Merge branch 'dev' into gsl-experiment
This commit is contained in:
commit
8019ac6802
@ -28,7 +28,7 @@ internal class ExpressionsInterpretersBenchmark {
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@Benchmark
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fun mstExpression() {
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val expr = algebra.mstInField {
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symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
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symbol("x") * 2.0 + 2.0 / symbol("x") - 16.0
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}
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invokeAndSum(expr)
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@ -37,7 +37,7 @@ internal class ExpressionsInterpretersBenchmark {
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@Benchmark
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fun asmExpression() {
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val expr = algebra.mstInField {
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symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
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symbol("x") * 2.0 + 2.0 / symbol("x") - 16.0
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}.compile()
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invokeAndSum(expr)
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@ -2,9 +2,8 @@ package kscience.kmath.benchmarks
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import kotlinx.benchmark.Benchmark
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import kscience.kmath.commons.linear.CMMatrixContext
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import kscience.kmath.commons.linear.toCM
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import kscience.kmath.ejml.EjmlMatrixContext
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import kscience.kmath.ejml.toEjml
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import kscience.kmath.linear.BufferMatrixContext
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import kscience.kmath.linear.RealMatrixContext
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import kscience.kmath.linear.real
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@ -26,11 +25,11 @@ class DotBenchmark {
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val matrix1 = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
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val matrix2 = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
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val cmMatrix1 = matrix1.toCM()
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val cmMatrix2 = matrix2.toCM()
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val cmMatrix1 = CMMatrixContext { matrix1.toCM() }
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val cmMatrix2 = CMMatrixContext { matrix2.toCM() }
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val ejmlMatrix1 = matrix1.toEjml()
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val ejmlMatrix2 = matrix2.toEjml()
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val ejmlMatrix1 = EjmlMatrixContext { matrix1.toEjml() }
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val ejmlMatrix2 = EjmlMatrixContext { matrix2.toEjml() }
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}
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@Benchmark
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@ -49,22 +48,23 @@ class DotBenchmark {
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@Benchmark
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fun ejmlMultiplicationwithConversion() {
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val ejmlMatrix1 = matrix1.toEjml()
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val ejmlMatrix2 = matrix2.toEjml()
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EjmlMatrixContext {
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val ejmlMatrix1 = matrix1.toEjml()
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val ejmlMatrix2 = matrix2.toEjml()
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ejmlMatrix1 dot ejmlMatrix2
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}
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}
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@Benchmark
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fun bufferedMultiplication() {
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BufferMatrixContext(RealField, Buffer.Companion::real).invoke{
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BufferMatrixContext(RealField, Buffer.Companion::real).invoke {
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matrix1 dot matrix2
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}
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}
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@Benchmark
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fun realMultiplication(){
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fun realMultiplication() {
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RealMatrixContext {
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matrix1 dot matrix2
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}
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@ -1,25 +0,0 @@
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package kscience.kmath.benchmarks
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import kscience.kmath.structures.NDField
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import org.openjdk.jmh.annotations.Benchmark
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import org.openjdk.jmh.annotations.Scope
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import org.openjdk.jmh.annotations.State
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import org.openjdk.jmh.infra.Blackhole
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import kotlin.random.Random
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@State(Scope.Benchmark)
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class LargeNDBenchmark {
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val arraySize = 10000
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val RANDOM = Random(222)
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val src1 = DoubleArray(arraySize) { RANDOM.nextDouble() }
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val src2 = DoubleArray(arraySize) { RANDOM.nextDouble() }
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val field = NDField.real(arraySize)
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val kmathArray1 = field.produce { (a) -> src1[a] }
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val kmathArray2 = field.produce { (a) -> src2[a] }
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@Benchmark
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fun test10000(bh: Blackhole) {
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bh.consume(field.add(kmathArray1, kmathArray2))
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}
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}
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@ -5,10 +5,8 @@ import kotlinx.benchmark.Benchmark
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import kscience.kmath.commons.linear.CMMatrixContext
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import kscience.kmath.commons.linear.CMMatrixContext.dot
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import kscience.kmath.commons.linear.inverse
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import kscience.kmath.commons.linear.toCM
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import kscience.kmath.ejml.EjmlMatrixContext
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import kscience.kmath.ejml.inverse
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import kscience.kmath.ejml.toEjml
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import kscience.kmath.operations.invoke
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import kscience.kmath.structures.Matrix
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import org.openjdk.jmh.annotations.Scope
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@ -35,16 +33,14 @@ class LinearAlgebraBenchmark {
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@Benchmark
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fun cmLUPInversion() {
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CMMatrixContext {
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val cm = matrix.toCM() //avoid overhead on conversion
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inverse(cm)
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inverse(matrix)
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}
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}
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@Benchmark
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fun ejmlInverse() {
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EjmlMatrixContext {
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val km = matrix.toEjml() //avoid overhead on conversion
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inverse(km)
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inverse(matrix)
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}
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}
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}
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@ -95,8 +95,9 @@ public open class FunctionalExpressionRing<T, A : Ring<T>>(
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super<FunctionalExpressionSpace>.binaryOperationFunction(operation)
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}
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public open class FunctionalExpressionField<T, A : Field<T>>(algebra: A) :
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FunctionalExpressionRing<T, A>(algebra), Field<Expression<T>> {
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public open class FunctionalExpressionField<T, A : Field<T>>(
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algebra: A,
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) : FunctionalExpressionRing<T, A>(algebra), Field<Expression<T>> {
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/**
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* Builds an Expression of division an expression by another one.
