WIP Matrix refactor

This commit is contained in:
Alexander Nozik 2021-03-13 18:19:10 +03:00
parent d5ba816b7d
commit 5e6f65a181
10 changed files with 60 additions and 59 deletions

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@ -5,7 +5,7 @@ import space.kscience.kmath.dimensions.D3
import space.kscience.kmath.dimensions.DMatrixContext
import space.kscience.kmath.dimensions.Dimension
private fun DMatrixContext<Double>.simple() {
private fun DMatrixContext<Double, *>.simple() {
val m1 = produce<D2, D3> { i, j -> (i + j).toDouble() }
val m2 = produce<D3, D2> { i, j -> (i + j).toDouble() }
@ -17,7 +17,7 @@ private object D5 : Dimension {
override val dim: UInt = 5u
}
private fun DMatrixContext<Double>.custom() {
private fun DMatrixContext<Double, *>.custom() {
val m1 = produce<D2, D5> { i, j -> (i + j).toDouble() }
val m2 = produce<D5, D2> { i, j -> (i - j).toDouble() }
val m3 = produce<D2, D2> { i, j -> (i - j).toDouble() }

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@ -99,8 +99,8 @@ public object CMLinearSpace : LinearSpace<Double, RealField> {
ArrayRealVector(array).wrap()
}
private fun RealMatrix.wrap(): CMMatrix = CMMatrix(this)
private fun RealVector.wrap(): CMVector = CMVector(this)
internal fun RealMatrix.wrap(): CMMatrix = CMMatrix(this)
internal fun RealVector.wrap(): CMVector = CMVector(this)
override fun buildVector(size: Int, initializer: RealField.(Int) -> Double): Vector<Double> =
ArrayRealVector(DoubleArray(size) { RealField.initializer(it) }).wrap()

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@ -27,7 +27,7 @@ public fun CMLinearSpace.solve(
a: Matrix<Double>,
b: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).asMatrix()
): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).wrap()
public fun CMLinearSpace.solve(
a: Matrix<Double>,
@ -38,4 +38,4 @@ public fun CMLinearSpace.solve(
public fun CMLinearSpace.inverse(
a: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMMatrix = solver(a, decomposition).inverse.asMatrix()
): CMMatrix = solver(a, decomposition).inverse.wrap()

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@ -3,11 +3,30 @@ package space.kscience.kmath.linear
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.Ring
public class MatrixBuilder<T : Any, A : Ring<T>>(
public val linearSpace: LinearSpace<T, A>,
public val rows: Int,
public val columns: Int,
) {
public operator fun invoke(vararg elements: T): Matrix<T> {
require(rows * columns == elements.size) { "The number of elements ${elements.size} is not equal $rows * $columns" }
return linearSpace.buildMatrix(rows, columns) { i, j -> elements[i * columns + j] }
}
//TODO add specific matrix builder functions like diagonal, etc
}
@UnstableKMathAPI
public fun <T : Any> LinearSpace<T, Ring<T>>.matrix(rows: Int, columns: Int, vararg elements: T): Matrix<T> {
require(rows * columns == elements.size) { "The number of elements ${elements.size} is not equal $rows * $columns" }
return buildMatrix(rows, columns) { i, j -> elements[i * columns + j] }
public fun <T : Any, A : Ring<T>> LinearSpace<T, A>.matrix(rows: Int, columns: Int): MatrixBuilder<T, A> =
MatrixBuilder(this, rows, columns)
/**
* Build a square matrix from given elements.
*/
@UnstableKMathAPI
public fun <T : Any> LinearSpace<T, Ring<T>>.square(vararg elements: T): Matrix<T> {
val size: Int = kotlin.math.sqrt(elements.size.toDouble()).toInt()
return matrix(size,size)(*elements)
}
@UnstableKMathAPI

