kscience/kmath
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Merge pull request #280 from mipt-npm/dev

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Alexander Nozik 2021-04-16 19:45:55 +03:00 committed by GitHub
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1
.github/workflows/build.yml vendored
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@ -8,6 +8,7 @@ jobs:
matrix:
os: [ macOS-latest, windows-latest ]
runs-on: ${{matrix.os}}
timeout-minutes: 30
steps:
- name: Checkout the repo
uses: actions/checkout@v2

2
.github/workflows/publish.yml vendored
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@ -12,7 +12,7 @@ jobs:
name: publish
strategy:
matrix:
os: [macOS-latest, windows-latest]
os: [ macOS-latest, windows-latest ]
runs-on: ${{matrix.os}}
steps:
- name: Checkout the repo

4
.gitignore vendored
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@ -1,7 +1,11 @@
.gradle
build/
out/
.idea/
!.idea/copyright/
.vscode/
# Avoid ignoring Gradle wrapper jar file (.jar files are usually ignored)

6
.idea/copyright/kmath.xml Normal file
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@ -0,0 +1,6 @@
<component name="CopyrightManager">
<copyright>
<option name="notice" value="Copyright 2018-2021 KMath contributors.&#10;Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file." />
<option name="myName" value="kmath" />
</copyright>
</component>

7
.idea/copyright/profiles_settings.xml Normal file
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@ -0,0 +1,7 @@
<component name="CopyrightManager">
<settings default="kmath">
<module2copyright>
<element module="Project Files" copyright="kmath" />
</module2copyright>
</settings>
</component>

16
CHANGELOG.md
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@ -4,20 +4,35 @@
### Added
- ScaleOperations interface
- Field extends ScaleOperations
- Basic integration API
- Basic MPP distributions and samplers
- bindSymbolOrNull
- Blocking chains and Statistics
- Multiplatform integration
- Integration for any Field element
### 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
- Redesign advanced Chain API
- Redesign MST. Remove MSTExpression.
- Move MST 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.
- MSTExpression
### Fixed
- Ring inherits RingOperations, not GroupOperations
### Security
@ -73,6 +88,7 @@
- `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)

74
README.md
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@ -1,9 +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)
[![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%20AND%20a:%22kmath-core%22)
[![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 +88,12 @@ 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 +109,8 @@ 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 +120,15 @@ 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 +148,12 @@ 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)
@ -159,22 +164,23 @@ 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/>
* ### [kmath-functions](kmath-functions)
> Functions and interpolation
> Functions, integration and interpolation
>
> **Maturity**: PROTOTYPE
> **Maturity**: EXPERIMENTAL
>
> **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/src/commonMain/kotlin/space/kscience/kmath/functions/Piecewise.kt) : Piecewise functions.
> - [polynomials](kmath-functions/src/commonMain/kotlin/space/kscience/kmath/functions/Polynomial.kt) : Polynomial functions.
> - [linear interpolation](kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/LinearInterpolator.kt) : Linear XY interpolator.
> - [spline interpolation](kmath-functions/src/commonMain/kotlin/space/kscience/kmath/interpolation/SplineInterpolator.kt) : Cubic spline XY interpolator.
> - [integration](kmath-functions/#) : Univariate and multivariate quadratures
<hr/>
@ -208,9 +214,9 @@ 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/>
@ -245,6 +251,10 @@ cases. We expect the worst KMath benchmarks will perform better than native Pyth
native/SciPy (mostly due to boxing operations on primitive numbers). The best performance of optimized parts could be
better than SciPy.
## Requirements
KMath currently relies on JDK 11 for compilation and execution of Kotlin-JVM part. We recommend to use GraalVM-CE 11 for execution in order to get better performance.
### Repositories
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
@ -256,8 +266,8 @@ repositories {
}
dependencies {
api("space.kscience:kmath-core:0.3.0-dev-2")
// api("space.kscience:kmath-core-jvm:0.3.0-dev-2") for jvm-specific version
api("space.kscience:kmath-core:0.3.0-dev-6")
// api("space.kscience:kmath-core-jvm:0.3.0-dev-6") for jvm-specific version
}
```

37
build.gradle.kts
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@ -3,7 +3,8 @@
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
import ru.mipt.npm.gradle.KSciencePublishingPlugin
import org.jetbrains.dokka.gradle.DokkaTask
import java.net.URL
plugins {
id("ru.mipt.npm.gradle.project")
@ -15,21 +16,41 @@ allprojects {
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/")
maven{
setUrl("http://logicrunch.research.it.uu.se/maven/")
isAllowInsecureProtocol = true
}
mavenCentral()
}
group = "space.kscience"
version = "0.3.0-dev-2"
version = "0.3.0-dev-6"
}
subprojects {
if (name.startsWith("kmath")) apply<KSciencePublishingPlugin>()
if (name.startsWith("kmath")) apply<MavenPublishPlugin>()
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 {

2
docs/algebra.md
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@ -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`

29
docs/images/KM.svg
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clip-path="url(#clipPath184)"
id="g180"><g
transform="matrix(621.6,0,0,981.6,4900,1478.4)"
@ -285,7 +306,7 @@
style="image-rendering:optimizeSpeed"
height="1"
width="1" /></g></g></g><g
id="g190"><g
id="g190"><g
clip-path="url(#clipPath196)"
id="g192"><g
transform="matrix(861.6,0,0,981.6,5630,1478.4)"
@ -297,7 +318,7 @@
style="image-rendering:optimizeSpeed"
height="1"
width="1" /></g></g></g><g
id="g202"><g
id="g202"><g
clip-path="url(#clipPath208)"
id="g204"><g
transform="matrix(1370.4,0,0,12,2370,1468)"
@ -309,7 +330,7 @@
style="image-rendering:optimizeSpeed"
height="1"
width="1" /></g></g></g><g
id="g214"><g
id="g214"><g
clip-path="url(#clipPath220)"
id="g216"><g
transform="matrix(861.6,0,0,12,3920,1468)"
@ -321,7 +342,7 @@
style="image-rendering:optimizeSpeed"
height="1"
width="1" /></g></g></g><g
id="g226"><g
id="g226"><g
clip-path="url(#clipPath232)"
id="g228"><g
transform="matrix(621.6,0,0,12,4900,1468)"
@ -333,7 +354,7 @@
style="image-rendering:optimizeSpeed"
height="1"
width="1" /></g></g></g><g
id="g238"><g
id="g238"><g
clip-path="url(#clipPath244)"
id="g240"><g
transform="matrix(861.6,0,0,12,5630,1468)"
@ -345,7 +366,7 @@
style="image-rendering:optimizeSpeed"
height="1"
width="1" /></g></g></g><g
id="g250"><g
id="g250"><g
clip-path="url(#clipPath256)"
id="g252"><g
transform="matrix(861.6,0,0,21.6,3920,1448.4)"
@ -357,7 +378,7 @@
style="image-rendering:optimizeSpeed"
height="1"
width="1" /></g></g></g><g
id="g262"><g
id="g262"><g
clip-path="url(#clipPath268)"
id="g264"><g
transform="matrix(621.6,0,0,21.6,4900,1448.4)"

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4
docs/nd-structure.md
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@ -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:

62
docs/templates/ARTIFACT-TEMPLATE.md vendored
View File

@ -1,34 +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/${name}/_latestVersion)
>
> **Gradle:**
>
> ```gradle
> repositories {
> maven { url 'https://repo.kotlin.link' }
> maven { url 'https://dl.bintray.com/hotkeytlt/maven' }
> maven { url "https://dl.bintray.com/kotlin/kotlin-eap" } // include for builds based on kotlin-eap
> }
>
> dependencies {
> implementation '${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}:${version}")
> }
> ```
## Artifact:
The Maven coordinates of this project are `${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}")
}
```

9
docs/templates/README-TEMPLATE.md vendored
View File

@ -1,9 +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)
[![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%20AND%20a:%22kmath-core%22)
[![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
@ -95,6 +94,10 @@ cases. We expect the worst KMath benchmarks will perform better than native Pyth
native/SciPy (mostly due to boxing operations on primitive numbers). The best performance of optimized parts could be
better than SciPy.
## Requirements
KMath currently relies on JDK 11 for compilation and execution of Kotlin-JVM part. We recommend to use GraalVM-CE 11 for execution in order to get better performance.
### Repositories
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

28
examples/build.gradle.kts
View File

@ -4,11 +4,12 @@
*/
import org.jetbrains.kotlin.gradle.tasks.KotlinCompile
import ru.mipt.npm.gradle.Maturity
plugins {
kotlin("jvm")
kotlin("plugin.allopen")
id("kotlinx.benchmark")
id("org.jetbrains.kotlinx.benchmark")
}
allOpen.annotation("org.openjdk.jmh.annotations.State")
@ -25,7 +26,10 @@ repositories {
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/")
maven{
setUrl("http://logicrunch.research.it.uu.se/maven/")
isAllowInsecureProtocol = true
}
mavenCentral()
}
@ -58,7 +62,7 @@ dependencies {
implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7")
implementation("org.jetbrains.kotlinx:kotlinx-io:0.2.0-npm-dev-11")
implementation("org.jetbrains.kotlinx:kotlinx.benchmark.runtime:0.2.0-dev-20")
implementation("org.jetbrains.kotlinx:kotlinx-benchmark-runtime:0.3.0")
implementation("org.slf4j:slf4j-simple:1.7.30")
// plotting
@ -105,19 +109,31 @@ benchmark {
iterationTimeUnit = "ms" // time unity for iterationTime, default is seconds
include("MatrixInverseBenchmark")
}
configurations.register("bigInt") {
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("BigIntBenchmark")
}
}
kotlin.sourceSets.all {
with(languageSettings) {
useExperimentalAnnotation("kotlin.contracts.ExperimentalContracts")
useExperimentalAnnotation("kotlin.ExperimentalUnsignedTypes")
useExperimentalAnnotation("space.kscience.kmath.misc.UnstableKMathAPI")
}
}
tasks.withType<KotlinCompile> {
kotlinOptions.jvmTarget = "11"
kotlinOptions{
jvmTarget = "11"
freeCompilerArgs = freeCompilerArgs + "-Xjvm-default=all"
}
}
readme{
maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL
readme {
maturity = Maturity.EXPERIMENTAL
}

41
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/BigIntBenchmark.kt Normal file
View File

@ -0,0 +1,41 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.benchmarks
import kotlinx.benchmark.Blackhole
import org.openjdk.jmh.annotations.Benchmark
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import space.kscience.kmath.operations.BigIntField
import space.kscience.kmath.operations.JBigIntegerField
import space.kscience.kmath.operations.invoke
@State(Scope.Benchmark)
internal class BigIntBenchmark {
val kmNumber = BigIntField.number(Int.MAX_VALUE)
val jvmNumber = JBigIntegerField.number(Int.MAX_VALUE)
@Benchmark
fun kmAdd(blackhole: Blackhole) = BigIntField {
blackhole.consume(kmNumber + kmNumber + kmNumber)
}
@Benchmark
fun jvmAdd(blackhole: Blackhole) = JBigIntegerField {
blackhole.consume(jvmNumber + jvmNumber + jvmNumber)
}
@Benchmark
fun kmMultiply(blackhole: Blackhole) = BigIntField {
blackhole.consume(kmNumber * kmNumber * kmNumber)
}
@Benchmark
fun jvmMultiply(blackhole: Blackhole) = JBigIntegerField {
blackhole.consume(jvmNumber * jvmNumber * jvmNumber)
}
}

6
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/BufferBenchmark.kt
View File

@ -10,14 +10,14 @@ 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
import space.kscience.kmath.structures.RealBuffer
@State(Scope.Benchmark)
internal class BufferBenchmark {
@Benchmark
fun genericRealBufferReadWrite() {
val buffer = RealBuffer(size) { it.toDouble() }
fun genericDoubleBufferReadWrite() {
val buffer = DoubleBuffer(size) { it.toDouble() }
(0 until size).forEach {
buffer[it]

4
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt
View File

@ -13,7 +13,7 @@ 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.RealField
import space.kscience.kmath.operations.DoubleField
import kotlin.random.Random
@State(Scope.Benchmark)
@ -56,7 +56,7 @@ internal class DotBenchmark {
@Benchmark
fun bufferedDot(blackhole: Blackhole) {
LinearSpace.auto(RealField).invoke {
LinearSpace.auto(DoubleField).invoke {
blackhole.consume(matrix1 dot matrix2)
}
}

22
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt
View File

@ -9,14 +9,12 @@ 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.expressions.symbol
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.asm.compileToExpression
import space.kscience.kmath.expressions.*
import space.kscience.kmath.misc.symbol
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.bindSymbol
import space.kscience.kmath.operations.invoke
import kotlin.random.Random
@State(Scope.Benchmark)
@ -33,20 +31,20 @@ internal class ExpressionsInterpretersBenchmark {
@Benchmark
fun mstExpression(blackhole: Blackhole) {
val expr = algebra.mstInField {
val expr = MstField {
val x = bindSymbol(x)
x * 2.0 + number(2.0) / x - 16.0
}
}.toExpression(algebra)
invokeAndSum(expr, blackhole)
}
@Benchmark
fun asmExpression(blackhole: Blackhole) {
val expr = algebra.mstInField {
val expr = MstField {
val x = bindSymbol(x)
x * 2.0 + number(2.0) / x - 16.0
}.compile()
}.compileToExpression(algebra)
invokeAndSum(expr, blackhole)
}
@ -73,7 +71,7 @@ internal class ExpressionsInterpretersBenchmark {
}
private companion object {
private val algebra = RealField
private val algebra = DoubleField
private val x by symbol
}
}

14
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/NDFieldBenchmark.kt
View File

@ -10,7 +10,7 @@ import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.nd.*
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.structures.Buffer
@State(Scope.Benchmark)
@ -18,7 +18,7 @@ internal class NDFieldBenchmark {
@Benchmark
fun autoFieldAdd(blackhole: Blackhole) {
with(autoField) {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += one }
blackhole.consume(res)
}
@ -27,7 +27,7 @@ internal class NDFieldBenchmark {
@Benchmark
fun specializedFieldAdd(blackhole: Blackhole) {
with(specializedField) {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
@ -37,7 +37,7 @@ internal class NDFieldBenchmark {
@Benchmark
fun boxingFieldAdd(blackhole: Blackhole) {
with(genericField) {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
@ -46,8 +46,8 @@ internal class NDFieldBenchmark {
private companion object {
private const val dim = 1000
private const val n = 100
private val autoField = NDAlgebra.auto(RealField, dim, dim)
private val specializedField = NDAlgebra.real(dim, dim)
private val genericField = NDAlgebra.field(RealField, Buffer.Companion::boxing, dim, dim)
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)
}
}

14
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/ViktorBenchmark.kt
View File

@ -10,11 +10,11 @@ import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import org.jetbrains.bio.viktor.F64Array
import space.kscience.kmath.nd.NDAlgebra
import space.kscience.kmath.nd.NDStructure
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.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.viktor.ViktorNDField
@State(Scope.Benchmark)
@ -22,7 +22,7 @@ internal class ViktorBenchmark {
@Benchmark
fun automaticFieldAddition(blackhole: Blackhole) {
with(autoField) {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
@ -31,7 +31,7 @@ internal class ViktorBenchmark {
@Benchmark
fun realFieldAddition(blackhole: Blackhole) {
with(realField) {
var res: NDStructure<Double> = one
var res: StructureND<Double> = one
repeat(n) { res += 1.0 }
blackhole.consume(res)
}
@ -59,8 +59,8 @@ internal class ViktorBenchmark {
private const val n = 100
// automatically build context most suited for given type.
private val autoField = NDAlgebra.auto(RealField, dim, dim)
private val realField = NDAlgebra.real(dim, dim)
private val autoField = AlgebraND.auto(DoubleField, dim, dim)
private val realField = AlgebraND.real(dim, dim)
private val viktorField = ViktorNDField(dim, dim)
}
}

12
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt
View File

@ -10,11 +10,11 @@ import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import org.jetbrains.bio.viktor.F64Array
import space.kscience.kmath.nd.NDAlgebra
import space.kscience.kmath.nd.AlgebraND
import space.kscience.kmath.nd.auto
import space.kscience.kmath.nd.real
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.viktor.ViktorNDField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.viktor.ViktorFieldND
@State(Scope.Benchmark)
internal class ViktorLogBenchmark {
@ -51,8 +51,8 @@ internal class ViktorLogBenchmark {
private const val n = 100
// automatically build context most suited for given type.
private val autoField = NDAlgebra.auto(RealField, dim, dim)
private val realNdField = NDAlgebra.real(dim, dim)
private val viktorField = ViktorNDField(intArrayOf(dim, dim))
private val autoField = AlgebraND.auto(DoubleField, dim, dim)
private val realNdField = AlgebraND.real(dim, dim)
private val viktorField = ViktorFieldND(intArrayOf(dim, dim))
}
}

26
examples/src/main/kotlin/space/kscience/kmath/ast/astRendering.kt Normal file
View File

