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Remove second generic from DifferentiableExpression

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This commit is contained in:
Alexander Nozik 2021-05-25 16:53:53 +03:00
parent 12805712d3
commit f2b7a08ad8
9 changed files with 39 additions and 29 deletions
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1
CHANGELOG.md
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@ -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

4
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt
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@ -106,7 +106,7 @@ public class DerivativeStructureField(
public companion object :
AutoDiffProcessor<Double, DerivativeStructure, DerivativeStructureField, Expression<Double>> {
public override fun process(function: DerivativeStructureField.() -> DerivativeStructure): DifferentiableExpression<Double, Expression<Double>> =
public override fun process(function: DerivativeStructureField.() -> DerivativeStructure): DifferentiableExpression<Double> =
DerivativeStructureExpression(function)
}
}
@ -116,7 +116,7 @@ public class DerivativeStructureField(
*/
public class DerivativeStructureExpression(
public val function: DerivativeStructureField.() -> DerivativeStructure,
) : DifferentiableExpression<Double, Expression<Double>> {
) : DifferentiableExpression<Double> {
public override operator fun invoke(arguments: Map<Symbol, Double>): Double =
DerivativeStructureField(0, arguments).function().value

9
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt
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@ -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<Double, Expression<Double>>) {
public override fun diffFunction(expression: DifferentiableExpression<Double>) {
function(expression)
val gradientFunction = ObjectiveFunctionGradient {
val args = it.toMap()

8
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt
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@ -25,7 +25,7 @@ public fun FunctionOptimization.Companion.chiSquared(
y: Buffer<Double>,
yErr: Buffer<Double>,
model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure,
): DifferentiableExpression<Double, Expression<Double>> = chiSquared(DerivativeStructureField, x, y, yErr, model)
): DifferentiableExpression<Double> = 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<Double>,
yErr: Iterable<Double>,
model: DerivativeStructureField.(x: DerivativeStructure) -> DerivativeStructure,
): DifferentiableExpression<Double, Expression<Double>> = chiSquared(
): DifferentiableExpression<Double> = chiSquared(
DerivativeStructureField,
x.toList().asBuffer(),
y.toList().asBuffer(),
@ -54,12 +54,12 @@ public fun Expression<Double>.optimize(
/**
* Optimize differentiable expression
*/
public fun DifferentiableExpression<Double, Expression<Double>>.optimize(
public fun DifferentiableExpression<Double>.optimize(
vararg symbols: Symbol,
configuration: CMOptimization.() -> Unit,
): OptimizationResult<Double> = optimizeWith(CMOptimization, symbols = symbols, configuration)
public fun DifferentiableExpression<Double, Expression<Double>>.minimize(
public fun DifferentiableExpression<Double>.minimize(
vararg startPoint: Pair<Symbol, Double>,
configuration: CMOptimization.() -> Unit = {},
): OptimizationResult<Double> {

34
kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt
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@ -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<T, out R : Expression<T>> : Expression<T> {
public interface DifferentiableExpression<T> : Expression<T> {
/**
* Differentiates this expression by ordered collection of [symbols].
*
* @param symbols the symbols.
* @return the derivative or `null`.
*/
public fun derivativeOrNull(symbols: List<Symbol>): R?
public fun derivativeOrNull(symbols: List<Symbol>): Expression<T>?
}
public fun <T, R : Expression<T>> DifferentiableExpression<T, R>.derivative(symbols: List<Symbol>): R =
public fun <T> DifferentiableExpression<T>.derivative(symbols: List<Symbol>): Expression<T> =
derivativeOrNull(symbols) ?: error("Derivative by symbols $symbols not provided")
public fun <T, R : Expression<T>> DifferentiableExpression<T, R>.derivative(vararg symbols: Symbol): R =
public fun <T> DifferentiableExpression<T>.derivative(vararg symbols: Symbol): Expression<T> =
derivative(symbols.toList())
public fun <T, R : Expression<T>> DifferentiableExpression<T, R>.derivative(name: String): R =
public fun <T> DifferentiableExpression<T>.derivative(name: String): Expression<T> =
derivative(StringSymbol(name))
/**
* A special type of [DifferentiableExpression] which returns typed expressions as derivatives
*/
public interface SpecialDifferentiableExpression<T, R: Expression<T>>: DifferentiableExpression<T> {
override fun derivativeOrNull(symbols: List<Symbol>): R?
}
public fun <T, R : Expression<T>> SpecialDifferentiableExpression<T, R>.derivative(symbols: List<Symbol>): R =
derivativeOrNull(symbols) ?: error("Derivative by symbols $symbols not provided")
public fun <T, R : Expression<T>> SpecialDifferentiableExpression<T, R>.derivative(vararg symbols: Symbol): R =
derivative(symbols.toList())
public fun <T, R : Expression<T>> SpecialDifferentiableExpression<T, R>.derivative(name: String): R =
derivative(StringSymbol(name))
/**
* A [DifferentiableExpression] that defines only first derivatives
*/
public abstract class FirstDerivativeExpression<T, R : Expression<T>> : DifferentiableExpression<T, R> {
public abstract class FirstDerivativeExpression<T> : DifferentiableExpression<T> {
/**
* Returns first derivative of this expression by given [symbol].
*/
public abstract fun derivativeOrNull(symbol: Symbol): R?
public abstract fun derivativeOrNull(symbol: Symbol): Expression<T>?
public final override fun derivativeOrNull(symbols: List<Symbol>): R? {
public final override fun derivativeOrNull(symbols: List<Symbol>): Expression<T>? {
val dSymbol = symbols.firstOrNull() ?: return null
return derivativeOrNull(dSymbol)
}
@ -49,5 +65,5 @@ public abstract class FirstDerivativeExpression<T, R : Expression<T>> : Differen
* A factory that converts an expression in autodiff variables to a [DifferentiableExpression]
*/
public fun interface AutoDiffProcessor<T : Any, I : Any, A : ExpressionAlgebra<T, I>, out R : Expression<T>> {
public fun process(function: A.() -> I): DifferentiableExpression<T, R>
public fun process(function: A.() -> I): DifferentiableExpression<T>
}

