Test added, examples moved to folder "examples".

0.3.1

examples/src/main/kotlin/space/kscience/kmath/series/DTWTest.kt

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+/*
+ * 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.algebra
+import space.kscience.kmath.operations.bufferAlgebra
+import space.kscience.kmath.structures.asBuffer
+
+fun main() = with(Double.algebra.bufferAlgebra.seriesAlgebra()) {
+    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 = firstSequence.asBuffer()
+    val seriesTwo = secondSequence.asBuffer()
+
+    val result = DoubleFieldOpsND.dynamicTimeWarping(seriesOne, seriesTwo)
+    println("Total penalty coefficient: ${result.totalCost}")
+    print("Alignment: ")
+    println(result.alignMatrix)
+    for ((i , j) in result.alignMatrix.indices) {
+        if (result.alignMatrix[i, j] > 0.0) {
+            print("[$i, $j] ")
+        }
+    }
+}

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/series/DynamicTimeWarping.kt

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+/*
+ * 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.PerformancePitfall
+import space.kscience.kmath.nd.*
+import space.kscience.kmath.nd.DoubleBufferND
+import space.kscience.kmath.nd.ShapeND
+import space.kscience.kmath.structures.DoubleBuffer
+import kotlin.math.abs
+
+
+/**
+ * Stores a result of [dynamicTimeWarping]. The class contains:
+ * 1. [Total penalty cost][totalCost] for series alignment.
+ * 2. [Align matrix][alignMatrix] that describes which point of the first series matches to point of the other series.
+ */
+public data class DynamicTimeWarpingData(
+    val totalCost : Double = 0.0,
+    val alignMatrix : DoubleBufferND = DoubleFieldOpsND.structureND(ShapeND(0, 0)) { (_, _) -> 0.0}
+)
+
+/**
+ * DTW method implementation. Returns alignment matrix for two series comparing and penalty for this alignment.
+ */
+@OptIn(PerformancePitfall::class)
+public fun DoubleFieldOpsND.dynamicTimeWarping(series1 : DoubleBuffer, series2 : DoubleBuffer) : DynamicTimeWarpingData {
+    // Create a special matrix of costs alignment for the two series.
+    val costMatrix = structureND(ShapeND(series1.size, series2.size)) { (row, col) ->
+        abs(series1[row] - series2[col])
+    }
+
+    // Initialise the cost matrix by formulas
+    // costMatrix[i, j] = euclideanNorm(series1(i), series2(j)) +
+    //     min(costMatrix[i - 1, j], costMatrix[i, j - 1], costMatrix[i - 1, j - 1]).
+    for ((row, col) in costMatrix.indices) {
+        costMatrix[row, col] += when {
+            row == 0 && col == 0 -> continue
+            row == 0 -> costMatrix[row, col - 1]
+            col == 0 -> costMatrix[row - 1, col]
+            else -> minOf(
+                costMatrix[row, col - 1],
+                costMatrix[row - 1, col],
+                costMatrix[row - 1, col - 1]
+            )
+        }
+    }
+
+    // alignMatrix contains non-zero values at position where two points from series matches
+    // Values are penalty for concatenation of current points.
+    val alignMatrix = structureND(ShapeND(series1.size, series2.size)) { _ -> 0.0}
+    var index1 = series1.size - 1
+    var index2 = series2.size - 1
+    var cost = 0.0
+    var pathLength = 0
+
+    alignMatrix[index1, index2] = costMatrix[index1, index2]
+    cost += costMatrix[index1, index2]
+    pathLength++
+    while (index1 != 0 || index2 != 0) {
+        when {
+            index1 == 0 -> {
+                index2--
+            }
+            index2 == 0 -> {
+                index1--
+            }
+            costMatrix[index1, index2] == costMatrix[index1, index2 - 1] + abs(series1[index1] - series2[index2]) -> {
+                index2--
+            }
+            costMatrix[index1, index2] == costMatrix[index1 - 1, index2] + abs(series1[index1] - series2[index2]) -> {
+                index1--
+            }
+            costMatrix[index1, index2] == costMatrix[index1 - 1, index2 - 1] + abs(series1[index1] - series2[index2]) -> {
+                index1--
+                index2--
+            }
+        }
+        alignMatrix[index1, index2] = costMatrix[index1, index2]
+        cost += costMatrix[index1, index2]
+        pathLength++
+    }
+    cost /= pathLength
+    
+    return DynamicTimeWarpingData(cost, alignMatrix)
+}
+
+

kmath-stat/src/commonTest/kotlin/space/kscience/kmath/series/DTWTest.kt

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+/*
+ * 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.asBuffer
+import space.kscience.kmath.structures.toDoubleBuffer
+import kotlin.math.PI
+import kotlin.test.Test
+import kotlin.test.assertEquals
+
+
+class DTWTest {
+
+    @Test
+    fun someData() {
+        val firstSequence: DoubleArray = doubleArrayOf(0.0, 2.0, 3.0, 1.0, 2.0, 3.0, 1.0, 1.0)
+        val secondSequence: DoubleArray = doubleArrayOf(0.0, 2.0, 3.0, 1.0, 2.0, 3.0, 1.0, 1.0)
+
+        val seriesOne = firstSequence.asBuffer()
+        val seriesTwo = secondSequence.asBuffer()
+
+        val result = DoubleFieldOpsND.dynamicTimeWarping(seriesOne, seriesTwo)
+        assertEquals(result.totalCost, 0.0)
+    }
+
+    @Test
+    fun pathTest() = with(Double.algebra.bufferAlgebra.seriesAlgebra()) {
+        val s1 = series(10) { DoubleField.sin(2 * PI * it / 100)}.toDoubleBuffer()
+        val s2 = series(20) {sin(PI * it / 100)}.toDoubleBuffer()
+        val s3 = series(20) {sin(PI * it / 100  + 2 * PI)}.toDoubleBuffer()
+
+        val resS1S2 = DoubleFieldOpsND.dynamicTimeWarping(s1, s2).alignMatrix
+        var pathLengthS1S2 = 0
+        for ((i,j) in resS1S2.indices) {
+            if (resS1S2[i, j] > 0.0) {
+                ++pathLengthS1S2
+            }
+        }
+
+        val resS1S3 = DoubleFieldOpsND.dynamicTimeWarping(s1, s3).alignMatrix
+        var pathLengthS1S3 = 0
+        for ((i,j) in resS1S3.indices) {
+            if (resS1S2[i, j] > 0.0) {
+                ++pathLengthS1S3
+            }
+        }
+        assertEquals(pathLengthS1S3, pathLengthS1S2)
+    }
+
+}