@ -0,0 +1,26 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast
import space.kscience.kmath.ast.rendering.FeaturedMathRendererWithPostProcess
import space.kscience.kmath.ast.rendering.LatexSyntaxRenderer
import space.kscience.kmath.ast.rendering.MathMLSyntaxRenderer
import space.kscience.kmath.ast.rendering.renderWithStringBuilder
public fun main() {
val mst = "exp(sqrt(x))-asin(2*x)/(2e10+x^3)/(-12)".parseMath()
val syntax = FeaturedMathRendererWithPostProcess.Default.render(mst)
println("MathSyntax:")
println(syntax)
println()
val latex = LatexSyntaxRenderer.renderWithStringBuilder(syntax)
println("LaTeX:")
println(latex)
println()
val mathML = MathMLSyntaxRenderer.renderWithStringBuilder(syntax)
println("MathML:")
println(mathML)
}

14
examples/src/main/kotlin/space/kscience/kmath/ast/expressions.kt
View File

@ -5,16 +5,20 @@
package space.kscience.kmath.ast
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.expressions.MstField
import space.kscience.kmath.expressions.interpret
import space.kscience.kmath.misc.Symbol.Companion.x
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.bindSymbol
import space.kscience.kmath.operations.invoke
fun main() {
val expr = RealField.mstInField {
val x = bindSymbol("x")
val expr = MstField {
val x = bindSymbol(x)
x * 2.0 + number(2.0) / x - 16.0
}
repeat(10000000) {
expr.invoke("x" to 1.0)
expr.interpret(DoubleField, x to 1.0)
}
}

16
examples/src/main/kotlin/space/kscience/kmath/ast/kotlingradSupport.kt
View File

@ -5,12 +5,12 @@
package space.kscience.kmath.ast
import space.kscience.kmath.asm.compile
import space.kscience.kmath.asm.compileToExpression
import space.kscience.kmath.expressions.derivative
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.expressions.symbol
import space.kscience.kmath.kotlingrad.differentiable
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.kotlingrad.toDiffExpression
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
@ -19,11 +19,11 @@ import space.kscience.kmath.operations.RealField
fun main() {
val x by symbol
val actualDerivative = MstExpression(RealField, "x^2-4*x-44".parseMath())
.differentiable()
val actualDerivative = "x^2-4*x-44".parseMath()
.toDiffExpression(DoubleField)
.derivative(x)
.compile()
val expectedDerivative = MstExpression(RealField, "2*x-4".parseMath()).compile()
val expectedDerivative = "2*x-4".parseMath().compileToExpression(DoubleField)
assert(actualDerivative("x" to 123.0) == expectedDerivative("x" to 123.0))
}

30
examples/src/main/kotlin/space/kscience/kmath/commons/fit/fitWithAutoDiff.kt
View File

@ -12,11 +12,14 @@ import kscience.plotly.models.ScatterMode
import kscience.plotly.models.TraceValues
import space.kscience.kmath.commons.optimization.chiSquared
import space.kscience.kmath.commons.optimization.minimize
import space.kscience.kmath.expressions.symbol
import space.kscience.kmath.real.RealVector
import space.kscience.kmath.distributions.NormalDistribution
import space.kscience.kmath.misc.symbol
import space.kscience.kmath.optimization.FunctionOptimization
import space.kscience.kmath.optimization.OptimizationResult
import space.kscience.kmath.real.DoubleVector
import space.kscience.kmath.real.map
import space.kscience.kmath.real.step
import space.kscience.kmath.stat.*
import space.kscience.kmath.stat.RandomGenerator
import space.kscience.kmath.structures.asIterable
import space.kscience.kmath.structures.toList
import kotlin.math.pow
@ -31,17 +34,16 @@ private val c by symbol
/**
* Shortcut to use buffers in plotly
*/
operator fun TraceValues.invoke(vector: RealVector) {
operator fun TraceValues.invoke(vector: DoubleVector) {
numbers = vector.asIterable()
}
/**
* Least squares fie with auto-differentiation. Uses `kmath-commons` and `kmath-for-real` modules.
*/
fun main() {
suspend fun main() {
//A generator for a normally distributed values
val generator = Distribution.normal()
val generator = NormalDistribution(2.0, 7.0)
//A chain/flow of random values with the given seed
val chain = generator.sample(RandomGenerator.default(112667))
@ -54,7 +56,7 @@ fun main() {
//Perform an operation on each x value (much more effective, than numpy)
val y = x.map {
val value = it.pow(2) + it + 1
value + chain.nextDouble() * sqrt(value)
value + chain.next() * sqrt(value)
}
// this will also work, but less effective:
// val y = x.pow(2)+ x + 1 + chain.nextDouble()
@ -63,10 +65,10 @@ fun main() {
val yErr = y.map { sqrt(it) }//RealVector.same(x.size, sigma)
// compute differentiable chi^2 sum for given model ax^2 + bx + c
val chi2 = Fitting.chiSquared(x, y, yErr) { x1 ->
val chi2 = FunctionOptimization.chiSquared(x, y, yErr) { x1 ->
//bind variables to autodiff context
val a = bind(a)
val b = bind(b)
val a = bindSymbol(a)
val b = bindSymbol(b)
//Include default value for c if it is not provided as a parameter
val c = bindSymbolOrNull(c) ?: one
a * x1.pow(2) + b * x1 + c
@ -95,13 +97,13 @@ fun main() {
}
}
br()
h3{
h3 {
+"Fit result: $result"
}
h3{
h3 {
+"Chi2/dof = ${result.value / (x.size - 3)}"
}
}
page.makeFile()
}
}

17
examples/src/main/kotlin/space/kscience/kmath/functions/integrate.kt Normal file
View File

@ -0,0 +1,17 @@
package space.kscience.kmath.functions
import space.kscience.kmath.integration.integrate
import space.kscience.kmath.integration.value
import space.kscience.kmath.operations.DoubleField
import kotlin.math.pow
fun main() {
//Define a function
val function: UnivariateFunction<Double> = { x -> 3 * x.pow(2) + 2 * x + 1 }
//get the result of the integration
val result = DoubleField.integrate(0.0..10.0, function = function)
//the value is nullable because in some cases the integration could not succeed
println(result.value)
}

27
examples/src/main/kotlin/space/kscience/kmath/functions/matrixIntegration.kt Normal file
View File

@ -0,0 +1,27 @@
package space.kscience.kmath.functions
import space.kscience.kmath.integration.integrate
import space.kscience.kmath.integration.value
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.nd.nd
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
fun main(): Unit = DoubleField {
nd(2, 2) {
//Produce a diagonal StructureND
fun diagonal(v: Double) = produce { (i, j) ->
if (i == j) v else 0.0
}
//Define a function in a nd space
val function: (Double) -> StructureND<Double> = { x: Double -> 3 * number(x).pow(2) + 2 * diagonal(x) + 1 }
//get the result of the integration
val result = integrate(0.0..10.0, function = function)
//the value is nullable because in some cases the integration could not succeed
println(result.value)
}
}

10
examples/src/main/kotlin/space/kscience/kmath/linear/gradient.kt
View File

@ -6,11 +6,11 @@
package space.kscience.kmath.linear
import space.kscience.kmath.real.*
import space.kscience.kmath.structures.RealBuffer
import space.kscience.kmath.structures.DoubleBuffer
fun main() {
val x0 = Point(0.0, 0.0, 0.0)
val sigma = Point(1.0, 1.0, 1.0)
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)
@ -19,9 +19,9 @@ fun main() {
fun ((Point<Double>) -> Double).grad(x: Point<Double>): Point<Double> {
require(x.size == x0.size)
return RealBuffer(x.size) { i ->
return DoubleBuffer(x.size) { i ->
val h = sigma[i] / 5
val dVector = RealBuffer(x.size) { if (it == i) h else 0.0 }
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

6
examples/src/main/kotlin/space/kscience/kmath/operations/ComplexDemo.kt
View File

@ -7,17 +7,17 @@ package space.kscience.kmath.operations
import space.kscience.kmath.complex.Complex
import space.kscience.kmath.complex.complex
import space.kscience.kmath.nd.NDAlgebra
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)

37
examples/src/main/kotlin/space/kscience/kmath/stat/DistributionBenchmark.kt
View File

@ -3,26 +3,27 @@
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package kscience.kmath.commons.prob
package space.kscience.kmath.stat
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.async
import kotlinx.coroutines.runBlocking
import org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
import org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler
import org.apache.commons.rng.simple.RandomSource
import space.kscience.kmath.stat.*
import space.kscience.kmath.samplers.GaussianSampler
import java.time.Duration
import java.time.Instant
import org.apache.commons.rng.sampling.distribution.GaussianSampler as CMGaussianSampler
private fun runChain(): Duration {
private suspend fun runKMathChained(): Duration {
val generator = RandomGenerator.fromSource(RandomSource.MT, 123L)
val normal = Distribution.normal(NormalSamplerMethod.Ziggurat)
val normal = GaussianSampler(7.0, 2.0)
val chain = normal.sample(generator)
val startTime = Instant.now()
var sum = 0.0
repeat(10000001) { counter ->
sum += chain.nextDouble()
sum += chain.next()
if (counter % 100000 == 0) {
val duration = Duration.between(startTime, Instant.now())
@ -34,9 +35,15 @@ private fun runChain(): Duration {
return Duration.between(startTime, Instant.now())
}
private fun runDirect(): Duration {
val provider = RandomSource.create(RandomSource.MT, 123L)
val sampler = ZigguratNormalizedGaussianSampler(provider)
private fun runApacheDirect(): Duration {
val rng = RandomSource.create(RandomSource.MT, 123L)
val sampler = CMGaussianSampler.of(
BoxMullerNormalizedGaussianSampler.of(rng),
7.0,
2.0
)
val startTime = Instant.now()
var sum = 0.0
@ -56,11 +63,9 @@ private fun runDirect(): Duration {
/**
* Comparing chain sampling performance with direct sampling performance
*/
fun main() {
runBlocking(Dispatchers.Default) {
val chainJob = async { runChain() }
val directJob = async { runDirect() }
println("Chain: ${chainJob.await()}")
println("Direct: ${directJob.await()}")
}
fun main(): Unit = runBlocking(Dispatchers.Default) {
val directJob = async { runApacheDirect() }
val chainJob = async { runKMathChained() }
println("KMath Chained: ${chainJob.await()}")
println("Apache Direct: ${directJob.await()}")
}

9
examples/src/main/kotlin/space/kscience/kmath/stat/DistributionDemo.kt
View File

@ -8,14 +8,15 @@ package space.kscience.kmath.stat
import kotlinx.coroutines.runBlocking
import space.kscience.kmath.chains.Chain
import space.kscience.kmath.chains.collectWithState
import space.kscience.kmath.distributions.NormalDistribution
/**
* The state of distribution averager
* The state of distribution averager.
*/
private data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)
/**
* Averaging
* Averaging.
*/
private fun Chain<Double>.mean(): Chain<Double> = collectWithState(AveragingChainState(), { it.copy() }) { chain ->
val next = chain.next()
@ -26,7 +27,7 @@ private fun Chain<Double>.mean(): Chain<Double> = collectWithState(AveragingChai
fun main() {
val normal = Distribution.normal()
val normal = NormalDistribution(0.0, 2.0)
val chain = normal.sample(RandomGenerator.default).mean()
runBlocking {
@ -37,4 +38,4 @@ fun main() {
}
}
}
}
}

12
examples/src/main/kotlin/space/kscience/kmath/structures/ComplexND.kt
View File

@ -9,8 +9,8 @@ package space.kscience.kmath.structures
import space.kscience.kmath.complex.*
import space.kscience.kmath.linear.transpose
import space.kscience.kmath.nd.NDAlgebra
import space.kscience.kmath.nd.NDStructure
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
@ -20,12 +20,12 @@ 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
}
@ -36,7 +36,7 @@ fun main() {
val complexTime = measureTimeMillis {
complexField {
var res: NDStructure<Complex> = one
var res: StructureND<Complex> = one
repeat(n) {
res += 1.0
}

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

@ -9,7 +9,7 @@ import kotlinx.coroutines.GlobalScope
import org.nd4j.linalg.factory.Nd4j
import space.kscience.kmath.nd.*
import space.kscience.kmath.nd4j.Nd4jArrayField
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.viktor.ViktorNDField
import kotlin.contracts.InvocationKind
@ -29,56 +29,56 @@ 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 }
}
}

112
examples/src/main/kotlin/space/kscience/kmath/structures/ParallelRealNDField.kt
View File

@ -1,112 +0,0 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.structures
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.*
import space.kscience.kmath.operations.ExtendedField
import space.kscience.kmath.operations.NumbersAddOperations
import space.kscience.kmath.operations.RealField
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>,
NumbersAddOperations<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 NDStructure<Double>.unaryMinus(): NDStructure<Double> = map { -it }
override fun scale(a: NDStructure<Double>, value: Double): NDStructure<Double> = a.map { it * value }
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)

108
examples/src/main/kotlin/space/kscience/kmath/structures/StreamDoubleFieldND.kt Normal file
View File

@ -0,0 +1,108 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.structures
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 [java.util.stream.DoubleStream] for parallel
* execution.
*/
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)

8
examples/src/main/kotlin/space/kscience/kmath/structures/StructureReadBenchmark.kt
View File

@ -5,17 +5,17 @@
package space.kscience.kmath.structures
import space.kscience.kmath.nd.BufferND
import space.kscience.kmath.nd.DefaultStrides
import space.kscience.kmath.nd.NDBuffer
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
@ -39,4 +39,4 @@ fun main() {
strides.indices().forEach { res = array[strides.offset(it)] }
}
println("Array reading finished in $time3 millis")
}
}

8
examples/src/main/kotlin/space/kscience/kmath/structures/StructureWriteBenchmark.kt
View File

@ -5,14 +5,14 @@
package space.kscience.kmath.structures
import space.kscience.kmath.nd.NDStructure
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.buffered(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")
@ -25,10 +25,10 @@ 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
}

2
gradle.properties
View File

@ -9,5 +9,5 @@ kotlin.mpp.stability.nowarn=true
kotlin.native.enableDependencyPropagation=false
kotlin.parallel.tasks.in.project=true
org.gradle.configureondemand=true
org.gradle.jvmargs=-XX:MaxMetaspaceSize=2G
org.gradle.jvmargs=-XX:MaxMetaspaceSize=1G
org.gradle.parallel=true

5
gradle/wrapper/gradle-wrapper.properties vendored
View File

@ -1,8 +1,3 @@
#
# Copyright 2018-2021 KMath contributors.
# Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
#
distributionBase=GRADLE_USER_HOME
distributionPath=wrapper/dists
distributionUrl=https\://services.gradle.org/distributions/gradle-6.8.3-bin.zip

122
kmath-ast/README.md
View File

@ -1,49 +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: `space.kscience:kmath-ast:0.3.0-dev-2`.
>
> 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://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-2'
> }
> ```
> **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-2")
> }
> ```
## Artifact:
The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-6`.
**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-6'
}
```
**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-6")
}
```
## Dynamic expression code generation
@ -55,7 +49,7 @@ 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:
@ -88,8 +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
@ -103,7 +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:
@ -117,3 +111,39 @@ var executable = function (constants, arguments) {
#### Known issues
- This feature uses `eval` which can be unavailable in several environments.
## Rendering expressions
kmath-ast also includes an extensible engine to display expressions in LaTeX or MathML syntax.
Example usage:
```kotlin
import space.kscience.kmath.ast.*
import space.kscience.kmath.ast.rendering.*
public fun main() {
val mst = "exp(sqrt(x))-asin(2*x)/(2e10+x^3)/(-12)".parseMath()
val syntax = FeaturedMathRendererWithPostProcess.Default.render(mst)
val latex = LatexSyntaxRenderer.renderWithStringBuilder(syntax)
println("LaTeX:")
println(latex)
println()
val mathML = MathMLSyntaxRenderer.renderWithStringBuilder(syntax)
println("MathML:")
println(mathML)
}
```
Result LaTeX:
![](http://chart.googleapis.com/chart?cht=tx&chl=e%5E%7B%5Csqrt%7Bx%7D%7D-%5Cfrac%7B%5Cfrac%7B%5Coperatorname%7Bsin%7D%5E%7B-1%7D%5C,%5Cleft(2%5C,x%5Cright)%7D%7B2%5Ctimes10%5E%7B10%7D%2Bx%5E%7B3%7D%7D%7D%7B-12%7D)
Result MathML (embedding MathML is not allowed by GitHub Markdown):
```html
<mrow><msup><mrow><mi>e</mi></mrow><mrow><msqrt><mi>x</mi></msqrt></mrow></msup><mo>-</mo><mfrac><mrow><mfrac><mrow><msup><mrow><mo>sin</mo></mrow><mrow><mo>-</mo><mn>1</mn></mrow></msup><mspace width="0.167em"></mspace><mfenced open="(" close=")" separators=""><mn>2</mn><mspace width="0.167em"></mspace><mi>x</mi></mfenced></mrow><mrow><mn>2</mn><mo>&times;</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>10</mn></mrow></msup><mo>+</mo><msup><mrow><mi>x</mi></mrow><mrow><mn>3</mn></mrow></msup></mrow></mfrac></mrow><mrow><mo>-</mo><mn>12</mn></mrow></mfrac></mrow>
```
It is also possible to create custom algorithms of render, and even add support of other markup languages
(see API reference).

