kscience/kmath
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Merge branch 'dev' into feature/mp-samplers

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# Conflicts:
#	examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt
#	examples/src/main/kotlin/space/kscience/kmath/stat/DistributionBenchmark.kt
#	examples/src/main/kotlin/space/kscience/kmath/stat/DistributionDemo.kt
#	kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt
#	kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt
#	kmath-coroutines/src/commonMain/kotlin/kscience/kmath/chains/BlockingRealChain.kt
#	kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/SamplerAlgebra.kt
#	kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Distribution.kt
#	kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/RandomChain.kt
#	kmath-stat/src/jvmMain/kotlin/space/kscience/kmath/stat/distributions.kt
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Iaroslav Postovalov 2021-03-31 01:48:26 +07:00
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107
.github/workflows/build.yml vendored
View File

@ -3,105 +3,34 @@ name: Gradle build
on: [ push ]
jobs:
build-ubuntu:
runs-on: ubuntu-20.04
build:
strategy:
matrix:
os: [ macOS-latest, windows-latest ]
runs-on: ${{matrix.os}}
steps:
- uses: actions/checkout@v2
- name: Checkout the repo
uses: actions/checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v1
with:
java-version: 11
- name: Grant execute permission for gradlew
run: chmod +x gradlew
- name: Install Chrome
run: |
sudo apt install -y libappindicator1 fonts-liberation
wget https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb
sudo dpkg -i google-chrome*.deb
- name: Cache gradle
uses: actions/cache@v2
with:
path: |
.gradle
build
~/.gradle
key: gradle
restore-keys: gradle
- name: Cache konan
uses: actions/cache@v2
with:
path: |
~/.konan/dependencies
~/.konan/kotlin-native-prebuilt-linux-*
key: ${{ runner.os }}-konan
restore-keys: ${{ runner.os }}-konan
- name: Build with Gradle
run: ./gradlew -Dorg.gradle.daemon=false --build-cache build
build-osx:
runs-on: macos-latest
steps:
- uses: actions/checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v1
with:
java-version: 11
- name: Grant execute permission for gradlew
run: chmod +x gradlew
- name: Cache gradle
uses: actions/cache@v2
with:
path: |
.gradle
build
~/.gradle
key: gradle
restore-keys: gradle
- name: Cache konan
uses: actions/cache@v2
with:
path: |
~/.konan/dependencies
~/.konan/kotlin-native-prebuilt-macos-*
key: ${{ runner.os }}-konan
restore-keys: ${{ runner.os }}-konan
- name: Build with Gradle
run: sudo ./gradlew -Dorg.gradle.daemon=false --build-cache build
build-windows:
runs-on: windows-latest
steps:
- uses: actions/checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v1
with:
java-version: 11
- name: Grant execute permission for gradlew
run: chmod +x gradlew
- name: Add msys to path
if: matrix.os == 'windows-latest'
run: SETX PATH "%PATH%;C:\msys64\mingw64\bin"
- name: Cache gradle
uses: actions/cache@v2
with:
path: |
.gradle
build
~/.gradle
key: ${{ runner.os }}-gradle
restore-keys: ${{ runner.os }}-gradle
path: ~/.gradle/caches
key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }}
restore-keys: |
${{ runner.os }}-gradle-
- name: Cache konan
uses: actions/cache@v2
with:
path: |
~/.konan/dependencies
~/.konan/kotlin-native-prebuilt-mingw-*
key: ${{ runner.os }}-konan
restore-keys: ${{ runner.os }}-konan
- name: Build with Gradle
run: ./gradlew --build-cache build
path: ~/.konan
key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }}
restore-keys: |
${{ runner.os }}-gradle-
- name: Build
run: ./gradlew build --no-daemon --stacktrace

40
.github/workflows/pages.yml vendored Normal file
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@ -0,0 +1,40 @@
name: Dokka publication
on:
push:
branches:
- master
jobs:
build:
runs-on: ubuntu-20.04
steps:
- name: Checkout the repo
uses: actions/checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v1
with:
java-version: 11
- name: Cache gradle
uses: actions/cache@v2
with:
path: ~/.gradle/caches
key: ubuntu-20.04-gradle-${{ hashFiles('*.gradle.kts') }}
restore-keys: |
ubuntu-20.04-gradle-
- name: Cache konan
uses: actions/cache@v2
with:
path: ~/.konan
key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }}
restore-keys: |
${{ runner.os }}-gradle-
- name: Build
run: |
./gradlew dokkaHtmlMultiModule --no-daemon --no-parallel --stacktrace
mv build/dokka/htmlMultiModule/-modules.html build/dokka/htmlMultiModule/index.html
- name: Deploy to GitHub Pages
uses: JamesIves/github-pages-deploy-action@4.1.0
with:
branch: gh-pages
folder: build/dokka/htmlMultiModule

136
.github/workflows/publish.yml vendored
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@ -1,117 +1,59 @@
name: Bintray Publish
name: Gradle publish
on:
workflow_dispatch:
release:
types:
- created
jobs:
build-ubuntu:
runs-on: ubuntu-20.04
publish:
environment:
name: publish
strategy:
matrix:
os: [ macOS-latest, windows-latest ]
runs-on: ${{matrix.os}}
steps:
- uses: actions/checkout@v2
- name: Checkout the repo
uses: actions/checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v1
with:
java-version: 11
- name: Grant execute permission for gradlew
run: chmod +x gradlew
- name: Install Chrome
run: |
sudo apt install -y libappindicator1 fonts-liberation
wget https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb
sudo dpkg -i google-chrome*.deb
- name: Cache gradle
uses: actions/cache@v2
with:
path: |
.gradle
build
~/.gradle
key: gradle
restore-keys: gradle
- name: Cache konan
uses: actions/cache@v2
with:
path: |
~/.konan/dependencies
~/.konan/kotlin-native-prebuilt-linux-*
key: ${{ runner.os }}-konan
restore-keys: ${{ runner.os }}-konan
- name: Build with Gradle
run: ./gradlew -Dorg.gradle.daemon=false --build-cache build
- name: Run release task
run: ./gradlew release -PbintrayUser=${{ secrets.BINTRAY_USER }} -PbintrayApiKey=${{ secrets.BINTRAY_KEY }}
build-osx:
runs-on: macos-latest
steps:
- uses: actions/checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v1
with:
java-version: 11
- name: Grant execute permission for gradlew
run: chmod +x gradlew
- name: Cache gradle
uses: actions/cache@v2
with:
path: |
.gradle
build
~/.gradle
key: gradle
restore-keys: gradle
- name: Cache konan
uses: actions/cache@v2
with:
path: |
~/.konan/dependencies
~/.konan/kotlin-native-prebuilt-macos-*
key: ${{ runner.os }}-konan
restore-keys: ${{ runner.os }}-konan
- name: Build with Gradle
run: sudo ./gradlew -Dorg.gradle.daemon=false --build-cache build
- name: Run release task
run: ./gradlew release -PbintrayUser=${{ secrets.BINTRAY_USER }} -PbintrayApiKey=${{ secrets.BINTRAY_KEY }}
build-windows:
runs-on: windows-latest
steps:
- uses: actions/checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v1
with:
java-version: 11
- name: Grant execute permission for gradlew
run: chmod +x gradlew
- name: Add msys to path
if: matrix.os == 'windows-latest'
run: SETX PATH "%PATH%;C:\msys64\mingw64\bin"
- name: Cache gradle
uses: actions/cache@v2
with:
path: |
.gradle
build
~/.gradle
key: ${{ runner.os }}-gradle
restore-keys: ${{ runner.os }}-gradle
path: ~/.gradle/caches
key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }}
restore-keys: |
${{ runner.os }}-gradle-
- name: Cache konan
uses: actions/cache@v2
with:
path: |
~/.konan/dependencies
~/.konan/kotlin-native-prebuilt-mingw-*
key: ${{ runner.os }}-konan
restore-keys: ${{ runner.os }}-konan
- name: Build with Gradle
run: ./gradlew --build-cache build
- name: Run release task
run: ./gradlew release -PbintrayUser=${{ secrets.BINTRAY_USER }} -PbintrayApiKey=${{ secrets.BINTRAY_KEY }}
path: ~/.konan
key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }}
restore-keys: |
${{ runner.os }}-gradle-
- name: Publish Windows Artifacts
if: matrix.os == 'windows-latest'
run: >
./gradlew release --no-daemon
-Ppublishing.enabled=true
-Ppublishing.github.user=${{ secrets.PUBLISHING_GITHUB_USER }}
-Ppublishing.github.token=${{ secrets.PUBLISHING_GITHUB_TOKEN }}
-Ppublishing.space.user=${{ secrets.PUBLISHING_SPACE_USER }}
-Ppublishing.space.token=${{ secrets.PUBLISHING_SPACE_TOKEN }}
- name: Publish Mac Artifacts
if: matrix.os == 'macOS-latest'
run: >
./gradlew release --no-daemon
-Ppublishing.enabled=true
-Ppublishing.platform=macosX64
-Ppublishing.github.user=${{ secrets.PUBLISHING_GITHUB_USER }}
-Ppublishing.github.token=${{ secrets.PUBLISHING_GITHUB_TOKEN }}
-Ppublishing.space.user=${{ secrets.PUBLISHING_SPACE_USER }}
-Ppublishing.space.token=${{ secrets.PUBLISHING_SPACE_TOKEN }}

5
.gitignore vendored
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@ -2,9 +2,14 @@
build/
out/
.idea/
.vscode/
# Avoid ignoring Gradle wrapper jar file (.jar files are usually ignored)
!gradle-wrapper.jar
# Cache of project
.gradletasknamecache
# Generated by javac -h and runtime
*.class
*.log

35
CHANGELOG.md
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@ -2,6 +2,32 @@
## [Unreleased]
### Added
- ScaleOperations interface
- Field extends ScaleOperations
- Basic integration API
### Changed
- Exponential operations merged with hyperbolic functions
- Space is replaced by Group. Space is reserved for vector spaces.
- VectorSpace is now a vector space
- Buffer factories for primitives moved to MutableBuffer.Companion
- NDStructure and NDAlgebra to StructureND and AlgebraND respectively
- Real -> Double
- DataSets are moved from functions to core
### Deprecated
### Removed
- Nearest in Domain. To be implemented in geometry package.
- Number multiplication and division in main Algebra chain
- `contentEquals` from Buffer. It moved to the companion.
### Fixed
### Security
## [0.2.0]
### 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)
@ -21,11 +47,11 @@
- Basic Quaternion vector support in `kmath-complex`.
### Changed
- Package changed from `scientifik` to `kscience.kmath`
- Gradle version: 6.6 -> 6.8
- Package changed from `scientifik` to `space.kscience`
- Gradle version: 6.6 -> 6.8.2
- Minor exceptions refactor (throwing `IllegalArgumentException` by argument checks instead of `IllegalStateException`)
- `Polynomial` secondary constructor made function
- Kotlin version: 1.3.72 -> 1.4.21
- Kotlin version: 1.3.72 -> 1.4.30
- `kmath-ast` doesn't depend on heavy `kotlin-reflect` library
- Full autodiff refactoring based on `Symbol`
- `kmath-prob` renamed to `kmath-stat`
@ -41,6 +67,8 @@
- Refactor histograms. They are marked as prototype
- `Complex` and related features moved to a separate module `kmath-complex`
- Refactor AlgebraElement
- `symbol` method in `Algebra` renamed to `bindSymbol` to avoid ambiguity
- Add `out` projection to `Buffer` generic
### Deprecated
@ -50,6 +78,7 @@
- `toGrid` method.
- Public visibility of `BufferAccessor2D`
- `Real` class
- StructureND identity and equals
### Fixed
- `symbol` method in `MstExtendedField` (https://github.com/mipt-npm/kmath/pull/140)

84
README.md
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@ -1,11 +1,8 @@
[![JetBrains Research](https://jb.gg/badges/research.svg)](https://confluence.jetbrains.com/display/ALL/JetBrains+on+GitHub)
[![DOI](https://zenodo.org/badge/129486382.svg)](https://zenodo.org/badge/latestdoi/129486382)
![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg)
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)
[![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22)
[![Space](https://img.shields.io/maven-metadata/v?label=Space&metadataUrl=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fkscience%2Fkmath%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/)
# KMath
@ -89,12 +86,12 @@ KMath is a modular library. Different modules provide different features with di
> **Maturity**: PROTOTYPE
>
> **Features:**
> - [expression-language](kmath-ast/src/jvmMain/kotlin/kscience/kmath/ast/parser.kt) : Expression language and its parser
> - [mst](kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MST.kt) : MST (Mathematical Syntax Tree) as expression language's syntax intermediate representation
> - [mst-building](kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MstAlgebra.kt) : MST building algebraic structure
> - [mst-interpreter](kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MST.kt) : MST interpreter
> - [mst-jvm-codegen](kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/asm.kt) : Dynamic MST to JVM bytecode compiler
> - [mst-js-codegen](kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/estree.kt) : Dynamic MST to JS compiler
> - [expression-language](kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/ast/parser.kt) : Expression language and its parser
> - [mst](kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/MST.kt) : MST (Mathematical Syntax Tree) as expression language's syntax intermediate representation
> - [mst-building](kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/MstAlgebra.kt) : MST building algebraic structure
> - [mst-interpreter](kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/MST.kt) : MST interpreter
> - [mst-jvm-codegen](kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt) : Dynamic MST to JVM bytecode compiler
> - [mst-js-codegen](kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt) : Dynamic MST to JS compiler
<hr/>
@ -110,8 +107,8 @@ KMath is a modular library. Different modules provide different features with di
> **Maturity**: PROTOTYPE
>
> **Features:**
> - [complex](kmath-complex/src/commonMain/kotlin/kscience/kmath/complex/Complex.kt) : Complex Numbers
> - [quaternion](kmath-complex/src/commonMain/kotlin/kscience/kmath/complex/Quaternion.kt) : Quaternions
> - [complex](kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt) : Complex Numbers
> - [quaternion](kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt) : Quaternions
<hr/>
@ -121,15 +118,15 @@ KMath is a modular library. Different modules provide different features with di
> **Maturity**: DEVELOPMENT
>
> **Features:**
> - [algebras](kmath-core/src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt) : Algebraic structures like rings, spaces and fields.
> - [nd](kmath-core/src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt) : Many-dimensional structures and operations on them.
> - [linear](kmath-core/src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt) : Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. Advanced linear algebra operations like matrix inversion and LU decomposition.
> - [buffers](kmath-core/src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
> - [expressions](kmath-core/src/commonMain/kotlin/kscience/kmath/expressions) : By writing a single mathematical expression once, users will be able to apply different types of
> - [algebras](kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt) : Algebraic structures like rings, spaces and fields.
> - [nd](kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/StructureND.kt) : Many-dimensional structures and operations on them.
> - [linear](kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt) : Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. Advanced linear algebra operations like matrix inversion and LU decomposition.
> - [buffers](kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
> - [expressions](kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions) : By writing a single mathematical expression once, users will be able to apply different types of
objects to the expression by providing a context. Expressions can be used for a wide variety of purposes from high
performance calculations to code generation.
> - [domains](kmath-core/src/commonMain/kotlin/kscience/kmath/domains) : Domains
> - [autodif](kmath-core/src/commonMain/kotlin/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation
> - [domains](kmath-core/src/commonMain/kotlin/space/kscience/kmath/domains) : Domains
> - [autodif](kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation
<hr/>
@ -149,6 +146,12 @@ performance calculations to code generation.
>
>
> **Maturity**: PROTOTYPE
>
> **Features:**
> - [ejml-vector](kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt) : The Point implementation using SimpleMatrix.
> - [ejml-matrix](kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt) : The Matrix implementation using SimpleMatrix.
> - [ejml-linear-space](kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt) : The LinearSpace implementation using SimpleMatrix.
<hr/>
* ### [kmath-for-real](kmath-for-real)
@ -159,9 +162,9 @@ One can still use generic algebras though.
> **Maturity**: EXPERIMENTAL
>
> **Features:**
> - [RealVector](kmath-for-real/src/commonMain/kotlin/kscience/kmath/real/RealVector.kt) : Numpy-like operations for Buffers/Points
> - [RealMatrix](kmath-for-real/src/commonMain/kotlin/kscience/kmath/real/RealMatrix.kt) : Numpy-like operations for 2d real structures
> - [grids](kmath-for-real/src/commonMain/kotlin/kscience/kmath/structures/grids.kt) : Uniform grid generators
> - [DoubleVector](kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/DoubleVector.kt) : Numpy-like operations for Buffers/Points
> - [DoubleMatrix](kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/DoubleMatrix.kt) : Numpy-like operations for 2d real structures
> - [grids](kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/structures/grids.kt) : Uniform grid generators
<hr/>
@ -171,10 +174,10 @@ One can still use generic algebras though.
> **Maturity**: PROTOTYPE
>
> **Features:**
> - [piecewise](kmath-functions/Piecewise functions.) : src/commonMain/kotlin/kscience/kmath/functions/Piecewise.kt
> - [polynomials](kmath-functions/Polynomial functions.) : src/commonMain/kotlin/kscience/kmath/functions/Polynomial.kt
> - [linear interpolation](kmath-functions/Linear XY interpolator.) : src/commonMain/kotlin/kscience/kmath/interpolation/LinearInterpolator.kt
> - [spline interpolation](kmath-functions/Cubic spline XY interpolator.) : src/commonMain/kotlin/kscience/kmath/interpolation/SplineInterpolator.kt
> - [piecewise](kmath-functions/Piecewise functions.) : src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt
> - [polynomials](kmath-functions/Polynomial functions.) : src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt
> - [linear interpolation](kmath-functions/Linear XY interpolator.) : src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt
> - [spline interpolation](kmath-functions/Cubic spline XY interpolator.) : src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt
<hr/>
@ -208,9 +211,9 @@ One can still use generic algebras though.
> **Maturity**: EXPERIMENTAL
>
> **Features:**
> - [nd4jarraystructure](kmath-nd4j/src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt) : NDStructure wrapper for INDArray
> - [nd4jarrayrings](kmath-nd4j/src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt) : Rings over Nd4jArrayStructure of Int and Long
> - [nd4jarrayfields](kmath-nd4j/src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt) : Fields over Nd4jArrayStructure of Float and Double
> - [nd4jarraystructure](kmath-nd4j/#) : NDStructure wrapper for INDArray
> - [nd4jarrayrings](kmath-nd4j/#) : Rings over Nd4jArrayStructure of Int and Long
> - [nd4jarrayfields](kmath-nd4j/#) : Fields over Nd4jArrayStructure of Float and Double
<hr/>
@ -247,33 +250,22 @@ better than SciPy.
### Repositories
Release artifacts are accessible from bintray with following configuration (see documentation of
[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details):
Release and development artifacts are accessible from mipt-npm [Space](https://www.jetbrains.com/space/) repository `https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven` (see documentation of
[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details). The repository could be reached through [repo.kotlin.link](https://repo.kotlin.link) proxy:
```kotlin
repositories {
maven("https://dl.bintray.com/mipt-npm/kscience")
// maven("https://dl.bintray.com/mipt-npm/dev") for dev versions
maven("https://repo.kotlin.link")
}
dependencies {
api("kscience.kmath:kmath-core:0.2.0-dev-7")
// api("kscience.kmath:kmath-core-jvm:0.2.0-dev-7") for jvm-specific version
api("space.kscience:kmath-core:0.3.0-dev-3")
// api("kscience.kmath:kmath-core-jvm:0.3.0-dev-3") for jvm-specific version
}
```
Gradle `6.0+` is required for multiplatform artifacts.
#### Development
Development builds are uploaded to the separate repository:
```kotlin
repositories {
maven("https://dl.bintray.com/mipt-npm/dev")
}
```
## Contributing
The project requires a lot of additional work. The most important thing we need is a feedback about what features are

