kscience/kmath
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Implement kmath-nd4j: module that implements NDStructure for INDArray of ND4J #116

Merged
CommanderTvis merged 50 commits from nd4j into dev 2020-10-29 19:58:53 +03:00
Conversation 2 Commits 50 Files Changed 19 +4504 -4858
247 changed files with 4504 additions and 4858 deletions
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1
.space.kts Normal file
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@ -0,0 +1 @@
job("Build") { gradlew("openjdk:11", "build") }

10
CHANGELOG.md
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@ -2,17 +2,27 @@
## [Unreleased]
### Added
- `fun` annotation for SAM interfaces in library
- Explicit `public` visibility for all public APIs
- Better trigonometric and hyperbolic functions for `AutoDiffField` (https://github.com/mipt-npm/kmath/pull/140).
- ND4J support module submitting `NDStructure` and `NDAlgebra` over `INDArray`.
### Changed
- Package changed from `scientifik` to `kscience.kmath`.
- Gradle version: 6.6 -> 6.6.1
- Minor exceptions refactor (throwing `IllegalArgumentException` by argument checks instead of `IllegalStateException`)
- `Polynomial` secondary constructor made function.
### Deprecated
### Removed
- `kmath-koma` module because it doesn't support Kotlin 1.4.
### Fixed
- `symbol` method in `MstExtendedField` (https://github.com/mipt-npm/kmath/pull/140)
### Security
## [0.1.4]
### Added

11
README.md
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@ -3,7 +3,7 @@
![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg)
Bintray: [ ![Download](https://api.bintray.com/packages/mipt-npm/scientifik/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/scientifik/kmath-core/_latestVersion)
Bintray: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-core/_latestVersion)
Bintray-dev: [ ![Download](https://api.bintray.com/packages/mipt-npm/dev/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/dev/kmath-core/_latestVersion)
@ -54,9 +54,6 @@ can be used for a wide variety of purposes from high performance calculations to
library in Kotlin code and maybe rewrite some parts to better suit the Kotlin programming paradigm, however there is no fixed roadmap for that. Feel free
to submit a feature request if you want something to be done first.
* **Koma wrapper** [Koma](https://github.com/kyonifer/koma) is a well established numerics library in Kotlin, specifically linear algebra.
The plan is to have wrappers for koma implementations for compatibility with kmath API.
## Planned features
* **Messaging** A mathematical notation to support multi-language and multi-node communication for mathematical tasks.
@ -83,12 +80,12 @@ Release artifacts are accessible from bintray with following configuration (see
```kotlin
repositories{
maven("https://dl.bintray.com/mipt-npm/scientifik")
maven("https://dl.bintray.com/mipt-npm/kscience")
}
dependencies{
api("scientifik:kmath-core:${kmathVersion}")
//api("scientifik:kmath-core-jvm:${kmathVersion}") for jvm-specific version
api("kscience.kmath:kmath-core:${kmathVersion}")
//api("kscience.kmath:kmath-core-jvm:${kmathVersion}") for jvm-specific version
}
```

22
build.gradle.kts
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@ -1,13 +1,10 @@
import org.jetbrains.kotlin.gradle.dsl.KotlinProjectExtension
import scientifik.ScientifikPublishPlugin
plugins {
id("scientifik.publish") apply false
id("ru.mipt.npm.base")
id("org.jetbrains.changelog") version "0.4.0"
}
val kmathVersion by extra("0.1.4")
val bintrayRepo by extra("scientifik")
val kmathVersion by extra("0.2.0-dev-1")
val bintrayRepo by extra("kscience")
val githubProject by extra("kmath")
allprojects {
@ -20,17 +17,6 @@ allprojects {
group = "kscience.kmath"
version = kmathVersion
afterEvaluate {
extensions.findByType<KotlinProjectExtension>()?.run {
sourceSets.all {
languageSettings.useExperimentalAnnotation("kotlin.contracts.ExperimentalContracts")
}
}
}
}
subprojects {
if (name.startsWith("kmath"))
apply<ScientifikPublishPlugin>()
}
subprojects { if (name.startsWith("kmath")) apply(plugin = "ru.mipt.npm.publish") }

8
doc/algebra.md
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@ -5,7 +5,7 @@ operation, say `+`, one needs two objects of a type `T` and an algebra context,
say `Space<T>`. Next one needs to run the actual operation in the context:
```kotlin
import scientifik.kmath.operations.*
import kscience.kmath.operations.*
val a: T = ...
val b: T = ...
@ -47,7 +47,7 @@ but it also holds reference to the `ComplexField` singleton, which allows perfor
numbers without explicit involving the context like:
```kotlin
import scientifik.kmath.operations.*
import kscience.kmath.operations.*
// Using elements
val c1 = Complex(1.0, 1.0)
@ -82,7 +82,7 @@ operations in all performance-critical places. The performance of element operat
KMath submits both contexts and elements for builtin algebraic structures:
```kotlin
import scientifik.kmath.operations.*
import kscience.kmath.operations.*
val c1 = Complex(1.0, 2.0)
val c2 = ComplexField.i
@ -95,7 +95,7 @@ val c3 = ComplexField { c1 + c2 }
Also, `ComplexField` features special operations to mix complex and real numbers, for example:
```kotlin
import scientifik.kmath.operations.*
import kscience.kmath.operations.*
val c1 = Complex(1.0, 2.0)
val c2 = ComplexField { c1 - 1.0 } // Returns: Complex(re=0.0, im=2.0)

3
doc/features.md
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@ -12,6 +12,3 @@ api and multiple library back-ends.
* [Expressions](./expressions.md)
* Commons math integration
* Koma integration

47
examples/build.gradle.kts
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@ -1,58 +1,48 @@
import org.jetbrains.kotlin.allopen.gradle.AllOpenExtension
import org.jetbrains.kotlin.gradle.tasks.KotlinCompile
plugins {
java
kotlin("jvm")
kotlin("plugin.allopen") version "1.3.72"
id("kotlinx.benchmark") version "0.2.0-dev-8"
kotlin("plugin.allopen") version "1.4.20-dev-3898-14"
id("kotlinx.benchmark") version "0.2.0-dev-20"
}
configure<AllOpenExtension> {
annotation("org.openjdk.jmh.annotations.State")
}
allOpen.annotation("org.openjdk.jmh.annotations.State")
repositories {
maven("http://dl.bintray.com/kyonifer/maven")
maven("https://dl.bintray.com/mipt-npm/scientifik")
maven("https://dl.bintray.com/mipt-npm/kscience")
maven("https://dl.bintray.com/mipt-npm/dev")
maven("https://dl.bintray.com/kotlin/kotlin-dev/")
mavenCentral()
}
sourceSets {
register("benchmarks")
}
sourceSets.register("benchmarks")
dependencies {
implementation(project(":kmath-ast"))
// implementation(project(":kmath-ast"))
implementation(project(":kmath-core"))
implementation(project(":kmath-coroutines"))
implementation(project(":kmath-commons"))
implementation(project(":kmath-prob"))
implementation(project(":kmath-koma"))
implementation(project(":kmath-viktor"))
implementation(project(":kmath-dimensions"))
implementation("com.kyonifer:koma-core-ejml:0.12")
implementation("org.jetbrains.kotlinx:kotlinx-io-jvm:0.2.0-npm-dev-6")
implementation("org.jetbrains.kotlinx:kotlinx.benchmark.runtime:0.2.0-dev-8")
implementation("org.jetbrains.kotlinx:kotlinx.benchmark.runtime:0.2.0-dev-20")
"benchmarksCompile"(sourceSets.main.get().output + sourceSets.main.get().compileClasspath) //sourceSets.main.output + sourceSets.main.runtimeClasspath
}
// Configure benchmark
benchmark {
// Setup configurations
targets {
targets
// This one matches sourceSet name above
register("benchmarks")
}
.register("benchmarks")
configurations {
register("fast") {
warmups = 5 // number of warmup iterations
iterations = 3 // number of iterations
iterationTime = 500 // time in seconds per iteration
iterationTimeUnit = "ms" // time unity for iterationTime, default is seconds
}
configurations.register("fast") {
warmups = 5 // number of warmup iterations
iterations = 3 // number of iterations
iterationTime = 500 // time in seconds per iteration
iterationTimeUnit = "ms" // time unity for iterationTime, default is seconds
}
}
@ -63,9 +53,4 @@ kotlin.sourceSets.all {
}
}
tasks.withType<KotlinCompile> {
kotlinOptions {
jvmTarget = Scientifik.JVM_TARGET.toString()
freeCompilerArgs = freeCompilerArgs + "-Xopt-in=kotlin.RequiresOptIn"
}
}
tasks.withType<KotlinCompile> { kotlinOptions.jvmTarget = "11" }

39
examples/src/benchmarks/kotlin/kscience/kmath/structures/ArrayBenchmark.kt Normal file
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@ -0,0 +1,39 @@
package kscience.kmath.structures
import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import java.nio.IntBuffer
@State(Scope.Benchmark)
class ArrayBenchmark {
@Benchmark
fun benchmarkArrayRead() {
var res = 0
for (i in 1.._root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) res += _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.array[_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size - i]
}
@Benchmark
fun benchmarkBufferRead() {
var res = 0
for (i in 1.._root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) res += _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.arrayBuffer.get(
_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size - i)
}
@Benchmark
fun nativeBufferRead() {
var res = 0
for (i in 1.._root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) res += _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.nativeBuffer.get(
_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size - i)
}
companion object {
const val size: Int = 1000
val array: IntArray = IntArray(_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) { it }
val arrayBuffer: IntBuffer = IntBuffer.wrap(_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.array)
val nativeBuffer: IntBuffer = IntBuffer.allocate(_root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size).also {
for (i in 0 until _root_ide_package_.kscience.kmath.structures.ArrayBenchmark.Companion.size) it.put(i, i)
}
}
}

6
examples/src/benchmarks/kotlin/scientifik/kmath/structures/BufferBenchmark.kt → examples/src/benchmarks/kotlin/kscience/kmath/structures/BufferBenchmark.kt
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@ -1,10 +1,10 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import kscience.kmath.operations.Complex
import kscience.kmath.operations.complex
import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import scientifik.kmath.operations.Complex
import scientifik.kmath.operations.complex
@State(Scope.Benchmark)
class BufferBenchmark {

6
examples/src/benchmarks/kotlin/scientifik/kmath/structures/NDFieldBenchmark.kt → examples/src/benchmarks/kotlin/kscience/kmath/structures/NDFieldBenchmark.kt
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@ -1,10 +1,10 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import scientifik.kmath.operations.RealField
import scientifik.kmath.operations.invoke
@State(Scope.Benchmark)
class NDFieldBenchmark {

8
examples/src/benchmarks/kotlin/scientifik/kmath/structures/ViktorBenchmark.kt → examples/src/benchmarks/kotlin/kscience/kmath/structures/ViktorBenchmark.kt
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@ -1,12 +1,12 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
import kscience.kmath.viktor.ViktorNDField
import org.jetbrains.bio.viktor.F64Array
import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import scientifik.kmath.operations.RealField
import scientifik.kmath.operations.invoke
import scientifik.kmath.viktor.ViktorNDField
@State(Scope.Benchmark)
class ViktorBenchmark {

2
examples/src/benchmarks/kotlin/scientifik/kmath/utils/utils.kt → examples/src/benchmarks/kotlin/kscience/kmath/utils/utils.kt
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@ -1,4 +1,4 @@
package scientifik.kmath.utils
package kscience.kmath.utils
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract

48
examples/src/benchmarks/kotlin/scientifik/kmath/structures/ArrayBenchmark.kt
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@ -1,48 +0,0 @@
package scientifik.kmath.structures
import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import java.nio.IntBuffer
@State(Scope.Benchmark)
class ArrayBenchmark {
@Benchmark
fun benchmarkArrayRead() {
var res = 0
for (i in 1..size) {
res += array[size - i]
}
}
@Benchmark
fun benchmarkBufferRead() {
var res = 0
for (i in 1..size) {
res += arrayBuffer.get(size - i)
}
}
@Benchmark
fun nativeBufferRead() {
var res = 0
for (i in 1..size) {
res += nativeBuffer.get(size - i)
}
}
companion object {
val size = 1000
val array = IntArray(size) { it }
val arrayBuffer = IntBuffer.wrap(array)
val nativeBuffer = IntBuffer.allocate(size).also {
for (i in 0 until size) {
it.put(i, i)
}
}
}
}

70
examples/src/main/kotlin/kscience/kmath/ast/ExpressionsInterpretersBenchmark.kt Normal file
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@ -0,0 +1,70 @@
//package kscience.kmath.ast
//
//import kscience.kmath.asm.compile
//import kscience.kmath.expressions.Expression
//import kscience.kmath.expressions.expressionInField
//import kscience.kmath.expressions.invoke
//import kscience.kmath.operations.Field
//import kscience.kmath.operations.RealField
//import kotlin.random.Random
//import kotlin.system.measureTimeMillis
//
//class ExpressionsInterpretersBenchmark {
// private val algebra: Field<Double> = RealField
// fun functionalExpression() {
// val expr = algebra.expressionInField {
// variable("x") * const(2.0) + const(2.0) / variable("x") - const(16.0)
// }
//
// invokeAndSum(expr)
// }
//
// fun mstExpression() {
// val expr = algebra.mstInField {
// symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
// }
//
// invokeAndSum(expr)
// }
//
// fun asmExpression() {
// val expr = algebra.mstInField {
// symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
// }.compile()
//
// invokeAndSum(expr)
// }
//
// private fun invokeAndSum(expr: Expression<Double>) {
// val random = Random(0)
// var sum = 0.0
//
// repeat(1000000) {
// sum += expr("x" to random.nextDouble())
// }
//
// println(sum)
// }
//}
//
//fun main() {
// val benchmark = ExpressionsInterpretersBenchmark()
//
// val fe = measureTimeMillis {
// benchmark.functionalExpression()
// }
//
// println("fe=$fe")
//
// val mst = measureTimeMillis {
// benchmark.mstExpression()
// }
//
// println("mst=$mst")
//
// val asm = measureTimeMillis {
// benchmark.asmExpression()
// }
//
// println("asm=$asm")
//}

6
examples/src/main/kotlin/scientifik/kmath/commons/prob/DistributionBenchmark.kt → examples/src/main/kotlin/kscience/kmath/commons/prob/DistributionBenchmark.kt
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@ -1,12 +1,12 @@
package scientifik.kmath.commons.prob
package kscience.kmath.commons.prob
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.async
import kotlinx.coroutines.runBlocking
import kscience.kmath.chains.BlockingRealChain
import kscience.kmath.prob.*
import org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
import org.apache.commons.rng.simple.RandomSource
import scientifik.kmath.chains.BlockingRealChain
import scientifik.kmath.prob.*
import java.time.Duration
import java.time.Instant

12
examples/src/main/kotlin/scientifik/kmath/commons/prob/DistributionDemo.kt → examples/src/main/kotlin/kscience/kmath/commons/prob/DistributionDemo.kt
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@ -1,11 +1,11 @@
package scientifik.kmath.commons.prob
package kscience.kmath.commons.prob
import kotlinx.coroutines.runBlocking
import scientifik.kmath.chains.Chain
import scientifik.kmath.chains.collectWithState
import scientifik.kmath.prob.Distribution
import scientifik.kmath.prob.RandomGenerator
import scientifik.kmath.prob.normal
import kscience.kmath.chains.Chain
import kscience.kmath.chains.collectWithState
import kscience.kmath.prob.Distribution
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.normal
data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)

2
examples/src/main/kotlin/scientifik/kmath/operations/BigIntDemo.kt → examples/src/main/kotlin/kscience/kmath/operations/BigIntDemo.kt
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@ -1,4 +1,4 @@
package scientifik.kmath.operations
package kscience.kmath.operations
fun main() {
val res = BigIntField {

8
examples/src/main/kotlin/scientifik/kmath/operations/ComplexDemo.kt → examples/src/main/kotlin/kscience/kmath/operations/ComplexDemo.kt
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@ -1,8 +1,8 @@
package scientifik.kmath.operations
package kscience.kmath.operations
import scientifik.kmath.structures.NDElement
import scientifik.kmath.structures.NDField
import scientifik.kmath.structures.complex
import kscience.kmath.structures.NDElement
import kscience.kmath.structures.NDField
import kscience.kmath.structures.complex
fun main() {
val element = NDElement.complex(2, 2) { index: IntArray ->

10
examples/src/main/kotlin/scientifik/kmath/structures/ComplexND.kt → examples/src/main/kotlin/kscience/kmath/structures/ComplexND.kt
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@ -1,9 +1,9 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import scientifik.kmath.linear.transpose
import scientifik.kmath.operations.Complex
import scientifik.kmath.operations.ComplexField
import scientifik.kmath.operations.invoke
import kscience.kmath.linear.transpose
import kscience.kmath.operations.Complex
import kscience.kmath.operations.ComplexField
import kscience.kmath.operations.invoke
import kotlin.system.measureTimeMillis
fun main() {

6
examples/src/main/kotlin/scientifik/kmath/structures/NDField.kt → examples/src/main/kotlin/kscience/kmath/structures/NDField.kt
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@ -1,8 +1,8 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import kotlinx.coroutines.GlobalScope
import scientifik.kmath.operations.RealField
import scientifik.kmath.operations.invoke
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
import kotlin.system.measureTimeMillis

4
examples/src/main/kotlin/scientifik/kmath/structures/StructureReadBenchmark.kt → examples/src/main/kotlin/kscience/kmath/structures/StructureReadBenchmark.kt
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@ -1,8 +1,8 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import kotlin.system.measureTimeMillis
fun main(args: Array<String>) {
fun main() {
val n = 6000
val array = DoubleArray(n * n) { 1.0 }

6
examples/src/main/kotlin/scientifik/kmath/structures/StructureWriteBenchmark.kt → examples/src/main/kotlin/kscience/kmath/structures/StructureWriteBenchmark.kt
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@ -1,10 +1,8 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import kotlin.system.measureTimeMillis
fun main(args: Array<String>) {
fun main() {
val n = 6000
val structure = NDStructure.build(intArrayOf(n, n), Buffer.Companion::auto) { 1.0 }

12
examples/src/main/kotlin/scientifik/kmath/structures/typeSafeDimensions.kt → examples/src/main/kotlin/kscience/kmath/structures/typeSafeDimensions.kt
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@ -1,10 +1,10 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import scientifik.kmath.dimensions.D2
import scientifik.kmath.dimensions.D3
import scientifik.kmath.dimensions.DMatrixContext
import scientifik.kmath.dimensions.Dimension
import scientifik.kmath.operations.RealField
import kscience.kmath.dimensions.D2
import kscience.kmath.dimensions.D3
import kscience.kmath.dimensions.DMatrixContext
import kscience.kmath.dimensions.Dimension
import kscience.kmath.operations.RealField
fun DMatrixContext<Double, RealField>.simple() {
val m1 = produce<D2, D3> { i, j -> (i + j).toDouble() }

70
examples/src/main/kotlin/scientifik/kmath/ast/ExpressionsInterpretersBenchmark.kt
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@ -1,70 +0,0 @@
package scientifik.kmath.ast
import scientifik.kmath.asm.compile
import scientifik.kmath.expressions.Expression
import scientifik.kmath.expressions.expressionInField
import scientifik.kmath.expressions.invoke
import scientifik.kmath.operations.Field
import scientifik.kmath.operations.RealField
import kotlin.random.Random
import kotlin.system.measureTimeMillis
class ExpressionsInterpretersBenchmark {
private val algebra: Field<Double> = RealField
fun functionalExpression() {
val expr = algebra.expressionInField {
variable("x") * const(2.0) + const(2.0) / variable("x") - const(16.0)
}
invokeAndSum(expr)
}
fun mstExpression() {
val expr = algebra.mstInField {
symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
}
invokeAndSum(expr)
}
fun asmExpression() {
val expr = algebra.mstInField {
symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
}.compile()
invokeAndSum(expr)
}
private fun invokeAndSum(expr: Expression<Double>) {
val random = Random(0)
var sum = 0.0
repeat(1000000) {
sum += expr("x" to random.nextDouble())
}
println(sum)
}
}
fun main() {
val benchmark = ExpressionsInterpretersBenchmark()
val fe = measureTimeMillis {
benchmark.functionalExpression()
}
println("fe=$fe")
val mst = measureTimeMillis {
benchmark.mstExpression()
}
println("mst=$mst")
val asm = measureTimeMillis {
benchmark.asmExpression()
}
println("asm=$asm")
}

53
examples/src/main/kotlin/scientifik/kmath/linear/LinearAlgebraBenchmark.kt
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@ -1,53 +0,0 @@
package scientifik.kmath.linear
import koma.matrix.ejml.EJMLMatrixFactory
import scientifik.kmath.commons.linear.CMMatrixContext
import scientifik.kmath.commons.linear.inverse
import scientifik.kmath.commons.linear.toCM
import scientifik.kmath.operations.RealField
import scientifik.kmath.operations.invoke
import scientifik.kmath.structures.Matrix
import kotlin.random.Random
import kotlin.system.measureTimeMillis
fun main() {
val random = Random(1224)
val dim = 100
//creating invertible matrix
val u = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val l = Matrix.real(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
val matrix = l dot u
val n = 5000 // iterations
MatrixContext.real {
repeat(50) { val res = inverse(matrix) }
val inverseTime = measureTimeMillis { repeat(n) { val res = inverse(matrix) } }
println("[kmath] Inversion of $n matrices $dim x $dim finished in $inverseTime millis")
}
//commons-math
val commonsTime = measureTimeMillis {
CMMatrixContext {
val cm = matrix.toCM() //avoid overhead on conversion
repeat(n) { val res = inverse(cm) }
}
}
println("[commons-math] Inversion of $n matrices $dim x $dim finished in $commonsTime millis")
//koma-ejml
val komaTime = measureTimeMillis {
(KomaMatrixContext(EJMLMatrixFactory(), RealField)) {
val km = matrix.toKoma() //avoid overhead on conversion
repeat(n) {
val res = inverse(km)
}
}
}
println("[koma-ejml] Inversion of $n matrices $dim x $dim finished in $komaTime millis")
}

49
examples/src/main/kotlin/scientifik/kmath/linear/MultiplicationBenchmark.kt
View File

@ -1,49 +0,0 @@
package scientifik.kmath.linear
import koma.matrix.ejml.EJMLMatrixFactory
import scientifik.kmath.commons.linear.CMMatrixContext
import scientifik.kmath.commons.linear.toCM
import scientifik.kmath.operations.RealField
import scientifik.kmath.operations.invoke
import scientifik.kmath.structures.Matrix
import kotlin.random.Random
import kotlin.system.measureTimeMillis
fun main() {
val random = Random(12224)
val dim = 1000
//creating invertible matrix
val matrix1 = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val matrix2 = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
// //warmup
// matrix1 dot matrix2
CMMatrixContext {
val cmMatrix1 = matrix1.toCM()
val cmMatrix2 = matrix2.toCM()
val cmTime = measureTimeMillis {
cmMatrix1 dot cmMatrix2
}
println("CM implementation time: $cmTime")
}
(KomaMatrixContext(EJMLMatrixFactory(), RealField)) {
val komaMatrix1 = matrix1.toKoma()
val komaMatrix2 = matrix2.toKoma()
val komaTime = measureTimeMillis {
komaMatrix1 dot komaMatrix2
}
println("Koma-ejml implementation time: $komaTime")
}
val genericTime = measureTimeMillis {
val res = matrix1 dot matrix2
}
println("Generic implementation time: $genericTime")
}

BIN
gradle/wrapper/gradle-wrapper.jar vendored
View File

Binary file not shown.

2
gradle/wrapper/gradle-wrapper.properties vendored
View File

@ -1,5 +1,5 @@
distributionBase=GRADLE_USER_HOME
distributionPath=wrapper/dists
distributionUrl=https\://services.gradle.org/distributions/gradle-6.5.1-bin.zip
distributionUrl=https\://services.gradle.org/distributions/gradle-6.6.1-bin.zip
zipStoreBase=GRADLE_USER_HOME
zipStorePath=wrapper/dists

21
gradlew.bat vendored
View File

@ -40,7 +40,7 @@ if defined JAVA_HOME goto findJavaFromJavaHome
set JAVA_EXE=java.exe
%JAVA_EXE% -version >NUL 2>&1
if "%ERRORLEVEL%" == "0" goto init
if "%ERRORLEVEL%" == "0" goto execute
echo.
echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
@ -54,7 +54,7 @@ goto fail
set JAVA_HOME=%JAVA_HOME:"=%
set JAVA_EXE=%JAVA_HOME%/bin/java.exe
if exist "%JAVA_EXE%" goto init
if exist "%JAVA_EXE%" goto execute
echo.
echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
@ -64,21 +64,6 @@ echo location of your Java installation.
goto fail
:init
@rem Get command-line arguments, handling Windows variants
if not "%OS%" == "Windows_NT" goto win9xME_args
:win9xME_args
@rem Slurp the command line arguments.
set CMD_LINE_ARGS=
set _SKIP=2
:win9xME_args_slurp
if "x%~1" == "x" goto execute
set CMD_LINE_ARGS=%*
:execute
@rem Setup the command line
@ -86,7 +71,7 @@ set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
@rem Execute Gradle
"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %CMD_LINE_ARGS%
"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %*
:end
@rem End local scope for the variables with windows NT shell

