14,12 +14,12 @@ private fun Appendable.appendEjmlVector(type: String, ejmlMatrixType: String) { @Language("kotlin") val text = """/** * [EjmlVector] specialization for [$type]. */ -public class Ejml${type}Vector(public override val origin: M) : EjmlVector<$type, M>(origin) { +public class Ejml${type}Vector(override val origin: M) : EjmlVector<$type, M>(origin) { init { require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } } - public override operator fun get(index: Int): $type = origin[0, index] + override operator fun get(index: Int): $type = origin[0, index] }""" appendLine(text) appendLine() @@ -29,8 +29,8 @@ private fun Appendable.appendEjmlMatrix(type: String, ejmlMatrixType: String) { val text = """/** * [EjmlMatrix] specialization for [$type]. */ -public class Ejml${type}Matrix(public override val origin: M) : EjmlMatrix<$type, M>(origin) { - public override operator fun get(i: Int, j: Int): $type = origin[i, j] +public class Ejml${type}Matrix(override val origin: M) : EjmlMatrix<$type, M>(origin) { + override operator fun get(i: Int, j: Int): $type = origin[i, j] }""" appendLine(text) appendLine() @@ -54,23 +54,23 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, /** * The [${kmathAlgebra}] reference. */ - public override val elementAlgebra: $kmathAlgebra get() = $kmathAlgebra + override val elementAlgebra: $kmathAlgebra get() = $kmathAlgebra @Suppress("UNCHECKED_CAST") - public override fun Matrix<${type}>.toEjml(): Ejml${type}Matrix<${ejmlMatrixType}> = when { + override fun Matrix<${type}>.toEjml(): Ejml${type}Matrix<${ejmlMatrixType}> = when { this is Ejml${type}Matrix<*> && origin is $ejmlMatrixType -> this as Ejml${type}Matrix<${ejmlMatrixType}> else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } } @Suppress("UNCHECKED_CAST") - public override fun Point<${type}>.toEjml(): Ejml${type}Vector<${ejmlMatrixType}> = when { + override fun Point<${type}>.toEjml(): Ejml${type}Vector<${ejmlMatrixType}> = when { this is Ejml${type}Vector<*> && origin is $ejmlMatrixType -> this as Ejml${type}Vector<${ejmlMatrixType}> else -> Ejml${type}Vector(${ejmlMatrixType}(size, 1).also { (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } }) } - public override fun buildMatrix( + override fun buildMatrix( rows: Int, columns: Int, initializer: ${kmathAlgebra}.(i: Int, j: Int) -> ${type}, @@ -80,7 +80,7 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, } }.wrapMatrix() - public override fun buildVector( + override fun buildVector( size: Int, initializer: ${kmathAlgebra}.(Int) -> ${type}, ): Ejml${type}Vector<${ejmlMatrixType}> = Ejml${type}Vector(${ejmlMatrixType}(size, 1).also { @@ -90,21 +90,21 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, private fun T.wrapMatrix() = Ejml${type}Matrix(this) private fun T.wrapVector() = Ejml${type}Vector(this) - public override fun Matrix<${type}>.unaryMinus(): Matrix<${type}> = this * elementAlgebra { -one } + override fun Matrix<${type}>.unaryMinus(): Matrix<${type}> = this * elementAlgebra { -one } - public override fun Matrix<${type}>.dot(other: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { + override fun Matrix<${type}>.dot(other: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { val out = ${ejmlMatrixType}(1, 1) CommonOps_${ops}.mult(toEjml().origin, other.toEjml().origin, out) return out.wrapMatrix() } - public override fun Matrix<${type}>.dot(vector: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { + override fun Matrix<${type}>.dot(vector: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { val out = ${ejmlMatrixType}(1, 1) CommonOps_${ops}.mult(toEjml().origin, vector.toEjml().origin, out) return out.wrapVector() } - public override operator fun Matrix<${type}>.minus(other: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { + override operator fun Matrix<${type}>.minus(other: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { val out = ${ejmlMatrixType}(1, 1) CommonOps_${ops}.add( @@ -123,19 +123,19 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, return out.wrapMatrix() } - public override operator fun Matrix<${type}>.times(value: ${type}): Ejml${type}Matrix<${ejmlMatrixType}> { + override operator fun Matrix<${type}>.times(value: ${type}): Ejml${type}Matrix<${ejmlMatrixType}> { val res = ${ejmlMatrixType}(1, 1) CommonOps_${ops}.scale(value, toEjml().origin, res) return res.wrapMatrix() } - public override fun Point<${type}>.unaryMinus(): Ejml${type}Vector<${ejmlMatrixType}> { + override fun Point<${type}>.unaryMinus(): Ejml${type}Vector<${ejmlMatrixType}> { val res = ${ejmlMatrixType}(1, 1) CommonOps_${ops}.changeSign(toEjml().origin, res) return res.wrapVector() } - public override fun Matrix<${type}>.plus(other: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { + override fun Matrix<${type}>.plus(other: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> { val out = ${ejmlMatrixType}(1, 1) CommonOps_${ops}.add( @@ -154,7 +154,7 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, return out.wrapMatrix() } - public override fun Point<${type}>.plus(other: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { + override fun Point<${type}>.plus(other: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { val out = ${ejmlMatrixType}(1, 1) CommonOps_${ops}.add( @@ -173,7 +173,7 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, return out.wrapVector() } - public override fun Point<${type}>.minus(other: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { + override fun Point<${type}>.minus(other: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> { val out = ${ejmlMatrixType}(1, 1) CommonOps_${ops}.add( @@ -192,18 +192,18 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, return out.wrapVector() } - public override fun ${type}.times(m: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> = m * this + override fun ${type}.times(m: Matrix<${type}>): Ejml${type}Matrix<${ejmlMatrixType}> = m * this - public override fun Point<${type}>.times(value: ${type}): Ejml${type}Vector<${ejmlMatrixType}> { + override fun Point<${type}>.times(value: ${type}): Ejml${type}Vector<${ejmlMatrixType}> { val res = ${ejmlMatrixType}(1, 1) CommonOps_${ops}.scale(value, toEjml().origin, res) return res.wrapVector() } - public override fun ${type}.times(v: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> = v * this + override fun ${type}.times(v: Point<${type}>): Ejml${type}Vector<${ejmlMatrixType}> = v * this @UnstableKMathAPI - public override fun getFeature(structure: Matrix<${type}>, type: KClass): F? { + override fun getFeature(structure: Matrix<${type}>, type: KClass): F? { structure.getFeature(type)?.let { return it } val origin = structure.toEjml().origin diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/LatexSyntaxRenderer.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/LatexSyntaxRenderer.kt index 01717b0f9..2df3d3cc7 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/LatexSyntaxRenderer.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/LatexSyntaxRenderer.kt @@ -27,7 +27,7 @@ import space.kscience.kmath.misc.UnstableKMathAPI */ @UnstableKMathAPI public object LatexSyntaxRenderer : SyntaxRenderer { - public override fun render(node: MathSyntax, output: Appendable): Unit = output.run { + override fun render(node: MathSyntax, output: Appendable): Unit = output.run { fun render(syntax: MathSyntax) = render(syntax, output) when (node) { diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathMLSyntaxRenderer.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathMLSyntaxRenderer.kt index cda8e2322..8b5819b84 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathMLSyntaxRenderer.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathMLSyntaxRenderer.kt @@ -16,7 +16,7 @@ import space.kscience.kmath.misc.UnstableKMathAPI */ @UnstableKMathAPI public object MathMLSyntaxRenderer : SyntaxRenderer { - public override fun render(node: MathSyntax, output: Appendable) { + override fun render(node: MathSyntax, output: Appendable) { output.append("") renderPart(node, output) output.append("") diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt index 68d829724..fdef35ebd 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt @@ -29,7 +29,7 @@ public fun interface MathRenderer { */ @UnstableKMathAPI public open class FeaturedMathRenderer(public val features: List) : MathRenderer { - public override fun render(mst: MST): MathSyntax { + override fun render(mst: MST): MathSyntax { for (feature in features) feature.render(this, mst)?.let { return it } throw UnsupportedOperationException("Renderer $this has no appropriate feature to render node $mst.") } @@ -56,7 +56,7 @@ public open class FeaturedMathRendererWithPostProcess( features: List, public val stages: List, ) : FeaturedMathRenderer(features) { - public override fun render(mst: MST): MathSyntax { + override fun render(mst: MST): MathSyntax { val res = super.render(mst) for (stage in stages) stage.perform(res) return res diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathSyntax.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathSyntax.kt index a71985fbc..38450403d 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathSyntax.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathSyntax.kt @@ -150,9 +150,9 @@ public data class OperandSyntax( */ @UnstableKMathAPI public data class UnaryOperatorSyntax( - public override val operation: String, + override val operation: String, public var prefix: MathSyntax, - public override val operand: OperandSyntax, + override val operand: OperandSyntax, ) : UnarySyntax() { init { operand.parent = this @@ -166,8 +166,8 @@ public data class UnaryOperatorSyntax( */ @UnstableKMathAPI public data class UnaryPlusSyntax( - public override val operation: String, - public override val operand: OperandSyntax, + override val operation: String, + override val operand: OperandSyntax, ) : UnarySyntax() { init { operand.parent = this @@ -181,8 +181,8 @@ public data class UnaryPlusSyntax( */ @UnstableKMathAPI public data class UnaryMinusSyntax( - public override val operation: String, - public override val operand: OperandSyntax, + override val operation: String, + override val operand: OperandSyntax, ) : UnarySyntax() { init { operand.parent = this @@ -197,8 +197,8 @@ public data class UnaryMinusSyntax( */ @UnstableKMathAPI public data class RadicalSyntax( - public override val operation: String, - public override val operand: MathSyntax, + override val operation: String, + override val operand: MathSyntax, ) : UnarySyntax() { init { operand.parent = this @@ -215,8 +215,8 @@ public data class RadicalSyntax( */ @UnstableKMathAPI public data class ExponentSyntax( - public override val operation: String, - public override val operand: OperandSyntax, + override val operation: String, + override val operand: OperandSyntax, public var useOperatorForm: Boolean, ) : UnarySyntax() { init { @@ -233,9 +233,9 @@ public data class ExponentSyntax( */ @UnstableKMathAPI public data class SuperscriptSyntax( - public override val operation: String, - public override val left: MathSyntax, - public override val right: MathSyntax, + override val operation: String, + override val left: MathSyntax, + override val right: MathSyntax, ) : BinarySyntax() { init { left.parent = this @@ -252,9 +252,9 @@ public data class SuperscriptSyntax( */ @UnstableKMathAPI public data class SubscriptSyntax( - public override val operation: String, - public override val left: MathSyntax, - public override val right: MathSyntax, + override val operation: String, + override val left: MathSyntax, + override val right: MathSyntax, ) : BinarySyntax() { init { left.parent = this @@ -270,10 +270,10 @@ public data class SubscriptSyntax( */ @UnstableKMathAPI public data class BinaryOperatorSyntax( - public override val operation: String, + override val operation: String, public var prefix: MathSyntax, - public override val left: MathSyntax, - public override val right: MathSyntax, + override val left: MathSyntax, + override val right: MathSyntax, ) : BinarySyntax() { init { left.parent = this @@ -290,9 +290,9 @@ public data class BinaryOperatorSyntax( */ @UnstableKMathAPI public data class BinaryPlusSyntax( - public override val operation: String, - public override val left: OperandSyntax, - public override val right: OperandSyntax, + override val operation: String, + override val left: OperandSyntax, + override val right: OperandSyntax, ) : BinarySyntax() { init { left.parent = this @@ -309,9 +309,9 @@ public data class BinaryPlusSyntax( */ @UnstableKMathAPI public data class BinaryMinusSyntax( - public override val operation: String, - public override val left: OperandSyntax, - public override val right: OperandSyntax, + override val operation: String, + override val left: OperandSyntax, + override val right: OperandSyntax, ) : BinarySyntax() { init { left.parent = this @@ -329,9 +329,9 @@ public data class BinaryMinusSyntax( */ @UnstableKMathAPI public data class FractionSyntax( - public override val operation: String, - public override val left: OperandSyntax, - public override val right: OperandSyntax, + override val operation: String, + override val left: OperandSyntax, + override val right: OperandSyntax, public var infix: Boolean, ) : BinarySyntax() { init { @@ -349,9 +349,9 @@ public data class FractionSyntax( */ @UnstableKMathAPI public data class RadicalWithIndexSyntax( - public override val operation: String, - public override val left: MathSyntax, - public override val right: MathSyntax, + override val operation: String, + override val left: MathSyntax, + override val right: MathSyntax, ) : BinarySyntax() { init { left.parent = this @@ -369,9 +369,9 @@ public data class RadicalWithIndexSyntax( */ @UnstableKMathAPI public data class MultiplicationSyntax( - public override val operation: String, - public override val left: OperandSyntax, - public override val right: OperandSyntax, + override val operation: String, + override val left: OperandSyntax, + override val right: OperandSyntax, public var times: Boolean, ) : BinarySyntax() { init { diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt index 203cdf8b3..37e9a8c19 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt @@ -57,7 +57,7 @@ else */ @UnstableKMathAPI public class PrettyPrintFloats(public val types: Set>) : RenderFeature { - public override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? { + override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? { if (node !is MST.Numeric || node.value::class !in types) return null val toString = when (val v = node.value) { @@ -117,7 +117,7 @@ public class PrettyPrintFloats(public val types: Set>) : Rend */ @UnstableKMathAPI public class PrettyPrintIntegers(public val types: Set>) : RenderFeature { - public override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? = + override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? = if (node !is MST.Numeric || node.value::class !in types) null else @@ -140,7 +140,7 @@ public class PrettyPrintIntegers(public val types: Set>) : Re */ @UnstableKMathAPI public class PrettyPrintPi(public val symbols: Set) : RenderFeature { - public override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? = + override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? = if (node !is Symbol || node.identity !in symbols) null else @@ -202,7 +202,7 @@ public abstract class Binary(public val operations: Collection?) : Rende */ @UnstableKMathAPI public class BinaryPlus(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = + override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = BinaryPlusSyntax( operation = node.operation, left = OperandSyntax(parent.render(node.left), true), @@ -224,7 +224,7 @@ public class BinaryPlus(operations: Collection?) : Binary(operations) { */ @UnstableKMathAPI public class BinaryMinus(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = + override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = BinaryMinusSyntax( operation = node.operation, left = OperandSyntax(operand = parent.render(node.left), parentheses = true), @@ -246,7 +246,7 @@ public class BinaryMinus(operations: Collection?) : Binary(operations) { */ @UnstableKMathAPI public class UnaryPlus(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryPlusSyntax( + override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryPlusSyntax( operation = node.operation, operand = OperandSyntax(operand = parent.render(node.value), parentheses = true), ) @@ -266,7 +266,7 @@ public class UnaryPlus(operations: Collection?) : Unary(operations) { */ @UnstableKMathAPI public class UnaryMinus(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryMinusSyntax( + override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryMinusSyntax( operation = node.operation, operand = OperandSyntax(operand = parent.render(node.value), parentheses = true), ) @@ -286,7 +286,7 @@ public class UnaryMinus(operations: Collection?) : Unary(operations) { */ @UnstableKMathAPI public class Fraction(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = FractionSyntax( + override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = FractionSyntax( operation = node.operation, left = OperandSyntax(operand = parent.render(node.left), parentheses = true), right = OperandSyntax(operand = parent.render(node.right), parentheses = true), @@ -308,7 +308,7 @@ public class Fraction(operations: Collection?) : Binary(operations) { */ @UnstableKMathAPI public class BinaryOperator(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = + override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = BinaryOperatorSyntax( operation = node.operation, prefix = OperatorNameSyntax(name = node.operation), @@ -331,7 +331,7 @@ public class BinaryOperator(operations: Collection?) : Binary(operations */ @UnstableKMathAPI public class UnaryOperator(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = + override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryOperatorSyntax( operation = node.operation, prefix = OperatorNameSyntax(node.operation), @@ -353,7 +353,7 @@ public class UnaryOperator(operations: Collection?) : Unary(operations) */ @UnstableKMathAPI public class Power(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = + override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = SuperscriptSyntax( operation = node.operation, left = OperandSyntax(parent.render(node.left), true), @@ -373,7 +373,7 @@ public class Power(operations: Collection?) : Binary(operations) { */ @UnstableKMathAPI public class SquareRoot(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = + override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = RadicalSyntax(operation = node.operation, operand = parent.render(node.value)) public companion object { @@ -391,7 +391,7 @@ public class SquareRoot(operations: Collection?) : Unary(operations) { */ @UnstableKMathAPI public class Exponent(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = ExponentSyntax( + override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = ExponentSyntax( operation = node.operation, operand = OperandSyntax(operand = parent.render(node.value), parentheses = true), useOperatorForm = true, @@ -412,7 +412,7 @@ public class Exponent(operations: Collection?) : Unary(operations) { */ @UnstableKMathAPI public class Multiplication(operations: Collection?) : Binary(operations) { - public override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = + override fun renderBinary(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = MultiplicationSyntax( operation = node.operation, left = OperandSyntax(operand = parent.render(node.left), parentheses = true), @@ -435,7 +435,7 @@ public class Multiplication(operations: Collection?) : Binary(operations */ @UnstableKMathAPI public class InverseTrigonometricOperations(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = + override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryOperatorSyntax( operation = node.operation, prefix = OperatorNameSyntax(name = node.operation.replaceFirst("a", "arc")), @@ -462,7 +462,7 @@ public class InverseTrigonometricOperations(operations: Collection?) : U */ @UnstableKMathAPI public class InverseHyperbolicOperations(operations: Collection?) : Unary(operations) { - public override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = + override fun renderUnary(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryOperatorSyntax( operation = node.operation, prefix = OperatorNameSyntax(name = node.operation.replaceFirst("a", "ar")), diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/phases.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/phases.kt index 6da4994a6..574bb54f4 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/phases.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/phases.kt @@ -205,7 +205,7 @@ public val BetterExponent: PostProcessPhase = PostProcessPhase { node -> @UnstableKMathAPI public class SimplifyParentheses(public val precedenceFunction: (MathSyntax) -> Int) : PostProcessPhase { - public override fun perform(node: MathSyntax): Unit = when (node) { + override fun perform(node: MathSyntax): Unit = when (node) { is NumberSyntax -> Unit is SymbolSyntax -> Unit is OperatorNameSyntax -> Unit diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt index d0ab8b1e8..0925fee7e 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt @@ -25,10 +25,10 @@ public class DerivativeStructureField( NumbersAddOperations { public val numberOfVariables: Int = bindings.size - public override val zero: DerivativeStructure by lazy { DerivativeStructure(numberOfVariables, order) } - public override val one: DerivativeStructure by lazy { DerivativeStructure(numberOfVariables, order, 1.0) } + override val zero: DerivativeStructure by lazy { DerivativeStructure(numberOfVariables, order) } + override val one: DerivativeStructure by lazy { DerivativeStructure(numberOfVariables, order, 1.0) } - public override fun number(value: Number): DerivativeStructure = const(value.toDouble()) + override fun number(value: Number): DerivativeStructure = const(value.toDouble()) /** * A class that implements both [DerivativeStructure] and a [Symbol] @@ -39,10 +39,10 @@ public class DerivativeStructureField( symbol: Symbol, value: Double, ) : DerivativeStructure(size, order, index, value), Symbol { - public override val identity: String = symbol.identity - public override fun toString(): String = identity - public override fun equals(other: Any?): Boolean = this.identity == (other as? Symbol)?.identity - public override fun hashCode(): Int = identity.hashCode() + override val identity: String = symbol.identity + override fun toString(): String = identity + override fun equals(other: Any?): Boolean = this.identity == (other as? Symbol)?.identity + override fun hashCode(): Int = identity.hashCode() } /** @@ -52,10 +52,10 @@ public class DerivativeStructureField( key.identity to DerivativeStructureSymbol(numberOfVariables, index, key, value) }.toMap() - public override fun const(value: Double): DerivativeStructure = DerivativeStructure(numberOfVariables, order, value) + override fun const(value: Double): DerivativeStructure = DerivativeStructure(numberOfVariables, order, value) - public override fun bindSymbolOrNull(value: String): DerivativeStructureSymbol? = variables[value] - public override fun bindSymbol(value: String): DerivativeStructureSymbol = variables.getValue(value) + override fun bindSymbolOrNull(value: String): DerivativeStructureSymbol? = variables[value] + override fun bindSymbol(value: String): DerivativeStructureSymbol = variables.getValue(value) public fun bindSymbolOrNull(symbol: Symbol): DerivativeStructureSymbol? = variables[symbol.identity] public fun bindSymbol(symbol: Symbol): DerivativeStructureSymbol = variables.getValue(symbol.identity) @@ -68,45 +68,45 @@ public class DerivativeStructureField( public fun DerivativeStructure.derivative(vararg symbols: Symbol): Double = derivative(symbols.toList()) - public override fun DerivativeStructure.unaryMinus(): DerivativeStructure = negate() + override fun DerivativeStructure.unaryMinus(): DerivativeStructure = negate() - public override fun add(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.add(b) + override fun add(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.add(b) - public override fun scale(a: DerivativeStructure, value: Double): DerivativeStructure = a.multiply(value) + override fun scale(a: DerivativeStructure, value: Double): DerivativeStructure = a.multiply(value) - public override fun multiply(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.multiply(b) - public override fun divide(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.divide(b) - public override fun sin(arg: DerivativeStructure): DerivativeStructure = arg.sin() - public override fun cos(arg: DerivativeStructure): DerivativeStructure = arg.cos() - public override fun tan(arg: DerivativeStructure): DerivativeStructure = arg.tan() - public override fun asin(arg: DerivativeStructure): DerivativeStructure = arg.asin() - public override fun acos(arg: DerivativeStructure): DerivativeStructure = arg.acos() - public override fun atan(arg: DerivativeStructure): DerivativeStructure = arg.atan() - public override fun sinh(arg: DerivativeStructure): DerivativeStructure = arg.sinh() - public override fun cosh(arg: DerivativeStructure): DerivativeStructure = arg.cosh() - public override fun tanh(arg: DerivativeStructure): DerivativeStructure = arg.tanh() - public override fun asinh(arg: DerivativeStructure): DerivativeStructure = arg.asinh() - public override fun acosh(arg: DerivativeStructure): DerivativeStructure = arg.acosh() - public override fun atanh(arg: DerivativeStructure): DerivativeStructure = arg.atanh() + override fun multiply(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.multiply(b) + override fun divide(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.divide(b) + override fun sin(arg: DerivativeStructure): DerivativeStructure = arg.sin() + override fun cos(arg: DerivativeStructure): DerivativeStructure = arg.cos() + override fun tan(arg: DerivativeStructure): DerivativeStructure = arg.tan() + override fun asin(arg: DerivativeStructure): DerivativeStructure = arg.asin() + override fun acos(arg: DerivativeStructure): DerivativeStructure = arg.acos() + override fun atan(arg: DerivativeStructure): DerivativeStructure = arg.atan() + override fun sinh(arg: DerivativeStructure): DerivativeStructure = arg.sinh() + override fun cosh(arg: DerivativeStructure): DerivativeStructure = arg.cosh() + override fun tanh(arg: DerivativeStructure): DerivativeStructure = arg.tanh() + override fun asinh(arg: DerivativeStructure): DerivativeStructure = arg.asinh() + override fun acosh(arg: DerivativeStructure): DerivativeStructure = arg.acosh() + override fun atanh(arg: DerivativeStructure): DerivativeStructure = arg.atanh() - public override fun power(arg: DerivativeStructure, pow: Number): DerivativeStructure = when (pow) { + override fun power(arg: DerivativeStructure, pow: Number): DerivativeStructure = when (pow) { is Double -> arg.pow(pow) is Int -> arg.pow(pow) else -> arg.pow(pow.toDouble()) } public fun power(arg: DerivativeStructure, pow: DerivativeStructure): DerivativeStructure = arg.pow(pow) - public override fun exp(arg: DerivativeStructure): DerivativeStructure = arg.exp() - public override fun ln(arg: DerivativeStructure): DerivativeStructure = arg.log() + override fun exp(arg: DerivativeStructure): DerivativeStructure = arg.exp() + override fun ln(arg: DerivativeStructure): DerivativeStructure = arg.log() - public override operator fun DerivativeStructure.plus(b: Number): DerivativeStructure = add(b.toDouble()) - public override operator fun DerivativeStructure.minus(b: Number): DerivativeStructure = subtract(b.toDouble()) - public override operator fun Number.plus(b: DerivativeStructure): DerivativeStructure = b + this - public override operator fun Number.minus(b: DerivativeStructure): DerivativeStructure = b - this + override operator fun DerivativeStructure.plus(b: Number): DerivativeStructure = add(b.toDouble()) + override operator fun DerivativeStructure.minus(b: Number): DerivativeStructure = subtract(b.toDouble()) + override operator fun Number.plus(b: DerivativeStructure): DerivativeStructure = b + this + override operator fun Number.minus(b: DerivativeStructure): DerivativeStructure = b - this public companion object : AutoDiffProcessor> { - public override fun process(function: DerivativeStructureField.() -> DerivativeStructure): DifferentiableExpression = + override fun process(function: DerivativeStructureField.() -> DerivativeStructure): DifferentiableExpression = DerivativeStructureExpression(function) } } @@ -117,13 +117,13 @@ public class DerivativeStructureField( public class DerivativeStructureExpression( public val function: DerivativeStructureField.() -> DerivativeStructure, ) : DifferentiableExpression { - public override operator fun invoke(arguments: Map): Double = + override operator fun invoke(arguments: Map): Double = DerivativeStructureField(0, arguments).function().value /** * Get the derivative expression with given orders */ - public override fun derivativeOrNull(symbols: List): Expression = Expression { arguments -> + override fun derivativeOrNull(symbols: List): Expression = Expression { arguments -> with(DerivativeStructureField(symbols.size, arguments)) { function().derivative(symbols) } } } diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt index 11b097831..1997a633e 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt @@ -15,18 +15,18 @@ import kotlin.reflect.KClass import kotlin.reflect.cast public class CMMatrix(public val origin: RealMatrix) : Matrix { - public override val rowNum: Int get() = origin.rowDimension - public override val colNum: Int get() = origin.columnDimension + override val rowNum: Int get() = origin.rowDimension + override val colNum: Int get() = origin.columnDimension - public override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j) + override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j) } public class CMVector(public val origin: RealVector) : Point { - public override val size: Int get() = origin.dimension + override val size: Int get() = origin.dimension - public override operator fun get(index: Int): Double = origin.getEntry(index) + override operator fun get(index: Int): Double = origin.getEntry(index) - public override operator fun iterator(): Iterator = origin.toArray().iterator() + override operator fun iterator(): Iterator = origin.toArray().iterator() } public fun RealVector.toPoint(): CMVector = CMVector(this) @@ -34,7 +34,7 @@ public fun RealVector.toPoint(): CMVector = CMVector(this) public object CMLinearSpace : LinearSpace { override val elementAlgebra: DoubleField get() = DoubleField - public override fun buildMatrix( + override fun buildMatrix( rows: Int, columns: Int, initializer: DoubleField.(i: Int, j: Int) -> Double, @@ -73,16 +73,16 @@ public object CMLinearSpace : LinearSpace { override fun Point.minus(other: Point): CMVector = toCM().origin.subtract(other.toCM().origin).wrap() - public override fun Matrix.dot(other: Matrix): CMMatrix = + override fun Matrix.dot(other: Matrix): CMMatrix = toCM().origin.multiply(other.toCM().origin).wrap() - public override fun Matrix.dot(vector: Point): CMVector = + override fun Matrix.dot(vector: Point): CMVector = toCM().origin.preMultiply(vector.toCM().origin).wrap() - public override operator fun Matrix.minus(other: Matrix): CMMatrix = + override operator fun Matrix.minus(other: Matrix): CMMatrix = toCM().origin.subtract(other.toCM().origin).wrap() - public override operator fun Matrix.times(value: Double): CMMatrix = + override operator fun Matrix.times(value: Double): CMMatrix = toCM().origin.scalarMultiply(value).wrap() override fun Double.times(m: Matrix): CMMatrix = diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt index a46f06568..bca106e68 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt @@ -52,11 +52,11 @@ public class CMOptimization( public fun exportOptimizationData(): List = optimizationData.values.toList() - public override fun initialGuess(map: Map) { + override fun initialGuess(map: Map) { addOptimizationData(InitialGuess(map.toDoubleArray())) } - public override fun function(expression: Expression) { + override fun function(expression: Expression) { val objectiveFunction = ObjectiveFunction { val args = it.toMap() expression(args) @@ -64,7 +64,7 @@ public class CMOptimization( addOptimizationData(objectiveFunction) } - public override fun diffFunction(expression: DifferentiableExpression) { + override fun diffFunction(expression: DifferentiableExpression) { function(expression) val gradientFunction = ObjectiveFunctionGradient { val args = it.toMap() diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt index 4e2fbf980..afbfd9a24 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt @@ -16,31 +16,31 @@ public class CMRandomGeneratorWrapper( ) : org.apache.commons.math3.random.RandomGenerator { private var generator: RandomGenerator = factory(intArrayOf()) - public override fun nextBoolean(): Boolean = generator.nextBoolean() - public override fun nextFloat(): Float = generator.nextDouble().toFloat() + override fun nextBoolean(): Boolean = generator.nextBoolean() + override fun nextFloat(): Float = generator.nextDouble().toFloat() - public override fun setSeed(seed: Int) { + override fun setSeed(seed: Int) { generator = factory(intArrayOf(seed)) } - public override fun setSeed(seed: IntArray) { + override fun setSeed(seed: IntArray) { generator = factory(seed) } - public override fun setSeed(seed: Long) { + override fun setSeed(seed: Long) { setSeed(seed.toInt()) } - public override fun nextBytes(bytes: ByteArray) { + override fun nextBytes(bytes: ByteArray) { generator.fillBytes(bytes) } - public override fun nextInt(): Int = generator.nextInt() - public override fun nextInt(n: Int): Int = generator.nextInt(n) + override fun nextInt(): Int = generator.nextInt() + override fun nextInt(n: Int): Int = generator.nextInt(n) @PerformancePitfall - public override fun nextGaussian(): Double = runBlocking { GaussianSampler(0.0, 1.0).next(generator) } + override fun nextGaussian(): Double = runBlocking { GaussianSampler(0.0, 1.0).next(generator) } - public override fun nextDouble(): Double = generator.nextDouble() - public override fun nextLong(): Long = generator.nextLong() + override fun nextDouble(): Double = generator.nextDouble() + override fun nextLong(): Long = generator.nextLong() } diff --git a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt index a96d046c9..8b064a05f 100644 --- a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt +++ b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt @@ -54,8 +54,8 @@ private val PI_DIV_2 = Complex(PI / 2, 0) @OptIn(UnstableKMathAPI::class) public object ComplexField : ExtendedField, Norm, NumbersAddOperations, ScaleOperations { - public override val zero: Complex = 0.0.toComplex() - public override val one: Complex = 1.0.toComplex() + override val zero: Complex = 0.0.toComplex() + override val one: Complex = 1.0.toComplex() /** * The imaginary unit. @@ -68,13 +68,13 @@ public object ComplexField : ExtendedField, Norm, Num override fun scale(a: Complex, value: Double): Complex = Complex(a.re * value, a.im * value) - public override fun add(a: Complex, b: Complex): Complex = Complex(a.re + b.re, a.im + b.im) -// public override fun multiply(a: Complex, k: Number): Complex = Complex(a.re * k.toDouble(), a.im * k.toDouble()) + override fun add(a: Complex, b: Complex): Complex = Complex(a.re + b.re, a.im + b.im) +// override fun multiply(a: Complex, k: Number): Complex = Complex(a.re * k.toDouble(), a.im * k.toDouble()) - public override fun multiply(a: Complex, b: Complex): Complex = + override fun multiply(a: Complex, b: Complex): Complex = Complex(a.re * b.re - a.im * b.im, a.re * b.im + a.im * b.re) - public override fun divide(a: Complex, b: Complex): Complex = when { + override fun divide(a: Complex, b: Complex): Complex = when { abs(b.im) < abs(b.re) -> { val wr = b.im / b.re val wd = b.re + wr * b.im @@ -100,31 +100,31 @@ public object ComplexField : ExtendedField, Norm, Num override operator fun Complex.div(k: Number): Complex = Complex(re / k.toDouble(), im / k.toDouble()) - public override fun sin(arg: Complex): Complex = i * (exp(-i * arg) - exp(i * arg)) / 2.0 - public override fun cos(arg: Complex): Complex = (exp(-i * arg) + exp(i * arg)) / 2.0 + override fun sin(arg: Complex): Complex = i * (exp(-i * arg) - exp(i * arg)) / 2.0 + override fun cos(arg: Complex): Complex = (exp(-i * arg) + exp(i * arg)) / 2.0 - public override fun tan(arg: Complex): Complex { + override fun tan(arg: Complex): Complex { val e1 = exp(-i * arg) val e2 = exp(i * arg) return i * (e1 - e2) / (e1 + e2) } - public override fun asin(arg: Complex): Complex = -i * ln(sqrt(1 - (arg * arg)) + i * arg) - public override fun acos(arg: Complex): Complex = PI_DIV_2 + i * ln(sqrt(1 - (arg * arg)) + i * arg) + override fun asin(arg: Complex): Complex = -i * ln(sqrt(1 - (arg * arg)) + i * arg) + override fun acos(arg: Complex): Complex = PI_DIV_2 + i * ln(sqrt(1 - (arg * arg)) + i * arg) - public override fun atan(arg: Complex): Complex { + override fun atan(arg: Complex): Complex { val iArg = i * arg return i * (ln(1 - iArg) - ln(1 + iArg)) / 2 } - public override fun power(arg: Complex, pow: Number): Complex = if (arg.im == 0.0) + override fun power(arg: Complex, pow: Number): Complex = if (arg.im == 0.0) arg.re.pow(pow.toDouble()).toComplex() else exp(pow * ln(arg)) - public override fun exp(arg: Complex): Complex = exp(arg.re) * (cos(arg.im) + i * sin(arg.im)) + override fun exp(arg: Complex): Complex = exp(arg.re) * (cos(arg.im) + i * sin(arg.im)) - public override fun ln(arg: Complex): Complex = ln(arg.r) + i * atan2(arg.im, arg.re) + override fun ln(arg: Complex): Complex = ln(arg.r) + i * atan2(arg.im, arg.re) /** * Adds complex number to real one. @@ -171,9 +171,9 @@ public object ComplexField : ExtendedField, Norm, Num */ public operator fun Double.times(c: Complex): Complex = Complex(c.re * this, c.im * this) - public override fun norm(arg: Complex): Complex = sqrt(arg.conjugate * arg) + override fun norm(arg: Complex): Complex = sqrt(arg.conjugate * arg) - public override fun bindSymbolOrNull(value: String): Complex? = if (value == "i") i else null + override fun bindSymbolOrNull(value: String): Complex? = if (value == "i") i else null } /** @@ -187,16 +187,16 @@ public data class Complex(val re: Double, val im: Double) { public constructor(re: Number, im: Number) : this(re.toDouble(), im.toDouble()) public constructor(re: Number) : this(re.toDouble(), 0.0) - public override fun toString(): String = "($re + i * $im)" + override fun toString(): String = "($re + i * $im)" public companion object : MemorySpec { - public override val objectSize: Int + override val objectSize: Int get() = 16 - public override fun MemoryReader.read(offset: Int): Complex = + override fun MemoryReader.read(offset: Int): Complex = Complex(readDouble(offset), readDouble(offset + 8)) - public override fun MemoryWriter.write(offset: Int, value: Complex) { + override fun MemoryWriter.write(offset: Int, value: Complex) { writeDouble(offset, value.re) writeDouble(offset + 8, value.im) } diff --git a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt index 2c783eda0..1b54fc227 100644 --- a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt +++ b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt @@ -27,10 +27,10 @@ public class ComplexFieldND( NumbersAddOperations>, ExtendedField> { - public override val zero: BufferND by lazy { produce { zero } } - public override val one: BufferND by lazy { produce { one } } + override val zero: BufferND by lazy { produce { zero } } + override val one: BufferND by lazy { produce { one } } - public override fun number(value: Number): BufferND { + override fun number(value: Number): BufferND { val d = value.toComplex() // minimize conversions return produce { d } } @@ -81,25 +81,25 @@ public class ComplexFieldND( // return BufferedNDFieldElement(this, buffer) // } - public override fun power(arg: StructureND, pow: Number): BufferND = arg.map { power(it, pow) } + override fun power(arg: StructureND, pow: Number): BufferND = arg.map { power(it, pow) } - public override fun exp(arg: StructureND): BufferND = arg.map { exp(it) } + override fun exp(arg: StructureND): BufferND = arg.map { exp(it) } - public override fun ln(arg: StructureND): BufferND = arg.map { ln(it) } + override fun ln(arg: StructureND): BufferND = arg.map { ln(it) } - public override fun sin(arg: StructureND): BufferND = arg.map { sin(it) } - public override fun cos(arg: StructureND): BufferND = arg.map { cos(it) } - public override fun tan(arg: StructureND): BufferND = arg.map { tan(it) } - public override fun asin(arg: StructureND): BufferND = arg.map { asin(it) } - public override fun acos(arg: StructureND): BufferND = arg.map { acos(it) } - public override fun atan(arg: StructureND): BufferND = arg.map { atan(it) } + override fun sin(arg: StructureND): BufferND = arg.map { sin(it) } + override fun cos(arg: StructureND): BufferND = arg.map { cos(it) } + override fun tan(arg: StructureND): BufferND = arg.map { tan(it) } + override fun asin(arg: StructureND): BufferND = arg.map { asin(it) } + override fun acos(arg: StructureND): BufferND = arg.map { acos(it) } + override fun atan(arg: StructureND): BufferND = arg.map { atan(it) } - public override fun sinh(arg: StructureND): BufferND = arg.map { sinh(it) } - public override fun cosh(arg: StructureND): BufferND = arg.map { cosh(it) } - public override fun tanh(arg: StructureND): BufferND = arg.map { tanh(it) } - public override fun asinh(arg: StructureND): BufferND = arg.map { asinh(it) } - public override fun acosh(arg: StructureND): BufferND = arg.map { acosh(it) } - public override fun atanh(arg: StructureND): BufferND = arg.map { atanh(it) } + override fun sinh(arg: StructureND): BufferND = arg.map { sinh(it) } + override fun cosh(arg: StructureND): BufferND = arg.map { cosh(it) } + override fun tanh(arg: StructureND): BufferND = arg.map { tanh(it) } + override fun asinh(arg: StructureND): BufferND = arg.map { asinh(it) } + override fun acosh(arg: StructureND): BufferND = arg.map { acosh(it) } + override fun atanh(arg: StructureND): BufferND = arg.map { atanh(it) } } diff --git a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt index 28aae7bb4..423cef1d1 100644 --- a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt +++ b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt @@ -63,20 +63,20 @@ public object QuaternionField : Field, Norm, */ public val k: Quaternion = Quaternion(0, 0, 0, 1) - public override fun add(a: Quaternion, b: Quaternion): Quaternion = + override fun add(a: Quaternion, b: Quaternion): Quaternion = Quaternion(a.w + b.w, a.x + b.x, a.y + b.y, a.z + b.z) - public override fun scale(a: Quaternion, value: Double): Quaternion = + override fun scale(a: Quaternion, value: Double): Quaternion = Quaternion(a.w * value, a.x * value, a.y * value, a.z * value) - public override fun multiply(a: Quaternion, b: Quaternion): Quaternion = Quaternion( + override fun multiply(a: Quaternion, b: Quaternion): Quaternion = Quaternion( a.w * b.w - a.x * b.x - a.y * b.y - a.z * b.z, a.w * b.x + a.x * b.w + a.y * b.z - a.z * b.y, a.w * b.y - a.x * b.z + a.y * b.w + a.z * b.x, a.w * b.z + a.x * b.y - a.y * b.x + a.z * b.w, ) - public override fun divide(a: Quaternion, b: Quaternion): Quaternion { + override fun divide(a: Quaternion, b: Quaternion): Quaternion { val s = b.w * b.w + b.x * b.x + b.y * b.y + b.z * b.z return Quaternion( @@ -87,7 +87,7 @@ public object QuaternionField : Field, Norm, ) } - public override fun power(arg: Quaternion, pow: Number): Quaternion { + override fun power(arg: Quaternion, pow: Number): Quaternion { if (pow is Int) return pwr(arg, pow) if (floor(pow.toDouble()) == pow.toDouble()) return pwr(arg, pow.toInt()) return exp(pow * ln(arg)) @@ -131,7 +131,7 @@ public object QuaternionField : Field, Norm, return Quaternion(a2 * a2 - 6 * a2 * n1 + n1 * n1, x.x * n2, x.y * n2, x.z * n2) } - public override fun exp(arg: Quaternion): Quaternion { + override fun exp(arg: Quaternion): Quaternion { val un = arg.x * arg.x + arg.y * arg.y + arg.z * arg.z if (un == 0.0) return exp(arg.w).toQuaternion() val n1 = sqrt(un) @@ -140,7 +140,7 @@ public object QuaternionField : Field, Norm, return Quaternion(ea * cos(n1), n2 * arg.x, n2 * arg.y, n2 * arg.z) } - public override fun ln(arg: Quaternion): Quaternion { + override fun ln(arg: Quaternion): Quaternion { val nu2 = arg.x * arg.x + arg.y * arg.y + arg.z * arg.z if (nu2 == 0.0) @@ -158,21 +158,21 @@ public object QuaternionField : Field, Norm, return Quaternion(ln(n), th * arg.x, th * arg.y, th * arg.z) } - public override operator fun Number.plus(b: Quaternion): Quaternion = Quaternion(toDouble() + b.w, b.x, b.y, b.z) + override operator fun Number.plus(b: Quaternion): Quaternion = Quaternion(toDouble() + b.w, b.x, b.y, b.z) - public override operator fun Number.minus(b: Quaternion): Quaternion = + override operator fun Number.minus(b: Quaternion): Quaternion = Quaternion(toDouble() - b.w, -b.x, -b.y, -b.z) - public override operator fun Quaternion.plus(b: Number): Quaternion = Quaternion(w + b.toDouble(), x, y, z) - public override operator fun Quaternion.minus(b: Number): Quaternion = Quaternion(w - b.toDouble(), x, y, z) + override operator fun Quaternion.plus(b: Number): Quaternion = Quaternion(w + b.toDouble(), x, y, z) + override operator fun Quaternion.minus(b: Number): Quaternion = Quaternion(w - b.toDouble(), x, y, z) - public override operator fun Number.times(b: Quaternion): Quaternion = + override operator fun Number.times(b: Quaternion): Quaternion = Quaternion(toDouble() * b.w, toDouble() * b.x, toDouble() * b.y, toDouble() * b.z) - public override fun Quaternion.unaryMinus(): Quaternion = Quaternion(-w, -x, -y, -z) - public override fun norm(arg: Quaternion): Quaternion = sqrt(arg.conjugate * arg) + override fun Quaternion.unaryMinus(): Quaternion = Quaternion(-w, -x, -y, -z) + override fun norm(arg: Quaternion): Quaternion = sqrt(arg.conjugate * arg) - public override fun bindSymbolOrNull(value: String): Quaternion? = when (value) { + override fun bindSymbolOrNull(value: String): Quaternion? = when (value) { "i" -> i "j" -> j "k" -> k @@ -181,12 +181,12 @@ public object QuaternionField : Field, Norm, override fun number(value: Number): Quaternion = value.toQuaternion() - public override fun sinh(arg: Quaternion): Quaternion = (exp(arg) - exp(-arg)) / 2.0 - public override fun cosh(arg: Quaternion): Quaternion = (exp(arg) + exp(-arg)) / 2.0 - public override fun tanh(arg: Quaternion): Quaternion = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg)) - public override fun asinh(arg: Quaternion): Quaternion = ln(sqrt(arg * arg + one) + arg) - public override fun acosh(arg: Quaternion): Quaternion = ln(arg + sqrt((arg - one) * (arg + one))) - public override fun atanh(arg: Quaternion): Quaternion = (ln(arg + one) - ln(one - arg)) / 2.0 + override fun sinh(arg: Quaternion): Quaternion = (exp(arg) - exp(-arg)) / 2.0 + override fun cosh(arg: Quaternion): Quaternion = (exp(arg) + exp(-arg)) / 2.0 + override fun tanh(arg: Quaternion): Quaternion = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg)) + override fun asinh(arg: Quaternion): Quaternion = ln(sqrt(arg * arg + one) + arg) + override fun acosh(arg: Quaternion): Quaternion = ln(arg + sqrt((arg - one) * (arg + one))) + override fun atanh(arg: Quaternion): Quaternion = (ln(arg + one) - ln(one - arg)) / 2.0 } /** @@ -224,16 +224,16 @@ public data class Quaternion( /** * Returns a string representation of this quaternion. */ - public override fun toString(): String = "($w + $x * i + $y * j + $z * k)" + override fun toString(): String = "($w + $x * i + $y * j + $z * k)" public companion object : MemorySpec { - public override val objectSize: Int + override val objectSize: Int get() = 32 - public override fun MemoryReader.read(offset: Int): Quaternion = + override fun MemoryReader.read(offset: Int): Quaternion = Quaternion(readDouble(offset), readDouble(offset + 8), readDouble(offset + 16), readDouble(offset + 24)) - public override fun MemoryWriter.write(offset: Int, value: Quaternion) { + override fun MemoryWriter.write(offset: Int, value: Quaternion) { writeDouble(offset, value.w) writeDouble(offset + 8, value.x) writeDouble(offset + 16, value.y) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/HyperSquareDomain.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/HyperSquareDomain.kt index f5560d935..bd5514623 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/HyperSquareDomain.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/HyperSquareDomain.kt @@ -17,17 +17,17 @@ import space.kscience.kmath.structures.indices */ @UnstableKMathAPI public class HyperSquareDomain(private val lower: Buffer, private val upper: Buffer) : DoubleDomain { - public override val dimension: Int get() = lower.size + override val dimension: Int get() = lower.size - public override operator fun contains(point: Point): Boolean = point.indices.all { i -> + override operator fun contains(point: Point): Boolean = point.indices.all { i -> point[i] in lower[i]..upper[i] } - public override fun getLowerBound(num: Int): Double = lower[num] + override fun getLowerBound(num: Int): Double = lower[num] - public override fun getUpperBound(num: Int): Double = upper[num] + override fun getUpperBound(num: Int): Double = upper[num] - public override fun volume(): Double { + override fun volume(): Double { var res = 1.0 for (i in 0 until dimension) { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/UnconstrainedDomain.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/UnconstrainedDomain.kt index 7ffc0659d..32a5fc56c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/UnconstrainedDomain.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/UnconstrainedDomain.kt @@ -8,12 +8,12 @@ import space.kscience.kmath.linear.Point import space.kscience.kmath.misc.UnstableKMathAPI @UnstableKMathAPI -public class UnconstrainedDomain(public override val dimension: Int) : DoubleDomain { - public override operator fun contains(point: Point): Boolean = true +public class UnconstrainedDomain(override val dimension: Int) : DoubleDomain { + override operator fun contains(point: Point): Boolean = true - public override fun getLowerBound(num: Int): Double = Double.NEGATIVE_INFINITY + override fun getLowerBound(num: Int): Double = Double.NEGATIVE_INFINITY - public override fun getUpperBound(num: Int): Double = Double.POSITIVE_INFINITY + override fun getUpperBound(num: Int): Double = Double.POSITIVE_INFINITY - public override fun volume(): Double = Double.POSITIVE_INFINITY + override fun volume(): Double = Double.POSITIVE_INFINITY } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/UnivariateDomain.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/UnivariateDomain.kt index e7acada85..9020ef8cb 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/UnivariateDomain.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains/UnivariateDomain.kt @@ -10,24 +10,24 @@ import space.kscience.kmath.misc.UnstableKMathAPI @UnstableKMathAPI public class UnivariateDomain(public val range: ClosedFloatingPointRange) : DoubleDomain { - public override val dimension: Int get() = 1 + override val dimension: Int get() = 1 public operator fun contains(d: Double): Boolean = range.contains(d) - public override operator fun contains(point: Point): Boolean { + override operator fun contains(point: Point): Boolean { require(point.size == 0) return contains(point[0]) } - public override fun getLowerBound(num: Int): Double { + override fun getLowerBound(num: Int): Double { require(num == 0) return range.start } - public override fun getUpperBound(num: Int): Double { + override fun getUpperBound(num: Int): Double { require(num == 0) return range.endInclusive } - public override fun volume(): Double = range.endInclusive - range.start + override fun volume(): Double = range.endInclusive - range.start } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt index a10e29cf0..5935424b6 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt @@ -20,25 +20,25 @@ public abstract class FunctionalExpressionAlgebra>( /** * Builds an Expression of constant expression which does not depend on arguments. */ - public override fun const(value: T): Expression = Expression { value } + override fun const(value: T): Expression = Expression { value } /** * Builds an Expression to access a variable. */ - public override fun bindSymbolOrNull(value: String): Expression? = Expression { arguments -> + override fun bindSymbolOrNull(value: String): Expression? = Expression { arguments -> algebra.bindSymbolOrNull(value) ?: arguments[StringSymbol(value)] ?: error("Symbol '$value' is not supported in $this") } - public override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = + override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = { left, right -> Expression { arguments -> algebra.binaryOperationFunction(operation)(left.invoke(arguments), right.invoke(arguments)) } } - public override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = { arg -> + override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = { arg -> Expression { arguments -> algebra.unaryOperationFunction(operation)(arg.invoke(arguments)) } } } @@ -49,21 +49,21 @@ public abstract class FunctionalExpressionAlgebra>( public open class FunctionalExpressionGroup>( algebra: A, ) : FunctionalExpressionAlgebra(algebra), Group> { - public override val zero: Expression get() = const(algebra.zero) + override val zero: Expression get() = const(algebra.zero) - public override fun Expression.unaryMinus(): Expression = + override fun Expression.unaryMinus(): Expression = unaryOperation(GroupOperations.MINUS_OPERATION, this) /** * Builds an Expression of addition of two another expressions. */ - public override fun add(a: Expression, b: Expression): Expression = + override fun add(a: Expression, b: Expression): Expression = binaryOperation(GroupOperations.PLUS_OPERATION, a, b) // /** // * Builds an Expression of multiplication of expression by number. // */ -// public override fun multiply(a: Expression, k: Number): Expression = Expression { arguments -> +// override fun multiply(a: Expression, k: Number): Expression = Expression { arguments -> // algebra.multiply(a.invoke(arguments), k) // } @@ -72,10 +72,10 @@ public open class FunctionalExpressionGroup>( public operator fun T.plus(arg: Expression): Expression = arg + this public operator fun T.minus(arg: Expression): Expression = arg - this - public override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = + override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = super.unaryOperationFunction(operation) - public override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = + override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = super.binaryOperationFunction(operation) } @@ -83,21 +83,21 @@ public open class FunctionalExpressionGroup>( public open class FunctionalExpressionRing>( algebra: A, ) : FunctionalExpressionGroup(algebra), Ring> { - public override val one: Expression get() = const(algebra.one) + override val one: Expression get() = const(algebra.one) /** * Builds an Expression of multiplication of two expressions. */ - public override fun multiply(a: Expression, b: Expression): Expression = + override fun multiply(a: Expression, b: Expression): Expression = binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, b) public operator fun Expression.times(arg: T): Expression = this * const(arg) public operator fun T.times(arg: Expression): Expression = arg * this - public override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = + override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = super.unaryOperationFunction(operation) - public override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = + override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = super.binaryOperationFunction(operation) } @@ -107,65 +107,65 @@ public open class FunctionalExpressionField>( /** * Builds an Expression of division an expression by another one. */ - public override fun divide(a: Expression, b: Expression): Expression = + override fun divide(a: Expression, b: Expression): Expression = binaryOperationFunction(FieldOperations.DIV_OPERATION)(a, b) public operator fun Expression.div(arg: T): Expression = this / const(arg) public operator fun T.div(arg: Expression): Expression = arg / this - public override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = + override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = super.unaryOperationFunction(operation) - public override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = + override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = super.binaryOperationFunction(operation) - public override fun scale(a: Expression, value: Double): Expression = algebra { + override fun scale(a: Expression, value: Double): Expression = algebra { Expression { args -> a(args) * value } } - public override fun bindSymbolOrNull(value: String): Expression? = + override fun bindSymbolOrNull(value: String): Expression? = super.bindSymbolOrNull(value) } public open class FunctionalExpressionExtendedField>( algebra: A, ) : FunctionalExpressionField(algebra), ExtendedField> { - public override fun number(value: Number): Expression = const(algebra.number(value)) + override fun number(value: Number): Expression = const(algebra.number(value)) - public override fun sqrt(arg: Expression): Expression = + override fun sqrt(arg: Expression): Expression = unaryOperationFunction(PowerOperations.SQRT_OPERATION)(arg) - public override fun sin(arg: Expression): Expression = + override fun sin(arg: Expression): Expression = unaryOperationFunction(TrigonometricOperations.SIN_OPERATION)(arg) - public override fun cos(arg: Expression): Expression = + override fun cos(arg: Expression): Expression = unaryOperationFunction(TrigonometricOperations.COS_OPERATION)(arg) - public override fun asin(arg: Expression): Expression = + override fun asin(arg: Expression): Expression = unaryOperationFunction(TrigonometricOperations.ASIN_OPERATION)(arg) - public override fun acos(arg: Expression): Expression = + override fun acos(arg: Expression): Expression = unaryOperationFunction(TrigonometricOperations.ACOS_OPERATION)(arg) - public override fun atan(arg: Expression): Expression = + override fun atan(arg: Expression): Expression = unaryOperationFunction(TrigonometricOperations.ATAN_OPERATION)(arg) - public override fun power(arg: Expression, pow: Number): Expression = + override fun power(arg: Expression, pow: Number): Expression = binaryOperationFunction(PowerOperations.POW_OPERATION)(arg, number(pow)) - public override fun exp(arg: Expression): Expression = + override fun exp(arg: Expression): Expression = unaryOperationFunction(ExponentialOperations.EXP_OPERATION)(arg) - public override fun ln(arg: Expression): Expression = + override fun ln(arg: Expression): Expression = unaryOperationFunction(ExponentialOperations.LN_OPERATION)(arg) - public override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = + override fun unaryOperationFunction(operation: String): (arg: Expression) -> Expression = super.unaryOperationFunction(operation) - public override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = + override fun binaryOperationFunction(operation: String): (left: Expression, right: Expression) -> Expression = super.binaryOperationFunction(operation) - public override fun bindSymbol(value: String): Expression = super.bindSymbol(value) + override fun bindSymbol(value: String): Expression = super.bindSymbol(value) } public inline fun > A.expressionInGroup( diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt index 4729f19ea..d8489e30c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/MstAlgebra.kt @@ -12,14 +12,14 @@ import space.kscience.kmath.operations.* * [Algebra] over [MST] nodes. */ public object MstNumericAlgebra : NumericAlgebra { - public override fun number(value: Number): MST.Numeric = MST.Numeric(value) - public override fun bindSymbolOrNull(value: String): Symbol = StringSymbol(value) + override fun number(value: Number): MST.Numeric = MST.Numeric(value) + override fun bindSymbolOrNull(value: String): Symbol = StringSymbol(value) override fun bindSymbol(value: String): Symbol = bindSymbolOrNull(value) - public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = + override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = { arg -> MST.Unary(operation, arg) } - public override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = + override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = { left, right -> MST.Binary(operation, left, right) } } @@ -27,27 +27,27 @@ public object MstNumericAlgebra : NumericAlgebra { * [Group] over [MST] nodes. */ public object MstGroup : Group, NumericAlgebra, ScaleOperations { - public override val zero: MST.Numeric = number(0.0) + override val zero: MST.Numeric = number(0.0) - public override fun number(value: Number): MST.Numeric = MstNumericAlgebra.number(value) - public override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) - public override fun add(a: MST, b: MST): MST.Binary = binaryOperationFunction(GroupOperations.PLUS_OPERATION)(a, b) - public override operator fun MST.unaryPlus(): MST.Unary = + override fun number(value: Number): MST.Numeric = MstNumericAlgebra.number(value) + override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) + override fun add(a: MST, b: MST): MST.Binary = binaryOperationFunction(GroupOperations.PLUS_OPERATION)(a, b) + override operator fun MST.unaryPlus(): MST.Unary = unaryOperationFunction(GroupOperations.PLUS_OPERATION)(this) - public override operator fun MST.unaryMinus(): MST.Unary = + override operator fun MST.unaryMinus(): MST.Unary = unaryOperationFunction(GroupOperations.MINUS_OPERATION)(this) - public override operator fun MST.minus(b: MST): MST.Binary = + override operator fun MST.minus(b: MST): MST.Binary = binaryOperationFunction(GroupOperations.MINUS_OPERATION)(this, b) - public override fun scale(a: MST, value: Double): MST.Binary = + override fun scale(a: MST, value: Double): MST.Binary = binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, number(value)) - public override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = + override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = MstNumericAlgebra.binaryOperationFunction(operation) - public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = + override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = MstNumericAlgebra.unaryOperationFunction(operation) } @@ -57,27 +57,27 @@ public object MstGroup : Group, NumericAlgebra, ScaleOperations { @Suppress("OVERRIDE_BY_INLINE") @OptIn(UnstableKMathAPI::class) public object MstRing : Ring, NumbersAddOperations, ScaleOperations { - public override inline val zero: MST.Numeric get() = MstGroup.zero - public override val one: MST.Numeric = number(1.0) + override inline val zero: MST.Numeric get() = MstGroup.zero + override val one: MST.Numeric = number(1.0) - public override fun number(value: Number): MST.Numeric = MstGroup.number(value) - public override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) - public override fun add(a: MST, b: MST): MST.Binary = MstGroup.add(a, b) + override fun number(value: Number): MST.Numeric = MstGroup.number(value) + override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) + override fun add(a: MST, b: MST): MST.Binary = MstGroup.add(a, b) - public override fun scale(a: MST, value: Double): MST.Binary = + override fun scale(a: MST, value: Double): MST.Binary = MstGroup.binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, MstGroup.number(value)) - public override fun multiply(a: MST, b: MST): MST.Binary = + override fun multiply(a: MST, b: MST): MST.Binary = binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, b) - public override operator fun MST.unaryPlus(): MST.Unary = MstGroup { +this@unaryPlus } - public override operator fun MST.unaryMinus(): MST.Unary = MstGroup { -this@unaryMinus } - public override operator fun MST.minus(b: MST): MST.Binary = MstGroup { this@minus - b } + override operator fun MST.unaryPlus(): MST.Unary = MstGroup { +this@unaryPlus } + override operator fun MST.unaryMinus(): MST.Unary = MstGroup { -this@unaryMinus } + override operator fun MST.minus(b: MST): MST.Binary = MstGroup { this@minus - b } - public override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = + override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = MstGroup.binaryOperationFunction(operation) - public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = + override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = MstNumericAlgebra.unaryOperationFunction(operation) } @@ -87,28 +87,28 @@ public object MstRing : Ring, NumbersAddOperations, ScaleOperations, NumbersAddOperations, ScaleOperations { - public override inline val zero: MST.Numeric get() = MstRing.zero - public override inline val one: MST.Numeric get() = MstRing.one + override inline val zero: MST.Numeric get() = MstRing.zero + override inline val one: MST.Numeric get() = MstRing.one - public override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) - public override fun number(value: Number): MST.Numeric = MstRing.number(value) - public override fun add(a: MST, b: MST): MST.Binary = MstRing.add(a, b) + override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) + override fun number(value: Number): MST.Numeric = MstRing.number(value) + override fun add(a: MST, b: MST): MST.Binary = MstRing.add(a, b) - public override fun scale(a: MST, value: Double): MST.Binary = + override fun scale(a: MST, value: Double): MST.Binary = MstGroup.binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, MstGroup.number(value)) - public override fun multiply(a: MST, b: MST): MST.Binary = MstRing.multiply(a, b) - public override fun divide(a: MST, b: MST): MST.Binary = + override fun multiply(a: MST, b: MST): MST.Binary = MstRing.multiply(a, b) + override fun divide(a: MST, b: MST): MST.Binary = binaryOperationFunction(FieldOperations.DIV_OPERATION)(a, b) - public override operator fun MST.unaryPlus(): MST.Unary = MstRing { +this@unaryPlus } - public override operator fun MST.unaryMinus(): MST.Unary = MstRing { -this@unaryMinus } - public override operator fun MST.minus(b: MST): MST.Binary = MstRing { this@minus - b } + override operator fun MST.unaryPlus(): MST.Unary = MstRing { +this@unaryPlus } + override operator fun MST.unaryMinus(): MST.Unary = MstRing { -this@unaryMinus } + override operator fun MST.minus(b: MST): MST.Binary = MstRing { this@minus - b } - public override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = + override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = MstRing.binaryOperationFunction(operation) - public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = + override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = MstRing.unaryOperationFunction(operation) } @@ -117,45 +117,45 @@ public object MstField : Field, NumbersAddOperations, ScaleOperations< */ @Suppress("OVERRIDE_BY_INLINE") public object MstExtendedField : ExtendedField, NumericAlgebra { - public override inline val zero: MST.Numeric get() = MstField.zero - public override inline val one: MST.Numeric get() = MstField.one + override inline val zero: MST.Numeric get() = MstField.zero + override inline val one: MST.Numeric get() = MstField.one - public override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) - public override fun number(value: Number): MST.Numeric = MstRing.number(value) - public override fun sin(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.SIN_OPERATION)(arg) - public override fun cos(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.COS_OPERATION)(arg) - public override fun tan(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.TAN_OPERATION)(arg) - public override fun asin(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.ASIN_OPERATION)(arg) - public override fun acos(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.ACOS_OPERATION)(arg) - public override fun atan(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.ATAN_OPERATION)(arg) - public override fun sinh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.SINH_OPERATION)(arg) - public override fun cosh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.COSH_OPERATION)(arg) - public override fun tanh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.TANH_OPERATION)(arg) - public override fun asinh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.ASINH_OPERATION)(arg) - public override fun acosh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.ACOSH_OPERATION)(arg) - public override fun atanh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.ATANH_OPERATION)(arg) - public override fun add(a: MST, b: MST): MST.Binary = MstField.add(a, b) - public override fun sqrt(arg: MST): MST = unaryOperationFunction(PowerOperations.SQRT_OPERATION)(arg) + override fun bindSymbolOrNull(value: String): Symbol = MstNumericAlgebra.bindSymbolOrNull(value) + override fun number(value: Number): MST.Numeric = MstRing.number(value) + override fun sin(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.SIN_OPERATION)(arg) + override fun cos(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.COS_OPERATION)(arg) + override fun tan(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.TAN_OPERATION)(arg) + override fun asin(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.ASIN_OPERATION)(arg) + override fun acos(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.ACOS_OPERATION)(arg) + override fun atan(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.ATAN_OPERATION)(arg) + override fun sinh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.SINH_OPERATION)(arg) + override fun cosh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.COSH_OPERATION)(arg) + override fun tanh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.TANH_OPERATION)(arg) + override fun asinh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.ASINH_OPERATION)(arg) + override fun acosh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.ACOSH_OPERATION)(arg) + override fun atanh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.ATANH_OPERATION)(arg) + override fun add(a: MST, b: MST): MST.Binary = MstField.add(a, b) + override fun sqrt(arg: MST): MST = unaryOperationFunction(PowerOperations.SQRT_OPERATION)(arg) - public override fun scale(a: MST, value: Double): MST = + override fun scale(a: MST, value: Double): MST = binaryOperation(GroupOperations.PLUS_OPERATION, a, number(value)) - public override fun multiply(a: MST, b: MST): MST.Binary = MstField.multiply(a, b) - public override fun divide(a: MST, b: MST): MST.Binary = MstField.divide(a, b) - public override operator fun MST.unaryPlus(): MST.Unary = MstField { +this@unaryPlus } - public override operator fun MST.unaryMinus(): MST.Unary = MstField { -this@unaryMinus } - public override operator fun MST.minus(b: MST): MST.Binary = MstField { this@minus - b } + override fun multiply(a: MST, b: MST): MST.Binary = MstField.multiply(a, b) + override fun divide(a: MST, b: MST): MST.Binary = MstField.divide(a, b) + override operator fun MST.unaryPlus(): MST.Unary = MstField { +this@unaryPlus } + override operator fun MST.unaryMinus(): MST.Unary = MstField { -this@unaryMinus } + override operator fun MST.minus(b: MST): MST.Binary = MstField { this@minus - b } - public override fun power(arg: MST, pow: Number): MST.Binary = + override fun power(arg: MST, pow: Number): MST.Binary = binaryOperationFunction(PowerOperations.POW_OPERATION)(arg, number(pow)) - public override fun exp(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.EXP_OPERATION)(arg) - public override fun ln(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.LN_OPERATION)(arg) + override fun exp(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.EXP_OPERATION)(arg) + override fun ln(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.LN_OPERATION)(arg) - public override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = + override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary = MstField.binaryOperationFunction(operation) - public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = + override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary = MstField.unaryOperationFunction(operation) } @@ -164,7 +164,7 @@ public object MstExtendedField : ExtendedField, NumericAlgebra { */ @UnstableKMathAPI public object MstLogicAlgebra : LogicAlgebra { - public override fun bindSymbolOrNull(value: String): MST = super.bindSymbolOrNull(value) ?: StringSymbol(value) + override fun bindSymbolOrNull(value: String): MST = super.bindSymbolOrNull(value) ?: StringSymbol(value) override fun const(boolean: Boolean): Symbol = if (boolean) { LogicAlgebra.TRUE diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt index 960f6fd79..bf9469f41 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt @@ -60,8 +60,8 @@ public open class SimpleAutoDiffField>( public val context: F, bindings: Map, ) : Field>, ExpressionAlgebra>, NumbersAddOperations> { - public override val zero: AutoDiffValue get() = const(context.zero) - public override val one: AutoDiffValue get() = const(context.one) + override val zero: AutoDiffValue get() = const(context.zero) + override val one: AutoDiffValue get() = const(context.one) // this stack contains pairs of blocks and values to apply them to private var stack: Array = arrayOfNulls(8) @@ -149,17 +149,17 @@ public open class SimpleAutoDiffField>( // // Overloads for Double constants // -// public override operator fun Number.plus(b: AutoDiffValue): AutoDiffValue = +// override operator fun Number.plus(b: AutoDiffValue): AutoDiffValue = // derive(const { this@plus.toDouble() * one + b.value }) { z -> // b.d += z.d // } // -// public override operator fun AutoDiffValue.plus(b: Number): AutoDiffValue = b.plus(this) +// override operator fun AutoDiffValue.plus(b: Number): AutoDiffValue = b.plus(this) // -// public override operator fun Number.minus(b: AutoDiffValue): AutoDiffValue = +// override operator fun Number.minus(b: AutoDiffValue): AutoDiffValue = // derive(const { this@minus.toDouble() * one - b.value }) { z -> b.d -= z.d } // -// public override operator fun AutoDiffValue.minus(b: Number): AutoDiffValue = +// override operator fun AutoDiffValue.minus(b: Number): AutoDiffValue = // derive(const { this@minus.value - one * b.toDouble() }) { z -> d += z.d } @@ -168,25 +168,25 @@ public open class SimpleAutoDiffField>( // Basic math (+, -, *, /) - public override fun add(a: AutoDiffValue, b: AutoDiffValue): AutoDiffValue = + override fun add(a: AutoDiffValue, b: AutoDiffValue): AutoDiffValue = derive(const { a.value + b.value }) { z -> a.d += z.d b.d += z.d } - public override fun multiply(a: AutoDiffValue, b: AutoDiffValue): AutoDiffValue = + override fun multiply(a: AutoDiffValue, b: AutoDiffValue): AutoDiffValue = derive(const { a.value * b.value }) { z -> a.d += z.d * b.value b.d += z.d * a.value } - public override fun divide(a: AutoDiffValue, b: AutoDiffValue): AutoDiffValue = + override fun divide(a: AutoDiffValue, b: AutoDiffValue): AutoDiffValue = derive(const { a.value / b.value }) { z -> a.d += z.d / b.value b.d -= z.d * a.value / (b.value * b.value) } - public override fun scale(a: AutoDiffValue, value: Double): AutoDiffValue = + override fun scale(a: AutoDiffValue, value: Double): AutoDiffValue = derive(const { value * a.value }) { z -> a.d += z.d * value } @@ -236,12 +236,12 @@ public class SimpleAutoDiffExpression>( public val field: F, public val function: SimpleAutoDiffField.() -> AutoDiffValue, ) : FirstDerivativeExpression() { - public override operator fun invoke(arguments: Map): T { + override operator fun invoke(arguments: Map): T { //val bindings = arguments.entries.map { it.key.bind(it.value) } return SimpleAutoDiffField(field, arguments).function().value } - public override fun derivativeOrNull(symbol: Symbol): Expression = Expression { arguments -> + override fun derivativeOrNull(symbol: Symbol): Expression = Expression { arguments -> //val bindings = arguments.entries.map { it.key.bind(it.value) } val derivationResult = SimpleAutoDiffField(field, arguments).differentiate(function) derivationResult.derivative(symbol) @@ -346,28 +346,28 @@ public class SimpleAutoDiffExtendedField>( override fun bindSymbol(value: String): AutoDiffValue = super.bindSymbol(value) - public override fun number(value: Number): AutoDiffValue = const { number(value) } + override fun number(value: Number): AutoDiffValue = const { number(value) } - public override fun scale(a: AutoDiffValue, value: Double): AutoDiffValue = a * number(value) + override fun scale(a: AutoDiffValue, value: Double): AutoDiffValue = a * number(value) // x ^ 2 public fun sqr(x: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).sqr(x) // x ^ 1/2 - public override fun sqrt(arg: AutoDiffValue): AutoDiffValue = + override fun sqrt(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).sqrt(arg) // x ^ y (const) - public override fun power(arg: AutoDiffValue, pow: Number): AutoDiffValue = + override fun power(arg: AutoDiffValue, pow: Number): AutoDiffValue = (this as SimpleAutoDiffField).pow(arg, pow.toDouble()) // exp(x) - public override fun exp(arg: AutoDiffValue): AutoDiffValue = + override fun exp(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).exp(arg) // ln(x) - public override fun ln(arg: AutoDiffValue): AutoDiffValue = + override fun ln(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).ln(arg) // x ^ y (any) @@ -377,40 +377,40 @@ public class SimpleAutoDiffExtendedField>( ): AutoDiffValue = exp(y * ln(x)) // sin(x) - public override fun sin(arg: AutoDiffValue): AutoDiffValue = + override fun sin(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).sin(arg) // cos(x) - public override fun cos(arg: AutoDiffValue): AutoDiffValue = + override fun cos(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).cos(arg) - public override fun tan(arg: AutoDiffValue): AutoDiffValue = + override fun tan(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).tan(arg) - public override fun asin(arg: AutoDiffValue): AutoDiffValue = + override fun asin(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).asin(arg) - public override fun acos(arg: AutoDiffValue): AutoDiffValue = + override fun acos(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).acos(arg) - public override fun atan(arg: AutoDiffValue): AutoDiffValue = + override fun atan(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).atan(arg) - public override fun sinh(arg: AutoDiffValue): AutoDiffValue = + override fun sinh(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).sinh(arg) - public override fun cosh(arg: AutoDiffValue): AutoDiffValue = + override fun cosh(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).cosh(arg) - public override fun tanh(arg: AutoDiffValue): AutoDiffValue = + override fun tanh(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).tanh(arg) - public override fun asinh(arg: AutoDiffValue): AutoDiffValue = + override fun asinh(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).asinh(arg) - public override fun acosh(arg: AutoDiffValue): AutoDiffValue = + override fun acosh(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).acosh(arg) - public override fun atanh(arg: AutoDiffValue): AutoDiffValue = + override fun atanh(arg: AutoDiffValue): AutoDiffValue = (this as SimpleAutoDiffField).atanh(arg) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt index 16aadab3b..4b624b6a0 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt @@ -26,11 +26,11 @@ public class MatrixWrapper internal constructor( */ @UnstableKMathAPI @Suppress("UNCHECKED_CAST") - public override fun getFeature(type: KClass): F? = + override fun getFeature(type: KClass): F? = features.singleOrNull(type::isInstance) as? F ?: origin.getFeature(type) - public override fun toString(): String = "MatrixWrapper(matrix=$origin, features=$features)" + override fun toString(): String = "MatrixWrapper(matrix=$origin, features=$features)" } /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt index 38985f216..7b0b06a58 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt @@ -127,7 +127,7 @@ public interface GroupND> : Group>, AlgebraND * @param b the addend. * @return the sum. */ - public override fun add(a: StructureND, b: StructureND): StructureND = + override fun add(a: StructureND, b: StructureND): StructureND = combine(a, b) { aValue, bValue -> add(aValue, bValue) } // /** @@ -137,7 +137,7 @@ public interface GroupND> : Group>, AlgebraND // * @param k the multiplier. // * @return the product. // */ -// public override fun multiply(a: NDStructure, k: Number): NDStructure = a.map { multiply(it, k) } +// override fun multiply(a: NDStructure, k: Number): NDStructure = a.map { multiply(it, k) } // TODO move to extensions after KEEP-176 @@ -194,7 +194,7 @@ public interface RingND> : Ring>, GroupND, b: StructureND): StructureND = + override fun multiply(a: StructureND, b: StructureND): StructureND = combine(a, b) { aValue, bValue -> multiply(aValue, bValue) } //TODO move to extensions after KEEP-176 @@ -234,7 +234,7 @@ public interface FieldND> : Field>, RingND, b: StructureND): StructureND = + override fun divide(a: StructureND, b: StructureND): StructureND = combine(a, b) { aValue, bValue -> divide(aValue, bValue) } //TODO move to extensions after KEEP-176 diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt index 71532594e..925301272 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt @@ -22,15 +22,15 @@ public class DoubleFieldND( ScaleOperations>, ExtendedField> { - public override val zero: BufferND by lazy { produce { zero } } - public override val one: BufferND by lazy { produce { one } } + override val zero: BufferND by lazy { produce { zero } } + override val one: BufferND by lazy { produce { one } } - public override fun number(value: Number): BufferND { + override fun number(value: Number): BufferND { val d = value.toDouble() // minimize conversions return produce { d } } - public override val StructureND.buffer: DoubleBuffer + override val StructureND.buffer: DoubleBuffer get() = when { !shape.contentEquals(this@DoubleFieldND.shape) -> throw ShapeMismatchException( this@DoubleFieldND.shape, @@ -41,7 +41,7 @@ public class DoubleFieldND( } @Suppress("OVERRIDE_BY_INLINE") - public override inline fun StructureND.map( + override inline fun StructureND.map( transform: DoubleField.(Double) -> Double, ): BufferND { val buffer = DoubleBuffer(strides.linearSize) { offset -> DoubleField.transform(buffer.array[offset]) } @@ -49,7 +49,7 @@ public class DoubleFieldND( } @Suppress("OVERRIDE_BY_INLINE") - public override inline fun produce(initializer: DoubleField.(IntArray) -> Double): BufferND { + override inline fun produce(initializer: DoubleField.(IntArray) -> Double): BufferND { val array = DoubleArray(strides.linearSize) { offset -> val index = strides.index(offset) DoubleField.initializer(index) @@ -58,7 +58,7 @@ public class DoubleFieldND( } @Suppress("OVERRIDE_BY_INLINE") - public override inline fun StructureND.mapIndexed( + override inline fun StructureND.mapIndexed( transform: DoubleField.(index: IntArray, Double) -> Double, ): BufferND = BufferND( strides, @@ -70,7 +70,7 @@ public class DoubleFieldND( }) @Suppress("OVERRIDE_BY_INLINE") - public override inline fun combine( + override inline fun combine( a: StructureND, b: StructureND, transform: DoubleField.(Double, Double) -> Double, @@ -81,26 +81,26 @@ public class DoubleFieldND( return BufferND(strides, buffer) } - public override fun scale(a: StructureND, value: Double): StructureND = a.map { it * value } + override fun scale(a: StructureND, value: Double): StructureND = a.map { it * value } - public override fun power(arg: StructureND, pow: Number): BufferND = arg.map { power(it, pow) } + override fun power(arg: StructureND, pow: Number): BufferND = arg.map { power(it, pow) } - public override fun exp(arg: StructureND): BufferND = arg.map { exp(it) } - public override fun ln(arg: StructureND): BufferND = arg.map { ln(it) } + override fun exp(arg: StructureND): BufferND = arg.map { exp(it) } + override fun ln(arg: StructureND): BufferND = arg.map { ln(it) } - public override fun sin(arg: StructureND): BufferND = arg.map { sin(it) } - public override fun cos(arg: StructureND): BufferND = arg.map { cos(it) } - public override fun tan(arg: StructureND): BufferND = arg.map { tan(it) } - public override fun asin(arg: StructureND): BufferND = arg.map { asin(it) } - public override fun acos(arg: StructureND): BufferND = arg.map { acos(it) } - public override fun atan(arg: StructureND): BufferND = arg.map { atan(it) } + override fun sin(arg: StructureND): BufferND = arg.map { sin(it) } + override fun cos(arg: StructureND): BufferND = arg.map { cos(it) } + override fun tan(arg: StructureND): BufferND = arg.map { tan(it) } + override fun asin(arg: StructureND): BufferND = arg.map { asin(it) } + override fun acos(arg: StructureND): BufferND = arg.map { acos(it) } + override fun atan(arg: StructureND): BufferND = arg.map { atan(it) } - public override fun sinh(arg: StructureND): BufferND = arg.map { sinh(it) } - public override fun cosh(arg: StructureND): BufferND = arg.map { cosh(it) } - public override fun tanh(arg: StructureND): BufferND = arg.map { tanh(it) } - public override fun asinh(arg: StructureND): BufferND = arg.map { asinh(it) } - public override fun acosh(arg: StructureND): BufferND = arg.map { acosh(it) } - public override fun atanh(arg: StructureND): BufferND = arg.map { atanh(it) } + override fun sinh(arg: StructureND): BufferND = arg.map { sinh(it) } + override fun cosh(arg: StructureND): BufferND = arg.map { cosh(it) } + override fun tanh(arg: StructureND): BufferND = arg.map { tanh(it) } + override fun asinh(arg: StructureND): BufferND = arg.map { asinh(it) } + override fun acosh(arg: StructureND): BufferND = arg.map { acosh(it) } + override fun atanh(arg: StructureND): BufferND = arg.map { atanh(it) } } public fun AlgebraND.Companion.real(vararg shape: Int): DoubleFieldND = DoubleFieldND(shape) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt index 150ebf6fb..d916bc0d6 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt @@ -16,14 +16,14 @@ import kotlin.jvm.JvmInline * A structure that is guaranteed to be one-dimensional */ public interface Structure1D : StructureND, Buffer { - public override val dimension: Int get() = 1 + override val dimension: Int get() = 1 - public override operator fun get(index: IntArray): T { + override operator fun get(index: IntArray): T { require(index.size == 1) { "Index dimension mismatch. Expected 1 but found ${index.size}" } return get(index[0]) } - public override operator fun iterator(): Iterator = (0 until size).asSequence().map(::get).iterator() + override operator fun iterator(): Iterator = (0 until size).asSequence().map(::get).iterator() public companion object } @@ -32,7 +32,7 @@ public interface Structure1D : StructureND, Buffer { * A mutable structure that is guaranteed to be one-dimensional */ public interface MutableStructure1D : Structure1D, MutableStructureND, MutableBuffer { - public override operator fun set(index: IntArray, value: T) { + override operator fun set(index: IntArray, value: T) { require(index.size == 1) { "Index dimension mismatch. Expected 1 but found ${index.size}" } set(index[0], value) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt index f353b6974..cb69bdc00 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt @@ -29,7 +29,7 @@ public interface Structure2D : StructureND { */ public val colNum: Int - public override val shape: IntArray get() = intArrayOf(rowNum, colNum) + override val shape: IntArray get() = intArrayOf(rowNum, colNum) /** * The buffer of rows of this structure. It gets elements from the structure dynamically. