teldufalsari/kmath
2
0
Fork 0
forked from kscience/kmath
Code Pull Requests 1 Activity

Rewrite EJML module by dropping ejml-simple abstraction level; multiple build script changes

Browse Source
This commit is contained in:
Iaroslav Postovalov 2021-04-28 18:03:28 +07:00
parent 0f786e4f6f
commit 598b2e1587
No known key found for this signature in database
GPG Key ID: 46E15E4A31B3BCD7
23 changed files with 281 additions and 249 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
.github/workflows/pages.yml vendored
View File

@ -30,9 +30,7 @@ jobs:
restore-keys: |
${{ runner.os }}-gradle-
- name: Build
run: |
./gradlew dokkaHtmlMultiModule --no-daemon --no-parallel --stacktrace
mv build/dokka/htmlMultiModule/-modules.html build/dokka/htmlMultiModule/index.html
run: ./gradlew dokkaHtmlMultiModule --no-daemon --no-parallel --stacktrace
- name: Deploy to GitHub Pages
uses: JamesIves/github-pages-deploy-action@4.1.0
with:

3
CHANGELOG.md
View File

@ -10,7 +10,7 @@
- Blocking chains and Statistics
- Multiplatform integration
- Integration for any Field element
- Extendend operations for ND4J fields
- Extended operations for ND4J fields
### Changed
- Exponential operations merged with hyperbolic functions
@ -24,6 +24,7 @@
- Redesign MST. Remove MSTExpression.
- Move MST to core
- Separated benchmarks and examples
- Rewritten EJML module without ejml-simple
### Deprecated

6
benchmarks/build.gradle.kts
View File

@ -9,14 +9,10 @@ sourceSets.register("benchmarks")
repositories {
mavenCentral()
jcenter()
maven("https://repo.kotlin.link")
maven("https://clojars.org/repo")
maven("https://dl.bintray.com/egor-bogomolov/astminer/")
maven("https://dl.bintray.com/hotkeytlt/maven")
maven("https://jitpack.io")
maven {
setUrl("http://logicrunch.research.it.uu.se/maven/")
maven("http://logicrunch.research.it.uu.se/maven") {
isAllowInsecureProtocol = true
}
}

10
benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt
View File

@ -10,7 +10,7 @@ import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.commons.linear.CMLinearSpace
import space.kscience.kmath.ejml.EjmlLinearSpace
import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.invoke
import space.kscience.kmath.operations.DoubleField
@ -29,8 +29,8 @@ internal class DotBenchmark {
val cmMatrix1 = CMLinearSpace { matrix1.toCM() }
val cmMatrix2 = CMLinearSpace { matrix2.toCM() }
val ejmlMatrix1 = EjmlLinearSpace { matrix1.toEjml() }
val ejmlMatrix2 = EjmlLinearSpace { matrix2.toEjml() }
val ejmlMatrix1 = EjmlLinearSpaceDDRM { matrix1.toEjml() }
val ejmlMatrix2 = EjmlLinearSpaceDDRM { matrix2.toEjml() }
}
@Benchmark
@ -42,14 +42,14 @@ internal class DotBenchmark {
@Benchmark
fun ejmlDot(blackhole: Blackhole) {
EjmlLinearSpace {
EjmlLinearSpaceDDRM {
blackhole.consume(ejmlMatrix1 dot ejmlMatrix2)
}
}
@Benchmark
fun ejmlDotWithConversion(blackhole: Blackhole) {
EjmlLinearSpace {
EjmlLinearSpaceDDRM {
blackhole.consume(matrix1 dot matrix2)
}
}

21
benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt
View File

@ -11,25 +11,26 @@ import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.commons.linear.CMLinearSpace
import space.kscience.kmath.commons.linear.inverse
import space.kscience.kmath.ejml.EjmlLinearSpace
import space.kscience.kmath.ejml.inverse
import space.kscience.kmath.ejml.EjmlLinearSpaceDDRM
import space.kscience.kmath.linear.InverseMatrixFeature
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.inverseWithLup
import space.kscience.kmath.linear.invoke
import space.kscience.kmath.nd.getFeature
import kotlin.random.Random
@State(Scope.Benchmark)
internal class MatrixInverseBenchmark {
companion object {
val random = Random(1224)
const val dim = 100
private companion object {
private val random = Random(1224)
private const val dim = 100
private val space = LinearSpace.real
//creating invertible matrix
val u = space.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val l = space.buildMatrix(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
val matrix = space { l dot u }
private val u = space.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
private val l = space.buildMatrix(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
private val matrix = space { l dot u }
}
@Benchmark
@ -46,8 +47,8 @@ internal class MatrixInverseBenchmark {
@Benchmark
fun ejmlInverse(blackhole: Blackhole) {
with(EjmlLinearSpace) {
blackhole.consume(inverse(matrix))
with(EjmlLinearSpaceDDRM) {
blackhole.consume(matrix.getFeature<InverseMatrixFeature<Double>>()?.inverse)
}
}
}

