Added Levenberg-Marquardt algorithm and svd Golub-Kahan #513
1
.gitignore
vendored
1
.gitignore
vendored
@ -4,6 +4,7 @@ out/
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.idea/
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.vscode/
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.fleet/
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|
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# Avoid ignoring Gradle wrapper jar file (.jar files are usually ignored)
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|
47
.space.kts
47
.space.kts
@ -1,3 +1,48 @@
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import kotlin.io.path.readText
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|
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val projectName = "kmath"
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|
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job("Build") {
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gradlew("openjdk:11", "build")
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//Perform only jvm tests
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gradlew("spc.registry.jetbrains.space/p/sci/containers/kotlin-ci:1.0.3", "test", "jvmTest")
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}
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|
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job("Publish") {
|
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startOn {
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gitPush { enabled = false }
|
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}
|
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container("spc.registry.jetbrains.space/p/sci/containers/kotlin-ci:1.0.3") {
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env["SPACE_USER"] = "{{ project:space_user }}"
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env["SPACE_TOKEN"] = "{{ project:space_token }}"
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kotlinScript { api ->
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val spaceUser = System.getenv("SPACE_USER")
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val spaceToken = System.getenv("SPACE_TOKEN")
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|
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// write the version to the build directory
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api.gradlew("version")
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|
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//read the version from build file
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val version = java.nio.file.Path.of("build/project-version.txt").readText()
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val revisionSuffix = if (version.endsWith("SNAPSHOT")) {
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"-" + api.gitRevision().take(7)
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} else {
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""
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}
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api.space().projects.automation.deployments.start(
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project = api.projectIdentifier(),
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targetIdentifier = TargetIdentifier.Key(projectName),
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version = version+revisionSuffix,
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// automatically update deployment status based on the status of a job
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syncWithAutomationJob = true
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)
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api.gradlew(
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"publishAllPublicationsToSpaceRepository",
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"-Ppublishing.space.user=\"$spaceUser\"",
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"-Ppublishing.space.token=\"$spaceToken\"",
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)
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}
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}
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}
|
@ -14,7 +14,7 @@
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### Security
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## 0.3.1-dev-RC - 2023-04-09
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## 0.3.1 - 2023-04-09
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### Added
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- Wasm support for `memory`, `core`, `complex` and `functions` modules.
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|
@ -15,7 +15,7 @@ allprojects {
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}
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group = "space.kscience"
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version = "0.3.1-dev-RC"
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version = "0.3.1"
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}
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subprojects {
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|
@ -3,8 +3,11 @@
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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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@file:OptIn(UnstableKMathAPI::class)
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package space.kscience.kmath.ast
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import space.kscience.kmath.UnstableKMathAPI
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import space.kscience.kmath.expressions.Expression
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import space.kscience.kmath.expressions.MST
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import space.kscience.kmath.expressions.Symbol
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|
@ -5,6 +5,7 @@
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package space.kscience.kmath.wasm
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import space.kscience.kmath.UnstableKMathAPI
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import space.kscience.kmath.expressions.MstExtendedField
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import space.kscience.kmath.expressions.MstRing
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import space.kscience.kmath.expressions.invoke
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@ -15,6 +16,7 @@ import space.kscience.kmath.operations.invoke
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import kotlin.test.Test
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import kotlin.test.assertEquals
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@OptIn(UnstableKMathAPI::class)
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internal class TestWasmSpecific {
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@Test
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fun int() {
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|
@ -5,6 +5,7 @@
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package space.kscience.kmath.ast
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import space.kscience.kmath.UnstableKMathAPI
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import space.kscience.kmath.expressions.Expression
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import space.kscience.kmath.expressions.MST
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import space.kscience.kmath.expressions.Symbol
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@ -30,6 +31,7 @@ private object GenericAsmCompilerTestContext : CompilerTestContext {
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asmCompile(algebra as Algebra<Double>, arguments)
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}
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@OptIn(UnstableKMathAPI::class)
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private object PrimitiveAsmCompilerTestContext : CompilerTestContext {
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override fun MST.compileToExpression(algebra: IntRing): Expression<Int> = asmCompileToExpression(algebra)
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override fun MST.compile(algebra: IntRing, arguments: Map<Symbol, Int>): Int = asmCompile(algebra, arguments)
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|
File diff suppressed because it is too large
Load Diff
@ -9,7 +9,7 @@ package space.kscience.kmath.misc