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index 3a1ec430e..cef34dce2 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -166,13 +166,13 @@ public interface GroupOperations : Algebra { */ public operator fun T.minus(b: T): T = add(this, -b) - public override fun unaryOperationFunction(operation: String): (arg: T) -> T = when (operation) { + override fun unaryOperationFunction(operation: String): (arg: T) -> T = when (operation) { PLUS_OPERATION -> { arg -> +arg } MINUS_OPERATION -> { arg -> -arg } else -> super.unaryOperationFunction(operation) } - public override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = when (operation) { + override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = when (operation) { PLUS_OPERATION -> ::add MINUS_OPERATION -> { left, right -> left - right } else -> super.binaryOperationFunction(operation) @@ -226,7 +226,7 @@ public interface RingOperations : GroupOperations { */ public operator fun T.times(b: T): T = multiply(this, b) - public override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = when (operation) { + override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = when (operation) { TIMES_OPERATION -> ::multiply else -> super.binaryOperationFunction(operation) } @@ -277,7 +277,7 @@ public interface FieldOperations : RingOperations { */ public operator fun T.div(b: T): T = divide(this, b) - public override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = when (operation) { + override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = when (operation) { DIV_OPERATION -> ::divide else -> super.binaryOperationFunction(operation) } @@ -298,5 +298,5 @@ public interface FieldOperations : RingOperations { * @param T the type of element of this field. */ public interface Field : Ring, FieldOperations, ScaleOperations, NumericAlgebra { - public override fun number(value: Number): T = scale(one, value.toDouble()) + override fun number(value: Number): T = scale(one, value.toDouble()) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index c332b086e..4ccbfc531 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -49,16 +49,16 @@ public class BigInt internal constructor( private val sign: Byte, private val magnitude: Magnitude, ) : Comparable { - public override fun compareTo(other: BigInt): Int = when { + override fun compareTo(other: BigInt): Int = when { (sign == 0.toByte()) and (other.sign == 0.toByte()) -> 0 sign < other.sign -> -1 sign > other.sign -> 1 else -> sign * compareMagnitudes(magnitude, other.magnitude) } - public override fun equals(other: Any?): Boolean = other is BigInt && compareTo(other) == 0 + override fun equals(other: Any?): Boolean = other is BigInt && compareTo(other) == 0 - public override fun hashCode(): Int = magnitude.hashCode() + sign + override fun hashCode(): Int = magnitude.hashCode() + sign public fun abs(): BigInt = if (sign == 0.toByte()) this else BigInt(1, magnitude) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/NumericAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/NumericAlgebra.kt index deeb07e0e..7a8fa5668 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/NumericAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/NumericAlgebra.kt @@ -87,7 +87,7 @@ public interface NumericAlgebra : Algebra { public fun rightSideNumberOperation(operation: String, left: T, right: Number): T = rightSideNumberOperationFunction(operation)(left, right) - public override fun bindSymbolOrNull(value: String): T? = when (value) { + override fun bindSymbolOrNull(value: String): T? = when (value) { "pi" -> number(PI) "e" -> number(E) else -> super.bindSymbolOrNull(value) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt index 36c13d6ec..19cb5f25c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt @@ -15,10 +15,10 @@ public interface ExtendedFieldOperations : TrigonometricOperations, PowerOperations, ExponentialOperations { - public override fun tan(arg: T): T = sin(arg) / cos(arg) - public override fun tanh(arg: T): T = sinh(arg) / cosh(arg) + override fun tan(arg: T): T = sin(arg) / cos(arg) + override fun tanh(arg: T): T = sinh(arg) / cosh(arg) - public override fun unaryOperationFunction(operation: String): (arg: T) -> T = when (operation) { + override fun unaryOperationFunction(operation: String): (arg: T) -> T = when (operation) { TrigonometricOperations.COS_OPERATION -> ::cos TrigonometricOperations.SIN_OPERATION -> ::sin TrigonometricOperations.TAN_OPERATION -> ::tan @@ -42,14 +42,14 @@ public interface ExtendedFieldOperations : * Advanced Number-like field that implements basic operations. */ public interface ExtendedField : ExtendedFieldOperations, Field, NumericAlgebra, ScaleOperations { - public override fun sinh(arg: T): T = (exp(arg) - exp(-arg)) / 2.0 - public override fun cosh(arg: T): T = (exp(arg) + exp(-arg)) / 2.0 - public override fun tanh(arg: T): T = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg)) - public override fun asinh(arg: T): T = ln(sqrt(arg * arg + one) + arg) - public override fun acosh(arg: T): T = ln(arg + sqrt((arg - one) * (arg + one))) - public override fun atanh(arg: T): T = (ln(arg + one) - ln(one - arg)) / 2.0 + override fun sinh(arg: T): T = (exp(arg) - exp(-arg)) / 2.0 + override fun cosh(arg: T): T = (exp(arg) + exp(-arg)) / 2.0 + override fun tanh(arg: T): T = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg)) + override fun asinh(arg: T): T = ln(sqrt(arg * arg + one) + arg) + override fun acosh(arg: T): T = ln(arg + sqrt((arg - one) * (arg + one))) + override fun atanh(arg: T): T = (ln(arg + one) - ln(one - arg)) / 2.0 - public override fun rightSideNumberOperationFunction(operation: String): (left: T, right: Number) -> T = + override fun rightSideNumberOperationFunction(operation: String): (left: T, right: Number) -> T = when (operation) { PowerOperations.POW_OPERATION -> ::power else -> super.rightSideNumberOperationFunction(operation) @@ -61,50 +61,50 @@ public interface ExtendedField : ExtendedFieldOperations, Field, Numeri */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object DoubleField : ExtendedField, Norm, ScaleOperations { - public override inline val zero: Double get() = 0.0 - public override inline val one: Double get() = 1.0 + override inline val zero: Double get() = 0.0 + override inline val one: Double get() = 1.0 - public override inline fun number(value: Number): Double = value.toDouble() + override inline fun number(value: Number): Double = value.toDouble() - public override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = + override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = when (operation) { PowerOperations.POW_OPERATION -> ::power else -> super.binaryOperationFunction(operation) } - public override inline fun add(a: Double, b: Double): Double = a + b + override inline fun add(a: Double, b: Double): Double = a + b - public override inline fun multiply(a: Double, b: Double): Double = a * b - public override inline fun divide(a: Double, b: Double): Double = a / b + override inline fun multiply(a: Double, b: Double): Double = a * b + override inline fun divide(a: Double, b: Double): Double = a / b - public override inline fun scale(a: Double, value: Double): Double = a * value + override inline fun scale(a: Double, value: Double): Double = a * value - public override inline fun sin(arg: Double): Double = kotlin.math.sin(arg) - public override inline fun cos(arg: Double): Double = kotlin.math.cos(arg) - public override inline fun tan(arg: Double): Double = kotlin.math.tan(arg) - public override inline fun acos(arg: Double): Double = kotlin.math.acos(arg) - public override inline fun asin(arg: Double): Double = kotlin.math.asin(arg) - public override inline fun atan(arg: Double): Double = kotlin.math.atan(arg) + override inline fun sin(arg: Double): Double = kotlin.math.sin(arg) + override inline fun cos(arg: Double): Double = kotlin.math.cos(arg) + override inline fun tan(arg: Double): Double = kotlin.math.tan(arg) + override inline fun acos(arg: Double): Double = kotlin.math.acos(arg) + override inline fun asin(arg: Double): Double = kotlin.math.asin(arg) + override inline fun atan(arg: Double): Double = kotlin.math.atan(arg) - public override inline fun sinh(arg: Double): Double = kotlin.math.sinh(arg) - public override inline fun cosh(arg: Double): Double = kotlin.math.cosh(arg) - public override inline fun tanh(arg: Double): Double = kotlin.math.tanh(arg) - public override inline fun asinh(arg: Double): Double = kotlin.math.asinh(arg) - public override inline fun acosh(arg: Double): Double = kotlin.math.acosh(arg) - public override inline fun atanh(arg: Double): Double = kotlin.math.atanh(arg) + override inline fun sinh(arg: Double): Double = kotlin.math.sinh(arg) + override inline fun cosh(arg: Double): Double = kotlin.math.cosh(arg) + override inline fun tanh(arg: Double): Double = kotlin.math.tanh(arg) + override inline fun asinh(arg: Double): Double = kotlin.math.asinh(arg) + override inline fun acosh(arg: Double): Double = kotlin.math.acosh(arg) + override inline fun atanh(arg: Double): Double = kotlin.math.atanh(arg) - public override inline fun sqrt(arg: Double): Double = kotlin.math.sqrt(arg) - public override inline fun power(arg: Double, pow: Number): Double = arg.kpow(pow.toDouble()) - public override inline fun exp(arg: Double): Double = kotlin.math.exp(arg) - public override inline fun ln(arg: Double): Double = kotlin.math.ln(arg) + override inline fun sqrt(arg: Double): Double = kotlin.math.sqrt(arg) + override inline fun power(arg: Double, pow: Number): Double = arg.kpow(pow.toDouble()) + override inline fun exp(arg: Double): Double = kotlin.math.exp(arg) + override inline fun ln(arg: Double): Double = kotlin.math.ln(arg) - public override inline fun norm(arg: Double): Double = abs(arg) + override inline fun norm(arg: Double): Double = abs(arg) - public override inline fun Double.unaryMinus(): Double = -this - public override inline fun Double.plus(b: Double): Double = this + b - public override inline fun Double.minus(b: Double): Double = this - b - public override inline fun Double.times(b: Double): Double = this * b - public override inline fun Double.div(b: Double): Double = this / b + override inline fun Double.unaryMinus(): Double = -this + override inline fun Double.plus(b: Double): Double = this + b + override inline fun Double.minus(b: Double): Double = this - b + override inline fun Double.times(b: Double): Double = this * b + override inline fun Double.div(b: Double): Double = this / b } /** @@ -112,50 +112,50 @@ public object DoubleField : ExtendedField, Norm, ScaleOp */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object FloatField : ExtendedField, Norm { - public override inline val zero: Float get() = 0.0f - public override inline val one: Float get() = 1.0f + override inline val zero: Float get() = 0.0f + override inline val one: Float get() = 1.0f - public override fun number(value: Number): Float = value.toFloat() + override fun number(value: Number): Float = value.toFloat() - public override fun binaryOperationFunction(operation: String): (left: Float, right: Float) -> Float = + override fun binaryOperationFunction(operation: String): (left: Float, right: Float) -> Float = when (operation) { PowerOperations.POW_OPERATION -> ::power else -> super.binaryOperationFunction(operation) } - public override inline fun add(a: Float, b: Float): Float = a + b - public override fun scale(a: Float, value: Double): Float = a * value.toFloat() + override inline fun add(a: Float, b: Float): Float = a + b + override fun scale(a: Float, value: Double): Float = a * value.toFloat() - public override inline fun multiply(a: Float, b: Float): Float = a * b + override inline fun multiply(a: Float, b: Float): Float = a * b - public override inline fun divide(a: Float, b: Float): Float = a / b + override inline fun divide(a: Float, b: Float): Float = a / b - public override inline fun sin(arg: Float): Float = kotlin.math.sin(arg) - public override inline fun cos(arg: Float): Float = kotlin.math.cos(arg) - public override inline fun tan(arg: Float): Float = kotlin.math.tan(arg) - public override inline fun acos(arg: Float): Float = kotlin.math.acos(arg) - public override inline fun asin(arg: Float): Float = kotlin.math.asin(arg) - public override inline fun atan(arg: Float): Float = kotlin.math.atan(arg) + override inline fun sin(arg: Float): Float = kotlin.math.sin(arg) + override inline fun cos(arg: Float): Float = kotlin.math.cos(arg) + override inline fun tan(arg: Float): Float = kotlin.math.tan(arg) + override inline fun acos(arg: Float): Float = kotlin.math.acos(arg) + override inline fun asin(arg: Float): Float = kotlin.math.asin(arg) + override inline fun atan(arg: Float): Float = kotlin.math.atan(arg) - public override inline fun sinh(arg: Float): Float = kotlin.math.sinh(arg) - public override inline fun cosh(arg: Float): Float = kotlin.math.cosh(arg) - public override inline fun tanh(arg: Float): Float = kotlin.math.tanh(arg) - public override inline fun asinh(arg: Float): Float = kotlin.math.asinh(arg) - public override inline fun acosh(arg: Float): Float = kotlin.math.acosh(arg) - public override inline fun atanh(arg: Float): Float = kotlin.math.atanh(arg) + override inline fun sinh(arg: Float): Float = kotlin.math.sinh(arg) + override inline fun cosh(arg: Float): Float = kotlin.math.cosh(arg) + override inline fun tanh(arg: Float): Float = kotlin.math.tanh(arg) + override inline fun asinh(arg: Float): Float = kotlin.math.asinh(arg) + override inline fun acosh(arg: Float): Float = kotlin.math.acosh(arg) + override inline fun atanh(arg: Float): Float = kotlin.math.atanh(arg) - public override inline fun sqrt(arg: Float): Float = kotlin.math.sqrt(arg) - public override inline fun power(arg: Float, pow: Number): Float = arg.kpow(pow.toFloat()) - public override inline fun exp(arg: Float): Float = kotlin.math.exp(arg) - public override inline fun ln(arg: Float): Float = kotlin.math.ln(arg) + override inline fun sqrt(arg: Float): Float = kotlin.math.sqrt(arg) + override inline fun power(arg: Float, pow: Number): Float = arg.kpow(pow.toFloat()) + override inline fun exp(arg: Float): Float = kotlin.math.exp(arg) + override inline fun ln(arg: Float): Float = kotlin.math.ln(arg) - public override inline fun norm(arg: Float): Float = abs(arg) + override inline fun norm(arg: Float): Float = abs(arg) - public override inline fun Float.unaryMinus(): Float = -this - public override inline fun Float.plus(b: Float): Float = this + b - public override inline fun Float.minus(b: Float): Float = this - b - public override inline fun Float.times(b: Float): Float = this * b - public override inline fun Float.div(b: Float): Float = this / b + override inline fun Float.unaryMinus(): Float = -this + override inline fun Float.plus(b: Float): Float = this + b + override inline fun Float.minus(b: Float): Float = this - b + override inline fun Float.times(b: Float): Float = this * b + override inline fun Float.div(b: Float): Float = this / b } /** @@ -163,21 +163,21 @@ public object FloatField : ExtendedField, Norm { */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object IntRing : Ring, Norm, NumericAlgebra { - public override inline val zero: Int + override inline val zero: Int get() = 0 - public override inline val one: Int + override inline val one: Int get() = 1 - public override fun number(value: Number): Int = value.toInt() - public override inline fun add(a: Int, b: Int): Int = a + b - public override inline fun multiply(a: Int, b: Int): Int = a * b - public override inline fun norm(arg: Int): Int = abs(arg) + override fun number(value: Number): Int = value.toInt() + override inline fun add(a: Int, b: Int): Int = a + b + override inline fun multiply(a: Int, b: Int): Int = a * b + override inline fun norm(arg: Int): Int = abs(arg) - public override inline fun Int.unaryMinus(): Int = -this - public override inline fun Int.plus(b: Int): Int = this + b - public override inline fun Int.minus(b: Int): Int = this - b - public override inline fun Int.times(b: Int): Int = this * b + override inline fun Int.unaryMinus(): Int = -this + override inline fun Int.plus(b: Int): Int = this + b + override inline fun Int.minus(b: Int): Int = this - b + override inline fun Int.times(b: Int): Int = this * b } /** @@ -185,21 +185,21 @@ public object IntRing : Ring, Norm, NumericAlgebra { */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object ShortRing : Ring, Norm, NumericAlgebra { - public override inline val zero: Short + override inline val zero: Short get() = 0 - public override inline val one: Short + override inline val one: Short get() = 1 - public override fun number(value: Number): Short = value.toShort() - public override inline fun add(a: Short, b: Short): Short = (a + b).toShort() - public override inline fun multiply(a: Short, b: Short): Short = (a * b).toShort() - public override fun norm(arg: Short): Short = if (arg > 0) arg else (-arg).toShort() + override fun number(value: Number): Short = value.toShort() + override inline fun add(a: Short, b: Short): Short = (a + b).toShort() + override inline fun multiply(a: Short, b: Short): Short = (a * b).toShort() + override fun norm(arg: Short): Short = if (arg > 0) arg else (-arg).toShort() - public override inline fun Short.unaryMinus(): Short = (-this).toShort() - public override inline fun Short.plus(b: Short): Short = (this + b).toShort() - public override inline fun Short.minus(b: Short): Short = (this - b).toShort() - public override inline fun Short.times(b: Short): Short = (this * b).toShort() + override inline fun Short.unaryMinus(): Short = (-this).toShort() + override inline fun Short.plus(b: Short): Short = (this + b).toShort() + override inline fun Short.minus(b: Short): Short = (this - b).toShort() + override inline fun Short.times(b: Short): Short = (this * b).toShort() } /** @@ -207,21 +207,21 @@ public object ShortRing : Ring, Norm, NumericAlgebra */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object ByteRing : Ring, Norm, NumericAlgebra { - public override inline val zero: Byte + override inline val zero: Byte get() = 0 - public override inline val one: Byte + override inline val one: Byte get() = 1 - public override fun number(value: Number): Byte = value.toByte() - public override inline fun add(a: Byte, b: Byte): Byte = (a + b).toByte() - public override inline fun multiply(a: Byte, b: Byte): Byte = (a * b).toByte() - public override fun norm(arg: Byte): Byte = if (arg > 0) arg else (-arg).toByte() + override fun number(value: Number): Byte = value.toByte() + override inline fun add(a: Byte, b: Byte): Byte = (a + b).toByte() + override inline fun multiply(a: Byte, b: Byte): Byte = (a * b).toByte() + override fun norm(arg: Byte): Byte = if (arg > 0) arg else (-arg).toByte() - public override inline fun Byte.unaryMinus(): Byte = (-this).toByte() - public override inline fun Byte.plus(b: Byte): Byte = (this + b).toByte() - public override inline fun Byte.minus(b: Byte): Byte = (this - b).toByte() - public override inline fun Byte.times(b: Byte): Byte = (this * b).toByte() + override inline fun Byte.unaryMinus(): Byte = (-this).toByte() + override inline fun Byte.plus(b: Byte): Byte = (this + b).toByte() + override inline fun Byte.minus(b: Byte): Byte = (this - b).toByte() + override inline fun Byte.times(b: Byte): Byte = (this * b).toByte() } /** @@ -229,19 +229,19 @@ public object ByteRing : Ring, Norm, NumericAlgebra { */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object LongRing : Ring, Norm, NumericAlgebra { - public override inline val zero: Long + override inline val zero: Long get() = 0L - public override inline val one: Long + override inline val one: Long get() = 1L - public override fun number(value: Number): Long = value.toLong() - public override inline fun add(a: Long, b: Long): Long = a + b - public override inline fun multiply(a: Long, b: Long): Long = a * b - public override fun norm(arg: Long): Long = abs(arg) + override fun number(value: Number): Long = value.toLong() + override inline fun add(a: Long, b: Long): Long = a + b + override inline fun multiply(a: Long, b: Long): Long = a * b + override fun norm(arg: Long): Long = abs(arg) - public override inline fun Long.unaryMinus(): Long = (-this) - public override inline fun Long.plus(b: Long): Long = (this + b) - public override inline fun Long.minus(b: Long): Long = (this - b) - public override inline fun Long.times(b: Long): Long = (this * b) + override inline fun Long.unaryMinus(): Long = (-this) + override inline fun Long.plus(b: Long): Long = (this + b) + override inline fun Long.minus(b: Long): Long = (this - b) + override inline fun Long.times(b: Long): Long = (this * b) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt index 34b5e373b..c83496853 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt @@ -19,7 +19,7 @@ public object DoubleBufferFieldOperations : ExtendedFieldOperations, b: Buffer): DoubleBuffer { + override fun add(a: Buffer, b: Buffer): DoubleBuffer { require(b.size == a.size) { "The size of the first buffer ${a.size} should be the same as for second one: ${b.size} " } @@ -31,7 +31,7 @@ public object DoubleBufferFieldOperations : ExtendedFieldOperations, k: Number): RealBuffer { +// override fun multiply(a: Buffer, k: Number): RealBuffer { // val kValue = k.toDouble() // // return if (a is RealBuffer) { @@ -40,7 +40,7 @@ public object DoubleBufferFieldOperations : ExtendedFieldOperations, k: Number): RealBuffer { +// override fun divide(a: Buffer, k: Number): RealBuffer { // val kValue = k.toDouble() // // return if (a is RealBuffer) { @@ -49,7 +49,7 @@ public object DoubleBufferFieldOperations : ExtendedFieldOperations, b: Buffer): DoubleBuffer { + override fun multiply(a: Buffer, b: Buffer): DoubleBuffer { require(b.size == a.size) { "The size of the first buffer ${a.size} should be the same as for second one: ${b.size} " } @@ -62,7 +62,7 @@ public object DoubleBufferFieldOperations : ExtendedFieldOperations, b: Buffer): DoubleBuffer { + override fun divide(a: Buffer, b: Buffer): DoubleBuffer { require(b.size == a.size) { "The size of the first buffer ${a.size} should be the same as for second one: ${b.size} " } @@ -74,87 +74,87 @@ public object DoubleBufferFieldOperations : ExtendedFieldOperations): DoubleBuffer = if (arg is DoubleBuffer) { + override fun sin(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { sin(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { sin(arg[it]) }) - public override fun cos(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun cos(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { cos(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { cos(arg[it]) }) - public override fun tan(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun tan(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { tan(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { tan(arg[it]) }) - public override fun asin(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun asin(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { asin(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { asin(arg[it]) }) - public override fun acos(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun acos(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { acos(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { acos(arg[it]) }) - public override fun atan(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun atan(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { atan(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { atan(arg[it]) }) - public override fun sinh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun sinh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { sinh(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { sinh(arg[it]) }) - public override fun cosh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun cosh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { cosh(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { cosh(arg[it]) }) - public override fun tanh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun tanh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { tanh(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { tanh(arg[it]) }) - public override fun asinh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun asinh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { asinh(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { asinh(arg[it]) }) - public override fun acosh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun acosh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { acosh(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { acosh(arg[it]) }) - public override fun atanh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun atanh(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { atanh(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { atanh(arg[it]) }) - public override fun power(arg: Buffer, pow: Number): DoubleBuffer = if (arg is DoubleBuffer) { + override fun power(arg: Buffer, pow: Number): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { array[it].pow(pow.toDouble()) }) } else DoubleBuffer(DoubleArray(arg.size) { arg[it].pow(pow.toDouble()) }) - public override fun exp(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun exp(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { exp(array[it]) }) } else DoubleBuffer(DoubleArray(arg.size) { exp(arg[it]) }) - public override fun ln(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { + override fun ln(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { ln(array[it]) }) } else @@ -167,8 +167,8 @@ public object DoubleBufferFieldOperations : ExtendedFieldOperations> { - public override val zero: Buffer by lazy { DoubleBuffer(size) { 0.0 } } - public override val one: Buffer by lazy { DoubleBuffer(size) { 1.0 } } + override val zero: Buffer by lazy { DoubleBuffer(size) { 0.0 } } + override val one: Buffer by lazy { DoubleBuffer(size) { 1.0 } } override fun number(value: Number): Buffer = DoubleBuffer(size) { value.toDouble() } @@ -176,12 +176,12 @@ public class DoubleBufferField(public val size: Int) : ExtendedField, b: Buffer): DoubleBuffer { + override fun add(a: Buffer, b: Buffer): DoubleBuffer { require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } return DoubleBufferFieldOperations.add(a, b) } - public override fun scale(a: Buffer, value: Double): DoubleBuffer { + override fun scale(a: Buffer, value: Double): DoubleBuffer { require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } return if (a is DoubleBuffer) { @@ -190,87 +190,87 @@ public class DoubleBufferField(public val size: Int) : ExtendedField, b: Buffer): DoubleBuffer { + override fun multiply(a: Buffer, b: Buffer): DoubleBuffer { require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } return DoubleBufferFieldOperations.multiply(a, b) } - public override fun divide(a: Buffer, b: Buffer): DoubleBuffer { + override fun divide(a: Buffer, b: Buffer): DoubleBuffer { require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } return DoubleBufferFieldOperations.divide(a, b) } - public override fun sin(arg: Buffer): DoubleBuffer { + override fun sin(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.sin(arg) } - public override fun cos(arg: Buffer): DoubleBuffer { + override fun cos(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.cos(arg) } - public override fun tan(arg: Buffer): DoubleBuffer { + override fun tan(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.tan(arg) } - public override fun asin(arg: Buffer): DoubleBuffer { + override fun asin(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.asin(arg) } - public override fun acos(arg: Buffer): DoubleBuffer { + override fun acos(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.acos(arg) } - public override fun atan(arg: Buffer): DoubleBuffer { + override fun atan(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.atan(arg) } - public override fun sinh(arg: Buffer): DoubleBuffer { + override fun sinh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.sinh(arg) } - public override fun cosh(arg: Buffer): DoubleBuffer { + override fun cosh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.cosh(arg) } - public override fun tanh(arg: Buffer): DoubleBuffer { + override fun tanh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.tanh(arg) } - public override fun asinh(arg: Buffer): DoubleBuffer { + override fun asinh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.asinh(arg) } - public override fun acosh(arg: Buffer): DoubleBuffer { + override fun acosh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.acosh(arg) } - public override fun atanh(arg: Buffer): DoubleBuffer { + override fun atanh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.atanh(arg) } - public override fun power(arg: Buffer, pow: Number): DoubleBuffer { + override fun power(arg: Buffer, pow: Number): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.power(arg, pow) } - public override fun exp(arg: Buffer): DoubleBuffer { + override fun exp(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.exp(arg) } - public override fun ln(arg: Buffer): DoubleBuffer { + override fun ln(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } return DoubleBufferFieldOperations.ln(arg) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt index 8c98ab9c8..5d660c8cb 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt @@ -48,8 +48,8 @@ public class MutableMemoryBuffer(memory: Memory, spec: MemorySpec) : private val writer: MemoryWriter = memory.writer() - public override operator fun set(index: Int, value: T): Unit = writer.write(spec, spec.objectSize * index, value) - public override fun copy(): MutableBuffer = MutableMemoryBuffer(memory.copy(), spec) + override operator fun set(index: Int, value: T): Unit = writer.write(spec, spec.objectSize * index, value) + override fun copy(): MutableBuffer = MutableMemoryBuffer(memory.copy(), spec) public companion object { public fun create(spec: MemorySpec, size: Int): MutableMemoryBuffer = diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt index 3d4c68b3c..8dadecff7 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt @@ -14,16 +14,16 @@ import kotlin.jvm.JvmInline */ @JvmInline public value class ShortBuffer(public val array: ShortArray) : MutableBuffer { - public override val size: Int get() = array.size + override val size: Int get() = array.size - public override operator fun get(index: Int): Short = array[index] + override operator fun get(index: Int): Short = array[index] - public override operator fun set(index: Int, value: Short) { + override operator fun set(index: Int, value: Short) { array[index] = value } - public override operator fun iterator(): ShortIterator = array.iterator() - public override fun copy(): MutableBuffer = ShortBuffer(array.copyOf()) + override operator fun iterator(): ShortIterator = array.iterator() + override fun copy(): MutableBuffer = ShortBuffer(array.copyOf()) } /** diff --git a/kmath-core/src/jvmMain/kotlin/space/kscience/kmath/operations/BigNumbers.kt b/kmath-core/src/jvmMain/kotlin/space/kscience/kmath/operations/BigNumbers.kt index 9b46369bb..7ac2c6f83 100644 --- a/kmath-core/src/jvmMain/kotlin/space/kscience/kmath/operations/BigNumbers.kt +++ b/kmath-core/src/jvmMain/kotlin/space/kscience/kmath/operations/BigNumbers.kt @@ -13,16 +13,16 @@ import java.math.MathContext * A field over [BigInteger]. */ public object JBigIntegerField : Ring, NumericAlgebra { - public override val zero: BigInteger get() = BigInteger.ZERO + override val zero: BigInteger get() = BigInteger.ZERO - public override val one: BigInteger get() = BigInteger.ONE + override val one: BigInteger get() = BigInteger.ONE - public override fun number(value: Number): BigInteger = BigInteger.valueOf(value.toLong()) - public override fun add(a: BigInteger, b: BigInteger): BigInteger = a.add(b) - public override operator fun BigInteger.minus(b: BigInteger): BigInteger = subtract(b) - public override fun multiply(a: BigInteger, b: BigInteger): BigInteger = a.multiply(b) + override fun number(value: Number): BigInteger = BigInteger.valueOf(value.toLong()) + override fun add(a: BigInteger, b: BigInteger): BigInteger = a.add(b) + override operator fun BigInteger.minus(b: BigInteger): BigInteger = subtract(b) + override fun multiply(a: BigInteger, b: BigInteger): BigInteger = a.multiply(b) - public override operator fun BigInteger.unaryMinus(): BigInteger = negate() + override operator fun BigInteger.unaryMinus(): BigInteger = negate() } /** @@ -33,24 +33,24 @@ public object JBigIntegerField : Ring, NumericAlgebra { public abstract class JBigDecimalFieldBase internal constructor( private val mathContext: MathContext = MathContext.DECIMAL64, ) : Field, PowerOperations, NumericAlgebra, ScaleOperations { - public override val zero: BigDecimal + override val zero: BigDecimal get() = BigDecimal.ZERO - public override val one: BigDecimal + override val one: BigDecimal get() = BigDecimal.ONE - public override fun add(a: BigDecimal, b: BigDecimal): BigDecimal = a.add(b) - public override operator fun BigDecimal.minus(b: BigDecimal): BigDecimal = subtract(b) - public override fun number(value: Number): BigDecimal = BigDecimal.valueOf(value.toDouble()) + override fun add(a: BigDecimal, b: BigDecimal): BigDecimal = a.add(b) + override operator fun BigDecimal.minus(b: BigDecimal): BigDecimal = subtract(b) + override fun number(value: Number): BigDecimal = BigDecimal.valueOf(value.toDouble()) - public override fun scale(a: BigDecimal, value: Double): BigDecimal = + override fun scale(a: BigDecimal, value: Double): BigDecimal = a.multiply(value.toBigDecimal(mathContext), mathContext) - public override fun multiply(a: BigDecimal, b: BigDecimal): BigDecimal = a.multiply(b, mathContext) - public override fun divide(a: BigDecimal, b: BigDecimal): BigDecimal = a.divide(b, mathContext) - public override fun power(arg: BigDecimal, pow: Number): BigDecimal = arg.pow(pow.toInt(), mathContext) - public override fun sqrt(arg: BigDecimal): BigDecimal = arg.sqrt(mathContext) - public override operator fun BigDecimal.unaryMinus(): BigDecimal = negate(mathContext) + override fun multiply(a: BigDecimal, b: BigDecimal): BigDecimal = a.multiply(b, mathContext) + override fun divide(a: BigDecimal, b: BigDecimal): BigDecimal = a.divide(b, mathContext) + override fun power(arg: BigDecimal, pow: Number): BigDecimal = arg.pow(pow.toInt(), mathContext) + override fun sqrt(arg: BigDecimal): BigDecimal = arg.sqrt(mathContext) + override operator fun BigDecimal.unaryMinus(): BigDecimal = negate(mathContext) } /** diff --git a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingChain.kt b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingChain.kt index 70849f942..87aebff61 100644 --- a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingChain.kt +++ b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingChain.kt @@ -32,9 +32,9 @@ public interface BlockingBufferChain : BlockingChain, BufferChain { public fun nextBufferBlocking(size: Int): Buffer - public override fun nextBlocking(): T = nextBufferBlocking(1)[0] + override fun nextBlocking(): T = nextBufferBlocking(1)[0] - public override suspend fun nextBuffer(size: Int): Buffer = nextBufferBlocking(size) + override suspend fun nextBuffer(size: Int): Buffer = nextBufferBlocking(size) override suspend fun fork(): BlockingBufferChain } diff --git a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingDoubleChain.kt b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingDoubleChain.kt index 88456e124..25e20291e 100644 --- a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingDoubleChain.kt +++ b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/BlockingDoubleChain.kt @@ -15,7 +15,7 @@ public interface BlockingDoubleChain : BlockingBufferChain { /** * Returns an [DoubleArray] chunk of [size] values of [next]. */ - public override fun nextBufferBlocking(size: Int): DoubleBuffer + override fun nextBufferBlocking(size: Int): DoubleBuffer override suspend fun fork(): BlockingDoubleChain diff --git a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/Chain.kt b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/Chain.kt index b29165e32..8523ac864 100644 --- a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/Chain.kt +++ b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/Chain.kt @@ -39,8 +39,8 @@ public fun Sequence.asChain(): Chain = iterator().asChain() * A simple chain of independent tokens. [fork] returns the same chain. */ public class SimpleChain(private val gen: suspend () -> R) : Chain { - public override suspend fun next(): R = gen() - public override suspend fun fork(): Chain = this + override suspend fun next(): R = gen() + override suspend fun fork(): Chain = this } /** @@ -52,13 +52,13 @@ public class MarkovChain(private val seed: suspend () -> R, private public fun value(): R? = value - public override suspend fun next(): R = mutex.withLock { + override suspend fun next(): R = mutex.withLock { val newValue = gen(value ?: seed()) value = newValue newValue } - public override suspend fun fork(): Chain = MarkovChain(seed = { value ?: seed() }, gen = gen) + override suspend fun fork(): Chain = MarkovChain(seed = { value ?: seed() }, gen = gen) } /** @@ -77,21 +77,21 @@ public class StatefulChain( public fun value(): R? = value - public override suspend fun next(): R = mutex.withLock { + override suspend fun next(): R = mutex.withLock { val newValue = state.gen(value ?: state.seed()) value = newValue newValue } - public override suspend fun fork(): Chain = StatefulChain(forkState(state), seed, forkState, gen) + override suspend fun fork(): Chain = StatefulChain(forkState(state), seed, forkState, gen) } /** * A chain that repeats the same value */ public class ConstantChain(public val value: T) : Chain { - public override suspend fun next(): T = value - public override suspend fun fork(): Chain = this + override suspend fun next(): T = value + override suspend fun fork(): Chain = this } /** diff --git a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/RingBuffer.kt b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/RingBuffer.kt index 05f2876e3..93c4a401b 100644 --- a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/RingBuffer.kt +++ b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/RingBuffer.kt @@ -22,10 +22,10 @@ public class RingBuffer( ) : Buffer { private val mutex: Mutex = Mutex() - public override var size: Int = size + override var size: Int = size private set - public override operator fun get(index: Int): T { + override operator fun get(index: Int): T { require(index >= 0) { "Index must be positive" } require(index < size) { "Index $index is out of circular buffer size $size" } return buffer[startIndex.forward(index)] as T @@ -36,7 +36,7 @@ public class RingBuffer( /** * Iterator could provide wrong results if buffer is changed in initialization (iteration is safe) */ - public override operator fun iterator(): Iterator = object : AbstractIterator() { + override operator fun iterator(): Iterator = object : AbstractIterator() { private var count = size private var index = startIndex val copy = buffer.copy() diff --git a/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt b/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt index ded8c9c44..f9ef62529 100644 --- a/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt +++ b/kmath-coroutines/src/jvmMain/kotlin/space/kscience/kmath/structures/LazyStructureND.kt @@ -13,7 +13,7 @@ import space.kscience.kmath.nd.StructureND public class LazyStructureND( public val scope: CoroutineScope, - public override val shape: IntArray, + override val shape: IntArray, public val function: suspend (IntArray) -> T, ) : StructureND { private val cache: MutableMap> = HashMap() @@ -23,10 +23,10 @@ public class LazyStructureND( } public suspend fun await(index: IntArray): T = deferred(index).await() - public override operator fun get(index: IntArray): T = runBlocking { deferred(index).await() } + override operator fun get(index: IntArray): T = runBlocking { deferred(index).await() } @OptIn(PerformancePitfall::class) - public override fun elements(): Sequence> { + override fun elements(): Sequence> { val strides = DefaultStrides(shape) val res = runBlocking { strides.indices().toList().map { index -> index to await(index) } } return res.asSequence() diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt index cec31eb7d..27fd3fc53 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt @@ -17,6 +17,6 @@ import space.kscience.kmath.nd.Structure2D * @author Iaroslav Postovalov */ public abstract class EjmlMatrix(public open val origin: M) : Structure2D { - public override val rowNum: Int get() = origin.numRows - public override val colNum: Int get() = origin.numCols + override val rowNum: Int get() = origin.numRows + override val colNum: Int get() = origin.numCols } diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt index 5d10d1fbb..37995c27e 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt @@ -17,10 +17,10 @@ import space.kscience.kmath.linear.Point * @author Iaroslav Postovalov */ public abstract class EjmlVector(public open val origin: M) : Point { - public override val size: Int + override val size: Int get() = origin.numCols - public override operator fun iterator(): Iterator = object : Iterator { + override operator fun iterator(): Iterator = object : Iterator { private var cursor: Int = 0 override fun next(): T { @@ -31,5 +31,5 @@ public abstract class EjmlVector(public open val origin: override fun hasNext(): Boolean = cursor < origin.numCols * origin.numRows } - public override fun toString(): String = "EjmlVector(origin=$origin)" + override fun toString(): String = "EjmlVector(origin=$origin)" } diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt index 139c55697..5de8fc8a5 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt @@ -34,37 +34,37 @@ import kotlin.reflect.cast /** * [EjmlVector] specialization for [Double]. */ -public class EjmlDoubleVector(public override val origin: M) : EjmlVector(origin) { +public class EjmlDoubleVector(override val origin: M) : EjmlVector(origin) { init { require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } } - public override operator fun get(index: Int): Double = origin[0, index] + override operator fun get(index: Int): Double = origin[0, index] } /** * [EjmlVector] specialization for [Float]. */ -public class EjmlFloatVector(public override val origin: M) : EjmlVector(origin) { +public class EjmlFloatVector(override val origin: M) : EjmlVector(origin) { init { require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } } - public override operator fun get(index: Int): Float = origin[0, index] + override operator fun get(index: Int): Float = origin[0, index] } /** * [EjmlMatrix] specialization for [Double]. */ -public class EjmlDoubleMatrix(public override val origin: M) : EjmlMatrix(origin) { - public override operator fun get(i: Int, j: Int): Double = origin[i, j] +public class EjmlDoubleMatrix(override val origin: M) : EjmlMatrix(origin) { + override operator fun get(i: Int, j: Int): Double = origin[i, j] } /** * [EjmlMatrix] specialization for [Float]. */ -public class EjmlFloatMatrix(public override val origin: M) : EjmlMatrix(origin) { - public override operator fun get(i: Int, j: Int): Float = origin[i, j] +public class EjmlFloatMatrix(override val origin: M) : EjmlMatrix(origin) { + override operator fun get(i: Int, j: Int): Float = origin[i, j] } /** @@ -75,23 +75,23 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace.toEjml(): EjmlDoubleMatrix = when { + override fun Matrix.toEjml(): EjmlDoubleMatrix = when { this is EjmlDoubleMatrix<*> && origin is DMatrixRMaj -> this as EjmlDoubleMatrix else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } } @Suppress("UNCHECKED_CAST") - public override fun Point.toEjml(): EjmlDoubleVector = when { + override fun Point.toEjml(): EjmlDoubleVector = when { this is EjmlDoubleVector<*> && origin is DMatrixRMaj -> this as EjmlDoubleVector else -> EjmlDoubleVector(DMatrixRMaj(size, 1).also { (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } }) } - public override fun buildMatrix( + override fun buildMatrix( rows: Int, columns: Int, initializer: DoubleField.(i: Int, j: Int) -> Double, @@ -101,7 +101,7 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace Double, ): EjmlDoubleVector = EjmlDoubleVector(DMatrixRMaj(size, 1).also { @@ -111,21 +111,21 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace T.wrapMatrix() = EjmlDoubleMatrix(this) private fun T.wrapVector() = EjmlDoubleVector(this) - public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } - public override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { + override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { val out = DMatrixRMaj(1, 1) CommonOps_DDRM.mult(toEjml().origin, other.toEjml().origin, out) return out.wrapMatrix() } - public override fun Matrix.dot(vector: Point): EjmlDoubleVector { + override fun Matrix.dot(vector: Point): EjmlDoubleVector { val out = DMatrixRMaj(1, 1) CommonOps_DDRM.mult(toEjml().origin, vector.toEjml().origin, out) return out.wrapVector() } - public override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { + override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { val out = DMatrixRMaj(1, 1) CommonOps_DDRM.add( @@ -139,19 +139,19 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace.times(value: Double): EjmlDoubleMatrix { + override operator fun Matrix.times(value: Double): EjmlDoubleMatrix { val res = DMatrixRMaj(1, 1) CommonOps_DDRM.scale(value, toEjml().origin, res) return res.wrapMatrix() } - public override fun Point.unaryMinus(): EjmlDoubleVector { + override fun Point.unaryMinus(): EjmlDoubleVector { val res = DMatrixRMaj(1, 1) CommonOps_DDRM.changeSign(toEjml().origin, res) return res.wrapVector() } - public override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { + override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { val out = DMatrixRMaj(1, 1) CommonOps_DDRM.add( @@ -165,7 +165,7 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace.plus(other: Point): EjmlDoubleVector { + override fun Point.plus(other: Point): EjmlDoubleVector { val out = DMatrixRMaj(1, 1) CommonOps_DDRM.add( @@ -179,7 +179,7 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace.minus(other: Point): EjmlDoubleVector { + override fun Point.minus(other: Point): EjmlDoubleVector { val out = DMatrixRMaj(1, 1) CommonOps_DDRM.add( @@ -193,18 +193,18 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace): EjmlDoubleMatrix = m * this + override fun Double.times(m: Matrix): EjmlDoubleMatrix = m * this - public override fun Point.times(value: Double): EjmlDoubleVector { + override fun Point.times(value: Double): EjmlDoubleVector { val res = DMatrixRMaj(1, 1) CommonOps_DDRM.scale(value, toEjml().origin, res) return res.wrapVector() } - public override fun Double.times(v: Point): EjmlDoubleVector = v * this + override fun Double.times(v: Point): EjmlDoubleVector = v * this @UnstableKMathAPI - public override fun getFeature(structure: Matrix, type: KClass): F? { + override fun getFeature(structure: Matrix, type: KClass): F? { structure.getFeature(type)?.let { return it } val origin = structure.toEjml().origin @@ -309,23 +309,23 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace.toEjml(): EjmlFloatMatrix = when { + override fun Matrix.toEjml(): EjmlFloatMatrix = when { this is EjmlFloatMatrix<*> && origin is FMatrixRMaj -> this as EjmlFloatMatrix else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } } @Suppress("UNCHECKED_CAST") - public override fun Point.toEjml(): EjmlFloatVector = when { + override fun Point.toEjml(): EjmlFloatVector = when { this is EjmlFloatVector<*> && origin is FMatrixRMaj -> this as EjmlFloatVector else -> EjmlFloatVector(FMatrixRMaj(size, 1).also { (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } }) } - public override fun buildMatrix( + override fun buildMatrix( rows: Int, columns: Int, initializer: FloatField.(i: Int, j: Int) -> Float, @@ -335,7 +335,7 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace Float, ): EjmlFloatVector = EjmlFloatVector(FMatrixRMaj(size, 1).also { @@ -345,21 +345,21 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace T.wrapMatrix() = EjmlFloatMatrix(this) private fun T.wrapVector() = EjmlFloatVector(this) - public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } - public override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { + override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { val out = FMatrixRMaj(1, 1) CommonOps_FDRM.mult(toEjml().origin, other.toEjml().origin, out) return out.wrapMatrix() } - public override fun Matrix.dot(vector: Point): EjmlFloatVector { + override fun Matrix.dot(vector: Point): EjmlFloatVector { val out = FMatrixRMaj(1, 1) CommonOps_FDRM.mult(toEjml().origin, vector.toEjml().origin, out) return out.wrapVector() } - public override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { + override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { val out = FMatrixRMaj(1, 1) CommonOps_FDRM.add( @@ -373,19 +373,19 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace.times(value: Float): EjmlFloatMatrix { + override operator fun Matrix.times(value: Float): EjmlFloatMatrix { val res = FMatrixRMaj(1, 1) CommonOps_FDRM.scale(value, toEjml().origin, res) return res.wrapMatrix() } - public override fun Point.unaryMinus(): EjmlFloatVector { + override fun Point.unaryMinus(): EjmlFloatVector { val res = FMatrixRMaj(1, 1) CommonOps_FDRM.changeSign(toEjml().origin, res) return res.wrapVector() } - public override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { + override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { val out = FMatrixRMaj(1, 1) CommonOps_FDRM.add( @@ -399,7 +399,7 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace.plus(other: Point): EjmlFloatVector { + override fun Point.plus(other: Point): EjmlFloatVector { val out = FMatrixRMaj(1, 1) CommonOps_FDRM.add( @@ -413,7 +413,7 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace.minus(other: Point): EjmlFloatVector { + override fun Point.minus(other: Point): EjmlFloatVector { val out = FMatrixRMaj(1, 1) CommonOps_FDRM.add( @@ -427,18 +427,18 @@ public object EjmlLinearSpaceFDRM : EjmlLinearSpace): EjmlFloatMatrix = m * this + override fun Float.times(m: Matrix): EjmlFloatMatrix = m * this - public override fun Point.times(value: Float): EjmlFloatVector { + override fun Point.times(value: Float): EjmlFloatVector { val res = FMatrixRMaj(1, 1) CommonOps_FDRM.scale(value, toEjml().origin, res) return res.wrapVector() } - public override fun Float.times(v: Point): EjmlFloatVector = v * this + override fun Float.times(v: Point): EjmlFloatVector = v * this @UnstableKMathAPI - public override fun getFeature(structure: Matrix, type: KClass): F? { + override fun getFeature(structure: Matrix, type: KClass): F? { structure.getFeature(type)?.let { return it } val origin = structure.toEjml().origin @@ -543,23 +543,23 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace.toEjml(): EjmlDoubleMatrix = when { + override fun Matrix.toEjml(): EjmlDoubleMatrix = when { this is EjmlDoubleMatrix<*> && origin is DMatrixSparseCSC -> this as EjmlDoubleMatrix else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } } @Suppress("UNCHECKED_CAST") - public override fun Point.toEjml(): EjmlDoubleVector = when { + override fun Point.toEjml(): EjmlDoubleVector = when { this is EjmlDoubleVector<*> && origin is DMatrixSparseCSC -> this as EjmlDoubleVector else -> EjmlDoubleVector(DMatrixSparseCSC(size, 1).also { (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } }) } - public override fun buildMatrix( + override fun buildMatrix( rows: Int, columns: Int, initializer: DoubleField.(i: Int, j: Int) -> Double, @@ -569,7 +569,7 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace Double, ): EjmlDoubleVector = EjmlDoubleVector(DMatrixSparseCSC(size, 1).also { @@ -579,21 +579,21 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace T.wrapMatrix() = EjmlDoubleMatrix(this) private fun T.wrapVector() = EjmlDoubleVector(this) - public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } - public override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { + override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { val out = DMatrixSparseCSC(1, 1) CommonOps_DSCC.mult(toEjml().origin, other.toEjml().origin, out) return out.wrapMatrix() } - public override fun Matrix.dot(vector: Point): EjmlDoubleVector { + override fun Matrix.dot(vector: Point): EjmlDoubleVector { val out = DMatrixSparseCSC(1, 1) CommonOps_DSCC.mult(toEjml().origin, vector.toEjml().origin, out) return out.wrapVector() } - public override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { + override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { val out = DMatrixSparseCSC(1, 1) CommonOps_DSCC.add( @@ -609,19 +609,19 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace.times(value: Double): EjmlDoubleMatrix { + override operator fun Matrix.times(value: Double): EjmlDoubleMatrix { val res = DMatrixSparseCSC(1, 1) CommonOps_DSCC.scale(value, toEjml().origin, res) return res.wrapMatrix() } - public override fun Point.unaryMinus(): EjmlDoubleVector { + override fun Point.unaryMinus(): EjmlDoubleVector { val res = DMatrixSparseCSC(1, 1) CommonOps_DSCC.changeSign(toEjml().origin, res) return res.wrapVector() } - public override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { + override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { val out = DMatrixSparseCSC(1, 1) CommonOps_DSCC.add( @@ -637,7 +637,7 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace.plus(other: Point): EjmlDoubleVector { + override fun Point.plus(other: Point): EjmlDoubleVector { val out = DMatrixSparseCSC(1, 1) CommonOps_DSCC.add( @@ -653,7 +653,7 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace.minus(other: Point): EjmlDoubleVector { + override fun Point.minus(other: Point): EjmlDoubleVector { val out = DMatrixSparseCSC(1, 1) CommonOps_DSCC.add( @@ -669,18 +669,18 @@ public object EjmlLinearSpaceDSCC : EjmlLinearSpace): EjmlDoubleMatrix = m * this + override fun Double.times(m: Matrix): EjmlDoubleMatrix = m * this - public override fun Point.times(value: Double): EjmlDoubleVector { + override fun Point.times(value: Double): EjmlDoubleVector { val res = DMatrixSparseCSC(1, 1) CommonOps_DSCC.scale(value, toEjml().origin, res) return res.wrapVector() } - public override fun Double.times(v: Point): EjmlDoubleVector = v * this + override fun Double.times(v: Point): EjmlDoubleVector = v * this @UnstableKMathAPI - public override fun getFeature(structure: Matrix, type: KClass): F? { + override fun getFeature(structure: Matrix, type: KClass): F? { structure.getFeature(type)?.let { return it } val origin = structure.toEjml().origin @@ -772,23 +772,23 @@ public object EjmlLinearSpaceFSCC : EjmlLinearSpace.toEjml(): EjmlFloatMatrix = when { + override fun Matrix.toEjml(): EjmlFloatMatrix = when { this is EjmlFloatMatrix<*> && origin is FMatrixSparseCSC -> this as EjmlFloatMatrix else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } } @Suppress("UNCHECKED_CAST") - public override fun Point.toEjml(): EjmlFloatVector = when { + override fun Point.toEjml(): EjmlFloatVector = when { this is EjmlFloatVector<*> && origin is FMatrixSparseCSC -> this as EjmlFloatVector else -> EjmlFloatVector(FMatrixSparseCSC(size, 1).also { (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } }) } - public override fun buildMatrix( + override fun buildMatrix( rows: Int, columns: Int, initializer: FloatField.(i: Int, j: Int) -> Float, @@ -798,7 +798,7 @@ public object EjmlLinearSpaceFSCC : EjmlLinearSpace Float, ): EjmlFloatVector = EjmlFloatVector(FMatrixSparseCSC(size, 1).also { @@ -808,21 +808,21 @@ public object EjmlLinearSpaceFSCC : EjmlLinearSpace T.wrapMatrix() = EjmlFloatMatrix(this) private fun T.wrapVector() = EjmlFloatVector(this) - public override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } - public override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { + override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { val out = FMatrixSparseCSC(1, 1) CommonOps_FSCC.mult(toEjml().origin, other.toEjml().origin, out) return out.wrapMatrix() } - public override fun Matrix.dot(vector: Point): EjmlFloatVector { + override fun Matrix.dot(vector: Point): EjmlFloatVector { val out = FMatrixSparseCSC(1, 1) CommonOps_FSCC.mult(toEjml().origin, vector.toEjml().origin, out) return out.wrapVector() } - public override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { + override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { val out = FMatrixSparseCSC(1, 1) CommonOps_FSCC.add( @@ -838,19 +838,19 @@ public object EjmlLinearSpaceFSCC : EjmlLinearSpace.times(value: Float): EjmlFloatMatrix { + override operator fun Matrix.times(value: Float): EjmlFloatMatrix { val res = FMatrixSparseCSC(1, 1) CommonOps_FSCC.scale(value, toEjml().origin, res) return res.wrapMatrix() } - public override fun Point.unaryMinus(): EjmlFloatVector { + override fun Point.unaryMinus(): EjmlFloatVector { val res = FMatrixSparseCSC(1, 1) CommonOps_FSCC.changeSign(toEjml().origin, res) return res.wrapVector() } - public override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { + override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { val out = FMatrixSparseCSC(1, 1) CommonOps_FSCC.add( @@ -866,7 +866,7 @@ public object EjmlLinearSpaceFSCC : EjmlLinearSpace.plus(other: Point): EjmlFloatVector { + override fun Point.plus(other: Point): EjmlFloatVector { val out = FMatrixSparseCSC(1, 1) CommonOps_FSCC.add( @@ -882,7 +882,7 @@ public object EjmlLinearSpaceFSCC : EjmlLinearSpace.minus(other: Point): EjmlFloatVector { + override fun Point.minus(other: Point): EjmlFloatVector { val out = FMatrixSparseCSC(1, 1) CommonOps_FSCC.add( @@ -898,18 +898,18 @@ public object EjmlLinearSpaceFSCC : EjmlLinearSpace): EjmlFloatMatrix = m * this + override fun Float.times(m: Matrix): EjmlFloatMatrix = m * this - public override fun Point.times(value: Float): EjmlFloatVector { + override fun Point.times(value: Float): EjmlFloatVector { val res = FMatrixSparseCSC(1, 1) CommonOps_FSCC.scale(value, toEjml().origin, res) return res.wrapVector() } - public override fun Float.times(v: Point): EjmlFloatVector = v * this + override fun Float.times(v: Point): EjmlFloatVector = v * this @UnstableKMathAPI - public override fun getFeature(structure: Matrix, type: KClass): F? { + override fun getFeature(structure: Matrix, type: KClass): F? { structure.getFeature(type)?.let { return it } val origin = structure.toEjml().origin diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt index 5f35d0ab6..a2ad5801c 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt @@ -30,7 +30,7 @@ public fun interface Piecewise { public interface PiecewisePolynomial> : Piecewise> { public val pieces: Collection, Polynomial>> - public override fun findPiece(arg: T): Polynomial? + override fun findPiece(arg: T): Polynomial? } /** diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt index f0c858b03..f0f744530 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt @@ -98,13 +98,13 @@ public fun > Polynomial.integrate( public class PolynomialSpace( private val ring: C, ) : Group>, ScaleOperations> where C : Ring, C : ScaleOperations { - public override val zero: Polynomial = Polynomial(emptyList()) + override val zero: Polynomial = Polynomial(emptyList()) override fun Polynomial.unaryMinus(): Polynomial = ring { Polynomial(coefficients.map { -it }) } - public override fun add(a: Polynomial, b: Polynomial): Polynomial { + override fun add(a: Polynomial, b: Polynomial): Polynomial { val dim = max(a.coefficients.size, b.coefficients.size) return ring { @@ -114,7 +114,7 @@ public class PolynomialSpace( } } - public override fun scale(a: Polynomial, value: Double): Polynomial = + override fun scale(a: Polynomial, value: Double): Polynomial = ring { Polynomial(List(a.coefficients.size) { index -> a.coefficients[index] * value }) } /** diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt index 24c049647..edd0e6b0a 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt @@ -21,9 +21,9 @@ internal fun > insureSorted(points: XYColumnarData<*, T, *>) { /** * Reference JVM implementation: https://github.com/apache/commons-math/blob/master/src/main/java/org/apache/commons/math4/analysis/interpolation/LinearInterpolator.java */ -public class LinearInterpolator>(public override val algebra: Field) : PolynomialInterpolator { +public class LinearInterpolator>(override val algebra: Field) : PolynomialInterpolator { @OptIn(UnstableKMathAPI::class) - public override fun interpolatePolynomials(points: XYColumnarData): PiecewisePolynomial = algebra { + override fun interpolatePolynomials(points: XYColumnarData): PiecewisePolynomial = algebra { require(points.size > 0) { "Point array should not be empty" } insureSorted(points) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt index bf291c315..39c33ee69 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt @@ -23,13 +23,13 @@ import space.kscience.kmath.structures.MutableBufferFactory * https://github.com/apache/commons-math/blob/eb57d6d457002a0bb5336d789a3381a24599affe/src/main/java/org/apache/commons/math4/analysis/interpolation/SplineInterpolator.java */ public class SplineInterpolator>( - public override val algebra: Field, + override val algebra: Field, public val bufferFactory: MutableBufferFactory, ) : PolynomialInterpolator { //TODO possibly optimize zeroed buffers @OptIn(UnstableKMathAPI::class) - public override fun interpolatePolynomials(points: XYColumnarData): PiecewisePolynomial = algebra { + override fun interpolatePolynomials(points: XYColumnarData): PiecewisePolynomial = algebra { require(points.size >= 3) { "Can't use spline interpolator with less than 3 points" } insureSorted(points) // Number of intervals. The number of data points is n + 1. diff --git a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt index 2a4837ee0..2b91c2334 100644 --- a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt +++ b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt @@ -15,15 +15,15 @@ import kotlin.math.sqrt public interface Vector2D : Point, Vector{ public val x: Double public val y: Double - public override val size: Int get() = 2 + override val size: Int get() = 2 - public override operator fun get(index: Int): Double = when (index) { + override operator fun get(index: Int): Double = when (index) { 1 -> x 2 -> y else -> error("Accessing outside of point bounds") } - public override operator fun iterator(): Iterator = listOf(x, y).iterator() + override operator fun iterator(): Iterator = listOf(x, y).iterator() } public val Vector2D.r: Double @@ -41,13 +41,13 @@ private data class Vector2DImpl( * 2D Euclidean space */ public object Euclidean2DSpace : GeometrySpace, ScaleOperations { - public override val zero: Vector2D by lazy { Vector2D(0.0, 0.0) } + override val zero: Vector2D by lazy { Vector2D(0.0, 0.0) } public fun Vector2D.norm(): Double = sqrt(x * x + y * y) override fun Vector2D.unaryMinus(): Vector2D = Vector2D(-x, -y) - public override fun Vector2D.distanceTo(other: Vector2D): Double = (this - other).norm() - public override fun add(a: Vector2D, b: Vector2D): Vector2D = Vector2D(a.x + b.x, a.y + b.y) - public override fun scale(a: Vector2D, value: Double): Vector2D = Vector2D(a.x * value, a.y * value) - public override fun Vector2D.dot(other: Vector2D): Double = x * other.x + y * other.y + override fun Vector2D.distanceTo(other: Vector2D): Double = (this - other).norm() + override fun add(a: Vector2D, b: Vector2D): Vector2D = Vector2D(a.x + b.x, a.y + b.y) + override fun scale(a: Vector2D, value: Double): Vector2D = Vector2D(a.x * value, a.y * value) + override fun Vector2D.dot(other: Vector2D): Double = x * other.x + y * other.y } diff --git a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt index 37e7d2cb2..628106b0b 100644 --- a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt +++ b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt @@ -16,16 +16,16 @@ public interface Vector3D : Point, Vector { public val x: Double public val y: Double public val z: Double - public override val size: Int get() = 3 + override val size: Int get() = 3 - public override operator fun get(index: Int): Double = when (index) { + override operator fun get(index: Int): Double = when (index) { 1 -> x 2 -> y 3 -> z else -> error("Accessing outside of point bounds") } - public override operator fun iterator(): Iterator = listOf(x, y, z).iterator() + override operator fun iterator(): Iterator = listOf(x, y, z).iterator() } @Suppress("FunctionName") @@ -40,19 +40,19 @@ private data class Vector3DImpl( ) : Vector3D public object Euclidean3DSpace : GeometrySpace, ScaleOperations { - public override val zero: Vector3D by lazy { Vector3D(0.0, 0.0, 0.0) } + override val zero: Vector3D by lazy { Vector3D(0.0, 0.0, 0.0) } public fun Vector3D.norm(): Double = sqrt(x * x + y * y + z * z) override fun Vector3D.unaryMinus(): Vector3D = Vector3D(-x, -y, -z) - public override fun Vector3D.distanceTo(other: Vector3D): Double = (this - other).norm() + override fun Vector3D.distanceTo(other: Vector3D): Double = (this - other).norm() - public override fun add(a: Vector3D, b: Vector3D): Vector3D = + override fun add(a: Vector3D, b: Vector3D): Vector3D = Vector3D(a.x + b.x, a.y + b.y, a.z + b.z) - public override fun scale(a: Vector3D, value: Double): Vector3D = + override fun scale(a: Vector3D, value: Double): Vector3D = Vector3D(a.x * value, a.y * value, a.z * value) - public override fun Vector3D.dot(other: Vector3D): Double = + override fun Vector3D.dot(other: Vector3D): Double = x * other.x + y * other.y + z * other.z } diff --git a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt index 6d48d3738..79b6b4e02 100644 --- a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt +++ b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/IndexedHistogramSpace.kt @@ -20,7 +20,7 @@ import space.kscience.kmath.operations.invoke */ public data class DomainBin>( public val domain: Domain, - public override val value: Number, + override val value: Number, ) : Bin, Domain by domain @OptIn(UnstableKMathAPI::class) diff --git a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt index 0ad96ad46..f461ee4fa 100644 --- a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt +++ b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt @@ -27,15 +27,15 @@ public class UnivariateBin( public val standardDeviation: Double, ) : Bin, ClosedFloatingPointRange by domain.range { - public override val dimension: Int get() = 1 + override val dimension: Int get() = 1 - public override fun contains(point: Buffer): Boolean = point.size == 1 && contains(point[0]) + override fun contains(point: Buffer): Boolean = point.size == 1 && contains(point[0]) } @OptIn(UnstableKMathAPI::class) public interface UnivariateHistogram : Histogram{ public operator fun get(value: Double): UnivariateBin? - public override operator fun get(point: Buffer): UnivariateBin? = get(point[0]) + override operator fun get(point: Buffer): UnivariateBin? = get(point[0]) public companion object { /** diff --git a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt index cf6f9471d..a30020dff 100644 --- a/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt +++ b/kmath-jafama/src/main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt @@ -12,50 +12,50 @@ import space.kscience.kmath.operations.ScaleOperations */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object JafamaDoubleField : ExtendedField, Norm, ScaleOperations { - public override inline val zero: Double get() = 0.0 - public override inline val one: Double get() = 1.0 + override inline val zero: Double get() = 0.0 + override inline val one: Double get() = 1.0 - public override inline fun number(value: Number): Double = value.toDouble() + override inline fun number(value: Number): Double = value.toDouble() - public override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = + override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = when (operation) { PowerOperations.POW_OPERATION -> ::power else -> super.binaryOperationFunction(operation) } - public override inline fun add(a: Double, b: Double): Double = a + b + override inline fun add(a: Double, b: Double): Double = a + b - public override inline fun multiply(a: Double, b: Double): Double = a * b - public override inline fun divide(a: Double, b: Double): Double = a / b + override inline fun multiply(a: Double, b: Double): Double = a * b + override inline fun divide(a: Double, b: Double): Double = a / b - public override inline fun scale(a: Double, value: Double): Double = a * value + override inline fun scale(a: Double, value: Double): Double = a * value - public override inline fun sin(arg: Double): Double = FastMath.sin(arg) - public override inline fun cos(arg: Double): Double = FastMath.cos(arg) - public override inline fun tan(arg: Double): Double = FastMath.tan(arg) - public override inline fun acos(arg: Double): Double = FastMath.acos(arg) - public override inline fun asin(arg: Double): Double = FastMath.asin(arg) - public override inline fun atan(arg: Double): Double = FastMath.atan(arg) + override inline fun sin(arg: Double): Double = FastMath.sin(arg) + override inline fun cos(arg: Double): Double = FastMath.cos(arg) + override inline fun tan(arg: Double): Double = FastMath.tan(arg) + override inline fun acos(arg: Double): Double = FastMath.acos(arg) + override inline fun asin(arg: Double): Double = FastMath.asin(arg) + override inline fun atan(arg: Double): Double = FastMath.atan(arg) - public override inline fun sinh(arg: Double): Double = FastMath.sinh(arg) - public override inline fun cosh(arg: Double): Double = FastMath.cosh(arg) - public override inline fun tanh(arg: Double): Double = FastMath.tanh(arg) - public override inline fun asinh(arg: Double): Double = FastMath.asinh(arg) - public override inline fun acosh(arg: Double): Double = FastMath.acosh(arg) - public override inline fun atanh(arg: Double): Double = FastMath.atanh(arg) + override inline fun sinh(arg: Double): Double = FastMath.sinh(arg) + override inline fun cosh(arg: Double): Double = FastMath.cosh(arg) + override inline fun tanh(arg: Double): Double = FastMath.tanh(arg) + override inline fun asinh(arg: Double): Double = FastMath.asinh(arg) + override inline fun acosh(arg: Double): Double = FastMath.acosh(arg) + override inline fun atanh(arg: Double): Double = FastMath.atanh(arg) - public override inline fun sqrt(arg: Double): Double = FastMath.sqrt(arg) - public override inline fun power(arg: Double, pow: Number): Double = FastMath.pow(arg, pow.toDouble()) - public override inline fun exp(arg: Double): Double = FastMath.exp(arg) - public override inline fun ln(arg: Double): Double = FastMath.log(arg) + override inline fun sqrt(arg: Double): Double = FastMath.sqrt(arg) + override inline fun power(arg: Double, pow: Number): Double = FastMath.pow(arg, pow.toDouble()) + override inline fun exp(arg: Double): Double = FastMath.exp(arg) + override inline fun ln(arg: Double): Double = FastMath.log(arg) - public override inline fun norm(arg: Double): Double = FastMath.abs(arg) + override inline fun norm(arg: Double): Double = FastMath.abs(arg) - public override inline fun Double.unaryMinus(): Double = -this - public override inline fun Double.plus(b: Double): Double = this + b - public override inline fun Double.minus(b: Double): Double = this - b - public override inline fun Double.times(b: Double): Double = this * b - public override inline fun Double.div(b: Double): Double = this / b + override inline fun Double.unaryMinus(): Double = -this + override inline fun Double.plus(b: Double): Double = this + b + override inline fun Double.minus(b: Double): Double = this - b + override inline fun Double.times(b: Double): Double = this * b + override inline fun Double.div(b: Double): Double = this / b } /** @@ -63,48 +63,48 @@ public object JafamaDoubleField : ExtendedField, Norm, S */ @Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public object StrictJafamaDoubleField : ExtendedField, Norm, ScaleOperations { - public override inline val zero: Double get() = 0.0 - public override inline val one: Double get() = 1.0 + override inline val zero: Double get() = 0.0 + override inline val one: Double get() = 1.0 - public override inline fun number(value: Number): Double = value.toDouble() + override inline fun number(value: Number): Double = value.toDouble() - public override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = + override fun binaryOperationFunction(operation: String): (left: Double, right: Double) -> Double = when (operation) { PowerOperations.POW_OPERATION -> ::power else -> super.binaryOperationFunction(operation) } - public override inline fun add(a: Double, b: Double): Double = a + b + override inline fun add(a: Double, b: Double): Double = a + b - public override inline fun multiply(a: Double, b: Double): Double = a * b - public override inline fun divide(a: Double, b: Double): Double = a / b + override inline fun multiply(a: Double, b: Double): Double = a * b + override inline fun divide(a: Double, b: Double): Double = a / b - public override inline fun scale(a: Double, value: Double): Double = a * value + override inline fun scale(a: Double, value: Double): Double = a * value - public override inline fun sin(arg: Double): Double = StrictFastMath.sin(arg) - public override inline fun cos(arg: Double): Double = StrictFastMath.cos(arg) - public override inline fun tan(arg: Double): Double = StrictFastMath.tan(arg) - public override inline fun acos(arg: Double): Double = StrictFastMath.acos(arg) - public override inline fun asin(arg: Double): Double = StrictFastMath.asin(arg) - public override inline fun atan(arg: Double): Double = StrictFastMath.atan(arg) + override inline fun sin(arg: Double): Double = StrictFastMath.sin(arg) + override inline fun cos(arg: Double): Double = StrictFastMath.cos(arg) + override inline fun tan(arg: Double): Double = StrictFastMath.tan(arg) + override inline fun acos(arg: Double): Double = StrictFastMath.acos(arg) + override inline fun asin(arg: Double): Double = StrictFastMath.asin(arg) + override inline fun atan(arg: Double): Double = StrictFastMath.atan(arg) - public override inline fun sinh(arg: Double): Double = StrictFastMath.sinh(arg) - public override inline fun cosh(arg: Double): Double = StrictFastMath.cosh(arg) - public override inline fun tanh(arg: Double): Double = StrictFastMath.tanh(arg) - public override inline fun asinh(arg: Double): Double = StrictFastMath.asinh(arg) - public override inline fun acosh(arg: Double): Double = StrictFastMath.acosh(arg) - public override inline fun atanh(arg: Double): Double = StrictFastMath.atanh(arg) + override inline fun sinh(arg: Double): Double = StrictFastMath.sinh(arg) + override inline fun cosh(arg: Double): Double = StrictFastMath.cosh(arg) + override inline fun tanh(arg: Double): Double = StrictFastMath.tanh(arg) + override inline fun asinh(arg: Double): Double = StrictFastMath.asinh(arg) + override inline fun acosh(arg: Double): Double = StrictFastMath.acosh(arg) + override inline fun atanh(arg: Double): Double = StrictFastMath.atanh(arg) - public override inline fun sqrt(arg: Double): Double = StrictFastMath.sqrt(arg) - public override inline fun power(arg: Double, pow: Number): Double = StrictFastMath.pow(arg, pow.toDouble()) - public override inline fun exp(arg: Double): Double = StrictFastMath.exp(arg) - public override inline fun ln(arg: Double): Double = StrictFastMath.log(arg) + override inline fun sqrt(arg: Double): Double = StrictFastMath.sqrt(arg) + override inline fun power(arg: Double, pow: Number): Double = StrictFastMath.pow(arg, pow.toDouble()) + override inline fun exp(arg: Double): Double = StrictFastMath.exp(arg) + override inline fun ln(arg: Double): Double = StrictFastMath.log(arg) - public override inline fun norm(arg: Double): Double = StrictFastMath.abs(arg) + override inline fun norm(arg: Double): Double = StrictFastMath.abs(arg) - public override inline fun Double.unaryMinus(): Double = -this - public override inline fun Double.plus(b: Double): Double = this + b - public override inline fun Double.minus(b: Double): Double = this - b - public override inline fun Double.times(b: Double): Double = this * b - public override inline fun Double.div(b: Double): Double = this / b + override inline fun Double.unaryMinus(): Double = -this + override inline fun Double.plus(b: Double): Double = this + b + override inline fun Double.minus(b: Double): Double = this - b + override inline fun Double.times(b: Double): Double = this * b + override inline fun Double.div(b: Double): Double = this / b } diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KMathNumber.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KMathNumber.kt index 9c9d07b81..f4386f434 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KMathNumber.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KMathNumber.kt @@ -16,15 +16,15 @@ import space.kscience.kmath.operations.NumericAlgebra * @property algebra The algebra. * @property value The value of this number. */ -public class KMathNumber(public val algebra: A, public override val value: T) : +public class KMathNumber(public val algebra: A, override val value: T) : SConst>(value) where T : Number, A : NumericAlgebra { /** * Returns a string representation of the [value]. */ - public override fun toString(): String = value.toString() + override fun toString(): String = value.toString() /** * Wraps [Number] to [KMathNumber]. */ - public override fun wrap(number: Number): KMathNumber = KMathNumber(algebra, algebra.number(number)) + override fun wrap(number: Number): KMathNumber = KMathNumber(algebra, algebra.number(number)) } diff --git a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt index 28f6cd59e..3a94e8259 100644 --- a/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt +++ b/kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt @@ -25,9 +25,9 @@ public class KotlingradExpression>( public val algebra: A, public val mst: MST, ) : SpecialDifferentiableExpression> { - public override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) + override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) - public override fun derivativeOrNull(symbols: List): KotlingradExpression = + override fun derivativeOrNull(symbols: List): KotlingradExpression = KotlingradExpression( algebra, symbols.map(Symbol::identity) diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt index e94bda12a..7a650df3c 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt @@ -39,20 +39,20 @@ public sealed interface Nd4jArrayAlgebra> : AlgebraND.ndArray: INDArray - public override fun produce(initializer: C.(IntArray) -> T): Nd4jArrayStructure { + override fun produce(initializer: C.(IntArray) -> T): Nd4jArrayStructure { val struct = Nd4j.create(*shape)!!.wrap() struct.indicesIterator().forEach { struct[it] = elementContext.initializer(it) } return struct } @PerformancePitfall - public override fun StructureND.map(transform: C.(T) -> T): Nd4jArrayStructure { + override fun StructureND.map(transform: C.(T) -> T): Nd4jArrayStructure { val newStruct = ndArray.dup().wrap() newStruct.elements().forEach { (idx, value) -> newStruct[idx] = elementContext.transform(value) } return newStruct } - public override fun StructureND.mapIndexed( + override fun StructureND.mapIndexed( transform: C.(index: IntArray, T) -> T, ): Nd4jArrayStructure { val new = Nd4j.create(*this@Nd4jArrayAlgebra.shape).wrap() @@ -60,7 +60,7 @@ public sealed interface Nd4jArrayAlgebra> : AlgebraND, b: StructureND, transform: C.(T, T) -> T, @@ -79,16 +79,16 @@ public sealed interface Nd4jArrayAlgebra> : AlgebraND> : GroupND, Nd4jArrayAlgebra { - public override val zero: Nd4jArrayStructure + override val zero: Nd4jArrayStructure get() = Nd4j.zeros(*shape).wrap() - public override fun add(a: StructureND, b: StructureND): Nd4jArrayStructure = + override fun add(a: StructureND, b: StructureND): Nd4jArrayStructure = a.ndArray.add(b.ndArray).wrap() - public override operator fun StructureND.minus(b: StructureND): Nd4jArrayStructure = + override operator fun StructureND.minus(b: StructureND): Nd4jArrayStructure = ndArray.sub(b.ndArray).wrap() - public override operator fun StructureND.unaryMinus(): Nd4jArrayStructure = + override operator fun StructureND.unaryMinus(): Nd4jArrayStructure = ndArray.neg().wrap() public fun multiply(a: StructureND, k: Number): Nd4jArrayStructure = @@ -104,23 +104,23 @@ public sealed interface Nd4jArrayGroup> : GroupND, Nd4j @OptIn(UnstableKMathAPI::class) public sealed interface Nd4jArrayRing> : RingND, Nd4jArrayGroup { - public override val one: Nd4jArrayStructure + override val one: Nd4jArrayStructure get() = Nd4j.ones(*shape).wrap() - public override fun multiply(a: StructureND, b: StructureND): Nd4jArrayStructure = + override fun multiply(a: StructureND, b: StructureND): Nd4jArrayStructure = a.ndArray.mul(b.ndArray).wrap() // -// public override operator fun Nd4jArrayStructure.minus(b: Number): Nd4jArrayStructure { +// override operator fun Nd4jArrayStructure.minus(b: Number): Nd4jArrayStructure { // check(this) // return ndArray.sub(b).wrap() // } // -// public override operator fun Nd4jArrayStructure.plus(b: Number): Nd4jArrayStructure { +// override operator fun Nd4jArrayStructure.plus(b: Number): Nd4jArrayStructure { // check(this) // return ndArray.add(b).wrap() // } // -// public override operator fun Number.minus(b: Nd4jArrayStructure): Nd4jArrayStructure { +// override operator fun Number.minus(b: Nd4jArrayStructure): Nd4jArrayStructure { // check(b) // return b.ndArray.rsub(this).wrap() // } @@ -153,7 +153,7 @@ public sealed interface Nd4jArrayRing> : RingND, Nd4jAr * @param F the type field of structure elements. */ public sealed interface Nd4jArrayField> : FieldND, Nd4jArrayRing { - public override fun divide(a: StructureND, b: StructureND): Nd4jArrayStructure = + override fun divide(a: StructureND, b: StructureND): Nd4jArrayStructure = a.ndArray.div(b.ndArray).wrap() public operator fun Number.div(b: StructureND): Nd4jArrayStructure = b.ndArray.rdiv(this).wrap() @@ -194,38 +194,38 @@ public sealed interface Nd4jArrayField> : FieldND, Nd4 */ public sealed interface Nd4jArrayExtendedField> : ExtendedField>, Nd4jArrayField { - public override fun sin(arg: StructureND): StructureND = Transforms.sin(arg.ndArray).wrap() - public override fun cos(arg: StructureND): StructureND = Transforms.cos(arg.ndArray).wrap() - public override fun asin(arg: StructureND): StructureND = Transforms.asin(arg.ndArray).wrap() - public override fun acos(arg: StructureND): StructureND = Transforms.acos(arg.ndArray).wrap() - public override fun atan(arg: StructureND): StructureND = Transforms.atan(arg.ndArray).wrap() + override fun sin(arg: StructureND): StructureND = Transforms.sin(arg.ndArray).wrap() + override fun cos(arg: StructureND): StructureND = Transforms.cos(arg.ndArray).wrap() + override fun asin(arg: StructureND): StructureND = Transforms.asin(arg.ndArray).wrap() + override fun acos(arg: StructureND): StructureND = Transforms.acos(arg.ndArray).wrap() + override fun atan(arg: StructureND): StructureND = Transforms.atan(arg.ndArray).wrap() - public override fun power(arg: StructureND, pow: Number): StructureND = + override fun power(arg: StructureND, pow: Number): StructureND = Transforms.pow(arg.ndArray, pow).wrap() - public override fun exp(arg: StructureND): StructureND = Transforms.exp(arg.ndArray).wrap() - public override fun ln(arg: StructureND): StructureND = Transforms.log(arg.ndArray).wrap() - public override fun sqrt(arg: StructureND): StructureND = Transforms.sqrt(arg.ndArray).wrap() - public override fun sinh(arg: StructureND): StructureND = Transforms.sinh(arg.ndArray).wrap() - public override fun cosh(arg: StructureND): StructureND = Transforms.cosh(arg.ndArray).wrap() - public override fun tanh(arg: StructureND): StructureND = Transforms.tanh(arg.ndArray).wrap() + override fun exp(arg: StructureND): StructureND = Transforms.exp(arg.ndArray).wrap() + override fun ln(arg: StructureND): StructureND = Transforms.log(arg.ndArray).wrap() + override fun sqrt(arg: StructureND): StructureND = Transforms.sqrt(arg.ndArray).wrap() + override fun sinh(arg: StructureND): StructureND = Transforms.sinh(arg.ndArray).wrap() + override fun cosh(arg: StructureND): StructureND = Transforms.cosh(arg.ndArray).wrap() + override fun tanh(arg: StructureND): StructureND = Transforms.tanh(arg.ndArray).wrap() - public override fun asinh(arg: StructureND): StructureND = + override fun asinh(arg: StructureND): StructureND = Nd4j.getExecutioner().exec(ASinh(arg.ndArray, arg.ndArray.ulike())).wrap() - public override fun acosh(arg: StructureND): StructureND = + override fun acosh(arg: StructureND): StructureND = Nd4j.getExecutioner().exec(ACosh(arg.ndArray, arg.ndArray.ulike())).wrap() - public override fun atanh(arg: StructureND): StructureND = Transforms.atanh(arg.ndArray).wrap() + override fun atanh(arg: StructureND): StructureND = Transforms.atanh(arg.ndArray).wrap() } /** * Represents [FieldND] over [Nd4jArrayDoubleStructure]. */ -public class DoubleNd4jArrayField(public override val shape: IntArray) : Nd4jArrayExtendedField { - public override val elementContext: DoubleField get() = DoubleField +public class DoubleNd4jArrayField(override val shape: IntArray) : Nd4jArrayExtendedField { + override val elementContext: DoubleField get() = DoubleField - public override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asDoubleStructure() + override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asDoubleStructure() @OptIn(PerformancePitfall::class) override val StructureND.ndArray: INDArray @@ -240,27 +240,27 @@ public class DoubleNd4jArrayField(public override val shape: IntArray) : Nd4jArr return a.ndArray.mul(value).wrap() } - public override operator fun StructureND.div(arg: Double): Nd4jArrayStructure { + override operator fun StructureND.div(arg: Double): Nd4jArrayStructure { return ndArray.div(arg).wrap() } - public override operator fun StructureND.plus(arg: Double): Nd4jArrayStructure { + override operator fun StructureND.plus(arg: Double): Nd4jArrayStructure { return ndArray.add(arg).wrap() } - public override operator fun StructureND.minus(arg: Double): Nd4jArrayStructure { + override operator fun StructureND.minus(arg: Double): Nd4jArrayStructure { return ndArray.sub(arg).wrap() } - public override operator fun StructureND.times(arg: Double): Nd4jArrayStructure { + override operator fun StructureND.times(arg: Double): Nd4jArrayStructure { return ndArray.mul(arg).wrap() } - public override operator fun Double.div(arg: StructureND): Nd4jArrayStructure { + override operator fun Double.div(arg: StructureND): Nd4jArrayStructure { return arg.ndArray.rdiv(this).wrap() } - public override operator fun Double.minus(arg: StructureND): Nd4jArrayStructure { + override operator fun Double.minus(arg: StructureND): Nd4jArrayStructure { return arg.ndArray.rsub(this).wrap() } } @@ -268,13 +268,13 @@ public class DoubleNd4jArrayField(public override val shape: IntArray) : Nd4jArr /** * Represents [FieldND] over [Nd4jArrayStructure] of [Float]. */ -public class FloatNd4jArrayField(public override val shape: IntArray) : Nd4jArrayExtendedField { - public override val elementContext: FloatField get() = FloatField +public class FloatNd4jArrayField(override val shape: IntArray) : Nd4jArrayExtendedField { + override val elementContext: FloatField get() = FloatField - public override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asFloatStructure() + override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asFloatStructure() @OptIn(PerformancePitfall::class) - public override val StructureND.ndArray: INDArray + override val StructureND.ndArray: INDArray get() = when (this) { is Nd4jArrayStructure -> checkShape(ndArray) else -> Nd4j.zeros(*shape).also { @@ -285,36 +285,36 @@ public class FloatNd4jArrayField(public override val shape: IntArray) : Nd4jArra override fun scale(a: StructureND, value: Double): StructureND = a.ndArray.mul(value).wrap() - public override operator fun StructureND.div(arg: Float): Nd4jArrayStructure = + override operator fun StructureND.div(arg: Float): Nd4jArrayStructure = ndArray.div(arg).wrap() - public override operator fun StructureND.plus(arg: Float): Nd4jArrayStructure = + override operator fun StructureND.plus(arg: Float): Nd4jArrayStructure = ndArray.add(arg).wrap() - public override operator fun StructureND.minus(arg: Float): Nd4jArrayStructure = + override operator fun StructureND.minus(arg: Float): Nd4jArrayStructure = ndArray.sub(arg).wrap() - public override operator fun StructureND.times(arg: Float): Nd4jArrayStructure = + override operator fun StructureND.times(arg: Float): Nd4jArrayStructure = ndArray.mul(arg).wrap() - public override operator fun Float.div(arg: StructureND): Nd4jArrayStructure = + override operator fun Float.div(arg: StructureND): Nd4jArrayStructure = arg.ndArray.rdiv(this).wrap() - public override operator fun Float.minus(arg: StructureND): Nd4jArrayStructure = + override operator fun Float.minus(arg: StructureND): Nd4jArrayStructure = arg.ndArray.rsub(this).wrap() } /** * Represents [RingND] over [Nd4jArrayIntStructure]. */ -public class IntNd4jArrayRing(public override val shape: IntArray) : Nd4jArrayRing { - public override val elementContext: IntRing +public class IntNd4jArrayRing(override val shape: IntArray) : Nd4jArrayRing { + override val elementContext: IntRing get() = IntRing - public override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asIntStructure() + override fun INDArray.wrap(): Nd4jArrayStructure = checkShape(this).asIntStructure() @OptIn(PerformancePitfall::class) - public override val StructureND.ndArray: INDArray + override val StructureND.ndArray: INDArray get() = when (this) { is Nd4jArrayStructure -> checkShape(ndArray) else -> Nd4j.zeros(*shape).also { @@ -322,15 +322,15 @@ public class IntNd4jArrayRing(public override val shape: IntArray) : Nd4jArrayRi } } - public override operator fun StructureND.plus(arg: Int): Nd4jArrayStructure = + override operator fun StructureND.plus(arg: Int): Nd4jArrayStructure = ndArray.add(arg).wrap() - public override operator fun StructureND.minus(arg: Int): Nd4jArrayStructure = + override operator fun StructureND.minus(arg: Int): Nd4jArrayStructure = ndArray.sub(arg).wrap() - public override operator fun StructureND.times(arg: Int): Nd4jArrayStructure = + override operator fun StructureND.times(arg: Int): Nd4jArrayStructure = ndArray.mul(arg).wrap() - public override operator fun Int.minus(arg: StructureND): Nd4jArrayStructure = + override operator fun Int.minus(arg: StructureND): Nd4jArrayStructure = arg.ndArray.rsub(this).wrap() } diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt index ffddcef90..97427d5c6 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt @@ -22,13 +22,13 @@ public sealed class Nd4jArrayStructure : MutableStructureND { */ public abstract val ndArray: INDArray - public override val shape: IntArray get() = ndArray.shape().toIntArray() + override val shape: IntArray get() = ndArray.shape().toIntArray() internal abstract fun elementsIterator(): Iterator> internal fun indicesIterator(): Iterator = ndArray.indicesIterator() @PerformancePitfall - public override fun elements(): Sequence> = Sequence(::elementsIterator) + override fun elements(): Sequence> = Sequence(::elementsIterator) } private data class Nd4jArrayIntStructure(override val ndArray: INDArray) : Nd4jArrayStructure() { diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt index 456f7c2a9..0674c565e 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt @@ -33,105 +33,105 @@ public sealed interface Nd4jTensorAlgebra : AnalyticTensorAlgebra */ public val StructureND.ndArray: INDArray - public override fun T.plus(other: Tensor): Tensor = other.ndArray.add(this).wrap() - public override fun Tensor.plus(value: T): Tensor = ndArray.add(value).wrap() + override fun T.plus(other: Tensor): Tensor = other.ndArray.add(this).wrap() + override fun Tensor.plus(value: T): Tensor = ndArray.add(value).wrap() - public override fun Tensor.plus(other: Tensor): Tensor = ndArray.add(other.ndArray).wrap() + override fun Tensor.plus(other: Tensor): Tensor = ndArray.add(other.ndArray).wrap() - public override fun Tensor.plusAssign(value: T) { + override fun Tensor.plusAssign(value: T) { ndArray.addi(value) } - public override fun Tensor.plusAssign(other: Tensor) { + override fun Tensor.plusAssign(other: Tensor) { ndArray.addi(other.ndArray) } - public override fun T.minus(other: Tensor): Tensor = other.ndArray.rsub(this).wrap() - public override fun Tensor.minus(value: T): Tensor = ndArray.sub(value).wrap() - public override fun Tensor.minus(other: Tensor): Tensor = ndArray.sub(other.ndArray).wrap() + override fun T.minus(other: Tensor): Tensor = other.ndArray.rsub(this).wrap() + override fun Tensor.minus(value: T): Tensor = ndArray.sub(value).wrap() + override fun Tensor.minus(other: Tensor): Tensor = ndArray.sub(other.ndArray).wrap() - public override fun Tensor.minusAssign(value: T) { + override fun Tensor.minusAssign(value: T) { ndArray.rsubi(value) } - public override fun Tensor.minusAssign(other: Tensor) { + override fun Tensor.minusAssign(other: Tensor) { ndArray.subi(other.ndArray) } - public override fun T.times(other: Tensor): Tensor = other.ndArray.mul(this).wrap() + override fun T.times(other: Tensor): Tensor = other.ndArray.mul(this).wrap() - public override fun Tensor.times(value: T): Tensor = + override fun Tensor.times(value: T): Tensor = ndArray.mul(value).wrap() - public override fun Tensor.times(other: Tensor): Tensor = ndArray.mul(other.ndArray).wrap() + override fun Tensor.times(other: Tensor): Tensor = ndArray.mul(other.ndArray).wrap() - public override fun Tensor.timesAssign(value: T) { + override fun Tensor.timesAssign(value: T) { ndArray.muli(value) } - public override fun Tensor.timesAssign(other: Tensor) { + override fun Tensor.timesAssign(other: Tensor) { ndArray.mmuli(other.ndArray) } - public override fun Tensor.unaryMinus(): Tensor = ndArray.neg().wrap() - public override fun Tensor.get(i: Int): Tensor = ndArray.slice(i.toLong()).wrap() - public override fun Tensor.transpose(i: Int, j: Int): Tensor = ndArray.swapAxes(i, j).wrap() - public override fun Tensor.dot(other: Tensor): Tensor = ndArray.mmul(other.ndArray).wrap() + override fun Tensor.unaryMinus(): Tensor = ndArray.neg().wrap() + override fun Tensor.get(i: Int): Tensor = ndArray.slice(i.toLong()).wrap() + override fun Tensor.transpose(i: Int, j: Int): Tensor = ndArray.swapAxes(i, j).wrap() + override fun Tensor.dot(other: Tensor): Tensor = ndArray.mmul(other.ndArray).wrap() - public override fun Tensor.min(dim: Int, keepDim: Boolean): Tensor = + override fun Tensor.min(dim: Int, keepDim: Boolean): Tensor = ndArray.min(keepDim, dim).wrap() - public override fun Tensor.sum(dim: Int, keepDim: Boolean): Tensor = + override fun Tensor.sum(dim: Int, keepDim: Boolean): Tensor = ndArray.sum(keepDim, dim).wrap() - public override fun Tensor.max(dim: Int, keepDim: Boolean): Tensor = + override fun Tensor.max(dim: Int, keepDim: Boolean): Tensor = ndArray.max(keepDim, dim).wrap() - public override fun Tensor.view(shape: IntArray): Tensor = ndArray.reshape(shape).wrap() - public override fun Tensor.viewAs(other: Tensor): Tensor = view(other.shape) + override fun Tensor.view(shape: IntArray): Tensor = ndArray.reshape(shape).wrap() + override fun Tensor.viewAs(other: Tensor): Tensor = view(other.shape) - public override fun Tensor.argMax(dim: Int, keepDim: Boolean): Tensor = + override fun Tensor.argMax(dim: Int, keepDim: Boolean): Tensor = ndBase.get().argmax(ndArray, keepDim, dim).wrap() - public override fun Tensor.mean(dim: Int, keepDim: Boolean): Tensor = ndArray.mean(keepDim, dim).wrap() + override fun Tensor.mean(dim: Int, keepDim: Boolean): Tensor = ndArray.mean(keepDim, dim).wrap() - public override fun Tensor.exp(): Tensor = Transforms.exp(ndArray).wrap() - public override fun Tensor.ln(): Tensor = Transforms.log(ndArray).wrap() - public override fun Tensor.sqrt(): Tensor = Transforms.sqrt(ndArray).wrap() - public override fun Tensor.cos(): Tensor = Transforms.cos(ndArray).wrap() - public override fun Tensor.acos(): Tensor = Transforms.acos(ndArray).wrap() - public override fun Tensor.cosh(): Tensor = Transforms.cosh(ndArray).wrap() + override fun Tensor.exp(): Tensor = Transforms.exp(ndArray).wrap() + override fun Tensor.ln(): Tensor = Transforms.log(ndArray).wrap() + override fun Tensor.sqrt(): Tensor = Transforms.sqrt(ndArray).wrap() + override fun Tensor.cos(): Tensor = Transforms.cos(ndArray).wrap() + override fun Tensor.acos(): Tensor = Transforms.acos(ndArray).wrap() + override fun Tensor.cosh(): Tensor = Transforms.cosh(ndArray).wrap() - public override fun Tensor.acosh(): Tensor = + override fun Tensor.acosh(): Tensor = Nd4j.getExecutioner().exec(ACosh(ndArray, ndArray.ulike())).wrap() - public override fun Tensor.sin(): Tensor = Transforms.sin(ndArray).wrap() - public override fun Tensor.asin(): Tensor = Transforms.asin(ndArray).wrap() - public override fun Tensor.sinh(): Tensor = Transforms.sinh(ndArray).wrap() + override fun Tensor.sin(): Tensor = Transforms.sin(ndArray).wrap() + override fun Tensor.asin(): Tensor = Transforms.asin(ndArray).wrap() + override fun Tensor.sinh(): Tensor = Transforms.sinh(ndArray).wrap() - public override fun Tensor.asinh(): Tensor = + override fun Tensor.asinh(): Tensor = Nd4j.getExecutioner().exec(ASinh(ndArray, ndArray.ulike())).wrap() - public override fun Tensor.tan(): Tensor = Transforms.tan(ndArray).wrap() - public override fun Tensor.atan(): Tensor = Transforms.atan(ndArray).wrap() - public override fun Tensor.tanh(): Tensor = Transforms.tanh(ndArray).wrap() - public override fun Tensor.atanh(): Tensor = Transforms.atanh(ndArray).wrap() - public override fun Tensor.ceil(): Tensor = Transforms.ceil(ndArray).wrap() - public override fun Tensor.floor(): Tensor = Transforms.floor(ndArray).wrap() - public override fun Tensor.std(dim: Int, keepDim: Boolean): Tensor = ndArray.std(true, keepDim, dim).wrap() - public override fun T.div(other: Tensor): Tensor = other.ndArray.rdiv(this).wrap() - public override fun Tensor.div(value: T): Tensor = ndArray.div(value).wrap() - public override fun Tensor.div(other: Tensor): Tensor = ndArray.div(other.ndArray).wrap() + override fun Tensor.tan(): Tensor = Transforms.tan(ndArray).wrap() + override fun Tensor.atan(): Tensor = Transforms.atan(ndArray).wrap() + override fun Tensor.tanh(): Tensor = Transforms.tanh(ndArray).wrap() + override fun Tensor.atanh(): Tensor = Transforms.atanh(ndArray).wrap() + override fun Tensor.ceil(): Tensor = Transforms.ceil(ndArray).wrap() + override fun Tensor.floor(): Tensor = Transforms.floor(ndArray).wrap() + override fun Tensor.std(dim: Int, keepDim: Boolean): Tensor = ndArray.std(true, keepDim, dim).wrap() + override fun T.div(other: Tensor): Tensor = other.ndArray.rdiv(this).wrap() + override fun Tensor.div(value: T): Tensor = ndArray.div(value).wrap() + override fun Tensor.div(other: Tensor): Tensor = ndArray.div(other.ndArray).wrap() - public override fun Tensor.divAssign(value: T) { + override fun Tensor.divAssign(value: T) { ndArray.divi(value) } - public override fun Tensor.divAssign(other: Tensor) { + override fun Tensor.divAssign(other: Tensor) { ndArray.divi(other.ndArray) } - public override fun Tensor.variance(dim: Int, keepDim: Boolean): Tensor = + override fun Tensor.variance(dim: Int, keepDim: Boolean): Tensor = Nd4j.getExecutioner().exec(Variance(ndArray, true, true, dim)).wrap() private companion object { @@ -143,10 +143,10 @@ public sealed interface Nd4jTensorAlgebra : AnalyticTensorAlgebra * [Double] specialization of [Nd4jTensorAlgebra]. */ public object DoubleNd4jTensorAlgebra : Nd4jTensorAlgebra { - public override fun INDArray.wrap(): Nd4jArrayStructure = asDoubleStructure() + override fun INDArray.wrap(): Nd4jArrayStructure = asDoubleStructure() @OptIn(PerformancePitfall::class) - public override val StructureND.ndArray: INDArray + override val StructureND.ndArray: INDArray get() = when (this) { is Nd4jArrayStructure -> ndArray else -> Nd4j.zeros(*shape).also { @@ -154,22 +154,22 @@ public object DoubleNd4jTensorAlgebra : Nd4jTensorAlgebra { } } - public override fun Tensor.valueOrNull(): Double? = + override fun Tensor.valueOrNull(): Double? = if (shape contentEquals intArrayOf(1)) ndArray.getDouble(0) else null // TODO rewrite @PerformancePitfall - public override fun diagonalEmbedding( + override fun diagonalEmbedding( diagonalEntries: Tensor, offset: Int, dim1: Int, dim2: Int, ): Tensor = DoubleTensorAlgebra.diagonalEmbedding(diagonalEntries, offset, dim1, dim2) - public override fun Tensor.sum(): Double = ndArray.sumNumber().toDouble() - public override fun Tensor.min(): Double = ndArray.minNumber().toDouble() - public override fun Tensor.max(): Double = ndArray.maxNumber().toDouble() - public override fun Tensor.mean(): Double = ndArray.meanNumber().toDouble() - public override fun Tensor.std(): Double = ndArray.stdNumber().toDouble() - public override fun Tensor.variance(): Double = ndArray.varNumber().toDouble() + override fun Tensor.sum(): Double = ndArray.sumNumber().toDouble() + override fun Tensor.min(): Double = ndArray.minNumber().toDouble() + override fun Tensor.max(): Double = ndArray.maxNumber().toDouble() + override fun Tensor.mean(): Double = ndArray.meanNumber().toDouble() + override fun Tensor.std(): Double = ndArray.stdNumber().toDouble() + override fun Tensor.variance(): Double = ndArray.varNumber().toDouble() } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/Distribution.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/Distribution.kt index e3adcdc44..5a74a9a18 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/Distribution.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/Distribution.kt @@ -19,7 +19,7 @@ public interface Distribution : Sampler { */ public fun probability(arg: T): Double - public override fun sample(generator: RandomGenerator): Chain + override fun sample(generator: RandomGenerator): Chain /** * An empty companion. Distribution factories should be written as its extensions diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/NormalDistribution.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/NormalDistribution.kt index 04ec8b171..66e041f05 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/NormalDistribution.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/NormalDistribution.kt @@ -23,14 +23,14 @@ public class NormalDistribution(public val sampler: GaussianSampler) : Univariat normalized: NormalizedGaussianSampler = ZigguratNormalizedGaussianSampler, ) : this(GaussianSampler(mean, standardDeviation, normalized)) - public override fun probability(arg: Double): Double { + override fun probability(arg: Double): Double { val x1 = (arg - sampler.mean) / sampler.standardDeviation return exp(-0.5 * x1 * x1 - (ln(sampler.standardDeviation) + 0.5 * ln(2 * PI))) } - public override fun sample(generator: RandomGenerator): Chain = sampler.sample(generator) + override fun sample(generator: RandomGenerator): Chain = sampler.sample(generator) - public override fun cumulative(arg: Double): Double { + override fun cumulative(arg: Double): Double { val dev = arg - sampler.mean return when { diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterExponentialSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterExponentialSampler.kt index a231842df..77d29981f 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterExponentialSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterExponentialSampler.kt @@ -24,7 +24,7 @@ public class AhrensDieterExponentialSampler(public val mean: Double) : Sampler 0) { "mean is not strictly positive: $mean" } } - public override fun sample(generator: RandomGenerator): BlockingDoubleChain = object : BlockingDoubleChain { + override fun sample(generator: RandomGenerator): BlockingDoubleChain = object : BlockingDoubleChain { override fun nextBlocking(): Double { // Step 1: var a = 0.0 diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt index 2f32eee85..93605c7d8 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt @@ -113,8 +113,8 @@ public class AhrensDieterMarsagliaTsangGammaSampler private constructor( } } - public override fun sample(generator: RandomGenerator): Chain = delegate.sample(generator) - public override fun toString(): String = delegate.toString() + override fun sample(generator: RandomGenerator): Chain = delegate.sample(generator) + override fun toString(): String = delegate.toString() public companion object { public fun of( diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt index db4f598b7..36ddd3c8e 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt @@ -76,7 +76,7 @@ public open class AliasMethodDiscreteSampler private constructor( } } - public override fun sample(generator: RandomGenerator): Chain = generator.chain { + override fun sample(generator: RandomGenerator): Chain = generator.chain { // This implements the algorithm as per Vose (1991): // v = uniform() in [0, 1) // j = uniform(n) in [0, n) @@ -107,7 +107,7 @@ public open class AliasMethodDiscreteSampler private constructor( if (generator.nextLong() ushr 11 < probability[j]) j else alias[j] } - public override fun toString(): String = "Alias method" + override fun toString(): String = "Alias method" public companion object { private const val DEFAULT_ALPHA = 0 diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/GaussianSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/GaussianSampler.kt index d7d8e87b7..9219df43e 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/GaussianSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/GaussianSampler.kt @@ -28,7 +28,7 @@ public class GaussianSampler( require(standardDeviation > 0.0) { "standard deviation is not strictly positive: $standardDeviation" } } - public override fun sample(generator: RandomGenerator): BlockingDoubleChain = normalized + override fun sample(generator: RandomGenerator): BlockingDoubleChain = normalized .sample(generator) .map { standardDeviation * it + mean } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt index 9bb48fe4e..14737decb 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt @@ -27,7 +27,7 @@ public class KempSmallMeanPoissonSampler internal constructor( private val p0: Double, private val mean: Double, ) : Sampler { - public override fun sample(generator: RandomGenerator): BlockingIntChain = object : BlockingIntChain { + override fun sample(generator: RandomGenerator): BlockingIntChain = object : BlockingIntChain { override fun nextBlocking(): Int { //TODO move to nextBufferBlocking // Note on the algorithm: @@ -60,7 +60,7 @@ public class KempSmallMeanPoissonSampler internal constructor( override suspend fun fork(): BlockingIntChain = sample(generator.fork()) } - public override fun toString(): String = "Kemp Small Mean Poisson deviate" + override fun toString(): String = "Kemp Small Mean Poisson deviate" } public fun KempSmallMeanPoissonSampler(mean: Double): KempSmallMeanPoissonSampler { diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt index e95778b9e..2177e41ab 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt @@ -58,7 +58,7 @@ public class SmallMeanPoissonSampler(public val mean: Double) : Sampler { throw IllegalArgumentException("No p(x=0) probability for mean: $mean") }.toInt() - public override fun sample(generator: RandomGenerator): BlockingIntChain = object : BlockingIntChain { + override fun sample(generator: RandomGenerator): BlockingIntChain = object : BlockingIntChain { override fun nextBlocking(): Int { var n = 0 var r = 1.0 @@ -76,7 +76,7 @@ public class SmallMeanPoissonSampler(public val mean: Double) : Sampler { override suspend fun fork(): BlockingIntChain = sample(generator.fork()) } - public override fun toString(): String = "Small Mean Poisson deviate" + override fun toString(): String = "Small Mean Poisson deviate" } @@ -113,7 +113,7 @@ public class LargeMeanPoissonSampler(public val mean: Double) : Sampler { private val p1: Double = a1 / aSum private val p2: Double = a2 / aSum - public override fun sample(generator: RandomGenerator): BlockingIntChain = object : BlockingIntChain { + override fun sample(generator: RandomGenerator): BlockingIntChain = object : BlockingIntChain { override fun nextBlocking(): Int { val exponential = AhrensDieterExponentialSampler(1.0).sample(generator) val gaussian = ZigguratNormalizedGaussianSampler.sample(generator) @@ -197,7 +197,7 @@ public class LargeMeanPoissonSampler(public val mean: Double) : Sampler { } private fun getFactorialLog(n: Int): Double = factorialLog.value(n) - public override fun toString(): String = "Large Mean Poisson deviate" + override fun toString(): String = "Large Mean Poisson deviate" public companion object { private const val MAX_MEAN: Double = 0.5 * Int.MAX_VALUE diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt index 9769146fb..ac2c2098f 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt @@ -27,13 +27,13 @@ public class Mean( override suspend fun evaluate(data: Buffer): T = super.evaluate(data) - public override suspend fun computeIntermediate(data: Buffer): Pair = + override suspend fun computeIntermediate(data: Buffer): Pair = evaluateBlocking(data) to data.size - public override suspend fun composeIntermediate(first: Pair, second: Pair): Pair = + override suspend fun composeIntermediate(first: Pair, second: Pair): Pair = group { first.first + second.first } to (first.second + second.second) - public override suspend fun toResult(intermediate: Pair): T = group { + override suspend fun toResult(intermediate: Pair): T = group { division(intermediate.first, intermediate.second) } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Median.