51
build.gradle.kts
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@ -1,34 +1,49 @@
import ru.mipt.npm.gradle.KSciencePublishPlugin
import org.jetbrains.dokka.gradle.DokkaTask
import ru.mipt.npm.gradle.KSciencePublishingPlugin
import java.net.URL
plugins {
id("ru.mipt.npm.project")
id("ru.mipt.npm.gradle.project")
}
internal val kmathVersion: String by extra("0.2.0-dev-7")
internal val bintrayRepo: String by extra("kscience")
internal val githubProject: String by extra("kmath")
allprojects {
repositories {
jcenter()
maven("https://clojars.org/repo")
maven("https://dl.bintray.com/egor-bogomolov/astminer/")
maven("https://dl.bintray.com/hotkeytlt/maven")
maven("https://dl.bintray.com/kotlin/kotlin-eap")
maven("https://dl.bintray.com/kotlin/kotlinx")
maven("https://dl.bintray.com/mipt-npm/dev")
maven("https://dl.bintray.com/mipt-npm/kscience")
maven("https://jitpack.io")
maven("http://logicrunch.research.it.uu.se/maven/")
mavenCentral()
}
group = "kscience.kmath"
version = kmathVersion
group = "space.kscience"
version = "0.3.0-dev-4"
}
subprojects {
if (name.startsWith("kmath")) apply<KSciencePublishPlugin>()
if (name.startsWith("kmath")) apply<KSciencePublishingPlugin>()
afterEvaluate {
tasks.withType<DokkaTask> {
dokkaSourceSets.all {
val readmeFile = File(this@subprojects.projectDir, "./README.md")
if (readmeFile.exists())
includes.setFrom(includes + readmeFile.absolutePath)
arrayOf(
"http://ejml.org/javadoc/",
"https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/",
"https://deeplearning4j.org/api/latest/"
).map { URL("${it}package-list") to URL(it) }.forEach { (a, b) ->
externalDocumentationLink {
packageListUrl.set(a)
url.set(b)
}
}
}
}
}
}
readme {
@ -36,5 +51,11 @@ readme {
}
ksciencePublish {
spaceRepo = "https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven"
}
github("kmath")
space()
sonatype()
}
apiValidation {
nonPublicMarkers.add("space.kscience.kmath.misc.UnstableKMathAPI")
}

10
docs/algebra.md
View File

@ -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 kscience.kmath.operations.*
import space.kscience.kmath.operations.*
val a: T = ...
val b: T = ...
@ -31,7 +31,7 @@ multiplication;
- [Ring](http://mathworld.wolfram.com/Ring.html) adds multiplication and its neutral element (i.e. 1);
- [Field](http://mathworld.wolfram.com/Field.html) adds division operation.
A typical implementation of `Field<T>` is the `RealField` which works on doubles, and `VectorSpace` for `Space<T>`.
A typical implementation of `Field<T>` is the `DoubleField` which works on doubles, and `VectorSpace` for `Space<T>`.
In some cases algebra context can hold additional operations like `exp` or `sin`, and then it inherits appropriate
interface. Also, contexts may have operations, which produce elements outside of the context. For example, `Matrix.dot`
@ -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 kscience.kmath.operations.*
import space.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 kscience.kmath.operations.*
import space.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 kscience.kmath.operations.*
import space.kscience.kmath.operations.*
val c1 = Complex(1.0, 2.0)
val c2 = ComplexField { c1 - 1.0 } // Returns: Complex(re=0.0, im=2.0)

29
docs/images/KM.svg
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id="path16"
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@ -141,7 +162,7 @@
style="image-rendering:optimizeSpeed"
height="1"
width="1" /></g></g></g><g
id="g46"><g
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clip-path="url(#clipPath52)"
id="g48"><g
transform="matrix(861.6,0,0,12,5630,2778)"
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style="image-rendering:optimizeSpeed"
height="1"
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clip-path="url(#clipPath64)"
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transform="matrix(1300.8,0,0,91.2,970,2688.8)"
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4
docs/nd-structure.md
View File

@ -10,11 +10,11 @@ structures. In `kmath` performance depends on which particular context was used
Let us consider following contexts:
```kotlin
// automatically build context most suited for given type.
val autoField = NDField.auto(RealField, dim, dim)
val autoField = NDField.auto(DoubleField, dim, dim)
// specialized nd-field for Double. It works as generic Double field as well
val specializedField = NDField.real(dim, dim)
//A generic boxing field. It should be used for objects, not primitives.
val genericField = NDField.buffered(RealField, dim, dim)
val genericField = NDField.buffered(DoubleField, dim, dim)
```
Now let us perform several tests and see which implementation is best suited for each case:

65
docs/templates/ARTIFACT-TEMPLATE.md vendored
View File

@ -1,37 +1,28 @@
> #### Artifact:
>
> This module artifact: `${group}:${name}:${version}`.
>
> Bintray release version: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/${name}/images/download.svg) ](https://bintray.com/mipt-npm/kscience/${name}/_latestVersion)
>
> Bintray development version: [ ![Download](https://api.bintray.com/packages/mipt-npm/dev/${name}/images/download.svg) ](https://bintray.com/mipt-npm/dev/${name}/_latestVersion)
>
> **Gradle:**
>
> ```gradle
> repositories {
> maven { url "https://dl.bintray.com/kotlin/kotlin-eap" }
> maven { url 'https://dl.bintray.com/mipt-npm/kscience' }
> maven { url 'https://dl.bintray.com/mipt-npm/dev' }
> maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
>
> }
>
> dependencies {
> implementation '${group}:${name}:${version}'
> }
> ```
> **Gradle Kotlin DSL:**
>
> ```kotlin
> repositories {
> maven("https://dl.bintray.com/kotlin/kotlin-eap")
> 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("${group}:${name}:${version}")
> }
> ```
## Artifact:
The Maven coordinates of this project are `${group}:${name}:${version}`.
**Gradle:**
```gradle
repositories {
maven { url 'https://repo.kotlin.link' }
maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
}
dependencies {
implementation '${group}:${name}:${version}'
}
```
**Gradle Kotlin DSL:**
```kotlin
repositories {
maven("https://repo.kotlin.link")
maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
}
dependencies {
implementation("${group}:${name}:${version}")
}
```

26
docs/templates/README-TEMPLATE.md vendored
View File

@ -1,11 +1,8 @@
[![JetBrains Research](https://jb.gg/badges/research.svg)](https://confluence.jetbrains.com/display/ALL/JetBrains+on+GitHub)
[![DOI](https://zenodo.org/badge/129486382.svg)](https://zenodo.org/badge/latestdoi/129486382)
![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg)
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)
[![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22)
[![Space](https://img.shields.io/maven-metadata/v?label=Space&metadataUrl=https%3A%2F%2Fmaven.pkg.jetbrains.space%2Fmipt-npm%2Fp%2Fsci%2Fmaven%2Fkscience%2Fkmath%2Fkmath-core%2Fmaven-metadata.xml)](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/)
# KMath
@ -97,33 +94,22 @@ better than SciPy.
### Repositories
Release artifacts are accessible from bintray with following configuration (see documentation of
[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details):
Release and development artifacts are accessible from mipt-npm [Space](https://www.jetbrains.com/space/) repository `https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven` (see documentation of
[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details). The repository could be reached through [repo.kotlin.link](https://repo.kotlin.link) proxy:
```kotlin
repositories {
maven("https://dl.bintray.com/mipt-npm/kscience")
// maven("https://dl.bintray.com/mipt-npm/dev") for dev versions
maven("https://repo.kotlin.link")
}
dependencies {
api("kscience.kmath:kmath-core:$version")
api("${group}:kmath-core:$version")
// api("kscience.kmath:kmath-core-jvm:$version") for jvm-specific version
}
```
Gradle `6.0+` is required for multiplatform artifacts.
#### Development
Development builds are uploaded to the separate repository:
```kotlin
repositories {
maven("https://dl.bintray.com/mipt-npm/dev")
}
```
## Contributing
The project requires a lot of additional work. The most important thing we need is a feedback about what features are

28
examples/build.gradle.kts
View File

@ -1,7 +1,6 @@
import org.jetbrains.kotlin.gradle.tasks.KotlinCompile
plugins {
java
kotlin("jvm")
kotlin("plugin.allopen")
id("kotlinx.benchmark")
@ -12,6 +11,7 @@ sourceSets.register("benchmarks")
repositories {
jcenter()
maven("https://repo.kotlin.link")
maven("https://clojars.org/repo")
maven("https://dl.bintray.com/egor-bogomolov/astminer/")
maven("https://dl.bintray.com/hotkeytlt/maven")
@ -69,6 +69,14 @@ benchmark {
targets.register("benchmarks")
// This one matches sourceSet name above
configurations.register("buffer") {
warmups = 1 // 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
include("BufferBenchmark")
}
configurations.register("dot") {
warmups = 1 // number of warmup iterations
iterations = 3 // number of iterations
@ -76,6 +84,22 @@ benchmark {
iterationTimeUnit = "ms" // time unity for iterationTime, default is seconds
include("DotBenchmark")
}
configurations.register("expressions") {
warmups = 1 // 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
include("ExpressionsInterpretersBenchmark")
}
configurations.register("matrixInverse") {
warmups = 1 // 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
include("MatrixInverseBenchmark")
}
}
kotlin.sourceSets.all {
@ -89,6 +113,6 @@ tasks.withType<KotlinCompile> {
kotlinOptions.jvmTarget = "11"
}
readme{
readme {
maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL
}

34
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ArrayBenchmark.kt
View File

@ -1,34 +0,0 @@
package kscience.kmath.benchmarks
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)
internal 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[size - i]
}
@Benchmark
fun nativeBufferRead() {
var res = 0
for (i in 1..size) res += nativeBuffer[size - i]
}
companion object {
const val size: Int = 1000
val array: IntArray = IntArray(size) { it }
val arrayBuffer: IntBuffer = IntBuffer.wrap(array)
val nativeBuffer: IntBuffer = IntBuffer.allocate(size).also { for (i in 0 until size) it.put(i, i) }
}
}

34
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/BufferBenchmark.kt
View File

@ -1,34 +0,0 @@
package kscience.kmath.benchmarks
import kscience.kmath.complex.Complex
import kscience.kmath.complex.complex
import kscience.kmath.structures.MutableBuffer
import kscience.kmath.structures.RealBuffer
import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
@State(Scope.Benchmark)
internal class BufferBenchmark {
@Benchmark
fun genericRealBufferReadWrite() {
val buffer = RealBuffer(size) { it.toDouble() }
(0 until size).forEach {
buffer[it]
}
}
@Benchmark
fun complexBufferReadWrite() {
val buffer = MutableBuffer.complex(size / 2) { Complex(it.toDouble(), -it.toDouble()) }
(0 until size / 2).forEach {
buffer[it]
}
}
companion object {
const val size: Int = 100
}
}

67
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/DotBenchmark.kt
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@ -1,67 +0,0 @@
package kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kscience.kmath.commons.linear.CMMatrixContext
import kscience.kmath.ejml.EjmlMatrixContext
import kscience.kmath.linear.BufferMatrixContext
import kscience.kmath.linear.Matrix
import kscience.kmath.linear.RealMatrixContext
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
import kscience.kmath.structures.Buffer
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import kotlin.random.Random
@State(Scope.Benchmark)
internal class DotBenchmark {
companion object {
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 }
val cmMatrix1 = CMMatrixContext { matrix1.toCM() }
val cmMatrix2 = CMMatrixContext { matrix2.toCM() }
val ejmlMatrix1 = EjmlMatrixContext { matrix1.toEjml() }
val ejmlMatrix2 = EjmlMatrixContext { matrix2.toEjml() }
}
@Benchmark
fun cmDot() {
CMMatrixContext {
cmMatrix1 dot cmMatrix2
}
}
@Benchmark
fun ejmlDot() {
EjmlMatrixContext {
ejmlMatrix1 dot ejmlMatrix2
}
}
@Benchmark
fun ejmlDotWithConversion() {
EjmlMatrixContext {
matrix1 dot matrix2
}
}
@Benchmark
fun bufferedDot() {
BufferMatrixContext(RealField, Buffer.Companion::real).invoke {
matrix1 dot matrix2
}
}
@Benchmark
fun realDot() {
RealMatrixContext {
matrix1 dot matrix2
}
}
}

65
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt
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package kscience.kmath.benchmarks
import kscience.kmath.asm.compile
import kscience.kmath.ast.MstField
import kscience.kmath.ast.mstInField
import kscience.kmath.expressions.Expression
import kscience.kmath.expressions.expressionInField
import kscience.kmath.expressions.invoke
import kscience.kmath.expressions.symbol
import kscience.kmath.operations.Field
import kscience.kmath.operations.RealField
import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import kotlin.random.Random
@State(Scope.Benchmark)
internal class ExpressionsInterpretersBenchmark {
private val algebra: Field<Double> = RealField
@Benchmark
fun functionalExpression() {
val expr = algebra.expressionInField {
symbol("x") * const(2.0) + const(2.0) / symbol("x") - const(16.0)
}
invokeAndSum(expr)
}
@Benchmark
fun mstExpression() {
val expr = algebra.mstInField {
symbol("x") * 2.0 + 2.0 / symbol("x") - 16.0
}
invokeAndSum(expr)
}
@Benchmark
fun asmExpression() {
val expr = algebra.mstInField {
MstField.symbol("x") * 2.0 + 2.0 / MstField.symbol("x") - 16.0
}.compile()
invokeAndSum(expr)
}
@Benchmark
fun rawExpression() {
val x by symbol
val expr = Expression<Double> { args -> args.getValue(x) * 2.0 + 2.0 / args.getValue(x) - 16.0 }
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)
}
}

48
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/LinearAlgebraBenchmark.kt
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package kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kscience.kmath.commons.linear.CMMatrixContext
import kscience.kmath.commons.linear.CMMatrixContext.dot
import kscience.kmath.commons.linear.inverse
import kscience.kmath.ejml.EjmlMatrixContext
import kscience.kmath.ejml.inverse
import kscience.kmath.linear.Matrix
import kscience.kmath.linear.MatrixContext
import kscience.kmath.linear.inverseWithLup
import kscience.kmath.linear.real
import kscience.kmath.operations.invoke
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import kotlin.random.Random
@State(Scope.Benchmark)
internal class LinearAlgebraBenchmark {
companion object {
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
}
@Benchmark
fun kmathLupInversion() {
MatrixContext.real.inverseWithLup(matrix)
}
@Benchmark
fun cmLUPInversion() {
CMMatrixContext {
inverse(matrix)
}
}
@Benchmark
fun ejmlInverse() {
EjmlMatrixContext {
inverse(matrix)
}
}
}

45
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/NDFieldBenchmark.kt
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package kscience.kmath.benchmarks
import kscience.kmath.nd.*
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
import kscience.kmath.structures.Buffer
import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
@State(Scope.Benchmark)
internal class NDFieldBenchmark {
@Benchmark
fun autoFieldAdd() {
autoField {
var res: NDStructure<Double> = one
repeat(n) { res += one }
}
}
@Benchmark
fun specializedFieldAdd() {
specializedField {
var res: NDStructure<Double> = one
repeat(n) { res += 1.0 }
}
}
@Benchmark
fun boxingFieldAdd() {
genericField {
var res: NDStructure<Double> = one
repeat(n) { res += 1.0 }
}
}
companion object {
const val dim: Int = 1000
const val n: Int = 100
val autoField = NDAlgebra.auto(RealField, dim, dim)
val specializedField: RealNDField = NDAlgebra.real(dim, dim)
val genericField = NDAlgebra.field(RealField, Buffer.Companion::boxing, dim, dim)
}
}

52
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ViktorBenchmark.kt
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package kscience.kmath.benchmarks
import kscience.kmath.nd.*
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
@State(Scope.Benchmark)
internal class ViktorBenchmark {
final val dim: Int = 1000
final val n: Int = 100
// automatically build context most suited for given type.
final val autoField: NDField<Double, RealField> = NDAlgebra.auto(RealField, dim, dim)
final val realField: RealNDField = NDAlgebra.real(dim, dim)
final val viktorField: ViktorNDField = ViktorNDField(dim, dim)
@Benchmark
fun automaticFieldAddition() {
autoField {
var res: NDStructure<Double> = one
repeat(n) { res += 1.0 }
}
}
@Benchmark
fun realFieldAddition() {
realField {
var res: NDStructure<Double> = one
repeat(n) { res += 1.0 }
}
}
@Benchmark
fun viktorFieldAddition() {
viktorField {
var res = one
repeat(n) { res += 1.0 }
}
}
@Benchmark
fun rawViktor() {
val one = F64Array.full(init = 1.0, shape = intArrayOf(dim, dim))
var res = one
repeat(n) { res = res + one }
}
}

49
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ViktorLogBenchmark.kt
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package kscience.kmath.benchmarks
import kscience.kmath.nd.*
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
@State(Scope.Benchmark)
internal class ViktorLogBenchmark {
final val dim: Int = 1000
final val n: Int = 100
// automatically build context most suited for given type.
final val autoField: NDField<Double, RealField> = NDAlgebra.auto(RealField, dim, dim)
final val realField: RealNDField = NDAlgebra.real(dim, dim)
final val viktorField: ViktorNDField = ViktorNDField(intArrayOf(dim, dim))
@Benchmark
fun realFieldLog() {
realField {
val fortyTwo = produce { 42.0 }
var res = one
repeat(n) { res = ln(fortyTwo) }
}
}
@Benchmark
fun viktorFieldLog() {
viktorField {
val fortyTwo = produce { 42.0 }
var res = one
repeat(n) { res = ln(fortyTwo) }
}
}
@Benchmark
fun rawViktorLog() {
val fortyTwo = F64Array.full(dim, dim, init = 42.0)
var res: F64Array
repeat(n) {
res = fortyTwo.log()
}
}
}

38
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/ArrayBenchmark.kt Normal file
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package space.kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import java.nio.IntBuffer
@State(Scope.Benchmark)
internal class ArrayBenchmark {
@Benchmark
fun benchmarkArrayRead(blackhole: Blackhole) {
var res = 0
for (i in 1..size) res += array[size - i]
blackhole.consume(res)
}
@Benchmark
fun benchmarkBufferRead(blackhole: Blackhole) {
var res = 0
for (i in 1..size) res += arrayBuffer[size - i]
blackhole.consume(res)
}
@Benchmark
fun nativeBufferRead(blackhole: Blackhole) {
var res = 0
for (i in 1..size) res += nativeBuffer[size - i]
blackhole.consume(res)
}
private companion object {
private const val size = 1000
private val array = IntArray(size) { it }
private val arrayBuffer = IntBuffer.wrap(array)
private val nativeBuffer = IntBuffer.allocate(size).also { for (i in 0 until size) it.put(i, i) }
}
}

34
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/BufferBenchmark.kt Normal file
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package space.kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.complex.Complex
import space.kscience.kmath.complex.complex
import space.kscience.kmath.structures.DoubleBuffer
import space.kscience.kmath.structures.MutableBuffer
@State(Scope.Benchmark)
internal class BufferBenchmark {
@Benchmark
fun genericDoubleBufferReadWrite() {
val buffer = DoubleBuffer(size) { it.toDouble() }
(0 until size).forEach {
buffer[it]
}
}
@Benchmark
fun complexBufferReadWrite() {
val buffer = MutableBuffer.complex(size / 2) { Complex(it.toDouble(), -it.toDouble()) }
(0 until size / 2).forEach {
buffer[it]
}
}
private companion object {
private const val size = 100
}
}

65
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt Normal file
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package space.kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.commons.linear.CMLinearSpace
import space.kscience.kmath.ejml.EjmlLinearSpace
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.invoke
import space.kscience.kmath.operations.DoubleField
import kotlin.random.Random
@State(Scope.Benchmark)
internal class DotBenchmark {
companion object {
val random = Random(12224)
const val dim = 1000
//creating invertible matrix
val matrix1 = LinearSpace.real.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val matrix2 = LinearSpace.real.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val cmMatrix1 = CMLinearSpace { matrix1.toCM() }
val cmMatrix2 = CMLinearSpace { matrix2.toCM() }
val ejmlMatrix1 = EjmlLinearSpace { matrix1.toEjml() }
val ejmlMatrix2 = EjmlLinearSpace { matrix2.toEjml() }
}
@Benchmark
fun cmDot(blackhole: Blackhole) {
CMLinearSpace.run {
blackhole.consume(cmMatrix1 dot cmMatrix2)
}
}
@Benchmark
fun ejmlDot(blackhole: Blackhole) {
EjmlLinearSpace {
blackhole.consume(ejmlMatrix1 dot ejmlMatrix2)
}
}
@Benchmark
fun ejmlDotWithConversion(blackhole: Blackhole) {
EjmlLinearSpace {
blackhole.consume(matrix1 dot matrix2)
}
}
@Benchmark
fun bufferedDot(blackhole: Blackhole) {
LinearSpace.auto(DoubleField).invoke {
blackhole.consume(matrix1 dot matrix2)
}
}
@Benchmark
fun realDot(blackhole: Blackhole) {
LinearSpace.real {
blackhole.consume(matrix1 dot matrix2)
}
}
}