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* The same as [zipWithNext], but includes link between last and first element
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*/
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public inline fun <T, R> List<T>.zipWithNextCircular(transform: (a: T, b: T) -> R): List<R> {
|
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if (isEmpty()) return emptyList()
|
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if (size < 2) return emptyList()
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return indices.map { i ->
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if (i == size - 1) {
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transform(last(), first())
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@ -19,4 +19,4 @@ public inline fun <T, R> List<T>.zipWithNextCircular(transform: (a: T, b: T) ->
|
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}
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}
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public fun <T> List<T>.zipWithNextCircular(): List<Pair<T,T>> = zipWithNextCircular { l, r -> l to r }
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public fun <T> List<T>.zipWithNextCircular(): List<Pair<T, T>> = zipWithNextCircular { l, r -> l to r }
|
@ -5,7 +5,6 @@ import space.kscience.kmath.UnstableKMathAPI
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/**
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* Non-boxing access to primitive [Double]
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*/
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@UnstableKMathAPI
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public fun Buffer<Double>.getDouble(index: Int): Double = if (this is BufferView) {
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val originIndex = originIndex(index)
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|
@ -6,6 +6,7 @@
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package space.kscience.kmath.kotlingrad
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import ai.hypergraph.kotlingrad.api.*
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import space.kscience.kmath.UnstableKMathAPI
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import space.kscience.kmath.asm.compileToExpression
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import space.kscience.kmath.ast.parseMath
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import space.kscience.kmath.expressions.MstNumericAlgebra
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@ -17,6 +18,7 @@ import kotlin.test.assertEquals
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import kotlin.test.assertTrue
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import kotlin.test.fail
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@OptIn(UnstableKMathAPI::class)
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internal class AdaptingTests {
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@Test
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fun symbol() {
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|
@ -1,3 +1,14 @@
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public abstract interface annotation class space/kscience/kmath/PerformancePitfall : java/lang/annotation/Annotation {
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public abstract fun message ()Ljava/lang/String;
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}
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public abstract interface annotation class space/kscience/kmath/UnsafeKMathAPI : java/lang/annotation/Annotation {
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public abstract fun message ()Ljava/lang/String;
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}
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public abstract interface annotation class space/kscience/kmath/UnstableKMathAPI : java/lang/annotation/Annotation {
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}
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public final class space/kscience/kmath/memory/ByteBufferMemory : space/kscience/kmath/memory/Memory {
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public fun <init> (Ljava/nio/ByteBuffer;II)V
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public synthetic fun <init> (Ljava/nio/ByteBuffer;IIILkotlin/jvm/internal/DefaultConstructorMarker;)V
|
||||
@ -36,7 +47,8 @@ public final class space/kscience/kmath/memory/MemoryKt {
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public static final fun write (Lspace/kscience/kmath/memory/Memory;Lkotlin/jvm/functions/Function1;)V
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}
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public abstract interface class space/kscience/kmath/memory/MemoryReader {
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public abstract interface class space/kscience/kmath/memory/MemoryReader : java/lang/AutoCloseable {
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public abstract fun close ()V
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public abstract fun getMemory ()Lspace/kscience/kmath/memory/Memory;
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public abstract fun readByte (I)B
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public abstract fun readDouble (I)D
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@ -44,7 +56,6 @@ public abstract interface class space/kscience/kmath/memory/MemoryReader {
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public abstract fun readInt (I)I
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public abstract fun readLong (I)J
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public abstract fun readShort (I)S
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public abstract fun release ()V
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}
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public abstract interface class space/kscience/kmath/memory/MemorySpec {
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@ -59,9 +70,9 @@ public final class space/kscience/kmath/memory/MemorySpecKt {
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public static final fun writeArray (Lspace/kscience/kmath/memory/MemoryWriter;Lspace/kscience/kmath/memory/MemorySpec;I[Ljava/lang/Object;)V
|
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}
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public abstract interface class space/kscience/kmath/memory/MemoryWriter {
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public abstract interface class space/kscience/kmath/memory/MemoryWriter : java/lang/AutoCloseable {
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public abstract fun close ()V
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public abstract fun getMemory ()Lspace/kscience/kmath/memory/Memory;
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public abstract fun release ()V
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public abstract fun writeByte (IB)V
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public abstract fun writeDouble (ID)V
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public abstract fun writeFloat (IF)V
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|
@ -6,6 +6,7 @@
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package space.kscience.kmath.distributions
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import space.kscience.kmath.chains.Chain
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import space.kscience.kmath.operations.DoubleField.pow
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import space.kscience.kmath.random.RandomGenerator
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import space.kscience.kmath.samplers.GaussianSampler
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import space.kscience.kmath.samplers.InternalErf
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@ -34,8 +35,23 @@ public class NormalDistribution(public val sampler: GaussianSampler) : Distribut
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}
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}
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private companion object {
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public companion object {
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private val SQRT2 = sqrt(2.0)
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|
||||
/**
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* Zelen & Severo approximation for the standard normal CDF.