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Median.kt index 70754eab7..2cc867fb2 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Median.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Median.kt @@ -12,7 +12,7 @@ import space.kscience.kmath.structures.asSequence * Non-composable median */ public class Median(private val comparator: Comparator) : BlockingStatistic { - public override fun evaluateBlocking(data: Buffer): T = + override fun evaluateBlocking(data: Buffer): T = data.asSequence().sortedWith(comparator).toList()[data.size / 2] //TODO check if this is correct public companion object { diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomChain.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomChain.kt index 5041e7359..d4bc36b5b 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomChain.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomChain.kt @@ -31,7 +31,7 @@ public fun RandomGenerator.chain(generator: suspend RandomGenerator.() -> R) * A type-specific double chunk random chain */ public class UniformDoubleChain(public val generator: RandomGenerator) : BlockingDoubleChain { - public override fun nextBufferBlocking(size: Int): DoubleBuffer = generator.nextDoubleBuffer(size) + override fun nextBufferBlocking(size: Int): DoubleBuffer = generator.nextDoubleBuffer(size) override suspend fun nextBuffer(size: Int): DoubleBuffer = nextBufferBlocking(size) override suspend fun fork(): UniformDoubleChain = UniformDoubleChain(generator.fork()) diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomGenerator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomGenerator.kt index 3ff12f383..5698f1a79 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomGenerator.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomGenerator.kt @@ -97,17 +97,17 @@ public interface RandomGenerator { * @property random the underlying [Random] object. */ public class DefaultGenerator(public val random: Random = Random) : RandomGenerator { - public override fun nextBoolean(): Boolean = random.nextBoolean() - public override fun nextDouble(): Double = random.nextDouble() - public override fun nextInt(): Int = random.nextInt() - public override fun nextInt(until: Int): Int = random.nextInt(until) - public override fun nextLong(): Long = random.nextLong() - public override fun nextLong(until: Long): Long = random.nextLong(until) + override fun nextBoolean(): Boolean = random.nextBoolean() + override fun nextDouble(): Double = random.nextDouble() + override fun nextInt(): Int = random.nextInt() + override fun nextInt(until: Int): Int = random.nextInt(until) + override fun nextLong(): Long = random.nextLong() + override fun nextLong(until: Long): Long = random.nextLong(until) - public override fun fillBytes(array: ByteArray, fromIndex: Int, toIndex: Int) { + override fun fillBytes(array: ByteArray, fromIndex: Int, toIndex: Int) { random.nextBytes(array, fromIndex, toIndex) } - public override fun nextBytes(size: Int): ByteArray = random.nextBytes(size) - public override fun fork(): RandomGenerator = RandomGenerator.default(random.nextLong()) + override fun nextBytes(size: Int): ByteArray = random.nextBytes(size) + override fun fork(): RandomGenerator = RandomGenerator.default(random.nextLong()) } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt index 27465eff4..849cf152a 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt @@ -19,7 +19,7 @@ import space.kscience.kmath.operations.invoke * @property value the value to sample. */ public class ConstantSampler(public val value: T) : Sampler { - public override fun sample(generator: RandomGenerator): Chain = ConstantChain(value) + override fun sample(generator: RandomGenerator): Chain = ConstantChain(value) } /** @@ -28,7 +28,7 @@ public class ConstantSampler(public val value: T) : Sampler { * @property chainBuilder the provider of [Chain]. */ public class BasicSampler(public val chainBuilder: (RandomGenerator) -> Chain) : Sampler { - public override fun sample(generator: RandomGenerator): Chain = chainBuilder(generator) + override fun sample(generator: RandomGenerator): Chain = chainBuilder(generator) } /** @@ -39,17 +39,17 @@ public class BasicSampler(public val chainBuilder: (RandomGenerator public class SamplerSpace(public val algebra: S) : Group>, ScaleOperations> where S : Group, S : ScaleOperations { - public override val zero: Sampler = ConstantSampler(algebra.zero) + override val zero: Sampler = ConstantSampler(algebra.zero) - public override fun add(a: Sampler, b: Sampler): Sampler = BasicSampler { generator -> + override fun add(a: Sampler, b: Sampler): Sampler = BasicSampler { generator -> a.sample(generator).zip(b.sample(generator)) { aValue, bValue -> algebra { aValue + bValue } } } - public override fun scale(a: Sampler, value: Double): Sampler = BasicSampler { generator -> + override fun scale(a: Sampler, value: Double): Sampler = BasicSampler { generator -> a.sample(generator).map { a -> algebra { a * value } } } - public override fun Sampler.unaryMinus(): Sampler = scale(this, -1.0) + override fun Sampler.unaryMinus(): Sampler = scale(this, -1.0) } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt index f29b7415c..499dcac6a 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt @@ -44,7 +44,7 @@ public interface ComposableStatistic : Statistic { //Transform block to result public suspend fun toResult(intermediate: I): R - public override suspend fun evaluate(data: Buffer): R = toResult(computeIntermediate(data)) + override suspend fun evaluate(data: Buffer): R = toResult(computeIntermediate(data)) } @FlowPreview diff --git a/kmath-stat/src/jvmMain/kotlin/space/kscience/kmath/stat/RandomSourceGenerator.kt b/kmath-stat/src/jvmMain/kotlin/space/kscience/kmath/stat/RandomSourceGenerator.kt index 1ff6481ac..7aaac7d32 100644 --- a/kmath-stat/src/jvmMain/kotlin/space/kscience/kmath/stat/RandomSourceGenerator.kt +++ b/kmath-stat/src/jvmMain/kotlin/space/kscience/kmath/stat/RandomSourceGenerator.kt @@ -17,19 +17,19 @@ public class RandomSourceGenerator internal constructor(public val source: Rando internal val random: UniformRandomProvider = seed?.let { RandomSource.create(source, seed) } ?: RandomSource.create(source) - public override fun nextBoolean(): Boolean = random.nextBoolean() - public override fun nextDouble(): Double = random.nextDouble() - public override fun nextInt(): Int = random.nextInt() - public override fun nextInt(until: Int): Int = random.nextInt(until) - public override fun nextLong(): Long = random.nextLong() - public override fun nextLong(until: Long): Long = random.nextLong(until) + override fun nextBoolean(): Boolean = random.nextBoolean() + override fun nextDouble(): Double = random.nextDouble() + override fun nextInt(): Int = random.nextInt() + override fun nextInt(until: Int): Int = random.nextInt(until) + override fun nextLong(): Long = random.nextLong() + override fun nextLong(until: Long): Long = random.nextLong(until) - public override fun fillBytes(array: ByteArray, fromIndex: Int, toIndex: Int) { + override fun fillBytes(array: ByteArray, fromIndex: Int, toIndex: Int) { require(toIndex > fromIndex) random.nextBytes(array, fromIndex, toIndex - fromIndex) } - public override fun fork(): RandomGenerator = RandomSourceGenerator(source, nextLong()) + override fun fork(): RandomGenerator = RandomSourceGenerator(source, nextLong()) } /** @@ -43,14 +43,14 @@ public class RandomGeneratorProvider(public val generator: RandomGenerator) : Un * * @return the next random value. */ - public override fun nextBoolean(): Boolean = generator.nextBoolean() + override fun nextBoolean(): Boolean = generator.nextBoolean() /** * Generates a [Float] value between 0 and 1. * * @return the next random value between 0 and 1. */ - public override fun nextFloat(): Float = generator.nextDouble().toFloat() + override fun nextFloat(): Float = generator.nextDouble().toFloat() /** * Generates [Byte] values and places them into a user-supplied array. @@ -59,7 +59,7 @@ public class RandomGeneratorProvider(public val generator: RandomGenerator) : Un * * @param bytes byte array in which to put the random bytes. */ - public override fun nextBytes(bytes: ByteArray): Unit = generator.fillBytes(bytes) + override fun nextBytes(bytes: ByteArray): Unit = generator.fillBytes(bytes) /** * Generates [Byte] values and places them into a user-supplied array. @@ -71,7 +71,7 @@ public class RandomGeneratorProvider(public val generator: RandomGenerator) : Un * @param start the index at which to start inserting the generated bytes. * @param len the number of bytes to insert. */ - public override fun nextBytes(bytes: ByteArray, start: Int, len: Int) { + override fun nextBytes(bytes: ByteArray, start: Int, len: Int) { generator.fillBytes(bytes, start, start + len) } @@ -80,7 +80,7 @@ public class RandomGeneratorProvider(public val generator: RandomGenerator) : Un * * @return the next random value. */ - public override fun nextInt(): Int = generator.nextInt() + override fun nextInt(): Int = generator.nextInt() /** * Generates an [Int] value between 0 (inclusive) and the specified value (exclusive). @@ -88,21 +88,21 @@ public class RandomGeneratorProvider(public val generator: RandomGenerator) : Un * @param n the bound on the random number to be returned. Must be positive. * @return a random integer between 0 (inclusive) and [n] (exclusive). */ - public override fun nextInt(n: Int): Int = generator.nextInt(n) + override fun nextInt(n: Int): Int = generator.nextInt(n) /** * Generates a [Double] value between 0 and 1. * * @return the next random value between 0 and 1. */ - public override fun nextDouble(): Double = generator.nextDouble() + override fun nextDouble(): Double = generator.nextDouble() /** * Generates a [Long] value. * * @return the next random value. */ - public override fun nextLong(): Long = generator.nextLong() + override fun nextLong(): Long = generator.nextLong() /** * Generates a [Long] value between 0 (inclusive) and the specified value (exclusive). @@ -110,7 +110,7 @@ public class RandomGeneratorProvider(public val generator: RandomGenerator) : Un * @param n Bound on the random number to be returned. Must be positive. * @return a random long value between 0 (inclusive) and [n] (exclusive). */ - public override fun nextLong(n: Long): Long = generator.nextLong(n) + override fun nextLong(n: Long): Long = generator.nextLong(n) } /** diff --git a/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt index 88f0c941e..3067b5efb 100644 --- a/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt +++ b/kmath-symja/src/main/kotlin/space/kscience/kmath/symja/SymjaExpression.kt @@ -30,9 +30,9 @@ public class SymjaExpression>( public val mst: MST, public val evaluator: ExprEvaluator = DEFAULT_EVALUATOR, ) : SpecialDifferentiableExpression> { - public override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) + override fun invoke(arguments: Map): T = mst.interpret(algebra, arguments) - public override fun derivativeOrNull(symbols: List): SymjaExpression = SymjaExpression( + override fun derivativeOrNull(symbols: List): SymjaExpression = SymjaExpression( algebra, symbols.map(Symbol::toIExpr).fold(mst.toIExpr(), F::D).toMst(evaluator), evaluator, diff --git a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorBuffer.kt b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorBuffer.kt index bbf502faf..c7f45c6da 100644 --- a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorBuffer.kt +++ b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorBuffer.kt @@ -10,15 +10,15 @@ import space.kscience.kmath.structures.MutableBuffer @Suppress("NOTHING_TO_INLINE", "OVERRIDE_BY_INLINE") public class ViktorBuffer(public val flatArray: F64FlatArray) : MutableBuffer { - public override val size: Int + override val size: Int get() = flatArray.size - public override inline fun get(index: Int): Double = flatArray[index] + override inline fun get(index: Int): Double = flatArray[index] - public override inline fun set(index: Int, value: Double) { + override inline fun set(index: Int, value: Double) { flatArray[index] = value } - public override fun copy(): MutableBuffer = ViktorBuffer(flatArray.copy().flatten()) - public override operator fun iterator(): Iterator = flatArray.data.iterator() + override fun copy(): MutableBuffer = ViktorBuffer(flatArray.copy().flatten()) + override operator fun iterator(): Iterator = flatArray.data.iterator() } diff --git a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt index 915637e2c..2be964017 100644 --- a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt +++ b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt @@ -16,16 +16,16 @@ import space.kscience.kmath.operations.ScaleOperations @Suppress("OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") public class ViktorStructureND(public val f64Buffer: F64Array) : MutableStructureND { - public override val shape: IntArray get() = f64Buffer.shape + override val shape: IntArray get() = f64Buffer.shape - public override inline fun get(index: IntArray): Double = f64Buffer.get(*index) + override inline fun get(index: IntArray): Double = f64Buffer.get(*index) - public override inline fun set(index: IntArray, value: Double) { + override inline fun set(index: IntArray, value: Double) { f64Buffer.set(*index, value = value) } @PerformancePitfall - public override fun elements(): Sequence> = + override fun elements(): Sequence> = DefaultStrides(shape).indices().map { it to get(it) } } @@ -33,7 +33,7 @@ public fun F64Array.asStructure(): ViktorStructureND = ViktorStructureND(this) @OptIn(UnstableKMathAPI::class) @Suppress("OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE") -public class ViktorFieldND(public override val shape: IntArray) : FieldND, +public class ViktorFieldND(override val shape: IntArray) : FieldND, NumbersAddOperations>, ExtendedField>, ScaleOperations> { @@ -47,30 +47,30 @@ public class ViktorFieldND(public override val shape: IntArray) : FieldND produce { this@f64Buffer[it] }.f64Buffer } - public override val zero: ViktorStructureND by lazy { F64Array.full(init = 0.0, shape = shape).asStructure() } - public override val one: ViktorStructureND by lazy { F64Array.full(init = 1.0, shape = shape).asStructure() } + override val zero: ViktorStructureND by lazy { F64Array.full(init = 0.0, shape = shape).asStructure() } + override val one: ViktorStructureND by lazy { F64Array.full(init = 1.0, shape = shape).asStructure() } private val strides: Strides = DefaultStrides(shape) - public override val elementContext: DoubleField get() = DoubleField + override val elementContext: DoubleField get() = DoubleField - public override fun produce(initializer: DoubleField.(IntArray) -> Double): ViktorStructureND = + override fun produce(initializer: DoubleField.(IntArray) -> Double): ViktorStructureND = F64Array(*shape).apply { this@ViktorFieldND.strides.indices().forEach { index -> set(value = DoubleField.initializer(index), indices = index) } }.asStructure() - public override fun StructureND.unaryMinus(): StructureND = -1 * this + override fun StructureND.unaryMinus(): StructureND = -1 * this - public override fun StructureND.map(transform: DoubleField.(Double) -> Double): ViktorStructureND = + override fun StructureND.map(transform: DoubleField.(Double) -> Double): ViktorStructureND = F64Array(*this@ViktorFieldND.shape).apply { this@ViktorFieldND.strides.indices().forEach { index -> set(value = DoubleField.transform(this@map[index]), indices = index) } }.asStructure() - public override fun StructureND.mapIndexed( + override fun StructureND.mapIndexed( transform: DoubleField.(index: IntArray, Double) -> Double, ): ViktorStructureND = F64Array(*this@ViktorFieldND.shape).apply { this@ViktorFieldND.strides.indices().forEach { index -> @@ -78,7 +78,7 @@ public class ViktorFieldND(public override val shape: IntArray) : FieldND, b: StructureND, transform: DoubleField.(Double, Double) -> Double, @@ -88,39 +88,39 @@ public class ViktorFieldND(public override val shape: IntArray) : FieldND, b: StructureND): ViktorStructureND = + override fun add(a: StructureND, b: StructureND): ViktorStructureND = (a.f64Buffer + b.f64Buffer).asStructure() - public override fun scale(a: StructureND, value: Double): ViktorStructureND = + override fun scale(a: StructureND, value: Double): ViktorStructureND = (a.f64Buffer * value).asStructure() - public override inline fun StructureND.plus(b: StructureND): ViktorStructureND = + override inline fun StructureND.plus(b: StructureND): ViktorStructureND = (f64Buffer + b.f64Buffer).asStructure() - public override inline fun StructureND.minus(b: StructureND): ViktorStructureND = + override inline fun StructureND.minus(b: StructureND): ViktorStructureND = (f64Buffer - b.f64Buffer).asStructure() - public override inline fun StructureND.times(k: Number): ViktorStructureND = + override inline fun StructureND.times(k: Number): ViktorStructureND = (f64Buffer * k.toDouble()).asStructure() - public override inline fun StructureND.plus(arg: Double): ViktorStructureND = + override inline fun StructureND.plus(arg: Double): ViktorStructureND = (f64Buffer.plus(arg)).asStructure() - public override fun number(value: Number): ViktorStructureND = + override fun number(value: Number): ViktorStructureND = F64Array.full(init = value.toDouble(), shape = shape).asStructure() - public override fun sin(arg: StructureND): ViktorStructureND = arg.map { sin(it) } - public override fun cos(arg: StructureND): ViktorStructureND = arg.map { cos(it) } - public override fun tan(arg: StructureND): ViktorStructureND = arg.map { tan(it) } - public override fun asin(arg: StructureND): ViktorStructureND = arg.map { asin(it) } - public override fun acos(arg: StructureND): ViktorStructureND = arg.map { acos(it) } - public override fun atan(arg: StructureND): ViktorStructureND = arg.map { atan(it) } + override fun sin(arg: StructureND): ViktorStructureND = arg.map { sin(it) } + override fun cos(arg: StructureND): ViktorStructureND = arg.map { cos(it) } + override fun tan(arg: StructureND): ViktorStructureND = arg.map { tan(it) } + override fun asin(arg: StructureND): ViktorStructureND = arg.map { asin(it) } + override fun acos(arg: StructureND): ViktorStructureND = arg.map { acos(it) } + override fun atan(arg: StructureND): ViktorStructureND = arg.map { atan(it) } - public override fun power(arg: StructureND, pow: Number): ViktorStructureND = arg.map { it.pow(pow) } + override fun power(arg: StructureND, pow: Number): ViktorStructureND = arg.map { it.pow(pow) } - public override fun exp(arg: StructureND): ViktorStructureND = arg.f64Buffer.exp().asStructure() + override fun exp(arg: StructureND): ViktorStructureND = arg.f64Buffer.exp().asStructure() - public override fun ln(arg: StructureND): ViktorStructureND = arg.f64Buffer.log().asStructure() + override fun ln(arg: StructureND): ViktorStructureND = arg.f64Buffer.log().asStructure() } public fun ViktorNDField(vararg shape: Int): ViktorFieldND = ViktorFieldND(shape) From bc2841295027760a1d8110df7fbda04c84c47810 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Wed, 21 Jul 2021 00:00:35 +0700 Subject: [PATCH 089/132] Update publish.yml --- .github/workflows/build.yml | 8 ++++---- .github/workflows/publish.yml | 10 ++++++---- 2 files changed, 10 insertions(+), 8 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 2b611a46a..2eb9f34b3 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -2,9 +2,7 @@ name: Gradle build on: push: - branches: - - dev - - master + branches: [ dev, master ] pull_request: jobs: @@ -26,7 +24,9 @@ jobs: - name: Cache gradle uses: actions/cache@v2 with: - path: ~/.gradle/caches + path: | + ~/.gradle/caches + ~/.gradle/wrapper key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }} restore-keys: | ${{ runner.os }}-gradle- diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index d1698d79b..13bbabbc9 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -42,11 +42,13 @@ jobs: if: matrix.os == 'windows-latest' run: > ./gradlew release --no-daemon -Ppublishing.enabled=true - -Ppublishing.space.user=${{ secrets.PUBLISHING_SPACE_USER }} - -Ppublishing.space.token=${{ secrets.PUBLISHING_SPACE_TOKEN }} + -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }} + -Ppublishing.space.token=${{ secrets.SPACE_APP_SECRET }} + -Ppublishing.sonatype=false - name: Publish Mac Artifacts if: matrix.os == 'macOS-latest' run: > ./gradlew release --no-daemon -Ppublishing.enabled=true -Ppublishing.platform=macosX64 - -Ppublishing.space.user=${{ secrets.PUBLISHING_SPACE_USER }} - -Ppublishing.space.token=${{ secrets.PUBLISHING_SPACE_TOKEN }} + -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }} + -Ppublishing.space.token=${{ secrets.SPACE_APP_SECRET }} + -Ppublishing.sonatype=false From ec8f14a6e91035fc5f3e01a55edaa8d99975ab38 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Wed, 21 Jul 2021 00:00:35 +0700 Subject: [PATCH 090/132] Fix publish.yml --- .github/workflows/publish.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index 13bbabbc9..05c1c603e 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -40,9 +40,9 @@ jobs: ${{ runner.os }}-gradle- - name: Publish Windows Artifacts if: matrix.os == 'windows-latest' + shell: cmd run: > - ./gradlew release --no-daemon -Ppublishing.enabled=true - -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }} + ./gradlew release --no-daemon -Ppublishing.enabled=true -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }} -Ppublishing.space.token=${{ secrets.SPACE_APP_SECRET }} -Ppublishing.sonatype=false - name: Publish Mac Artifacts From 8b3298f7a888bee9682d4ba9276ffb1c81b141ef Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sun, 20 Jun 2021 17:57:33 +0700 Subject: [PATCH 091/132] Exact conversions from Long to Int, Int indexing of Dimension --- .../kmath/structures/typeSafeDimensions.kt | 2 +- .../commons/random/CMRandomGeneratorWrapper.kt | 3 ++- .../kotlin/space/kscience/kmath/misc/numbers.kt | 8 ++++++++ .../kotlin/space/kscience/kmath/misc/numbers.kt | 12 ++++++++++++ .../space/kscience/kmath/misc/numbersJVM.kt | 8 ++++++++ .../kotlin/space/kscience/kmath/misc/numbers.kt | 12 ++++++++++++ .../dimensions/{Dimensions.kt => Dimension.kt} | 16 ++++++++-------- .../space/kscience/kmath/dimensions/Wrappers.kt | 16 ++++++++-------- .../kmath/dimensions/{dimJs.kt => Dimension.kt} | 8 ++++---- .../kmath/dimensions/{dimJvm.kt => Dimension.kt} | 14 ++++++++------ .../dimensions/{dimNative.kt => Dimension.kt} | 8 ++++---- .../kotlin/space/kscience/kmath/nd4j/arrays.kt | 4 +++- .../kscience/kmath/samplers/PoissonSampler.kt | 5 +++-- .../ZigguratNormalizedGaussianSampler.kt | 3 ++- 14 files changed, 83 insertions(+), 36 deletions(-) create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/numbers.kt create mode 100644 kmath-core/src/jsMain/kotlin/space/kscience/kmath/misc/numbers.kt create mode 100644 kmath-core/src/jvmMain/kotlin/space/kscience/kmath/misc/numbersJVM.kt create mode 100644 kmath-core/src/nativeMain/kotlin/space/kscience/kmath/misc/numbers.kt rename kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/{Dimensions.kt => Dimension.kt} (67%) rename kmath-dimensions/src/jsMain/kotlin/space/kscience/kmath/dimensions/{dimJs.kt => Dimension.kt} (62%) rename kmath-dimensions/src/jvmMain/kotlin/space/kscience/kmath/dimensions/{dimJvm.kt => Dimension.kt} (69%) rename kmath-dimensions/src/nativeMain/kotlin/space/kscience/kmath/dimensions/{dimNative.kt => Dimension.kt} (65%) diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/typeSafeDimensions.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/typeSafeDimensions.kt index 955f86fa9..c28b566b9 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/structures/typeSafeDimensions.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/typeSafeDimensions.kt @@ -19,7 +19,7 @@ private fun DMatrixContext.simple() { } private object D5 : Dimension { - override val dim: UInt = 5u + override val dim: Int = 5 } private fun DMatrixContext.custom() { diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt index afbfd9a24..6aeebb68c 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt @@ -8,6 +8,7 @@ package space.kscience.kmath.commons.random import kotlinx.coroutines.runBlocking import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.samplers.GaussianSampler +import space.kscience.kmath.misc.toIntExact import space.kscience.kmath.stat.RandomGenerator import space.kscience.kmath.stat.next @@ -28,7 +29,7 @@ public class CMRandomGeneratorWrapper( } override fun setSeed(seed: Long) { - setSeed(seed.toInt()) + setSeed(seed.toIntExact()) } override fun nextBytes(bytes: ByteArray) { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/numbers.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/numbers.kt new file mode 100644 index 000000000..f879a06d5 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/numbers.kt @@ -0,0 +1,8 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.misc + +public expect fun Long.toIntExact(): Int diff --git a/kmath-core/src/jsMain/kotlin/space/kscience/kmath/misc/numbers.kt b/kmath-core/src/jsMain/kotlin/space/kscience/kmath/misc/numbers.kt new file mode 100644 index 000000000..68a3c995b --- /dev/null +++ b/kmath-core/src/jsMain/kotlin/space/kscience/kmath/misc/numbers.kt @@ -0,0 +1,12 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.misc + +public actual fun Long.toIntExact(): Int { + val i = toInt() + if (i.toLong() == this) throw ArithmeticException("integer overflow") + return i +} diff --git a/kmath-core/src/jvmMain/kotlin/space/kscience/kmath/misc/numbersJVM.kt b/kmath-core/src/jvmMain/kotlin/space/kscience/kmath/misc/numbersJVM.kt new file mode 100644 index 000000000..5ba0dbc9b --- /dev/null +++ b/kmath-core/src/jvmMain/kotlin/space/kscience/kmath/misc/numbersJVM.kt @@ -0,0 +1,8 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.misc + +public actual fun Long.toIntExact(): Int = Math.toIntExact(this) diff --git a/kmath-core/src/nativeMain/kotlin/space/kscience/kmath/misc/numbers.kt b/kmath-core/src/nativeMain/kotlin/space/kscience/kmath/misc/numbers.kt new file mode 100644 index 000000000..68a3c995b --- /dev/null +++ b/kmath-core/src/nativeMain/kotlin/space/kscience/kmath/misc/numbers.kt @@ -0,0 +1,12 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.misc + +public actual fun Long.toIntExact(): Int { + val i = toInt() + if (i.toLong() == this) throw ArithmeticException("integer overflow") + return i +} diff --git a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Dimensions.kt b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt similarity index 67% rename from kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Dimensions.kt rename to kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt index 8b17d252f..e57c22834 100644 --- a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Dimensions.kt +++ b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt @@ -8,47 +8,47 @@ package space.kscience.kmath.dimensions import kotlin.reflect.KClass /** - * Represents a quantity of dimensions in certain structure. + * Represents a quantity of dimensions in certain structure. **This interface must be implemented only by objects.** * * @property dim The number of dimensions. */ public interface Dimension { - public val dim: UInt + public val dim: Int public companion object } -public fun KClass.dim(): UInt = Dimension.resolve(this).dim +public fun KClass.dim(): Int = Dimension.resolve(this).dim public expect fun Dimension.Companion.resolve(type: KClass): D /** * Finds or creates [Dimension] with [Dimension.dim] equal to [dim]. */ -public expect fun Dimension.Companion.of(dim: UInt): Dimension +public expect fun Dimension.Companion.of(dim: Int): Dimension /** * Finds [Dimension.dim] of given type [D]. */ -public inline fun Dimension.Companion.dim(): UInt = D::class.dim() +public inline fun Dimension.Companion.dim(): Int = D::class.dim() /** * Type representing 1 dimension. */ public object D1 : Dimension { - override val dim: UInt get() = 1U + override val dim: Int get() = 1 } /** * Type representing 2 dimensions. */ public object D2 : Dimension { - override val dim: UInt get() = 2U + override val dim: Int get() = 2 } /** * Type representing 3 dimensions. */ public object D3 : Dimension { - override val dim: UInt get() = 3U + override val dim: Int get() = 3 } diff --git a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt index a2ee14301..deb297913 100644 --- a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt +++ b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt @@ -23,11 +23,11 @@ public interface DMatrix : Structure2D { * Coerces a regular matrix to a matrix with type-safe dimensions and throws a error if coercion failed */ public inline fun coerce(structure: Structure2D): DMatrix { - require(structure.rowNum == Dimension.dim().toInt()) { + require(structure.rowNum == Dimension.dim()) { "Row number mismatch: expected ${Dimension.dim()} but found ${structure.rowNum}" } - require(structure.colNum == Dimension.dim().toInt()) { + require(structure.colNum == Dimension.dim()) { "Column number mismatch: expected ${Dimension.dim()} but found ${structure.colNum}" } @@ -61,7 +61,7 @@ public value class DMatrixWrapper( public interface DPoint : Point { public companion object { public inline fun coerce(point: Point): DPoint { - require(point.size == Dimension.dim().toInt()) { + require(point.size == Dimension.dim()) { "Vector dimension mismatch: expected ${Dimension.dim()}, but found ${point.size}" } @@ -92,11 +92,11 @@ public value class DPointWrapper(public val point: Point>(public val context: LinearSpace) { public inline fun Matrix.coerce(): DMatrix { - require(rowNum == Dimension.dim().toInt()) { + require(rowNum == Dimension.dim()) { "Row number mismatch: expected ${Dimension.dim()} but found $rowNum" } - require(colNum == Dimension.dim().toInt()) { + require(colNum == Dimension.dim()) { "Column number mismatch: expected ${Dimension.dim()} but found $colNum" } @@ -111,7 +111,7 @@ public value class DMatrixContext>(public val context: ): DMatrix { val rows = Dimension.dim() val cols = Dimension.dim() - return context.buildMatrix(rows.toInt(), cols.toInt(), initializer).coerce() + return context.buildMatrix(rows, cols, initializer).coerce() } public inline fun point(noinline initializer: A.(Int) -> T): DPoint { @@ -119,7 +119,7 @@ public value class DMatrixContext>(public val context: return DPoint.coerceUnsafe( context.buildVector( - size.toInt(), + size, initializer ) ) @@ -167,4 +167,4 @@ public inline fun DMatrixContext.on public inline fun DMatrixContext.zero(): DMatrix = produce { _, _ -> 0.0 - } \ No newline at end of file + } diff --git a/kmath-dimensions/src/jsMain/kotlin/space/kscience/kmath/dimensions/dimJs.kt b/kmath-dimensions/src/jsMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt similarity index 62% rename from kmath-dimensions/src/jsMain/kotlin/space/kscience/kmath/dimensions/dimJs.kt rename to kmath-dimensions/src/jsMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt index 27912f5bc..610e8b4c0 100644 --- a/kmath-dimensions/src/jsMain/kotlin/space/kscience/kmath/dimensions/dimJs.kt +++ b/kmath-dimensions/src/jsMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt @@ -7,17 +7,17 @@ package space.kscience.kmath.dimensions import kotlin.reflect.KClass -private val dimensionMap: MutableMap = hashMapOf(1u to D1, 2u to D2, 3u to D3) +private val dimensionMap: MutableMap = hashMapOf(1 to D1, 2 to D2, 3 to D3) @Suppress("UNCHECKED_CAST") public actual fun Dimension.Companion.resolve(type: KClass): D = dimensionMap .entries - .map(MutableMap.MutableEntry::value) + .map(MutableMap.MutableEntry::value) .find { it::class == type } as? D ?: error("Can't resolve dimension $type") -public actual fun Dimension.Companion.of(dim: UInt): Dimension = dimensionMap.getOrPut(dim) { +public actual fun Dimension.Companion.of(dim: Int): Dimension = dimensionMap.getOrPut(dim) { object : Dimension { - override val dim: UInt get() = dim + override val dim: Int get() = dim } } diff --git a/kmath-dimensions/src/jvmMain/kotlin/space/kscience/kmath/dimensions/dimJvm.kt b/kmath-dimensions/src/jvmMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt similarity index 69% rename from kmath-dimensions/src/jvmMain/kotlin/space/kscience/kmath/dimensions/dimJvm.kt rename to kmath-dimensions/src/jvmMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt index f21a3e18f..e6d8b3b35 100644 --- a/kmath-dimensions/src/jvmMain/kotlin/space/kscience/kmath/dimensions/dimJvm.kt +++ b/kmath-dimensions/src/jvmMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt @@ -3,6 +3,8 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ +@file:JvmName("DimensionJVM") + package space.kscience.kmath.dimensions import kotlin.reflect.KClass @@ -10,12 +12,12 @@ import kotlin.reflect.KClass public actual fun Dimension.Companion.resolve(type: KClass): D = type.objectInstance ?: error("No object instance for dimension class") -public actual fun Dimension.Companion.of(dim: UInt): Dimension = when (dim) { - 1u -> D1 - 2u -> D2 - 3u -> D3 +public actual fun Dimension.Companion.of(dim: Int): Dimension = when (dim) { + 1 -> D1 + 2 -> D2 + 3 -> D3 else -> object : Dimension { - override val dim: UInt get() = dim + override val dim: Int get() = dim } -} \ No newline at end of file +} diff --git a/kmath-dimensions/src/nativeMain/kotlin/space/kscience/kmath/dimensions/dimNative.kt b/kmath-dimensions/src/nativeMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt similarity index 65% rename from kmath-dimensions/src/nativeMain/kotlin/space/kscience/kmath/dimensions/dimNative.kt rename to kmath-dimensions/src/nativeMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt index 9aa58e64a..64edbe935 100644 --- a/kmath-dimensions/src/nativeMain/kotlin/space/kscience/kmath/dimensions/dimNative.kt +++ b/kmath-dimensions/src/nativeMain/kotlin/space/kscience/kmath/dimensions/Dimension.kt @@ -9,17 +9,17 @@ import kotlin.native.concurrent.ThreadLocal import kotlin.reflect.KClass @ThreadLocal -private val dimensionMap: MutableMap = hashMapOf(1u to D1, 2u to D2, 3u to D3) +private val dimensionMap: MutableMap = hashMapOf(1 to D1, 2 to D2, 3 to D3) @Suppress("UNCHECKED_CAST") public actual fun Dimension.Companion.resolve(type: KClass): D = dimensionMap .entries - .map(MutableMap.MutableEntry::value) + .map(MutableMap.MutableEntry::value) .find { it::class == type } as? D ?: error("Can't resolve dimension $type") -public actual fun Dimension.Companion.of(dim: UInt): Dimension = dimensionMap.getOrPut(dim) { +public actual fun Dimension.Companion.of(dim: Int): Dimension = dimensionMap.getOrPut(dim) { object : Dimension { - override val dim: UInt get() = dim + override val dim: Int get() = dim } } diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/arrays.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/arrays.kt index 75a334ca7..3ca756600 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/arrays.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/arrays.kt @@ -5,4 +5,6 @@ package space.kscience.kmath.nd4j -internal fun LongArray.toIntArray(): IntArray = IntArray(size) { this[it].toInt() } +import space.kscience.kmath.misc.toIntExact + +internal fun LongArray.toIntArray(): IntArray = IntArray(size) { this[it].toIntExact() } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt index 2177e41ab..96131aa4b 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt @@ -7,6 +7,7 @@ package space.kscience.kmath.samplers import space.kscience.kmath.chains.BlockingIntChain import space.kscience.kmath.internal.InternalUtils +import space.kscience.kmath.misc.toIntExact import space.kscience.kmath.stat.RandomGenerator import space.kscience.kmath.stat.Sampler import space.kscience.kmath.structures.IntBuffer @@ -119,7 +120,7 @@ public class LargeMeanPoissonSampler(public val mean: Double) : Sampler { val gaussian = ZigguratNormalizedGaussianSampler.sample(generator) val smallMeanPoissonSampler = if (mean - lambda < Double.MIN_VALUE) { - null + null } else { KempSmallMeanPoissonSampler(mean - lambda).sample(generator) } @@ -188,7 +189,7 @@ public class LargeMeanPoissonSampler(public val mean: Double) : Sampler { } } - return min(y2 + y.toLong(), Int.MAX_VALUE.toLong()).toInt() + return min(y2 + y.toLong(), Int.MAX_VALUE.toLong()).toIntExact() } override fun nextBufferBlocking(size: Int): IntBuffer = IntBuffer(size) { nextBlocking() } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ZigguratNormalizedGaussianSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ZigguratNormalizedGaussianSampler.kt index 24148271d..81b8c3d4b 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ZigguratNormalizedGaussianSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ZigguratNormalizedGaussianSampler.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.samplers import space.kscience.kmath.chains.BlockingDoubleChain +import space.kscience.kmath.misc.toIntExact import space.kscience.kmath.stat.RandomGenerator import space.kscience.kmath.structures.DoubleBuffer import kotlin.math.* @@ -58,7 +59,7 @@ public object ZigguratNormalizedGaussianSampler : NormalizedGaussianSampler { private fun sampleOne(generator: RandomGenerator): Double { val j = generator.nextLong() - val i = (j and LAST.toLong()).toInt() + val i = (j and LAST.toLong()).toIntExact() return if (abs(j) < K[i]) j * W[i] else fix(generator, j, i) } From ef50a4d963e94581ad636cc956ba7fba6c1203c1 Mon Sep 17 00:00:00 2001 From: Peter Klimai Date: Wed, 21 Jul 2021 12:33:45 +0300 Subject: [PATCH 092/132] Fix package name --- .../{kaceince => kscience}/kmath/real/DoubleMatrixTest.kt | 2 +- .../{kaceince => kscience}/kmath/real/DoubleVectorTest.kt | 2 +- .../kotlin/{kaceince => kscience}/kmath/real/GridTest.kt | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) rename kmath-for-real/src/commonTest/kotlin/{kaceince => kscience}/kmath/real/DoubleMatrixTest.kt (99%) rename kmath-for-real/src/commonTest/kotlin/{kaceince => kscience}/kmath/real/DoubleVectorTest.kt (97%) rename kmath-for-real/src/commonTest/kotlin/{kaceince => kscience}/kmath/real/GridTest.kt (96%) diff --git a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt b/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleMatrixTest.kt similarity index 99% rename from kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt rename to kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleMatrixTest.kt index a9c5f9e1a..e7b8434c5 100644 --- a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleMatrixTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleMatrixTest.kt @@ -3,7 +3,7 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ -package kaceince.kmath.real +package kscience.kmath.real import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.matrix diff --git a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleVectorTest.kt b/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleVectorTest.kt similarity index 97% rename from kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleVectorTest.kt rename to kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleVectorTest.kt index 9de54381c..345013306 100644 --- a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/DoubleVectorTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleVectorTest.kt @@ -3,7 +3,7 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ -package kaceince.kmath.real +package kscience.kmath.real import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.asMatrix diff --git a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/GridTest.kt b/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/GridTest.kt similarity index 96% rename from kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/GridTest.kt rename to kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/GridTest.kt index 0d3b80336..a59fdfca4 100644 --- a/kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/GridTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/GridTest.kt @@ -3,7 +3,7 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ -package kaceince.kmath.real +package kscience.kmath.real import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.real.DoubleVector From c263b1acbe0a6de89bb45b9fa433c72c7323fc22 Mon Sep 17 00:00:00 2001 From: Peter Klimai Date: Wed, 21 Jul 2021 13:25:35 +0300 Subject: [PATCH 093/132] Fix package name again --- .../kotlin/{ => space}/kscience/kmath/real/DoubleMatrixTest.kt | 2 +- .../kotlin/{ => space}/kscience/kmath/real/DoubleVectorTest.kt | 2 +- .../kotlin/{ => space}/kscience/kmath/real/GridTest.kt | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) rename kmath-for-real/src/commonTest/kotlin/{ => space}/kscience/kmath/real/DoubleMatrixTest.kt (99%) rename kmath-for-real/src/commonTest/kotlin/{ => space}/kscience/kmath/real/DoubleVectorTest.kt (97%) rename kmath-for-real/src/commonTest/kotlin/{ => space}/kscience/kmath/real/GridTest.kt (96%) diff --git a/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleMatrixTest.kt b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleMatrixTest.kt similarity index 99% rename from kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleMatrixTest.kt rename to kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleMatrixTest.kt index e7b8434c5..e3f015511 100644 --- a/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleMatrixTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleMatrixTest.kt @@ -3,7 +3,7 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ -package kscience.kmath.real +package space.kscience.kmath.real import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.matrix diff --git a/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleVectorTest.kt b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleVectorTest.kt similarity index 97% rename from kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleVectorTest.kt rename to kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleVectorTest.kt index 345013306..48e55ea01 100644 --- a/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/DoubleVectorTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleVectorTest.kt @@ -3,7 +3,7 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ -package kscience.kmath.real +package space.kscience.kmath.real import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.asMatrix diff --git a/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/GridTest.kt b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/GridTest.kt similarity index 96% rename from kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/GridTest.kt rename to kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/GridTest.kt index a59fdfca4..8fed8d10e 100644 --- a/kmath-for-real/src/commonTest/kotlin/kscience/kmath/real/GridTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/GridTest.kt @@ -3,7 +3,7 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ -package kscience.kmath.real +package space.kscience.kmath.real import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.real.DoubleVector From 2d3a5fb5c82bf47075596d4f13db2b9afb09d5b5 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Wed, 21 Jul 2021 00:45:29 +0700 Subject: [PATCH 094/132] Fix publish.yml --- .github/workflows/publish.yml | 2 -- README.md | 8 ++++---- kmath-kotlingrad/README.md | 4 ++-- settings.gradle.kts | 2 +- 4 files changed, 7 insertions(+), 9 deletions(-) diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index 05c1c603e..cbf13d03d 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -44,11 +44,9 @@ jobs: run: > ./gradlew release --no-daemon -Ppublishing.enabled=true -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }} -Ppublishing.space.token=${{ secrets.SPACE_APP_SECRET }} - -Ppublishing.sonatype=false - name: Publish Mac Artifacts if: matrix.os == 'macOS-latest' run: > ./gradlew release --no-daemon -Ppublishing.enabled=true -Ppublishing.platform=macosX64 -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }} -Ppublishing.space.token=${{ secrets.SPACE_APP_SECRET }} - -Ppublishing.sonatype=false diff --git a/README.md b/README.md index 7645256d9..a15c4384f 100644 --- a/README.md +++ b/README.md @@ -132,7 +132,7 @@ KMath is a modular library. Different modules provide different features with di objects to the expression by providing a context. Expressions can be used for a wide variety of purposes from high performance calculations to code generation. > - [domains](kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains) : Domains -> - [autodif](kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation +> - [autodiff](kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation
@@ -222,8 +222,8 @@ One can still use generic algebras though. > **Maturity**: EXPERIMENTAL > > **Features:** -> - [differentiable-mst-expression](kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : MST based DifferentiableExpression. -> - [differentiable-mst-expression](kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : Conversions between Kotlin∇'s SFun and MST +> - [differentiable-mst-expression](kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt) : MST based DifferentiableExpression. +> - [scalars-adapters](kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/scalarsAdapters.kt) : Conversions between Kotlin∇'s SFun and MST
@@ -264,7 +264,7 @@ One can still use generic algebras though. > > **Features:** > - [tensor algebra](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt) : Basic linear algebra operations on tensors (plus, dot, etc.) -> - [tensor algebra with broadcasting](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting. +> - [tensor algebra with broadcasting](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt) : Basic linear algebra operations implemented with broadcasting. > - [linear algebra operations](kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt) : Advanced linear algebra operations like LU decomposition, SVD, etc.
diff --git a/kmath-kotlingrad/README.md b/kmath-kotlingrad/README.md index 304a0639b..3b337460f 100644 --- a/kmath-kotlingrad/README.md +++ b/kmath-kotlingrad/README.md @@ -2,8 +2,8 @@ [Kotlin∇](https://www.htmlsymbols.xyz/unicode/U+2207) integration module. - - [differentiable-mst-expression](src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : MST based DifferentiableExpression. - - [differentiable-mst-expression](src/main/kotlin/space/kscience/kmath/kotlingrad/DifferentiableMstExpression.kt) : Conversions between Kotlin∇'s SFun and MST + - [differentiable-mst-expression](src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt) : MST based DifferentiableExpression. + - [scalars-adapters](src/main/kotlin/space/kscience/kmath/kotlingrad/scalarsAdapters.kt) : Conversions between Kotlin∇'s SFun and MST ## Artifact: diff --git a/settings.gradle.kts b/settings.gradle.kts index 445f75c09..18f867df3 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -5,7 +5,7 @@ pluginManagement { gradlePluginPortal() } - val toolsVersion = "0.10.1" + val toolsVersion = "0.10.2" val kotlinVersion = "1.5.21" plugins { From dd01c39cbe6dbd080078731b2c3741215119a6ad Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Wed, 21 Jul 2021 00:45:29 +0700 Subject: [PATCH 095/132] Fix publish.yml --- buildSrc/build.gradle.kts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/buildSrc/build.gradle.kts b/buildSrc/build.gradle.kts index 3427a6d61..36a1ffd9e 100644 --- a/buildSrc/build.gradle.kts +++ b/buildSrc/build.gradle.kts @@ -11,7 +11,7 @@ repositories { dependencies { api("org.jetbrains.kotlinx:kotlinx-serialization-json:1.1.0") - api("ru.mipt.npm:gradle-tools:0.10.1") + api("ru.mipt.npm:gradle-tools:0.10.2") api("org.jetbrains.kotlinx:kotlinx-benchmark-plugin:0.3.1") } From fe21f0c954feeabacfe2aab976a533552a39a418 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Wed, 28 Jul 2021 05:52:23 +0700 Subject: [PATCH 096/132] Update plotly.kt and SLF4J --- examples/build.gradle.kts | 4 ++-- kmath-nd4j/build.gradle.kts | 2 +- kmath-symja/build.gradle.kts | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/examples/build.gradle.kts b/examples/build.gradle.kts index 406b8f470..4cc6fecc0 100644 --- a/examples/build.gradle.kts +++ b/examples/build.gradle.kts @@ -41,9 +41,9 @@ dependencies { // } else implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7") - implementation("org.slf4j:slf4j-simple:1.7.30") + implementation("org.slf4j:slf4j-simple:1.7.31") // plotting - implementation("space.kscience:plotlykt-server:0.4.0") + implementation("space.kscience:plotlykt-server:0.4.2") //jafama implementation(project(":kmath-jafama")) } diff --git a/kmath-nd4j/build.gradle.kts b/kmath-nd4j/build.gradle.kts index 6e890a937..dcb6f1b4a 100644 --- a/kmath-nd4j/build.gradle.kts +++ b/kmath-nd4j/build.gradle.kts @@ -9,7 +9,7 @@ dependencies { api(project(":kmath-tensors")) api("org.nd4j:nd4j-api:1.0.0-M1") testImplementation("org.nd4j:nd4j-native-platform:1.0.0-M1") - testImplementation("org.slf4j:slf4j-simple:1.7.30") + testImplementation("org.slf4j:slf4j-simple:1.7.31") } readme { diff --git a/kmath-symja/build.gradle.kts b/kmath-symja/build.gradle.kts index f305c03b8..65c329d52 100644 --- a/kmath-symja/build.gradle.kts +++ b/kmath-symja/build.gradle.kts @@ -34,7 +34,7 @@ dependencies { api("org.hipparchus:hipparchus-stat:1.8") api(project(":kmath-core")) - testImplementation("org.slf4j:slf4j-simple:1.7.30") + testImplementation("org.slf4j:slf4j-simple:1.7.31") } readme { From afd590878421093e4203aca8238f964900465a3e Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Fri, 7 May 2021 19:59:21 +0700 Subject: [PATCH 097/132] Revise grammar of KDoc comments, refresh documentation files --- README.md | 68 ++++++++------ docs/algebra.md | 83 +++++------------ docs/buffers.md | 17 ++-- docs/codestyle.md | 19 ++-- docs/contexts.md | 44 ++++----- docs/expressions.md | 23 ++--- docs/features.md | 14 --- docs/linear.md | 32 ++++--- docs/nd-structure.md | 18 ++-- docs/readme.md | 14 +++ docs/templates/README-TEMPLATE.md | 66 ++++++++------ .../kscience/kmath/ast/kotlingradSupport.kt | 4 +- .../space/kscience/kmath/ast/symjaSupport.kt | 4 +- .../kmath/commons/fit/fitWithAutoDiff.kt | 3 +- .../space/kscience/kmath/jafama/JafamaDemo.kt | 15 ++++ .../kscience/kmath/jafama/KMathaJafamaDemo.kt | 17 ---- .../kscience/kmath/stat/DistributionDemo.kt | 3 - .../kscience/kmath/structures/NDField.kt | 2 +- .../kmath/tensors/DataSetNormalization.kt | 4 +- .../tensors/LinearSystemSolvingWithLUP.kt | 2 +- .../kscience/kmath/tensors/NeuralNetwork.kt | 2 +- .../space/kscience/kmath/tensors/PCA.kt | 4 +- kmath-ast/README.md | 5 +- kmath-ast/docs/README-TEMPLATE.md | 5 +- .../kmath/ast/rendering/MathSyntax.kt | 4 +- .../kmath/ast/rendering/SyntaxRenderer.kt | 2 +- .../kscience/kmath/ast/rendering/features.kt | 8 +- .../kmath/asm/internal/codegenUtils.kt | 4 +- .../DerivativeStructureExpression.kt | 2 +- .../DerivativeStructureExpressionTest.kt | 2 +- .../commons/optimization/OptimizeTest.kt | 2 +- .../expressions/DifferentiableExpression.kt | 2 +- .../kscience/kmath/expressions/Expression.kt | 4 +- .../FunctionalExpressionAlgebra.kt | 2 +- .../kscience/kmath/linear/LinearSolver.kt | 4 +- .../kscience/kmath/linear/LinearSpace.kt | 4 +- .../kscience/kmath/linear/LupDecomposition.kt | 4 +- .../kscience/kmath/linear/MatrixFeatures.kt | 2 +- .../kscience/kmath/linear/MatrixWrapper.kt | 9 +- .../space/kscience/kmath/misc/annotations.kt | 6 +- .../space/kscience/kmath/nd/AlgebraND.kt | 26 +++--- .../space/kscience/kmath/nd/Structure1D.kt | 2 +- .../space/kscience/kmath/nd/Structure2D.kt | 5 +- .../space/kscience/kmath/nd/StructureND.kt | 10 +-- .../kscience/kmath/operations/Algebra.kt | 62 +++++++------ .../kmath/operations/AlgebraElements.kt | 2 +- .../space/kscience/kmath/operations/BigInt.kt | 4 +- .../kmath/operations/NumericAlgebra.kt | 32 +++---- .../kmath/operations/OptionalOperations.kt | 4 +- .../kscience/kmath/structures/DoubleBuffer.kt | 4 +- .../kmath/structures/FlaggedBuffer.kt | 2 +- .../kscience/kmath/structures/FloatBuffer.kt | 4 +- .../kscience/kmath/structures/IntBuffer.kt | 4 +- .../kscience/kmath/structures/LongBuffer.kt | 4 +- .../kscience/kmath/structures/ShortBuffer.kt | 4 +- .../space/kscience/kmath/chains/Chain.kt | 14 +-- .../kscience/kmath/streaming/BufferFlow.kt | 2 +- .../kscience/kmath/dimensions/Wrappers.kt | 4 +- kmath-for-real/build.gradle.kts | 2 +- .../space/kscience/kmath/real/RealVector.kt | 2 +- .../kotlin/space/kscience/kmath/real/grids.kt | 4 +- .../kscience/kmath/functions/Piecewise.kt | 10 +-- .../kmath/integration/GaussIntegrator.kt | 20 +++-- .../integration/GaussIntegratorRuleFactory.kt | 4 +- .../kmath/integration/SimpsonIntegrator.kt | 15 ++-- .../kmath/integration/SplineIntegrator.kt | 13 +-- .../kmath/integration/UnivariateIntegrand.kt | 4 +- .../kscience/kmath/histogram/Histogram.kt | 2 +- .../kmath/histogram/UnivariateHistogram.kt | 7 +- kmath-jafama/README.md | 20 +---- kmath-kotlingrad/README.md | 2 +- kmath-kotlingrad/docs/README-TEMPLATE.md | 2 +- .../space/kscience/kmath/memory/Memory.kt | 2 +- .../kscience/kmath/memory/DataViewMemory.kt | 2 +- .../kscience/kmath/memory/ByteBufferMemory.kt | 2 +- .../kscience/kmath/memory/NativeMemory.kt | 4 +- .../kscience/kmath/nd4j/Nd4jArrayAlgebra.kt | 2 +- .../kscience/kmath/nd4j/Nd4jArrayStructure.kt | 2 +- .../kscience/kmath/nd4j/Nd4jTensorAlgebra.kt | 2 +- .../kmath/distributions/Distribution.kt | 2 +- .../distributions/FactorizedDistribution.kt | 4 +- .../kscience/kmath/internal/InternalGamma.kt | 2 +- .../optimization/FunctionOptimization.kt | 15 ++-- .../NoDerivFunctionOptimization.kt | 2 +- .../kmath/optimization/Optimization.kt | 2 +- .../AhrensDieterMarsagliaTsangGammaSampler.kt | 4 +- .../samplers/AliasMethodDiscreteSampler.kt | 12 +-- .../samplers/KempSmallMeanPoissonSampler.kt | 5 +- .../kscience/kmath/samplers/PoissonSampler.kt | 8 +- .../kscience/kmath/stat/RandomGenerator.kt | 6 +- .../kscience/kmath/stat/SamplerAlgebra.kt | 2 +- .../space/kscience/kmath/stat/Statistic.kt | 7 +- .../kmath/stat/RandomSourceGenerator.kt | 2 +- .../tensors/api/LinearOpsTensorAlgebra.kt | 38 ++++---- .../kmath/tensors/api/TensorAlgebra.kt | 13 ++- .../api/TensorPartialDivisionAlgebra.kt | 2 +- .../kmath/tensors/core/DoubleTensorAlgebra.kt | 90 ++++++++++--------- .../kmath/tensors/core/internal/utils.kt | 4 +- 98 files changed, 523 insertions(+), 538 deletions(-) delete mode 100644 docs/features.md create mode 100644 docs/readme.md create mode 100644 examples/src/main/kotlin/space/kscience/kmath/jafama/JafamaDemo.kt delete mode 100644 examples/src/main/kotlin/space/kscience/kmath/jafama/KMathaJafamaDemo.kt diff --git a/README.md b/README.md index a15c4384f..db069d4e0 100644 --- a/README.md +++ b/README.md @@ -6,10 +6,10 @@ # KMath -Could be pronounced as `key-math`. The **K**otlin **Math**ematics library was initially intended as a Kotlin-based analog to -Python's NumPy library. Later we found that kotlin is much more flexible language and allows superior architecture -designs. In contrast to `numpy` and `scipy` it is modular and has a lightweight core. The `numpy`-like experience could -be achieved with [kmath-for-real](/kmath-for-real) extension module. +Could be pronounced as `key-math`. The **K**otlin **Math**ematics library was initially intended as a Kotlin-based +analog to Python's NumPy library. Later we found that kotlin is much more flexible language and allows superior +architecture designs. In contrast to `numpy` and `scipy` it is modular and has a lightweight core. The `numpy`-like +experience could be achieved with [kmath-for-real](/kmath-for-real) extension module. [Documentation site (**WIP**)](https://mipt-npm.github.io/kmath/) @@ -21,26 +21,33 @@ be achieved with [kmath-for-real](/kmath-for-real) extension module. # Goal -* Provide a flexible and powerful API to work with mathematics abstractions in Kotlin-multiplatform (JVM, JS and Native). +* Provide a flexible and powerful API to work with mathematics abstractions in Kotlin-multiplatform (JVM, JS and Native) + . * Provide basic multiplatform implementations for those abstractions (without significant performance optimization). * Provide bindings and wrappers with those abstractions for popular optimized platform libraries. ## Non-goals -* Be like NumPy. It was the idea at the beginning, but we decided that we can do better in terms of API. +* Be like NumPy. It was the idea at the beginning, but we decided that we can do better in API. * Provide the best performance out of the box. We have specialized libraries for that. Need only API wrappers for them. * Cover all cases as immediately and in one bundle. We will modularize everything and add new features gradually. -* Provide specialized behavior in the core. API is made generic on purpose, so one needs to specialize for types, like -for `Double` in the core. For that we will have specialization modules like `kmath-for-real`, which will give better -experience for those, who want to work with specific types. +* Provide specialized behavior in the core. API is made generic on purpose, so one needs to specialize for types, like + for `Double` in the core. For that we will have specialization modules like `kmath-for-real`, which will give better + experience for those, who want to work with specific types. ## Features and stability -KMath is a modular library. Different modules provide different features with different API stability guarantees. All core modules are released with the same version, but with different API change policy. The features are described in module definitions below. The module stability could have following levels: +KMath is a modular library. Different modules provide different features with different API stability guarantees. All +core modules are released with the same version, but with different API change policy. The features are described in +module definitions below. The module stability could have the following levels: -* **PROTOTYPE**. On this level there are no compatibility guarantees. All methods and classes form those modules could break any moment. You can still use it, but be sure to fix the specific version. -* **EXPERIMENTAL**. The general API is decided, but some changes could be made. Volatile API is marked with `@UnstableKmathAPI` or other stability warning annotations. -* **DEVELOPMENT**. API breaking generally follows semantic versioning ideology. There could be changes in minor versions, but not in patch versions. API is protected with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool. +* **PROTOTYPE**. On this level there are no compatibility guarantees. All methods and classes form those modules could + break any moment. You can still use it, but be sure to fix the specific version. +* **EXPERIMENTAL**. The general API is decided, but some changes could be made. Volatile API is marked + with `@UnstableKmathAPI` or other stability warning annotations. +* **DEVELOPMENT**. API breaking generally follows semantic versioning ideology. There could be changes in minor + versions, but not in patch versions. API is protected + with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool. * **STABLE**. The API stabilized. Breaking changes are allowed only in major releases. @@ -161,7 +168,7 @@ performance calculations to code generation.
* ### [kmath-for-real](kmath-for-real) -> Extension module that should be used to achieve numpy-like behavior. +> Extension module that should be used to achieve numpy-like behavior. All operations are specialized to work with `Double` numbers without declaring algebraic contexts. One can still use generic algebras though. > @@ -278,30 +285,33 @@ One can still use generic algebras though. ## Multi-platform support -KMath is developed as a multi-platform library, which means that most of the interfaces are declared in the -[common source sets](/kmath-core/src/commonMain) and implemented there wherever it is possible. In some cases, features -are delegated to platform-specific implementations even if they could be provided in the common module for performance -reasons. Currently, the Kotlin/JVM is the primary platform, however Kotlin/Native and Kotlin/JS contributions and +KMath is developed as a multi-platform library, which means that most of the interfaces are declared in the +[common source sets](/kmath-core/src/commonMain) and implemented there wherever it is possible. In some cases, features +are delegated to platform-specific implementations even if they could be provided in the common module for performance +reasons. Currently, the Kotlin/JVM is the primary platform, however Kotlin/Native and Kotlin/JS contributions and feedback are also welcome. ## Performance -Calculation performance is one of major goals of KMath in the future, but in some cases it is impossible to achieve -both performance and flexibility. +Calculation performance is one of major goals of KMath in the future, but in some cases it is impossible to achieve both +performance and flexibility. -We expect to focus on creating convenient universal API first and then work on increasing performance for specific -cases. We expect the worst KMath benchmarks will perform better than native Python, but worse than optimized -native/SciPy (mostly due to boxing operations on primitive numbers). The best performance of optimized parts could be +We expect to focus on creating convenient universal API first and then work on increasing performance for specific +cases. We expect the worst KMath benchmarks will perform better than native Python, but worse than optimized +native/SciPy (mostly due to boxing operations on primitive numbers). The best performance of optimized parts could be better than SciPy. ## Requirements -KMath currently relies on JDK 11 for compilation and execution of Kotlin-JVM part. We recommend to use GraalVM-CE 11 for execution in order to get better performance. +KMath currently relies on JDK 11 for compilation and execution of Kotlin-JVM part. We recommend to use GraalVM-CE 11 for +execution to get better performance. ### Repositories -Release and development artifacts are accessible from mipt-npm [Space](https://www.jetbrains.com/space/) repository `https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven` (see documentation of -[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details). The repository could be reached through [repo.kotlin.link](https://repo.kotlin.link) proxy: +Release and development artifacts are accessible from mipt-npm [Space](https://www.jetbrains.com/space/) +repository `https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven` (see documentation of +[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details). The repository could +be reached through [repo.kotlin.link](https://repo.kotlin.link) proxy: ```kotlin repositories { @@ -318,7 +328,7 @@ Gradle `6.0+` is required for multiplatform artifacts. ## Contributing -The project requires a lot of additional work. The most important thing we need is a feedback about what features are -required the most. Feel free to create feature requests. We are also welcome to code contributions, -especially in issues marked with +The project requires a lot of additional work. The most important thing we need is a feedback about what features are +required the most. Feel free to create feature requests. We are also welcome to code contributions, especially in issues +marked with [waiting for a hero](https://github.com/mipt-npm/kmath/labels/waiting%20for%20a%20hero) label. diff --git a/docs/algebra.md b/docs/algebra.md index 84693bb81..20158a125 100644 --- a/docs/algebra.md +++ b/docs/algebra.md @@ -1,85 +1,45 @@ # Algebraic Structures and Algebraic Elements -The mathematical operations in KMath are generally separated from mathematical objects. This means that to perform an -operation, say `+`, one needs two objects of a type `T` and an algebra context, which draws appropriate operation up, -say `Space`. Next one needs to run the actual operation in the context: +The mathematical operations in KMath are generally separated from mathematical objects. This means that to perform an +operation, say `+`, one needs two objects of a type `T` and an algebra context, which draws appropriate operation up, +say `Group`. Next one needs to run the actual operation in the context: ```kotlin import space.kscience.kmath.operations.* val a: T = ... val b: T = ... -val space: Space = ... +val group: Group = ... -val c = space { a + b } +val c = group { a + b } ``` -At first glance, this distinction seems to be a needless complication, but in fact one needs to remember that in -mathematics, one could draw up different operations on same objects. For example, one could use different types of +At first glance, this distinction seems to be a needless complication, but in fact one needs to remember that in +mathematics, one could draw up different operations on same objects. For example, one could use different types of geometry for vectors. ## Algebraic Structures -Mathematical contexts have the following hierarchy: +Primary mathematical contexts have the following hierarchy: -**Algebra** ← **Space** ← **Ring** ← **Field** +`Field <: Ring <: Group <: Algebra` These interfaces follow real algebraic structures: -- [Space](https://mathworld.wolfram.com/VectorSpace.html) defines addition, its neutral element (i.e. 0) and scalar -multiplication; -- [Ring](http://mathworld.wolfram.com/Ring.html) adds multiplication and its neutral element (i.e. 1); +- [Group](https://mathworld.wolfram.com/Group.html) defines addition, its identity element (i.e., 0) and additive + inverse (-x); +- [Ring](http://mathworld.wolfram.com/Ring.html) adds multiplication and its identity element (i.e., 1); - [Field](http://mathworld.wolfram.com/Field.html) adds division operation. A typical implementation of `Field` is the `DoubleField` which works on doubles, and `VectorSpace` for `Space`. In some cases algebra context can hold additional operations like `exp` or `sin`, and then it inherits appropriate -interface. Also, contexts may have operations, which produce elements outside of the context. For example, `Matrix.dot` -operation produces a matrix with new dimensions, which can be incompatible with initial matrix in terms of linear -operations. - -## Algebraic Element - -To achieve more familiar behavior (where you apply operations directly to mathematical objects), without involving -contexts KMath submits special type objects called `MathElement`. A `MathElement` is basically some object coupled to -a mathematical context. For example `Complex` is the pair of real numbers representing real and imaginary parts, -but it also holds reference to the `ComplexField` singleton, which allows performing direct operations on `Complex` -numbers without explicit involving the context like: - -```kotlin -import space.kscience.kmath.operations.* - -// Using elements -val c1 = Complex(1.0, 1.0) -val c2 = Complex(1.0, -1.0) -val c3 = c1 + c2 + 3.0.toComplex() - -// Using context -val c4 = ComplexField { c1 + i - 2.0 } -``` - -Both notations have their pros and cons. - -The hierarchy for algebraic elements follows the hierarchy for the corresponding algebraic structures. - -**MathElement** ← **SpaceElement** ← **RingElement** ← **FieldElement** - -`MathElement` is the generic common ancestor of the class with context. - -One major distinction between algebraic elements and algebraic contexts is that elements have three type -parameters: - -1. The type of elements, the field operates on. -2. The self-type of the element returned from operation (which has to be an algebraic element). -3. The type of the algebra over first type-parameter. - -The middle type is needed for of algebra members do not store context. For example, it is impossible to add a context -to regular `Double`. The element performs automatic conversions from context types and back. One should use context -operations in all performance-critical places. The performance of element operations is not guaranteed. +interface. Also, contexts may have operations, which produce elements outside the context. For example, `Matrix.dot` +operation produces a matrix with new dimensions, which can be incompatible with initial matrix in linear operations. ## Spaces and Fields -KMath submits both contexts and elements for builtin algebraic structures: +KMath introduces contexts for builtin algebraic structures: ```kotlin import space.kscience.kmath.operations.* @@ -102,13 +62,13 @@ val c2 = ComplexField { c1 - 1.0 } // Returns: Complex(re=0.0, im=2.0) val c3 = ComplexField { c1 - i * 2.0 } ``` -**Note**: In theory it is possible to add behaviors directly to the context, but as for now Kotlin does not support -that. Watch [KT-10468](https://youtrack.jetbrains.com/issue/KT-10468) and +**Note**: In theory it is possible to add behaviors directly to the context, but as for now Kotlin does not support +that. Watch [KT-10468](https://youtrack.jetbrains.com/issue/KT-10468) and [KEEP-176](https://github.com/Kotlin/KEEP/pull/176) for updates. ## Nested fields -Contexts allow one to build more complex structures. For example, it is possible to create a `Matrix` from complex +Contexts allow one to build more complex structures. For example, it is possible to create a `Matrix` from complex elements like so: ```kotlin @@ -118,8 +78,9 @@ val element = NDElement.complex(shape = intArrayOf(2, 2)) { index: IntArray -> ``` The `element` in this example is a member of the `Field` of 2D structures, each element of which is a member of its own -`ComplexField`. It is important one does not need to create a special n-d class to hold complex -numbers and implement operations on it, one just needs to provide a field for its elements. +`ComplexField`. It is important one does not need to create a special n-d class to hold complex numbers and implement +operations on it, one just needs to provide a field for its elements. -**Note**: Fields themselves do not solve the problem of JVM boxing, but it is possible to solve with special contexts like +**Note**: Fields themselves do not solve the problem of JVM boxing, but it is possible to solve with special contexts +like `MemorySpec`. diff --git a/docs/buffers.md b/docs/buffers.md index 679bd4e78..e7573497e 100644 --- a/docs/buffers.md +++ b/docs/buffers.md @@ -1,17 +1,20 @@ # Buffers -Buffer is one of main building blocks of kmath. It is a basic interface allowing random-access read and write (with `MutableBuffer`). -There are different types of buffers: +Buffer is one of main building blocks of kmath. It is a basic interface allowing random-access read and write ( +with `MutableBuffer`). There are different types of buffers: -* Primitive buffers wrapping like `RealBuffer` which are wrapping primitive arrays. +* Primitive buffers wrapping like `DoubleBuffer` which are wrapping primitive arrays. * Boxing `ListBuffer` wrapping a list * Functionally defined `VirtualBuffer` which does not hold a state itself, but provides a function to calculate value * `MemoryBuffer` allows direct allocation of objects in continuous memory block. -Some kmath features require a `BufferFactory` class to operate properly. A general convention is to use functions defined in -`Buffer` and `MutableBuffer` companion classes. For example factory `Buffer.Companion::auto` in most cases creates the most suitable -buffer for given reified type (for types with custom memory buffer it still better to use their own `MemoryBuffer.create()` factory). +Some kmath features require a `BufferFactory` class to operate properly. A general convention is to use functions +defined in +`Buffer` and `MutableBuffer` companion classes. For example factory `Buffer.Companion::auto` in most cases creates the +most suitable buffer for given reified type (for types with custom memory buffer it still better to use their +own `MemoryBuffer.create()` factory). ## Buffer performance -One should avoid using default boxing buffer wherever it is possible. Try to use primitive buffers or memory buffers instead +One should avoid using default boxing buffer wherever it is possible. Try to use primitive buffers or memory buffers +instead . diff --git a/docs/codestyle.md b/docs/codestyle.md index 541dc4973..73ba5f754 100644 --- a/docs/codestyle.md +++ b/docs/codestyle.md @@ -1,26 +1,20 @@ # Coding Conventions -KMath code follows general [Kotlin conventions](https://kotlinlang.org/docs/reference/coding-conventions.html), but -with a number of small changes and clarifications. +Generally, KMath code follows general [Kotlin coding conventions](https://kotlinlang.org/docs/reference/coding-conventions.html), but with a number of small changes and clarifications. ## Utility Class Naming -Filename should coincide with a name of one of the classes contained in the file or start with small letter and -describe its contents. +Filename should coincide with a name of one of the classes contained in the file or start with small letter and describe its contents. -The code convention [here](https://kotlinlang.org/docs/reference/coding-conventions.html#source-file-names) says that -file names should start with a capital letter even if file does not contain classes. Yet starting utility classes and -aggregators with a small letter seems to be a good way to visually separate those files. +The code convention [here](https://kotlinlang.org/docs/reference/coding-conventions.html#source-file-names) says that file names should start with a capital letter even if file does not contain classes. Yet starting utility classes and aggregators with a small letter seems to be a good way to visually separate those files. This convention could be changed in future in a non-breaking way. ## Private Variable Naming -Private variables' names may start with underscore `_` for of the private mutable variable is shadowed by the public -read-only value with the same meaning. +Private variables' names may start with underscore `_` for of the private mutable variable is shadowed by the public read-only value with the same meaning. -This rule does not permit underscores in names, but it is sometimes useful to "underscore" the fact that public and -private versions draw up the same entity. It is allowed only for private variables. +This rule does not permit underscores in names, but it is sometimes useful to "underscore" the fact that public and private versions draw up the same entity. It is allowed only for private variables. This convention could be changed in future in a non-breaking way. @@ -30,5 +24,4 @@ Use one-liners when they occupy single code window line both for functions and p `val b: String get() = "fff"`. The same should be performed with multiline expressions when they could be cleanly separated. -There is no universal consensus whenever use `fun a() = ...` or `fun a() { return ... }`. Yet from reader outlook -one-lines seem to better show that the property or function is easily calculated. +There is no universal consensus whenever use `fun a() = ...` or `fun a() { return ... }`. Yet from reader outlook one-lines seem to better show that the property or function is easily calculated. diff --git a/docs/contexts.md b/docs/contexts.md index 58b198046..c26333860 100644 --- a/docs/contexts.md +++ b/docs/contexts.md @@ -2,18 +2,17 @@ ## The problem -A known problem for implementing mathematics in statically-typed languages (but not only in them) is that different -sets of mathematical operators can be defined on the same mathematical objects. Sometimes there is no single way to -treat some operations, including basic arithmetic operations, on a Java/Kotlin `Number`. Sometimes there are different ways to -define the same structure, such as Euclidean and elliptic geometry vector spaces over real vectors. Another problem arises when -one wants to add some kind of behavior to an existing entity. In dynamic languages those problems are usually solved -by adding dynamic context-specific behaviors at runtime, but this solution has a lot of drawbacks. +A known problem for implementing mathematics in statically-typed languages (but not only in them) is that different sets +of mathematical operators can be defined on the same mathematical objects. Sometimes there is no single way to treat +some operations, including basic arithmetic operations, on a Java/Kotlin `Number`. Sometimes there are different ways to +define the same structure, such as Euclidean and elliptic geometry vector spaces over real vectors. Another problem +arises when one wants to add some kind of behavior to an existing entity. In dynamic languages those problems are +usually solved by adding dynamic context-specific behaviors at runtime, but this solution has a lot of drawbacks. ## Context-oriented approach -One possible solution to these problems is to divorce numerical representations from behaviors. -For example in Kotlin one can define a separate class which represents some entity without any operations, -ex. a complex number: +One possible solution to these problems is to divorce numerical representations from behaviors. For example in Kotlin +one can define a separate class representing some entity without any operations, ex. a complex number: ```kotlin data class Complex(val re: Double, val im: Double) @@ -28,9 +27,10 @@ object ComplexOperations { } ``` -In Java, applying such external operations could be very cumbersome, but Kotlin has a unique feature which allows us -implement this naturally: [extensions with receivers](https://kotlinlang.org/docs/reference/extensions.html#extension-functions). -In Kotlin, an operation on complex number could be implemented as: +In Java, applying such external operations could be cumbersome, but Kotlin has a unique feature that allows us +implement this +naturally: [extensions with receivers](https://kotlinlang.org/docs/reference/extensions.html#extension-functions). In +Kotlin, an operation on complex number could be implemented as: ```kotlin with(ComplexOperations) { c1 + c2 - c3 } @@ -52,20 +52,20 @@ In KMath, contexts are not only responsible for operations, but also for raw obj ### Type classes -An obvious candidate to get more or less the same functionality is the type class, which allows one to bind a behavior to -a specific type without modifying the type itself. On the plus side, type classes do not require explicit context +An obvious candidate to get more or less the same functionality is the type class, which allows one to bind a behavior +to a specific type without modifying the type itself. On the plus side, type classes do not require explicit context declaration, so the code looks cleaner. On the minus side, if there are different sets of behaviors for the same types, -it is impossible to combine them into one module. Also, unlike type classes, context can have parameters or even -state. For example in KMath, sizes and strides for `NDElement` or `Matrix` could be moved to context to optimize -performance in case of a large amount of structures. +it is impossible to combine them into one module. Also, unlike type classes, context can have parameters or even state. +For example in KMath, sizes and strides for `NDElement` or `Matrix` could be moved to context to optimize performance in +case of a large amount of structures. ### Wildcard imports and importing-on-demand -Sometimes, one may wish to use a single context throughout a file. In this case, is possible to import all members -from a package or file, via `import context.complex.*`. Effectively, this is the same as enclosing an entire file -with a single context. However when using multiple contexts, this technique can introduce operator ambiguity, due to -namespace pollution. If there are multiple scoped contexts which define the same operation, it is still possible to -to import specific operations as needed, without using an explicit context with extension functions, for example: +Sometimes, one may wish to use a single context throughout a file. In this case, is possible to import all members from +a package or file, via `import context.complex.*`. Effectively, this is the same as enclosing an entire file with a +single context. However, when using multiple contexts, this technique can introduce operator ambiguity, due to namespace +pollution. If there are multiple scoped contexts that define the same operation, it is still possible to import +specific operations as needed, without using an explicit context with extension functions, for example: ``` import context.complex.op1 diff --git a/docs/expressions.md b/docs/expressions.md index 1e05e5340..e6250110c 100644 --- a/docs/expressions.md +++ b/docs/expressions.md @@ -1,26 +1,21 @@ # Expressions -**Experimental: this API is in early stage and could change any time** - -Expressions is an experimental feature which allows to construct lazily or immediately calculated parametric mathematical -expressions. +Expressions is a feature, which allows constructing lazily or immediately calculated parametric mathematical expressions. The potential use-cases for it (so far) are following: -* Lazy evaluation (in general simple lambda is better, but there are some border cases) +* lazy evaluation (in general simple lambda is better, but there are some border cases); +* automatic differentiation in single-dimension and in multiple dimensions; +* generation of mathematical syntax trees with subsequent code generation for other languages; +* symbolic computations, especially differentiation (and some other actions with `kmath-symja` integration with Symja's `IExpr`—integration, simplification, and more); +* visualization with `kmath-jupyter`. -* Automatic differentiation in single-dimension and in multiple dimensions - -* Generation of mathematical syntax trees with subsequent code generation for other languages - -* Maybe symbolic computations (needs additional research) - -The workhorse of this API is `Expression` interface which exposes single `operator fun invoke(arguments: Map): T` -method. `ExpressionContext` is used to generate expressions and introduce variables. +The workhorse of this API is `Expression` interface, which exposes single `operator fun invoke(arguments: Map): T` +method. `ExpressionAlgebra` is used to generate expressions and introduce variables. Currently there are two implementations: * Generic `ExpressionField` in `kmath-core` which allows construction of custom lazy expressions -* Auto-differentiation expression in `kmath-commons` module allows to use full power of `DerivativeStructure` +* Auto-differentiation expression in `kmath-commons` module allows using full power of `DerivativeStructure` from commons-math. **TODO: add example** diff --git a/docs/features.md b/docs/features.md deleted file mode 100644 index 1068a4417..000000000 --- a/docs/features.md +++ /dev/null @@ -1,14 +0,0 @@ -# Features - -* [Algebra](algebra.md) - [Context-based](contexts.md) operations on different primitives and structures. - -* [NDStructures](nd-structure.md) - -* [Linear algebra](linear.md) - Matrices, operations and linear equations solving. To be moved to separate module. Currently supports basic -api and multiple library back-ends. - -* [Histograms](histograms.md) - Multidimensional histogram calculation and operations. - -* [Expressions](expressions.md) - -* Commons math integration diff --git a/docs/linear.md b/docs/linear.md index 6ccc6caac..2a05499ef 100644 --- a/docs/linear.md +++ b/docs/linear.md @@ -1,19 +1,31 @@ ## Basic linear algebra layout -KMath support for linear algebra organized in a context-oriented way. Meaning that operations are in most cases declared -in context classes, and are not the members of classes that store data. This allows more flexible approach to maintain multiple -back-ends. The new operations added as extensions to contexts instead of being member functions of data structures. +KMath support for linear algebra organized in a context-oriented way, which means that operations are in most cases declared in context classes, and are not the members of classes that store data. This allows more flexible approach to maintain multiple back-ends. The new operations added as extensions to contexts instead of being member functions of data structures. -Two major contexts used for linear algebra and hyper-geometry: +The main context for linear algebra over matrices and vectors is `LinearSpace`, which defines addition and dot products of matrices and vectors: -* `VectorSpace` forms a mathematical space on top of array-like structure (`Buffer` and its type alias `Point` used for geometry). +```kotlin +import space.kscience.kmath.linear.* -* `MatrixContext` forms a space-like context for 2d-structures. It does not store matrix size and therefore does not implement -`Space` interface (it is impossible to create zero element without knowing the matrix size). +LinearSpace.Companion.real { + val vec = buildVector(10) { i -> i.toDouble() } + val mat = buildMatrix(10, 10) { i, j -> i.toDouble() + j } -## Vector spaces + // Addition + vec + vec + mat + mat + // Multiplication by scalar + vec * 2.0 + mat * 2.0 -## Matrix operations + // Dot product + mat dot vec + mat dot mat +} +``` -## Back-end overview \ No newline at end of file +## Backends overview + +### EJML +### Commons Math diff --git a/docs/nd-structure.md b/docs/nd-structure.md index ab214094e..3e9203ec0 100644 --- a/docs/nd-structure.md +++ b/docs/nd-structure.md @@ -11,16 +11,16 @@ Let us consider following contexts: ```kotlin // automatically build context most suited for given type. val autoField = NDField.auto(DoubleField, dim, dim) - // specialized nd-field for Double. It works as generic Double field as well + // specialized nd-field for Double. It works as generic Double field as well. val specializedField = NDField.real(dim, dim) //A generic boxing field. It should be used for objects, not primitives. val genericField = NDField.buffered(DoubleField, dim, dim) ``` -Now let us perform several tests and see which implementation is best suited for each case: +Now let us perform several tests and see, which implementation is best suited for each case: ## Test case -In order to test performance we will take 2d-structures with `dim = 1000` and add a structure filled with `1.0` +To test performance we will take 2d-structures with `dim = 1000` and add a structure filled with `1.0` to it `n = 1000` times. ## Specialized @@ -35,8 +35,8 @@ The code to run this looks like: ``` The performance of this code is the best of all tests since it inlines all operations and is specialized for operation with doubles. We will measure everything else relative to this one, so time for this test will be `1x` (real time -on my computer is about 4.5 seconds). The only problem with this approach is that it requires to specify type -from the beginning. Everyone do so anyway, so it is the recommended approach. +on my computer is about 4.5 seconds). The only problem with this approach is that it requires specifying type +from the beginning. Everyone does so anyway, so it is the recommended approach. ## Automatic Let's do the same with automatic field inference: @@ -49,7 +49,7 @@ Let's do the same with automatic field inference: } ``` Ths speed of this operation is approximately the same as for specialized case since `NDField.auto` just -returns the same `RealNDField` in this case. Of course it is usually better to use specialized method to be sure. +returns the same `RealNDField` in this case. Of course, it is usually better to use specialized method to be sure. ## Lazy Lazy field does not produce a structure when asked, instead it generates an empty structure and fills it on-demand @@ -63,7 +63,7 @@ When one calls } } ``` -The result will be calculated almost immediately but the result will be empty. In order to get the full result +The result will be calculated almost immediately but the result will be empty. To get the full result structure one needs to call all its elements. In this case computation overhead will be huge. So this field never should be used if one expects to use the full result structure. Though if one wants only small fraction, it could save a lot of time. @@ -94,7 +94,7 @@ The boxing field produced by } } ``` -obviously is the slowest one, because it requires to box and unbox the `double` on each operation. It takes about +is the slowest one, because it requires boxing and unboxing the `double` on each operation. It takes about `15x` time (**TODO: there seems to be a problem here, it should be slow, but not that slow**). This field should never be used for primitives. @@ -123,6 +123,6 @@ for i in range(1000): ``` gives the completion time of about `1.1x`, which means that specialized kotlin code in fact is working faster (I think it is because better memory management). Of course if one writes `res += 1.0`, the performance will be different, -but it would be differenc case, because numpy overrides `+=` with in-place operations. In-place operations are +but it would be different case, because numpy overrides `+=` with in-place operations. In-place operations are available in `kmath` with `MutableNDStructure` but there is no field for it (one can still work with mapping functions). \ No newline at end of file diff --git a/docs/readme.md b/docs/readme.md new file mode 100644 index 000000000..2953b7113 --- /dev/null +++ b/docs/readme.md @@ -0,0 +1,14 @@ +# Documentation + +* [Algebra](algebra.md): [context-based](contexts.md) operations on different primitives and structures. + +* [NDStructures](nd-structure.md) + +* [Linear algebra](linear.md): matrices, operations and linear equations solving. To be moved to separate module. + Currently, supports basic API and multiple library back-ends. + +* [Histograms](histograms.md): multidimensional histogram calculation and operations. + +* [Expressions](expressions.md) + +* Commons math integration diff --git a/docs/templates/README-TEMPLATE.md b/docs/templates/README-TEMPLATE.md index bad11a31a..e75d4c5ed 100644 --- a/docs/templates/README-TEMPLATE.md +++ b/docs/templates/README-TEMPLATE.md @@ -6,10 +6,10 @@ # KMath -Could be pronounced as `key-math`. The **K**otlin **Math**ematics library was initially intended as a Kotlin-based analog to -Python's NumPy library. Later we found that kotlin is much more flexible language and allows superior architecture -designs. In contrast to `numpy` and `scipy` it is modular and has a lightweight core. The `numpy`-like experience could -be achieved with [kmath-for-real](/kmath-for-real) extension module. +Could be pronounced as `key-math`. The **K**otlin **Math**ematics library was initially intended as a Kotlin-based +analog to Python's NumPy library. Later we found that kotlin is much more flexible language and allows superior +architecture designs. In contrast to `numpy` and `scipy` it is modular and has a lightweight core. The `numpy`-like +experience could be achieved with [kmath-for-real](/kmath-for-real) extension module. [Documentation site (**WIP**)](https://mipt-npm.github.io/kmath/) @@ -21,26 +21,33 @@ be achieved with [kmath-for-real](/kmath-for-real) extension module. # Goal -* Provide a flexible and powerful API to work with mathematics abstractions in Kotlin-multiplatform (JVM, JS and Native). +* Provide a flexible and powerful API to work with mathematics abstractions in Kotlin-multiplatform (JVM, JS and Native) + . * Provide basic multiplatform implementations for those abstractions (without significant performance optimization). * Provide bindings and wrappers with those abstractions for popular optimized platform libraries. ## Non-goals -* Be like NumPy. It was the idea at the beginning, but we decided that we can do better in terms of API. +* Be like NumPy. It was the idea at the beginning, but we decided that we can do better in API. * Provide the best performance out of the box. We have specialized libraries for that. Need only API wrappers for them. * Cover all cases as immediately and in one bundle. We will modularize everything and add new features gradually. -* Provide specialized behavior in the core. API is made generic on purpose, so one needs to specialize for types, like -for `Double` in the core. For that we will have specialization modules like `kmath-for-real`, which will give better -experience for those, who want to work with specific types. +* Provide specialized behavior in the core. API is made generic on purpose, so one needs to specialize for types, like + for `Double` in the core. For that we will have specialization modules like `kmath-for-real`, which will give better + experience for those, who want to work with specific types. ## Features and stability -KMath is a modular library. Different modules provide different features with different API stability guarantees. All core modules are released with the same version, but with different API change policy. The features are described in module definitions below. The module stability could have following levels: +KMath is a modular library. Different modules provide different features with different API stability guarantees. All +core modules are released with the same version, but with different API change policy. The features are described in +module definitions below. The module stability could have the following levels: -* **PROTOTYPE**. On this level there are no compatibility guarantees. All methods and classes form those modules could break any moment. You can still use it, but be sure to fix the specific version. -* **EXPERIMENTAL**. The general API is decided, but some changes could be made. Volatile API is marked with `@UnstableKmathAPI` or other stability warning annotations. -* **DEVELOPMENT**. API breaking generally follows semantic versioning ideology. There could be changes in minor versions, but not in patch versions. API is protected with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool. +* **PROTOTYPE**. On this level there are no compatibility guarantees. All methods and classes form those modules could + break any moment. You can still use it, but be sure to fix the specific version. +* **EXPERIMENTAL**. The general API is decided, but some changes could be made. Volatile API is marked + with `@UnstableKmathAPI` or other stability warning annotations. +* **DEVELOPMENT**. API breaking generally follows semantic versioning ideology. There could be changes in minor + versions, but not in patch versions. API is protected + with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool. * **STABLE**. The API stabilized. Breaking changes are allowed only in major releases. @@ -78,30 +85,33 @@ $modules ## Multi-platform support -KMath is developed as a multi-platform library, which means that most of the interfaces are declared in the -[common source sets](/kmath-core/src/commonMain) and implemented there wherever it is possible. In some cases, features -are delegated to platform-specific implementations even if they could be provided in the common module for performance -reasons. Currently, the Kotlin/JVM is the primary platform, however Kotlin/Native and Kotlin/JS contributions and +KMath is developed as a multi-platform library, which means that most of the interfaces are declared in the +[common source sets](/kmath-core/src/commonMain) and implemented there wherever it is possible. In some cases, features +are delegated to platform-specific implementations even if they could be provided in the common module for performance +reasons. Currently, the Kotlin/JVM is the primary platform, however Kotlin/Native and Kotlin/JS contributions and feedback are also welcome. ## Performance -Calculation performance is one of major goals of KMath in the future, but in some cases it is impossible to achieve -both performance and flexibility. +Calculation performance is one of major goals of KMath in the future, but in some cases it is impossible to achieve both +performance and flexibility. -We expect to focus on creating convenient universal API first and then work on increasing performance for specific -cases. We expect the worst KMath benchmarks will perform better than native Python, but worse than optimized -native/SciPy (mostly due to boxing operations on primitive numbers). The best performance of optimized parts could be +We expect to focus on creating convenient universal API first and then work on increasing performance for specific +cases. We expect the worst KMath benchmarks will perform better than native Python, but worse than optimized +native/SciPy (mostly due to boxing operations on primitive numbers). The best performance of optimized parts could be better than SciPy. ## Requirements -KMath currently relies on JDK 11 for compilation and execution of Kotlin-JVM part. We recommend to use GraalVM-CE 11 for execution in order to get better performance. +KMath currently relies on JDK 11 for compilation and execution of Kotlin-JVM part. We recommend to use GraalVM-CE 11 for +execution to get better performance. ### Repositories -Release and development artifacts are accessible from mipt-npm [Space](https://www.jetbrains.com/space/) repository `https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven` (see documentation of -[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details). The repository could be reached through [repo.kotlin.link](https://repo.kotlin.link) proxy: +Release and development artifacts are accessible from mipt-npm [Space](https://www.jetbrains.com/space/) +repository `https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven` (see documentation of +[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details). The repository could +be reached through [repo.kotlin.link](https://repo.kotlin.link) proxy: ```kotlin repositories { @@ -118,7 +128,7 @@ Gradle `6.0+` is required for multiplatform artifacts. ## Contributing -The project requires a lot of additional work. The most important thing we need is a feedback about what features are -required the most. Feel free to create feature requests. We are also welcome to code contributions, -especially in issues marked with +The project requires a lot of additional work. The most important thing we need is a feedback about what features are +required the most. Feel free to create feature requests. We are also welcome to code contributions, especially in issues +marked with [waiting for a hero](https://github.com/mipt-npm/kmath/labels/waiting%20for%20a%20hero) label. diff --git a/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt b/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt index 6ceaa962a..dec3bfb81 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt @@ -13,8 +13,8 @@ import space.kscience.kmath.kotlingrad.toKotlingradExpression import space.kscience.kmath.operations.DoubleField /** - * In this example, x^2-4*x-44 function is differentiated with Kotlin∇, and the autodiff result is compared with - * valid derivative in a certain point. + * In this example, *x2 − 4 x − 44* function is differentiated with Kotlin∇, and the + * derivation result is compared with valid derivative in a certain point. */ fun main() { val actualDerivative = "x^2-4*x-44" diff --git a/examples/src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt b/examples/src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt index a9eca0500..7e09faeff 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt @@ -13,8 +13,8 @@ import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.symja.toSymjaExpression /** - * In this example, x^2-4*x-44 function is differentiated with Symja, and the autodiff result is compared with - * valid derivative in a certain point. + * In this example, *x2 − 4 x − 44* function is differentiated with Symja, and the + * derivation result is compared with valid derivative in a certain point. */ fun main() { val actualDerivative = "x^2-4*x-44" diff --git a/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt b/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt index 5e64235e3..9118d09ae 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt @@ -25,8 +25,7 @@ import space.kscience.plotly.models.TraceValues import kotlin.math.pow import kotlin.math.sqrt -//Forward declaration of symbols that will be used in expressions. -// This declaration is required for +// Forward declaration of symbols that will be used in expressions. private val a by symbol private val b by symbol private val c by symbol diff --git a/examples/src/main/kotlin/space/kscience/kmath/jafama/JafamaDemo.kt b/examples/src/main/kotlin/space/kscience/kmath/jafama/JafamaDemo.kt new file mode 100644 index 000000000..9c3d0fdbe --- /dev/null +++ b/examples/src/main/kotlin/space/kscience/kmath/jafama/JafamaDemo.kt @@ -0,0 +1,15 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.jafama + +import space.kscience.kmath.operations.invoke + +fun main() { + val a = 2.0 + val b = StrictJafamaDoubleField { exp(a) } + println(JafamaDoubleField { b + a }) + println(StrictJafamaDoubleField { ln(b) }) +} diff --git a/examples/src/main/kotlin/space/kscience/kmath/jafama/KMathaJafamaDemo.kt b/examples/src/main/kotlin/space/kscience/kmath/jafama/KMathaJafamaDemo.kt deleted file mode 100644 index 879aab08f..000000000 --- a/examples/src/main/kotlin/space/kscience/kmath/jafama/KMathaJafamaDemo.kt +++ /dev/null @@ -1,17 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ - -package space.kscience.kmath.jafama - -import net.jafama.FastMath - - -fun main(){ - val a = JafamaDoubleField.number(2.0) - val b = StrictJafamaDoubleField.power(FastMath.E,a) - - println(JafamaDoubleField.add(b,a)) - println(StrictJafamaDoubleField.ln(b)) -} diff --git a/examples/src/main/kotlin/space/kscience/kmath/stat/DistributionDemo.kt b/examples/src/main/kotlin/space/kscience/kmath/stat/DistributionDemo.kt index b319766e3..bde83cea9 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/stat/DistributionDemo.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/stat/DistributionDemo.kt @@ -10,9 +10,6 @@ import space.kscience.kmath.chains.Chain import space.kscience.kmath.chains.collectWithState import space.kscience.kmath.distributions.NormalDistribution -/** - * The state of distribution averager. - */ private data class AveragingChainState(var num: Int = 0, var value: Double = 0.0) /** diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt index 501bf98db..e1621d477 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt @@ -32,7 +32,7 @@ fun main() { // automatically build context most suited for given type. val autoField = AlgebraND.auto(DoubleField, dim, dim) - // specialized nd-field for Double. It works as generic Double field as well + // specialized nd-field for Double. It works as generic Double field as well. val realField = AlgebraND.real(dim, dim) //A generic boxing field. It should be used for objects, not primitives. val boxingField = AlgebraND.field(DoubleField, Buffer.Companion::boxing, dim, dim) diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt index 74795cc68..ad6890b15 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt @@ -17,7 +17,7 @@ fun main() = BroadcastDoubleTensorAlgebra { // work in context with broadcast m dataset += fromArray( intArrayOf(5), - doubleArrayOf(0.0, 1.0, 1.5, 3.0, 5.0) // rows means + doubleArrayOf(0.0, 1.0, 1.5, 3.0, 5.0) // row means ) @@ -28,7 +28,7 @@ fun main() = BroadcastDoubleTensorAlgebra { // work in context with broadcast m println("Mean:\n$mean") println("Standard deviation:\n$std") - // also we can calculate other statistic as minimum and maximum of rows + // also, we can calculate other statistic as minimum and maximum of rows println("Minimum:\n${dataset.min(0, false)}") println("Maximum:\n${dataset.max(0, false)}") diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt index 6453ca44e..3e6a60c31 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt @@ -42,7 +42,7 @@ fun main() = BroadcastDoubleTensorAlgebra {// work in context with linear operat // get P, L, U such that PA = LU val (p, l, u) = a.lu() - // check that P is permutation matrix + // check P is permutation matrix println("P:\n$p") // L is lower triangular matrix and U is upper triangular matrix println("L:\n$l") diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt index b262bee02..55a9aa67a 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt @@ -186,7 +186,7 @@ fun main() = BroadcastDoubleTensorAlgebra { x += fromArray( intArrayOf(5), - doubleArrayOf(0.0, -1.0, -2.5, -3.0, 5.5) // rows means + doubleArrayOf(0.0, -1.0, -2.5, -3.0, 5.5) // row means ) diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt index 411e048d7..b973abdef 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt @@ -65,8 +65,8 @@ fun main(): Unit = BroadcastDoubleTensorAlgebra { // work in context with broad val datasetReduced = v dot stack(listOf(xScaled, yScaled)) println("Reduced data:\n$datasetReduced") - // we can restore original data from reduced data. - // for example, find 7th element of dataset + // we can restore original data from reduced data; + // for example, find 7th element of dataset. val n = 7 val restored = (datasetReduced[n] dot v.view(intArrayOf(1, 2))) * std + mean println("Original value:\n${dataset[n]}") diff --git a/kmath-ast/README.md b/kmath-ast/README.md index c3c4c38a1..686506f6f 100644 --- a/kmath-ast/README.md +++ b/kmath-ast/README.md @@ -106,7 +106,7 @@ var executable = function (constants, arguments) { }; ``` -JS also supports very experimental expression optimization with [WebAssembly](https://webassembly.org/) IR generation. +JS also supports experimental expression optimization with [WebAssembly](https://webassembly.org/) IR generation. Currently, only expressions inside `DoubleField` and `IntRing` are supported. ```kotlin @@ -161,7 +161,10 @@ public fun main() { Result LaTeX: +