74
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt Normal file
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package space.kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.asm.compile
import space.kscience.kmath.ast.mstInField
import space.kscience.kmath.expressions.Expression
import space.kscience.kmath.expressions.expressionInField
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.misc.symbol
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.bindSymbol
import kotlin.random.Random
@State(Scope.Benchmark)
internal class ExpressionsInterpretersBenchmark {
@Benchmark
fun functionalExpression(blackhole: Blackhole) {
val expr = algebra.expressionInField {
val x = bindSymbol(x)
x * const(2.0) + const(2.0) / x - const(16.0)
}
invokeAndSum(expr, blackhole)
}
@Benchmark
fun mstExpression(blackhole: Blackhole) {
val expr = algebra.mstInField {
val x = bindSymbol(x)
x * 2.0 + number(2.0) / x - 16.0
}
invokeAndSum(expr, blackhole)
}
@Benchmark
fun asmExpression(blackhole: Blackhole) {
val expr = algebra.mstInField {
val x = bindSymbol(x)
x * 2.0 + number(2.0) / x - 16.0
}.compile()
invokeAndSum(expr, blackhole)
}
@Benchmark
fun rawExpression(blackhole: Blackhole) {
val expr = Expression<Double> { args ->
val x = args.getValue(x)
x * 2.0 + 2.0 / x - 16.0
}
invokeAndSum(expr, blackhole)
}
private fun invokeAndSum(expr: Expression<Double>, blackhole: Blackhole) {
val random = Random(0)
var sum = 0.0
repeat(1000000) {
sum += expr(x to random.nextDouble())
}
blackhole.consume(sum)
}
private companion object {
private val algebra = DoubleField
private val x by symbol
}
}

48
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt Normal file
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package space.kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.commons.linear.CMLinearSpace
import space.kscience.kmath.commons.linear.inverse
import space.kscience.kmath.ejml.EjmlLinearSpace
import space.kscience.kmath.ejml.inverse
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.inverseWithLup
import space.kscience.kmath.linear.invoke
import kotlin.random.Random
@State(Scope.Benchmark)
internal class MatrixInverseBenchmark {
companion object {
val random = Random(1224)
const val dim = 100
private val space = LinearSpace.real
//creating invertible matrix
val u = space.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val l = space.buildMatrix(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
val matrix = space { l dot u }
}
@Benchmark
fun kmathLupInversion(blackhole: Blackhole) {
blackhole.consume(LinearSpace.real.inverseWithLup(matrix))
}
@Benchmark
fun cmLUPInversion(blackhole: Blackhole) {
with(CMLinearSpace) {
blackhole.consume(inverse(matrix))
}
}
@Benchmark
fun ejmlInverse(blackhole: Blackhole) {
with(EjmlLinearSpace) {
blackhole.consume(inverse(matrix))
}
}
}

48
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt Normal file
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package space.kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.nd.*
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.structures.Buffer
@State(Scope.Benchmark)
internal class NDFieldBenchmark {
@Benchmark
fun autoFieldAdd(blackhole: Blackhole) {
with(autoField) {
var res: StructureND<Double> = one
repeat(n) { res += one }
blackhole.consume(res)
}
}
@Benchmark
fun specializedFieldAdd(blackhole: Blackhole) {
with(specializedField) {
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
}
@Benchmark
fun boxingFieldAdd(blackhole: Blackhole) {
with(genericField) {
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
}
private companion object {
private const val dim = 1000
private const val n = 100
private val autoField = AlgebraND.auto(DoubleField, dim, dim)
private val specializedField = AlgebraND.real(dim, dim)
private val genericField = AlgebraND.field(DoubleField, Buffer.Companion::boxing, dim, dim)
}
}

61
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt Normal file
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package space.kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import org.jetbrains.bio.viktor.F64Array
import space.kscience.kmath.nd.AlgebraND
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.nd.auto
import space.kscience.kmath.nd.real
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.viktor.ViktorNDField
@State(Scope.Benchmark)
internal class ViktorBenchmark {
@Benchmark
fun automaticFieldAddition(blackhole: Blackhole) {
with(autoField) {
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
}
@Benchmark
fun realFieldAddition(blackhole: Blackhole) {
with(realField) {
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
}
@Benchmark
fun viktorFieldAddition(blackhole: Blackhole) {
with(viktorField) {
var res = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
}
@Benchmark
fun rawViktor(blackhole: Blackhole) {
val one = F64Array.full(init = 1.0, shape = intArrayOf(dim, dim))
var res = one
repeat(n) { res = res + one }
blackhole.consume(res)
}
private companion object {
private const val dim = 1000
private const val n = 100
// automatically build context most suited for given type.
private val autoField = AlgebraND.auto(DoubleField, dim, dim)
private val realField = AlgebraND.real(dim, dim)
private val viktorField = ViktorNDField(dim, dim)
}
}

53
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt Normal file
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package space.kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import org.jetbrains.bio.viktor.F64Array
import space.kscience.kmath.nd.AlgebraND
import space.kscience.kmath.nd.auto
import space.kscience.kmath.nd.real
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.viktor.ViktorFieldND
@State(Scope.Benchmark)
internal class ViktorLogBenchmark {
@Benchmark
fun realFieldLog(blackhole: Blackhole) {
with(realNdField) {
val fortyTwo = produce { 42.0 }
var res = one
repeat(n) { res = ln(fortyTwo) }
blackhole.consume(res)
}
}
@Benchmark
fun viktorFieldLog(blackhole: Blackhole) {
with(viktorField) {
val fortyTwo = produce { 42.0 }
var res = one
repeat(n) { res = ln(fortyTwo) }
blackhole.consume(res)
}
}
@Benchmark
fun rawViktorLog(blackhole: Blackhole) {
val fortyTwo = F64Array.full(dim, dim, init = 42.0)
lateinit var res: F64Array
repeat(n) { res = fortyTwo.log() }
blackhole.consume(res)
}
private companion object {
private const val dim = 1000
private const val n = 100
// automatically build context most suited for given type.
private val autoField = AlgebraND.auto(DoubleField, dim, dim)
private val realNdField = AlgebraND.real(dim, dim)
private val viktorField = ViktorFieldND(intArrayOf(dim, dim))
}
}

24
examples/src/main/kotlin/kscience/kmath/ast/KotlingradSupport.kt
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package kscience.kmath.ast
import kscience.kmath.asm.compile
import kscience.kmath.expressions.derivative
import kscience.kmath.expressions.invoke
import kscience.kmath.expressions.symbol
import kscience.kmath.kotlingrad.differentiable
import kscience.kmath.operations.RealField
/**
* In this example, x^2-4*x-44 function is differentiated with Kotlin∇, and the autodiff result is compared with
* valid derivative.
*/
fun main() {
val x by symbol
val actualDerivative = MstExpression(RealField, "x^2-4*x-44".parseMath())
.differentiable()
.derivative(x)
.compile()
val expectedDerivative = MstExpression(RealField, "2*x-4".parseMath()).compile()
assert(actualDerivative("x" to 123.0) == expectedDerivative("x" to 123.0))
}

103
examples/src/main/kotlin/kscience/kmath/structures/ParallelRealNDField.kt
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package kscience.kmath.structures
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.nd.*
import kscience.kmath.operations.ExtendedField
import kscience.kmath.operations.RealField
import kscience.kmath.operations.RingWithNumbers
import java.util.*
import java.util.stream.IntStream
/**
* A demonstration implementation of NDField over Real using Java [DoubleStream] for parallel execution
*/
@OptIn(UnstableKMathAPI::class)
class StreamRealNDField(
override val shape: IntArray,
) : NDField<Double, RealField>,
RingWithNumbers<NDStructure<Double>>,
ExtendedField<NDStructure<Double>> {
private val strides = DefaultStrides(shape)
override val elementContext: RealField get() = RealField
override val zero: NDBuffer<Double> by lazy { produce { zero } }
override val one: NDBuffer<Double> by lazy { produce { one } }
override fun number(value: Number): NDBuffer<Double> {
val d = value.toDouble() // minimize conversions
return produce { d }
}
private val NDStructure<Double>.buffer: RealBuffer
get() = when {
!shape.contentEquals(this@StreamRealNDField.shape) -> throw ShapeMismatchException(
this@StreamRealNDField.shape,
shape
)
this is NDBuffer && this.strides == this@StreamRealNDField.strides -> this.buffer as RealBuffer
else -> RealBuffer(strides.linearSize) { offset -> get(strides.index(offset)) }
}
override fun produce(initializer: RealField.(IntArray) -> Double): NDBuffer<Double> {
val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
val index = strides.index(offset)
RealField.initializer(index)
}.toArray()
return NDBuffer(strides, array.asBuffer())
}
override fun NDStructure<Double>.map(
transform: RealField.(Double) -> Double,
): NDBuffer<Double> {
val array = Arrays.stream(buffer.array).parallel().map { RealField.transform(it) }.toArray()
return NDBuffer(strides, array.asBuffer())
}
override fun NDStructure<Double>.mapIndexed(
transform: RealField.(index: IntArray, Double) -> Double,
): NDBuffer<Double> {
val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
RealField.transform(
strides.index(offset),
buffer.array[offset]
)
}.toArray()
return NDBuffer(strides, array.asBuffer())
}
override fun combine(
a: NDStructure<Double>,
b: NDStructure<Double>,
transform: RealField.(Double, Double) -> Double,
): NDBuffer<Double> {
val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
RealField.transform(a.buffer.array[offset], b.buffer.array[offset])
}.toArray()
return NDBuffer(strides, array.asBuffer())
}
override fun power(arg: NDStructure<Double>, pow: Number): NDBuffer<Double> = arg.map() { power(it, pow) }
override fun exp(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { exp(it) }
override fun ln(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { ln(it) }
override fun sin(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { sin(it) }
override fun cos(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { cos(it) }
override fun tan(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { tan(it) }
override fun asin(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { asin(it) }
override fun acos(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { acos(it) }
override fun atan(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { atan(it) }
override fun sinh(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { sinh(it) }
override fun cosh(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { cosh(it) }
override fun tanh(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { tanh(it) }
override fun asinh(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { asinh(it) }
override fun acosh(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { acosh(it) }
override fun atanh(arg: NDStructure<Double>): NDBuffer<Double> = arg.map() { atanh(it) }
}
fun NDAlgebra.Companion.realWithStream(vararg shape: Int): StreamRealNDField = StreamRealNDField(shape)

15
examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt Normal file
View File

@ -0,0 +1,15 @@
package space.kscience.kmath.ast
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.DoubleField
fun main() {
val expr = DoubleField.mstInField {
val x = bindSymbol("x")
x * 2.0 + number(2.0) / x - 16.0
}
repeat(10000000) {
expr.invoke("x" to 1.0)
}
}

24
examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt Normal file
View File

@ -0,0 +1,24 @@
package space.kscience.kmath.ast
import space.kscience.kmath.asm.compile
import space.kscience.kmath.expressions.derivative
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.kotlingrad.differentiable
import space.kscience.kmath.misc.symbol
import space.kscience.kmath.operations.DoubleField
/**
* In this example, x^2-4*x-44 function is differentiated with Kotlin∇, and the autodiff result is compared with
* valid derivative.
*/
fun main() {
val x by symbol
val actualDerivative = MstExpression(DoubleField, "x^2-4*x-44".parseMath())
.differentiable()
.derivative(x)
.compile()
val expectedDerivative = MstExpression(DoubleField, "2*x-4".parseMath()).compile()
assert(actualDerivative("x" to 123.0) == expectedDerivative("x" to 123.0))
}

0
examples/src/main/kotlin/kscience/kmath/commons/fit/fitWithAutoDiff.kt → examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt
View File

28
examples/src/main/kotlin/space/kscience/kmath/linear/gradient.kt Normal file
View File

@ -0,0 +1,28 @@
package space.kscience.kmath.linear
import space.kscience.kmath.real.*
import space.kscience.kmath.structures.DoubleBuffer
fun main() {
val x0 = DoubleVector(0.0, 0.0, 0.0)
val sigma = DoubleVector(1.0, 1.0, 1.0)
val gaussian: (Point<Double>) -> Double = { x ->
require(x.size == x0.size)
kotlin.math.exp(-((x - x0) / sigma).square().sum())
}
fun ((Point<Double>) -> Double).grad(x: Point<Double>): Point<Double> {
require(x.size == x0.size)
return DoubleBuffer(x.size) { i ->
val h = sigma[i] / 5
val dVector = DoubleBuffer(x.size) { if (it == i) h else 0.0 }
val f1 = invoke(x + dVector / 2)
val f0 = invoke(x - dVector / 2)
(f1 - f0) / h
}
}
println(gaussian.grad(x0))
}

2
examples/src/main/kotlin/kscience/kmath/operations/BigIntDemo.kt → examples/src/main/kotlin/space/kscience/kmath/operations/BigIntDemo.kt
View File

@ -1,4 +1,4 @@
package kscience.kmath.operations
package space.kscience.kmath.operations
fun main() {
val res = BigIntField { number(1) * 2 }

12
examples/src/main/kotlin/kscience/kmath/operations/ComplexDemo.kt → examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt
View File

@ -1,18 +1,18 @@
package kscience.kmath.operations
package space.kscience.kmath.operations
import kscience.kmath.complex.Complex
import kscience.kmath.complex.complex
import kscience.kmath.nd.NDAlgebra
import space.kscience.kmath.complex.Complex
import space.kscience.kmath.complex.complex
import space.kscience.kmath.nd.AlgebraND
fun main() {
// 2d element
val element = NDAlgebra.complex(2, 2).produce { (i, j) ->
val element = AlgebraND.complex(2, 2).produce { (i, j) ->
Complex(i.toDouble() - j.toDouble(), i.toDouble() + j.toDouble())
}
println(element)
// 1d element operation
val result = with(NDAlgebra.complex(8)) {
val result = with(AlgebraND.complex(8)) {
val a = produce { (it) -> i * it - it.toDouble() }
val b = 3
val c = Complex(1.0, 1.0)

0
examples/src/main/kotlin/kscience/kmath/stat/DistributionBenchmark.kt → examples/src/main/kotlin/space/kscience/kmath/stat/DistributionBenchmark.kt
View File

0
examples/src/main/kotlin/kscience/kmath/stat/DistributionDemo.kt → examples/src/main/kotlin/space/kscience/kmath/stat/DistributionDemo.kt
View File

24
examples/src/main/kotlin/kscience/kmath/structures/ComplexND.kt → examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt
View File

@ -1,26 +1,26 @@
@file:Suppress("unused")
package kscience.kmath.structures
package space.kscience.kmath.structures
import kscience.kmath.complex.*
import kscience.kmath.linear.transpose
import kscience.kmath.nd.NDAlgebra
import kscience.kmath.nd.NDStructure
import kscience.kmath.nd.as2D
import kscience.kmath.nd.real
import kscience.kmath.operations.invoke
import space.kscience.kmath.complex.*
import space.kscience.kmath.linear.transpose
import space.kscience.kmath.nd.AlgebraND
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.nd.as2D
import space.kscience.kmath.nd.real
import space.kscience.kmath.operations.invoke
import kotlin.system.measureTimeMillis
fun main() {
val dim = 1000
val n = 1000
val realField = NDAlgebra.real(dim, dim)
val complexField: ComplexNDField = NDAlgebra.complex(dim, dim)
val realField = AlgebraND.real(dim, dim)
val complexField: ComplexFieldND = AlgebraND.complex(dim, dim)
val realTime = measureTimeMillis {
realField {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) {
res += 1.0
}
@ -31,7 +31,7 @@ fun main() {
val complexTime = measureTimeMillis {
complexField {
var res: NDStructure<Complex> = one
var res: StructureND<Complex> = one
repeat(n) {
res += 1.0
}

34
examples/src/main/kotlin/kscience/kmath/structures/NDField.kt → examples/src/main/kotlin/space/kscience/kmath/structures/NDField.kt
View File

@ -1,12 +1,12 @@
package kscience.kmath.structures
package space.kscience.kmath.structures
import kotlinx.coroutines.GlobalScope
import kscience.kmath.nd.*
import kscience.kmath.nd4j.Nd4jArrayField
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
import kscience.kmath.viktor.ViktorNDField
import org.nd4j.linalg.factory.Nd4j
import space.kscience.kmath.nd.*
import space.kscience.kmath.nd4j.Nd4jArrayField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.viktor.ViktorNDField
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
import kotlin.system.measureTimeMillis
@ -24,56 +24,56 @@ fun main() {
val n = 1000
// automatically build context most suited for given type.
val autoField = NDAlgebra.auto(RealField, dim, dim)
val autoField = AlgebraND.auto(DoubleField, dim, dim)
// specialized nd-field for Double. It works as generic Double field as well
val realField = NDAlgebra.real(dim, dim)
val realField = AlgebraND.real(dim, dim)
//A generic boxing field. It should be used for objects, not primitives.
val boxingField = NDAlgebra.field(RealField, Buffer.Companion::boxing, dim, dim)
val boxingField = AlgebraND.field(DoubleField, Buffer.Companion::boxing, dim, dim)
// Nd4j specialized field.
val nd4jField = Nd4jArrayField.real(dim, dim)
//viktor field
val viktorField = ViktorNDField(dim,dim)
val viktorField = ViktorNDField(dim, dim)
//parallel processing based on Java Streams
val parallelField = NDAlgebra.realWithStream(dim,dim)
val parallelField = AlgebraND.realWithStream(dim, dim)
measureAndPrint("Boxing addition") {
boxingField {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
}
}
measureAndPrint("Specialized addition") {
realField {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
}
}
measureAndPrint("Nd4j specialized addition") {
nd4jField {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
}
}
measureAndPrint("Viktor addition") {
viktorField {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
}
}
measureAndPrint("Parallel stream addition") {
parallelField {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
}
}
measureAndPrint("Automatic field addition") {
autoField {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
}
}

107
examples/src/main/kotlin/space/kscience/kmath/structures/StreamDoubleFieldND.kt Normal file
View File

