Switch to kotlin 1.3 eap and mpp build
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README.md
29
README.md
@ -40,8 +40,33 @@ but worse than optimized native/scipy (mostly due to boxing operations on primit
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of optimized parts should be better than scipy.
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## Releases
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The project is currently in pre-release stage. Work builds could be obtained with
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[![](https://jitpack.io/v/altavir/kmath.svg)](https://jitpack.io/#altavir/kmath).
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The project is currently in pre-release stage. Nightly builds could be used by adding additional repository to (groovy) gradle config:
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```groovy
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repositories {
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maven { url = "http://npm.mipt.ru:8081/artifactory/gradle-dev" }
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mavenCentral()
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}
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```
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or for kotlin gradle dsl:
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```kotlin
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repositories {
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maven { setUrl("http://npm.mipt.ru:8081/artifactory/gradle-dev") }
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mavenCentral()
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}
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```
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Then use regular dependency like
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```groovy
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compile(group: 'scientifik', name: 'kmath-core-jvm', version: '0.0.1-SNAPSHOT')
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```
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or in kotlin
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```kotlin
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compile(group = "scientifik", name = "kmath-core-jvm", version = "0.0.1-SNAPSHOT")
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```
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Work builds could be obtained with [![](https://jitpack.io/v/altavir/kmath.svg)](https://jitpack.io/#altavir/kmath).
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## Contributing
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The project requires a lot of additional work. Please fill free to contribute in any way and propose new features.
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build.gradle
17
build.gradle
@ -1,17 +1,19 @@
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buildscript {
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ext.kotlin_version = '1.2.71'
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ext.kotlin_version = '1.3.0-rc-116'
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repositories {
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jcenter()
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maven {
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url = "http://dl.bintray.com/kotlin/kotlin-eap"
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}
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}
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dependencies {
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classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
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classpath "org.jfrog.buildinfo:build-info-extractor-gradle:4+"
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}
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}
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allprojects{
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apply plugin: 'maven'
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allprojects {
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apply plugin: 'maven-publish'
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apply plugin: "com.jfrog.artifactory"
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@ -27,13 +29,11 @@ artifactory {
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repoKey = 'gradle-dev-local'
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username = "${artifactory_user}"
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password = "${artifactory_password}"
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maven = true
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}
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defaults {
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publications 'defaultPublication'
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publishBuildInfo = true
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publications('jvm', 'kotlinMultiplatform', 'metadata')
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publishBuildInfo = false
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publishArtifacts = true
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publishPom = true
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publishIvy = false
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@ -44,7 +44,6 @@ artifactory {
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repoKey = 'gradle-dev'
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username = "${artifactory_user}"
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password = "${artifactory_password}"
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maven = true
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}
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}
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}
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@ -1,22 +0,0 @@
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plugins{
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id "kotlin-platform-common"
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}
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description = "Platform-independent interfaces for kotlin maths"
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repositories {
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mavenCentral()
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}
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dependencies {
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compile "org.jetbrains.kotlin:kotlin-stdlib-common:$kotlin_version"
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testCompile "org.jetbrains.kotlin:kotlin-test-annotations-common:$kotlin_version"
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testCompile "org.jetbrains.kotlin:kotlin-test-common:$kotlin_version"
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}
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kotlin {
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experimental {
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coroutines "enable"
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}
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}
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@ -1,38 +0,0 @@
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package scientifik.kmath.structures
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import scientifik.kmath.operations.Field
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/**
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* Create a platform-optimized NDArray of doubles
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*/
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expect fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double = { 0.0 }): NDArray<Double>
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fun real2DArray(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }): NDArray<Double> {
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return realNDArray(listOf(dim1, dim2)) { initializer(it[0], it[1]) }
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}
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fun real3DArray(dim1: Int, dim2: Int, dim3: Int, initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }): NDArray<Double> {
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return realNDArray(listOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
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}
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class SimpleNDField<T: Any>(field: Field<T>, shape: List<Int>) : BufferNDField<T>(shape, field) {
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override fun createBuffer(capacity: Int, initializer: (Int) -> T): Buffer<T> {
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val array = ArrayList<T>(capacity)
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(0 until capacity).forEach {
