forked from kscience/kmath
Minor refactoring + domains
This commit is contained in:
parent
71846a3279
commit
668d13c9d1
@ -2,7 +2,7 @@ plugins {
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id("scientifik.publish") apply false
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}
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val kmathVersion by extra("0.1.4-dev-7")
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val kmathVersion by extra("0.1.4-dev-8")
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val bintrayRepo by extra("scientifik")
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val githubProject by extra("kmath")
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@ -4,8 +4,8 @@ import org.jetbrains.kotlin.gradle.tasks.KotlinCompile
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plugins {
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java
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kotlin("jvm")
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kotlin("plugin.allopen") version "1.3.71"
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id("kotlinx.benchmark") version "0.2.0-dev-7"
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kotlin("plugin.allopen") version "1.3.72"
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id("kotlinx.benchmark") version "0.2.0-dev-8"
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}
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configure<AllOpenExtension> {
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@ -33,8 +33,8 @@ dependencies {
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implementation(project(":kmath-dimensions"))
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implementation("com.kyonifer:koma-core-ejml:0.12")
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implementation("org.jetbrains.kotlinx:kotlinx-io-jvm:0.2.0-npm-dev-6")
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implementation("org.jetbrains.kotlinx:kotlinx.benchmark.runtime:0.2.0-dev-7")
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"benchmarksCompile"(sourceSets.main.get().compileClasspath)
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implementation("org.jetbrains.kotlinx:kotlinx.benchmark.runtime:0.2.0-dev-8")
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"benchmarksCompile"(sourceSets.main.get().output + sourceSets.main.get().compileClasspath) //sourceSets.main.output + sourceSets.main.runtimeClasspath
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}
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// Configure benchmark
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@ -20,7 +20,7 @@ class ViktorBenchmark {
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final val viktorField = ViktorNDField(intArrayOf(dim, dim))
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@Benchmark
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fun `Automatic field addition`() {
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fun automaticFieldAddition() {
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autoField.run {
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var res = one
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repeat(n) {
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@ -30,7 +30,7 @@ class ViktorBenchmark {
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}
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@Benchmark
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fun `Viktor field addition`() {
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fun viktorFieldAddition() {
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viktorField.run {
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var res = one
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repeat(n) {
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@ -40,7 +40,7 @@ class ViktorBenchmark {
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}
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@Benchmark
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fun `Raw Viktor`() {
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fun rawViktor() {
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val one = F64Array.full(init = 1.0, shape = *intArrayOf(dim, dim))
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var res = one
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repeat(n) {
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@ -49,7 +49,7 @@ class ViktorBenchmark {
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}
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@Benchmark
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fun `Real field log`() {
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fun realdFieldLog() {
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realField.run {
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val fortyTwo = produce { 42.0 }
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var res = one
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@ -61,7 +61,7 @@ class ViktorBenchmark {
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}
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@Benchmark
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fun `Raw Viktor log`() {
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fun rawViktorLog() {
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val fortyTwo = F64Array.full(dim, dim, init = 42.0)
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var res: F64Array
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repeat(n) {
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@ -0,0 +1,38 @@
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package scientifik.kmath.commons.random
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import scientifik.kmath.prob.RandomGenerator
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class CMRandomGeneratorWrapper(val factory: (IntArray) -> RandomGenerator) :
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org.apache.commons.math3.random.RandomGenerator {
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private var generator = factory(intArrayOf())
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override fun nextBoolean(): Boolean = generator.nextBoolean()
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override fun nextFloat(): Float = generator.nextDouble().toFloat()
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override fun setSeed(seed: Int) {
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generator = factory(intArrayOf(seed))
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}
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override fun setSeed(seed: IntArray) {
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generator = factory(seed)
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}
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override fun setSeed(seed: Long) {
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setSeed(seed.toInt())
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}
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override fun nextBytes(bytes: ByteArray) {
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generator.fillBytes(bytes)
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}
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override fun nextInt(): Int = generator.nextInt()
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override fun nextInt(n: Int): Int = generator.nextInt(n)
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override fun nextGaussian(): Double = TODO()
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override fun nextDouble(): Double = generator.nextDouble()
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override fun nextLong(): Long = generator.nextLong()
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}
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@ -0,0 +1,15 @@
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package scientifik.kmath.domains
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import scientifik.kmath.linear.Point
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/**
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* A simple geometric domain
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*/
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interface Domain<T : Any> {
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operator fun contains(point: Point<T>): Boolean
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/**
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* Number of hyperspace dimensions
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*/
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val dimension: Int
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}
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@ -0,0 +1,67 @@
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/*
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* Copyright 2015 Alexander Nozik.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package scientifik.kmath.domains
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import scientifik.kmath.linear.Point
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import scientifik.kmath.structures.DoubleBuffer
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import scientifik.kmath.structures.indices
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/**
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*
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* HyperSquareDomain class.