@ -0,0 +1,107 @@
package space.kscience.kmath.structures
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.*
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.ExtendedField
import space.kscience.kmath.operations.NumbersAddOperations
import java.util.*
import java.util.stream.IntStream
/**
* A demonstration implementation of NDField over Real using Java [DoubleStream] for parallel execution
*/
@OptIn(UnstableKMathAPI::class)
class StreamDoubleFieldND(
override val shape: IntArray,
) : FieldND<Double, DoubleField>,
NumbersAddOperations<StructureND<Double>>,
ExtendedField<StructureND<Double>> {
private val strides = DefaultStrides(shape)
override val elementContext: DoubleField get() = DoubleField
override val zero: BufferND<Double> by lazy { produce { zero } }
override val one: BufferND<Double> by lazy { produce { one } }
override fun number(value: Number): BufferND<Double> {
val d = value.toDouble() // minimize conversions
return produce { d }
}
private val StructureND<Double>.buffer: DoubleBuffer
get() = when {
!shape.contentEquals(this@StreamDoubleFieldND.shape) -> throw ShapeMismatchException(
this@StreamDoubleFieldND.shape,
shape
)
this is BufferND && this.strides == this@StreamDoubleFieldND.strides -> this.buffer as DoubleBuffer
else -> DoubleBuffer(strides.linearSize) { offset -> get(strides.index(offset)) }
}
override fun produce(initializer: DoubleField.(IntArray) -> Double): BufferND<Double> {
val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
val index = strides.index(offset)
DoubleField.initializer(index)
}.toArray()
return BufferND(strides, array.asBuffer())
}
override fun StructureND<Double>.map(
transform: DoubleField.(Double) -> Double,
): BufferND<Double> {
val array = Arrays.stream(buffer.array).parallel().map { DoubleField.transform(it) }.toArray()
return BufferND(strides, array.asBuffer())
}
override fun StructureND<Double>.mapIndexed(
transform: DoubleField.(index: IntArray, Double) -> Double,
): BufferND<Double> {
val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
DoubleField.transform(
strides.index(offset),
buffer.array[offset]
)
}.toArray()
return BufferND(strides, array.asBuffer())
}
override fun combine(
a: StructureND<Double>,
b: StructureND<Double>,
transform: DoubleField.(Double, Double) -> Double,
): BufferND<Double> {
val array = IntStream.range(0, strides.linearSize).parallel().mapToDouble { offset ->
DoubleField.transform(a.buffer.array[offset], b.buffer.array[offset])
}.toArray()
return BufferND(strides, array.asBuffer())
}
override fun StructureND<Double>.unaryMinus(): StructureND<Double> = map { -it }
override fun scale(a: StructureND<Double>, value: Double): StructureND<Double> = a.map { it * value }
override fun power(arg: StructureND<Double>, pow: Number): BufferND<Double> = arg.map { power(it, pow) }
override fun exp(arg: StructureND<Double>): BufferND<Double> = arg.map { exp(it) }
override fun ln(arg: StructureND<Double>): BufferND<Double> = arg.map { ln(it) }
override fun sin(arg: StructureND<Double>): BufferND<Double> = arg.map { sin(it) }
override fun cos(arg: StructureND<Double>): BufferND<Double> = arg.map { cos(it) }
override fun tan(arg: StructureND<Double>): BufferND<Double> = arg.map { tan(it) }
override fun asin(arg: StructureND<Double>): BufferND<Double> = arg.map { asin(it) }
override fun acos(arg: StructureND<Double>): BufferND<Double> = arg.map { acos(it) }
override fun atan(arg: StructureND<Double>): BufferND<Double> = arg.map { atan(it) }
override fun sinh(arg: StructureND<Double>): BufferND<Double> = arg.map { sinh(it) }
override fun cosh(arg: StructureND<Double>): BufferND<Double> = arg.map { cosh(it) }
override fun tanh(arg: StructureND<Double>): BufferND<Double> = arg.map { tanh(it) }
override fun asinh(arg: StructureND<Double>): BufferND<Double> = arg.map { asinh(it) }
override fun acosh(arg: StructureND<Double>): BufferND<Double> = arg.map { acosh(it) }
override fun atanh(arg: StructureND<Double>): BufferND<Double> = arg.map { atanh(it) }
}
fun AlgebraND.Companion.realWithStream(vararg shape: Int): StreamDoubleFieldND = StreamDoubleFieldND(shape)

11
examples/src/main/kotlin/kscience/kmath/structures/StructureReadBenchmark.kt → examples/src/main/kotlin/space/kscience/kmath/structures/StructureReadBenchmark.kt
View File

@ -1,15 +1,16 @@
package kscience.kmath.structures
package space.kscience.kmath.structures
import kscience.kmath.nd.DefaultStrides
import kscience.kmath.nd.NDBuffer
import space.kscience.kmath.nd.BufferND
import space.kscience.kmath.nd.DefaultStrides
import kotlin.system.measureTimeMillis
@Suppress("ASSIGNED_BUT_NEVER_ACCESSED_VARIABLE")
fun main() {
val n = 6000
val array = DoubleArray(n * n) { 1.0 }
val buffer = RealBuffer(array)
val buffer = DoubleBuffer(array)
val strides = DefaultStrides(intArrayOf(n, n))
val structure = NDBuffer(strides, buffer)
val structure = BufferND(strides, buffer)
measureTimeMillis {
var res = 0.0

13
examples/src/main/kotlin/kscience/kmath/structures/StructureWriteBenchmark.kt → examples/src/main/kotlin/space/kscience/kmath/structures/StructureWriteBenchmark.kt
View File

@ -1,12 +1,13 @@
package kscience.kmath.structures
package space.kscience.kmath.structures
import kscience.kmath.nd.NDStructure
import kscience.kmath.nd.mapToBuffer
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.nd.mapToBuffer
import kotlin.system.measureTimeMillis
@Suppress("UNUSED_VARIABLE")
fun main() {
val n = 6000
val structure = NDStructure.build(intArrayOf(n, n), Buffer.Companion::auto) { 1.0 }
val structure = StructureND.buffered(intArrayOf(n, n), Buffer.Companion::auto) { 1.0 }
structure.mapToBuffer { it + 1 } // warm-up
val time1 = measureTimeMillis { val res = structure.mapToBuffer { it + 1 } }
println("Structure mapping finished in $time1 millis")
@ -19,10 +20,10 @@ fun main() {
println("Array mapping finished in $time2 millis")
val buffer = RealBuffer(DoubleArray(n * n) { 1.0 })
val buffer = DoubleBuffer(DoubleArray(n * n) { 1.0 })
val time3 = measureTimeMillis {
val target = RealBuffer(DoubleArray(n * n))
val target = DoubleBuffer(DoubleArray(n * n))
val res = array.forEachIndexed { index, value ->
target[index] = value + 1
}

14
examples/src/main/kotlin/kscience/kmath/structures/typeSafeDimensions.kt → examples/src/main/kotlin/space/kscience/kmath/structures/typeSafeDimensions.kt
View File

@ -1,11 +1,11 @@
package kscience.kmath.structures
package space.kscience.kmath.structures
import kscience.kmath.dimensions.D2
import kscience.kmath.dimensions.D3
import kscience.kmath.dimensions.DMatrixContext
import kscience.kmath.dimensions.Dimension
import space.kscience.kmath.dimensions.D2
import space.kscience.kmath.dimensions.D3
import space.kscience.kmath.dimensions.DMatrixContext
import space.kscience.kmath.dimensions.Dimension
private fun DMatrixContext<Double>.simple() {
private fun DMatrixContext<Double, *>.simple() {
val m1 = produce<D2, D3> { i, j -> (i + j).toDouble() }
val m2 = produce<D3, D2> { i, j -> (i + j).toDouble() }
@ -17,7 +17,7 @@ private object D5 : Dimension {
override val dim: UInt = 5u
}
private fun DMatrixContext<Double>.custom() {
private fun DMatrixContext<Double, *>.custom() {
val m1 = produce<D2, D5> { i, j -> (i + j).toDouble() }
val m2 = produce<D5, D2> { i, j -> (i - j).toDouble() }
val m3 = produce<D2, D2> { i, j -> (i - j).toDouble() }

4
gradle.properties
View File

@ -3,6 +3,6 @@ kotlin.mpp.enableGranularSourceSetsMetadata=true
kotlin.mpp.stability.nowarn=true
kotlin.native.enableDependencyPropagation=false
kotlin.parallel.tasks.in.project=true
org.gradle.jvmargs=-XX:MaxMetaspaceSize=512m
org.gradle.configureondemand=true
org.gradle.jvmargs=-XX:MaxMetaspaceSize=9G
org.gradle.parallel=true
systemProp.org.gradle.internal.publish.checksums.insecure=true

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-6.8.1-bin.zip
distributionUrl=https\://services.gradle.org/distributions/gradle-6.8.3-bin.zip
zipStoreBase=GRADLE_USER_HOME
zipStorePath=wrapper/dists

97
kmath-ast/README.md
View File

@ -1,52 +1,43 @@
# Abstract Syntax Tree Expression Representation and Operations (`kmath-ast`)
# Module kmath-ast
This subproject implements the following features:
Abstract syntax tree expression representation and related optimizations.
- [expression-language](src/jvmMain/kotlin/kscience/kmath/ast/parser.kt) : Expression language and its parser
- [mst](src/commonMain/kotlin/kscience/kmath/ast/MST.kt) : MST (Mathematical Syntax Tree) as expression language's syntax intermediate representation
- [mst-building](src/commonMain/kotlin/kscience/kmath/ast/MstAlgebra.kt) : MST building algebraic structure
- [mst-interpreter](src/commonMain/kotlin/kscience/kmath/ast/MST.kt) : MST interpreter
- [mst-jvm-codegen](src/jvmMain/kotlin/kscience/kmath/asm/asm.kt) : Dynamic MST to JVM bytecode compiler
- [mst-js-codegen](src/jsMain/kotlin/kscience/kmath/estree/estree.kt) : Dynamic MST to JS compiler
- [expression-language](src/jvmMain/kotlin/space/kscience/kmath/ast/parser.kt) : Expression language and its parser
- [mst](src/commonMain/kotlin/space/kscience/kmath/ast/MST.kt) : MST (Mathematical Syntax Tree) as expression language's syntax intermediate representation
- [mst-building](src/commonMain/kotlin/space/kscience/kmath/ast/MstAlgebra.kt) : MST building algebraic structure
- [mst-interpreter](src/commonMain/kotlin/space/kscience/kmath/ast/MST.kt) : MST interpreter
- [mst-jvm-codegen](src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt) : Dynamic MST to JVM bytecode compiler
- [mst-js-codegen](src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt) : Dynamic MST to JS compiler
> #### Artifact:
>
> This module artifact: `kscience.kmath:kmath-ast:0.2.0-dev-7`.
>
> Bintray release version: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-ast/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-ast/_latestVersion)
>
> Bintray development version: [ ![Download](https://api.bintray.com/packages/mipt-npm/dev/kmath-ast/images/download.svg) ](https://bintray.com/mipt-npm/dev/kmath-ast/_latestVersion)
>
> **Gradle:**
>
> ```gradle
> repositories {
> maven { url "https://dl.bintray.com/kotlin/kotlin-eap" }
> 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 'kscience.kmath:kmath-ast:0.2.0-dev-7'
> }
> ```
> **Gradle Kotlin DSL:**
>
> ```kotlin
> repositories {
> maven("https://dl.bintray.com/kotlin/kotlin-eap")
> 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("kscience.kmath:kmath-ast:0.2.0-dev-7")
> }
> ```
## Artifact:
The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-3`.
**Gradle:**
```gradle
repositories {
maven { url 'https://repo.kotlin.link' }
maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
}
dependencies {
implementation 'space.kscience:kmath-ast:0.3.0-dev-3'
}
```
**Gradle Kotlin DSL:**
```kotlin
repositories {
maven("https://repo.kotlin.link")
maven("https://dl.bintray.com/kotlin/kotlin-eap") // include for builds based on kotlin-eap
maven("https://dl.bintray.com/hotkeytlt/maven") // required for a
}
dependencies {
implementation("space.kscience:kmath-ast:0.3.0-dev-3")
}
```
## Dynamic expression code generation
@ -58,19 +49,19 @@ a special implementation of `Expression<T>` with implemented `invoke` function.
For example, the following builder:
```kotlin
RealField.mstInField { symbol("x") + 2 }.compile()
DoubleField.mstInField { symbol("x") + 2 }.compile()
```
… leads to generation of bytecode, which can be decompiled to the following Java class:
```java
package kscience.kmath.asm.generated;
package space.kscience.kmath.asm.generated;
import java.util.Map;
import kotlin.jvm.functions.Function2;
import kscience.kmath.asm.internal.MapIntrinsics;
import kscience.kmath.expressions.Expression;
import kscience.kmath.expressions.Symbol;
import space.kscience.kmath.asm.internal.MapIntrinsics;
import space.kscience.kmath.expressions.Expression;
import space.kscience.kmath.expressions.Symbol;
public final class AsmCompiledExpression_45045_0 implements Expression<Double> {
private final Object[] constants;
@ -91,8 +82,8 @@ public final class AsmCompiledExpression_45045_0 implements Expression<Double> {
This API extends MST and MstExpression, so you may optimize as both of them:
```kotlin
RealField.mstInField { symbol("x") + 2 }.compile()
RealField.expression("x+2".parseMath())
DoubleField.mstInField { symbol("x") + 2 }.compile()
DoubleField.expression("x+2".parseMath())
```
#### Known issues
@ -106,7 +97,7 @@ RealField.expression("x+2".parseMath())
A similar feature is also available on JS.
```kotlin
RealField.mstInField { symbol("x") + 2 }.compile()
DoubleField.mstInField { symbol("x") + 2 }.compile()
```
The code above returns expression implemented with such a JS function:

27
kmath-ast/build.gradle.kts
View File

@ -1,7 +1,7 @@
import ru.mipt.npm.gradle.Maturity
plugins {
id("ru.mipt.npm.mpp")
id("ru.mipt.npm.gradle.mpp")
}
kotlin.js {
@ -33,19 +33,24 @@ kotlin.sourceSets {
jsMain {
dependencies {
implementation(npm("astring", "1.4.3"))
implementation(npm("astring", "1.7.0"))
}
}
jvmMain {
dependencies {
api("com.github.h0tk3y.betterParse:better-parse:0.4.0")
implementation("org.ow2.asm:asm:9.0")
implementation("org.ow2.asm:asm-commons:9.0")
api("com.github.h0tk3y.betterParse:better-parse:0.4.1")
implementation("org.ow2.asm:asm:9.1")
implementation("org.ow2.asm:asm-commons:9.1")
}
}
}
//Workaround for https://github.com/Kotlin/dokka/issues/1455
tasks.dokkaHtml {
dependsOn(tasks.build)
}
readme {
maturity = Maturity.PROTOTYPE
propertyByTemplate("artifact", rootProject.file("docs/templates/ARTIFACT-TEMPLATE.md"))
@ -53,36 +58,36 @@ readme {
feature(
id = "expression-language",
description = "Expression language and its parser",
ref = "src/jvmMain/kotlin/kscience/kmath/ast/parser.kt"
ref = "src/jvmMain/kotlin/space/kscience/kmath/ast/parser.kt"
)
feature(
id = "mst",
description = "MST (Mathematical Syntax Tree) as expression language's syntax intermediate representation",
ref = "src/commonMain/kotlin/kscience/kmath/ast/MST.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/ast/MST.kt"
)
feature(
id = "mst-building",
description = "MST building algebraic structure",
ref = "src/commonMain/kotlin/kscience/kmath/ast/MstAlgebra.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/ast/MstAlgebra.kt"
)
feature(
id = "mst-interpreter",
description = "MST interpreter",
ref = "src/commonMain/kotlin/kscience/kmath/ast/MST.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/ast/MST.kt"
)
feature(
id = "mst-jvm-codegen",
description = "Dynamic MST to JVM bytecode compiler",
ref = "src/jvmMain/kotlin/kscience/kmath/asm/asm.kt"
ref = "src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt"
)
feature(
id = "mst-js-codegen",
description = "Dynamic MST to JS compiler",
ref = "src/jsMain/kotlin/kscience/kmath/estree/estree.kt"
ref = "src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt"
)
}

20
kmath-ast/docs/README-TEMPLATE.md
View File

@ -1,6 +1,6 @@
# Abstract Syntax Tree Expression Representation and Operations (`kmath-ast`)
# Module kmath-ast
This subproject implements the following features:
Abstract syntax tree expression representation and related optimizations.
${features}
@ -16,19 +16,19 @@ a special implementation of `Expression<T>` with implemented `invoke` function.
For example, the following builder:
```kotlin
RealField.mstInField { symbol("x") + 2 }.compile()
DoubleField.mstInField { symbol("x") + 2 }.compile()
```
… leads to generation of bytecode, which can be decompiled to the following Java class:
```java
package kscience.kmath.asm.generated;
package space.kscience.kmath.asm.generated;
import java.util.Map;
import kotlin.jvm.functions.Function2;
import kscience.kmath.asm.internal.MapIntrinsics;
import kscience.kmath.expressions.Expression;
import kscience.kmath.expressions.Symbol;
import space.kscience.kmath.asm.internal.MapIntrinsics;
import space.kscience.kmath.expressions.Expression;
import space.kscience.kmath.expressions.Symbol;
public final class AsmCompiledExpression_45045_0 implements Expression<Double> {
private final Object[] constants;
@ -49,8 +49,8 @@ public final class AsmCompiledExpression_45045_0 implements Expression<Double> {
This API extends MST and MstExpression, so you may optimize as both of them:
```kotlin
RealField.mstInField { symbol("x") + 2 }.compile()
RealField.expression("x+2".parseMath())
DoubleField.mstInField { symbol("x") + 2 }.compile()
DoubleField.expression("x+2".parseMath())
```
#### Known issues
@ -64,7 +64,7 @@ RealField.expression("x+2".parseMath())
A similar feature is also available on JS.
```kotlin
RealField.mstInField { symbol("x") + 2 }.compile()
DoubleField.mstInField { symbol("x") + 2 }.compile()
```
The code above returns expression implemented with such a JS function:

8
kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MST.kt → kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/MST.kt
View File

@ -1,7 +1,7 @@
package kscience.kmath.ast
package space.kscience.kmath.ast
import kscience.kmath.operations.Algebra
import kscience.kmath.operations.NumericAlgebra
import space.kscience.kmath.operations.Algebra
import space.kscience.kmath.operations.NumericAlgebra
/**
* A Mathematical Syntax Tree (MST) node for mathematical expressions.
@ -55,7 +55,7 @@ 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)
is MST.Symbolic -> bindSymbol(node.value)
is MST.Unary -> when {
this is NumericAlgebra && node.value is MST.Numeric -> unaryOperationFunction(node.operation)(number(node.value.value))

94
kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MstAlgebra.kt → kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/MstAlgebra.kt
View File