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array.add(initializer(it))
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}
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return object : Buffer<T> {
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override fun get(index: Int): T = array[index]
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override fun set(index: Int, value: T) {
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array[index] = initializer(index)
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}
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}
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}
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}
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fun <T: Any> simpleNDArray(field: Field<T>, shape: List<Int>, initializer: (List<Int>) -> T): NDArray<T> {
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return SimpleNDField(field, shape).produce { initializer(it) }
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}
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58
kmath-core/build.gradle
Normal file
58
kmath-core/build.gradle
Normal file
@ -0,0 +1,58 @@
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plugins {
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id 'kotlin-multiplatform'// version '1.3.0-rc-116'
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id "me.champeau.gradle.jmh" version "0.4.5"
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}
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repositories {
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maven { url = 'http://dl.bintray.com/kotlin/kotlin-eap' }
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mavenCentral()
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}
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kotlin {
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targets {
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fromPreset(presets.jvm, 'jvm')
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fromPreset(presets.js, 'js')
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// For ARM, preset should be changed to presets.iosArm32 or presets.iosArm64
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// For Linux, preset should be changed to e.g. presets.linuxX64
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// For MacOS, preset should be changed to e.g. presets.macosX64
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//fromPreset(presets.mingwX64, 'mingw')
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}
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sourceSets {
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commonMain {
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dependencies {
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implementation 'org.jetbrains.kotlin:kotlin-stdlib-common'
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}
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}
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commonTest {
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dependencies {
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implementation 'org.jetbrains.kotlin:kotlin-test-common'
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implementation 'org.jetbrains.kotlin:kotlin-test-annotations-common'
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}
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}
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jvmMain {
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dependencies {
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implementation 'org.jetbrains.kotlin:kotlin-stdlib-jdk8'
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}
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}
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jvmTest {
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dependencies {
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implementation 'org.jetbrains.kotlin:kotlin-test'
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implementation 'org.jetbrains.kotlin:kotlin-test-junit'
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}
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}
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jsMain {
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dependencies {
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implementation 'org.jetbrains.kotlin:kotlin-stdlib-js'
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}
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}
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jsTest {
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dependencies {
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implementation 'org.jetbrains.kotlin:kotlin-test-js'
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}
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}
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// mingwMain {
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// }
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// mingwTest {
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// }
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}
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}
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@ -1,8 +1,5 @@
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package scientifik.kmath.misc
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import kotlin.coroutines.experimental.buildSequence
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/**
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* Convert double range to sequence.
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*
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@ -14,14 +11,14 @@ import kotlin.coroutines.experimental.buildSequence
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fun ClosedFloatingPointRange<Double>.toSequence(step: Double): Sequence<Double> {
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return when {
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step == 0.0 -> error("Zero step in double progression")
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step > 0 -> buildSequence {
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step > 0 -> sequence {
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var current = start
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while (current <= endInclusive) {
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yield(current)
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current += step
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}
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}
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else -> buildSequence {
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else -> sequence {
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var current = endInclusive
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while (current >= start) {
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yield(current)
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@ -1,7 +1,6 @@
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package scientifik.kmath.structures
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import scientifik.kmath.operations.Field
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import kotlin.coroutines.experimental.buildSequence
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/**
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@ -42,7 +41,7 @@ abstract class BufferNDField<T>(shape: List<Int>, field: Field<T>) : NDField<T>(
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//TODO introduce a fast way to calculate index of the next element?
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protected fun index(offset: Int): List<Int> {
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return buildSequence {
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return sequence {
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var current = offset
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var strideIndex = strides.size - 2
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while (strideIndex >= 0) {
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@ -4,6 +4,7 @@ import scientifik.kmath.operations.DoubleField
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import scientifik.kmath.operations.Field
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import scientifik.kmath.operations.Space
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import scientifik.kmath.operations.SpaceElement
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import scientifik.kmath.structures.NDArrays.createSimpleNDFieldFactory
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/**
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* The space for linear elements. Supports scalar product alongside with standard linear operations.
