fix dot bug introduced in the last refactor. Add test for parallel linear algebra.

CHANGELOG.md

@@ -9,6 +9,7 @@
 - New Attributes-kt module that could be used as stand-alone. It declares. type-safe attributes containers.
 - Explicit `mutableStructureND` builders for mutable structures.
 - `Buffer.asList()` zero-copy transformation.
+- Wasm support.
 - Parallel implementation of `LinearSpace` for Float64
 - Parallel buffer factories
 

kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/Float64LinearSpace.kt

@@ -54,7 +54,7 @@ public object Float64LinearSpace : LinearSpace<Double, Float64Field> {
         require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
         val rows = this@dot.rows.map { it.linearize() }
         val columns = other.columns.map { it.linearize() }
-        val indices = 0 until this.rowNum
+        val indices = 0 until this.colNum
         return buildMatrix(rowNum, other.colNum) { i, j ->
             val r = rows[i]
             val c = columns[j]
@@ -70,7 +70,7 @@ public object Float64LinearSpace : LinearSpace<Double, Float64Field> {
     override fun Matrix<Double>.dot(vector: Point<Double>): Float64Buffer {
         require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" }
         val rows = this@dot.rows.map { it.linearize() }
-        val indices = 0 until this.rowNum
+        val indices = 0 until this.colNum
         return Float64Buffer(rowNum) { i ->
             val r = rows[i]
             var res = 0.0

kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt

@@ -28,13 +28,13 @@ class DoubleLUSolverTest {
     }
 
     @Test
-    fun testDecomposition() = Double.algebra.linearSpace.run {
+    fun testDecomposition() = with(Double.algebra.linearSpace){
         val matrix = matrix(2, 2)(
             3.0, 1.0,
             2.0, 3.0
         )
 
-        val lup = lup(matrix)
+        val lup = elementAlgebra.lup(matrix)
 
         //Check determinant
 //        assertEquals(7.0, lup.determinant)

kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt

@@ -8,6 +8,7 @@ package space.kscience.kmath.linear
 import space.kscience.kmath.PerformancePitfall
 import space.kscience.kmath.UnstableKMathAPI
 import space.kscience.kmath.nd.StructureND
+import space.kscience.kmath.operations.Float64Field
 import space.kscience.kmath.operations.algebra
 import kotlin.test.Test
 import kotlin.test.assertEquals
@@ -58,7 +59,7 @@ class MatrixTest {
     }
 
     @Test
-    fun test2DDot() = Double.algebra.linearSpace.run {
+    fun test2DDot() = Float64Field.linearSpace {
         val firstMatrix = buildMatrix(2, 3) { i, j -> (i + j).toDouble() }
         val secondMatrix = buildMatrix(3, 2) { i, j -> (i + j).toDouble() }
 
@@ -70,6 +71,5 @@ class MatrixTest {
         assertEquals(8.0, result[0, 1])
         assertEquals(8.0, result[1, 0])
         assertEquals(14.0, result[1, 1])
-
     }
 }

kmath-core/src/jvmMain/kotlin/space/kscience/kmath/linear/Float64ParallelLinearSpace.kt

@@ -69,7 +69,7 @@ public object Float64ParallelLinearSpace : LinearSpace<Double, Float64Field> {
         require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
         val rows = this@dot.rows.map { it.linearize() }
         val columns = other.columns.map { it.linearize() }
-        val indices = 0 until this.rowNum
+        val indices = 0 until this.colNum
         return buildMatrix(rowNum, other.colNum) { i, j ->
             val r = rows[i]
             val c = columns[j]
@@ -85,7 +85,7 @@ public object Float64ParallelLinearSpace : LinearSpace<Double, Float64Field> {
     override fun Matrix<Double>.dot(vector: Point<Double>): Float64Buffer {
         require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" }
         val rows = this@dot.rows.map { it.linearize() }
-        val indices = 0 until this.rowNum
+        val indices = 0 until this.colNum
         return Float64Buffer(rowNum) { i ->
             val r = rows[i]
             var res = 0.0

kmath-core/src/jvmTest/kotlin/space/kscience/kmath/linear/ParallelMatrixTest.kt

@@ -0,0 +1,74 @@
+/*
+ * 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.PerformancePitfall
+import space.kscience.kmath.UnstableKMathAPI
+import space.kscience.kmath.nd.StructureND
+import space.kscience.kmath.operations.Float64Field
+import kotlin.test.Test
+import kotlin.test.assertEquals
+import kotlin.test.assertTrue
+
+@UnstableKMathAPI
+@OptIn(PerformancePitfall::class)
+@Suppress("UNUSED_VARIABLE")
+class ParallelMatrixTest {
+
+    @Test
+    fun testTranspose() =  Float64Field.linearSpace.parallel{
+        val matrix = one(3, 3)
+        val transposed = matrix.transposed()
+        assertTrue { StructureND.contentEquals(matrix, transposed) }
+    }
+
+    @Test
+    fun testBuilder() = Float64Field.linearSpace.parallel{
+        val matrix = matrix(2, 3)(
+            1.0, 0.0, 0.0,
+            0.0, 1.0, 2.0
+        )
+
+        assertEquals(2.0, matrix[1, 2])
+    }
+
+    @Test
+    fun testMatrixExtension() = Float64Field.linearSpace.parallel{
+        val transitionMatrix: Matrix<Double> = VirtualMatrix(type,6, 6) { row, col ->
+            when {
+                col == 0 -> .50
+                row + 1 == col -> .50
+                row == 5 && col == 5 -> 1.0
+                else -> 0.0
+            }
+        }
+
+        infix fun Matrix<Double>.pow(power: Int): Matrix<Double> {
+            var res = this
+            repeat(power - 1) {
+                res =  res dot this@pow
+            }
+            return res
+        }
+
+        val toTenthPower = transitionMatrix pow 10
+    }
+
+    @Test
+    fun test2DDot() = Float64Field.linearSpace.parallel {
+        val firstMatrix = buildMatrix(2, 3) { i, j -> (i + j).toDouble() }
+        val secondMatrix = buildMatrix(3, 2) { i, j -> (i + j).toDouble() }
+
+//            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])
+    }
+}