15
kmath-ast/build.gradle.kts
View File

@ -6,7 +6,8 @@
import ru.mipt.npm.gradle.Maturity
plugins {
id("ru.mipt.npm.gradle.mpp")
kotlin("multiplatform")
id("ru.mipt.npm.gradle.common")
}
kotlin.js {
@ -63,36 +64,36 @@ 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"
)
}

48
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}
@ -16,7 +16,7 @@ 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:
@ -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:
@ -78,3 +78,39 @@ var executable = function (constants, arguments) {
#### Known issues
- This feature uses `eval` which can be unavailable in several environments.
## Rendering expressions
kmath-ast also includes an extensible engine to display expressions in LaTeX or MathML syntax.
Example usage:
```kotlin
import space.kscience.kmath.ast.*
import space.kscience.kmath.ast.rendering.*
public fun main() {
val mst = "exp(sqrt(x))-asin(2*x)/(2e10+x^3)/(-12)".parseMath()
val syntax = FeaturedMathRendererWithPostProcess.Default.render(mst)
val latex = LatexSyntaxRenderer.renderWithStringBuilder(syntax)
println("LaTeX:")
println(latex)
println()
val mathML = MathMLSyntaxRenderer.renderWithStringBuilder(syntax)
println("MathML:")
println(mathML)
}
```
Result LaTeX:
![](http://chart.googleapis.com/chart?cht=tx&chl=e%5E%7B%5Csqrt%7Bx%7D%7D-%5Cfrac%7B%5Cfrac%7B%5Coperatorname%7Bsin%7D%5E%7B-1%7D%5C,%5Cleft(2%5C,x%5Cright)%7D%7B2%5Ctimes10%5E%7B10%7D%2Bx%5E%7B3%7D%7D%7D%7B-12%7D)
Result MathML (embedding MathML is not allowed by GitHub Markdown):
```html
<mrow><msup><mrow><mi>e</mi></mrow><mrow><msqrt><mi>x</mi></msqrt></mrow></msup><mo>-</mo><mfrac><mrow><mfrac><mrow><msup><mrow><mo>sin</mo></mrow><mrow><mo>-</mo><mn>1</mn></mrow></msup><mspace width="0.167em"></mspace><mfenced open="(" close=")" separators=""><mn>2</mn><mspace width="0.167em"></mspace><mi>x</mi></mfenced></mrow><mrow><mn>2</mn><mo>&times;</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>10</mn></mrow></msup><mo>+</mo><msup><mrow><mi>x</mi></mrow><mrow><mn>3</mn></mrow></msup></mrow></mfrac></mrow><mrow><mo>-</mo><mn>12</mn></mrow></mfrac></mrow>
```
It is also possible to create custom algorithms of render, and even add support of other markup languages
(see API reference).

141
kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/MstExpression.kt
View File

@ -1,141 +0,0 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast
import space.kscience.kmath.expressions.*
import space.kscience.kmath.operations.*
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
/**
* The expression evaluates MST on-flight. Should be much faster than functional expression, but slower than
* ASM-generated expressions.
*
* @property algebra the algebra that provides operations.
* @property mst the [MST] node.
* @author Alexander Nozik
*/
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 bindSymbol(value: String): T = try {
algebra.bindSymbol(value)
} catch (ignored: IllegalStateException) {
null
} ?: arguments.getValue(StringSymbol(value))
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<*>)
(algebra as NumericAlgebra<T>).number(value)
else
error("Numeric nodes are not supported by $this")
}
override operator fun invoke(arguments: Map<Symbol, T>): T = InnerAlgebra(arguments).evaluate(mst)
}
/**
* Builds [MstExpression] over [Algebra].
*
* @author Alexander Nozik
*/
public inline fun <reified T : Any, A : Algebra<T>, E : Algebra<MST>> A.mst(
mstAlgebra: E,
block: E.() -> MST,
): MstExpression<T, A> = MstExpression(this, mstAlgebra.block())
/**
* Builds [MstExpression] over [Group].
*
* @author Alexander Nozik
*/
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, MstGroup.block())
}
/**
* Builds [MstExpression] over [Ring].
*
* @author Alexander Nozik
*/
public inline fun <reified T : Any, A : Ring<T>> A.mstInRing(block: MstRing.() -> MST): MstExpression<T, A> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return MstExpression(this, MstRing.block())
}
/**
* Builds [MstExpression] over [Field].
*
* @author Alexander Nozik
*/
public inline fun <reified T : Any, A : Field<T>> A.mstInField(block: MstField.() -> MST): MstExpression<T, A> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return MstExpression(this, MstField.block())
}
/**
* Builds [MstExpression] over [ExtendedField].
*
* @author Iaroslav Postovalov
*/
public inline fun <reified T : Any, A : ExtendedField<T>> A.mstInExtendedField(block: MstExtendedField.() -> MST): MstExpression<T, A> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return MstExpression(this, MstExtendedField.block())
}
/**
* Builds [MstExpression] over [FunctionalExpressionGroup].
*
* @author Alexander Nozik
*/
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.mstInGroup(block)
}
/**
* Builds [MstExpression] over [FunctionalExpressionRing].
*
* @author Alexander Nozik
*/
public inline fun <reified T : Any, A : Ring<T>> FunctionalExpressionRing<T, A>.mstInRing(block: MstRing.() -> MST): MstExpression<T, A> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return algebra.mstInRing(block)
}
/**
* Builds [MstExpression] over [FunctionalExpressionField].
*
* @author Alexander Nozik
*/
public inline fun <reified T : Any, A : Field<T>> FunctionalExpressionField<T, A>.mstInField(block: MstField.() -> MST): MstExpression<T, A> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return algebra.mstInField(block)
}
/**
* Builds [MstExpression] over [FunctionalExpressionExtendedField].
*
* @author Iaroslav Postovalov
*/
public inline fun <reified T : Any, A : ExtendedField<T>> FunctionalExpressionExtendedField<T, A>.mstInExtendedField(
block: MstExtendedField.() -> MST,
): MstExpression<T, A> {
contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
return algebra.mstInExtendedField(block)
}

134
kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/LatexSyntaxRenderer.kt Normal file
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@ -0,0 +1,134 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
/**
* [SyntaxRenderer] implementation for LaTeX.
*
* The generated string is a valid LaTeX fragment to be used in the Math Mode.
*
* Example usage:
*
* ```
* \documentclass{article}
* \begin{document}
* \begin{equation}
* %code generated by the syntax renderer
* \end{equation}
* \end{document}
* ```
*
* @author Iaroslav Postovalov
*/
public object LatexSyntaxRenderer : SyntaxRenderer {
public override fun render(node: MathSyntax, output: Appendable): Unit = output.run {
fun render(syntax: MathSyntax) = render(syntax, output)
when (node) {
is NumberSyntax -> append(node.string)
is SymbolSyntax -> append(node.string)
is OperatorNameSyntax -> {
append("\\operatorname{")
append(node.name)
append('}')
}
is SpecialSymbolSyntax -> when (node.kind) {
SpecialSymbolSyntax.Kind.INFINITY -> append("\\infty")
SpecialSymbolSyntax.Kind.SMALL_PI -> append("\\pi")
}
is OperandSyntax -> {
if (node.parentheses) append("\\left(")
render(node.operand)
if (node.parentheses) append("\\right)")
}
is UnaryOperatorSyntax -> {
render(node.prefix)
append("\\,")
render(node.operand)
}
is UnaryPlusSyntax -> {
append('+')
render(node.operand)
}
is UnaryMinusSyntax -> {
append('-')
render(node.operand)
}
is RadicalSyntax -> {
append("\\sqrt")
append('{')
render(node.operand)
append('}')
}
is SuperscriptSyntax -> {
render(node.left)
append("^{")
render(node.right)
append('}')
}
is SubscriptSyntax -> {
render(node.left)
append("_{")
render(node.right)
append('}')
}
is BinaryOperatorSyntax -> {
render(node.prefix)
append("\\left(")
render(node.left)
append(',')
render(node.right)
append("\\right)")
}
is BinaryPlusSyntax -> {
render(node.left)
append('+')
render(node.right)
}
is BinaryMinusSyntax -> {
render(node.left)
append('-')
render(node.right)
}
is FractionSyntax -> {
append("\\frac{")
render(node.left)
append("}{")
render(node.right)
append('}')
}
is RadicalWithIndexSyntax -> {
append("\\sqrt")
append('[')
render(node.left)
append(']')
append('{')
render(node.right)
append('}')
}
is MultiplicationSyntax -> {
render(node.left)
append(if (node.times) "\\times" else "\\,")
render(node.right)
}
}
}
}

139
kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathMLSyntaxRenderer.kt Normal file
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@ -0,0 +1,139 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
/**
* [SyntaxRenderer] implementation for MathML.
*
* The generated XML string is a valid MathML instance.
*
* @author Iaroslav Postovalov
*/
public object MathMLSyntaxRenderer : SyntaxRenderer {
public override fun render(node: MathSyntax, output: Appendable) {
output.append("<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow>")
render0(node, output)
output.append("</mrow></math>")
}
private fun render0(node: MathSyntax, output: Appendable): Unit = output.run {
fun tag(tagName: String, vararg attr: Pair<String, String>, block: () -> Unit = {}) {
append('<')
append(tagName)
if (attr.isNotEmpty()) {
append(' ')
var count = 0
for ((name, value) in attr) {
if (++count > 1) append(' ')
append(name)
append("=\"")
append(value)
append('"')
}
}
append('>')
block()
append("</")
append(tagName)
append('>')
}
fun render(syntax: MathSyntax) = render0(syntax, output)
when (node) {
is NumberSyntax -> tag("mn") { append(node.string) }
is SymbolSyntax -> tag("mi") { append(node.string) }
is OperatorNameSyntax -> tag("mo") { append(node.name) }
is SpecialSymbolSyntax -> when (node.kind) {
SpecialSymbolSyntax.Kind.INFINITY -> tag("mo") { append("&infin;") }
SpecialSymbolSyntax.Kind.SMALL_PI -> tag("mo") { append("&pi;") }
}
is OperandSyntax -> if (node.parentheses) {
tag("mfenced", "open" to "(", "close" to ")", "separators" to "") {
render(node.operand)
}
} else {
render(node.operand)
}
is UnaryOperatorSyntax -> {
render(node.prefix)
tag("mspace", "width" to "0.167em")
render(node.operand)
}
is UnaryPlusSyntax -> {
tag("mo") { append('+') }
render(node.operand)
}
is UnaryMinusSyntax -> {
tag("mo") { append("-") }
render(node.operand)
}
is RadicalSyntax -> tag("msqrt") { render(node.operand) }
is SuperscriptSyntax -> tag("msup") {
tag("mrow") { render(node.left) }
tag("mrow") { render(node.right) }
}
is SubscriptSyntax -> tag("msub") {
tag("mrow") { render(node.left) }
tag("mrow") { render(node.right) }
}
is BinaryOperatorSyntax -> {
render(node.prefix)
tag("mfenced", "open" to "(", "close" to ")", "separators" to "") {
render(node.left)
tag("mo") { append(',') }
render(node.right)
}
}
is BinaryPlusSyntax -> {
render(node.left)
tag("mo") { append('+') }
render(node.right)
}
is BinaryMinusSyntax -> {
render(node.left)
tag("mo") { append('-') }
render(node.right)
}
is FractionSyntax -> tag("mfrac") {
tag("mrow") {
render(node.left)
}
tag("mrow") {
render(node.right)
}
}
is RadicalWithIndexSyntax -> tag("mroot") {
tag("mrow") { render(node.right) }
tag("mrow") { render(node.left) }
}
is MultiplicationSyntax -> {
render(node.left)
if (node.times) tag("mo") { append("&times;") } else tag("mspace", "width" to "0.167em")
render(node.right)
}
}
}
}

108
kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/rendering/MathRenderer.kt Normal file
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@ -0,0 +1,108 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
import space.kscience.kmath.expressions.MST
/**
* Renders [MST] to [MathSyntax].
*
* @author Iaroslav Postovalov
*/
public fun interface MathRenderer {
/**
* Renders [MST] to [MathSyntax].
*/
public fun render(mst: MST): MathSyntax
}
/**
* Implements [MST] render process with sequence of features.
*
* @property features The applied features.
* @author Iaroslav Postovalov
*/
public open class FeaturedMathRenderer(public val features: List<RenderFeature>) : MathRenderer {
public override fun render(mst: MST): MathSyntax {
for (feature in features) feature.render(this, mst)?.let { return it }
throw UnsupportedOperationException("Renderer $this has no appropriate feature to render node $mst.")
}
/**
* Logical unit of [MST] rendering.
*/
public fun interface RenderFeature {
/**
* Renders [MST] to [MathSyntax] in the context of owning renderer.
*/
public fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax?
}
}
/**
* Extends [FeaturedMathRenderer] by adding post-processing stages.
*
* @property stages The applied stages.
* @author Iaroslav Postovalov
*/
public open class FeaturedMathRendererWithPostProcess(
features: List<RenderFeature>,
public val stages: List<PostProcessStage>,
) : FeaturedMathRenderer(features) {
public override fun render(mst: MST): MathSyntax {
val res = super.render(mst)
for (stage in stages) stage.perform(res)
return res
}
/**
* Logical unit of [MathSyntax] post-processing.
*/
public fun interface PostProcessStage {
/**
* Performs the specified action over [MathSyntax].
*/
public fun perform(node: MathSyntax)
}
public companion object {
/**
* The default setup of [FeaturedMathRendererWithPostProcess].
*/
public val Default: FeaturedMathRendererWithPostProcess = FeaturedMathRendererWithPostProcess(
listOf(
// Printing known operations
BinaryPlus.Default,
BinaryMinus.Default,
UnaryPlus.Default,
UnaryMinus.Default,
Multiplication.Default,
Fraction.Default,
Power.Default,
SquareRoot.Default,
Exponential.Default,
InverseTrigonometricOperations.Default,
// Fallback option for unknown operations - printing them as operator
BinaryOperator.Default,
UnaryOperator.Default,
// Pretty printing for some objects
PrettyPrintFloats.Default,
PrettyPrintIntegers.Default,
PrettyPrintPi.Default,
// Printing terminal nodes as string
PrintNumeric,
PrintSymbolic,
),
listOf(
SimplifyParentheses.Default,
BetterMultiplication,
),
)
}
}