@ -1,14 +1,14 @@
package kscience.kmath.ast
package space.kscience.kmath.ast
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.operations.*
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.*
/**
* [Algebra] over [MST] nodes.
*/
public object MstAlgebra : NumericAlgebra<MST> {
public override fun number(value: Number): MST.Numeric = MST.Numeric(value)
public override fun symbol(value: String): MST.Symbolic = MST.Symbolic(value)
public override fun bindSymbol(value: String): MST.Symbolic = MST.Symbolic(value)
public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary =
{ arg -> MST.Unary(operation, arg) }
@ -18,25 +18,25 @@ public object MstAlgebra : NumericAlgebra<MST> {
}
/**
* [Space] over [MST] nodes.
* [Group] over [MST] nodes.
*/
public object MstSpace : Space<MST>, NumericAlgebra<MST> {
public override val zero: MST.Numeric by lazy { number(0.0) }
public object MstGroup : Group<MST>, NumericAlgebra<MST>, ScaleOperations<MST> {
public override val zero: MST.Numeric = number(0.0)
public override fun number(value: Number): MST.Numeric = MstAlgebra.number(value)
public override fun symbol(value: String): MST.Symbolic = MstAlgebra.symbol(value)
public override fun add(a: MST, b: MST): MST.Binary = binaryOperationFunction(SpaceOperations.PLUS_OPERATION)(a, b)
public override fun bindSymbol(value: String): MST.Symbolic = MstAlgebra.bindSymbol(value)
public override fun add(a: MST, b: MST): MST.Binary = binaryOperationFunction(GroupOperations.PLUS_OPERATION)(a, b)
public override operator fun MST.unaryPlus(): MST.Unary =
unaryOperationFunction(SpaceOperations.PLUS_OPERATION)(this)
unaryOperationFunction(GroupOperations.PLUS_OPERATION)(this)
public override operator fun MST.unaryMinus(): MST.Unary =
unaryOperationFunction(SpaceOperations.MINUS_OPERATION)(this)
unaryOperationFunction(GroupOperations.MINUS_OPERATION)(this)
public override operator fun MST.minus(b: MST): MST.Binary =
binaryOperationFunction(SpaceOperations.MINUS_OPERATION)(this, b)
binaryOperationFunction(GroupOperations.MINUS_OPERATION)(this, b)
public override fun multiply(a: MST, k: Number): MST.Binary =
binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, number(k))
public override fun scale(a: MST, value: Double): MST.Binary =
binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, number(value))
public override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary =
MstAlgebra.binaryOperationFunction(operation)
@ -49,25 +49,26 @@ public object MstSpace : Space<MST>, NumericAlgebra<MST> {
* [Ring] over [MST] nodes.
*/
@OptIn(UnstableKMathAPI::class)
public object MstRing : Ring<MST>, RingWithNumbers<MST> {
public override val zero: MST.Numeric
get() = MstSpace.zero
public object MstRing : Ring<MST>, NumbersAddOperations<MST>, ScaleOperations<MST> {
public override val zero: MST.Numeric get() = MstGroup.zero
public override val one: MST.Numeric = number(1.0)
public override val one: MST.Numeric by lazy { number(1.0) }
public override fun number(value: Number): MST.Numeric = MstGroup.number(value)
public override fun bindSymbol(value: String): MST.Symbolic = MstAlgebra.bindSymbol(value)
public override fun add(a: MST, b: MST): MST.Binary = MstGroup.add(a, b)
public override fun scale(a: MST, value: Double): MST.Binary =
MstGroup.binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, MstGroup.number(value))
public override fun number(value: Number): MST.Numeric = MstSpace.number(value)
public override fun symbol(value: String): MST.Symbolic = MstSpace.symbol(value)
public override fun add(a: MST, b: MST): MST.Binary = MstSpace.add(a, b)
public override fun multiply(a: MST, k: Number): MST.Binary = MstSpace.multiply(a, k)
public override fun multiply(a: MST, b: MST): MST.Binary =
binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, b)
public override operator fun MST.unaryPlus(): MST.Unary = MstSpace { +this@unaryPlus }
public override operator fun MST.unaryMinus(): MST.Unary = MstSpace { -this@unaryMinus }
public override operator fun MST.minus(b: MST): MST.Binary = MstSpace { this@minus - b }
public override operator fun MST.unaryPlus(): MST.Unary = MstGroup { +this@unaryPlus }
public override operator fun MST.unaryMinus(): MST.Unary = MstGroup { -this@unaryMinus }
public override operator fun MST.minus(b: MST): MST.Binary = MstGroup { this@minus - b }
public override fun binaryOperationFunction(operation: String): (left: MST, right: MST) -> MST.Binary =
MstSpace.binaryOperationFunction(operation)
MstGroup.binaryOperationFunction(operation)
public override fun unaryOperationFunction(operation: String): (arg: MST) -> MST.Unary =
MstAlgebra.unaryOperationFunction(operation)
@ -77,17 +78,18 @@ public object MstRing : Ring<MST>, RingWithNumbers<MST> {
* [Field] over [MST] nodes.
*/
@OptIn(UnstableKMathAPI::class)
public object MstField : Field<MST>, RingWithNumbers<MST> {
public override val zero: MST.Numeric
get() = MstRing.zero
public object MstField : Field<MST>, NumbersAddOperations<MST>, ScaleOperations<MST> {
public override val zero: MST.Numeric get() = MstRing.zero
public override val one: MST.Numeric
get() = MstRing.one
public override val one: MST.Numeric get() = MstRing.one
public override fun symbol(value: String): MST.Symbolic = MstRing.symbol(value)
public override fun bindSymbol(value: String): MST.Symbolic = MstAlgebra.bindSymbol(value)
public override fun number(value: Number): MST.Numeric = MstRing.number(value)
public override fun add(a: MST, b: MST): MST.Binary = MstRing.add(a, b)
public override fun multiply(a: MST, k: Number): MST.Binary = MstRing.multiply(a, k)
public override fun scale(a: MST, value: Double): MST.Binary =
MstGroup.binaryOperationFunction(RingOperations.TIMES_OPERATION)(a, MstGroup.number(value))
public override fun multiply(a: MST, b: MST): MST.Binary = MstRing.multiply(a, b)
public override fun divide(a: MST, b: MST): MST.Binary =
binaryOperationFunction(FieldOperations.DIV_OPERATION)(a, b)
@ -107,13 +109,10 @@ public object MstField : Field<MST>, RingWithNumbers<MST> {
* [ExtendedField] over [MST] nodes.
*/
public object MstExtendedField : ExtendedField<MST>, NumericAlgebra<MST> {
public override val zero: MST.Numeric
get() = MstField.zero
public override val zero: MST.Numeric get() = MstField.zero
public override val one: MST.Numeric get() = MstField.one
public override val one: MST.Numeric
get() = MstField.one
public override fun symbol(value: String): MST.Symbolic = MstField.symbol(value)
public override fun bindSymbol(value: String): MST.Symbolic = MstAlgebra.bindSymbol(value)
public override fun number(value: Number): MST.Numeric = MstRing.number(value)
public override fun sin(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.SIN_OPERATION)(arg)
public override fun cos(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.COS_OPERATION)(arg)
@ -121,14 +120,17 @@ public object MstExtendedField : ExtendedField<MST>, NumericAlgebra<MST> {
public override fun asin(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.ASIN_OPERATION)(arg)
public override fun acos(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.ACOS_OPERATION)(arg)
public override fun atan(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.ATAN_OPERATION)(arg)
public override fun sinh(arg: MST): MST.Unary = unaryOperationFunction(HyperbolicOperations.SINH_OPERATION)(arg)
public override fun cosh(arg: MST): MST.Unary = unaryOperationFunction(HyperbolicOperations.COSH_OPERATION)(arg)
public override fun tanh(arg: MST): MST.Unary = unaryOperationFunction(HyperbolicOperations.TANH_OPERATION)(arg)
public override fun asinh(arg: MST): MST.Unary = unaryOperationFunction(HyperbolicOperations.ASINH_OPERATION)(arg)
public override fun acosh(arg: MST): MST.Unary = unaryOperationFunction(HyperbolicOperations.ACOSH_OPERATION)(arg)
public override fun atanh(arg: MST): MST.Unary = unaryOperationFunction(HyperbolicOperations.ATANH_OPERATION)(arg)
public override fun sinh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.SINH_OPERATION)(arg)
public override fun cosh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.COSH_OPERATION)(arg)
public override fun tanh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.TANH_OPERATION)(arg)
public override fun asinh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.ASINH_OPERATION)(arg)
public override fun acosh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.ACOSH_OPERATION)(arg)
public override fun atanh(arg: MST): MST.Unary = unaryOperationFunction(ExponentialOperations.ATANH_OPERATION)(arg)
public override fun add(a: MST, b: MST): MST.Binary = MstField.add(a, b)
public override fun multiply(a: MST, k: Number): MST.Binary = MstField.multiply(a, k)
public override fun scale(a: MST, value: Double): MST =
binaryOperation(GroupOperations.PLUS_OPERATION, a, number(value))
public override fun multiply(a: MST, b: MST): MST.Binary = MstField.multiply(a, b)
public override fun divide(a: MST, b: MST): MST.Binary = MstField.divide(a, b)
public override operator fun MST.unaryPlus(): MST.Unary = MstField { +this@unaryPlus }

37
kmath-ast/src/commonMain/kotlin/kscience/kmath/ast/MstExpression.kt → kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/MstExpression.kt
View File

@ -1,7 +1,9 @@
package kscience.kmath.ast
package space.kscience.kmath.ast
import kscience.kmath.expressions.*
import kscience.kmath.operations.*
import space.kscience.kmath.expressions.*
import space.kscience.kmath.misc.StringSymbol
import space.kscience.kmath.misc.Symbol
import space.kscience.kmath.operations.*
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@ -15,14 +17,23 @@ import kotlin.contracts.contract
*/
public class MstExpression<T, out A : Algebra<T>>(public val algebra: A, public val mst: MST) : Expression<T> {
private inner class InnerAlgebra(val arguments: Map<Symbol, T>) : NumericAlgebra<T> {
override fun symbol(value: String): T = try {
algebra.symbol(value)
override fun bindSymbol(value: String): T = try {
algebra.bindSymbol(value)
} catch (ignored: IllegalStateException) {
null
} ?: arguments.getValue(StringSymbol(value))
override fun unaryOperationFunction(operation: String): (arg: T) -> T = algebra.unaryOperationFunction(operation)
override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = algebra.binaryOperationFunction(operation)
override fun unaryOperation(operation: String, arg: T): T =
algebra.unaryOperation(operation, arg)
override fun binaryOperation(operation: String, left: T, right: T): T =
algebra.binaryOperation(operation, left, right)
override fun unaryOperationFunction(operation: String): (arg: T) -> T =
algebra.unaryOperationFunction(operation)
override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T =
algebra.binaryOperationFunction(operation)
@Suppress("UNCHECKED_CAST")
override fun number(value: Number): T = if (algebra is NumericAlgebra<*>)
@ -45,13 +56,13 @@ public inline fun <reified T : Any, A : Algebra<T>, E : Algebra<MST>> A.mst(
): MstExpression<T, A> = MstExpression(this, mstAlgebra.block())
/**
* Builds [MstExpression] over [Space].
* Builds [MstExpression] over [Group].
*
* @author Alexander Nozik
*/
public inline fun <reified T : Any, A : Space<T>> A.mstInSpace(block: MstSpace.() -> MST): MstExpression<T, A> {
public inline fun <reified T : Any, A : Group<T>> A.mstInGroup(block: MstGroup.() -> MST): MstExpression<T, A> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return MstExpression(this, MstSpace.block())
return MstExpression(this, MstGroup.block())
}
/**
@ -85,13 +96,13 @@ public inline fun <reified T : Any, A : ExtendedField<T>> A.mstInExtendedField(b
}
/**
* Builds [MstExpression] over [FunctionalExpressionSpace].
* Builds [MstExpression] over [FunctionalExpressionGroup].
*
* @author Alexander Nozik
*/
public inline fun <reified T : Any, A : Space<T>> FunctionalExpressionSpace<T, A>.mstInSpace(block: MstSpace.() -> MST): MstExpression<T, A> {
public inline fun <reified T : Any, A : Group<T>> FunctionalExpressionGroup<T, A>.mstInGroup(block: MstGroup.() -> MST): MstExpression<T, A> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return algebra.mstInSpace(block)
return algebra.mstInGroup(block)
}
/**

3
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/internal/astring/astring.typealises.kt
View File

@ -1,3 +0,0 @@
package kscience.kmath.estree.internal.astring
internal typealias Generator = Any

7
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/internal/stream/stream.kt
View File

@ -1,7 +0,0 @@
package kscience.kmath.estree.internal.stream
import kscience.kmath.estree.internal.emitter.Emitter
internal open external class Stream : Emitter {
open fun pipe(dest: Any, options: Any): Any
}

20
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/estree.kt → kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt
View File

@ -1,20 +1,20 @@
package kscience.kmath.estree
package space.kscience.kmath.estree
import kscience.kmath.ast.MST
import kscience.kmath.ast.MST.*
import kscience.kmath.ast.MstExpression
import kscience.kmath.estree.internal.ESTreeBuilder
import kscience.kmath.estree.internal.estree.BaseExpression
import kscience.kmath.expressions.Expression
import kscience.kmath.operations.Algebra
import kscience.kmath.operations.NumericAlgebra
import space.kscience.kmath.ast.MST
import space.kscience.kmath.ast.MST.*
import space.kscience.kmath.ast.MstExpression
import space.kscience.kmath.estree.internal.ESTreeBuilder
import space.kscience.kmath.estree.internal.estree.BaseExpression
import space.kscience.kmath.expressions.Expression
import space.kscience.kmath.operations.Algebra
import space.kscience.kmath.operations.NumericAlgebra
@PublishedApi
internal fun <T> MST.compileWith(algebra: Algebra<T>): Expression<T> {
fun ESTreeBuilder<T>.visit(node: MST): BaseExpression = when (node) {
is Symbolic -> {
val symbol = try {
algebra.symbol(node.value)
algebra.bindSymbol(node.value)
} catch (ignored: IllegalStateException) {
null
}

10
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/internal/ESTreeBuilder.kt → kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/ESTreeBuilder.kt
View File

@ -1,9 +1,9 @@
package kscience.kmath.estree.internal
package space.kscience.kmath.estree.internal
import kscience.kmath.estree.internal.astring.generate
import kscience.kmath.estree.internal.estree.*
import kscience.kmath.expressions.Expression
import kscience.kmath.expressions.Symbol
import space.kscience.kmath.estree.internal.astring.generate
import space.kscience.kmath.estree.internal.estree.*
import space.kscience.kmath.expressions.Expression
import space.kscience.kmath.misc.Symbol
internal class ESTreeBuilder<T>(val bodyCallback: ESTreeBuilder<T>.() -> BaseExpression) {
private class GeneratedExpression<T>(val executable: dynamic, val constants: Array<dynamic>) : Expression<T> {

4
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/internal/astring/astring.kt → kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/astring/astring.kt
View File

@ -1,9 +1,9 @@
@file:JsModule("astring")
@file:JsNonModule
package kscience.kmath.estree.internal.astring
package space.kscience.kmath.estree.internal.astring
import kscience.kmath.estree.internal.estree.BaseNode
import space.kscience.kmath.estree.internal.estree.BaseNode
internal external interface Options {
var indent: String?

3
kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/astring/astring.typealises.kt Normal file
View File

@ -0,0 +1,3 @@
package space.kscience.kmath.estree.internal.astring
internal typealias Generator = Any

2
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/internal/emitter/emitter.kt → kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/emitter/emitter.kt
View File

@ -1,4 +1,4 @@
package kscience.kmath.estree.internal.emitter
package space.kscience.kmath.estree.internal.emitter
internal open external class Emitter {
constructor(obj: Any)

2
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/internal/estree/estree.extensions.kt → kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/estree/estree.extensions.kt
View File

@ -1,4 +1,4 @@
package kscience.kmath.estree.internal.estree
package space.kscience.kmath.estree.internal.estree
internal fun Program(sourceType: String, vararg body: dynamic) = object : Program {
override var type = "Program"

2
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/internal/estree/estree.kt → kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/estree/estree.kt
View File

@ -1,4 +1,4 @@
package kscience.kmath.estree.internal.estree
package space.kscience.kmath.estree.internal.estree
import kotlin.js.RegExp

7
kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/stream/stream.kt Normal file
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@ -0,0 +1,7 @@
package space.kscience.kmath.estree.internal.stream
import space.kscience.kmath.estree.internal.emitter.Emitter
internal open external class Stream : Emitter {
open fun pipe(dest: Any, options: Any): Any
}

2
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/internal/tsstdlib/lib.es2015.iterable.kt → kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/tsstdlib/lib.es2015.iterable.kt
View File

@ -1,4 +1,4 @@
package kscience.kmath.estree.internal.tsstdlib
package space.kscience.kmath.estree.internal.tsstdlib
internal external interface IteratorYieldResult<TYield> {
var done: Boolean?

2
kmath-ast/src/jsMain/kotlin/kscience/kmath/estree/internal/tsstdlib/lib.es5.kt → kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/internal/tsstdlib/lib.es5.kt
View File

@ -1,6 +1,6 @@
@file:Suppress("UNUSED_TYPEALIAS_PARAMETER", "DEPRECATION")
package kscience.kmath.estree.internal.tsstdlib
package space.kscience.kmath.estree.internal.tsstdlib
import kotlin.js.RegExp

41
kmath-ast/src/jsTest/kotlin/kscience/kmath/estree/TestESTreeOperationsSupport.kt
View File

@ -1,41 +0,0 @@
package kscience.kmath.estree
import kscience.kmath.ast.mstInExtendedField
import kscience.kmath.ast.mstInField
import kscience.kmath.ast.mstInSpace
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.RealField
import kotlin.random.Random
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestESTreeOperationsSupport {
@Test
fun testUnaryOperationInvocation() {
val expression = RealField.mstInSpace { -symbol("x") }.compile()
val res = expression("x" to 2.0)
assertEquals(-2.0, res)
}
@Test
fun testBinaryOperationInvocation() {
val expression = RealField.mstInSpace { -symbol("x") + number(1.0) }.compile()
val res = expression("x" to 2.0)
assertEquals(-1.0, res)
}
@Test
fun testConstProductInvocation() {
val res = RealField.mstInField { symbol("x") * 2 }("x" to 2.0)
assertEquals(4.0, res)
}
@Test
fun testMultipleCalls() {
val e = RealField.mstInExtendedField { sin(symbol("x")).pow(4) - 6 * symbol("x") / tanh(symbol("x")) }.compile()
val r = Random(0)
var s = 0.0
repeat(1000000) { s += e("x" to r.nextDouble()) }
println(s)
}
}

54
kmath-ast/src/jsTest/kotlin/kscience/kmath/estree/TestESTreeSpecialization.kt
View File

@ -1,54 +0,0 @@
package kscience.kmath.estree
import kscience.kmath.ast.mstInField
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.RealField
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestESTreeSpecialization {
@Test
fun testUnaryPlus() {
val expr = RealField.mstInField { unaryOperationFunction("+")(symbol("x")) }.compile()
assertEquals(2.0, expr("x" to 2.0))
}
@Test
fun testUnaryMinus() {
val expr = RealField.mstInField { unaryOperationFunction("-")(symbol("x")) }.compile()
assertEquals(-2.0, expr("x" to 2.0))
}
@Test
fun testAdd() {
val expr = RealField.mstInField { binaryOperationFunction("+")(symbol("x"), symbol("x")) }.compile()
assertEquals(4.0, expr("x" to 2.0))
}
@Test
fun testSine() {
val expr = RealField.mstInField { unaryOperationFunction("sin")(symbol("x")) }.compile()
assertEquals(0.0, expr("x" to 0.0))
}
@Test
fun testMinus() {
val expr = RealField.mstInField { binaryOperationFunction("-")(symbol("x"), symbol("x")) }.compile()
assertEquals(0.0, expr("x" to 2.0))
}
@Test
fun testDivide() {
val expr = RealField.mstInField { binaryOperationFunction("/")(symbol("x"), symbol("x")) }.compile()
assertEquals(1.0, expr("x" to 2.0))
}
@Test
fun testPower() {
val expr = RealField
.mstInField { binaryOperationFunction("pow")(symbol("x"), number(2)) }
.compile()
assertEquals(4.0, expr("x" to 2.0))
}
}

50
kmath-ast/src/jsTest/kotlin/kscience/kmath/estree/TestESTreeConsistencyWithInterpreter.kt → kmath-ast/src/jsTest/kotlin/space/kscience/kmath/estree/TestESTreeConsistencyWithInterpreter.kt
View File

@ -1,41 +1,41 @@
package kscience.kmath.estree
package space.kscience.kmath.estree
import kscience.kmath.ast.*
import kscience.kmath.complex.ComplexField
import kscience.kmath.complex.toComplex
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.ByteRing
import kscience.kmath.operations.RealField
import space.kscience.kmath.ast.*
import space.kscience.kmath.complex.ComplexField
import space.kscience.kmath.complex.toComplex
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.ByteRing
import space.kscience.kmath.operations.DoubleField
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestESTreeConsistencyWithInterpreter {
@Test
fun mstSpace() {
val res1 = MstSpace.mstInSpace {
val res1 = MstGroup.mstInGroup {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
number(3.toByte()) - (number(2.toByte()) + (multiply(
number(3.toByte()) - (number(2.toByte()) + (scale(
add(number(1), number(1)),
2
2.0
) + number(1.toByte()) * 3.toByte() - number(1.toByte())))
),
number(1)
) + symbol("x") + zero
) + bindSymbol("x") + zero
}("x" to MST.Numeric(2))
val res2 = MstSpace.mstInSpace {
val res2 = MstGroup.mstInGroup {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
number(3.toByte()) - (number(2.toByte()) + (multiply(
number(3.toByte()) - (number(2.toByte()) + (scale(
add(number(1), number(1)),
2
2.0
) + number(1.toByte()) * 3.toByte() - number(1.toByte())))
),
number(1)
) + symbol("x") + zero
) + bindSymbol("x") + zero
}.compile()("x" to MST.Numeric(2))
assertEquals(res1, res2)
@ -46,9 +46,9 @@ internal class TestESTreeConsistencyWithInterpreter {
val res1 = ByteRing.mstInRing {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
(symbol("x") - (2.toByte() + (multiply(
(bindSymbol("x") - (2.toByte() + (scale(
add(number(1), number(1)),
2
2.0
) + 1.toByte()))) * 3.0 - 1.toByte()
),
@ -59,9 +59,9 @@ internal class TestESTreeConsistencyWithInterpreter {
val res2 = ByteRing.mstInRing {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
(symbol("x") - (2.toByte() + (multiply(
(bindSymbol("x") - (2.toByte() + (scale(
add(number(1), number(1)),
2
2.0
) + 1.toByte()))) * 3.0 - 1.toByte()
),
number(1)
@ -73,17 +73,17 @@ internal class TestESTreeConsistencyWithInterpreter {
@Test
fun realField() {
val res1 = RealField.mstInField {
val res1 = DoubleField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(3.0 - (symbol("x") + (multiply(add(number(1.0), number(1.0)), 2) + 1.0))) * 3 - 1.0
(3.0 - (bindSymbol("x") + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0
+ number(1),
number(1) / 2 + number(2.0) * one
) + zero
}("x" to 2.0)
val res2 = RealField.mstInField {
val res2 = DoubleField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(3.0 - (symbol("x") + (multiply(add(number(1.0), number(1.0)), 2) + 1.0))) * 3 - 1.0
(3.0 - (bindSymbol("x") + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0
+ number(1),
number(1) / 2 + number(2.0) * one
) + zero
@ -96,7 +96,7 @@ internal class TestESTreeConsistencyWithInterpreter {
fun complexField() {
val res1 = ComplexField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(3.0 - (symbol("x") + (multiply(add(number(1.0), number(1.0)), 2) + 1.0))) * 3 - 1.0
(3.0 - (bindSymbol("x") + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0
+ number(1),
number(1) / 2 + number(2.0) * one
) + zero
@ -104,7 +104,7 @@ internal class TestESTreeConsistencyWithInterpreter {
val res2 = ComplexField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(3.0 - (symbol("x") + (multiply(add(number(1.0), number(1.0)), 2) + 1.0))) * 3 - 1.0
(3.0 - (bindSymbol("x") + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0
+ number(1),
number(1) / 2 + number(2.0) * one
) + zero