+ ![](https://latex.codecogs.com/gif.latex?%5Coperatorname{exp}%5C,%5Cleft(%5Csqrt{x}%5Cright)-%5Cfrac{%5Cfrac{%5Coperatorname{arcsin}%5C,%5Cleft(2%5C,x%5Cright)}{2%5Ctimes10^{10}%2Bx^{3}}}{12}+x^{2/3}) +
Result MathML (can be used with MathJax or other renderers): diff --git a/kmath-ast/docs/README-TEMPLATE.md b/kmath-ast/docs/README-TEMPLATE.md index b90f8ff08..9494af63a 100644 --- a/kmath-ast/docs/README-TEMPLATE.md +++ b/kmath-ast/docs/README-TEMPLATE.md @@ -77,7 +77,7 @@ var executable = function (constants, arguments) { }; ``` -JS also supports very experimental expression optimization with [WebAssembly](https://webassembly.org/) IR generation. +JS also supports experimental expression optimization with [WebAssembly](https://webassembly.org/) IR generation. Currently, only expressions inside `DoubleField` and `IntRing` are supported. ```kotlin @@ -132,7 +132,10 @@ public fun main() { Result LaTeX: +
+ ![](https://latex.codecogs.com/gif.latex?%5Coperatorname{exp}%5C,%5Cleft(%5Csqrt{x}%5Cright)-%5Cfrac{%5Cfrac{%5Coperatorname{arcsin}%5C,%5Cleft(2%5C,x%5Cright)}{2%5Ctimes10^{10}%2Bx^{3}}}{12}+x^{2/3}) +
Result MathML (can be used with MathJax or other renderers): diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathSyntax.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathSyntax.kt index 38450403d..ee23ab408 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathSyntax.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathSyntax.kt @@ -8,7 +8,7 @@ package space.kscience.kmath.ast.rendering import space.kscience.kmath.misc.UnstableKMathAPI /** - * Mathematical typography syntax node. + * Syntax node for mathematical typography. * * @author Iaroslav Postovalov */ @@ -301,7 +301,7 @@ public data class BinaryPlusSyntax( } /** - * Represents binary, infix subtraction (*42 - 42*). + * Represents binary, infix subtraction (*42 − 42*). * * @param left The minuend. * @param right The subtrahend. diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/SyntaxRenderer.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/SyntaxRenderer.kt index fb2b3b66f..362c07d72 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/SyntaxRenderer.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/SyntaxRenderer.kt @@ -9,7 +9,7 @@ import space.kscience.kmath.misc.UnstableKMathAPI /** * Abstraction of writing [MathSyntax] as a string of an actual markup language. Typical implementation should - * involve traversal of MathSyntax with handling each its subtype. + * involve traversal of MathSyntax with handling each subtype. * * @author Iaroslav Postovalov */ diff --git a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt index 37e9a8c19..8a4804916 100644 --- a/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt +++ b/kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/features.kt @@ -49,7 +49,7 @@ else NumberSyntax(string = s) /** - * Special printing for numeric types which are printed in form of + * Special printing for numeric types that are printed in form of * *('-'? (DIGIT+ ('.' DIGIT+)? ('E' '-'? DIGIT+)? | 'Infinity')) | 'NaN'*. * * @property types The suitable types. @@ -110,7 +110,7 @@ public class PrettyPrintFloats(public val types: Set>) : Rend } /** - * Special printing for numeric types which are printed in form of *'-'? DIGIT+*. + * Special printing for numeric types that are printed in form of *'-'? DIGIT+*. * * @property types The suitable types. * @author Iaroslav Postovalov @@ -155,7 +155,7 @@ public class PrettyPrintPi(public val symbols: Set) : RenderFeature { } /** - * Abstract printing of unary operations which discards [MST] if their operation is not in [operations] or its type is + * Abstract printing of unary operations that discards [MST] if their operation is not in [operations] or its type is * not [MST.Unary]. * * @param operations the allowed operations. If `null`, any operation is accepted. @@ -176,7 +176,7 @@ public abstract class Unary(public val operations: Collection?) : Render } /** - * Abstract printing of unary operations which discards [MST] if their operation is not in [operations] or its type is + * Abstract printing of unary operations that discards [MST] if their operation is not in [operations] or its type is * not [MST.Binary]. * * @property operations the allowed operations. If `null`, any operation is accepted. diff --git a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt index a84248f63..06e040e93 100644 --- a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt +++ b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt @@ -57,13 +57,13 @@ internal fun MethodVisitor.label(): Label = Label().also(::visitLabel) /** * Creates a class name for [Expression] subclassed to implement [mst] provided. * - * This methods helps to avoid collisions of class name to prevent loading several classes with the same name. If there + * These methods help to avoid collisions of class name to prevent loading several classes with the same name. If there * is a colliding class, change [collision] parameter or leave it `0` to check existing classes recursively. * * @author Iaroslav Postovalov */ internal tailrec fun buildName(mst: MST, collision: Int = 0): String { - val name = "space.kscience.kmath.asm.generated.AsmCompiledExpression_${mst.hashCode()}_$collision" + val name = "space.kscience.kmath.asm.generated.CompiledExpression_${mst.hashCode()}_$collision" try { Class.forName(name) diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt index 0925fee7e..d5473063a 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt @@ -31,7 +31,7 @@ public class DerivativeStructureField( override fun number(value: Number): DerivativeStructure = const(value.toDouble()) /** - * A class that implements both [DerivativeStructure] and a [Symbol] + * A class implementing both [DerivativeStructure] and [Symbol]. */ public inner class DerivativeStructureSymbol( size: Int, diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt index 0bf1d53f0..3c57f5467 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt @@ -34,7 +34,7 @@ internal class AutoDiffTest { println(z.derivative(x)) println(z.derivative(y, x)) assertEquals(z.derivative(x, y), z.derivative(y, x)) - //check that improper order cause failure + // check improper order cause failure assertFails { z.derivative(x, x, y) } } } diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt index 15c9120ec..b0e5d7904 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt @@ -27,7 +27,7 @@ internal class OptimizeTest { fun testGradientOptimization() { val result = normal.optimize(x, y) { initialGuess(x to 1.0, y to 1.0) - //no need to select optimizer. Gradient optimizer is used by default because gradients are provided by function + // no need to select optimizer. Gradient optimizer is used by default because gradients are provided by function. } println(result.point) println(result.value) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt index ce1265b2f..19befe6e6 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt @@ -6,7 +6,7 @@ package space.kscience.kmath.expressions /** - * Represents expression which structure can be differentiated. + * Represents expression, which structure can be differentiated. * * @param T the type this expression takes as argument and returns. */ diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt index 84e66918f..5105c2bec 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt @@ -43,7 +43,7 @@ public operator fun Expression.invoke(vararg pairs: Pair): T = /** * Calls this expression from arguments. * - * @param pairs the pairs of arguments' names to values. + * @param pairs the pairs of arguments' names to value. * @return a value. */ @JvmName("callByString") @@ -60,7 +60,7 @@ public operator fun Expression.invoke(vararg pairs: Pair): T = public interface ExpressionAlgebra : Algebra { /** - * A constant expression which does not depend on arguments + * A constant expression that does not depend on arguments. */ public fun const(value: T): E } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt index 5935424b6..838118339 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt @@ -18,7 +18,7 @@ public abstract class FunctionalExpressionAlgebra>( public val algebra: A, ) : ExpressionAlgebra> { /** - * Builds an Expression of constant expression which does not depend on arguments. + * Builds an Expression of constant expression that does not depend on arguments. */ override fun const(value: T): Expression = Expression { value } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSolver.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSolver.kt index 9c3ffd819..d63f141ba 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSolver.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSolver.kt @@ -8,8 +8,8 @@ package space.kscience.kmath.linear import space.kscience.kmath.nd.as1D /** - * A group of methods to solve for *X* in equation *X = A -1 · B*, where *A* and *B* are matrices or - * vectors. + * A group of methods to solve for *X* in equation *X = A−1 · B*, where *A* and *B* are + * matrices or vectors. * * @param T the type of items. */ diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt index badf2794e..63b881105 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt @@ -164,7 +164,7 @@ public interface LinearSpace> { public operator fun T.times(v: Point): Point = v * this /** - * Get a feature of the structure in this scope. Structure features take precedence other context features + * Get a feature of the structure in this scope. Structure features take precedence other context features. * * @param F the type of feature. * @param structure the structure. @@ -195,7 +195,7 @@ public interface LinearSpace> { } /** - * Get a feature of the structure in this scope. Structure features take precedence other context features + * Get a feature of the structure in this scope. Structure features take precedence other context features. * * @param T the type of items in the matrices. * @param F the type of feature. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt index f3653d394..25f53f65d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt @@ -114,7 +114,7 @@ public fun > LinearSpace>.lup( for (i in 0 until col) sum -= luRow[i] * lu[i, col] luRow[col] = sum - // maintain best permutation choice + // maintain the best permutation choice if (abs(sum) > largest) { largest = abs(sum) max = row @@ -241,7 +241,7 @@ public fun LinearSpace.solveWithLup(a: Matrix, b: M } /** - * Inverses a square matrix using LUP decomposition. Non square matrix will throw a error. + * Inverses a square matrix using LUP decomposition. Non square matrix will throw an error. */ public fun LinearSpace.inverseWithLup(matrix: Matrix): Matrix = solveWithLup(matrix, one(matrix.rowNum, matrix.colNum)) \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt index e0d733a66..b70e9d8a9 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixFeatures.kt @@ -31,7 +31,7 @@ public object ZeroFeature : DiagonalFeature public object UnitFeature : DiagonalFeature /** - * Matrices with this feature can be inverted: [inverse] = `a`-1 where `a` is the owning matrix. + * Matrices with this feature can be inverted: *[inverse] = a−1* where *a* is the owning matrix. * * @param T the type of matrices' items. */ diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt index 4b624b6a0..df3852d72 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt @@ -22,7 +22,8 @@ public class MatrixWrapper internal constructor( ) : Matrix by origin { /** - * Get the first feature matching given class. Does not guarantee that matrix has only one feature matching the criteria + * Get the first feature matching given class. Does not guarantee that matrix has only one feature matching the + * criteria. */ @UnstableKMathAPI @Suppress("UNCHECKED_CAST") @@ -61,7 +62,7 @@ public operator fun Matrix.plus(newFeatures: Collection LinearSpace>.one( rows: Int, @@ -87,7 +88,7 @@ public class TransposedFeature(public val original: Matrix) : Ma * Create a virtual transposed matrix without copying anything. `A.transpose().transpose() === A` */ @OptIn(UnstableKMathAPI::class) -public fun Matrix.transpose(): Matrix = getFeature>()?.original ?: VirtualMatrix( +public fun Matrix.transpose(): Matrix = getFeature>()?.original ?: (VirtualMatrix( colNum, rowNum, -) { i, j -> get(j, i) } + TransposedFeature(this) \ No newline at end of file +) { i, j -> get(j, i) } + TransposedFeature(this)) \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt index e521e6237..99f959c86 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/annotations.kt @@ -7,8 +7,8 @@ package space.kscience.kmath.misc /** * Marks declarations that are still experimental in the KMath APIs, which means that the design of the corresponding - * declarations has open issues which may (or may not) lead to their changes in the future. Roughly speaking, there is - * a chance that those declarations will be deprecated in the near future or the semantics of their behavior may change + * declarations has open issues that may (or may not) lead to their changes in the future. Roughly speaking, there is + * a chance of those declarations will be deprecated in the near future or the semantics of their behavior may change * in some way that may break some code. */ @MustBeDocumented @@ -17,7 +17,7 @@ package space.kscience.kmath.misc public annotation class UnstableKMathAPI /** - * Marks API which could cause performance problems. The code, marked by this API is not necessary slow, but could cause + * Marks API that could cause performance problems. The code marked by this API is unnecessary slow but could cause * slow-down in some cases. Refer to the documentation and benchmark it to be sure. */ @MustBeDocumented diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt index 7b0b06a58..454a33e86 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/AlgebraND.kt @@ -11,7 +11,7 @@ import space.kscience.kmath.structures.* import kotlin.reflect.KClass /** - * An exception is thrown when the expected ans actual shape of NDArray differs. + * An exception is thrown when the expected and actual shape of NDArray differ. * * @property expected the expected shape. * @property actual the actual shape. @@ -63,7 +63,7 @@ public interface AlgebraND> { structure.map { value -> this@invoke(value) } /** - * Get a feature of the structure in this scope. Structure features take precedence other context features + * Get a feature of the structure in this scope. Structure features take precedence other context features. * * @param F the type of feature. * @param structure the structure. @@ -79,7 +79,7 @@ public interface AlgebraND> { /** - * Get a feature of the structure in this scope. Structure features take precedence other context features + * Get a feature of the structure in this scope. Structure features take precedence other context features. * * @param T the type of items in the matrices. * @param F the type of feature. @@ -130,15 +130,6 @@ public interface GroupND> : Group>, AlgebraND override fun add(a: StructureND, b: StructureND): StructureND = combine(a, b) { aValue, bValue -> add(aValue, bValue) } -// /** -// * Element-wise multiplication by scalar. -// * -// * @param a the multiplicand. -// * @param k the multiplier. -// * @return the product. -// */ -// override fun multiply(a: NDStructure, k: Number): NDStructure = a.map { multiply(it, k) } - // TODO move to extensions after KEEP-176 /** @@ -226,7 +217,7 @@ public interface RingND> : Ring>, GroupND> : Field>, RingND, ScaleOperations> { +public interface FieldND> : Field>, RingND { /** * Element-wise division. * @@ -256,6 +247,15 @@ public interface FieldND> : Field>, RingND): StructureND = arg.map { divide(it, this@div) } + /** + * Element-wise scaling. + * + * @param a the multiplicand. + * @param value the multiplier. + * @return the product. + */ + override fun scale(a: StructureND, value: Double): StructureND = a.map { scale(it, value) } + // @ThreadLocal // public companion object { // private val realNDFieldCache: MutableMap = hashMapOf() diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt index d916bc0d6..1af80149c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt @@ -110,7 +110,7 @@ internal class MutableBuffer1DWrapper(val buffer: MutableBuffer) : Mutable } /** - * Represent a [StructureND] as [Structure1D]. Throw error in case of dimension mismatch + * Represent a [StructureND] as [Structure1D]. Throw error in case of dimension mismatch. */ public fun StructureND.as1D(): Structure1D = this as? Structure1D ?: if (shape.size == 1) { when (this) { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt index cb69bdc00..293faaeda 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt @@ -144,13 +144,16 @@ private class MutableStructure2DWrapper(val structure: MutableStructureND) } /** - * Represent a [StructureND] as [Structure1D]. Throw error in case of dimension mismatch + * Represents a [StructureND] as [Structure2D]. Throws runtime error in case of dimension mismatch. */ public fun StructureND.as2D(): Structure2D = this as? Structure2D ?: when (shape.size) { 2 -> Structure2DWrapper(this) else -> error("Can't create 2d-structure from ${shape.size}d-structure") } +/** + * Represents a [StructureND] as [Structure2D]. Throws runtime error in case of dimension mismatch. + */ public fun MutableStructureND.as2D(): MutableStructure2D = this as? MutableStructure2D ?: when (shape.size) { 2 -> MutableStructure2DWrapper(this) else -> error("Can't create 2d-structure from ${shape.size}d-structure") diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt index 1ad8289bc..716bd15f3 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt @@ -16,7 +16,7 @@ import kotlin.reflect.KClass public interface StructureFeature /** - * Represents n-dimensional structure, i.e. multidimensional container of items of the same type and size. The number + * Represents n-dimensional structure i.e., multidimensional container of items of the same type and size. The number * of dimensions and items in an array is defined by its shape, which is a sequence of non-negative integers that * specify the sizes of each dimension. * @@ -26,7 +26,7 @@ public interface StructureFeature */ public interface StructureND { /** - * The shape of structure, i.e. non-empty sequence of non-negative integers that specify sizes of dimensions of + * The shape of structure i.e., non-empty sequence of non-negative integers that specify sizes of dimensions of * this structure. */ public val shape: IntArray @@ -53,8 +53,8 @@ public interface StructureND { public fun elements(): Sequence> /** - * Feature is some additional structure information which allows to access it special properties or hints. - * If the feature is not present, null is returned. + * Feature is some additional structure information that allows to access it special properties or hints. + * If the feature is not present, `null` is returned. */ @UnstableKMathAPI public fun getFeature(type: KClass): F? = null @@ -177,7 +177,7 @@ public inline fun MutableStructureND.mapInPlace(action: (IntArray, T) -> elements().forEach { (index, oldValue) -> this[index] = action(index, oldValue) } /** - * A way to convert ND index to linear one and back. + * A way to convert ND indices to linear one and back. */ public interface Strides { /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt index cef34dce2..1009742e1 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt @@ -23,15 +23,13 @@ public interface Algebra { * Wraps a raw string to [T] object. This method is designed for three purposes: * * 1. Mathematical constants (`e`, `pi`). - * 2. Variables for expression-like contexts (`a`, `b`, `c`...). - * 3. Literals (`{1, 2}`, (`(3; 4)`)). + * 1. Variables for expression-like contexts (`a`, `b`, `c`…). + * 1. Literals (`{1, 2}`, (`(3; 4)`)). * - * In case if algebra can't parse the string, this method must throw [kotlin.IllegalStateException]. - * - * Returns `null` if symbol could not be bound to the context + * If algebra can't parse the string, then this method must throw [kotlin.IllegalStateException]. * * @param value the raw string. - * @return an object. + * @return an object or `null` if symbol could not be bound to the context. */ public fun bindSymbolOrNull(value: String): T? = null @@ -42,13 +40,12 @@ public interface Algebra { bindSymbolOrNull(value) ?: error("Symbol '$value' is not supported in $this") /** - * Dynamically dispatches an unary operation with the certain name. + * Dynamically dispatches a unary operation with the certain name. * - * This function must has two features: + * Implementations must fulfil the following requirements: * - * 1. In case operation is not defined in the structure, the function throws [kotlin.IllegalStateException]. - * 2. This function is symmetric with second `unaryOperation` overload: - * i.e. `unaryOperationFunction(a)(b) == unaryOperation(a, b)`. + * 1. If operation is not defined in the structure, then the function throws [kotlin.IllegalStateException]. + * 1. Equivalence to [unaryOperation]: for any `a` and `b`, `unaryOperationFunction(a)(b) == unaryOperation(a, b)`. * * @param operation the name of operation. * @return an operation. @@ -57,13 +54,13 @@ public interface Algebra { error("Unary operation $operation not defined in $this") /** - * Dynamically invokes an unary operation with the certain name. + * Dynamically invokes a unary operation with the certain name. * - * This function must follow two properties: + * Implementations must fulfil the following requirements: * - * 1. In case if operation is not defined in the structure, the function throws [kotlin.IllegalStateException]. - * 2. This function is symmetric with second [unaryOperationFunction] overload: - * i.e. `unaryOperationFunction(a)(b) == unaryOperation(a, b)`. + * 1. If operation is not defined in the structure, then the function throws [kotlin.IllegalStateException]. + * 1. Equivalence to [unaryOperationFunction]: i.e., for any `a` and `b`, + * `unaryOperationFunction(a)(b) == unaryOperation(a, b)`. * * @param operation the name of operation. * @param arg the argument of operation. @@ -74,11 +71,11 @@ public interface Algebra { /** * Dynamically dispatches a binary operation with the certain name. * - * This function must follow two properties: + * Implementations must fulfil the following requirements: * - * 1. In case if operation is not defined in the structure, the function throws [kotlin.IllegalStateException]. - * 2. This function is symmetric with second [binaryOperationFunction] overload: - * i.e. `binaryOperationFunction(a)(b, c) == binaryOperation(a, b, c)`. + * 1. If operation is not defined in the structure, then the function throws [kotlin.IllegalStateException]. + * 1. Equivalence to [binaryOperation]: for any `a`, `b`, and `c`, + * `binaryOperationFunction(a)(b, c) == binaryOperation(a, b, c)`. * * @param operation the name of operation. * @return an operation. @@ -89,11 +86,11 @@ public interface Algebra { /** * Dynamically invokes a binary operation with the certain name. * - * This function must follow two properties: + * Implementations must fulfil the following requirements: * - * 1. In case if operation is not defined in the structure, the function throws [kotlin.IllegalStateException]. - * 2. This function is symmetric with second [binaryOperationFunction] overload: - * i.e. `binaryOperationFunction(a)(b, c) == binaryOperation(a, b, c)`. + * 1. If operation is not defined in the structure, then the function throws [kotlin.IllegalStateException]. + * 1. Equivalence to [binaryOperationFunction]: for any `a`, `b`, and `c`, + * `binaryOperationFunction(a)(b, c) == binaryOperation(a, b, c)`. * * @param operation the name of operation. * @param left the first argument of operation. @@ -115,7 +112,7 @@ public fun Algebra.bindSymbol(symbol: Symbol): T = bindSymbol(symbol.iden public inline operator fun , R> A.invoke(block: A.() -> R): R = run(block) /** - * Represents group without neutral element (also known as inverse semigroup), i.e. algebraic structure with + * Represents group without neutral element (also known as inverse semigroup) i.e., algebraic structure with * associative, binary operation [add]. * * @param T the type of element of this semispace. @@ -130,7 +127,7 @@ public interface GroupOperations : Algebra { */ public fun add(a: T, b: T): T - // Operations to be performed in this context. Could be moved to extensions in case of KEEP-176 + // Operations to be performed in this context. Could be moved to extensions in case of KEEP-176. /** * The negation of this element. @@ -192,7 +189,7 @@ public interface GroupOperations : Algebra { } /** - * Represents group, i.e. algebraic structure with associative, binary operation [add]. + * Represents group i.e., algebraic structure with associative, binary operation [add]. * * @param T the type of element of this semispace. */ @@ -204,7 +201,7 @@ public interface Group : GroupOperations { } /** - * Represents ring without multiplicative and additive identities, i.e. algebraic structure with + * Represents ring without multiplicative and additive identities i.e., algebraic structure with * associative, binary, commutative operation [add] and associative, operation [multiply] distributive over [add]. * * @param T the type of element of this semiring. @@ -240,7 +237,7 @@ public interface RingOperations : GroupOperations { } /** - * Represents ring, i.e. algebraic structure with two associative binary operations called "addition" and + * Represents ring i.e., algebraic structure with two associative binary operations called "addition" and * "multiplication" and their neutral elements. * * @param T the type of element of this ring. @@ -253,8 +250,9 @@ public interface Ring : Group, RingOperations { } /** - * Represents field without without multiplicative and additive identities, i.e. algebraic structure with associative, binary, commutative operations - * [add] and [multiply]; binary operation [divide] as multiplication of left operand by reciprocal of right one. + * Represents field without multiplicative and additive identities i.e., algebraic structure with associative, binary, + * commutative operations [add] and [multiply]; binary operation [divide] as multiplication of left operand by + * reciprocal of right one. * * @param T the type of element of this semifield. */ @@ -291,7 +289,7 @@ public interface FieldOperations : RingOperations { } /** - * Represents field, i.e. algebraic structure with three operations: associative, commutative addition and + * Represents field i.e., algebraic structure with three operations: associative, commutative addition and * multiplication, and division. **This interface differs from the eponymous mathematical definition: fields in KMath * also support associative multiplication by scalar.** * diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt index 403a9c9b1..6b0e2cabd 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt @@ -8,7 +8,7 @@ package space.kscience.kmath.operations import space.kscience.kmath.misc.UnstableKMathAPI /** - * The generic mathematics elements which is able to store its context + * The generic mathematics elements that is able to store its context * * @param C the type of mathematical context for this element. * @param T the type wrapped by this wrapper. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 4ccbfc531..8111691aa 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -121,7 +121,7 @@ public class BigInt internal constructor( var r = ZERO val bitSize = - (BASE_SIZE * (this.magnitude.size - 1) + log2(this.magnitude.lastOrNull()?.toFloat() ?: 0f + 1)).toInt() + (BASE_SIZE * (this.magnitude.size - 1) + log2(this.magnitude.lastOrNull()?.toFloat() ?: (0f + 1))).toInt() for (i in bitSize downTo 0) { r = r shl 1 @@ -442,7 +442,7 @@ public fun UIntArray.toBigInt(sign: Byte): BigInt { } /** - * Returns null if a valid number can not be read from a string + * Returns `null` if a valid number cannot be read from a string */ public fun String.parseBigInteger(): BigInt? { if (isEmpty()) return null diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/NumericAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/NumericAlgebra.kt index 7a8fa5668..92070b33d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/NumericAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/NumericAlgebra.kt @@ -26,11 +26,11 @@ public interface NumericAlgebra : Algebra { /** * Dynamically dispatches a binary operation with the certain name with numeric first argument. * - * This function must follow two properties: + * Implementations must fulfil the following requirements: * - * 1. In case if operation is not defined in the structure, the function throws [kotlin.IllegalStateException]. - * 2. This function is symmetric with the other [leftSideNumberOperation] overload: - * i.e. `leftSideNumberOperationFunction(a)(b, c) == leftSideNumberOperation(a, b)`. + * 1. If operation is not defined in the structure, then function throws [kotlin.IllegalStateException]. + * 1. Equivalence to [leftSideNumberOperation]: for any `a`, `b`, and `c`, + * `leftSideNumberOperationFunction(a)(b, c) == leftSideNumberOperation(a, b)`. * * @param operation the name of operation. * @return an operation. @@ -41,11 +41,11 @@ public interface NumericAlgebra : Algebra { /** * Dynamically invokes a binary operation with the certain name with numeric first argument. * - * This function must follow two properties: + * Implementations must fulfil the following requirements: * - * 1. In case if operation is not defined in the structure, the function throws [kotlin.IllegalStateException]. - * 2. This function is symmetric with second [leftSideNumberOperation] overload: - * i.e. `leftSideNumberOperationFunction(a)(b, c) == leftSideNumberOperation(a, b, c)`. + * 1. If operation is not defined in the structure, then the function throws [kotlin.IllegalStateException]. + * 1. Equivalence to [leftSideNumberOperation]: for any `a`, `b`, and `c`, + * `leftSideNumberOperationFunction(a)(b, c) == leftSideNumberOperation(a, b, c)`. * * @param operation the name of operation. * @param left the first argument of operation. @@ -58,11 +58,11 @@ public interface NumericAlgebra : Algebra { /** * Dynamically dispatches a binary operation with the certain name with numeric first argument. * - * This function must follow two properties: + * Implementations must fulfil the following requirements: * - * 1. In case if operation is not defined in the structure, the function throws [kotlin.IllegalStateException]. - * 2. This function is symmetric with the other [rightSideNumberOperationFunction] overload: - * i.e. `rightSideNumberOperationFunction(a)(b, c) == leftSideNumberOperation(a, b, c)`. + * 1. If operation is not defined in the structure, then the function throws [kotlin.IllegalStateException]. + * 1. Equivalence to [rightSideNumberOperation]: for any `a`, `b`, and `c`, + * `rightSideNumberOperationFunction(a)(b, c) == leftSideNumberOperation(a, b, c)`. * * @param operation the name of operation. * @return an operation. @@ -73,11 +73,11 @@ public interface NumericAlgebra : Algebra { /** * Dynamically invokes a binary operation with the certain name with numeric second argument. * - * This function must follow two properties: + * Implementations must fulfil the following requirements: * - * 1. In case if operation is not defined in the structure, the function throws [kotlin.IllegalStateException]. - * 2. This function is symmetric with the other [rightSideNumberOperationFunction] overload: - * i.e. `rightSideNumberOperationFunction(a)(b, c) == rightSideNumberOperation(a, b, c)`. + * 1. If operation is not defined in the structure, then the function throws [kotlin.IllegalStateException]. + * 1. Equivalence to [rightSideNumberOperationFunction]: for any `a`, `b`, and `c`, + * `rightSideNumberOperationFunction(a)(b, c) == rightSideNumberOperation(a, b, c)`. * * @param operation the name of operation. * @param left the first argument of operation. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt index 86365394f..31bd47bc3 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt @@ -330,13 +330,13 @@ public fun >> atanh(arg: T): */ public interface Norm { /** - * Computes the norm of [arg] (i.e. absolute value or vector length). + * Computes the norm of [arg] (i.e., absolute value or vector length). */ public fun norm(arg: T): R } /** - * Computes the norm of [arg] (i.e. absolute value or vector length). + * Computes the norm of [arg] (i.e., absolute value or vector length). */ @UnstableKMathAPI public fun >, R> norm(arg: T): R = arg.context.norm(arg) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBuffer.kt index b4ef37598..7a79663c4 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBuffer.kt @@ -32,7 +32,7 @@ public value class DoubleBuffer(public val array: DoubleArray) : MutableBuffer Double): DoubleBuffer = DoubleBuffer(DoubleArray(size) { init(it) }) @@ -47,7 +47,7 @@ public fun DoubleBuffer(vararg doubles: Double): DoubleBuffer = DoubleBuffer(dou public fun DoubleBuffer.contentEquals(vararg doubles: Double): Boolean = array.contentEquals(doubles) /** - * Returns a new [DoubleArray] containing all of the elements of this [Buffer]. + * Returns a new [DoubleArray] containing all the elements of this [Buffer]. */ public fun Buffer.toDoubleArray(): DoubleArray = when (this) { is DoubleBuffer -> array.copyOf() diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt index 0b16a3afc..efb8504c2 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt @@ -51,7 +51,7 @@ public fun FlaggedBuffer<*>.hasFlag(index: Int, flag: ValueFlag): Boolean = (get public fun FlaggedBuffer<*>.isMissing(index: Int): Boolean = hasFlag(index, ValueFlag.MISSING) /** - * A real buffer which supports flags for each value like NaN or Missing + * A [Double] buffer that supports flags for each value like `NaN` or Missing. */ public class FlaggedDoubleBuffer(public val values: DoubleArray, public val flags: ByteArray) : FlaggedBuffer, Buffer { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FloatBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FloatBuffer.kt index 58b7c6aea..e7e98fc71 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FloatBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FloatBuffer.kt @@ -34,7 +34,7 @@ public value class FloatBuffer(public val array: FloatArray) : MutableBuffer Float): FloatBuffer = FloatBuffer(FloatArray(size) { init(it) }) @@ -44,7 +44,7 @@ public inline fun FloatBuffer(size: Int, init: (Int) -> Float): FloatBuffer = Fl public fun FloatBuffer(vararg floats: Float): FloatBuffer = FloatBuffer(floats) /** - * Returns a new [FloatArray] containing all of the elements of this [Buffer]. + * Returns a new [FloatArray] containing all the elements of this [Buffer]. */ public fun Buffer.toFloatArray(): FloatArray = when (this) { is FloatBuffer -> array.copyOf() diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/IntBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/IntBuffer.kt index 57b6cfde3..35b722e2b 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/IntBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/IntBuffer.kt @@ -33,7 +33,7 @@ public value class IntBuffer(public val array: IntArray) : MutableBuffer { * [init] function. * * The function [init] is called for each array element sequentially starting from the first one. - * It should return the value for an buffer element given its index. + * It should return the value for a buffer element given its index. */ public inline fun IntBuffer(size: Int, init: (Int) -> Int): IntBuffer = IntBuffer(IntArray(size) { init(it) }) @@ -43,7 +43,7 @@ public inline fun IntBuffer(size: Int, init: (Int) -> Int): IntBuffer = IntBuffe public fun IntBuffer(vararg ints: Int): IntBuffer = IntBuffer(ints) /** - * Returns a new [IntArray] containing all of the elements of this [Buffer]. + * Returns a new [IntArray] containing all the elements of this [Buffer]. */ public fun Buffer.toIntArray(): IntArray = when (this) { is IntBuffer -> array.copyOf() diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/LongBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/LongBuffer.kt index 57affa1c5..c69f4646d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/LongBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/LongBuffer.kt @@ -33,7 +33,7 @@ public value class LongBuffer(public val array: LongArray) : MutableBuffer * [init] function. * * The function [init] is called for each array element sequentially starting from the first one. - * It should return the value for an buffer element given its index. + * It should return the value for a buffer element given its index. */ public inline fun LongBuffer(size: Int, init: (Int) -> Long): LongBuffer = LongBuffer(LongArray(size) { init(it) }) @@ -43,7 +43,7 @@ public inline fun LongBuffer(size: Int, init: (Int) -> Long): LongBuffer = LongB public fun LongBuffer(vararg longs: Long): LongBuffer = LongBuffer(longs) /** - * Returns a new [LongArray] containing all of the elements of this [Buffer]. + * Returns a new [LongArray] containing all the elements of this [Buffer]. */ public fun Buffer.toLongArray(): LongArray = when (this) { is LongBuffer -> array.copyOf() diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt index 8dadecff7..20691511b 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt @@ -31,7 +31,7 @@ public value class ShortBuffer(public val array: ShortArray) : MutableBuffer Short): ShortBuffer = ShortBuffer(ShortArray(size) { init(it) }) @@ -41,7 +41,7 @@ public inline fun ShortBuffer(size: Int, init: (Int) -> Short): ShortBuffer = Sh public fun ShortBuffer(vararg shorts: Short): ShortBuffer = ShortBuffer(shorts) /** - * Returns a new [ShortArray] containing all of the elements of this [Buffer]. + * Returns a new [ShortArray] containing all the elements of this [Buffer]. */ public fun Buffer.toShortArray(): ShortArray = when (this) { is ShortBuffer -> array.copyOf() diff --git a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/Chain.kt b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/Chain.kt index 8523ac864..f8d2549e5 100644 --- a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/Chain.kt +++ b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/chains/Chain.kt @@ -13,7 +13,7 @@ import kotlinx.coroutines.sync.withLock /** * A not-necessary-Markov chain of some type - * @param T - the chain element type + * @param T the chain element type */ public interface Chain : Flow { /** @@ -22,7 +22,7 @@ public interface Chain : Flow { public suspend fun next(): T /** - * Create a copy of current chain state. Consuming resulting chain does not affect initial chain + * Create a copy of current chain state. Consuming resulting chain does not affect initial chain. */ public suspend fun fork(): Chain @@ -62,9 +62,11 @@ public class MarkovChain(private val seed: suspend () -> R, private } /** - * A chain with possibly mutable state. The state must not be changed outside the chain. Two chins should never share the state - * @param S - the state of the chain - * @param forkState - the function to copy current state without modifying it + * A chain with possibly mutable state. The state must not be changed outside the chain. Two chins should never share + * the state. + * + * @param S the state of the chain. + * @param forkState the function to copy current state without modifying it. */ public class StatefulChain( private val state: S, @@ -96,7 +98,7 @@ public class ConstantChain(public val value: T) : Chain { /** * Map the chain result using suspended transformation. Initial chain result can no longer be safely consumed - * since mapped chain consumes tokens. Accepts regular transformation function + * since mapped chain consumes tokens. Accepts regular transformation function. */ public fun Chain.map(func: suspend (T) -> R): Chain = object : Chain { override suspend fun next(): R = func(this@map.next()) diff --git a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/BufferFlow.kt b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/BufferFlow.kt index 0d6a1178a..4d4493aa4 100644 --- a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/BufferFlow.kt +++ b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/BufferFlow.kt @@ -76,7 +76,7 @@ public fun Flow.chunked(bufferSize: Int): Flow = flow { /** * Map a flow to a moving window buffer. The window step is one. - * In order to get different steps, one could use skip operation. + * To get different steps, one could use skip operation. */ public fun Flow.windowed(window: Int): Flow> = flow { require(window > 1) { "Window size must be more than one" } diff --git a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt index deb297913..eb099bd79 100644 --- a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt +++ b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt @@ -20,7 +20,7 @@ import kotlin.jvm.JvmInline public interface DMatrix : Structure2D { public companion object { /** - * Coerces a regular matrix to a matrix with type-safe dimensions and throws a error if coercion failed + * Coerces a regular matrix to a matrix with type-safe dimensions and throws an error if coercion failed */ public inline fun coerce(structure: Structure2D): DMatrix { require(structure.rowNum == Dimension.dim()) { @@ -35,7 +35,7 @@ public interface DMatrix : Structure2D { } /** - * The same as [DMatrix.coerce] but without dimension checks. Use with caution + * The same as [DMatrix.coerce] but without dimension checks. Use with caution. */ public fun coerceUnsafe(structure: Structure2D): DMatrix = DMatrixWrapper(structure) diff --git a/kmath-for-real/build.gradle.kts b/kmath-for-real/build.gradle.kts index 25fdefaba..4cccaef5c 100644 --- a/kmath-for-real/build.gradle.kts +++ b/kmath-for-real/build.gradle.kts @@ -12,7 +12,7 @@ kotlin.sourceSets.commonMain { readme { description = """ - Extension module that should be used to achieve numpy-like behavior. + Extension module that should be used to achieve numpy-like behavior. All operations are specialized to work with `Double` numbers without declaring algebraic contexts. One can still use generic algebras though. """.trimIndent() diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt index d3867ea89..0508e9ca3 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt @@ -22,7 +22,7 @@ public typealias DoubleVector = Point public fun DoubleVector(vararg doubles: Double): DoubleVector = doubles.asBuffer() /** - * Fill the vector of given [size] with given [value] + * Fill the vector with given [size] with given [value] */ @UnstableKMathAPI public fun Buffer.Companion.same(size: Int, value: Number): DoubleVector = double(size) { value.toDouble() } diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/grids.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/grids.kt index c3556216d..1926ef02c 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/grids.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/grids.kt @@ -45,8 +45,8 @@ public fun Buffer.Companion.withFixedStep(range: ClosedFloatingPointRange> PiecewisePolynomial( } /** - * An optimized piecewise which uses not separate pieces, but a range separated by delimiters. - * The pieces search is logarithmic + * An optimized piecewise that uses not separate pieces, but a range separated by delimiters. + * The pieces search is logarithmic. */ private class OrderedPiecewisePolynomial>( override val pieces: List, Polynomial>>, @@ -79,7 +79,7 @@ public class PiecewiseBuilder>(delimiter: T) { /** * Dynamically adds a piece to the right side (beyond maximum argument value of previous piece) * - * @param right new rightmost position. If is less then current rightmost position, an error is thrown. + * @param right new rightmost position. If is less than current rightmost position, an error is thrown. * @param piece the sub-function. */ public fun putRight(right: T, piece: Polynomial) { @@ -91,7 +91,7 @@ public class PiecewiseBuilder>(delimiter: T) { /** * Dynamically adds a piece to the left side (beyond maximum argument value of previous piece) * - * @param left the new leftmost position. If is less then current rightmost position, an error is thrown. + * @param left the new leftmost position. If is less than current rightmost position, an error is thrown. * @param piece the sub-function. */ public fun putLeft(left: T, piece: Polynomial) { @@ -114,7 +114,7 @@ public fun > PiecewisePolynomial( ): PiecewisePolynomial = PiecewiseBuilder(startingPoint).apply(builder).build() /** - * Return a value of polynomial function with given [ring] an given [arg] or null if argument is outside of piecewise + * Return a value of polynomial function with given [ring] a given [arg] or null if argument is outside piecewise * definition. */ public fun , C : Ring> PiecewisePolynomial.value(ring: C, arg: T): T? = diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt index 283f97557..278ef6abe 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt @@ -10,15 +10,17 @@ import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.asBuffer import space.kscience.kmath.structures.indices - - /** * A simple one-pass integrator based on Gauss rule * Following integrand features are accepted: - * [GaussIntegratorRuleFactory] - A factory for computing the Gauss integration rule. By default uses [GaussLegendreRuleFactory] - * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. - * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. - * [UnivariateIntegrandRanges] - Set of ranges and number of points per range. Defaults to given [IntegrationRange] and [IntegrandMaxCalls] + * + * * [GaussIntegratorRuleFactory]—a factory for computing the Gauss integration rule. By default, uses + * [GaussLegendreRuleFactory]. + * * [IntegrationRange]—the univariate range of integration. By default, uses `0..1` interval. + * * [IntegrandMaxCalls]—the maximum number of function calls during integration. For non-iterative rules, always + * uses the maximum number of points. By default, uses 10 points. + * * [UnivariateIntegrandRanges]—set of ranges and number of points per range. Defaults to given + * [IntegrationRange] and [IntegrandMaxCalls]. */ public class GaussIntegrator( public val algebra: Field, @@ -71,14 +73,14 @@ public class GaussIntegrator( } /** - * Create a Gauss-Legendre integrator for this field + * Create a Gauss-Legendre integrator for this field. * @see [GaussIntegrator] */ -public val Field.gaussIntegrator: GaussIntegrator get() = GaussIntegrator(this) +public val Field.gaussIntegrator: GaussIntegrator get() = GaussIntegrator(this) /** - * Integrate using [intervals] segments with Gauss-Legendre rule of [order] order + * Integrate using [intervals] segments with Gauss-Legendre rule of [order] order. */ @UnstableKMathAPI public fun GaussIntegrator.integrate( diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt index 594ca9940..2eceec135 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt @@ -72,7 +72,7 @@ public object GaussLegendreRuleFactory : GaussIntegratorRuleFactory { } // Get previous rule. - // If it has not been computed yet it will trigger a recursive call + // If it has not been computed, yet it will trigger a recursive call // to this method. val previousPoints: Buffer = getOrBuildRule(numPoints - 1).first @@ -146,7 +146,7 @@ public object GaussLegendreRuleFactory : GaussIntegratorRuleFactory { } // If "numPoints" is odd, 0 is a root. // Note: as written, the test for oddness will work for negative - // integers too (although it is not necessary here), preventing + // integers too (although it is unnecessary here), preventing // a FindBugs warning. if (numPoints % 2 != 0) { var pmc = 1.0 diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt index baa9d4af8..c01c30ec2 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SimpsonIntegrator.kt @@ -13,9 +13,10 @@ import space.kscience.kmath.operations.sum /** * Use double pass Simpson rule integration with a fixed number of points. - * Requires [UnivariateIntegrandRanges] or [IntegrationRange] and [IntegrandMaxCalls] - * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. - * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. + * Requires [UnivariateIntegrandRanges] or [IntegrationRange] and [IntegrandMaxCalls]. + * * [IntegrationRange]—the univariate range of integration. By default, uses `0..1` interval. + * * [IntegrandMaxCalls]—the maximum number of function calls during integration. For non-iterative rules, always + * uses the maximum number of points. By default, uses 10 points. */ @UnstableKMathAPI public class SimpsonIntegrator( @@ -63,12 +64,12 @@ public val Field.simpsonIntegrator: SimpsonIntegrator get() = Si /** * Use double pass Simpson rule integration with a fixed number of points. - * Requires [UnivariateIntegrandRanges] or [IntegrationRange] and [IntegrandMaxCalls] - * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. - * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. + * Requires [UnivariateIntegrandRanges] or [IntegrationRange] and [IntegrandMaxCalls]. + * * [IntegrationRange]—the univariate range of integration. By default, uses `0.0..1.0` interval. + * * [IntegrandMaxCalls]—the maximum number of function calls during integration. For non-iterative rules, always uses + * the maximum number of points. By default, uses 10 points. */ public object DoubleSimpsonIntegrator : UnivariateIntegrator { - private fun integrateRange( integrand: UnivariateIntegrand, range: ClosedRange, numPoints: Int, ): Double { diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt index 23d7bdd8d..07b37bd6a 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt @@ -45,8 +45,9 @@ public fun > PiecewisePolynomial.integrate( /** * A generic spline-interpolation-based analytic integration - * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. - * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. + * * [IntegrationRange]—the univariate range of integration. By default, uses `0..1` interval. + * * [IntegrandMaxCalls]—the maximum number of function calls during integration. For non-iterative rules, always uses + * the maximum number of points. By default, uses 10 points. */ @UnstableKMathAPI public class SplineIntegrator>( @@ -57,6 +58,7 @@ public class SplineIntegrator>( val range = integrand.getFeature()?.range ?: 0.0..1.0 val interpolator: PolynomialInterpolator = SplineInterpolator(algebra, bufferFactory) + val nodes: Buffer = integrand.getFeature()?.nodes ?: run { val numPoints = integrand.getFeature()?.maxCalls ?: 100 val step = (range.endInclusive - range.start) / (numPoints - 1) @@ -75,15 +77,16 @@ public class SplineIntegrator>( /** * A simplified double-based spline-interpolation-based analytic integration - * [IntegrationRange] - the univariate range of integration. By default uses 0..1 interval. - * [IntegrandMaxCalls] - the maximum number of function calls during integration. For non-iterative rules, always uses the maximum number of points. By default uses 10 points. + * * [IntegrationRange]—the univariate range of integration. By default, uses `0.0..1.0` interval. + * * [IntegrandMaxCalls]—the maximum number of function calls during integration. For non-iterative rules, always + * uses the maximum number of points. By default, uses 10 points. */ @UnstableKMathAPI public object DoubleSplineIntegrator : UnivariateIntegrator { override fun integrate(integrand: UnivariateIntegrand): UnivariateIntegrand { val range = integrand.getFeature()?.range ?: 0.0..1.0 - val interpolator: PolynomialInterpolator = SplineInterpolator(DoubleField, ::DoubleBuffer) + val nodes: Buffer = integrand.getFeature()?.nodes ?: run { val numPoints = integrand.getFeature()?.maxCalls ?: 100 val step = (range.endInclusive - range.start) / (numPoints - 1) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt index 7f68284a7..9c8aeef1b 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt @@ -40,8 +40,8 @@ public class IntegrationRange(public val range: ClosedRange) : Integrand } /** - * Set of univariate integration ranges. First components correspond to ranges themselves, second components to number of - * integration nodes per range + * Set of univariate integration ranges. First components correspond to the ranges themselves, second components to + * number of integration nodes per range. */ public class UnivariateIntegrandRanges(public val ranges: List, Int>>) : IntegrandFeature { public constructor(vararg pairs: Pair, Int>) : this(pairs.toList()) diff --git a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt index 31da4f392..4e803fc63 100644 --- a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt +++ b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt @@ -11,7 +11,7 @@ import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.asBuffer /** - * The binned data element. Could be a histogram bin with a number of counts or an artificial construct + * The binned data element. Could be a histogram bin with a number of counts or an artificial construct. */ public interface Bin : Domain { /** diff --git a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt index f461ee4fa..ca37279c3 100644 --- a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt +++ b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt @@ -16,9 +16,10 @@ public val UnivariateDomain.center: Double get() = (range.endInclusive + range.start) / 2 /** - * A univariate bin based an a range - * @param value The value of histogram including weighting - * @param standardDeviation Standard deviation of the bin value. Zero or negative if not applicable + * A univariate bin based on a range + * + * @property value The value of histogram including weighting + * @property standardDeviation Standard deviation of the bin value. Zero or negative if not applicable */ @UnstableKMathAPI public class UnivariateBin( diff --git a/kmath-jafama/README.md b/kmath-jafama/README.md index 71097771d..3c5d4e19d 100644 --- a/kmath-jafama/README.md +++ b/kmath-jafama/README.md @@ -52,22 +52,4 @@ fun main() { According to KMath benchmarks on GraalVM, Jafama functions are slower than JDK math; however, there are indications that on Hotspot Jafama is a bit faster. -
- -Report for benchmark configuration jafamaDouble - - -* Run on OpenJDK 64-Bit Server VM (build 11.0.11+8-jvmci-21.1-b05) with Java process: - -``` -/home/commandertvis/graalvm-ce-java11/bin/java -XX:+UnlockExperimentalVMOptions -XX:+EnableJVMCIProduct -XX:-UnlockExperimentalVMOptions -XX:ThreadPriorityPolicy=1 -javaagent:/home/commandertvis/.gradle/caches/modules-2/files-2.1/org.jetbrains.kotlinx/kotlinx-coroutines-core-jvm/1.5.0/d8cebccdcddd029022aa8646a5a953ff88b13ac8/kotlinx-coroutines-core-jvm-1.5.0.jar -Dfile.encoding=UTF-8 -Duser.country=US -Duser.language=en -Duser.variant -ea -``` -* JMH 1.21 was used in `thrpt` mode with 1 warmup iteration by 1000 ms and 5 measurement iterations by 1000 ms. - -| Benchmark | Score | -|:---------:|:-----:| -|`space.kscience.kmath.benchmarks.JafamaBenchmark.core`|14.35014650168397 ± 0.9200669832937576 ops/s| -|`space.kscience.kmath.benchmarks.JafamaBenchmark.jafama`|12.048429204455887 ± 1.2882929181842269 ops/s| -|`space.kscience.kmath.benchmarks.JafamaBenchmark.strictJafama`|12.977653357239152 ± 1.4122819627470866 ops/s| -
- +> **Can't find appropriate benchmark data. Try generating readme files after running benchmarks**. diff --git a/kmath-kotlingrad/README.md b/kmath-kotlingrad/README.md index 3b337460f..aeb44ea13 100644 --- a/kmath-kotlingrad/README.md +++ b/kmath-kotlingrad/README.md @@ -1,6 +1,6 @@ # Module kmath-kotlingrad -[Kotlin∇](https://www.htmlsymbols.xyz/unicode/U+2207) integration module. +[Kotlin∇](https://github.com/breandan/kotlingrad) integration module. - [differentiable-mst-expression](src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt) : MST based DifferentiableExpression. - [scalars-adapters](src/main/kotlin/space/kscience/kmath/kotlingrad/scalarsAdapters.kt) : Conversions between Kotlin∇'s SFun and MST diff --git a/kmath-kotlingrad/docs/README-TEMPLATE.md b/kmath-kotlingrad/docs/README-TEMPLATE.md index ac38c849b..bc99bdf5f 100644 --- a/kmath-kotlingrad/docs/README-TEMPLATE.md +++ b/kmath-kotlingrad/docs/README-TEMPLATE.md @@ -1,6 +1,6 @@ # Module kmath-kotlingrad -[Kotlin∇](https://www.htmlsymbols.xyz/unicode/U+2207) integration module. +[Kotlin∇](https://github.com/breandan/kotlingrad) integration module. ${features} diff --git a/kmath-memory/src/commonMain/kotlin/space/kscience/kmath/memory/Memory.kt b/kmath-memory/src/commonMain/kotlin/space/kscience/kmath/memory/Memory.kt index 930b21095..e8e51e9e2 100644 --- a/kmath-memory/src/commonMain/kotlin/space/kscience/kmath/memory/Memory.kt +++ b/kmath-memory/src/commonMain/kotlin/space/kscience/kmath/memory/Memory.kt @@ -156,6 +156,6 @@ public expect fun Memory.Companion.allocate(length: Int): Memory /** * Wraps a [Memory] around existing [ByteArray]. This operation is unsafe since the array is not copied - * and could be mutated independently from the resulting [Memory]. + * and could be mutated independently of the resulting [Memory]. */ public expect fun Memory.Companion.wrap(array: ByteArray): Memory diff --git a/kmath-memory/src/jsMain/kotlin/space/kscience/kmath/memory/DataViewMemory.kt b/kmath-memory/src/jsMain/kotlin/space/kscience/kmath/memory/DataViewMemory.kt index 9a622ea36..6153743fc 100644 --- a/kmath-memory/src/jsMain/kotlin/space/kscience/kmath/memory/DataViewMemory.kt +++ b/kmath-memory/src/jsMain/kotlin/space/kscience/kmath/memory/DataViewMemory.kt @@ -95,7 +95,7 @@ public actual fun Memory.Companion.allocate(length: Int): Memory { /** * Wraps a [Memory] around existing [ByteArray]. This operation is unsafe since the array is not copied - * and could be mutated independently from the resulting [Memory]. + * and could be mutated independently of the resulting [Memory]. */ public actual fun Memory.Companion.wrap(array: ByteArray): Memory { @Suppress("CAST_NEVER_SUCCEEDS") val int8Array = array as Int8Array diff --git a/kmath-memory/src/jvmMain/kotlin/space/kscience/kmath/memory/ByteBufferMemory.kt b/kmath-memory/src/jvmMain/kotlin/space/kscience/kmath/memory/ByteBufferMemory.kt index 944e8455b..aef68fd80 100644 --- a/kmath-memory/src/jvmMain/kotlin/space/kscience/kmath/memory/ByteBufferMemory.kt +++ b/kmath-memory/src/jvmMain/kotlin/space/kscience/kmath/memory/ByteBufferMemory.kt @@ -103,7 +103,7 @@ public actual fun Memory.Companion.allocate(length: Int): Memory = /** * Wraps a [Memory] around existing [ByteArray]. This operation is unsafe since the array is not copied - * and could be mutated independently from the resulting [Memory]. + * and could be mutated independently of the resulting [Memory]. */ public actual fun Memory.Companion.wrap(array: ByteArray): Memory = ByteBufferMemory(checkNotNull(ByteBuffer.wrap(array))) diff --git a/kmath-memory/src/nativeMain/kotlin/space/kscience/kmath/memory/NativeMemory.kt b/kmath-memory/src/nativeMain/kotlin/space/kscience/kmath/memory/NativeMemory.kt index d31c9e8f4..5146d9689 100644 --- a/kmath-memory/src/nativeMain/kotlin/space/kscience/kmath/memory/NativeMemory.kt +++ b/kmath-memory/src/nativeMain/kotlin/space/kscience/kmath/memory/NativeMemory.kt @@ -60,7 +60,7 @@ internal class NativeMemory( } override fun writeByte(offset: Int, value: Byte) { - array.set(position(offset), value) + array[position(offset)] = value } override fun writeShort(offset: Int, value: Short) { @@ -85,7 +85,7 @@ internal class NativeMemory( /** * Wraps a [Memory] around existing [ByteArray]. This operation is unsafe since the array is not copied - * and could be mutated independently from the resulting [Memory]. + * and could be mutated independently of the resulting [Memory]. */ public actual fun Memory.Companion.wrap(array: ByteArray): Memory = NativeMemory(array) diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt index 7a650df3c..f69f831e8 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt @@ -35,7 +35,7 @@ public sealed interface Nd4jArrayAlgebra> : AlgebraND /** - * Unwraps to or acquires [INDArray] from [StructureND]. + * Unwraps to or get [INDArray] from [StructureND]. */ public val StructureND.ndArray: INDArray diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt index 97427d5c6..2a0fdc86c 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt @@ -17,7 +17,7 @@ import space.kscience.kmath.nd.StructureND */ public sealed class Nd4jArrayStructure : MutableStructureND { /** - * The wrapped [INDArray]. Since KMath uses [Int] indexes, assuming that the size of [INDArray] is less or equal to + * The wrapped [INDArray]. Since KMath uses [Int] indexes, assuming the size of [INDArray] is less or equal to * [Int.MAX_VALUE]. */ public abstract val ndArray: INDArray diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt index 0674c565e..1fdf845a6 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt @@ -29,7 +29,7 @@ public sealed interface Nd4jTensorAlgebra : AnalyticTensorAlgebra public fun INDArray.wrap(): Nd4jArrayStructure /** - * Unwraps to or acquires [INDArray] from [StructureND]. + * Unwraps to or gets [INDArray] from [StructureND]. */ public val StructureND.ndArray: INDArray diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/Distribution.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/Distribution.kt index 5a74a9a18..3d3f95f8f 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/Distribution.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/Distribution.kt @@ -22,7 +22,7 @@ public interface Distribution : Sampler { override fun sample(generator: RandomGenerator): Chain /** - * An empty companion. Distribution factories should be written as its extensions + * An empty companion. Distribution factories should be written as its extensions. */ public companion object } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/FactorizedDistribution.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/FactorizedDistribution.kt index dde429244..1218f13c5 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/FactorizedDistribution.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/distributions/FactorizedDistribution.kt @@ -10,12 +10,12 @@ import space.kscience.kmath.chains.SimpleChain import space.kscience.kmath.stat.RandomGenerator /** - * A multivariate distribution which takes a map of parameters + * A multivariate distribution that takes a map of parameters. */ public interface NamedDistribution : Distribution> /** - * A multivariate distribution that has independent distributions for separate axis + * A multivariate distribution that has independent distributions for separate axis. */ public class FactorizedDistribution(public val distributions: Collection>) : NamedDistribution { diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/internal/InternalGamma.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/internal/InternalGamma.kt index a584af4f9..6e7eb039d 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/internal/InternalGamma.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/internal/InternalGamma.kt @@ -110,7 +110,7 @@ internal object InternalGamma { x <= 8.0 -> { val n = floor(x - 1.5).toInt() - val prod = (1..n).fold(1.0, { prod, i -> prod * (x - i) }) + val prod = (1..n).fold(1.0) { prod, i -> prod * (x - i) } logGamma1p(x - (n + 1)) + ln(prod) } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index f54ba5723..997f1bbe3 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -11,27 +11,28 @@ import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.indices /** - * A likelihood function optimization problem with provided derivatives + * A likelihood function optimization problem with provided derivatives. */ public interface FunctionOptimization : Optimization { /** - * The optimization direction. If true search for function maximum, if false, search for the minimum + * The optimization direction. If true search for function maximum, if false, search for the minimum. */ public var maximize: Boolean /** - * Define the initial guess for the optimization problem + * Defines the initial guess for the optimization problem. */ public fun initialGuess(map: Map) /** - * Set a differentiable expression as objective function as function and gradient provider + * Set a differentiable expression as objective function as function and gradient provider. */ public fun diffFunction(expression: DifferentiableExpression) public companion object { /** - * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation + * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic + * differentiation. */ public fun chiSquared( autoDiff: AutoDiffProcessor>, @@ -61,7 +62,7 @@ public interface FunctionOptimization : Optimization { } /** - * Define a chi-squared-based objective function + * Defines a chi-squared-based objective function. */ public fun FunctionOptimization.chiSquared( autoDiff: AutoDiffProcessor>, @@ -76,7 +77,7 @@ public fun FunctionOptimization.chiSquared( } /** - * Optimize differentiable expression using specific [OptimizationProblemFactory] + * Optimizes differentiable expression using specific [OptimizationProblemFactory]. */ public fun > DifferentiableExpression.optimizeWith( factory: OptimizationProblemFactory, diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt index 0f2167549..44b66169f 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/NoDerivFunctionOptimization.kt @@ -16,7 +16,7 @@ import kotlin.math.pow */ public interface NoDerivFunctionOptimization : Optimization { /** - * The optimization direction. If true search for function maximum, if false, search for the minimum + * The optimization direction. If `true` search for function maximum, search for the minimum otherwise. */ public var maximize: Boolean diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt index 15ae494f6..f85658d87 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimization.kt @@ -24,7 +24,7 @@ public operator fun OptimizationResult.plus( ): OptimizationResult = OptimizationResult(point, value, features + feature) /** - * An optimization problem builder over [T] variables + * A builder of optimization problems over [T] variables */ public interface Optimization { diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt index 93605c7d8..993215d41 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt @@ -14,9 +14,9 @@ import kotlin.math.* /** * Sampling from the [gamma distribution](http://mathworld.wolfram.com/GammaDistribution.html). - * - For 0 < alpha < 1: + * * For 0 < alpha < 1: * Ahrens, J. H. and Dieter, U., Computer methods for sampling from gamma, beta, Poisson and binomial distributions, Computing, 12, 223-246, 1974. - * - For alpha >= 1: + * * For alpha >= 1: * Marsaglia and Tsang, A Simple Method for Generating Gamma Variables. ACM Transactions on Mathematical Software, Volume 26 Issue 3, September, 2000. * * Based on Commons RNG implementation. diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt index 36ddd3c8e..5390a2e09 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/AliasMethodDiscreteSampler.kt @@ -20,7 +20,7 @@ import kotlin.math.min * implements Vose's algorithm. * * Vose, M.D., A linear algorithm for generating random numbers with a given distribution, IEEE Transactions on - * Software Engineering, 17, 972-975, 1991. he algorithm will sample values in O(1) time after a pre-processing step + * Software Engineering, 17, 972-975, 1991. The algorithm will sample values in O(1) time after a pre-processing step * of O(n) time. * * The alias tables are constructed using fraction probabilities with an assumed denominator of 253. In the generic @@ -77,7 +77,7 @@ public open class AliasMethodDiscreteSampler private constructor( } override fun sample(generator: RandomGenerator): Chain = generator.chain { - // This implements the algorithm as per Vose (1991): + // This implements the algorithm in accordance with Vose (1991): // v = uniform() in [0, 1) // j = uniform(n) in [0, n) // if v < prob[j] then @@ -95,7 +95,7 @@ public open class AliasMethodDiscreteSampler private constructor( // p(j) == 1 => j // However it is assumed these edge cases are rare: // - // The probability table will be 1 for approximately 1/n samples, i.e. only the + // The probability table will be 1 for approximately 1/n samples i.e., only the // last unpaired probability. This is only worth checking for when the table size (n) // is small. But in that case the user should zero-pad the table for performance. // @@ -211,7 +211,7 @@ public open class AliasMethodDiscreteSampler private constructor( // c: 2=2/3; 6=1/3 (6 is the alias) // d: 1=1/3; 6=2/3 (6 is the alias) // - // The sample is obtained by randomly selecting a section, then choosing which category + // The sample is obtained by randomly selecting a section, then choosing, which category // from the pair based on a uniform random deviate. val sumProb = InternalUtils.validateProbabilities(probabilities) // Allow zero-padding @@ -241,9 +241,9 @@ public open class AliasMethodDiscreteSampler private constructor( val alias = IntArray(n) // This loop uses each large in turn to fill the alias table for small probabilities that - // do not reach the requirement to fill an entire section alone (i.e. p < mean). + // do not reach the requirement to fill an entire section alone (i.e., p < mean). // Since the sum of the small should be less than the sum of the large it should use up - // all the small first. However floating point round-off can result in + // all the small first. However, floating point round-off can result in // misclassification of items as small or large. The Vose algorithm handles this using // a while loop conditioned on the size of both sets and a subsequent loop to use // unpaired items. diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt index 14737decb..0105731c4 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt @@ -13,7 +13,7 @@ import kotlin.math.exp /** * Sampler for the Poisson distribution. - * - Kemp, A, W, (1981) Efficient Generation of Logarithmically Distributed Pseudo-Random Variables. Journal of the Royal Statistical Society. Vol. 30, No. 3, pp. 249-253. + * * Kemp, A, W, (1981) Efficient Generation of Logarithmically Distributed Pseudo-Random Variables. Journal of the Royal Statistical Society. Vol. 30, No. 3, pp. 249-253. * This sampler is suitable for mean < 40. For large means, LargeMeanPoissonSampler should be used instead. * * Note: The algorithm uses a recurrence relation to compute the Poisson probability and a rolling summation for the cumulative probability. When the mean is large the initial probability (Math.exp(-mean)) is zero and an exception is raised by the constructor. @@ -66,8 +66,7 @@ public class KempSmallMeanPoissonSampler internal constructor( public fun KempSmallMeanPoissonSampler(mean: Double): KempSmallMeanPoissonSampler { require(mean > 0) { "Mean is not strictly positive: $mean" } val p0 = exp(-mean) - // Probability must be positive. As mean increases then p(0) decreases. + // Probability must be positive. As mean increases, p(0) decreases. require(p0 > 0) { "No probability for mean: $mean" } return KempSmallMeanPoissonSampler(p0, mean) } - diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt index 96131aa4b..f0f94900e 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/PoissonSampler.kt @@ -18,11 +18,11 @@ private const val PIVOT = 40.0 /** * Sampler for the Poisson distribution. - * - For small means, a Poisson process is simulated using uniform deviates, as described in + * * For small means, a Poisson process is simulated using uniform deviates, as described in * Knuth (1969). Seminumerical Algorithms. The Art of Computer Programming, Volume 2. Chapter 3.4.1.F.3 * Important integer-valued distributions: The Poisson distribution. Addison Wesley. * The Poisson process (and hence, the returned value) is bounded by 1000 * mean. - * - For large means, we use the rejection algorithm described in + * * For large means, we use the rejection algorithm described in * Devroye, Luc. (1981). The Computer Generation of Poisson Random Variables Computing vol. 26 pp. 197-207. * * Based on Commons RNG implementation. @@ -35,10 +35,10 @@ public fun PoissonSampler(mean: Double): Sampler { /** * Sampler for the Poisson distribution. - * - For small means, a Poisson process is simulated using uniform deviates, as described in + * * For small means, a Poisson process is simulated using uniform deviates, as described in * Knuth (1969). Seminumerical Algorithms. The Art of Computer Programming, Volume 2. Chapter 3.4.1.F.3 Important * integer-valued distributions: The Poisson distribution. Addison Wesley. - * - The Poisson process (and hence, the returned value) is bounded by 1000 * mean. + * * The Poisson process (and hence, the returned value) is bounded by 1000 * mean. * This sampler is suitable for mean < 40. For large means, [LargeMeanPoissonSampler] should be used instead. * * Based on Commons RNG implementation. diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomGenerator.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomGenerator.kt index 5698f1a79..f280a78aa 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomGenerator.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomGenerator.kt @@ -23,7 +23,7 @@ public interface RandomGenerator { public fun nextDouble(): Double /** - * A chunk of doubles of given [size] + * A chunk of doubles of given [size]. */ public fun nextDoubleBuffer(size: Int): DoubleBuffer = DoubleBuffer(size) { nextDouble() } @@ -57,7 +57,7 @@ public interface RandomGenerator { public fun nextLong(until: Long): Long /** - * Fills a subrange of the specified byte [array] starting from [fromIndex] inclusive and ending [toIndex] exclusive + * Fills a subrange with the specified byte [array] starting from [fromIndex] inclusive and ending [toIndex] exclusive * with random bytes. * * @return [array] with the subrange filled with random bytes. @@ -70,7 +70,7 @@ public interface RandomGenerator { public fun nextBytes(size: Int): ByteArray = ByteArray(size).also { fillBytes(it) } /** - * Create a new generator which is independent from current generator (operations on new generator do not affect this one + * Create a new generator that is independent of current generator (operations on new generator do not affect this one * and vise versa). The statistical properties of new generator should be the same as for this one. * For pseudo-random generator, the fork is keeping the same sequence of numbers for given call order for each run. * diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt index 849cf152a..044e489b2 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt @@ -32,7 +32,7 @@ public class BasicSampler(public val chainBuilder: (RandomGenerator } /** - * A space of samplers. Allows to perform simple operations on distributions. + * A space of samplers. Allows performing simple operations on distributions. * * @property algebra the space to provide addition and scalar multiplication for [T]. */ diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt index 499dcac6a..0af901fc9 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt @@ -30,9 +30,10 @@ public interface BlockingStatistic : Statistic { /** * A statistic tha could be computed separately on different blocks of data and then composed - * @param T - source type - * @param I - intermediate block type - * @param R - result type + * + * @param T the source type. + * @param I the intermediate block type. + * @param R the result type. */ public interface ComposableStatistic : Statistic { //compute statistic on a single block diff --git a/kmath-stat/src/jvmMain/kotlin/space/kscience/kmath/stat/RandomSourceGenerator.kt b/kmath-stat/src/jvmMain/kotlin/space/kscience/kmath/stat/RandomSourceGenerator.kt index 7aaac7d32..202a1c8dd 100644 --- a/kmath-stat/src/jvmMain/kotlin/space/kscience/kmath/stat/RandomSourceGenerator.kt +++ b/kmath-stat/src/jvmMain/kotlin/space/kscience/kmath/stat/RandomSourceGenerator.kt @@ -55,7 +55,7 @@ public class RandomGeneratorProvider(public val generator: RandomGenerator) : Un /** * Generates [Byte] values and places them into a user-supplied array. * - * The number of random bytes produced is equal to the length of the the byte array. + * The number of random bytes produced is equal to the length of the byte array. * * @param bytes byte array in which to put the random bytes. */ diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt index 6bdecfa85..af4ae8239 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt @@ -23,7 +23,7 @@ public interface LinearOpsTensorAlgebra : TensorPartialDivisionAlgebra { /** * Computes the multiplicative inverse matrix of a square matrix input, or of each square matrix in a batched input. * Given a square matrix `A`, return the matrix `AInv` satisfying - * `A dot AInv = AInv dot A = eye(a.shape[0])`. + * `A dot AInv == AInv dot A == eye(a.shape[0])`. * For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.inv * * @return the multiplicative inverse of a matrix. @@ -36,25 +36,27 @@ public interface LinearOpsTensorAlgebra : TensorPartialDivisionAlgebra { * Computes the Cholesky decomposition of a Hermitian (or symmetric for real-valued matrices) * positive-definite matrix or the Cholesky decompositions for a batch of such matrices. * Each decomposition has the form: - * Given a tensor `input`, return the tensor `L` satisfying `input = L dot L.H`, - * where L is a lower-triangular matrix and L.H is the conjugate transpose of L, + * Given a tensor `input`, return the tensor `L` satisfying `input = L dot LH`, + * where `L` is a lower-triangular matrix and `LH` is the conjugate transpose of `L`, * which is just a transpose for the case of real-valued input matrices. * For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.cholesky * - * @return the batch of L matrices. + * @receiver the `input`. + * @return the batch of `L` matrices. */ public fun Tensor.cholesky(): Tensor /** * QR decomposition. * - * Computes the QR decomposition of a matrix or a batch of matrices, and returns a pair `(Q, R)` of tensors. - * Given a tensor `input`, return tensors (Q, R) satisfying ``input = Q dot R``, + * Computes the QR decomposition of a matrix or a batch of matrices, and returns a pair `Q to R` of tensors. + * Given a tensor `input`, return tensors `Q to R` satisfying `input == Q dot R`, * with `Q` being an orthogonal matrix or batch of orthogonal matrices * and `R` being an upper triangular matrix or batch of upper triangular matrices. * For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.qr * - * @return pair of Q and R tensors. + * @receiver the `input`. + * @return pair of `Q` and `R` tensors. */ public fun Tensor.qr(): Pair, Tensor> @@ -67,7 +69,8 @@ public interface LinearOpsTensorAlgebra : TensorPartialDivisionAlgebra { * `L` being a lower triangular matrix or batch of matrices, * `U` being an upper triangular matrix or batch of matrices. * - * * @return triple of P, L and U tensors + * @receiver the `input`. + * @return triple of P, L and U tensors */ public fun Tensor.lu(): Triple, Tensor, Tensor> @@ -75,22 +78,25 @@ public interface LinearOpsTensorAlgebra : TensorPartialDivisionAlgebra { * Singular Value Decomposition. * * Computes the singular value decomposition of either a matrix or batch of matrices `input`. - * The singular value decomposition is represented as a triple `(U, S, V)`, - * such that `input = U dot diagonalEmbedding(S) dot V.H`, - * where V.H is the conjugate transpose of V. - * If input is a batch of tensors, then U, S, and Vh are also batched with the same batch dimensions as input. + * The singular value decomposition is represented as a triple `Triple(U, S, V)`, + * such that `input = U dot diagonalEmbedding(S) dot VH`, + * where `VH` is the conjugate transpose of V. + * If `input` is a batch of tensors, then `U`, `S`, and `VH` are also batched with the same batch dimensions as + * `input`. * For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.svd * - * @return triple `(U, S, V)`. + * @receiver the `input`. + * @return triple `Triple(U, S, V)`. */ public fun Tensor.svd(): Triple, Tensor, Tensor> /** - * Returns eigenvalues and eigenvectors of a real symmetric matrix input or a batch of real symmetric matrices, - * represented by a pair (eigenvalues, eigenvectors). + * Returns eigenvalues and eigenvectors of a real symmetric matrix `input` or a batch of real symmetric matrices, + * represented by a pair `eigenvalues to eigenvectors`. * For more information: https://pytorch.org/docs/stable/generated/torch.symeig.html * - * @return a pair (eigenvalues, eigenvectors) + * @receiver the `input`. + * @return a pair `eigenvalues to eigenvectors` */ public fun Tensor.symEig(): Pair, Tensor> diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt index 62b8ef046..d48e7b1c9 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt @@ -14,7 +14,6 @@ import space.kscience.kmath.operations.Algebra * @param T the type of items in the tensors. */ public interface TensorAlgebra : Algebra> { - /** * Returns a single tensor value of unit dimension if tensor shape equals to [1]. * @@ -189,7 +188,7 @@ public interface TensorAlgebra : Algebra> { /** * View this tensor as the same size as [other]. - * ``this.viewAs(other) is equivalent to this.view(other.shape)``. + * `this.viewAs(other)` is equivalent to `this.view(other.shape)`. * For more information: https://pytorch.org/cppdocs/notes/tensor_indexing.html * * @param other the result tensor has the same size as other. @@ -217,14 +216,14 @@ public interface TensorAlgebra : Algebra> { * a 1 is prepended to its dimension for the purpose of the batched matrix multiply and removed after. * If the second argument is 1-dimensional, a 1 is appended to its dimension for the purpose of the batched matrix * multiple and removed after. - * The non-matrix (i.e. batch) dimensions are broadcast (and thus must be broadcastable). + * The non-matrix (i.e., batch) dimensions are broadcast (and thus must be broadcastable). * For example, if `input` is a (j × 1 × n × n) tensor and `other` is a * (k × n × n) tensor, out will be a (j × k × n × n) tensor. * * For more information: https://pytorch.org/docs/stable/generated/torch.matmul.html * - * @param other tensor to be multiplied - * @return mathematical product of two tensors + * @param other tensor to be multiplied. + * @return a mathematical product of two tensors. */ public infix fun Tensor.dot(other: Tensor): Tensor @@ -234,7 +233,7 @@ public interface TensorAlgebra : Algebra> { * To facilitate creating batched diagonal matrices, * the 2D planes formed by the last two dimensions of the returned tensor are chosen by default. * - * The argument [offset] controls which diagonal to consider: + * The argument [offset] controls, which diagonal to consider: * 1. If [offset] = 0, it is the main diagonal. * 1. If [offset] > 0, it is above the main diagonal. * 1. If [offset] < 0, it is below the main diagonal. @@ -321,7 +320,7 @@ public interface TensorAlgebra : Algebra> { * * @param dim the dimension to reduce. * @param keepDim whether the output tensor has [dim] retained or not. - * @return the the index of maximum value of each row of the input tensor in the given dimension [dim]. + * @return the index of maximum value of each row of the input tensor in the given dimension [dim]. */ public fun Tensor.argMax(dim: Int, keepDim: Boolean): Tensor } diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorPartialDivisionAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorPartialDivisionAlgebra.kt index 02bf5415d..867d4b26e 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorPartialDivisionAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorPartialDivisionAlgebra.kt @@ -49,7 +49,7 @@ public interface TensorPartialDivisionAlgebra : TensorAlgebra { /** * Each element of this tensor is divided by each element of the [other] tensor. * - * @param other tensor to be divide by. + * @param other tensor to be divided by. */ public operator fun Tensor.divAssign(other: Tensor) } diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt index d182558c5..d6ad8e8e2 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt @@ -90,37 +90,37 @@ public open class DoubleTensorAlgebra : } /** - * Returns a tensor filled with the scalar value 0.0, with the shape defined by the variable argument [shape]. + * Returns a tensor filled with the scalar value `0.0`, with the shape defined by the variable argument [shape]. * * @param shape array of integers defining the shape of the output tensor. - * @return tensor filled with the scalar value 0.0, with the [shape] shape. + * @return tensor filled with the scalar value `0.0`, with the [shape] shape. */ public fun zeros(shape: IntArray): DoubleTensor = full(0.0, shape) /** - * Returns a tensor filled with the scalar value 0.0, with the same shape as a given array. + * Returns a tensor filled with the scalar value `0.0`, with the same shape as a given array. * - * @return tensor filled with the scalar value 0.0, with the same shape as `input` tensor. + * @return tensor filled with the scalar value `0.0`, with the same shape as `input` tensor. */ public fun Tensor.zeroesLike(): DoubleTensor = tensor.fullLike(0.0) /** - * Returns a tensor filled with the scalar value 1.0, with the shape defined by the variable argument [shape]. + * Returns a tensor filled with the scalar value `1.0`, with the shape defined by the variable argument [shape]. * * @param shape array of integers defining the shape of the output tensor. - * @return tensor filled with the scalar value 1.0, with the [shape] shape. + * @return tensor filled with the scalar value `1.0`, with the [shape] shape. */ public fun ones(shape: IntArray): DoubleTensor = full(1.0, shape) /** - * Returns a tensor filled with the scalar value 1.0, with the same shape as a given array. + * Returns a tensor filled with the scalar value `1.0`, with the same shape as a given array. * - * @return tensor filled with the scalar value 1.0, with the same shape as `input` tensor. + * @return tensor filled with the scalar value `1.0`, with the same shape as `input` tensor. */ public fun Tensor.onesLike(): DoubleTensor = tensor.fullLike(1.0) /** - * Returns a 2-D tensor with shape ([n], [n]), with ones on the diagonal and zeros elsewhere. + * Returns a 2D tensor with shape ([n], [n]), with ones on the diagonal and zeros elsewhere. * * @param n the number of rows and columns * @return a 2-D tensor with ones on the diagonal and zeros elsewhere. @@ -311,7 +311,6 @@ public open class DoubleTensorAlgebra : return resTensor } - override fun Tensor.view(shape: IntArray): DoubleTensor { checkView(tensor, shape) return DoubleTensor(shape, tensor.mutableBuffer.array(), tensor.bufferStart) @@ -444,7 +443,7 @@ public open class DoubleTensorAlgebra : /** * Compares element-wise two tensors. - * Comparison of two Double values occurs with 1e-5 precision. + * Comparison of two Double values occurs with `1e-5` precision. * * @param other the tensor to compare with `input` tensor. * @return true if two tensors have the same shape and elements, false otherwise. @@ -473,23 +472,24 @@ public open class DoubleTensorAlgebra : } /** - * Returns a tensor of random numbers drawn from normal distributions with 0.0 mean and 1.0 standard deviation. + * Returns a tensor of random numbers drawn from normal distributions with `0.0` mean and `1.0` standard deviation. * * @param shape the desired shape for the output tensor. * @param seed the random seed of the pseudo-random number generator. * @return tensor of a given shape filled with numbers from the normal distribution - * with 0.0 mean and 1.0 standard deviation. + * with `0.0` mean and `1.0` standard deviation. */ public fun randomNormal(shape: IntArray, seed: Long = 0): DoubleTensor = DoubleTensor(shape, getRandomNormals(shape.reduce(Int::times), seed)) /** * Returns a tensor with the same shape as `input` of random numbers drawn from normal distributions - * with 0.0 mean and 1.0 standard deviation. + * with `0.0` mean and `1.0` standard deviation. * + * @receiver the `input`. * @param seed the random seed of the pseudo-random number generator. - * @return tensor with the same shape as `input` filled with numbers from the normal distribution - * with 0.0 mean and 1.0 standard deviation. + * @return a tensor with the same shape as `input` filled with numbers from the normal distribution + * with `0.0` mean and `1.0` standard deviation. */ public fun Tensor.randomNormalLike(seed: Long = 0): DoubleTensor = DoubleTensor(tensor.shape, getRandomNormals(tensor.shape.reduce(Int::times), seed)) @@ -512,10 +512,10 @@ public open class DoubleTensorAlgebra : } /** - * Builds tensor from rows of input tensor + * Builds tensor from rows of the input tensor. * * @param indices the [IntArray] of 1-dimensional indices - * @return tensor with rows corresponding to rows by [indices] + * @return tensor with rows corresponding to row by [indices] */ public fun Tensor.rowsByIndices(indices: IntArray): DoubleTensor = stack(indices.map { this[it] }) @@ -615,12 +615,12 @@ public open class DoubleTensorAlgebra : } /** - * Returns the covariance matrix M of given vectors. + * Returns the covariance matrix `M` of given vectors. * - * M[i, j] contains covariance of i-th and j-th given vectors + * `M[i, j]` contains covariance of `i`-th and `j`-th given vectors * * @param tensors the [List] of 1-dimensional tensors with same shape - * @return the covariance matrix + * @return `M`. */ public fun cov(tensors: List>): DoubleTensor { check(tensors.isNotEmpty()) { "List must have at least 1 element" } @@ -703,14 +703,14 @@ public open class DoubleTensorAlgebra : /** * Unpacks the data and pivots from a LU factorization of a tensor. - * Given a tensor [luTensor], return tensors (P, L, U) satisfying ``P * luTensor = L * U``, + * Given a tensor [luTensor], return tensors `Triple(P, L, U)` satisfying `P dot luTensor = L dot U`, * with `P` being a permutation matrix or batch of matrices, * `L` being a lower triangular matrix or batch of matrices, * `U` being an upper triangular matrix or batch of matrices. * * @param luTensor the packed LU factorization data * @param pivotsTensor the packed LU factorization pivots - * @return triple of P, L and U tensors + * @return triple of `P`, `L` and `U` tensors */ public fun luPivot( luTensor: Tensor, @@ -746,14 +746,15 @@ public open class DoubleTensorAlgebra : /** * QR decomposition. * - * Computes the QR decomposition of a matrix or a batch of matrices, and returns a pair `(Q, R)` of tensors. - * Given a tensor `input`, return tensors (Q, R) satisfying ``input = Q * R``, + * Computes the QR decomposition of a matrix or a batch of matrices, and returns a pair `Q to R` of tensors. + * Given a tensor `input`, return tensors `Q to R` satisfying `input == Q dot R`, * with `Q` being an orthogonal matrix or batch of orthogonal matrices * and `R` being an upper triangular matrix or batch of upper triangular matrices. * - * @param epsilon permissible error when comparing tensors for equality. + * @receiver the `input`. + * @param epsilon the permissible error when comparing tensors for equality. * Used when checking the positive definiteness of the input matrix or matrices. - * @return pair of Q and R tensors. + * @return a pair of `Q` and `R` tensors. */ public fun Tensor.cholesky(epsilon: Double): DoubleTensor { checkSquareMatrix(shape) @@ -793,13 +794,14 @@ public open class DoubleTensorAlgebra : * Singular Value Decomposition. * * Computes the singular value decomposition of either a matrix or batch of matrices `input`. - * The singular value decomposition is represented as a triple `(U, S, V)`, - * such that ``input = U.dot(diagonalEmbedding(S).dot(V.T))``. - * If input is a batch of tensors, then U, S, and Vh are also batched with the same batch dimensions as input. + * The singular value decomposition is represented as a triple `Triple(U, S, V)`, + * such that `input == U dot diagonalEmbedding(S) dot V.transpose()`. + * If `input` is a batch of tensors, then U, S, and Vh are also batched with the same batch dimensions as `input. * - * @param epsilon permissible error when calculating the dot product of vectors, - * i.e. the precision with which the cosine approaches 1 in an iterative algorithm. - * @return triple `(U, S, V)`. + * @receiver the `input`. + * @param epsilon permissible error when calculating the dot product of vectors + * i.e., the precision with which the cosine approaches 1 in an iterative algorithm. + * @return a triple `Triple(U, S, V)`. */ public fun Tensor.svd(epsilon: Double): Triple { val size = tensor.dimension @@ -834,11 +836,11 @@ public open class DoubleTensorAlgebra : /** * Returns eigenvalues and eigenvectors of a real symmetric matrix input or a batch of real symmetric matrices, - * represented by a pair (eigenvalues, eigenvectors). + * represented by a pair `eigenvalues to eigenvectors`. * - * @param epsilon permissible error when comparing tensors for equality + * @param epsilon the permissible error when comparing tensors for equality * and when the cosine approaches 1 in the SVD algorithm. - * @return a pair (eigenvalues, eigenvectors) + * @return a pair `eigenvalues to eigenvectors`. */ public fun Tensor.symEig(epsilon: Double): Pair { checkSymmetric(tensor, epsilon) @@ -857,11 +859,11 @@ public open class DoubleTensorAlgebra : * Computes the determinant of a square matrix input, or of each square matrix in a batched input * using LU factorization algorithm. * - * @param epsilon error in the LU algorithm - permissible error when comparing the determinant of a matrix with zero + * @param epsilon the error in the LU algorithm—permissible error when comparing the determinant of a matrix + * with zero. * @return the determinant. */ public fun Tensor.detLU(epsilon: Double = 1e-9): DoubleTensor { - checkSquareMatrix(tensor.shape) val luTensor = tensor.copy() val pivotsTensor = tensor.setUpPivots() @@ -889,9 +891,9 @@ public open class DoubleTensorAlgebra : * Computes the multiplicative inverse matrix of a square matrix input, or of each square matrix in a batched input * using LU factorization algorithm. * Given a square matrix `a`, return the matrix `aInv` satisfying - * ``a.dot(aInv) = aInv.dot(a) = eye(a.shape[0])``. + * `a dot aInv == aInv dot a == eye(a.shape[0])`. * - * @param epsilon error in the LU algorithm - permissible error when comparing the determinant of a matrix with zero + * @param epsilon error in the LU algorithm—permissible error when comparing the determinant of a matrix with zero * @return the multiplicative inverse of a matrix. */ public fun Tensor.invLU(epsilon: Double = 1e-9): DoubleTensor { @@ -908,16 +910,16 @@ public open class DoubleTensorAlgebra : } /** - * LUP decomposition + * LUP decomposition. * * Computes the LUP decomposition of a matrix or a batch of matrices. - * Given a tensor `input`, return tensors (P, L, U) satisfying ``P * input = L * U``, + * Given a tensor `input`, return tensors `Triple(P, L, U)` satisfying `P dot input == L dot U`, * with `P` being a permutation matrix or batch of matrices, * `L` being a lower triangular matrix or batch of matrices, * `U` being an upper triangular matrix or batch of matrices. * - * @param epsilon permissible error when comparing the determinant of a matrix with zero - * @return triple of P, L and U tensors + * @param epsilon permissible error when comparing the determinant of a matrix with zero. + * @return triple of `P`, `L` and `U` tensors. */ public fun Tensor.lu(epsilon: Double = 1e-9): Triple { val (lu, pivots) = tensor.luFactor(epsilon) diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt index e337eeef9..ff89568ea 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt @@ -14,7 +14,7 @@ import space.kscience.kmath.tensors.core.DoubleTensor import kotlin.math.