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@ -38,7 +38,7 @@ class MatrixTest {
infix fun Matrix<Double>.pow(power: Int): Matrix<Double> {
var res = this
repeat(power - 1) {
res = RealLinearSpace.invoke { res dot this@pow }
res = LinearSpace.real.run { res dot this@pow }
}
return res
}

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@ -14,12 +14,12 @@ class RealLUSolverTest {
@Test
fun testDecomposition() {
val matrix = Matrix.square(
3.0, 1.0,
1.0, 3.0
)
LinearSpace.real.run {
val matrix = square(
3.0, 1.0,
1.0, 3.0
)
val lup = lup(matrix)
//Check determinant
@ -31,14 +31,14 @@ class RealLUSolverTest {
@Test
fun testInvert() {
val matrix = Matrix.square(
val matrix = LinearSpace.real.square(
3.0, 1.0,
1.0, 3.0
)
val inverted = LinearSpace.real.inverseWithLup(matrix)
val expected = Matrix.square(
val expected = LinearSpace.real.square(
0.375, -0.125,
-0.125, 0.375
)

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@ -1,5 +1,6 @@
package space.kscience.kmath.structures
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.nd.*
import space.kscience.kmath.operations.Norm
import space.kscience.kmath.operations.invoke
@ -33,7 +34,9 @@ class NumberNDFieldTest {
@Test
fun testGeneration() {
val array = Structure2D.real(3, 3) { i, j -> (i * 10 + j).toDouble() }
val array = LinearSpace.real.buildMatrix(3, 3) { i, j ->
(i * 10 + j).toDouble()
}
for (i in 0..2) {
for (j in 0..2) {

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@ -9,23 +9,4 @@ import space.kscience.kmath.nd.Matrix
*/
public infix fun Matrix<Double>.dot(other: Matrix<Double>): Matrix<Double> = LinearSpace.real.run{
this@dot dot other
// require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
// val resultArray = DoubleArray(this.rowNum * other.colNum)
//
// //convert to array to insure there is no memory indirection
// fun Buffer<Double>.unsafeArray() = if (this is RealBuffer)
// this.array
// else
// DoubleArray(size) { get(it) }
//
// val a = this.buffer.unsafeArray()
// val b = other.buffer.unsafeArray()
//
// for (i in (0 until rowNum))
// for (j in (0 until other.colNum))
// for (k in (0 until colNum))
// resultArray[i * other.colNum + j] += a[i * colNum + k] * b[k * other.colNum + j]
//
// val buffer = RealBuffer(resultArray)
// return BufferMatrix(rowNum, other.colNum, buffer)
}