43
kmath-ast/src/jsTest/kotlin/space/kscience/kmath/estree/TestESTreeOperationsSupport.kt Normal file
View File

@ -0,0 +1,43 @@
package space.kscience.kmath.estree
import space.kscience.kmath.ast.mstInExtendedField
import space.kscience.kmath.ast.mstInField
import space.kscience.kmath.ast.mstInGroup
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.DoubleField
import kotlin.random.Random
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestESTreeOperationsSupport {
@Test
fun testUnaryOperationInvocation() {
val expression = DoubleField.mstInGroup { -bindSymbol("x") }.compile()
val res = expression("x" to 2.0)
assertEquals(-2.0, res)
}
@Test
fun testBinaryOperationInvocation() {
val expression = DoubleField.mstInGroup { -bindSymbol("x") + number(1.0) }.compile()
val res = expression("x" to 2.0)
assertEquals(-1.0, res)
}
@Test
fun testConstProductInvocation() {
val res = DoubleField.mstInField { bindSymbol("x") * 2 }("x" to 2.0)
assertEquals(4.0, res)
}
@Test
fun testMultipleCalls() {
val e =
DoubleField.mstInExtendedField { sin(bindSymbol("x")).pow(4) - 6 * bindSymbol("x") / tanh(bindSymbol("x")) }
.compile()
val r = Random(0)
var s = 0.0
repeat(1000000) { s += e("x" to r.nextDouble()) }
println(s)
}
}

54
kmath-ast/src/jsTest/kotlin/space/kscience/kmath/estree/TestESTreeSpecialization.kt Normal file
View File

@ -0,0 +1,54 @@
package space.kscience.kmath.estree
import space.kscience.kmath.ast.mstInField
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.DoubleField
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestESTreeSpecialization {
@Test
fun testUnaryPlus() {
val expr = DoubleField.mstInField { unaryOperationFunction("+")(bindSymbol("x")) }.compile()
assertEquals(2.0, expr("x" to 2.0))
}
@Test
fun testUnaryMinus() {
val expr = DoubleField.mstInField { unaryOperationFunction("-")(bindSymbol("x")) }.compile()
assertEquals(-2.0, expr("x" to 2.0))
}
@Test
fun testAdd() {
val expr = DoubleField.mstInField { binaryOperationFunction("+")(bindSymbol("x"), bindSymbol("x")) }.compile()
assertEquals(4.0, expr("x" to 2.0))
}
@Test
fun testSine() {
val expr = DoubleField.mstInField { unaryOperationFunction("sin")(bindSymbol("x")) }.compile()
assertEquals(0.0, expr("x" to 0.0))
}
@Test
fun testMinus() {
val expr = DoubleField.mstInField { binaryOperationFunction("-")(bindSymbol("x"), bindSymbol("x")) }.compile()
assertEquals(0.0, expr("x" to 2.0))
}
@Test
fun testDivide() {
val expr = DoubleField.mstInField { binaryOperationFunction("/")(bindSymbol("x"), bindSymbol("x")) }.compile()
assertEquals(1.0, expr("x" to 2.0))
}
@Test
fun testPower() {
val expr = DoubleField
.mstInField { binaryOperationFunction("pow")(bindSymbol("x"), number(2)) }
.compile()
assertEquals(4.0, expr("x" to 2.0))
}
}

12
kmath-ast/src/jsTest/kotlin/kscience/kmath/estree/TestESTreeVariables.kt → kmath-ast/src/jsTest/kotlin/space/kscience/kmath/estree/TestESTreeVariables.kt
View File

@ -1,8 +1,8 @@
package kscience.kmath.estree
package space.kscience.kmath.estree
import kscience.kmath.ast.mstInRing
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.ByteRing
import space.kscience.kmath.ast.mstInRing
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.ByteRing
import kotlin.test.Test
import kotlin.test.assertEquals
import kotlin.test.assertFailsWith
@ -10,13 +10,13 @@ import kotlin.test.assertFailsWith
internal class TestESTreeVariables {
@Test
fun testVariable() {
val expr = ByteRing.mstInRing { symbol("x") }.compile()
val expr = ByteRing.mstInRing { bindSymbol("x") }.compile()
assertEquals(1.toByte(), expr("x" to 1.toByte()))
}
@Test
fun testUndefinedVariableFails() {
val expr = ByteRing.mstInRing { symbol("x") }.compile()
val expr = ByteRing.mstInRing { bindSymbol("x") }.compile()
assertFailsWith<NoSuchElementException> { expr() }
}
}

20
kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/asm.kt → kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt
View File

@ -1,13 +1,13 @@
package kscience.kmath.asm
package space.kscience.kmath.asm
import kscience.kmath.asm.internal.AsmBuilder
import kscience.kmath.asm.internal.buildName
import kscience.kmath.ast.MST
import kscience.kmath.ast.MST.*
import kscience.kmath.ast.MstExpression
import kscience.kmath.expressions.Expression
import kscience.kmath.operations.Algebra
import kscience.kmath.operations.NumericAlgebra
import space.kscience.kmath.asm.internal.AsmBuilder
import space.kscience.kmath.asm.internal.buildName
import space.kscience.kmath.ast.MST
import space.kscience.kmath.ast.MST.*
import space.kscience.kmath.ast.MstExpression
import space.kscience.kmath.expressions.Expression
import space.kscience.kmath.operations.Algebra
import space.kscience.kmath.operations.NumericAlgebra
/**
* Compiles given MST to an Expression using AST compiler.
@ -22,7 +22,7 @@ internal fun <T : Any> MST.compileWith(type: Class<T>, algebra: Algebra<T>): Exp
fun AsmBuilder<T>.visit(node: MST): Unit = when (node) {
is Symbolic -> {
val symbol = try {
algebra.symbol(node.value)
algebra.bindSymbol(node.value)
} catch (ignored: IllegalStateException) {
null
}

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

@ -1,15 +1,14 @@
package kscience.kmath.asm.internal
package space.kscience.kmath.asm.internal
import kscience.kmath.asm.internal.AsmBuilder.ClassLoader
import kscience.kmath.ast.MST
import kscience.kmath.expressions.Expression
import org.objectweb.asm.*
import org.objectweb.asm.Opcodes.*
import org.objectweb.asm.Type.*
import org.objectweb.asm.commons.InstructionAdapter
import space.kscience.kmath.asm.internal.AsmBuilder.ClassLoader
import space.kscience.kmath.ast.MST
import space.kscience.kmath.expressions.Expression
import java.lang.invoke.MethodHandles
import java.lang.invoke.MethodType
import java.lang.reflect.Modifier
import java.util.stream.Collectors.toMap
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@ -310,7 +309,7 @@ internal class AsmBuilder<T>(
/**
* ASM type for [Expression].
*/
val EXPRESSION_TYPE: Type by lazy { getObjectType("kscience/kmath/expressions/Expression") }
val EXPRESSION_TYPE: Type by lazy { getObjectType("space/kscience/kmath/expressions/Expression") }
/**
* ASM type for [java.util.Map].
@ -335,11 +334,11 @@ internal class AsmBuilder<T>(
/**
* ASM type for MapIntrinsics.
*/
val MAP_INTRINSICS_TYPE: Type by lazy { getObjectType("kscience/kmath/asm/internal/MapIntrinsics") }
val MAP_INTRINSICS_TYPE: Type by lazy { getObjectType("space/kscience/kmath/asm/internal/MapIntrinsics") }
/**
* ASM Type for [kscience.kmath.expressions.Symbol].
*/
val SYMBOL_TYPE: Type by lazy { getObjectType("kscience/kmath/expressions/Symbol") }
val SYMBOL_TYPE: Type by lazy { getObjectType("space/kscience/kmath/expressions/Symbol") }
}
}

8
kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/codegenUtils.kt → kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt
View File

@ -1,9 +1,9 @@
package kscience.kmath.asm.internal
package space.kscience.kmath.asm.internal
import kscience.kmath.ast.MST
import kscience.kmath.expressions.Expression
import org.objectweb.asm.*
import org.objectweb.asm.commons.InstructionAdapter
import space.kscience.kmath.ast.MST
import space.kscience.kmath.expressions.Expression
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@ -86,7 +86,7 @@ internal inline fun ClassWriter.visitField(
descriptor: String,
signature: String?,
value: Any?,
block: FieldVisitor.() -> Unit
block: FieldVisitor.() -> Unit,
): FieldVisitor {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return visitField(access, name, descriptor, signature, value).apply(block)

6
kmath-ast/src/jvmMain/kotlin/kscience/kmath/asm/internal/mapIntrinsics.kt → kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt
View File

@ -1,9 +1,9 @@
@file:JvmName("MapIntrinsics")
package kscience.kmath.asm.internal
package space.kscience.kmath.asm.internal
import kscience.kmath.expressions.StringSymbol
import kscience.kmath.expressions.Symbol
import space.kscience.kmath.misc.StringSymbol
import space.kscience.kmath.misc.Symbol
/**
* Gets value with given [key] or throws [NoSuchElementException] whenever it is not present.

24
kmath-ast/src/jvmMain/kotlin/kscience/kmath/ast/parser.kt → kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/ast/parser.kt
View File

@ -1,6 +1,6 @@
// TODO move to common when https://github.com/h0tk3y/better-parse/pull/33 is merged
// TODO move to common when https://github.com/h0tk3y/better-parse/pull/37 is merged
package kscience.kmath.ast
package space.kscience.kmath.ast
import com.github.h0tk3y.betterParse.combinators.*
import com.github.h0tk3y.betterParse.grammar.Grammar
@ -13,10 +13,10 @@ import com.github.h0tk3y.betterParse.lexer.literalToken
import com.github.h0tk3y.betterParse.lexer.regexToken
import com.github.h0tk3y.betterParse.parser.ParseResult
import com.github.h0tk3y.betterParse.parser.Parser
import kscience.kmath.operations.FieldOperations
import kscience.kmath.operations.PowerOperations
import kscience.kmath.operations.RingOperations
import kscience.kmath.operations.SpaceOperations
import space.kscience.kmath.operations.FieldOperations
import space.kscience.kmath.operations.GroupOperations
import space.kscience.kmath.operations.PowerOperations
import space.kscience.kmath.operations.RingOperations
/**
* better-parse implementation of grammar defined in the ArithmeticsEvaluator.g4.
@ -25,8 +25,8 @@ import kscience.kmath.operations.SpaceOperations
*/
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]*")
private val num: Token by regexToken("[\\d.]+(?:[eE][-+]?\\d+)?".toRegex())
private val id: Token by regexToken("[a-z_A-Z][\\da-z_A-Z]*".toRegex())
private val lpar: Token by literalToken("(")
private val rpar: Token by literalToken(")")
private val comma: Token by literalToken(",")
@ -35,7 +35,7 @@ public object ArithmeticsEvaluator : Grammar<MST>() {
private val div: Token by literalToken("/")
private val minus: Token by literalToken("-")
private val plus: Token by literalToken("+")
private val ws: Token by regexToken("\\s+", ignore = true)
private val ws: Token by regexToken("\\s+".toRegex(), ignore = true)
private val number: Parser<MST> by num use { MST.Numeric(text.toDouble()) }
private val singular: Parser<MST> by id use { MST.Symbolic(text) }
@ -55,7 +55,7 @@ public object ArithmeticsEvaluator : Grammar<MST>() {
.or(binaryFunction)
.or(unaryFunction)
.or(singular)
.or(-minus and parser(ArithmeticsEvaluator::term) map { MST.Unary(SpaceOperations.MINUS_OPERATION, it) })
.or(-minus and parser(ArithmeticsEvaluator::term) map { MST.Unary(GroupOperations.MINUS_OPERATION, it) })
.or(-lpar and parser(ArithmeticsEvaluator::subSumChain) and -rpar)
private val powChain: Parser<MST> by leftAssociative(term = term, operator = pow) { a, _, b ->
@ -77,9 +77,9 @@ public object ArithmeticsEvaluator : Grammar<MST>() {
operator = plus or minus use TokenMatch::type
) { a, op, b ->
if (op == plus)
MST.Binary(SpaceOperations.PLUS_OPERATION, a, b)
MST.Binary(GroupOperations.PLUS_OPERATION, a, b)
else
MST.Binary(SpaceOperations.MINUS_OPERATION, a, b)
MST.Binary(GroupOperations.MINUS_OPERATION, a, b)
}
override val rootParser: Parser<MST> by subSumChain

41
kmath-ast/src/jvmTest/kotlin/kscience/kmath/asm/TestAsmOperationsSupport.kt
View File

@ -1,41 +0,0 @@
package kscience.kmath.asm
import kscience.kmath.ast.mstInExtendedField
import kscience.kmath.ast.mstInField
import kscience.kmath.ast.mstInSpace
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.RealField
import kotlin.random.Random
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestAsmOperationsSupport {
@Test
fun testUnaryOperationInvocation() {
val expression = RealField.mstInSpace { -symbol("x") }.compile()
val res = expression("x" to 2.0)
assertEquals(-2.0, res)
}
@Test
fun testBinaryOperationInvocation() {
val expression = RealField.mstInSpace { -symbol("x") + number(1.0) }.compile()
val res = expression("x" to 2.0)
assertEquals(-1.0, res)
}
@Test
fun testConstProductInvocation() {
val res = RealField.mstInField { symbol("x") * 2 }("x" to 2.0)
assertEquals(4.0, res)
}
@Test
fun testMultipleCalls() {
val e = RealField.mstInExtendedField { sin(symbol("x")).pow(4) - 6 * symbol("x") / tanh(symbol("x")) }.compile()
val r = Random(0)
var s = 0.0
repeat(1000000) { s += e("x" to r.nextDouble()) }
println(s)
}
}

54
kmath-ast/src/jvmTest/kotlin/kscience/kmath/asm/TestAsmSpecialization.kt
View File

@ -1,54 +0,0 @@
package kscience.kmath.asm
import kscience.kmath.ast.mstInField
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.RealField
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestAsmSpecialization {
@Test
fun testUnaryPlus() {
val expr = RealField.mstInField { unaryOperationFunction("+")(symbol("x")) }.compile()
assertEquals(2.0, expr("x" to 2.0))
}
@Test
fun testUnaryMinus() {
val expr = RealField.mstInField { unaryOperationFunction("-")(symbol("x")) }.compile()
assertEquals(-2.0, expr("x" to 2.0))
}
@Test
fun testAdd() {
val expr = RealField.mstInField { binaryOperationFunction("+")(symbol("x"), symbol("x")) }.compile()
assertEquals(4.0, expr("x" to 2.0))
}
@Test
fun testSine() {
val expr = RealField.mstInField { unaryOperationFunction("sin")(symbol("x")) }.compile()
assertEquals(0.0, expr("x" to 0.0))
}
@Test
fun testMinus() {
val expr = RealField.mstInField { binaryOperationFunction("-")(symbol("x"), symbol("x")) }.compile()
assertEquals(0.0, expr("x" to 2.0))
}
@Test
fun testDivide() {
val expr = RealField.mstInField { binaryOperationFunction("/")(symbol("x"), symbol("x")) }.compile()
assertEquals(1.0, expr("x" to 2.0))
}
@Test
fun testPower() {
val expr = RealField
.mstInField { binaryOperationFunction("pow")(symbol("x"), number(2)) }
.compile()
assertEquals(4.0, expr("x" to 2.0))
}
}

49
kmath-ast/src/jvmTest/kotlin/kscience/kmath/asm/TestAsmConsistencyWithInterpreter.kt → kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/asm/TestAsmConsistencyWithInterpreter.kt
View File

@ -1,40 +1,41 @@
package kscience.kmath.asm
package space.kscience.kmath.asm
import kscience.kmath.ast.*
import kscience.kmath.complex.*
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.ByteRing
import kscience.kmath.operations.RealField
import space.kscience.kmath.ast.*
import space.kscience.kmath.complex.ComplexField
import space.kscience.kmath.complex.toComplex
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.ByteRing
import space.kscience.kmath.operations.DoubleField
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestAsmConsistencyWithInterpreter {
@Test
fun mstSpace() {
val res1 = MstSpace.mstInSpace {
val res1 = MstGroup.mstInGroup {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
number(3.toByte()) - (number(2.toByte()) + (multiply(
number(3.toByte()) - (number(2.toByte()) + (scale(
add(number(1), number(1)),
2
2.0
) + number(1.toByte()) * 3.toByte() - number(1.toByte())))
),
number(1)
) + symbol("x") + zero
) + bindSymbol("x") + zero
}("x" to MST.Numeric(2))
val res2 = MstSpace.mstInSpace {
val res2 = MstGroup.mstInGroup {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
number(3.toByte()) - (number(2.toByte()) + (multiply(
number(3.toByte()) - (number(2.toByte()) + (scale(
add(number(1), number(1)),
2
2.0
) + number(1.toByte()) * 3.toByte() - number(1.toByte())))
),
number(1)
) + symbol("x") + zero
) + bindSymbol("x") + zero
}.compile()("x" to MST.Numeric(2))
assertEquals(res1, res2)
@ -45,9 +46,9 @@ internal class TestAsmConsistencyWithInterpreter {
val res1 = ByteRing.mstInRing {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
(symbol("x") - (2.toByte() + (multiply(
(bindSymbol("x") - (2.toByte() + (scale(
add(number(1), number(1)),
2
2.0
) + 1.toByte()))) * 3.0 - 1.toByte()
),
@ -58,9 +59,9 @@ internal class TestAsmConsistencyWithInterpreter {
val res2 = ByteRing.mstInRing {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
(symbol("x") - (2.toByte() + (multiply(
(bindSymbol("x") - (2.toByte() + (scale(
add(number(1), number(1)),
2
2.0
) + 1.toByte()))) * 3.0 - 1.toByte()
),
number(1)
@ -72,17 +73,17 @@ internal class TestAsmConsistencyWithInterpreter {
@Test
fun realField() {
val res1 = RealField.mstInField {
val res1 = DoubleField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(3.0 - (symbol("x") + (multiply(add(number(1.0), number(1.0)), 2) + 1.0))) * 3 - 1.0
(3.0 - (bindSymbol("x") + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0
+ number(1),
number(1) / 2 + number(2.0) * one
) + zero
}("x" to 2.0)
val res2 = RealField.mstInField {
val res2 = DoubleField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(3.0 - (symbol("x") + (multiply(add(number(1.0), number(1.0)), 2) + 1.0))) * 3 - 1.0
(3.0 - (bindSymbol("x") + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0
+ number(1),
number(1) / 2 + number(2.0) * one
) + zero
@ -95,7 +96,7 @@ internal class TestAsmConsistencyWithInterpreter {
fun complexField() {
val res1 = ComplexField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(3.0 - (symbol("x") + (multiply(add(number(1.0), number(1.0)), 2) + 1.0))) * 3 - 1.0
(3.0 - (bindSymbol("x") + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0
+ number(1),
number(1) / 2 + number(2.0) * one
) + zero
@ -103,7 +104,7 @@ internal class TestAsmConsistencyWithInterpreter {
val res2 = ComplexField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(3.0 - (symbol("x") + (multiply(add(number(1.0), number(1.0)), 2) + 1.0))) * 3 - 1.0
(3.0 - (bindSymbol("x") + (scale(add(number(1.0), number(1.0)), 2.0) + 1.0))) * 3 - 1.0
+ number(1),
number(1) / 2 + number(2.0) * one
) + zero