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* The error upper boundary by 7.5 * 10e-8.
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*/
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public fun zSNormalCDF(x: Double): Double {
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val t = 1 / (1 + 0.2316419 * abs(x))
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val sum = 0.319381530 * t -
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0.356563782 * t.pow(2) +
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1.781477937 * t.pow(3) -
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1.821255978 * t.pow(4) +
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1.330274429 * t.pow(5)
|
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val temp = sum * exp(-abs(x).pow(2) / 2) / (2 * PI).pow(0.5)
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return if (x >= 0) 1 - temp else temp
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}
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -191,7 +191,7 @@ public open class SeriesAlgebra<T, out A : Ring<T>, out BA : BufferAlgebra<T, A>
|
||||
crossinline operation: A.(left: T, right: T) -> T,
|
||||
): Series<T> {
|
||||
val newRange = offsetIndices.intersect(other.offsetIndices)
|
||||
return seriesByOffset(startOffset = newRange.first, size = newRange.last - newRange.first) { offset ->
|
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return seriesByOffset(startOffset = newRange.first, size = newRange.last + 1 - newRange.first) { offset ->
|
||||
elementAlgebra.operation(
|
||||
getByOffset(offset),
|
||||
other.getByOffset(offset)
|
||||
@ -199,12 +199,25 @@ public open class SeriesAlgebra<T, out A : Ring<T>, out BA : BufferAlgebra<T, A>
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Zip buffer with itself, but shifted
|
||||
* */
|
||||
public inline fun Buffer<T>.zipWithShift(
|
||||
shift: Int = 1,
|
||||
crossinline operation: A.(left: T, right: T) -> T
|
||||
): Buffer<T> {
|
||||
val shifted = this.moveBy(shift)
|
||||
return zip(shifted, operation)
|
||||
}
|
||||
|
||||
override fun Buffer<T>.unaryMinus(): Buffer<T> = map { -it }
|
||||
|
||||
override fun add(left: Buffer<T>, right: Buffer<T>): Series<T> = left.zip(right) { l, r -> l + r }
|
||||
|
||||
override fun multiply(left: Buffer<T>, right: Buffer<T>): Buffer<T> = left.zip(right) { l, r -> l * r }
|
||||
|
||||
public fun Buffer<T>.difference(shift: Int=1): Buffer<T> = this.zipWithShift(shift) {l, r -> r - l}
|
||||
|
||||
public companion object
|
||||
}
|
||||
|
||||
|
@ -0,0 +1,82 @@
|
||||
/*
|
||||
* 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.distributions.NormalDistribution
|
||||
import space.kscience.kmath.operations.DoubleField.pow
|
||||
import space.kscience.kmath.operations.fold
|
||||
import kotlin.math.absoluteValue
|
||||
|
||||
|
||||
/**
|
||||
* Container class for Variance Ratio Test result:
|
||||
* ratio itself, corresponding Z-score, also it's p-value
|
||||
*/
|
||||
public data class VarianceRatioTestResult(
|
||||
val varianceRatio: Double = 1.0,
|
||||
val zScore: Double = 0.0,
|
||||
val pValue: Double = 0.5,
|
||||
)
|
||||
|
||||
|
||||
/**
|
||||
* Calculates the Z-statistic and the p-value for the Lo and MacKinlay's Variance Ratio test (1987)
|
||||
* under Homoscedastic or Heteroscedstic assumptions
|
||||
* with two-sided p-value test
|
||||
* https://ssrn.com/abstract=346975
|
||||
*
|
||||
* @author https://github.com/mrFendel