* /** - * Returns a reference to [IntArray] containing all of the elements of this [Buffer] or copy the data. + * Returns a reference to [IntArray] containing all the elements of this [Buffer] or copy the data. */ internal fun Buffer.array(): IntArray = when (this) { is IntBuffer -> array @@ -22,7 +22,7 @@ internal fun Buffer.array(): IntArray = when (this) { } /** - * Returns a reference to [DoubleArray] containing all of the elements of this [Buffer] or copy the data. + * Returns a reference to [DoubleArray] containing all the elements of this [Buffer] or copy the data. */ @PublishedApi internal fun Buffer.array(): DoubleArray = when (this) { From 56fed6c16a9f721504e484547370bf721a5356fd Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Thu, 29 Jul 2021 23:55:27 +0700 Subject: [PATCH 098/132] Use Gradle caching --- .github/workflows/build.yml | 2 +- .github/workflows/pages.yml | 2 +- .github/workflows/publish.yml | 5 +++-- 3 files changed, 5 insertions(+), 4 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 2eb9f34b3..78c1522c7 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -38,4 +38,4 @@ jobs: restore-keys: | ${{ runner.os }}-gradle- - name: Build - run: ./gradlew build --no-daemon --stacktrace + run: ./gradlew build --build-cache --no-daemon --stacktrace diff --git a/.github/workflows/pages.yml b/.github/workflows/pages.yml index 1836287c8..86a0e130e 100644 --- a/.github/workflows/pages.yml +++ b/.github/workflows/pages.yml @@ -20,7 +20,7 @@ jobs: key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }} restore-keys: | ${{ runner.os }}-gradle- - - run: ./gradlew dokkaHtmlMultiModule --no-daemon --no-parallel --stacktrace + - run: ./gradlew dokkaHtmlMultiModule --build-cache --no-daemon --no-parallel --stacktrace - uses: JamesIves/github-pages-deploy-action@4.1.0 with: branch: gh-pages diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index cbf13d03d..dbc4a9473 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -42,11 +42,12 @@ jobs: if: matrix.os == 'windows-latest' shell: cmd run: > - ./gradlew release --no-daemon -Ppublishing.enabled=true -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }} + ./gradlew release --no-daemon --build-cache -Ppublishing.enabled=true + -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }} -Ppublishing.space.token=${{ secrets.SPACE_APP_SECRET }} - name: Publish Mac Artifacts if: matrix.os == 'macOS-latest' run: > - ./gradlew release --no-daemon -Ppublishing.enabled=true -Ppublishing.platform=macosX64 + ./gradlew release --no-daemon --build-cache -Ppublishing.enabled=true -Ppublishing.platform=macosX64 -Ppublishing.space.user=${{ secrets.SPACE_APP_ID }} -Ppublishing.space.token=${{ secrets.SPACE_APP_SECRET }} From 8e766497c628b190fba9814d8b39c2556ddddd6c Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Thu, 5 Aug 2021 16:09:12 +0700 Subject: [PATCH 099/132] Extend CI timeout and update GraalVM --- .github/workflows/build.yml | 4 ++-- .github/workflows/pages.yml | 3 ++- .github/workflows/publish.yml | 2 +- 3 files changed, 5 insertions(+), 4 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 78c1522c7..cde58b6d6 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -11,14 +11,14 @@ jobs: matrix: os: [ macOS-latest, windows-latest ] runs-on: ${{matrix.os}} - timeout-minutes: 30 + timeout-minutes: 40 steps: - name: Checkout the repo uses: actions/checkout@v2 - name: Set up JDK 11 uses: DeLaGuardo/setup-graalvm@4.0 with: - graalvm: 21.1.0 + graalvm: 21.2.0 java: java11 arch: amd64 - name: Cache gradle diff --git a/.github/workflows/pages.yml b/.github/workflows/pages.yml index 86a0e130e..23ed54357 100644 --- a/.github/workflows/pages.yml +++ b/.github/workflows/pages.yml @@ -7,11 +7,12 @@ on: jobs: build: runs-on: ubuntu-20.04 + timeout-minutes: 40 steps: - uses: actions/checkout@v2 - uses: DeLaGuardo/setup-graalvm@4.0 with: - graalvm: 21.1.0 + graalvm: 21.2.0 java: java11 arch: amd64 - uses: actions/cache@v2 diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index dbc4a9473..c5075cb0f 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -19,7 +19,7 @@ jobs: - name: Set up JDK 11 uses: DeLaGuardo/setup-graalvm@4.0 with: - graalvm: 21.1.0 + graalvm: 21.2.0 java: java11 arch: amd64 - name: Cache gradle From 86a45504e37d93be835e2d31da15a61acc074160 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Thu, 10 Jun 2021 01:02:57 +0700 Subject: [PATCH 100/132] Add contentEquals extension to ND algebra and LinearSpace --- .../kscience/kmath/linear/LinearSpace.kt | 2 +- .../space/kscience/kmath/nd/StructureND.kt | 41 +++++++++++++++++++ 2 files changed, 42 insertions(+), 1 deletion(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt index 63b881105..fdb5c2090 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt @@ -29,7 +29,7 @@ public typealias MutableMatrix = MutableStructure2D public typealias Point = Buffer /** - * Basic operations on matrices and vectors. Operates on [Matrix]. + * Basic operations on matrices and vectors. * * @param T the type of items in the matrices. * @param A the type of ring over [T]. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt index 716bd15f3..cfb20f441 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt @@ -5,8 +5,11 @@ package space.kscience.kmath.nd +import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.Ring +import space.kscience.kmath.operations.invoke import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.BufferFactory import kotlin.jvm.JvmName @@ -145,6 +148,44 @@ public interface StructureND { } } +/** + * Indicates whether some [StructureND] is equal to another one. + */ +@PerformancePitfall +public fun > AlgebraND>.contentEquals( + st1: StructureND, + st2: StructureND, +): Boolean = StructureND.contentEquals(st1, st2) + +/** + * Indicates whether some [StructureND] is equal to another one. + */ +@PerformancePitfall +public fun > LinearSpace>.contentEquals( + st1: StructureND, + st2: StructureND, +): Boolean = StructureND.contentEquals(st1, st2) + +/** + * Indicates whether some [StructureND] is equal to another one with [absoluteTolerance]. + */ +@PerformancePitfall +public fun > GroupND>.contentEquals( + st1: StructureND, + st2: StructureND, + absoluteTolerance: T, +): Boolean = st1.elements().all { (index, value) -> elementContext { (value - st2[index]) } < absoluteTolerance } + +/** + * Indicates whether some [StructureND] is equal to another one with [absoluteTolerance]. + */ +@PerformancePitfall +public fun > LinearSpace>.contentEquals( + st1: StructureND, + st2: StructureND, + absoluteTolerance: T, +): Boolean = st1.elements().all { (index, value) -> elementAlgebra { (value - st2[index]) } < absoluteTolerance } + /** * Returns the value at the specified indices. * From adff75bb6b616ec93d4e8ca1ce87e37fdbfc8648 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Thu, 5 Aug 2021 18:56:29 +0700 Subject: [PATCH 101/132] Avoid using kapt in kmath-jupyter #398 --- kmath-jupyter/build.gradle.kts | 4 ++++ settings.gradle.kts | 11 +++-------- 2 files changed, 7 insertions(+), 8 deletions(-) diff --git a/kmath-jupyter/build.gradle.kts b/kmath-jupyter/build.gradle.kts index 83a6a771a..5bd08c485 100644 --- a/kmath-jupyter/build.gradle.kts +++ b/kmath-jupyter/build.gradle.kts @@ -20,3 +20,7 @@ readme { kotlin.sourceSets.all { languageSettings.useExperimentalAnnotation("space.kscience.kmath.misc.UnstableKMathAPI") } + +tasks.processJupyterApiResources { + libraryProducers = listOf("space.kscience.kmath.jupyter.KMathJupyter") +} diff --git a/settings.gradle.kts b/settings.gradle.kts index 18f867df3..f05092bb1 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -5,18 +5,13 @@ pluginManagement { gradlePluginPortal() } - val toolsVersion = "0.10.2" val kotlinVersion = "1.5.21" plugins { - id("ru.mipt.npm.gradle.project") version toolsVersion - id("ru.mipt.npm.gradle.mpp") version toolsVersion - id("ru.mipt.npm.gradle.jvm") version toolsVersion - kotlin("multiplatform") version kotlinVersion - kotlin("jvm") version kotlinVersion - kotlin("plugin.allopen") version kotlinVersion id("org.jetbrains.kotlinx.benchmark") version "0.3.1" - kotlin("jupyter.api") version "0.10.0-131-1" + id("ru.mipt.npm.gradle.project") version "0.10.2" + kotlin("multiplatform") version kotlinVersion + kotlin("plugin.allopen") version kotlinVersion } } From da27c2e49482ff8286ee4d805e04e4e69b64dad9 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sun, 8 Aug 2021 12:27:16 +0700 Subject: [PATCH 102/132] Fix path to LICENSE in the notice --- .idea/copyright/kmath.xml | 2 +- .../kotlin/space/kscience/kmath/benchmarks/ArrayBenchmark.kt | 2 +- .../space/kscience/kmath/benchmarks/BigIntBenchmark.kt | 2 +- .../space/kscience/kmath/benchmarks/BufferBenchmark.kt | 2 +- .../kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt | 2 +- .../kmath/benchmarks/ExpressionsInterpretersBenchmark.kt | 2 +- .../space/kscience/kmath/benchmarks/JafamaBenchmark.kt | 2 +- .../kscience/kmath/benchmarks/MatrixInverseBenchmark.kt | 2 +- .../space/kscience/kmath/benchmarks/NDFieldBenchmark.kt | 2 +- .../space/kscience/kmath/benchmarks/ViktorBenchmark.kt | 2 +- .../space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt | 2 +- .../main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt | 2 +- .../kscience/kmath/benchmarks/addBenchmarkProperties.kt | 2 +- .../kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt | 2 +- docs/images/KM.svg | 5 +++++ docs/images/KM_mono.svg | 5 +++++ docs/images/KMath.svg | 5 +++++ docs/images/KMath_mono.svg | 5 +++++ .../src/main/kotlin/space/kscience/kmath/ast/astRendering.kt | 2 +- .../src/main/kotlin/space/kscience/kmath/ast/expressions.kt | 2 +- .../kotlin/space/kscience/kmath/ast/kotlingradSupport.kt | 2 +- .../src/main/kotlin/space/kscience/kmath/ast/symjaSupport.kt | 2 +- .../space/kscience/kmath/commons/fit/fitWithAutoDiff.kt | 2 +- .../main/kotlin/space/kscience/kmath/functions/integrate.kt | 2 +- .../kotlin/space/kscience/kmath/functions/interpolate.kt | 2 +- .../space/kscience/kmath/functions/interpolateSquare.kt | 2 +- .../space/kscience/kmath/functions/matrixIntegration.kt | 2 +- .../main/kotlin/space/kscience/kmath/jafama/JafamaDemo.kt | 2 +- .../src/main/kotlin/space/kscience/kmath/linear/gradient.kt | 2 +- .../kotlin/space/kscience/kmath/operations/BigIntDemo.kt | 2 +- .../kotlin/space/kscience/kmath/operations/ComplexDemo.kt | 2 +- .../space/kscience/kmath/stat/DistributionBenchmark.kt | 2 +- .../kotlin/space/kscience/kmath/stat/DistributionDemo.kt | 2 +- .../main/kotlin/space/kscience/kmath/structures/ComplexND.kt | 2 +- .../main/kotlin/space/kscience/kmath/structures/NDField.kt | 2 +- .../space/kscience/kmath/structures/StreamDoubleFieldND.kt | 2 +- .../kscience/kmath/structures/StructureReadBenchmark.kt | 2 +- .../kscience/kmath/structures/StructureWriteBenchmark.kt | 2 +- .../space/kscience/kmath/structures/typeSafeDimensions.kt | 2 +- .../space/kscience/kmath/tensors/DataSetNormalization.kt | 2 +- .../kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt | 2 +- .../kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt | 2 +- .../main/kotlin/space/kscience/kmath/tensors/OLSWithSVD.kt | 2 +- examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt | 2 +- .../src/commonMain/kotlin/space/kscience/kmath/ast/parser.kt | 2 +- .../kscience/kmath/ast/rendering/LatexSyntaxRenderer.kt | 2 +- .../kscience/kmath/ast/rendering/MathMLSyntaxRenderer.kt | 2 +- .../space/kscience/kmath/ast/rendering/MathRenderer.kt | 2 +- .../kotlin/space/kscience/kmath/ast/rendering/MathSyntax.kt | 2 +- .../space/kscience/kmath/ast/rendering/SyntaxRenderer.kt | 2 +- .../kotlin/space/kscience/kmath/ast/rendering/features.kt | 2 +- .../kscience/kmath/ast/rendering/multiplatformToString.kt | 2 +- .../kotlin/space/kscience/kmath/ast/rendering/phases.kt | 2 +- .../kmath/ast/TestCompilerConsistencyWithInterpreter.kt | 2 +- .../space/kscience/kmath/ast/TestCompilerOperations.kt | 2 +- .../kotlin/space/kscience/kmath/ast/TestCompilerVariables.kt | 2 +- .../commonTest/kotlin/space/kscience/kmath/ast/TestParser.kt | 2 +- .../kotlin/space/kscience/kmath/ast/TestParserPrecedence.kt | 2 +- .../space/kscience/kmath/ast/rendering/TestFeatures.kt | 2 +- .../kotlin/space/kscience/kmath/ast/rendering/TestLatex.kt | 2 +- .../kotlin/space/kscience/kmath/ast/rendering/TestMathML.kt | 2 +- .../kotlin/space/kscience/kmath/ast/rendering/TestStages.kt | 2 +- .../kotlin/space/kscience/kmath/ast/rendering/TestUtils.kt | 2 +- .../src/commonTest/kotlin/space/kscience/kmath/ast/utils.kt | 2 +- .../kscience/kmath/ast/rendering/multiplatformToString.kt | 2 +- .../src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt | 2 +- .../space/kscience/kmath/estree/internal/ESTreeBuilder.kt | 2 +- .../kmath/estree/internal/astring/astring.typealises.kt | 2 +- .../kotlin/space/kscience/kmath/internal/astring/astring.kt | 2 +- .../kscience/kmath/internal/astring/astring.typealises.kt | 2 +- .../kotlin/space/kscience/kmath/internal/base64/base64.kt | 2 +- .../space/kscience/kmath/internal/binaryen/index.binaryen.kt | 2 +- .../kmath/internal/binaryen/index.binaryen.typealiases.kt | 2 +- .../kotlin/space/kscience/kmath/internal/emitter/emitter.kt | 2 +- .../kscience/kmath/internal/estree/estree.extensions.kt | 2 +- .../kotlin/space/kscience/kmath/internal/estree/estree.kt | 2 +- .../kotlin/space/kscience/kmath/internal/stream/stream.kt | 2 +- .../kscience/kmath/internal/tsstdlib/lib.es2015.iterable.kt | 2 +- .../kotlin/space/kscience/kmath/internal/tsstdlib/lib.es5.kt | 2 +- .../internal/webassembly/lib.dom.WebAssembly.module_dukat.kt | 2 +- .../internal/webassembly/nonDeclarations.WebAssembly.kt | 2 +- .../kotlin/space/kscience/kmath/wasm/internal/WasmBuilder.kt | 2 +- .../kscience/kmath/wasm/internal/f64StandardFunctions.kt | 2 +- .../src/jsMain/kotlin/space/kscience/kmath/wasm/wasm.kt | 2 +- .../kotlin/space/kscience/kmath/ast/TestExecutionTime.kt | 2 +- .../src/jsTest/kotlin/space/kscience/kmath/ast/utils.kt | 2 +- .../kotlin/space/kscience/kmath/wasm/TestWasmSpecific.kt | 2 +- kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt | 2 +- .../kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt | 2 +- .../kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt | 2 +- .../space/kscience/kmath/asm/internal/mapIntrinsics.kt | 2 +- .../kscience/kmath/ast/rendering/multiplatformToString.kt | 2 +- .../src/jvmTest/kotlin/space/kscience/kmath/ast/utils.kt | 2 +- .../commons/expressions/DerivativeStructureExpression.kt | 2 +- .../kmath/commons/integration/CMGaussRuleIntegrator.kt | 2 +- .../space/kscience/kmath/commons/integration/CMIntegrator.kt | 2 +- .../kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt | 2 +- .../kotlin/space/kscience/kmath/commons/linear/CMSolver.kt | 2 +- .../kscience/kmath/commons/optimization/CMOptimization.kt | 2 +- .../space/kscience/kmath/commons/optimization/cmFit.kt | 2 +- .../kmath/commons/random/CMRandomGeneratorWrapper.kt | 2 +- .../kscience/kmath/commons/transform/Transformations.kt | 2 +- .../commons/expressions/DerivativeStructureExpressionTest.kt | 2 +- .../kscience/kmath/commons/integration/IntegrationTest.kt | 2 +- .../kscience/kmath/commons/optimization/OptimizeTest.kt | 2 +- .../kotlin/space/kscience/kmath/complex/Complex.kt | 2 +- .../kotlin/space/kscience/kmath/complex/ComplexFieldND.kt | 2 +- .../kotlin/space/kscience/kmath/complex/Quaternion.kt | 2 +- .../space/kscience/kmath/complex/ComplexBufferSpecTest.kt | 2 +- .../kotlin/space/kscience/kmath/complex/ComplexFieldTest.kt | 2 +- .../kotlin/space/kscience/kmath/complex/ComplexTest.kt | 2 +- .../kscience/kmath/complex/ExpressionFieldForComplexTest.kt | 2 +- .../space/kscience/kmath/complex/QuaternionFieldTest.kt | 2 +- .../kotlin/space/kscience/kmath/data/ColumnarData.kt | 2 +- .../kotlin/space/kscience/kmath/data/XYColumnarData.kt | 2 +- .../kotlin/space/kscience/kmath/data/XYZColumnarData.kt | 2 +- .../commonMain/kotlin/space/kscience/kmath/domains/Domain.kt | 2 +- .../kotlin/space/kscience/kmath/domains/DoubleDomain.kt | 2 +- .../kotlin/space/kscience/kmath/domains/HyperSquareDomain.kt | 2 +- .../space/kscience/kmath/domains/UnconstrainedDomain.kt | 2 +- .../kotlin/space/kscience/kmath/domains/UnivariateDomain.kt | 2 +- .../kscience/kmath/expressions/DifferentiableExpression.kt | 2 +- .../kotlin/space/kscience/kmath/expressions/Expression.kt | 2 +- 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.../space/kscience/kmath/expressions/SimpleAutoDiffTest.kt | 2 +- .../kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt | 2 +- .../kotlin/space/kscience/kmath/linear/MatrixTest.kt | 2 +- .../kotlin/space/kscience/kmath/misc/CumulativeKtTest.kt | 2 +- .../space/kscience/kmath/operations/BigIntAlgebraTest.kt | 2 +- .../space/kscience/kmath/operations/BigIntConstructorTest.kt | 2 +- .../space/kscience/kmath/operations/BigIntConversionsTest.kt | 2 +- .../space/kscience/kmath/operations/BigIntOperationsTest.kt | 2 +- .../space/kscience/kmath/operations/DoubleFieldTest.kt | 2 +- .../kotlin/space/kscience/kmath/structures/NDFieldTest.kt | 2 +- .../space/kscience/kmath/structures/NumberNDFieldTest.kt | 2 +- .../space/kscience/kmath/testutils/AlgebraicVerifier.kt | 2 +- .../kotlin/space/kscience/kmath/testutils/FieldVerifier.kt | 2 +- .../kotlin/space/kscience/kmath/testutils/RingVerifier.kt | 2 +- .../kotlin/space/kscience/kmath/testutils/SpaceVerifier.kt | 2 +- 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.../kotlin/space/kscience/kmath/geometry/ReferenceFrame.kt | 2 +- .../kotlin/space/kscience/kmath/histogram/Counter.kt | 2 +- .../space/kscience/kmath/histogram/DoubleHistogramSpace.kt | 2 +- .../kotlin/space/kscience/kmath/histogram/Histogram.kt | 2 +- .../space/kscience/kmath/histogram/IndexedHistogramSpace.kt | 2 +- .../kscience/kmath/histogram/MultivariateHistogramTest.kt | 2 +- .../space/kscience/kmath/histogram/TreeHistogramSpace.kt | 2 +- .../space/kscience/kmath/histogram/UnivariateHistogram.kt | 2 +- .../space/kscience/kmath/histogram/TreeHistogramTest.kt | 2 +- .../main/kotlin/space/kscience/kmath/jafama/KMathJafama.kt | 5 +++++ .../main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt | 5 +++++ .../kotlin/space/kscience/kmath/kotlingrad/KMathNumber.kt | 2 +- .../space/kscience/kmath/kotlingrad/KotlingradExpression.kt | 2 +- .../space/kscience/kmath/kotlingrad/scalarsAdapters.kt | 2 +- .../kotlin/space/kscience/kmath/kotlingrad/AdaptingTests.kt | 2 +- .../commonMain/kotlin/space/kscience/kmath/memory/Memory.kt | 2 +- .../kotlin/space/kscience/kmath/memory/MemorySpec.kt | 2 +- .../kotlin/space/kscience/kmath/memory/DataViewMemory.kt | 2 +- .../kotlin/space/kscience/kmath/memory/ByteBufferMemory.kt | 2 +- .../kotlin/space/kscience/kmath/memory/NativeMemory.kt | 2 +- .../kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt | 2 +- .../kotlin/space/kscience/kmath/nd4j/Nd4jArrayIterator.kt | 2 +- .../kotlin/space/kscience/kmath/nd4j/Nd4jArrayStructure.kt | 2 +- .../kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt | 2 +- .../src/main/kotlin/space/kscience/kmath/nd4j/arrays.kt | 2 +- .../kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebraTest.kt | 2 +- .../space/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt | 2 +- .../space/kscience/kmath/distributions/Distribution.kt | 2 +- .../kscience/kmath/distributions/FactorizedDistribution.kt | 2 +- .../space/kscience/kmath/distributions/NormalDistribution.kt | 2 +- .../kotlin/space/kscience/kmath/internal/InternalErf.kt | 2 +- .../kotlin/space/kscience/kmath/internal/InternalGamma.kt | 2 +- .../kotlin/space/kscience/kmath/internal/InternalUtils.kt | 2 +- .../kscience/kmath/optimization/FunctionOptimization.kt | 2 +- .../kmath/optimization/NoDerivFunctionOptimization.kt | 2 +- .../kotlin/space/kscience/kmath/optimization/Optimization.kt | 2 +- .../kotlin/space/kscience/kmath/optimization/XYFit.kt | 2 +- .../kmath/samplers/AhrensDieterExponentialSampler.kt | 2 +- .../kmath/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt | 2 +- .../kscience/kmath/samplers/AliasMethodDiscreteSampler.kt | 2 +- .../kotlin/space/kscience/kmath/samplers/BoxMullerSampler.kt | 2 +- .../kotlin/space/kscience/kmath/samplers/GaussianSampler.kt | 2 +- .../kscience/kmath/samplers/KempSmallMeanPoissonSampler.kt | 2 +- .../kmath/samplers/MarsagliaNormalizedGaussianSampler.kt | 2 +- .../kscience/kmath/samplers/NormalizedGaussianSampler.kt | 2 +- .../kotlin/space/kscience/kmath/samplers/PoissonSampler.kt | 2 +- .../kmath/samplers/ZigguratNormalizedGaussianSampler.kt | 2 +- .../commonMain/kotlin/space/kscience/kmath/stat/MCScope.kt | 2 +- .../src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt | 2 +- .../commonMain/kotlin/space/kscience/kmath/stat/Median.kt | 2 +- .../kotlin/space/kscience/kmath/stat/RandomChain.kt | 2 +- .../kotlin/space/kscience/kmath/stat/RandomGenerator.kt | 2 +- .../commonMain/kotlin/space/kscience/kmath/stat/Sampler.kt | 2 +- .../kotlin/space/kscience/kmath/stat/SamplerAlgebra.kt | 2 +- .../commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt | 2 +- .../kotlin/space/kscience/kmath/stat/UniformDistribution.kt | 2 +- .../space/kscience/kmath/stat/RandomSourceGenerator.kt | 2 +- .../space/kscience/kmath/stat/CommonsDistributionsTest.kt | 2 +- .../jvmTest/kotlin/space/kscience/kmath/stat/MCScopeTest.kt | 2 +- .../jvmTest/kotlin/space/kscience/kmath/stat/SamplerTest.kt | 2 +- .../kotlin/space/kscience/kmath/stat/StatisticTest.kt | 2 +- .../kotlin/space/kscience/kmath/symja/SymjaExpression.kt | 2 +- .../src/main/kotlin/space/kscience/kmath/symja/adapters.kt | 2 +- .../kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt | 2 +- .../kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt | 2 +- .../kotlin/space/kscience/kmath/tensors/api/Tensor.kt | 5 +++++ .../kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt | 2 +- .../kmath/tensors/api/TensorPartialDivisionAlgebra.kt | 2 +- .../kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt | 2 +- .../space/kscience/kmath/tensors/core/BufferedTensor.kt | 5 +++++ .../kotlin/space/kscience/kmath/tensors/core/DoubleTensor.kt | 2 +- .../space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt | 2 +- .../kotlin/space/kscience/kmath/tensors/core/IntTensor.kt | 2 +- .../kmath/tensors/core/internal/TensorLinearStructure.kt | 2 +- .../kscience/kmath/tensors/core/internal/broadcastUtils.kt | 2 +- .../space/kscience/kmath/tensors/core/internal/checks.kt | 2 +- .../space/kscience/kmath/tensors/core/internal/linUtils.kt | 2 +- .../kscience/kmath/tensors/core/internal/tensorCastsUtils.kt | 2 +- .../space/kscience/kmath/tensors/core/internal/utils.kt | 2 +- .../kotlin/space/kscience/kmath/tensors/core/tensorCasts.kt | 2 +- .../space/kscience/kmath/tensors/core/TestBroadcasting.kt | 5 +++++ .../kmath/tensors/core/TestDoubleAnalyticTensorAlgebra.kt | 5 +++++ .../kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt | 5 +++++ .../space/kscience/kmath/tensors/core/TestDoubleTensor.kt | 5 +++++ .../kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt | 5 +++++ .../main/kotlin/space/kscience/kmath/viktor/ViktorBuffer.kt | 2 +- .../kotlin/space/kscience/kmath/viktor/ViktorStructureND.kt | 2 +- 331 files changed, 383 insertions(+), 318 deletions(-) diff --git a/.idea/copyright/kmath.xml b/.idea/copyright/kmath.xml index 17e44e4d0..1070e5d33 100644 --- a/.idea/copyright/kmath.xml +++ b/.idea/copyright/kmath.xml @@ -1,6 +1,6 @@ - diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ArrayBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ArrayBenchmark.kt index ff933997f..17983e88c 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ArrayBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ArrayBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt index 749cd5e75..6f501dedb 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BufferBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BufferBenchmark.kt index 39819d407..5cf194b67 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BufferBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BufferBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt index 2c5a03a97..629408479 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt index 0294f924b..8c3c8ec2b 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt index 5d4eee7c0..9c6551302 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/JafamaBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt index e3179c05c..1072a55c3 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt index 5e0c6735f..0cd9a46ab 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt index d2359a791..1ddc79cf8 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt index eac8634f5..8622e8f30 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt index eaa0f59d8..6859de845 100644 --- a/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/JmhReport.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt index b55e1320e..72c9ff0ad 100644 --- a/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/benchmarks/addBenchmarkProperties.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ package space.kscience.kmath.benchmarks diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt index a0d40c1ee..1d2aaeaaf 100644 --- a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt @@ -1,6 +1,6 @@ /* * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ @file:Suppress("KDocUnresolvedReference") diff --git a/docs/images/KM.svg b/docs/images/KM.svg index 83af21f35..f5ec452c7 100644 --- a/docs/images/KM.svg +++ b/docs/images/KM.svg @@ -1,4 +1,9 @@ + + + + + + + + Date: Thu, 12 Aug 2021 20:28:45 +0300 Subject: [PATCH 103/132] Fix JS bug with null cast --- .../kotlin/space/kscience/kmath/misc/Featured.kt | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt index 648b6376f..be1c8380c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt @@ -16,13 +16,14 @@ public interface Featured { public typealias FeatureKey = KClass -public interface Feature> { +public interface Feature> { /** * A key used for extraction */ @Suppress("UNCHECKED_CAST") - public val key: FeatureKey get() = this::class as FeatureKey + public val key: FeatureKey + get() = this::class as FeatureKey } /** @@ -30,7 +31,7 @@ public interface Feature> { */ public class FeatureSet> private constructor(public val features: Map, F>) : Featured { @Suppress("UNCHECKED_CAST") - override fun getFeature(type: FeatureKey): T? = features[type] as? T + override fun getFeature(type: FeatureKey): T? = features[type]?.let { it as T } public inline fun getFeature(): T? = getFeature(T::class) @@ -49,6 +50,7 @@ public class FeatureSet> private constructor(public val features: public companion object { public fun > of(vararg features: F): FeatureSet = FeatureSet(features.associateBy { it.key }) - public fun > of(features: Iterable): FeatureSet = FeatureSet(features.associateBy { it.key }) + public fun > of(features: Iterable): FeatureSet = + FeatureSet(features.associateBy { it.key }) } } From aaa298616d2668f80062079ede547f4228246b5e Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 16 Aug 2021 09:55:03 +0300 Subject: [PATCH 104/132] QOW is working more or less --- examples/build.gradle.kts | 1 + .../fitWithAutoDiff.kt => fit/chiSquared.kt} | 13 +- .../kotlin/space/kscience/kmath/fit/qowFit.kt | 105 ++++++++++ .../kmath/functions/matrixIntegration.kt | 2 +- kmath-commons/build.gradle.kts | 1 + .../kmath/commons/optimization/CMOptimizer.kt | 7 +- .../DerivativeStructureExpressionTest.kt | 4 +- .../commons/optimization/OptimizeTest.kt | 3 +- .../kscience/kmath/data/XYColumnarData.kt | 20 +- .../kmath/data/XYErrorColumnarData.kt | 25 ++- .../kscience/kmath/expressions/Expression.kt | 7 +- .../kmath/expressions/specialExpressions.kt | 17 +- .../space/kscience/kmath/misc/Featured.kt | 7 +- .../space/kscience/kmath/misc/logging.kt | 14 +- .../kmath/expressions/ExpressionFieldTest.kt | 6 +- .../kmath/integration/GaussIntegrator.kt | 3 +- .../kmath/interpolation/Interpolator.kt | 6 +- kmath-optimization/build.gradle.kts | 20 ++ .../optimization/FunctionOptimization.kt | 33 ++- .../kmath/optimization/OptimizationBuilder.kt | 8 +- .../kmath/optimization/OptimizationProblem.kt | 0 .../kscience/kmath/optimization/Optimizer.kt | 0 .../kmath/optimization/QowOptimizer.kt | 72 +++---- .../kscience/kmath/optimization/XYFit.kt | 125 ++++++++++++ .../kmath/optimization/logLikelihood.kt | 66 ++++++ kmath-stat/build.gradle.kts | 3 +- .../kmath/optimization/XYOptimization.kt | 189 ------------------ settings.gradle.kts | 1 + 28 files changed, 477 insertions(+), 281 deletions(-) rename examples/src/main/kotlin/space/kscience/kmath/{commons/fit/fitWithAutoDiff.kt => fit/chiSquared.kt} (91%) create mode 100644 examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt create mode 100644 kmath-optimization/build.gradle.kts rename {kmath-stat => kmath-optimization}/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt (65%) rename {kmath-stat => kmath-optimization}/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt (94%) rename {kmath-stat => kmath-optimization}/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt (77%) create mode 100644 kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt create mode 100644 kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/logLikelihood.kt delete mode 100644 kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt diff --git a/examples/build.gradle.kts b/examples/build.gradle.kts index 4cc6fecc0..d06005321 100644 --- a/examples/build.gradle.kts +++ b/examples/build.gradle.kts @@ -20,6 +20,7 @@ dependencies { implementation(project(":kmath-coroutines")) implementation(project(":kmath-commons")) implementation(project(":kmath-complex")) + implementation(project(":kmath-optimization")) implementation(project(":kmath-stat")) implementation(project(":kmath-viktor")) implementation(project(":kmath-dimensions")) diff --git a/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt b/examples/src/main/kotlin/space/kscience/kmath/fit/chiSquared.kt similarity index 91% rename from examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt rename to examples/src/main/kotlin/space/kscience/kmath/fit/chiSquared.kt index 8d95ebb4a..c1070de52 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/fit/chiSquared.kt @@ -3,19 +3,17 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. */ -package space.kscience.kmath.commons.fit +package space.kscience.kmath.fit import kotlinx.html.br import kotlinx.html.h3 import space.kscience.kmath.commons.expressions.DSProcessor import space.kscience.kmath.commons.optimization.CMOptimizer import space.kscience.kmath.distributions.NormalDistribution +import space.kscience.kmath.expressions.binding import space.kscience.kmath.expressions.chiSquaredExpression import space.kscience.kmath.expressions.symbol -import space.kscience.kmath.optimization.FunctionOptimizationTarget -import space.kscience.kmath.optimization.optimizeWith -import space.kscience.kmath.optimization.resultPoint -import space.kscience.kmath.optimization.resultValue +import space.kscience.kmath.optimization.* import space.kscience.kmath.real.DoubleVector import space.kscience.kmath.real.map import space.kscience.kmath.real.step @@ -25,6 +23,7 @@ import space.kscience.kmath.structures.toList import space.kscience.plotly.* import space.kscience.plotly.models.ScatterMode import space.kscience.plotly.models.TraceValues +import kotlin.math.abs import kotlin.math.pow import kotlin.math.sqrt @@ -45,7 +44,7 @@ operator fun TraceValues.invoke(vector: DoubleVector) { */ suspend fun main() { //A generator for a normally distributed values - val generator = NormalDistribution(2.0, 7.0) + val generator = NormalDistribution(0.0, 1.0) //A chain/flow of random values with the given seed val chain = generator.sample(RandomGenerator.default(112667)) @@ -56,7 +55,7 @@ suspend fun main() { //Perform an operation on each x value (much more effective, than numpy) - val y = x.map { + val y = x.map { it -> val value = it.pow(2) + it + 1 value + chain.next() * sqrt(value) } diff --git a/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt b/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt new file mode 100644 index 000000000..944f80697 --- /dev/null +++ b/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt @@ -0,0 +1,105 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.fit + +import kotlinx.html.br +import kotlinx.html.h3 +import space.kscience.kmath.commons.expressions.DSProcessor +import space.kscience.kmath.data.XYErrorColumnarData +import space.kscience.kmath.distributions.NormalDistribution +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.expressions.binding +import space.kscience.kmath.expressions.symbol +import space.kscience.kmath.optimization.QowOptimizer +import space.kscience.kmath.optimization.fitWith +import space.kscience.kmath.optimization.resultPoint +import space.kscience.kmath.real.map +import space.kscience.kmath.real.step +import space.kscience.kmath.stat.RandomGenerator +import space.kscience.kmath.structures.asIterable +import space.kscience.kmath.structures.toList +import space.kscience.plotly.* +import space.kscience.plotly.models.ScatterMode +import kotlin.math.abs +import kotlin.math.pow +import kotlin.math.sqrt + +// Forward declaration of symbols that will be used in expressions. +private val a by symbol +private val b by symbol +private val c by symbol + + +/** + * Least squares fie with auto-differentiation. Uses `kmath-commons` and `kmath-for-real` modules. + */ +suspend fun main() { + //A generator for a normally distributed values + val generator = NormalDistribution(0.0, 1.0) + + //A chain/flow of random values with the given seed + val chain = generator.sample(RandomGenerator.default(112667)) + + + //Create a uniformly distributed x values like numpy.arrange + val x = 1.0..100.0 step 1.0 + + + //Perform an operation on each x value (much more effective, than numpy) + val y = x.map { it -> + val value = it.pow(2) + it + 100 + value + chain.next() * sqrt(value) + } + // this will also work, but less effective: + // val y = x.pow(2)+ x + 1 + chain.nextDouble() + + // create same errors for all xs + val yErr = y.map { sqrt(abs(it)) } + require(yErr.asIterable().all { it > 0 }) { "All errors must be strictly positive" } + + val result = XYErrorColumnarData.of(x, y, yErr).fitWith( + QowOptimizer, + DSProcessor, + mapOf(a to 1.0, b to 1.2, c to 99.0) + ) { arg -> + //bind variables to autodiff context + val a by binding + val b by binding + //Include default value for c if it is not provided as a parameter + val c = bindSymbolOrNull(c) ?: one + a * arg.pow(2) + b * arg + c + } + + //display a page with plot and numerical results + val page = Plotly.page { + plot { + scatter { + mode = ScatterMode.markers + x(x) + y(y) + error_y { + array = yErr.toList() + } + name = "data" + } + scatter { + mode = ScatterMode.lines + x(x) + y(x.map { result.model(result.resultPoint + (Symbol.x to it)) }) + name = "fit" + } + } + br() + h3 { + +"Fit result: ${result.resultPoint}" + } +// h3 { +// +"Chi2/dof = ${result.resultValue / (x.size - 3)}" +// } + } + + page.makeFile() +} diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt index 2619d3d74..e5ba29d73 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt @@ -22,7 +22,7 @@ fun main(): Unit = DoubleField { } //Define a function in a nd space - val function: (Double) -> StructureND = { x: Double -> 3 * number(x).pow(2) + 2 * diagonal(x) + 1 } + val function: (Double) -> StructureND = { x: Double -> 3 * x.pow(2) + 2 * diagonal(x) + 1 } //get the result of the integration val result = gaussIntegrator.integrate(0.0..10.0, function = function) diff --git a/kmath-commons/build.gradle.kts b/kmath-commons/build.gradle.kts index a208c956c..96c17a215 100644 --- a/kmath-commons/build.gradle.kts +++ b/kmath-commons/build.gradle.kts @@ -9,6 +9,7 @@ dependencies { api(project(":kmath-core")) api(project(":kmath-complex")) api(project(":kmath-coroutines")) + api(project(":kmath-optimization")) api(project(":kmath-stat")) api(project(":kmath-functions")) api("org.apache.commons:commons-math3:3.6.1") diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimizer.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimizer.kt index abf95daf6..11eb6fba8 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimizer.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimizer.kt @@ -18,6 +18,7 @@ import space.kscience.kmath.expressions.SymbolIndexer import space.kscience.kmath.expressions.derivative import space.kscience.kmath.expressions.withSymbols import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.misc.log import space.kscience.kmath.optimization.* import kotlin.collections.set import kotlin.reflect.KClass @@ -108,15 +109,17 @@ public object CMOptimizer : Optimizer> { val objectiveFunction = ObjectiveFunction { val args = startPoint + it.toMap() - problem.expression(args) + val res = problem.expression(args) + res } addOptimizationData(objectiveFunction) val gradientFunction = ObjectiveFunctionGradient { val args = startPoint + it.toMap() - DoubleArray(symbols.size) { index -> + val res = DoubleArray(symbols.size) { index -> problem.expression.derivative(symbols[index])(args) } + res } addOptimizationData(gradientFunction) diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt index 3c57f5467..56252ab34 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt @@ -42,8 +42,8 @@ internal class AutoDiffTest { @Test fun autoDifTest() { val f = DerivativeStructureExpression { - val x by binding() - val y by binding() + val x by binding + val y by binding x.pow(2) + 2 * x * y + y.pow(2) + 1 } diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt index 170fceceb..facbf3a9a 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt @@ -15,6 +15,7 @@ import space.kscience.kmath.expressions.chiSquaredExpression import space.kscience.kmath.expressions.symbol import space.kscience.kmath.optimization.* import space.kscience.kmath.stat.RandomGenerator +import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.asBuffer import space.kscience.kmath.structures.map import kotlin.math.pow @@ -58,7 +59,7 @@ internal class OptimizeTest { it.pow(2) + it + 1 + chain.next() } - val yErr = List(x.size) { sigma }.asBuffer() + val yErr = DoubleBuffer(x.size) { sigma } val chi2 = DSProcessor.chiSquaredExpression( x, y, yErr diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt index bd0e13b9d..2fce772cc 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYColumnarData.kt @@ -32,19 +32,21 @@ public interface XYColumnarData : ColumnarData { Symbol.y -> y else -> null } -} -@Suppress("FunctionName") -@UnstableKMathAPI -public fun XYColumnarData(x: Buffer, y: Buffer): XYColumnarData { - require(x.size == y.size) { "Buffer size mismatch. x buffer size is ${x.size}, y buffer size is ${y.size}" } - return object : XYColumnarData { - override val size: Int = x.size - override val x: Buffer = x - override val y: Buffer = y + public companion object{ + @UnstableKMathAPI + public fun of(x: Buffer, y: Buffer): XYColumnarData { + require(x.size == y.size) { "Buffer size mismatch. x buffer size is ${x.size}, y buffer size is ${y.size}" } + return object : XYColumnarData { + override val size: Int = x.size + override val x: Buffer = x + override val y: Buffer = y + } + } } } + /** * Represent a [ColumnarData] as an [XYColumnarData]. The presence or respective columns is checked on creation. */ diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt index 7199de888..8ddd6406f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/data/XYErrorColumnarData.kt @@ -5,15 +5,13 @@ package space.kscience.kmath.data -import space.kscience.kmath.data.XYErrorColumnarData.Companion import space.kscience.kmath.expressions.Symbol -import space.kscience.kmath.expressions.symbol import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.structures.Buffer /** - * A [ColumnarData] with additional [Companion.yErr] column for an [Symbol.y] error + * A [ColumnarData] with additional [Symbol.yError] column for an [Symbol.y] error * Inherits [XYColumnarData]. */ @UnstableKMathAPI @@ -23,11 +21,24 @@ public interface XYErrorColumnarData : XYColumnarData = when (symbol) { Symbol.x -> x Symbol.y -> y - Companion.yErr -> yErr + Symbol.yError -> yErr else -> error("A column for symbol $symbol not found") } - public companion object{ - public val yErr: Symbol by symbol + public companion object { + public fun of( + x: Buffer, y: Buffer, yErr: Buffer + ): XYErrorColumnarData { + require(x.size == y.size) { "Buffer size mismatch. x buffer size is ${x.size}, y buffer size is ${y.size}" } + require(y.size == yErr.size) { "Buffer size mismatch. y buffer size is ${x.size}, yErr buffer size is ${y.size}" } + + return object : XYErrorColumnarData { + override val size: Int = x.size + override val x: Buffer = x + override val y: Buffer = y + override val yErr: Buffer = yErr + } + } } -} \ No newline at end of file +} + diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt index 5105c2bec..e94cb98eb 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt @@ -68,6 +68,7 @@ public interface ExpressionAlgebra : Algebra { /** * Bind a symbol by name inside the [ExpressionAlgebra] */ -public fun ExpressionAlgebra.binding(): ReadOnlyProperty = ReadOnlyProperty { _, property -> - bindSymbol(property.name) ?: error("A variable with name ${property.name} does not exist") -} +public val ExpressionAlgebra.binding: ReadOnlyProperty + get() = ReadOnlyProperty { _, property -> + bindSymbol(property.name) ?: error("A variable with name ${property.name} does not exist") + } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/specialExpressions.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/specialExpressions.kt index ede4a779c..6b17dfca5 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/specialExpressions.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/specialExpressions.kt @@ -7,13 +7,18 @@ package space.kscience.kmath.expressions import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.asIterable import space.kscience.kmath.structures.indices +import kotlin.jvm.JvmName /** * Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic * differentiation. + * + * **WARNING** All elements of [yErr] must be positive. */ -public fun AutoDiffProcessor.chiSquaredExpression( +@JvmName("genericChiSquaredExpression") +public fun , I : Any, A> AutoDiffProcessor.chiSquaredExpression( x: Buffer, y: Buffer, yErr: Buffer, @@ -35,4 +40,14 @@ public fun AutoDiffProcessor.chiSquaredExpression sum } +} + +public fun AutoDiffProcessor.chiSquaredExpression( + x: Buffer, + y: Buffer, + yErr: Buffer, + model: A.(I) -> I, +): DifferentiableExpression where A : ExtendedField, A : ExpressionAlgebra { + require(yErr.asIterable().all { it > 0.0 }) { "All errors must be strictly positive" } + return chiSquaredExpression(x, y, yErr, model) } \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt index be1c8380c..29b7caec6 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/Featured.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.misc +import kotlin.jvm.JvmInline import kotlin.reflect.KClass /** @@ -29,7 +30,8 @@ public interface Feature> { /** * A container for a set of features */ -public class FeatureSet> private constructor(public val features: Map, F>) : Featured { +@JvmInline +public value class FeatureSet> private constructor(public val features: Map, F>) : Featured { @Suppress("UNCHECKED_CAST") override fun getFeature(type: FeatureKey): T? = features[type]?.let { it as T } @@ -48,6 +50,9 @@ public class FeatureSet> private constructor(public val features: public operator fun iterator(): Iterator = features.values.iterator() + override fun toString(): String = features.values.joinToString(prefix = "[ ", postfix = " ]") + + public companion object { public fun > of(vararg features: F): FeatureSet = FeatureSet(features.associateBy { it.key }) public fun > of(features: Iterable): FeatureSet = diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/logging.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/logging.kt index d13840841..9dfc564c3 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/logging.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/misc/logging.kt @@ -5,10 +5,18 @@ package space.kscience.kmath.misc -public interface Loggable { - public fun log(tag: String = INFO, block: () -> String) +import space.kscience.kmath.misc.Loggable.Companion.INFO + +public fun interface Loggable { + public fun log(tag: String, block: () -> String) public companion object { public const val INFO: String = "INFO" + + public val console: Loggable = Loggable { tag, block -> + println("[$tag] ${block()}") + } } -} \ No newline at end of file +} + +public fun Loggable.log(block: () -> String): Unit = log(INFO, block) \ No newline at end of file diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt index 4d1b00b3d..80c5943cf 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/expressions/ExpressionFieldTest.kt @@ -16,7 +16,7 @@ class ExpressionFieldTest { @Test fun testExpression() { val expression = with(FunctionalExpressionField(DoubleField)) { - val x by binding() + val x by binding x * x + 2 * x + one } @@ -27,7 +27,7 @@ class ExpressionFieldTest { @Test fun separateContext() { fun FunctionalExpressionField.expression(): Expression { - val x by binding() + val x by binding return x * x + 2 * x + one } @@ -38,7 +38,7 @@ class ExpressionFieldTest { @Test fun valueExpression() { val expressionBuilder: FunctionalExpressionField.() -> Expression = { - val x by binding() + val x by binding x * x + 2 * x + one } diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt index 9b938394a..9785d7744 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegrator.kt @@ -73,7 +73,8 @@ public class GaussIntegrator( } /** - * Create a Gauss-Legendre integrator for this field. + * Create a Gauss integrator for this field. By default, uses Legendre rule to compute points and weights. + * Custom rules could be provided by [GaussIntegratorRuleFactory] feature. * @see [GaussIntegrator] */ public val Field.gaussIntegrator: GaussIntegrator get() = GaussIntegrator(this) diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt index f4a0abd5d..b13adefa5 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/Interpolator.kt @@ -42,20 +42,20 @@ public fun > PolynomialInterpolator.interpolatePolynomials( x: Buffer, y: Buffer, ): PiecewisePolynomial { - val pointSet = XYColumnarData(x, y) + val pointSet = XYColumnarData.of(x, y) return interpolatePolynomials(pointSet) } public fun > PolynomialInterpolator.interpolatePolynomials( data: Map, ): PiecewisePolynomial { - val pointSet = XYColumnarData(data.keys.toList().asBuffer(), data.values.toList().asBuffer()) + val pointSet = XYColumnarData.of(data.keys.toList().asBuffer(), data.values.toList().asBuffer()) return interpolatePolynomials(pointSet) } public fun > PolynomialInterpolator.interpolatePolynomials( data: List>, ): PiecewisePolynomial { - val pointSet = XYColumnarData(data.map { it.first }.asBuffer(), data.map { it.second }.asBuffer()) + val pointSet = XYColumnarData.of(data.map { it.first }.asBuffer(), data.map { it.second }.asBuffer()) return interpolatePolynomials(pointSet) } diff --git a/kmath-optimization/build.gradle.kts b/kmath-optimization/build.gradle.kts new file mode 100644 index 000000000..ca013b2f4 --- /dev/null +++ b/kmath-optimization/build.gradle.kts @@ -0,0 +1,20 @@ +plugins { + id("ru.mipt.npm.gradle.mpp") + id("ru.mipt.npm.gradle.native") +} + +kscience { + useAtomic() +} + +kotlin.sourceSets { + commonMain { + dependencies { + api(project(":kmath-coroutines")) + } + } +} + +readme { + maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL +} \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt similarity index 65% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt rename to kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt index 1af6c4bda..02602b068 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt @@ -5,13 +5,11 @@ package space.kscience.kmath.optimization -import space.kscience.kmath.expressions.* +import space.kscience.kmath.expressions.DifferentiableExpression +import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.misc.FeatureSet -import space.kscience.kmath.operations.ExtendedField -import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.indices -public class OptimizationValue(public val value: T) : OptimizationFeature{ +public class OptimizationValue(public val value: T) : OptimizationFeature { override fun toString(): String = "Value($value)" } @@ -23,9 +21,28 @@ public enum class FunctionOptimizationTarget : OptimizationFeature { public class FunctionOptimization( override val features: FeatureSet, public val expression: DifferentiableExpression, -) : OptimizationProblem{ +) : OptimizationProblem { - public companion object + + override fun equals(other: Any?): Boolean { + if (this === other) return true + if (other == null || this::class != other::class) return false + + other as FunctionOptimization<*> + + if (features != other.features) return false + if (expression != other.expression) return false + + return true + } + + override fun hashCode(): Int { + var result = features.hashCode() + result = 31 * result + expression.hashCode() + return result + } + + override fun toString(): String = "FunctionOptimization(features=$features)" } public fun FunctionOptimization.withFeatures( @@ -47,7 +64,7 @@ public suspend fun DifferentiableExpression.optimizeWith( return optimizer.optimize(problem) } -public val FunctionOptimization.resultValueOrNull:T? +public val FunctionOptimization.resultValueOrNull: T? get() = getFeature>()?.point?.let { expression(it) } public val FunctionOptimization.resultValue: T diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt similarity index 94% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt rename to kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt index 7d52ae26e..10a25c029 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt @@ -72,15 +72,15 @@ public suspend fun DifferentiableExpression.optimizeWith( public class XYOptimizationBuilder( public val data: XYColumnarData, public val model: DifferentiableExpression, -) : OptimizationBuilder() { +) : OptimizationBuilder() { public var pointToCurveDistance: PointToCurveDistance = PointToCurveDistance.byY public var pointWeight: PointWeight = PointWeight.byYSigma - override fun build(): XYOptimization = XYOptimization( - FeatureSet.of(features), + override fun build(): XYFit = XYFit( data, model, + FeatureSet.of(features), pointToCurveDistance, pointWeight ) @@ -90,4 +90,4 @@ public fun XYOptimization( data: XYColumnarData, model: DifferentiableExpression, builder: XYOptimizationBuilder.() -> Unit, -): XYOptimization = XYOptimizationBuilder(data, model).apply(builder).build() \ No newline at end of file +): XYFit = XYOptimizationBuilder(data, model).apply(builder).build() \ No newline at end of file diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt rename to kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationProblem.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt rename to kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/Optimizer.kt diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt similarity index 77% rename from kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt rename to kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt index 365c58952..f0969d2f6 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt @@ -11,6 +11,7 @@ import space.kscience.kmath.expressions.SymbolIndexer import space.kscience.kmath.expressions.derivative import space.kscience.kmath.linear.* import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.misc.log import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.DoubleL2Norm @@ -21,14 +22,14 @@ import space.kscience.kmath.structures.DoubleL2Norm * See [the article](http://arxiv.org/abs/physics/0604127). */ @UnstableKMathAPI -public class QowOptimizer : Optimizer { +public object QowOptimizer : Optimizer { private val linearSpace: LinearSpace = LinearSpace.double private val solver: LinearSolver = linearSpace.lupSolver() @OptIn(UnstableKMathAPI::class) - private inner class QoWeight( - val problem: XYOptimization, + private class QoWeight( + val problem: XYFit, val parameters: Map, ) : Map by parameters, SymbolIndexer { override val symbols: List = parameters.keys.toList() @@ -39,8 +40,8 @@ public class QowOptimizer : Optimizer { * Derivatives of the spectrum over parameters. First index in the point number, second one - index of parameter */ val derivs: Matrix by lazy { - linearSpace.buildMatrix(problem.data.size, symbols.size) { i, k -> - problem.distance(i).derivative(symbols[k])(parameters) + linearSpace.buildMatrix(problem.data.size, symbols.size) { d, s -> + problem.distance(d).derivative(symbols[s])(parameters) } } @@ -48,25 +49,27 @@ public class QowOptimizer : Optimizer { * Array of dispersions in each point */ val dispersion: Point by lazy { - DoubleBuffer(problem.data.size) { i -> - problem.weight(i).invoke(parameters) + DoubleBuffer(problem.data.size) { d -> + problem.weight(d).invoke(parameters) } } val prior: DifferentiableExpression? get() = problem.getFeature>() + + override fun toString(): String = parameters.toString() } /** - * The signed distance from the model to the [i]-th point of data. + * The signed distance from the model to the [d]-th point of data. */ - private fun QoWeight.distance(i: Int, parameters: Map): Double = problem.distance(i)(parameters) + private fun QoWeight.distance(d: Int, parameters: Map): Double = problem.distance(d)(parameters) /** * The derivative of [distance] */ - private fun QoWeight.distanceDerivative(symbol: Symbol, i: Int, parameters: Map): Double = - problem.distance(i).derivative(symbol)(parameters) + private fun QoWeight.distanceDerivative(symbol: Symbol, d: Int, parameters: Map): Double = + problem.distance(d).derivative(symbol)(parameters) /** * Теоретическая ковариация весовых функций. @@ -74,8 +77,8 @@ public class QowOptimizer : Optimizer { * D(\phi)=E(\phi_k(\theta_0) \phi_l(\theta_0))= disDeriv_k * disDeriv_l /sigma^2 */ private fun QoWeight.covarF(): Matrix = - linearSpace.matrix(size, size).symmetric { k, l -> - (0 until data.size).sumOf { i -> derivs[k, i] * derivs[l, i] / dispersion[i] } + linearSpace.matrix(size, size).symmetric { s1, s2 -> + (0 until data.size).sumOf { d -> derivs[d, s1] * derivs[d, s2] / dispersion[d] } } /** @@ -89,12 +92,12 @@ public class QowOptimizer : Optimizer { * количество вызывов функции будет dim^2 вместо dim Первый индекс - * номер точки, второй - номер переменной, по которой берется производная */ - val eqvalues = linearSpace.buildMatrix(data.size, size) { i, l -> - distance(i, theta) * derivs[l, i] / dispersion[i] + val eqvalues = linearSpace.buildMatrix(data.size, size) { d, s -> + distance(d, theta) * derivs[d, s] / dispersion[d] } - buildMatrix(size, size) { k, l -> - (0 until data.size).sumOf { i -> eqvalues[i, l] * eqvalues[i, k] } + buildMatrix(size, size) { s1, s2 -> + (0 until data.size).sumOf { d -> eqvalues[d, s2] * eqvalues[d, s1] } } } @@ -106,20 +109,20 @@ public class QowOptimizer : Optimizer { ): Matrix = with(linearSpace) { //Возвращает производную k-того Eq по l-тому параметру //val res = Array(fitDim) { DoubleArray(fitDim) } - val sderiv = buildMatrix(data.size, size) { i, l -> - distanceDerivative(symbols[l], i, theta) + val sderiv = buildMatrix(data.size, size) { d, s -> + distanceDerivative(symbols[s], d, theta) } - buildMatrix(size, size) { k, l -> - val base = (0 until data.size).sumOf { i -> - require(dispersion[i] > 0) - sderiv[i, l] * derivs[k, i] / dispersion[i] + buildMatrix(size, size) { s1, s2 -> + val base = (0 until data.size).sumOf { d -> + require(dispersion[d] > 0) + sderiv[d, s2] * derivs[d, s1] / dispersion[d] } prior?.let { prior -> //Check if this one is correct val pi = prior(theta) - val deriv1 = prior.derivative(symbols[k])(theta) - val deriv2 = prior.derivative(symbols[l])(theta) + val deriv1 = prior.derivative(symbols[s1])(theta) + val deriv2 = prior.derivative(symbols[s2])(theta) base + deriv1 * deriv2 / pi / pi } ?: base } @@ -130,13 +133,13 @@ public class QowOptimizer : Optimizer { * Значения уравнений метода квазиоптимальных весов */ private fun QoWeight.getEqValues(theta: Map = this): Point { - val distances = DoubleBuffer(data.size) { i -> distance(i, theta) } + val distances = DoubleBuffer(data.size) { d -> distance(d, theta) } - return DoubleBuffer(size) { k -> - val base = (0 until data.size).sumOf { i -> distances[i] * derivs[k, i] / dispersion[i] } + return DoubleBuffer(size) { s -> + val base = (0 until data.size).sumOf { d -> distances[d] * derivs[d, s] / dispersion[d] } //Поправка на априорную вероятность prior?.let { prior -> - base - prior.derivative(symbols[k])(theta) / prior(theta) + base - prior.derivative(symbols[s])(theta) / prior(theta) } ?: base } } @@ -163,15 +166,15 @@ public class QowOptimizer : Optimizer { val logger = problem.getFeature() - var dis: Double//норма невязки - // Для удобства работаем всегда с полным набором параметров + var dis: Double //discrepancy value + // Working with the full set of parameters var par = problem.startPoint logger?.log { "Starting newtonian iteration from: \n\t$par" } - var eqvalues = getEqValues(par)//значения функций + var eqvalues = getEqValues(par) //Values of the weight functions - dis = DoubleL2Norm.norm(eqvalues)// невязка + dis = DoubleL2Norm.norm(eqvalues) // discrepancy logger?.log { "Starting discrepancy is $dis" } var i = 0 var flag = false @@ -238,7 +241,8 @@ public class QowOptimizer : Optimizer { return covar } - override suspend fun optimize(problem: XYOptimization): XYOptimization { + override suspend fun optimize(problem: XYFit): XYFit { + val qowSteps = 2 val initialWeight = QoWeight(problem, problem.startPoint) val res = initialWeight.newtonianRun() return res.problem.withFeature(OptimizationResult(res.parameters)) diff --git a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt new file mode 100644 index 000000000..cbd765923 --- /dev/null +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt @@ -0,0 +1,125 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ +@file:OptIn(UnstableKMathAPI::class) + +package space.kscience.kmath.optimization + +import space.kscience.kmath.data.XYColumnarData +import space.kscience.kmath.expressions.* +import space.kscience.kmath.misc.FeatureSet +import space.kscience.kmath.misc.Loggable +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.ExtendedField +import space.kscience.kmath.operations.bindSymbol +import kotlin.math.pow + +/** + * Specify the way to compute distance from point to the curve as DifferentiableExpression + */ +public interface PointToCurveDistance : OptimizationFeature { + public fun distance(problem: XYFit, index: Int): DifferentiableExpression + + public companion object { + public val byY: PointToCurveDistance = object : PointToCurveDistance { + override fun distance(problem: XYFit, index: Int): DifferentiableExpression { + val x = problem.data.x[index] + val y = problem.data.y[index] + + return object : DifferentiableExpression { + override fun derivativeOrNull( + symbols: List + ): Expression? = problem.model.derivativeOrNull(symbols)?.let { derivExpression -> + Expression { arguments -> + derivExpression.invoke(arguments + (Symbol.x to x)) + } + } + + override fun invoke(arguments: Map): Double = + problem.model(arguments + (Symbol.x to x)) - y + } + } + + override fun toString(): String = "PointToCurveDistanceByY" + } + } +} + +/** + * Compute a wight of the point. The more the weight, the more impact this point will have on the fit. + * By default, uses Dispersion^-1 + */ +public interface PointWeight : OptimizationFeature { + public fun weight(problem: XYFit, index: Int): DifferentiableExpression + + public companion object { + public fun bySigma(sigmaSymbol: Symbol): PointWeight = object : PointWeight { + override fun weight(problem: XYFit, index: Int): DifferentiableExpression = + object : DifferentiableExpression { + override fun invoke(arguments: Map): Double { + return problem.data[sigmaSymbol]?.get(index)?.pow(-2) ?: 1.0 + } + + override fun derivativeOrNull(symbols: List): Expression = Expression { 0.0 } + } + + override fun toString(): String = "PointWeightBySigma($sigmaSymbol)" + + } + + public val byYSigma: PointWeight = bySigma(Symbol.yError) + } +} + +/** + * A fit problem for X-Y-Yerr data. Also known as "least-squares" problem. + */ +public class XYFit( + public val data: XYColumnarData, + public val model: DifferentiableExpression, + override val features: FeatureSet, + internal val pointToCurveDistance: PointToCurveDistance = PointToCurveDistance.byY, + internal val pointWeight: PointWeight = PointWeight.byYSigma, +) : OptimizationProblem { + public fun distance(index: Int): DifferentiableExpression = pointToCurveDistance.distance(this, index) + + public fun weight(index: Int): DifferentiableExpression = pointWeight.weight(this, index) +} + +public fun XYFit.withFeature(vararg features: OptimizationFeature): XYFit { + return XYFit(data, model, this.features.with(*features), pointToCurveDistance, pointWeight) +} + +/** + * Fit given dta with + */ +public suspend fun XYColumnarData.fitWith( + optimizer: Optimizer, + processor: AutoDiffProcessor, + startingPoint: Map, + vararg features: OptimizationFeature = emptyArray(), + xSymbol: Symbol = Symbol.x, + pointToCurveDistance: PointToCurveDistance = PointToCurveDistance.byY, + pointWeight: PointWeight = PointWeight.byYSigma, + model: A.(I) -> I +): XYFit where A : ExtendedField, A : ExpressionAlgebra { + val modelExpression = processor.differentiate { + val x = bindSymbol(xSymbol) + model(x) + } + + var actualFeatures = FeatureSet.of(*features, OptimizationStartPoint(startingPoint)) + + if (actualFeatures.getFeature() == null) { + actualFeatures = actualFeatures.with(OptimizationLog(Loggable.console)) + } + val problem = XYFit( + this, + modelExpression, + actualFeatures, + pointToCurveDistance, + pointWeight + ) + return optimizer.optimize(problem) +} \ No newline at end of file diff --git a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/logLikelihood.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/logLikelihood.kt new file mode 100644 index 000000000..6701887a2 --- /dev/null +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/logLikelihood.kt @@ -0,0 +1,66 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.optimization + +import space.kscience.kmath.data.XYColumnarData +import space.kscience.kmath.data.indices +import space.kscience.kmath.expressions.DifferentiableExpression +import space.kscience.kmath.expressions.Expression +import space.kscience.kmath.expressions.Symbol +import space.kscience.kmath.expressions.derivative +import space.kscience.kmath.misc.UnstableKMathAPI +import kotlin.math.PI +import kotlin.math.ln +import kotlin.math.pow +import kotlin.math.sqrt + + +private val oneOver2Pi = 1.0 / sqrt(2 * PI) + +@UnstableKMathAPI +internal fun XYFit.logLikelihood(): DifferentiableExpression = object : DifferentiableExpression { + override fun derivativeOrNull(symbols: List): Expression = Expression { arguments -> + data.indices.sumOf { index -> + val d = distance(index)(arguments) + val weight = weight(index)(arguments) + val weightDerivative = weight(index)(arguments) + + // -1 / (sqrt(2 PI) * sigma) + 2 (x-mu)/ 2 sigma^2 * d mu/ d theta - (x-mu)^2 / 2 * d w/ d theta + return@sumOf -oneOver2Pi * sqrt(weight) + //offset derivative + d * model.derivative(symbols)(arguments) * weight - //model derivative + d.pow(2) * weightDerivative / 2 //weight derivative + } + } + + override fun invoke(arguments: Map): Double { + return data.indices.sumOf { index -> + val d = distance(index)(arguments) + val weight = weight(index)(arguments) + //1/sqrt(2 PI sigma^2) - (x-mu)^2/ (2 * sigma^2) + oneOver2Pi * ln(weight) - d.pow(2) * weight + } / 2 + } + +} + +/** + * Optimize given XY (least squares) [problem] using this function [Optimizer]. + * The problem is treated as maximum likelihood problem and is done via maximizing logarithmic likelihood, respecting + * possible weight dependency on the model and parameters. + */ +@UnstableKMathAPI +public suspend fun Optimizer>.maximumLogLikelihood(problem: XYFit): XYFit { + val functionOptimization = FunctionOptimization(problem.features, problem.logLikelihood()) + val result = optimize(functionOptimization.withFeatures(FunctionOptimizationTarget.MAXIMIZE)) + return XYFit(problem.data, problem.model, result.features) +} + +@UnstableKMathAPI +public suspend fun Optimizer>.maximumLogLikelihood( + data: XYColumnarData, + model: DifferentiableExpression, + builder: XYOptimizationBuilder.() -> Unit, +): XYFit = maximumLogLikelihood(XYOptimization(data, model, builder)) diff --git a/kmath-stat/build.gradle.kts b/kmath-stat/build.gradle.kts index e3e396b6f..41a1666f8 100644 --- a/kmath-stat/build.gradle.kts +++ b/kmath-stat/build.gradle.kts @@ -1,6 +1,5 @@ plugins { - kotlin("multiplatform") - id("ru.mipt.npm.gradle.common") + id("ru.mipt.npm.gradle.mpp") id("ru.mipt.npm.gradle.native") } diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt deleted file mode 100644 index 68c0c77eb..000000000 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYOptimization.kt +++ /dev/null @@ -1,189 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. - */ -@file:OptIn(UnstableKMathAPI::class) - -package space.kscience.kmath.optimization - -import space.kscience.kmath.data.XYColumnarData -import space.kscience.kmath.data.indices -import space.kscience.kmath.expressions.DifferentiableExpression -import space.kscience.kmath.expressions.Expression -import space.kscience.kmath.expressions.Symbol -import space.kscience.kmath.expressions.derivative -import space.kscience.kmath.misc.FeatureSet -import space.kscience.kmath.misc.UnstableKMathAPI -import kotlin.math.PI -import kotlin.math.ln -import kotlin.math.pow -import kotlin.math.sqrt - -/** - * Specify the way to compute distance from point to the curve as DifferentiableExpression - */ -public interface PointToCurveDistance : OptimizationFeature { - public fun distance(problem: XYOptimization, index: Int): DifferentiableExpression - - public companion object { - public val byY: PointToCurveDistance = object : PointToCurveDistance { - override fun distance(problem: XYOptimization, index: Int): DifferentiableExpression { - - val x = problem.data.x[index] - val y = problem.data.y[index] - return object : DifferentiableExpression { - override fun derivativeOrNull(symbols: List): Expression? = - problem.model.derivativeOrNull(symbols) - - override fun invoke(arguments: Map): Double = - problem.model(arguments + (Symbol.x to x)) - y - } - } - - override fun toString(): String = "PointToCurveDistanceByY" - } - } -} - -/** - * Compute a wight of the point. The more the weight, the more impact this point will have on the fit. - * By default uses Dispersion^-1 - */ -public interface PointWeight : OptimizationFeature { - public fun weight(problem: XYOptimization, index: Int): DifferentiableExpression - - public companion object { - public fun bySigma(sigmaSymbol: Symbol): PointWeight = object : PointWeight { - override fun weight(problem: XYOptimization, index: Int): DifferentiableExpression = - object : DifferentiableExpression { - override fun invoke(arguments: Map): Double { - return problem.data[sigmaSymbol]?.get(index)?.pow(-2) ?: 1.0 - } - - override fun derivativeOrNull(symbols: List): Expression = Expression { 0.0 } - } - - override fun toString(): String = "PointWeightBySigma($sigmaSymbol)" - - } - - public val byYSigma: PointWeight = bySigma(Symbol.yError) - } -} - -/** - * An optimization for XY data. - */ -public class XYOptimization( - override val features: FeatureSet, - public val data: XYColumnarData, - public val model: DifferentiableExpression, - internal val pointToCurveDistance: PointToCurveDistance = PointToCurveDistance.byY, - internal val pointWeight: PointWeight = PointWeight.byYSigma, -) : OptimizationProblem { - public fun distance(index: Int): DifferentiableExpression = pointToCurveDistance.distance(this, index) - - public fun weight(index: Int): DifferentiableExpression = pointWeight.weight(this, index) -} - -public fun XYOptimization.withFeature(vararg features: OptimizationFeature): XYOptimization { - return XYOptimization(this.features.with(*features), data, model, pointToCurveDistance, pointWeight) -} - -private val oneOver2Pi = 1.0 / sqrt(2 * PI) - -internal fun XYOptimization.likelihood(): DifferentiableExpression = object : DifferentiableExpression { - override fun derivativeOrNull(symbols: List): Expression = Expression { arguments -> - data.indices.sumOf { index -> - - val d = distance(index)(arguments) - val weight = weight(index)(arguments) - val weightDerivative = weight(index)(arguments) - - // -1 / (sqrt(2 PI) * sigma) + 2 (x-mu)/ 2 sigma^2 * d mu/ d theta - (x-mu)^2 / 2 * d w/ d theta - return@sumOf -oneOver2Pi * sqrt(weight) + //offset derivative - d * model.derivative(symbols)(arguments) * weight - //model derivative - d.pow(2) * weightDerivative / 2 //weight derivative - } - } - - override fun invoke(arguments: Map): Double { - return data.indices.sumOf { index -> - val d = distance(index)(arguments) - val weight = weight(index)(arguments) - //1/sqrt(2 PI sigma^2) - (x-mu)^2/ (2 * sigma^2) - oneOver2Pi * ln(weight) - d.pow(2) * weight - } / 2 - } - -} - -/** - * Optimize given XY (least squares) [problem] using this function [Optimizer]. - * The problem is treated as maximum likelihood problem and is done via maximizing logarithmic likelihood, respecting - * possible weight dependency on the model and parameters. - */ -public suspend fun Optimizer>.maximumLogLikelihood(problem: XYOptimization): XYOptimization { - val functionOptimization = FunctionOptimization(problem.features, problem.likelihood()) - val result = optimize(functionOptimization.withFeatures(FunctionOptimizationTarget.MAXIMIZE)) - return XYOptimization(result.features, problem.data, problem.model) -} - -public suspend fun Optimizer>.maximumLogLikelihood( - data: XYColumnarData, - model: DifferentiableExpression, - builder: XYOptimizationBuilder.() -> Unit, -): XYOptimization = maximumLogLikelihood(XYOptimization(data, model, builder)) - -//public suspend fun XYColumnarData.fitWith( -// optimizer: XYOptimization, -// problemBuilder: XYOptimizationBuilder.() -> Unit = {}, -// -//) - - -// -//@UnstableKMathAPI -//public interface XYFit : OptimizationProblem { -// -// public val algebra: Field -// -// /** -// * Set X-Y data for this fit optionally including x and y errors -// */ -// public fun data( -// dataSet: ColumnarData, -// xSymbol: Symbol, -// ySymbol: Symbol, -// xErrSymbol: Symbol? = null, -// yErrSymbol: Symbol? = null, -// ) -// -// public fun model(model: (T) -> DifferentiableExpression) -// -// /** -// * Set the differentiable model for this fit -// */ -// public fun model( -// autoDiff: AutoDiffProcessor>, -// modelFunction: A.(I) -> I, -// ): Unit where A : ExtendedField, A : ExpressionAlgebra = model { arg -> -// autoDiff.process { modelFunction(const(arg)) } -// } -//} - -// -///** -// * Define a chi-squared-based objective function -// */ -//public fun FunctionOptimization.chiSquared( -// autoDiff: AutoDiffProcessor>, -// x: Buffer, -// y: Buffer, -// yErr: Buffer, -// model: A.(I) -> I, -//) where A : ExtendedField, A : ExpressionAlgebra { -// val chiSquared = FunctionOptimization.chiSquared(autoDiff, x, y, yErr, model) -// function(chiSquared) -// maximize = false -//} \ No newline at end of file diff --git a/settings.gradle.kts b/settings.gradle.kts index f05092bb1..d1cbbe74c 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -26,6 +26,7 @@ include( ":kmath-histograms", ":kmath-commons", ":kmath-viktor", + ":kmath-optimization", ":kmath-stat", ":kmath-nd4j", ":kmath-dimensions", From 8d33d6beabf859a75317d087dd4adf70051b6c1a Mon Sep 17 00:00:00 2001 From: darksnake Date: Mon, 16 Aug 2021 16:40:56 +0300 Subject: [PATCH 105/132] Fixed QOW optimization --- .../kotlin/space/kscience/kmath/fit/qowFit.kt | 11 +++++---- .../kmath/optimization/QowOptimizer.kt | 2 +- .../kscience/kmath/optimization/XYFit.kt | 23 ++++++++++++++++++- .../kmath/optimization/logLikelihood.kt | 2 +- 4 files changed, 30 insertions(+), 8 deletions(-) diff --git a/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt b/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt index 944f80697..04764d763 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt @@ -14,6 +14,7 @@ import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.expressions.binding import space.kscience.kmath.expressions.symbol import space.kscience.kmath.optimization.QowOptimizer +import space.kscience.kmath.optimization.chiSquaredOrNull import space.kscience.kmath.optimization.fitWith import space.kscience.kmath.optimization.resultPoint import space.kscience.kmath.real.map @@ -50,7 +51,7 @@ suspend fun main() { //Perform an operation on each x value (much more effective, than numpy) val y = x.map { it -> - val value = it.pow(2) + it + 100 + val value = it.pow(2) + it + 1 value + chain.next() * sqrt(value) } // this will also work, but less effective: @@ -63,7 +64,7 @@ suspend fun main() { val result = XYErrorColumnarData.of(x, y, yErr).fitWith( QowOptimizer, DSProcessor, - mapOf(a to 1.0, b to 1.2, c to 99.0) + mapOf(a to 0.9, b to 1.2, c to 2.0) ) { arg -> //bind variables to autodiff context val a by binding @@ -96,9 +97,9 @@ suspend fun main() { h3 { +"Fit result: ${result.resultPoint}" } -// h3 { -// +"Chi2/dof = ${result.resultValue / (x.size - 3)}" -// } + h3 { + +"Chi2/dof = ${result.chiSquaredOrNull!! / (x.size - 3)}" + } } page.makeFile() diff --git a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt index f0969d2f6..4fe8520da 100644 --- a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt @@ -50,7 +50,7 @@ public object QowOptimizer : Optimizer { */ val dispersion: Point by lazy { DoubleBuffer(problem.data.size) { d -> - problem.weight(d).invoke(parameters) + 1.0/problem.weight(d).invoke(parameters) } } diff --git a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt index cbd765923..07fea3126 100644 --- a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt @@ -7,6 +7,7 @@ package space.kscience.kmath.optimization import space.kscience.kmath.data.XYColumnarData +import space.kscience.kmath.data.indices import space.kscience.kmath.expressions.* import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.Loggable @@ -81,6 +82,7 @@ public class XYFit( override val features: FeatureSet, internal val pointToCurveDistance: PointToCurveDistance = PointToCurveDistance.byY, internal val pointWeight: PointWeight = PointWeight.byYSigma, + public val xSymbol: Symbol = Symbol.x, ) : OptimizationProblem { public fun distance(index: Int): DifferentiableExpression = pointToCurveDistance.distance(this, index) @@ -119,7 +121,26 @@ public suspend fun XYColumnarData.fitWith( modelExpression, actualFeatures, pointToCurveDistance, - pointWeight + pointWeight, + xSymbol ) return optimizer.optimize(problem) +} + +/** + * Compute chi squared value for completed fit. Return null for incomplete fit + */ +public val XYFit.chiSquaredOrNull: Double? get() { + val result = resultPointOrNull ?: return null + + return data.indices.sumOf { index-> + + val x = data.x[index] + val y = data.y[index] + val yErr = data[Symbol.yError]?.get(index) ?: 1.0 + + val mu = model.invoke(result + (xSymbol to x) ) + + ((y - mu)/yErr).pow(2) + } } \ No newline at end of file diff --git a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/logLikelihood.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/logLikelihood.kt index 6701887a2..b4cb2f1cf 100644 --- a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/logLikelihood.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/logLikelihood.kt @@ -26,7 +26,7 @@ internal fun XYFit.logLikelihood(): DifferentiableExpression = object : data.indices.sumOf { index -> val d = distance(index)(arguments) val weight = weight(index)(arguments) - val weightDerivative = weight(index)(arguments) + val weightDerivative = weight(index).derivative(symbols)(arguments) // -1 / (sqrt(2 PI) * sigma) + 2 (x-mu)/ 2 sigma^2 * d mu/ d theta - (x-mu)^2 / 2 * d w/ d theta return@sumOf -oneOver2Pi * sqrt(weight) + //offset derivative From 9023098090d16ea8131d1f1bd179169a2b72d2b3 Mon Sep 17 00:00:00 2001 From: Veniamin Viflyantsev Date: Tue, 17 Aug 2021 13:59:59 +0300 Subject: [PATCH 106/132] implementation of geometry projections of vectors to a line/plane --- .../kmath/geometry/Euclidean2DSpace.kt | 8 +- .../kmath/geometry/Euclidean3DSpace.kt | 8 +- .../kscience/kmath/geometry/Projections.kt | 20 +++++ .../kmath/geometry/Euclidean2DSpaceTest.kt | 62 ++++++++++++++ .../kmath/geometry/Euclidean3DSpaceTest.kt | 74 +++++++++++++++++ .../kmath/geometry/ProjectionAlongTest.kt | 60 ++++++++++++++ .../kmath/geometry/ProjectionOntoLineTest.kt | 82 +++++++++++++++++++ .../kscience/kmath/geometry/Vector2DTest.kt | 36 ++++++++ .../kscience/kmath/geometry/Vector3DTest.kt | 41 ++++++++++ .../kscience/kmath/geometry/testUtils.kt | 41 ++++++++++ 10 files changed, 424 insertions(+), 8 deletions(-) create mode 100644 kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Projections.kt create mode 100644 kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean2DSpaceTest.kt create mode 100644 kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean3DSpaceTest.kt create mode 100644 kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt create mode 100644 kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt create mode 100644 kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt create mode 100644 kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt create mode 100644 kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/testUtils.kt diff --git a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt index 252e2fcd5..e8b1ce95b 100644 --- a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt +++ b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean2DSpace.kt @@ -12,14 +12,14 @@ import space.kscience.kmath.operations.invoke import kotlin.math.sqrt @OptIn(UnstableKMathAPI::class) -public interface Vector2D : Point, Vector{ +public interface Vector2D : Point, Vector { public val x: Double public val y: Double override val size: Int get() = 2 override operator fun get(index: Int): Double = when (index) { - 1 -> x - 2 -> y + 0 -> x + 1 -> y else -> error("Accessing outside of point bounds") } @@ -27,7 +27,7 @@ public interface Vector2D : Point, Vector{ } public val Vector2D.r: Double - get() = Euclidean2DSpace { sqrt(norm()) } + get() = Euclidean2DSpace { norm() } @Suppress("FunctionName") public fun Vector2D(x: Double, y: Double): Vector2D = Vector2DImpl(x, y) diff --git a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt index b0b2d2079..d567bee9a 100644 --- a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt +++ b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Euclidean3DSpace.kt @@ -19,9 +19,9 @@ public interface Vector3D : Point, Vector { override val size: Int get() = 3 override operator fun get(index: Int): Double = when (index) { - 1 -> x - 2 -> y - 3 -> z + 0 -> x + 1 -> y + 2 -> z else -> error("Accessing outside of point bounds") } @@ -31,7 +31,7 @@ public interface Vector3D : Point, Vector { @Suppress("FunctionName") public fun Vector3D(x: Double, y: Double, z: Double): Vector3D = Vector3DImpl(x, y, z) -public val Vector3D.r: Double get() = Euclidean3DSpace { sqrt(norm()) } +public val Vector3D.r: Double get() = Euclidean3DSpace { norm() } private data class Vector3DImpl( override val x: Double, diff --git a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Projections.kt b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Projections.kt new file mode 100644 index 000000000..d13ef03a1 --- /dev/null +++ b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Projections.kt @@ -0,0 +1,20 @@ +package space.kscience.kmath.geometry + +/** + * Project vector to a line + * @param vector to project + * @param line line to which vector should be projected + */ +public fun GeometrySpace.projectToLine(vector: V, line: Line): V = with(line) { + base + (direction dot (vector - base)) / (direction dot direction) * direction +} + +/** + * Project vector to a hyper-plane, which is defined by a normal and base + * In 2d case it is projection to a line, in 3d case it is projection to a plane + * @param vector to project + * @param normal normal (perpendicular) vector to a hyper-plane to which vector should be projected + * @param base point belonging to a hyper-plane to which vector should be projected + */ +public fun GeometrySpace.projectAlong(vector: V, normal: V, base: V): V = + vector + normal * ((base - vector) dot normal) / (normal dot normal) diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean2DSpaceTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean2DSpaceTest.kt new file mode 100644 index 000000000..6d5ae9948 --- /dev/null +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean2DSpaceTest.kt @@ -0,0 +1,62 @@ +package space.kscience.kmath.geometry + +import kotlin.math.sqrt +import kotlin.test.Test +import kotlin.test.assertEquals + +internal class Euclidean2DSpaceTest { + @Test + fun getZero() { + assertVectorEquals(Vector2D(0.0, 0.0), Euclidean2DSpace.zero) + } + + @Test + fun norm() { + with(Euclidean2DSpace) { + assertEquals(0.0, zero.norm()) + assertEquals(1.0, Vector2D(1.0, 0.0).norm()) + assertEquals(sqrt(2.0), Vector2D(1.0, 1.0).norm()) + assertEquals(sqrt(5.002001), Vector2D(-2.0, 1.001).norm()) + } + } + + @Test + fun dotProduct() { + with(Euclidean2DSpace) { + assertEquals(0.0, zero dot zero) + assertEquals(0.0, zero dot Vector2D(1.0, 0.0)) + assertEquals(0.0, Vector2D(-2.0, 0.001) dot zero) + assertEquals(0.0, Vector2D(1.0, 0.0) dot Vector2D(0.0, 1.0)) + + assertEquals(1.0, Vector2D(1.0, 0.0) dot Vector2D(1.0, 0.0)) + assertEquals(-2.0, Vector2D(0.0, 1.0) dot Vector2D(1.0, -2.0)) + assertEquals(2.0, Vector2D(1.0, 1.0) dot Vector2D(1.0, 1.0)) + assertEquals(4.001001, Vector2D(-2.0, 1.001) dot Vector2D(-2.0, 0.001)) + + assertEquals(-4.998, Vector2D(1.0, 2.0) dot Vector2D(-5.0, 0.001)) + } + } + + @Test + fun add() { + with(Euclidean2DSpace) { + assertVectorEquals( + Vector2D(-2.0, 0.001), + Vector2D(-2.0, 0.001) + zero + ) + assertVectorEquals( + Vector2D(-3.0, 3.001), + Vector2D(2.0, 3.0) + Vector2D(-5.0, 0.001) + ) + } + } + + @Test + fun multiply() { + with(Euclidean2DSpace) { + assertVectorEquals(Vector2D(-4.0, 0.0), Vector2D(-2.0, 0.0) * 2) + assertVectorEquals(Vector2D(4.0, 0.0), Vector2D(-2.0, 0.0) * -2) + assertVectorEquals(Vector2D(300.0, 0.0003), Vector2D(100.0, 0.0001) * 3) + } + } +} \ No newline at end of file diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean3DSpaceTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean3DSpaceTest.kt new file mode 100644 index 000000000..9cce44c65 --- /dev/null +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean3DSpaceTest.kt @@ -0,0 +1,74 @@ +package space.kscience.kmath.geometry + +import kotlin.test.Test +import kotlin.test.assertEquals + +internal class Euclidean3DSpaceTest { + @Test + fun getZero() { + assertVectorEquals(Vector3D(0.0, 0.0, 0.0), Euclidean3DSpace.zero) + } + + @Test + fun distance() { + with(Euclidean3DSpace) { + assertEquals(0.0, zero.distanceTo(zero)) + assertEquals(1.0, zero.distanceTo(Vector3D(1.0, 0.0, 0.0))) + assertEquals(kotlin.math.sqrt(5.000001), Vector3D(1.0, -2.0, 0.001).distanceTo(zero)) + assertEquals(0.0, Vector3D(1.0, -2.0, 0.001).distanceTo(Vector3D(1.0, -2.0, 0.001))) + assertEquals(0.0, Vector3D(1.0, 0.0, 0.0).distanceTo(Vector3D(1.0, 0.0, 0.0))) + assertEquals(kotlin.math.sqrt(2.0), Vector3D(1.0, 0.0, 0.0).distanceTo(Vector3D(1.0, 1.0, 1.0))) + assertEquals(3.1622778182822584, Vector3D(0.0, 1.0, 0.0).distanceTo(Vector3D(1.0, -2.0, 0.001))) + assertEquals(0.0, Vector3D(1.0, -2.0, 0.001).distanceTo(Vector3D(1.0, -2.0, 0.001))) + assertEquals(9.695050335093676, Vector3D(1.0, 2.0, 3.0).distanceTo(Vector3D(7.0, -5.0, 0.001))) + } + } + + @Test + fun norm() { + with(Euclidean3DSpace) { + assertEquals(0.0, zero.norm()) + assertEquals(1.0, Vector3D(1.0, 0.0, 0.0).norm()) + assertEquals(kotlin.math.sqrt(3.0), Vector3D(1.0, 1.0, 1.0).norm()) + assertEquals(kotlin.math.sqrt(5.000001), Vector3D(1.0, -2.0, 0.001).norm()) + } + } + + @Test + fun dotProduct() { + with(Euclidean3DSpace) { + assertEquals(0.0, zero dot zero) + assertEquals(0.0, zero dot Vector3D(1.0, 0.0, 0.0)) + assertEquals(0.0, Vector3D(1.0, -2.0, 0.001) dot zero) + + assertEquals(1.0, Vector3D(1.0, 0.0, 0.0) dot Vector3D(1.0, 0.0, 0.0)) + assertEquals(1.0, Vector3D(1.0, 0.0, 0.0) dot Vector3D(1.0, 1.0, 1.0)) + assertEquals(-2.0, Vector3D(0.0, 1.0, 0.0) dot Vector3D(1.0, -2.0, 0.001)) + assertEquals(3.0, Vector3D(1.0, 1.0, 1.0) dot Vector3D(1.0, 1.0, 1.0)) + assertEquals(5.000001, Vector3D(1.0, -2.0, 0.001) dot Vector3D(1.0, -2.0, 0.001)) + + assertEquals(-2.997, Vector3D(1.0, 2.0, 3.0) dot Vector3D(7.0, -5.0, 0.001)) + } + } + + @Test + fun add() { + with(Euclidean3DSpace) { + assertVectorEquals( + Vector3D(1.0, -2.0, 0.001), + Vector3D(1.0, -2.0, 0.001) + zero + ) + assertVectorEquals( + Vector3D(8.0, -3.0, 3.001), + Vector3D(1.0, 2.0, 3.0) + Vector3D(7.0, -5.0, 0.001) + ) + } + } + + @Test + fun multiply() { + with(Euclidean3DSpace) { + assertVectorEquals(Vector3D(2.0, -4.0, 0.0), Vector3D(1.0, -2.0, 0.0) * 2) + } + } +} \ No newline at end of file diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt new file mode 100644 index 000000000..cc940035f --- /dev/null +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt @@ -0,0 +1,60 @@ +package space.kscience.kmath.geometry + +import kotlin.test.Test +import kotlin.test.assertTrue + +internal class ProjectionAlongTest { + @Test + fun projectionIntoYEqualsX() { + with(Euclidean2DSpace) { + val normal = Vector2D(-2.0, 2.0) + val base = Vector2D(2.3, 2.3) + + assertVectorEquals(zero, projectAlong(zero, normal, base)) + + grid(-10.0..10.0, -10.0..10.0, 0.15).forEach { (x, y) -> + val d = (y - x) / 2.0 + assertVectorEquals(Vector2D(x + d, y - d), projectAlong(Vector2D(x, y), normal, base)) + } + } + } + + @Test + fun projectionOntoLine() { + with(Euclidean2DSpace) { + val a = 5.0 + val b = -3.0 + val c = -15.0 + val normal = Vector2D(-5.0, 3.0) + val base = Vector2D(3.0, 0.0) + + grid(-10.0..10.0, -10.0..10.0, 0.15).forEach { (x, y) -> + val xProj = (b * (b * x - a * y) - a * c) / (a * a + b * b) + val yProj = (a * (-b * x + a * y) - b * c) / (a * a + b * b) + assertVectorEquals(Vector2D(xProj, yProj), projectAlong(Vector2D(x, y), normal, base)) + } + } + } + + @Test + fun projectOntoPlane() { + val normal = Vector3D(1.0, 3.5, 0.07) + val base = Vector3D(2.0, -0.0037, 11.1111) + + with(Euclidean3DSpace) { + for (x in (-10.0..10.0).generateList(0.15)) { + for (y in (-10.0..10.0).generateList(0.15)) { + for (z in (-10.0..10.0).generateList(0.15)) { + val v = Vector3D(x, y, z) + val result = projectAlong(v, normal, base) + + // assert that result is on plane + assertTrue(isOrthogonal(result - base, normal)) + // assert that PV vector is collinear to normal vector + assertTrue(isCollinear(v - result, normal)) + } + } + } + } + } +} \ No newline at end of file diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt new file mode 100644 index 000000000..1190b156d --- /dev/null +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt @@ -0,0 +1,82 @@ +package space.kscience.kmath.geometry + +import kotlin.test.Test +import kotlin.test.assertTrue + +internal class ProjectionOntoLineTest { + @Test + fun projectionIntoOx() { + with(Euclidean2DSpace) { + val ox = Line(zero, Vector2D(1.0, 0.0)) + + grid(-10.0..10.0, -10.0..10.0, 0.15).forEach { (x, y) -> + assertVectorEquals(Vector2D(x, 0.0), projectToLine(Vector2D(x, y), ox)) + } + } + } + + @Test + fun projectionIntoOy() { + with(Euclidean2DSpace) { + val line = Line(zero, Vector2D(0.0, 1.0)) + + grid(-10.0..10.0, -10.0..10.0, 0.15).forEach { (x, y) -> + assertVectorEquals(Vector2D(0.0, y), projectToLine(Vector2D(x, y), line)) + } + } + } + + @Test + fun projectionIntoYEqualsX() { + with(Euclidean2DSpace) { + val line = Line(zero, Vector2D(1.0, 1.0)) + + assertVectorEquals(zero, projectToLine(zero, line)) + + grid(-10.0..10.0, -10.0..10.0, 0.15).forEach { (x, y) -> + val d = (y - x) / 2.0 + assertVectorEquals(Vector2D(x + d, y - d), projectToLine(Vector2D(x, y), line)) + } + } + } + + @Test + fun projectionOntoLine2d() { + with(Euclidean2DSpace) { + val a = 5.0 + val b = -3.0 + val c = -15.0 + val line = Line(Vector2D(3.0, 0.0), Vector2D(3.0, 5.0)) + + grid(-10.0..10.0, -10.0..10.0, 0.15).forEach { (x, y) -> + val xProj = (b * (b * x - a * y) - a * c) / (a * a + b * b) + val yProj = (a * (-b * x + a * y) - b * c) / (a * a + b * b) + assertVectorEquals(Vector2D(xProj, yProj), projectToLine(Vector2D(x, y), line)) + } + } + } + + @Test + fun projectionOntoLine3d() { + val line = Line3D( + base = Vector3D(1.0, 3.5, 0.07), + direction = Vector3D(2.0, -0.0037, 11.1111) + ) + + with(Euclidean3DSpace) { + for (x in (-10.0..10.0).generateList(0.15)) { + for (y in (-10.0..10.0).generateList(0.15)) { + for (z in (-10.0..10.0).generateList(0.15)) { + val v = Vector3D(x, y, z) + val result = projectToLine(v, line) + + // assert that result is on line + assertTrue(isCollinear(result - line.base, line.direction)) + // assert that PV vector is orthogonal to direction vector + assertTrue(isOrthogonal(v - result, line.direction)) + } + } + } + } + } +} \ No newline at end of file diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt new file mode 100644 index 000000000..647004f43 --- /dev/null +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt @@ -0,0 +1,36 @@ +package space.kscience.kmath.geometry + +import space.kscience.kmath.structures.asSequence +import space.kscience.kmath.structures.toList +import kotlin.test.assertEquals +import kotlin.test.Test + +internal class Vector2DTest { + private val vector = Vector2D(1.0, -7.999) + + @Test + fun getSize() { + assertEquals(2, vector.size) + } + + @Test + fun get() { + assertEquals(1.0, vector[0]) + assertEquals(-7.999, vector[1]) + } + + @Test + operator fun iterator() { + assertEquals(listOf(1.0, -7.999), vector.toList()) + } + + @Test + fun getX() { + assertEquals(1.0, vector.x) + } + + @Test + fun getY() { + assertEquals(-7.999, vector.y) + } +} \ No newline at end of file diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt new file mode 100644 index 000000000..83271160f --- /dev/null +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt @@ -0,0 +1,41 @@ +package space.kscience.kmath.geometry + +import space.kscience.kmath.structures.toList +import kotlin.test.Test +import kotlin.test.assertEquals + +internal class Vector3DTest { + private val vector = Vector3D(1.0, -7.999, 0.001) + + @Test + fun getSize() { + assertEquals(3, vector.size) + } + + @Test + fun get() { + assertEquals(1.0, vector[0]) + assertEquals(-7.999, vector[1]) + assertEquals(0.001, vector[2]) + } + + @Test + operator fun iterator() { + assertEquals(listOf(1.0, -7.999, 0.001), vector.toList()) + } + + @Test + fun getX() { + assertEquals(1.0, vector.x) + } + + @Test + fun getY() { + assertEquals(-7.999, vector.y) + } + + @Test + fun getZ() { + assertEquals(0.001, vector.z) + } +} \ No newline at end of file diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/testUtils.