43
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/asm/TestAsmOperationsSupport.kt Normal file
View File

@ -0,0 +1,43 @@
package space.kscience.kmath.asm
import space.kscience.kmath.ast.mstInExtendedField
import space.kscience.kmath.ast.mstInField
import space.kscience.kmath.ast.mstInGroup
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.DoubleField
import kotlin.random.Random
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestAsmOperationsSupport {
@Test
fun testUnaryOperationInvocation() {
val expression = DoubleField.mstInGroup { -bindSymbol("x") }.compile()
val res = expression("x" to 2.0)
assertEquals(-2.0, res)
}
@Test
fun testBinaryOperationInvocation() {
val expression = DoubleField.mstInGroup { -bindSymbol("x") + number(1.0) }.compile()
val res = expression("x" to 2.0)
assertEquals(-1.0, res)
}
@Test
fun testConstProductInvocation() {
val res = DoubleField.mstInField { bindSymbol("x") * 2 }("x" to 2.0)
assertEquals(4.0, res)
}
@Test
fun testMultipleCalls() {
val e =
DoubleField.mstInExtendedField { sin(bindSymbol("x")).pow(4) - 6 * bindSymbol("x") / tanh(bindSymbol("x")) }
.compile()
val r = Random(0)
var s = 0.0
repeat(1000000) { s += e("x" to r.nextDouble()) }
println(s)
}
}

54
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/asm/TestAsmSpecialization.kt Normal file
View File

@ -0,0 +1,54 @@
package space.kscience.kmath.asm
import space.kscience.kmath.ast.mstInField
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.DoubleField
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestAsmSpecialization {
@Test
fun testUnaryPlus() {
val expr = DoubleField.mstInField { unaryOperationFunction("+")(bindSymbol("x")) }.compile()
assertEquals(2.0, expr("x" to 2.0))
}
@Test
fun testUnaryMinus() {
val expr = DoubleField.mstInField { unaryOperationFunction("-")(bindSymbol("x")) }.compile()
assertEquals(-2.0, expr("x" to 2.0))
}
@Test
fun testAdd() {
val expr = DoubleField.mstInField { binaryOperationFunction("+")(bindSymbol("x"), bindSymbol("x")) }.compile()
assertEquals(4.0, expr("x" to 2.0))
}
@Test
fun testSine() {
val expr = DoubleField.mstInField { unaryOperationFunction("sin")(bindSymbol("x")) }.compile()
assertEquals(0.0, expr("x" to 0.0))
}
@Test
fun testMinus() {
val expr = DoubleField.mstInField { binaryOperationFunction("-")(bindSymbol("x"), bindSymbol("x")) }.compile()
assertEquals(0.0, expr("x" to 2.0))
}
@Test
fun testDivide() {
val expr = DoubleField.mstInField { binaryOperationFunction("/")(bindSymbol("x"), bindSymbol("x")) }.compile()
assertEquals(1.0, expr("x" to 2.0))
}
@Test
fun testPower() {
val expr = DoubleField
.mstInField { binaryOperationFunction("pow")(bindSymbol("x"), number(2)) }
.compile()
assertEquals(4.0, expr("x" to 2.0))
}
}

12
kmath-ast/src/jvmTest/kotlin/kscience/kmath/asm/TestAsmVariables.kt → kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/asm/TestAsmVariables.kt
View File

@ -1,8 +1,8 @@
package kscience.kmath.asm
package space.kscience.kmath.asm
import kscience.kmath.ast.mstInRing
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.ByteRing
import space.kscience.kmath.ast.mstInRing
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.ByteRing
import kotlin.test.Test
import kotlin.test.assertEquals
import kotlin.test.assertFailsWith
@ -10,13 +10,13 @@ import kotlin.test.assertFailsWith
internal class TestAsmVariables {
@Test
fun testVariable() {
val expr = ByteRing.mstInRing { symbol("x") }.compile()
val expr = ByteRing.mstInRing { bindSymbol("x") }.compile()
assertEquals(1.toByte(), expr("x" to 1.toByte()))
}
@Test
fun testUndefinedVariableFails() {
val expr = ByteRing.mstInRing { symbol("x") }.compile()
val expr = ByteRing.mstInRing { bindSymbol("x") }.compile()
assertFailsWith<NoSuchElementException> { expr() }
}
}

8
kmath-ast/src/jvmTest/kotlin/kscience/kmath/ast/ParserPrecedenceTest.kt → kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/ParserPrecedenceTest.kt
View File

@ -1,12 +1,12 @@
package kscience.kmath.ast
package space.kscience.kmath.ast
import kscience.kmath.operations.Field
import kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.Field
import kotlin.test.Test
import kotlin.test.assertEquals
internal class ParserPrecedenceTest {
private val f: Field<Double> = RealField
private val f: Field<Double> = DoubleField
@Test
fun test1(): Unit = assertEquals(6.0, f.evaluate("2*2+2".parseMath()))

16
kmath-ast/src/jvmTest/kotlin/kscience/kmath/ast/ParserTest.kt → kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/ParserTest.kt
View File

@ -1,10 +1,10 @@
package kscience.kmath.ast
package space.kscience.kmath.ast
import kscience.kmath.complex.Complex
import kscience.kmath.complex.ComplexField
import kscience.kmath.expressions.invoke
import kscience.kmath.operations.Algebra
import kscience.kmath.operations.RealField
import space.kscience.kmath.complex.Complex
import space.kscience.kmath.complex.ComplexField
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.Algebra
import space.kscience.kmath.operations.DoubleField
import kotlin.test.Test
import kotlin.test.assertEquals
@ -33,14 +33,14 @@ internal class ParserTest {
@Test
fun `evaluate MST with unary function`() {
val mst = "sin(0)".parseMath()
val res = RealField.evaluate(mst)
val res = DoubleField.evaluate(mst)
assertEquals(0.0, res)
}
@Test
fun `evaluate MST with binary function`() {
val magicalAlgebra = object : Algebra<String> {
override fun symbol(value: String): String = value
override fun bindSymbol(value: String): String = value
override fun unaryOperationFunction(operation: String): (arg: String) -> String {
throw NotImplementedError()

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

@ -1,5 +1,5 @@
plugins {
id("ru.mipt.npm.jvm")
id("ru.mipt.npm.gradle.jvm")
}
description = "Commons math binding for kmath"
@ -12,6 +12,6 @@ dependencies {
api("org.apache.commons:commons-math3:3.6.1")
}
readme{
readme {
maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL
}

118
kmath-commons/src/main/kotlin/kscience/kmath/commons/linear/CMMatrix.kt
View File

@ -1,118 +0,0 @@
package kscience.kmath.commons.linear
import kscience.kmath.linear.*
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.structures.RealBuffer
import org.apache.commons.math3.linear.*
import kotlin.reflect.KClass
import kotlin.reflect.cast
public inline class CMMatrix(public val origin: RealMatrix) : Matrix<Double> {
public override val rowNum: Int get() = origin.rowDimension
public override val colNum: Int get() = origin.columnDimension
@UnstableKMathAPI
override fun <T : Any> getFeature(type: KClass<T>): T? = when (type) {
DiagonalFeature::class -> if (origin is DiagonalMatrix) DiagonalFeature else null
DeterminantFeature::class, LupDecompositionFeature::class -> object :
DeterminantFeature<Double>,
LupDecompositionFeature<Double> {
private val lup by lazy { LUDecomposition(origin) }
override val determinant: Double by lazy { lup.determinant }
override val l: Matrix<Double> by lazy { CMMatrix(lup.l) + LFeature }
override val u: Matrix<Double> by lazy { CMMatrix(lup.u) + UFeature }
override val p: Matrix<Double> by lazy { CMMatrix(lup.p) }
}
CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<Double> {
override val l: Matrix<Double> by lazy {
val cholesky = CholeskyDecomposition(origin)
CMMatrix(cholesky.l) + LFeature
}
}
QRDecompositionFeature::class -> object : QRDecompositionFeature<Double> {
private val qr by lazy { QRDecomposition(origin) }
override val q: Matrix<Double> by lazy { CMMatrix(qr.q) + OrthogonalFeature }
override val r: Matrix<Double> by lazy { CMMatrix(qr.r) + UFeature }
}
SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature<Double> {
private val sv by lazy { SingularValueDecomposition(origin) }
override val u: Matrix<Double> by lazy { CMMatrix(sv.u) }
override val s: Matrix<Double> by lazy { CMMatrix(sv.s) }
override val v: Matrix<Double> by lazy { CMMatrix(sv.v) }
override val singularValues: Point<Double> by lazy { RealBuffer(sv.singularValues) }
}
else -> null
}?.let(type::cast)
public override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
}
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, CMMatrix> {
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))
}
@OptIn(UnstableKMathAPI::class)
public fun Matrix<Double>.toCM(): CMMatrix = when (val matrix = origin) {
is CMMatrix -> matrix
else -> {
//TODO add feature analysis
val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
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): CMMatrix =
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))

27
kmath-commons/src/main/kotlin/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt → kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt
View File

@ -1,10 +1,12 @@
package kscience.kmath.commons.expressions
package space.kscience.kmath.commons.expressions
import kscience.kmath.expressions.*
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.operations.ExtendedField
import kscience.kmath.operations.RingWithNumbers
import org.apache.commons.math3.analysis.differentiation.DerivativeStructure
import space.kscience.kmath.expressions.*
import space.kscience.kmath.misc.StringSymbol
import space.kscience.kmath.misc.Symbol
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.ExtendedField
import space.kscience.kmath.operations.NumbersAddOperations
/**
* A field over commons-math [DerivativeStructure].
@ -16,7 +18,8 @@ import org.apache.commons.math3.analysis.differentiation.DerivativeStructure
public class DerivativeStructureField(
public val order: Int,
bindings: Map<Symbol, Double>,
) : ExtendedField<DerivativeStructure>, ExpressionAlgebra<Double, DerivativeStructure>, RingWithNumbers<DerivativeStructure> {
) : ExtendedField<DerivativeStructure>, ExpressionAlgebra<Double, DerivativeStructure>,
NumbersAddOperations<DerivativeStructure> {
public val numberOfVariables: Int = bindings.size
public override val zero: DerivativeStructure by lazy { DerivativeStructure(numberOfVariables, order) }
@ -48,11 +51,11 @@ public class DerivativeStructureField(
override fun const(value: Double): DerivativeStructure = DerivativeStructure(numberOfVariables, order, value)
public override fun bindOrNull(symbol: Symbol): DerivativeStructureSymbol? = variables[symbol.identity]
public override fun bindSymbolOrNull(symbol: Symbol): DerivativeStructureSymbol? = variables[symbol.identity]
public fun bind(symbol: Symbol): DerivativeStructureSymbol = variables.getValue(symbol.identity)
override fun symbol(value: String): DerivativeStructureSymbol = bind(StringSymbol(value))
override fun bindSymbol(value: String): DerivativeStructureSymbol = bind(StringSymbol(value))
public fun DerivativeStructure.derivative(symbols: List<Symbol>): Double {
require(symbols.size <= order) { "The order of derivative ${symbols.size} exceeds computed order $order" }
@ -62,13 +65,11 @@ public class DerivativeStructureField(
public fun DerivativeStructure.derivative(vararg symbols: Symbol): Double = derivative(symbols.toList())
override fun DerivativeStructure.unaryMinus(): DerivativeStructure = negate()
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 scale(a: DerivativeStructure, value: Double): DerivativeStructure = a.multiply(value)
public override fun multiply(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.multiply(b)
public override fun divide(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.divide(b)

92
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt Normal file
View File

@ -0,0 +1,92 @@
package space.kscience.kmath.commons.integration
import org.apache.commons.math3.analysis.integration.IterativeLegendreGaussIntegrator
import org.apache.commons.math3.analysis.integration.SimpsonIntegrator
import space.kscience.kmath.integration.*
import space.kscience.kmath.misc.UnstableKMathAPI
/**
* Integration wrapper for Common-maths UnivariateIntegrator
*/
public class CMIntegrator(
private val defaultMaxCalls: Int = 200,
public val integratorBuilder: (Integrand) -> org.apache.commons.math3.analysis.integration.UnivariateIntegrator,
) : UnivariateIntegrator<Double> {
public class TargetRelativeAccuracy(public val value: Double) : IntegrandFeature
public class TargetAbsoluteAccuracy(public val value: Double) : IntegrandFeature
public class MinIterations(public val value: Int) : IntegrandFeature
public class MaxIterations(public val value: Int) : IntegrandFeature
override fun integrate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
val integrator = integratorBuilder(integrand)
val maxCalls = integrand.getFeature<IntegrandMaxCalls>()?.maxCalls ?: defaultMaxCalls
val remainingCalls = maxCalls - integrand.calls
val range = integrand.getFeature<IntegrationRange<Double>>()?.range
?: error("Integration range is not provided")
val res = integrator.integrate(remainingCalls, integrand.function, range.start, range.endInclusive)
return integrand +
IntegrandValue(res) +
IntegrandAbsoluteAccuracy(integrator.absoluteAccuracy) +
IntegrandRelativeAccuracy(integrator.relativeAccuracy) +
IntegrandCalls(integrator.evaluations + integrand.calls)
}
public companion object {
/**
* Create a Simpson integrator based on [SimpsonIntegrator]
*/
public fun simpson(defaultMaxCalls: Int = 200): CMIntegrator = CMIntegrator(defaultMaxCalls) { integrand ->
val absoluteAccuracy = integrand.getFeature<TargetAbsoluteAccuracy>()?.value
?: SimpsonIntegrator.DEFAULT_ABSOLUTE_ACCURACY
val relativeAccuracy = integrand.getFeature<TargetRelativeAccuracy>()?.value
?: SimpsonIntegrator.DEFAULT_ABSOLUTE_ACCURACY
val minIterations = integrand.getFeature<MinIterations>()?.value
?: SimpsonIntegrator.DEFAULT_MIN_ITERATIONS_COUNT
val maxIterations = integrand.getFeature<MaxIterations>()?.value
?: SimpsonIntegrator.SIMPSON_MAX_ITERATIONS_COUNT
SimpsonIntegrator(relativeAccuracy, absoluteAccuracy, minIterations, maxIterations)
}
/**
* Create a Gauss-Legandre integrator based on [IterativeLegendreGaussIntegrator]
*/
public fun legandre(numPoints: Int, defaultMaxCalls: Int = numPoints * 5): CMIntegrator =
CMIntegrator(defaultMaxCalls) { integrand ->
val absoluteAccuracy = integrand.getFeature<TargetAbsoluteAccuracy>()?.value
?: IterativeLegendreGaussIntegrator.DEFAULT_ABSOLUTE_ACCURACY
val relativeAccuracy = integrand.getFeature<TargetRelativeAccuracy>()?.value
?: IterativeLegendreGaussIntegrator.DEFAULT_ABSOLUTE_ACCURACY
val minIterations = integrand.getFeature<MinIterations>()?.value
?: IterativeLegendreGaussIntegrator.DEFAULT_MIN_ITERATIONS_COUNT
val maxIterations = integrand.getFeature<MaxIterations>()?.value
?: IterativeLegendreGaussIntegrator.DEFAULT_MAX_ITERATIONS_COUNT
IterativeLegendreGaussIntegrator(
numPoints,
relativeAccuracy,
absoluteAccuracy,
minIterations,
maxIterations
)
}
}
}
@UnstableKMathAPI
public var MutableList<IntegrandFeature>.targetAbsoluteAccuracy: Double?
get() = filterIsInstance<CMIntegrator.TargetAbsoluteAccuracy>().lastOrNull()?.value
set(value) {
value?.let { add(CMIntegrator.TargetAbsoluteAccuracy(value)) }
}
@UnstableKMathAPI
public var MutableList<IntegrandFeature>.targetRelativeAccuracy: Double?
get() = filterIsInstance<CMIntegrator.TargetRelativeAccuracy>().lastOrNull()?.value
set(value) {
value?.let { add(CMIntegrator.TargetRelativeAccuracy(value)) }
}

94
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt Normal file
View File

@ -0,0 +1,94 @@
/*
* 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 space.kscience.kmath.commons.integration
import org.apache.commons.math3.analysis.integration.gauss.GaussIntegrator
import org.apache.commons.math3.analysis.integration.gauss.GaussIntegratorFactory
import space.kscience.kmath.integration.*
/**
* A simple one-pass integrator based on Gauss rule
*/
public class GaussRuleIntegrator(
private val numpoints: Int,
private var type: GaussRule = GaussRule.LEGANDRE,
) : UnivariateIntegrator<Double> {
override fun integrate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
val range = integrand.getFeature<IntegrationRange<Double>>()?.range
?: error("Integration range is not provided")
val integrator: GaussIntegrator = getIntegrator(range)
//TODO check performance
val res: Double = integrator.integrate(integrand.function)
return integrand + IntegrandValue(res) + IntegrandCalls(integrand.calls + numpoints)
}
private fun getIntegrator(range: ClosedRange<Double>): GaussIntegrator {
return when (type) {
GaussRule.LEGANDRE -> factory.legendre(
numpoints,
range.start,
range.endInclusive
)
GaussRule.LEGANDREHP -> factory.legendreHighPrecision(
numpoints,
range.start,
range.endInclusive
)
GaussRule.UNIFORM -> GaussIntegrator(
getUniformRule(
range.start,
range.endInclusive,
numpoints
)
)
}
}
private fun getUniformRule(
min: Double,
max: Double,
numPoints: Int,
): org.apache.commons.math3.util.Pair<DoubleArray, DoubleArray> {
assert(numPoints > 2)
val points = DoubleArray(numPoints)
val weights = DoubleArray(numPoints)
val step = (max - min) / (numPoints - 1)
points[0] = min
for (i in 1 until numPoints) {
points[i] = points[i - 1] + step
weights[i] = step
}
return org.apache.commons.math3.util.Pair<DoubleArray, DoubleArray>(points, weights)
}
public enum class GaussRule {
UNIFORM, LEGANDRE, LEGANDREHP
}
public companion object {
private val factory: GaussIntegratorFactory = GaussIntegratorFactory()
public fun integrate(
range: ClosedRange<Double>,
numPoints: Int = 100,
type: GaussRule = GaussRule.LEGANDRE,
function: (Double) -> Double,
): Double = GaussRuleIntegrator(numPoints, type).integrate(
UnivariateIntegrand(function, IntegrationRange(range))
).value!!
}
}

