Add proper test for symmetric matrices eigenValueDecomposition
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/*
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* Copyright 2018-2024 KMath contributors.
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* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
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*/
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package space.kscience.kmath.linear
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import space.kscience.kmath.commons.linear.CMLinearSpace
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import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
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import space.kscience.kmath.nd.StructureND
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import space.kscience.kmath.operations.algebra
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import space.kscience.kmath.structures.Float64
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import kotlin.random.Random
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fun main() {
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val dim = 46
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val random = Random(123)
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val u = Float64.algebra.linearSpace.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
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listOf(CMLinearSpace, EjmlLinearSpaceDDRM).forEach { algebra ->
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with(algebra) {
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//create a simmetric matrix
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val matrix = buildMatrix(dim, dim) { row, col ->
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if (row >= col) u[row, col] else u[col, row]
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}
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val eigen = matrix.getOrComputeAttribute(EIG) ?: error("Failed to compute eigenvalue decomposition")
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check(
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StructureND.contentEquals(
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matrix,
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eigen.v dot eigen.d dot eigen.v.transposed(),
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1e-4
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)
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) { "$algebra decomposition failed" }
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println("$algebra eigenvalue decomposition complete and checked" )
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}
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}
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}
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@ -7,6 +7,7 @@ package space.kscience.kmath.linear
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import space.kscience.attributes.PolymorphicAttribute
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import space.kscience.attributes.PolymorphicAttribute
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import space.kscience.attributes.safeTypeOf
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import space.kscience.attributes.safeTypeOf
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import space.kscience.kmath.UnstableKMathAPI
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public interface EigenDecomposition<T> {
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public interface EigenDecomposition<T> {
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/**
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/**
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@ -24,5 +25,6 @@ public class EigenDecompositionAttribute<T> :
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PolymorphicAttribute<EigenDecomposition<T>>(safeTypeOf()),
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PolymorphicAttribute<EigenDecomposition<T>>(safeTypeOf()),
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MatrixAttribute<EigenDecomposition<T>>
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MatrixAttribute<EigenDecomposition<T>>
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@UnstableKMathAPI
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public val <T> MatrixScope<T>.EIG: EigenDecompositionAttribute<T>
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public val <T> MatrixScope<T>.EIG: EigenDecompositionAttribute<T>
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get() = EigenDecompositionAttribute()
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get() = EigenDecompositionAttribute()
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@ -1,13 +1,20 @@
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plugins {
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plugins {
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id("space.kscience.gradle.jvm")
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id("space.kscience.gradle.mpp")
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}
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}
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val ejmlVerision = "0.43.1"
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val ejmlVerision = "0.43.1"
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dependencies {
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kscience {
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jvm()
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jvmMain {
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api(projects.kmathCore)
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api(projects.kmathCore)
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api(projects.kmathComplex)
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api(projects.kmathComplex)
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api("org.ejml:ejml-all:$ejmlVerision")
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api("org.ejml:ejml-all:$ejmlVerision")
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}
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jvmTest {
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implementation(projects.testUtils)
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}
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}
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}
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readme {
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readme {
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@ -29,11 +36,3 @@ readme {
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ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt"
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ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt"
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) { "LinearSpace implementations." }
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) { "LinearSpace implementations." }
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}
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}
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//kotlin.sourceSets.main {
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// val codegen by tasks.creating {
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// ejmlCodegen(kotlin.srcDirs.first().absolutePath + "/space/kscience/kmath/ejml/_generated.kt")
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// }
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//
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// kotlin.srcDirs(files().builtBy(codegen))
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//}
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@ -278,8 +278,8 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace<Double, Float64Field, DMatri
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}
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}
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override val v: Matrix<Float64> by lazy {
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override val v: Matrix<Float64> by lazy {
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val eigenvectors = List(origin.numRows) { cmEigen.getEigenVector(it) }
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val eigenvectors = List(origin.numRows) { cmEigen.getEigenVector(it) }.filterNotNull()
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buildMatrix(origin.numRows, origin.numCols) { row, column ->
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buildMatrix(eigenvectors.size, origin.numCols) { row, column ->
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eigenvectors[row][column]
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eigenvectors[row][column]
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}
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}
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}
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}
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@ -18,12 +18,15 @@ import space.kscience.kmath.nd.StructureND
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import space.kscience.kmath.nd.toArray
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import space.kscience.kmath.nd.toArray
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import space.kscience.kmath.operations.algebra
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import space.kscience.kmath.operations.algebra
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import space.kscience.kmath.structures.Float64
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import space.kscience.kmath.structures.Float64
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import space.kscience.kmath.testutils.assertStructureEquals
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import kotlin.random.Random
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import kotlin.random.Random
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import kotlin.random.asJavaRandom
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import kotlin.random.asJavaRandom
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import kotlin.test.*
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import kotlin.test.*
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internal fun <T : Any> assertMatrixEquals(expected: StructureND<T>, actual: StructureND<T>) {
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internal fun <T : Any> assertMatrixEquals(expected: StructureND<T>, actual: StructureND<T>) {
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assertTrue { StructureND.contentEquals(expected, actual) }
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expected.elements().forEach { (index, value) ->
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assertEquals(value, actual[index], "Structure element with index ${index.toList()} should be equal to $value but is ${actual[index]}")
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}
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}
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}
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@OptIn(UnstableKMathAPI::class)
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@OptIn(UnstableKMathAPI::class)
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@ -108,8 +111,12 @@ internal class EjmlMatrixTest {
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@Test
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@Test
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fun eigenValueDecomposition() = EjmlLinearSpaceDDRM {
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fun eigenValueDecomposition() = EjmlLinearSpaceDDRM {
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val matrix = EjmlDoubleMatrix(randomMatrix)
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val dim = 46
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val u = buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
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val matrix = buildMatrix(dim, dim) { row, col ->
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if (row >= col) u[row, col] else u[col, row]
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}
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val eigen = matrix.getOrComputeAttribute(EIG) ?: fail()
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val eigen = matrix.getOrComputeAttribute(EIG) ?: fail()
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assertMatrixEquals(matrix, eigen.v dot eigen.d dot eigen.v.transposed())
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assertStructureEquals(matrix, eigen.v dot eigen.d dot eigen.v.transposed())
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}
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}
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}
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}
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package space.kscience.kmath.testutils
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package space.kscience.kmath.testutils
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import space.kscience.kmath.PerformancePitfall
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import space.kscience.kmath.nd.StructureND
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import space.kscience.kmath.structures.Buffer
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import space.kscience.kmath.structures.Buffer
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import space.kscience.kmath.structures.Float64
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import space.kscience.kmath.structures.Float64
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import space.kscience.kmath.structures.indices
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import space.kscience.kmath.structures.indices
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@ -19,3 +21,11 @@ public fun assertBufferEquals(expected: Buffer<Float64>, result: Buffer<Float64>
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assertEquals(expected[it], result[it], tolerance)
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assertEquals(expected[it], result[it], tolerance)
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}
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}
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}
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}
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@OptIn(PerformancePitfall::class)
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public fun assertStructureEquals(expected: StructureND<Float64>, result: StructureND<Float64>, tolerance: Double = 1e-4) {
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assertEquals(expected.shape, result.shape, "Structure shape mismatch")
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expected.indices.forEach {
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assertEquals(expected[it], result[it], tolerance)
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}
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}
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