|
||||
*/
|
||||
public fun SeriesAlgebra<Double, *, *, *>.varianceRatioTest(
|
||||
series: Series<Double>,
|
||||
shift: Int,
|
||||
homoscedastic: Boolean = true,
|
||||
): VarianceRatioTestResult {
|
||||
|
||||
require(shift > 1) { "Shift must be greater than one" }
|
||||
require(shift < series.size) { "Shift must be smaller than sample size" }
|
||||
val sum = { x: Double, y: Double -> x + y }
|
||||
|
||||
|
||||
val mean = series.fold(0.0, sum) / series.size
|
||||
val demeanedSquares = series.map { (it - mean).pow(2) }
|
||||
val variance = demeanedSquares.fold(0.0, sum)
|
||||
if (variance == 0.0) return VarianceRatioTestResult()
|
||||
|
||||
|
||||
var seriesAgg = series
|
||||
for (i in 1..<shift) {
|
||||
seriesAgg = seriesAgg.zip(series.moveTo(i)) { v1, v2 -> v1 + v2 }
|
||||
}
|
||||
|
||||
val demeanedSquaresAgg = seriesAgg.map { (it - shift * mean).pow(2) }
|
||||
val varianceAgg = demeanedSquaresAgg.fold(0.0, sum)
|
||||
|
||||
val varianceRatio =
|
||||
varianceAgg * (series.size.toDouble() - 1) / variance / (series.size.toDouble() - shift.toDouble() + 1) / (1 - shift.toDouble() / series.size.toDouble()) / shift.toDouble()
|
||||
|
||||
|
||||
// calculating asymptotic variance
|
||||
val phi = if (homoscedastic) { // under homoscedastic null hypothesis
|
||||
2 * (2 * shift - 1.0) * (shift - 1.0) / (3 * shift * series.size)
|
||||
} else { // under heteroscedastic null hypothesis
|
||||
var accumulator = 0.0
|
||||
for (j in 1..<shift) {
|
||||
val temp = demeanedSquares
|
||||
val delta = series.size * temp.zipWithShift(j) { v1, v2 -> v1 * v2 }.fold(0.0, sum) / variance.pow(2)
|
||||
accumulator += delta * 4 * (shift - j).toDouble().pow(2) / shift.toDouble().pow(2)
|
||||
}
|
||||
accumulator
|
||||
}
|
||||
|
||||
val zScore = (varianceRatio - 1) / phi.pow(0.5)
|
||||
val pValue = 2 * (1 - NormalDistribution.zSNormalCDF(zScore.absoluteValue))
|
||||
return VarianceRatioTestResult(varianceRatio, zScore, pValue)
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
@ -0,0 +1,72 @@
|
||||
/*
|
||||
* 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.operations.algebra
|
||||
import space.kscience.kmath.operations.bufferAlgebra
|
||||
import kotlin.math.PI
|
||||
import kotlin.test.Test
|
||||
import kotlin.test.assertEquals
|
||||
|
||||
class TestVarianceRatioTest {
|
||||
|
||||
@Test
|
||||
fun monotonicData() {
|
||||
with(Double.algebra.bufferAlgebra.seriesAlgebra()) {
|
||||
val monotonicData = series(10) { it * 1.0 }
|
||||
val resultHomo = varianceRatioTest(monotonicData, 2, homoscedastic = true)
|
||||
assertEquals(1.818181, resultHomo.varianceRatio, 1e-6)
|
||||
// homoscedastic zScore
|
||||
assertEquals(2.587318, resultHomo.zScore, 1e-6)
|
||||
assertEquals(.0096, resultHomo.pValue, 1e-4)
|
||||
val resultHetero = varianceRatioTest(monotonicData, 2, homoscedastic = false)
|
||||
// heteroscedastic zScore
|
||||
assertEquals(0.819424, resultHetero.zScore, 1e-6)
|
||||
assertEquals(.4125, resultHetero.pValue, 1e-4)
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
fun volatileData() {
|
||||
with(Double.algebra.bufferAlgebra.seriesAlgebra()) {
|
||||
val volatileData = series(10) { sin(PI * it + PI/2) + 1.0}
|
||||
val resultHomo = varianceRatioTest(volatileData, 2)
|
||||
assertEquals(0.0, resultHomo.varianceRatio, 1e-6)
|
||||
// homoscedastic zScore
|
||||
assertEquals(-3.162277, resultHomo.zScore, 1e-6)
|
||||
assertEquals(.0015, resultHomo.pValue, 1e-4)
|
||||