141
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt Normal file
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@ -0,0 +1,141 @@
package space.kscience.kmath.commons.linear
import org.apache.commons.math3.linear.*
import space.kscience.kmath.linear.*
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.StructureFeature
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.structures.DoubleBuffer
import kotlin.reflect.KClass
import kotlin.reflect.cast
public inline class CMMatrix(public val origin: RealMatrix) : Matrix<Double> {
public override val rowNum: Int get() = origin.rowDimension
public override val colNum: Int get() = origin.columnDimension
public override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
}
public inline 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 RealVector.toPoint(): CMVector = CMVector(this)
public object CMLinearSpace : LinearSpace<Double, DoubleField> {
override val elementAlgebra: DoubleField get() = DoubleField
public override fun buildMatrix(
rows: Int,
columns: Int,
initializer: DoubleField.(i: Int, j: Int) -> Double,
): CMMatrix {
val array = Array(rows) { i -> DoubleArray(columns) { j -> DoubleField.initializer(i, j) } }
return CMMatrix(Array2DRowRealMatrix(array))
}
@OptIn(UnstableKMathAPI::class)
public fun Matrix<Double>.toCM(): CMMatrix = when (val matrix = origin) {
is CMMatrix -> matrix
else -> {
//TODO add feature analysis
val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
Array2DRowRealMatrix(array).wrap()
}
}
public fun Point<Double>.toCM(): CMVector = if (this is CMVector) this else {
val array = DoubleArray(size) { this[it] }
ArrayRealVector(array).wrap()
}
internal fun RealMatrix.wrap(): CMMatrix = CMMatrix(this)
internal fun RealVector.wrap(): CMVector = CMVector(this)
override fun buildVector(size: Int, initializer: DoubleField.(Int) -> Double): Point<Double> =
ArrayRealVector(DoubleArray(size) { DoubleField.initializer(it) }).wrap()
override fun Matrix<Double>.plus(other: Matrix<Double>): CMMatrix =
toCM().origin.add(other.toCM().origin).wrap()
override fun Point<Double>.plus(other: Point<Double>): CMVector =
toCM().origin.add(other.toCM().origin).wrap()
override fun Point<Double>.minus(other: Point<Double>): CMVector =
toCM().origin.subtract(other.toCM().origin).wrap()
public override fun Matrix<Double>.dot(other: Matrix<Double>): CMMatrix =
toCM().origin.multiply(other.toCM().origin).wrap()
public override fun Matrix<Double>.dot(vector: Point<Double>): CMVector =
toCM().origin.preMultiply(vector.toCM().origin).wrap()
public override operator fun Matrix<Double>.minus(other: Matrix<Double>): CMMatrix =
toCM().origin.subtract(other.toCM().origin).wrap()
public override operator fun Matrix<Double>.times(value: Double): CMMatrix =
toCM().origin.scalarMultiply(value).wrap()
override fun Double.times(m: Matrix<Double>): CMMatrix =
m * this
override fun Point<Double>.times(value: Double): CMVector =
toCM().origin.mapMultiply(value).wrap()
override fun Double.times(v: Point<Double>): CMVector =
v * this
@UnstableKMathAPI
override fun <F : StructureFeature> getFeature(structure: Matrix<Double>, type: KClass<out F>): F? {
//Return the feature if it is intrinsic to the structure
structure.getFeature(type)?.let { return it }
val origin = structure.toCM().origin
return when (type) {
DiagonalFeature::class -> if (origin is DiagonalMatrix) DiagonalFeature else null
DeterminantFeature::class, LupDecompositionFeature::class -> object :
DeterminantFeature<Double>,
LupDecompositionFeature<Double> {
private val lup by lazy { LUDecomposition(origin) }
override val determinant: Double by lazy { lup.determinant }
override val l: Matrix<Double> by lazy { CMMatrix(lup.l) + LFeature }
override val u: Matrix<Double> by lazy { CMMatrix(lup.u) + UFeature }
override val p: Matrix<Double> by lazy { CMMatrix(lup.p) }
}
CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<Double> {
override val l: Matrix<Double> by lazy {
val cholesky = CholeskyDecomposition(origin)
CMMatrix(cholesky.l) + LFeature
}
}
QRDecompositionFeature::class -> object : QRDecompositionFeature<Double> {
private val qr by lazy { QRDecomposition(origin) }
override val q: Matrix<Double> by lazy { CMMatrix(qr.q) + OrthogonalFeature }
override val r: Matrix<Double> by lazy { CMMatrix(qr.r) + UFeature }
}
SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature<Double> {
private val sv by lazy { SingularValueDecomposition(origin) }
override val u: Matrix<Double> by lazy { CMMatrix(sv.u) }
override val s: Matrix<Double> by lazy { CMMatrix(sv.s) }
override val v: Matrix<Double> by lazy { CMMatrix(sv.v) }
override val singularValues: Point<Double> by lazy { DoubleBuffer(sv.singularValues) }
}
else -> null
}?.let(type::cast)
}
}
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))

26
kmath-commons/src/main/kotlin/kscience/kmath/commons/linear/CMSolver.kt → kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt
View File

@ -1,8 +1,8 @@
package kscience.kmath.commons.linear
package space.kscience.kmath.commons.linear
import kscience.kmath.linear.Matrix
import kscience.kmath.linear.Point
import org.apache.commons.math3.linear.*
import space.kscience.kmath.linear.Matrix
import space.kscience.kmath.linear.Point
public enum class CMDecomposition {
LUP,
@ -12,9 +12,9 @@ public enum class CMDecomposition {
CHOLESKY
}
public fun CMMatrixContext.solver(
public fun CMLinearSpace.solver(
a: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
decomposition: CMDecomposition = CMDecomposition.LUP,
): DecompositionSolver = when (decomposition) {
CMDecomposition.LUP -> LUDecomposition(a.toCM().origin).solver
CMDecomposition.RRQR -> RRQRDecomposition(a.toCM().origin).solver
@ -23,19 +23,19 @@ public fun CMMatrixContext.solver(
CMDecomposition.CHOLESKY -> CholeskyDecomposition(a.toCM().origin).solver
}
public fun CMMatrixContext.solve(
public fun CMLinearSpace.solve(
a: Matrix<Double>,
b: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).asMatrix()
decomposition: CMDecomposition = CMDecomposition.LUP,
): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).wrap()
public fun CMMatrixContext.solve(
public fun CMLinearSpace.solve(
a: Matrix<Double>,
b: Point<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
decomposition: CMDecomposition = CMDecomposition.LUP,
): CMVector = solver(a, decomposition).solve(b.toCM().origin).toPoint()
public fun CMMatrixContext.inverse(
public fun CMLinearSpace.inverse(
a: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMMatrix = solver(a, decomposition).inverse.asMatrix()
decomposition: CMDecomposition = CMDecomposition.LUP,
): CMMatrix = solver(a, decomposition).inverse.wrap()

62
kmath-commons/src/main/kotlin/kscience/kmath/commons/optimization/CMOptimizationProblem.kt → kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt
View File

@ -1,10 +1,5 @@
package kscience.kmath.commons.optimization
package space.kscience.kmath.commons.optimization
import kscience.kmath.expressions.*
import kscience.kmath.stat.OptimizationFeature
import kscience.kmath.stat.OptimizationProblem
import kscience.kmath.stat.OptimizationProblemFactory
import kscience.kmath.stat.OptimizationResult
import org.apache.commons.math3.optim.*
import org.apache.commons.math3.optim.nonlinear.scalar.GoalType
import org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer
@ -14,17 +9,36 @@ import org.apache.commons.math3.optim.nonlinear.scalar.gradient.NonLinearConjuga
import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.AbstractSimplex
import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.NelderMeadSimplex
import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.SimplexOptimizer
import space.kscience.kmath.expressions.DifferentiableExpression
import space.kscience.kmath.expressions.Expression
import space.kscience.kmath.expressions.SymbolIndexer
import space.kscience.kmath.expressions.derivative
import space.kscience.kmath.misc.Symbol
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.optimization.*
import kotlin.reflect.KClass
public operator fun PointValuePair.component1(): DoubleArray = point
public operator fun PointValuePair.component2(): Double = value
public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
OptimizationProblem<Double>, SymbolIndexer, OptimizationFeature {
@OptIn(UnstableKMathAPI::class)
public class CMOptimization(
override val symbols: List<Symbol>,
) : FunctionOptimization<Double>, NoDerivFunctionOptimization<Double>, SymbolIndexer, OptimizationFeature {
private val optimizationData: HashMap<KClass<out OptimizationData>, OptimizationData> = HashMap()
private var optimizatorBuilder: (() -> MultivariateOptimizer)? = null
public var convergenceChecker: ConvergenceChecker<PointValuePair> = SimpleValueChecker(DEFAULT_RELATIVE_TOLERANCE,
DEFAULT_ABSOLUTE_TOLERANCE, DEFAULT_MAX_ITER)
private var optimizerBuilder: (() -> MultivariateOptimizer)? = null
public var convergenceChecker: ConvergenceChecker<PointValuePair> = SimpleValueChecker(
DEFAULT_RELATIVE_TOLERANCE,
DEFAULT_ABSOLUTE_TOLERANCE,
DEFAULT_MAX_ITER
)
override var maximize: Boolean
get() = optimizationData[GoalType::class] == GoalType.MAXIMIZE
set(value) {
optimizationData[GoalType::class] = if (value) GoalType.MAXIMIZE else GoalType.MINIMIZE
}
public fun addOptimizationData(data: OptimizationData) {
optimizationData[data::class] = data
@ -40,7 +54,7 @@ public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
addOptimizationData(InitialGuess(map.toDoubleArray()))
}
public override fun expression(expression: Expression<Double>): Unit {
public override fun function(expression: Expression<Double>): Unit {
val objectiveFunction = ObjectiveFunction {
val args = it.toMap()
expression(args)
@ -48,8 +62,8 @@ public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
addOptimizationData(objectiveFunction)
}
public override fun diffExpression(expression: DifferentiableExpression<Double, Expression<Double>>) {
expression(expression)
public override fun diffFunction(expression: DifferentiableExpression<Double, Expression<Double>>) {
function(expression)
val gradientFunction = ObjectiveFunctionGradient {
val args = it.toMap()
DoubleArray(symbols.size) { index ->
@ -57,8 +71,8 @@ public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
}
}
addOptimizationData(gradientFunction)
if (optimizatorBuilder == null) {
optimizatorBuilder = {
if (optimizerBuilder == null) {
optimizerBuilder = {
NonLinearConjugateGradientOptimizer(
NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES,
convergenceChecker
@ -70,8 +84,8 @@ public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
public fun simplex(simplex: AbstractSimplex) {
addOptimizationData(simplex)
//Set optimization builder to simplex if it is not present
if (optimizatorBuilder == null) {
optimizatorBuilder = { SimplexOptimizer(convergenceChecker) }
if (optimizerBuilder == null) {
optimizerBuilder = { SimplexOptimizer(convergenceChecker) }
}
}
@ -84,7 +98,7 @@ public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
}
public fun optimizer(block: () -> MultivariateOptimizer) {
optimizatorBuilder = block
optimizerBuilder = block
}
override fun update(result: OptimizationResult<Double>) {
@ -92,19 +106,19 @@ public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
}
override fun optimize(): OptimizationResult<Double> {
val optimizer = optimizatorBuilder?.invoke() ?: error("Optimizer not defined")
val optimizer = optimizerBuilder?.invoke() ?: error("Optimizer not defined")
val (point, value) = optimizer.optimize(*optimizationData.values.toTypedArray())
return OptimizationResult(point.toMap(), value, setOf(this))
}
public companion object : OptimizationProblemFactory<Double, CMOptimizationProblem> {
public companion object : OptimizationProblemFactory<Double, CMOptimization> {
public const val DEFAULT_RELATIVE_TOLERANCE: Double = 1e-4
public const val DEFAULT_ABSOLUTE_TOLERANCE: Double = 1e-4
public const val DEFAULT_MAX_ITER: Int = 1000
override fun build(symbols: List<Symbol>): CMOptimizationProblem = CMOptimizationProblem(symbols)
override fun build(symbols: List<Symbol>): CMOptimization = CMOptimization(symbols)
}
}
public fun CMOptimizationProblem.initialGuess(vararg pairs: Pair<Symbol, Double>): Unit = initialGuess(pairs.toMap())
public fun CMOptimizationProblem.simplexSteps(vararg pairs: Pair<Symbol, Double>): Unit = simplexSteps(pairs.toMap())
public fun CMOptimization.initialGuess(vararg pairs: Pair<Symbol, Double>): Unit = initialGuess(pairs.toMap())
public fun CMOptimization.simplexSteps(vararg pairs: Pair<Symbol, Double>): Unit = simplexSteps(pairs.toMap())

49
kmath-commons/src/main/kotlin/kscience/kmath/commons/optimization/cmFit.kt → kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt
View File

@ -1,21 +1,21 @@
package kscience.kmath.commons.optimization
package space.kscience.kmath.commons.optimization
import kscience.kmath.commons.expressions.DerivativeStructureField
import kscience.kmath.expressions.DifferentiableExpression
import kscience.kmath.expressions.Expression
import kscience.kmath.expressions.Symbol
import kscience.kmath.stat.Fitting
import kscience.kmath.stat.OptimizationResult
import kscience.kmath.stat.optimizeWith
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.asBuffer
import org.apache.commons.math3.analysis.differentiation.DerivativeStructure
import org.apache.commons.math3.optim.nonlinear.scalar.GoalType
import space.kscience.kmath.commons.expressions.DerivativeStructureField
import space.kscience.kmath.expressions.DifferentiableExpression
import space.kscience.kmath.expressions.Expression
import space.kscience.kmath.misc.Symbol
import space.kscience.kmath.optimization.FunctionOptimization
import space.kscience.kmath.optimization.OptimizationResult
import space.kscience.kmath.optimization.noDerivOptimizeWith
import space.kscience.kmath.optimization.optimizeWith
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.asBuffer
/**
* Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation
*/
public fun Fitting.chiSquared(
public fun FunctionOptimization.Companion.chiSquared(
x: Buffer<Double>,
y: Buffer<Double>,
yErr: Buffer<Double>,
@ -25,7 +25,7 @@ public fun Fitting.chiSquared(
/**
* Generate a chi squared expression from given x-y-sigma data and inline model. Provides automatic differentiation
*/
public fun Fitting.chiSquared(
public fun FunctionOptimization.Companion.chiSquared(
x: Iterable<Double>,
y: Iterable<Double>,
yErr: Iterable<Double>,
@ -43,25 +43,26 @@ public fun Fitting.chiSquared(
*/
public fun Expression<Double>.optimize(
vararg symbols: Symbol,
configuration: CMOptimizationProblem.() -> Unit,
): OptimizationResult<Double> = optimizeWith(CMOptimizationProblem, symbols = symbols, configuration)
configuration: CMOptimization.() -> Unit,
): OptimizationResult<Double> = noDerivOptimizeWith(CMOptimization, symbols = symbols, configuration)
/**
* Optimize differentiable expression
*/
public fun DifferentiableExpression<Double, Expression<Double>>.optimize(
vararg symbols: Symbol,
configuration: CMOptimizationProblem.() -> Unit,
): OptimizationResult<Double> = optimizeWith(CMOptimizationProblem, symbols = symbols, configuration)
configuration: CMOptimization.() -> Unit,
): OptimizationResult<Double> = optimizeWith(CMOptimization, symbols = symbols, configuration)
public fun DifferentiableExpression<Double, Expression<Double>>.minimize(
vararg startPoint: Pair<Symbol, Double>,
configuration: CMOptimizationProblem.() -> Unit = {},
configuration: CMOptimization.() -> Unit = {},
): OptimizationResult<Double> {
require(startPoint.isNotEmpty()) { "Must provide a list of symbols for optimization" }
val problem = CMOptimizationProblem(startPoint.map { it.first }).apply(configuration)
problem.diffExpression(this)
problem.initialGuess(startPoint.toMap())
problem.goal(GoalType.MINIMIZE)
return problem.optimize()
val symbols = startPoint.map { it.first }.toTypedArray()
return optimize(*symbols){
maximize = false
initialGuess(startPoint.toMap())
diffFunction(this@minimize)
configuration()
}
}

4
kmath-commons/src/main/kotlin/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt → kmath-commons/src/main/kotlin/space/kscience/kmath/commons/random/CMRandomGeneratorWrapper.kt
View File

@ -1,6 +1,6 @@
package kscience.kmath.commons.random
package space.kscience.kmath.commons.random
import kscience.kmath.stat.RandomGenerator
import space.kscience.kmath.stat.RandomGenerator
public class CMRandomGeneratorWrapper(
public val factory: (IntArray) -> RandomGenerator,

29
kmath-commons/src/main/kotlin/kscience/kmath/commons/transform/Transformations.kt → kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt
View File

@ -1,13 +1,14 @@
package kscience.kmath.commons.transform
package space.kscience.kmath.commons.transform
import kotlinx.coroutines.FlowPreview
import kotlinx.coroutines.flow.Flow
import kotlinx.coroutines.flow.map
import kscience.kmath.complex.*
import kscience.kmath.streaming.chunked
import kscience.kmath.streaming.spread
import kscience.kmath.structures.*
import org.apache.commons.math3.transform.*
import space.kscience.kmath.complex.Complex
import space.kscience.kmath.streaming.chunked
import space.kscience.kmath.streaming.spread
import space.kscience.kmath.structures.*
/**
@ -17,7 +18,7 @@ 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) }
private fun Buffer<Double>.asArray() = if (this is RealBuffer) {
private fun Buffer<Double>.asArray() = if (this is DoubleBuffer) {
array
} else {
DoubleArray(size) { i -> get(i) }
@ -33,34 +34,34 @@ public object Transformations {
public fun fourier(
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
direction: TransformType = TransformType.FORWARD,
): SuspendBufferTransform<Complex, Complex> = {
FastFourierTransformer(normalization).transform(it.toArray(), direction).asBuffer()
}
public fun realFourier(
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
direction: TransformType = TransformType.FORWARD,
): SuspendBufferTransform<Double, Complex> = {
FastFourierTransformer(normalization).transform(it.asArray(), direction).asBuffer()
}
public fun sine(
normalization: DstNormalization = DstNormalization.STANDARD_DST_I,
direction: TransformType = TransformType.FORWARD
direction: TransformType = TransformType.FORWARD,
): SuspendBufferTransform<Double, Double> = {
FastSineTransformer(normalization).transform(it.asArray(), direction).asBuffer()
}
public fun cosine(
normalization: DctNormalization = DctNormalization.STANDARD_DCT_I,
direction: TransformType = TransformType.FORWARD
direction: TransformType = TransformType.FORWARD,
): SuspendBufferTransform<Double, Double> = {
FastCosineTransformer(normalization).transform(it.asArray(), direction).asBuffer()
}
public fun hadamard(
direction: TransformType = TransformType.FORWARD
direction: TransformType = TransformType.FORWARD,
): SuspendBufferTransform<Double, Double> = {
FastHadamardTransformer().transform(it.asArray(), direction).asBuffer()
}
@ -72,7 +73,7 @@ public object Transformations {
@FlowPreview
public fun Flow<Buffer<Complex>>.FFT(
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
direction: TransformType = TransformType.FORWARD,
): Flow<Buffer<Complex>> {
val transform = Transformations.fourier(normalization, direction)
return map { transform(it) }
@ -82,7 +83,7 @@ public fun Flow<Buffer<Complex>>.FFT(
@JvmName("realFFT")
public fun Flow<Buffer<Double>>.FFT(
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
direction: TransformType = TransformType.FORWARD,
): Flow<Buffer<Complex>> {
val transform = Transformations.realFourier(normalization, direction)
return map(transform)
@ -96,7 +97,7 @@ public fun Flow<Buffer<Double>>.FFT(
public fun Flow<Double>.FFT(
bufferSize: Int = Int.MAX_VALUE,
normalization: DftNormalization = DftNormalization.STANDARD,
direction: TransformType = TransformType.FORWARD
direction: TransformType = TransformType.FORWARD,
): Flow<Complex> = chunked(bufferSize).FFT(normalization, direction).spread()
/**

14
kmath-commons/src/test/kotlin/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt → kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt
View File

@ -1,6 +1,10 @@
package kscience.kmath.commons.expressions
package space.kscience.kmath.commons.expressions
import kscience.kmath.expressions.*
import space.kscience.kmath.expressions.binding
import space.kscience.kmath.expressions.derivative
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.misc.Symbol
import space.kscience.kmath.misc.symbol
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
import kotlin.test.Test
@ -24,13 +28,13 @@ internal class AutoDiffTest {
fun derivativeStructureFieldTest() {
diff(2, x to 1.0, y to 1.0) {
val x = bind(x)//by binding()
val y = symbol("y")
val y = bindSymbol("y")
val z = x * (-sin(x * y) + y) + 2.0
println(z.derivative(x))
println(z.derivative(y,x))
println(z.derivative(y, x))
assertEquals(z.derivative(x, y), z.derivative(y, x))
//check that improper order cause failure
assertFails { z.derivative(x,x,y) }
assertFails { z.derivative(x, x, y) }
}
}

30
kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt Normal file
View File

@ -0,0 +1,30 @@
package space.kscience.kmath.commons.integration
import org.junit.jupiter.api.Test
import space.kscience.kmath.integration.integrate
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.DoubleField.sin
import kotlin.math.PI
import kotlin.math.abs
import kotlin.test.assertTrue
@UnstableKMathAPI
internal class IntegrationTest {
private val function: (Double) -> Double = { sin(it) }
@Test
fun simpson() {
val res = CMIntegrator.simpson().integrate(0.0..2 * PI, function)
assertTrue { abs(res) < 1e-3 }
}
@Test
fun customSimpson() {
val res = CMIntegrator.simpson().integrate(0.0..PI, function) {
targetRelativeAccuracy = 1e-4
targetAbsoluteAccuracy = 1e-4
}
assertTrue { abs(res - 2) < 1e-3 }
assertTrue { abs(res - 2) > 1e-12 }
}
}

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