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt
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@ -232,7 +232,7 @@ public fun <T : Any, F : Field<T>> F.simpleAutoDiff(
public class SimpleAutoDiffExpression<T : Any, F : Field<T>>(
public val field: F,
public val function: SimpleAutoDiffField<T, F>.() -> AutoDiffValue<T>,
) : FirstDerivativeExpression<T, Expression<T>>() {
) : FirstDerivativeExpression<T>() {
public override operator fun invoke(arguments: Map<Symbol, T>): T {
//val bindings = arguments.entries.map { it.key.bind(it.value) }
return SimpleAutoDiffField(field, arguments).function().value

2
kmath-kotlingrad/src/main/kotlin/space/kscience/kmath/kotlingrad/KotlingradExpression.kt
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@ -24,7 +24,7 @@ import space.kscience.kmath.operations.NumericAlgebra
public class KotlingradExpression<T : Number, A : NumericAlgebra<T>>(
public val algebra: A,
public val mst: MST,
) : DifferentiableExpression<T, KotlingradExpression<T, A>> {
) : SpecialDifferentiableExpression<T, KotlingradExpression<T, A>> {
public override fun invoke(arguments: Map<Symbol, T>): T = mst.interpret(algebra, arguments)
public override fun derivativeOrNull(symbols: List<Symbol>): KotlingradExpression<T, A> =

6
kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/FunctionOptimization.kt
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@ -27,7 +27,7 @@ public interface FunctionOptimization<T : Any> : Optimization<T> {
/**
* Set a differentiable expression as objective function as function and gradient provider
*/
public fun diffFunction(expression: DifferentiableExpression<T, Expression<T>>)
public fun diffFunction(expression: DifferentiableExpression<T>)
public companion object {
/**
@ -39,7 +39,7 @@ public interface FunctionOptimization<T : Any> : Optimization<T> {
y: Buffer<T>,
yErr: Buffer<T>,
model: A.(I) -> I,
): DifferentiableExpression<T, Expression<T>> where A : ExtendedField<I>, A : ExpressionAlgebra<T, I> {
): DifferentiableExpression<T> where A : ExtendedField<I>, A : ExpressionAlgebra<T, I> {
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 <T: Any, I : Any, A> FunctionOptimization<T>.chiSquared(
/**
* Optimize differentiable expression using specific [OptimizationProblemFactory]
*/
public fun <T : Any, F : FunctionOptimization<T>> DifferentiableExpression<T, Expression<T>>.optimizeWith(
public fun <T : Any, F : FunctionOptimization<T>> DifferentiableExpression<T>.optimizeWith(
factory: OptimizationProblemFactory<T, F>,
vararg symbols: Symbol,
configuration: F.() -> Unit,

2
kmath-stat/src/commonMain/kotlin/space/kscience/kmath/optimization/XYFit.kt
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@ -27,7 +27,7 @@ public interface XYFit<T : Any> : Optimization<T> {
yErrSymbol: Symbol? = null,
)
public fun model(model: (T) -> DifferentiableExpression<T, *>)
public fun model(model: (T) -> DifferentiableExpression<T>)
/**
* Set the differentiable model for this fit