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@ -1,7 +1,7 @@
package kaceince.kmath.real
import space.kscience.kmath.linear.Matrix
import space.kscience.kmath.linear.build
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.matrix
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.real.*
import space.kscience.kmath.structures.contentEquals
@ -30,11 +30,11 @@ internal class RealMatrixTest {
@Test
fun testRepeatStackVertical() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = LinearSpace.real.matrix(2, 3)(
1.0, 0.0, 0.0,
0.0, 1.0, 2.0
)
val matrix2 = Matrix.build(6, 3)(
val matrix2 = LinearSpace.real.matrix(6, 3)(
1.0, 0.0, 0.0,
0.0, 1.0, 2.0,
1.0, 0.0, 0.0,
@ -47,12 +47,12 @@ internal class RealMatrixTest {
@Test
fun testMatrixAndDouble() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = LinearSpace.real.matrix(2, 3)(
1.0, 0.0, 3.0,
4.0, 6.0, 2.0
)
val matrix2 = (matrix1 * 2.5 + 1.0 - 2.0) / 2.0
val expectedResult = Matrix.build(2, 3)(
val expectedResult = LinearSpace.real.matrix(2, 3)(
0.75, -0.5, 3.25,
4.5, 7.0, 2.0
)
@ -61,13 +61,13 @@ internal class RealMatrixTest {
@Test
fun testDoubleAndMatrix() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = LinearSpace.real.matrix(2, 3)(
1.0, 0.0, 3.0,
4.0, 6.0, 2.0
)
val matrix2 = 20.0 - (10.0 + (5.0 * matrix1))
//val matrix2 = 10.0 + (5.0 * matrix1)
val expectedResult = Matrix.build(2, 3)(
val expectedResult = LinearSpace.real.matrix(2, 3)(
5.0, 10.0, -5.0,
-10.0, -20.0, 0.0
)
@ -76,15 +76,15 @@ internal class RealMatrixTest {
@Test
fun testSquareAndPower() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = LinearSpace.real.matrix(2, 3)(
-1.0, 0.0, 3.0,
4.0, -6.0, -2.0
)
val matrix2 = Matrix.build(2, 3)(
val matrix2 = LinearSpace.real.matrix(2, 3)(
1.0, 0.0, 9.0,
16.0, 36.0, 4.0
)
val matrix3 = Matrix.build(2, 3)(
val matrix3 = LinearSpace.real.matrix(2, 3)(
-1.0, 0.0, 27.0,
64.0, -216.0, -8.0
)
@ -95,16 +95,16 @@ internal class RealMatrixTest {
@OptIn(UnstableKMathAPI::class)
@Test
fun testTwoMatrixOperations() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = LinearSpace.real.matrix(2, 3)(
-1.0, 0.0, 3.0,
4.0, -6.0, 7.0
)
val matrix2 = Matrix.build(2, 3)(
val matrix2 = LinearSpace.real.matrix(2, 3)(
1.0, 0.0, 3.0,
4.0, 6.0, -2.0
)
val result = matrix1 * matrix2 + matrix1 - matrix2
val expectedResult = Matrix.build(2, 3)(
val expectedResult = LinearSpace.real.matrix(2, 3)(
-3.0, 0.0, 9.0,
16.0, -48.0, -5.0
)
@ -113,16 +113,16 @@ internal class RealMatrixTest {
@Test
fun testColumnOperations() {
val matrix1 = Matrix.build(2, 4)(
val matrix1 = LinearSpace.real.matrix(2, 4)(
-1.0, 0.0, 3.0, 15.0,
4.0, -6.0, 7.0, -11.0
)
val matrix2 = Matrix.build(2, 5)(
val matrix2 = LinearSpace.real.matrix(2, 5)(
-1.0, 0.0, 3.0, 15.0, -1.0,
4.0, -6.0, 7.0, -11.0, 4.0
)
val col1 = Matrix.build(2, 1)(0.0, -6.0)
val cols1to2 = Matrix.build(2, 2)(
val col1 = LinearSpace.real.matrix(2, 1)(0.0, -6.0)
val cols1to2 = LinearSpace.real.matrix(2, 2)(
0.0, 3.0,
-6.0, 7.0
)
@ -147,7 +147,7 @@ internal class RealMatrixTest {
@Test
fun testAllElementOperations() {
val matrix1 = Matrix.build(2, 4)(
val matrix1 = LinearSpace.real.matrix(2, 4)(
-1.0, 0.0, 3.0, 15.0,
4.0, -6.0, 7.0, -11.0
)

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@ -2,9 +2,7 @@ package kaceince.kmath.real
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.asMatrix
import space.kscience.kmath.linear.real
import space.kscience.kmath.linear.transpose
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.real.plus
import space.kscience.kmath.structures.Buffer
import kotlin.test.Test
@ -32,7 +30,7 @@ internal class RealVectorTest {
val vector2 = Buffer.real(5) { 5 - it.toDouble() }
val matrix1 = vector1.asMatrix()
val matrix2 = vector2.asMatrix().transpose()
val product = LinearSpace.real { matrix1 dot matrix2 }
val product = LinearSpace.real.run { matrix1 dot matrix2 }
assertEquals(5.0, product[1, 0])
assertEquals(6.0, product[2, 2])
}