Add proper test for symmetric matrices eigenValueDecomposition

examples/src/main/kotlin/space/kscience/kmath/linear/eigenValueDecomposition.kt

@@ -0,0 +1,40 @@
+/*
+ * Copyright 2018-2024 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.commons.linear.CMLinearSpace
+import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
+import space.kscience.kmath.nd.StructureND
+import space.kscience.kmath.operations.algebra
+import space.kscience.kmath.structures.Float64
+import kotlin.random.Random
+
+fun main() {
+    val dim = 46
+
+    val random = Random(123)
+
+    val u = Float64.algebra.linearSpace.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
+
+    listOf(CMLinearSpace, EjmlLinearSpaceDDRM).forEach { algebra ->
+        with(algebra) {
+            //create a simmetric matrix
+            val matrix = buildMatrix(dim, dim) { row, col ->
+                if (row >= col) u[row, col] else u[col, row]
+            }
+            val eigen = matrix.getOrComputeAttribute(EIG) ?: error("Failed to compute eigenvalue decomposition")
+            check(
+                StructureND.contentEquals(
+                    matrix,
+                    eigen.v dot eigen.d dot eigen.v.transposed(),
+                    1e-4
+                )
+            ) { "$algebra decomposition failed" }
+            println("$algebra eigenvalue decomposition complete and checked" )
+        }
+    }
+
+}

kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/EigenDecomposition.kt

@@ -7,6 +7,7 @@ package space.kscience.kmath.linear
 
 import space.kscience.attributes.PolymorphicAttribute
 import space.kscience.attributes.safeTypeOf
+import space.kscience.kmath.UnstableKMathAPI
 
 public interface EigenDecomposition<T> {
     /**
@@ -24,5 +25,6 @@ public class EigenDecompositionAttribute<T> :
     PolymorphicAttribute<EigenDecomposition<T>>(safeTypeOf()),
     MatrixAttribute<EigenDecomposition<T>>
 
+@UnstableKMathAPI
 public val <T> MatrixScope<T>.EIG: EigenDecompositionAttribute<T>
     get() = EigenDecompositionAttribute()

kmath-ejml/build.gradle.kts

@@ -1,13 +1,20 @@
 plugins {
-    id("space.kscience.gradle.jvm")
+    id("space.kscience.gradle.mpp")
 }
 
 val ejmlVerision = "0.43.1"
 
-dependencies {
+kscience {
+    jvm()
+    jvmMain {
         api(projects.kmathCore)
         api(projects.kmathComplex)
         api("org.ejml:ejml-all:$ejmlVerision")
+    }
+
+    jvmTest {
+        implementation(projects.testUtils)
+    }
 }
 
 readme {
@@ -29,11 +36,3 @@ readme {
         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))
-//}

kmath-ejml/src/jvmMain/kotlin/space/kscience/kmath/ejml/implementations.kt

@@ -278,8 +278,8 @@ public object EjmlLinearSpaceDDRM : EjmlLinearSpace<Double, Float64Field, DMatri
                     }
 
                     override val v: Matrix<Float64> by lazy {
-                        val eigenvectors = List(origin.numRows) { cmEigen.getEigenVector(it) }
-                        buildMatrix(origin.numRows, origin.numCols) { row, column ->
+                        val eigenvectors = List(origin.numRows) { cmEigen.getEigenVector(it) }.filterNotNull()
+                        buildMatrix(eigenvectors.size, origin.numCols) { row, column ->
                             eigenvectors[row][column]
                         }
                     }

kmath-ejml/src/jvmTest/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt

@@ -18,12 +18,15 @@ import space.kscience.kmath.nd.StructureND
 import space.kscience.kmath.nd.toArray
 import space.kscience.kmath.operations.algebra
 import space.kscience.kmath.structures.Float64
+import space.kscience.kmath.testutils.assertStructureEquals
 import kotlin.random.Random
 import kotlin.random.asJavaRandom
 import kotlin.test.*
 
 internal fun <T : Any> assertMatrixEquals(expected: StructureND<T>, actual: StructureND<T>) {
-    assertTrue { StructureND.contentEquals(expected, actual) }
+    expected.elements().forEach { (index, value) ->
+        assertEquals(value, actual[index], "Structure element with index ${index.toList()} should be equal to $value but is ${actual[index]}")
+    }
 }
 
 @OptIn(UnstableKMathAPI::class)
@@ -108,8 +111,12 @@ internal class EjmlMatrixTest {
 
     @Test
     fun eigenValueDecomposition() = EjmlLinearSpaceDDRM {
-        val matrix = EjmlDoubleMatrix(randomMatrix)
+        val dim = 46
+        val u = buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
+        val matrix = buildMatrix(dim, dim) { row, col ->
+            if (row >= col) u[row, col] else u[col, row]
+        }
         val eigen = matrix.getOrComputeAttribute(EIG) ?: fail()
-        assertMatrixEquals(matrix, eigen.v dot eigen.d dot eigen.v.transposed())
+        assertStructureEquals(matrix, eigen.v dot eigen.d dot eigen.v.transposed())
     }
 }

test-utils/src/commonMain/kotlin/asserts.kt

@@ -5,6 +5,8 @@
 
 package space.kscience.kmath.testutils
 
+import space.kscience.kmath.PerformancePitfall
+import space.kscience.kmath.nd.StructureND
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.structures.Float64
 import space.kscience.kmath.structures.indices
@@ -19,3 +21,11 @@ public fun assertBufferEquals(expected: Buffer<Float64>, result: Buffer<Float64>
         assertEquals(expected[it], result[it], tolerance)
     }
 }
+
+@OptIn(PerformancePitfall::class)
+public fun assertStructureEquals(expected: StructureND<Float64>, result: StructureND<Float64>, tolerance: Double = 1e-4) {
+    assertEquals(expected.shape, result.shape, "Structure shape mismatch")
+    expected.indices.forEach {
+        assertEquals(expected[it], result[it], tolerance)
+    }
+}