forked from kscience/kmath
Basic matrix inversion
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@ -55,6 +55,26 @@ abstract class MatrixSpace<T : Any>(val rows: Int, val columns: Int, val field:
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(0 until a.columns).asSequence().map { k -> field.multiply(a[i, k], b[k, j]) }.reduce { first, second -> field.add(first, second) }
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}
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}
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override fun equals(other: Any?): Boolean {
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if (this === other) return true
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if (other !is MatrixSpace<*>) return false
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if (rows != other.rows) return false
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if (columns != other.columns) return false
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if (field != other.field) return false
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return true
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}
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override fun hashCode(): Int {
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var result = rows
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result = 31 * result + columns
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result = 31 * result + field.hashCode()
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return result
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}
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}
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infix fun <T : Any> Matrix<T>.dot(b: Matrix<T>): Matrix<T> = this.context.multiply(this, b)
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@ -90,8 +110,38 @@ interface Matrix<T : Any> : SpaceElement<Matrix<T>, MatrixSpace<T>> {
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}
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companion object {
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fun <T : Any> one(rows: Int, columns: Int, field: Field<T>): Matrix<T> {
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return matrix(rows, columns, field) { i, j -> if (i == j) field.one else field.zero }
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/**
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* Create [ArrayMatrix] with custom field
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*/
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fun <T : Any> of(rows: Int, columns: Int, field: Field<T>, initializer: (Int, Int) -> T) =
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ArrayMatrix(ArrayMatrixSpace(rows, columns, field), initializer)
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/**
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* Create [ArrayMatrix] of doubles. The implementation in general should be faster than generic one due to boxing.
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*/
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fun ofReal(rows: Int, columns: Int, initializer: (Int, Int) -> Double) =
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ArrayMatrix(ArrayMatrixSpace(rows, columns, DoubleField, realNDFieldFactory), initializer)
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/**
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* Create a diagonal value matrix. By default value equals [Field.one].
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*/
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fun <T : Any> diagonal(rows: Int, columns: Int, field: Field<T>, values: (Int) -> T = { field.one }): Matrix<T> {
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return of(rows, columns, field) { i, j -> if (i == j) values(i) else field.zero }
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}
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/**
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* Equality check on two generic matrices
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*/
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fun equals(mat1: Matrix<*>, mat2: Matrix<*>): Boolean {
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if (mat1 === mat2) return true
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if (mat1.context != mat2.context) return false
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for (i in 0 until mat1.rows) {
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for (j in 0 until mat2.columns) {
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if (mat1[i, j] != mat2[i, j]) return false
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}
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}
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return true
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}
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}
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}
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@ -117,6 +167,30 @@ interface Vector<T : Any> : SpaceElement<Vector<T>, VectorSpace<T>> {
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get() = context.size
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operator fun get(i: Int): T
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companion object {
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/**
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* Create vector with custom field
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*/
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fun <T : Any> of(size: Int, field: Field<T>, initializer: (Int) -> T) =
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ArrayVector(ArrayVectorSpace(size, field), initializer)
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/**
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* Create vector of [Double]
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*/
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fun ofReal(size: Int, initializer: (Int) -> Double) =
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ArrayVector(ArrayVectorSpace(size, DoubleField, realNDFieldFactory), initializer)
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fun equals(v1: Vector<*>, v2: Vector<*>): Boolean {
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if (v1 === v2) return true
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if (v1.context != v2.context) return false
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for (i in 0 until v2.size) {
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if (v1[i] != v2[i]) return false
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}
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return true
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}
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}
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}
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@ -195,40 +269,15 @@ class ArrayVector<T : Any> internal constructor(override val context: ArrayVecto
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interface LinearSolver<T : Any> {
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fun solve(a: Matrix<T>, b: Matrix<T>): Matrix<T>
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fun solve(a: Matrix<T>, b: Vector<T>): Vector<T> = solve(a, b.toMatrix()).toVector()
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fun inverse(a: Matrix<T>): Matrix<T> = solve(a, Matrix.one(a.rows, a.columns, a.context.field))
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fun inverse(a: Matrix<T>): Matrix<T> = solve(a, Matrix.diagonal(a.rows, a.columns, a.context.field))
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}
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/**
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* Create vector with custom field
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*/
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fun <T : Any> vector(size: Int, field: Field<T>, initializer: (Int) -> T) =
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ArrayVector(ArrayVectorSpace(size, field), initializer)
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/**
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* Create vector of [Double]
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*/
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fun realVector(size: Int, initializer: (Int) -> Double) =
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ArrayVector(ArrayVectorSpace(size, DoubleField, realNDFieldFactory), initializer)
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/**
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* Convert vector to array (copying content of array)
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*/
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fun <T : Any> Array<T>.asVector(field: Field<T>) = vector(size, field) { this[it] }
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fun DoubleArray.asVector() = realVector(this.size) { this[it] }
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/**
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* Create [ArrayMatrix] with custom field
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*/
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fun <T : Any> matrix(rows: Int, columns: Int, field: Field<T>, initializer: (Int, Int) -> T) =
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ArrayMatrix(ArrayMatrixSpace(rows, columns, field), initializer)
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/**
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* Create [ArrayMatrix] of doubles.
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*/
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fun realMatrix(rows: Int, columns: Int, initializer: (Int, Int) -> Double) =
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ArrayMatrix(ArrayMatrixSpace(rows, columns, DoubleField, realNDFieldFactory), initializer)
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fun <T : Any> Array<T>.toVector(field: Field<T>) = Vector.of(size, field) { this[it] }
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fun DoubleArray.toVector() = Vector.ofReal(this.size) { this[it] }
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/**
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* Convert matrix to vector if it is possible
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@ -243,7 +292,7 @@ fun <T : Any> Matrix<T>.toVector(): Vector<T> {
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// //Generic vector
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// vector(rows, context.field) { get(it, 0) }
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// }
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vector(rows, context.field) { get(it, 0) }
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Vector.of(rows, context.field) { get(it, 0) }
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}
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else -> error("Can't convert matrix with more than one column to vector")
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}
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@ -257,6 +306,6 @@ fun <T : Any> Vector<T>.toMatrix(): Matrix<T> {
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// //Generic vector
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// matrix(size, 1, context.field) { i, j -> get(i) }
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// }
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return matrix(size, 1, context.field) { i, j -> get(i) }
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return Matrix.of(size, 1, context.field) { i, j -> get(i) }
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}
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@ -2,13 +2,20 @@ package scientifik.kmath.linear
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import scientifik.kmath.operations.DoubleField
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import kotlin.test.Test
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import kotlin.test.assertEquals
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import kotlin.test.assertTrue
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class RealLUSolverTest {
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@Test
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fun testInvert() {
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val matrix = Matrix.one(2, 2, DoubleField)
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fun testInvertOne() {
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val matrix = Matrix.diagonal(2, 2, DoubleField)
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val inverted = RealLUSolver.inverse(matrix)
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assertEquals(1.0, inverted[0, 0])
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assertTrue { Matrix.equals(matrix,inverted) }
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}
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// @Test
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// fun testInvert() {
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// val matrix = realMatrix(2,2){}
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// val inverted = RealLUSolver.inverse(matrix)
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// assertTrue { Matrix.equals(matrix,inverted) }
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// }
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}
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