val resultHetero = varianceRatioTest(volatileData, 2, homoscedastic = false)
|
||||
// heteroscedastic zScore
|
||||
assertEquals(-1.0540925, resultHetero.zScore, 1e-6)
|
||||
assertEquals(.2918, resultHetero.pValue, 1e-4)
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
fun negativeData() {
|
||||
with(Double.algebra.bufferAlgebra.seriesAlgebra()) {
|
||||
val negativeData = series(10) { sin(it * 1.2)}
|
||||
val resultHomo = varianceRatioTest(negativeData, 3)
|
||||
assertEquals(1.240031, resultHomo.varianceRatio, 1e-6)
|
||||
// homoscedastic zScore
|
||||
assertEquals(0.509183, resultHomo.zScore, 1e-6)
|
||||
val resultHetero = varianceRatioTest(negativeData, 3, homoscedastic = false)
|
||||
// heteroscedastic zScore
|
||||
assertEquals(0.209202, resultHetero.zScore, 1e-6)
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
fun zeroVolatility() {
|
||||
with(Double.algebra.bufferAlgebra.seriesAlgebra()) {
|
||||
val zeroVolData = series(10) { 0.0 }
|
||||
val result = varianceRatioTest(zeroVolData, 4)
|
||||
assertEquals(1.0, result.varianceRatio, 1e-6)
|
||||
assertEquals(0.0, result.zScore, 1e-6)
|
||||
assertEquals(0.5, result.pValue, 1e-4)
|
||||
}
|
||||
}
|
||||
}
|
@ -29,7 +29,7 @@ public class space/kscience/kmath/viktor/ViktorFieldND : space/kscience/kmath/vi
|
||||
public synthetic fun getOne ()Ljava/lang/Object;
|
||||
public synthetic fun getOne ()Lspace/kscience/kmath/nd/StructureND;
|
||||
public fun getOne ()Lspace/kscience/kmath/viktor/ViktorStructureND;
|
||||
public fun getShape ()[I
|
||||
public fun getShape-IIYLAfE ()[I
|
||||
public synthetic fun getZero ()Ljava/lang/Object;
|
||||
public synthetic fun getZero ()Lspace/kscience/kmath/nd/StructureND;
|
||||
public fun getZero ()Lspace/kscience/kmath/viktor/ViktorStructureND;
|
||||
@ -85,8 +85,8 @@ public class space/kscience/kmath/viktor/ViktorFieldOpsND : space/kscience/kmath
|
||||
public fun sin (Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/viktor/ViktorStructureND;
|
||||
public synthetic fun sinh (Ljava/lang/Object;)Ljava/lang/Object;
|
||||
public fun sinh (Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/viktor/ViktorStructureND;
|
||||
public synthetic fun structureND ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
|
||||
public fun structureND ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/viktor/ViktorStructureND;
|
||||
public synthetic fun structureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/StructureND;
|
||||
public fun structureND-qL90JFI ([ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/viktor/ViktorStructureND;
|
||||
public synthetic fun tan (Ljava/lang/Object;)Ljava/lang/Object;
|
||||
public fun tan (Lspace/kscience/kmath/nd/StructureND;)Lspace/kscience/kmath/viktor/ViktorStructureND;
|
||||
public synthetic fun times (Ljava/lang/Object;Ljava/lang/Number;)Ljava/lang/Object;
|
||||
@ -112,7 +112,7 @@ public final class space/kscience/kmath/viktor/ViktorStructureND : space/kscienc
|
||||
public fun get ([I)Ljava/lang/Double;
|
||||
public synthetic fun get ([I)Ljava/lang/Object;
|
||||
public final fun getF64Buffer ()Lorg/jetbrains/bio/viktor/F64Array;
|
||||
public fun getShape ()[I
|
||||
public fun getShape-IIYLAfE ()[I
|
||||
public fun set ([ID)V
|
||||
public synthetic fun set ([ILjava/lang/Object;)V
|
||||
}
|
||||
|
4
test-utils/README.md
Normal file
4
test-utils/README.md
Normal file
@ -0,0 +1,4 @@
|
||||
# Module test-utils
|
||||
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user