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/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
/**
* Mathematical typography syntax node.
*
* @author Iaroslav Postovalov
*/
public sealed class MathSyntax {
/**
* The parent node of this syntax node.
*/
public var parent: MathSyntax? = null
}
/**
* Terminal node, which should not have any children nodes.
*
* @author Iaroslav Postovalov
*/
public sealed class TerminalSyntax : MathSyntax()
/**
* Node containing a certain operation.
*
* @author Iaroslav Postovalov
*/
public sealed class OperationSyntax : MathSyntax() {
/**
* The operation token.
*/
public abstract val operation: String
}
/**
* Unary node, which has only one child.
*
* @author Iaroslav Postovalov
*/
public sealed class UnarySyntax : OperationSyntax() {
/**
* The operand of this node.
*/
public abstract val operand: MathSyntax
}
/**
* Binary node, which has only two children.
*
* @author Iaroslav Postovalov
*/
public sealed class BinarySyntax : OperationSyntax() {
/**
* The left-hand side operand.
*/
public abstract val left: MathSyntax
/**
* The right-hand side operand.
*/
public abstract val right: MathSyntax
}
/**
* Represents a number.
*
* @property string The digits of number.
* @author Iaroslav Postovalov
*/
public data class NumberSyntax(public var string: String) : TerminalSyntax()
/**
* Represents a symbol.
*
* @property string The symbol.
* @author Iaroslav Postovalov
*/
public data class SymbolSyntax(public var string: String) : TerminalSyntax()
/**
* Represents special typing for operator name.
*
* @property name The operator name.
* @see BinaryOperatorSyntax
* @see UnaryOperatorSyntax
* @author Iaroslav Postovalov
*/
public data class OperatorNameSyntax(public var name: String) : TerminalSyntax()
/**
* Represents a usage of special symbols.
*
* @property kind The kind of symbol.
* @author Iaroslav Postovalov
*/
public data class SpecialSymbolSyntax(public var kind: Kind) : TerminalSyntax() {
/**
* The kind of symbol.
*/
public enum class Kind {
/**
* The infinity (&infin;) symbol.
*/
INFINITY,
/**
* The Pi (&pi;) symbol.
*/
SMALL_PI;
}
}
/**
* Represents operand of a certain operator wrapped with parentheses or not.
*
* @property operand The operand.
* @property parentheses Whether the operand should be wrapped with parentheses.
* @author Iaroslav Postovalov
*/
public data class OperandSyntax(
public val operand: MathSyntax,
public var parentheses: Boolean,
) : MathSyntax() {
init {
operand.parent = this
}
}
/**
* Represents unary, prefix operator syntax (like f x).
*
* @property prefix The prefix.
* @author Iaroslav Postovalov
*/
public data class UnaryOperatorSyntax(
public override val operation: String,
public var prefix: MathSyntax,
public override val operand: OperandSyntax,
) : UnarySyntax() {
init {
operand.parent = this
}
}
/**
* Represents prefix, unary plus operator.
*
* @author Iaroslav Postovalov
*/
public data class UnaryPlusSyntax(
public override val operation: String,
public override val operand: OperandSyntax,
) : UnarySyntax() {
init {
operand.parent = this
}
}
/**
* Represents prefix, unary minus operator.
*
* @author Iaroslav Postovalov
*/
public data class UnaryMinusSyntax(
public override val operation: String,
public override val operand: OperandSyntax,
) : UnarySyntax() {
init {
operand.parent = this
}
}
/**
* Represents radical with a node inside it.
*
* @property operand The radicand.
* @author Iaroslav Postovalov
*/
public data class RadicalSyntax(
public override val operation: String,
public override val operand: MathSyntax,
) : UnarySyntax() {
init {
operand.parent = this
}
}
/**
* Represents a syntax node with superscript (usually, for exponentiation).
*
* @property left The node.
* @property right The superscript.
* @author Iaroslav Postovalov
*/
public data class SuperscriptSyntax(
public override val operation: String,
public override val left: MathSyntax,
public override val right: MathSyntax,
) : BinarySyntax() {
init {
left.parent = this
right.parent = this
}
}
/**
* Represents a syntax node with subscript.
*
* @property left The node.
* @property right The subscript.
* @author Iaroslav Postovalov
*/
public data class SubscriptSyntax(
public override val operation: String,
public override val left: MathSyntax,
public override val right: MathSyntax,
) : BinarySyntax() {
init {
left.parent = this
right.parent = this
}
}
/**
* Represents binary, prefix operator syntax (like f(a, b)).
*
* @property prefix The prefix.
* @author Iaroslav Postovalov
*/
public data class BinaryOperatorSyntax(
public override val operation: String,
public var prefix: MathSyntax,
public override val left: MathSyntax,
public override val right: MathSyntax,
) : BinarySyntax() {
init {
left.parent = this
right.parent = this
}
}
/**
* Represents binary, infix addition.
*
* @param left The augend.
* @param right The addend.
* @author Iaroslav Postovalov
*/
public data class BinaryPlusSyntax(
public override val operation: String,
public override val left: OperandSyntax,
public override val right: OperandSyntax,
) : BinarySyntax() {
init {
left.parent = this
right.parent = this
}
}
/**
* Represents binary, infix subtraction.
*
* @param left The minuend.
* @param right The subtrahend.
* @author Iaroslav Postovalov
*/
public data class BinaryMinusSyntax(
public override val operation: String,
public override val left: OperandSyntax,
public override val right: OperandSyntax,
) : BinarySyntax() {
init {
left.parent = this
right.parent = this
}
}
/**
* Represents fraction with numerator and denominator.
*
* @property left The numerator.
* @property right The denominator.
* @author Iaroslav Postovalov
*/
public data class FractionSyntax(
public override val operation: String,
public override val left: MathSyntax,
public override val right: MathSyntax,
) : BinarySyntax() {
init {
left.parent = this
right.parent = this
}
}
/**
* Represents radical syntax with index.
*
* @property left The index.
* @property right The radicand.
* @author Iaroslav Postovalov
*/
public data class RadicalWithIndexSyntax(
public override val operation: String,
public override val left: MathSyntax,
public override val right: MathSyntax,
) : BinarySyntax() {
init {
left.parent = this
right.parent = this
}
}
/**
* Represents binary, infix multiplication in the form of coefficient (2 x) or with operator (x&times;2).
*
* @property left The multiplicand.
* @property right The multiplier.
* @property times whether the times (&times;) symbol should be used.
* @author Iaroslav Postovalov
*/
public data class MultiplicationSyntax(
public override val operation: String,
public override val left: OperandSyntax,
public override val right: OperandSyntax,
public var times: Boolean,
) : BinarySyntax() {
init {
left.parent = this
right.parent = this
}
}

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/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
/**
* Abstraction of writing [MathSyntax] as a string of an actual markup language. Typical implementation should
* involve traversal of MathSyntax with handling each its subtype.
*
* @author Iaroslav Postovalov
*/
public fun interface SyntaxRenderer {
/**
* Renders the [MathSyntax] to [output].
*/
public fun render(node: MathSyntax, output: Appendable)
}
/**
* Calls [SyntaxRenderer.render] with given [node] and a new [StringBuilder] instance, and returns its content.
*
* @author Iaroslav Postovalov
*/
public fun SyntaxRenderer.renderWithStringBuilder(node: MathSyntax): String {
val sb = StringBuilder()
render(node, sb)
return sb.toString()
}

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/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
import space.kscience.kmath.ast.rendering.FeaturedMathRenderer.RenderFeature
import space.kscience.kmath.expressions.MST
import space.kscience.kmath.operations.*
import kotlin.reflect.KClass
/**
* Prints any [MST.Symbolic] as a [SymbolSyntax] containing the [MST.Symbolic.value] of it.
*
* @author Iaroslav Postovalov
*/
public object PrintSymbolic : RenderFeature {
public override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? {
if (node !is MST.Symbolic) return null
return SymbolSyntax(string = node.value)
}
}
/**
* Prints any [MST.Numeric] as a [NumberSyntax] containing the [Any.toString] result of it.
*
* @author Iaroslav Postovalov
*/
public object PrintNumeric : RenderFeature {
public override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? {
if (node !is MST.Numeric) return null
return NumberSyntax(string = node.value.toString())
}
}
private fun printSignedNumberString(s: String): MathSyntax {
if (s.startsWith('-'))
return UnaryMinusSyntax(
operation = GroupOperations.MINUS_OPERATION,
operand = OperandSyntax(
operand = NumberSyntax(string = s.removePrefix("-")),
parentheses = true,
),
)
return NumberSyntax(string = s)
}
/**
* Special printing for numeric types which are printed in form of
* *('-'? (DIGIT+ ('.' DIGIT+)? ('E' '-'? DIGIT+)? | 'Infinity')) | 'NaN'*.
*
* @property types The suitable types.
*/
public class PrettyPrintFloats(public val types: Set<KClass<out Number>>) : RenderFeature {
public override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? {
if (node !is MST.Numeric || node.value::class !in types) return null
val toString = node.value.toString().removeSuffix(".0")
if ('E' in toString) {
val (beforeE, afterE) = toString.split('E')
val significand = beforeE.toDouble().toString().removeSuffix(".0")
val exponent = afterE.toDouble().toString().removeSuffix(".0")
return MultiplicationSyntax(
operation = RingOperations.TIMES_OPERATION,
left = OperandSyntax(operand = NumberSyntax(significand), parentheses = true),
right = OperandSyntax(
operand = SuperscriptSyntax(
operation = PowerOperations.POW_OPERATION,
left = NumberSyntax(string = "10"),
right = printSignedNumberString(exponent),
),
parentheses = true,
),
times = true,
)
}
if (toString.endsWith("Infinity")) {
val infty = SpecialSymbolSyntax(SpecialSymbolSyntax.Kind.INFINITY)
if (toString.startsWith('-'))
return UnaryMinusSyntax(
operation = GroupOperations.MINUS_OPERATION,
operand = OperandSyntax(operand = infty, parentheses = true),
)
return infty
}
return printSignedNumberString(toString)
}
public companion object {
/**
* The default instance containing [Float], and [Double].
*/
public val Default: PrettyPrintFloats = PrettyPrintFloats(setOf(Float::class, Double::class))
}
}
/**
* Special printing for numeric types which are printed in form of *'-'? DIGIT+*.
*
* @property types The suitable types.
*/
public class PrettyPrintIntegers(public val types: Set<KClass<out Number>>) : RenderFeature {
public override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? {
if (node !is MST.Numeric || node.value::class !in types)
return null
return printSignedNumberString(node.value.toString())
}
public companion object {
/**
* The default instance containing [Byte], [Short], [Int], and [Long].
*/
public val Default: PrettyPrintIntegers =
PrettyPrintIntegers(setOf(Byte::class, Short::class, Int::class, Long::class))
}
}
/**
* Special printing for symbols meaning Pi.
*
* @property symbols The allowed symbols.
*/
public class PrettyPrintPi(public val symbols: Set<String>) : RenderFeature {
public override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? {
if (node !is MST.Symbolic || node.value !in symbols) return null
return SpecialSymbolSyntax(kind = SpecialSymbolSyntax.Kind.SMALL_PI)
}
public companion object {
/**
* The default instance containing `pi`.
*/
public val Default: PrettyPrintPi = PrettyPrintPi(setOf("pi"))
}
}
/**
* Abstract printing of unary operations which discards [MST] if their operation is not in [operations] or its type is
* not [MST.Unary].
*
* @param operations the allowed operations. If `null`, any operation is accepted.
*/
public abstract class Unary(public val operations: Collection<String>?) : RenderFeature {
/**
* The actual render function.
*/
protected abstract fun render0(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax?
public final override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? {
if (node !is MST.Unary || operations != null && node.operation !in operations) return null
return render0(renderer, node)
}
}
/**
* Abstract printing of unary operations which discards [MST] if their operation is not in [operations] or its type is
* not [MST.Binary].
*
* @property operations the allowed operations. If `null`, any operation is accepted.
*/
public abstract class Binary(public val operations: Collection<String>?) : RenderFeature {
/**
* The actual render function.
*/
protected abstract fun render0(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax?
public final override fun render(renderer: FeaturedMathRenderer, node: MST): MathSyntax? {
if (node !is MST.Binary || operations != null && node.operation !in operations) return null
return render0(renderer, node)
}
}
public class BinaryPlus(operations: Collection<String>?) : Binary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = BinaryPlusSyntax(
operation = node.operation,
left = OperandSyntax(parent.render(node.left), true),
right = OperandSyntax(parent.render(node.right), true),
)
public companion object {
public val Default: BinaryPlus = BinaryPlus(setOf(GroupOperations.PLUS_OPERATION))
}
}
public class BinaryMinus(operations: Collection<String>?) : Binary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = BinaryMinusSyntax(
operation = node.operation,
left = OperandSyntax(operand = parent.render(node.left), parentheses = true),
right = OperandSyntax(operand = parent.render(node.right), parentheses = true),
)
public companion object {
public val Default: BinaryMinus = BinaryMinus(setOf(GroupOperations.MINUS_OPERATION))
}
}
public class UnaryPlus(operations: Collection<String>?) : Unary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryPlusSyntax(
operation = node.operation,
operand = OperandSyntax(operand = parent.render(node.value), parentheses = true),
)
public companion object {
public val Default: UnaryPlus = UnaryPlus(setOf(GroupOperations.PLUS_OPERATION))
}
}
public class UnaryMinus(operations: Collection<String>?) : Unary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryMinusSyntax(
operation = node.operation,
operand = OperandSyntax(operand = parent.render(node.value), parentheses = true),
)
public companion object {
public val Default: UnaryMinus = UnaryMinus(setOf(GroupOperations.MINUS_OPERATION))
}
}
public class Fraction(operations: Collection<String>?) : Binary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = FractionSyntax(
operation = node.operation,
left = parent.render(node.left),
right = parent.render(node.right),
)
public companion object {
public val Default: Fraction = Fraction(setOf(FieldOperations.DIV_OPERATION))
}
}
public class BinaryOperator(operations: Collection<String>?) : Binary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = BinaryOperatorSyntax(
operation = node.operation,
prefix = OperatorNameSyntax(name = node.operation),
left = parent.render(node.left),
right = parent.render(node.right),
)
public companion object {
public val Default: BinaryOperator = BinaryOperator(null)
}
}
public class UnaryOperator(operations: Collection<String>?) : Unary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryOperatorSyntax(
operation = node.operation,
prefix = OperatorNameSyntax(node.operation),
operand = OperandSyntax(parent.render(node.value), true),
)
public companion object {
public val Default: UnaryOperator = UnaryOperator(null)
}
}
public class Power(operations: Collection<String>?) : Binary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = SuperscriptSyntax(
operation = node.operation,
left = OperandSyntax(parent.render(node.left), true),
right = OperandSyntax(parent.render(node.right), true),
)
public companion object {
public val Default: Power = Power(setOf(PowerOperations.POW_OPERATION))
}
}
public class SquareRoot(operations: Collection<String>?) : Unary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax =
RadicalSyntax(operation = node.operation, operand = parent.render(node.value))
public companion object {
public val Default: SquareRoot = SquareRoot(setOf(PowerOperations.SQRT_OPERATION))
}
}
public class Exponential(operations: Collection<String>?) : Unary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = SuperscriptSyntax(
operation = node.operation,
left = SymbolSyntax(string = "e"),
right = parent.render(node.value),
)
public companion object {
public val Default: Exponential = Exponential(setOf(ExponentialOperations.EXP_OPERATION))
}
}
public class Multiplication(operations: Collection<String>?) : Binary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Binary): MathSyntax = MultiplicationSyntax(
operation = node.operation,
left = OperandSyntax(operand = parent.render(node.left), parentheses = true),
right = OperandSyntax(operand = parent.render(node.right), parentheses = true),
times = true,
)
public companion object {
public val Default: Multiplication = Multiplication(setOf(
RingOperations.TIMES_OPERATION,
))
}
}
public class InverseTrigonometricOperations(operations: Collection<String>?) : Unary(operations) {
public override fun render0(parent: FeaturedMathRenderer, node: MST.Unary): MathSyntax = UnaryOperatorSyntax(
operation = node.operation,
prefix = SuperscriptSyntax(
operation = PowerOperations.POW_OPERATION,
left = OperatorNameSyntax(name = node.operation.removePrefix("a")),
right = UnaryMinusSyntax(
operation = GroupOperations.MINUS_OPERATION,
operand = OperandSyntax(operand = NumberSyntax(string = "1"), parentheses = true),
),
),
operand = OperandSyntax(operand = parent.render(node.value), parentheses = true),
)
public companion object {
public val Default: InverseTrigonometricOperations = InverseTrigonometricOperations(setOf(
TrigonometricOperations.ACOS_OPERATION,
TrigonometricOperations.ASIN_OPERATION,
TrigonometricOperations.ATAN_OPERATION,
ExponentialOperations.ACOSH_OPERATION,
ExponentialOperations.ASINH_OPERATION,
ExponentialOperations.ATANH_OPERATION,
))
}
}

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/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
import space.kscience.kmath.operations.FieldOperations
import space.kscience.kmath.operations.GroupOperations
import space.kscience.kmath.operations.PowerOperations
import space.kscience.kmath.operations.RingOperations
/**
* Removes unnecessary times (&times;) symbols from [MultiplicationSyntax].
*
* @author Iaroslav Postovalov
*/
public object BetterMultiplication : FeaturedMathRendererWithPostProcess.PostProcessStage {
public override fun perform(node: MathSyntax) {
when (node) {
is NumberSyntax -> Unit
is SymbolSyntax -> Unit
is OperatorNameSyntax -> Unit
is SpecialSymbolSyntax -> Unit
is OperandSyntax -> perform(node.operand)
is UnaryOperatorSyntax -> {
perform(node.prefix)
perform(node.operand)
}
is UnaryPlusSyntax -> perform(node.operand)
is UnaryMinusSyntax -> perform(node.operand)
is RadicalSyntax -> perform(node.operand)
is SuperscriptSyntax -> {
perform(node.left)
perform(node.right)
}
is SubscriptSyntax -> {
perform(node.left)
perform(node.right)
}
is BinaryOperatorSyntax -> {
perform(node.prefix)
perform(node.left)
perform(node.right)
}
is BinaryPlusSyntax -> {
perform(node.left)
perform(node.right)
}
is BinaryMinusSyntax -> {
perform(node.left)
perform(node.right)
}
is FractionSyntax -> {
perform(node.left)
perform(node.right)
}
is RadicalWithIndexSyntax -> {
perform(node.left)
perform(node.right)
}
is MultiplicationSyntax -> {
node.times = node.right.operand is NumberSyntax && !node.right.parentheses
|| node.left.operand is NumberSyntax && node.right.operand is FractionSyntax
|| node.left.operand is NumberSyntax && node.right.operand is NumberSyntax
|| node.left.operand is NumberSyntax && node.right.operand is SuperscriptSyntax && node.right.operand.left is NumberSyntax
perform(node.left)
perform(node.right)
}
}
}
}
/**
* Removes unnecessary parentheses from [OperandSyntax].
*
* @property precedenceFunction Returns the precedence number for syntax node. Higher number is lower priority.
* @author Iaroslav Postovalov
*/
public class SimplifyParentheses(public val precedenceFunction: (MathSyntax) -> Int) :
FeaturedMathRendererWithPostProcess.PostProcessStage {
public override fun perform(node: MathSyntax) {
when (node) {
is NumberSyntax -> Unit
is SymbolSyntax -> Unit
is OperatorNameSyntax -> Unit
is SpecialSymbolSyntax -> Unit
is OperandSyntax -> {
val isRightOfSuperscript =
(node.parent is SuperscriptSyntax) && (node.parent as SuperscriptSyntax).right === node
val precedence = precedenceFunction(node.operand)
val needParenthesesByPrecedence = when (val parent = node.parent) {
null -> false
is BinarySyntax -> {
val parentPrecedence = precedenceFunction(parent)
parentPrecedence < precedence ||
parentPrecedence == precedence && parentPrecedence != 0 && node === parent.right
}
else -> precedence > precedenceFunction(parent)
}
node.parentheses = !isRightOfSuperscript
&& (needParenthesesByPrecedence || node.parent is UnaryOperatorSyntax)
perform(node.operand)
}
is UnaryOperatorSyntax -> {
perform(node.prefix)
perform(node.operand)
}
is UnaryPlusSyntax -> perform(node.operand)
is UnaryMinusSyntax -> {
perform(node.operand)
}
is RadicalSyntax -> perform(node.operand)
is SuperscriptSyntax -> {
perform(node.left)
perform(node.right)
}
is SubscriptSyntax -> {
perform(node.left)
perform(node.right)
}
is BinaryOperatorSyntax -> {
perform(node.prefix)
perform(node.left)
perform(node.right)
}
is BinaryPlusSyntax -> {
perform(node.left)
perform(node.right)
}
is BinaryMinusSyntax -> {
perform(node.left)
perform(node.right)
}
is FractionSyntax -> {
perform(node.left)
perform(node.right)
}
is MultiplicationSyntax -> {
perform(node.left)
perform(node.right)
}
is RadicalWithIndexSyntax -> {
perform(node.left)
perform(node.right)
}
}
}
public companion object {
/**
* The default configuration of [SimplifyParentheses] where power is 1, multiplicative operations are 2,
* additive operations are 3.
*/
public val Default: SimplifyParentheses = SimplifyParentheses {
when (it) {
is TerminalSyntax -> 0
is UnarySyntax -> 2
is BinarySyntax -> when (it.operation) {
PowerOperations.POW_OPERATION -> 1
RingOperations.TIMES_OPERATION -> 3
FieldOperations.DIV_OPERATION -> 3
GroupOperations.MINUS_OPERATION -> 4
GroupOperations.PLUS_OPERATION -> 4
else -> 0
}
else -> 0
}
}
}
}