18
kmath-ast/README.md
View File

@ -8,32 +8,32 @@ This subproject implements the following features:
- Evaluating expressions by traversing MST.
> #### Artifact:
> This module is distributed in the artifact `scientifik:kmath-ast:0.1.4-dev-8`.
> This module is distributed in the artifact `kscience.kmath:kmath-ast:0.1.4-dev-8`.
>
> **Gradle:**
>
> ```gradle
> repositories {
> maven { url 'https://dl.bintray.com/mipt-npm/scientifik' }
> maven { url 'https://dl.bintray.com/mipt-npm/kscience' }
> maven { url 'https://dl.bintray.com/mipt-npm/dev' }
> maven { url https://dl.bintray.com/hotkeytlt/maven' }
> }
>
> dependencies {
> implementation 'scientifik:kmath-ast:0.1.4-dev-8'
> implementation 'kscience.kmath:kmath-ast:0.1.4-dev-8'
> }
> ```
> **Gradle Kotlin DSL:**
>
> ```kotlin
> repositories {
> maven("https://dl.bintray.com/mipt-npm/scientifik")
> maven("https://dl.bintray.com/mipt-npm/kscience")
> maven("https://dl.bintray.com/mipt-npm/dev")
> maven("https://dl.bintray.com/hotkeytlt/maven")
> }
>
> dependencies {
> implementation("scientifik:kmath-ast:0.1.4-dev-8")
> implementation("kscience.kmath:kmath-ast:0.1.4-dev-8")
> }
> ```
>
@ -52,12 +52,12 @@ RealField.mstInField { symbol("x") + 2 }.compile()
… leads to generation of bytecode, which can be decompiled to the following Java class:
```java
package scientifik.kmath.asm.generated;
package kscience.kmath.asm.generated;
import java.util.Map;
import scientifik.kmath.asm.internal.MapIntrinsics;
import scientifik.kmath.expressions.Expression;
import scientifik.kmath.operations.RealField;
import kscience.kmath.asm.internal.MapIntrinsics;
import kscience.kmath.expressions.Expression;
import kscience.kmath.operations.RealField;
public final class AsmCompiledExpression_1073786867_0 implements Expression<Double> {
private final RealField algebra;

4
kmath-ast/build.gradle.kts
View File

@ -1,12 +1,11 @@
plugins {
id("scientifik.mpp")
id("ru.mipt.npm.mpp")
}
kotlin.sourceSets {
commonMain {
dependencies {
api(project(":kmath-core"))
implementation("com.github.h0tk3y.betterParse:better-parse:0.4.0")
}
}
@ -14,6 +13,7 @@ kotlin.sourceSets {
dependencies {
implementation("org.ow2.asm:asm:8.0.1")
implementation("org.ow2.asm:asm-commons:8.0.1")
implementation("com.github.h0tk3y.betterParse:better-parse:0.4.0")
implementation(kotlin("reflect"))
}
}

29
kmath-ast/src/commonMain/kotlin/scientifik/kmath/ast/MST.kt → kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MST.kt
View File

@ -1,26 +1,28 @@
package scientifik.kmath.ast
package kscience.kmath.ast
import scientifik.kmath.operations.Algebra
import scientifik.kmath.operations.NumericAlgebra
import scientifik.kmath.operations.RealField
import kscience.kmath.operations.Algebra
import kscience.kmath.operations.NumericAlgebra
import kscience.kmath.operations.RealField
/**
* A Mathematical Syntax Tree node for mathematical expressions.
*
* @author Alexander Nozik
*/
sealed class MST {
public sealed class MST {
/**
* A node containing raw string.
*
* @property value the value of this node.
*/
data class Symbolic(val value: String) : MST()
public data class Symbolic(val value: String) : MST()
/**
* A node containing a numeric value or scalar.
*
* @property value the value of this number.
*/
data class Numeric(val value: Number) : MST()
public data class Numeric(val value: Number) : MST()
/**
* A node containing an unary operation.
@ -28,9 +30,7 @@ sealed class MST {
* @property operation the identifier of operation.
* @property value the argument of this operation.
*/
data class Unary(val operation: String, val value: MST) : MST() {
companion object
}
public data class Unary(val operation: String, val value: MST) : MST()
/**
* A node containing binary operation.
@ -39,9 +39,7 @@ sealed class MST {
* @property left the left operand.
* @property right the right operand.
*/
data class Binary(val operation: String, val left: MST, val right: MST) : MST() {
companion object
}
public data class Binary(val operation: String, val left: MST, val right: MST) : MST()
}
// TODO add a function with named arguments
@ -52,8 +50,9 @@ sealed class MST {
* @receiver the algebra that provides operations.
* @param node the node to evaluate.
* @return the value of expression.
* @author Alexander Nozik
*/
fun <T> Algebra<T>.evaluate(node: MST): T = when (node) {
public fun <T> Algebra<T>.evaluate(node: MST): T = when (node) {
is MST.Numeric -> (this as? NumericAlgebra<T>)?.number(node.value)
?: error("Numeric nodes are not supported by $this")
is MST.Symbolic -> symbol(node.value)
@ -84,4 +83,4 @@ fun <T> Algebra<T>.evaluate(node: MST): T = when (node) {
* @param algebra the algebra that provides operations.
* @return the value of expression.
*/
fun <T> MST.interpret(algebra: Algebra<T>): T = algebra.evaluate(this)
public fun <T> MST.interpret(algebra: Algebra<T>): T = algebra.evaluate(this)

53
kmath-ast/src/commonMain/kotlin/scientifik/kmath/ast/MstAlgebra.kt → kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MstAlgebra.kt
View File

@ -1,11 +1,11 @@
package scientifik.kmath.ast
package kscience.kmath.ast
import scientifik.kmath.operations.*
import kscience.kmath.operations.*
/**
* [Algebra] over [MST] nodes.
*/
object MstAlgebra : NumericAlgebra<MST> {
public object MstAlgebra : NumericAlgebra<MST> {
override fun number(value: Number): MST = MST.Numeric(value)
override fun symbol(value: String): MST = MST.Symbolic(value)
@ -20,7 +20,7 @@ object MstAlgebra : NumericAlgebra<MST> {
/**
* [Space] over [MST] nodes.
*/
object MstSpace : Space<MST>, NumericAlgebra<MST> {
public object MstSpace : Space<MST>, NumericAlgebra<MST> {
override val zero: MST = number(0.0)
override fun number(value: Number): MST = MstAlgebra.number(value)
@ -37,8 +37,9 @@ object MstSpace : Space<MST>, NumericAlgebra<MST> {
/**
* [Ring] over [MST] nodes.
*/
object MstRing : Ring<MST>, NumericAlgebra<MST> {
override val zero: MST = number(0.0)
public object MstRing : Ring<MST>, NumericAlgebra<MST> {
override val zero: MST
get() = MstSpace.zero
override val one: MST = number(1.0)
override fun number(value: Number): MST = MstSpace.number(value)
@ -58,18 +59,21 @@ object MstRing : Ring<MST>, NumericAlgebra<MST> {
/**
* [Field] over [MST] nodes.
*/
object MstField : Field<MST> {
override val zero: MST = number(0.0)
override val one: MST = number(1.0)
public object MstField : Field<MST> {
public override val zero: MST
get() = MstRing.zero
override fun symbol(value: String): MST = MstRing.symbol(value)
override fun number(value: Number): MST = MstRing.number(value)
override fun add(a: MST, b: MST): MST = MstRing.add(a, b)
override fun multiply(a: MST, k: Number): MST = MstRing.multiply(a, k)
override fun multiply(a: MST, b: MST): MST = MstRing.multiply(a, b)
override fun divide(a: MST, b: MST): MST = binaryOperation(FieldOperations.DIV_OPERATION, a, b)
public override val one: MST
get() = MstRing.one
override fun binaryOperation(operation: String, left: MST, right: MST): MST =
public override fun symbol(value: String): MST = MstRing.symbol(value)
public override fun number(value: Number): MST = MstRing.number(value)
public override fun add(a: MST, b: MST): MST = MstRing.add(a, b)
public override fun multiply(a: MST, k: Number): MST = MstRing.multiply(a, k)
public override fun multiply(a: MST, b: MST): MST = MstRing.multiply(a, b)
public override fun divide(a: MST, b: MST): MST = binaryOperation(FieldOperations.DIV_OPERATION, a, b)
public override fun binaryOperation(operation: String, left: MST, right: MST): MST =
MstRing.binaryOperation(operation, left, right)
override fun unaryOperation(operation: String, arg: MST): MST = MstRing.unaryOperation(operation, arg)
@ -78,15 +82,26 @@ object MstField : Field<MST> {
/**
* [ExtendedField] over [MST] nodes.
*/
object MstExtendedField : ExtendedField<MST> {
override val zero: MST = number(0.0)
override val one: MST = number(1.0)
public object MstExtendedField : ExtendedField<MST> {
override val zero: MST
get() = MstField.zero
override val one: MST
get() = MstField.one
override fun symbol(value: String): MST = MstField.symbol(value)
override fun sin(arg: MST): MST = unaryOperation(TrigonometricOperations.SIN_OPERATION, arg)
override fun cos(arg: MST): MST = unaryOperation(TrigonometricOperations.COS_OPERATION, arg)
override fun tan(arg: MST): MST = unaryOperation(TrigonometricOperations.TAN_OPERATION, arg)
override fun asin(arg: MST): MST = unaryOperation(TrigonometricOperations.ASIN_OPERATION, arg)
override fun acos(arg: MST): MST = unaryOperation(TrigonometricOperations.ACOS_OPERATION, arg)
override fun atan(arg: MST): MST = unaryOperation(TrigonometricOperations.ATAN_OPERATION, arg)
override fun sinh(arg: MST): MST = unaryOperation(HyperbolicOperations.SINH_OPERATION, arg)
override fun cosh(arg: MST): MST = unaryOperation(HyperbolicOperations.COSH_OPERATION, arg)
override fun tanh(arg: MST): MST = unaryOperation(HyperbolicOperations.TANH_OPERATION, arg)
override fun asinh(arg: MST): MST = unaryOperation(HyperbolicOperations.ASINH_OPERATION, arg)
override fun acosh(arg: MST): MST = unaryOperation(HyperbolicOperations.ACOSH_OPERATION, arg)
override fun atanh(arg: MST): MST = unaryOperation(HyperbolicOperations.ATANH_OPERATION, arg)
override fun add(a: MST, b: MST): MST = MstField.add(a, b)
override fun multiply(a: MST, k: Number): MST = MstField.multiply(a, k)
override fun multiply(a: MST, b: MST): MST = MstField.multiply(a, b)

47
kmath-ast/src/commonMain/kotlin/scientifik/kmath/ast/MstExpression.kt → kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MstExpression.kt
View File

@ -1,7 +1,7 @@
package scientifik.kmath.ast
package kscience.kmath.ast
import scientifik.kmath.expressions.*
import scientifik.kmath.operations.*
import kscience.kmath.expressions.*
import kscience.kmath.operations.*
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@ -11,8 +11,9 @@ import kotlin.contracts.contract
*
* @property algebra the algebra that provides operations.
* @property mst the [MST] node.
* @author Alexander Nozik
*/
class MstExpression<T>(val algebra: Algebra<T>, val mst: MST) : Expression<T> {
public class MstExpression<T>(public val algebra: Algebra<T>, public val mst: MST) : Expression<T> {
private inner class InnerAlgebra(val arguments: Map<String, T>) : NumericAlgebra<T> {
override fun symbol(value: String): T = arguments[value] ?: algebra.symbol(value)
override fun unaryOperation(operation: String, arg: T): T = algebra.unaryOperation(operation, arg)
@ -31,72 +32,92 @@ class MstExpression<T>(val algebra: Algebra<T>, val mst: MST) : Expression<T> {
/**
* Builds [MstExpression] over [Algebra].
*
* @author Alexander Nozik
*/
inline fun <reified T : Any, A : Algebra<T>, E : Algebra<MST>> A.mst(
public inline fun <reified T : Any, A : Algebra<T>, E : Algebra<MST>> A.mst(
mstAlgebra: E,
block: E.() -> MST
): MstExpression<T> = MstExpression(this, mstAlgebra.block())
/**
* Builds [MstExpression] over [Space].
*
* @author Alexander Nozik
*/
inline fun <reified T : Any> Space<T>.mstInSpace(block: MstSpace.() -> MST): MstExpression<T> {
public inline fun <reified T : Any> Space<T>.mstInSpace(block: MstSpace.() -> MST): MstExpression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return MstExpression(this, MstSpace.block())
}
/**
* Builds [MstExpression] over [Ring].
*
* @author Alexander Nozik
*/
inline fun <reified T : Any> Ring<T>.mstInRing(block: MstRing.() -> MST): MstExpression<T> {
public inline fun <reified T : Any> Ring<T>.mstInRing(block: MstRing.() -> MST): MstExpression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return MstExpression(this, MstRing.block())
}
/**
* Builds [MstExpression] over [Field].
*
* @author Alexander Nozik
*/
inline fun <reified T : Any> Field<T>.mstInField(block: MstField.() -> MST): MstExpression<T> {
public inline fun <reified T : Any> Field<T>.mstInField(block: MstField.() -> MST): MstExpression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return MstExpression(this, MstField.block())
}
/**
* Builds [MstExpression] over [ExtendedField].
*
* @author Iaroslav Postovalov
*/
inline fun <reified T : Any> Field<T>.mstInExtendedField(block: MstExtendedField.() -> MST): MstExpression<T> {
public inline fun <reified T : Any> Field<T>.mstInExtendedField(block: MstExtendedField.() -> MST): MstExpression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return MstExpression(this, MstExtendedField.block())
}
/**
* Builds [MstExpression] over [FunctionalExpressionSpace].
*
* @author Alexander Nozik
*/
inline fun <reified T : Any, A : Space<T>> FunctionalExpressionSpace<T, A>.mstInSpace(block: MstSpace.() -> MST): MstExpression<T> {
public inline fun <reified T : Any, A : Space<T>> FunctionalExpressionSpace<T, A>.mstInSpace(block: MstSpace.() -> MST): MstExpression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return algebra.mstInSpace(block)
}
/**
* Builds [MstExpression] over [FunctionalExpressionRing].
*
* @author Alexander Nozik
*/
inline fun <reified T : Any, A : Ring<T>> FunctionalExpressionRing<T, A>.mstInRing(block: MstRing.() -> MST): MstExpression<T> {
public inline fun <reified T : Any, A : Ring<T>> FunctionalExpressionRing<T, A>.mstInRing(block: MstRing.() -> MST): MstExpression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return algebra.mstInRing(block)
}
/**
* Builds [MstExpression] over [FunctionalExpressionField].
*
* @author Alexander Nozik
*/
inline fun <reified T : Any, A : Field<T>> FunctionalExpressionField<T, A>.mstInField(block: MstField.() -> MST): MstExpression<T> {
public inline fun <reified T : Any, A : Field<T>> FunctionalExpressionField<T, A>.mstInField(block: MstField.() -> MST): MstExpression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return algebra.mstInField(block)
}
/**
* Builds [MstExpression] over [FunctionalExpressionExtendedField].
*
* @author Iaroslav Postovalov
*/
inline fun <reified T : Any, A : ExtendedField<T>> FunctionalExpressionExtendedField<T, A>.mstInExtendedField(block: MstExtendedField.() -> MST): MstExpression<T> {
public inline fun <reified T : Any, A : ExtendedField<T>> FunctionalExpressionExtendedField<T, A>.mstInExtendedField(
block: MstExtendedField.() -> MST
): MstExpression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return algebra.mstInExtendedField(block)
}

39
kmath-ast/src/jvmMain/kotlin/scientifik/kmath/asm/asm.kt → kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/asm.kt
View File

@ -1,19 +1,24 @@
package scientifik.kmath.asm
package kscience.kmath.asm
import scientifik.kmath.asm.internal.AsmBuilder
import scientifik.kmath.asm.internal.MstType
import scientifik.kmath.asm.internal.buildAlgebraOperationCall
import scientifik.kmath.asm.internal.buildName
import scientifik.kmath.ast.MST
import scientifik.kmath.ast.MstExpression
import scientifik.kmath.expressions.Expression
import scientifik.kmath.operations.Algebra
import kscience.kmath.asm.internal.AsmBuilder
import kscience.kmath.asm.internal.MstType
import kscience.kmath.asm.internal.buildAlgebraOperationCall
import kscience.kmath.asm.internal.buildName
import kscience.kmath.ast.MST
import kscience.kmath.ast.MstExpression
import kscience.kmath.expressions.Expression
import kscience.kmath.operations.Algebra
import kotlin.reflect.KClass
/**
* Compile given MST to an Expression using AST compiler
* Compiles given MST to an Expression using AST compiler.
*
* @param type the target type.
* @param algebra the target algebra.
* @return the compiled expression.
* @author Alexander Nozik
*/
fun <T : Any> MST.compileWith(type: KClass<T>, algebra: Algebra<T>): Expression<T> {
public fun <T : Any> MST.compileWith(type: KClass<T>, algebra: Algebra<T>): Expression<T> {
fun AsmBuilder<T>.visit(node: MST) {
when (node) {
is MST.Symbolic -> {
@ -54,11 +59,15 @@ fun <T : Any> MST.compileWith(type: KClass<T>, algebra: Algebra<T>): Expression<
}
/**
* Compile an [MST] to ASM using given algebra
* Compiles an [MST] to ASM using given algebra.
*
* @author Alexander Nozik.
*/
inline fun <reified T : Any> Algebra<T>.expression(mst: MST): Expression<T> = mst.compileWith(T::class, this)
public inline fun <reified T : Any> Algebra<T>.expression(mst: MST): Expression<T> = mst.compileWith(T::class, this)
/**
* Optimize performance of an [MstExpression] using ASM codegen
* Optimizes performance of an [MstExpression] using ASM codegen.
*
* @author Alexander Nozik.
*/
inline fun <reified T : Any> MstExpression<T>.compile(): Expression<T> = mst.compileWith(T::class, algebra)
public inline fun <reified T : Any> MstExpression<T>.compile(): Expression<T> = mst.compileWith(T::class, algebra)

15
kmath-ast/src/jvmMain/kotlin/scientifik/kmath/asm/internal/AsmBuilder.kt → kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/AsmBuilder.kt
View File

@ -1,13 +1,13 @@
package scientifik.kmath.asm.internal
package kscience.kmath.asm.internal
import kscience.kmath.asm.internal.AsmBuilder.ClassLoader
import kscience.kmath.ast.MST
import kscience.kmath.expressions.Expression
import kscience.kmath.operations.Algebra
import kscience.kmath.operations.NumericAlgebra
import org.objectweb.asm.*
import org.objectweb.asm.Opcodes.*
import org.objectweb.asm.commons.InstructionAdapter
import scientifik.kmath.asm.internal.AsmBuilder.ClassLoader
import scientifik.kmath.ast.MST
import scientifik.kmath.expressions.Expression
import scientifik.kmath.operations.Algebra
import scientifik.kmath.operations.NumericAlgebra
import java.util.*
import java.util.stream.Collectors
import kotlin.reflect.KClass
@ -20,6 +20,7 @@ import kotlin.reflect.KClass
* @property algebra the algebra the applied AsmExpressions use.
* @property className the unique class name of new loaded class.
* @property invokeLabel0Visitor the function to apply to this object when generating invoke method, label 0.
* @author Iaroslav Postovalov
*/
internal class AsmBuilder<T> internal constructor(
private val classOfT: KClass<*>,
@ -563,6 +564,6 @@ internal class AsmBuilder<T> internal constructor(
/**
* ASM type for MapIntrinsics.
*/
internal val MAP_INTRINSICS_TYPE: Type by lazy { Type.getObjectType("scientifik/kmath/asm/internal/MapIntrinsics") }
internal val MAP_INTRINSICS_TYPE: Type by lazy { Type.getObjectType("kscience/kmath/asm/internal/MapIntrinsics") }
}
}

7
kmath-ast/src/jvmMain/kotlin/scientifik/kmath/asm/internal/MstType.kt → kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/MstType.kt
View File

@ -1,7 +1,10 @@
package scientifik.kmath.asm.internal
package kscience.kmath.asm.internal
import scientifik.kmath.ast.MST
import kscience.kmath.ast.MST
/**
* Represents types known in [MST], numbers and general values.
*/
internal enum class MstType {
GENERAL,
NUMBER;

53
kmath-ast/src/jvmMain/kotlin/scientifik/kmath/asm/internal/codegenUtils.kt → kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/codegenUtils.kt
View File

@ -1,11 +1,14 @@
package scientifik.kmath.asm.internal
package kscience.kmath.asm.internal
import kscience.kmath.ast.MST
import kscience.kmath.expressions.Expression
import kscience.kmath.operations.Algebra
import kscience.kmath.operations.FieldOperations
import kscience.kmath.operations.RingOperations
import kscience.kmath.operations.SpaceOperations
import org.objectweb.asm.*
import org.objectweb.asm.Opcodes.INVOKEVIRTUAL
import org.objectweb.asm.commons.InstructionAdapter
import scientifik.kmath.ast.MST
import scientifik.kmath.expressions.Expression
import scientifik.kmath.operations.Algebra
import java.lang.reflect.Method
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@ -13,20 +16,27 @@ import kotlin.reflect.KClass
private val methodNameAdapters: Map<Pair<String, Int>, String> by lazy {
hashMapOf(
"+" to 2 to "add",
"*" to 2 to "multiply",
"/" to 2 to "divide",
"+" to 1 to "unaryPlus",
"-" to 1 to "unaryMinus",
"-" to 2 to "minus"
SpaceOperations.PLUS_OPERATION to 2 to "add",
RingOperations.TIMES_OPERATION to 2 to "multiply",
FieldOperations.DIV_OPERATION to 2 to "divide",
SpaceOperations.PLUS_OPERATION to 1 to "unaryPlus",
SpaceOperations.MINUS_OPERATION to 1 to "unaryMinus",
SpaceOperations.MINUS_OPERATION to 2 to "minus"
)
}
/**
* Returns ASM [Type] for given [KClass].
*
* @author Iaroslav Postovalov
*/
internal val KClass<*>.asm: Type
get() = Type.getType(java)
/**
* Returns singleton array with this value if the [predicate] is true, returns empty array otherwise.
*
* @author Iaroslav Postovalov
*/
internal inline fun <reified T> T.wrapToArrayIf(predicate: (T) -> Boolean): Array<T> {
contract { callsInPlace(predicate, InvocationKind.EXACTLY_ONCE) }
@ -35,11 +45,15 @@ internal inline fun <reified T> T.wrapToArrayIf(predicate: (T) -> Boolean): Arra
/**
* Creates an [InstructionAdapter] from this [MethodVisitor].
*
* @author Iaroslav Postovalov
*/
private fun MethodVisitor.instructionAdapter(): InstructionAdapter = InstructionAdapter(this)
/**
* Creates an [InstructionAdapter] from this [MethodVisitor] and applies [block] to it.
*
* @author Iaroslav Postovalov
*/
internal inline fun MethodVisitor.instructionAdapter(block: InstructionAdapter.() -> Unit): InstructionAdapter {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
@ -48,6 +62,8 @@ internal inline fun MethodVisitor.instructionAdapter(block: InstructionAdapter.(
/**
* Constructs a [Label], then applies it to this visitor.
*
* @author Iaroslav Postovalov
*/
internal fun MethodVisitor.label(): Label = Label().also { visitLabel(it) }
@ -56,9 +72,11 @@ internal fun MethodVisitor.label(): Label = Label().also { visitLabel(it) }
*
* This methods helps to avoid collisions of class name to prevent loading several classes with the same name. If there
* is a colliding class, change [collision] parameter or leave it `0` to check existing classes recursively.
*
* @author Iaroslav Postovalov
*/
internal tailrec fun buildName(mst: MST, collision: Int = 0): String {
val name = "scientifik.kmath.asm.generated.AsmCompiledExpression_${mst.hashCode()}_$collision"
val name = "kscience.kmath.asm.generated.AsmCompiledExpression_${mst.hashCode()}_$collision"
try {
Class.forName(name)
@ -75,6 +93,11 @@ internal inline fun ClassWriter(flags: Int, block: ClassWriter.() -> Unit): Clas
return ClassWriter(flags).apply(block)
}
/**
* Invokes [visitField] and applies [block] to the [FieldVisitor].
*
* @author Iaroslav Postovalov
*/
internal inline fun ClassWriter.visitField(
access: Int,
name: String,
@ -104,7 +127,7 @@ private fun <T> AsmBuilder<T>.findSpecific(context: Algebra<T>, name: String, pa
* Checks if the target [context] for code generation contains a method with needed [name] and arity, also builds
* type expectation stack for needed arity.
*
* @return `true` if contains, else `false`.
* @author Iaroslav Postovalov
*/
private fun <T> AsmBuilder<T>.buildExpectationStack(
context: Algebra<T>,
@ -136,7 +159,7 @@ private fun <T> AsmBuilder<T>.mapTypes(method: Method, parameterTypes: Array<Mst
* Checks if the target [context] for code generation contains a method with needed [name] and arity and inserts
* [AsmBuilder.invokeAlgebraOperation] of this method.
*
* @return `true` if contains, else `false`.
* @author Iaroslav Postovalov
*/
private fun <T> AsmBuilder<T>.tryInvokeSpecific(
context: Algebra<T>,
@ -160,7 +183,9 @@ private fun <T> AsmBuilder<T>.tryInvokeSpecific(
}
/**
* Builds specialized algebra call with option to fallback to generic algebra operation accepting String.
* Builds specialized [context] call with option to fallback to generic algebra operation accepting [String].
*
* @author Iaroslav Postovalov
*/
internal inline fun <T> AsmBuilder<T>.buildAlgebraOperationCall(
context: Algebra<T>,

7
kmath-ast/src/jvmMain/kotlin/scientifik/kmath/asm/internal/mapIntrinsics.kt → kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/mapIntrinsics.kt
View File

@ -1,7 +1,12 @@
@file:JvmName("MapIntrinsics")
package scientifik.kmath.asm.internal
package kscience.kmath.asm.internal
/**
* Gets value with given [key] or throws [IllegalStateException] whenever it is not present.
*
* @author Iaroslav Postovalov
*/
@JvmOverloads
internal fun <K, V> Map<K, V>.getOrFail(key: K, default: V? = null): V =
this[key] ?: default ?: error("Parameter not found: $key")

37
kmath-ast/src/commonMain/kotlin/scientifik/kmath/ast/parser.kt → kmath-ast/src/jvmMain/kotlin/kscience/kmath/ast/parser.kt
View File

@ -1,4 +1,4 @@
package scientifik.kmath.ast
package kscience.kmath.ast
import com.github.h0tk3y.betterParse.combinators.*
import com.github.h0tk3y.betterParse.grammar.Grammar
@ -10,15 +10,16 @@ import com.github.h0tk3y.betterParse.lexer.TokenMatch
import com.github.h0tk3y.betterParse.lexer.regexToken
import com.github.h0tk3y.betterParse.parser.ParseResult
import com.github.h0tk3y.betterParse.parser.Parser
import scientifik.kmath.operations.FieldOperations
import scientifik.kmath.operations.PowerOperations
import scientifik.kmath.operations.RingOperations
import scientifik.kmath.operations.SpaceOperations
import kscience.kmath.operations.FieldOperations
import kscience.kmath.operations.PowerOperations
import kscience.kmath.operations.RingOperations
import kscience.kmath.operations.SpaceOperations
/**
* TODO move to core
* TODO move to common after IR version is released
* @author Alexander Nozik and Iaroslav Postovalov
*/
object ArithmeticsEvaluator : Grammar<MST>() {
public object ArithmeticsEvaluator : Grammar<MST>() {
// TODO replace with "...".toRegex() when better-parse 0.4.1 is released
private val num: Token by regexToken("[\\d.]+(?:[eE][-+]?\\d+)?")
private val id: Token by regexToken("[a-z_A-Z][\\da-z_A-Z]*")
@ -35,23 +36,23 @@ object ArithmeticsEvaluator : Grammar<MST>() {
private val number: Parser<MST> by num use { MST.Numeric(text.toDouble()) }
private val singular: Parser<MST> by id use { MST.Symbolic(text) }
private val unaryFunction: Parser<MST> by (id and skip(lpar) and parser(::subSumChain) and skip(rpar))
private val unaryFunction: Parser<MST> by (id and -lpar and parser(ArithmeticsEvaluator::subSumChain) and -rpar)
.map { (id, term) -> MST.Unary(id.text, term) }
private val binaryFunction: Parser<MST> by id
.and(skip(lpar))
.and(parser(::subSumChain))
.and(skip(comma))
.and(parser(::subSumChain))
.and(skip(rpar))
.and(-lpar)
.and(parser(ArithmeticsEvaluator::subSumChain))
.and(-comma)
.and(parser(ArithmeticsEvaluator::subSumChain))
.and(-rpar)
.map { (id, left, right) -> MST.Binary(id.text, left, right) }
private val term: Parser<MST> by number
.or(binaryFunction)
.or(unaryFunction)
.or(singular)
.or(skip(minus) and parser(::term) map { MST.Unary(SpaceOperations.MINUS_OPERATION, it) })
.or(skip(lpar) and parser(::subSumChain) and skip(rpar))
.or(-minus and parser(ArithmeticsEvaluator::term) map { MST.Unary(SpaceOperations.MINUS_OPERATION, it) })
.or(-lpar and parser(ArithmeticsEvaluator::subSumChain) and -rpar)
private val powChain: Parser<MST> by leftAssociative(term = term, operator = pow) { a, _, b ->
MST.Binary(PowerOperations.POW_OPERATION, a, b)
@ -85,13 +86,15 @@ object ArithmeticsEvaluator : Grammar<MST>() {
*
* @receiver the string to parse.
* @return the [MST] node.
* @author Alexander Nozik
*/
fun String.tryParseMath(): ParseResult<MST> = ArithmeticsEvaluator.tryParseToEnd(this)
public fun String.tryParseMath(): ParseResult<MST> = ArithmeticsEvaluator.tryParseToEnd(this)
/**
* Parses the string into [MST].
*
* @receiver the string to parse.
* @return the [MST] node.
* @author Alexander Nozik
*/
fun String.parseMath(): MST = ArithmeticsEvaluator.parseToEnd(this)
public fun String.parseMath(): MST = ArithmeticsEvaluator.parseToEnd(this)

14
kmath-ast/src/jvmTest/kotlin/scietifik/kmath/asm/TestAsmAlgebras.kt
View File

@ -1,12 +1,12 @@
package scietifik.kmath.asm
import scientifik.kmath.asm.compile
import scientifik.kmath.ast.mstInField
import scientifik.kmath.ast.mstInRing
import scientifik.kmath.ast.mstInSpace
import scientifik.kmath.expressions.invoke
import scientifik.kmath.operations.ByteRing
import scientifik.kmath.operations.RealField
import kscience.kmath.asm.compile
import kscience.kmath.ast.mstInField
import kscience.kmath.ast.mstInRing
import kscience.kmath.ast.mstInSpace
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.ByteRing
import kscience.kmath.operations.RealField
import kotlin.test.Test
import kotlin.test.assertEquals

10
kmath-ast/src/jvmTest/kotlin/scietifik/kmath/asm/TestAsmExpressions.kt
View File

@ -1,10 +1,10 @@
package scietifik.kmath.asm
import scientifik.kmath.asm.compile
import scientifik.kmath.ast.mstInField
import scientifik.kmath.ast.mstInSpace
import scientifik.kmath.expressions.invoke
import scientifik.kmath.operations.RealField
import kscience.kmath.asm.compile
import kscience.kmath.ast.mstInField
import kscience.kmath.ast.mstInSpace
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.RealField
import kotlin.test.Test
import kotlin.test.assertEquals

8
kmath-ast/src/jvmTest/kotlin/scietifik/kmath/asm/TestAsmSpecialization.kt
View File

@ -1,9 +1,9 @@
package scietifik.kmath.asm
import scientifik.kmath.asm.compile
import scientifik.kmath.ast.mstInField
import scientifik.kmath.expressions.invoke
import scientifik.kmath.operations.RealField
import kscience.kmath.asm.compile
import kscience.kmath.ast.mstInField
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.RealField
import kotlin.test.Test
import kotlin.test.assertEquals

6
kmath-ast/src/jvmTest/kotlin/scietifik/kmath/asm/TestAsmVariables.kt
View File

@ -1,8 +1,8 @@
package scietifik.kmath.asm
import scientifik.kmath.ast.mstInRing
import scientifik.kmath.expressions.invoke
import scientifik.kmath.operations.ByteRing
import kscience.kmath.ast.mstInRing
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.ByteRing
import kotlin.test.Test
import kotlin.test.assertEquals
import kotlin.test.assertFailsWith

14
kmath-ast/src/jvmTest/kotlin/scietifik/kmath/ast/AsmTest.kt
View File

@ -1,12 +1,12 @@
package scietifik.kmath.ast
import scientifik.kmath.asm.compile
import scientifik.kmath.asm.expression
import scientifik.kmath.ast.mstInField
import scientifik.kmath.ast.parseMath
import scientifik.kmath.expressions.invoke
import scientifik.kmath.operations.Complex
import scientifik.kmath.operations.ComplexField
import kscience.kmath.asm.compile
import kscience.kmath.asm.expression
import kscience.kmath.ast.mstInField
import kscience.kmath.ast.parseMath
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.Complex
import kscience.kmath.operations.ComplexField
import kotlin.test.Test
import kotlin.test.assertEquals

8
kmath-ast/src/jvmTest/kotlin/scietifik/kmath/ast/ParserPrecedenceTest.kt
View File

@ -1,9 +1,9 @@
package scietifik.kmath.ast
import scientifik.kmath.ast.evaluate
import scientifik.kmath.ast.parseMath
import scientifik.kmath.operations.Field
import scientifik.kmath.operations.RealField
import kscience.kmath.ast.evaluate
import kscience.kmath.ast.parseMath
import kscience.kmath.operations.Field
import kscience.kmath.operations.RealField
import kotlin.test.Test
import kotlin.test.assertEquals

16
kmath-ast/src/jvmTest/kotlin/scietifik/kmath/ast/ParserTest.kt
View File

@ -1,13 +1,13 @@
package scietifik.kmath.ast
import scientifik.kmath.ast.evaluate
import scientifik.kmath.ast.mstInField
import scientifik.kmath.ast.parseMath
import scientifik.kmath.expressions.invoke
import scientifik.kmath.operations.Algebra
import scientifik.kmath.operations.Complex
import scientifik.kmath.operations.ComplexField
import scientifik.kmath.operations.RealField
import kscience.kmath.ast.evaluate
import kscience.kmath.ast.mstInField
import kscience.kmath.ast.parseMath
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.Algebra
import kscience.kmath.operations.Complex
import kscience.kmath.operations.ComplexField
import kscience.kmath.operations.RealField