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@ -18,7 +19,7 @@ abstract class LinearSpace<T : Any, V : LinearStructure<out T>>(val rows: Int, v
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abstract fun produce(initializer: (Int, Int) -> T): V
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/**
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* Produce new linear space with given dimensions
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* Produce new linear space with given dimensions. The space produced could be raised from cache since [LinearSpace] does not have mutable elements
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*/
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abstract fun produceSpace(rows: Int, columns: Int): LinearSpace<T, V>
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@ -36,12 +37,12 @@ abstract class LinearSpace<T : Any, V : LinearStructure<out T>>(val rows: Int, v
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}
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/**
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* Dot product
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* Dot product. Throws exception on dimension mismatch
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*/
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fun multiply(a: V, b: V): V {
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if (a.rows != b.columns) {
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//TODO replace by specific exception
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error("Dimension mismatch in vector dot product")
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error("Dimension mismatch in linear structure dot product: [${a.rows},${a.columns}]*[${b.rows},${b.columns}]")
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}
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return produceSpace(a.rows, b.columns).produce { i, j ->
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(0..a.columns).asSequence().map { k -> field.multiply(a[i, k], b[k, j]) }.reduce { first, second -> field.add(first, second) }
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@ -55,16 +56,25 @@ abstract class LinearSpace<T : Any, V : LinearStructure<out T>>(val rows: Int, v
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* A matrix-like structure that is not dependent on specific space implementation
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*/
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interface LinearStructure<T : Any> {
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/**
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* Number of rows
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*/
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val rows: Int
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/**
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* Number of columns
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*/
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val columns: Int
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/**
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* Get element in row [i] and column [j]. Throws error in case of call ounside structure dimensions
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*/
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operator fun get(i: Int, j: Int): T
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fun transpose(): LinearStructure<T> {
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return object : LinearStructure<T> {
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override val rows: Int = this@LinearStructure.columns
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override val columns: Int = this@LinearStructure.rows
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override fun get(i: Int, j: Int): T = this@LinearStructure.get(j, i)
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override fun get(i: Int, j: Int): T = this@LinearStructure[j, i]
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}
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}
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}
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@ -78,15 +88,23 @@ interface Vector<T : Any> : LinearStructure<T> {
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/**
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* DoubleArray-based implementation of vector space
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* NDArray-based implementation of vector space. By default uses slow [SimpleNDField], but could be overridden with custom [NDField] factory.
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*/
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class ArraySpace<T : Any>(rows: Int, columns: Int, field: Field<T>) : LinearSpace<T, LinearStructure<out T>>(rows, columns, field) {
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class ArraySpace<T : Any>(
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rows: Int,
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columns: Int,
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field: Field<T>,
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val ndFactory: NDFieldFactory<T> = createSimpleNDFieldFactory(field)
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) : LinearSpace<T, LinearStructure<out T>>(rows, columns, field) {