27
kmath-ast/src/commonTest/kotlin/space/kscisnce/kmath/ast/InterpretTest.kt Normal file
View File

@ -0,0 +1,27 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscisnce.kmath.ast
import space.kscience.kmath.expressions.MstField
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.expressions.toExpression
import space.kscience.kmath.misc.Symbol.Companion.x
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.bindSymbol
import space.kscience.kmath.operations.invoke
import kotlin.test.Test
class InterpretTest {
@Test
fun interpretation(){
val expr = MstField {
val x = bindSymbol(x)
x * 2.0 + number(2.0) / x - 16.0
}.toExpression(DoubleField)
expr(x to 2.2)
}
}

44
kmath-ast/src/jsMain/kotlin/space/kscience/kmath/estree/estree.kt
View File

@ -5,12 +5,13 @@
package space.kscience.kmath.estree
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.expressions.MST
import space.kscience.kmath.expressions.MST.*
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.misc.Symbol
import space.kscience.kmath.operations.Algebra
import space.kscience.kmath.operations.NumericAlgebra
@ -18,11 +19,7 @@ import space.kscience.kmath.operations.NumericAlgebra
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.bindSymbol(node.value)
} catch (ignored: IllegalStateException) {
null
}
val symbol = algebra.bindSymbolOrNull(node.value)
if (symbol != null)
constant(symbol)
@ -34,16 +31,17 @@ internal fun <T> MST.compileWith(algebra: Algebra<T>): Expression<T> {
is Unary -> when {
algebra is NumericAlgebra && node.value is Numeric -> constant(
algebra.unaryOperationFunction(node.operation)(algebra.number(node.value.value)))
algebra.unaryOperationFunction(node.operation)(algebra.number((node.value as Numeric).value)))
else -> call(algebra.unaryOperationFunction(node.operation), visit(node.value))
}
is Binary -> when {
algebra is NumericAlgebra && node.left is Numeric && node.right is Numeric -> constant(
algebra
.binaryOperationFunction(node.operation)
.invoke(algebra.number(node.left.value), algebra.number(node.right.value))
algebra.binaryOperationFunction(node.operation).invoke(
algebra.number((node.left as Numeric).value),
algebra.number((node.right as Numeric).value)
)
)
algebra is NumericAlgebra && node.left is Numeric -> call(
@ -69,19 +67,21 @@ internal fun <T> MST.compileWith(algebra: Algebra<T>): Expression<T> {
return ESTreeBuilder<T> { visit(this@compileWith) }.instance
}
/**
* Create a compiled expression with given [MST] and given [algebra].
*/
public fun <T : Any> MST.compileToExpression(algebra: Algebra<T>): Expression<T> = compileWith(algebra)
/**
* Compiles an [MST] to ESTree generated expression using given algebra.
*
* @author Alexander Nozik.
* Compile given MST to expression and evaluate it against [arguments]
*/
public fun <T : Any> Algebra<T>.expression(mst: MST): Expression<T> =
mst.compileWith(this)
public inline fun <reified T : Any> MST.compile(algebra: Algebra<T>, arguments: Map<Symbol, T>): T =
compileToExpression(algebra).invoke(arguments)
/**
* Optimizes performance of an [MstExpression] by compiling it into ESTree generated expression.
*
* @author Alexander Nozik.
* Compile given MST to expression and evaluate it against [arguments]
*/
public fun <T : Any> MstExpression<T, Algebra<T>>.compile(): Expression<T> =
mst.compileWith(algebra)
public inline fun <reified T : Any> MST.compile(algebra: Algebra<T>, vararg arguments: Pair<Symbol, T>): T =
compileToExpression(algebra).invoke(*arguments)

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

@ -8,7 +8,7 @@ package space.kscience.kmath.estree.internal
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.expressions.Symbol
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> {

86
kmath-ast/src/jsTest/kotlin/space/kscience/kmath/estree/TestESTreeConsistencyWithInterpreter.kt
View File

@ -5,19 +5,22 @@
package space.kscience.kmath.estree
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.expressions.*
import space.kscience.kmath.misc.Symbol
import space.kscience.kmath.operations.ByteRing
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestESTreeConsistencyWithInterpreter {
@Test
fun mstSpace() {
val res1 = MstGroup.mstInGroup {
val mst = MstGroup {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
number(3.toByte()) - (number(2.toByte()) + (scale(
@ -28,27 +31,17 @@ internal class TestESTreeConsistencyWithInterpreter {
number(1)
) + bindSymbol("x") + zero
}("x" to MST.Numeric(2))
}
val res2 = MstGroup.mstInGroup {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
number(3.toByte()) - (number(2.toByte()) + (scale(
add(number(1), number(1)),
2.0
) + number(1.toByte()) * 3.toByte() - number(1.toByte())))
),
number(1)
) + bindSymbol("x") + zero
}.compile()("x" to MST.Numeric(2))
assertEquals(res1, res2)
assertEquals(
mst.interpret(MstGroup, Symbol.x to MST.Numeric(2)),
mst.compile(MstGroup, Symbol.x to MST.Numeric(2))
)
}
@Test
fun byteRing() {
val res1 = ByteRing.mstInRing {
val mst = MstRing {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
(bindSymbol("x") - (2.toByte() + (scale(
@ -59,62 +52,43 @@ internal class TestESTreeConsistencyWithInterpreter {
number(1)
) * number(2)
}("x" to 3.toByte())
}
val res2 = ByteRing.mstInRing {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
(bindSymbol("x") - (2.toByte() + (scale(
add(number(1), number(1)),
2.0
) + 1.toByte()))) * 3.0 - 1.toByte()
),
number(1)
) * number(2)
}.compile()("x" to 3.toByte())
assertEquals(res1, res2)
assertEquals(
mst.interpret(ByteRing, Symbol.x to 3.toByte()),
mst.compile(ByteRing, Symbol.x to 3.toByte())
)
}
@Test
fun realField() {
val res1 = RealField.mstInField {
val mst = MstField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(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 {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(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
}.compile()("x" to 2.0)
assertEquals(res1, res2)
assertEquals(
mst.interpret(DoubleField, Symbol.x to 2.0),
mst.compile(DoubleField, Symbol.x to 2.0)
)
}
@Test
fun complexField() {
val res1 = ComplexField.mstInField {
val mst = MstField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(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.toComplex())
}
val res2 = ComplexField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(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
}.compile()("x" to 2.0.toComplex())
assertEquals(res1, res2)
assertEquals(
mst.interpret(ComplexField, Symbol.x to 2.0.toComplex()),
mst.compile(ComplexField, Symbol.x to 2.0.toComplex())
)
}
}

17
kmath-ast/src/jsTest/kotlin/space/kscience/kmath/estree/TestESTreeOperationsSupport.kt
View File

@ -5,11 +5,10 @@
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.MstExtendedField
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import kotlin.random.Random
import kotlin.test.Test
import kotlin.test.assertEquals
@ -17,27 +16,29 @@ import kotlin.test.assertEquals
internal class TestESTreeOperationsSupport {
@Test
fun testUnaryOperationInvocation() {
val expression = RealField.mstInGroup { -bindSymbol("x") }.compile()
val expression = MstExtendedField { -bindSymbol("x") }.compileToExpression(DoubleField)
val res = expression("x" to 2.0)
assertEquals(-2.0, res)
}
@Test
fun testBinaryOperationInvocation() {
val expression = RealField.mstInGroup { -bindSymbol("x") + number(1.0) }.compile()
val expression = MstExtendedField { -bindSymbol("x") + number(1.0) }.compileToExpression(DoubleField)
val res = expression("x" to 2.0)
assertEquals(-1.0, res)
}
@Test
fun testConstProductInvocation() {
val res = RealField.mstInField { bindSymbol("x") * 2 }("x" to 2.0)
val res = MstExtendedField { bindSymbol("x") * 2 }.compileToExpression(DoubleField)("x" to 2.0)
assertEquals(4.0, res)
}
@Test
fun testMultipleCalls() {
val e = RealField.mstInExtendedField { sin(bindSymbol("x")).pow(4) - 6 * bindSymbol("x") / tanh(bindSymbol("x")) }.compile()
val e =
MstExtendedField { sin(bindSymbol("x")).pow(4) - 6 * bindSymbol("x") / tanh(bindSymbol("x")) }
.compileToExpression(DoubleField)
val r = Random(0)
var s = 0.0
repeat(1000000) { s += e("x" to r.nextDouble()) }

32
kmath-ast/src/jsTest/kotlin/space/kscience/kmath/estree/TestESTreeSpecialization.kt
View File

@ -5,54 +5,64 @@
package space.kscience.kmath.estree
import space.kscience.kmath.ast.mstInField
import space.kscience.kmath.expressions.MstExtendedField
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestESTreeSpecialization {
@Test
fun testUnaryPlus() {
val expr = RealField.mstInField { unaryOperationFunction("+")(bindSymbol("x")) }.compile()
val expr = MstExtendedField { unaryOperationFunction("+")(bindSymbol("x")) }.compileToExpression(DoubleField)
assertEquals(2.0, expr("x" to 2.0))
}
@Test
fun testUnaryMinus() {
val expr = RealField.mstInField { unaryOperationFunction("-")(bindSymbol("x")) }.compile()
val expr = MstExtendedField { unaryOperationFunction("-")(bindSymbol("x")) }.compileToExpression(DoubleField)
assertEquals(-2.0, expr("x" to 2.0))
}
@Test
fun testAdd() {
val expr = RealField.mstInField { binaryOperationFunction("+")(bindSymbol("x"), bindSymbol("x")) }.compile()
val expr = MstExtendedField {
binaryOperationFunction("+")(bindSymbol("x"),
bindSymbol("x"))
}.compileToExpression(DoubleField)
assertEquals(4.0, expr("x" to 2.0))
}
@Test
fun testSine() {
val expr = RealField.mstInField { unaryOperationFunction("sin")(bindSymbol("x")) }.compile()
val expr = MstExtendedField { unaryOperationFunction("sin")(bindSymbol("x")) }.compileToExpression(DoubleField)
assertEquals(0.0, expr("x" to 0.0))
}
@Test
fun testMinus() {
val expr = RealField.mstInField { binaryOperationFunction("-")(bindSymbol("x"), bindSymbol("x")) }.compile()
val expr = MstExtendedField {
binaryOperationFunction("-")(bindSymbol("x"),
bindSymbol("x"))
}.compileToExpression(DoubleField)
assertEquals(0.0, expr("x" to 2.0))
}
@Test
fun testDivide() {
val expr = RealField.mstInField { binaryOperationFunction("/")(bindSymbol("x"), bindSymbol("x")) }.compile()
val expr = MstExtendedField {
binaryOperationFunction("/")(bindSymbol("x"),
bindSymbol("x"))
}.compileToExpression(DoubleField)
assertEquals(1.0, expr("x" to 2.0))
}
@Test
fun testPower() {
val expr = RealField
.mstInField { binaryOperationFunction("pow")(bindSymbol("x"), number(2)) }
.compile()
val expr = MstExtendedField {
binaryOperationFunction("pow")(bindSymbol("x"), number(2))
}.compileToExpression(DoubleField)
assertEquals(4.0, expr("x" to 2.0))
}

7
kmath-ast/src/jsTest/kotlin/space/kscience/kmath/estree/TestESTreeVariables.kt
View File

@ -5,9 +5,10 @@
package space.kscience.kmath.estree
import space.kscience.kmath.ast.mstInRing
import space.kscience.kmath.expressions.MstRing
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.ByteRing
import space.kscience.kmath.operations.invoke
import kotlin.test.Test
import kotlin.test.assertEquals
import kotlin.test.assertFailsWith
@ -15,13 +16,13 @@ import kotlin.test.assertFailsWith
internal class TestESTreeVariables {
@Test
fun testVariable() {
val expr = ByteRing.mstInRing { bindSymbol("x") }.compile()
val expr = MstRing{ bindSymbol("x") }.compileToExpression(ByteRing)
assertEquals(1.toByte(), expr("x" to 1.toByte()))
}
@Test
fun testUndefinedVariableFails() {
val expr = ByteRing.mstInRing { bindSymbol("x") }.compile()
val expr = MstRing { bindSymbol("x") }.compileToExpression(ByteRing)
assertFailsWith<NoSuchElementException> { expr() }
}
}

49
kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/asm.kt
View File

@ -7,10 +7,11 @@ package space.kscience.kmath.asm
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.expressions.MST
import space.kscience.kmath.expressions.MST.*
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.misc.Symbol
import space.kscience.kmath.operations.Algebra
import space.kscience.kmath.operations.NumericAlgebra
@ -26,11 +27,7 @@ import space.kscience.kmath.operations.NumericAlgebra
internal fun <T : Any> MST.compileWith(type: Class<T>, algebra: Algebra<T>): Expression<T> {
fun AsmBuilder<T>.visit(node: MST): Unit = when (node) {
is Symbolic -> {
val symbol = try {
algebra.bindSymbol(node.value)
} catch (ignored: IllegalStateException) {
null
}
val symbol = algebra.bindSymbolOrNull(node.value)
if (symbol != null)
loadObjectConstant(symbol as Any)
@ -42,15 +39,17 @@ internal fun <T : Any> MST.compileWith(type: Class<T>, algebra: Algebra<T>): Exp
is Unary -> when {
algebra is NumericAlgebra && node.value is Numeric -> loadObjectConstant(
algebra.unaryOperationFunction(node.operation)(algebra.number(node.value.value)))
algebra.unaryOperationFunction(node.operation)(algebra.number((node.value as Numeric).value)))
else -> buildCall(algebra.unaryOperationFunction(node.operation)) { visit(node.value) }
}
is Binary -> when {
algebra is NumericAlgebra && node.left is Numeric && node.right is Numeric -> loadObjectConstant(
algebra.binaryOperationFunction(node.operation)
.invoke(algebra.number(node.left.value), algebra.number(node.right.value))
algebra.binaryOperationFunction(node.operation).invoke(
algebra.number((node.left as Numeric).value),
algebra.number((node.right as Numeric).value)
)
)
algebra is NumericAlgebra && node.left is Numeric -> buildCall(
@ -75,18 +74,22 @@ internal fun <T : Any> MST.compileWith(type: Class<T>, algebra: Algebra<T>): Exp
return AsmBuilder<T>(type, buildName(this)) { visit(this@compileWith) }.instance
}
/**
* Compiles an [MST] to ASM using given algebra.
*
* @author Alexander Nozik.
*/
public inline fun <reified T : Any> Algebra<T>.expression(mst: MST): Expression<T> =
mst.compileWith(T::class.java, this)
/**
* Optimizes performance of an [MstExpression] using ASM codegen.
*
* @author Alexander Nozik.
* Create a compiled expression with given [MST] and given [algebra].
*/
public inline fun <reified T : Any> MstExpression<T, Algebra<T>>.compile(): Expression<T> =
mst.compileWith(T::class.java, algebra)
public inline fun <reified T : Any> MST.compileToExpression(algebra: Algebra<T>): Expression<T> =
compileWith(T::class.java, algebra)
/**
* Compile given MST to expression and evaluate it against [arguments]
*/
public inline fun <reified T : Any> MST.compile(algebra: Algebra<T>, arguments: Map<Symbol, T>): T =
compileToExpression(algebra).invoke(arguments)
/**
* Compile given MST to expression and evaluate it against [arguments]
*/
public inline fun <reified T : Any> MST.compile(algebra: Algebra<T>, vararg arguments: Pair<Symbol, T>): T =
compileToExpression(algebra).invoke(*arguments)

2
kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/AsmBuilder.kt
View File

@ -10,8 +10,8 @@ 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 space.kscience.kmath.expressions.MST
import java.lang.invoke.MethodHandles
import java.lang.invoke.MethodType
import java.util.stream.Collectors.toMap

4
kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/codegenUtils.kt
View File

@ -7,8 +7,8 @@ package space.kscience.kmath.asm.internal
import org.objectweb.asm.*
import org.objectweb.asm.commons.InstructionAdapter
import space.kscience.kmath.ast.MST
import space.kscience.kmath.expressions.Expression
import space.kscience.kmath.expressions.MST
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@ -91,7 +91,7 @@ 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)

4
kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/asm/internal/mapIntrinsics.kt
View File

@ -7,8 +7,8 @@
package space.kscience.kmath.asm.internal
import space.kscience.kmath.expressions.StringSymbol
import space.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.

