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first DTW method realization

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E––jenY-Poltavchiny 2023-06-11 05:31:09 +03:00
parent b8809d1c21
commit 55bcd202bf
3 changed files with 72 additions and 36 deletions
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2
kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/_generated.kt
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@ -19,9 +19,9 @@ import org.ejml.sparse.csc.factory.DecompositionFactory_DSCC
import org.ejml.sparse.csc.factory.DecompositionFactory_FSCC
import org.ejml.sparse.csc.factory.LinearSolverFactory_DSCC
import org.ejml.sparse.csc.factory.LinearSolverFactory_FSCC
import space.kscience.kmath.UnstableKMathAPI
import space.kscience.kmath.linear.*
import space.kscience.kmath.linear.Matrix
import space.kscience.kmath.UnstableKMathAPI
import space.kscience.kmath.nd.StructureFeature
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.FloatField

65
kmath-stat/src/commonMain/kotlin/space/kscience/kmath/series/DynamicTimeWarping.kt
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@ -5,6 +5,11 @@
package space.kscience.kmath.series
import space.kscience.kmath.nd.*
import space.kscience.kmath.nd.DoubleBufferND
import space.kscience.kmath.nd.ShapeND
import space.kscience.kmath.nd.ndAlgebra
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.structures.DoubleBuffer
import kotlin.math.abs
@ -12,9 +17,11 @@ public const val LEFT_OFFSET : Int = -1
public const val BOTTOM_OFFSET : Int = 1
public const val DIAGONAL_OFFSET : Int = 0
// TODO: Change container for alignMatrix to kmath special ND structure
public data class DynamicTimeWarpingData(val totalCost : Double = 0.0,
val alignMatrix : Array<BooleanArray> = Array(0) {BooleanArray(0)}) {
val alignMatrix : IntBufferND = IntRingOpsND.structureND(ShapeND(0, 0)) { (i, j) -> 0}) {
override fun equals(other: Any?): Boolean {
if (this === other) return true
if (other == null || this::class != other::class) return false
@ -22,16 +29,9 @@ public data class DynamicTimeWarpingData(val totalCost : Double = 0.0,
other as DynamicTimeWarpingData
if (totalCost != other.totalCost) return false
if (!alignMatrix.contentDeepEquals(other.alignMatrix)) return false
return true
}
override fun hashCode(): Int {
var result = totalCost.hashCode()
result = 31 * result + alignMatrix.contentDeepHashCode()
return result
}
}
/**
@ -42,25 +42,20 @@ public data class DynamicTimeWarpingData(val totalCost : Double = 0.0,
* There is special cases for i = 0 or j = 0.
*/
public fun costMatrix(series1 : DoubleBuffer, series2 : DoubleBuffer) : Array<DoubleArray> {
val dtwMatrix: Array<DoubleArray> = Array(series1.size){ row ->
DoubleArray(series2.size) { col ->
abs(series1[row] - series2[col])
}
public fun costMatrix(series1 : DoubleBuffer, series2 : DoubleBuffer) : DoubleBufferND {
val dtwMatrix = DoubleField.ndAlgebra.structureND(ShapeND(series1.size, series2.size)) {
(row, col) -> abs(series1[row] - series2[col])
}
for (i in dtwMatrix.indices) {
for (j in dtwMatrix[i].indices) {
dtwMatrix[i][j] += when {
i == 0 && j == 0 -> 0.0
i == 0 -> dtwMatrix[i][j-1]
j == 0 -> dtwMatrix[i-1][j]
else -> minOf(
dtwMatrix[i][j-1],
dtwMatrix[i-1][j],
dtwMatrix[i-1][j-1]
)
}
for ( (row, col) in dtwMatrix.indices) {
dtwMatrix[row, col] += when {
row == 0 && col == 0 -> 0.0
row == 0 -> dtwMatrix[row, col - 1]
col == 0 -> dtwMatrix[row - 1, col]
else -> minOf(
dtwMatrix[row, col - 1],
dtwMatrix[row - 1, col],
dtwMatrix[row - 1, col - 1]
)
}
}
return dtwMatrix
@ -95,27 +90,27 @@ public fun dynamicTimeWarping(series1 : DoubleBuffer, series2 : DoubleBuffer) :
var cost = 0.0
var pathLength = 0
val costMatrix = costMatrix(series1, series2)
val alignMatrix : Array<BooleanArray> = Array(costMatrix.size) { BooleanArray(costMatrix.first().size) }
val indexes = PathIndices(alignMatrix.lastIndex, alignMatrix.last().lastIndex)
val alignMatrix: IntBufferND = IntRingOpsND.structureND(ShapeND(series1.size, series2.size)) {(row, col) -> 0}
val indexes = PathIndices(alignMatrix.indices.shape.first() - 1, alignMatrix.indices.shape.last() - 1)
with(indexes) {
alignMatrix[id_x][id_y] = true
cost += costMatrix[id_x][id_y]
alignMatrix[id_x, id_y] = 1
cost += costMatrix[id_x, id_y]
pathLength++
while (id_x != 0 || id_y != 0) {
when {
id_x == 0 || costMatrix[id_x][id_y] == costMatrix[id_x][id_y - 1] + abs(series1[id_x] - series2[id_y]) -> {
id_x == 0 || costMatrix[id_x, id_y] == costMatrix[id_x, id_y - 1] + abs(series1[id_x] - series2[id_y]) -> {
moveOption(LEFT_OFFSET)
}
id_y == 0 || costMatrix[id_x][id_y] == costMatrix[id_x - 1][id_y] + abs(series1[id_x] - series2[id_y]) -> {
id_y == 0 || costMatrix[id_x, id_y] == costMatrix[id_x - 1, id_y] + abs(series1[id_x] - series2[id_y]) -> {
moveOption(BOTTOM_OFFSET)
}
costMatrix[id_x][id_y] == costMatrix[id_x - 1][id_y - 1] + abs(series1[id_x] - series2[id_y]) -> {
costMatrix[id_x, id_y] == costMatrix[id_x - 1, id_y - 1] + abs(series1[id_x] - series2[id_y]) -> {
moveOption(DIAGONAL_OFFSET)
}
}
alignMatrix[id_x][id_y] = true
cost += costMatrix[id_x][id_y]
alignMatrix[id_x, id_y] = 1
cost += costMatrix[id_x, id_y]
pathLength++
}
cost /= pathLength