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*
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* @author Alexander Nozik
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*/
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class HyperSquareDomain(private val lower: DoubleBuffer, private val upper: DoubleBuffer) : RealDomain {
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override operator fun contains(point: Point<Double>): Boolean = point.indices.all { i ->
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point[i] in lower[i]..upper[i]
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}
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override val dimension: Int get() = lower.size
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override fun getLowerBound(num: Int, point: Point<Double>): Double? = lower[num]
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override fun getLowerBound(num: Int): Double? = lower[num]
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override fun getUpperBound(num: Int, point: Point<Double>): Double? = upper[num]
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override fun getUpperBound(num: Int): Double? = upper[num]
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override fun nearestInDomain(point: Point<Double>): Point<Double> {
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val res: DoubleArray = DoubleArray(point.size) { i ->
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when {
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point[i] < lower[i] -> lower[i]
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point[i] > upper[i] -> upper[i]
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else -> point[i]
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}
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}
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return DoubleBuffer(*res)
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}
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override fun volume(): Double {
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var res = 1.0
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for (i in 0 until dimension) {
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if (lower[i].isInfinite() || upper[i].isInfinite()) {
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return Double.POSITIVE_INFINITY
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}
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if (upper[i] > lower[i]) {
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res *= upper[i] - lower[i]
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}
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}
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return res
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}
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}
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@ -0,0 +1,65 @@
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/*
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* Copyright 2015 Alexander Nozik.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package scientifik.kmath.domains
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import scientifik.kmath.linear.Point
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/**
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* n-dimensional volume
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*
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* @author Alexander Nozik
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*/
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interface RealDomain: Domain<Double> {
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fun nearestInDomain(point: Point<Double>): Point<Double>
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/**
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* The lower edge for the domain going down from point
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* @param num
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* @param point
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* @return
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*/
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fun getLowerBound(num: Int, point: Point<Double>): Double?
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/**
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* The upper edge of the domain going up from point
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* @param num
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* @param point
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* @return
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*/
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fun getUpperBound(num: Int, point: Point<Double>): Double?
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/**
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* Global lower edge
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* @param num
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* @return
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*/
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fun getLowerBound(num: Int): Double?
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/**
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* Global upper edge
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* @param num
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* @return
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*/
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fun getUpperBound(num: Int): Double?
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/**
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* Hyper volume
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* @return
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*/
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fun volume(): Double
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}
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@ -0,0 +1,36 @@
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/*
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* Copyright 2015 Alexander Nozik.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package scientifik.kmath.domains
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import scientifik.kmath.linear.Point
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class UnconstrainedDomain(override val dimension: Int) : RealDomain {
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override operator fun contains(point: Point<Double>): Boolean = true
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override fun getLowerBound(num: Int, point: Point<Double>): Double? = Double.NEGATIVE_INFINITY
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override fun getLowerBound(num: Int): Double? = Double.NEGATIVE_INFINITY
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override fun getUpperBound(num: Int, point: Point<Double>): Double? = Double.POSITIVE_INFINITY
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override fun getUpperBound(num: Int): Double? = Double.POSITIVE_INFINITY
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override fun nearestInDomain(point: Point<Double>): Point<Double> = point
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override fun volume(): Double = Double.POSITIVE_INFINITY
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}
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@ -0,0 +1,48 @@
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package scientifik.kmath.domains
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import scientifik.kmath.linear.Point
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import scientifik.kmath.structures.asBuffer
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inline class UnivariateDomain(val range: ClosedFloatingPointRange<Double>) : RealDomain {
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operator fun contains(d: Double): Boolean = range.contains(d)
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override operator fun contains(point: Point<Double>): Boolean {
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require(point.size == 0)
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return contains(point[0])
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}
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override fun nearestInDomain(point: Point<Double>): Point<Double> {