import kotlin.test.Test
import kotlin.test.assertEquals

5
kmath-commons/build.gradle.kts
View File

@ -1,13 +1,12 @@
plugins {
id("scientifik.jvm")
id("ru.mipt.npm.jvm")
}
description = "Commons math binding for kmath"
dependencies {
api(project(":kmath-core"))
api(project(":kmath-coroutines"))
api(project(":kmath-prob"))
api(project(":kmath-functions"))
// api(project(":kmath-functions"))
api("org.apache.commons:commons-math3:3.6.1")
}

128
kmath-commons/src/main/kotlin/kscience/kmath/commons/expressions/DiffExpression.kt Normal file
View File

@ -0,0 +1,128 @@
package kscience.kmath.commons.expressions
import kscience.kmath.expressions.Expression
import kscience.kmath.expressions.ExpressionAlgebra
import kscience.kmath.operations.ExtendedField
import kscience.kmath.operations.Field
import kscience.kmath.operations.invoke
import org.apache.commons.math3.analysis.differentiation.DerivativeStructure
import kotlin.properties.ReadOnlyProperty
/**
* A field wrapping commons-math derivative structures
*/
public class DerivativeStructureField(
public val order: Int,
public val parameters: Map<String, Double>
) : ExtendedField<DerivativeStructure> {
public override val zero: DerivativeStructure by lazy { DerivativeStructure(order, parameters.size) }
public override val one: DerivativeStructure by lazy { DerivativeStructure(order, parameters.size, 1.0) }
private val variables: Map<String, DerivativeStructure> = parameters.mapValues { (key, value) ->
DerivativeStructure(parameters.size, order, parameters.keys.indexOf(key), value)
}
public val variable: ReadOnlyProperty<Any?, DerivativeStructure> = ReadOnlyProperty { _, property ->
variables[property.name] ?: error("A variable with name ${property.name} does not exist")
}
public fun variable(name: String, default: DerivativeStructure? = null): DerivativeStructure =
variables[name] ?: default ?: error("A variable with name $name does not exist")
public fun Number.const(): DerivativeStructure = DerivativeStructure(order, parameters.size, toDouble())
public fun DerivativeStructure.deriv(parName: String, order: Int = 1): Double {
return deriv(mapOf(parName to order))
}
public fun DerivativeStructure.deriv(orders: Map<String, Int>): Double {
return getPartialDerivative(*parameters.keys.map { orders[it] ?: 0 }.toIntArray())
}
public fun DerivativeStructure.deriv(vararg orders: Pair<String, Int>): Double = deriv(mapOf(*orders))
public override fun add(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.add(b)
public override fun multiply(a: DerivativeStructure, k: Number): DerivativeStructure = when (k) {
is Double -> a.multiply(k)
is Int -> a.multiply(k)
else -> a.multiply(k.toDouble())
}
public override fun multiply(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.multiply(b)
public override fun divide(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.divide(b)
public override fun sin(arg: DerivativeStructure): DerivativeStructure = arg.sin()
public override fun cos(arg: DerivativeStructure): DerivativeStructure = arg.cos()
public override fun tan(arg: DerivativeStructure): DerivativeStructure = arg.tan()
public override fun asin(arg: DerivativeStructure): DerivativeStructure = arg.asin()
public override fun acos(arg: DerivativeStructure): DerivativeStructure = arg.acos()
public override fun atan(arg: DerivativeStructure): DerivativeStructure = arg.atan()
public override fun sinh(arg: DerivativeStructure): DerivativeStructure = arg.sinh()
public override fun cosh(arg: DerivativeStructure): DerivativeStructure = arg.cosh()
public override fun tanh(arg: DerivativeStructure): DerivativeStructure = arg.tanh()
public override fun asinh(arg: DerivativeStructure): DerivativeStructure = arg.asinh()
public override fun acosh(arg: DerivativeStructure): DerivativeStructure = arg.acosh()
public override fun atanh(arg: DerivativeStructure): DerivativeStructure = arg.atanh()
public override fun power(arg: DerivativeStructure, pow: Number): DerivativeStructure = when (pow) {
is Double -> arg.pow(pow)
is Int -> arg.pow(pow)
else -> arg.pow(pow.toDouble())
}
public fun power(arg: DerivativeStructure, pow: DerivativeStructure): DerivativeStructure = arg.pow(pow)
public override fun exp(arg: DerivativeStructure): DerivativeStructure = arg.exp()
public override fun ln(arg: DerivativeStructure): DerivativeStructure = arg.log()
public override operator fun DerivativeStructure.plus(b: Number): DerivativeStructure = add(b.toDouble())
public override operator fun DerivativeStructure.minus(b: Number): DerivativeStructure = subtract(b.toDouble())
public override operator fun Number.plus(b: DerivativeStructure): DerivativeStructure = b + this
public override operator fun Number.minus(b: DerivativeStructure): DerivativeStructure = b - this
}
/**
* A constructs that creates a derivative structure with required order on-demand
*/
public class DiffExpression(public val function: DerivativeStructureField.() -> DerivativeStructure) :
Expression<Double> {
public override operator fun invoke(arguments: Map<String, Double>): Double = DerivativeStructureField(
0,
arguments
).function().value
/**
* Get the derivative expression with given orders
* TODO make result [DiffExpression]
*/
public fun derivative(orders: Map<String, Int>): Expression<Double> = Expression { arguments ->
(DerivativeStructureField(orders.values.max() ?: 0, arguments)) { function().deriv(orders) }
}
//TODO add gradient and maybe other vector operators
}
public fun DiffExpression.derivative(vararg orders: Pair<String, Int>): Expression<Double> = derivative(mapOf(*orders))
public fun DiffExpression.derivative(name: String): Expression<Double> = derivative(name to 1)
/**
* A context for [DiffExpression] (not to be confused with [DerivativeStructure])
*/
public object DiffExpressionAlgebra : ExpressionAlgebra<Double, DiffExpression>, Field<DiffExpression> {
public override val zero: DiffExpression = DiffExpression { 0.0.const() }
public override val one: DiffExpression = DiffExpression { 1.0.const() }
public override fun variable(name: String, default: Double?): DiffExpression =
DiffExpression { variable(name, default?.const()) }
public override fun const(value: Double): DiffExpression = DiffExpression { value.const() }
public override fun add(a: DiffExpression, b: DiffExpression): DiffExpression =
DiffExpression { a.function(this) + b.function(this) }
public override fun multiply(a: DiffExpression, k: Number): DiffExpression = DiffExpression { a.function(this) * k }
public override fun multiply(a: DiffExpression, b: DiffExpression): DiffExpression =
DiffExpression { a.function(this) * b.function(this) }
public override fun divide(a: DiffExpression, b: DiffExpression): DiffExpression =
DiffExpression { a.function(this) / b.function(this) }
}

93
kmath-commons/src/main/kotlin/kscience/kmath/commons/linear/CMMatrix.kt Normal file
View File

@ -0,0 +1,93 @@
package kscience.kmath.commons.linear
import kscience.kmath.linear.*
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.NDStructure
import org.apache.commons.math3.linear.*
public class CMMatrix(public val origin: RealMatrix, features: Set<MatrixFeature>? = null) :
FeaturedMatrix<Double> {
public override val rowNum: Int get() = origin.rowDimension
public override val colNum: Int get() = origin.columnDimension
public override val features: Set<MatrixFeature> = features ?: sequence<MatrixFeature> {
if (origin is DiagonalMatrix) yield(DiagonalFeature)
}.toHashSet()
public override fun suggestFeature(vararg features: MatrixFeature): CMMatrix =
CMMatrix(origin, this.features + features)
public override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
public override fun equals(other: Any?): Boolean {
return NDStructure.equals(this, other as? NDStructure<*> ?: return false)
}
public override fun hashCode(): Int {
var result = origin.hashCode()
result = 31 * result + features.hashCode()
return result
}
}
public fun Matrix<Double>.toCM(): CMMatrix = if (this is CMMatrix) {
this
} else {
//TODO add feature analysis
val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
CMMatrix(Array2DRowRealMatrix(array))
}
public fun RealMatrix.asMatrix(): CMMatrix = CMMatrix(this)
public class CMVector(public val origin: RealVector) : Point<Double> {
public override val size: Int get() = origin.dimension
public override operator fun get(index: Int): Double = origin.getEntry(index)
public override operator fun iterator(): Iterator<Double> = origin.toArray().iterator()
}
public fun Point<Double>.toCM(): CMVector = if (this is CMVector) this else {
val array = DoubleArray(size) { this[it] }
CMVector(ArrayRealVector(array))
}
public fun RealVector.toPoint(): CMVector = CMVector(this)
public object CMMatrixContext : MatrixContext<Double> {
public override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> Double): CMMatrix {
val array = Array(rows) { i -> DoubleArray(columns) { j -> initializer(i, j) } }
return CMMatrix(Array2DRowRealMatrix(array))
}
public override fun Matrix<Double>.dot(other: Matrix<Double>): CMMatrix =
CMMatrix(toCM().origin.multiply(other.toCM().origin))
public override fun Matrix<Double>.dot(vector: Point<Double>): CMVector =
CMVector(toCM().origin.preMultiply(vector.toCM().origin))
public override operator fun Matrix<Double>.unaryMinus(): CMMatrix =
produce(rowNum, colNum) { i, j -> -get(i, j) }
public override fun add(a: Matrix<Double>, b: Matrix<Double>): CMMatrix =
CMMatrix(a.toCM().origin.multiply(b.toCM().origin))
public override operator fun Matrix<Double>.minus(b: Matrix<Double>): CMMatrix =
CMMatrix(toCM().origin.subtract(b.toCM().origin))
public override fun multiply(a: Matrix<Double>, k: Number): CMMatrix =
CMMatrix(a.toCM().origin.scalarMultiply(k.toDouble()))
public override operator fun Matrix<Double>.times(value: Double): Matrix<Double> =
produce(rowNum, colNum) { i, j -> get(i, j) * value }
}
public operator fun CMMatrix.plus(other: CMMatrix): CMMatrix =
CMMatrix(origin.add(other.origin))
public operator fun CMMatrix.minus(other: CMMatrix): CMMatrix =
CMMatrix(origin.subtract(other.origin))
public infix fun CMMatrix.dot(other: CMMatrix): CMMatrix =
CMMatrix(origin.multiply(other.origin))

41
kmath-commons/src/main/kotlin/kscience/kmath/commons/linear/CMSolver.kt Normal file
View File

@ -0,0 +1,41 @@
package kscience.kmath.commons.linear
import kscience.kmath.linear.Point
import kscience.kmath.structures.Matrix
import org.apache.commons.math3.linear.*
public enum class CMDecomposition {
LUP,
QR,
RRQR,
EIGEN,
CHOLESKY
}
public fun CMMatrixContext.solver(
a: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): DecompositionSolver = when (decomposition) {
CMDecomposition.LUP -> LUDecomposition(a.toCM().origin).solver
CMDecomposition.RRQR -> RRQRDecomposition(a.toCM().origin).solver
CMDecomposition.QR -> QRDecomposition(a.toCM().origin).solver
CMDecomposition.EIGEN -> EigenDecomposition(a.toCM().origin).solver
CMDecomposition.CHOLESKY -> CholeskyDecomposition(a.toCM().origin).solver
}
public fun CMMatrixContext.solve(
a: Matrix<Double>,
b: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).asMatrix()
public fun CMMatrixContext.solve(
a: Matrix<Double>,
b: Point<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMVector = solver(a, decomposition).solve(b.toCM().origin).toPoint()
public fun CMMatrixContext.inverse(
a: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMMatrix = solver(a, decomposition).inverse.asMatrix()

33
kmath-commons/src/main/kotlin/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt Normal file
View File

@ -0,0 +1,33 @@
package kscience.kmath.commons.random
import kscience.kmath.prob.RandomGenerator
public class CMRandomGeneratorWrapper(public val factory: (IntArray) -> RandomGenerator) :
org.apache.commons.math3.random.RandomGenerator {
private var generator: RandomGenerator = factory(intArrayOf())
public override fun nextBoolean(): Boolean = generator.nextBoolean()
public override fun nextFloat(): Float = generator.nextDouble().toFloat()
public override fun setSeed(seed: Int) {
generator = factory(intArrayOf(seed))
}
public override fun setSeed(seed: IntArray) {
generator = factory(seed)
}
public override fun setSeed(seed: Long) {
setSeed(seed.toInt())
}
public override fun nextBytes(bytes: ByteArray) {
generator.fillBytes(bytes)
}
public override fun nextInt(): Int = generator.nextInt()
public override fun nextInt(n: Int): Int = generator.nextInt(n)
public override fun nextGaussian(): Double = TODO()
public override fun nextDouble(): Double = generator.nextDouble()
public override fun nextLong(): Long = generator.nextLong()
}

37
kmath-commons/src/main/kotlin/scientifik/kmath/commons/transform/Transformations.kt → kmath-commons/src/main/kotlin/kscience/kmath/commons/transform/Transformations.kt
View File

@ -1,20 +1,19 @@
package scientifik.kmath.commons.transform
package kscience.kmath.commons.transform
import kotlinx.coroutines.FlowPreview
import kotlinx.coroutines.flow.Flow
import kotlinx.coroutines.flow.map
import kscience.kmath.operations.Complex
import kscience.kmath.streaming.chunked
import kscience.kmath.streaming.spread
import kscience.kmath.structures.*
import org.apache.commons.math3.transform.*
import scientifik.kmath.operations.Complex
import scientifik.kmath.streaming.chunked
import scientifik.kmath.streaming.spread
import scientifik.kmath.structures.*
/**
* Streaming and buffer transformations
*/
object Transformations {
public object Transformations {
private fun Buffer<Complex>.toArray(): Array<org.apache.commons.math3.complex.Complex> =
Array(size) { org.apache.commons.math3.complex.Complex(get(it).re, get(it).im) }
@ -32,35 +31,35 @@ object Transformations {
Complex(value.real, value.imaginary)
}
fun fourier(
public fun fourier(
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
): SuspendBufferTransform<Complex, Complex> = {
FastFourierTransformer(normalization).transform(it.toArray(), direction).asBuffer()
}
fun realFourier(
public fun realFourier(
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
): SuspendBufferTransform<Double, Complex> = {
FastFourierTransformer(normalization).transform(it.asArray(), direction).asBuffer()
}
fun sine(
public fun sine(
normalization: DstNormalization = DstNormalization.STANDARD_DST_I,
direction: TransformType = TransformType.FORWARD
): SuspendBufferTransform<Double, Double> = {
FastSineTransformer(normalization).transform(it.asArray(), direction).asBuffer()
}
fun cosine(
public fun cosine(
normalization: DctNormalization = DctNormalization.STANDARD_DCT_I,
direction: TransformType = TransformType.FORWARD
): SuspendBufferTransform<Double, Double> = {
FastCosineTransformer(normalization).transform(it.asArray(), direction).asBuffer()
}
fun hadamard(
public fun hadamard(
direction: TransformType = TransformType.FORWARD
): SuspendBufferTransform<Double, Double> = {
FastHadamardTransformer().transform(it.asArray(), direction).asBuffer()
@ -71,7 +70,7 @@ object Transformations {
* Process given [Flow] with commons-math fft transformation
*/
@FlowPreview
fun Flow<Buffer<Complex>>.FFT(
public fun Flow<Buffer<Complex>>.FFT(
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
): Flow<Buffer<Complex>> {
@ -81,7 +80,7 @@ fun Flow<Buffer<Complex>>.FFT(
@FlowPreview
@JvmName("realFFT")
fun Flow<Buffer<Double>>.FFT(
public fun Flow<Buffer<Double>>.FFT(
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
): Flow<Buffer<Complex>> {
@ -90,20 +89,18 @@ fun Flow<Buffer<Double>>.FFT(
}
/**
* Process a continous flow of real numbers in FFT splitting it in chunks of [bufferSize].
* Process a continuous flow of real numbers in FFT splitting it in chunks of [bufferSize].
*/
@FlowPreview
@JvmName("realFFT")
fun Flow<Double>.FFT(
public fun Flow<Double>.FFT(
bufferSize: Int = Int.MAX_VALUE,
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
): Flow<Complex> {
return chunked(bufferSize).FFT(normalization,direction).spread()
}
): Flow<Complex> = chunked(bufferSize).FFT(normalization, direction).spread()
/**
* Map a complex flow into real flow by taking real part of each number
*/
@FlowPreview
fun Flow<Complex>.real(): Flow<Double> = map{it.re}
public fun Flow<Complex>.real(): Flow<Double> = map { it.re }

137
kmath-commons/src/main/kotlin/scientifik/kmath/commons/expressions/DiffExpression.kt
View File

@ -1,137 +0,0 @@
package scientifik.kmath.commons.expressions
import org.apache.commons.math3.analysis.differentiation.DerivativeStructure
import scientifik.kmath.expressions.Expression
import scientifik.kmath.expressions.ExpressionAlgebra
import scientifik.kmath.operations.ExtendedField
import scientifik.kmath.operations.Field
import scientifik.kmath.operations.invoke
import kotlin.properties.ReadOnlyProperty
import kotlin.reflect.KProperty
/**
* A field wrapping commons-math derivative structures
*/
class DerivativeStructureField(
val order: Int,
val parameters: Map<String, Double>
) : ExtendedField<DerivativeStructure> {
override val zero: DerivativeStructure by lazy { DerivativeStructure(order, parameters.size) }
override val one: DerivativeStructure by lazy { DerivativeStructure(order, parameters.size, 1.0) }
private val variables: Map<String, DerivativeStructure> = parameters.mapValues { (key, value) ->
DerivativeStructure(parameters.size, order, parameters.keys.indexOf(key), value)
}
val variable: ReadOnlyProperty<Any?, DerivativeStructure> = object : ReadOnlyProperty<Any?, DerivativeStructure> {
override fun getValue(thisRef: Any?, property: KProperty<*>): DerivativeStructure =
variables[property.name] ?: error("A variable with name ${property.name} does not exist")
}
fun variable(name: String, default: DerivativeStructure? = null): DerivativeStructure =
variables[name] ?: default ?: error("A variable with name $name does not exist")
fun Number.const(): DerivativeStructure = DerivativeStructure(order, parameters.size, toDouble())
fun DerivativeStructure.deriv(parName: String, order: Int = 1): Double {
return deriv(mapOf(parName to order))
}
fun DerivativeStructure.deriv(orders: Map<String, Int>): Double {
return getPartialDerivative(*parameters.keys.map { orders[it] ?: 0 }.toIntArray())
}
fun DerivativeStructure.deriv(vararg orders: Pair<String, Int>): Double = deriv(mapOf(*orders))
override fun add(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.add(b)
override fun multiply(a: DerivativeStructure, k: Number): DerivativeStructure = when (k) {
is Double -> a.multiply(k)
is Int -> a.multiply(k)
else -> a.multiply(k.toDouble())
}
override fun multiply(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.multiply(b)
override fun divide(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.divide(b)
override fun sin(arg: DerivativeStructure): DerivativeStructure = arg.sin()
override fun cos(arg: DerivativeStructure): DerivativeStructure = arg.cos()
override fun tan(arg: DerivativeStructure): DerivativeStructure = arg.tan()
override fun asin(arg: DerivativeStructure): DerivativeStructure = arg.asin()
override fun acos(arg: DerivativeStructure): DerivativeStructure = arg.acos()
override fun atan(arg: DerivativeStructure): DerivativeStructure = arg.atan()
override fun sinh(arg: DerivativeStructure): DerivativeStructure = arg.sinh()
override fun cosh(arg: DerivativeStructure): DerivativeStructure = arg.cosh()
override fun tanh(arg: DerivativeStructure): DerivativeStructure = arg.tanh()
override fun asinh(arg: DerivativeStructure): DerivativeStructure = arg.asinh()
override fun acosh(arg: DerivativeStructure): DerivativeStructure = arg.acosh()
override fun atanh(arg: DerivativeStructure): DerivativeStructure = arg.atanh()
override fun power(arg: DerivativeStructure, pow: Number): DerivativeStructure = when (pow) {
is Double -> arg.pow(pow)
is Int -> arg.pow(pow)
else -> arg.pow(pow.toDouble())
}
fun power(arg: DerivativeStructure, pow: DerivativeStructure): DerivativeStructure = arg.pow(pow)
override fun exp(arg: DerivativeStructure): DerivativeStructure = arg.exp()
override fun ln(arg: DerivativeStructure): DerivativeStructure = arg.log()
override operator fun DerivativeStructure.plus(b: Number): DerivativeStructure = add(b.toDouble())
override operator fun DerivativeStructure.minus(b: Number): DerivativeStructure = subtract(b.toDouble())
override operator fun Number.plus(b: DerivativeStructure): DerivativeStructure = b + this
override operator fun Number.minus(b: DerivativeStructure): DerivativeStructure = b - this
}
/**
* A constructs that creates a derivative structure with required order on-demand
*/
class DiffExpression(val function: DerivativeStructureField.() -> DerivativeStructure) : Expression<Double> {
override operator fun invoke(arguments: Map<String, Double>): Double = DerivativeStructureField(
0,
arguments
).run(function).value
/**
* Get the derivative expression with given orders
* TODO make result [DiffExpression]
*/
fun derivative(orders: Map<String, Int>): Expression<Double> = object : Expression<Double> {
override operator fun invoke(arguments: Map<String, Double>): Double =
(DerivativeStructureField(orders.values.max() ?: 0, arguments)) { function().deriv(orders) }
}
//TODO add gradient and maybe other vector operators
}
fun DiffExpression.derivative(vararg orders: Pair<String, Int>): Expression<Double> = derivative(mapOf(*orders))
fun DiffExpression.derivative(name: String): Expression<Double> = derivative(name to 1)
/**
* A context for [DiffExpression] (not to be confused with [DerivativeStructure])
*/
object DiffExpressionAlgebra : ExpressionAlgebra<Double, DiffExpression>, Field<DiffExpression> {
override fun variable(name: String, default: Double?): DiffExpression =
DiffExpression { variable(name, default?.const()) }
override fun const(value: Double): DiffExpression =
DiffExpression { value.const() }
override fun add(a: DiffExpression, b: DiffExpression): DiffExpression =
DiffExpression { a.function(this) + b.function(this) }
override val zero: DiffExpression = DiffExpression { 0.0.const() }
override fun multiply(a: DiffExpression, k: Number): DiffExpression =
DiffExpression { a.function(this) * k }
override val one: DiffExpression = DiffExpression { 1.0.const() }
override fun multiply(a: DiffExpression, b: DiffExpression): DiffExpression =
DiffExpression { a.function(this) * b.function(this) }
override fun divide(a: DiffExpression, b: DiffExpression): DiffExpression =
DiffExpression { a.function(this) / b.function(this) }
}

93
kmath-commons/src/main/kotlin/scientifik/kmath/commons/linear/CMMatrix.kt
View File

@ -1,93 +0,0 @@
package scientifik.kmath.commons.linear
import org.apache.commons.math3.linear.*
import scientifik.kmath.linear.*
import scientifik.kmath.structures.Matrix
import scientifik.kmath.structures.NDStructure
class CMMatrix(val origin: RealMatrix, features: Set<MatrixFeature>? = null) :
FeaturedMatrix<Double> {
override val rowNum: Int get() = origin.rowDimension
override val colNum: Int get() = origin.columnDimension
override val features: Set<MatrixFeature> = features ?: sequence<MatrixFeature> {
if (origin is DiagonalMatrix) yield(DiagonalFeature)
}.toHashSet()
override fun suggestFeature(vararg features: MatrixFeature): CMMatrix =
CMMatrix(origin, this.features + features)
override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
override fun equals(other: Any?): Boolean {
return NDStructure.equals(this, other as? NDStructure<*> ?: return false)
}
override fun hashCode(): Int {
var result = origin.hashCode()
result = 31 * result + features.hashCode()
return result
}
}
fun Matrix<Double>.toCM(): CMMatrix = if (this is CMMatrix) {
this
} else {
//TODO add feature analysis
val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
CMMatrix(Array2DRowRealMatrix(array))
}
fun RealMatrix.asMatrix(): CMMatrix = CMMatrix(this)
class CMVector(val origin: RealVector) : Point<Double> {
override val size: Int get() = origin.dimension
override operator fun get(index: Int): Double = origin.getEntry(index)
override operator fun iterator(): Iterator<Double> = origin.toArray().iterator()
}
fun Point<Double>.toCM(): CMVector = if (this is CMVector) this else {
val array = DoubleArray(size) { this[it] }
CMVector(ArrayRealVector(array))
}
fun RealVector.toPoint(): CMVector = CMVector(this)
object CMMatrixContext : MatrixContext<Double> {
override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> Double): CMMatrix {
val array = Array(rows) { i -> DoubleArray(columns) { j -> initializer(i, j) } }
return CMMatrix(Array2DRowRealMatrix(array))
}
override fun Matrix<Double>.dot(other: Matrix<Double>): CMMatrix =
CMMatrix(this.toCM().origin.multiply(other.toCM().origin))
override fun Matrix<Double>.dot(vector: Point<Double>): CMVector =
CMVector(this.toCM().origin.preMultiply(vector.toCM().origin))
override operator fun Matrix<Double>.unaryMinus(): CMMatrix =
produce(rowNum, colNum) { i, j -> -get(i, j) }
override fun add(a: Matrix<Double>, b: Matrix<Double>): CMMatrix =
CMMatrix(a.toCM().origin.multiply(b.toCM().origin))
override operator fun Matrix<Double>.minus(b: Matrix<Double>): CMMatrix =
CMMatrix(this.toCM().origin.subtract(b.toCM().origin))
override fun multiply(a: Matrix<Double>, k: Number): CMMatrix =
CMMatrix(a.toCM().origin.scalarMultiply(k.toDouble()))
override operator fun Matrix<Double>.times(value: Double): Matrix<Double> =
produce(rowNum, colNum) { i, j -> get(i, j) * value }
}
operator fun CMMatrix.plus(other: CMMatrix): CMMatrix =
CMMatrix(this.origin.add(other.origin))
operator fun CMMatrix.minus(other: CMMatrix): CMMatrix =
CMMatrix(this.origin.subtract(other.origin))
infix fun CMMatrix.dot(other: CMMatrix): CMMatrix =
CMMatrix(this.origin.multiply(other.origin))

40
kmath-commons/src/main/kotlin/scientifik/kmath/commons/linear/CMSolver.kt
View File

@ -1,40 +0,0 @@
package scientifik.kmath.commons.linear
import org.apache.commons.math3.linear.*
import scientifik.kmath.linear.Point
import scientifik.kmath.structures.Matrix
enum class CMDecomposition {
LUP,
QR,
RRQR,
EIGEN,
CHOLESKY
}
fun CMMatrixContext.solver(a: Matrix<Double>, decomposition: CMDecomposition = CMDecomposition.LUP) =
when (decomposition) {
CMDecomposition.LUP -> LUDecomposition(a.toCM().origin).solver
CMDecomposition.RRQR -> RRQRDecomposition(a.toCM().origin).solver
CMDecomposition.QR -> QRDecomposition(a.toCM().origin).solver
CMDecomposition.EIGEN -> EigenDecomposition(a.toCM().origin).solver
CMDecomposition.CHOLESKY -> CholeskyDecomposition(a.toCM().origin).solver
}
fun CMMatrixContext.solve(
a: Matrix<Double>,
b: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
) = solver(a, decomposition).solve(b.toCM().origin).asMatrix()
fun CMMatrixContext.solve(
a: Matrix<Double>,
b: Point<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
) = solver(a, decomposition).solve(b.toCM().origin).toPoint()
fun CMMatrixContext.inverse(
a: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
) = solver(a, decomposition).inverse.asMatrix()

33
kmath-commons/src/main/kotlin/scientifik/kmath/commons/random/CMRandomGeneratorWrapper.kt
View File

@ -1,33 +0,0 @@
package scientifik.kmath.commons.random
import scientifik.kmath.prob.RandomGenerator
class CMRandomGeneratorWrapper(val factory: (IntArray) -> RandomGenerator) :
org.apache.commons.math3.random.RandomGenerator {
private var generator: RandomGenerator = factory(intArrayOf())
override fun nextBoolean(): Boolean = generator.nextBoolean()
override fun nextFloat(): Float = generator.nextDouble().toFloat()
override fun setSeed(seed: Int) {
generator = factory(intArrayOf(seed))
}
override fun setSeed(seed: IntArray) {
generator = factory(seed)
}
override fun setSeed(seed: Long) {
setSeed(seed.toInt())
}
override fun nextBytes(bytes: ByteArray) {
generator.fillBytes(bytes)
}
override fun nextInt(): Int = generator.nextInt()
override fun nextInt(n: Int): Int = generator.nextInt(n)
override fun nextGaussian(): Double = TODO()
override fun nextDouble(): Double = generator.nextDouble()
override fun nextLong(): Long = generator.nextLong()
}

12
kmath-commons/src/test/kotlin/scientifik/kmath/commons/expressions/AutoDiffTest.kt → kmath-commons/src/test/kotlin/kscience/kmath/commons/expressions/AutoDiffTest.kt
View File

@ -1,17 +1,21 @@
package scientifik.kmath.commons.expressions
package kscience.kmath.commons.expressions
import scientifik.kmath.expressions.invoke
import kscience.kmath.expressions.invoke
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
import kotlin.test.Test
import kotlin.test.assertEquals
inline fun <R> diff(order: Int, vararg parameters: Pair<String, Double>, block: DerivativeStructureField.() -> R): R {
internal inline fun <R> diff(
order: Int,
vararg parameters: Pair<String, Double>,
block: DerivativeStructureField.() -> R
): R {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return DerivativeStructureField(order, mapOf(*parameters)).run(block)
}
class AutoDiffTest {
internal class AutoDiffTest {
@Test
fun derivativeStructureFieldTest() {
val res = diff(3, "x" to 1.0, "y" to 1.0) {

12
kmath-core/README.md
View File

@ -10,31 +10,31 @@ The core features of KMath:
- Automatic differentiation.
> #### Artifact:
> This module is distributed in the artifact `scientifik:kmath-core:0.1.4-dev-8`.
> This module is distributed in the artifact `kscience.kmath:kmath-core:0.1.4-dev-8`.
>
> **Gradle:**
>
> ```gradle
> repositories {
> maven { url 'https://dl.bintray.com/mipt-npm/scientifik' }
> maven { url 'https://dl.bintray.com/mipt-npm/kscience' }
> maven { url 'https://dl.bintray.com/mipt-npm/dev' }
> maven { url https://dl.bintray.com/hotkeytlt/maven' }
> }
>
> dependencies {
> implementation 'scientifik:kmath-core:0.1.4-dev-8'
> implementation 'kscience.kmath:kmath-core:0.1.4-dev-8'
> }
> ```
> **Gradle Kotlin DSL:**
>
> ```kotlin
> repositories {
> maven("https://dl.bintray.com/mipt-npm/scientifik")
> maven("https://dl.bintray.com/mipt-npm/kscience")
> maven("https://dl.bintray.com/mipt-npm/dev")
> maven("https://dl.bintray.com/hotkeytlt/maven")
> }
>
> dependencies {``
> implementation("scientifik:kmath-core:0.1.4-dev-8")
> dependencies {
> implementation("kscience.kmath:kmath-core:0.1.4-dev-8")
> }
> ```

4
kmath-core/build.gradle.kts
View File

@ -1,6 +1,4 @@
plugins {
id("scientifik.mpp")
}
plugins { id("ru.mipt.npm.mpp") }
kotlin.sourceSets.commonMain {
dependencies {

10
kmath-core/src/commonMain/kotlin/scientifik/kmath/domains/Domain.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/domains/Domain.kt
View File

@ -1,20 +1,20 @@
package scientifik.kmath.domains
package kscience.kmath.domains
import scientifik.kmath.linear.Point
import kscience.kmath.linear.Point
/**
* A simple geometric domain.
*
* @param T the type of element of this domain.
*/
interface Domain<T : Any> {
public interface Domain<T : Any> {
/**
* Checks if the specified point is contained in this domain.
*/
operator fun contains(point: Point<T>): Boolean
public operator fun contains(point: Point<T>): Boolean
/**
* Number of hyperspace dimensions.
*/
val dimension: Int
public val dimension: Int
}

37
kmath-core/src/commonMain/kotlin/scientifik/kmath/domains/HyperSquareDomain.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/domains/HyperSquareDomain.kt
View File

@ -13,11 +13,11 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package scientifik.kmath.domains
package kscience.kmath.domains
import scientifik.kmath.linear.Point
import scientifik.kmath.structures.RealBuffer
import scientifik.kmath.structures.indices
import kscience.kmath.linear.Point
import kscience.kmath.structures.RealBuffer
import kscience.kmath.structures.indices
/**
*
@ -25,23 +25,22 @@ import scientifik.kmath.structures.indices
*
* @author Alexander Nozik
*/
class HyperSquareDomain(private val lower: RealBuffer, private val upper: RealBuffer) : RealDomain {