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val ndField by lazy {
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ndFactory(listOf(rows, columns))
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}
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override fun produce(initializer: (Int, Int) -> T): LinearStructure<T> = ArrayMatrix<T>(this, initializer)
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override fun produceSpace(rows: Int, columns: Int): LinearSpace<T, LinearStructure<out T>> {
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return ArraySpace(rows, columns, field)
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return ArraySpace(rows, columns, field, ndFactory)
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}
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}
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@ -95,14 +113,16 @@ class ArraySpace<T : Any>(rows: Int, columns: Int, field: Field<T>) : LinearSpac
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*/
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class ArrayMatrix<T : Any>(override val context: ArraySpace<T>, initializer: (Int, Int) -> T) : LinearStructure<T>, SpaceElement<LinearStructure<out T>, ArraySpace<T>> {
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val list: List<List<T>> = (0 until rows).map { i -> (0 until columns).map { j -> initializer(i, j) } }
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private val array = context.ndField.produce { list -> initializer(list[0], list[1]) }
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//val list: List<List<T>> = (0 until rows).map { i -> (0 until columns).map { j -> initializer(i, j) } }
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override val rows: Int get() = context.rows
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override val columns: Int get() = context.columns
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override fun get(i: Int, j: Int): T {
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return list[i][j]
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return array[i, j]
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}
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override val self: ArrayMatrix<T> get() = this
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@ -117,7 +137,7 @@ class ArrayVector<T : Any>(override val context: ArraySpace<T>, initializer: (In
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}
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}
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val list: List<T> = (0 until context.rows).map(initializer)
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private val array = context.ndField.produce { list -> initializer(list[0]) }
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override val rows: Int get() = context.rows
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@ -125,20 +145,25 @@ class ArrayVector<T : Any>(override val context: ArraySpace<T>, initializer: (In
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override val columns: Int = 1
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override fun get(i: Int, j: Int): T {
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return list[i]
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return array[i]
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}
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override val self: ArrayVector<T> get() = this
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}
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fun <T : Any> vector(size: Int, field: Field<T>, initializer: (Int) -> T) = ArrayVector(ArraySpace(size, 1, field), initializer)
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//TODO replace by primitive array version
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fun realVector(size: Int, initializer: (Int) -> Double) = vector(size, DoubleField, initializer)
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fun <T : Any> vector(size: Int, field: Field<T>, initializer: (Int) -> T) =
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ArrayVector(ArraySpace(size, 1, field), initializer)
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fun realVector(size: Int, initializer: (Int) -> Double) =
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ArrayVector(ArraySpace(size, 1, DoubleField, realNDFieldFactory), initializer)
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fun <T : Any> Array<T>.asVector(field: Field<T>) = vector(size, field) { this[it] }
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//TODO add inferred field from field element
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fun DoubleArray.asVector() = realVector(this.size) { this[it] }
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fun <T : Any> matrix(rows: Int, columns: Int, field: Field<T>, initializer: (Int, Int) -> T) = ArrayMatrix<T>(ArraySpace(rows, columns, field), initializer)
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fun realMatrix(rows: Int, columns: Int, initializer: (Int, Int) -> Double) = matrix(rows, columns, DoubleField, initializer)
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fun <T : Any> matrix(rows: Int, columns: Int, field: Field<T>, initializer: (Int, Int) -> T) =
