[orx-gradient-descent] convert to MPP
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96
orx-gradient-descent/build.gradle.kts
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96
orx-gradient-descent/build.gradle.kts
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@@ -0,0 +1,96 @@
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import Orx_embed_shaders_gradle.EmbedShadersTask
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plugins {
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kotlin("multiplatform")
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kotlin("plugin.serialization")
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id("orx.embed-shaders")
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}
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val kotlinxSerializationVersion: String by rootProject.extra
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val kotestVersion: String by rootProject.extra
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val junitJupiterVersion: String by rootProject.extra
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val jvmTarget: String by rootProject.extra
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val kotlinApiVersion: String by rootProject.extra
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val kotlinVersion: String by rootProject.extra
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val kotlinLoggingVersion: String by rootProject.extra
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val kluentVersion: String by rootProject.extra
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val openrndrVersion: String by rootProject.extra
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val openrndrOS: String by rootProject.extra
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val spekVersion: String by rootProject.extra
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kotlin {
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jvm {
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compilations {
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val demo by creating {
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defaultSourceSet {
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kotlin.srcDir("src/demo")
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dependencies {
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implementation(project(":orx-camera"))
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implementation("org.openrndr:openrndr-application:$openrndrVersion")
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implementation("org.openrndr:openrndr-extensions:$openrndrVersion")
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runtimeOnly("org.openrndr:openrndr-gl3:$openrndrVersion")
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runtimeOnly("org.openrndr:openrndr-gl3-natives-$openrndrOS:$openrndrVersion")
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implementation(compilations["main"]!!.output.allOutputs)
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}
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}
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}
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}
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compilations.all {
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kotlinOptions.jvmTarget = jvmTarget
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kotlinOptions.apiVersion = kotlinApiVersion
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}
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testRuns["test"].executionTask.configure {
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useJUnitPlatform()
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}
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}
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js(IR) {
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browser()
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nodejs()
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}
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sourceSets {
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@Suppress("UNUSED_VARIABLE")
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val commonMain by getting {
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dependencies {
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implementation(project(":orx-parameters"))
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implementation(project(":orx-shader-phrases"))
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implementation("org.jetbrains.kotlinx:kotlinx-serialization-core:$kotlinxSerializationVersion")
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implementation("org.openrndr:openrndr-application:$openrndrVersion")
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implementation("org.openrndr:openrndr-draw:$openrndrVersion")
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implementation("org.openrndr:openrndr-filter:$openrndrVersion")
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implementation("org.jetbrains.kotlin:kotlin-reflect:$kotlinVersion")
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implementation("io.github.microutils:kotlin-logging:$kotlinLoggingVersion")
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}
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}
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@Suppress("UNUSED_VARIABLE")
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val commonTest by getting {
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dependencies {
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implementation(kotlin("test-common"))
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implementation(kotlin("test-annotations-common"))
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implementation("org.jetbrains.kotlinx:kotlinx-serialization-json:$kotlinxSerializationVersion")
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implementation("io.kotest:kotest-assertions-core:$kotestVersion")
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}
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}
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@Suppress("UNUSED_VARIABLE")
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val jvmTest by getting {
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dependencies {
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implementation(kotlin("test-common"))
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implementation(kotlin("test-annotations-common"))
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implementation(kotlin("test-junit5"))
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implementation("org.jetbrains.kotlinx:kotlinx-serialization-json:$kotlinxSerializationVersion")
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runtimeOnly("org.junit.jupiter:junit-jupiter-api:$junitJupiterVersion")
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runtimeOnly("org.junit.jupiter:junit-jupiter-engine:$junitJupiterVersion")
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implementation("org.spekframework.spek2:spek-dsl-jvm:$spekVersion")
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implementation("org.amshove.kluent:kluent:$kluentVersion")
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}
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}
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@Suppress("UNUSED_VARIABLE")
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val jsTest by getting {
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dependencies {
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implementation(kotlin("test-js"))
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}
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}
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}
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}
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@@ -175,12 +175,3 @@ fun minimize(_x0: DoubleArray,
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return MinimizationResult(x0, f0, g0, H1, iteration)
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}
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fun <T : Any> minimizeModel(model: T, endOnLineSearch: Boolean = false, tol: Double = 1e-8, maxIterations: Int = 1000, function: (T) -> Double) {
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val doubles = modelToArray(model)
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val weights = DoubleArray(doubles.size) { 1.0 }
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val solution = minimize(doubles, weights, endOnLineSearch, tol, maxIterations) {
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arrayToModel(it, model)
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function(model)
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}
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arrayToModel(solution.solution, model)
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}
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12
orx-gradient-descent/src/jvmMain/kotlin/GradientDescent.kt
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12
orx-gradient-descent/src/jvmMain/kotlin/GradientDescent.kt
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@@ -0,0 +1,12 @@
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@file:JvmName("GradientDescentJvmKt")
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package org.openrndr.extra.gradientdescent
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fun <T : Any> minimizeModel(model: T, endOnLineSearch: Boolean = false, tol: Double = 1e-8, maxIterations: Int = 1000, function: (T) -> Double) {
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val doubles = modelToArray(model)
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val weights = DoubleArray(doubles.size) { 1.0 }
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val solution = minimize(doubles, weights, endOnLineSearch, tol, maxIterations) {
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arrayToModel(it, model)
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function(model)
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}
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arrayToModel(solution.solution, model)
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}
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