public class HyperSquareDomain(private val lower: RealBuffer, private val upper: RealBuffer) : RealDomain {
public override val dimension: Int get() = lower.size
override operator fun contains(point: Point<Double>): Boolean = point.indices.all { i ->
public override operator fun contains(point: Point<Double>): Boolean = point.indices.all { i ->
point[i] in lower[i]..upper[i]
}
override val dimension: Int get() = lower.size
public override fun getLowerBound(num: Int, point: Point<Double>): Double? = lower[num]
override fun getLowerBound(num: Int, point: Point<Double>): Double? = lower[num]
public override fun getLowerBound(num: Int): Double? = lower[num]
override fun getLowerBound(num: Int): Double? = lower[num]
public override fun getUpperBound(num: Int, point: Point<Double>): Double? = upper[num]
override fun getUpperBound(num: Int, point: Point<Double>): Double? = upper[num]
public override fun getUpperBound(num: Int): Double? = upper[num]
override fun getUpperBound(num: Int): Double? = upper[num]
override fun nearestInDomain(point: Point<Double>): Point<Double> {
public override fun nearestInDomain(point: Point<Double>): Point<Double> {
val res = DoubleArray(point.size) { i ->
when {
point[i] < lower[i] -> lower[i]
@ -53,16 +52,14 @@ class HyperSquareDomain(private val lower: RealBuffer, private val upper: RealBu
return RealBuffer(*res)
}
override fun volume(): Double {
public override fun volume(): Double {
var res = 1.0
for (i in 0 until dimension) {
if (lower[i].isInfinite() || upper[i].isInfinite()) {
return Double.POSITIVE_INFINITY
}
if (upper[i] > lower[i]) {
res *= upper[i] - lower[i]
}
if (lower[i].isInfinite() || upper[i].isInfinite()) return Double.POSITIVE_INFINITY
if (upper[i] > lower[i]) res *= upper[i] - lower[i]
}
return res
}
}

18
kmath-core/src/commonMain/kotlin/scientifik/kmath/domains/RealDomain.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/domains/RealDomain.kt
View File

@ -13,17 +13,17 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package scientifik.kmath.domains
package kscience.kmath.domains
import scientifik.kmath.linear.Point
import kscience.kmath.linear.Point
/**
* n-dimensional volume
*
* @author Alexander Nozik
*/
interface RealDomain : Domain<Double> {
fun nearestInDomain(point: Point<Double>): Point<Double>
public interface RealDomain : Domain<Double> {
public fun nearestInDomain(point: Point<Double>): Point<Double>
/**
* The lower edge for the domain going down from point
@ -31,7 +31,7 @@ interface RealDomain : Domain<Double> {
* @param point
* @return
*/
fun getLowerBound(num: Int, point: Point<Double>): Double?
public fun getLowerBound(num: Int, point: Point<Double>): Double?
/**
* The upper edge of the domain going up from point
@ -39,25 +39,25 @@ interface RealDomain : Domain<Double> {
* @param point
* @return
*/
fun getUpperBound(num: Int, point: Point<Double>): Double?
public fun getUpperBound(num: Int, point: Point<Double>): Double?
/**
* Global lower edge
* @param num
* @return
*/
fun getLowerBound(num: Int): Double?
public fun getLowerBound(num: Int): Double?
/**
* Global upper edge
* @param num
* @return
*/
fun getUpperBound(num: Int): Double?
public fun getUpperBound(num: Int): Double?
/**
* Hyper volume
* @return
*/
fun volume(): Double
public fun volume(): Double
}

34
kmath-core/src/commonMain/kotlin/kscience/kmath/domains/UnconstrainedDomain.kt Normal file
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@ -0,0 +1,34 @@
/*
* Copyright 2015 Alexander Nozik.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package kscience.kmath.domains
import kscience.kmath.linear.Point
public class UnconstrainedDomain(public override val dimension: Int) : RealDomain {
public override operator fun contains(point: Point<Double>): Boolean = true
public override fun getLowerBound(num: Int, point: Point<Double>): Double? = Double.NEGATIVE_INFINITY
public override fun getLowerBound(num: Int): Double? = Double.NEGATIVE_INFINITY
public override fun getUpperBound(num: Int, point: Point<Double>): Double? = Double.POSITIVE_INFINITY
public override fun getUpperBound(num: Int): Double? = Double.POSITIVE_INFINITY
public override fun nearestInDomain(point: Point<Double>): Point<Double> = point
public override fun volume(): Double = Double.POSITIVE_INFINITY
}

49
kmath-core/src/commonMain/kotlin/kscience/kmath/domains/UnivariateDomain.kt Normal file
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@ -0,0 +1,49 @@
package kscience.kmath.domains
import kscience.kmath.linear.Point
import kscience.kmath.structures.asBuffer
public inline class UnivariateDomain(public val range: ClosedFloatingPointRange<Double>) : RealDomain {
public override val dimension: Int
get() = 1
public operator fun contains(d: Double): Boolean = range.contains(d)
public override operator fun contains(point: Point<Double>): Boolean {
require(point.size == 0)
return contains(point[0])
}
public override fun nearestInDomain(point: Point<Double>): Point<Double> {
require(point.size == 1)
val value = point[0]
return when {
value in range -> point
value >= range.endInclusive -> doubleArrayOf(range.endInclusive).asBuffer()
else -> doubleArrayOf(range.start).asBuffer()
}
}
public override fun getLowerBound(num: Int, point: Point<Double>): Double? {
require(num == 0)
return range.start
}
public override fun getUpperBound(num: Int, point: Point<Double>): Double? {
require(num == 0)
return range.endInclusive
}
public override fun getLowerBound(num: Int): Double? {
require(num == 0)
return range.start
}
public override fun getUpperBound(num: Int): Double? {
require(num == 0)
return range.endInclusive
}
public override fun volume(): Double = range.endInclusive - range.start
}

41
kmath-core/src/commonMain/kotlin/kscience/kmath/expressions/Expression.kt Normal file
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@ -0,0 +1,41 @@
package kscience.kmath.expressions
import kscience.kmath.operations.Algebra
/**
* An elementary function that could be invoked on a map of arguments
*/
public fun interface Expression<T> {
/**
* Calls this expression from arguments.
*
* @param arguments the map of arguments.
* @return the value.
*/
public operator fun invoke(arguments: Map<String, T>): T
public companion object
}
/**
* Calls this expression from arguments.
*
* @param pairs the pair of arguments' names to values.
* @return the value.
*/
public operator fun <T> Expression<T>.invoke(vararg pairs: Pair<String, T>): T = invoke(mapOf(*pairs))
/**
* A context for expression construction
*/
public interface ExpressionAlgebra<T, E> : Algebra<E> {
/**
* Introduce a variable into expression context
*/
public fun variable(name: String, default: T? = null): E
/**
* A constant expression which does not depend on arguments
*/
public fun const(value: T): E
}

171
kmath-core/src/commonMain/kotlin/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt Normal file
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@ -0,0 +1,171 @@
package kscience.kmath.expressions
import kscience.kmath.operations.*
internal class FunctionalUnaryOperation<T>(val context: Algebra<T>, val name: String, private val expr: Expression<T>) :
Expression<T> {
public override operator fun invoke(arguments: Map<String, T>): T =
context.unaryOperation(name, expr.invoke(arguments))
}
internal class FunctionalBinaryOperation<T>(
val context: Algebra<T>,
val name: String,
val first: Expression<T>,
val second: Expression<T>
) : Expression<T> {
public override operator fun invoke(arguments: Map<String, T>): T =
context.binaryOperation(name, first.invoke(arguments), second.invoke(arguments))
}
internal class FunctionalVariableExpression<T>(val name: String, val default: T? = null) : Expression<T> {
public override operator fun invoke(arguments: Map<String, T>): T =
arguments[name] ?: default ?: error("Parameter not found: $name")
}
internal class FunctionalConstantExpression<T>(val value: T) : Expression<T> {
public override operator fun invoke(arguments: Map<String, T>): T = value
}
internal class FunctionalConstProductExpression<T>(
val context: Space<T>,
private val expr: Expression<T>,
val const: Number
) : Expression<T> {
public override operator fun invoke(arguments: Map<String, T>): T = context.multiply(expr.invoke(arguments), const)
}
/**
* A context class for [Expression] construction.
*
* @param algebra The algebra to provide for Expressions built.
*/
public abstract class FunctionalExpressionAlgebra<T, A : Algebra<T>>(public val algebra: A) :
ExpressionAlgebra<T, Expression<T>> {
/**
* Builds an Expression of constant expression which does not depend on arguments.
*/
public override fun const(value: T): Expression<T> = FunctionalConstantExpression(value)
/**
* Builds an Expression to access a variable.
*/
public override fun variable(name: String, default: T?): Expression<T> = FunctionalVariableExpression(name, default)
/**
* Builds an Expression of dynamic call of binary operation [operation] on [left] and [right].
*/
public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
FunctionalBinaryOperation(algebra, operation, left, right)
/**
* Builds an Expression of dynamic call of unary operation with name [operation] on [arg].
*/
public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
FunctionalUnaryOperation(algebra, operation, arg)
}
/**
* A context class for [Expression] construction for [Space] algebras.
*/
public open class FunctionalExpressionSpace<T, A : Space<T>>(algebra: A) :
FunctionalExpressionAlgebra<T, A>(algebra), Space<Expression<T>> {
public override val zero: Expression<T> get() = const(algebra.zero)
/**
* Builds an Expression of addition of two another expressions.
*/
public override fun add(a: Expression<T>, b: Expression<T>): Expression<T> =
binaryOperation(SpaceOperations.PLUS_OPERATION, a, b)
/**
* Builds an Expression of multiplication of expression by number.
*/
public override fun multiply(a: Expression<T>, k: Number): Expression<T> =
FunctionalConstProductExpression(algebra, a, k)
public operator fun Expression<T>.plus(arg: T): Expression<T> = this + const(arg)
public operator fun Expression<T>.minus(arg: T): Expression<T> = this - const(arg)
public operator fun T.plus(arg: Expression<T>): Expression<T> = arg + this
public operator fun T.minus(arg: Expression<T>): Expression<T> = arg - this
public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
super<FunctionalExpressionAlgebra>.unaryOperation(operation, arg)
public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
super<FunctionalExpressionAlgebra>.binaryOperation(operation, left, right)
}
public open class FunctionalExpressionRing<T, A>(algebra: A) : FunctionalExpressionSpace<T, A>(algebra),
Ring<Expression<T>> where A : Ring<T>, A : NumericAlgebra<T> {
public override val one: Expression<T>
get() = const(algebra.one)
/**
* Builds an Expression of multiplication of two expressions.
*/
public override fun multiply(a: Expression<T>, b: Expression<T>): Expression<T> =
binaryOperation(RingOperations.TIMES_OPERATION, a, b)
public operator fun Expression<T>.times(arg: T): Expression<T> = this * const(arg)
public operator fun T.times(arg: Expression<T>): Expression<T> = arg * this
public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
super<FunctionalExpressionSpace>.unaryOperation(operation, arg)
public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
super<FunctionalExpressionSpace>.binaryOperation(operation, left, right)
}
public open class FunctionalExpressionField<T, A>(algebra: A) :
FunctionalExpressionRing<T, A>(algebra),
Field<Expression<T>> where A : Field<T>, A : NumericAlgebra<T> {
/**
* Builds an Expression of division an expression by another one.
*/
public override fun divide(a: Expression<T>, b: Expression<T>): Expression<T> =
binaryOperation(FieldOperations.DIV_OPERATION, a, b)
public operator fun Expression<T>.div(arg: T): Expression<T> = this / const(arg)
public operator fun T.div(arg: Expression<T>): Expression<T> = arg / this
public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
super<FunctionalExpressionRing>.unaryOperation(operation, arg)
public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
super<FunctionalExpressionRing>.binaryOperation(operation, left, right)
}
public open class FunctionalExpressionExtendedField<T, A>(algebra: A) :
FunctionalExpressionField<T, A>(algebra),
ExtendedField<Expression<T>> where A : ExtendedField<T>, A : NumericAlgebra<T> {
public override fun sin(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.SIN_OPERATION, arg)
public override fun cos(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.COS_OPERATION, arg)
public override fun asin(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.ASIN_OPERATION, arg)
public override fun acos(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.ACOS_OPERATION, arg)
public override fun atan(arg: Expression<T>): Expression<T> = unaryOperation(TrigonometricOperations.ATAN_OPERATION, arg)
public override fun power(arg: Expression<T>, pow: Number): Expression<T> =
binaryOperation(PowerOperations.POW_OPERATION, arg, number(pow))
public override fun exp(arg: Expression<T>): Expression<T> = unaryOperation(ExponentialOperations.EXP_OPERATION, arg)
public override fun ln(arg: Expression<T>): Expression<T> = unaryOperation(ExponentialOperations.LN_OPERATION, arg)
public override fun unaryOperation(operation: String, arg: Expression<T>): Expression<T> =
super<FunctionalExpressionField>.unaryOperation(operation, arg)
public override fun binaryOperation(operation: String, left: Expression<T>, right: Expression<T>): Expression<T> =
super<FunctionalExpressionField>.binaryOperation(operation, left, right)
}
public inline fun <T, A : Space<T>> A.expressionInSpace(block: FunctionalExpressionSpace<T, A>.() -> Expression<T>): Expression<T> =
FunctionalExpressionSpace(this).block()
public inline fun <T, A : Ring<T>> A.expressionInRing(block: FunctionalExpressionRing<T, A>.() -> Expression<T>): Expression<T> =
FunctionalExpressionRing(this).block()
public inline fun <T, A : Field<T>> A.expressionInField(block: FunctionalExpressionField<T, A>.() -> Expression<T>): Expression<T> =
FunctionalExpressionField(this).block()
public inline fun <T, A : ExtendedField<T>> A.expressionInExtendedField(block: FunctionalExpressionExtendedField<T, A>.() -> Expression<T>): Expression<T> =
FunctionalExpressionExtendedField(this).block()

18
kmath-core/src/commonMain/kotlin/scientifik/kmath/expressions/Builders.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/expressions/expressionBuilders.kt
View File

@ -1,16 +1,16 @@
package scientifik.kmath.expressions
package kscience.kmath.expressions
import scientifik.kmath.operations.ExtendedField
import scientifik.kmath.operations.Field
import scientifik.kmath.operations.Ring
import scientifik.kmath.operations.Space
import kscience.kmath.operations.ExtendedField
import kscience.kmath.operations.Field
import kscience.kmath.operations.Ring
import kscience.kmath.operations.Space
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
/**
* Creates a functional expression with this [Space].
*/
inline fun <T> Space<T>.spaceExpression(block: FunctionalExpressionSpace<T, Space<T>>.() -> Expression<T>): Expression<T> {
public inline fun <T> Space<T>.spaceExpression(block: FunctionalExpressionSpace<T, Space<T>>.() -> Expression<T>): Expression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return FunctionalExpressionSpace(this).block()
}
@ -18,7 +18,7 @@ inline fun <T> Space<T>.spaceExpression(block: FunctionalExpressionSpace<T, Spac
/**
* Creates a functional expression with this [Ring].
*/
inline fun <T> Ring<T>.ringExpression(block: FunctionalExpressionRing<T, Ring<T>>.() -> Expression<T>): Expression<T> {
public inline fun <T> Ring<T>.ringExpression(block: FunctionalExpressionRing<T, Ring<T>>.() -> Expression<T>): Expression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return FunctionalExpressionRing(this).block()
}
@ -26,7 +26,7 @@ inline fun <T> Ring<T>.ringExpression(block: FunctionalExpressionRing<T, Ring<T>
/**
* Creates a functional expression with this [Field].
*/
inline fun <T> Field<T>.fieldExpression(block: FunctionalExpressionField<T, Field<T>>.() -> Expression<T>): Expression<T> {
public inline fun <T> Field<T>.fieldExpression(block: FunctionalExpressionField<T, Field<T>>.() -> Expression<T>): Expression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return FunctionalExpressionField(this).block()
}
@ -34,7 +34,7 @@ inline fun <T> Field<T>.fieldExpression(block: FunctionalExpressionField<T, Fiel
/**
* Creates a functional expression with this [ExtendedField].
*/
inline fun <T> ExtendedField<T>.extendedFieldExpression(block: FunctionalExpressionExtendedField<T, ExtendedField<T>>.() -> Expression<T>): Expression<T> {
public inline fun <T> ExtendedField<T>.extendedFieldExpression(block: FunctionalExpressionExtendedField<T, ExtendedField<T>>.() -> Expression<T>): Expression<T> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return FunctionalExpressionExtendedField(this).block()
}

113
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/BufferMatrix.kt Normal file
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@ -0,0 +1,113 @@
package kscience.kmath.linear
import kscience.kmath.operations.RealField
import kscience.kmath.operations.Ring
import kscience.kmath.structures.*
/**
* Basic implementation of Matrix space based on [NDStructure]
*/
public class BufferMatrixContext<T : Any, R : Ring<T>>(
public override val elementContext: R,
private val bufferFactory: BufferFactory<T>
) : GenericMatrixContext<T, R> {
public override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): BufferMatrix<T> {
val buffer = bufferFactory(rows * columns) { offset -> initializer(offset / columns, offset % columns) }
return BufferMatrix(rows, columns, buffer)
}
public override fun point(size: Int, initializer: (Int) -> T): Point<T> = bufferFactory(size, initializer)
public companion object
}
@Suppress("OVERRIDE_BY_INLINE")
public object RealMatrixContext : GenericMatrixContext<Double, RealField> {
public override val elementContext: RealField
get() = RealField
public override inline fun produce(
rows: Int,
columns: Int,
initializer: (i: Int, j: Int) -> Double
): Matrix<Double> {
val buffer = RealBuffer(rows * columns) { offset -> initializer(offset / columns, offset % columns) }
return BufferMatrix(rows, columns, buffer)
}
public override inline fun point(size: Int, initializer: (Int) -> Double): Point<Double> =
RealBuffer(size, initializer)
}
public class BufferMatrix<T : Any>(
public override val rowNum: Int,
public override val colNum: Int,
public val buffer: Buffer<out T>,
public override val features: Set<MatrixFeature> = emptySet()
) : FeaturedMatrix<T> {
override val shape: IntArray
get() = intArrayOf(rowNum, colNum)
init {
require(buffer.size == rowNum * colNum) { "Dimension mismatch for matrix structure" }
}
public override fun suggestFeature(vararg features: MatrixFeature): BufferMatrix<T> =
BufferMatrix(rowNum, colNum, buffer, this.features + features)
public override operator fun get(index: IntArray): T = get(index[0], index[1])
public override operator fun get(i: Int, j: Int): T = buffer[i * colNum + j]
public override fun elements(): Sequence<Pair<IntArray, T>> = sequence {
for (i in 0 until rowNum) for (j in 0 until colNum) yield(intArrayOf(i, j) to get(i, j))
}
public override fun equals(other: Any?): Boolean {
if (this === other) return true
return when (other) {
is NDStructure<*> -> return NDStructure.equals(this, other)
else -> false
}
}
public override fun hashCode(): Int {
var result = buffer.hashCode()
result = 31 * result + features.hashCode()
return result
}
public override fun toString(): String {
return if (rowNum <= 5 && colNum <= 5)
"Matrix(rowsNum = $rowNum, colNum = $colNum, features=$features)\n" +
rows.asSequence().joinToString(prefix = "(", postfix = ")", separator = "\n ") { buffer ->
buffer.asSequence().joinToString(separator = "\t") { it.toString() }
}
else "Matrix(rowsNum = $rowNum, colNum = $colNum, features=$features)"
}
}
/**
* Optimized dot product for real matrices
*/
public infix fun BufferMatrix<Double>.dot(other: BufferMatrix<Double>): BufferMatrix<Double> {
require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
val array = DoubleArray(this.rowNum * other.colNum)
//convert to array to insure there is not memory indirection
fun Buffer<out Double>.unsafeArray() = if (this is RealBuffer)
array
else
DoubleArray(size) { get(it) }
val a = this.buffer.unsafeArray()
val b = other.buffer.unsafeArray()
for (i in (0 until rowNum))
for (j in (0 until other.colNum))
for (k in (0 until colNum))
array[i * other.colNum + j] += a[i * colNum + k] * b[k * other.colNum + j]
val buffer = RealBuffer(array)
return BufferMatrix(rowNum, other.colNum, buffer)
}

51
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/FeaturedMatrix.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/linear/FeaturedMatrix.kt
View File

@ -1,20 +1,17 @@
package scientifik.kmath.linear
package kscience.kmath.linear
import scientifik.kmath.operations.Ring
import scientifik.kmath.structures.Matrix
import scientifik.kmath.structures.Structure2D
import scientifik.kmath.structures.asBuffer
import kotlin.contracts.contract
import kscience.kmath.operations.Ring
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.Structure2D
import kscience.kmath.structures.asBuffer
import kotlin.math.sqrt
/**
* A 2d structure plus optional matrix-specific features
*/
interface FeaturedMatrix<T : Any> : Matrix<T> {
public interface FeaturedMatrix<T : Any> : Matrix<T> {
override val shape: IntArray get() = intArrayOf(rowNum, colNum)
val features: Set<MatrixFeature>
public val features: Set<MatrixFeature>
/**
* Suggest new feature for this matrix. The result is the new matrix that may or may not reuse existing data structure.
@ -22,44 +19,42 @@ interface FeaturedMatrix<T : Any> : Matrix<T> {
* The implementation does not guarantee to check that matrix actually have the feature, so one should be careful to
* add only those features that are valid.
*/
fun suggestFeature(vararg features: MatrixFeature): FeaturedMatrix<T>
public fun suggestFeature(vararg features: MatrixFeature): FeaturedMatrix<T>
companion object
public companion object
}
inline fun Structure2D.Companion.real(rows: Int, columns: Int, initializer: (Int, Int) -> Double): Matrix<Double> {
contract { callsInPlace(initializer) }
return MatrixContext.real.produce(rows, columns, initializer)
}
public inline fun Structure2D.Companion.real(rows: Int, columns: Int, initializer: (Int, Int) -> Double): Matrix<Double> =
MatrixContext.real.produce(rows, columns, initializer)
/**
* Build a square matrix from given elements.
*/
fun <T : Any> Structure2D.Companion.square(vararg elements: T): FeaturedMatrix<T> {
public fun <T : Any> Structure2D.Companion.square(vararg elements: T): FeaturedMatrix<T> {
val size: Int = sqrt(elements.size.toDouble()).toInt()
require(size * size == elements.size) { "The number of elements ${elements.size} is not a full square" }
val buffer = elements.asBuffer()
return BufferMatrix(size, size, buffer)
}
val Matrix<*>.features: Set<MatrixFeature> get() = (this as? FeaturedMatrix)?.features ?: emptySet()
public val Matrix<*>.features: Set<MatrixFeature> get() = (this as? FeaturedMatrix)?.features ?: emptySet()
/**
* Check if matrix has the given feature class
*/
inline fun <reified T : Any> Matrix<*>.hasFeature(): Boolean =
public inline fun <reified T : Any> Matrix<*>.hasFeature(): Boolean =
features.find { it is T } != null
/**
* Get the first feature matching given class. Does not guarantee that matrix has only one feature matching the criteria
*/
inline fun <reified T : Any> Matrix<*>.getFeature(): T? =
public inline fun <reified T : Any> Matrix<*>.getFeature(): T? =
features.filterIsInstance<T>().firstOrNull()
/**
* Diagonal matrix of ones. The matrix is virtual no actual matrix is created
*/
fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.one(rows: Int, columns: Int): FeaturedMatrix<T> =
public fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.one(rows: Int, columns: Int): FeaturedMatrix<T> =
VirtualMatrix(rows, columns, DiagonalFeature) { i, j ->
if (i == j) elementContext.one else elementContext.zero
}
@ -68,20 +63,20 @@ fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.one(rows: Int, columns: In
/**
* A virtual matrix of zeroes
*/
fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.zero(rows: Int, columns: Int): FeaturedMatrix<T> =
public fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.zero(rows: Int, columns: Int): FeaturedMatrix<T> =
VirtualMatrix(rows, columns) { _, _ -> elementContext.zero }
class TransposedFeature<T : Any>(val original: Matrix<T>) : MatrixFeature
public class TransposedFeature<T : Any>(public val original: Matrix<T>) : MatrixFeature
/**
* Create a virtual transposed matrix without copying anything. `A.transpose().transpose() === A`
*/
fun <T : Any> Matrix<T>.transpose(): Matrix<T> {
return this.getFeature<TransposedFeature<T>>()?.original ?: VirtualMatrix(
this.colNum,
this.rowNum,
public fun <T : Any> Matrix<T>.transpose(): Matrix<T> {
return getFeature<TransposedFeature<T>>()?.original ?: VirtualMatrix(
colNum,
rowNum,
setOf(TransposedFeature(this))
) { i, j -> get(j, i) }
}
infix fun Matrix<Double>.dot(other: Matrix<Double>): Matrix<Double> = with(MatrixContext.real) { dot(other) }
public infix fun Matrix<Double>.dot(other: Matrix<Double>): Matrix<Double> = with(MatrixContext.real) { dot(other) }

62
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/LUPDecomposition.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/linear/LUPDecomposition.kt
View File

@ -1,25 +1,25 @@
package scientifik.kmath.linear
package kscience.kmath.linear
import scientifik.kmath.operations.Field
import scientifik.kmath.operations.RealField
import scientifik.kmath.operations.Ring
import scientifik.kmath.operations.invoke
import scientifik.kmath.structures.BufferAccessor2D
import scientifik.kmath.structures.Matrix
import scientifik.kmath.structures.Structure2D
import kscience.kmath.operations.Field
import kscience.kmath.operations.RealField
import kscience.kmath.operations.Ring
import kscience.kmath.operations.invoke
import kscience.kmath.structures.BufferAccessor2D
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.Structure2D
import kotlin.reflect.KClass
/**
* Common implementation of [LUPDecompositionFeature]
*/
class LUPDecomposition<T : Any>(
val context: GenericMatrixContext<T, out Field<T>>,
val lu: Structure2D<T>,
val pivot: IntArray,
public class LUPDecomposition<T : Any>(
public val context: GenericMatrixContext<T, out Field<T>>,
public val lu: Structure2D<T>,
public val pivot: IntArray,
private val even: Boolean
) : LUPDecompositionFeature<T>, DeterminantFeature<T> {
val elementContext: Field<T> get() = context.elementContext
public val elementContext: Field<T>
get() = context.elementContext
/**
* Returns the matrix L of the decomposition.
@ -44,7 +44,6 @@ class LUPDecomposition<T : Any>(
if (j >= i) lu[i, j] else elementContext.zero
}
/**
* Returns the P rows permutation matrix.
*
@ -55,7 +54,6 @@ class LUPDecomposition<T : Any>(
if (j == pivot[i]) elementContext.one else elementContext.zero
}
/**
* Return the determinant of the matrix
* @return determinant of the matrix
@ -66,22 +64,18 @@ class LUPDecomposition<T : Any>(
}
fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.abs(value: T): T =
public fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.abs(value: T): T =
if (value > elementContext.zero) value else elementContext { -value }
/**
* Create a lup decomposition of generic matrix
*/
fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
public inline fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
type: KClass<T>,
matrix: Matrix<T>,
checkSingular: (T) -> Boolean
): LUPDecomposition<T> {
if (matrix.rowNum != matrix.colNum) {
error("LU decomposition supports only square matrices")
}
require(matrix.rowNum == matrix.colNum) { "LU decomposition supports only square matrices" }
val m = matrix.colNum
val pivot = IntArray(matrix.rowNum)
@ -154,15 +148,15 @@ fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
}
}
inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
matrix: Matrix<T>,
noinline checkSingular: (T) -> Boolean
checkSingular: (T) -> Boolean
): LUPDecomposition<T> = lup(T::class, matrix, checkSingular)
fun GenericMatrixContext<Double, RealField>.lup(matrix: Matrix<Double>): LUPDecomposition<Double> =
public fun GenericMatrixContext<Double, RealField>.lup(matrix: Matrix<Double>): LUPDecomposition<Double> =
lup(Double::class, matrix) { it < 1e-11 }
fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Matrix<T> {
public fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Matrix<T> {
require(matrix.rowNum == pivot.size) { "Matrix dimension mismatch. Expected ${pivot.size}, but got ${matrix.colNum}" }
BufferAccessor2D(type, matrix.rowNum, matrix.colNum).run {
@ -207,27 +201,27 @@ fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Mat
}
}
inline fun <reified T : Any> LUPDecomposition<T>.solve(matrix: Matrix<T>): Matrix<T> = solve(T::class, matrix)
public inline fun <reified T : Any> LUPDecomposition<T>.solve(matrix: Matrix<T>): Matrix<T> = solve(T::class, matrix)
/**
* Solve a linear equation **a*x = b**
*/
inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.solve(
public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.solve(
a: Matrix<T>,
b: Matrix<T>,
noinline checkSingular: (T) -> Boolean
checkSingular: (T) -> Boolean
): Matrix<T> {
// Use existing decomposition if it is provided by matrix
val decomposition = a.getFeature() ?: lup(T::class, a, checkSingular)
return decomposition.solve(T::class, b)
}
fun RealMatrixContext.solve(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> = solve(a, b) { it < 1e-11 }
public fun RealMatrixContext.solve(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> = solve(a, b) { it < 1e-11 }
inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.inverse(
public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.inverse(
matrix: Matrix<T>,
noinline checkSingular: (T) -> Boolean
checkSingular: (T) -> Boolean
): Matrix<T> = solve(matrix, one(matrix.rowNum, matrix.colNum), checkSingular)
fun RealMatrixContext.inverse(matrix: Matrix<Double>): Matrix<Double> =
public fun RealMatrixContext.inverse(matrix: Matrix<Double>): Matrix<Double> =
solve(matrix, one(matrix.rowNum, matrix.colNum)) { it < 1e-11 }

27
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/LinearAlgebra.kt Normal file
View File

@ -0,0 +1,27 @@
package kscience.kmath.linear
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.VirtualBuffer
public typealias Point<T> = Buffer<T>
/**
* A group of methods to resolve equation A dot X = B, where A and B are matrices or vectors
*/
public interface LinearSolver<T : Any> {
public fun solve(a: Matrix<T>, b: Matrix<T>): Matrix<T>
public fun solve(a: Matrix<T>, b: Point<T>): Point<T> = solve(a, b.asMatrix()).asPoint()
public fun inverse(a: Matrix<T>): Matrix<T>
}
/**
* Convert matrix to vector if it is possible
*/
public fun <T : Any> Matrix<T>.asPoint(): Point<T> =
if (this.colNum == 1)
VirtualBuffer(rowNum) { get(it, 0) }
else
error("Can't convert matrix with more than one column to vector")
public fun <T : Any> Point<T>.asMatrix(): VirtualMatrix<T> = VirtualMatrix(size, 1) { i, _ -> get(i) }

24
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/MatrixBuilder.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixBuilder.kt
View File

@ -1,12 +1,12 @@
package scientifik.kmath.linear