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/testUtils.kt new file mode 100644 index 000000000..773d6d90c --- /dev/null +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/testUtils.kt @@ -0,0 +1,41 @@ +package space.kscience.kmath.geometry + +import kotlin.math.abs +import kotlin.test.assertEquals + +fun ClosedRange.generateList(step: Double): List = generateSequence(start) { previous -> + if (previous == Double.POSITIVE_INFINITY) return@generateSequence null + val next = previous + step + if (next > endInclusive) null else next +}.toList() + +fun grid( + xRange: ClosedRange, + yRange: ClosedRange, + step: Double +): List> { + val xs = xRange.generateList(step) + val ys = yRange.generateList(step) + + return xs.flatMap { x -> ys.map { y -> x to y } } +} + +fun assertVectorEquals(expected: Vector2D, actual: Vector2D, eps: Double = 1e-6) { + assertEquals(expected.x, actual.x, eps) + assertEquals(expected.y, actual.y, eps) +} + +fun assertVectorEquals(expected: Vector3D, actual: Vector3D, eps: Double = 1e-6) { + assertEquals(expected.x, actual.x, eps) + assertEquals(expected.y, actual.y, eps) + assertEquals(expected.z, actual.z, eps) +} + +fun GeometrySpace.isCollinear(a: V, b: V, eps: Double = 1e-6): Boolean { + val aDist = a.distanceTo(zero) + val bDist = b.distanceTo(zero) + return abs(aDist) < eps || abs(bDist) < eps || abs(abs((a dot b) / (aDist * bDist)) - 1) < eps +} + +fun GeometrySpace.isOrthogonal(a: V, b: V, eps: Double = 1e-6): Boolean = + abs(a dot b) < eps From b74bc320159c8cc1124058773d07b73a0b015cb7 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Mon, 16 Aug 2021 13:24:45 +0300 Subject: [PATCH 107/132] Ignore TestExecutionTime suite to reduce build time --- .../space/kscience/kmath/ast/TestExecutionTime.kt | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt index 2433f6316..f8c429d5a 100644 --- a/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt +++ b/kmath-ast/src/jsTest/kotlin/space/kscience/kmath/ast/TestExecutionTime.kt @@ -11,19 +11,21 @@ import space.kscience.kmath.operations.bindSymbol import space.kscience.kmath.operations.invoke import kotlin.math.sin import kotlin.random.Random +import kotlin.test.Ignore import kotlin.test.Test import kotlin.time.measureTime import space.kscience.kmath.estree.compileToExpression as estreeCompileToExpression import space.kscience.kmath.wasm.compileToExpression as wasmCompileToExpression // TODO move to benchmarks when https://github.com/Kotlin/kotlinx-benchmark/pull/38 or similar feature is merged +@Ignore internal class TestExecutionTime { private companion object { private const val times = 1_000_000 private val x by symbol private val algebra = DoubleField - private val functional = DoubleField.expressionInExtendedField { + private val functional = algebra.expressionInExtendedField { bindSymbol(x) * const(2.0) + const(2.0) / bindSymbol(x) - const(16.0) / sin(bindSymbol(x)) } @@ -31,9 +33,9 @@ internal class TestExecutionTime { x * number(2.0) + number(2.0) / x - number(16.0) / sin(x) } - private val mst = node.toExpression(DoubleField) - private val wasm = node.wasmCompileToExpression(DoubleField) - private val estree = node.estreeCompileToExpression(DoubleField) + private val mst = node.toExpression(algebra) + private val wasm = node.wasmCompileToExpression(algebra) + private val estree = node.estreeCompileToExpression(algebra) // In JavaScript, the expression below is implemented like // _no_name_provided__125.prototype.invoke_178 = function (args) { @@ -44,7 +46,7 @@ internal class TestExecutionTime { private val raw = Expression { args -> val x = args[x]!! - x * 2.0 + 2.0 / x - 16.0 / sin(x) + algebra { x * 2.0 + 2.0 / x - 16.0 / sin(x) } } private val justCalculate = { args: dynamic -> From ca6955beb557f662da2f77578dc6c95cdddfd015 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Tue, 17 Aug 2021 21:38:54 +0700 Subject: [PATCH 108/132] Fix copyright in ejmlCodegen.kt --- .../kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt index 1d2aaeaaf..68bb10428 100644 --- a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt @@ -362,7 +362,7 @@ fun ejmlCodegen(outputFile: String): Unit = File(outputFile).run { writer().use { it.appendLine("/*") it.appendLine(" * Copyright 2018-2021 KMath contributors.") - it.appendLine(" * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.") + it.appendLine(" * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file.") it.appendLine(" */") it.appendLine() it.appendLine("/* This file is generated with buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt */") From 603db46eb848e1ac3d1c7015bfe25f74fc78f3e2 Mon Sep 17 00:00:00 2001 From: Veniamin Viflyantsev Date: Tue, 17 Aug 2021 21:10:26 +0300 Subject: [PATCH 109/132] increased test timeouts in geometry project --- kmath-geometry/build.gradle.kts | 14 ++++++++++++++ .../kscience/kmath/geometry/ProjectionAlongTest.kt | 7 ++++--- .../kmath/geometry/ProjectionOntoLineTest.kt | 7 ++++--- 3 files changed, 22 insertions(+), 6 deletions(-) diff --git a/kmath-geometry/build.gradle.kts b/kmath-geometry/build.gradle.kts index 7eb814683..653d113a6 100644 --- a/kmath-geometry/build.gradle.kts +++ b/kmath-geometry/build.gradle.kts @@ -4,6 +4,20 @@ plugins { id("ru.mipt.npm.gradle.native") } +kotlin.js { + nodejs { + testTask { + useMocha().timeout = "5000" + } + } + + browser { + testTask { + useMocha().timeout = "5000" + } + } +} + kotlin.sourceSets.commonMain { dependencies { api(project(":kmath-core")) diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt index cc940035f..78ce98dc4 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt @@ -42,9 +42,10 @@ internal class ProjectionAlongTest { val base = Vector3D(2.0, -0.0037, 11.1111) with(Euclidean3DSpace) { - for (x in (-10.0..10.0).generateList(0.15)) { - for (y in (-10.0..10.0).generateList(0.15)) { - for (z in (-10.0..10.0).generateList(0.15)) { + val testDomain = (-10.0..10.0).generateList(0.15) + for (x in testDomain) { + for (y in testDomain) { + for (z in testDomain) { val v = Vector3D(x, y, z) val result = projectAlong(v, normal, base) diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt index 1190b156d..ec74ff59b 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt @@ -64,9 +64,10 @@ internal class ProjectionOntoLineTest { ) with(Euclidean3DSpace) { - for (x in (-10.0..10.0).generateList(0.15)) { - for (y in (-10.0..10.0).generateList(0.15)) { - for (z in (-10.0..10.0).generateList(0.15)) { + val testDomain = (-10.0..10.0).generateList(0.15) + for (x in testDomain) { + for (y in testDomain) { + for (z in testDomain) { val v = Vector3D(x, y, z) val result = projectToLine(v, line) From f271ded526ca5c3dcc07a0afed900a60ca181299 Mon Sep 17 00:00:00 2001 From: Ven Date: Tue, 17 Aug 2021 21:17:02 +0300 Subject: [PATCH 110/132] Apply suggestions from code review Co-authored-by: Iaroslav Postovalov <38042667+CommanderTvis@users.noreply.github.com> --- .../kscience/kmath/geometry/Projections.kt | 6 ++--- .../kmath/geometry/Euclidean2DSpaceTest.kt | 4 ++-- .../kmath/geometry/Euclidean3DSpaceTest.kt | 4 ++-- .../kmath/geometry/ProjectionAlongTest.kt | 2 +- .../kmath/geometry/ProjectionOntoLineTest.kt | 2 +- .../kscience/kmath/geometry/Vector2DTest.kt | 10 ++++----- .../kscience/kmath/geometry/Vector3DTest.kt | 12 +++++----- .../kscience/kmath/geometry/testUtils.kt | 22 +++++++++---------- 8 files changed, 31 insertions(+), 31 deletions(-) diff --git a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Projections.kt b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Projections.kt index d13ef03a1..205bc17e7 100644 --- a/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Projections.kt +++ b/kmath-geometry/src/commonMain/kotlin/space/kscience/kmath/geometry/Projections.kt @@ -1,7 +1,7 @@ package space.kscience.kmath.geometry /** - * Project vector to a line + * Project vector onto a line. * @param vector to project * @param line line to which vector should be projected */ @@ -10,8 +10,8 @@ public fun GeometrySpace.projectToLine(vector: V, line: Line) } /** - * Project vector to a hyper-plane, which is defined by a normal and base - * In 2d case it is projection to a line, in 3d case it is projection to a plane + * Project vector onto a hyperplane, which is defined by a normal and base. + * In 2D case it is the projection to a line, in 3d case it is the one to a plane. * @param vector to project * @param normal normal (perpendicular) vector to a hyper-plane to which vector should be projected * @param base point belonging to a hyper-plane to which vector should be projected diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean2DSpaceTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean2DSpaceTest.kt index 6d5ae9948..5913b2fa9 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean2DSpaceTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean2DSpaceTest.kt @@ -6,7 +6,7 @@ import kotlin.test.assertEquals internal class Euclidean2DSpaceTest { @Test - fun getZero() { + fun zero() { assertVectorEquals(Vector2D(0.0, 0.0), Euclidean2DSpace.zero) } @@ -59,4 +59,4 @@ internal class Euclidean2DSpaceTest { assertVectorEquals(Vector2D(300.0, 0.0003), Vector2D(100.0, 0.0001) * 3) } } -} \ No newline at end of file +} diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean3DSpaceTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean3DSpaceTest.kt index 9cce44c65..2c74cbd27 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean3DSpaceTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Euclidean3DSpaceTest.kt @@ -5,7 +5,7 @@ import kotlin.test.assertEquals internal class Euclidean3DSpaceTest { @Test - fun getZero() { + fun zero() { assertVectorEquals(Vector3D(0.0, 0.0, 0.0), Euclidean3DSpace.zero) } @@ -71,4 +71,4 @@ internal class Euclidean3DSpaceTest { assertVectorEquals(Vector3D(2.0, -4.0, 0.0), Vector3D(1.0, -2.0, 0.0) * 2) } } -} \ No newline at end of file +} diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt index 78ce98dc4..65291ee4e 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt @@ -58,4 +58,4 @@ internal class ProjectionAlongTest { } } } -} \ No newline at end of file +} diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt index ec74ff59b..0f74e1efb 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt @@ -80,4 +80,4 @@ internal class ProjectionOntoLineTest { } } } -} \ No newline at end of file +} diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt index 647004f43..84b1f4fd6 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt @@ -9,7 +9,7 @@ internal class Vector2DTest { private val vector = Vector2D(1.0, -7.999) @Test - fun getSize() { + fun size() { assertEquals(2, vector.size) } @@ -20,17 +20,17 @@ internal class Vector2DTest { } @Test - operator fun iterator() { + fun iterator() { assertEquals(listOf(1.0, -7.999), vector.toList()) } @Test - fun getX() { + fun x() { assertEquals(1.0, vector.x) } @Test - fun getY() { + fun y() { assertEquals(-7.999, vector.y) } -} \ No newline at end of file +} diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt index 83271160f..717e78871 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt @@ -8,7 +8,7 @@ internal class Vector3DTest { private val vector = Vector3D(1.0, -7.999, 0.001) @Test - fun getSize() { + fun size() { assertEquals(3, vector.size) } @@ -20,22 +20,22 @@ internal class Vector3DTest { } @Test - operator fun iterator() { + fun iterator() { assertEquals(listOf(1.0, -7.999, 0.001), vector.toList()) } @Test - fun getX() { + fun x() { assertEquals(1.0, vector.x) } @Test - fun getY() { + fun y() { assertEquals(-7.999, vector.y) } @Test - fun getZ() { + fun z() { assertEquals(0.001, vector.z) } -} \ No newline at end of file +} diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/testUtils.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/testUtils.kt index 773d6d90c..1277c0130 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/testUtils.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/testUtils.kt @@ -20,22 +20,22 @@ fun grid( return xs.flatMap { x -> ys.map { y -> x to y } } } -fun assertVectorEquals(expected: Vector2D, actual: Vector2D, eps: Double = 1e-6) { - assertEquals(expected.x, actual.x, eps) - assertEquals(expected.y, actual.y, eps) +fun assertVectorEquals(expected: Vector2D, actual: Vector2D, absoluteTolerance: Double = 1e-6) { + assertEquals(expected.x, actual.x, absoluteTolerance) + assertEquals(expected.y, actual.y, absoluteTolerance) } -fun assertVectorEquals(expected: Vector3D, actual: Vector3D, eps: Double = 1e-6) { - assertEquals(expected.x, actual.x, eps) - assertEquals(expected.y, actual.y, eps) - assertEquals(expected.z, actual.z, eps) +fun assertVectorEquals(expected: Vector3D, actual: Vector3D, absoluteTolerance: Double = 1e-6) { + assertEquals(expected.x, actual.x, absoluteTolerance) + assertEquals(expected.y, actual.y, absoluteTolerance) + assertEquals(expected.z, actual.z, absoluteTolerance) } -fun GeometrySpace.isCollinear(a: V, b: V, eps: Double = 1e-6): Boolean { +fun GeometrySpace.isCollinear(a: V, b: V, absoluteTolerance: Double = 1e-6): Boolean { val aDist = a.distanceTo(zero) val bDist = b.distanceTo(zero) - return abs(aDist) < eps || abs(bDist) < eps || abs(abs((a dot b) / (aDist * bDist)) - 1) < eps + return abs(aDist) < absoluteTolerance || abs(bDist) < absoluteTolerance || abs(abs((a dot b) / (aDist * bDist)) - 1) < absoluteTolerance } -fun GeometrySpace.isOrthogonal(a: V, b: V, eps: Double = 1e-6): Boolean = - abs(a dot b) < eps +fun GeometrySpace.isOrthogonal(a: V, b: V, absoluteTolerance: Double = 1e-6): Boolean = + abs(a dot b) < absoluteTolerance From 47ac2dd0a9959072c1e9cc19e78cc88d99f1c68f Mon Sep 17 00:00:00 2001 From: Veniamin Viflyantsev Date: Tue, 17 Aug 2021 23:47:52 +0300 Subject: [PATCH 111/132] returned back test timeouts, decrease number of cases that tests check to make it faster --- kmath-geometry/build.gradle.kts | 14 -------------- .../kscience/kmath/geometry/ProjectionAlongTest.kt | 2 +- .../kmath/geometry/ProjectionOntoLineTest.kt | 2 +- 3 files changed, 2 insertions(+), 16 deletions(-) diff --git a/kmath-geometry/build.gradle.kts b/kmath-geometry/build.gradle.kts index 653d113a6..7eb814683 100644 --- a/kmath-geometry/build.gradle.kts +++ b/kmath-geometry/build.gradle.kts @@ -4,20 +4,6 @@ plugins { id("ru.mipt.npm.gradle.native") } -kotlin.js { - nodejs { - testTask { - useMocha().timeout = "5000" - } - } - - browser { - testTask { - useMocha().timeout = "5000" - } - } -} - kotlin.sourceSets.commonMain { dependencies { api(project(":kmath-core")) diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt index 65291ee4e..55fc39aad 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionAlongTest.kt @@ -42,7 +42,7 @@ internal class ProjectionAlongTest { val base = Vector3D(2.0, -0.0037, 11.1111) with(Euclidean3DSpace) { - val testDomain = (-10.0..10.0).generateList(0.15) + val testDomain = (-10.0..10.0).generateList(0.43) for (x in testDomain) { for (y in testDomain) { for (z in testDomain) { diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt index 0f74e1efb..ab6ef3628 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/ProjectionOntoLineTest.kt @@ -64,7 +64,7 @@ internal class ProjectionOntoLineTest { ) with(Euclidean3DSpace) { - val testDomain = (-10.0..10.0).generateList(0.15) + val testDomain = (-10.0..10.0).generateList(0.43) for (x in testDomain) { for (y in testDomain) { for (z in testDomain) { From 3c6b068c395c64adead8f8248798dae5038e9a2f Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Wed, 18 Aug 2021 20:33:53 +0700 Subject: [PATCH 112/132] Avoid using kapt in kmath-jupyter --- .../src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt | 1 - 1 file changed, 1 deletion(-) diff --git a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt index 05e2dc0da..d7438bf0f 100644 --- a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt +++ b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt @@ -31,7 +31,6 @@ import space.kscience.kmath.structures.asSequence */ public fun Number.toMst(): MST.Numeric = MST.Numeric(this) -@JupyterLibrary internal class KMathJupyter : JupyterIntegration() { private val mathRender = FeaturedMathRendererWithPostProcess.Default private val syntaxRender = MathMLSyntaxRenderer From 0b90dd4df25a34f48b7446341d64ad85534b2281 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Thu, 19 Aug 2021 03:24:54 +0700 Subject: [PATCH 113/132] Fix #408 --- .../kmath/samplers/ZigguratNormalizedGaussianSampler.kt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ZigguratNormalizedGaussianSampler.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ZigguratNormalizedGaussianSampler.kt index 2d5750bc7..bda6f9819 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ZigguratNormalizedGaussianSampler.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/samplers/ZigguratNormalizedGaussianSampler.kt @@ -59,7 +59,7 @@ public object ZigguratNormalizedGaussianSampler : NormalizedGaussianSampler { private fun sampleOne(generator: RandomGenerator): Double { val j = generator.nextLong() - val i = (j and LAST.toLong()).toIntExact() + val i = (j and LAST.toLong()).toInt() return if (abs(j) < K[i]) j * W[i] else fix(generator, j, i) } From 7e0820d861763535e5c163215feb6d3f3bb86432 Mon Sep 17 00:00:00 2001 From: Iaroslav Postovalov Date: Sat, 21 Aug 2021 19:58:06 +0700 Subject: [PATCH 114/132] Add debug property for dumping classes generated with ASM --- .../kscience/kmath/asm/internal/AsmBuilder.kt | 17 +++++++++++------ 1 file changed, 11 insertions(+), 6 deletions(-) diff --git a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt index de7da30df..418d6141b 100644 --- a/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt +++ b/kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt @@ -14,9 +14,11 @@ import space.kscience.kmath.expressions.Expression import space.kscience.kmath.expressions.MST import java.lang.invoke.MethodHandles import java.lang.invoke.MethodType +import java.nio.file.Paths import java.util.stream.Collectors.toMap import kotlin.contracts.InvocationKind import kotlin.contracts.contract +import kotlin.io.path.writeBytes /** * ASM Builder is a structure that abstracts building a class designated to unwrap [MST] to plain Java expression. @@ -194,15 +196,18 @@ internal class AsmBuilder( visitEnd() } - val cls = classLoader.defineClass(className, classWriter.toByteArray()) - // java.io.File("dump.class").writeBytes(classWriter.toByteArray()) + val binary = classWriter.toByteArray() + val cls = classLoader.defineClass(className, binary) + + if (System.getProperty("space.kscience.communicator.prettyapi.dump.generated.classes") == "1") + Paths.get("$className.class").writeBytes(binary) + val l = MethodHandles.publicLookup() - if (hasConstants) - l.findConstructor(cls, MethodType.methodType(Void.TYPE, Array::class.java)) - .invoke(constants.toTypedArray()) as Expression + (if (hasConstants) + l.findConstructor(cls, MethodType.methodType(Void.TYPE, Array::class.java))(constants.toTypedArray()) else - l.findConstructor(cls, MethodType.methodType(Void.TYPE)).invoke() as Expression + l.findConstructor(cls, MethodType.methodType(Void.TYPE))()) as Expression } /** From 8581b32448e92e94cac04866426377beddc2f2a3 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 27 Aug 2021 18:13:54 +0300 Subject: [PATCH 115/132] Apply suggestions from code review Co-authored-by: Iaroslav Postovalov <38042667+CommanderTvis@users.noreply.github.com> --- .gitignore | 2 -- .../src/main/kotlin/space/kscience/kmath/structures/buffers.kt | 2 +- kmath-optimization/build.gradle.kts | 2 +- .../space/kscience/kmath/optimization/OptimizationBuilder.kt | 2 +- 4 files changed, 3 insertions(+), 5 deletions(-) diff --git a/.gitignore b/.gitignore index c5903368f..d6c4af4e3 100644 --- a/.gitignore +++ b/.gitignore @@ -18,5 +18,3 @@ out/ # Generated by javac -h and runtime *.class *.log - -/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt index eabb16701..0f7fdc46a 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt @@ -19,4 +19,4 @@ fun main() { with(DoubleField.bufferAlgebra(5)) { println(number(2.0) + produce(1, 2, 3, 4, 5)) } -} \ No newline at end of file +} diff --git a/kmath-optimization/build.gradle.kts b/kmath-optimization/build.gradle.kts index ca013b2f4..68b82ad65 100644 --- a/kmath-optimization/build.gradle.kts +++ b/kmath-optimization/build.gradle.kts @@ -17,4 +17,4 @@ kotlin.sourceSets { readme { maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL -} \ No newline at end of file +} diff --git a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt index 10a25c029..416d0195d 100644 --- a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/OptimizationBuilder.kt @@ -11,7 +11,7 @@ import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.misc.FeatureSet public abstract class OptimizationBuilder> { - public val features: ArrayList = ArrayList() + public val features: MutableList = ArrayList() public fun addFeature(feature: OptimizationFeature) { features.add(feature) From 55ea3658b99a26200475fd705f208cd4acdc9f8b Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Fri, 27 Aug 2021 18:16:24 +0300 Subject: [PATCH 116/132] Update CHANGELOG.md Co-authored-by: Iaroslav Postovalov <38042667+CommanderTvis@users.noreply.github.com> --- CHANGELOG.md | 1 - 1 file changed, 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index eadf5877d..ec3f5252a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -13,7 +13,6 @@ - Extended operations for ND4J fields - Jupyter Notebook integration module (kmath-jupyter) - `@PerformancePitfall` annotation to mark possibly slow API -- BigInt operation performance improvement and fixes by @zhelenskiy (#328) - Unified architecture for Integration and Optimization using features. - `BigInt` operation performance improvement and fixes by @zhelenskiy (#328) - Integration between `MST` and Symja `IExpr` From 49ec5d15549daaf3848a09f9f3c6f441803587d6 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 19 Sep 2021 20:48:36 +0300 Subject: [PATCH 117/132] Refactor ND builders to suit new discoverability pattern --- .../kmath/benchmarks/NDFieldBenchmark.kt | 6 +- .../kmath/benchmarks/ViktorBenchmark.kt | 9 +- .../kmath/benchmarks/ViktorLogBenchmark.kt | 9 +- docs/diagrams/core.puml | 1020 +++++++++++++++++ .../kmath/functions/matrixIntegration.kt | 4 +- .../kscience/kmath/operations/ComplexDemo.kt | 12 +- .../kscience/kmath/structures/ComplexND.kt | 10 +- .../kscience/kmath/structures/NDField.kt | 12 +- .../kmath/structures/StreamDoubleFieldND.kt | 2 +- gradle.properties | 2 + .../kscience/kmath/complex/ComplexFieldND.kt | 5 +- kmath-core/build.gradle.kts | 7 + .../kmath/linear/BufferedLinearSpace.kt | 7 +- .../kscience/kmath/nd/BufferAlgebraND.kt | 43 +- .../space/kscience/kmath/nd/DoubleFieldND.kt | 4 +- .../space/kscience/kmath/nd/ShortRingND.kt | 2 +- .../space/kscience/kmath/operations/BigInt.kt | 3 +- .../kscience/kmath/structures/NDFieldTest.kt | 8 +- .../kmath/structures/NumberNDFieldTest.kt | 10 +- .../kmath/histogram/DoubleHistogramSpace.kt | 3 +- .../kscience/kmath/jupyter/KMathJupyter.kt | 1 - .../kmath/optimization/QowOptimizer.kt | 22 +- settings.gradle.kts | 4 +- 23 files changed, 1130 insertions(+), 75 deletions(-) create mode 100644 docs/diagrams/core.puml diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt index 0cd9a46ab..fbf4bdaba 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt @@ -46,8 +46,8 @@ internal class NDFieldBenchmark { private companion object { private const val dim = 1000 private const val n = 100 - private val autoField = AlgebraND.auto(DoubleField, dim, dim) - private val specializedField = AlgebraND.real(dim, dim) - private val genericField = AlgebraND.field(DoubleField, Buffer.Companion::boxing, dim, dim) + private val autoField = DoubleField.autoNd(dim, dim) + private val specializedField = DoubleField.nd(dim, dim) + private val genericField = DoubleField.nd(Buffer.Companion::boxing, dim, dim) } } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt index 1ddc79cf8..6ea64ba3c 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt @@ -10,10 +10,9 @@ import kotlinx.benchmark.Blackhole import kotlinx.benchmark.Scope import kotlinx.benchmark.State import org.jetbrains.bio.viktor.F64Array -import space.kscience.kmath.nd.AlgebraND import space.kscience.kmath.nd.StructureND -import space.kscience.kmath.nd.auto -import space.kscience.kmath.nd.real +import space.kscience.kmath.nd.autoNd +import space.kscience.kmath.nd.nd import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.viktor.ViktorNDField @@ -59,8 +58,8 @@ internal class ViktorBenchmark { private const val n = 100 // automatically build context most suited for given type. - private val autoField = AlgebraND.auto(DoubleField, dim, dim) - private val realField = AlgebraND.real(dim, dim) + private val autoField = DoubleField.autoNd(dim, dim) + private val realField = DoubleField.nd(dim, dim) private val viktorField = ViktorNDField(dim, dim) } } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt index 8622e8f30..afe44ea99 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt @@ -10,9 +10,8 @@ import kotlinx.benchmark.Blackhole import kotlinx.benchmark.Scope import kotlinx.benchmark.State import org.jetbrains.bio.viktor.F64Array -import space.kscience.kmath.nd.AlgebraND -import space.kscience.kmath.nd.auto -import space.kscience.kmath.nd.real +import space.kscience.kmath.nd.autoNd +import space.kscience.kmath.nd.nd import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.viktor.ViktorFieldND @@ -51,8 +50,8 @@ internal class ViktorLogBenchmark { private const val n = 100 // automatically build context most suited for given type. - private val autoField = AlgebraND.auto(DoubleField, dim, dim) - private val realNdField = AlgebraND.real(dim, dim) + private val autoField = DoubleField.autoNd(dim, dim) + private val realNdField = DoubleField.nd(dim, dim) private val viktorField = ViktorFieldND(intArrayOf(dim, dim)) } } diff --git a/docs/diagrams/core.puml b/docs/diagrams/core.puml new file mode 100644 index 000000000..87f8f2e2d --- /dev/null +++ b/docs/diagrams/core.puml @@ -0,0 +1,1020 @@ +@startuml +interface "ColumnarData" { + size: Int +} +interface "XYColumnarData" { + x: Buffer + y: Buffer +} +interface "XYErrorColumnarData" { + yErr: Buffer +} +interface "XYZColumnarData" { + z: Buffer +} +interface "Domain" { + dimension: Int +} +interface "DoubleDomain" { + +} +class "HyperSquareDomain" { + lower: Buffer + upper: Buffer +} +class "UnconstrainedDomain" { + dimension: Int +} +class "UnivariateDomain" { + range: ClosedFloatingPointRange +} +interface "DifferentiableExpression" { + +} +interface "SpecialDifferentiableExpression" { + +} +abstract "FirstDerivativeExpression" { + +} +interface "AutoDiffProcessor" { + +} +interface "Expression" { + +} +interface "ExpressionAlgebra" { + +} +abstract "FunctionalExpressionAlgebra" { + algebra: A +} +class "FunctionalExpressionGroup" { + algebra: A +} +class "FunctionalExpressionRing" { + algebra: A +} +class "FunctionalExpressionField" { + algebra: A +} +class "FunctionalExpressionExtendedField" { + algebra: A +} +interface "MST" { + +} +class "Numeric" { + value: Number +} +class "Unary" { + operation: String + value: MST +} +class "Binary" { + operation: String + left: MST + right: MST +} +class "InnerAlgebra" { + algebra: Algebra + arguments: Map +} +class "MstNumericAlgebra" { + number() + bindSymbolOrNull() + bindSymbol() + unaryOperationFunction() + binaryOperationFunction() +} +class "MstGroup" { + zero: MST.Numericnumber() + bindSymbolOrNull() + add() + unaryPlus() + unaryMinus() + minus() + scale() + binaryOperationFunction() + unaryOperationFunction() +} +class "MstRing" { + zero: MST.Numeric + one: MST.Numericnumber() + bindSymbolOrNull() + add() + scale() + multiply() + unaryPlus() + unaryMinus() + minus() + binaryOperationFunction() + unaryOperationFunction() +} +class "MstField" { + zero: MST.Numeric + one: MST.NumericbindSymbolOrNull() + number() + add() + scale() + multiply() + divide() + unaryPlus() + unaryMinus() + minus() + binaryOperationFunction() + unaryOperationFunction() +} +class "MstExtendedField" { + zero: MST.Numeric + one: MST.NumericbindSymbolOrNull() + number() + sin() + cos() + tan() + asin() + acos() + atan() + sinh() + cosh() + tanh() + asinh() + acosh() + atanh() + add() + sqrt() + scale() + multiply() + divide() + unaryPlus() + unaryMinus() + minus() + power() + exp() + ln() + binaryOperationFunction() + unaryOperationFunction() +} +class "MstLogicAlgebra" { + bindSymbolOrNull() + const() + not() + and() + or() + xor() +} +class "AutoDiffValue" { + value: T +} +class "DerivationResult" { + value: T + derivativeValues: Map + context: Field +} +class "SimpleAutoDiffField" { + context: F + bindings: Map +} +class "AutoDiffVariableWithDerivative" { + identity: String + value: T + d: T +} +class "SimpleAutoDiffExpression" { + field: F + function: SimpleAutoDiffField +} +class "SimpleAutoDiffExtendedField" { + context: F + bindings: Map +} +interface "Symbol" { + identity: String +} +class "StringSymbol" { + identity: String +} +interface "SymbolIndexer" { + symbols: List +} +class "SimpleSymbolIndexer" { + symbols: List +} +class "BufferedLinearSpace" { + elementAlgebra: A + bufferFactory: BufferFactory +} +interface "LinearSolver" { + +} +interface "LinearSpace" { + elementAlgebra: A +} +class "LupDecomposition" { + context: LinearSpace + elementContext: Field + lu: Matrix + pivot: IntArray + even: Boolean +} +class "MatrixBuilder" { + linearSpace: LinearSpace + rows: Int + columns: Int +} +class "SymmetricMatrixFeature" { + +} +interface "MatrixFeature" { + +} +interface "DiagonalFeature" { + +} +class "ZeroFeature" { + +} +class "UnitFeature" { + +} +interface "InverseMatrixFeature" { + inverse: Matrix +} +interface "DeterminantFeature" { + determinant: T +} +class "LFeature" { + +} +class "UFeature" { + +} +interface "LUDecompositionFeature" { + l: Matrix + u: Matrix +} +interface "LupDecompositionFeature" { + l: Matrix + u: Matrix + p: Matrix +} +class "OrthogonalFeature" { + +} +interface "QRDecompositionFeature" { + q: Matrix + r: Matrix +} +interface "CholeskyDecompositionFeature" { + l: Matrix +} +interface "SingularValueDecompositionFeature" { + u: Matrix + s: Matrix + v: Matrix + singularValues: Point +} +class "MatrixWrapper" { + origin: Matrix + features: FeatureSet +} +class "TransposedFeature" { + original: Matrix +} +class "VirtualMatrix" { + rowNum: Int + colNum: Int + generator: (i:Int,j:Int)->T +} +class "UnstableKMathAPI" { + +} +class "PerformancePitfall" { + message: String +} +interface "Featured" { + +} +interface "Feature" { + key: FeatureKey +} +class "FeatureSet" { + features: Map +} +interface "Loggable" { + +} +class "ShapeMismatchException" { + expected: IntArray + actual: IntArray +} +interface "AlgebraND" { + shape: IntArray + elementContext: C +} +interface "GroupND" { + +} +interface "RingND" { + +} +interface "FieldND" { + +} +interface "BufferAlgebraND" { + strides: Strides + bufferFactory: BufferFactory + buffer: Buffer +} +class "BufferedGroupND" { + shape: IntArray + elementContext: A + bufferFactory: BufferFactory +} +class "BufferedRingND" { + shape: IntArray + elementContext: R + bufferFactory: BufferFactory +} +class "BufferedFieldND" { + shape: IntArray + elementContext: R + bufferFactory: BufferFactory +} +class "BufferND" { + strides: Strides + buffer: Buffer +} +class "MutableBufferND" { + strides: Strides + mutableBuffer: MutableBuffer +} +class "DoubleFieldND" { + shape: IntArray +} +class "ShortRingND" { + shape: IntArray +} +interface "Structure1D" { + dimension: Int +} +interface "MutableStructure1D" { + +} +class "Structure1DWrapper" { + structure: StructureND +} +class "MutableStructure1DWrapper" { + structure: MutableStructureND +} +class "Buffer1DWrapper" { + buffer: Buffer +} +class "MutableBuffer1DWrapper" { + buffer: MutableBuffer +} +interface "Structure2D" { + rowNum: Int + colNum: Int + shape: IntArray + rows: List + columns: List +} +interface "MutableStructure2D" { + rows: List + columns: List +} +class "Structure2DWrapper" { + structure: StructureND +} +class "MutableStructure2DWrapper" { + structure: MutableStructureND +} +interface "StructureFeature" { + +} +interface "StructureND" { + shape: IntArray + dimension: Int +} +interface "MutableStructureND" { + +} +interface "Strides" { + shape: IntArray + strides: IntArray + linearSize: Int +} +class "DefaultStrides" { + shape: IntArray +} +class "KMathContext" { + +} +interface "Algebra" { + +} +interface "GroupOperations" { + +} +interface "Group" { + zero: T +} +interface "RingOperations" { + +} +interface "Ring" { + one: T +} +interface "FieldOperations" { + +} +interface "Field" { + +} +interface "AlgebraElement" { + context: C +} +interface "GroupElement" { + +} +interface "RingElement" { + +} +interface "FieldElement" { + +} +class "BigIntField" { + zero: BigInt + one: BigIntnumber() + unaryMinus() + add() + scale() + multiply() + divide() + unaryPlus() + unaryMinus() +} +class "BigInt" { + sign: Byte + magnitude: Magnitude +} +interface "BufferAlgebra" { + bufferFactory: BufferFactory + elementAlgebra: A +} +class "BufferField" { + bufferFactory: BufferFactory + elementAlgebra: A + size: Int +} +interface "LogicAlgebra" { + +} +class "BooleanAlgebra" { + const() + not() + and() + or() + xor() +} +interface "ExtendedFieldOperations" { + +} +interface "ExtendedField" { + +} +class "DoubleField" { + zero: Double + one: Doublenumber() + binaryOperationFunction() + add() + multiply() + divide() + scale() + sin() + cos() + tan() + acos() + asin() + atan() + sinh() + cosh() + tanh() + asinh() + acosh() + atanh() + sqrt() + power() + exp() + ln() + norm() + unaryMinus() + plus() + minus() + times() + div() +} +class "FloatField" { + zero: Float + one: Floatnumber() + binaryOperationFunction() + add() + scale() + multiply() + divide() + sin() + cos() + tan() + acos() + asin() + atan() + sinh() + cosh() + tanh() + asinh() + acosh() + atanh() + sqrt() + power() + exp() + ln() + norm() + unaryMinus() + plus() + minus() + times() + div() +} +class "IntRing" { + zero: Int + one: Intnumber() + add() + multiply() + norm() + unaryMinus() + plus() + minus() + times() +} +class "ShortRing" { + zero: Short + one: Shortnumber() + add() + multiply() + norm() + unaryMinus() + plus() + minus() + times() +} +class "ByteRing" { + zero: Byte + one: Bytenumber() + add() + multiply() + norm() + unaryMinus() + plus() + minus() + times() +} +class "LongRing" { + zero: Long + one: Longnumber() + add() + multiply() + norm() + unaryMinus() + plus() + minus() + times() +} +interface "NumericAlgebra" { + +} +interface "ScaleOperations" { + +} +interface "NumbersAddOperations" { + +} +interface "TrigonometricOperations" { + +} +interface "PowerOperations" { + +} +interface "ExponentialOperations" { + +} +interface "Norm" { + +} +interface "Buffer" { + size: Int +} +interface "MutableBuffer" { + +} +class "ListBuffer" { + list: List +} +class "MutableListBuffer" { + list: MutableList +} +class "ArrayBuffer" { + array: Array +} +class "ReadOnlyBuffer" { + buffer: MutableBuffer +} +class "VirtualBuffer" { + size: Int + generator: (Int)->T +} +class "BufferAccessor2D" { + rowNum: Int + colNum: Int + factory: MutableBufferFactory +} +class "Row" { + buffer: MutableBuffer + rowIndex: Int +} +class "DoubleBuffer" { + array: DoubleArray +} +class "DoubleBufferFieldOperations" { + unaryMinus() + add() + multiply() + divide() + sin() + cos() + tan() + asin() + acos() + atan() + sinh() + cosh() + tanh() + asinh() + acosh() + atanh() + power() + exp() + ln() +} +class "DoubleL2Norm" { + norm() +} +class "DoubleBufferField" { + size: Int +} +enum "ValueFlag" { + NAN + MISSING + NEGATIVE_INFINITY + POSITIVE_INFINITY +} +interface "FlaggedBuffer" { + +} +class "FlaggedDoubleBuffer" { + values: DoubleArray + flags: ByteArray +} +class "FloatBuffer" { + array: FloatArray +} +class "IntBuffer" { + array: IntArray +} +class "LongBuffer" { + array: LongArray +} +class "MemoryBuffer" { + memory: Memory + spec: MemorySpec +} +class "MutableMemoryBuffer" { + memory: Memory + spec: MemorySpec +} +class "ShortBuffer" { + array: ShortArray +} +class "ExpressionFieldTest" { + x +} +class "InterpretTest" { + +} +class "SimpleAutoDiffTest" { + x + y + z +} +class "DoubleLUSolverTest" { + +} +class "MatrixTest" { + +} +class "CumulativeKtTest" { + +} +class "BigIntAlgebraTest" { + +} +class "BigIntConstructorTest" { + +} +class "BigIntConversionsTest" { + +} +class "BigIntOperationsTest" { + +} +class "DoubleFieldTest" { + +} +class "NDFieldTest" { + +} +class "NumberNDFieldTest" { + algebra + array1 + array2 +} +class "L2Norm" { + norm() +} +interface "AlgebraicVerifier" { + algebra: A +} +class "FieldVerifier" { + algebra: A + a: T + b: T + c: T + x: Number +} +class "RingVerifier" { + algebra: A + a: T + b: T + c: T + x: Number +} +class "SpaceVerifier" { + algebra: S + a: T + b: T + c: T + x: Number +} +class "JBigIntegerField" { + zero: BigInteger + one: BigIntegernumber() + add() + minus() + multiply() + unaryMinus() +} +abstract "JBigDecimalFieldBase" { + mathContext: MathContext +} +class "JBigDecimalField" { + mathContext: MathContext +} +"ColumnarData" <|--- XYColumnarData +"XYColumnarData" <|--- XYErrorColumnarData +"XYColumnarData" <|--- XYZColumnarData +"Domain" <|--- DoubleDomain +"DoubleDomain" <|--- HyperSquareDomain +"DoubleDomain" <|--- UnconstrainedDomain +"DoubleDomain" <|--- UnivariateDomain +"Expression" <|--- DifferentiableExpression +"DifferentiableExpression" <|--- SpecialDifferentiableExpression +"DifferentiableExpression" <|--- FirstDerivativeExpression +"Algebra" <|--- ExpressionAlgebra +"ExpressionAlgebra" <|--- FunctionalExpressionAlgebra +"FunctionalExpressionAlgebra" <|--- FunctionalExpressionGroup +"Group" <|--- FunctionalExpressionGroup +"FunctionalExpressionGroup" <|--- FunctionalExpressionRing +"Ring" <|--- FunctionalExpressionRing +"FunctionalExpressionRing" <|--- FunctionalExpressionField +"Field" <|--- FunctionalExpressionField +"ScaleOperations" <|--- FunctionalExpressionField +"FunctionalExpressionField" <|--- FunctionalExpressionExtendedField +"ExtendedField" <|--- FunctionalExpressionExtendedField +"MST" <|--- Numeric +"MST" <|--- Unary +"MST" <|--- Binary +"NumericAlgebra" <|--- InnerAlgebra +"NumericAlgebra" <|--- MstNumericAlgebra +"Group" <|--- MstGroup +"NumericAlgebra" <|--- MstGroup +"ScaleOperations" <|--- MstGroup +"Ring" <|--- MstRing +"NumbersAddOperations" <|--- MstRing +"ScaleOperations" <|--- MstRing +"Field" <|--- MstField +"NumbersAddOperations" <|--- MstField +"ScaleOperations" <|--- MstField +"ExtendedField" <|--- MstExtendedField +"NumericAlgebra" <|--- MstExtendedField +"LogicAlgebra" <|--- MstLogicAlgebra +"Field" <|--- SimpleAutoDiffField +"ExpressionAlgebra" <|--- SimpleAutoDiffField +"NumbersAddOperations" <|--- SimpleAutoDiffField +"AutoDiffValue" <|--- AutoDiffVariableWithDerivative +"Symbol" <|--- AutoDiffVariableWithDerivative +"FirstDerivativeExpression" <|--- SimpleAutoDiffExpression +"ExtendedField" <|--- SimpleAutoDiffExtendedField +"ScaleOperations" <|--- SimpleAutoDiffExtendedField +'"" <|--- SimpleAutoDiffExtendedField +"SimpleAutoDiffField" <|--- SimpleAutoDiffExtendedField +"MST" <|--- Symbol +"Symbol" <|--- StringSymbol +"SymbolIndexer" <|--- SimpleSymbolIndexer +"LinearSpace" <|--- BufferedLinearSpace +"LupDecompositionFeature" <|--- LupDecomposition +"DeterminantFeature" <|--- LupDecomposition +"MatrixFeature" <|--- SymmetricMatrixFeature +"StructureFeature" <|--- MatrixFeature +"MatrixFeature" <|--- DiagonalFeature +"DiagonalFeature" <|--- ZeroFeature +"DiagonalFeature" <|--- UnitFeature +"MatrixFeature" <|--- InverseMatrixFeature +"MatrixFeature" <|--- DeterminantFeature +"MatrixFeature" <|--- LFeature +"MatrixFeature" <|--- UFeature +"MatrixFeature" <|--- LUDecompositionFeature +"MatrixFeature" <|--- LupDecompositionFeature +"MatrixFeature" <|--- OrthogonalFeature +"MatrixFeature" <|--- QRDecompositionFeature +"MatrixFeature" <|--- CholeskyDecompositionFeature +"MatrixFeature" <|--- SingularValueDecompositionFeature +'"Matrixbyorigin{ +' +' +' @UnstableKMathAPI +' @Suppress +'overridefungetFeature:F? = +'features.getFeature +' +'overridefuntoString" +'}" <|--- MatrixWrapper +"MatrixFeature" <|--- TransposedFeature +"Matrix" <|--- VirtualMatrix +"Featured" <|--- FeatureSet +"RuntimeException" <|--- ShapeMismatchException +"Group" <|--- GroupND +"AlgebraND" <|--- GroupND +"Ring" <|--- RingND +"GroupND" <|--- RingND +"Field" <|--- FieldND +"RingND" <|--- FieldND +"AlgebraND" <|--- BufferAlgebraND +"GroupND" <|--- BufferedGroupND +"BufferAlgebraND" <|--- BufferedGroupND +"BufferedGroupND" <|--- BufferedRingND +"RingND" <|--- BufferedRingND +"BufferedRingND" <|--- BufferedFieldND +"FieldND" <|--- BufferedFieldND +"StructureND" <|--- BufferND +"MutableStructureND" <|--- MutableBufferND +"BufferND" <|--- MutableBufferND +"BufferedFieldND" <|--- DoubleFieldND +'" +'" <|--- DoubleFieldND +'"NumbersAddOperations" <|--- DoubleFieldND +'" +'" <|--- DoubleFieldND +'"ScaleOperations" <|--- DoubleFieldND +'" +'" <|--- DoubleFieldND +"ExtendedField" <|--- DoubleFieldND +"BufferedRingND" <|--- ShortRingND +'" +'" <|--- ShortRingND +"NumbersAddOperations" <|--- ShortRingND +"StructureND" <|--- Structure1D +"Buffer" <|--- Structure1D +"Structure1D" <|--- MutableStructure1D +"MutableStructureND" <|--- MutableStructure1D +"MutableBuffer" <|--- MutableStructure1D +"Structure1D" <|--- Structure1DWrapper +"MutableStructure1D" <|--- MutableStructure1DWrapper +"Structure1D" <|--- Buffer1DWrapper +"MutableStructure1D" <|--- MutableBuffer1DWrapper +"StructureND" <|--- Structure2D +"Structure2D" <|--- MutableStructure2D +"MutableStructureND" <|--- MutableStructure2D +"Structure2D" <|--- Structure2DWrapper +"MutableStructure2D" <|--- MutableStructure2DWrapper +"Feature" <|--- StructureFeature +"Featured" <|--- StructureND +"StructureND" <|--- MutableStructureND +"Strides" <|--- DefaultStrides +"Algebra" <|--- GroupOperations +"GroupOperations" <|--- Group +"GroupOperations" <|--- RingOperations +"Group" <|--- Ring +"RingOperations" <|--- Ring +"RingOperations" <|--- FieldOperations +"Ring" <|--- Field +"FieldOperations" <|--- Field +"ScaleOperations" <|--- Field +"NumericAlgebra" <|--- Field +"AlgebraElement" <|--- GroupElement +"GroupElement" <|--- RingElement +"RingElement" <|--- FieldElement +"Field" <|--- BigIntField +"NumbersAddOperations" <|--- BigIntField +"ScaleOperations" <|--- BigIntField +"Comparable" <|--- BigInt +"Algebra" <|--- BufferAlgebra +"BufferAlgebra" <|--- BufferField +"Field" <|--- BufferField +"Algebra" <|--- LogicAlgebra +"LogicAlgebra" <|--- BooleanAlgebra +"FieldOperations" <|--- ExtendedFieldOperations +'" +'" <|--- ExtendedFieldOperations +'"TrigonometricOperations" <|--- ExtendedFieldOperations +'" +'" <|--- ExtendedFieldOperations +'"PowerOperations" <|--- ExtendedFieldOperations +'" +'" <|--- ExtendedFieldOperations +"ExponentialOperations" <|--- ExtendedFieldOperations +"ExtendedFieldOperations" <|--- ExtendedField +"Field" <|--- ExtendedField +"NumericAlgebra" <|--- ExtendedField +"ScaleOperations" <|--- ExtendedField +"ExtendedField" <|--- DoubleField +"Norm" <|--- DoubleField +"ScaleOperations" <|--- DoubleField +"ExtendedField" <|--- FloatField +"Norm" <|--- FloatField +"Ring" <|--- IntRing +"Norm" <|--- IntRing +"NumericAlgebra" <|--- IntRing +"Ring" <|--- ShortRing +"Norm" <|--- ShortRing +"NumericAlgebra" <|--- ShortRing +"Ring" <|--- ByteRing +"Norm" <|--- ByteRing +"NumericAlgebra" <|--- ByteRing +"Ring" <|--- LongRing +"Norm" <|--- LongRing +"NumericAlgebra" <|--- LongRing +"Algebra" <|--- NumericAlgebra +"Algebra" <|--- ScaleOperations +"Ring" <|--- NumbersAddOperations +"NumericAlgebra" <|--- NumbersAddOperations +"Algebra" <|--- TrigonometricOperations +"Algebra" <|--- PowerOperations +"Algebra" <|--- ExponentialOperations +"Buffer" <|--- MutableBuffer +"Buffer" <|--- ListBuffer +"MutableBuffer" <|--- MutableListBuffer +"MutableBuffer" <|--- ArrayBuffer +"Buffer" <|--- ReadOnlyBuffer +"Buffer" <|--- VirtualBuffer +"MutableBuffer" <|--- Row +"MutableBuffer" <|--- DoubleBuffer +"ExtendedFieldOperations" <|--- DoubleBufferFieldOperations +"Norm" <|--- DoubleL2Norm +"ExtendedField" <|--- DoubleBufferField +"Norm" <|--- DoubleBufferField +"Buffer" <|--- FlaggedBuffer +"FlaggedBuffer" <|--- FlaggedDoubleBuffer +'" +'" <|--- FlaggedDoubleBuffer +"Buffer" <|--- FlaggedDoubleBuffer +"MutableBuffer" <|--- FloatBuffer +"MutableBuffer" <|--- IntBuffer +"MutableBuffer" <|--- LongBuffer +"Buffer" <|--- MemoryBuffer +"MemoryBuffer" <|--- MutableMemoryBuffer +'" +'" <|--- MutableMemoryBuffer +"MutableBuffer" <|--- MutableMemoryBuffer +"MutableBuffer" <|--- ShortBuffer +"Norm" <|--- L2Norm +"RingVerifier" <|--- FieldVerifier +"SpaceVerifier" <|--- RingVerifier +"AlgebraicVerifier" <|--- SpaceVerifier +"Ring" <|--- JBigIntegerField +"NumericAlgebra" <|--- JBigIntegerField +"Field" <|--- JBigDecimalFieldBase +"PowerOperations" <|--- JBigDecimalFieldBase +"NumericAlgebra" <|--- JBigDecimalFieldBase +"ScaleOperations" <|--- JBigDecimalFieldBase +"JBigDecimalFieldBase" <|--- JBigDecimalField +@enduml \ No newline at end of file diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt index 569a57070..d932fdb9f 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt @@ -9,12 +9,12 @@ import space.kscience.kmath.integration.gaussIntegrator import space.kscience.kmath.integration.integrate import space.kscience.kmath.integration.value import space.kscience.kmath.nd.StructureND -import space.kscience.kmath.nd.nd +import space.kscience.kmath.nd.withNd import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke fun main(): Unit = DoubleField { - nd(2, 2) { + withNd(2, 2) { //Produce a diagonal StructureND fun diagonal(v: Double) = produce { (i, j) -> diff --git a/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt b/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt index eefc6e896..8b511f961 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt @@ -6,18 +6,20 @@ package space.kscience.kmath.operations import space.kscience.kmath.complex.Complex -import space.kscience.kmath.complex.complex -import space.kscience.kmath.nd.AlgebraND +import space.kscience.kmath.complex.ComplexField +import space.kscience.kmath.complex.withNd +import space.kscience.kmath.nd.StructureND +import space.kscience.kmath.nd.autoNd fun main() { // 2d element - val element = AlgebraND.complex(2, 2).produce { (i, j) -> - Complex(i.toDouble() - j.toDouble(), i.toDouble() + j.toDouble()) + val element = ComplexField.autoNd(2, 2).produce { (i, j) -> + Complex(i - j, i + j) } println(element) // 1d element operation - val result = with(AlgebraND.complex(8)) { + val result: StructureND = ComplexField.withNd(8) { val a = produce { (it) -> i * it - it.toDouble() } val b = 3 val c = Complex(1.0, 1.0) diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt index 752e00bdf..c591f5682 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt @@ -9,10 +9,10 @@ package space.kscience.kmath.structures import space.kscience.kmath.complex.* import space.kscience.kmath.linear.transpose -import space.kscience.kmath.nd.AlgebraND import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.as2D -import space.kscience.kmath.nd.real +import space.kscience.kmath.nd.nd +import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke import kotlin.system.measureTimeMillis @@ -20,8 +20,8 @@ fun main() { val dim = 1000 val n = 1000 - val realField = AlgebraND.real(dim, dim) - val complexField: ComplexFieldND = AlgebraND.complex(dim, dim) + val realField = DoubleField.nd(dim, dim) + val complexField: ComplexFieldND = ComplexField.nd(dim, dim) val realTime = measureTimeMillis { realField { @@ -49,7 +49,7 @@ fun main() { fun complexExample() { //Create a context for 2-d structure with complex values ComplexField { - nd(4, 8) { + withNd(4, 8) { //a constant real-valued structure val x = one * 2.5 operator fun Number.plus(other: Complex) = Complex(this.toDouble() + other.re, other.im) diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt index c842960be..c9cafbba8 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt @@ -8,7 +8,9 @@ package space.kscience.kmath.structures import kotlinx.coroutines.DelicateCoroutinesApi import kotlinx.coroutines.GlobalScope import org.nd4j.linalg.factory.Nd4j -import space.kscience.kmath.nd.* +import space.kscience.kmath.nd.StructureND +import space.kscience.kmath.nd.autoNd +import space.kscience.kmath.nd.nd import space.kscience.kmath.nd4j.Nd4jArrayField import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke @@ -31,17 +33,17 @@ fun main() { val n = 1000 // automatically build context most suited for given type. - val autoField = AlgebraND.auto(DoubleField, dim, dim) + val autoField = DoubleField.autoNd(dim, dim) // specialized nd-field for Double. It works as generic Double field as well. - val realField = AlgebraND.real(dim, dim) + val realField = DoubleField.nd(dim, dim) //A generic boxing field. It should be used for objects, not primitives. - val boxingField = AlgebraND.field(DoubleField, Buffer.Companion::boxing, dim, dim) + val boxingField = DoubleField.nd(Buffer.Companion::boxing, dim, dim) // Nd4j specialized field. val nd4jField = Nd4jArrayField.real(dim, dim) //viktor field val viktorField = ViktorNDField(dim, dim) //parallel processing based on Java Streams - val parallelField = AlgebraND.realWithStream(dim, dim) + val parallelField = DoubleField.ndStreaming(dim, dim) measureAndPrint("Boxing addition") { boxingField { diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/StreamDoubleFieldND.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/StreamDoubleFieldND.kt index e443a588d..b1248bd0f 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/structures/StreamDoubleFieldND.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/StreamDoubleFieldND.kt @@ -105,4 +105,4 @@ class StreamDoubleFieldND(override val shape: IntArray) : FieldND): BufferND = arg.map { atanh(it) } } -fun AlgebraND.Companion.realWithStream(vararg shape: Int): StreamDoubleFieldND = StreamDoubleFieldND(shape) +fun DoubleField.ndStreaming(vararg shape: Int): StreamDoubleFieldND = StreamDoubleFieldND(shape) diff --git a/gradle.properties b/gradle.properties index b97db1c54..49bbf36dd 100644 --- a/gradle.properties +++ b/gradle.properties @@ -7,6 +7,8 @@ kotlin.code.style=official kotlin.mpp.enableGranularSourceSetsMetadata=true kotlin.mpp.stability.nowarn=true kotlin.native.enableDependencyPropagation=false +kotlin.jupyter.add.scanner=false + org.gradle.configureondemand=true org.gradle.jvmargs=-XX:MaxMetaspaceSize=2G org.gradle.parallel=true diff --git a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt index ae4e05631..41bcb83df 100644 --- a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt +++ b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt @@ -6,7 +6,6 @@ package space.kscience.kmath.complex import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.nd.AlgebraND import space.kscience.kmath.nd.BufferND import space.kscience.kmath.nd.BufferedFieldND import space.kscience.kmath.nd.StructureND @@ -113,12 +112,12 @@ public inline fun BufferedFieldND.produceInline(initializ } -public fun AlgebraND.Companion.complex(vararg shape: Int): ComplexFieldND = ComplexFieldND(shape) +public fun ComplexField.nd(vararg shape: Int): ComplexFieldND = ComplexFieldND(shape) /** * Produce a context for n-dimensional operations inside this real field */ -public inline fun ComplexField.nd(vararg shape: Int, action: ComplexFieldND.() -> R): R { +public inline fun ComplexField.withNd(vararg shape: Int, action: ComplexFieldND.() -> R): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } return ComplexFieldND(shape).action() } diff --git a/kmath-core/build.gradle.kts b/kmath-core/build.gradle.kts index 564d06f49..e4436c1df 100644 --- a/kmath-core/build.gradle.kts +++ b/kmath-core/build.gradle.kts @@ -2,6 +2,7 @@ plugins { kotlin("multiplatform") id("ru.mipt.npm.gradle.common") id("ru.mipt.npm.gradle.native") +// id("com.xcporter.metaview") version "0.0.5" } kotlin.sourceSets { @@ -12,6 +13,12 @@ kotlin.sourceSets { } } +//generateUml { +// classTree { +// +// } +//} + readme { description = "Core classes, algebra definitions, basic linear algebra" maturity = ru.mipt.npm.gradle.Maturity.DEVELOPMENT diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt index 5471cb925..14235515c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt @@ -6,7 +6,10 @@ package space.kscience.kmath.linear import space.kscience.kmath.misc.PerformancePitfall -import space.kscience.kmath.nd.* +import space.kscience.kmath.nd.BufferedRingND +import space.kscience.kmath.nd.as2D +import space.kscience.kmath.nd.nd +import space.kscience.kmath.nd.unwrap import space.kscience.kmath.operations.Ring import space.kscience.kmath.operations.invoke import space.kscience.kmath.structures.Buffer @@ -23,7 +26,7 @@ public class BufferedLinearSpace>( private fun ndRing( rows: Int, cols: Int, - ): BufferedRingND = AlgebraND.ring(elementAlgebra, bufferFactory, rows, cols) + ): BufferedRingND = elementAlgebra.nd(bufferFactory, rows, cols) override fun buildMatrix(rows: Int, columns: Int, initializer: A.(i: Int, j: Int) -> T): Matrix = ndRing(rows, columns).produce { (i, j) -> elementAlgebra.initializer(i, j) }.as2D() diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt index 9ece51ff8..b01beb02d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt @@ -5,11 +5,13 @@ package space.kscience.kmath.nd +import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.* import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.BufferFactory import kotlin.contracts.InvocationKind import kotlin.contracts.contract +import kotlin.jvm.JvmName public interface BufferAlgebraND> : AlgebraND { public val strides: Strides @@ -85,58 +87,61 @@ public open class BufferedFieldND>( } // group factories -public fun > AlgebraND.Companion.group( - space: A, +public fun > A.nd( bufferFactory: BufferFactory, vararg shape: Int, -): BufferedGroupND = BufferedGroupND(shape, space, bufferFactory) +): BufferedGroupND = BufferedGroupND(shape, this, bufferFactory) -public inline fun , R> A.ndGroup( +@JvmName("withNdGroup") +public inline fun , R> A.withNd( noinline bufferFactory: BufferFactory, vararg shape: Int, action: BufferedGroupND.() -> R, ): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } - return AlgebraND.group(this, bufferFactory, *shape).run(action) + return nd(bufferFactory, *shape).run(action) } //ring factories -public fun > AlgebraND.Companion.ring( - ring: A, +public fun > A.nd( bufferFactory: BufferFactory, vararg shape: Int, -): BufferedRingND = BufferedRingND(shape, ring, bufferFactory) +): BufferedRingND = BufferedRingND(shape, this, bufferFactory) -public inline fun , R> A.ndRing( +@JvmName("withNdRing") +public inline fun , R> A.withNd( noinline bufferFactory: BufferFactory, vararg shape: Int, action: BufferedRingND.() -> R, ): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } - return AlgebraND.ring(this, bufferFactory, *shape).run(action) + return nd(bufferFactory, *shape).run(action) } //field factories -public fun > AlgebraND.Companion.field( - field: A, +public fun > A.nd( bufferFactory: BufferFactory, vararg shape: Int, -): BufferedFieldND = BufferedFieldND(shape, field, bufferFactory) +): BufferedFieldND = BufferedFieldND(shape, this, bufferFactory) +/** + * Create a [FieldND] for this [Field] inferring proper buffer factory from the type + */ +@UnstableKMathAPI @Suppress("UNCHECKED_CAST") -public inline fun > AlgebraND.Companion.auto( - field: A, +public inline fun > A.autoNd( vararg shape: Int, -): FieldND = when (field) { +): FieldND = when (this) { DoubleField -> DoubleFieldND(shape) as FieldND - else -> BufferedFieldND(shape, field, Buffer.Companion::auto) + else -> BufferedFieldND(shape, this, Buffer.Companion::auto) } -public inline fun , R> A.ndField( +@JvmName("withNdField") +public inline fun , R> A.withNd( noinline bufferFactory: BufferFactory, vararg shape: Int, action: BufferedFieldND.() -> R, ): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } - return AlgebraND.field(this, bufferFactory, *shape).run(action) + return nd(bufferFactory, *shape).run(action) } \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt index a448e351e..fed4aca0b 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt @@ -103,12 +103,12 @@ public class DoubleFieldND( override fun atanh(arg: StructureND): BufferND = arg.map { atanh(it) } } -public fun AlgebraND.Companion.real(vararg shape: Int): DoubleFieldND = DoubleFieldND(shape) +public fun DoubleField.nd(vararg shape: Int): DoubleFieldND = DoubleFieldND(shape) /** * Produce a context for n-dimensional operations inside this real field */ -public inline fun DoubleField.nd(vararg shape: Int, action: DoubleFieldND.() -> R): R { +public inline fun DoubleField.withNd(vararg shape: Int, action: DoubleFieldND.() -> R): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } return DoubleFieldND(shape).run(action) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt index f96978cfc..5b6e2cd22 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt @@ -34,7 +34,7 @@ public class ShortRingND( public inline fun BufferedRingND.produceInline(crossinline initializer: ShortRing.(Int) -> Short): BufferND = BufferND(strides, ShortBuffer(ShortArray(strides.linearSize) { offset -> ShortRing.initializer(offset) })) -public inline fun ShortRing.nd(vararg shape: Int, action: ShortRingND.() -> R): R { +public inline fun ShortRing.withNd(vararg shape: Int, action: ShortRingND.() -> R): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } return ShortRingND(shape).run(action) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 2dd61270d..02741e6ab 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -6,7 +6,6 @@ package space.kscience.kmath.operations import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.nd.AlgebraND import space.kscience.kmath.nd.BufferedRingND import space.kscience.kmath.operations.BigInt.Companion.BASE import space.kscience.kmath.operations.BigInt.Companion.BASE_SIZE @@ -533,5 +532,5 @@ public inline fun Buffer.Companion.bigInt(size: Int, initializer: (Int) -> BigIn public inline fun MutableBuffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): MutableBuffer = boxing(size, initializer) -public fun AlgebraND.Companion.bigInt(vararg shape: Int): BufferedRingND = +public fun BigIntField.nd(vararg shape: Int): BufferedRingND = BufferedRingND(shape, BigIntField, Buffer.Companion::bigInt) diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NDFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NDFieldTest.kt index f623b00e8..6d4531f41 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NDFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NDFieldTest.kt @@ -5,9 +5,9 @@ package space.kscience.kmath.structures -import space.kscience.kmath.nd.AlgebraND import space.kscience.kmath.nd.get -import space.kscience.kmath.nd.real +import space.kscience.kmath.nd.nd +import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke import space.kscience.kmath.testutils.FieldVerifier import kotlin.test.Test @@ -16,12 +16,12 @@ import kotlin.test.assertEquals internal class NDFieldTest { @Test fun verify() { - (AlgebraND.real(12, 32)) { FieldVerifier(this, one + 3, one - 23, one * 12, 6.66) } + (DoubleField.nd(12, 32)) { FieldVerifier(this, one + 3, one - 23, one * 12, 6.66) } } @Test fun testStrides() { - val ndArray = AlgebraND.real(10, 10).produce { (it[0] + it[1]).toDouble() } + val ndArray = DoubleField.nd(10, 10).produce { (it[0] + it[1]).toDouble() } assertEquals(ndArray[5, 5], 10.0) } } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt index 1803fff71..1045933b7 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt @@ -7,7 +7,11 @@ package space.kscience.kmath.structures import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.misc.PerformancePitfall -import space.kscience.kmath.nd.* +import space.kscience.kmath.nd.StructureND +import space.kscience.kmath.nd.combine +import space.kscience.kmath.nd.get +import space.kscience.kmath.nd.nd +import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Norm import space.kscience.kmath.operations.invoke import kotlin.math.abs @@ -17,7 +21,7 @@ import kotlin.test.assertEquals @Suppress("UNUSED_VARIABLE") class NumberNDFieldTest { - val algebra = AlgebraND.real(3, 3) + val algebra = DoubleField.nd(3, 3) val array1 = algebra.produce { (i, j) -> (i + j).toDouble() } val array2 = algebra.produce { (i, j) -> (i - j).toDouble() } @@ -83,7 +87,7 @@ class NumberNDFieldTest { @Test fun testInternalContext() { algebra { - (AlgebraND.real(*array1.shape)) { with(L2Norm) { 1 + norm(array1) + exp(array2) } } + (DoubleField.nd(*array1.shape)) { with(L2Norm) { 1 + norm(array1) + exp(array2) } } } } } diff --git a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/DoubleHistogramSpace.kt b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/DoubleHistogramSpace.kt index 27b14b65e..37ab8a1b2 100644 --- a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/DoubleHistogramSpace.kt +++ b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/DoubleHistogramSpace.kt @@ -9,6 +9,7 @@ import space.kscience.kmath.domains.Domain import space.kscience.kmath.domains.HyperSquareDomain import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.* +import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.structures.* import kotlin.math.floor @@ -28,7 +29,7 @@ public class DoubleHistogramSpace( public val dimension: Int get() = lower.size private val shape = IntArray(binNums.size) { binNums[it] + 2 } - override val histogramValueSpace: DoubleFieldND = AlgebraND.real(*shape) + override val histogramValueSpace: DoubleFieldND = DoubleField.nd(*shape) override val strides: Strides get() = histogramValueSpace.strides private val binSize = DoubleBuffer(dimension) { (upper[it] - lower[it]) / binNums[it] } diff --git a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt index d7438bf0f..e646d2bd0 100644 --- a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt +++ b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt @@ -11,7 +11,6 @@ import kotlinx.html.stream.createHTML import kotlinx.html.unsafe import org.jetbrains.kotlinx.jupyter.api.DisplayResult import org.jetbrains.kotlinx.jupyter.api.HTML -import org.jetbrains.kotlinx.jupyter.api.annotations.JupyterLibrary import org.jetbrains.kotlinx.jupyter.api.libraries.JupyterIntegration import space.kscience.kmath.ast.rendering.FeaturedMathRendererWithPostProcess import space.kscience.kmath.ast.rendering.MathMLSyntaxRenderer diff --git a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt index 4fe8520da..00df0944f 100644 --- a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt @@ -16,6 +16,14 @@ import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.DoubleL2Norm +public class QowRuns(public val runs: Int) : OptimizationFeature { + init { + require(runs >= 1) { "Number of runs must be more than zero" } + } + + override fun toString(): String = "QowRuns(runs=$runs)" +} + /** * An optimizer based onf Fyodor Tkachev's quasi-optimal weights method. @@ -56,7 +64,7 @@ public object QowOptimizer : Optimizer { val prior: DifferentiableExpression? get() = problem.getFeature>() - override fun toString(): String = parameters.toString() + override fun toString(): String = parameters.toString() } /** @@ -242,9 +250,15 @@ public object QowOptimizer : Optimizer { } override suspend fun optimize(problem: XYFit): XYFit { - val qowSteps = 2 - val initialWeight = QoWeight(problem, problem.startPoint) - val res = initialWeight.newtonianRun() + val qowRuns = problem.getFeature()?.runs ?: 2 + + + var qow = QoWeight(problem, problem.startPoint) + var res = qow.newtonianRun() + repeat(qowRuns - 1) { + qow = QoWeight(problem, res.parameters) + res = qow.newtonianRun() + } return res.problem.withFeature(OptimizationResult(res.parameters)) } } \ No newline at end of file diff --git a/settings.gradle.kts b/settings.gradle.kts index d1cbbe74c..0fc77b38e 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -5,11 +5,11 @@ pluginManagement { gradlePluginPortal() } - val kotlinVersion = "1.5.21" + val kotlinVersion = "1.5.30" plugins { id("org.jetbrains.kotlinx.benchmark") version "0.3.1" - id("ru.mipt.npm.gradle.project") version "0.10.2" + id("ru.mipt.npm.gradle.project") version "0.10.3" kotlin("multiplatform") version kotlinVersion kotlin("plugin.allopen") version kotlinVersion } From 546d56aeee3615d66fcbfda22d7e27329eb711ca Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 19 Sep 2021 21:13:07 +0300 Subject: [PATCH 118/132] Refactor buffer builders to suit new discoverability pattern --- CHANGELOG.md | 1 + .../space/kscience/kmath/operations/ComplexDemo.kt | 4 ++-- .../kotlin/space/kscience/kmath/complex/Complex.kt | 2 ++ .../kotlin/space/kscience/kmath/operations/BigInt.kt | 10 ++++++++++ .../space/kscience/kmath/operations/numbers.kt | 12 ++++++++++++ 5 files changed, 27 insertions(+), 2 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index ec3f5252a..19b7dae32 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -39,6 +39,7 @@ - Rename `DifferentiableMstExpression` to `KotlingradExpression` - `FeatureSet` now accepts only `Feature`. It is possible to override keys and use interfaces. - Use `Symbol` factory function instead of `StringSymbol` +- New discoverability pattern: `.algebra.` ### Deprecated - Specialized `DoubleBufferAlgebra` diff --git a/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt b/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt index 8b511f961..743f05b13 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt @@ -7,13 +7,13 @@ package space.kscience.kmath.operations import space.kscience.kmath.complex.Complex import space.kscience.kmath.complex.ComplexField +import space.kscience.kmath.complex.nd import space.kscience.kmath.complex.withNd import space.kscience.kmath.nd.StructureND -import space.kscience.kmath.nd.autoNd fun main() { // 2d element - val element = ComplexField.autoNd(2, 2).produce { (i, j) -> + val element = ComplexField.nd(2, 2).produce { (i, j) -> Complex(i - j, i + j) } println(element) diff --git a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt index 08bd12205..793587492 100644 --- a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt +++ b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt @@ -203,6 +203,8 @@ public data class Complex(val re: Double, val im: Double) { } } +public val Complex.Companion.algebra: ComplexField get() = ComplexField + /** * Creates a complex number with real part equal to this real. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 02741e6ab..9797027c7 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -526,11 +526,21 @@ public fun String.parseBigInteger(): BigInt? { } } +public val BigInt.algebra: BigIntField get() = BigIntField + +@Deprecated("Use BigInt::buffer") public inline fun Buffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): Buffer = boxing(size, initializer) +public inline fun BigInt.buffer(size: Int, initializer: (Int) -> BigInt): Buffer = + Buffer.boxing(size, initializer) + +@Deprecated("Use BigInt::mutableBuffer") public inline fun MutableBuffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): MutableBuffer = boxing(size, initializer) +public inline fun BigInt.mutableBuffer(size: Int, initializer: (Int) -> BigInt): Buffer = + Buffer.boxing(size, initializer) + public fun BigIntField.nd(vararg shape: Int): BufferedRingND = BufferedRingND(shape, BigIntField, Buffer.Companion::bigInt) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt index e75d815cf..c90553aaa 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt @@ -107,6 +107,8 @@ public object DoubleField : ExtendedField, Norm, ScaleOp override inline fun Double.div(b: Double): Double = this / b } +public val Double.Companion.algebra: DoubleField get() = DoubleField + /** * A field for [Float] without boxing. Does not produce appropriate field element. */ @@ -158,6 +160,8 @@ public object FloatField : ExtendedField, Norm { override inline fun Float.div(b: Float): Float = this / b } +public val Float.Companion.algebra: FloatField get() = FloatField + /** * A field for [Int] without boxing. Does not produce corresponding ring element. */ @@ -180,6 +184,8 @@ public object IntRing : Ring, Norm, NumericAlgebra { override inline fun Int.times(b: Int): Int = this * b } +public val Int.Companion.algebra: IntRing get() = IntRing + /** * A field for [Short] without boxing. Does not produce appropriate ring element. */ @@ -202,6 +208,8 @@ public object ShortRing : Ring, Norm, NumericAlgebra override inline fun Short.times(b: Short): Short = (this * b).toShort() } +public val Short.Companion.algebra: ShortRing get() = ShortRing + /** * A field for [Byte] without boxing. Does not produce appropriate ring element. */ @@ -224,6 +232,8 @@ public object ByteRing : Ring, Norm, NumericAlgebra { override inline fun Byte.times(b: Byte): Byte = (this * b).toByte() } +public val Byte.Companion.algebra: ByteRing get() = ByteRing + /** * A field for [Double] without boxing. Does not produce appropriate ring element. */ @@ -245,3 +255,5 @@ public object LongRing : Ring, Norm, NumericAlgebra { override inline fun Long.minus(b: Long): Long = (this - b) override inline fun Long.times(b: Long): Long = (this * b) } + +public val Long.Companion.algebra: LongRing get() = LongRing From 9fcc1b3af27ad348b44d6fc073d9cef832f7786b Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sun, 19 Sep 2021 21:17:26 +0300 Subject: [PATCH 119/132] Split Buffer.kt for better readability --- .../kscience/kmath/structures/ArrayBuffer.kt | 32 ++++ .../space/kscience/kmath/structures/Buffer.kt | 164 ------------------ .../kscience/kmath/structures/ListBuffer.kt | 58 +++++++ .../kmath/structures/MutableBuffer.kt | 97 +++++++++++ 4 files changed, 187 insertions(+), 164 deletions(-) create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ArrayBuffer.kt create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ListBuffer.kt create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MutableBuffer.kt diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ArrayBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ArrayBuffer.kt new file mode 100644 index 000000000..d49f70355 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ArrayBuffer.kt @@ -0,0 +1,32 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. + */ + +package space.kscience.kmath.structures + +/** + * [MutableBuffer] implementation over [Array]. + * + * @param T the type of elements contained in the buffer. + * @property array The underlying array. + */ +public class ArrayBuffer(internal val array: Array) : MutableBuffer { + // Can't inline because array is invariant + override val size: Int get() = array.size + + override operator fun get(index: Int): T = array[index] + + override operator fun set(index: Int, value: T) { + array[index] = value + } + + override operator fun iterator(): Iterator = array.iterator() + override fun copy(): MutableBuffer = ArrayBuffer(array.copyOf()) +} + + +/** + * Returns an [ArrayBuffer] that wraps the original array. + */ +public fun Array.asBuffer(): ArrayBuffer = ArrayBuffer(this) \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt index 6a97d18c2..c22a4ba39 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt @@ -98,170 +98,6 @@ public interface Buffer { */ public val Buffer<*>.indices: IntRange get() = 0 until size -/** - * A generic mutable random-access structure for both primitives and objects. - * - * @param T the type of elements contained in the buffer. - */ -public interface MutableBuffer : Buffer { - /** - * Sets the array element at the specified [index] to the specified [value]. - */ - public operator fun set(index: Int, value: T) - - /** - * Returns a shallow copy of the buffer. - */ - public fun copy(): MutableBuffer - - public companion object { - /** - * Creates a [DoubleBuffer] with the specified [size], where each element is calculated by calling the specified - * [initializer] function. - */ - public inline fun double(size: Int, initializer: (Int) -> Double): DoubleBuffer = - DoubleBuffer(size, initializer) - - /** - * Creates a [ShortBuffer] with the specified [size], where each element is calculated by calling the specified - * [initializer] function. - */ - public inline fun short(size: Int, initializer: (Int) -> Short): ShortBuffer = - ShortBuffer(size, initializer) - - /** - * Creates a [IntBuffer] with the specified [size], where each element is calculated by calling the specified - * [initializer] function. - */ - public inline fun int(size: Int, initializer: (Int) -> Int): IntBuffer = - IntBuffer(size, initializer) - - /** - * Creates a [LongBuffer] with the specified [size], where each element is calculated by calling the specified - * [initializer] function. - */ - public inline fun long(size: Int, initializer: (Int) -> Long): LongBuffer = - LongBuffer(size, initializer) - - - /** - * Creates a [FloatBuffer] with the specified [size], where each element is calculated by calling the specified - * [initializer] function. - */ - public inline fun float(size: Int, initializer: (Int) -> Float): FloatBuffer = - FloatBuffer(size, initializer) - - - /** - * Create a boxing mutable buffer of given type - */ - public inline fun boxing(size: Int, initializer: (Int) -> T): MutableBuffer = - MutableListBuffer(MutableList(size, initializer)) - - /** - * Creates a [MutableBuffer] of given [type]. If the type is primitive, specialized buffers are used - * ([IntBuffer], [DoubleBuffer], etc.), [ListBuffer] is returned otherwise. - * - * The [size] is specified, and each element is calculated by calling the specified [initializer] function. - */ - @Suppress("UNCHECKED_CAST") - public inline fun auto(type: KClass, size: Int, initializer: (Int) -> T): MutableBuffer = - when (type) { - Double::class -> double(size) { initializer(it) as Double } as MutableBuffer - Short::class -> short(size) { initializer(it) as Short } as MutableBuffer - Int::class -> int(size) { initializer(it) as Int } as MutableBuffer - Float::class -> float(size) { initializer(it) as Float } as MutableBuffer - Long::class -> long(size) { initializer(it) as Long } as MutableBuffer - else -> boxing(size, initializer) - } - - /** - * Creates a [MutableBuffer] of given type [T]. If the type is primitive, specialized buffers are used - * ([IntBuffer], [DoubleBuffer], etc.), [ListBuffer] is returned otherwise. - * - * The [size] is specified, and each element is calculated by calling the specified [initializer] function. - */ - @Suppress("UNCHECKED_CAST") - public inline fun auto(size: Int, initializer: (Int) -> T): MutableBuffer = - auto(T::class, size, initializer) - } -} - -/** - * [Buffer] implementation over [List]. - * - * @param T the type of elements contained in the buffer. - * @property list The underlying list. - */ -public class ListBuffer(public val list: List) : Buffer { - - public constructor(size: Int, initializer: (Int) -> T) : this(List(size, initializer)) - - override val size: Int get() = list.size - - override operator fun get(index: Int): T = list[index] - override operator fun iterator(): Iterator = list.iterator() -} - -/** - * Returns an [ListBuffer] that wraps the original list. - */ -public fun List.asBuffer(): ListBuffer = ListBuffer(this) - -/** - * [MutableBuffer] implementation over [MutableList]. - * - * @param T the type of elements contained in the buffer. - * @property list The underlying list. - */ -@JvmInline -public value class MutableListBuffer(public val list: MutableList) : MutableBuffer { - - public constructor(size: Int, initializer: (Int) -> T) : this(MutableList(size, initializer)) - - override val size: Int get() = list.size - - override operator fun get(index: Int): T = list[index] - - override operator fun set(index: Int, value: T) { - list[index] = value - } - - override operator fun iterator(): Iterator = list.iterator() - override fun copy(): MutableBuffer = MutableListBuffer(ArrayList(list)) -} - -/** - * Returns an [MutableListBuffer] that wraps the original list. - */ -public fun MutableList.asMutableBuffer(): MutableListBuffer = MutableListBuffer(this) - -/** - * [MutableBuffer] implementation over [Array]. - * - * @param T the type of elements contained in the buffer. - * @property array The underlying array. - */ -public class ArrayBuffer(internal val array: Array) : MutableBuffer { - // Can't inline because array is invariant - override val size: Int get() = array.size - - override operator fun get(index: Int): T = array[index] - - override operator fun set(index: Int, value: T) { - array[index] = value - } - - override operator fun iterator(): Iterator = array.iterator() - override fun copy(): MutableBuffer = ArrayBuffer(array.copyOf()) -} - - -/** - * Returns an [ArrayBuffer] that wraps the original array. - */ -public fun Array.asBuffer(): ArrayBuffer = ArrayBuffer(this) - /** * Immutable wrapper for [MutableBuffer]. * diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ListBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ListBuffer.kt new file mode 100644 index 000000000..fdba68d19 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ListBuffer.kt @@ -0,0 +1,58 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. + */ + +package space.kscience.kmath.structures + +import kotlin.jvm.JvmInline + +/** + * [Buffer] implementation over [List]. + * + * @param T the type of elements contained in the buffer. + * @property list The underlying list. + */ +public class ListBuffer(public val list: List) : Buffer { + + public constructor(size: Int, initializer: (Int) -> T) : this(List(size, initializer)) + + override val size: Int get() = list.size + + override operator fun get(index: Int): T = list[index] + override operator fun iterator(): Iterator = list.iterator() +} + + +/** + * Returns an [ListBuffer] that wraps the original list. + */ +public fun List.asBuffer(): ListBuffer = ListBuffer(this) + +/** + * [MutableBuffer] implementation over [MutableList]. + * + * @param T the type of elements contained in the buffer. + * @property list The underlying list. + */ +@JvmInline +public value class MutableListBuffer(public val list: MutableList) : MutableBuffer { + + public constructor(size: Int, initializer: (Int) -> T) : this(MutableList(size, initializer)) + + override val size: Int get() = list.size + + override operator fun get(index: Int): T = list[index] + + override operator fun set(index: Int, value: T) { + list[index] = value + } + + override operator fun iterator(): Iterator = list.iterator() + override fun copy(): MutableBuffer = MutableListBuffer(ArrayList(list)) +} + +/** + * Returns an [MutableListBuffer] that wraps the original list. + */ +public fun MutableList.asMutableBuffer(): MutableListBuffer = MutableListBuffer(this) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MutableBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MutableBuffer.kt new file mode 100644 index 000000000..97185b918 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MutableBuffer.kt @@ -0,0 +1,97 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. + */ + +package space.kscience.kmath.structures + +import kotlin.reflect.KClass + +/** + * A generic mutable random-access structure for both primitives and objects. + * + * @param T the type of elements contained in the buffer. + */ +public interface MutableBuffer : Buffer { + /** + * Sets the array element at the specified [index] to the specified [value]. + */ + public operator fun set(index: Int, value: T) + + /** + * Returns a shallow copy of the buffer. + */ + public fun copy(): MutableBuffer + + public companion object { + /** + * Creates a [DoubleBuffer] with the specified [size], where each element is calculated by calling the specified + * [initializer] function. + */ + public inline fun double(size: Int, initializer: (Int) -> Double): DoubleBuffer = + DoubleBuffer(size, initializer) + + /** + * Creates a [ShortBuffer] with the specified [size], where each element is calculated by calling the specified + * [initializer] function. + */ + public inline fun short(size: Int, initializer: (Int) -> Short): ShortBuffer = + ShortBuffer(size, initializer) + + /** + * Creates a [IntBuffer] with the specified [size], where each element is calculated by calling the specified + * [initializer] function. + */ + public inline fun int(size: Int, initializer: (Int) -> Int): IntBuffer = + IntBuffer(size, initializer) + + /** + * Creates a [LongBuffer] with the specified [size], where each element is calculated by calling the specified + * [initializer] function. + */ + public inline fun long(size: Int, initializer: (Int) -> Long): LongBuffer = + LongBuffer(size, initializer) + + + /** + * Creates a [FloatBuffer] with the specified [size], where each element is calculated by calling the specified + * [initializer] function. + */ + public inline fun float(size: Int, initializer: (Int) -> Float): FloatBuffer = + FloatBuffer(size, initializer) + + + /** + * Create a boxing mutable buffer of given type + */ + public inline fun boxing(size: Int, initializer: (Int) -> T): MutableBuffer = + MutableListBuffer(MutableList(size, initializer)) + + /** + * Creates a [MutableBuffer] of given [type]. If the type is primitive, specialized buffers are used + * ([IntBuffer], [DoubleBuffer], etc.), [ListBuffer] is returned otherwise. + * + * The [size] is specified, and each element is calculated by calling the specified [initializer] function. + */ + @Suppress("UNCHECKED_CAST") + public inline fun auto(type: KClass, size: Int, initializer: (Int) -> T): MutableBuffer = + when (type) { + Double::class -> double(size) { initializer(it) as Double } as MutableBuffer + Short::class -> short(size) { initializer(it) as Short } as MutableBuffer + Int::class -> int(size) { initializer(it) as Int } as MutableBuffer + Float::class -> float(size) { initializer(it) as Float } as MutableBuffer + Long::class -> long(size) { initializer(it) as Long } as MutableBuffer + else -> boxing(size, initializer) + } + + /** + * Creates a [MutableBuffer] of given type [T]. If the type is primitive, specialized buffers are used + * ([IntBuffer], [DoubleBuffer], etc.), [ListBuffer] is returned otherwise. + * + * The [size] is specified, and each element is calculated by calling the specified [initializer] function. + */ + @Suppress("UNCHECKED_CAST") + public inline fun auto(size: Int, initializer: (Int) -> T): MutableBuffer = + auto(T::class, size, initializer) + } +} \ No newline at end of file From 89eebbecb76280586f39646bc08cf6a6975bdae7 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Tue, 21 Sep 2021 21:24:27 +0300 Subject: [PATCH 120/132] Fix EJML inversion issue --- CHANGELOG.md | 1 + benchmarks/build.gradle.kts | 10 +++++ .../kscience/kmath/benchmarks/DotBenchmark.kt | 11 +++-- .../benchmarks/MatrixInverseBenchmark.kt | 15 ++++--- .../kmath/benchmarks/NDFieldBenchmark.kt | 10 +++-- .../kmath/benchmarks/ViktorBenchmark.kt | 8 ++-- .../kmath/benchmarks/ViktorLogBenchmark.kt | 8 ++-- .../kmath/functions/matrixIntegration.kt | 8 ++-- .../kscience/kmath/operations/ComplexDemo.kt | 31 -------------- .../kscience/kmath/operations/complexDemo.kt | 41 +++++++++++++++++++ .../kscience/kmath/structures/ComplexND.kt | 8 ++-- .../kscience/kmath/structures/NDField.kt | 10 ++--- .../kscience/kmath/structures/buffers.kt | 4 +- .../kscience/kmath/commons/linear/CMMatrix.kt | 6 ++- .../kscience/kmath/commons/linear/CMSolver.kt | 12 +++--- .../kscience/kmath/complex/ComplexFieldND.kt | 9 +++- .../kmath/linear/BufferedLinearSpace.kt | 19 +++++---- .../kscience/kmath/linear/LinearSpace.kt | 21 ++++++---- .../kscience/kmath/linear/LupDecomposition.kt | 6 +-- .../kscience/kmath/linear/MatrixWrapper.kt | 9 ++-- .../kscience/kmath/nd/BufferAlgebraND.kt | 20 ++++----- .../space/kscience/kmath/nd/DoubleFieldND.kt | 4 +- .../space/kscience/kmath/nd/ShortRingND.kt | 2 +- .../space/kscience/kmath/nd/Structure1D.kt | 6 ++- .../space/kscience/kmath/nd/Structure2D.kt | 2 - .../space/kscience/kmath/nd/StructureND.kt | 23 +++++++++-- .../kmath/operations/BufferAlgebra.kt | 24 +++++++---- .../kscience/kmath/structures/ArrayBuffer.kt | 2 + .../space/kscience/kmath/structures/Buffer.kt | 7 ++++ .../kmath/structures/BufferAccessor2D.kt | 2 + .../kmath/structures/FlaggedBuffer.kt | 8 +++- .../kscience/kmath/structures/ListBuffer.kt | 2 + .../kscience/kmath/structures/MemoryBuffer.kt | 2 + .../kscience/kmath/structures/NDFieldTest.kt | 6 +-- .../kmath/structures/NumberNDFieldTest.kt | 6 +-- .../kscience/kmath/streaming/RingBuffer.kt | 2 + .../kscience/kmath/ejml/EjmlLinearSpace.kt | 6 +++ .../kscience/kmath/ejml/EjmlMatrixTest.kt | 25 +++++++++-- .../space/kscience/kmath/real/RealMatrix.kt | 37 +++++++++-------- .../kotlin/space/kscience/kmath/real/dot.kt | 5 ++- .../kmath/integration/SplineIntegrator.kt | 2 + .../kmath/histogram/DoubleHistogramSpace.kt | 2 +- .../kscience/kmath/viktor/ViktorBuffer.kt | 6 ++- 43 files changed, 284 insertions(+), 164 deletions(-) delete mode 100644 examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt create mode 100644 examples/src/main/kotlin/space/kscience/kmath/operations/complexDemo.kt diff --git a/CHANGELOG.md b/CHANGELOG.md index 19b7dae32..c27dafeb4 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -40,6 +40,7 @@ - `FeatureSet` now accepts only `Feature`. It is possible to override keys and use interfaces. - Use `Symbol` factory function instead of `StringSymbol` - New discoverability pattern: `.algebra.` +- Adjusted commons-math API for linear solvers to match conventions. ### Deprecated - Specialized `DoubleBufferAlgebra` diff --git a/benchmarks/build.gradle.kts b/benchmarks/build.gradle.kts index d96c5a8b6..fa72dc8ee 100644 --- a/benchmarks/build.gradle.kts +++ b/benchmarks/build.gradle.kts @@ -105,6 +105,16 @@ benchmark { commonConfiguration() include("JafamaBenchmark") } + + configurations.register("viktor") { + commonConfiguration() + include("ViktorBenchmark") + } + + configurations.register("viktorLog") { + commonConfiguration() + include("ViktorLogBenchmark") + } } // Fix kotlinx-benchmarks bug diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt index 7806cd06c..6373d1ce5 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt @@ -13,7 +13,10 @@ import space.kscience.kmath.commons.linear.CMLinearSpace import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.invoke +import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.algebra +import space.kscience.kmath.structures.Buffer import kotlin.random.Random @State(Scope.Benchmark) @@ -35,7 +38,7 @@ internal class DotBenchmark { @Benchmark fun cmDot(blackhole: Blackhole) { - CMLinearSpace.run { + CMLinearSpace { blackhole.consume(cmMatrix1 dot cmMatrix2) } } @@ -56,14 +59,14 @@ internal class DotBenchmark { @Benchmark fun bufferedDot(blackhole: Blackhole) { - LinearSpace.auto(DoubleField).invoke { + with(DoubleField.linearSpace(Buffer.Companion::auto)) { blackhole.consume(matrix1 dot matrix2) } } @Benchmark - fun realDot(blackhole: Blackhole) { - LinearSpace.double { + fun doubleDot(blackhole: Blackhole) { + with(Double.algebra.linearSpace) { blackhole.consume(matrix1 dot matrix2) } } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt index 21d7ca41c..5d331af9a 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt @@ -10,13 +10,12 @@ import kotlinx.benchmark.Blackhole import kotlinx.benchmark.Scope import kotlinx.benchmark.State import space.kscience.kmath.commons.linear.CMLinearSpace -import space.kscience.kmath.commons.linear.inverse +import space.kscience.kmath.commons.linear.lupSolver import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM -import space.kscience.kmath.linear.InverseMatrixFeature -import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.invoke +import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.linear.lupSolver -import space.kscience.kmath.nd.getFeature +import space.kscience.kmath.operations.algebra import kotlin.random.Random @State(Scope.Benchmark) @@ -25,7 +24,7 @@ internal class MatrixInverseBenchmark { private val random = Random(1224) private const val dim = 100 - private val space = LinearSpace.double + private val space = Double.algebra.linearSpace //creating invertible matrix private val u = space.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } @@ -35,20 +34,20 @@ internal class MatrixInverseBenchmark { @Benchmark fun kmathLupInversion(blackhole: Blackhole) { - blackhole.consume(LinearSpace.double.lupSolver().inverse(matrix)) + blackhole.consume(Double.algebra.linearSpace.lupSolver().inverse(matrix)) } @Benchmark fun cmLUPInversion(blackhole: Blackhole) { CMLinearSpace { - blackhole.consume(inverse(matrix)) + blackhole.consume(lupSolver().inverse(matrix)) } } @Benchmark fun ejmlInverse(blackhole: Blackhole) { EjmlLinearSpaceDDRM { - blackhole.consume(matrix.getFeature>()?.inverse) + blackhole.consume(matrix.toEjml().inverse()) } } } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt index fbf4bdaba..f72bc3ba0 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt @@ -9,7 +9,9 @@ import kotlinx.benchmark.Benchmark import kotlinx.benchmark.Blackhole import kotlinx.benchmark.Scope import kotlinx.benchmark.State -import space.kscience.kmath.nd.* +import space.kscience.kmath.nd.StructureND +import space.kscience.kmath.nd.autoNdAlgebra +import space.kscience.kmath.nd.ndAlgebra import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.structures.Buffer @@ -46,8 +48,8 @@ internal class NDFieldBenchmark { private companion object { private const val dim = 1000 private const val n = 100 - private val autoField = DoubleField.autoNd(dim, dim) - private val specializedField = DoubleField.nd(dim, dim) - private val genericField = DoubleField.nd(Buffer.Companion::boxing, dim, dim) + private val autoField = DoubleField.autoNdAlgebra(dim, dim) + private val specializedField = DoubleField.ndAlgebra(dim, dim) + private val genericField = DoubleField.ndAlgebra(Buffer.Companion::boxing, dim, dim) } } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt index 6ea64ba3c..b97a05a52 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt @@ -11,8 +11,8 @@ import kotlinx.benchmark.Scope import kotlinx.benchmark.State import org.jetbrains.bio.viktor.F64Array import space.kscience.kmath.nd.StructureND -import space.kscience.kmath.nd.autoNd -import space.kscience.kmath.nd.nd +import space.kscience.kmath.nd.autoNdAlgebra +import space.kscience.kmath.nd.ndAlgebra import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.viktor.ViktorNDField @@ -58,8 +58,8 @@ internal class ViktorBenchmark { private const val n = 100 // automatically build context most suited for given type. - private val autoField = DoubleField.autoNd(dim, dim) - private val realField = DoubleField.nd(dim, dim) + private val autoField = DoubleField.autoNdAlgebra(dim, dim) + private val realField = DoubleField.ndAlgebra(dim, dim) private val viktorField = ViktorNDField(dim, dim) } } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt index afe44ea99..91e9dcd76 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt @@ -10,8 +10,8 @@ import kotlinx.benchmark.Blackhole import kotlinx.benchmark.Scope import kotlinx.benchmark.State import org.jetbrains.bio.viktor.F64Array -import space.kscience.kmath.nd.autoNd -import space.kscience.kmath.nd.nd +import space.kscience.kmath.nd.autoNdAlgebra +import space.kscience.kmath.nd.ndAlgebra import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.viktor.ViktorFieldND @@ -50,8 +50,8 @@ internal class ViktorLogBenchmark { private const val n = 100 // automatically build context most suited for given type. - private val autoField = DoubleField.autoNd(dim, dim) - private val realNdField = DoubleField.nd(dim, dim) + private val autoField = DoubleField.autoNdAlgebra(dim, dim) + private val realNdField = DoubleField.ndAlgebra(dim, dim) private val viktorField = ViktorFieldND(intArrayOf(dim, dim)) } } diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt index d932fdb9f..93b5671fe 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt @@ -9,12 +9,12 @@ import space.kscience.kmath.integration.gaussIntegrator import space.kscience.kmath.integration.integrate import space.kscience.kmath.integration.value import space.kscience.kmath.nd.StructureND -import space.kscience.kmath.nd.withNd -import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.nd.withNdAlgebra +import space.kscience.kmath.operations.algebra import space.kscience.kmath.operations.invoke -fun main(): Unit = DoubleField { - withNd(2, 2) { +fun main(): Unit = Double.algebra { + withNdAlgebra(2, 2) { //Produce a diagonal StructureND fun diagonal(v: Double) = produce { (i, j) -> diff --git a/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt b/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt deleted file mode 100644 index 743f05b13..000000000 --- a/examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt +++ /dev/null @@ -1,31 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. - */ - -package space.kscience.kmath.operations - -import space.kscience.kmath.complex.Complex -import space.kscience.kmath.complex.ComplexField -import space.kscience.kmath.complex.nd -import space.kscience.kmath.complex.withNd -import space.kscience.kmath.nd.StructureND - -fun main() { - // 2d element - val element = ComplexField.nd(2, 2).produce { (i, j) -> - Complex(i - j, i + j) - } - println(element) - - // 1d element operation - val result: StructureND = ComplexField.withNd(8) { - val a = produce { (it) -> i * it - it.toDouble() } - val b = 3 - val c = Complex(1.0, 1.0) - - (a pow b) + c - } - - println(result) -} diff --git a/examples/src/main/kotlin/space/kscience/kmath/operations/complexDemo.kt b/examples/src/main/kotlin/space/kscience/kmath/operations/complexDemo.kt new file mode 100644 index 000000000..319221bcc --- /dev/null +++ b/examples/src/main/kotlin/space/kscience/kmath/operations/complexDemo.kt @@ -0,0 +1,41 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. + */ + +package space.kscience.kmath.operations + +import space.kscience.kmath.complex.Complex +import space.kscience.kmath.complex.algebra +import space.kscience.kmath.complex.bufferAlgebra +import space.kscience.kmath.complex.ndAlgebra +import space.kscience.kmath.nd.BufferND +import space.kscience.kmath.nd.StructureND + +fun main() = Complex.algebra { + val complex = 2 + 2 * i + println(complex * 8 - 5 * i) + + //flat buffer + val buffer = bufferAlgebra(8).run { + buffer { Complex(it, -it) }.map { Complex(it.im, it.re) } + } + println(buffer) + + + // 2d element + val element: BufferND = ndAlgebra(2, 2).produce { (i, j) -> + Complex(i - j, i + j) + } + println(element) + + // 1d element operation + val result: StructureND = ndAlgebra(8).run { + val a = produce { (it) -> i * it - it.toDouble() } + val b = 3 + val c = Complex(1.0, 1.0) + + (a pow b) + c + } + println(result) +} diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt index c591f5682..d4554b3ba 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt @@ -11,7 +11,7 @@ import space.kscience.kmath.complex.