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ArrayMatrix(ArraySpace(rows, columns, field), initializer)
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fun realMatrix(rows: Int, columns: Int, initializer: (Int, Int) -> Double) =
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ArrayMatrix(ArraySpace(rows, columns, DoubleField, realNDFieldFactory), initializer)
|
@ -136,7 +136,7 @@ operator fun <T> Function1<T, T>.invoke(ndArray: NDArray<T>): NDArray<T> = ndArr
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* Summation operation for [NDArray] and single element
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*/
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operator fun <T> NDArray<T>.plus(arg: T): NDArray<T> = transform { _, value ->
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with(context.field){
|
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with(context.field) {
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arg + value
|
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}
|
||||
}
|
||||
@ -150,7 +150,7 @@ operator fun <T> T.plus(arg: NDArray<T>): NDArray<T> = arg + this
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* Subtraction operation between [NDArray] and single element
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*/
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operator fun <T> NDArray<T>.minus(arg: T): NDArray<T> = transform { _, value ->
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with(context.field){
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with(context.field) {
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arg - value
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}
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}
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@ -159,7 +159,7 @@ operator fun <T> NDArray<T>.minus(arg: T): NDArray<T> = transform { _, value ->
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* Reverse minus operation
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*/
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operator fun <T> T.minus(arg: NDArray<T>): NDArray<T> = arg.transform { _, value ->
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with(arg.context.field){
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with(arg.context.field) {
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this@minus - value
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}
|
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}
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@ -170,7 +170,7 @@ operator fun <T> T.minus(arg: NDArray<T>): NDArray<T> = arg.transform { _, value
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* Product operation for [NDArray] and single element
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*/
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operator fun <T> NDArray<T>.times(arg: T): NDArray<T> = transform { _, value ->
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with(context.field){
|
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with(context.field) {
|
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arg * value
|
||||
}
|
||||
}
|
||||
@ -184,7 +184,7 @@ operator fun <T> T.times(arg: NDArray<T>): NDArray<T> = arg * this
|
||||
* Division operation between [NDArray] and single element
|
||||
*/
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||||
operator fun <T> NDArray<T>.div(arg: T): NDArray<T> = transform { _, value ->
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||||
with(context.field){
|
||||
with(context.field) {
|
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arg / value
|
||||
}
|
||||
}
|
||||
@ -193,8 +193,8 @@ operator fun <T> NDArray<T>.div(arg: T): NDArray<T> = transform { _, value ->
|
||||
* Reverse division operation
|
||||
*/
|
||||
operator fun <T> T.div(arg: NDArray<T>): NDArray<T> = arg.transform { _, value ->
|
||||
with(arg.context.field){
|
||||
this@div/ value
|
||||
with(arg.context.field) {
|
||||
this@div / value
|
||||
}
|
||||
}
|
||||
|
@ -0,0 +1,54 @@
|
||||
package scientifik.kmath.structures
|
||||
|
||||
import scientifik.kmath.operations.Field
|
||||
|
||||
typealias NDFieldFactory<T> = (shape: List<Int>) -> NDField<T>
|
||||
|
||||
/**
|
||||
* The factory class for fast platform-dependent implementation of NDField of doubles
|
||||
*/
|
||||
expect val realNDFieldFactory: NDFieldFactory<Double>
|
||||
|
||||
object NDArrays {
|
||||
/**
|
||||
* Create a platform-optimized NDArray of doubles
|
||||
*/
|
||||
fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double = { 0.0 }): NDArray<Double> {
|
||||
return realNDFieldFactory(shape).produce(initializer)
|
||||
}
|
||||
|
||||
fun real1DArray(dim: Int, initializer: (Int) -> Double = { _ -> 0.0 }): NDArray<Double> {
|
||||
return realNDArray(listOf(dim)) { initializer(it[0]) }
|
||||
}
|
||||
|
||||
fun real2DArray(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }): NDArray<Double> {
|
||||
return realNDArray(listOf(dim1, dim2)) { initializer(it[0], it[1]) }
|
||||
}
|
||||
|
||||
fun real3DArray(dim1: Int, dim2: Int, dim3: Int, initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }): NDArray<Double> {
|
||||
return realNDArray(listOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
|
||||
}
|
||||
|
||||
class SimpleNDField<T : Any>(field: Field<T>, shape: List<Int>) : BufferNDField<T>(shape, field) {