package kscience.kmath.linear
import scientifik.kmath.structures.Buffer
import scientifik.kmath.structures.BufferFactory
import scientifik.kmath.structures.Structure2D
import scientifik.kmath.structures.asBuffer
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.BufferFactory
import kscience.kmath.structures.Structure2D
import kscience.kmath.structures.asBuffer
class MatrixBuilder(val rows: Int, val columns: Int) {
operator fun <T : Any> invoke(vararg elements: T): FeaturedMatrix<T> {
public class MatrixBuilder(public val rows: Int, public val columns: Int) {
public operator fun <T : Any> invoke(vararg elements: T): FeaturedMatrix<T> {
require(rows * columns == elements.size) { "The number of elements ${elements.size} is not equal $rows * $columns" }
val buffer = elements.asBuffer()
return BufferMatrix(rows, columns, buffer)
@ -15,14 +15,14 @@ class MatrixBuilder(val rows: Int, val columns: Int) {
//TODO add specific matrix builder functions like diagonal, etc
}
fun Structure2D.Companion.build(rows: Int, columns: Int): MatrixBuilder = MatrixBuilder(rows, columns)
public fun Structure2D.Companion.build(rows: Int, columns: Int): MatrixBuilder = MatrixBuilder(rows, columns)
fun <T : Any> Structure2D.Companion.row(vararg values: T): FeaturedMatrix<T> {
public fun <T : Any> Structure2D.Companion.row(vararg values: T): FeaturedMatrix<T> {
val buffer = values.asBuffer()
return BufferMatrix(1, values.size, buffer)
}
inline fun <reified T : Any> Structure2D.Companion.row(
public inline fun <reified T : Any> Structure2D.Companion.row(
size: Int,
factory: BufferFactory<T> = Buffer.Companion::auto,
noinline builder: (Int) -> T
@ -31,12 +31,12 @@ inline fun <reified T : Any> Structure2D.Companion.row(
return BufferMatrix(1, size, buffer)
}
fun <T : Any> Structure2D.Companion.column(vararg values: T): FeaturedMatrix<T> {
public fun <T : Any> Structure2D.Companion.column(vararg values: T): FeaturedMatrix<T> {
val buffer = values.asBuffer()
return BufferMatrix(values.size, 1, buffer)
}
inline fun <reified T : Any> Structure2D.Companion.column(
public inline fun <reified T : Any> Structure2D.Companion.column(
size: Int,
factory: BufferFactory<T> = Buffer.Companion::auto,
noinline builder: (Int) -> T

47
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/MatrixContext.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixContext.kt
View File

@ -1,41 +1,42 @@
package scientifik.kmath.linear
package kscience.kmath.linear
import scientifik.kmath.operations.Ring
import scientifik.kmath.operations.SpaceOperations
import scientifik.kmath.operations.invoke
import scientifik.kmath.operations.sum
import scientifik.kmath.structures.Buffer
import scientifik.kmath.structures.BufferFactory
import scientifik.kmath.structures.Matrix
import scientifik.kmath.structures.asSequence
import kscience.kmath.operations.Ring
import kscience.kmath.operations.SpaceOperations
import kscience.kmath.operations.invoke
import kscience.kmath.operations.sum
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.BufferFactory
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.asSequence
/**
* Basic operations on matrices. Operates on [Matrix]
*/
interface MatrixContext<T : Any> : SpaceOperations<Matrix<T>> {
public interface MatrixContext<T : Any> : SpaceOperations<Matrix<T>> {
/**
* Produce a matrix with this context and given dimensions
*/
fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): Matrix<T>
public fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): Matrix<T>
infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T>
public infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T>
infix fun Matrix<T>.dot(vector: Point<T>): Point<T>
public infix fun Matrix<T>.dot(vector: Point<T>): Point<T>
operator fun Matrix<T>.times(value: T): Matrix<T>
public operator fun Matrix<T>.times(value: T): Matrix<T>
operator fun T.times(m: Matrix<T>): Matrix<T> = m * this
public operator fun T.times(m: Matrix<T>): Matrix<T> = m * this
companion object {
public companion object {
/**
* Non-boxing double matrix
*/
val real: RealMatrixContext = RealMatrixContext
public val real: RealMatrixContext
get() = RealMatrixContext
/**
* A structured matrix with custom buffer
*/
fun <T : Any, R : Ring<T>> buffered(
public fun <T : Any, R : Ring<T>> buffered(
ring: R,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing
): GenericMatrixContext<T, R> = BufferMatrixContext(ring, bufferFactory)
@ -43,21 +44,21 @@ interface MatrixContext<T : Any> : SpaceOperations<Matrix<T>> {
/**
* Automatic buffered matrix, unboxed if it is possible
*/
inline fun <reified T : Any, R : Ring<T>> auto(ring: R): GenericMatrixContext<T, R> =
public inline fun <reified T : Any, R : Ring<T>> auto(ring: R): GenericMatrixContext<T, R> =
buffered(ring, Buffer.Companion::auto)
}
}
interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
public interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
/**
* The ring context for matrix elements
*/
val elementContext: R
public val elementContext: R
/**
* Produce a point compatible with matrix space
*/
fun point(size: Int, initializer: (Int) -> T): Point<T>
public fun point(size: Int, initializer: (Int) -> T): Point<T>
override infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T> {
//TODO add typed error
@ -102,7 +103,7 @@ interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
override fun multiply(a: Matrix<T>, k: Number): Matrix<T> =
produce(a.rowNum, a.colNum) { i, j -> elementContext { a[i, j] * k } }
operator fun Number.times(matrix: FeaturedMatrix<T>): Matrix<T> = matrix * this
public operator fun Number.times(matrix: FeaturedMatrix<T>): Matrix<T> = matrix * this
override operator fun Matrix<T>.times(value: T): Matrix<T> =
produce(rowNum, colNum) { i, j -> elementContext { get(i, j) * value } }

62
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixFeatures.kt Normal file
View File

@ -0,0 +1,62 @@
package kscience.kmath.linear
/**
* A marker interface representing some matrix feature like diagonal, sparse, zero, etc. Features used to optimize matrix
* operations performance in some cases.
*/
public interface MatrixFeature
/**
* The matrix with this feature is considered to have only diagonal non-null elements
*/
public object DiagonalFeature : MatrixFeature
/**
* Matrix with this feature has all zero elements
*/
public object ZeroFeature : MatrixFeature
/**
* Matrix with this feature have unit elements on diagonal and zero elements in all other places
*/
public object UnitFeature : MatrixFeature
/**
* Inverted matrix feature
*/
public interface InverseMatrixFeature<T : Any> : MatrixFeature {
public val inverse: FeaturedMatrix<T>
}
/**
* A determinant container
*/
public interface DeterminantFeature<T : Any> : MatrixFeature {
public val determinant: T
}
@Suppress("FunctionName")
public fun <T : Any> DeterminantFeature(determinant: T): DeterminantFeature<T> = object : DeterminantFeature<T> {
override val determinant: T = determinant
}
/**
* Lower triangular matrix
*/
public object LFeature : MatrixFeature
/**
* Upper triangular feature
*/
public object UFeature : MatrixFeature
/**
* TODO add documentation
*/
public interface LUPDecompositionFeature<T : Any> : MatrixFeature {
public val l: FeaturedMatrix<T>
public val u: FeaturedMatrix<T>
public val p: FeaturedMatrix<T>
}
//TODO add sparse matrix feature

32
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/VectorSpace.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/linear/VectorSpace.kt
View File

@ -1,21 +1,21 @@
package scientifik.kmath.linear
package kscience.kmath.linear
import scientifik.kmath.operations.RealField
import scientifik.kmath.operations.Space
import scientifik.kmath.operations.invoke
import scientifik.kmath.structures.Buffer
import scientifik.kmath.structures.BufferFactory
import kscience.kmath.operations.RealField
import kscience.kmath.operations.Space
import kscience.kmath.operations.invoke
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.BufferFactory
/**
* A linear space for vectors.
* Could be used on any point-like structure
*/
interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
val size: Int
val space: S
public interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
public val size: Int
public val space: S
override val zero: Point<T> get() = produce { space.zero }
fun produce(initializer: (Int) -> T): Point<T>
public fun produce(initializer: (Int) -> T): Point<T>
/**
* Produce a space-element of this vector space for expressions
@ -28,13 +28,13 @@ interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
//TODO add basis
companion object {
public companion object {
private val realSpaceCache: MutableMap<Int, BufferVectorSpace<Double, RealField>> = hashMapOf()
/**
* Non-boxing double vector space
*/
fun real(size: Int): BufferVectorSpace<Double, RealField> = realSpaceCache.getOrPut(size) {
public fun real(size: Int): BufferVectorSpace<Double, RealField> = realSpaceCache.getOrPut(size) {
BufferVectorSpace(
size,
RealField,
@ -45,7 +45,7 @@ interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
/**
* A structured vector space with custom buffer
*/
fun <T : Any, S : Space<T>> buffered(
public fun <T : Any, S : Space<T>> buffered(
size: Int,
space: S,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing
@ -54,16 +54,16 @@ interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
/**
* Automatic buffered vector, unboxed if it is possible
*/
inline fun <reified T : Any, S : Space<T>> auto(size: Int, space: S): VectorSpace<T, S> =
public inline fun <reified T : Any, S : Space<T>> auto(size: Int, space: S): VectorSpace<T, S> =
buffered(size, space, Buffer.Companion::auto)
}
}
class BufferVectorSpace<T : Any, S : Space<T>>(
public class BufferVectorSpace<T : Any, S : Space<T>>(
override val size: Int,
override val space: S,
val bufferFactory: BufferFactory<T>
public val bufferFactory: BufferFactory<T>
) : VectorSpace<T, S> {
override fun produce(initializer: (Int) -> T): Buffer<T> = bufferFactory(size, initializer)
//override fun produceElement(initializer: (Int) -> T): Vector<T, S> = BufferVector(this, produce(initializer))

29
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/VirtualMatrix.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/linear/VirtualMatrix.kt
View File

@ -1,15 +1,19 @@
package scientifik.kmath.linear
package kscience.kmath.linear
import scientifik.kmath.structures.Matrix
import kscience.kmath.structures.Matrix
class VirtualMatrix<T : Any>(
public class VirtualMatrix<T : Any>(
override val rowNum: Int,
override val colNum: Int,
override val features: Set<MatrixFeature> = emptySet(),
val generator: (i: Int, j: Int) -> T
public val generator: (i: Int, j: Int) -> T
) : FeaturedMatrix<T> {
constructor(rowNum: Int, colNum: Int, vararg features: MatrixFeature, generator: (i: Int, j: Int) -> T) : this(
public constructor(
rowNum: Int,
colNum: Int,
vararg features: MatrixFeature,
generator: (i: Int, j: Int) -> T
) : this(
rowNum,
colNum,
setOf(*features),
@ -42,18 +46,15 @@ class VirtualMatrix<T : Any>(
}
companion object {
public companion object {
/**
* Wrap a matrix adding additional features to it
*/
fun <T : Any> wrap(matrix: Matrix<T>, vararg features: MatrixFeature): FeaturedMatrix<T> {
return if (matrix is VirtualMatrix) {
public fun <T : Any> wrap(matrix: Matrix<T>, vararg features: MatrixFeature): FeaturedMatrix<T> {
return if (matrix is VirtualMatrix)
VirtualMatrix(matrix.rowNum, matrix.colNum, matrix.features + features, matrix.generator)
} else {
VirtualMatrix(matrix.rowNum, matrix.colNum, matrix.features + features) { i, j ->
matrix[i, j]
}
}
else
VirtualMatrix(matrix.rowNum, matrix.colNum, matrix.features + features) { i, j -> matrix[i, j] }
}
}
}

100
kmath-core/src/commonMain/kotlin/scientifik/kmath/misc/AutoDiff.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/misc/AutoDiff.kt
View File

@ -1,11 +1,11 @@
package scientifik.kmath.misc
package kscience.kmath.misc
import scientifik.kmath.linear.Point
import scientifik.kmath.operations.ExtendedField
import scientifik.kmath.operations.Field
import scientifik.kmath.operations.invoke
import scientifik.kmath.operations.sum
import scientifik.kmath.structures.asBuffer
import kscience.kmath.linear.Point
import kscience.kmath.operations.ExtendedField
import kscience.kmath.operations.Field
import kscience.kmath.operations.invoke
import kscience.kmath.operations.sum
import kscience.kmath.structures.asBuffer
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@ -18,24 +18,24 @@ import kotlin.contracts.contract
* Differentiable variable with value and derivative of differentiation ([deriv]) result
* with respect to this variable.
*/
open class Variable<T : Any>(val value: T)
public open class Variable<T : Any>(public val value: T)
class DerivationResult<T : Any>(
public class DerivationResult<T : Any>(
value: T,
val deriv: Map<Variable<T>, T>,
val context: Field<T>
public val deriv: Map<Variable<T>, T>,
public val context: Field<T>
) : Variable<T>(value) {
fun deriv(variable: Variable<T>): T = deriv[variable] ?: context.zero
public fun deriv(variable: Variable<T>): T = deriv[variable] ?: context.zero
/**
* compute divergence
*/
fun div(): T = context { sum(deriv.values) }
public fun div(): T = context { sum(deriv.values) }
/**
* Compute a gradient for variables in given order
*/
fun grad(vararg variables: Variable<T>): Point<T> {
public fun grad(vararg variables: Variable<T>): Point<T> {
check(variables.isNotEmpty()) { "Variable order is not provided for gradient construction" }
return variables.map(::deriv).asBuffer()
}
@ -54,7 +54,7 @@ class DerivationResult<T : Any>(
* assertEquals(9.0, x.d) // dy/dx
* ```
*/
inline fun <T : Any, F : Field<T>> F.deriv(body: AutoDiffField<T, F>.() -> Variable<T>): DerivationResult<T> {
public inline fun <T : Any, F : Field<T>> F.deriv(body: AutoDiffField<T, F>.() -> Variable<T>): DerivationResult<T> {
contract { callsInPlace(body, InvocationKind.EXACTLY_ONCE) }
return (AutoDiffContext(this)) {
@ -65,15 +65,14 @@ inline fun <T : Any, F : Field<T>> F.deriv(body: AutoDiffField<T, F>.() -> Varia
}
}
abstract class AutoDiffField<T : Any, F : Field<T>> : Field<Variable<T>> {
abstract val context: F
public abstract class AutoDiffField<T : Any, F : Field<T>> : Field<Variable<T>> {
public abstract val context: F
/**
* A variable accessing inner state of derivatives.
* Use this function in inner builders to avoid creating additional derivative bindings
*/
abstract var Variable<T>.d: T
public abstract var Variable<T>.d: T
/**
* Performs update of derivative after the rest of the formula in the back-pass.
@ -86,11 +85,11 @@ abstract class AutoDiffField<T : Any, F : Field<T>> : Field<Variable<T>> {
* }
* ```
*/
abstract fun <R> derive(value: R, block: F.(R) -> Unit): R
public abstract fun <R> derive(value: R, block: F.(R) -> Unit): R
abstract fun variable(value: T): Variable<T>
public abstract fun variable(value: T): Variable<T>
inline fun variable(block: F.() -> T): Variable<T> = variable(context.block())
public inline fun variable(block: F.() -> T): Variable<T> = variable(context.block())
// Overloads for Double constants
@ -152,7 +151,6 @@ internal class AutoDiffContext<T : Any, F : Field<T>>(override val context: F) :
// Basic math (+, -, *, /)
override fun add(a: Variable<T>, b: Variable<T>): Variable<T> = derive(variable { a.value + b.value }) { z ->
a.d += z.d
b.d += z.d
@ -176,35 +174,73 @@ internal class AutoDiffContext<T : Any, F : Field<T>>(override val context: F) :
// Extensions for differentiation of various basic mathematical functions
// x ^ 2
fun <T : Any, F : Field<T>> AutoDiffField<T, F>.sqr(x: Variable<T>): Variable<T> =
public fun <T : Any, F : Field<T>> AutoDiffField<T, F>.sqr(x: Variable<T>): Variable<T> =
derive(variable { x.value * x.value }) { z -> x.d += z.d * 2 * x.value }
// x ^ 1/2
fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sqrt(x: Variable<T>): Variable<T> =
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sqrt(x: Variable<T>): Variable<T> =
derive(variable { sqrt(x.value) }) { z -> x.d += z.d * 0.5 / z.value }
// x ^ y (const)
fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Double): Variable<T> =
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Double): Variable<T> =
derive(variable { power(x.value, y) }) { z -> x.d += z.d * y * power(x.value, y - 1) }
fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Int): Variable<T> = pow(x, y.toDouble())
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Int): Variable<T> =
pow(x, y.toDouble())
// exp(x)
fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.exp(x: Variable<T>): Variable<T> =
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.exp(x: Variable<T>): Variable<T> =
derive(variable { exp(x.value) }) { z -> x.d += z.d * z.value }
// ln(x)
fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.ln(x: Variable<T>): Variable<T> =
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.ln(x: Variable<T>): Variable<T> =
derive(variable { ln(x.value) }) { z -> x.d += z.d / x.value }
// x ^ y (any)
fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Variable<T>): Variable<T> =
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.pow(x: Variable<T>, y: Variable<T>): Variable<T> =
exp(y * ln(x))
// sin(x)
fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sin(x: Variable<T>): Variable<T> =
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sin(x: Variable<T>): Variable<T> =
derive(variable { sin(x.value) }) { z -> x.d += z.d * cos(x.value) }
// cos(x)
fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.cos(x: Variable<T>): Variable<T> =
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.cos(x: Variable<T>): Variable<T> =
derive(variable { cos(x.value) }) { z -> x.d -= z.d * sin(x.value) }
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.tan(x: Variable<T>): Variable<T> =
derive(variable { tan(x.value) }) { z ->
val c = cos(x.value)
x.d += z.d / (c * c)
}
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.asin(x: Variable<T>): Variable<T> =
derive(variable { asin(x.value) }) { z -> x.d += z.d / sqrt(one - x.value * x.value) }
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.acos(x: Variable<T>): Variable<T> =
derive(variable { acos(x.value) }) { z -> x.d -= z.d / sqrt(one - x.value * x.value) }
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.atan(x: Variable<T>): Variable<T> =
derive(variable { atan(x.value) }) { z -> x.d += z.d / (one + x.value * x.value) }
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.sinh(x: Variable<T>): Variable<T> =
derive(variable { sin(x.value) }) { z -> x.d += z.d * cosh(x.value) }
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.cosh(x: Variable<T>): Variable<T> =
derive(variable { cos(x.value) }) { z -> x.d += z.d * sinh(x.value) }
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.tanh(x: Variable<T>): Variable<T> =
derive(variable { tan(x.value) }) { z ->
val c = cosh(x.value)
x.d += z.d / (c * c)
}
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.asinh(x: Variable<T>): Variable<T> =
derive(variable { asinh(x.value) }) { z -> x.d += z.d / sqrt(one + x.value * x.value) }
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.acosh(x: Variable<T>): Variable<T> =
derive(variable { acosh(x.value) }) { z -> x.d += z.d / (sqrt((x.value - one) * (x.value + one))) }
public fun <T : Any, F : ExtendedField<T>> AutoDiffField<T, F>.atanh(x: Variable<T>): Variable<T> =
derive(variable { atanh(x.value) }) { z -> x.d += z.d / (one - x.value * x.value) }

12
kmath-core/src/commonMain/kotlin/scientifik/kmath/misc/Grids.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/misc/Grids.kt
View File

@ -1,4 +1,4 @@
package scientifik.kmath.misc
package kscience.kmath.misc
import kotlin.math.abs
@ -10,17 +10,21 @@ import kotlin.math.abs
*
* If step is negative, the same goes from upper boundary downwards
*/
fun ClosedFloatingPointRange<Double>.toSequenceWithStep(step: Double): Sequence<Double> = when {
public fun ClosedFloatingPointRange<Double>.toSequenceWithStep(step: Double): Sequence<Double> = when {
step == 0.0 -> error("Zero step in double progression")
step > 0 -> sequence {
var current = start
while (current <= endInclusive) {
yield(current)
current += step
}
}
else -> sequence {
var current = endInclusive
while (current >= start) {
yield(current)
current += step
@ -31,7 +35,7 @@ fun ClosedFloatingPointRange<Double>.toSequenceWithStep(step: Double): Sequence<
/**
* Convert double range to sequence with the fixed number of points
*/
fun ClosedFloatingPointRange<Double>.toSequenceWithPoints(numPoints: Int): Sequence<Double> {
public fun ClosedFloatingPointRange<Double>.toSequenceWithPoints(numPoints: Int): Sequence<Double> {
require(numPoints > 1) { "The number of points should be more than 2" }
return toSequenceWithStep(abs(endInclusive - start) / (numPoints - 1))
}
@ -40,7 +44,7 @@ fun ClosedFloatingPointRange<Double>.toSequenceWithPoints(numPoints: Int): Seque
* Convert double range to array of evenly spaced doubles, where the size of array equals [numPoints]
*/
@Deprecated("Replace by 'toSequenceWithPoints'")
fun ClosedFloatingPointRange<Double>.toGrid(numPoints: Int): DoubleArray {
public fun ClosedFloatingPointRange<Double>.toGrid(numPoints: Int): DoubleArray {
require(numPoints >= 2) { "Can't create generic grid with less than two points" }
return DoubleArray(numPoints) { i -> start + (endInclusive - start) / (numPoints - 1) * i }
}

74
kmath-core/src/commonMain/kotlin/kscience/kmath/misc/cumulative.kt Normal file
View File

@ -0,0 +1,74 @@
package kscience.kmath.misc
import kscience.kmath.operations.Space
import kscience.kmath.operations.invoke
import kotlin.jvm.JvmName
/**
* Generic cumulative operation on iterator.
*
* @param T the type of initial iterable.
* @param R the type of resulting iterable.
* @param initial lazy evaluated.
*/
public inline fun <T, R> Iterator<T>.cumulative(initial: R, crossinline operation: (R, T) -> R): Iterator<R> =
object : Iterator<R> {
var state: R = initial
override fun hasNext(): Boolean = this@cumulative.hasNext()
override fun next(): R {
state = operation(state, this@cumulative.next())
return state
}
}
public inline fun <T, R> Iterable<T>.cumulative(initial: R, crossinline operation: (R, T) -> R): Iterable<R> =
Iterable { this@cumulative.iterator().cumulative(initial, operation) }
public inline fun <T, R> Sequence<T>.cumulative(initial: R, crossinline operation: (R, T) -> R): Sequence<R> =
Sequence { this@cumulative.iterator().cumulative(initial, operation) }
public fun <T, R> List<T>.cumulative(initial: R, operation: (R, T) -> R): List<R> =
iterator().cumulative(initial, operation).asSequence().toList()
//Cumulative sum
/**
* Cumulative sum with custom space
*/
public fun <T> Iterable<T>.cumulativeSum(space: Space<T>): Iterable<T> =
space { cumulative(zero) { element: T, sum: T -> sum + element } }
@JvmName("cumulativeSumOfDouble")
public fun Iterable<Double>.cumulativeSum(): Iterable<Double> = cumulative(0.0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfInt")
public fun Iterable<Int>.cumulativeSum(): Iterable<Int> = cumulative(0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfLong")
public fun Iterable<Long>.cumulativeSum(): Iterable<Long> = cumulative(0L) { element, sum -> sum + element }
public fun <T> Sequence<T>.cumulativeSum(space: Space<T>): Sequence<T> =
space { cumulative(zero) { element: T, sum: T -> sum + element } }
@JvmName("cumulativeSumOfDouble")
public fun Sequence<Double>.cumulativeSum(): Sequence<Double> = cumulative(0.0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfInt")
public fun Sequence<Int>.cumulativeSum(): Sequence<Int> = cumulative(0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfLong")
public fun Sequence<Long>.cumulativeSum(): Sequence<Long> = cumulative(0L) { element, sum -> sum + element }
public fun <T> List<T>.cumulativeSum(space: Space<T>): List<T> =
space { cumulative(zero) { element: T, sum: T -> sum + element } }
@JvmName("cumulativeSumOfDouble")
public fun List<Double>.cumulativeSum(): List<Double> = cumulative(0.0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfInt")
public fun List<Int>.cumulativeSum(): List<Int> = cumulative(0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfLong")
public fun List<Long>.cumulativeSum(): List<Long> = cumulative(0L) { element, sum -> sum + element }

91
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/Algebra.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt
View File

@ -1,31 +1,31 @@
package scientifik.kmath.operations
package kscience.kmath.operations
/**
* Stub for DSL the [Algebra] is.
*/
@DslMarker
annotation class KMathContext
public annotation class KMathContext
/**
* Represents an algebraic structure.
*
* @param T the type of element of this structure.
*/
interface Algebra<T> {
public interface Algebra<T> {
/**
* Wrap raw string or variable
*/
fun symbol(value: String): T = error("Wrapping of '$value' is not supported in $this")
public fun symbol(value: String): T = error("Wrapping of '$value' is not supported in $this")
/**
* Dynamic call of unary operation with name [operation] on [arg]
*/
fun unaryOperation(operation: String, arg: T): T
public fun unaryOperation(operation: String, arg: T): T
/**
* Dynamic call of binary operation [operation] on [left] and [right]
*/
fun binaryOperation(operation: String, left: T, right: T): T
public fun binaryOperation(operation: String, left: T, right: T): T
}
/**
@ -33,29 +33,30 @@ interface Algebra<T> {
*
* @param T the type of element of this structure.
*/
interface NumericAlgebra<T> : Algebra<T> {
public interface NumericAlgebra<T> : Algebra<T> {
/**
* Wraps a number.
*/
fun number(value: Number): T
public fun number(value: Number): T
/**
* Dynamic call of binary operation [operation] on [left] and [right] where left element is [Number].
*/
fun leftSideNumberOperation(operation: String, left: Number, right: T): T =
public fun leftSideNumberOperation(operation: String, left: Number, right: T): T =
binaryOperation(operation, number(left), right)
/**
* Dynamic call of binary operation [operation] on [left] and [right] where right element is [Number].
*/
fun rightSideNumberOperation(operation: String, left: T, right: Number): T =
public fun rightSideNumberOperation(operation: String, left: T, right: Number): T =
leftSideNumberOperation(operation, right, left)
}
/**
* Call a block with an [Algebra] as receiver.
*/
inline operator fun <A : Algebra<*>, R> A.invoke(block: A.() -> R): R = run(block)
// TODO add contract when KT-32313 is fixed
public inline operator fun <A : Algebra<*>, R> A.invoke(block: A.() -> R): R = block()
/**
* Represents "semispace", i.e. algebraic structure with associative binary operation called "addition" as well as
@ -63,7 +64,7 @@ inline operator fun <A : Algebra<*>, R> A.invoke(block: A.() -> R): R = run(bloc
*
* @param T the type of element of this semispace.
*/
interface SpaceOperations<T> : Algebra<T> {
public interface SpaceOperations<T> : Algebra<T> {
/**
* Addition of two elements.
*
@ -71,7 +72,7 @@ interface SpaceOperations<T> : Algebra<T> {
* @param b the augend.
* @return the sum.
*/
fun add(a: T, b: T): T
public fun add(a: T, b: T): T
/**
* Multiplication of element by scalar.
@ -80,7 +81,7 @@ interface SpaceOperations<T> : Algebra<T> {
* @param k the multiplicand.
* @return the produce.
*/
fun multiply(a: T, k: Number): T
public fun multiply(a: T, k: Number): T
// Operations to be performed in this context. Could be moved to extensions in case of KEEP-176
@ -90,7 +91,7 @@ interface SpaceOperations<T> : Algebra<T> {
* @receiver this value.
* @return the additive inverse of this value.
*/
operator fun T.unaryMinus(): T = multiply(this, -1.0)
public operator fun T.unaryMinus(): T = multiply(this, -1.0)
/**
* Returns this value.
@ -98,7 +99,7 @@ interface SpaceOperations<T> : Algebra<T> {
* @receiver this value.
* @return this value.
*/
operator fun T.unaryPlus(): T = this
public operator fun T.unaryPlus(): T = this
/**
* Addition of two elements.
@ -107,7 +108,7 @@ interface SpaceOperations<T> : Algebra<T> {
* @param b the augend.
* @return the sum.
*/
operator fun T.plus(b: T): T = add(this, b)
public operator fun T.plus(b: T): T = add(this, b)
/**
* Subtraction of two elements.
@ -116,7 +117,7 @@ interface SpaceOperations<T> : Algebra<T> {
* @param b the subtrahend.
* @return the difference.
*/
operator fun T.minus(b: T): T = add(this, -b)
public operator fun T.minus(b: T): T = add(this, -b)
/**
* Multiplication of this element by a scalar.
@ -125,7 +126,7 @@ interface SpaceOperations<T> : Algebra<T> {
* @param k the multiplicand.
* @return the product.
*/
operator fun T.times(k: Number): T = multiply(this, k.toDouble())
public operator fun T.times(k: Number): T = multiply(this, k.toDouble())
/**
* Division of this element by scalar.
@ -134,7 +135,7 @@ interface SpaceOperations<T> : Algebra<T> {
* @param k the divisor.
* @return the quotient.
*/
operator fun T.div(k: Number): T = multiply(this, 1.0 / k.toDouble())
public operator fun T.div(k: Number): T = multiply(this, 1.0 / k.toDouble())
/**
* Multiplication of this number by element.
@ -143,7 +144,7 @@ interface SpaceOperations<T> : Algebra<T> {
* @param b the multiplicand.
* @return the product.
*/
operator fun Number.times(b: T): T = b * this
public operator fun Number.times(b: T): T = b * this
override fun unaryOperation(operation: String, arg: T): T = when (operation) {
PLUS_OPERATION -> arg
@ -157,18 +158,16 @@ interface SpaceOperations<T> : Algebra<T> {
else -> error("Binary operation $operation not defined in $this")
}
companion object {
public companion object {
/**
* The identifier of addition.
*/
const val PLUS_OPERATION: String = "+"
public const val PLUS_OPERATION: String = "+"
/**
* The identifier of subtraction (and negation).
*/
const val MINUS_OPERATION: String = "-"
const val NOT_OPERATION: String = "!"
public const val MINUS_OPERATION: String = "-"
}
}
@ -178,11 +177,11 @@ interface SpaceOperations<T> : Algebra<T> {
*
* @param T the type of element of this group.
*/
interface Space<T> : SpaceOperations<T> {
public interface Space<T> : SpaceOperations<T> {
/**
* The neutral element of addition.
*/
val zero: T
public val zero: T
}
/**
@ -191,14 +190,14 @@ interface Space<T> : SpaceOperations<T> {
*
* @param T the type of element of this semiring.
*/
interface RingOperations<T> : SpaceOperations<T> {
public interface RingOperations<T> : SpaceOperations<T> {
/**
* Multiplies two elements.
*
* @param a the multiplier.
* @param b the multiplicand.
*/
fun multiply(a: T, b: T): T
public fun multiply(a: T, b: T): T
/**
* Multiplies this element by scalar.
@ -206,18 +205,18 @@ interface RingOperations<T> : SpaceOperations<T> {
* @receiver the multiplier.
* @param b the multiplicand.
*/
operator fun T.times(b: T): T = multiply(this, b)
public operator fun T.times(b: T): T = multiply(this, b)
override fun binaryOperation(operation: String, left: T, right: T): T = when (operation) {
TIMES_OPERATION -> multiply(left, right)
else -> super.binaryOperation(operation, left, right)
}
companion object {
public companion object {
/**
* The identifier of multiplication.
*/
const val TIMES_OPERATION: String = "*"
public const val TIMES_OPERATION: String = "*"
}
}
@ -227,11 +226,11 @@ interface RingOperations<T> : SpaceOperations<T> {
*
* @param T the type of element of this ring.
*/
interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
public interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
/**
* neutral operation for multiplication
*/
val one: T
public val one: T
override fun number(value: Number): T = one * value.toDouble()