* import space.kscience.kmath.linear.transpose import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.as2D -import space.kscience.kmath.nd.nd +import space.kscience.kmath.nd.ndAlgebra import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke import kotlin.system.measureTimeMillis @@ -20,8 +20,8 @@ fun main() { val dim = 1000 val n = 1000 - val realField = DoubleField.nd(dim, dim) - val complexField: ComplexFieldND = ComplexField.nd(dim, dim) + val realField = DoubleField.ndAlgebra(dim, dim) + val complexField: ComplexFieldND = ComplexField.ndAlgebra(dim, dim) val realTime = measureTimeMillis { realField { @@ -49,7 +49,7 @@ fun main() { fun complexExample() { //Create a context for 2-d structure with complex values ComplexField { - withNd(4, 8) { + withNdAlgebra(4, 8) { //a constant real-valued structure val x = one * 2.5 operator fun Number.plus(other: Complex) = Complex(this.toDouble() + other.re, other.im) diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt index c9cafbba8..5b0e2eb30 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt @@ -9,8 +9,8 @@ import kotlinx.coroutines.DelicateCoroutinesApi import kotlinx.coroutines.GlobalScope import org.nd4j.linalg.factory.Nd4j import space.kscience.kmath.nd.StructureND -import space.kscience.kmath.nd.autoNd -import space.kscience.kmath.nd.nd +import space.kscience.kmath.nd.autoNdAlgebra +import space.kscience.kmath.nd.ndAlgebra import space.kscience.kmath.nd4j.Nd4jArrayField import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke @@ -33,11 +33,11 @@ fun main() { val n = 1000 // automatically build context most suited for given type. - val autoField = DoubleField.autoNd(dim, dim) + val autoField = DoubleField.autoNdAlgebra(dim, dim) // specialized nd-field for Double. It works as generic Double field as well. - val realField = DoubleField.nd(dim, dim) + val realField = DoubleField.ndAlgebra(dim, dim) //A generic boxing field. It should be used for objects, not primitives. - val boxingField = DoubleField.nd(Buffer.Companion::boxing, dim, dim) + val boxingField = DoubleField.ndAlgebra(Buffer.Companion::boxing, dim, dim) // Nd4j specialized field. val nd4jField = Nd4jArrayField.real(dim, dim) //viktor field diff --git a/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt b/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt index 0f7fdc46a..d78141507 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/structures/buffers.kt @@ -6,8 +6,8 @@ package space.kscience.kmath.structures import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.buffer import space.kscience.kmath.operations.bufferAlgebra -import space.kscience.kmath.operations.produce inline fun MutableBuffer.Companion.same( n: Int, @@ -17,6 +17,6 @@ inline fun MutableBuffer.Companion.same( fun main() { with(DoubleField.bufferAlgebra(5)) { - println(number(2.0) + produce(1, 2, 3, 4, 5)) + println(number(2.0) + buffer(1, 2, 3, 4, 5)) } } diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt index 7defd6841..14e7fc365 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt @@ -10,6 +10,7 @@ import space.kscience.kmath.linear.* import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureFeature import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer import kotlin.reflect.KClass import kotlin.reflect.cast @@ -21,12 +22,15 @@ public class CMMatrix(public val origin: RealMatrix) : Matrix { override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j) } -public class CMVector(public val origin: RealVector) : Point { +@JvmInline +public value class CMVector(public val origin: RealVector) : Point { override val size: Int get() = origin.dimension override operator fun get(index: Int): Double = origin.getEntry(index) override operator fun iterator(): Iterator = origin.toArray().iterator() + + override fun toString(): String = Buffer.toString(this) } public fun RealVector.toPoint(): CMVector = CMVector(this) diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt index b9fbc07ae..d1fb441b0 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt @@ -18,7 +18,7 @@ public enum class CMDecomposition { CHOLESKY } -public fun CMLinearSpace.solver( +private fun CMLinearSpace.solver( a: Matrix, decomposition: CMDecomposition = CMDecomposition.LUP, ): DecompositionSolver = when (decomposition) { @@ -48,9 +48,11 @@ public fun CMLinearSpace.inverse( public fun CMLinearSpace.solver(decomposition: CMDecomposition): LinearSolver = object : LinearSolver { - override fun solve(a: Matrix, b: Matrix): Matrix = solve(a, b, decomposition) + override fun solve(a: Matrix, b: Matrix): Matrix = solver(a, decomposition).solve(b.toCM().origin).wrap() - override fun solve(a: Matrix, b: Point): Point = solve(a, b, decomposition) + override fun solve(a: Matrix, b: Point): Point = solver(a, decomposition).solve(b.toCM().origin).toPoint() - override fun inverse(matrix: Matrix): Matrix = inverse(matrix, decomposition) -} \ No newline at end of file + override fun inverse(matrix: Matrix): Matrix = solver(matrix, decomposition).inverse.wrap() +} + +public fun CMLinearSpace.lupSolver(): LinearSolver = solver((CMDecomposition.LUP)) \ No newline at end of file diff --git a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt index 41bcb83df..29e790d16 100644 --- a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt +++ b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt @@ -9,8 +9,10 @@ import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.BufferND import space.kscience.kmath.nd.BufferedFieldND import space.kscience.kmath.nd.StructureND +import space.kscience.kmath.operations.BufferField import space.kscience.kmath.operations.ExtendedField import space.kscience.kmath.operations.NumbersAddOperations +import space.kscience.kmath.operations.bufferAlgebra import space.kscience.kmath.structures.Buffer import kotlin.contracts.InvocationKind import kotlin.contracts.contract @@ -111,13 +113,16 @@ public inline fun BufferedFieldND.produceInline(initializ return BufferND(strides, buffer) } +@UnstableKMathAPI +public fun ComplexField.bufferAlgebra(size: Int): BufferField = + bufferAlgebra(Buffer.Companion::complex, size) -public fun ComplexField.nd(vararg shape: Int): ComplexFieldND = ComplexFieldND(shape) +public fun ComplexField.ndAlgebra(vararg shape: Int): ComplexFieldND = ComplexFieldND(shape) /** * Produce a context for n-dimensional operations inside this real field */ -public inline fun ComplexField.withNd(vararg shape: Int, action: ComplexFieldND.() -> R): R { +public inline fun ComplexField.withNdAlgebra(vararg shape: Int, action: ComplexFieldND.() -> R): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } return ComplexFieldND(shape).action() } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt index 14235515c..5f17de607 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt @@ -8,17 +8,15 @@ package space.kscience.kmath.linear import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.BufferedRingND import space.kscience.kmath.nd.as2D -import space.kscience.kmath.nd.nd +import space.kscience.kmath.nd.ndAlgebra import space.kscience.kmath.nd.unwrap +import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Ring import space.kscience.kmath.operations.invoke -import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.BufferFactory -import space.kscience.kmath.structures.VirtualBuffer -import space.kscience.kmath.structures.indices +import space.kscience.kmath.structures.* -public class BufferedLinearSpace>( +public class BufferedLinearSpace>( override val elementAlgebra: A, private val bufferFactory: BufferFactory, ) : LinearSpace { @@ -26,7 +24,7 @@ public class BufferedLinearSpace>( private fun ndRing( rows: Int, cols: Int, - ): BufferedRingND = elementAlgebra.nd(bufferFactory, rows, cols) + ): BufferedRingND = elementAlgebra.ndAlgebra(bufferFactory, rows, cols) override fun buildMatrix(rows: Int, columns: Int, initializer: A.(i: Int, j: Int) -> T): Matrix = ndRing(rows, columns).produce { (i, j) -> elementAlgebra.initializer(i, j) }.as2D() @@ -92,3 +90,10 @@ public class BufferedLinearSpace>( unwrap().map { it * value }.as2D() } } + + +public fun > A.linearSpace(bufferFactory: BufferFactory): BufferedLinearSpace = + BufferedLinearSpace(this, bufferFactory) + +public val DoubleField.linearSpace: BufferedLinearSpace + get() = BufferedLinearSpace(this, ::DoubleBuffer) \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt index e94e984b3..1d8985b59 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt @@ -6,8 +6,13 @@ package space.kscience.kmath.linear import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.nd.* -import space.kscience.kmath.operations.* +import space.kscience.kmath.nd.MutableStructure2D +import space.kscience.kmath.nd.Structure2D +import space.kscience.kmath.nd.StructureFeature +import space.kscience.kmath.nd.as1D +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.Ring +import space.kscience.kmath.operations.invoke import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.BufferFactory import space.kscience.kmath.structures.DoubleBuffer @@ -34,7 +39,7 @@ public typealias Point = Buffer * @param T the type of items in the matrices. * @param A the type of ring over [T]. */ -public interface LinearSpace> { +public interface LinearSpace> { public val elementAlgebra: A /** @@ -172,7 +177,8 @@ public interface LinearSpace> { * @return a feature object or `null` if it isn't present. */ @UnstableKMathAPI - public fun computeFeature(structure: Matrix, type: KClass): F? = structure.getFeature(type) + public fun computeFeature(structure: Matrix, type: KClass): F? = + structure.getFeature(type) public companion object { @@ -184,6 +190,7 @@ public interface LinearSpace> { bufferFactory: BufferFactory = Buffer.Companion::boxing, ): LinearSpace = BufferedLinearSpace(algebra, bufferFactory) + @Deprecated("use DoubleField.linearSpace") public val double: LinearSpace = buffered(DoubleField, ::DoubleBuffer) /** @@ -213,10 +220,8 @@ public inline operator fun , R> LS.invoke(block: LS.() -> * Convert matrix to vector if it is possible. */ public fun Matrix.asVector(): Point = - if (this.colNum == 1) - as1D() - else - error("Can't convert matrix with more than one column to vector") + if (this.colNum == 1) as1D() + else error("Can't convert matrix with more than one column to vector") /** * Creates an n × 1 [VirtualMatrix], where n is the size of the given buffer. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt index 34fc661ed..95dd6d45c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt @@ -5,9 +5,7 @@ package space.kscience.kmath.linear -import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.nd.getFeature import space.kscience.kmath.operations.* import space.kscience.kmath.structures.BufferAccessor2D import space.kscience.kmath.structures.DoubleBuffer @@ -214,7 +212,6 @@ internal fun LupDecomposition.solve( /** * Produce a generic solver based on LUP decomposition */ -@PerformancePitfall() @OptIn(UnstableKMathAPI::class) public fun , F : Field> LinearSpace.lupSolver( bufferFactory: MutableBufferFactory, @@ -222,13 +219,12 @@ public fun , F : Field> LinearSpace.lupSolver( ): LinearSolver = object : LinearSolver { override fun solve(a: Matrix, b: Matrix): Matrix { // Use existing decomposition if it is provided by matrix - val decomposition = a.getFeature() ?: lup(bufferFactory, a, singularityCheck) + val decomposition = computeFeature(a) ?: lup(bufferFactory, a, singularityCheck) return decomposition.solve(bufferFactory, b) } override fun inverse(matrix: Matrix): Matrix = solve(matrix, one(matrix.rowNum, matrix.colNum)) } -@PerformancePitfall public fun LinearSpace.lupSolver(singularityThreshold: Double = 1e-11): LinearSolver = lupSolver(::DoubleBuffer) { it < singularityThreshold } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt index 3ba4e8648..a40c0384c 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt @@ -8,7 +8,6 @@ package space.kscience.kmath.linear import space.kscience.kmath.misc.FeatureSet import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureFeature -import space.kscience.kmath.nd.getFeature import space.kscience.kmath.operations.Ring import kotlin.reflect.KClass @@ -26,7 +25,6 @@ public class MatrixWrapper internal constructor( * Get the first feature matching given class. Does not guarantee that matrix has only one feature matching the * criteria. */ - @UnstableKMathAPI @Suppress("UNCHECKED_CAST") override fun getFeature(type: KClass): F? = features.getFeature(type) ?: origin.getFeature(type) @@ -90,8 +88,7 @@ public class TransposedFeature(public val original: Matrix) : Ma /** * Create a virtual transposed matrix without copying anything. `A.transpose().transpose() === A` */ +@Suppress("UNCHECKED_CAST") @OptIn(UnstableKMathAPI::class) -public fun Matrix.transpose(): Matrix = getFeature>()?.original ?: VirtualMatrix( - colNum, - rowNum, -) { i, j -> get(j, i) }.withFeature(TransposedFeature(this)) +public fun Matrix.transpose(): Matrix = getFeature(TransposedFeature::class)?.original as? Matrix + ?: VirtualMatrix(colNum, rowNum) { i, j -> get(j, i) }.withFeature(TransposedFeature(this)) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt index b01beb02d..ae72f3689 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferAlgebraND.kt @@ -87,39 +87,39 @@ public open class BufferedFieldND>( } // group factories -public fun > A.nd( +public fun > A.ndAlgebra( bufferFactory: BufferFactory, vararg shape: Int, ): BufferedGroupND = BufferedGroupND(shape, this, bufferFactory) @JvmName("withNdGroup") -public inline fun , R> A.withNd( +public inline fun , R> A.withNdAlgebra( noinline bufferFactory: BufferFactory, vararg shape: Int, action: BufferedGroupND.() -> R, ): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } - return nd(bufferFactory, *shape).run(action) + return ndAlgebra(bufferFactory, *shape).run(action) } //ring factories -public fun > A.nd( +public fun > A.ndAlgebra( bufferFactory: BufferFactory, vararg shape: Int, ): BufferedRingND = BufferedRingND(shape, this, bufferFactory) @JvmName("withNdRing") -public inline fun , R> A.withNd( +public inline fun , R> A.withNdAlgebra( noinline bufferFactory: BufferFactory, vararg shape: Int, action: BufferedRingND.() -> R, ): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } - return nd(bufferFactory, *shape).run(action) + return ndAlgebra(bufferFactory, *shape).run(action) } //field factories -public fun > A.nd( +public fun > A.ndAlgebra( bufferFactory: BufferFactory, vararg shape: Int, ): BufferedFieldND = BufferedFieldND(shape, this, bufferFactory) @@ -129,7 +129,7 @@ public fun > A.nd( */ @UnstableKMathAPI @Suppress("UNCHECKED_CAST") -public inline fun > A.autoNd( +public inline fun > A.autoNdAlgebra( vararg shape: Int, ): FieldND = when (this) { DoubleField -> DoubleFieldND(shape) as FieldND @@ -137,11 +137,11 @@ public inline fun > A.autoNd( } @JvmName("withNdField") -public inline fun , R> A.withNd( +public inline fun , R> A.withNdAlgebra( noinline bufferFactory: BufferFactory, vararg shape: Int, action: BufferedFieldND.() -> R, ): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } - return nd(bufferFactory, *shape).run(action) + return ndAlgebra(bufferFactory, *shape).run(action) } \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt index fed4aca0b..0c7d4d5d1 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/DoubleFieldND.kt @@ -103,12 +103,12 @@ public class DoubleFieldND( override fun atanh(arg: StructureND): BufferND = arg.map { atanh(it) } } -public fun DoubleField.nd(vararg shape: Int): DoubleFieldND = DoubleFieldND(shape) +public fun DoubleField.ndAlgebra(vararg shape: Int): DoubleFieldND = DoubleFieldND(shape) /** * Produce a context for n-dimensional operations inside this real field */ -public inline fun DoubleField.withNd(vararg shape: Int, action: DoubleFieldND.() -> R): R { +public inline fun DoubleField.withNdAlgebra(vararg shape: Int, action: DoubleFieldND.() -> R): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } return DoubleFieldND(shape).run(action) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt index 5b6e2cd22..b56bef230 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/ShortRingND.kt @@ -34,7 +34,7 @@ public class ShortRingND( public inline fun BufferedRingND.produceInline(crossinline initializer: ShortRing.(Int) -> Short): BufferND = BufferND(strides, ShortBuffer(ShortArray(strides.linearSize) { offset -> ShortRing.initializer(offset) })) -public inline fun ShortRing.withNd(vararg shape: Int, action: ShortRingND.() -> R): R { +public inline fun ShortRing.withNdAlgebra(vararg shape: Int, action: ShortRingND.() -> R): R { contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) } return ShortRingND(shape).run(action) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt index d0e2354d2..91cd5abe9 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt @@ -67,12 +67,14 @@ private class MutableStructure1DWrapper(val structure: MutableStructureND) structure[intArrayOf(index)] = value } - @PerformancePitfall + @OptIn(PerformancePitfall::class) override fun copy(): MutableBuffer = structure .elements() .map(Pair::second) .toMutableList() .asMutableBuffer() + + override fun toString(): String = Buffer.toString(this) } @@ -107,6 +109,8 @@ internal class MutableBuffer1DWrapper(val buffer: MutableBuffer) : Mutable } override fun copy(): MutableBuffer = buffer.copy() + + override fun toString(): String = Buffer.toString(this) } /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt index 7fb8ea251..57836a9ef 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt @@ -6,7 +6,6 @@ package space.kscience.kmath.nd import space.kscience.kmath.misc.PerformancePitfall -import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.MutableListBuffer import space.kscience.kmath.structures.VirtualBuffer @@ -108,7 +107,6 @@ private value class Structure2DWrapper(val structure: StructureND) : S override operator fun get(i: Int, j: Int): T = structure[i, j] - @UnstableKMathAPI override fun getFeature(type: KClass): F? = structure.getFeature(type) @PerformancePitfall diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt index 0675f5baf..6123336ba 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt @@ -9,12 +9,12 @@ import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.misc.Feature import space.kscience.kmath.misc.Featured import space.kscience.kmath.misc.PerformancePitfall -import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.Ring import space.kscience.kmath.operations.invoke import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.BufferFactory import kotlin.jvm.JvmName +import kotlin.math.abs import kotlin.native.concurrent.ThreadLocal import kotlin.reflect.KClass @@ -61,7 +61,6 @@ public interface StructureND : Featured { * Feature is some additional structure information that allows to access it special properties or hints. * If the feature is not present, `null` is returned. */ - @UnstableKMathAPI override fun getFeature(type: KClass): F? = null public companion object { @@ -80,6 +79,22 @@ public interface StructureND : Featured { return st1.elements().all { (index, value) -> value == st2[index] } } + @PerformancePitfall + public fun contentEquals( + st1: StructureND, + st2: StructureND, + tolerance: Double = 1e-11 + ): Boolean { + if (st1 === st2) return true + + // fast comparison of buffers if possible + if (st1 is BufferND && st2 is BufferND && st1.strides == st2.strides) + return Buffer.contentEquals(st1.buffer, st2.buffer) + + //element by element comparison if it could not be avoided + return st1.elements().all { (index, value) -> abs(value - st2[index]) < tolerance } + } + /** * Debug output to string */ @@ -196,8 +211,8 @@ public fun > LinearSpace>.contentEquals( */ public operator fun StructureND.get(vararg index: Int): T = get(index) -@UnstableKMathAPI -public inline fun StructureND<*>.getFeature(): T? = getFeature(T::class) +//@UnstableKMathAPI +//public inline fun StructureND<*>.getFeature(): T? = getFeature(T::class) /** * Represents mutable [StructureND]. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BufferAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BufferAlgebra.kt index 9f4d741fd..e82b62c1b 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BufferAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BufferAlgebra.kt @@ -17,6 +17,12 @@ import space.kscience.kmath.structures.DoubleBuffer public interface BufferAlgebra> : Algebra> { public val bufferFactory: BufferFactory public val elementAlgebra: A + public val size: Int + + public fun buffer(vararg elements: T): Buffer { + require(elements.size == size) { "Expected $size elements but found ${elements.size}" } + return bufferFactory(size) { elements[it] } + } //TODO move to multi-receiver inline extension public fun Buffer.map(block: (T) -> T): Buffer = bufferFactory(size) { block(get(it)) } @@ -39,6 +45,11 @@ public interface BufferAlgebra> : Algebra> { } } +@UnstableKMathAPI +public fun BufferField.buffer(initializer: (Int) -> T): Buffer { + return bufferFactory(size, initializer) +} + @UnstableKMathAPI public fun > BufferAlgebra.sin(arg: Buffer): Buffer = arg.map(elementAlgebra::sin) @@ -104,14 +115,9 @@ public fun > BufferAlgebra.pow(arg: Buffer, p public class BufferField>( override val bufferFactory: BufferFactory, override val elementAlgebra: A, - public val size: Int + override val size: Int ) : BufferAlgebra, Field> { - public fun produce(vararg elements: T): Buffer { - require(elements.size == size) { "Expected $size elements but found ${elements.size}" } - return bufferFactory(size) { elements[it] } - } - override val zero: Buffer = bufferFactory(size) { elementAlgebra.zero } override val one: Buffer = bufferFactory(size) { elementAlgebra.one } @@ -135,11 +141,15 @@ public class BufferField>( //Double buffer specialization @UnstableKMathAPI -public fun BufferField.produce(vararg elements: Number): Buffer { +public fun BufferField.buffer(vararg elements: Number): Buffer { require(elements.size == size) { "Expected $size elements but found ${elements.size}" } return bufferFactory(size) { elements[it].toDouble() } } +@UnstableKMathAPI +public fun > A.bufferAlgebra(bufferFactory: BufferFactory, size: Int): BufferField = + BufferField(bufferFactory, this, size) + @UnstableKMathAPI public fun DoubleField.bufferAlgebra(size: Int): BufferField = BufferField(::DoubleBuffer, DoubleField, size) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ArrayBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ArrayBuffer.kt index d49f70355..393ee99d6 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ArrayBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ArrayBuffer.kt @@ -23,6 +23,8 @@ public class ArrayBuffer(internal val array: Array) : MutableBuffer { override operator fun iterator(): Iterator = array.iterator() override fun copy(): MutableBuffer = ArrayBuffer(array.copyOf()) + + override fun toString(): String = Buffer.toString(this) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt index c22a4ba39..fc23169ca 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt @@ -45,7 +45,12 @@ public interface Buffer { */ public operator fun iterator(): Iterator + override fun toString(): String + public companion object { + + public fun toString(buffer: Buffer<*>): String = buffer.asSequence().joinToString(prefix = "[", separator = ", ", postfix = "]") + /** * Check the element-by-element match of content of two buffers. */ @@ -126,6 +131,8 @@ public class VirtualBuffer(override val size: Int, private val generator: } override operator fun iterator(): Iterator = (0 until size).asSequence().map(generator).iterator() + + override fun toString(): String = Buffer.toString(this) } /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt index 005a693eb..d6a48f42d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt @@ -49,6 +49,8 @@ internal class BufferAccessor2D( override fun copy(): MutableBuffer = factory(colNum) { get(it) } override operator fun iterator(): Iterator = (0 until colNum).map(::get).iterator() + override fun toString(): String = Buffer.toString(this) + } /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt index 665558829..700a4f17f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FlaggedBuffer.kt @@ -53,8 +53,10 @@ public fun FlaggedBuffer<*>.isMissing(index: Int): Boolean = hasFlag(index, Valu /** * A [Double] buffer that supports flags for each value like `NaN` or Missing. */ -public class FlaggedDoubleBuffer(public val values: DoubleArray, public val flags: ByteArray) : FlaggedBuffer, - Buffer { +public class FlaggedDoubleBuffer( + public val values: DoubleArray, + public val flags: ByteArray +) : FlaggedBuffer, Buffer { init { require(values.size == flags.size) { "Values and flags must have the same dimensions" } } @@ -68,6 +70,8 @@ public class FlaggedDoubleBuffer(public val values: DoubleArray, public val flag override operator fun iterator(): Iterator = values.indices.asSequence().map { if (isValid(it)) values[it] else null }.iterator() + + override fun toString(): String = Buffer.toString(this) } public inline fun FlaggedDoubleBuffer.forEachValid(block: (Double) -> Unit) { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ListBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ListBuffer.kt index fdba68d19..666722177 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ListBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ListBuffer.kt @@ -21,6 +21,8 @@ public class ListBuffer(public val list: List) : Buffer { override operator fun get(index: Int): T = list[index] override operator fun iterator(): Iterator = list.iterator() + + override fun toString(): String = Buffer.toString(this) } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt index 996785570..3e08dbbb1 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt @@ -22,6 +22,8 @@ public open class MemoryBuffer(protected val memory: Memory, protected override operator fun get(index: Int): T = reader.read(spec, spec.objectSize * index) override operator fun iterator(): Iterator = (0 until size).asSequence().map { get(it) }.iterator() + override fun toString(): String = Buffer.toString(this) + public companion object { public fun create(spec: MemorySpec, size: Int): MemoryBuffer = MemoryBuffer(Memory.allocate(size * spec.objectSize), spec) diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NDFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NDFieldTest.kt index 6d4531f41..05a67ab09 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NDFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NDFieldTest.kt @@ -6,7 +6,7 @@ package space.kscience.kmath.structures import space.kscience.kmath.nd.get -import space.kscience.kmath.nd.nd +import space.kscience.kmath.nd.ndAlgebra import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.invoke import space.kscience.kmath.testutils.FieldVerifier @@ -16,12 +16,12 @@ import kotlin.test.assertEquals internal class NDFieldTest { @Test fun verify() { - (DoubleField.nd(12, 32)) { FieldVerifier(this, one + 3, one - 23, one * 12, 6.66) } + (DoubleField.ndAlgebra(12, 32)) { FieldVerifier(this, one + 3, one - 23, one * 12, 6.66) } } @Test fun testStrides() { - val ndArray = DoubleField.nd(10, 10).produce { (it[0] + it[1]).toDouble() } + val ndArray = DoubleField.ndAlgebra(10, 10).produce { (it[0] + it[1]).toDouble() } assertEquals(ndArray[5, 5], 10.0) } } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt index 1045933b7..b2982b335 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt @@ -10,7 +10,7 @@ import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.combine import space.kscience.kmath.nd.get -import space.kscience.kmath.nd.nd +import space.kscience.kmath.nd.ndAlgebra import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Norm import space.kscience.kmath.operations.invoke @@ -21,7 +21,7 @@ import kotlin.test.assertEquals @Suppress("UNUSED_VARIABLE") class NumberNDFieldTest { - val algebra = DoubleField.nd(3, 3) + val algebra = DoubleField.ndAlgebra(3, 3) val array1 = algebra.produce { (i, j) -> (i + j).toDouble() } val array2 = algebra.produce { (i, j) -> (i - j).toDouble() } @@ -87,7 +87,7 @@ class NumberNDFieldTest { @Test fun testInternalContext() { algebra { - (DoubleField.nd(*array1.shape)) { with(L2Norm) { 1 + norm(array1) + exp(array2) } } + (DoubleField.ndAlgebra(*array1.shape)) { with(L2Norm) { 1 + norm(array1) + exp(array2) } } } } } diff --git a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/RingBuffer.kt b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/RingBuffer.kt index 4b12b031d..573b406e2 100644 --- a/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/RingBuffer.kt +++ b/kmath-coroutines/src/commonMain/kotlin/space/kscience/kmath/streaming/RingBuffer.kt @@ -69,6 +69,8 @@ public class RingBuffer( @Suppress("NOTHING_TO_INLINE") private inline fun Int.forward(n: Int): Int = (this + n) % (buffer.size) + override fun toString(): String = Buffer.toString(this) + public companion object { public inline fun build(size: Int, empty: T): RingBuffer { val buffer = MutableBuffer.auto(size) { empty } as MutableBuffer diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt index 022a7874e..4a53af60d 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt @@ -5,9 +5,12 @@ package space.kscience.kmath.ejml +import space.kscience.kmath.linear.InverseMatrixFeature import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.Matrix import space.kscience.kmath.linear.Point +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.nd.Structure2D import space.kscience.kmath.operations.Ring /** @@ -36,4 +39,7 @@ public abstract class EjmlLinearSpace, out M : org.ejml ): EjmlMatrix public abstract override fun buildVector(size: Int, initializer: A.(Int) -> T): EjmlVector + + @UnstableKMathAPI + public fun EjmlMatrix.inverse(): Structure2D = computeFeature(this, InverseMatrixFeature::class)?.inverse as Structure2D } diff --git a/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt b/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt index 5667815ac..5b8b2af98 100644 --- a/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt +++ b/kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt @@ -9,12 +9,11 @@ import org.ejml.data.DMatrixRMaj import org.ejml.dense.row.CommonOps_DDRM import org.ejml.dense.row.RandomMatrices_DDRM import org.ejml.dense.row.factory.DecompositionFactory_DDRM -import space.kscience.kmath.linear.DeterminantFeature -import space.kscience.kmath.linear.LupDecompositionFeature -import space.kscience.kmath.linear.computeFeature +import space.kscience.kmath.linear.* import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureND +import space.kscience.kmath.operations.algebra import kotlin.random.Random import kotlin.random.asJavaRandom import kotlin.test.* @@ -82,4 +81,24 @@ internal class EjmlMatrixTest { val m = randomMatrix assertSame(m, EjmlDoubleMatrix(m).origin) } + + @Test + fun inverse() = EjmlLinearSpaceDDRM { + val random = Random(1224) + val dim = 20 + + val space = Double.algebra.linearSpace + + //creating invertible matrix + val u = space.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } + val l = space.buildMatrix(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 } + val matrix = space { l dot u } + val inverted = matrix.toEjml().inverse() + + val res = matrix dot inverted + + println(StructureND.toString(res)) + + assertTrue { StructureND.contentEquals(one(dim, dim), res, 1e-3) } + } } diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt index 098beb2cf..88932d59b 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt @@ -12,6 +12,7 @@ import space.kscience.kmath.linear.* import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.algebra import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.asIterable @@ -32,18 +33,18 @@ import kotlin.math.pow public typealias RealMatrix = Matrix public fun realMatrix(rowNum: Int, colNum: Int, initializer: DoubleField.(i: Int, j: Int) -> Double): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, colNum, initializer) + Double.algebra.linearSpace.buildMatrix(rowNum, colNum, initializer) @OptIn(UnstableKMathAPI::class) public fun realMatrix(rowNum: Int, colNum: Int): MatrixBuilder = - LinearSpace.double.matrix(rowNum, colNum) + Double.algebra.linearSpace.matrix(rowNum, colNum) public fun Array.toMatrix(): RealMatrix { - return LinearSpace.double.buildMatrix(size, this[0].size) { row, col -> this@toMatrix[row][col] } + return Double.algebra.linearSpace.buildMatrix(size, this[0].size) { row, col -> this@toMatrix[row][col] } } public fun Sequence.toMatrix(): RealMatrix = toList().let { - LinearSpace.double.buildMatrix(it.size, it[0].size) { row, col -> it[row][col] } + Double.algebra.linearSpace.buildMatrix(it.size, it[0].size) { row, col -> it[row][col] } } public fun RealMatrix.repeatStackVertical(n: Int): RealMatrix = @@ -56,37 +57,37 @@ public fun RealMatrix.repeatStackVertical(n: Int): RealMatrix = */ public operator fun RealMatrix.times(double: Double): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> + Double.algebra.linearSpace.buildMatrix(rowNum, colNum) { row, col -> get(row, col) * double } public operator fun RealMatrix.plus(double: Double): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> + Double.algebra.linearSpace.buildMatrix(rowNum, colNum) { row, col -> get(row, col) + double } public operator fun RealMatrix.minus(double: Double): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> + Double.algebra.linearSpace.buildMatrix(rowNum, colNum) { row, col -> get(row, col) - double } public operator fun RealMatrix.div(double: Double): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> + Double.algebra.linearSpace.buildMatrix(rowNum, colNum) { row, col -> get(row, col) / double } public operator fun Double.times(matrix: RealMatrix): RealMatrix = - LinearSpace.double.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> + Double.algebra.linearSpace.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> this@times * matrix[row, col] } public operator fun Double.plus(matrix: RealMatrix): RealMatrix = - LinearSpace.double.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> + Double.algebra.linearSpace.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> this@plus + matrix[row, col] } public operator fun Double.minus(matrix: RealMatrix): RealMatrix = - LinearSpace.double.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> + Double.algebra.linearSpace.buildMatrix(matrix.rowNum, matrix.colNum) { row, col -> this@minus - matrix[row, col] } @@ -101,20 +102,20 @@ public operator fun Double.minus(matrix: RealMatrix): RealMatrix = @UnstableKMathAPI public operator fun RealMatrix.times(other: RealMatrix): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> this@times[row, col] * other[row, col] } + Double.algebra.linearSpace.buildMatrix(rowNum, colNum) { row, col -> this@times[row, col] * other[row, col] } public operator fun RealMatrix.plus(other: RealMatrix): RealMatrix = - LinearSpace.double.run { this@plus + other } + Double.algebra.linearSpace.run { this@plus + other } public operator fun RealMatrix.minus(other: RealMatrix): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, colNum) { row, col -> this@minus[row, col] - other[row, col] } + Double.algebra.linearSpace.buildMatrix(rowNum, colNum) { row, col -> this@minus[row, col] - other[row, col] } /* * Operations on columns */ public inline fun RealMatrix.appendColumn(crossinline mapper: (Buffer) -> Double): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, colNum + 1) { row, col -> + Double.algebra.linearSpace.buildMatrix(rowNum, colNum + 1) { row, col -> if (col < colNum) get(row, col) else @@ -122,7 +123,7 @@ public inline fun RealMatrix.appendColumn(crossinline mapper: (Buffer) - } public fun RealMatrix.extractColumns(columnRange: IntRange): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, columnRange.count()) { row, col -> + Double.algebra.linearSpace.buildMatrix(rowNum, columnRange.count()) { row, col -> this@extractColumns[row, columnRange.first + col] } @@ -155,14 +156,14 @@ public fun RealMatrix.max(): Double? = elements().map { (_, value) -> value }.ma public fun RealMatrix.average(): Double = elements().map { (_, value) -> value }.average() public inline fun RealMatrix.map(crossinline transform: (Double) -> Double): RealMatrix = - LinearSpace.double.buildMatrix(rowNum, colNum) { i, j -> + Double.algebra.linearSpace.buildMatrix(rowNum, colNum) { i, j -> transform(get(i, j)) } /** * Inverse a square real matrix using LUP decomposition */ -public fun RealMatrix.inverseWithLup(): RealMatrix = LinearSpace.double.lupSolver().inverse(this) +public fun RealMatrix.inverseWithLup(): RealMatrix = Double.algebra.linearSpace.lupSolver().inverse(this) //extended operations diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt index ca2db8131..883a63f46 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt @@ -5,13 +5,14 @@ package space.kscience.kmath.real -import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.Matrix +import space.kscience.kmath.linear.linearSpace +import space.kscience.kmath.operations.algebra /** * Optimized dot product for real matrices */ -public infix fun Matrix.dot(other: Matrix): Matrix = LinearSpace.double.run { +public infix fun Matrix.dot(other: Matrix): Matrix = Double.algebra.linearSpace.run { this@dot dot other } \ No newline at end of file diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt index c99f3ff99..662cdf3d7 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt @@ -10,6 +10,7 @@ import space.kscience.kmath.functions.integrate import space.kscience.kmath.interpolation.PolynomialInterpolator import space.kscience.kmath.interpolation.SplineInterpolator import space.kscience.kmath.interpolation.interpolatePolynomials +import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Field @@ -23,6 +24,7 @@ import space.kscience.kmath.structures.map /** * Compute analytical indefinite integral of this [PiecewisePolynomial], keeping all intervals intact */ +@OptIn(PerformancePitfall::class) @UnstableKMathAPI public fun > PiecewisePolynomial.integrate(algebra: Field): PiecewisePolynomial = PiecewisePolynomial(pieces.map { it.first to it.second.integrate(algebra) }) diff --git a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/DoubleHistogramSpace.kt b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/DoubleHistogramSpace.kt index 37ab8a1b2..5446f05f8 100644 --- a/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/DoubleHistogramSpace.kt +++ b/kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/DoubleHistogramSpace.kt @@ -29,7 +29,7 @@ public class DoubleHistogramSpace( public val dimension: Int get() = lower.size private val shape = IntArray(binNums.size) { binNums[it] + 2 } - override val histogramValueSpace: DoubleFieldND = DoubleField.nd(*shape) + override val histogramValueSpace: DoubleFieldND = DoubleField.ndAlgebra(*shape) override val strides: Strides get() = histogramValueSpace.strides private val binSize = DoubleBuffer(dimension) { (upper[it] - lower[it]) / binNums[it] } diff --git a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorBuffer.kt b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorBuffer.kt index caebd9783..32fb65b8a 100644 --- a/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorBuffer.kt +++ b/kmath-viktor/src/main/kotlin/space/kscience/kmath/viktor/ViktorBuffer.kt @@ -6,10 +6,12 @@ package space.kscience.kmath.viktor import org.jetbrains.bio.viktor.F64FlatArray +import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.MutableBuffer @Suppress("NOTHING_TO_INLINE", "OVERRIDE_BY_INLINE") -public class ViktorBuffer(public val flatArray: F64FlatArray) : MutableBuffer { +@JvmInline +public value class ViktorBuffer(public val flatArray: F64FlatArray) : MutableBuffer { override val size: Int get() = flatArray.size @@ -21,4 +23,6 @@ public class ViktorBuffer(public val flatArray: F64FlatArray) : MutableBuffer = ViktorBuffer(flatArray.copy().flatten()) override operator fun iterator(): Iterator = flatArray.data.iterator() + + override fun toString(): String = Buffer.toString(this) } From 974d73e25c3e5c44956848a2b877cdc20f7c7436 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Wed, 22 Sep 2021 22:09:46 +0300 Subject: [PATCH 121/132] Adjust benchmarks. --- .../kmath/benchmarks/BigIntBenchmark.kt | 29 +++++++++--- .../kscience/kmath/benchmarks/DotBenchmark.kt | 44 +++++++++---------- .../kscience/kmath/linear/dotPerformance.kt | 34 ++++++++++++++ 3 files changed, 77 insertions(+), 30 deletions(-) create mode 100644 examples/src/main/kotlin/space/kscience/kmath/linear/dotPerformance.kt diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt index 6f501dedb..f2b2d4d7a 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt @@ -11,7 +11,10 @@ import org.openjdk.jmh.annotations.Benchmark import org.openjdk.jmh.annotations.Scope import org.openjdk.jmh.annotations.State import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.* +import space.kscience.kmath.operations.BigIntField +import space.kscience.kmath.operations.JBigIntegerField +import space.kscience.kmath.operations.invoke +import space.kscience.kmath.operations.parseBigInteger import java.math.BigInteger @@ -19,12 +22,24 @@ import java.math.BigInteger @State(Scope.Benchmark) internal class BigIntBenchmark { + val kmSmallNumber = BigIntField.number(100) + val jvmSmallNumber = JBigIntegerField.number(100) val kmNumber = BigIntField.number(Int.MAX_VALUE) val jvmNumber = JBigIntegerField.number(Int.MAX_VALUE) - val largeKmNumber = BigIntField { number(11).pow(100_000U) } - val largeJvmNumber: BigInteger = JBigIntegerField { number(11).pow(100_000) } + val kmLargeNumber = BigIntField { number(11).pow(100_000U) } + val jvmLargeNumber: BigInteger = JBigIntegerField { number(11).pow(100_000) } val bigExponent = 50_000 + @Benchmark + fun kmSmallAdd(blackhole: Blackhole) = BigIntField { + blackhole.consume(kmSmallNumber + kmSmallNumber + kmSmallNumber) + } + + @Benchmark + fun jvmSmallAdd(blackhole: Blackhole) = JBigIntegerField { + blackhole.consume(jvmSmallNumber + jvmSmallNumber + jvmSmallNumber) + } + @Benchmark fun kmAdd(blackhole: Blackhole) = BigIntField { blackhole.consume(kmNumber + kmNumber + kmNumber) @@ -37,12 +52,12 @@ internal class BigIntBenchmark { @Benchmark fun kmAddLarge(blackhole: Blackhole) = BigIntField { - blackhole.consume(largeKmNumber + largeKmNumber + largeKmNumber) + blackhole.consume(kmLargeNumber + kmLargeNumber + kmLargeNumber) } @Benchmark fun jvmAddLarge(blackhole: Blackhole) = JBigIntegerField { - blackhole.consume(largeJvmNumber + largeJvmNumber + largeJvmNumber) + blackhole.consume(jvmLargeNumber + jvmLargeNumber + jvmLargeNumber) } @Benchmark @@ -52,7 +67,7 @@ internal class BigIntBenchmark { @Benchmark fun kmMultiplyLarge(blackhole: Blackhole) = BigIntField { - blackhole.consume(largeKmNumber*largeKmNumber) + blackhole.consume(kmLargeNumber*kmLargeNumber) } @Benchmark @@ -62,7 +77,7 @@ internal class BigIntBenchmark { @Benchmark fun jvmMultiplyLarge(blackhole: Blackhole) = JBigIntegerField { - blackhole.consume(largeJvmNumber*largeJvmNumber) + blackhole.consume(jvmLargeNumber*jvmLargeNumber) } @Benchmark diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt index 6373d1ce5..33cb57c6f 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt @@ -11,7 +11,6 @@ import kotlinx.benchmark.Scope import kotlinx.benchmark.State import space.kscience.kmath.commons.linear.CMLinearSpace import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM -import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.invoke import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.operations.DoubleField @@ -26,8 +25,12 @@ internal class DotBenchmark { const val dim = 1000 //creating invertible matrix - val matrix1 = LinearSpace.double.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } - val matrix2 = LinearSpace.double.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 } + val matrix1 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j -> + if (i <= j) random.nextDouble() else 0.0 + } + val matrix2 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j -> + if (i <= j) random.nextDouble() else 0.0 + } val cmMatrix1 = CMLinearSpace { matrix1.toCM() } val cmMatrix2 = CMLinearSpace { matrix2.toCM() } @@ -37,37 +40,32 @@ internal class DotBenchmark { } @Benchmark - fun cmDot(blackhole: Blackhole) { - CMLinearSpace { - blackhole.consume(cmMatrix1 dot cmMatrix2) - } + fun cmDotWithConversion(blackhole: Blackhole) = CMLinearSpace { + blackhole.consume(matrix1 dot matrix2) } @Benchmark - fun ejmlDot(blackhole: Blackhole) { - EjmlLinearSpaceDDRM { - blackhole.consume(ejmlMatrix1 dot ejmlMatrix2) - } + fun cmDot(blackhole: Blackhole) = CMLinearSpace { + blackhole.consume(cmMatrix1 dot cmMatrix2) } @Benchmark - fun ejmlDotWithConversion(blackhole: Blackhole) { - EjmlLinearSpaceDDRM { - blackhole.consume(matrix1 dot matrix2) - } + fun ejmlDot(blackhole: Blackhole) = EjmlLinearSpaceDDRM { + blackhole.consume(ejmlMatrix1 dot ejmlMatrix2) } @Benchmark - fun bufferedDot(blackhole: Blackhole) { - with(DoubleField.linearSpace(Buffer.Companion::auto)) { - blackhole.consume(matrix1 dot matrix2) - } + fun ejmlDotWithConversion(blackhole: Blackhole) = EjmlLinearSpaceDDRM { + blackhole.consume(matrix1 dot matrix2) } @Benchmark - fun doubleDot(blackhole: Blackhole) { - with(Double.algebra.linearSpace) { - blackhole.consume(matrix1 dot matrix2) - } + fun bufferedDot(blackhole: Blackhole) = with(DoubleField.linearSpace(Buffer.Companion::auto)) { + blackhole.consume(matrix1 dot matrix2) + } + + @Benchmark + fun doubleDot(blackhole: Blackhole) = with(Double.algebra.linearSpace) { + blackhole.consume(matrix1 dot matrix2) } } diff --git a/examples/src/main/kotlin/space/kscience/kmath/linear/dotPerformance.kt b/examples/src/main/kotlin/space/kscience/kmath/linear/dotPerformance.kt new file mode 100644 index 000000000..31762b6d8 --- /dev/null +++ b/examples/src/main/kotlin/space/kscience/kmath/linear/dotPerformance.kt @@ -0,0 +1,34 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. + */ + +package space.kscience.kmath.linear + +import space.kscience.kmath.operations.algebra +import kotlin.random.Random +import kotlin.system.measureTimeMillis + +fun main() { + val random = Random(12224) + val dim = 1000 + + //creating invertible matrix + val matrix1 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j -> + if (i <= j) random.nextDouble() else 0.0 + } + val matrix2 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j -> + if (i <= j) random.nextDouble() else 0.0 + } + + val time = measureTimeMillis { + with(Double.algebra.linearSpace) { + repeat(10) { + val res = matrix1 dot matrix2 + } + } + } + + println(time) + +} \ No newline at end of file From 64781a6785dd2aef35ab3e99e2bb8a22413ad297 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Thu, 23 Sep 2021 21:44:18 +0300 Subject: [PATCH 122/132] Move Minuit tmp classes to optimization --- {kmath-stat => kmath-optimization}/src/commonMain/tmp/QowFit.kt | 0 .../src/commonMain/tmp/minuit/AnalyticalGradientCalculator.kt | 0 .../src/commonMain/tmp/minuit/CombinedMinimizer.kt | 0 .../src/commonMain/tmp/minuit/CombinedMinimumBuilder.kt | 0 .../src/commonMain/tmp/minuit/ContoursError.kt | 0 .../src/commonMain/tmp/minuit/DavidonErrorUpdator.kt | 0 .../src/commonMain/tmp/minuit/FunctionGradient.kt | 0 .../src/commonMain/tmp/minuit/FunctionMinimum.kt | 0 .../src/commonMain/tmp/minuit/GradientCalculator.kt | 0 .../src/commonMain/tmp/minuit/HessianGradientCalculator.kt | 0 .../src/commonMain/tmp/minuit/InitialGradientCalculator.kt | 0 .../src/commonMain/tmp/minuit/MINOSResult.kt | 0 .../src/commonMain/tmp/minuit/MINUITFitter.kt | 0 .../src/commonMain/tmp/minuit/MINUITPlugin.kt | 0 .../src/commonMain/tmp/minuit/MINUITUtils.kt | 0 .../src/commonMain/tmp/minuit/MinimumBuilder.kt | 0 .../src/commonMain/tmp/minuit/MinimumError.kt | 0 .../src/commonMain/tmp/minuit/MinimumErrorUpdator.kt | 0 .../src/commonMain/tmp/minuit/MinimumParameters.kt | 0 .../src/commonMain/tmp/minuit/MinimumSeed.kt | 0 .../src/commonMain/tmp/minuit/MinimumSeedGenerator.kt | 0 .../src/commonMain/tmp/minuit/MinimumState.kt | 0 .../src/commonMain/tmp/minuit/MinosError.kt | 0 .../src/commonMain/tmp/minuit/MinuitParameter.kt | 0 .../src/commonMain/tmp/minuit/MnAlgebraicSymMatrix.kt | 0 .../src/commonMain/tmp/minuit/MnApplication.kt | 0 .../src/commonMain/tmp/minuit/MnContours.kt | 0 .../src/commonMain/tmp/minuit/MnCovarianceSqueeze.kt | 0 .../src/commonMain/tmp/minuit/MnCross.kt | 0 .../src/commonMain/tmp/minuit/MnEigen.kt | 0 .../src/commonMain/tmp/minuit/MnFcn.kt | 0 .../src/commonMain/tmp/minuit/MnFunctionCross.kt | 0 .../src/commonMain/tmp/minuit/MnGlobalCorrelationCoeff.kt | 0 .../src/commonMain/tmp/minuit/MnHesse.kt | 0 .../src/commonMain/tmp/minuit/MnLineSearch.kt | 0 .../src/commonMain/tmp/minuit/MnMachinePrecision.kt | 0 .../src/commonMain/tmp/minuit/MnMigrad.kt | 0 .../src/commonMain/tmp/minuit/MnMinimize.kt | 0 .../src/commonMain/tmp/minuit/MnMinos.kt | 0 .../src/commonMain/tmp/minuit/MnParabola.kt | 0 .../src/commonMain/tmp/minuit/MnParabolaFactory.kt | 0 .../src/commonMain/tmp/minuit/MnParabolaPoint.kt | 0 .../src/commonMain/tmp/minuit/MnParameterScan.kt | 0 .../src/commonMain/tmp/minuit/MnPlot.kt | 0 .../src/commonMain/tmp/minuit/MnPosDef.kt | 0 .../src/commonMain/tmp/minuit/MnPrint.kt | 0 .../src/commonMain/tmp/minuit/MnScan.kt | 0 .../src/commonMain/tmp/minuit/MnSeedGenerator.kt | 0 .../src/commonMain/tmp/minuit/MnSimplex.kt | 0 .../src/commonMain/tmp/minuit/MnStrategy.kt | 0 .../src/commonMain/tmp/minuit/MnUserCovariance.kt | 0 .../src/commonMain/tmp/minuit/MnUserFcn.kt | 0 .../src/commonMain/tmp/minuit/MnUserParameterState.kt | 0 .../src/commonMain/tmp/minuit/MnUserParameters.kt | 0 .../src/commonMain/tmp/minuit/MnUserTransformation.kt | 0 .../src/commonMain/tmp/minuit/MnUtils.kt | 0 .../src/commonMain/tmp/minuit/ModularFunctionMinimizer.kt | 0 .../src/commonMain/tmp/minuit/NegativeG2LineSearch.kt | 0 .../src/commonMain/tmp/minuit/Numerical2PGradientCalculator.kt | 0 .../src/commonMain/tmp/minuit/ScanBuilder.kt | 0 .../src/commonMain/tmp/minuit/ScanMinimizer.kt | 0 .../src/commonMain/tmp/minuit/SimplexBuilder.kt | 0 .../src/commonMain/tmp/minuit/SimplexMinimizer.kt | 0 .../src/commonMain/tmp/minuit/SimplexParameters.kt | 0 .../src/commonMain/tmp/minuit/SimplexSeedGenerator.kt | 0 .../src/commonMain/tmp/minuit/SinParameterTransformation.kt | 0 .../src/commonMain/tmp/minuit/SqrtLowParameterTransformation.kt | 0 .../src/commonMain/tmp/minuit/SqrtUpParameterTransformation.kt | 0 .../src/commonMain/tmp/minuit/VariableMetricBuilder.kt | 0 .../src/commonMain/tmp/minuit/VariableMetricEDMEstimator.kt | 0 .../src/commonMain/tmp/minuit/VariableMetricMinimizer.kt | 0 .../src/commonMain/tmp/minuit/package-info.kt | 0 72 files changed, 0 insertions(+), 0 deletions(-) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/QowFit.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/AnalyticalGradientCalculator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/CombinedMinimizer.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/CombinedMinimumBuilder.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/ContoursError.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/DavidonErrorUpdator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/FunctionGradient.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/FunctionMinimum.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/GradientCalculator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/HessianGradientCalculator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/InitialGradientCalculator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MINOSResult.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MINUITFitter.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MINUITPlugin.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MINUITUtils.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MinimumBuilder.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MinimumError.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MinimumErrorUpdator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MinimumParameters.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MinimumSeed.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MinimumSeedGenerator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MinimumState.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MinosError.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MinuitParameter.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnAlgebraicSymMatrix.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnApplication.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnContours.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnCovarianceSqueeze.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnCross.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnEigen.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnFcn.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnFunctionCross.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnGlobalCorrelationCoeff.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnHesse.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnLineSearch.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnMachinePrecision.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnMigrad.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnMinimize.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnMinos.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnParabola.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnParabolaFactory.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnParabolaPoint.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnParameterScan.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnPlot.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnPosDef.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnPrint.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnScan.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnSeedGenerator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnSimplex.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnStrategy.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnUserCovariance.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnUserFcn.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnUserParameterState.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnUserParameters.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnUserTransformation.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/MnUtils.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/ModularFunctionMinimizer.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/NegativeG2LineSearch.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/Numerical2PGradientCalculator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/ScanBuilder.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/ScanMinimizer.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/SimplexBuilder.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/SimplexMinimizer.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/SimplexParameters.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/SimplexSeedGenerator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/SinParameterTransformation.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/SqrtLowParameterTransformation.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/SqrtUpParameterTransformation.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/VariableMetricBuilder.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/VariableMetricEDMEstimator.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/VariableMetricMinimizer.kt (100%) rename {kmath-stat => kmath-optimization}/src/commonMain/tmp/minuit/package-info.kt (100%) diff --git a/kmath-stat/src/commonMain/tmp/QowFit.kt b/kmath-optimization/src/commonMain/tmp/QowFit.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/QowFit.kt rename to kmath-optimization/src/commonMain/tmp/QowFit.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/AnalyticalGradientCalculator.kt b/kmath-optimization/src/commonMain/tmp/minuit/AnalyticalGradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/AnalyticalGradientCalculator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/AnalyticalGradientCalculator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/CombinedMinimizer.kt b/kmath-optimization/src/commonMain/tmp/minuit/CombinedMinimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/CombinedMinimizer.kt rename to kmath-optimization/src/commonMain/tmp/minuit/CombinedMinimizer.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/CombinedMinimumBuilder.kt b/kmath-optimization/src/commonMain/tmp/minuit/CombinedMinimumBuilder.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/CombinedMinimumBuilder.kt rename to kmath-optimization/src/commonMain/tmp/minuit/CombinedMinimumBuilder.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/ContoursError.kt b/kmath-optimization/src/commonMain/tmp/minuit/ContoursError.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/ContoursError.kt rename to kmath-optimization/src/commonMain/tmp/minuit/ContoursError.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/DavidonErrorUpdator.kt b/kmath-optimization/src/commonMain/tmp/minuit/DavidonErrorUpdator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/DavidonErrorUpdator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/DavidonErrorUpdator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/FunctionGradient.kt b/kmath-optimization/src/commonMain/tmp/minuit/FunctionGradient.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/FunctionGradient.kt rename to kmath-optimization/src/commonMain/tmp/minuit/FunctionGradient.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/FunctionMinimum.kt b/kmath-optimization/src/commonMain/tmp/minuit/FunctionMinimum.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/FunctionMinimum.kt rename to kmath-optimization/src/commonMain/tmp/minuit/FunctionMinimum.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/GradientCalculator.kt b/kmath-optimization/src/commonMain/tmp/minuit/GradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/GradientCalculator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/GradientCalculator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/HessianGradientCalculator.kt b/kmath-optimization/src/commonMain/tmp/minuit/HessianGradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/HessianGradientCalculator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/HessianGradientCalculator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/InitialGradientCalculator.kt b/kmath-optimization/src/commonMain/tmp/minuit/InitialGradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/InitialGradientCalculator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/InitialGradientCalculator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MINOSResult.kt b/kmath-optimization/src/commonMain/tmp/minuit/MINOSResult.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MINOSResult.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MINOSResult.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MINUITFitter.kt b/kmath-optimization/src/commonMain/tmp/minuit/MINUITFitter.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MINUITFitter.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MINUITFitter.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MINUITPlugin.kt b/kmath-optimization/src/commonMain/tmp/minuit/MINUITPlugin.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MINUITPlugin.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MINUITPlugin.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MINUITUtils.kt b/kmath-optimization/src/commonMain/tmp/minuit/MINUITUtils.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MINUITUtils.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MINUITUtils.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MinimumBuilder.kt b/kmath-optimization/src/commonMain/tmp/minuit/MinimumBuilder.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MinimumBuilder.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MinimumBuilder.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MinimumError.kt b/kmath-optimization/src/commonMain/tmp/minuit/MinimumError.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MinimumError.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MinimumError.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MinimumErrorUpdator.kt b/kmath-optimization/src/commonMain/tmp/minuit/MinimumErrorUpdator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MinimumErrorUpdator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MinimumErrorUpdator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MinimumParameters.kt b/kmath-optimization/src/commonMain/tmp/minuit/MinimumParameters.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MinimumParameters.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MinimumParameters.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MinimumSeed.kt b/kmath-optimization/src/commonMain/tmp/minuit/MinimumSeed.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MinimumSeed.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MinimumSeed.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MinimumSeedGenerator.kt b/kmath-optimization/src/commonMain/tmp/minuit/MinimumSeedGenerator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MinimumSeedGenerator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MinimumSeedGenerator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MinimumState.kt b/kmath-optimization/src/commonMain/tmp/minuit/MinimumState.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MinimumState.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MinimumState.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MinosError.kt b/kmath-optimization/src/commonMain/tmp/minuit/MinosError.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MinosError.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MinosError.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MinuitParameter.kt b/kmath-optimization/src/commonMain/tmp/minuit/MinuitParameter.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MinuitParameter.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MinuitParameter.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnAlgebraicSymMatrix.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnAlgebraicSymMatrix.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnAlgebraicSymMatrix.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnAlgebraicSymMatrix.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnApplication.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnApplication.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnApplication.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnApplication.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnContours.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnContours.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnContours.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnContours.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnCovarianceSqueeze.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnCovarianceSqueeze.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnCovarianceSqueeze.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnCovarianceSqueeze.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnCross.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnCross.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnCross.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnCross.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnEigen.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnEigen.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnEigen.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnEigen.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnFcn.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnFcn.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnFcn.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnFcn.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnFunctionCross.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnFunctionCross.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnFunctionCross.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnFunctionCross.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnGlobalCorrelationCoeff.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnGlobalCorrelationCoeff.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnGlobalCorrelationCoeff.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnGlobalCorrelationCoeff.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnHesse.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnHesse.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnHesse.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnHesse.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnLineSearch.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnLineSearch.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnLineSearch.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnLineSearch.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnMachinePrecision.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnMachinePrecision.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnMachinePrecision.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnMachinePrecision.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnMigrad.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnMigrad.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnMigrad.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnMigrad.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnMinimize.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnMinimize.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnMinimize.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnMinimize.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnMinos.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnMinos.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnMinos.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnMinos.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnParabola.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnParabola.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnParabola.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnParabola.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnParabolaFactory.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnParabolaFactory.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnParabolaFactory.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnParabolaFactory.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnParabolaPoint.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnParabolaPoint.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnParabolaPoint.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnParabolaPoint.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnParameterScan.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnParameterScan.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnParameterScan.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnParameterScan.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnPlot.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnPlot.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnPlot.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnPlot.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnPosDef.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnPosDef.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnPosDef.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnPosDef.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnPrint.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnPrint.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnPrint.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnPrint.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnScan.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnScan.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnScan.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnScan.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnSeedGenerator.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnSeedGenerator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnSeedGenerator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnSeedGenerator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnSimplex.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnSimplex.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnSimplex.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnSimplex.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnStrategy.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnStrategy.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnStrategy.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnStrategy.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnUserCovariance.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnUserCovariance.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnUserCovariance.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnUserCovariance.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnUserFcn.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnUserFcn.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnUserFcn.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnUserFcn.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnUserParameterState.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnUserParameterState.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnUserParameterState.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnUserParameterState.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnUserParameters.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnUserParameters.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnUserParameters.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnUserParameters.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnUserTransformation.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnUserTransformation.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnUserTransformation.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnUserTransformation.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/MnUtils.kt b/kmath-optimization/src/commonMain/tmp/minuit/MnUtils.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/MnUtils.kt rename to kmath-optimization/src/commonMain/tmp/minuit/MnUtils.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/ModularFunctionMinimizer.kt b/kmath-optimization/src/commonMain/tmp/minuit/ModularFunctionMinimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/ModularFunctionMinimizer.kt rename to kmath-optimization/src/commonMain/tmp/minuit/ModularFunctionMinimizer.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/NegativeG2LineSearch.kt b/kmath-optimization/src/commonMain/tmp/minuit/NegativeG2LineSearch.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/NegativeG2LineSearch.kt rename to kmath-optimization/src/commonMain/tmp/minuit/NegativeG2LineSearch.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/Numerical2PGradientCalculator.kt b/kmath-optimization/src/commonMain/tmp/minuit/Numerical2PGradientCalculator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/Numerical2PGradientCalculator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/Numerical2PGradientCalculator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/ScanBuilder.kt b/kmath-optimization/src/commonMain/tmp/minuit/ScanBuilder.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/ScanBuilder.kt rename to kmath-optimization/src/commonMain/tmp/minuit/ScanBuilder.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/ScanMinimizer.kt b/kmath-optimization/src/commonMain/tmp/minuit/ScanMinimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/ScanMinimizer.kt rename to kmath-optimization/src/commonMain/tmp/minuit/ScanMinimizer.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/SimplexBuilder.kt b/kmath-optimization/src/commonMain/tmp/minuit/SimplexBuilder.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/SimplexBuilder.kt rename to kmath-optimization/src/commonMain/tmp/minuit/SimplexBuilder.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/SimplexMinimizer.kt b/kmath-optimization/src/commonMain/tmp/minuit/SimplexMinimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/SimplexMinimizer.kt rename to kmath-optimization/src/commonMain/tmp/minuit/SimplexMinimizer.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/SimplexParameters.kt b/kmath-optimization/src/commonMain/tmp/minuit/SimplexParameters.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/SimplexParameters.kt rename to kmath-optimization/src/commonMain/tmp/minuit/SimplexParameters.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/SimplexSeedGenerator.kt b/kmath-optimization/src/commonMain/tmp/minuit/SimplexSeedGenerator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/SimplexSeedGenerator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/SimplexSeedGenerator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/SinParameterTransformation.kt b/kmath-optimization/src/commonMain/tmp/minuit/SinParameterTransformation.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/SinParameterTransformation.kt rename to kmath-optimization/src/commonMain/tmp/minuit/SinParameterTransformation.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/SqrtLowParameterTransformation.kt b/kmath-optimization/src/commonMain/tmp/minuit/SqrtLowParameterTransformation.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/SqrtLowParameterTransformation.kt rename to kmath-optimization/src/commonMain/tmp/minuit/SqrtLowParameterTransformation.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/SqrtUpParameterTransformation.kt b/kmath-optimization/src/commonMain/tmp/minuit/SqrtUpParameterTransformation.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/SqrtUpParameterTransformation.kt rename to kmath-optimization/src/commonMain/tmp/minuit/SqrtUpParameterTransformation.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/VariableMetricBuilder.kt b/kmath-optimization/src/commonMain/tmp/minuit/VariableMetricBuilder.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/VariableMetricBuilder.kt rename to kmath-optimization/src/commonMain/tmp/minuit/VariableMetricBuilder.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/VariableMetricEDMEstimator.kt b/kmath-optimization/src/commonMain/tmp/minuit/VariableMetricEDMEstimator.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/VariableMetricEDMEstimator.kt rename to kmath-optimization/src/commonMain/tmp/minuit/VariableMetricEDMEstimator.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/VariableMetricMinimizer.kt b/kmath-optimization/src/commonMain/tmp/minuit/VariableMetricMinimizer.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/VariableMetricMinimizer.kt rename to kmath-optimization/src/commonMain/tmp/minuit/VariableMetricMinimizer.kt diff --git a/kmath-stat/src/commonMain/tmp/minuit/package-info.kt b/kmath-optimization/src/commonMain/tmp/minuit/package-info.kt similarity index 100% rename from kmath-stat/src/commonMain/tmp/minuit/package-info.kt rename to kmath-optimization/src/commonMain/tmp/minuit/package-info.kt From a68884142fd65e42e9cb02d308beb8294ae11512 Mon Sep 17 00:00:00 2001 From: Paule <44635962+V3lop5@users.noreply.github.com> Date: Mon, 27 Sep 2021 12:36:48 +0200 Subject: [PATCH 123/132] Added gradle wrapper validation See https://github.com/marketplace/actions/gradle-wrapper-validation --- .github/workflows/build.yml | 2 ++ .github/workflows/publish.yml | 2 ++ 2 files changed, 4 insertions(+) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 9a9f04621..4ea3428c6 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -35,5 +35,7 @@ jobs: key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }} restore-keys: | ${{ runner.os }}-gradle- + - name: Gradle Wrapper Validation + uses: gradle/wrapper-validation-action@v1.0.4 - name: Build run: ./gradlew build --no-daemon --stacktrace diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index c5c110e89..2e51e72d8 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -40,6 +40,8 @@ jobs: key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }} restore-keys: | ${{ runner.os }}-gradle- + - name: Gradle Wrapper Validation + uses: gradle/wrapper-validation-action@v1.0.4 - name: Publish Windows Artifacts if: matrix.os == 'windows-latest' run: > From 01bbb4bb1313f91cc584a6c9b6fdf904e34cddb7 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sat, 2 Oct 2021 09:55:52 +0300 Subject: [PATCH 124/132] API cleanup --- build.gradle.kts | 2 +- .../space/kscience/kmath/tensors/PCA.kt | 10 +- ...rmalization.kt => dataSetNormalization.kt} | 6 +- ...thLUP.kt => linearSystemSolvingWithLUP.kt} | 6 +- .../{NeuralNetwork.kt => neuralNetwork.kt} | 0 .../kmath/linear/BufferedLinearSpace.kt | 19 ++- .../kmath/linear/DoubleLinearSpace.kt | 109 ++++++++++++++++++ .../space/kscience/kmath/nd/Structure1D.kt | 2 +- .../space/kscience/kmath/nd/Structure2D.kt | 4 +- .../space/kscience/kmath/operations/BigInt.kt | 4 +- .../kscience/kmath/structures/DoubleBuffer.kt | 6 + .../kmath/linear/DoubleLUSolverTest.kt | 35 +++--- .../space/kscience/kmath/linear/MatrixTest.kt | 30 ++--- .../kmath/structures/NumberNDFieldTest.kt | 10 +- .../kscience/kmath/dimensions/Wrappers.kt | 8 +- .../kscience/kmath/real/DoubleMatrixTest.kt | 12 +- .../kscience/kmath/real/DoubleVectorTest.kt | 8 +- .../kmath/optimization/QowOptimizer.kt | 3 +- .../core/BroadcastDoubleTensorAlgebra.kt | 11 +- .../kmath/tensors/core/DoubleTensorAlgebra.kt | 2 + settings.gradle.kts | 7 +- 21 files changed, 211 insertions(+), 83 deletions(-) rename examples/src/main/kotlin/space/kscience/kmath/tensors/{DataSetNormalization.kt => dataSetNormalization.kt} (84%) rename examples/src/main/kotlin/space/kscience/kmath/tensors/{LinearSystemSolvingWithLUP.kt => linearSystemSolvingWithLUP.kt} (92%) rename examples/src/main/kotlin/space/kscience/kmath/tensors/{NeuralNetwork.kt => neuralNetwork.kt} (100%) create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt diff --git a/build.gradle.kts b/build.gradle.kts index 6bb19cd35..68b894d06 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -19,7 +19,7 @@ allprojects { } group = "space.kscience" - version = "0.3.0-dev-14" + version = "0.3.0-dev-15" } subprojects { diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt index 3302b49a8..d83d47805 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/PCA.kt @@ -5,19 +5,19 @@ package space.kscience.kmath.tensors -import space.kscience.kmath.operations.invoke -import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra +import space.kscience.kmath.tensors.core.tensorAlgebra +import space.kscience.kmath.tensors.core.withBroadcast // simple PCA -fun main(): Unit = BroadcastDoubleTensorAlgebra { // work in context with broadcast methods +fun main(): Unit = Double.tensorAlgebra.withBroadcast { // work in context with broadcast methods val seed = 100500L // assume x is range from 0 until 10 val x = fromArray( intArrayOf(10), - (0 until 10).toList().map { it.toDouble() }.toDoubleArray() + DoubleArray(10) { it.toDouble() } ) // take y dependent on x with noise @@ -62,7 +62,7 @@ fun main(): Unit = BroadcastDoubleTensorAlgebra { // work in context with broad println("Eigenvector:\n$v") // reduce dimension of dataset - val datasetReduced = v dot stack(listOf(xScaled, yScaled)) + val datasetReduced = v dot stack(listOf(xScaled, yScaled)) println("Reduced data:\n$datasetReduced") // we can restore original data from reduced data; diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/dataSetNormalization.kt similarity index 84% rename from examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt rename to examples/src/main/kotlin/space/kscience/kmath/tensors/dataSetNormalization.kt index 3ef745da3..9d5b8c2a5 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/DataSetNormalization.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/dataSetNormalization.kt @@ -5,13 +5,13 @@ package space.kscience.kmath.tensors -import space.kscience.kmath.operations.invoke -import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra +import space.kscience.kmath.tensors.core.tensorAlgebra +import space.kscience.kmath.tensors.core.withBroadcast // Dataset normalization -fun main() = BroadcastDoubleTensorAlgebra { // work in context with broadcast methods +fun main() = Double.tensorAlgebra.withBroadcast { // work in context with broadcast methods // take dataset of 5-element vectors from normal distribution val dataset = randomNormal(intArrayOf(100, 5)) * 1.5 // all elements from N(0, 1.5) diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/linearSystemSolvingWithLUP.kt similarity index 92% rename from examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt rename to examples/src/main/kotlin/space/kscience/kmath/tensors/linearSystemSolvingWithLUP.kt index 27886413f..846e338da 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/tensors/LinearSystemSolvingWithLUP.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/linearSystemSolvingWithLUP.kt @@ -5,13 +5,13 @@ package space.kscience.kmath.tensors -import space.kscience.kmath.operations.invoke -import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra import space.kscience.kmath.tensors.core.DoubleTensor +import space.kscience.kmath.tensors.core.tensorAlgebra +import space.kscience.kmath.tensors.core.withBroadcast // solving linear system with LUP decomposition -fun main() = BroadcastDoubleTensorAlgebra {// work in context with linear operations +fun main() = Double.tensorAlgebra.withBroadcast {// work in context with linear operations // set true value of x val trueX = fromArray( diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/neuralNetwork.kt similarity index 100% rename from examples/src/main/kotlin/space/kscience/kmath/tensors/NeuralNetwork.kt rename to examples/src/main/kotlin/space/kscience/kmath/tensors/neuralNetwork.kt diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt index 5f17de607..3d562f26f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt @@ -8,12 +8,14 @@ package space.kscience.kmath.linear import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.BufferedRingND import space.kscience.kmath.nd.as2D +import space.kscience.kmath.nd.asND import space.kscience.kmath.nd.ndAlgebra -import space.kscience.kmath.nd.unwrap -import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Ring import space.kscience.kmath.operations.invoke -import space.kscience.kmath.structures.* +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.BufferFactory +import space.kscience.kmath.structures.VirtualBuffer +import space.kscience.kmath.structures.indices public class BufferedLinearSpace>( @@ -33,17 +35,17 @@ public class BufferedLinearSpace>( bufferFactory(size) { elementAlgebra.initializer(it) } override fun Matrix.unaryMinus(): Matrix = ndRing(rowNum, colNum).run { - unwrap().map { -it }.as2D() + asND().map { -it }.as2D() } override fun Matrix.plus(other: Matrix): Matrix = ndRing(rowNum, colNum).run { require(shape.contentEquals(other.shape)) { "Shape mismatch on Matrix::plus. Expected $shape but found ${other.shape}" } - unwrap().plus(other.unwrap()).as2D() + asND().plus(other.asND()).as2D() } override fun Matrix.minus(other: Matrix): Matrix = ndRing(rowNum, colNum).run { require(shape.contentEquals(other.shape)) { "Shape mismatch on Matrix::minus. Expected $shape but found ${other.shape}" } - unwrap().minus(other.unwrap()).as2D() + asND().minus(other.asND()).as2D() } private fun Buffer.linearize() = if (this is VirtualBuffer) { @@ -87,13 +89,10 @@ public class BufferedLinearSpace>( } override fun Matrix.times(value: T): Matrix = ndRing(rowNum, colNum).run { - unwrap().map { it * value }.as2D() + asND().map { it * value }.as2D() } } public fun > A.linearSpace(bufferFactory: BufferFactory): BufferedLinearSpace = BufferedLinearSpace(this, bufferFactory) - -public val DoubleField.linearSpace: BufferedLinearSpace - get() = BufferedLinearSpace(this, ::DoubleBuffer) \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt new file mode 100644 index 000000000..a3e031902 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt @@ -0,0 +1,109 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. + */ + +package space.kscience.kmath.linear + +import space.kscience.kmath.misc.PerformancePitfall +import space.kscience.kmath.nd.DoubleFieldND +import space.kscience.kmath.nd.as2D +import space.kscience.kmath.nd.asND +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.indices + +public object DoubleLinearSpace : LinearSpace { + + override val elementAlgebra: DoubleField get() = DoubleField + + private fun ndRing( + rows: Int, + cols: Int, + ): DoubleFieldND = DoubleFieldND(intArrayOf(rows, cols)) + + override fun buildMatrix( + rows: Int, + columns: Int, + initializer: DoubleField.(i: Int, j: Int) -> Double + ): Matrix = ndRing(rows, columns).produce { (i, j) -> DoubleField.initializer(i, j) }.as2D() + + + override fun buildVector(size: Int, initializer: DoubleField.(Int) -> Double): DoubleBuffer = + DoubleBuffer(size) { DoubleField.initializer(it) } + + override fun Matrix.unaryMinus(): Matrix = ndRing(rowNum, colNum).run { + asND().map { -it }.as2D() + } + + override fun Matrix.plus(other: Matrix): Matrix = ndRing(rowNum, colNum).run { + require(shape.contentEquals(other.shape)) { "Shape mismatch on Matrix::plus. Expected $shape but found ${other.shape}" } + asND().plus(other.asND()).as2D() + } + + override fun Matrix.minus(other: Matrix): Matrix = ndRing(rowNum, colNum).run { + require(shape.contentEquals(other.shape)) { "Shape mismatch on Matrix::minus. Expected $shape but found ${other.shape}" } + asND().minus(other.asND()).as2D() + } + + // Create a continuous in-memory representation of this vector for better memory layout handling + private fun Buffer.linearize() = if (this is DoubleBuffer) { + this + } else { + DoubleBuffer(size) { get(it) } + } + + @OptIn(PerformancePitfall::class) + override fun Matrix.dot(other: Matrix): Matrix { + require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" } + val rows = this@dot.rows.map { it.linearize() } + val columns = other.columns.map { it.linearize() } + return buildMatrix(rowNum, other.colNum) { i, j -> + val r = rows[i] + val c = columns[j] + var res = 0.0 + for (l in r.indices) { + res += r[l] * c[l] + } + res + } + } + + @OptIn(PerformancePitfall::class) + override fun Matrix.dot(vector: Point): DoubleBuffer { + require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" } + val rows = this@dot.rows.map { it.linearize() } + return DoubleBuffer(rowNum) { i -> + val r = rows[i] + var res = 0.0 + for (j in r.indices) { + res += r[j] * vector[j] + } + res + } + + } + + override fun Matrix.times(value: Double): Matrix = ndRing(rowNum, colNum).run { + asND().map { it * value }.as2D() + } + + public override fun Point.plus(other: Point): DoubleBuffer = DoubleBuffer(size) { + get(it) + other[it] + } + + public override fun Point.minus(other: Point): DoubleBuffer = DoubleBuffer(size) { + get(it) - other[it] + } + + public override fun Point.times(value: Double): DoubleBuffer = DoubleBuffer(size) { i -> get(i) * value } + + public operator fun Point.div(value: Double): DoubleBuffer = DoubleBuffer(size) { i -> get(i) / value } + + public override fun Double.times(v: Point): DoubleBuffer = v * this + + +} + +public val DoubleField.linearSpace: DoubleLinearSpace get() = DoubleLinearSpace diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt index 91cd5abe9..f2a4336eb 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt @@ -136,7 +136,7 @@ public fun Buffer.asND(): Structure1D = Buffer1DWrapper(this) /** * Expose inner buffer of this [Structure1D] if possible */ -internal fun Structure1D.unwrap(): Buffer = when { +internal fun Structure1D.asND(): Buffer = when { this is Buffer1DWrapper -> buffer this is Structure1DWrapper && structure is BufferND -> structure.buffer else -> this diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt index 57836a9ef..8d3cc3a3f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt @@ -160,10 +160,10 @@ public fun MutableStructureND.as2D(): MutableStructure2D = this as? Mu /** * Expose inner [StructureND] if possible */ -internal fun Structure2D.unwrap(): StructureND = +internal fun Structure2D.asND(): StructureND = if (this is Structure2DWrapper) structure else this -internal fun MutableStructure2D.unwrap(): MutableStructureND = +internal fun MutableStructure2D.asND(): MutableStructureND = if (this is MutableStructure2DWrapper) structure else this diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt index 9797027c7..82754e43d 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/BigInt.kt @@ -532,7 +532,7 @@ public val BigInt.algebra: BigIntField get() = BigIntField public inline fun Buffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): Buffer = boxing(size, initializer) -public inline fun BigInt.buffer(size: Int, initializer: (Int) -> BigInt): Buffer = +public inline fun BigInt.Companion.buffer(size: Int, initializer: (Int) -> BigInt): Buffer = Buffer.boxing(size, initializer) @Deprecated("Use BigInt::mutableBuffer") @@ -543,4 +543,4 @@ public inline fun BigInt.mutableBuffer(size: Int, initializer: (Int) -> BigInt): Buffer.boxing(size, initializer) public fun BigIntField.nd(vararg shape: Int): BufferedRingND = - BufferedRingND(shape, BigIntField, Buffer.Companion::bigInt) + BufferedRingND(shape, BigIntField, BigInt::buffer) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBuffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBuffer.kt index b94a36bab..3b554ab07 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBuffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBuffer.kt @@ -25,6 +25,12 @@ public value class DoubleBuffer(public val array: DoubleArray) : MutableBuffer assertMatrixEquals(expected: StructureND, actual: StructureND = VirtualMatrix(6, 6) { row, col -> when { col == 0 -> .50 @@ -49,7 +50,7 @@ class MatrixTest { infix fun Matrix.pow(power: Int): Matrix { var res = this repeat(power - 1) { - res = LinearSpace.double.run { res dot this@pow } + res = res dot this@pow } return res } @@ -58,19 +59,18 @@ class MatrixTest { } @Test - fun test2DDot() { + fun test2DDot() = Double.algebra.linearSpace.run { val firstMatrix = StructureND.auto(2, 3) { (i, j) -> (i + j).toDouble() }.as2D() val secondMatrix = StructureND.auto(3, 2) { (i, j) -> (i + j).toDouble() }.as2D() - LinearSpace.double.run { // val firstMatrix = produce(2, 3) { i, j -> (i + j).toDouble() } // val secondMatrix = produce(3, 2) { i, j -> (i + j).toDouble() } - val result = firstMatrix dot secondMatrix - assertEquals(2, result.rowNum) - assertEquals(2, result.colNum) - assertEquals(8.0, result[0, 1]) - assertEquals(8.0, result[1, 0]) - assertEquals(14.0, result[1, 1]) - } + val result = firstMatrix dot secondMatrix + assertEquals(2, result.rowNum) + assertEquals(2, result.colNum) + assertEquals(8.0, result[0, 1]) + assertEquals(8.0, result[1, 0]) + assertEquals(14.0, result[1, 1]) + } } diff --git a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt index b2982b335..e58976f4a 100644 --- a/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt +++ b/kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt @@ -5,7 +5,7 @@ package space.kscience.kmath.structures -import space.kscience.kmath.linear.LinearSpace +import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.combine @@ -13,6 +13,7 @@ import space.kscience.kmath.nd.get import space.kscience.kmath.nd.ndAlgebra import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Norm +import space.kscience.kmath.operations.algebra import space.kscience.kmath.operations.invoke import kotlin.math.abs import kotlin.math.pow @@ -42,17 +43,18 @@ class NumberNDFieldTest { } @Test - fun testGeneration() { + fun testGeneration() = Double.algebra.linearSpace.run { - val array = LinearSpace.double.buildMatrix(3, 3) { i, j -> + val array = buildMatrix(3, 3) { i, j -> (i * 10 + j).toDouble() } - for (i in 0..2) + for (i in 0..2) { for (j in 0..2) { val expected = (i * 10 + j).toDouble() assertEquals(expected, array[i, j], "Error at index [$i, $j]") } + } } @Test diff --git a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt index f6c4415dc..c47f43723 100644 --- a/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt +++ b/kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt @@ -5,13 +5,11 @@ package space.kscience.kmath.dimensions -import space.kscience.kmath.linear.LinearSpace -import space.kscience.kmath.linear.Matrix -import space.kscience.kmath.linear.Point -import space.kscience.kmath.linear.transpose +import space.kscience.kmath.linear.* import space.kscience.kmath.nd.Structure2D import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.Ring +import space.kscience.kmath.operations.algebra import kotlin.jvm.JvmInline /** @@ -151,7 +149,7 @@ public value class DMatrixContext>(public val context: context.run { (this@transpose as Matrix).transpose() }.coerce() public companion object { - public val real: DMatrixContext = DMatrixContext(LinearSpace.double) + public val real: DMatrixContext = DMatrixContext(Double.algebra.linearSpace) } } diff --git a/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleMatrixTest.kt b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleMatrixTest.kt index 79f05daa5..3277410c0 100644 --- a/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleMatrixTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleMatrixTest.kt @@ -5,12 +5,12 @@ package space.kscience.kmath.real -import space.kscience.kmath.linear.LinearSpace +import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.linear.matrix import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.nd.StructureND -import space.kscience.kmath.real.* +import space.kscience.kmath.operations.algebra import space.kscience.kmath.structures.contentEquals import kotlin.test.Test import kotlin.test.assertEquals @@ -59,13 +59,13 @@ internal class DoubleMatrixTest { } @Test - fun testMatrixAndDouble() { + fun testMatrixAndDouble() = Double.algebra.linearSpace.run { val matrix1 = realMatrix(2, 3)( 1.0, 0.0, 3.0, 4.0, 6.0, 2.0 ) val matrix2 = (matrix1 * 2.5 + 1.0 - 2.0) / 2.0 - val expectedResult = LinearSpace.double.matrix(2, 3)( + val expectedResult = matrix(2, 3)( 0.75, -0.5, 3.25, 4.5, 7.0, 2.0 ) @@ -159,8 +159,8 @@ internal class DoubleMatrixTest { } @Test - fun testAllElementOperations() { - val matrix1 = LinearSpace.double.matrix(2, 4)( + fun testAllElementOperations() = Double.algebra.linearSpace.run { + val matrix1 = matrix(2, 4)( -1.0, 0.0, 3.0, 15.0, 4.0, -6.0, 7.0, -11.0 ) diff --git a/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleVectorTest.kt b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleVectorTest.kt index 7bb936658..771981772 100644 --- a/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleVectorTest.kt +++ b/kmath-for-real/src/commonTest/kotlin/space/kscience/kmath/real/DoubleVectorTest.kt @@ -5,10 +5,10 @@ package space.kscience.kmath.real -import space.kscience.kmath.linear.LinearSpace import space.kscience.kmath.linear.asMatrix +import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.linear.transpose -import space.kscience.kmath.real.plus +import space.kscience.kmath.operations.algebra import space.kscience.kmath.structures.DoubleBuffer import kotlin.test.Test import kotlin.test.assertEquals @@ -30,12 +30,12 @@ internal class DoubleVectorTest { } @Test - fun testDot() { + fun testDot() = Double.algebra.linearSpace.run { val vector1 = DoubleBuffer(5) { it.toDouble() } val vector2 = DoubleBuffer(5) { 5 - it.toDouble() } val matrix1 = vector1.asMatrix() val matrix2 = vector2.asMatrix().transpose() - val product = LinearSpace.double.run { matrix1 dot matrix2 } + val product = matrix1 dot matrix2 assertEquals(5.0, product[1, 0]) assertEquals(6.0, product[2, 2]) } diff --git a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt index 00df0944f..68941304f 100644 --- a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt @@ -13,6 +13,7 @@ import space.kscience.kmath.linear.