|
||||
override fun createBuffer(capacity: Int, initializer: (Int) -> T): Buffer<T> {
|
||||
val array = ArrayList<T>(capacity)
|
||||
(0 until capacity).forEach {
|
||||
array.add(initializer(it))
|
||||
}
|
||||
|
||||
return object : Buffer<T> {
|
||||
override fun get(index: Int): T = array[index]
|
||||
|
||||
override fun set(index: Int, value: T) {
|
||||
array[index] = initializer(index)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fun <T : Any> createSimpleNDFieldFactory(field: Field<T>): NDFieldFactory<T> = { list -> SimpleNDField(field, list) }
|
||||
|
||||
fun <T : Any> simpleNDArray(field: Field<T>, shape: List<Int>, initializer: (List<Int>) -> T): NDArray<T> {
|
||||
return SimpleNDField(field, shape).produce { initializer(it) }
|
||||
}
|
||||
}
|
@ -1,7 +1,7 @@
|
||||
package scientifik.kmath.structures
|
||||
|
||||
import org.junit.Assert.assertEquals
|
||||
import org.junit.Test
|
||||
import kotlin.test.Test
|
||||
import kotlin.test.assertEquals
|
||||
|
||||
class ArrayMatrixTest {
|
||||
|
||||
@ -10,7 +10,7 @@ class ArrayMatrixTest {
|
||||
val vector1 = realVector(5) { it.toDouble() }
|
||||
val vector2 = realVector(5) { 5 - it.toDouble() }
|
||||
val sum = vector1 + vector2
|
||||
assertEquals(5.0, sum[2, 0], 0.1)
|
||||
assertEquals(5.0, sum[2, 0])
|
||||
}
|
||||
|
||||
@Test
|
||||
@ -21,6 +21,6 @@ class ArrayMatrixTest {
|
||||
vector1 dot (vector2.transpose())
|
||||
}
|
||||
|
||||
assertEquals(10.0, product[1, 0], 0.1)
|
||||
assertEquals(10.0, product[1, 0])
|
||||
}
|
||||
}
|
@ -1,8 +1,9 @@
|
||||
package scientifik.kmath.structures
|
||||
|
||||
import org.junit.Assert.assertEquals
|
||||
import scientifik.kmath.structures.NDArrays.real2DArray
|
||||
import kotlin.math.pow
|
||||
import kotlin.test.Test
|
||||
import kotlin.test.assertEquals
|
||||
|
||||
class RealNDFieldTest {
|
||||
val array1 = real2DArray(3, 3) { i, j -> (i + j).toDouble() }
|
||||
@ -11,13 +12,13 @@ class RealNDFieldTest {
|
||||
@Test
|
||||
fun testSum() {
|
||||
val sum = array1 + array2
|
||||
assertEquals(4.0, sum[2, 2], 0.1)
|
||||
assertEquals(4.0, sum[2, 2])
|
||||
}
|
||||
|
||||
@Test
|
||||
fun testProduct() {
|
||||
val product = array1 * array2
|
||||
assertEquals(0.0, product[2, 2], 0.1)
|
||||
assertEquals(0.0, product[2, 2])
|
||||
}
|
||||
|
||||
@Test
|
||||
@ -28,7 +29,7 @@ class RealNDFieldTest {
|
||||
for (i in 0..2) {
|
||||
for (j in 0..2) {
|
||||
val expected = (i * 10 + j).toDouble()
|
||||
assertEquals("Error at index [$i, $j]", expected, array[i, j], 0.1)
|
||||
assertEquals(expected, array[i, j],"Error at index [$i, $j]")
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -37,6 +38,6 @@ class RealNDFieldTest {
|
||||
fun testExternalFunction() {
|
||||
val function: (Double) -> Double = { x -> x.pow(2) + 2 * x + 1 }
|
||||
val result = function(array1) + 1.0
|
||||
assertEquals(10.0, result[1,1],0.01)
|
||||
assertEquals(10.0, result[1,1])
|
||||
}
|
||||
}
|
@ -1,6 +1,7 @@
|
||||
package scientifik.kmath.structures
|
||||
|
||||
import scientifik.kmath.operations.DoubleField
|
||||
import scientifik.kmath.structures.NDArrays.simpleNDArray
|
||||
import kotlin.test.Test
|
||||
import kotlin.test.assertEquals
|
||||
|
@ -0,0 +1,8 @@
|
||||
package scientifik.kmath.structures
|
||||
|
||||
import scientifik.kmath.operations.DoubleField
|
||||
|
||||
/**
|
||||
* Using boxing implementation for js
|
||||
*/
|
||||
actual val realNDFieldFactory: NDFieldFactory<Double> = NDArrays.createSimpleNDFieldFactory(DoubleField)
|
@ -17,8 +17,4 @@ private class RealNDField(shape: List<Int>) : BufferNDField<Double>(shape, Doubl
|
||||
}
|
||||
}
|
||||
|
||||
actual fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double): NDArray<Double> {
|
||||
//TODO create a cache for fields to save time generating strides?
|
||||
|
||||
return RealNDField(shape).produce { initializer(it) }
|
||||
}
|
||||
actual val realNDFieldFactory: NDFieldFactory<Double> = { shape -> RealNDField(shape) }
|
@ -1,38 +0,0 @@
|
||||
plugins{
|
||||
id "kotlin-platform-jvm"
|
||||
id "me.champeau.gradle.jmh" version "0.4.5"
|
||||
}
|
||||
|
||||
repositories {
|
||||
mavenCentral()
|
||||
}
|
||||
|
||||
dependencies {
|
||||
expectedBy project(":kmath-common")
|
||||
compile "org.jetbrains.kotlin:kotlin-stdlib-jdk8:$kotlin_version"
|
||||
testCompile "junit:junit:4.12"
|
||||
testCompile "org.jetbrains.kotlin:kotlin-test-junit:$kotlin_version"
|
||||
testCompile "org.jetbrains.kotlin:kotlin-test:$kotlin_version"
|
||||
}
|
||||
|
||||
compileKotlin {
|
||||
kotlinOptions.jvmTarget = "1.8"
|
||||
}
|
||||
compileTestKotlin {
|
||||
kotlinOptions.jvmTarget = "1.8"
|
||||
}
|
||||
sourceCompatibility = "1.8"
|
||||
|
||||
kotlin {
|
||||
experimental {
|
||||
coroutines "enable"
|
||||
}
|
||||
}
|
||||
|
||||
publishing {
|
||||
publications {
|
||||
defaultPublication(MavenPublication) {
|
||||
from components.java
|
||||
}
|
||||
}
|
||||
}
|
@ -1,4 +1,13 @@
|
||||
rootProject.name = 'kmath'
|
||||
include 'kmath-common'
|
||||
include 'kmath-jvm'
|
||||
pluginManagement {
|
||||
repositories {
|
||||
maven { url = 'http://dl.bintray.com/kotlin/kotlin-eap' }
|
||||
mavenCentral()
|
||||
maven { url = 'https://plugins.gradle.org/m2/' }
|
||||
}
|
||||
}
|
||||
|
||||
enableFeaturePreview('GRADLE_METADATA')
|
||||
|
||||
rootProject.name = 'kmath'
|
||||
include ':kmath-core'
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user