@ -255,7 +254,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
* @receiver the addend.
* @param b the augend.
*/
operator fun T.plus(b: Number): T = this + number(b)
public operator fun T.plus(b: Number): T = this + number(b)
/**
* Addition of scalar and element.
@ -263,7 +262,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
* @receiver the addend.
* @param b the augend.
*/
operator fun Number.plus(b: T): T = b + this
public operator fun Number.plus(b: T): T = b + this
/**
* Subtraction of element from number.
@ -272,7 +271,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
* @param b the subtrahend.
* @receiver the difference.
*/
operator fun T.minus(b: Number): T = this - number(b)
public operator fun T.minus(b: Number): T = this - number(b)
/**
* Subtraction of number from element.
@ -281,7 +280,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
* @param b the subtrahend.
* @receiver the difference.
*/
operator fun Number.minus(b: T): T = -b + this
public operator fun Number.minus(b: T): T = -b + this
}
/**
@ -290,7 +289,7 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
*
* @param T the type of element of this semifield.
*/
interface FieldOperations<T> : RingOperations<T> {
public interface FieldOperations<T> : RingOperations<T> {
/**
* Division of two elements.
*
@ -298,7 +297,7 @@ interface FieldOperations<T> : RingOperations<T> {
* @param b the divisor.
* @return the quotient.
*/
fun divide(a: T, b: T): T
public fun divide(a: T, b: T): T
/**
* Division of two elements.
@ -307,18 +306,18 @@ interface FieldOperations<T> : RingOperations<T> {
* @param b the divisor.
* @return the quotient.
*/
operator fun T.div(b: T): T = divide(this, b)
public operator fun T.div(b: T): T = divide(this, b)
override fun binaryOperation(operation: String, left: T, right: T): T = when (operation) {
DIV_OPERATION -> divide(left, right)
else -> super.binaryOperation(operation, left, right)
}
companion object {
public companion object {
/**
* The identifier of division.
*/
const val DIV_OPERATION: String = "/"
public const val DIV_OPERATION: String = "/"
}
}
@ -328,7 +327,7 @@ interface FieldOperations<T> : RingOperations<T> {
*
* @param T the type of element of this semifield.
*/
interface Field<T> : Ring<T>, FieldOperations<T> {
public interface Field<T> : Ring<T>, FieldOperations<T> {
/**
* Division of element by scalar.
*
@ -336,5 +335,5 @@ interface Field<T> : Ring<T>, FieldOperations<T> {
* @param b the divisor.
* @return the quotient.
*/
operator fun Number.div(b: T): T = this * divide(one, b)
public operator fun Number.div(b: T): T = this * divide(one, b)
}

30
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/AlgebraElements.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/operations/AlgebraElements.kt
View File

@ -1,15 +1,15 @@
package scientifik.kmath.operations
package kscience.kmath.operations
/**
* The generic mathematics elements which is able to store its context
*
* @param C the type of mathematical context for this element.
*/
interface MathElement<C> {
public interface MathElement<C> {
/**
* The context this element belongs to.
*/
val context: C
public val context: C
}
/**
@ -18,16 +18,16 @@ interface MathElement<C> {
* @param T the type wrapped by this wrapper.
* @param I the type of this wrapper.
*/
interface MathWrapper<T, I> {
public interface MathWrapper<T, I> {
/**
* Unwraps [I] to [T].
*/
fun unwrap(): T
public fun unwrap(): T
/**
* Wraps [T] to [I].
*/
fun T.wrap(): I
public fun T.wrap(): I
}
/**
@ -37,14 +37,14 @@ interface MathWrapper<T, I> {
* @param I self type of the element. Needed for static type checking.
* @param S the type of space.
*/
interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement<S>, MathWrapper<T, I> {
public interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement<S>, MathWrapper<T, I> {
/**
* Adds element to this one.
*
* @param b the augend.
* @return the sum.
*/
operator fun plus(b: T): I = context.add(unwrap(), b).wrap()
public operator fun plus(b: T): I = context.add(unwrap(), b).wrap()
/**
* Subtracts element from this one.
@ -52,7 +52,7 @@ interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement
* @param b the subtrahend.
* @return the difference.
*/
operator fun minus(b: T): I = context.add(unwrap(), context.multiply(b, -1.0)).wrap()
public operator fun minus(b: T): I = context.add(unwrap(), context.multiply(b, -1.0)).wrap()
/**
* Multiplies this element by number.
@ -60,7 +60,7 @@ interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement
* @param k the multiplicand.
* @return the product.
*/
operator fun times(k: Number): I = context.multiply(unwrap(), k.toDouble()).wrap()
public operator fun times(k: Number): I = context.multiply(unwrap(), k.toDouble()).wrap()
/**
* Divides this element by number.
@ -68,7 +68,7 @@ interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement
* @param k the divisor.
* @return the quotient.
*/
operator fun div(k: Number): I = context.multiply(unwrap(), 1.0 / k.toDouble()).wrap()
public operator fun div(k: Number): I = context.multiply(unwrap(), 1.0 / k.toDouble()).wrap()
}
/**
@ -78,14 +78,14 @@ interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement
* @param I self type of the element. Needed for static type checking.
* @param R the type of ring.
*/
interface RingElement<T, I : RingElement<T, I, R>, R : Ring<T>> : SpaceElement<T, I, R> {
public interface RingElement<T, I : RingElement<T, I, R>, R : Ring<T>> : SpaceElement<T, I, R> {
/**
* Multiplies this element by another one.
*
* @param b the multiplicand.
* @return the product.
*/
operator fun times(b: T): I = context.multiply(unwrap(), b).wrap()
public operator fun times(b: T): I = context.multiply(unwrap(), b).wrap()
}
/**
@ -95,7 +95,7 @@ interface RingElement<T, I : RingElement<T, I, R>, R : Ring<T>> : SpaceElement<T
* @param I self type of the element. Needed for static type checking.
* @param F the type of field.
*/
interface FieldElement<T, I : FieldElement<T, I, F>, F : Field<T>> : RingElement<T, I, F> {
public interface FieldElement<T, I : FieldElement<T, I, F>, F : Field<T>> : RingElement<T, I, F> {
override val context: F
/**
@ -104,5 +104,5 @@ interface FieldElement<T, I : FieldElement<T, I, F>, F : Field<T>> : RingElement
* @param b the divisor.
* @return the quotient.
*/
operator fun div(b: T): I = context.divide(unwrap(), b).wrap()
public operator fun div(b: T): I = context.divide(unwrap(), b).wrap()
}

27
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/AlgebraExtensions.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/operations/AlgebraExtensions.kt
View File

@ -1,4 +1,4 @@
package scientifik.kmath.operations
package kscience.kmath.operations
/**
* Returns the sum of all elements in the iterable in this [Space].
@ -7,7 +7,7 @@ package scientifik.kmath.operations
* @param data the iterable to sum up.
* @return the sum.
*/
fun <T> Space<T>.sum(data: Iterable<T>): T = data.fold(zero) { left, right -> add(left, right) }
public fun <T> Space<T>.sum(data: Iterable<T>): T = data.fold(zero) { left, right -> add(left, right) }
/**
* Returns the sum of all elements in the sequence in this [Space].
@ -16,7 +16,7 @@ fun <T> Space<T>.sum(data: Iterable<T>): T = data.fold(zero) { left, right -> ad
* @param data the sequence to sum up.
* @return the sum.
*/
fun <T> Space<T>.sum(data: Sequence<T>): T = data.fold(zero) { left, right -> add(left, right) }
public fun <T> Space<T>.sum(data: Sequence<T>): T = data.fold(zero) { left, right -> add(left, right) }
/**
* Returns an average value of elements in the iterable in this [Space].
@ -24,8 +24,9 @@ fun <T> Space<T>.sum(data: Sequence<T>): T = data.fold(zero) { left, right -> ad
* @receiver the algebra that provides addition and division.
* @param data the iterable to find average.
* @return the average value.
* @author Iaroslav Postovalov
*/
fun <T> Space<T>.average(data: Iterable<T>): T = sum(data) / data.count()
public fun <T> Space<T>.average(data: Iterable<T>): T = sum(data) / data.count()
/**
* Returns an average value of elements in the sequence in this [Space].
@ -33,8 +34,9 @@ fun <T> Space<T>.average(data: Iterable<T>): T = sum(data) / data.count()
* @receiver the algebra that provides addition and division.
* @param data the sequence to find average.
* @return the average value.
* @author Iaroslav Postovalov
*/
fun <T> Space<T>.average(data: Sequence<T>): T = sum(data) / data.count()
public fun <T> Space<T>.average(data: Sequence<T>): T = sum(data) / data.count()
/**
* Returns the sum of all elements in the iterable in provided space.
@ -43,7 +45,7 @@ fun <T> Space<T>.average(data: Sequence<T>): T = sum(data) / data.count()
* @param space the algebra that provides addition.
* @return the sum.
*/
fun <T> Iterable<T>.sumWith(space: Space<T>): T = space.sum(this)
public fun <T> Iterable<T>.sumWith(space: Space<T>): T = space.sum(this)
/**
* Returns the sum of all elements in the sequence in provided space.
@ -52,7 +54,7 @@ fun <T> Iterable<T>.sumWith(space: Space<T>): T = space.sum(this)
* @param space the algebra that provides addition.
* @return the sum.
*/
fun <T> Sequence<T>.sumWith(space: Space<T>): T = space.sum(this)
public fun <T> Sequence<T>.sumWith(space: Space<T>): T = space.sum(this)
/**
* Returns an average value of elements in the iterable in this [Space].
@ -60,8 +62,9 @@ fun <T> Sequence<T>.sumWith(space: Space<T>): T = space.sum(this)
* @receiver the iterable to find average.
* @param space the algebra that provides addition and division.
* @return the average value.
* @author Iaroslav Postovalov
*/
fun <T> Iterable<T>.averageWith(space: Space<T>): T = space.average(this)
public fun <T> Iterable<T>.averageWith(space: Space<T>): T = space.average(this)
/**
* Returns an average value of elements in the sequence in this [Space].
@ -69,8 +72,9 @@ fun <T> Iterable<T>.averageWith(space: Space<T>): T = space.average(this)
* @receiver the sequence to find average.
* @param space the algebra that provides addition and division.
* @return the average value.
* @author Iaroslav Postovalov
*/
fun <T> Sequence<T>.averageWith(space: Space<T>): T = space.average(this)
public fun <T> Sequence<T>.averageWith(space: Space<T>): T = space.average(this)
//TODO optimized power operation
@ -82,7 +86,7 @@ fun <T> Sequence<T>.averageWith(space: Space<T>): T = space.average(this)
* @param power the exponent.
* @return the base raised to the power.
*/
fun <T> Ring<T>.power(arg: T, power: Int): T {
public fun <T> Ring<T>.power(arg: T, power: Int): T {
require(power >= 0) { "The power can't be negative." }
require(power != 0 || arg != zero) { "The $zero raised to $power is not defined." }
if (power == 0) return one
@ -98,8 +102,9 @@ fun <T> Ring<T>.power(arg: T, power: Int): T {
* @param arg the base.
* @param power the exponent.
* @return the base raised to the power.
* @author Iaroslav Postovalov
*/
fun <T> Field<T>.power(arg: T, power: Int): T {
public fun <T> Field<T>.power(arg: T, power: Int): T {
require(power != 0 || arg != zero) { "The $zero raised to $power is not defined." }
if (power == 0) return one
if (power < 0) return one / (this as Ring<T>).power(arg, -power)

327
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/BigInt.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/operations/BigInt.kt
View File

@ -1,23 +1,22 @@
package scientifik.kmath.operations
package kscience.kmath.operations
import scientifik.kmath.operations.BigInt.Companion.BASE
import scientifik.kmath.operations.BigInt.Companion.BASE_SIZE
import scientifik.kmath.structures.*
import kotlin.contracts.contract
import kscience.kmath.operations.BigInt.Companion.BASE
import kscience.kmath.operations.BigInt.Companion.BASE_SIZE
import kscience.kmath.structures.*
import kotlin.math.log2
import kotlin.math.max
import kotlin.math.min
import kotlin.math.sign
typealias Magnitude = UIntArray
typealias TBase = ULong
public typealias Magnitude = UIntArray
public typealias TBase = ULong
/**
* Kotlin Multiplatform implementation of Big Integer numbers (KBigInteger).
*
* @author Robert Drynkin (https://github.com/robdrynkin) and Peter Klimai (https://github.com/pklimai)
*/
object BigIntField : Field<BigInt> {
public object BigIntField : Field<BigInt> {
override val zero: BigInt = BigInt.ZERO
override val one: BigInt = BigInt.ONE
@ -28,113 +27,92 @@ object BigIntField : Field<BigInt> {
override fun multiply(a: BigInt, b: BigInt): BigInt = a.times(b)
operator fun String.unaryPlus(): BigInt = this.parseBigInteger() ?: error("Can't parse $this as big integer")
public operator fun String.unaryPlus(): BigInt = this.parseBigInteger() ?: error("Can't parse $this as big integer")
operator fun String.unaryMinus(): BigInt =
public operator fun String.unaryMinus(): BigInt =
-(this.parseBigInteger() ?: error("Can't parse $this as big integer"))
override fun divide(a: BigInt, b: BigInt): BigInt = a.div(b)
}
class BigInt internal constructor(
public class BigInt internal constructor(
private val sign: Byte,
private val magnitude: Magnitude
) : Comparable<BigInt> {
public override fun compareTo(other: BigInt): Int = when {
(sign == 0.toByte()) and (other.sign == 0.toByte()) -> 0
sign < other.sign -> -1
sign > other.sign -> 1
else -> sign * compareMagnitudes(magnitude, other.magnitude)
}
override fun compareTo(other: BigInt): Int {
return when {
(this.sign == 0.toByte()) and (other.sign == 0.toByte()) -> 0
this.sign < other.sign -> -1
this.sign > other.sign -> 1
else -> this.sign * compareMagnitudes(this.magnitude, other.magnitude)
public override fun equals(other: Any?): Boolean =
if (other is BigInt) compareTo(other) == 0 else error("Can't compare KBigInteger to a different type")
public override fun hashCode(): Int = magnitude.hashCode() + sign
public fun abs(): BigInt = if (sign == 0.toByte()) this else BigInt(1, magnitude)
public operator fun unaryMinus(): BigInt =
if (this.sign == 0.toByte()) this else BigInt((-this.sign).toByte(), this.magnitude)
public operator fun plus(b: BigInt): BigInt = when {
b.sign == 0.toByte() -> this
sign == 0.toByte() -> b
this == -b -> ZERO
sign == b.sign -> BigInt(sign, addMagnitudes(magnitude, b.magnitude))
else -> {
val comp = compareMagnitudes(magnitude, b.magnitude)
if (comp == 1)
BigInt(sign, subtractMagnitudes(magnitude, b.magnitude))
else
BigInt((-sign).toByte(), subtractMagnitudes(b.magnitude, magnitude))
}
}
override fun equals(other: Any?): Boolean {
if (other is BigInt) {
return this.compareTo(other) == 0
} else error("Can't compare KBigInteger to a different type")
}
public operator fun minus(b: BigInt): BigInt = this + (-b)
override fun hashCode(): Int {
return magnitude.hashCode() + this.sign
}
fun abs(): BigInt = if (sign == 0.toByte()) this else BigInt(1, magnitude)
operator fun unaryMinus(): BigInt {
return if (this.sign == 0.toByte()) this else BigInt((-this.sign).toByte(), this.magnitude)
}
operator fun plus(b: BigInt): BigInt {
return when {
b.sign == 0.toByte() -> this
this.sign == 0.toByte() -> b
this == -b -> ZERO
this.sign == b.sign -> BigInt(this.sign, addMagnitudes(this.magnitude, b.magnitude))
else -> {
val comp: Int = compareMagnitudes(this.magnitude, b.magnitude)
if (comp == 1) {
BigInt(this.sign, subtractMagnitudes(this.magnitude, b.magnitude))
} else {
BigInt((-this.sign).toByte(), subtractMagnitudes(b.magnitude, this.magnitude))
}
}
}
}
operator fun minus(b: BigInt): BigInt {
return this + (-b)
}
operator fun times(b: BigInt): BigInt {
return when {
this.sign == 0.toByte() -> ZERO
b.sign == 0.toByte() -> ZERO
public operator fun times(b: BigInt): BigInt = when {
this.sign == 0.toByte() -> ZERO
b.sign == 0.toByte() -> ZERO
// TODO: Karatsuba
else -> BigInt((this.sign * b.sign).toByte(), multiplyMagnitudes(this.magnitude, b.magnitude))
}
else -> BigInt((this.sign * b.sign).toByte(), multiplyMagnitudes(this.magnitude, b.magnitude))
}
operator fun times(other: UInt): BigInt {
return when {
this.sign == 0.toByte() -> ZERO
other == 0U -> ZERO
else -> BigInt(this.sign, multiplyMagnitudeByUInt(this.magnitude, other))
}
public operator fun times(other: UInt): BigInt = when {
sign == 0.toByte() -> ZERO
other == 0U -> ZERO
else -> BigInt(sign, multiplyMagnitudeByUInt(magnitude, other))
}
operator fun times(other: Int): BigInt {
return if (other > 0)
this * kotlin.math.abs(other).toUInt()
else
-this * kotlin.math.abs(other).toUInt()
}
public operator fun times(other: Int): BigInt = if (other > 0)
this * kotlin.math.abs(other).toUInt()
else
-this * kotlin.math.abs(other).toUInt()
operator fun div(other: UInt): BigInt {
return BigInt(this.sign, divideMagnitudeByUInt(this.magnitude, other))
}
public operator fun div(other: UInt): BigInt = BigInt(this.sign, divideMagnitudeByUInt(this.magnitude, other))
operator fun div(other: Int): BigInt {
return BigInt(
(this.sign * other.sign).toByte(),
divideMagnitudeByUInt(this.magnitude, kotlin.math.abs(other).toUInt())
)
}
public operator fun div(other: Int): BigInt = BigInt(
(this.sign * other.sign).toByte(),
divideMagnitudeByUInt(this.magnitude, kotlin.math.abs(other).toUInt())
)
private fun division(other: BigInt): Pair<BigInt, BigInt> {
// Long division algorithm:
// https://en.wikipedia.org/wiki/Division_algorithm#Integer_division_(unsigned)_with_remainder
// TODO: Implement more effective algorithm
var q: BigInt = ZERO
var r: BigInt = ZERO
var q = ZERO
var r = ZERO
val bitSize =
(BASE_SIZE * (this.magnitude.size - 1) + log2(this.magnitude.lastOrNull()?.toFloat() ?: 0f + 1)).toInt()
for (i in bitSize downTo 0) {
r = r shl 1
r = r or ((abs(this) shr i) and ONE)
if (r >= abs(other)) {
r -= abs(other)
q += (ONE shl i)
@ -144,99 +122,84 @@ class BigInt internal constructor(
return Pair(BigInt((this.sign * other.sign).toByte(), q.magnitude), r)
}
operator fun div(other: BigInt): BigInt {
return this.division(other).first
}
public operator fun div(other: BigInt): BigInt = division(other).first
infix fun shl(i: Int): BigInt {
public infix fun shl(i: Int): BigInt {
if (this == ZERO) return ZERO
if (i == 0) return this
val fullShifts = i / BASE_SIZE + 1
val relShift = i % BASE_SIZE
val shiftLeft = { x: UInt -> if (relShift >= 32) 0U else x shl relShift }
val shiftRight = { x: UInt -> if (BASE_SIZE - relShift >= 32) 0U else x shr (BASE_SIZE - relShift) }
val newMagnitude = Magnitude(magnitude.size + fullShifts)
val newMagnitude: Magnitude = Magnitude(this.magnitude.size + fullShifts)
for (j in this.magnitude.indices) {
for (j in magnitude.indices) {
newMagnitude[j + fullShifts - 1] = shiftLeft(this.magnitude[j])
if (j != 0) {
if (j != 0)
newMagnitude[j + fullShifts - 1] = newMagnitude[j + fullShifts - 1] or shiftRight(this.magnitude[j - 1])
}
}
newMagnitude[this.magnitude.size + fullShifts - 1] = shiftRight(this.magnitude.last())
newMagnitude[magnitude.size + fullShifts - 1] = shiftRight(magnitude.last())
return BigInt(this.sign, stripLeadingZeros(newMagnitude))
}
infix fun shr(i: Int): BigInt {
public infix fun shr(i: Int): BigInt {
if (this == ZERO) return ZERO
if (i == 0) return this
val fullShifts = i / BASE_SIZE
val relShift = i % BASE_SIZE
val shiftRight = { x: UInt -> if (relShift >= 32) 0U else x shr relShift }
val shiftLeft = { x: UInt -> if (BASE_SIZE - relShift >= 32) 0U else x shl (BASE_SIZE - relShift) }
if (this.magnitude.size - fullShifts <= 0) {
return ZERO
}
val newMagnitude: Magnitude = Magnitude(this.magnitude.size - fullShifts)
if (this.magnitude.size - fullShifts <= 0) return ZERO
val newMagnitude: Magnitude = Magnitude(magnitude.size - fullShifts)
for (j in fullShifts until this.magnitude.size) {
newMagnitude[j - fullShifts] = shiftRight(this.magnitude[j])
if (j != this.magnitude.size - 1) {
newMagnitude[j - fullShifts] = newMagnitude[j - fullShifts] or shiftLeft(this.magnitude[j + 1])
}
for (j in fullShifts until magnitude.size) {
newMagnitude[j - fullShifts] = shiftRight(magnitude[j])
if (j != magnitude.size - 1)
newMagnitude[j - fullShifts] = newMagnitude[j - fullShifts] or shiftLeft(magnitude[j + 1])
}
return BigInt(this.sign, stripLeadingZeros(newMagnitude))
}
infix fun or(other: BigInt): BigInt {
public infix fun or(other: BigInt): BigInt {
if (this == ZERO) return other
if (other == ZERO) return this
val resSize = max(this.magnitude.size, other.magnitude.size)
val resSize = max(magnitude.size, other.magnitude.size)
val newMagnitude: Magnitude = Magnitude(resSize)
for (i in 0 until resSize) {
if (i < this.magnitude.size) {
newMagnitude[i] = newMagnitude[i] or this.magnitude[i]
}
if (i < other.magnitude.size) {
newMagnitude[i] = newMagnitude[i] or other.magnitude[i]
}
if (i < magnitude.size) newMagnitude[i] = newMagnitude[i] or magnitude[i]
if (i < other.magnitude.size) newMagnitude[i] = newMagnitude[i] or other.magnitude[i]
}
return BigInt(1, stripLeadingZeros(newMagnitude))
}
infix fun and(other: BigInt): BigInt {
public infix fun and(other: BigInt): BigInt {
if ((this == ZERO) or (other == ZERO)) return ZERO
val resSize = min(this.magnitude.size, other.magnitude.size)
val newMagnitude: Magnitude = Magnitude(resSize)
for (i in 0 until resSize) {
newMagnitude[i] = this.magnitude[i] and other.magnitude[i]
}
for (i in 0 until resSize) newMagnitude[i] = this.magnitude[i] and other.magnitude[i]
return BigInt(1, stripLeadingZeros(newMagnitude))
}
operator fun rem(other: Int): Int {
public operator fun rem(other: Int): Int {
val res = this - (this / other) * other
return if (res == ZERO) 0 else res.sign * res.magnitude[0].toInt()
}
operator fun rem(other: BigInt): BigInt {
return this - (this / other) * other
}
public operator fun rem(other: BigInt): BigInt = this - (this / other) * other
fun modPow(exponent: BigInt, m: BigInt): BigInt {
return when {
exponent == ZERO -> ONE
exponent % 2 == 1 -> (this * modPow(exponent - ONE, m)) % m
else -> {
val sqRoot = modPow(exponent / 2, m)
(sqRoot * sqRoot) % m
}
public fun modPow(exponent: BigInt, m: BigInt): BigInt = when {
exponent == ZERO -> ONE
exponent % 2 == 1 -> (this * modPow(exponent - ONE, m)) % m
else -> {
val sqRoot = modPow(exponent / 2, m)
(sqRoot * sqRoot) % m
}
}
@ -260,11 +223,11 @@ class BigInt internal constructor(
return res
}
companion object {
const val BASE: ULong = 0xffffffffUL
const val BASE_SIZE: Int = 32
val ZERO: BigInt = BigInt(0, uintArrayOf())
val ONE: BigInt = BigInt(1, uintArrayOf(1u))
public companion object {
public const val BASE: ULong = 0xffffffffUL
public const val BASE_SIZE: Int = 32
public val ZERO: BigInt = BigInt(0, uintArrayOf())
public val ONE: BigInt = BigInt(1, uintArrayOf(1u))
private val hexMapping: HashMap<UInt, String> = hashMapOf(
0U to "0", 1U to "1", 2U to "2", 3U to "3",
@ -291,9 +254,9 @@ class BigInt internal constructor(
}
private fun addMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude {
val resultLength: Int = max(mag1.size, mag2.size) + 1
val resultLength = max(mag1.size, mag2.size) + 1
val result = Magnitude(resultLength)
var carry: TBase = 0UL
var carry = 0uL
for (i in 0 until resultLength - 1) {
val res = when {
@ -301,20 +264,22 @@ class BigInt internal constructor(
i >= mag2.size -> mag1[i].toULong() + carry
else -> mag1[i].toULong() + mag2[i].toULong() + carry
}
result[i] = (res and BASE).toUInt()
carry = (res shr BASE_SIZE)
}
result[resultLength - 1] = carry.toUInt()
return stripLeadingZeros(result)
}
private fun subtractMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude {
val resultLength: Int = mag1.size
val resultLength = mag1.size
val result = Magnitude(resultLength)
var carry = 0L
for (i in 0 until resultLength) {
var res: Long =
var res =
if (i < mag2.size) mag1[i].toLong() - mag2[i].toLong() - carry
else mag1[i].toLong() - carry
@ -328,9 +293,9 @@ class BigInt internal constructor(
}
private fun multiplyMagnitudeByUInt(mag: Magnitude, x: UInt): Magnitude {
val resultLength: Int = mag.size + 1
val resultLength = mag.size + 1
val result = Magnitude(resultLength)
var carry: ULong = 0UL
var carry = 0uL
for (i in mag.indices) {
val cur: ULong = carry + mag[i].toULong() * x.toULong()
@ -343,16 +308,18 @@ class BigInt internal constructor(
}
private fun multiplyMagnitudes(mag1: Magnitude, mag2: Magnitude): Magnitude {
val resultLength: Int = mag1.size + mag2.size
val resultLength = mag1.size + mag2.size
val result = Magnitude(resultLength)
for (i in mag1.indices) {
var carry: ULong = 0UL
var carry = 0uL
for (j in mag2.indices) {
val cur: ULong = result[i + j].toULong() + mag1[i].toULong() * mag2[j].toULong() + carry
result[i + j] = (cur and BASE.toULong()).toUInt()
carry = cur shr BASE_SIZE
}
result[i + mag2.size] = (carry and BASE).toUInt()
}
@ -360,48 +327,46 @@ class BigInt internal constructor(
}
private fun divideMagnitudeByUInt(mag: Magnitude, x: UInt): Magnitude {
val resultLength: Int = mag.size
val resultLength = mag.size
val result = Magnitude(resultLength)
var carry: ULong = 0UL
var carry = 0uL
for (i in mag.size - 1 downTo 0) {
val cur: ULong = mag[i].toULong() + (carry shl BASE_SIZE)
result[i] = (cur / x).toUInt()
carry = cur % x
}
return stripLeadingZeros(result)
}
}
}
private fun stripLeadingZeros(mag: Magnitude): Magnitude {
if (mag.isEmpty() || mag.last() != 0U) {
return mag
}
var resSize: Int = mag.size - 1
if (mag.isEmpty() || mag.last() != 0U) return mag
var resSize = mag.size - 1
while (mag[resSize] == 0U) {
if (resSize == 0)
break
if (resSize == 0) break
resSize -= 1
}
return mag.sliceArray(IntRange(0, resSize))
}
fun abs(x: BigInt): BigInt = x.abs()
public fun abs(x: BigInt): BigInt = x.abs()
/**
* Convert this [Int] to [BigInt]
*/
fun Int.toBigInt(): BigInt = BigInt(sign.toByte(), uintArrayOf(kotlin.math.abs(this).toUInt()))
public fun Int.toBigInt(): BigInt = BigInt(sign.toByte(), uintArrayOf(kotlin.math.abs(this).toUInt()))
/**
* Convert this [Long] to [BigInt]
*/
fun Long.toBigInt(): BigInt = BigInt(
sign.toByte(), stripLeadingZeros(
public fun Long.toBigInt(): BigInt = BigInt(
sign.toByte(),
stripLeadingZeros(
uintArrayOf(
(kotlin.math.abs(this).toULong() and BASE).toUInt(),
((kotlin.math.abs(this).toULong() shr BASE_SIZE) and BASE).toUInt()
@ -412,12 +377,12 @@ fun Long.toBigInt(): BigInt = BigInt(
/**
* Convert UInt to [BigInt]
*/
fun UInt.toBigInt(): BigInt = BigInt(1, uintArrayOf(this))
public fun UInt.toBigInt(): BigInt = BigInt(1, uintArrayOf(this))
/**
* Convert ULong to [BigInt]
*/
fun ULong.toBigInt(): BigInt = BigInt(
public fun ULong.toBigInt(): BigInt = BigInt(
1,
stripLeadingZeros(
uintArrayOf(
@ -430,12 +395,12 @@ fun ULong.toBigInt(): BigInt = BigInt(
/**
* Create a [BigInt] with this array of magnitudes with protective copy
*/
fun UIntArray.toBigInt(sign: Byte): BigInt {
public fun UIntArray.toBigInt(sign: Byte): BigInt {
require(sign != 0.toByte() || !isNotEmpty())
return BigInt(sign, copyOf())
}
val hexChToInt: MutableMap<Char, Int> = hashMapOf(
private val hexChToInt: MutableMap<Char, Int> = hashMapOf(
'0' to 0, '1' to 1, '2' to 2, '3' to 3,
'4' to 4, '5' to 5, '6' to 6, '7' to 7,
'8' to 8, '9' to 9, 'A' to 10, 'B' to 11,
@ -445,9 +410,10 @@ val hexChToInt: MutableMap<Char, Int> = hashMapOf(
/**
* Returns null if a valid number can not be read from a string
*/
fun String.parseBigInteger(): BigInt? {
public fun String.parseBigInteger(): BigInt? {
val sign: Int
val sPositive: String
when {
this[0] == '+' -> {
sign = +1
@ -462,43 +428,42 @@ fun String.parseBigInteger(): BigInt? {
sign = +1
}
}
var res = BigInt.ZERO
var digitValue = BigInt.ONE
val sPositiveUpper = sPositive.toUpperCase()
if (sPositiveUpper.startsWith("0X")) { // hex representation
val sHex = sPositiveUpper.substring(2)
for (ch in sHex.reversed()) {
if (ch == '_') continue
res += digitValue * (hexChToInt[ch] ?: return null)
digitValue *= 16.toBigInt()
}
} else { // decimal representation
for (ch in sPositiveUpper.reversed()) {
if (ch == '_') continue
if (ch !in '0'..'9') {
return null
}
res += digitValue * (ch.toInt() - '0'.toInt())
digitValue *= 10.toBigInt()
} else for (ch in sPositiveUpper.reversed()) {
// decimal representation
if (ch == '_') continue
if (ch !in '0'..'9') {
return null
}
res += digitValue * (ch.toInt() - '0'.toInt())
digitValue *= 10.toBigInt()
}
return res * sign
}
inline fun Buffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): Buffer<BigInt> {
contract { callsInPlace(initializer) }
return boxing(size, initializer)
}
public inline fun Buffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): Buffer<BigInt> =
boxing(size, initializer)
inline fun MutableBuffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): MutableBuffer<BigInt> {
contract { callsInPlace(initializer) }
return boxing(size, initializer)
}
public inline fun MutableBuffer.Companion.bigInt(size: Int, initializer: (Int) -> BigInt): MutableBuffer<BigInt> =
boxing(size, initializer)
fun NDAlgebra.Companion.bigInt(vararg shape: Int): BoxingNDRing<BigInt, BigIntField> =
public fun NDAlgebra.Companion.bigInt(vararg shape: Int): BoxingNDRing<BigInt, BigIntField> =
BoxingNDRing(shape, BigIntField, Buffer.Companion::bigInt)
fun NDElement.Companion.bigInt(
public fun NDElement.Companion.bigInt(
vararg shape: Int,
initializer: BigIntField.(IntArray) -> BigInt
): BufferedNDRingElement<BigInt, BigIntField> = NDAlgebra.bigInt(*shape).produce(initializer)

58
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/Complex.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/operations/Complex.kt
View File

@ -1,24 +1,23 @@
package scientifik.kmath.operations
package kscience.kmath.operations
import scientifik.kmath.structures.Buffer
import scientifik.kmath.structures.MemoryBuffer
import scientifik.kmath.structures.MutableBuffer
import scientifik.memory.MemoryReader
import scientifik.memory.MemorySpec
import scientifik.memory.MemoryWriter
import kotlin.contracts.contract
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.MemoryBuffer
import kscience.kmath.structures.MutableBuffer
import kscience.memory.MemoryReader
import kscience.memory.MemorySpec
import kscience.memory.MemoryWriter
import kotlin.math.*
/**
* This complex's conjugate.
*/
val Complex.conjugate: Complex
public val Complex.conjugate: Complex
get() = Complex(re, -im)
/**
* This complex's reciprocal.
*/
val Complex.reciprocal: Complex
public val Complex.reciprocal: Complex
get() {
val scale = re * re + im * im
return Complex(re / scale, -im / scale)
@ -27,13 +26,13 @@ val Complex.reciprocal: Complex
/**
* Absolute value of complex number.
*/
val Complex.r: Double
public val Complex.r: Double
get() = sqrt(re * re + im * im)
/**
* An angle between vector represented by complex number and X axis.
*/
val Complex.theta: Double
public val Complex.theta: Double
get() = atan(im / re)
private val PI_DIV_2 = Complex(PI / 2, 0)
@ -41,14 +40,14 @@ private val PI_DIV_2 = Complex(PI / 2, 0)
/**
* A field of [Complex].
*/
object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
public object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
override val zero: Complex = 0.0.toComplex()
override val one: Complex = 1.0.toComplex()
/**
* The imaginary unit.
*/
val i: Complex = Complex(0.0, 1.0)
public val i: Complex = Complex(0.0, 1.0)
override fun add(a: Complex, b: Complex): Complex = Complex(a.re + b.re, a.im + b.im)
@ -116,7 +115,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
* @param c the augend.
* @return the sum.
*/
operator fun Double.plus(c: Complex): Complex = add(this.toComplex(), c)
public operator fun Double.plus(c: Complex): Complex = add(this.toComplex(), c)
/**
* Subtracts complex number from real one.
@ -125,7 +124,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
* @param c the subtrahend.
* @return the difference.
*/
operator fun Double.minus(c: Complex): Complex = add(this.toComplex(), -c)
public operator fun Double.minus(c: Complex): Complex = add(this.toComplex(), -c)
/**
* Adds real number to complex one.