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require(point.size == 1)
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val value = point[0]
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return when{
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value in range -> point
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value >= range.endInclusive -> doubleArrayOf(range.endInclusive).asBuffer()
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else -> doubleArrayOf(range.start).asBuffer()
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}
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}
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override fun getLowerBound(num: Int, point: Point<Double>): Double? {
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require(num == 0)
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return range.start
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}
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override fun getUpperBound(num: Int, point: Point<Double>): Double? {
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require(num == 0)
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return range.endInclusive
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}
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override fun getLowerBound(num: Int): Double? {
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require(num == 0)
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return range.start
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}
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override fun getUpperBound(num: Int): Double? {
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require(num == 0)
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return range.endInclusive
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}
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override fun volume(): Double = range.endInclusive - range.start
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override val dimension: Int get() = 1
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}
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@ -12,26 +12,23 @@ import scientifik.kmath.structures.asBuffer
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import scientifik.kmath.structures.asIterable
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import kotlin.math.sqrt
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typealias RealPoint = Point<Double>
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fun DoubleArray.asVector() = RealVector(this.asBuffer())
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fun List<Double>.asVector() = RealVector(this.asBuffer())
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object VectorL2Norm : Norm<Point<out Number>, Double> {
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override fun norm(arg: Point<out Number>): Double = sqrt(arg.asIterable().sumByDouble { it.toDouble() })
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}
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inline class RealVector(private val point: Point<Double>) :
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SpaceElement<Point<Double>, RealVector, VectorSpace<Double, RealField>>, Point<Double> {
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SpaceElement<RealPoint, RealVector, VectorSpace<Double, RealField>>, RealPoint {
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override val context: VectorSpace<Double, RealField>
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get() = space(
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point.size
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)
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override val context: VectorSpace<Double, RealField> get() = space(point.size)
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override fun unwrap(): Point<Double> = point
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override fun unwrap(): RealPoint = point
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override fun Point<Double>.wrap(): RealVector =
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RealVector(this)
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override fun RealPoint.wrap(): RealVector = RealVector(this)
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override val size: Int get() = point.size
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@ -48,12 +45,8 @@ inline class RealVector(private val point: Point<Double>) :
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operator fun invoke(vararg values: Double): RealVector = values.asVector()
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fun space(dim: Int): BufferVectorSpace<Double, RealField> =
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spaceCache.getOrPut(dim) {
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BufferVectorSpace(
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dim,
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RealField
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) { size, init -> Buffer.real(size, init) }
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fun space(dim: Int): BufferVectorSpace<Double, RealField> = spaceCache.getOrPut(dim) {
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BufferVectorSpace(dim, RealField) { size, init -> Buffer.real(size, init) }
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}
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}
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}
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@ -27,6 +27,10 @@ typealias RealMatrix = Matrix<Double>
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fun realMatrix(rowNum: Int, colNum: Int, initializer: (i: Int, j: Int) -> Double): RealMatrix =
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MatrixContext.real.produce(rowNum, colNum, initializer)
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fun Array<DoubleArray>.toMatrix(): RealMatrix{
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return MatrixContext.real.produce(size, this[0].size) { row, col -> this[row][col] }
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}
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fun Sequence<DoubleArray>.toMatrix(): RealMatrix = toList().let {
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MatrixContext.real.produce(it.size, it[0].size) { row, col -> it[row][col] }
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}
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@ -1,18 +1,10 @@
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package scientifik.kmath.histogram
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import scientifik.kmath.domains.Domain
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import scientifik.kmath.linear.Point
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import scientifik.kmath.structures.ArrayBuffer
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import scientifik.kmath.structures.DoubleBuffer
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/**
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* A simple geometric domain
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* TODO move to geometry module
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*/
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interface Domain<T : Any> {
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operator fun contains(vector: Point<out T>): Boolean
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val dimension: Int
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}
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/**
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* The bin in the histogram. The histogram is by definition always done in the real space
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*/
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@ -10,6 +10,7 @@ interface MemorySpec<T : Any> {
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val objectSize: Int
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fun MemoryReader.read(offset: Int): T
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//TODO consider thread safety
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fun MemoryWriter.write(offset: Int, value: T)
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}
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Reference in New Issue
Block a user