41
kmath-stat/src/commonTest/kotlin/space/kscience/kmath/series/DTWTest.kt Normal file
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@ -0,0 +1,41 @@
/*
* Copyright 2018-2023 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.series
import space.kscience.kmath.nd.*
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.algebra
import space.kscience.kmath.operations.bufferAlgebra
import space.kscience.kmath.structures.DoubleBuffer
import space.kscience.kmath.structures.asBuffer
import kotlin.test.Test
import kotlin.test.assertEquals
class DTWTest {
@Test
fun someData() : Unit {
with(Double.algebra.bufferAlgebra) {
val firstSequence: DoubleArray = doubleArrayOf(0.0, 2.0, 3.0, 1.0, 3.0, 0.1, 0.0, 1.0)
val secondSequence: DoubleArray = doubleArrayOf(1.0, 0.0, 3.0, 0.0, 0.0, 3.0, 2.0, 0.0, 2.0)
val seriesOne: DoubleBuffer = firstSequence.asBuffer()
val seriesTwo: DoubleBuffer = secondSequence.asBuffer()
val result = dynamicTimeWarping(seriesOne, seriesTwo)
println("Total penalty coefficient: ${result.totalCost}")
print("Alignment: ")
println(result.alignMatrix)
for ((i , j) in result.alignMatrix.indices) {
if (result.alignMatrix[i, j] == 1) {
print("[$i, $j] ")
}
}
}
}
}