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*/
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@ -43,7 +43,7 @@ public class BufferMatrix<T : Any>(
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if (this === other) return true
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return when (other) {
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is NDStructure<*> -> NDStructure.equals(this, other)
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is NDStructure<*> -> NDStructure.contentEquals(this, other)
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else -> false
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}
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}
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@ -224,6 +224,7 @@ public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext
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): Matrix<T> = solveWithLUP(matrix, one(matrix.rowNum, matrix.colNum), bufferFactory, checkSingular)
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@OptIn(UnstableKMathAPI::class)
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public fun RealMatrixContext.solveWithLUP(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> {
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// Use existing decomposition if it is provided by matrix
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val bufferFactory: MutableBufferFactory<Double> = MutableBuffer.Companion::real
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@ -3,6 +3,7 @@ package kscience.kmath.operations
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import kscience.kmath.memory.MemoryReader
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import kscience.kmath.memory.MemorySpec
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import kscience.kmath.memory.MemoryWriter
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import kscience.kmath.misc.UnstableKMathAPI
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import kscience.kmath.structures.Buffer
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import kscience.kmath.structures.MemoryBuffer
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import kscience.kmath.structures.MutableBuffer
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@ -41,6 +42,7 @@ private val PI_DIV_2 = Complex(PI / 2, 0)
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/**
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* A field of [Complex].
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*/
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@OptIn(UnstableKMathAPI::class)
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public object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex>, RingWithNumbers<Complex> {
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override val zero: Complex = 0.0.toComplex()
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override val one: Complex = 1.0.toComplex()
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@ -54,7 +54,7 @@ public interface NDStructure<T> {
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/**
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* Indicates whether some [NDStructure] is equal to another one.
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*/
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public fun equals(st1: NDStructure<*>, st2: NDStructure<*>): Boolean {
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public fun contentEquals(st1: NDStructure<*>, st2: NDStructure<*>): Boolean {
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if (st1 === st2) return true
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// fast comparison of buffers if possible
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@ -275,7 +275,7 @@ public abstract class NDBuffer<T> : NDStructure<T> {
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override fun elements(): Sequence<Pair<IntArray, T>> = strides.indices().map { it to this[it] }
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override fun equals(other: Any?): Boolean {
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return NDStructure.equals(this, other as? NDStructure<*> ?: return false)
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return NDStructure.contentEquals(this, other as? NDStructure<*> ?: return false)
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}
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override fun hashCode(): Int {
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@ -11,7 +11,7 @@ public typealias RealNDElement = BufferedNDFieldElement<Double, RealField>
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public class RealNDField(override val shape: IntArray) :
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BufferedNDField<Double, RealField>,
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ExtendedNDField<Double, RealField, NDBuffer<Double>>,
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RingWithNumbers<NDBuffer<Double>>{
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RingWithNumbers<NDBuffer<Double>> {
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override val strides: Strides = DefaultStrides(shape)
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@ -24,35 +24,31 @@ public class RealNDField(override val shape: IntArray) :
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return produce { d }
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}
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private inline fun buildBuffer(size: Int, crossinline initializer: (Int) -> Double): Buffer<Double> =
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RealBuffer(DoubleArray(size) { initializer(it) })
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/**
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* Inline transform an NDStructure to
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*/
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override fun map(
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@Suppress("OVERRIDE_BY_INLINE")
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override inline fun map(
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arg: NDBuffer<Double>,
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transform: RealField.(Double) -> Double
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transform: RealField.(Double) -> Double,
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): RealNDElement {
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check(arg)
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val array = buildBuffer(arg.strides.linearSize) { offset -> RealField.transform(arg.buffer[offset]) }
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val array = RealBuffer(arg.strides.linearSize) { offset -> RealField.transform(arg.buffer[offset]) }
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return BufferedNDFieldElement(this, array)
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}
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override fun produce(initializer: RealField.(IntArray) -> Double): RealNDElement {
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val array = buildBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) }
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@Suppress("OVERRIDE_BY_INLINE")
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override inline fun produce(initializer: RealField.(IntArray) -> Double): RealNDElement {
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val array = RealBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) }
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return BufferedNDFieldElement(this, array)
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}
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override fun mapIndexed(
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@Suppress("OVERRIDE_BY_INLINE")
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override inline fun mapIndexed(
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arg: NDBuffer<Double>,
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transform: RealField.(index: IntArray, Double) -> Double
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transform: RealField.(index: IntArray, Double) -> Double,
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): RealNDElement {
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check(arg)
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return BufferedNDFieldElement(
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this,
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buildBuffer(arg.strides.linearSize) { offset ->
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RealBuffer(arg.strides.linearSize) { offset ->
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elementContext.transform(
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arg.strides.index(offset),
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arg.buffer[offset]