4
kmath-ast/src/jvmMain/kotlin/space/kscience/kmath/ast/parser.kt
View File

@ -18,6 +18,7 @@ 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 space.kscience.kmath.expressions.MST
import space.kscience.kmath.operations.FieldOperations
import space.kscience.kmath.operations.GroupOperations
import space.kscience.kmath.operations.PowerOperations
@ -26,7 +27,8 @@ import space.kscience.kmath.operations.RingOperations
/**
* better-parse implementation of grammar defined in the ArithmeticsEvaluator.g4.
*
* @author Alexander Nozik and Iaroslav Postovalov
* @author Alexander Nozik
* @author Iaroslav Postovalov
*/
public object ArithmeticsEvaluator : Grammar<MST>() {
// TODO replace with "...".toRegex() when better-parse 0.4.1 is released

86
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/asm/TestAsmConsistencyWithInterpreter.kt
View File

@ -5,19 +5,22 @@
package space.kscience.kmath.asm
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.expressions.*
import space.kscience.kmath.misc.Symbol.Companion.x
import space.kscience.kmath.operations.ByteRing
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestAsmConsistencyWithInterpreter {
@Test
fun mstSpace() {
val res1 = MstGroup.mstInGroup {
val mst = MstGroup {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
number(3.toByte()) - (number(2.toByte()) + (scale(
@ -28,27 +31,17 @@ internal class TestAsmConsistencyWithInterpreter {
number(1)
) + bindSymbol("x") + zero
}("x" to MST.Numeric(2))
}
val res2 = MstGroup.mstInGroup {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
number(3.toByte()) - (number(2.toByte()) + (scale(
add(number(1), number(1)),
2.0
) + number(1.toByte()) * 3.toByte() - number(1.toByte())))
),
number(1)
) + bindSymbol("x") + zero
}.compile()("x" to MST.Numeric(2))
assertEquals(res1, res2)
assertEquals(
mst.interpret(MstGroup, x to MST.Numeric(2)),
mst.compile(MstGroup, x to MST.Numeric(2))
)
}
@Test
fun byteRing() {
val res1 = ByteRing.mstInRing {
val mst = MstRing {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
(bindSymbol("x") - (2.toByte() + (scale(
@ -59,62 +52,43 @@ internal class TestAsmConsistencyWithInterpreter {
number(1)
) * number(2)
}("x" to 3.toByte())
}
val res2 = ByteRing.mstInRing {
binaryOperationFunction("+")(
unaryOperationFunction("+")(
(bindSymbol("x") - (2.toByte() + (scale(
add(number(1), number(1)),
2.0
) + 1.toByte()))) * 3.0 - 1.toByte()
),
number(1)
) * number(2)
}.compile()("x" to 3.toByte())
assertEquals(res1, res2)
assertEquals(
mst.interpret(ByteRing, x to 3.toByte()),
mst.compile(ByteRing, x to 3.toByte())
)
}
@Test
fun realField() {
val res1 = RealField.mstInField {
val mst = MstField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(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 {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(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
}.compile()("x" to 2.0)
assertEquals(res1, res2)
assertEquals(
mst.interpret(DoubleField, x to 2.0),
mst.compile(DoubleField, x to 2.0)
)
}
@Test
fun complexField() {
val res1 = ComplexField.mstInField {
val mst = MstField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(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.toComplex())
}
val res2 = ComplexField.mstInField {
+(3 - 2 + 2 * number(1) + 1.0) + binaryOperationFunction("+")(
(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
}.compile()("x" to 2.0.toComplex())
assertEquals(res1, res2)
assertEquals(
mst.interpret(ComplexField, x to 2.0.toComplex()),
mst.compile(ComplexField, x to 2.0.toComplex())
)
}
}

19
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/asm/TestAsmOperationsSupport.kt
View File

@ -5,11 +5,12 @@
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.MstExtendedField
import space.kscience.kmath.expressions.MstField
import space.kscience.kmath.expressions.MstGroup
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import kotlin.random.Random
import kotlin.test.Test
import kotlin.test.assertEquals
@ -17,27 +18,29 @@ import kotlin.test.assertEquals
internal class TestAsmOperationsSupport {
@Test
fun testUnaryOperationInvocation() {
val expression = RealField.mstInGroup { -bindSymbol("x") }.compile()
val expression = MstGroup { -bindSymbol("x") }.compileToExpression(DoubleField)
val res = expression("x" to 2.0)
assertEquals(-2.0, res)
}
@Test
fun testBinaryOperationInvocation() {
val expression = RealField.mstInGroup { -bindSymbol("x") + number(1.0) }.compile()
val expression = MstGroup { -bindSymbol("x") + number(1.0) }.compileToExpression(DoubleField)
val res = expression("x" to 2.0)
assertEquals(-1.0, res)
}
@Test
fun testConstProductInvocation() {
val res = RealField.mstInField { bindSymbol("x") * 2 }("x" to 2.0)
val res = MstField { bindSymbol("x") * 2 }.compileToExpression(DoubleField)("x" to 2.0)
assertEquals(4.0, res)
}
@Test
fun testMultipleCalls() {
val e = RealField.mstInExtendedField { sin(bindSymbol("x")).pow(4) - 6 * bindSymbol("x") / tanh(bindSymbol("x")) }.compile()
val e =
MstExtendedField { sin(bindSymbol("x")).pow(4) - 6 * bindSymbol("x") / tanh(bindSymbol("x")) }
.compileToExpression(DoubleField)
val r = Random(0)
var s = 0.0
repeat(1000000) { s += e("x" to r.nextDouble()) }

32
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/asm/TestAsmSpecialization.kt
View File

@ -5,54 +5,64 @@
package space.kscience.kmath.asm
import space.kscience.kmath.ast.mstInField
import space.kscience.kmath.expressions.MstExtendedField
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import kotlin.test.Test
import kotlin.test.assertEquals
internal class TestAsmSpecialization {
@Test
fun testUnaryPlus() {
val expr = RealField.mstInField { unaryOperationFunction("+")(bindSymbol("x")) }.compile()
val expr = MstExtendedField { unaryOperationFunction("+")(bindSymbol("x")) }.compileToExpression(DoubleField)
assertEquals(2.0, expr("x" to 2.0))
}
@Test
fun testUnaryMinus() {
val expr = RealField.mstInField { unaryOperationFunction("-")(bindSymbol("x")) }.compile()
val expr = MstExtendedField { unaryOperationFunction("-")(bindSymbol("x")) }.compileToExpression(DoubleField)
assertEquals(-2.0, expr("x" to 2.0))
}
@Test
fun testAdd() {
val expr = RealField.mstInField { binaryOperationFunction("+")(bindSymbol("x"), bindSymbol("x")) }.compile()
val expr = MstExtendedField {
binaryOperationFunction("+")(bindSymbol("x"),
bindSymbol("x"))
}.compileToExpression(DoubleField)
assertEquals(4.0, expr("x" to 2.0))
}
@Test
fun testSine() {
val expr = RealField.mstInField { unaryOperationFunction("sin")(bindSymbol("x")) }.compile()
val expr = MstExtendedField { unaryOperationFunction("sin")(bindSymbol("x")) }.compileToExpression(DoubleField)
assertEquals(0.0, expr("x" to 0.0))
}
@Test
fun testMinus() {
val expr = RealField.mstInField { binaryOperationFunction("-")(bindSymbol("x"), bindSymbol("x")) }.compile()
val expr = MstExtendedField {
binaryOperationFunction("-")(bindSymbol("x"),
bindSymbol("x"))
}.compileToExpression(DoubleField)
assertEquals(0.0, expr("x" to 2.0))
}
@Test
fun testDivide() {
val expr = RealField.mstInField { binaryOperationFunction("/")(bindSymbol("x"), bindSymbol("x")) }.compile()
val expr = MstExtendedField {
binaryOperationFunction("/")(bindSymbol("x"),
bindSymbol("x"))
}.compileToExpression(DoubleField)
assertEquals(1.0, expr("x" to 2.0))
}
@Test
fun testPower() {
val expr = RealField
.mstInField { binaryOperationFunction("pow")(bindSymbol("x"), number(2)) }
.compile()
val expr = MstExtendedField {
binaryOperationFunction("pow")(bindSymbol("x"), number(2))
}.compileToExpression(DoubleField)
assertEquals(4.0, expr("x" to 2.0))
}

7
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/asm/TestAsmVariables.kt
View File

@ -5,9 +5,10 @@
package space.kscience.kmath.asm
import space.kscience.kmath.ast.mstInRing
import space.kscience.kmath.expressions.MstRing
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.operations.ByteRing
import space.kscience.kmath.operations.invoke
import kotlin.test.Test
import kotlin.test.assertEquals
import kotlin.test.assertFailsWith
@ -15,13 +16,13 @@ import kotlin.test.assertFailsWith
internal class TestAsmVariables {
@Test
fun testVariable() {
val expr = ByteRing.mstInRing { bindSymbol("x") }.compile()
val expr = MstRing { bindSymbol("x") }.compileToExpression(ByteRing)
assertEquals(1.toByte(), expr("x" to 1.toByte()))
}
@Test
fun testUndefinedVariableFails() {
val expr = ByteRing.mstInRing { bindSymbol("x") }.compile()
val expr = MstRing { bindSymbol("x") }.compileToExpression(ByteRing)
assertFailsWith<NoSuchElementException> { expr() }
}
}

5
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/ParserPrecedenceTest.kt
View File

@ -5,13 +5,14 @@
package space.kscience.kmath.ast
import space.kscience.kmath.expressions.evaluate
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.Field
import space.kscience.kmath.operations.RealField
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()))

13
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/ParserTest.kt
View File

@ -7,9 +7,12 @@ package space.kscience.kmath.ast
import space.kscience.kmath.complex.Complex
import space.kscience.kmath.complex.ComplexField
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.expressions.MstField
import space.kscience.kmath.expressions.evaluate
import space.kscience.kmath.expressions.interpret
import space.kscience.kmath.operations.Algebra
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import kotlin.test.Test
import kotlin.test.assertEquals
@ -23,7 +26,7 @@ internal class ParserTest {
@Test
fun `evaluate MSTExpression`() {
val res = ComplexField.mstInField { number(2) + number(2) * (number(2) + number(2)) }()
val res = MstField.invoke { number(2) + number(2) * (number(2) + number(2)) }.interpret(ComplexField)
assertEquals(Complex(10.0, 0.0), res)
}
@ -38,14 +41,14 @@ 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 bindSymbol(value: String): String = value
override fun bindSymbolOrNull(value: String): String = value
override fun unaryOperationFunction(operation: String): (arg: String) -> String {
throw NotImplementedError()

100
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/rendering/TestFeatures.kt Normal file
View File

@ -0,0 +1,100 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
import space.kscience.kmath.ast.rendering.TestUtils.testLatex
import space.kscience.kmath.expressions.MST.Numeric
import kotlin.test.Test
internal class TestFeatures {
@Test
fun printSymbolic() = testLatex("x", "x")
@Test
fun printNumeric() {
val num = object : Number() {
override fun toByte(): Byte = throw UnsupportedOperationException()
override fun toChar(): Char = throw UnsupportedOperationException()
override fun toDouble(): Double = throw UnsupportedOperationException()
override fun toFloat(): Float = throw UnsupportedOperationException()
override fun toInt(): Int = throw UnsupportedOperationException()
override fun toLong(): Long = throw UnsupportedOperationException()
override fun toShort(): Short = throw UnsupportedOperationException()
override fun toString(): String = "foo"
}
testLatex(Numeric(num), "foo")
}
@Test
fun prettyPrintFloats() {
testLatex(Numeric(Double.NaN), "NaN")
testLatex(Numeric(Double.POSITIVE_INFINITY), "\\infty")
testLatex(Numeric(Double.NEGATIVE_INFINITY), "-\\infty")
testLatex(Numeric(1.0), "1")
testLatex(Numeric(-1.0), "-1")
testLatex(Numeric(1.42), "1.42")
testLatex(Numeric(-1.42), "-1.42")
testLatex(Numeric(1.1e10), "1.1\\times10^{10}")
testLatex(Numeric(1.1e-10), "1.1\\times10^{-10}")
testLatex(Numeric(-1.1e-10), "-1.1\\times10^{-10}")
testLatex(Numeric(-1.1e10), "-1.1\\times10^{10}")
}
@Test
fun prettyPrintIntegers() {
testLatex(Numeric(42), "42")
testLatex(Numeric(-42), "-42")
}
@Test
fun prettyPrintPi() {
testLatex("pi", "\\pi")
}
@Test
fun binaryPlus() = testLatex("2+2", "2+2")
@Test
fun binaryMinus() = testLatex("2-2", "2-2")
@Test
fun fraction() = testLatex("2/2", "\\frac{2}{2}")
@Test
fun binaryOperator() = testLatex("f(x, y)", "\\operatorname{f}\\left(x,y\\right)")
@Test
fun unaryOperator() = testLatex("f(x)", "\\operatorname{f}\\,\\left(x\\right)")
@Test
fun power() = testLatex("x^y", "x^{y}")
@Test
fun squareRoot() = testLatex("sqrt(x)", "\\sqrt{x}")
@Test
fun exponential() = testLatex("exp(x)", "e^{x}")
@Test
fun multiplication() = testLatex("x*1", "x\\times1")
@Test
fun inverseTrigonometry() {
testLatex("asin(x)", "\\operatorname{sin}^{-1}\\,\\left(x\\right)")
testLatex("asinh(x)", "\\operatorname{sinh}^{-1}\\,\\left(x\\right)")
testLatex("acos(x)", "\\operatorname{cos}^{-1}\\,\\left(x\\right)")
testLatex("acosh(x)", "\\operatorname{cosh}^{-1}\\,\\left(x\\right)")
testLatex("atan(x)", "\\operatorname{tan}^{-1}\\,\\left(x\\right)")
testLatex("atanh(x)", "\\operatorname{tanh}^{-1}\\,\\left(x\\right)")
}
// @Test
// fun unaryPlus() {
// testLatex("+1", "+1")
// testLatex("+1", "++1")
// }
}

73
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/rendering/TestLatex.kt Normal file
View File

@ -0,0 +1,73 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
import space.kscience.kmath.ast.rendering.TestUtils.testLatex
import space.kscience.kmath.expressions.MST
import space.kscience.kmath.operations.GroupOperations
import kotlin.test.Test
internal class TestLatex {
@Test
fun number() = testLatex("42", "42")
@Test
fun symbol() = testLatex("x", "x")
@Test
fun operatorName() = testLatex("sin(1)", "\\operatorname{sin}\\,\\left(1\\right)")
@Test
fun specialSymbol() {
testLatex(MST.Numeric(Double.POSITIVE_INFINITY), "\\infty")
testLatex("pi", "\\pi")
}
@Test
fun operand() {
testLatex("sin(1)", "\\operatorname{sin}\\,\\left(1\\right)")
testLatex("1+1", "1+1")
}
@Test
fun unaryOperator() = testLatex("sin(1)", "\\operatorname{sin}\\,\\left(1\\right)")
@Test
fun unaryPlus() = testLatex(MST.Unary(GroupOperations.PLUS_OPERATION, MST.Numeric(1)), "+1")
@Test
fun unaryMinus() = testLatex("-x", "-x")
@Test
fun radical() = testLatex("sqrt(x)", "\\sqrt{x}")
@Test
fun superscript() = testLatex("x^y", "x^{y}")
@Test
fun subscript() = testLatex(SubscriptSyntax("", SymbolSyntax("x"), NumberSyntax("123")), "x_{123}")
@Test
fun binaryOperator() = testLatex("f(x, y)", "\\operatorname{f}\\left(x,y\\right)")
@Test
fun binaryPlus() = testLatex("x+x", "x+x")
@Test
fun binaryMinus() = testLatex("x-x", "x-x")
@Test
fun fraction() = testLatex("x/x", "\\frac{x}{x}")
@Test
fun radicalWithIndex() = testLatex(RadicalWithIndexSyntax("", SymbolSyntax("x"), SymbolSyntax("y")), "\\sqrt[x]{y}")
@Test
fun multiplication() {
testLatex("x*1", "x\\times1")
testLatex("1*x", "1\\,x")
}
}

92
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/rendering/TestMathML.kt Normal file
View File

