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

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This commit is contained in:
Alexander Nozik 2024-02-18 14:22:20 +03:00
parent 79642a869d
commit 41a325d428
6 changed files with 83 additions and 8 deletions
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1
CHANGELOG.md
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@ -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

4
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/Float64LinearSpace.kt
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@ -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

4
kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/DoubleLUSolverTest.kt
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@ -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)

4
kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt
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@ -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])
}
}

4
kmath-core/src/jvmMain/kotlin/space/kscience/kmath/linear/Float64ParallelLinearSpace.kt
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@ -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

74
kmath-core/src/jvmTest/kotlin/space/kscience/kmath/linear/ParallelMatrixTest.kt Normal file
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@ -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])
}
}