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@ -60,16 +56,17 @@ public class RealNDField(override val shape: IntArray) :
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})
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}
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override fun combine(
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@Suppress("OVERRIDE_BY_INLINE")
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override inline fun combine(
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a: NDBuffer<Double>,
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b: NDBuffer<Double>,
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transform: RealField.(Double, Double) -> Double
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transform: RealField.(Double, Double) -> Double,
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): RealNDElement {
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check(a, b)
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return BufferedNDFieldElement(
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this,
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buildBuffer(strides.linearSize) { offset -> elementContext.transform(a.buffer[offset], b.buffer[offset]) }
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)
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val buffer = RealBuffer(strides.linearSize) { offset ->
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elementContext.transform(a.buffer[offset], b.buffer[offset])
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}
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return BufferedNDFieldElement(this, buffer)
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}
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override fun NDBuffer<Double>.toElement(): FieldElement<NDBuffer<Double>, *, out BufferedNDField<Double, RealField>> =
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@ -7,6 +7,7 @@ import kscience.kmath.structures.as2D
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import kotlin.test.Test
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import kotlin.test.assertEquals
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@Suppress("UNUSED_VARIABLE")
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class MatrixTest {
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@Test
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fun testTranspose() {
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@ -8,6 +8,7 @@ import kotlin.math.pow
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import kotlin.test.Test
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import kotlin.test.assertEquals
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@Suppress("UNUSED_VARIABLE")
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class NumberNDFieldTest {
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val array1: RealNDElement = real2D(3, 3) { i, j -> (i + j).toDouble() }
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val array2: RealNDElement = real2D(3, 3) { i, j -> (i - j).toDouble() }
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@ -24,7 +24,7 @@ public class LazyNDStructure<T>(
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}
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public override fun equals(other: Any?): Boolean {
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return NDStructure.equals(this, other as? NDStructure<*> ?: return false)
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return NDStructure.contentEquals(this, other as? NDStructure<*> ?: return false)
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}
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public override fun hashCode(): Int {
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@ -6,6 +6,7 @@ import kscience.kmath.dimensions.DMatrixContext
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import kscience.kmath.dimensions.one
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import kotlin.test.Test
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@Suppress("UNUSED_VARIABLE")
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internal class DMatrixContextTest {
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@Test
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fun testDimensionSafeMatrix() {
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@ -3,6 +3,7 @@ package kscience.kmath.ejml
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import kscience.kmath.linear.*
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import kscience.kmath.misc.UnstableKMathAPI
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import kscience.kmath.structures.Matrix
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import kscience.kmath.structures.NDStructure
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import kscience.kmath.structures.RealBuffer
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import org.ejml.dense.row.factory.DecompositionFactory_DDRM
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import org.ejml.simple.SimpleMatrix
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@ -15,7 +16,7 @@ import kotlin.reflect.cast
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* @property origin the underlying [SimpleMatrix].
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* @author Iaroslav Postovalov
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*/
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public inline class EjmlMatrix(
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public class EjmlMatrix(
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public val origin: SimpleMatrix,
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) : Matrix<Double> {
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public override val rowNum: Int get() = origin.numRows()
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@ -49,7 +50,7 @@ public inline class EjmlMatrix(
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override val q: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(qr.getQ(null, false))) }
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override val r: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(qr.getR(null, false))) }
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}
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CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<Double> {
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CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<Double> {
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override val l: Matrix<Double> by lazy {
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val cholesky =
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DecompositionFactory_DDRM.chol(rowNum, true).apply { decompose(origin.ddrm.copy()) }
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@ -57,7 +58,7 @@ public inline class EjmlMatrix(
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EjmlMatrix(SimpleMatrix(cholesky.getT(null))) + LFeature
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}
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}
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LupDecompositionFeature::class -> object : LupDecompositionFeature<Double> {
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LupDecompositionFeature::class -> object : LupDecompositionFeature<Double> {
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private val lup by lazy {
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DecompositionFactory_DDRM.lu(origin.numRows(), origin.numCols()).apply { decompose(origin.ddrm.copy()) }
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}
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@ -73,7 +74,17 @@ public inline class EjmlMatrix(
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override val p: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(lup.getRowPivot(null))) }
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}
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else -> null
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}?.let{type.cast(it)}
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}?.let { type.cast(it) }
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public override operator fun get(i: Int, j: Int): Double = origin[i, j]
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override fun equals(other: Any?): Boolean {
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if (this === other) return true
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if (other !is Matrix<*>) return false
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return NDStructure.contentEquals(this, other)
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}
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override fun hashCode(): Int = origin.hashCode()
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}
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|
Loading…
Reference in New Issue
Block a user