@ -134,7 +133,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
* @param d the augend.
* @return the sum.
*/
operator fun Complex.plus(d: Double): Complex = d + this
public operator fun Complex.plus(d: Double): Complex = d + this
/**
* Subtracts real number from complex one.
@ -143,7 +142,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
* @param d the subtrahend.
* @return the difference.
*/
operator fun Complex.minus(d: Double): Complex = add(this, -d.toComplex())
public operator fun Complex.minus(d: Double): Complex = add(this, -d.toComplex())
/**
* Multiplies real number by complex one.
@ -152,7 +151,7 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
* @param c the multiplicand.
* @receiver the product.
*/
operator fun Double.times(c: Complex): Complex = Complex(c.re * this, c.im * this)
public operator fun Double.times(c: Complex): Complex = Complex(c.re * this, c.im * this)
override fun norm(arg: Complex): Complex = sqrt(arg.conjugate * arg)
@ -165,8 +164,9 @@ object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex> {
* @property re The real part.
* @property im The imaginary part.
*/
data class Complex(val re: Double, val im: Double) : FieldElement<Complex, Complex, ComplexField>, Comparable<Complex> {
constructor(re: Number, im: Number) : this(re.toDouble(), im.toDouble())
public data class Complex(val re: Double, val im: Double) : FieldElement<Complex, Complex, ComplexField>,
Comparable<Complex> {
public constructor(re: Number, im: Number) : this(re.toDouble(), im.toDouble())
override val context: ComplexField get() = ComplexField
@ -176,7 +176,7 @@ data class Complex(val re: Double, val im: Double) : FieldElement<Complex, Compl
override fun compareTo(other: Complex): Int = r.compareTo(other.r)
companion object : MemorySpec<Complex> {
public companion object : MemorySpec<Complex> {
override val objectSize: Int = 16
override fun MemoryReader.read(offset: Int): Complex =
@ -195,14 +195,10 @@ data class Complex(val re: Double, val im: Double) : FieldElement<Complex, Compl
* @receiver the real part.
* @return the new complex number.
*/
fun Number.toComplex(): Complex = Complex(this, 0.0)
public fun Number.toComplex(): Complex = Complex(this, 0.0)
inline fun Buffer.Companion.complex(size: Int, crossinline init: (Int) -> Complex): Buffer<Complex> {
contract { callsInPlace(init) }
return MemoryBuffer.create(Complex, size, init)
}
public inline fun Buffer.Companion.complex(size: Int, init: (Int) -> Complex): Buffer<Complex> =
MemoryBuffer.create(Complex, size, init)
inline fun MutableBuffer.Companion.complex(size: Int, crossinline init: (Int) -> Complex): Buffer<Complex> {
contract { callsInPlace(init) }
return MemoryBuffer.create(Complex, size, init)
}
public inline fun MutableBuffer.Companion.complex(size: Int, init: (Int) -> Complex): Buffer<Complex> =
MemoryBuffer.create(Complex, size, init)

266
kmath-core/src/commonMain/kotlin/kscience/kmath/operations/NumberAlgebra.kt Normal file
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@ -0,0 +1,266 @@
package kscience.kmath.operations
import kotlin.math.abs
import kotlin.math.pow as kpow
/**
* Advanced Number-like semifield that implements basic operations.
*/
public interface ExtendedFieldOperations<T> :
FieldOperations<T>,
TrigonometricOperations<T>,
HyperbolicOperations<T>,
PowerOperations<T>,
ExponentialOperations<T> {
public override fun tan(arg: T): T = sin(arg) / cos(arg)
public override fun tanh(arg: T): T = sinh(arg) / cosh(arg)
public override fun unaryOperation(operation: String, arg: T): T = when (operation) {
TrigonometricOperations.COS_OPERATION -> cos(arg)
TrigonometricOperations.SIN_OPERATION -> sin(arg)
TrigonometricOperations.TAN_OPERATION -> tan(arg)
TrigonometricOperations.ACOS_OPERATION -> acos(arg)
TrigonometricOperations.ASIN_OPERATION -> asin(arg)
TrigonometricOperations.ATAN_OPERATION -> atan(arg)
HyperbolicOperations.COSH_OPERATION -> cosh(arg)
HyperbolicOperations.SINH_OPERATION -> sinh(arg)
HyperbolicOperations.TANH_OPERATION -> tanh(arg)
HyperbolicOperations.ACOSH_OPERATION -> acosh(arg)
HyperbolicOperations.ASINH_OPERATION -> asinh(arg)
HyperbolicOperations.ATANH_OPERATION -> atanh(arg)
PowerOperations.SQRT_OPERATION -> sqrt(arg)
ExponentialOperations.EXP_OPERATION -> exp(arg)
ExponentialOperations.LN_OPERATION -> ln(arg)
else -> super.unaryOperation(operation, arg)
}
}
/**
* Advanced Number-like field that implements basic operations.
*/
public interface ExtendedField<T> : ExtendedFieldOperations<T>, Field<T> {
public override fun sinh(arg: T): T = (exp(arg) - exp(-arg)) / 2
public override fun cosh(arg: T): T = (exp(arg) + exp(-arg)) / 2
public override fun tanh(arg: T): T = (exp(arg) - exp(-arg)) / (exp(-arg) + exp(arg))
public override fun asinh(arg: T): T = ln(sqrt(arg * arg + one) + arg)
public override fun acosh(arg: T): T = ln(arg + sqrt((arg - one) * (arg + one)))
public override fun atanh(arg: T): T = (ln(arg + one) - ln(one - arg)) / 2
public override fun rightSideNumberOperation(operation: String, left: T, right: Number): T = when (operation) {
PowerOperations.POW_OPERATION -> power(left, right)
else -> super.rightSideNumberOperation(operation, left, right)
}
}
/**
* Real field element wrapping double.
*
* @property value the [Double] value wrapped by this [Real].
*
* TODO inline does not work due to compiler bug. Waiting for fix for KT-27586
*/
public inline class Real(public val value: Double) : FieldElement<Double, Real, RealField> {
public override val context: RealField
get() = RealField
public override fun unwrap(): Double = value
public override fun Double.wrap(): Real = Real(value)
public companion object
}
/**
* A field for [Double] without boxing. Does not produce appropriate field element.
*/
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
public object RealField : ExtendedField<Double>, Norm<Double, Double> {
public override val zero: Double
get() = 0.0
public override val one: Double
get() = 1.0
public override fun binaryOperation(operation: String, left: Double, right: Double): Double = when (operation) {
PowerOperations.POW_OPERATION -> left pow right
else -> super.binaryOperation(operation, left, right)
}
public override inline fun add(a: Double, b: Double): Double = a + b
public override inline fun multiply(a: Double, k: Number): Double = a * k.toDouble()
public override inline fun multiply(a: Double, b: Double): Double = a * b
public override inline fun divide(a: Double, b: Double): Double = a / b
public override inline fun sin(arg: Double): Double = kotlin.math.sin(arg)
public override inline fun cos(arg: Double): Double = kotlin.math.cos(arg)
public override inline fun tan(arg: Double): Double = kotlin.math.tan(arg)
public override inline fun acos(arg: Double): Double = kotlin.math.acos(arg)
public override inline fun asin(arg: Double): Double = kotlin.math.asin(arg)
public override inline fun atan(arg: Double): Double = kotlin.math.atan(arg)
public override inline fun sinh(arg: Double): Double = kotlin.math.sinh(arg)
public override inline fun cosh(arg: Double): Double = kotlin.math.cosh(arg)
public override inline fun tanh(arg: Double): Double = kotlin.math.tanh(arg)
public override inline fun asinh(arg: Double): Double = kotlin.math.asinh(arg)
public override inline fun acosh(arg: Double): Double = kotlin.math.acosh(arg)
public override inline fun atanh(arg: Double): Double = kotlin.math.atanh(arg)
public override inline fun power(arg: Double, pow: Number): Double = arg.kpow(pow.toDouble())
public override inline fun exp(arg: Double): Double = kotlin.math.exp(arg)
public override inline fun ln(arg: Double): Double = kotlin.math.ln(arg)
public override inline fun norm(arg: Double): Double = abs(arg)
public override inline fun Double.unaryMinus(): Double = -this
public override inline fun Double.plus(b: Double): Double = this + b
public override inline fun Double.minus(b: Double): Double = this - b
public override inline fun Double.times(b: Double): Double = this * b
public override inline fun Double.div(b: Double): Double = this / b
}
/**
* A field for [Float] without boxing. Does not produce appropriate field element.
*/
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
public object FloatField : ExtendedField<Float>, Norm<Float, Float> {
public override val zero: Float
get() = 0.0f
public override val one: Float
get() = 1.0f
public override fun binaryOperation(operation: String, left: Float, right: Float): Float = when (operation) {
PowerOperations.POW_OPERATION -> left pow right
else -> super.binaryOperation(operation, left, right)
}
public override inline fun add(a: Float, b: Float): Float = a + b
public override inline fun multiply(a: Float, k: Number): Float = a * k.toFloat()
public override inline fun multiply(a: Float, b: Float): Float = a * b
public override inline fun divide(a: Float, b: Float): Float = a / b
public override inline fun sin(arg: Float): Float = kotlin.math.sin(arg)
public override inline fun cos(arg: Float): Float = kotlin.math.cos(arg)
public override inline fun tan(arg: Float): Float = kotlin.math.tan(arg)
public override inline fun acos(arg: Float): Float = kotlin.math.acos(arg)
public override inline fun asin(arg: Float): Float = kotlin.math.asin(arg)
public override inline fun atan(arg: Float): Float = kotlin.math.atan(arg)
public override inline fun sinh(arg: Float): Float = kotlin.math.sinh(arg)
public override inline fun cosh(arg: Float): Float = kotlin.math.cosh(arg)
public override inline fun tanh(arg: Float): Float = kotlin.math.tanh(arg)
public override inline fun asinh(arg: Float): Float = kotlin.math.asinh(arg)
public override inline fun acosh(arg: Float): Float = kotlin.math.acosh(arg)
public override inline fun atanh(arg: Float): Float = kotlin.math.atanh(arg)
public override inline fun power(arg: Float, pow: Number): Float = arg.kpow(pow.toFloat())
public override inline fun exp(arg: Float): Float = kotlin.math.exp(arg)
public override inline fun ln(arg: Float): Float = kotlin.math.ln(arg)
public override inline fun norm(arg: Float): Float = abs(arg)
public override inline fun Float.unaryMinus(): Float = -this
public override inline fun Float.plus(b: Float): Float = this + b
public override inline fun Float.minus(b: Float): Float = this - b
public override inline fun Float.times(b: Float): Float = this * b
public override inline fun Float.div(b: Float): Float = this / b
}
/**
* A field for [Int] without boxing. Does not produce corresponding ring element.
*/
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
public object IntRing : Ring<Int>, Norm<Int, Int> {
public override val zero: Int
get() = 0
public override val one: Int
get() = 1
public override inline fun add(a: Int, b: Int): Int = a + b
public override inline fun multiply(a: Int, k: Number): Int = k.toInt() * a
public override inline fun multiply(a: Int, b: Int): Int = a * b
public override inline fun norm(arg: Int): Int = abs(arg)
public override inline fun Int.unaryMinus(): Int = -this
public override inline fun Int.plus(b: Int): Int = this + b
public override inline fun Int.minus(b: Int): Int = this - b
public override inline fun Int.times(b: Int): Int = this * b
}
/**
* A field for [Short] without boxing. Does not produce appropriate ring element.
*/
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
public object ShortRing : Ring<Short>, Norm<Short, Short> {
public override val zero: Short
get() = 0
public override val one: Short
get() = 1
public override inline fun add(a: Short, b: Short): Short = (a + b).toShort()
public override inline fun multiply(a: Short, k: Number): Short = (a * k.toShort()).toShort()
public override inline fun multiply(a: Short, b: Short): Short = (a * b).toShort()
public override fun norm(arg: Short): Short = if (arg > 0) arg else (-arg).toShort()
public override inline fun Short.unaryMinus(): Short = (-this).toShort()
public override inline fun Short.plus(b: Short): Short = (this + b).toShort()
public override inline fun Short.minus(b: Short): Short = (this - b).toShort()
public override inline fun Short.times(b: Short): Short = (this * b).toShort()
}
/**
* A field for [Byte] without boxing. Does not produce appropriate ring element.
*/
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
public object ByteRing : Ring<Byte>, Norm<Byte, Byte> {
public override val zero: Byte
get() = 0
public override val one: Byte
get() = 1
public override inline fun add(a: Byte, b: Byte): Byte = (a + b).toByte()
public override inline fun multiply(a: Byte, k: Number): Byte = (a * k.toByte()).toByte()
public override inline fun multiply(a: Byte, b: Byte): Byte = (a * b).toByte()
public override fun norm(arg: Byte): Byte = if (arg > 0) arg else (-arg).toByte()
public override inline fun Byte.unaryMinus(): Byte = (-this).toByte()
public override inline fun Byte.plus(b: Byte): Byte = (this + b).toByte()
public override inline fun Byte.minus(b: Byte): Byte = (this - b).toByte()
public override inline fun Byte.times(b: Byte): Byte = (this * b).toByte()
}
/**
* A field for [Double] without boxing. Does not produce appropriate ring element.
*/
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
public object LongRing : Ring<Long>, Norm<Long, Long> {
public override val zero: Long
get() = 0
public override val one: Long
get() = 1
public override inline fun add(a: Long, b: Long): Long = a + b
public override inline fun multiply(a: Long, k: Number): Long = a * k.toLong()
public override inline fun multiply(a: Long, b: Long): Long = a * b
public override fun norm(arg: Long): Long = abs(arg)
public override inline fun Long.unaryMinus(): Long = (-this)
public override inline fun Long.plus(b: Long): Long = (this + b)
public override inline fun Long.minus(b: Long): Long = (this - b)
public override inline fun Long.times(b: Long): Long = (this * b)
}

124
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/OptionalOperations.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/operations/OptionalOperations.kt
View File

@ -1,234 +1,234 @@
package scientifik.kmath.operations
package kscience.kmath.operations
/**
* A container for trigonometric operations for specific type.
*
* @param T the type of element of this structure.
*/
interface TrigonometricOperations<T> : Algebra<T> {
public interface TrigonometricOperations<T> : Algebra<T> {
/**
* Computes the sine of [arg].
*/
fun sin(arg: T): T
public fun sin(arg: T): T
/**
* Computes the cosine of [arg].
*/
fun cos(arg: T): T
public fun cos(arg: T): T
/**
* Computes the tangent of [arg].
*/
fun tan(arg: T): T
public fun tan(arg: T): T
/**
* Computes the inverse sine of [arg].
*/
fun asin(arg: T): T
public fun asin(arg: T): T
/**
* Computes the inverse cosine of [arg].
*/
fun acos(arg: T): T
public fun acos(arg: T): T
/**
* Computes the inverse tangent of [arg].
*/
fun atan(arg: T): T
public fun atan(arg: T): T
companion object {
public companion object {
/**
* The identifier of sine.
*/
const val SIN_OPERATION: String = "sin"
public const val SIN_OPERATION: String = "sin"
/**
* The identifier of cosine.
*/
const val COS_OPERATION: String = "cos"
public const val COS_OPERATION: String = "cos"
/**
* The identifier of tangent.
*/
const val TAN_OPERATION: String = "tan"
public const val TAN_OPERATION: String = "tan"
/**
* The identifier of inverse sine.
*/
const val ASIN_OPERATION: String = "asin"
public const val ASIN_OPERATION: String = "asin"
/**
* The identifier of inverse cosine.
*/
const val ACOS_OPERATION: String = "acos"
public const val ACOS_OPERATION: String = "acos"
/**
* The identifier of inverse tangent.
*/
const val ATAN_OPERATION: String = "atan"
public const val ATAN_OPERATION: String = "atan"
}
}
/**
* Computes the sine of [arg].
*/
fun <T : MathElement<out TrigonometricOperations<T>>> sin(arg: T): T = arg.context.sin(arg)
public fun <T : MathElement<out TrigonometricOperations<T>>> sin(arg: T): T = arg.context.sin(arg)
/**
* Computes the cosine of [arg].
*/
fun <T : MathElement<out TrigonometricOperations<T>>> cos(arg: T): T = arg.context.cos(arg)
public fun <T : MathElement<out TrigonometricOperations<T>>> cos(arg: T): T = arg.context.cos(arg)
/**
* Computes the tangent of [arg].
*/
fun <T : MathElement<out TrigonometricOperations<T>>> tan(arg: T): T = arg.context.tan(arg)
public fun <T : MathElement<out TrigonometricOperations<T>>> tan(arg: T): T = arg.context.tan(arg)
/**
* Computes the inverse sine of [arg].
*/
fun <T : MathElement<out TrigonometricOperations<T>>> asin(arg: T): T = arg.context.asin(arg)
public fun <T : MathElement<out TrigonometricOperations<T>>> asin(arg: T): T = arg.context.asin(arg)
/**
* Computes the inverse cosine of [arg].
*/
fun <T : MathElement<out TrigonometricOperations<T>>> acos(arg: T): T = arg.context.acos(arg)
public fun <T : MathElement<out TrigonometricOperations<T>>> acos(arg: T): T = arg.context.acos(arg)
/**
* Computes the inverse tangent of [arg].
*/
fun <T : MathElement<out TrigonometricOperations<T>>> atan(arg: T): T = arg.context.atan(arg)
public fun <T : MathElement<out TrigonometricOperations<T>>> atan(arg: T): T = arg.context.atan(arg)
/**
* A container for hyperbolic trigonometric operations for specific type.
*
* @param T the type of element of this structure.
*/
interface HyperbolicOperations<T> : Algebra<T> {
public interface HyperbolicOperations<T> : Algebra<T> {
/**
* Computes the hyperbolic sine of [arg].
*/
fun sinh(arg: T): T
public fun sinh(arg: T): T
/**
* Computes the hyperbolic cosine of [arg].
*/
fun cosh(arg: T): T
public fun cosh(arg: T): T
/**
* Computes the hyperbolic tangent of [arg].
*/
fun tanh(arg: T): T
public fun tanh(arg: T): T
/**
* Computes the inverse hyperbolic sine of [arg].
*/
fun asinh(arg: T): T
public fun asinh(arg: T): T
/**
* Computes the inverse hyperbolic cosine of [arg].
*/
fun acosh(arg: T): T
public fun acosh(arg: T): T
/**
* Computes the inverse hyperbolic tangent of [arg].
*/
fun atanh(arg: T): T
public fun atanh(arg: T): T
companion object {
public companion object {
/**
* The identifier of hyperbolic sine.
*/
const val SINH_OPERATION: String = "sinh"
public const val SINH_OPERATION: String = "sinh"
/**
* The identifier of hyperbolic cosine.
*/
const val COSH_OPERATION: String = "cosh"
public const val COSH_OPERATION: String = "cosh"
/**
* The identifier of hyperbolic tangent.
*/
const val TANH_OPERATION: String = "tanh"
public const val TANH_OPERATION: String = "tanh"
/**
* The identifier of inverse hyperbolic sine.
*/
const val ASINH_OPERATION: String = "asinh"
public const val ASINH_OPERATION: String = "asinh"
/**
* The identifier of inverse hyperbolic cosine.
*/
const val ACOSH_OPERATION: String = "acosh"
public const val ACOSH_OPERATION: String = "acosh"
/**
* The identifier of inverse hyperbolic tangent.
*/
const val ATANH_OPERATION: String = "atanh"
public const val ATANH_OPERATION: String = "atanh"
}
}
/**
* Computes the hyperbolic sine of [arg].
*/
fun <T : MathElement<out HyperbolicOperations<T>>> sinh(arg: T): T = arg.context.sinh(arg)
public fun <T : MathElement<out HyperbolicOperations<T>>> sinh(arg: T): T = arg.context.sinh(arg)
/**
* Computes the hyperbolic cosine of [arg].
*/
fun <T : MathElement<out HyperbolicOperations<T>>> cosh(arg: T): T = arg.context.cosh(arg)
public fun <T : MathElement<out HyperbolicOperations<T>>> cosh(arg: T): T = arg.context.cosh(arg)
/**
* Computes the hyperbolic tangent of [arg].
*/
fun <T : MathElement<out HyperbolicOperations<T>>> tanh(arg: T): T = arg.context.tanh(arg)
public fun <T : MathElement<out HyperbolicOperations<T>>> tanh(arg: T): T = arg.context.tanh(arg)
/**
* Computes the inverse hyperbolic sine of [arg].
*/
fun <T : MathElement<out HyperbolicOperations<T>>> asinh(arg: T): T = arg.context.asinh(arg)
public fun <T : MathElement<out HyperbolicOperations<T>>> asinh(arg: T): T = arg.context.asinh(arg)
/**
* Computes the inverse hyperbolic cosine of [arg].
*/
fun <T : MathElement<out HyperbolicOperations<T>>> acosh(arg: T): T = arg.context.acosh(arg)
public fun <T : MathElement<out HyperbolicOperations<T>>> acosh(arg: T): T = arg.context.acosh(arg)
/**
* Computes the inverse hyperbolic tangent of [arg].
*/
fun <T : MathElement<out HyperbolicOperations<T>>> atanh(arg: T): T = arg.context.atanh(arg)
public fun <T : MathElement<out HyperbolicOperations<T>>> atanh(arg: T): T = arg.context.atanh(arg)
/**
* A context extension to include power operations based on exponentiation.
*
* @param T the type of element of this structure.
*/
interface PowerOperations<T> : Algebra<T> {
public interface PowerOperations<T> : Algebra<T> {
/**
* Raises [arg] to the power [pow].
*/
fun power(arg: T, pow: Number): T
public fun power(arg: T, pow: Number): T
/**
* Computes the square root of the value [arg].
*/
fun sqrt(arg: T): T = power(arg, 0.5)
public fun sqrt(arg: T): T = power(arg, 0.5)
/**
* Raises this value to the power [pow].
*/
infix fun T.pow(pow: Number): T = power(this, pow)
public infix fun T.pow(pow: Number): T = power(this, pow)
companion object {
public companion object {
/**
* The identifier of exponentiation.
*/
const val POW_OPERATION: String = "pow"
public const val POW_OPERATION: String = "pow"
/**
* The identifier of square root.
*/
const val SQRT_OPERATION: String = "sqrt"
public const val SQRT_OPERATION: String = "sqrt"
}
}
@ -239,56 +239,56 @@ interface PowerOperations<T> : Algebra<T> {
* @param power the exponent.
* @return the base raised to the power.
*/
infix fun <T : MathElement<out PowerOperations<T>>> T.pow(power: Double): T = context.power(this, power)
public infix fun <T : MathElement<out PowerOperations<T>>> T.pow(power: Double): T = context.power(this, power)
/**
* Computes the square root of the value [arg].
*/
fun <T : MathElement<out PowerOperations<T>>> sqrt(arg: T): T = arg pow 0.5
public fun <T : MathElement<out PowerOperations<T>>> sqrt(arg: T): T = arg pow 0.5
/**
* Computes the square of the value [arg].
*/
fun <T : MathElement<out PowerOperations<T>>> sqr(arg: T): T = arg pow 2.0
public fun <T : MathElement<out PowerOperations<T>>> sqr(arg: T): T = arg pow 2.0
/**
* A container for operations related to `exp` and `ln` functions.
*
* @param T the type of element of this structure.
*/
interface ExponentialOperations<T> : Algebra<T> {
public interface ExponentialOperations<T> : Algebra<T> {
/**
* Computes Euler's number `e` raised to the power of the value [arg].
*/
fun exp(arg: T): T
public fun exp(arg: T): T
/**
* Computes the natural logarithm (base `e`) of the value [arg].
*/
fun ln(arg: T): T
public fun ln(arg: T): T
companion object {
public companion object {
/**
* The identifier of exponential function.
*/
const val EXP_OPERATION: String = "exp"
public const val EXP_OPERATION: String = "exp"
/**
* The identifier of natural logarithm.
*/
const val LN_OPERATION: String = "ln"
public const val LN_OPERATION: String = "ln"
}
}
/**
* The identifier of exponential function.
*/
fun <T : MathElement<out ExponentialOperations<T>>> exp(arg: T): T = arg.context.exp(arg)
public fun <T : MathElement<out ExponentialOperations<T>>> exp(arg: T): T = arg.context.exp(arg)
/**
* The identifier of natural logarithm.
*/
fun <T : MathElement<out ExponentialOperations<T>>> ln(arg: T): T = arg.context.ln(arg)
public fun <T : MathElement<out ExponentialOperations<T>>> ln(arg: T): T = arg.context.ln(arg)
/**
* A container for norm functional on element.
@ -296,14 +296,14 @@ fun <T : MathElement<out ExponentialOperations<T>>> ln(arg: T): T = arg.context.
* @param T the type of element having norm defined.
* @param R the type of norm.
*/
interface Norm<in T : Any, out R> {
public interface Norm<in T : Any, out R> {
/**
* Computes the norm of [arg] (i.e. absolute value or vector length).
*/
fun norm(arg: T): R
public fun norm(arg: T): R
}
/**
* Computes the norm of [arg] (i.e. absolute value or vector length).
*/
fun <T : MathElement<out Norm<T, R>>, R> norm(arg: T): R = arg.context.norm(arg)
public fun <T : MathElement<out Norm<T, R>>, R> norm(arg: T): R = arg.context.norm(arg)

41
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BoxingNDField.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BoxingNDField.kt
View File

@ -1,31 +1,30 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import scientifik.kmath.operations.Field
import scientifik.kmath.operations.FieldElement
import kscience.kmath.operations.Field
import kscience.kmath.operations.FieldElement
class BoxingNDField<T, F : Field<T>>(
override val shape: IntArray,
override val elementContext: F,
val bufferFactory: BufferFactory<T>
public class BoxingNDField<T, F : Field<T>>(
public override val shape: IntArray,
public override val elementContext: F,
public val bufferFactory: BufferFactory<T>
) : BufferedNDField<T, F> {
override val zero: BufferedNDFieldElement<T, F> by lazy { produce { zero } }
override val one: BufferedNDFieldElement<T, F> by lazy { produce { one } }
override val strides: Strides = DefaultStrides(shape)
public override val zero: BufferedNDFieldElement<T, F> by lazy { produce { zero } }
public override val one: BufferedNDFieldElement<T, F> by lazy { produce { one } }
public override val strides: Strides = DefaultStrides(shape)
fun buildBuffer(size: Int, initializer: (Int) -> T): Buffer<T> =
public fun buildBuffer(size: Int, initializer: (Int) -> T): Buffer<T> =
bufferFactory(size, initializer)
override fun check(vararg elements: NDBuffer<T>): Array<out NDBuffer<T>> {
if (!elements.all { it.strides == this.strides }) error("Element strides are not the same as context strides")
return elements
public override fun check(vararg elements: NDBuffer<T>) {
check(elements.all { it.strides == strides }) { "Element strides are not the same as context strides" }
}
override fun produce(initializer: F.(IntArray) -> T): BufferedNDFieldElement<T, F> =
public override fun produce(initializer: F.(IntArray) -> T): BufferedNDFieldElement<T, F> =
BufferedNDFieldElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) })
override fun map(arg: NDBuffer<T>, transform: F.(T) -> T): BufferedNDFieldElement<T, F> {
public override fun map(arg: NDBuffer<T>, transform: F.(T) -> T): BufferedNDFieldElement<T, F> {
check(arg)
return BufferedNDFieldElement(
@ -37,7 +36,7 @@ class BoxingNDField<T, F : Field<T>>(
}
override fun mapIndexed(
public override fun mapIndexed(
arg: NDBuffer<T>,
transform: F.(index: IntArray, T) -> T
): BufferedNDFieldElement<T, F> {
@ -56,7 +55,7 @@ class BoxingNDField<T, F : Field<T>>(
// return BufferedNDFieldElement(this, buffer)
}
override fun combine(
public override fun combine(
a: NDBuffer<T>,
b: NDBuffer<T>,
transform: F.(T, T) -> T
@ -67,15 +66,15 @@ class BoxingNDField<T, F : Field<T>>(
buildBuffer(strides.linearSize) { offset -> elementContext.transform(a.buffer[offset], b.buffer[offset]) })
}
override fun NDBuffer<T>.toElement(): FieldElement<NDBuffer<T>, *, out BufferedNDField<T, F>> =
public override fun NDBuffer<T>.toElement(): FieldElement<NDBuffer<T>, *, out BufferedNDField<T, F>> =
BufferedNDFieldElement(this@BoxingNDField, buffer)
}
inline fun <T : Any, F : Field<T>, R> F.nd(
public inline fun <T : Any, F : Field<T>, R> F.nd(
noinline bufferFactory: BufferFactory<T>,
vararg shape: Int,
action: NDField<T, F, *>.() -> R
): R {
val ndfield: BoxingNDField<T, F> = NDField.boxing(this, *shape, bufferFactory = bufferFactory)
val ndfield = NDField.boxing(this, *shape, bufferFactory = bufferFactory)
return ndfield.action()
}

13
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BoxingNDRing.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BoxingNDRing.kt
View File

@ -1,18 +1,18 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import scientifik.kmath.operations.Ring
import scientifik.kmath.operations.RingElement
import kscience.kmath.operations.Ring
import kscience.kmath.operations.RingElement
class BoxingNDRing<T, R : Ring<T>>(
public class BoxingNDRing<T, R : Ring<T>>(
override val shape: IntArray,
override val elementContext: R,
val bufferFactory: BufferFactory<T>
public val bufferFactory: BufferFactory<T>
) : BufferedNDRing<T, R> {
override val strides: Strides = DefaultStrides(shape)
override val zero: BufferedNDRingElement<T, R> by lazy { produce { zero } }
override val one: BufferedNDRingElement<T, R> by lazy { produce { one } }
fun buildBuffer(size: Int, initializer: (Int) -> T): Buffer<T> = bufferFactory(size, initializer)
public fun buildBuffer(size: Int, initializer: (Int) -> T): Buffer<T> = bufferFactory(size, initializer)
override fun check(vararg elements: NDBuffer<T>): Array<out NDBuffer<T>> {
if (!elements.all { it.strides == this.strides }) error("Element strides are not the same as context strides")
@ -60,6 +60,7 @@ class BoxingNDRing<T, R : Ring<T>>(
transform: R.(T, T) -> T
): BufferedNDRingElement<T, R> {
check(a, b)
return BufferedNDRingElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.transform(a.buffer[offset], b.buffer[offset]) })

19
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BufferAccessor2D.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BufferAccessor2D.kt
View File

@ -1,28 +1,27 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import kotlin.reflect.KClass
/**
* A context that allows to operate on a [MutableBuffer] as on 2d array
*/
class BufferAccessor2D<T : Any>(val type: KClass<T>, val rowNum: Int, val colNum: Int) {
operator fun Buffer<T>.get(i: Int, j: Int): T = get(i + colNum * j)
public class BufferAccessor2D<T : Any>(public val type: KClass<T>, public val rowNum: Int, public val colNum: Int) {
public operator fun Buffer<T>.get(i: Int, j: Int): T = get(i + colNum * j)
operator fun MutableBuffer<T>.set(i: Int, j: Int, value: T) {
public operator fun MutableBuffer<T>.set(i: Int, j: Int, value: T) {
set(i + colNum * j, value)
}
inline fun create(init: (i: Int, j: Int) -> T): MutableBuffer<T> =
public inline fun create(init: (i: Int, j: Int) -> T): MutableBuffer<T> =
MutableBuffer.auto(type, rowNum * colNum) { offset -> init(offset / colNum, offset % colNum) }
fun create(mat: Structure2D<T>): MutableBuffer<T> = create { i, j -> mat[i, j] }
public fun create(mat: Structure2D<T>): MutableBuffer<T> = create { i, j -> mat[i, j] }
//TODO optimize wrapper
fun MutableBuffer<T>.collect(): Structure2D<T> =
public fun MutableBuffer<T>.collect(): Structure2D<T> =
NDStructure.auto(type, rowNum, colNum) { (i, j) -> get(i, j) }.as2D()
inner class Row(val buffer: MutableBuffer<T>, val rowIndex: Int) : MutableBuffer<T> {
public inner class Row(public val buffer: MutableBuffer<T>, public val rowIndex: Int) : MutableBuffer<T> {
override val size: Int get() = colNum
override operator fun get(index: Int): T = buffer[rowIndex, index]
@ -39,5 +38,5 @@ class BufferAccessor2D<T : Any>(val type: KClass<T>, val rowNum: Int, val colNum
/**
* Get row
*/
fun MutableBuffer<T>.row(i: Int): Row = Row(this, i)
public fun MutableBuffer<T>.row(i: Int): Row = Row(this, i)
}

41
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BufferedNDAlgebra.kt Normal file
View File

@ -0,0 +1,41 @@
package kscience.kmath.structures
import kscience.kmath.operations.*
public interface BufferedNDAlgebra<T, C> : NDAlgebra<T, C, NDBuffer<T>> {
public val strides: Strides
public override fun check(vararg elements: NDBuffer<T>): Unit =
require(elements.all { it.strides == strides }) { ("Strides mismatch") }
/**
* Convert any [NDStructure] to buffered structure using strides from this context.
* If the structure is already [NDBuffer], conversion is free. If not, it could be expensive because iteration over
* indices.
*
* If the argument is [NDBuffer] with different strides structure, the new element will be produced.
*/
public fun NDStructure<T>.toBuffer(): NDBuffer<T> =
if (this is NDBuffer<T> && this.strides == this@BufferedNDAlgebra.strides)