@ -0,0 +1,92 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
import space.kscience.kmath.ast.rendering.TestUtils.testMathML
import space.kscience.kmath.expressions.MST
import space.kscience.kmath.operations.GroupOperations
import kotlin.test.Test
internal class TestMathML {
@Test
fun number() = testMathML("42", "<mn>42</mn>")
@Test
fun symbol() = testMathML("x", "<mi>x</mi>")
@Test
fun operatorName() = testMathML(
"sin(1)",
"<mo>sin</mo><mspace width=\"0.167em\"></mspace><mfenced open=\"(\" close=\")\" separators=\"\"><mn>1</mn></mfenced>",
)
@Test
fun specialSymbol() {
testMathML(MST.Numeric(Double.POSITIVE_INFINITY), "<mo>&infin;</mo>")
testMathML("pi", "<mo>&pi;</mo>")
}
@Test
fun operand() {
testMathML(
"sin(1)",
"<mo>sin</mo><mspace width=\"0.167em\"></mspace><mfenced open=\"(\" close=\")\" separators=\"\"><mn>1</mn></mfenced>",
)
testMathML("1+1", "<mn>1</mn><mo>+</mo><mn>1</mn>")
}
@Test
fun unaryOperator() = testMathML(
"sin(1)",
"<mo>sin</mo><mspace width=\"0.167em\"></mspace><mfenced open=\"(\" close=\")\" separators=\"\"><mn>1</mn></mfenced>",
)
@Test
fun unaryPlus() =
testMathML(MST.Unary(GroupOperations.PLUS_OPERATION, MST.Numeric(1)), "<mo>+</mo><mn>1</mn>")
@Test
fun unaryMinus() = testMathML("-x", "<mo>-</mo><mi>x</mi>")
@Test
fun radical() = testMathML("sqrt(x)", "<msqrt><mi>x</mi></msqrt>")
@Test
fun superscript() = testMathML("x^y", "<msup><mrow><mi>x</mi></mrow><mrow><mi>y</mi></mrow></msup>")
@Test
fun subscript() = testMathML(
SubscriptSyntax("", SymbolSyntax("x"), NumberSyntax("123")),
"<msub><mrow><mi>x</mi></mrow><mrow><mn>123</mn></mrow></msub>",
)
@Test
fun binaryOperator() = testMathML(
"f(x, y)",
"<mo>f</mo><mfenced open=\"(\" close=\")\" separators=\"\"><mi>x</mi><mo>,</mo><mi>y</mi></mfenced>",
)
@Test
fun binaryPlus() = testMathML("x+x", "<mi>x</mi><mo>+</mo><mi>x</mi>")
@Test
fun binaryMinus() = testMathML("x-x", "<mi>x</mi><mo>-</mo><mi>x</mi>")
@Test
fun fraction() = testMathML("x/x", "<mfrac><mrow><mi>x</mi></mrow><mrow><mi>x</mi></mrow></mfrac>")
@Test
fun radicalWithIndex() =
testMathML(RadicalWithIndexSyntax("", SymbolSyntax("x"), SymbolSyntax("y")),
"<mroot><mrow><mi>y</mi></mrow><mrow><mi>x</mi></mrow></mroot>")
@Test
fun multiplication() {
testMathML("x*1", "<mi>x</mi><mo>&times;</mo><mn>1</mn>")
testMathML("1*x", "<mn>1</mn><mspace width=\"0.167em\"></mspace><mi>x</mi>")
}
}

33
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/rendering/TestStages.kt Normal file
View File

@ -0,0 +1,33 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
import space.kscience.kmath.ast.rendering.TestUtils.testLatex
import kotlin.test.Test
internal class TestStages {
@Test
fun betterMultiplication() {
testLatex("a*1", "a\\times1")
testLatex("1*(2/3)", "1\\times\\left(\\frac{2}{3}\\right)")
testLatex("1*1", "1\\times1")
testLatex("2e10", "2\\times10^{10}")
testLatex("2*x", "2\\,x")
testLatex("2*(x+1)", "2\\,\\left(x+1\\right)")
testLatex("x*y", "x\\,y")
}
@Test
fun parentheses() {
testLatex("(x+1)", "x+1")
testLatex("x*x*x", "x\\,x\\,x")
testLatex("(x+x)*x", "\\left(x+x\\right)\\,x")
testLatex("x+x*x", "x+x\\,x")
testLatex("x+x^x*x+x", "x+x^{x}\\,x+x")
testLatex("(x+x)^x+x*x", "\\left(x+x\\right)^{x}+x\\,x")
testLatex("x^(x+x)", "x^{x+x}")
}
}

46
kmath-ast/src/jvmTest/kotlin/space/kscience/kmath/ast/rendering/TestUtils.kt Normal file
View File

@ -0,0 +1,46 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.ast.rendering
import space.kscience.kmath.ast.parseMath
import space.kscience.kmath.expressions.MST
import kotlin.test.assertEquals
internal object TestUtils {
private fun mathSyntax(mst: MST) = FeaturedMathRendererWithPostProcess.Default.render(mst)
private fun latex(mst: MST) = LatexSyntaxRenderer.renderWithStringBuilder(mathSyntax(mst))
private fun mathML(mst: MST) = MathMLSyntaxRenderer.renderWithStringBuilder(mathSyntax(mst))
internal fun testLatex(mst: MST, expectedLatex: String) = assertEquals(
expected = expectedLatex,
actual = latex(mst),
)
internal fun testLatex(expression: String, expectedLatex: String) = assertEquals(
expected = expectedLatex,
actual = latex(expression.parseMath()),
)
internal fun testLatex(expression: MathSyntax, expectedLatex: String) = assertEquals(
expected = expectedLatex,
actual = LatexSyntaxRenderer.renderWithStringBuilder(expression),
)
internal fun testMathML(mst: MST, expectedMathML: String) = assertEquals(
expected = "<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow>$expectedMathML</mrow></math>",
actual = mathML(mst),
)
internal fun testMathML(expression: String, expectedMathML: String) = assertEquals(
expected = "<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow>$expectedMathML</mrow></math>",
actual = mathML(expression.parseMath()),
)
internal fun testMathML(expression: MathSyntax, expectedMathML: String) = assertEquals(
expected = "<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow>$expectedMathML</mrow></math>",
actual = MathMLSyntaxRenderer.renderWithStringBuilder(expression),
)
}

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

@ -4,7 +4,8 @@
*/
plugins {
id("ru.mipt.npm.gradle.jvm")
kotlin("jvm")
id("ru.mipt.npm.gradle.common")
}
description = "Commons math binding for kmath"
@ -17,6 +18,6 @@ dependencies {
api("org.apache.commons:commons-math3:3.6.1")
}
readme{
readme {
maturity = ru.mipt.npm.gradle.Maturity.EXPERIMENTAL
}

24
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpression.kt
View File

@ -7,6 +7,7 @@ package space.kscience.kmath.commons.expressions
import org.apache.commons.math3.analysis.differentiation.DerivativeStructure
import space.kscience.kmath.expressions.*
import space.kscience.kmath.misc.Symbol
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.ExtendedField
import space.kscience.kmath.operations.NumbersAddOperations
@ -28,7 +29,7 @@ public class DerivativeStructureField(
public override val zero: DerivativeStructure by lazy { DerivativeStructure(numberOfVariables, order) }
public override val one: DerivativeStructure by lazy { DerivativeStructure(numberOfVariables, order, 1.0) }
override fun number(value: Number): DerivativeStructure = const(value.toDouble())
public override fun number(value: Number): DerivativeStructure = const(value.toDouble())
/**
* A class that implements both [DerivativeStructure] and a [Symbol]
@ -39,10 +40,10 @@ public class DerivativeStructureField(
symbol: Symbol,
value: Double,
) : DerivativeStructure(size, order, index, value), Symbol {
override val identity: String = symbol.identity
override fun toString(): String = identity
override fun equals(other: Any?): Boolean = this.identity == (other as? Symbol)?.identity
override fun hashCode(): Int = identity.hashCode()
public override val identity: String = symbol.identity
public override fun toString(): String = identity
public override fun equals(other: Any?): Boolean = this.identity == (other as? Symbol)?.identity
public override fun hashCode(): Int = identity.hashCode()
}
/**
@ -52,13 +53,13 @@ public class DerivativeStructureField(
key.identity to DerivativeStructureSymbol(numberOfVariables, index, key, value)
}.toMap()
override fun const(value: Double): DerivativeStructure = DerivativeStructure(numberOfVariables, order, value)
public override fun const(value: Double): DerivativeStructure = DerivativeStructure(numberOfVariables, order, value)
public override fun bindSymbolOrNull(symbol: Symbol): DerivativeStructureSymbol? = variables[symbol.identity]
public override fun bindSymbolOrNull(value: String): DerivativeStructureSymbol? = variables[value]
public override fun bindSymbol(value: String): DerivativeStructureSymbol = variables.getValue(value)
public fun bind(symbol: Symbol): DerivativeStructureSymbol = variables.getValue(symbol.identity)
override fun bindSymbol(value: String): DerivativeStructureSymbol = bind(StringSymbol(value))
public fun bindSymbolOrNull(symbol: Symbol): DerivativeStructureSymbol? = variables[symbol.identity]
public fun bindSymbol(symbol: Symbol): DerivativeStructureSymbol = variables.getValue(symbol.identity)
public fun DerivativeStructure.derivative(symbols: List<Symbol>): Double {
require(symbols.size <= order) { "The order of derivative ${symbols.size} exceeds computed order $order" }
@ -68,7 +69,7 @@ public class DerivativeStructureField(
public fun DerivativeStructure.derivative(vararg symbols: Symbol): Double = derivative(symbols.toList())
override fun DerivativeStructure.unaryMinus(): DerivativeStructure = negate()
public override fun DerivativeStructure.unaryMinus(): DerivativeStructure = negate()
public override fun add(a: DerivativeStructure, b: DerivativeStructure): DerivativeStructure = a.add(b)
@ -111,7 +112,6 @@ public class DerivativeStructureField(
}
}
/**
* A constructs that creates a derivative structure with required order on-demand
*/

97
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt Normal file
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@ -0,0 +1,97 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
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) +
IntegrandCallsPerformed(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)) }
}

83
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt Normal file
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@ -0,0 +1,83 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
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) + IntegrandCallsPerformed(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!!
}
}

32
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt
View File

@ -8,9 +8,9 @@ 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.NDStructure
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.structures.RealBuffer
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
@ -19,17 +19,9 @@ public class CMMatrix(public val origin: RealMatrix) : Matrix<Double> {
public override val colNum: Int get() = origin.columnDimension
public override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
override fun equals(other: Any?): Boolean {
if (this === other) return true
if (other !is NDStructure<*>) return false
return NDStructure.contentEquals(this, other)
}
override fun hashCode(): Int = origin.hashCode()
}
public inline class CMVector(public val origin: RealVector) : Point<Double> {
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)
@ -39,15 +31,15 @@ public inline class CMVector(public val origin: RealVector) : Point<Double> {
public fun RealVector.toPoint(): CMVector = CMVector(this)
public object CMLinearSpace : LinearSpace<Double, RealField> {
override val elementAlgebra: RealField get() = RealField
public object CMLinearSpace : LinearSpace<Double, DoubleField> {
override val elementAlgebra: DoubleField get() = DoubleField
public override fun buildMatrix(
rows: Int,
columns: Int,
initializer: RealField.(i: Int, j: Int) -> Double,
initializer: DoubleField.(i: Int, j: Int) -> Double,
): CMMatrix {
val array = Array(rows) { i -> DoubleArray(columns) { j -> RealField.initializer(i, j) } }
val array = Array(rows) { i -> DoubleArray(columns) { j -> DoubleField.initializer(i, j) } }
return CMMatrix(Array2DRowRealMatrix(array))
}
@ -69,8 +61,8 @@ public object CMLinearSpace : LinearSpace<Double, RealField> {
internal fun RealMatrix.wrap(): CMMatrix = CMMatrix(this)
internal fun RealVector.wrap(): CMVector = CMVector(this)
override fun buildVector(size: Int, initializer: RealField.(Int) -> Double): Point<Double> =
ArrayRealVector(DoubleArray(size) { RealField.initializer(it) }).wrap()
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()
@ -103,7 +95,7 @@ public object CMLinearSpace : LinearSpace<Double, RealField> {
v * this
@UnstableKMathAPI
override fun <F : Any> getFeature(structure: Matrix<Double>, type: KClass<F>): F? {
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 }
@ -140,7 +132,7 @@ public object CMLinearSpace : LinearSpace<Double, RealField> {
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) }
override val singularValues: Point<Double> by lazy { DoubleBuffer(sv.singularValues) }
}
else -> null
}?.let(type::cast)

8
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt
View File

@ -19,7 +19,7 @@ public enum class CMDecomposition {
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
@ -31,16 +31,16 @@ public fun CMLinearSpace.solver(
public fun CMLinearSpace.solve(
a: Matrix<Double>,
b: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
decomposition: CMDecomposition = CMDecomposition.LUP,
): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).wrap()
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 CMLinearSpace.inverse(
a: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
decomposition: CMDecomposition = CMDecomposition.LUP,
): CMMatrix = solver(a, decomposition).inverse.wrap()

60
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimizationProblem.kt → kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimization.kt
View File

@ -14,22 +14,36 @@ 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.*
import space.kscience.kmath.stat.OptimizationFeature
import space.kscience.kmath.stat.OptimizationProblem
import space.kscience.kmath.stat.OptimizationProblemFactory
import space.kscience.kmath.stat.OptimizationResult
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
@ -45,7 +59,7 @@ 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)
@ -53,8 +67,8 @@ 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 ->
@ -62,8 +76,8 @@ public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
}
}
addOptimizationData(gradientFunction)
if (optimizatorBuilder == null) {
optimizatorBuilder = {
if (optimizerBuilder == null) {
optimizerBuilder = {
NonLinearConjugateGradientOptimizer(
NonLinearConjugateGradientOptimizer.Formula.FLETCHER_REEVES,
convergenceChecker
@ -75,8 +89,8 @@ 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) }
}
}
@ -89,7 +103,7 @@ public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
}
public fun optimizer(block: () -> MultivariateOptimizer) {
optimizatorBuilder = block
optimizerBuilder = block
}
override fun update(result: OptimizationResult<Double>) {
@ -97,19 +111,19 @@ 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())

37
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/cmFit.kt
View File

@ -6,21 +6,21 @@
package space.kscience.kmath.commons.optimization
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.expressions.Symbol
import space.kscience.kmath.stat.Fitting
import space.kscience.kmath.stat.OptimizationResult
import space.kscience.kmath.stat.optimizeWith
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>,
@ -30,7 +30,7 @@ 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>,
@ -48,25 +48,26 @@ 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()
}
}

19
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/transform/Transformations.kt
View File

@ -15,6 +15,7 @@ import space.kscience.kmath.streaming.spread
import space.kscience.kmath.structures.*
/**
* Streaming and buffer transformations
*/
@ -22,7 +23,7 @@ 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) }
@ -38,34 +39,34 @@ 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()
}
@ -77,7 +78,7 @@ 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) }
@ -87,7 +88,7 @@ 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)
@ -101,7 +102,7 @@ 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()
/**

12
kmath-commons/src/test/kotlin/space/kscience/kmath/commons/expressions/DerivativeStructureExpressionTest.kt
View File

@ -5,7 +5,11 @@
package space.kscience.kmath.commons.expressions
import space.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
@ -28,14 +32,14 @@ internal class AutoDiffTest {
@Test
fun derivativeStructureFieldTest() {
diff(2, x to 1.0, y to 1.0) {
val x = bind(x)//by binding()
val x = bindSymbol(x)//by binding()
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) }
}
}

35
kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt Normal file
View File

@ -0,0 +1,35 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
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 }
}
}

27
kmath-commons/src/test/kotlin/space/kscience/kmath/commons/optimization/OptimizeTest.kt
View File

@ -5,21 +5,22 @@
package space.kscience.kmath.commons.optimization
import org.junit.jupiter.api.Test
import kotlinx.coroutines.runBlocking
import space.kscience.kmath.commons.expressions.DerivativeStructureExpression
import space.kscience.kmath.expressions.symbol
import space.kscience.kmath.stat.Distribution
import space.kscience.kmath.stat.Fitting
import space.kscience.kmath.distributions.NormalDistribution
import space.kscience.kmath.misc.symbol
import space.kscience.kmath.optimization.FunctionOptimization
import space.kscience.kmath.stat.RandomGenerator
import space.kscience.kmath.stat.normal
import kotlin.math.pow
import kotlin.test.Test
internal class OptimizeTest {
val x by symbol
val y by symbol
val normal = DerivativeStructureExpression {
exp(-bind(x).pow(2) / 2) + exp(-bind(y).pow(2) / 2)
exp(-bindSymbol(x).pow(2) / 2) + exp(-bindSymbol(y)
.pow(2) / 2)
}
@Test
@ -39,35 +40,35 @@ internal class OptimizeTest {
simplexSteps(x to 2.0, y to 0.5)
//this sets simplex optimizer
}
println(result.point)
println(result.value)
}
@Test
fun testCmFit() {
fun testCmFit() = runBlocking {
val a by symbol
val b by symbol
val c by symbol
val sigma = 1.0
val generator = Distribution.normal(0.0, sigma)
val generator = NormalDistribution(0.0, sigma)
val chain = generator.sample(RandomGenerator.default(112667))
val x = (1..100).map(Int::toDouble)
val y = x.map {
it.pow(2) + it + 1 + chain.nextDouble()
it.pow(2) + it + 1 + chain.next()
}
val yErr = List(x.size) { sigma }
val chi2 = Fitting.chiSquared(x, y, yErr) { x1 ->
val chi2 = FunctionOptimization.chiSquared(x, y, yErr) { x1 ->
val cWithDefault = bindSymbolOrNull(c) ?: one
bind(a) * x1.pow(2) + bind(b) * x1 + cWithDefault
bindSymbol(a) * x1.pow(2) + bindSymbol(b) * x1 + cWithDefault
}
val result = chi2.minimize(a to 1.5, b to 0.9, c to 1.0)
println(result)
println("Chi2/dof = ${result.value / (x.size - 3)}")
}
}
}

