forked from kscience/kmath
first DTW method realization
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@ -19,9 +19,9 @@ import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC
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import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC
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import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC
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import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC
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import space.kscience.kmath.UnstableKMathAPI
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import space.kscience.kmath.linear.*
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import space.kscience.kmath.linear.Matrix
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import space.kscience.kmath.UnstableKMathAPI
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import space.kscience.kmath.nd.StructureFeature
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import space.kscience.kmath.operations.DoubleField
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import space.kscience.kmath.operations.FloatField
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@ -5,6 +5,11 @@
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package space.kscience.kmath.series
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import space.kscience.kmath.nd.*
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import space.kscience.kmath.nd.DoubleBufferND
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import space.kscience.kmath.nd.ShapeND
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import space.kscience.kmath.nd.ndAlgebra
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import space.kscience.kmath.operations.DoubleField
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import space.kscience.kmath.structures.DoubleBuffer
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import kotlin.math.abs
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@ -12,9 +17,11 @@ public const val LEFT_OFFSET : Int = -1
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public const val BOTTOM_OFFSET : Int = 1
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public const val DIAGONAL_OFFSET : Int = 0
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// TODO: Change container for alignMatrix to kmath special ND structure
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public data class DynamicTimeWarpingData(val totalCost : Double = 0.0,
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val alignMatrix : Array<BooleanArray> = Array(0) {BooleanArray(0)}) {
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val alignMatrix : IntBufferND = IntRingOpsND.structureND(ShapeND(0, 0)) { (i, j) -> 0}) {
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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 == null || this::class != other::class) return false
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@ -22,16 +29,9 @@ public data class DynamicTimeWarpingData(val totalCost : Double = 0.0,
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other as DynamicTimeWarpingData
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if (totalCost != other.totalCost) return false
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if (!alignMatrix.contentDeepEquals(other.alignMatrix)) 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 = totalCost.hashCode()
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result = 31 * result + alignMatrix.contentDeepHashCode()
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return result
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}
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}
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/**
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@ -42,25 +42,20 @@ public data class DynamicTimeWarpingData(val totalCost : Double = 0.0,
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* There is special cases for i = 0 or j = 0.
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*/
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public fun costMatrix(series1 : DoubleBuffer, series2 : DoubleBuffer) : Array<DoubleArray> {
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val dtwMatrix: Array<DoubleArray> = Array(series1.size){ row ->
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DoubleArray(series2.size) { col ->
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abs(series1[row] - series2[col])
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}
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public fun costMatrix(series1 : DoubleBuffer, series2 : DoubleBuffer) : DoubleBufferND {
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val dtwMatrix = DoubleField.ndAlgebra.structureND(ShapeND(series1.size, series2.size)) {
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(row, col) -> abs(series1[row] - series2[col])
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}
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for (i in dtwMatrix.indices) {
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for (j in dtwMatrix[i].indices) {
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dtwMatrix[i][j] += when {
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i == 0 && j == 0 -> 0.0
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i == 0 -> dtwMatrix[i][j-1]
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j == 0 -> dtwMatrix[i-1][j]
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else -> minOf(
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dtwMatrix[i][j-1],
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dtwMatrix[i-1][j],
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dtwMatrix[i-1][j-1]
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)
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}
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for ( (row, col) in dtwMatrix.indices) {
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dtwMatrix[row, col] += when {
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row == 0 && col == 0 -> 0.0
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row == 0 -> dtwMatrix[row, col - 1]
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col == 0 -> dtwMatrix[row - 1, col]
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else -> minOf(
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dtwMatrix[row, col - 1],
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dtwMatrix[row - 1, col],
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dtwMatrix[row - 1, col - 1]
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)
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}
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}
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return dtwMatrix
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@ -95,27 +90,27 @@ public fun dynamicTimeWarping(series1 : DoubleBuffer, series2 : DoubleBuffer) :
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var cost = 0.0
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var pathLength = 0
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val costMatrix = costMatrix(series1, series2)
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val alignMatrix : Array<BooleanArray> = Array(costMatrix.size) { BooleanArray(costMatrix.first().size) }
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val indexes = PathIndices(alignMatrix.lastIndex, alignMatrix.last().lastIndex)
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val alignMatrix: IntBufferND = IntRingOpsND.structureND(ShapeND(series1.size, series2.size)) {(row, col) -> 0}
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val indexes = PathIndices(alignMatrix.indices.shape.first() - 1, alignMatrix.indices.shape.last() - 1)
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with(indexes) {
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alignMatrix[id_x][id_y] = true
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cost += costMatrix[id_x][id_y]
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alignMatrix[id_x, id_y] = 1
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cost += costMatrix[id_x, id_y]
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pathLength++
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while (id_x != 0 || id_y != 0) {
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when {
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id_x == 0 || costMatrix[id_x][id_y] == costMatrix[id_x][id_y - 1] + abs(series1[id_x] - series2[id_y]) -> {
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id_x == 0 || costMatrix[id_x, id_y] == costMatrix[id_x, id_y - 1] + abs(series1[id_x] - series2[id_y]) -> {
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moveOption(LEFT_OFFSET)
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}
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id_y == 0 || costMatrix[id_x][id_y] == costMatrix[id_x - 1][id_y] + abs(series1[id_x] - series2[id_y]) -> {
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id_y == 0 || costMatrix[id_x, id_y] == costMatrix[id_x - 1, id_y] + abs(series1[id_x] - series2[id_y]) -> {
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moveOption(BOTTOM_OFFSET)
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}
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costMatrix[id_x][id_y] == costMatrix[id_x - 1][id_y - 1] + abs(series1[id_x] - series2[id_y]) -> {
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costMatrix[id_x, id_y] == costMatrix[id_x - 1, id_y - 1] + abs(series1[id_x] - series2[id_y]) -> {
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moveOption(DIAGONAL_OFFSET)
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}
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}
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alignMatrix[id_x][id_y] = true
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cost += costMatrix[id_x][id_y]
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alignMatrix[id_x, id_y] = 1
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cost += costMatrix[id_x, id_y]
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pathLength++
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}
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cost /= pathLength
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@ -0,0 +1,41 @@
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/*
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* Copyright 2018-2023 KMath contributors.
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* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
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*/
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package space.kscience.kmath.series
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import space.kscience.kmath.nd.*
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import space.kscience.kmath.operations.DoubleField
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import space.kscience.kmath.operations.algebra
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import space.kscience.kmath.operations.bufferAlgebra
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import space.kscience.kmath.structures.DoubleBuffer
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import space.kscience.kmath.structures.asBuffer
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import kotlin.test.Test
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import kotlin.test.assertEquals
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class DTWTest {
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@Test
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fun someData() : Unit {
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with(Double.algebra.bufferAlgebra) {
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val firstSequence: DoubleArray = doubleArrayOf(0.0, 2.0, 3.0, 1.0, 3.0, 0.1, 0.0, 1.0)
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val secondSequence: DoubleArray = doubleArrayOf(1.0, 0.0, 3.0, 0.0, 0.0, 3.0, 2.0, 0.0, 2.0)
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val seriesOne: DoubleBuffer = firstSequence.asBuffer()
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val seriesTwo: DoubleBuffer = secondSequence.asBuffer()
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val result = dynamicTimeWarping(seriesOne, seriesTwo)
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println("Total penalty coefficient: ${result.totalCost}")
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print("Alignment: ")
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println(result.alignMatrix)
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for ((i , j) in result.alignMatrix.indices) {
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if (result.alignMatrix[i, j] == 1) {
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print("[$i, $j] ")
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}
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}
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}
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}
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}
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