this
else
produce { index -> this@toBuffer[index] }
/**
* Convert a buffer to element of this algebra
*/
public fun NDBuffer<T>.toElement(): MathElement<out BufferedNDAlgebra<T, C>>
}
public interface BufferedNDSpace<T, S : Space<T>> : NDSpace<T, S, NDBuffer<T>>, BufferedNDAlgebra<T, S> {
public override fun NDBuffer<T>.toElement(): SpaceElement<NDBuffer<T>, *, out BufferedNDSpace<T, S>>
}
public interface BufferedNDRing<T, R : Ring<T>> : NDRing<T, R, NDBuffer<T>>, BufferedNDSpace<T, R> {
override fun NDBuffer<T>.toElement(): RingElement<NDBuffer<T>, *, out BufferedNDRing<T, R>>
}
public interface BufferedNDField<T, F : Field<T>> : NDField<T, F, NDBuffer<T>>, BufferedNDRing<T, F> {
override fun NDBuffer<T>.toElement(): FieldElement<NDBuffer<T>, *, out BufferedNDField<T, F>>
}

25
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BufferedNDElement.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BufferedNDElement.kt
View File

@ -1,11 +1,11 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import scientifik.kmath.operations.*
import kscience.kmath.operations.*
/**
* Base class for an element with context, containing strides
*/
abstract class BufferedNDElement<T, C> : NDBuffer<T>(), NDElement<T, C, NDBuffer<T>> {
public abstract class BufferedNDElement<T, C> : NDBuffer<T>(), NDElement<T, C, NDBuffer<T>> {
abstract override val context: BufferedNDAlgebra<T, C>
override val strides: Strides get() = context.strides
@ -13,7 +13,7 @@ abstract class BufferedNDElement<T, C> : NDBuffer<T>(), NDElement<T, C, NDBuffer
override val shape: IntArray get() = context.shape
}
class BufferedNDSpaceElement<T, S : Space<T>>(
public class BufferedNDSpaceElement<T, S : Space<T>>(
override val context: BufferedNDSpace<T, S>,
override val buffer: Buffer<T>
) : BufferedNDElement<T, S>(), SpaceElement<NDBuffer<T>, BufferedNDSpaceElement<T, S>, BufferedNDSpace<T, S>> {
@ -26,7 +26,7 @@ class BufferedNDSpaceElement<T, S : Space<T>>(
}
}
class BufferedNDRingElement<T, R : Ring<T>>(
public class BufferedNDRingElement<T, R : Ring<T>>(
override val context: BufferedNDRing<T, R>,
override val buffer: Buffer<T>
) : BufferedNDElement<T, R>(), RingElement<NDBuffer<T>, BufferedNDRingElement<T, R>, BufferedNDRing<T, R>> {
@ -38,7 +38,7 @@ class BufferedNDRingElement<T, R : Ring<T>>(
}
}
class BufferedNDFieldElement<T, F : Field<T>>(
public class BufferedNDFieldElement<T, F : Field<T>>(
override val context: BufferedNDField<T, F>,
override val buffer: Buffer<T>
) : BufferedNDElement<T, F>(), FieldElement<NDBuffer<T>, BufferedNDFieldElement<T, F>, BufferedNDField<T, F>> {
@ -54,22 +54,21 @@ class BufferedNDFieldElement<T, F : Field<T>>(
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy.
*/
operator fun <T : Any, F : Field<T>> Function1<T, T>.invoke(
ndElement: BufferedNDElement<T, F>
): MathElement<out BufferedNDAlgebra<T, F>> = ndElement.context.run { map(ndElement) { invoke(it) }.toElement() }
public operator fun <T : Any, F : Field<T>> Function1<T, T>.invoke(ndElement: BufferedNDElement<T, F>): MathElement<out BufferedNDAlgebra<T, F>> =
ndElement.context.run { map(ndElement) { invoke(it) }.toElement() }
/* plus and minus */
/**
* Summation operation for [BufferedNDElement] and single element
*/
operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.plus(arg: T): NDElement<T, F, NDBuffer<T>> =
public operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.plus(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it + arg }.wrap()
/**
* Subtraction operation between [BufferedNDElement] and single element
*/
operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.minus(arg: T): NDElement<T, F, NDBuffer<T>> =
public operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.minus(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it - arg }.wrap()
/* prod and div */
@ -77,11 +76,11 @@ operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.minus(arg: T): NDEl
/**
* Product operation for [BufferedNDElement] and single element
*/
operator fun <T : Any, F : Ring<T>> BufferedNDElement<T, F>.times(arg: T): NDElement<T, F, NDBuffer<T>> =
public operator fun <T : Any, F : Ring<T>> BufferedNDElement<T, F>.times(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it * arg }.wrap()
/**
* Division operation between [BufferedNDElement] and single element
*/
operator fun <T : Any, F : Field<T>> BufferedNDElement<T, F>.div(arg: T): NDElement<T, F, NDBuffer<T>> =
public operator fun <T : Any, F : Field<T>> BufferedNDElement<T, F>.div(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it / arg }.wrap()

82
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/Buffers.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt
View File

@ -1,8 +1,7 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import scientifik.kmath.operations.Complex
import scientifik.kmath.operations.complex
import kotlin.contracts.contract
import kscience.kmath.operations.Complex
import kscience.kmath.operations.complex
import kotlin.reflect.KClass
/**
@ -10,44 +9,44 @@ import kotlin.reflect.KClass
*
* @param T the type of buffer.
*/
typealias BufferFactory<T> = (Int, (Int) -> T) -> Buffer<T>
public typealias BufferFactory<T> = (Int, (Int) -> T) -> Buffer<T>
/**
* Function that produces [MutableBuffer] from its size and function that supplies values.
*
* @param T the type of buffer.
*/
typealias MutableBufferFactory<T> = (Int, (Int) -> T) -> MutableBuffer<T>
public typealias MutableBufferFactory<T> = (Int, (Int) -> T) -> MutableBuffer<T>
/**
* A generic immutable random-access structure for both primitives and objects.
*
* @param T the type of elements contained in the buffer.
*/
interface Buffer<T> {
public interface Buffer<T> {
/**
* The size of this buffer.
*/
val size: Int
public val size: Int
/**
* Gets element at given index.
*/
operator fun get(index: Int): T
public operator fun get(index: Int): T
/**
* Iterates over all elements.
*/
operator fun iterator(): Iterator<T>
public operator fun iterator(): Iterator<T>
/**
* Checks content equality with another buffer.
*/
fun contentEquals(other: Buffer<*>): Boolean =
public fun contentEquals(other: Buffer<*>): Boolean =
asSequence().mapIndexed { index, value -> value == other[index] }.all { it }
companion object {
inline fun real(size: Int, initializer: (Int) -> Double): RealBuffer {
public companion object {
public inline fun real(size: Int, initializer: (Int) -> Double): RealBuffer {
val array = DoubleArray(size) { initializer(it) }
return RealBuffer(array)
}
@ -55,10 +54,11 @@ interface Buffer<T> {
/**
* Create a boxing buffer of given type
*/
inline fun <T> boxing(size: Int, initializer: (Int) -> T): Buffer<T> = ListBuffer(List(size, initializer))
public inline fun <T> boxing(size: Int, initializer: (Int) -> T): Buffer<T> =
ListBuffer(List(size, initializer))
@Suppress("UNCHECKED_CAST")
inline fun <T : Any> auto(type: KClass<T>, size: Int, crossinline initializer: (Int) -> T): Buffer<T> {
public inline fun <T : Any> auto(type: KClass<T>, size: Int, crossinline initializer: (Int) -> T): Buffer<T> {
//TODO add resolution based on Annotation or companion resolution
return when (type) {
Double::class -> RealBuffer(DoubleArray(size) { initializer(it) as Double }) as Buffer<T>
@ -74,7 +74,7 @@ interface Buffer<T> {
* Create most appropriate immutable buffer for given type avoiding boxing wherever possible
*/
@Suppress("UNCHECKED_CAST")
inline fun <reified T : Any> auto(size: Int, crossinline initializer: (Int) -> T): Buffer<T> =
public inline fun <reified T : Any> auto(size: Int, crossinline initializer: (Int) -> T): Buffer<T> =
auto(T::class, size, initializer)
}
}
@ -82,43 +82,43 @@ interface Buffer<T> {
/**
* Creates a sequence that returns all elements from this [Buffer].
*/
fun <T> Buffer<T>.asSequence(): Sequence<T> = Sequence(::iterator)
public fun <T> Buffer<T>.asSequence(): Sequence<T> = Sequence(::iterator)
/**
* Creates an iterable that returns all elements from this [Buffer].
*/
fun <T> Buffer<T>.asIterable(): Iterable<T> = Iterable(::iterator)
public fun <T> Buffer<T>.asIterable(): Iterable<T> = Iterable(::iterator)
/**
* Returns an [IntRange] of the valid indices for this [Buffer].
*/
val Buffer<*>.indices: IntRange get() = 0 until size
public val Buffer<*>.indices: IntRange get() = 0 until size
/**
* A generic mutable random-access structure for both primitives and objects.
*
* @param T the type of elements contained in the buffer.
*/
interface MutableBuffer<T> : Buffer<T> {
public interface MutableBuffer<T> : Buffer<T> {
/**
* Sets the array element at the specified [index] to the specified [value].
*/
operator fun set(index: Int, value: T)
public operator fun set(index: Int, value: T)
/**
* Returns a shallow copy of the buffer.
*/
fun copy(): MutableBuffer<T>
public fun copy(): MutableBuffer<T>
companion object {
public companion object {
/**
* Create a boxing mutable buffer of given type
*/
inline fun <T> boxing(size: Int, initializer: (Int) -> T): MutableBuffer<T> =
public inline fun <T> boxing(size: Int, initializer: (Int) -> T): MutableBuffer<T> =
MutableListBuffer(MutableList(size, initializer))
@Suppress("UNCHECKED_CAST")
inline fun <T : Any> auto(type: KClass<out T>, size: Int, initializer: (Int) -> T): MutableBuffer<T> =
public inline fun <T : Any> auto(type: KClass<out T>, size: Int, initializer: (Int) -> T): MutableBuffer<T> =
when (type) {
Double::class -> RealBuffer(DoubleArray(size) { initializer(it) as Double }) as MutableBuffer<T>
Short::class -> ShortBuffer(ShortArray(size) { initializer(it) as Short }) as MutableBuffer<T>
@ -131,12 +131,11 @@ interface MutableBuffer<T> : Buffer<T> {
* Create most appropriate mutable buffer for given type avoiding boxing wherever possible
*/
@Suppress("UNCHECKED_CAST")
inline fun <reified T : Any> auto(size: Int, initializer: (Int) -> T): MutableBuffer<T> =
public inline fun <reified T : Any> auto(size: Int, initializer: (Int) -> T): MutableBuffer<T> =
auto(T::class, size, initializer)
val real: MutableBufferFactory<Double> = { size: Int, initializer: (Int) -> Double ->
RealBuffer(DoubleArray(size) { initializer(it) })
}
public val real: MutableBufferFactory<Double> =
{ size, initializer -> RealBuffer(DoubleArray(size) { initializer(it) }) }
}
}
@ -146,7 +145,7 @@ interface MutableBuffer<T> : Buffer<T> {
* @param T the type of elements contained in the buffer.
* @property list The underlying list.
*/
inline class ListBuffer<T>(val list: List<T>) : Buffer<T> {
public inline class ListBuffer<T>(public val list: List<T>) : Buffer<T> {
override val size: Int
get() = list.size
@ -157,7 +156,7 @@ inline class ListBuffer<T>(val list: List<T>) : Buffer<T> {
/**
* Returns an [ListBuffer] that wraps the original list.
*/
fun <T> List<T>.asBuffer(): ListBuffer<T> = ListBuffer(this)
public fun <T> List<T>.asBuffer(): ListBuffer<T> = ListBuffer(this)
/**
* Creates a new [ListBuffer] with the specified [size], where each element is calculated by calling the specified
@ -166,10 +165,7 @@ fun <T> List<T>.asBuffer(): ListBuffer<T> = ListBuffer(this)
* The function [init] is called for each array element sequentially starting from the first one.
* It should return the value for an array element given its index.
*/
inline fun <T> ListBuffer(size: Int, init: (Int) -> T): ListBuffer<T> {
contract { callsInPlace(init) }
return List(size, init).asBuffer()
}
public inline fun <T> ListBuffer(size: Int, init: (Int) -> T): ListBuffer<T> = List(size, init).asBuffer()
/**
* [MutableBuffer] implementation over [MutableList].
@ -177,7 +173,7 @@ inline fun <T> ListBuffer(size: Int, init: (Int) -> T): ListBuffer<T> {
* @param T the type of elements contained in the buffer.
* @property list The underlying list.
*/
inline class MutableListBuffer<T>(val list: MutableList<T>) : MutableBuffer<T> {
public inline class MutableListBuffer<T>(public val list: MutableList<T>) : MutableBuffer<T> {
override val size: Int
get() = list.size
@ -197,7 +193,7 @@ inline class MutableListBuffer<T>(val list: MutableList<T>) : MutableBuffer<T> {
* @param T the type of elements contained in the buffer.
* @property array The underlying array.
*/
class ArrayBuffer<T>(private val array: Array<T>) : MutableBuffer<T> {
public class ArrayBuffer<T>(private val array: Array<T>) : MutableBuffer<T> {
// Can't inline because array is invariant
override val size: Int
get() = array.size
@ -215,7 +211,7 @@ class ArrayBuffer<T>(private val array: Array<T>) : MutableBuffer<T> {
/**
* Returns an [ArrayBuffer] that wraps the original array.
*/
fun <T> Array<T>.asBuffer(): ArrayBuffer<T> = ArrayBuffer(this)
public fun <T> Array<T>.asBuffer(): ArrayBuffer<T> = ArrayBuffer(this)
/**
* Immutable wrapper for [MutableBuffer].
@ -223,7 +219,7 @@ fun <T> Array<T>.asBuffer(): ArrayBuffer<T> = ArrayBuffer(this)
* @param T the type of elements contained in the buffer.
* @property buffer The underlying buffer.
*/
inline class ReadOnlyBuffer<T>(val buffer: MutableBuffer<T>) : Buffer<T> {
public inline class ReadOnlyBuffer<T>(public val buffer: MutableBuffer<T>) : Buffer<T> {
override val size: Int get() = buffer.size
override operator fun get(index: Int): T = buffer[index]
@ -237,7 +233,7 @@ inline class ReadOnlyBuffer<T>(val buffer: MutableBuffer<T>) : Buffer<T> {
*
* @param T the type of elements provided by the buffer.
*/
class VirtualBuffer<T>(override val size: Int, private val generator: (Int) -> T) : Buffer<T> {
public class VirtualBuffer<T>(override val size: Int, private val generator: (Int) -> T) : Buffer<T> {
override operator fun get(index: Int): T {
if (index < 0 || index >= size) throw IndexOutOfBoundsException("Expected index from 0 to ${size - 1}, but found $index")
return generator(index)
@ -257,14 +253,14 @@ class VirtualBuffer<T>(override val size: Int, private val generator: (Int) -> T
/**
* Convert this buffer to read-only buffer.
*/
fun <T> Buffer<T>.asReadOnly(): Buffer<T> = if (this is MutableBuffer) ReadOnlyBuffer(this) else this
public fun <T> Buffer<T>.asReadOnly(): Buffer<T> = if (this is MutableBuffer) ReadOnlyBuffer(this) else this
/**
* Typealias for buffer transformations.
*/
typealias BufferTransform<T, R> = (Buffer<T>) -> Buffer<R>
public typealias BufferTransform<T, R> = (Buffer<T>) -> Buffer<R>
/**
* Typealias for buffer transformations with suspend function.
*/
typealias SuspendBufferTransform<T, R> = suspend (Buffer<T>) -> Buffer<R>
public typealias SuspendBufferTransform<T, R> = suspend (Buffer<T>) -> Buffer<R>

48
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/ComplexNDField.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/ComplexNDField.kt
View File

@ -1,18 +1,18 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import scientifik.kmath.operations.Complex
import scientifik.kmath.operations.ComplexField
import scientifik.kmath.operations.FieldElement
import scientifik.kmath.operations.complex
import kscience.kmath.operations.Complex
import kscience.kmath.operations.ComplexField
import kscience.kmath.operations.FieldElement
import kscience.kmath.operations.complex
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
typealias ComplexNDElement = BufferedNDFieldElement<Complex, ComplexField>
public typealias ComplexNDElement = BufferedNDFieldElement<Complex, ComplexField>
/**
* An optimized nd-field for complex numbers
*/
class ComplexNDField(override val shape: IntArray) :
public class ComplexNDField(override val shape: IntArray) :
BufferedNDField<Complex, ComplexField>,
ExtendedNDField<Complex, ComplexField, NDBuffer<Complex>> {
@ -21,7 +21,7 @@ class ComplexNDField(override val shape: IntArray) :
override val zero: ComplexNDElement by lazy { produce { zero } }
override val one: ComplexNDElement by lazy { produce { one } }
inline fun buildBuffer(size: Int, crossinline initializer: (Int) -> Complex): Buffer<Complex> =
public inline fun buildBuffer(size: Int, crossinline initializer: (Int) -> Complex): Buffer<Complex> =
Buffer.complex(size) { initializer(it) }
/**
@ -97,7 +97,7 @@ class ComplexNDField(override val shape: IntArray) :
/**
* Fast element production using function inlining
*/
inline fun BufferedNDField<Complex, ComplexField>.produceInline(crossinline initializer: ComplexField.(Int) -> Complex): ComplexNDElement {
public inline fun BufferedNDField<Complex, ComplexField>.produceInline(initializer: ComplexField.(Int) -> Complex): ComplexNDElement {
val buffer = Buffer.complex(strides.linearSize) { offset -> ComplexField.initializer(offset) }
return BufferedNDFieldElement(this, buffer)
}
@ -105,14 +105,13 @@ inline fun BufferedNDField<Complex, ComplexField>.produceInline(crossinline init
/**
* Map one [ComplexNDElement] using function with indices.
*/
inline fun ComplexNDElement.mapIndexed(crossinline transform: ComplexField.(index: IntArray, Complex) -> Complex): ComplexNDElement =
public inline fun ComplexNDElement.mapIndexed(transform: ComplexField.(index: IntArray, Complex) -> Complex): ComplexNDElement =
context.produceInline { offset -> transform(strides.index(offset), buffer[offset]) }
/**
* Map one [ComplexNDElement] using function without indices.
*/
inline fun ComplexNDElement.map(crossinline transform: ComplexField.(Complex) -> Complex): ComplexNDElement {
contract { callsInPlace(transform) }
public inline fun ComplexNDElement.map(transform: ComplexField.(Complex) -> Complex): ComplexNDElement {
val buffer = Buffer.complex(strides.linearSize) { offset -> ComplexField.transform(buffer[offset]) }
return BufferedNDFieldElement(context, buffer)
}
@ -120,38 +119,35 @@ inline fun ComplexNDElement.map(crossinline transform: ComplexField.(Complex) ->
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy
*/
operator fun Function1<Complex, Complex>.invoke(ndElement: ComplexNDElement): ComplexNDElement =
public operator fun Function1<Complex, Complex>.invoke(ndElement: ComplexNDElement): ComplexNDElement =
ndElement.map { this@invoke(it) }
/* plus and minus */
/**
* Summation operation for [BufferedNDElement] and single element
*/
operator fun ComplexNDElement.plus(arg: Complex): ComplexNDElement = map { it + arg }
public operator fun ComplexNDElement.plus(arg: Complex): ComplexNDElement = map { it + arg }
/**
* Subtraction operation between [BufferedNDElement] and single element
*/
operator fun ComplexNDElement.minus(arg: Complex): ComplexNDElement =
map { it - arg }
public operator fun ComplexNDElement.minus(arg: Complex): ComplexNDElement = map { it - arg }
operator fun ComplexNDElement.plus(arg: Double): ComplexNDElement =
map { it + arg }
public operator fun ComplexNDElement.plus(arg: Double): ComplexNDElement = map { it + arg }
public operator fun ComplexNDElement.minus(arg: Double): ComplexNDElement = map { it - arg }
operator fun ComplexNDElement.minus(arg: Double): ComplexNDElement =
map { it - arg }
public fun NDField.Companion.complex(vararg shape: Int): ComplexNDField = ComplexNDField(shape)
fun NDField.Companion.complex(vararg shape: Int): ComplexNDField = ComplexNDField(shape)
fun NDElement.Companion.complex(vararg shape: Int, initializer: ComplexField.(IntArray) -> Complex): ComplexNDElement =
NDField.complex(*shape).produce(initializer)
public fun NDElement.Companion.complex(
vararg shape: Int,
initializer: ComplexField.(IntArray) -> Complex
): ComplexNDElement = NDField.complex(*shape).produce(initializer)
/**
* Produce a context for n-dimensional operations inside this real field
*/
inline fun <R> ComplexField.nd(vararg shape: Int, action: ComplexNDField.() -> R): R {
public inline fun <R> ComplexField.nd(vararg shape: Int, action: ComplexNDField.() -> R): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return NDField.complex(*shape).action()
}

6
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/ExtendedNDField.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/ExtendedNDField.kt
View File

@ -1,6 +1,6 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import scientifik.kmath.operations.ExtendedField
import kscience.kmath.operations.ExtendedField
/**
* [ExtendedField] over [NDStructure].
@ -9,7 +9,7 @@ import scientifik.kmath.operations.ExtendedField
* @param N the type of ND structure.
* @param F the extended field of structure elements.
*/
interface ExtendedNDField<T : Any, F : ExtendedField<T>, N : NDStructure<T>> : NDField<T, F, N>, ExtendedField<N>
public interface ExtendedNDField<T : Any, F : ExtendedField<T>, N : NDStructure<T>> : NDField<T, F, N>, ExtendedField<N>
///**
// * NDField that supports [ExtendedField] operations on its elements

21
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/FlaggedBuffer.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/FlaggedBuffer.kt
View File

@ -1,6 +1,5 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import kotlin.contracts.contract
import kotlin.experimental.and
/**
@ -8,7 +7,7 @@ import kotlin.experimental.and
*
* @property mask bit mask value of this flag.
*/
enum class ValueFlag(val mask: Byte) {
public enum class ValueFlag(public val mask: Byte) {
/**
* Reports the value is NaN.
*/
@ -33,23 +32,23 @@ enum class ValueFlag(val mask: Byte) {
/**
* A buffer with flagged values.
*/
interface FlaggedBuffer<T> : Buffer<T> {
fun getFlag(index: Int): Byte
public interface FlaggedBuffer<T> : Buffer<T> {
public fun getFlag(index: Int): Byte
}
/**
* The value is valid if all flags are down
*/
fun FlaggedBuffer<*>.isValid(index: Int): Boolean = getFlag(index) != 0.toByte()
public fun FlaggedBuffer<*>.isValid(index: Int): Boolean = getFlag(index) != 0.toByte()
fun FlaggedBuffer<*>.hasFlag(index: Int, flag: ValueFlag): Boolean = (getFlag(index) and flag.mask) != 0.toByte()
public fun FlaggedBuffer<*>.hasFlag(index: Int, flag: ValueFlag): Boolean = (getFlag(index) and flag.mask) != 0.toByte()
fun FlaggedBuffer<*>.isMissing(index: Int): Boolean = hasFlag(index, ValueFlag.MISSING)
public fun FlaggedBuffer<*>.isMissing(index: Int): Boolean = hasFlag(index, ValueFlag.MISSING)
/**
* A real buffer which supports flags for each value like NaN or Missing
*/
class FlaggedRealBuffer(val values: DoubleArray, val flags: ByteArray) : FlaggedBuffer<Double?>, Buffer<Double?> {
public class FlaggedRealBuffer(public val values: DoubleArray, public val flags: ByteArray) : FlaggedBuffer<Double?>, Buffer<Double?> {
init {
require(values.size == flags.size) { "Values and flags must have the same dimensions" }
}
@ -65,9 +64,7 @@ class FlaggedRealBuffer(val values: DoubleArray, val flags: ByteArray) : Flagged
}.iterator()
}
inline fun FlaggedRealBuffer.forEachValid(block: (Double) -> Unit) {
contract { callsInPlace(block) }
public inline fun FlaggedRealBuffer.forEachValid(block: (Double) -> Unit) {
indices
.asSequence()
.filter(::isValid)

18
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/FloatBuffer.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/FloatBuffer.kt
View File

@ -1,13 +1,12 @@
package scientifik.kmath.structures
import kotlin.contracts.contract
package kscience.kmath.structures
/**
* Specialized [MutableBuffer] implementation over [FloatArray].
*
* @property array the underlying array.
* @author Iaroslav Postovalov
*/
inline class FloatBuffer(val array: FloatArray) : MutableBuffer<Float> {
public inline class FloatBuffer(public val array: FloatArray) : MutableBuffer<Float> {
override val size: Int get() = array.size
override operator fun get(index: Int): Float = array[index]
@ -29,20 +28,17 @@ inline class FloatBuffer(val array: FloatArray) : MutableBuffer<Float> {
* The function [init] is called for each array element sequentially starting from the first one.
* It should return the value for an buffer element given its index.
*/
inline fun FloatBuffer(size: Int, init: (Int) -> Float): FloatBuffer {
contract { callsInPlace(init) }
return FloatBuffer(FloatArray(size) { init(it) })
}
public inline fun FloatBuffer(size: Int, init: (Int) -> Float): FloatBuffer = FloatBuffer(FloatArray(size) { init(it) })
/**
* Returns a new [FloatBuffer] of given elements.
*/
fun FloatBuffer(vararg floats: Float): FloatBuffer = FloatBuffer(floats)
public fun FloatBuffer(vararg floats: Float): FloatBuffer = FloatBuffer(floats)
/**
* Returns a [FloatArray] containing all of the elements of this [MutableBuffer].
*/
val MutableBuffer<out Float>.array: FloatArray
public val MutableBuffer<out Float>.array: FloatArray
get() = (if (this is FloatBuffer) array else FloatArray(size) { get(it) })
/**
@ -51,4 +47,4 @@ val MutableBuffer<out Float>.array: FloatArray
* @receiver the array.
* @return the new buffer.
*/
fun FloatArray.asBuffer(): FloatBuffer = FloatBuffer(this)
public fun FloatArray.asBuffer(): FloatBuffer = FloatBuffer(this)

14
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/IntBuffer.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/IntBuffer.kt
View File

@ -1,13 +1,11 @@
package scientifik.kmath.structures
import kotlin.contracts.contract
package kscience.kmath.structures
/**
* Specialized [MutableBuffer] implementation over [IntArray].
*
* @property array the underlying array.
*/
inline class IntBuffer(val array: IntArray) : MutableBuffer<Int> {
public inline class IntBuffer(public val array: IntArray) : MutableBuffer<Int> {
override val size: Int get() = array.size
override operator fun get(index: Int): Int = array[index]
@ -29,17 +27,17 @@ inline class IntBuffer(val array: IntArray) : MutableBuffer<Int> {
* The function [init] is called for each array element sequentially starting from the first one.
* It should return the value for an buffer element given its index.
*/
inline fun IntBuffer(size: Int, init: (Int) -> Int): IntBuffer = IntBuffer(IntArray(size) { init(it) })
public inline fun IntBuffer(size: Int, init: (Int) -> Int): IntBuffer = IntBuffer(IntArray(size) { init(it) })
/**
* Returns a new [IntBuffer] of given elements.
*/
fun IntBuffer(vararg ints: Int): IntBuffer = IntBuffer(ints)
public fun IntBuffer(vararg ints: Int): IntBuffer = IntBuffer(ints)
/**
* Returns a [IntArray] containing all of the elements of this [MutableBuffer].
*/
val MutableBuffer<out Int>.array: IntArray
public val MutableBuffer<out Int>.array: IntArray
get() = (if (this is IntBuffer) array else IntArray(size) { get(it) })
/**
@ -48,4 +46,4 @@ val MutableBuffer<out Int>.array: IntArray
* @receiver the array.
* @return the new buffer.
*/
fun IntArray.asBuffer(): IntBuffer = IntBuffer(this)
public fun IntArray.asBuffer(): IntBuffer = IntBuffer(this)

18
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/LongBuffer.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/LongBuffer.kt
View File

@ -1,13 +1,11 @@
package scientifik.kmath.structures
import kotlin.contracts.contract
package kscience.kmath.structures
/**
* Specialized [MutableBuffer] implementation over [LongArray].
*
* @property array the underlying array.
*/
inline class LongBuffer(val array: LongArray) : MutableBuffer<Long> {
public inline class LongBuffer(public val array: LongArray) : MutableBuffer<Long> {
override val size: Int get() = array.size
override operator fun get(index: Int): Long = array[index]
@ -20,7 +18,6 @@ inline class LongBuffer(val array: LongArray) : MutableBuffer<Long> {
override fun copy(): MutableBuffer<Long> =
LongBuffer(array.copyOf())
}
/**
@ -30,20 +27,17 @@ inline class LongBuffer(val array: LongArray) : MutableBuffer<Long> {
* The function [init] is called for each array element sequentially starting from the first one.
* It should return the value for an buffer element given its index.
*/
inline fun LongBuffer(size: Int, init: (Int) -> Long): LongBuffer {
contract { callsInPlace(init) }
return LongBuffer(LongArray(size) { init(it) })
}
public inline fun LongBuffer(size: Int, init: (Int) -> Long): LongBuffer = LongBuffer(LongArray(size) { init(it) })
/**
* Returns a new [LongBuffer] of given elements.
*/
fun LongBuffer(vararg longs: Long): LongBuffer = LongBuffer(longs)
public fun LongBuffer(vararg longs: Long): LongBuffer = LongBuffer(longs)
/**
* Returns a [IntArray] containing all of the elements of this [MutableBuffer].
*/
val MutableBuffer<out Long>.array: LongArray
public val MutableBuffer<out Long>.array: LongArray
get() = (if (this is LongBuffer) array else LongArray(size) { get(it) })
/**
@ -52,4 +46,4 @@ val MutableBuffer<out Long>.array: LongArray
* @receiver the array.
* @return the new buffer.
*/
fun LongArray.asBuffer(): LongBuffer = LongBuffer(this)
public fun LongArray.asBuffer(): LongBuffer = LongBuffer(this)

40
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/MemoryBuffer.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/structures/MemoryBuffer.kt
View File

@ -1,6 +1,6 @@
package scientifik.kmath.structures
package kscience.kmath.structures
import scientifik.memory.*
import kscience.memory.*
/**
* A non-boxing buffer over [Memory] object.
@ -9,7 +9,7 @@ import scientifik.memory.*
* @property memory the underlying memory segment.
* @property spec the spec of [T] type.
*/
open class MemoryBuffer<T : Any>(protected val memory: Memory, protected val spec: MemorySpec<T>) : Buffer<T> {
public open class MemoryBuffer<T : Any>(protected val memory: Memory, protected val spec: MemorySpec<T>) : Buffer<T> {
override val size: Int get() = memory.size / spec.objectSize
private val reader: MemoryReader = memory.reader()
@ -17,20 +17,17 @@ open class MemoryBuffer<T : Any>(protected val memory: Memory, protected val spe
override operator fun get(index: Int): T = reader.read(spec, spec.objectSize * index)
override operator fun iterator(): Iterator<T> = (0 until size).asSequence().map { get(it) }.iterator()
companion object {
fun <T : Any> create(spec: MemorySpec<T>, size: Int): MemoryBuffer<T> =
public companion object {
public fun <T : Any> create(spec: MemorySpec<T>, size: Int): MemoryBuffer<T> =
MemoryBuffer(Memory.allocate(size * spec.objectSize), spec)
inline fun <T : Any> create(
public inline fun <T : Any> create(
spec: MemorySpec<T>,
size: Int,
crossinline initializer: (Int) -> T
): MemoryBuffer<T> =
MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
(0 until size).forEach {
buffer[it] = initializer(it)
}
}
initializer: (Int) -> T
): MemoryBuffer<T> = MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
(0 until size).forEach { buffer[it] = initializer(it) }
}
}
}
@ -41,7 +38,7 @@ open class MemoryBuffer<T : Any>(protected val memory: Memory, protected val spe
* @property memory the underlying memory segment.
* @property spec the spec of [T] type.
*/
class MutableMemoryBuffer<T : Any>(memory: Memory, spec: MemorySpec<T>) : MemoryBuffer<T>(memory, spec),
public class MutableMemoryBuffer<T : Any>(memory: Memory, spec: MemorySpec<T>) : MemoryBuffer<T>(memory, spec),
MutableBuffer<T> {
private val writer: MemoryWriter = memory.writer()
@ -49,19 +46,16 @@ class MutableMemoryBuffer<T : Any>(memory: Memory, spec: MemorySpec<T>) : Memory
override operator fun set(index: Int, value: T): Unit = writer.write(spec, spec.objectSize * index, value)
override fun copy(): MutableBuffer<T> = MutableMemoryBuffer(memory.copy(), spec)
companion object {
fun <T : Any> create(spec: MemorySpec<T>, size: Int): MutableMemoryBuffer<T> =
public companion object {
public fun <T : Any> create(spec: MemorySpec<T>, size: Int): MutableMemoryBuffer<T> =
MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec)
inline fun <T : Any> create(
public inline fun <T : Any> create(
spec: MemorySpec<T>,
size: Int,
crossinline initializer: (Int) -> T
): MutableMemoryBuffer<T> =
MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
(0 until size).forEach {
buffer[it] = initializer(it)
}
}
): MutableMemoryBuffer<T> = MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
(0 until size).forEach { buffer[it] = initializer(it) }
}
}
}

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