* import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.misc.log import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.algebra import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.DoubleL2Norm @@ -32,7 +33,7 @@ public class QowRuns(public val runs: Int) : OptimizationFeature { @UnstableKMathAPI public object QowOptimizer : Optimizer { - private val linearSpace: LinearSpace = LinearSpace.double + private val linearSpace: LinearSpace = Double.algebra.linearSpace private val solver: LinearSolver = linearSpace.lupSolver() @OptIn(UnstableKMathAPI::class) diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt index 3eb8e5636..3d73fd53b 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BroadcastDoubleTensorAlgebra.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.tensors.core +import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.tensors.api.Tensor import space.kscience.kmath.tensors.core.internal.array import space.kscience.kmath.tensors.core.internal.broadcastTensors @@ -90,4 +91,12 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() { newOther.mutableBuffer.array()[tensor.bufferStart + i] } } -} \ No newline at end of file +} + + +/** + * Compute a value using broadcast double tensor algebra + */ +@UnstableKMathAPI +public fun DoubleTensorAlgebra.withBroadcast(block: BroadcastDoubleTensorAlgebra.() -> R): R = + BroadcastDoubleTensorAlgebra.block() \ No newline at end of file diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt index db18220cd..8e39e6cdd 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/DoubleTensorAlgebra.kt @@ -949,4 +949,6 @@ public open class DoubleTensorAlgebra : override fun Tensor.lu(): Triple = lu(1e-9) } +public val Double.Companion.tensorAlgebra: DoubleTensorAlgebra.Companion get() = DoubleTensorAlgebra + diff --git a/settings.gradle.kts b/settings.gradle.kts index 0fc77b38e..8cfa62133 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -5,11 +5,11 @@ pluginManagement { gradlePluginPortal() } - val kotlinVersion = "1.5.30" + val kotlinVersion = "1.6.0-M1" plugins { id("org.jetbrains.kotlinx.benchmark") version "0.3.1" - id("ru.mipt.npm.gradle.project") version "0.10.3" + id("ru.mipt.npm.gradle.project") version "0.10.4" kotlin("multiplatform") version kotlinVersion kotlin("plugin.allopen") version kotlinVersion } @@ -17,6 +17,9 @@ pluginManagement { rootProject.name = "kmath" +enableFeaturePreview("TYPESAFE_PROJECT_ACCESSORS") +enableFeaturePreview("VERSION_CATALOGS") + include( ":kmath-memory", ":kmath-complex", From 0f634688cc4ed5cba39596a4c72b58e30fec4d2f Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sat, 2 Oct 2021 15:56:57 +0300 Subject: [PATCH 125/132] API cleanup --- gradle.properties | 6 ++- .../DoubleBufferOperations.kt} | 48 +++++++++---------- .../kmath/operations/OptionalOperations.kt | 4 +- .../kscience/kmath/ejml/EjmlLinearSpace.kt | 4 +- .../space/kscience/kmath/real/RealVector.kt | 7 +-- 5 files changed, 37 insertions(+), 32 deletions(-) rename kmath-core/src/commonMain/kotlin/space/kscience/kmath/{structures/DoubleBufferField.kt => operations/DoubleBufferOperations.kt} (89%) diff --git a/gradle.properties b/gradle.properties index 49bbf36dd..959511c68 100644 --- a/gradle.properties +++ b/gradle.properties @@ -4,9 +4,11 @@ # kotlin.code.style=official -kotlin.mpp.enableGranularSourceSetsMetadata=true kotlin.mpp.stability.nowarn=true -kotlin.native.enableDependencyPropagation=false + +#kotlin.mpp.enableGranularSourceSetsMetadata=true +#kotlin.native.enableDependencyPropagation=false + kotlin.jupyter.add.scanner=false org.gradle.configureondemand=true diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferOperations.kt similarity index 89% rename from kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt rename to kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferOperations.kt index 2bf6de3cb..a95bd2541 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/DoubleBufferField.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferOperations.kt @@ -3,18 +3,18 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ -package space.kscience.kmath.structures +package space.kscience.kmath.operations import space.kscience.kmath.linear.Point -import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.* +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.fold import kotlin.math.* /** * [ExtendedFieldOperations] over [DoubleBuffer]. */ -@Deprecated("To be replaced by generic BufferAlgebra") -public object DoubleBufferFieldOperations : ExtendedFieldOperations> { +public object DoubleBufferOperations : ExtendedFieldOperations> { override fun Buffer.unaryMinus(): DoubleBuffer = if (this is DoubleBuffer) { DoubleBuffer(size) { -array[it] } } else { @@ -179,13 +179,13 @@ public class DoubleBufferField(public val size: Int) : ExtendedField = DoubleBuffer(size) { value.toDouble() } - override fun Buffer.unaryMinus(): Buffer = DoubleBufferFieldOperations.run { + override fun Buffer.unaryMinus(): Buffer = DoubleBufferOperations.run { -this@unaryMinus } override fun add(a: Buffer, b: Buffer): DoubleBuffer { require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } - return DoubleBufferFieldOperations.add(a, b) + return DoubleBufferOperations.add(a, b) } override fun scale(a: Buffer, value: Double): DoubleBuffer { @@ -199,87 +199,87 @@ public class DoubleBufferField(public val size: Int) : ExtendedField, b: Buffer): DoubleBuffer { require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } - return DoubleBufferFieldOperations.multiply(a, b) + return DoubleBufferOperations.multiply(a, b) } override fun divide(a: Buffer, b: Buffer): DoubleBuffer { require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } - return DoubleBufferFieldOperations.divide(a, b) + return DoubleBufferOperations.divide(a, b) } override fun sin(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.sin(arg) + return DoubleBufferOperations.sin(arg) } override fun cos(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.cos(arg) + return DoubleBufferOperations.cos(arg) } override fun tan(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.tan(arg) + return DoubleBufferOperations.tan(arg) } override fun asin(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.asin(arg) + return DoubleBufferOperations.asin(arg) } override fun acos(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.acos(arg) + return DoubleBufferOperations.acos(arg) } override fun atan(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.atan(arg) + return DoubleBufferOperations.atan(arg) } override fun sinh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.sinh(arg) + return DoubleBufferOperations.sinh(arg) } override fun cosh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.cosh(arg) + return DoubleBufferOperations.cosh(arg) } override fun tanh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.tanh(arg) + return DoubleBufferOperations.tanh(arg) } override fun asinh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.asinh(arg) + return DoubleBufferOperations.asinh(arg) } override fun acosh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.acosh(arg) + return DoubleBufferOperations.acosh(arg) } override fun atanh(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.atanh(arg) + return DoubleBufferOperations.atanh(arg) } override fun power(arg: Buffer, pow: Number): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.power(arg, pow) + return DoubleBufferOperations.power(arg, pow) } override fun exp(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.exp(arg) + return DoubleBufferOperations.exp(arg) } override fun ln(arg: Buffer): DoubleBuffer { require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferFieldOperations.ln(arg) + return DoubleBufferOperations.ln(arg) } override fun norm(arg: Buffer): Double = DoubleL2Norm.norm(arg) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt index 7f44eda49..3a2703c54 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt @@ -306,14 +306,14 @@ public fun >> tanh(arg: T): T */ @UnstableKMathAPI @Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> asinh(arg: T): T = arg.context.asinh(arg) +public fun >> asinh(arg: T): T = arg.context.asinh(arg) /** * Computes the inverse hyperbolic cosine of [arg]. */ @UnstableKMathAPI @Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> acosh(arg: T): T = arg.context.acosh(arg) +public fun >> acosh(arg: T): T = arg.context.acosh(arg) /** * Computes the inverse hyperbolic tangent of [arg]. diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt index 4a53af60d..25333157a 100644 --- a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt @@ -40,6 +40,8 @@ public abstract class EjmlLinearSpace, out M : org.ejml public abstract override fun buildVector(size: Int, initializer: A.(Int) -> T): EjmlVector + @Suppress("UNCHECKED_CAST") @UnstableKMathAPI - public fun EjmlMatrix.inverse(): Structure2D = computeFeature(this, InverseMatrixFeature::class)?.inverse as Structure2D + public fun EjmlMatrix.inverse(): Structure2D = + computeFeature(this, InverseMatrixFeature::class)?.inverse as Structure2D } diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt index b707ebfc5..cca1c3551 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt @@ -7,11 +7,12 @@ package space.kscience.kmath.real import space.kscience.kmath.linear.Point import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.Norm -import space.kscience.kmath.structures.* +import space.kscience.kmath.operations.DoubleL2Norm +import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.MutableBuffer.Companion.double +import space.kscience.kmath.structures.asBuffer +import space.kscience.kmath.structures.indices import kotlin.math.pow -import kotlin.math.sqrt public typealias DoubleVector = Point From 85aefb538096e96f9e50d68896c20378f3d9ba49 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sat, 2 Oct 2021 16:14:38 +0300 Subject: [PATCH 126/132] Completely remove AlgebraElements.kt --- CHANGELOG.md | 1 + .../kmath/ejml/codegen/ejmlCodegen.kt | 20 +-- .../kscience/kmath/linear/dotPerformance.kt | 2 +- .../kmath/operations/AlgebraElements.kt | 128 ----------------- .../kmath/operations/OptionalOperations.kt | 130 ------------------ .../kmath/optimization/QowOptimizer.kt | 3 +- 6 files changed, 14 insertions(+), 270 deletions(-) delete mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt diff --git a/CHANGELOG.md b/CHANGELOG.md index c27dafeb4..6cb9f57f4 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -53,6 +53,7 @@ - Expression algebra builders - Complex and Quaternion no longer are elements. - Second generic from DifferentiableExpression +- Algebra elements are completely removed. Use algebra contexts instead. ### Fixed - Ring inherits RingOperations, not GroupOperations diff --git a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt index a533e98a5..cfebf61e7 100644 --- a/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt +++ b/buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt @@ -240,10 +240,10 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, } override val q: Matrix<${type}> by lazy { - qr.getQ(null, false).wrapMatrix() + OrthogonalFeature + qr.getQ(null, false).wrapMatrix().withFeature(OrthogonalFeature) } - override val r: Matrix<${type}> by lazy { qr.getR(null, false).wrapMatrix() + UFeature } + override val r: Matrix<${type}> by lazy { qr.getR(null, false).wrapMatrix().withFeature(UFeature) } } CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<${type}> { @@ -251,7 +251,7 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, val cholesky = DecompositionFactory_${ops}.chol(structure.rowNum, true).apply { decompose(origin.copy()) } - cholesky.getT(null).wrapMatrix() + LFeature + cholesky.getT(null).wrapMatrix().withFeature(LFeature) } } @@ -261,11 +261,11 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, } override val l: Matrix<${type}> by lazy { - lup.getLower(null).wrapMatrix() + LFeature + lup.getLower(null).wrapMatrix().withFeature(LFeature) } override val u: Matrix<${type}> by lazy { - lup.getUpper(null).wrapMatrix() + UFeature + lup.getUpper(null).wrapMatrix().withFeature(UFeature) } override val p: Matrix<${type}> by lazy { lup.getRowPivot(null).wrapMatrix() } @@ -275,10 +275,10 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, } override val q: Matrix<${type}> by lazy { - qr.getQ(null, false).wrapMatrix() + OrthogonalFeature + qr.getQ(null, false).wrapMatrix().withFeature(OrthogonalFeature) } - override val r: Matrix<${type}> by lazy { qr.getR(null, false).wrapMatrix() + UFeature } + override val r: Matrix<${type}> by lazy { qr.getR(null, false).wrapMatrix().withFeature(UFeature) } } CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<${type}> { @@ -286,7 +286,7 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, val cholesky = DecompositionFactory_${ops}.cholesky().apply { decompose(origin.copy()) } - (cholesky.getT(null) as ${ejmlMatrixParentTypeMatrix}).wrapMatrix() + LFeature + (cholesky.getT(null) as ${ejmlMatrixParentTypeMatrix}).wrapMatrix().withFeature(LFeature) } } @@ -297,11 +297,11 @@ public object EjmlLinearSpace${ops} : EjmlLinearSpace<${type}, ${kmathAlgebra}, } override val l: Matrix<${type}> by lazy { - lu.getLower(null).wrapMatrix() + LFeature + lu.getLower(null).wrapMatrix().withFeature(LFeature) } override val u: Matrix<${type}> by lazy { - lu.getUpper(null).wrapMatrix() + UFeature + lu.getUpper(null).wrapMatrix().withFeature(UFeature) } override val inverse: Matrix<${type}> by lazy { diff --git a/examples/src/main/kotlin/space/kscience/kmath/linear/dotPerformance.kt b/examples/src/main/kotlin/space/kscience/kmath/linear/dotPerformance.kt index 31762b6d8..6e8767a5b 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/linear/dotPerformance.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/linear/dotPerformance.kt @@ -24,7 +24,7 @@ fun main() { val time = measureTimeMillis { with(Double.algebra.linearSpace) { repeat(10) { - val res = matrix1 dot matrix2 + matrix1 dot matrix2 } } } diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt deleted file mode 100644 index 7669e073a..000000000 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt +++ /dev/null @@ -1,128 +0,0 @@ -/* - * Copyright 2018-2021 KMath contributors. - * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. - */ - -package space.kscience.kmath.operations - -import space.kscience.kmath.misc.UnstableKMathAPI - -/** - * The generic mathematics elements that is able to store its context - * - * @param C the type of mathematical context for this element. - * @param T the type wrapped by this wrapper. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public interface AlgebraElement> { - /** - * The context this element belongs to. - */ - public val context: C -} -// -///** -// * Divides this element by number. -// * -// * @param k the divisor. -// * @return the quotient. -// */ -//public operator fun , S : Space> T.div(k: Number): T = -// context.multiply(this, 1.0 / k.toDouble()) -// -///** -// * Multiplies this element by number. -// * -// * @param k the multiplicand. -// * @return the product. -// */ -//public operator fun , S : Space> T.times(k: Number): T = -// context.multiply(this, k.toDouble()) - -/** - * Subtracts element from this one. - * - * @param b the subtrahend. - * @return the difference. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public operator fun , S : NumbersAddOperations> T.minus(b: T): T = - context.add(this, context.run { -b }) - -/** - * Adds element to this one. - * - * @receiver the augend. - * @param b the addend. - * @return the sum. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public operator fun , S : Ring> T.plus(b: T): T = - context.add(this, b) - -///** -// * Number times element -// */ -//public operator fun , S : Space> Number.times(element: T): T = -// element.times(this) - -/** - * Multiplies this element by another one. - * - * @receiver the multiplicand. - * @param b the multiplier. - * @return the product. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public operator fun , R : Ring> T.times(b: T): T = - context.multiply(this, b) - - -/** - * Divides this element by another one. - * - * @param b the divisor. - * @return the quotient. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public operator fun , F : Field> T.div(b: T): T = - context.divide(this, b) - - -/** - * The element of [Group]. - * - * @param T the type of space operation results. - * @param I self type of the element. Needed for static type checking. - * @param S the type of space. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public interface GroupElement, S : Group> : AlgebraElement - -/** - * The element of [Ring]. - * - * @param T the type of ring operation results. - * @param I self type of the element. Needed for static type checking. - * @param R the type of ring. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public interface RingElement, R : Ring> : GroupElement - -/** - * The element of [Field]. - * - * @param T the type of field operation results. - * @param I self type of the element. Needed for static type checking. - * @param F the type of field. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public interface FieldElement, F : Field> : RingElement diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt index 3a2703c54..d32e03533 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/OptionalOperations.kt @@ -5,8 +5,6 @@ package space.kscience.kmath.operations -import space.kscience.kmath.misc.UnstableKMathAPI - /** * A container for trigonometric operations for specific type. * @@ -76,48 +74,6 @@ public interface TrigonometricOperations : Algebra { } } -/** - * Computes the sine of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> sin(arg: T): T = arg.context.sin(arg) - -/** - * Computes the cosine of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> cos(arg: T): T = arg.context.cos(arg) - -/** - * Computes the tangent of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> tan(arg: T): T = arg.context.tan(arg) - -/** - * Computes the inverse sine of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> asin(arg: T): T = arg.context.asin(arg) - -/** - * Computes the inverse cosine of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> acos(arg: T): T = arg.context.acos(arg) - -/** - * Computes the inverse tangent of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> atan(arg: T): T = arg.context.atan(arg) - /** * A context extension to include power operations based on exponentiation. * @@ -152,31 +108,6 @@ public interface PowerOperations : Algebra { } } -/** - * Raises this element to the power [power]. - * - * @receiver the base. - * @param power the exponent. - * @return the base raised to the power. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public infix fun >> T.pow(power: Double): T = context.power(this, power) - -/** - * Computes the square root of the value [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> sqrt(arg: T): T = arg pow 0.5 - -/** - * Computes the square of the value [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> sqr(arg: T): T = arg pow 2.0 - /** * A container for operations related to `exp` and `ln` functions. * @@ -266,62 +197,6 @@ public interface ExponentialOperations : Algebra { } } -/** - * The identifier of exponential function. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> exp(arg: T): T = arg.context.exp(arg) - -/** - * The identifier of natural logarithm. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> ln(arg: T): T = arg.context.ln(arg) - - -/** - * Computes the hyperbolic sine of [arg]. - */ -@UnstableKMathAPI -public fun >> sinh(arg: T): T = arg.context.sinh(arg) - -/** - * Computes the hyperbolic cosine of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> cosh(arg: T): T = arg.context.cosh(arg) - -/** - * Computes the hyperbolic tangent of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> tanh(arg: T): T = arg.context.tanh(arg) - -/** - * Computes the inverse hyperbolic sine of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> asinh(arg: T): T = arg.context.asinh(arg) - -/** - * Computes the inverse hyperbolic cosine of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> acosh(arg: T): T = arg.context.acosh(arg) - -/** - * Computes the inverse hyperbolic tangent of [arg]. - */ -@UnstableKMathAPI -@Deprecated("AlgebraElements are considered odd and will be removed in future releases.") -public fun >> atanh(arg: T): T = arg.context.atanh(arg) - /** * A container for norm functional on element. * @@ -335,8 +210,3 @@ public interface Norm { public fun norm(arg: T): R } -/** - * Computes the norm of [arg] (i.e., absolute value or vector length). - */ -@UnstableKMathAPI -public fun >, R> norm(arg: T): R = arg.context.norm(arg) diff --git a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt index 68941304f..babbaf6cd 100644 --- a/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt +++ b/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt @@ -13,9 +13,10 @@ import space.kscience.kmath.linear.* import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.misc.log import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.DoubleL2Norm import space.kscience.kmath.operations.algebra import space.kscience.kmath.structures.DoubleBuffer -import space.kscience.kmath.structures.DoubleL2Norm + public class QowRuns(public val runs: Int) : OptimizationFeature { init { From abae29bbede98231c17ebe00708443ac39fbb854 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sat, 2 Oct 2021 18:54:45 +0300 Subject: [PATCH 127/132] DoubleBuffer algebra refactoring --- .../space/kscience/kmath/fit/chiSquared.kt | 11 +- .../kotlin/space/kscience/kmath/fit/qowFit.kt | 4 +- .../kmath/functions/interpolateSquare.kt | 2 +- .../commons/transform/Transformations.kt | 7 +- .../commons/optimization/OptimizeTest.kt | 2 +- .../kmath/expressions/specialExpressions.kt | 2 +- .../kmath/linear/DoubleLinearSpace.kt | 17 +- .../space/kscience/kmath/nd/Structure1D.kt | 2 +- .../kmath/operations/DoubleBufferField.kt | 130 +++ .../operations/DoubleBufferOperations.kt | 150 +-- .../bufferOperation.kt | 3 +- .../kscience/kmath/operations/numbers.kt | 5 +- .../space/kscience/kmath/structures/Buffer.kt | 4 +- .../kmath/streaming/RingBufferTest.kt | 2 +- .../space/kscience/kmath/ejml/_generated.kt | 995 ++++++++++++++++++ .../space/kscience/kmath/real/RealMatrix.kt | 2 +- .../integration/GaussIntegratorRuleFactory.kt | 2 +- .../kmath/integration/SplineIntegrator.kt | 6 +- .../kscience/kmath/geometry/Vector2DTest.kt | 5 +- .../kscience/kmath/geometry/Vector3DTest.kt | 2 +- .../kmath/histogram/UnivariateHistogram.kt | 4 +- .../kscience/kmath/jupyter/KMathJupyter.kt | 2 +- .../space/kscience/kmath/stat/Median.kt | 2 +- .../kmath/tensors/core/internal/linUtils.kt | 2 +- .../kmath/tensors/core/internal/utils.kt | 1 + 25 files changed, 1203 insertions(+), 161 deletions(-) create mode 100644 kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferField.kt rename kmath-core/src/commonMain/kotlin/space/kscience/kmath/{structures => operations}/bufferOperation.kt (97%) create mode 100644 kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt diff --git a/examples/src/main/kotlin/space/kscience/kmath/fit/chiSquared.kt b/examples/src/main/kotlin/space/kscience/kmath/fit/chiSquared.kt index 8db97d672..dbe0b8454 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/fit/chiSquared.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/fit/chiSquared.kt @@ -10,20 +10,21 @@ import kotlinx.html.h3 import space.kscience.kmath.commons.expressions.DSProcessor import space.kscience.kmath.commons.optimization.CMOptimizer import space.kscience.kmath.distributions.NormalDistribution -import space.kscience.kmath.expressions.binding import space.kscience.kmath.expressions.chiSquaredExpression import space.kscience.kmath.expressions.symbol -import space.kscience.kmath.optimization.* +import space.kscience.kmath.operations.asIterable +import space.kscience.kmath.operations.toList +import space.kscience.kmath.optimization.FunctionOptimizationTarget +import space.kscience.kmath.optimization.optimizeWith +import space.kscience.kmath.optimization.resultPoint +import space.kscience.kmath.optimization.resultValue import space.kscience.kmath.real.DoubleVector import space.kscience.kmath.real.map import space.kscience.kmath.real.step import space.kscience.kmath.stat.RandomGenerator -import space.kscience.kmath.structures.asIterable -import space.kscience.kmath.structures.toList import space.kscience.plotly.* import space.kscience.plotly.models.ScatterMode import space.kscience.plotly.models.TraceValues -import kotlin.math.abs import kotlin.math.pow import kotlin.math.sqrt diff --git a/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt b/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt index 04764d763..d52976671 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/fit/qowFit.kt @@ -13,6 +13,8 @@ import space.kscience.kmath.distributions.NormalDistribution import space.kscience.kmath.expressions.Symbol import space.kscience.kmath.expressions.binding import space.kscience.kmath.expressions.symbol +import space.kscience.kmath.operations.asIterable +import space.kscience.kmath.operations.toList import space.kscience.kmath.optimization.QowOptimizer import space.kscience.kmath.optimization.chiSquaredOrNull import space.kscience.kmath.optimization.fitWith @@ -20,8 +22,6 @@ import space.kscience.kmath.optimization.resultPoint import space.kscience.kmath.real.map import space.kscience.kmath.real.step import space.kscience.kmath.stat.RandomGenerator -import space.kscience.kmath.structures.asIterable -import space.kscience.kmath.structures.toList import space.kscience.plotly.* import space.kscience.plotly.models.ScatterMode import kotlin.math.abs diff --git a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolateSquare.kt b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolateSquare.kt index 76422d658..3f958b3b0 100644 --- a/examples/src/main/kotlin/space/kscience/kmath/functions/interpolateSquare.kt +++ b/examples/src/main/kotlin/space/kscience/kmath/functions/interpolateSquare.kt @@ -8,8 +8,8 @@ package space.kscience.kmath.functions import space.kscience.kmath.interpolation.SplineInterpolator import space.kscience.kmath.interpolation.interpolatePolynomials import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.real.map import space.kscience.kmath.real.step -import space.kscience.kmath.structures.map import space.kscience.plotly.Plotly import space.kscience.plotly.UnstablePlotlyAPI import space.kscience.plotly.makeFile diff --git a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt index 1a99e9fc6..73ab91542 100644 --- a/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt +++ b/kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt @@ -10,10 +10,13 @@ import kotlinx.coroutines.flow.Flow import kotlinx.coroutines.flow.map import org.apache.commons.math3.transform.* import space.kscience.kmath.complex.Complex +import space.kscience.kmath.operations.SuspendBufferTransform import space.kscience.kmath.streaming.chunked import space.kscience.kmath.streaming.spread -import space.kscience.kmath.structures.* - +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.VirtualBuffer +import space.kscience.kmath.structures.asBuffer /** diff --git a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt index 681ec9ebc..c670ceead 100644 --- a/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt +++ b/kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt @@ -13,11 +13,11 @@ import space.kscience.kmath.expressions.Symbol.Companion.x import space.kscience.kmath.expressions.Symbol.Companion.y import space.kscience.kmath.expressions.chiSquaredExpression import space.kscience.kmath.expressions.symbol +import space.kscience.kmath.operations.map import space.kscience.kmath.optimization.* import space.kscience.kmath.stat.RandomGenerator import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.asBuffer -import space.kscience.kmath.structures.map import kotlin.math.pow import kotlin.test.Test diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/specialExpressions.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/specialExpressions.kt index 6b17dfca5..907ce4004 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/specialExpressions.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/specialExpressions.kt @@ -6,8 +6,8 @@ package space.kscience.kmath.expressions import space.kscience.kmath.operations.ExtendedField +import space.kscience.kmath.operations.asIterable import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.asIterable import space.kscience.kmath.structures.indices import kotlin.jvm.JvmName diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt index a3e031902..4a1311b54 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt @@ -9,6 +9,7 @@ import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.DoubleFieldND import space.kscience.kmath.nd.as2D import space.kscience.kmath.nd.asND +import space.kscience.kmath.operations.DoubleBufferOperations import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer @@ -89,17 +90,21 @@ public object DoubleLinearSpace : LinearSpace { asND().map { it * value }.as2D() } - public override fun Point.plus(other: Point): DoubleBuffer = DoubleBuffer(size) { - get(it) + other[it] + public override fun Point.plus(other: Point): DoubleBuffer = DoubleBufferOperations.run { + this@plus + other } - public override fun Point.minus(other: Point): DoubleBuffer = DoubleBuffer(size) { - get(it) - other[it] + public override fun Point.minus(other: Point): DoubleBuffer = DoubleBufferOperations.run { + this@minus - other } - public override fun Point.times(value: Double): DoubleBuffer = DoubleBuffer(size) { i -> get(i) * value } + public override fun Point.times(value: Double): DoubleBuffer = DoubleBufferOperations.run { + scale(this@times, value) + } - public operator fun Point.div(value: Double): DoubleBuffer = DoubleBuffer(size) { i -> get(i) / value } + public operator fun Point.div(value: Double): DoubleBuffer = DoubleBufferOperations.run { + scale(this@div, 1.0 / value) + } public override fun Double.times(v: Point): DoubleBuffer = v * this diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt index f2a4336eb..3dcc77334 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt @@ -6,10 +6,10 @@ package space.kscience.kmath.nd import space.kscience.kmath.misc.PerformancePitfall +import space.kscience.kmath.operations.asSequence import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.MutableBuffer import space.kscience.kmath.structures.asMutableBuffer -import space.kscience.kmath.structures.asSequence import kotlin.jvm.JvmInline /** diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferField.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferField.kt new file mode 100644 index 000000000..acc2c2dc0 --- /dev/null +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferField.kt @@ -0,0 +1,130 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. + */ + +package space.kscience.kmath.operations + +import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.structures.DoubleBuffer + +/** + * [ExtendedField] over [DoubleBuffer]. + * + * @property size the size of buffers to operate on. + */ +public class DoubleBufferField(public val size: Int) : ExtendedField>, DoubleBufferOperations() { + override val zero: Buffer by lazy { DoubleBuffer(size) { 0.0 } } + override val one: Buffer by lazy { DoubleBuffer(size) { 1.0 } } + + override fun sinh(arg: Buffer): DoubleBuffer = super.sinh(arg) + + override fun cosh(arg: Buffer): DoubleBuffer = super.cosh(arg) + + override fun tanh(arg: Buffer): DoubleBuffer = super.tanh(arg) + + override fun asinh(arg: Buffer): DoubleBuffer = super.asinh(arg) + + override fun acosh(arg: Buffer): DoubleBuffer = super.acosh(arg) + + override fun atanh(arg: Buffer): DoubleBuffer= super.atanh(arg) + + // override fun number(value: Number): Buffer = DoubleBuffer(size) { value.toDouble() } +// +// override fun Buffer.unaryMinus(): Buffer = DoubleBufferOperations.run { +// -this@unaryMinus +// } +// +// override fun add(a: Buffer, b: Buffer): DoubleBuffer { +// require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } +// return DoubleBufferOperations.add(a, b) +// } +// + +// +// override fun multiply(a: Buffer, b: Buffer): DoubleBuffer { +// require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } +// return DoubleBufferOperations.multiply(a, b) +// } +// +// override fun divide(a: Buffer, b: Buffer): DoubleBuffer { +// require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } +// return DoubleBufferOperations.divide(a, b) +// } +// +// override fun sin(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.sin(arg) +// } +// +// override fun cos(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.cos(arg) +// } +// +// override fun tan(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.tan(arg) +// } +// +// override fun asin(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.asin(arg) +// } +// +// override fun acos(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.acos(arg) +// } +// +// override fun atan(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.atan(arg) +// } +// +// override fun sinh(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.sinh(arg) +// } +// +// override fun cosh(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.cosh(arg) +// } +// +// override fun tanh(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.tanh(arg) +// } +// +// override fun asinh(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.asinh(arg) +// } +// +// override fun acosh(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.acosh(arg) +// } +// +// override fun atanh(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.atanh(arg) +// } +// +// override fun power(arg: Buffer, pow: Number): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.power(arg, pow) +// } +// +// override fun exp(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.exp(arg) +// } +// +// override fun ln(arg: Buffer): DoubleBuffer { +// require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } +// return DoubleBufferOperations.ln(arg) +// } + +} \ No newline at end of file diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferOperations.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferOperations.kt index a95bd2541..50b821962 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferOperations.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/DoubleBufferOperations.kt @@ -8,13 +8,13 @@ package space.kscience.kmath.operations import space.kscience.kmath.linear.Point import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer -import space.kscience.kmath.structures.fold + import kotlin.math.* /** * [ExtendedFieldOperations] over [DoubleBuffer]. */ -public object DoubleBufferOperations : ExtendedFieldOperations> { +public abstract class DoubleBufferOperations : ExtendedFieldOperations>, Norm, Double> { override fun Buffer.unaryMinus(): DoubleBuffer = if (this is DoubleBuffer) { DoubleBuffer(size) { -array[it] } } else { @@ -32,7 +32,22 @@ public object DoubleBufferOperations : ExtendedFieldOperations> { DoubleBuffer(DoubleArray(a.size) { aArray[it] + bArray[it] }) } else DoubleBuffer(DoubleArray(a.size) { a[it] + b[it] }) } -// + + override fun Buffer.plus(b: Buffer): DoubleBuffer = add(this, b) + + override fun Buffer.minus(b: Buffer): DoubleBuffer { + require(b.size == this.size) { + "The size of the first buffer ${this.size} should be the same as for second one: ${b.size} " + } + + return if (this is DoubleBuffer && b is DoubleBuffer) { + val aArray = this.array + val bArray = b.array + DoubleBuffer(DoubleArray(this.size) { aArray[it] - bArray[it] }) + } else DoubleBuffer(DoubleArray(this.size) { this[it] - b[it] }) + } + + // // override fun multiply(a: Buffer, k: Number): RealBuffer { // val kValue = k.toDouble() // @@ -159,128 +174,21 @@ public object DoubleBufferOperations : ExtendedFieldOperations> { override fun ln(arg: Buffer): DoubleBuffer = if (arg is DoubleBuffer) { val array = arg.array DoubleBuffer(DoubleArray(arg.size) { ln(array[it]) }) - } else + } else { DoubleBuffer(DoubleArray(arg.size) { ln(arg[it]) }) + } + + override fun norm(arg: Buffer): Double = DoubleL2Norm.norm(arg) + + override fun scale(a: Buffer, value: Double): DoubleBuffer = if (a is DoubleBuffer) { + val aArray = a.array + DoubleBuffer(DoubleArray(a.size) { aArray[it] * value }) + } else DoubleBuffer(DoubleArray(a.size) { a[it] * value }) + + public companion object : DoubleBufferOperations() } public object DoubleL2Norm : Norm, Double> { override fun norm(arg: Point): Double = sqrt(arg.fold(0.0) { acc: Double, d: Double -> acc + d.pow(2) }) } -/** - * [ExtendedField] over [DoubleBuffer]. - * - * @property size the size of buffers to operate on. - */ -@Deprecated("To be replaced by generic BufferAlgebra") -public class DoubleBufferField(public val size: Int) : ExtendedField>, Norm, Double> { - override val zero: Buffer by lazy { DoubleBuffer(size) { 0.0 } } - override val one: Buffer by lazy { DoubleBuffer(size) { 1.0 } } - - override fun number(value: Number): Buffer = DoubleBuffer(size) { value.toDouble() } - - override fun Buffer.unaryMinus(): Buffer = DoubleBufferOperations.run { - -this@unaryMinus - } - - override fun add(a: Buffer, b: Buffer): DoubleBuffer { - require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } - return DoubleBufferOperations.add(a, b) - } - - override fun scale(a: Buffer, value: Double): DoubleBuffer { - require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } - - return if (a is DoubleBuffer) { - val aArray = a.array - DoubleBuffer(DoubleArray(a.size) { aArray[it] * value }) - } else DoubleBuffer(DoubleArray(a.size) { a[it] * value }) - } - - override fun multiply(a: Buffer, b: Buffer): DoubleBuffer { - require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } - return DoubleBufferOperations.multiply(a, b) - } - - override fun divide(a: Buffer, b: Buffer): DoubleBuffer { - require(a.size == size) { "The buffer size ${a.size} does not match context size $size" } - return DoubleBufferOperations.divide(a, b) - } - - override fun sin(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.sin(arg) - } - - override fun cos(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.cos(arg) - } - - override fun tan(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.tan(arg) - } - - override fun asin(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.asin(arg) - } - - override fun acos(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.acos(arg) - } - - override fun atan(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.atan(arg) - } - - override fun sinh(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.sinh(arg) - } - - override fun cosh(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.cosh(arg) - } - - override fun tanh(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.tanh(arg) - } - - override fun asinh(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.asinh(arg) - } - - override fun acosh(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.acosh(arg) - } - - override fun atanh(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.atanh(arg) - } - - override fun power(arg: Buffer, pow: Number): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.power(arg, pow) - } - - override fun exp(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.exp(arg) - } - - override fun ln(arg: Buffer): DoubleBuffer { - require(arg.size == size) { "The buffer size ${arg.size} does not match context size $size" } - return DoubleBufferOperations.ln(arg) - } - - override fun norm(arg: Buffer): Double = DoubleL2Norm.norm(arg) -} diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferOperation.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/bufferOperation.kt similarity index 97% rename from kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferOperation.kt rename to kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/bufferOperation.kt index bc3f5b64b..6bf3266e3 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferOperation.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/bufferOperation.kt @@ -3,9 +3,10 @@ * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. */ -package space.kscience.kmath.structures +package space.kscience.kmath.operations import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.structures.* /** * Typealias for buffer transformations. diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt index c90553aaa..4c0010bf9 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/numbers.kt @@ -14,7 +14,8 @@ public interface ExtendedFieldOperations : FieldOperations, TrigonometricOperations, PowerOperations, - ExponentialOperations { + ExponentialOperations, + ScaleOperations { override fun tan(arg: T): T = sin(arg) / cos(arg) override fun tanh(arg: T): T = sinh(arg) / cosh(arg) @@ -41,7 +42,7 @@ public interface ExtendedFieldOperations : /** * Advanced Number-like field that implements basic operations. */ -public interface ExtendedField : ExtendedFieldOperations, Field, NumericAlgebra, ScaleOperations { +public interface ExtendedField : ExtendedFieldOperations, Field, NumericAlgebra{ override fun sinh(arg: T): T = (exp(arg) - exp(-arg)) / 2.0 override fun cosh(arg: T): T = (exp(arg) + exp(-arg)) / 2.0 override fun tanh(arg: T): T = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg)) diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt index fc23169ca..c68bca2d9 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt @@ -5,6 +5,7 @@ package space.kscience.kmath.structures +import space.kscience.kmath.operations.asSequence import kotlin.jvm.JvmInline import kotlin.reflect.KClass @@ -49,7 +50,8 @@ public interface Buffer { public companion object { - public fun toString(buffer: Buffer<*>): String = buffer.asSequence().joinToString(prefix = "[", separator = ", ", postfix = "]") + public fun toString(buffer: Buffer<*>): String = + buffer.asSequence().joinToString(prefix = "[", separator = ", ", postfix = "]") /** * Check the element-by-element match of content of two buffers. diff --git a/kmath-coroutines/src/jvmTest/kotlin/space/kscience/kmath/streaming/RingBufferTest.kt b/kmath-coroutines/src/jvmTest/kotlin/space/kscience/kmath/streaming/RingBufferTest.kt index 14081b0f5..a3143a1ac 100644 --- a/kmath-coroutines/src/jvmTest/kotlin/space/kscience/kmath/streaming/RingBufferTest.kt +++ b/kmath-coroutines/src/jvmTest/kotlin/space/kscience/kmath/streaming/RingBufferTest.kt @@ -7,7 +7,7 @@ package space.kscience.kmath.streaming import kotlinx.coroutines.flow.* import kotlinx.coroutines.runBlocking -import space.kscience.kmath.structures.asSequence +import space.kscience.kmath.operations.asSequence import kotlin.test.Test import kotlin.test.assertEquals diff --git a/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt new file mode 100644 index 000000000..dce739dc2 --- /dev/null +++ b/kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt @@ -0,0 +1,995 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. + */ + +/* This file is generated with buildSrc/src/main/kotlin/space/kscience/kmath/ejml/codegen/ejmlCodegen.kt */ + +package space.kscience.kmath.ejml + +import org.ejml.data.* +import org.ejml.dense.row.CommonOps_DDRM +import org.ejml.dense.row.CommonOps_FDRM +import org.ejml.dense.row.factory.DecompositionFactory_DDRM +import org.ejml.dense.row.factory.DecompositionFactory_FDRM +import org.ejml.sparse.FillReducing +import org.ejml.sparse.csc.CommonOps_DSCC +import org.ejml.sparse.csc.CommonOps_FSCC +import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC +import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC +import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC +import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC +import space.kscience.kmath.linear.* +import space.kscience.kmath.linear.Matrix +import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.nd.StructureFeature +import space.kscience.kmath.operations.DoubleField +import space.kscience.kmath.operations.FloatField +import space.kscience.kmath.operations.invoke +import space.kscience.kmath.structures.DoubleBuffer +import space.kscience.kmath.structures.FloatBuffer +import kotlin.reflect.KClass +import kotlin.reflect.cast + +/** + * [EjmlVector] specialization for [Double]. + */ +public class EjmlDoubleVector(override val origin: M) : EjmlVector(origin) { + init { + require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } + } + + override operator fun get(index: Int): Double = origin[0, index] +} + +/** + * [EjmlVector] specialization for [Float]. + */ +public class EjmlFloatVector(override val origin: M) : EjmlVector(origin) { + init { + require(origin.numRows == 1) { "The origin matrix must have only one row to form a vector" } + } + + override operator fun get(index: Int): Float = origin[0, index] +} + +/** + * [EjmlMatrix] specialization for [Double]. + */ +public class EjmlDoubleMatrix(override val origin: M) : EjmlMatrix(origin) { + override operator fun get(i: Int, j: Int): Double = origin[i, j] +} + +/** + * [EjmlMatrix] specialization for [Float]. + */ +public class EjmlFloatMatrix(override val origin: M) : EjmlMatrix(origin) { + override operator fun get(i: Int, j: Int): Float = origin[i, j] +} + +/** + * [EjmlLinearSpace] implementation based on [CommonOps_DDRM], [DecompositionFactory_DDRM] operations and + * [DMatrixRMaj] matrices. + */ +public object EjmlLinearSpaceDDRM : EjmlLinearSpace() { + /** + * The [DoubleField] reference. + */ + override val elementAlgebra: DoubleField get() = DoubleField + + @Suppress("UNCHECKED_CAST") + override fun Matrix.toEjml(): EjmlDoubleMatrix = when { + this is EjmlDoubleMatrix<*> && origin is DMatrixRMaj -> this as EjmlDoubleMatrix + else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } + } + + @Suppress("UNCHECKED_CAST") + override fun Point.toEjml(): EjmlDoubleVector = when { + this is EjmlDoubleVector<*> && origin is DMatrixRMaj -> this as EjmlDoubleVector + else -> EjmlDoubleVector(DMatrixRMaj(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } + }) + } + + override fun buildMatrix( + rows: Int, + columns: Int, + initializer: DoubleField.(i: Int, j: Int) -> Double, + ): EjmlDoubleMatrix = DMatrixRMaj(rows, columns).also { + (0 until rows).forEach { row -> + (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } + } + }.wrapMatrix() + + override fun buildVector( + size: Int, + initializer: DoubleField.(Int) -> Double, + ): EjmlDoubleVector = EjmlDoubleVector(DMatrixRMaj(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } + }) + + private fun T.wrapMatrix() = EjmlDoubleMatrix(this) + private fun T.wrapVector() = EjmlDoubleVector(this) + + override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + + override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixRMaj(1, 1) + CommonOps_DDRM.mult(toEjml().origin, other.toEjml().origin, out) + return out.wrapMatrix() + } + + override fun Matrix.dot(vector: Point): EjmlDoubleVector { + val out = DMatrixRMaj(1, 1) + CommonOps_DDRM.mult(toEjml().origin, vector.toEjml().origin, out) + return out.wrapVector() + } + + override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixRMaj(1, 1) + + CommonOps_DDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + ) + + return out.wrapMatrix() + } + + override operator fun Matrix.times(value: Double): EjmlDoubleMatrix { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.scale(value, toEjml().origin, res) + return res.wrapMatrix() + } + + override fun Point.unaryMinus(): EjmlDoubleVector { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.changeSign(toEjml().origin, res) + return res.wrapVector() + } + + override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixRMaj(1, 1) + + CommonOps_DDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + ) + + return out.wrapMatrix() + } + + override fun Point.plus(other: Point): EjmlDoubleVector { + val out = DMatrixRMaj(1, 1) + + CommonOps_DDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + ) + + return out.wrapVector() + } + + override fun Point.minus(other: Point): EjmlDoubleVector { + val out = DMatrixRMaj(1, 1) + + CommonOps_DDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + ) + + return out.wrapVector() + } + + override fun Double.times(m: Matrix): EjmlDoubleMatrix = m * this + + override fun Point.times(value: Double): EjmlDoubleVector { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.scale(value, toEjml().origin, res) + return res.wrapVector() + } + + override fun Double.times(v: Point): EjmlDoubleVector = v * this + + @UnstableKMathAPI + override fun computeFeature(structure: Matrix, type: KClass): F? { + structure.getFeature(type)?.let { return it } + val origin = structure.toEjml().origin + + return when (type) { + InverseMatrixFeature::class -> object : InverseMatrixFeature { + override val inverse: Matrix by lazy { + val res = origin.copy() + CommonOps_DDRM.invert(res) + res.wrapMatrix() + } + } + + DeterminantFeature::class -> object : DeterminantFeature { + override val determinant: Double by lazy { CommonOps_DDRM.det(origin) } + } + + SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature { + private val svd by lazy { + DecompositionFactory_DDRM.svd(origin.numRows, origin.numCols, true, true, false) + .apply { decompose(origin.copy()) } + } + + override val u: Matrix by lazy { svd.getU(null, false).wrapMatrix() } + override val s: Matrix by lazy { svd.getW(null).wrapMatrix() } + override val v: Matrix by lazy { svd.getV(null, false).wrapMatrix() } + override val singularValues: Point by lazy { DoubleBuffer(svd.singularValues) } + } + + QRDecompositionFeature::class -> object : QRDecompositionFeature { + private val qr by lazy { + DecompositionFactory_DDRM.qr().apply { decompose(origin.copy()) } + } + + override val q: Matrix by lazy { + qr.getQ(null, false).wrapMatrix().withFeature(OrthogonalFeature) + } + + override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix().withFeature(UFeature) } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { + override val l: Matrix by lazy { + val cholesky = + DecompositionFactory_DDRM.chol(structure.rowNum, true).apply { decompose(origin.copy()) } + + cholesky.getT(null).wrapMatrix().withFeature(LFeature) + } + } + + LupDecompositionFeature::class -> object : LupDecompositionFeature { + private val lup by lazy { + DecompositionFactory_DDRM.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) } + } + + override val l: Matrix by lazy { + lup.getLower(null).wrapMatrix().withFeature(LFeature) + } + + override val u: Matrix by lazy { + lup.getUpper(null).wrapMatrix().withFeature(UFeature) + } + + override val p: Matrix by lazy { lup.getRowPivot(null).wrapMatrix() } + } + + else -> null + }?.let(type::cast) + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p matrix. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Matrix): EjmlDoubleMatrix { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res) + return res.wrapMatrix() + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p vector. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Point): EjmlDoubleVector { + val res = DMatrixRMaj(1, 1) + CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res) + return EjmlDoubleVector(res) + } +} + +/** + * [EjmlLinearSpace] implementation based on [CommonOps_FDRM], [DecompositionFactory_FDRM] operations and + * [FMatrixRMaj] matrices. + */ +public object EjmlLinearSpaceFDRM : EjmlLinearSpace() { + /** + * The [FloatField] reference. + */ + override val elementAlgebra: FloatField get() = FloatField + + @Suppress("UNCHECKED_CAST") + override fun Matrix.toEjml(): EjmlFloatMatrix = when { + this is EjmlFloatMatrix<*> && origin is FMatrixRMaj -> this as EjmlFloatMatrix + else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } + } + + @Suppress("UNCHECKED_CAST") + override fun Point.toEjml(): EjmlFloatVector = when { + this is EjmlFloatVector<*> && origin is FMatrixRMaj -> this as EjmlFloatVector + else -> EjmlFloatVector(FMatrixRMaj(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } + }) + } + + override fun buildMatrix( + rows: Int, + columns: Int, + initializer: FloatField.(i: Int, j: Int) -> Float, + ): EjmlFloatMatrix = FMatrixRMaj(rows, columns).also { + (0 until rows).forEach { row -> + (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } + } + }.wrapMatrix() + + override fun buildVector( + size: Int, + initializer: FloatField.(Int) -> Float, + ): EjmlFloatVector = EjmlFloatVector(FMatrixRMaj(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } + }) + + private fun T.wrapMatrix() = EjmlFloatMatrix(this) + private fun T.wrapVector() = EjmlFloatVector(this) + + override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + + override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { + val out = FMatrixRMaj(1, 1) + CommonOps_FDRM.mult(toEjml().origin, other.toEjml().origin, out) + return out.wrapMatrix() + } + + override fun Matrix.dot(vector: Point): EjmlFloatVector { + val out = FMatrixRMaj(1, 1) + CommonOps_FDRM.mult(toEjml().origin, vector.toEjml().origin, out) + return out.wrapVector() + } + + override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { + val out = FMatrixRMaj(1, 1) + + CommonOps_FDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + ) + + return out.wrapMatrix() + } + + override operator fun Matrix.times(value: Float): EjmlFloatMatrix { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.scale(value, toEjml().origin, res) + return res.wrapMatrix() + } + + override fun Point.unaryMinus(): EjmlFloatVector { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.changeSign(toEjml().origin, res) + return res.wrapVector() + } + + override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { + val out = FMatrixRMaj(1, 1) + + CommonOps_FDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + ) + + return out.wrapMatrix() + } + + override fun Point.plus(other: Point): EjmlFloatVector { + val out = FMatrixRMaj(1, 1) + + CommonOps_FDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + ) + + return out.wrapVector() + } + + override fun Point.minus(other: Point): EjmlFloatVector { + val out = FMatrixRMaj(1, 1) + + CommonOps_FDRM.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + ) + + return out.wrapVector() + } + + override fun Float.times(m: Matrix): EjmlFloatMatrix = m * this + + override fun Point.times(value: Float): EjmlFloatVector { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.scale(value, toEjml().origin, res) + return res.wrapVector() + } + + override fun Float.times(v: Point): EjmlFloatVector = v * this + + @UnstableKMathAPI + override fun computeFeature(structure: Matrix, type: KClass): F? { + structure.getFeature(type)?.let { return it } + val origin = structure.toEjml().origin + + return when (type) { + InverseMatrixFeature::class -> object : InverseMatrixFeature { + override val inverse: Matrix by lazy { + val res = origin.copy() + CommonOps_FDRM.invert(res) + res.wrapMatrix() + } + } + + DeterminantFeature::class -> object : DeterminantFeature { + override val determinant: Float by lazy { CommonOps_FDRM.det(origin) } + } + + SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature { + private val svd by lazy { + DecompositionFactory_FDRM.svd(origin.numRows, origin.numCols, true, true, false) + .apply { decompose(origin.copy()) } + } + + override val u: Matrix by lazy { svd.getU(null, false).wrapMatrix() } + override val s: Matrix by lazy { svd.getW(null).wrapMatrix() } + override val v: Matrix by lazy { svd.getV(null, false).wrapMatrix() } + override val singularValues: Point by lazy { FloatBuffer(svd.singularValues) } + } + + QRDecompositionFeature::class -> object : QRDecompositionFeature { + private val qr by lazy { + DecompositionFactory_FDRM.qr().apply { decompose(origin.copy()) } + } + + override val q: Matrix by lazy { + qr.getQ(null, false).wrapMatrix().withFeature(OrthogonalFeature) + } + + override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix().withFeature(UFeature) } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { + override val l: Matrix by lazy { + val cholesky = + DecompositionFactory_FDRM.chol(structure.rowNum, true).apply { decompose(origin.copy()) } + + cholesky.getT(null).wrapMatrix().withFeature(LFeature) + } + } + + LupDecompositionFeature::class -> object : LupDecompositionFeature { + private val lup by lazy { + DecompositionFactory_FDRM.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) } + } + + override val l: Matrix by lazy { + lup.getLower(null).wrapMatrix().withFeature(LFeature) + } + + override val u: Matrix by lazy { + lup.getUpper(null).wrapMatrix().withFeature(UFeature) + } + + override val p: Matrix by lazy { lup.getRowPivot(null).wrapMatrix() } + } + + else -> null + }?.let(type::cast) + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p matrix. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Matrix): EjmlFloatMatrix { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.solve(FMatrixRMaj(a.toEjml().origin), FMatrixRMaj(b.toEjml().origin), res) + return res.wrapMatrix() + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p vector. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Point): EjmlFloatVector { + val res = FMatrixRMaj(1, 1) + CommonOps_FDRM.solve(FMatrixRMaj(a.toEjml().origin), FMatrixRMaj(b.toEjml().origin), res) + return EjmlFloatVector(res) + } +} + +/** + * [EjmlLinearSpace] implementation based on [CommonOps_DSCC], [DecompositionFactory_DSCC] operations and + * [DMatrixSparseCSC] matrices. + */ +public object EjmlLinearSpaceDSCC : EjmlLinearSpace() { + /** + * The [DoubleField] reference. + */ + override val elementAlgebra: DoubleField get() = DoubleField + + @Suppress("UNCHECKED_CAST") + override fun Matrix.toEjml(): EjmlDoubleMatrix = when { + this is EjmlDoubleMatrix<*> && origin is DMatrixSparseCSC -> this as EjmlDoubleMatrix + else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } + } + + @Suppress("UNCHECKED_CAST") + override fun Point.toEjml(): EjmlDoubleVector = when { + this is EjmlDoubleVector<*> && origin is DMatrixSparseCSC -> this as EjmlDoubleVector + else -> EjmlDoubleVector(DMatrixSparseCSC(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } + }) + } + + override fun buildMatrix( + rows: Int, + columns: Int, + initializer: DoubleField.(i: Int, j: Int) -> Double, + ): EjmlDoubleMatrix = DMatrixSparseCSC(rows, columns).also { + (0 until rows).forEach { row -> + (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } + } + }.wrapMatrix() + + override fun buildVector( + size: Int, + initializer: DoubleField.(Int) -> Double, + ): EjmlDoubleVector = EjmlDoubleVector(DMatrixSparseCSC(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } + }) + + private fun T.wrapMatrix() = EjmlDoubleMatrix(this) + private fun T.wrapVector() = EjmlDoubleVector(this) + + override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + + override fun Matrix.dot(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.mult(toEjml().origin, other.toEjml().origin, out) + return out.wrapMatrix() + } + + override fun Matrix.dot(vector: Point): EjmlDoubleVector { + val out = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.mult(toEjml().origin, vector.toEjml().origin, out) + return out.wrapVector() + } + + override operator fun Matrix.minus(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixSparseCSC(1, 1) + + CommonOps_DSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapMatrix() + } + + override operator fun Matrix.times(value: Double): EjmlDoubleMatrix { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.scale(value, toEjml().origin, res) + return res.wrapMatrix() + } + + override fun Point.unaryMinus(): EjmlDoubleVector { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.changeSign(toEjml().origin, res) + return res.wrapVector() + } + + override fun Matrix.plus(other: Matrix): EjmlDoubleMatrix { + val out = DMatrixSparseCSC(1, 1) + + CommonOps_DSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapMatrix() + } + + override fun Point.plus(other: Point): EjmlDoubleVector { + val out = DMatrixSparseCSC(1, 1) + + CommonOps_DSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapVector() + } + + override fun Point.minus(other: Point): EjmlDoubleVector { + val out = DMatrixSparseCSC(1, 1) + + CommonOps_DSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapVector() + } + + override fun Double.times(m: Matrix): EjmlDoubleMatrix = m * this + + override fun Point.times(value: Double): EjmlDoubleVector { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.scale(value, toEjml().origin, res) + return res.wrapVector() + } + + override fun Double.times(v: Point): EjmlDoubleVector = v * this + + @UnstableKMathAPI + override fun computeFeature(structure: Matrix, type: KClass): F? { + structure.getFeature(type)?.let { return it } + val origin = structure.toEjml().origin + + return when (type) { + QRDecompositionFeature::class -> object : QRDecompositionFeature { + private val qr by lazy { + DecompositionFactory_DSCC.qr(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val q: Matrix by lazy { + qr.getQ(null, false).wrapMatrix().withFeature(OrthogonalFeature) + } + + override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix().withFeature(UFeature) } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { + override val l: Matrix by lazy { + val cholesky = + DecompositionFactory_DSCC.cholesky().apply { decompose(origin.copy()) } + + (cholesky.getT(null) as DMatrix).wrapMatrix().withFeature(LFeature) + } + } + + LUDecompositionFeature::class, DeterminantFeature::class, InverseMatrixFeature::class -> object : + LUDecompositionFeature, DeterminantFeature, InverseMatrixFeature { + private val lu by lazy { + DecompositionFactory_DSCC.lu(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val l: Matrix by lazy { + lu.getLower(null).wrapMatrix().withFeature(LFeature) + } + + override val u: Matrix by lazy { + lu.getUpper(null).wrapMatrix().withFeature(UFeature) + } + + override val inverse: Matrix by lazy { + var a = origin + val inverse = DMatrixRMaj(1, 1) + val solver = LinearSolverFactory_DSCC.lu(FillReducing.NONE) + if (solver.modifiesA()) a = a.copy() + val i = CommonOps_DDRM.identity(a.numRows) + solver.solve(i, inverse) + inverse.wrapMatrix() + } + + override val determinant: Double by lazy { elementAlgebra.number(lu.computeDeterminant().real) } + } + + else -> null + }?.let(type::cast) + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p matrix. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Matrix): EjmlDoubleMatrix { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.solve(DMatrixSparseCSC(a.toEjml().origin), DMatrixSparseCSC(b.toEjml().origin), res) + return res.wrapMatrix() + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p vector. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Point): EjmlDoubleVector { + val res = DMatrixSparseCSC(1, 1) + CommonOps_DSCC.solve(DMatrixSparseCSC(a.toEjml().origin), DMatrixSparseCSC(b.toEjml().origin), res) + return EjmlDoubleVector(res) + } +} + +/** + * [EjmlLinearSpace] implementation based on [CommonOps_FSCC], [DecompositionFactory_FSCC] operations and + * [FMatrixSparseCSC] matrices. + */ +public object EjmlLinearSpaceFSCC : EjmlLinearSpace() { + /** + * The [FloatField] reference. + */ + override val elementAlgebra: FloatField get() = FloatField + + @Suppress("UNCHECKED_CAST") + override fun Matrix.toEjml(): EjmlFloatMatrix = when { + this is EjmlFloatMatrix<*> && origin is FMatrixSparseCSC -> this as EjmlFloatMatrix + else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) } + } + + @Suppress("UNCHECKED_CAST") + override fun Point.toEjml(): EjmlFloatVector = when { + this is EjmlFloatVector<*> && origin is FMatrixSparseCSC -> this as EjmlFloatVector + else -> EjmlFloatVector(FMatrixSparseCSC(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = get(row) } + }) + } + + override fun buildMatrix( + rows: Int, + columns: Int, + initializer: FloatField.(i: Int, j: Int) -> Float, + ): EjmlFloatMatrix = FMatrixSparseCSC(rows, columns).also { + (0 until rows).forEach { row -> + (0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) } + } + }.wrapMatrix() + + override fun buildVector( + size: Int, + initializer: FloatField.(Int) -> Float, + ): EjmlFloatVector = EjmlFloatVector(FMatrixSparseCSC(size, 1).also { + (0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) } + }) + + private fun T.wrapMatrix() = EjmlFloatMatrix(this) + private fun T.wrapVector() = EjmlFloatVector(this) + + override fun Matrix.unaryMinus(): Matrix = this * elementAlgebra { -one } + + override fun Matrix.dot(other: Matrix): EjmlFloatMatrix { + val out = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.mult(toEjml().origin, other.toEjml().origin, out) + return out.wrapMatrix() + } + + override fun Matrix.dot(vector: Point): EjmlFloatVector { + val out = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.mult(toEjml().origin, vector.toEjml().origin, out) + return out.wrapVector() + } + + override operator fun Matrix.minus(other: Matrix): EjmlFloatMatrix { + val out = FMatrixSparseCSC(1, 1) + + CommonOps_FSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapMatrix() + } + + override operator fun Matrix.times(value: Float): EjmlFloatMatrix { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.scale(value, toEjml().origin, res) + return res.wrapMatrix() + } + + override fun Point.unaryMinus(): EjmlFloatVector { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.changeSign(toEjml().origin, res) + return res.wrapVector() + } + + override fun Matrix.plus(other: Matrix): EjmlFloatMatrix { + val out = FMatrixSparseCSC(1, 1) + + CommonOps_FSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapMatrix() + } + + override fun Point.plus(other: Point): EjmlFloatVector { + val out = FMatrixSparseCSC(1, 1) + + CommonOps_FSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra.one, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapVector() + } + + override fun Point.minus(other: Point): EjmlFloatVector { + val out = FMatrixSparseCSC(1, 1) + + CommonOps_FSCC.add( + elementAlgebra.one, + toEjml().origin, + elementAlgebra { -one }, + other.toEjml().origin, + out, + null, + null, + ) + + return out.wrapVector() + } + + override fun Float.times(m: Matrix): EjmlFloatMatrix = m * this + + override fun Point.times(value: Float): EjmlFloatVector { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.scale(value, toEjml().origin, res) + return res.wrapVector() + } + + override fun Float.times(v: Point): EjmlFloatVector = v * this + + @UnstableKMathAPI + override fun computeFeature(structure: Matrix, type: KClass): F? { + structure.getFeature(type)?.let { return it } + val origin = structure.toEjml().origin + + return when (type) { + QRDecompositionFeature::class -> object : QRDecompositionFeature { + private val qr by lazy { + DecompositionFactory_FSCC.qr(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val q: Matrix by lazy { + qr.getQ(null, false).wrapMatrix().withFeature(OrthogonalFeature) + } + + override val r: Matrix by lazy { qr.getR(null, false).wrapMatrix().withFeature(UFeature) } + } + + CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature { + override val l: Matrix by lazy { + val cholesky = + DecompositionFactory_FSCC.cholesky().apply { decompose(origin.copy()) } + + (cholesky.getT(null) as FMatrix).wrapMatrix().withFeature(LFeature) + } + } + + LUDecompositionFeature::class, DeterminantFeature::class, InverseMatrixFeature::class -> object : + LUDecompositionFeature, DeterminantFeature, InverseMatrixFeature { + private val lu by lazy { + DecompositionFactory_FSCC.lu(FillReducing.NONE).apply { decompose(origin.copy()) } + } + + override val l: Matrix by lazy { + lu.getLower(null).wrapMatrix().withFeature(LFeature) + } + + override val u: Matrix by lazy { + lu.getUpper(null).wrapMatrix().withFeature(UFeature) + } + + override val inverse: Matrix by lazy { + var a = origin + val inverse = FMatrixRMaj(1, 1) + val solver = LinearSolverFactory_FSCC.lu(FillReducing.NONE) + if (solver.modifiesA()) a = a.copy() + val i = CommonOps_FDRM.identity(a.numRows) + solver.solve(i, inverse) + inverse.wrapMatrix() + } + + override val determinant: Float by lazy { elementAlgebra.number(lu.computeDeterminant().real) } + } + + else -> null + }?.let(type::cast) + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p matrix. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Matrix): EjmlFloatMatrix { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.solve(FMatrixSparseCSC(a.toEjml().origin), FMatrixSparseCSC(b.toEjml().origin), res) + return res.wrapMatrix() + } + + /** + * Solves for *x* in the following equation: *x = [a] -1 · [b]*. + * + * @param a the base matrix. + * @param b n by p vector. + * @return the solution for *x* that is n by p. + */ + public fun solve(a: Matrix, b: Point): EjmlFloatVector { + val res = FMatrixSparseCSC(1, 1) + CommonOps_FSCC.solve(FMatrixSparseCSC(a.toEjml().origin), FMatrixSparseCSC(b.toEjml().origin), res) + return EjmlFloatVector(res) + } +} + diff --git a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt index 88932d59b..c1ee8b48f 100644 --- a/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt +++ b/kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt @@ -13,9 +13,9 @@ import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.algebra +import space.kscience.kmath.operations.asIterable import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer -import space.kscience.kmath.structures.asIterable import kotlin.math.pow /* diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt index b09129626..94c73832b 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/GaussIntegratorRuleFactory.kt @@ -5,10 +5,10 @@ package space.kscience.kmath.integration +import space.kscience.kmath.operations.map import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.asBuffer -import space.kscience.kmath.structures.map import kotlin.jvm.Synchronized import kotlin.math.ulp import kotlin.native.concurrent.ThreadLocal diff --git a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt index 662cdf3d7..6abe89aad 100644 --- a/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt +++ b/kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/SplineIntegrator.kt @@ -12,14 +12,10 @@ import space.kscience.kmath.interpolation.SplineInterpolator import space.kscience.kmath.interpolation.interpolatePolynomials import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.operations.Field -import space.kscience.kmath.operations.invoke -import space.kscience.kmath.operations.sum +import space.kscience.kmath.operations.* import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer import space.kscience.kmath.structures.MutableBufferFactory -import space.kscience.kmath.structures.map /** * Compute analytical indefinite integral of this [PiecewisePolynomial], keeping all intervals intact diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt index 84b1f4fd6..89ee23354 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector2DTest.kt @@ -1,9 +1,8 @@ package space.kscience.kmath.geometry -import space.kscience.kmath.structures.asSequence -import space.kscience.kmath.structures.toList -import kotlin.test.assertEquals +import space.kscience.kmath.operations.toList import kotlin.test.Test +import kotlin.test.assertEquals internal class Vector2DTest { private val vector = Vector2D(1.0, -7.999) diff --git a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt index 717e78871..70f8f4ebd 100644 --- a/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt +++ b/kmath-geometry/src/commonTest/kotlin/space/kscience/kmath/geometry/Vector3DTest.kt @@ -1,6 +1,6 @@ package space.kscience.kmath.geometry -import space.kscience.kmath.structures.toList +import space.kscience.kmath.operations.toList import kotlin.test.Test import kotlin.test.assertEquals diff --git a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt index 0841fcb4c..d5b74fb9b 100644 --- a/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt +++ b/kmath-histograms/src/jvmMain/kotlin/space/kscience/kmath/histogram/UnivariateHistogram.kt @@ -7,8 +7,8 @@ package space.kscience.kmath.histogram import space.kscience.kmath.domains.UnivariateDomain import space.kscience.kmath.misc.UnstableKMathAPI +import space.kscience.kmath.operations.asSequence import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.asSequence @UnstableKMathAPI @@ -34,7 +34,7 @@ public class UnivariateBin( } @OptIn(UnstableKMathAPI::class) -public interface UnivariateHistogram : Histogram{ +public interface UnivariateHistogram : Histogram { public operator fun get(value: Double): UnivariateBin? override operator fun get(point: Buffer): UnivariateBin? = get(point[0]) diff --git a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt index e646d2bd0..9731908b3 100644 --- a/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt +++ b/kmath-jupyter/src/main/kotlin/space/kscience/kmath/jupyter/KMathJupyter.kt @@ -21,9 +21,9 @@ import space.kscience.kmath.expressions.MST import space.kscience.kmath.expressions.MstRing import space.kscience.kmath.misc.PerformancePitfall import space.kscience.kmath.nd.Structure2D +import space.kscience.kmath.operations.asSequence import space.kscience.kmath.operations.invoke import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.asSequence /** * A function for conversion of number to MST for pretty print diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Median.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Median.kt index 54b2e42b3..664e4e8e7 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Median.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Median.kt @@ -5,8 +5,8 @@ package space.kscience.kmath.stat +import space.kscience.kmath.operations.asSequence import space.kscience.kmath.structures.Buffer -import space.kscience.kmath.structures.asSequence /** * Non-composable median diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt index a0f5d8080..d31e02677 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/linUtils.kt @@ -9,9 +9,9 @@ import space.kscience.kmath.nd.MutableStructure1D import space.kscience.kmath.nd.MutableStructure2D import space.kscience.kmath.nd.as1D import space.kscience.kmath.nd.as2D +import space.kscience.kmath.operations.asSequence import space.kscience.kmath.operations.invoke import space.kscience.kmath.structures.VirtualBuffer -import space.kscience.kmath.structures.asSequence import space.kscience.kmath.tensors.core.BufferedTensor import space.kscience.kmath.tensors.core.DoubleTensor import space.kscience.kmath.tensors.core.DoubleTensorAlgebra diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt index 6088c32e4..8428dae5c 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/internal/utils.kt @@ -6,6 +6,7 @@ package space.kscience.kmath.tensors.core.internal import space.kscience.kmath.nd.as1D +import space.kscience.kmath.operations.toMutableList import space.kscience.kmath.samplers.GaussianSampler import space.kscience.kmath.stat.RandomGenerator import space.kscience.kmath.structures.* From fd8a61c852b2514324647b39c8c4fc6c085035d2 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 4 Oct 2021 12:40:30 +0300 Subject: [PATCH 128/132] Fix Mean bug --- .../kscience/kmath/benchmarks/DotBenchmark.kt | 11 +++---- .../ExpressionsInterpretersBenchmark.kt | 5 +-- .../FunctionalExpressionAlgebra.kt | 4 +++ .../kmath/linear/DoubleLinearSpace.kt | 6 ++-- .../kotlin/space/kscience/kmath/stat/Mean.kt | 23 ++++++++++--- .../space/kscience/kmath/stat/Statistic.kt | 20 +++++++---- .../kscience/kmath/stat/StatisticTest.kt | 33 ++++++++++++++----- 7 files changed, 72 insertions(+), 30 deletions(-) diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt index 33cb57c6f..64f9b5dff 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt @@ -14,7 +14,6 @@ import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM import space.kscience.kmath.linear.invoke import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.operations.DoubleField -import space.kscience.kmath.operations.algebra import space.kscience.kmath.structures.Buffer import kotlin.random.Random @@ -25,11 +24,11 @@ internal class DotBenchmark { const val dim = 1000 //creating invertible matrix - val matrix1 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j -> - if (i <= j) random.nextDouble() else 0.0 + val matrix1 = DoubleField.linearSpace.buildMatrix(dim, dim) { _, _ -> + random.nextDouble() } - val matrix2 = Double.algebra.linearSpace.buildMatrix(dim, dim) { i, j -> - if (i <= j) random.nextDouble() else 0.0 + val matrix2 = DoubleField.linearSpace.buildMatrix(dim, dim) { _, _ -> + random.nextDouble() } val cmMatrix1 = CMLinearSpace { matrix1.toCM() } @@ -65,7 +64,7 @@ internal class DotBenchmark { } @Benchmark - fun doubleDot(blackhole: Blackhole) = with(Double.algebra.linearSpace) { + fun doubleDot(blackhole: Blackhole) = with(DoubleField.linearSpace) { blackhole.consume(matrix1 dot matrix2) } } diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt index 8c3c8ec2b..63e1511bd 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt @@ -75,8 +75,9 @@ internal class ExpressionsInterpretersBenchmark { private val algebra = DoubleField private const val times = 1_000_000 - private val functional = DoubleField.expressionInExtendedField { - bindSymbol(x) * number(2.0) + number(2.0) / bindSymbol(x) - number(16.0) / sin(bindSymbol(x)) + private val functional = DoubleField.expression { + val x = bindSymbol(Symbol.x) + x * number(2.0) + 2.0 / x - 16.0 / sin(x) } private val node = MstExtendedField { diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt index bb7f36fc5..36ccb96f7 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt @@ -192,3 +192,7 @@ public inline fun > A.expressionInField( public inline fun > A.expressionInExtendedField( block: FunctionalExpressionExtendedField.() -> Expression, ): Expression = FunctionalExpressionExtendedField(this).block() + +public inline fun DoubleField.expression( + block: FunctionalExpressionExtendedField.() -> Expression, +): Expression = FunctionalExpressionExtendedField(this).block() diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt index 4a1311b54..c2f53939f 100644 --- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt +++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/DoubleLinearSpace.kt @@ -13,7 +13,6 @@ import space.kscience.kmath.operations.DoubleBufferOperations import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.DoubleBuffer -import space.kscience.kmath.structures.indices public object DoubleLinearSpace : LinearSpace { @@ -30,7 +29,6 @@ public object DoubleLinearSpace : LinearSpace { initializer: DoubleField.(i: Int, j: Int) -> Double ): Matrix = ndRing(rows, columns).produce { (i, j) -> DoubleField.initializer(i, j) }.as2D() - override fun buildVector(size: Int, initializer: DoubleField.(Int) -> Double): DoubleBuffer = DoubleBuffer(size) { DoubleField.initializer(it) } @@ -50,9 +48,9 @@ public object DoubleLinearSpace : LinearSpace { // Create a continuous in-memory representation of this vector for better memory layout handling private fun Buffer.linearize() = if (this is DoubleBuffer) { - this + this.array } else { - DoubleBuffer(size) { get(it) } + DoubleArray(size) { get(it) } } @OptIn(PerformancePitfall::class) diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt index 7daed5798..1d09fffd1 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt @@ -27,8 +27,13 @@ public class Mean( override suspend fun evaluate(data: Buffer): T = super.evaluate(data) - override suspend fun computeIntermediate(data: Buffer): Pair = - evaluateBlocking(data) to data.size + override suspend fun computeIntermediate(data: Buffer): Pair = group { + var res = zero + for (i in data.indices) { + res += data[i] + } + res to data.size + } override suspend fun composeIntermediate(first: Pair, second: Pair): Pair = group { first.first + second.first } to (first.second + second.second) @@ -38,13 +43,23 @@ public class Mean( } public companion object { - //TODO replace with optimized version which respects overflow + @Deprecated("Use Double.mean instead") public val double: Mean = Mean(DoubleField) { sum, count -> sum / count } + @Deprecated("Use Int.mean instead") public val int: Mean = Mean(IntRing) { sum, count -> sum / count } + @Deprecated("Use Long.mean instead") public val long: Mean = Mean(LongRing) { sum, count -> sum / count } public fun evaluate(buffer: Buffer): Double = double.evaluateBlocking(buffer) public fun evaluate(buffer: Buffer): Int = int.evaluateBlocking(buffer) public fun evaluate(buffer: Buffer): Long = long.evaluateBlocking(buffer) } -} \ No newline at end of file +} + + +//TODO replace with optimized version which respects overflow +public val Double.Companion.mean: Mean get() = Mean(DoubleField) { sum, count -> sum / count } +public val Int.Companion.mean: Mean get() = Mean(IntRing) { sum, count -> sum / count } +public val Long.Companion.mean: Mean get() = Mean(LongRing) { sum, count -> sum / count } + + diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt index ab80fbe1c..107161514 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Statistic.kt @@ -8,7 +8,6 @@ package space.kscience.kmath.stat import kotlinx.coroutines.CoroutineDispatcher import kotlinx.coroutines.Dispatchers import kotlinx.coroutines.ExperimentalCoroutinesApi -import kotlinx.coroutines.FlowPreview import kotlinx.coroutines.flow.Flow import kotlinx.coroutines.flow.map import kotlinx.coroutines.flow.runningReduce @@ -18,16 +17,23 @@ import space.kscience.kmath.structures.Buffer /** * A function, that transforms a buffer of random quantities to some resulting value */ -public interface Statistic { +public fun interface Statistic { public suspend fun evaluate(data: Buffer): R } -public interface BlockingStatistic : Statistic { +public suspend operator fun Statistic.invoke(data: Buffer): R = evaluate(data) + +/** + * A statistic that is computed in a synchronous blocking mode + */ +public fun interface BlockingStatistic : Statistic { public fun evaluateBlocking(data: Buffer): R override suspend fun evaluate(data: Buffer): R = evaluateBlocking(data) } +public operator fun BlockingStatistic.invoke(data: Buffer): R = evaluateBlocking(data) + /** * A statistic tha could be computed separately on different blocks of data and then composed * @@ -48,8 +54,10 @@ public interface ComposableStatistic : Statistic { override suspend fun evaluate(data: Buffer): R = toResult(computeIntermediate(data)) } -@FlowPreview -@ExperimentalCoroutinesApi +/** + * Flow intermediate state of the [ComposableStatistic] + */ +@OptIn(ExperimentalCoroutinesApi::class) private fun ComposableStatistic.flowIntermediate( flow: Flow>, dispatcher: CoroutineDispatcher = Dispatchers.Default, @@ -64,7 +72,7 @@ private fun ComposableStatistic.flowIntermediate( * * The resulting flow contains values that include the whole previous statistics, not only the last chunk. */ -@OptIn(FlowPreview::class, ExperimentalCoroutinesApi::class) +@OptIn(ExperimentalCoroutinesApi::class) public fun ComposableStatistic.flow( flow: Flow>, dispatcher: CoroutineDispatcher = Dispatchers.Default, diff --git a/kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt b/kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt index c64bcc78c..2a3147869 100644 --- a/kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt +++ b/kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt @@ -5,11 +5,13 @@ package space.kscience.kmath.stat -import kotlinx.coroutines.flow.drop import kotlinx.coroutines.flow.first +import kotlinx.coroutines.flow.last +import kotlinx.coroutines.flow.take import kotlinx.coroutines.runBlocking import space.kscience.kmath.streaming.chunked import kotlin.test.Test +import kotlin.test.assertEquals internal class StatisticTest { //create a random number generator. @@ -22,12 +24,27 @@ internal class StatisticTest { val chunked = data.chunked(1000) @Test - fun testParallelMean() = runBlocking { - val average = Mean.double - .flow(chunked) //create a flow with results - .drop(99) // Skip first 99 values and use one with total data - .first() //get 1e5 data samples average - - println(average) + fun singleBlockingMean() { + val first = runBlocking { chunked.first()} + val res = Double.mean(first) + assertEquals(0.5,res, 1e-1) } + + @Test + fun singleSuspendMean() = runBlocking { + val first = runBlocking { chunked.first()} + val res = Double.mean(first) + assertEquals(0.5,res, 1e-1) + } + + @Test + fun parallelMean() = runBlocking { + val average = Double.mean + .flow(chunked) //create a flow from evaluated results + .take(100) // Take 100 data chunks from the source and accumulate them + .last() //get 1e5 data samples average + + assertEquals(0.5,average, 1e-3) + } + } From d9f36365d9caac00f70b2dfb9b0c352260e1ded9 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Mon, 4 Oct 2021 22:31:06 +0300 Subject: [PATCH 129/132] Fix Mean bug --- .../src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt | 6 +++--- .../kotlin/space/kscience/kmath/stat/StatisticTest.kt | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt index 1d09fffd1..2a9bd3cd4 100644 --- a/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt +++ b/kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Mean.kt @@ -50,9 +50,9 @@ public class Mean( @Deprecated("Use Long.mean instead") public val long: Mean = Mean(LongRing) { sum, count -> sum / count } - public fun evaluate(buffer: Buffer): Double = double.evaluateBlocking(buffer) - public fun evaluate(buffer: Buffer): Int = int.evaluateBlocking(buffer) - public fun evaluate(buffer: Buffer): Long = long.evaluateBlocking(buffer) + public fun evaluate(buffer: Buffer): Double = Double.mean.evaluateBlocking(buffer) + public fun evaluate(buffer: Buffer): Int = Int.mean.evaluateBlocking(buffer) + public fun evaluate(buffer: Buffer): Long = Long.mean.evaluateBlocking(buffer) } } diff --git a/kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt b/kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt index 2a3147869..777b93c29 100644 --- a/kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt +++ b/kmath-stat/src/jvmTest/kotlin/space/kscience/kmath/stat/StatisticTest.kt @@ -44,7 +44,7 @@ internal class StatisticTest { .take(100) // Take 100 data chunks from the source and accumulate them .last() //get 1e5 data samples average - assertEquals(0.5,average, 1e-3) + assertEquals(0.5,average, 1e-2) } } From 30e3e8039724bf84645f3efd28c4bf8fe7195a9f Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Wed, 6 Oct 2021 12:25:32 +0300 Subject: [PATCH 130/132] Add nd add benchmarks --- benchmarks/build.gradle.kts | 6 ++ .../kmath/benchmarks/NDFieldBenchmark.kt | 57 ++++++++++++------- kmath-nd4j/build.gradle.kts | 2 +- .../kscience/kmath/nd4j/Nd4jArrayAlgebra.kt | 3 +- .../kscience/kmath/nd4j/Nd4jTensorAlgebra.kt | 1 - .../tensors/core/tensorAlgebraExtensions.kt | 8 +++ 6 files changed, 55 insertions(+), 22 deletions(-) create mode 100644 kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorAlgebraExtensions.kt diff --git a/benchmarks/build.gradle.kts b/benchmarks/build.gradle.kts index fa72dc8ee..686c491b9 100644 --- a/benchmarks/build.gradle.kts +++ b/benchmarks/build.gradle.kts @@ -36,6 +36,7 @@ kotlin { implementation(project(":kmath-dimensions")) implementation(project(":kmath-for-real")) implementation(project(":kmath-jafama")) + implementation(project(":kmath-tensors")) implementation("org.jetbrains.kotlinx:kotlinx-benchmark-runtime:0.3.1") } } @@ -81,6 +82,11 @@ benchmark { include("BufferBenchmark") } + configurations.register("nd") { + commonConfiguration() + include("NDFieldBenchmark") + } + configurations.register("dot") { commonConfiguration() include("DotBenchmark") diff --git a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt index f72bc3ba0..76fec05d3 100644 --- a/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt +++ b/benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt @@ -12,44 +12,63 @@ import kotlinx.benchmark.State import space.kscience.kmath.nd.StructureND import space.kscience.kmath.nd.autoNdAlgebra import space.kscience.kmath.nd.ndAlgebra +import space.kscience.kmath.nd4j.nd4j import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.structures.Buffer +import space.kscience.kmath.tensors.core.DoubleTensor +import space.kscience.kmath.tensors.core.ones +import space.kscience.kmath.tensors.core.tensorAlgebra @State(Scope.Benchmark) internal class NDFieldBenchmark { @Benchmark - fun autoFieldAdd(blackhole: Blackhole) { - with(autoField) { - var res: StructureND = one - repeat(n) { res += one } - blackhole.consume(res) - } + fun autoFieldAdd(blackhole: Blackhole) = with(autoField) { + var res: StructureND = one + repeat(n) { res += one } + blackhole.consume(res) } @Benchmark - fun specializedFieldAdd(blackhole: Blackhole) { - with(specializedField) { - var res: StructureND = one - repeat(n) { res += 1.0 } - blackhole.consume(res) - } + fun specializedFieldAdd(blackhole: Blackhole) = with(specializedField) { + var res: StructureND = one + repeat(n) { res += 1.0 } + blackhole.consume(res) } - @Benchmark - fun boxingFieldAdd(blackhole: Blackhole) { - with(genericField) { - var res: StructureND = one - repeat(n) { res += 1.0 } - blackhole.consume(res) - } + fun boxingFieldAdd(blackhole: Blackhole) = with(genericField) { + var res: StructureND = one + repeat(n) { res += 1.0 } + blackhole.consume(res) } + @Benchmark + fun tensorAdd(blackhole: Blackhole) = with(Double.tensorAlgebra) { + var res: DoubleTensor = ones(dim, dim) + repeat(n) { res = res + 1.0 } + blackhole.consume(res) + } + + @Benchmark + fun tensorInPlaceAdd(blackhole: Blackhole) = with(Double.tensorAlgebra) { + val res: DoubleTensor = ones(dim, dim) + repeat(n) { res += 1.0 } + blackhole.consume(res) + } + +// @Benchmark +// fun nd4jAdd(blackhole: Blackhole) = with(nd4jField) { +// var res: StructureND = one +// repeat(n) { res += 1.0 } +// blackhole.consume(res) +// } + private companion object { private const val dim = 1000 private const val n = 100 private val autoField = DoubleField.autoNdAlgebra(dim, dim) private val specializedField = DoubleField.ndAlgebra(dim, dim) private val genericField = DoubleField.ndAlgebra(Buffer.Companion::boxing, dim, dim) + private val nd4jField = DoubleField.nd4j(dim, dim) } } diff --git a/kmath-nd4j/build.gradle.kts b/kmath-nd4j/build.gradle.kts index dcb6f1b4a..09264501f 100644 --- a/kmath-nd4j/build.gradle.kts +++ b/kmath-nd4j/build.gradle.kts @@ -9,7 +9,7 @@ dependencies { api(project(":kmath-tensors")) api("org.nd4j:nd4j-api:1.0.0-M1") testImplementation("org.nd4j:nd4j-native-platform:1.0.0-M1") - testImplementation("org.slf4j:slf4j-simple:1.7.31") + testImplementation("org.slf4j:slf4j-simple:1.7.32") } readme { diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt index 54df31556..b604bf5f2 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jArrayAlgebra.kt @@ -45,7 +45,6 @@ public sealed interface Nd4jArrayAlgebra> : AlgebraND.map(transform: C.(T) -> T): Nd4jArrayStructure { val newStruct = ndArray.dup().wrap() newStruct.elements().forEach { (idx, value) -> newStruct[idx] = elementContext.transform(value) } @@ -265,6 +264,8 @@ public class DoubleNd4jArrayField(override val shape: IntArray) : Nd4jArrayExten } } +public fun DoubleField.nd4j(vararg shape: Int): DoubleNd4jArrayField = DoubleNd4jArrayField(intArrayOf(*shape)) + /** * Represents [FieldND] over [Nd4jArrayStructure] of [Float]. */ diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt index 0ac37e19b..ee9251dd1 100644 --- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt +++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt @@ -158,7 +158,6 @@ public object DoubleNd4jTensorAlgebra : Nd4jTensorAlgebra { if (shape contentEquals intArrayOf(1)) ndArray.getDouble(0) else null // TODO rewrite - @PerformancePitfall override fun diagonalEmbedding( diagonalEntries: Tensor, offset: Int, diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorAlgebraExtensions.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorAlgebraExtensions.kt new file mode 100644 index 000000000..b73f95054 --- /dev/null +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorAlgebraExtensions.kt @@ -0,0 +1,8 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file. + */ + +package space.kscience.kmath.tensors.core + +public fun DoubleTensorAlgebra.ones(vararg shape: Int): DoubleTensor = ones(intArrayOf(*shape)) \ No newline at end of file From 09a9df5213b273c6848183355736729f58b39ba3 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Sat, 9 Oct 2021 20:19:36 +0300 Subject: [PATCH 131/132] Add complex power --- CHANGELOG.md | 1 + .../space/kscience/kmath/complex/Complex.kt | 29 +++++++++++++------ 2 files changed, 21 insertions(+), 9 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 6cb9f57f4..05376d425 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -16,6 +16,7 @@ - Unified architecture for Integration and Optimization using features. - `BigInt` operation performance improvement and fixes by @zhelenskiy (#328) - Integration between `MST` and Symja `IExpr` +- Complex power ### Changed - Exponential operations merged with hyperbolic functions diff --git a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt index 793587492..7d948cb61 100644 --- a/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt +++ b/kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt @@ -9,10 +9,7 @@ import space.kscience.kmath.memory.MemoryReader import space.kscience.kmath.memory.MemorySpec import space.kscience.kmath.memory.MemoryWriter import space.kscience.kmath.misc.UnstableKMathAPI -import space.kscience.kmath.operations.ExtendedField -import space.kscience.kmath.operations.Norm -import space.kscience.kmath.operations.NumbersAddOperations -import space.kscience.kmath.operations.ScaleOperations +import space.kscience.kmath.operations.* import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.MemoryBuffer import space.kscience.kmath.structures.MutableBuffer @@ -52,11 +49,23 @@ private val PI_DIV_2 = Complex(PI / 2, 0) * A field of [Complex]. */ @OptIn(UnstableKMathAPI::class) -public object ComplexField : ExtendedField, Norm, NumbersAddOperations, +public object ComplexField : + ExtendedField, + Norm, + NumbersAddOperations, ScaleOperations { + override val zero: Complex = 0.0.toComplex() override val one: Complex = 1.0.toComplex() + override fun bindSymbolOrNull(value: String): Complex? = if (value == "i") i else null + + override fun binaryOperationFunction(operation: String): (left: Complex, right: Complex) -> Complex = + when (operation) { + PowerOperations.POW_OPERATION -> ComplexField::power + else -> super.binaryOperationFunction(operation) + } + /** * The imaginary unit. */ @@ -117,10 +126,14 @@ public object ComplexField : ExtendedField, Norm, Num return i * (ln(1 - iArg) - ln(1 + iArg)) / 2 } - override fun power(arg: Complex, pow: Number): Complex = if (arg.im == 0.0) + override fun power(arg: Complex, pow: Number): Complex = if (arg.im == 0.0) { arg.re.pow(pow.toDouble()).toComplex() - else + } else { exp(pow * ln(arg)) + } + + public fun power(arg: Complex, pow: Complex): Complex = exp(pow * ln(arg)) + override fun exp(arg: Complex): Complex = exp(arg.re) * (cos(arg.im) + i * sin(arg.im)) @@ -172,8 +185,6 @@ public object ComplexField : ExtendedField, Norm, Num public operator fun Double.times(c: Complex): Complex = Complex(c.re * this, c.im * this) override fun norm(arg: Complex): Complex = sqrt(arg.conjugate * arg) - - override fun bindSymbolOrNull(value: String): Complex? = if (value == "i") i else null } /** From 8d2770c275e931e0e3788539f0d5067dc4c4f333 Mon Sep 17 00:00:00 2001 From: Alexander Nozik Date: Wed, 13 Oct 2021 09:06:54 +0300 Subject: [PATCH 132/132] Build tools to 0.10.5 --- build.gradle.kts | 2 +- settings.gradle.kts | 3 ++- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/build.gradle.kts b/build.gradle.kts index 68b894d06..665c057e9 100644 --- a/build.gradle.kts +++ b/build.gradle.kts @@ -19,7 +19,7 @@ allprojects { } group = "space.kscience" - version = "0.3.0-dev-15" + version = "0.3.0-dev-16" } subprojects { diff --git a/settings.gradle.kts b/settings.gradle.kts index 8cfa62133..528adb336 100644 --- a/settings.gradle.kts +++ b/settings.gradle.kts @@ -1,5 +1,6 @@ pluginManagement { repositories { + mavenLocal() maven("https://repo.kotlin.link") mavenCentral() gradlePluginPortal() @@ -9,7 +10,7 @@ pluginManagement { plugins { id("org.jetbrains.kotlinx.benchmark") version "0.3.1" - id("ru.mipt.npm.gradle.project") version "0.10.4" + id("ru.mipt.npm.gradle.project") version "0.10.5" kotlin("multiplatform") version kotlinVersion kotlin("plugin.allopen") version kotlinVersion }