70
kmath-complex/README.md
View File

@ -1,42 +1,36 @@
# The Core Module (`kmath-core`)
# Module kmath-complex
Complex and hypercomplex number systems in KMath:
Complex and hypercomplex number systems in KMath.
- [complex](src/commonMain/kotlin/kscience/kmath/complex/Complex.kt) : Complex Numbers
- [quaternion](src/commonMain/kotlin/kscience/kmath/complex/Quaternion.kt) : Quaternions
- [complex](src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt) : Complex Numbers
- [quaternion](src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt) : Quaternions
> #### Artifact:
>
> This module artifact: `space.kscience:kmath-complex:0.3.0-dev-2`.
>
> Bintray release version: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-complex/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-complex/_latestVersion)
>
> Bintray development version: [ ![Download](https://api.bintray.com/packages/mipt-npm/dev/kmath-complex/images/download.svg) ](https://bintray.com/mipt-npm/dev/kmath-complex/_latestVersion)
>
> **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-complex:0.3.0-dev-2'
> }
> ```
> **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-complex:0.3.0-dev-2")
> }
> ```
## Artifact:
The Maven coordinates of this project are `space.kscience:kmath-complex:0.3.0-dev-6`.
**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-complex:0.3.0-dev-6'
}
```
**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-complex:0.3.0-dev-6")
}
```

11
kmath-complex/build.gradle.kts
View File

@ -1,12 +1,13 @@
import ru.mipt.npm.gradle.Maturity
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
import ru.mipt.npm.gradle.Maturity
plugins {
id("ru.mipt.npm.gradle.mpp")
kotlin("multiplatform")
id("ru.mipt.npm.gradle.common")
id("ru.mipt.npm.gradle.native")
}
@ -30,12 +31,12 @@ readme {
feature(
id = "complex",
description = "Complex Numbers",
ref = "src/commonMain/kotlin/kscience/kmath/complex/Complex.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt"
)
feature(
id = "quaternion",
description = "Quaternions",
ref = "src/commonMain/kotlin/kscience/kmath/complex/Quaternion.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt"
)
}

4
kmath-complex/docs/README-TEMPLATE.md
View File

@ -1,6 +1,6 @@
# The Core Module (`kmath-core`)
# Module kmath-complex
Complex and hypercomplex number systems in KMath:
Complex and hypercomplex number systems in KMath.
${features}

11
kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Complex.kt
View File

@ -126,8 +126,8 @@ public object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex>, Num
/**
* Adds complex number to real one.
*
* @receiver the addend.
* @param c the augend.
* @receiver the augend.
* @param c the addend.
* @return the sum.
*/
public operator fun Double.plus(c: Complex): Complex = add(this.toComplex(), c)
@ -144,8 +144,8 @@ public object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex>, Num
/**
* Adds real number to complex one.
*
* @receiver the addend.
* @param d the augend.
* @receiver the augend.
* @param d the addend.
* @return the sum.
*/
public operator fun Complex.plus(d: Double): Complex = d + this
@ -170,8 +170,7 @@ public object ComplexField : ExtendedField<Complex>, Norm<Complex, Complex>, Num
public override fun norm(arg: Complex): Complex = sqrt(arg.conjugate * arg)
public override fun bindSymbol(value: String): Complex =
if (value == "i") i else super<ExtendedField>.bindSymbol(value)
public override fun bindSymbolOrNull(value: String): Complex? = if (value == "i") i else null
}
/**

124
kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexFieldND.kt Normal file
View File

@ -0,0 +1,124 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.complex
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.AlgebraND
import space.kscience.kmath.nd.BufferND
import space.kscience.kmath.nd.BufferedFieldND
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.operations.ExtendedField
import space.kscience.kmath.operations.NumbersAddOperations
import space.kscience.kmath.structures.Buffer
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
/**
* An optimized nd-field for complex numbers
*/
@OptIn(UnstableKMathAPI::class)
public class ComplexFieldND(
shape: IntArray,
) : BufferedFieldND<Complex, ComplexField>(shape, ComplexField, Buffer.Companion::complex),
NumbersAddOperations<StructureND<Complex>>,
ExtendedField<StructureND<Complex>> {
public override val zero: BufferND<Complex> by lazy { produce { zero } }
public override val one: BufferND<Complex> by lazy { produce { one } }
public override fun number(value: Number): BufferND<Complex> {
val d = value.toComplex() // minimize conversions
return produce { d }
}
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun map(
// arg: AbstractNDBuffer<Double>,
// transform: DoubleField.(Double) -> Double,
// ): RealNDElement {
// check(arg)
// val array = RealBuffer(arg.strides.linearSize) { offset -> DoubleField.transform(arg.buffer[offset]) }
// return BufferedNDFieldElement(this, array)
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun produce(initializer: DoubleField.(IntArray) -> Double): RealNDElement {
// val array = RealBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) }
// return BufferedNDFieldElement(this, array)
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun mapIndexed(
// arg: AbstractNDBuffer<Double>,
// transform: DoubleField.(index: IntArray, Double) -> Double,
// ): RealNDElement {
// check(arg)
// return BufferedNDFieldElement(
// this,
// RealBuffer(arg.strides.linearSize) { offset ->
// elementContext.transform(
// arg.strides.index(offset),
// arg.buffer[offset]
// )
// })
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun combine(
// a: AbstractNDBuffer<Double>,
// b: AbstractNDBuffer<Double>,
// transform: DoubleField.(Double, Double) -> Double,
// ): RealNDElement {
// check(a, b)
// val buffer = RealBuffer(strides.linearSize) { offset ->
// elementContext.transform(a.buffer[offset], b.buffer[offset])
// }
// return BufferedNDFieldElement(this, buffer)
// }
public override fun power(arg: StructureND<Complex>, pow: Number): BufferND<Complex> = arg.map { power(it, pow) }
public override fun exp(arg: StructureND<Complex>): BufferND<Complex> = arg.map { exp(it) }
public override fun ln(arg: StructureND<Complex>): BufferND<Complex> = arg.map { ln(it) }
public override fun sin(arg: StructureND<Complex>): BufferND<Complex> = arg.map { sin(it) }
public override fun cos(arg: StructureND<Complex>): BufferND<Complex> = arg.map { cos(it) }
public override fun tan(arg: StructureND<Complex>): BufferND<Complex> = arg.map { tan(it) }
public override fun asin(arg: StructureND<Complex>): BufferND<Complex> = arg.map { asin(it) }
public override fun acos(arg: StructureND<Complex>): BufferND<Complex> = arg.map { acos(it) }
public override fun atan(arg: StructureND<Complex>): BufferND<Complex> = arg.map { atan(it) }
public override fun sinh(arg: StructureND<Complex>): BufferND<Complex> = arg.map { sinh(it) }
public override fun cosh(arg: StructureND<Complex>): BufferND<Complex> = arg.map { cosh(it) }
public override fun tanh(arg: StructureND<Complex>): BufferND<Complex> = arg.map { tanh(it) }
public override fun asinh(arg: StructureND<Complex>): BufferND<Complex> = arg.map { asinh(it) }
public override fun acosh(arg: StructureND<Complex>): BufferND<Complex> = arg.map { acosh(it) }
public override fun atanh(arg: StructureND<Complex>): BufferND<Complex> = arg.map { atanh(it) }
}
/**
* Fast element production using function inlining
*/
public inline fun BufferedFieldND<Complex, ComplexField>.produceInline(initializer: ComplexField.(Int) -> Complex): BufferND<Complex> {
contract { callsInPlace(initializer, InvocationKind.EXACTLY_ONCE) }
val buffer = Buffer.complex(strides.linearSize) { offset -> ComplexField.initializer(offset) }
return BufferND(strides, buffer)
}
public fun AlgebraND.Companion.complex(vararg shape: Int): ComplexFieldND = ComplexFieldND(shape)
/**
* Produce a context for n-dimensional operations inside this real field
*/
public inline fun <R> ComplexField.nd(vararg shape: Int, action: ComplexFieldND.() -> R): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return ComplexFieldND(shape).action()
}

124
kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/ComplexNDField.kt
View File

@ -1,124 +0,0 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.complex
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.BufferedNDField
import space.kscience.kmath.nd.NDAlgebra
import space.kscience.kmath.nd.NDBuffer
import space.kscience.kmath.nd.NDStructure
import space.kscience.kmath.operations.ExtendedField
import space.kscience.kmath.operations.NumbersAddOperations
import space.kscience.kmath.structures.Buffer
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
/**
* An optimized nd-field for complex numbers
*/
@OptIn(UnstableKMathAPI::class)
public class ComplexNDField(
shape: IntArray,
) : BufferedNDField<Complex, ComplexField>(shape, ComplexField, Buffer.Companion::complex),
NumbersAddOperations<NDStructure<Complex>>,
ExtendedField<NDStructure<Complex>> {
override val zero: NDBuffer<Complex> by lazy { produce { zero } }
override val one: NDBuffer<Complex> by lazy { produce { one } }
override fun number(value: Number): NDBuffer<Complex> {
val d = value.toComplex() // minimize conversions
return produce { d }
}
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun map(
// arg: AbstractNDBuffer<Double>,
// transform: RealField.(Double) -> Double,
// ): RealNDElement {
// check(arg)
// val array = RealBuffer(arg.strides.linearSize) { offset -> RealField.transform(arg.buffer[offset]) }
// return BufferedNDFieldElement(this, array)
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun produce(initializer: RealField.(IntArray) -> Double): RealNDElement {
// val array = RealBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) }
// return BufferedNDFieldElement(this, array)
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun mapIndexed(
// arg: AbstractNDBuffer<Double>,
// transform: RealField.(index: IntArray, Double) -> Double,
// ): RealNDElement {
// check(arg)
// return BufferedNDFieldElement(
// this,
// RealBuffer(arg.strides.linearSize) { offset ->
// elementContext.transform(
// arg.strides.index(offset),
// arg.buffer[offset]
// )
// })
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun combine(
// a: AbstractNDBuffer<Double>,
// b: AbstractNDBuffer<Double>,
// transform: RealField.(Double, Double) -> Double,
// ): RealNDElement {
// check(a, b)
// val buffer = RealBuffer(strides.linearSize) { offset ->
// elementContext.transform(a.buffer[offset], b.buffer[offset])
// }
// return BufferedNDFieldElement(this, buffer)
// }
override fun power(arg: NDStructure<Complex>, pow: Number): NDBuffer<Complex> = arg.map { power(it, pow) }
override fun exp(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { exp(it) }
override fun ln(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { ln(it) }
override fun sin(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { sin(it) }
override fun cos(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { cos(it) }
override fun tan(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { tan(it) }
override fun asin(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { asin(it) }
override fun acos(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { acos(it) }
override fun atan(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { atan(it) }
override fun sinh(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { sinh(it) }
override fun cosh(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { cosh(it) }
override fun tanh(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { tanh(it) }
override fun asinh(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { asinh(it) }
override fun acosh(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { acosh(it) }
override fun atanh(arg: NDStructure<Complex>): NDBuffer<Complex> = arg.map { atanh(it) }
}
/**
* Fast element production using function inlining
*/
public inline fun BufferedNDField<Complex, ComplexField>.produceInline(initializer: ComplexField.(Int) -> Complex): NDBuffer<Complex> {
contract { callsInPlace(initializer, InvocationKind.EXACTLY_ONCE) }
val buffer = Buffer.complex(strides.linearSize) { offset -> ComplexField.initializer(offset) }
return NDBuffer(strides, buffer)
}
public fun NDAlgebra.Companion.complex(vararg shape: Int): ComplexNDField = ComplexNDField(shape)
/**
* Produce a context for n-dimensional operations inside this real field
*/
public inline fun <R> ComplexField.nd(vararg shape: Int, action: ComplexNDField.() -> R): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return ComplexNDField(shape).action()
}

6
kmath-complex/src/commonMain/kotlin/space/kscience/kmath/complex/Quaternion.kt
View File

@ -170,14 +170,14 @@ public object QuaternionField : Field<Quaternion>, Norm<Quaternion, Quaternion>,
public override fun Quaternion.unaryMinus(): Quaternion = Quaternion(-w, -x, -y, -z)
public override fun norm(arg: Quaternion): Quaternion = sqrt(arg.conjugate * arg)
public override fun bindSymbol(value: String): Quaternion = when (value) {
public override fun bindSymbolOrNull(value: String): Quaternion? = when (value) {
"i" -> i
"j" -> j
"k" -> k
else -> super<Field>.bindSymbol(value)
else -> null
}
override fun number(value: Number): Quaternion =value.toQuaternion()
override fun number(value: Number): Quaternion = value.toQuaternion()
public override fun sinh(arg: Quaternion): Quaternion = (exp(arg) - exp(-arg)) / 2.0
public override fun cosh(arg: Quaternion): Quaternion = (exp(arg) + exp(-arg)) / 2.0

4
kmath-complex/src/commonTest/kotlin/space/kscience/kmath/complex/ExpressionFieldForComplexTest.kt
View File

@ -6,9 +6,9 @@
package space.kscience.kmath.complex
import space.kscience.kmath.expressions.FunctionalExpressionField
import space.kscience.kmath.expressions.bindSymbol
import space.kscience.kmath.expressions.invoke
import space.kscience.kmath.expressions.symbol
import space.kscience.kmath.misc.symbol
import space.kscience.kmath.operations.bindSymbol
import kotlin.test.Test
import kotlin.test.assertEquals

80
kmath-core/README.md
View File

@ -1,49 +1,43 @@
# The Core Module (`kmath-core`)
# Module kmath-core
The core features of KMath:
The core interfaces of KMath.
- [algebras](src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt) : Algebraic structures like rings, spaces and fields.
- [nd](src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt) : Many-dimensional structures and operations on them.
- [linear](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](src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
- [expressions](src/commonMain/kotlin/kscience/kmath/expressions) : By writing a single mathematical expression once, users will be able to apply different types of
- [algebras](src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt) : Algebraic structures like rings, spaces and fields.
- [nd](src/commonMain/kotlin/space/kscience/kmath/structures/StructureND.kt) : Many-dimensional structures and operations on them.
- [linear](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](src/commonMain/kotlin/space/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
- [expressions](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](src/commonMain/kotlin/kscience/kmath/domains) : Domains
- [autodif](src/commonMain/kotlin/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation
- [domains](src/commonMain/kotlin/space/kscience/kmath/domains) : Domains
- [autodif](src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt) : Automatic differentiation
> #### Artifact:
>
> This module artifact: `space.kscience:kmath-core:0.3.0-dev-2`.
>
> Bintray release version: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-core/_latestVersion)
>
> Bintray development version: [ ![Download](https://api.bintray.com/packages/mipt-npm/dev/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/dev/kmath-core/_latestVersion)
>
> **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-core:0.3.0-dev-2'
> }
> ```
> **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-core:0.3.0-dev-2")
> }
> ```
## Artifact:
The Maven coordinates of this project are `space.kscience:kmath-core:0.3.0-dev-6`.
**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-core:0.3.0-dev-6'
}
```
**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-core:0.3.0-dev-6")
}
```

2065
kmath-core/api/kmath-core.api
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17
kmath-core/build.gradle.kts
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@ -6,7 +6,8 @@
import ru.mipt.npm.gradle.Maturity
plugins {
id("ru.mipt.npm.gradle.mpp")
kotlin("multiplatform")
id("ru.mipt.npm.gradle.common")
id("ru.mipt.npm.gradle.native")
}
@ -28,13 +29,13 @@ readme {
description = """
Algebraic structures like rings, spaces and fields.
""".trimIndent(),
ref = "src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt"
)
feature(
id = "nd",
description = "Many-dimensional structures and operations on them.",
ref = "src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/structures/StructureND.kt"
)
feature(
@ -42,13 +43,13 @@ readme {
description = """
Basic linear algebra operations (sums, products, etc.), backed by the `Space` API. Advanced linear algebra operations like matrix inversion and LU decomposition.
""".trimIndent(),
ref = "src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/operations/Algebra.kt"
)
feature(
id = "buffers",
description = "One-dimensional structure",
ref = "src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/structures/Buffers.kt"
)
feature(
@ -58,18 +59,18 @@ readme {
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.
""".trimIndent(),
ref = "src/commonMain/kotlin/kscience/kmath/expressions"
ref = "src/commonMain/kotlin/space/kscience/kmath/expressions"
)
feature(
id = "domains",
description = "Domains",
ref = "src/commonMain/kotlin/kscience/kmath/domains"
ref = "src/commonMain/kotlin/space/kscience/kmath/domains"
)
feature(
id = "autodif",
description = "Automatic differentiation",
ref = "src/commonMain/kotlin/kscience/kmath/expressions/SimpleAutoDiff.kt"
ref = "src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt"
)
}

4
kmath-core/docs/README-TEMPLATE.md
View File

@ -1,6 +1,6 @@
# The Core Module (`kmath-core`)
# Module kmath-core
The core features of KMath:
The core interfaces of KMath.
${features}

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