30
build.gradle.kts
View File

@ -4,14 +4,12 @@ plugins {
allprojects {
repositories {
jcenter()
maven("https://clojars.org/repo")
maven("https://dl.bintray.com/egor-bogomolov/astminer/")
maven("https://dl.bintray.com/hotkeytlt/maven")
maven("https://jitpack.io")
maven("http://logicrunch.research.it.uu.se/maven/") {
maven("http://logicrunch.research.it.uu.se/maven") {
isAllowInsecureProtocol = true
}
maven("https://maven.pkg.jetbrains.space/public/p/kotlinx-html/maven")
mavenCentral()
}
@ -23,22 +21,16 @@ subprojects {
if (name.startsWith("kmath")) apply<MavenPublishPlugin>()
afterEvaluate {
tasks.withType<org.jetbrains.dokka.gradle.DokkaTask> {
dokkaSourceSets.all {
val readmeFile = File(this@subprojects.projectDir, "./README.md")
if (readmeFile.exists())
includes.setFrom(includes + readmeFile.absolutePath)
tasks.withType<org.jetbrains.dokka.gradle.DokkaTaskPartial> {
dependsOn(tasks.getByName("assemble"))
arrayOf(
"http://ejml.org/javadoc/",
"https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/",
"https://deeplearning4j.org/api/latest/"
).map { java.net.URL("${it}package-list") to java.net.URL(it) }.forEach { (a, b) ->
externalDocumentationLink {
packageListUrl.set(a)
url.set(b)
}
}
dokkaSourceSets.all {
val readmeFile = File(this@subprojects.projectDir, "README.md")
if (readmeFile.exists()) includes.setFrom(includes + readmeFile.absolutePath)
externalDocumentationLink("http://ejml.org/javadoc/")
externalDocumentationLink("https://commons.apache.org/proper/commons-math/javadocs/api-3.6.1/")
externalDocumentationLink("https://deeplearning4j.org/api/latest/")
externalDocumentationLink("https://kotlin.github.io/kotlinx.coroutines/kotlinx-coroutines-core/")
}
}
}

6
docs/templates/ARTIFACT-TEMPLATE.md vendored
View File

@ -6,8 +6,7 @@ The Maven coordinates of this project are `${group}:${name}:${version}`.
```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
mavenCentral()
}
dependencies {
@ -18,8 +17,7 @@ dependencies {
```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
mavenCentral()
}
dependencies {

7
examples/build.gradle.kts
View File

@ -4,14 +4,11 @@ plugins {
repositories {
mavenCentral()
jcenter()
maven("https://repo.kotlin.link")
maven("https://clojars.org/repo")
maven("https://dl.bintray.com/egor-bogomolov/astminer/")
maven("https://dl.bintray.com/hotkeytlt/maven")
maven("https://jitpack.io")
maven{
setUrl("http://logicrunch.research.it.uu.se/maven/")
maven("https://maven.pkg.jetbrains.space/kotlin/p/kotlin/kotlin-js-wrappers")
maven("http://logicrunch.research.it.uu.se/maven") {
isAllowInsecureProtocol = true
}
}

6
kmath-ast/README.md
View File

@ -16,8 +16,7 @@ The Maven coordinates of this project are `space.kscience:kmath-ast:0.3.0-dev-7`
```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
mavenCentral()
}
dependencies {
@ -28,8 +27,7 @@ dependencies {
```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
mavenCentral()
}
dependencies {

6
kmath-complex/README.md
View File

@ -14,8 +14,7 @@ The Maven coordinates of this project are `space.kscience:kmath-complex:0.3.0-de
```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
mavenCentral()
}
dependencies {
@ -26,8 +25,7 @@ dependencies {
```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
mavenCentral()
}
dependencies {

6
kmath-core/README.md
View File

@ -21,8 +21,7 @@ The Maven coordinates of this project are `space.kscience:kmath-core:0.3.0-dev-7
```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
mavenCentral()
}
dependencies {
@ -33,8 +32,7 @@ dependencies {
```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
mavenCentral()
}
dependencies {

12
kmath-ejml/README.md
View File

@ -2,9 +2,9 @@
EJML based linear algebra implementation.
- [ejml-vector](src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt) : The Point implementation using SimpleMatrix.
- [ejml-matrix](src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt) : The Matrix implementation using SimpleMatrix.
- [ejml-linear-space](src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt) : The LinearSpace implementation using SimpleMatrix.
- [ejml-vector](src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt) : Point implementations.
- [ejml-matrix](src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt) : Matrix implementation.
- [ejml-linear-space](src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt) : LinearSpace implementations.
## Artifact:
@ -15,8 +15,7 @@ The Maven coordinates of this project are `space.kscience:kmath-ejml:0.3.0-dev-7
```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
mavenCentral()
}
dependencies {
@ -27,8 +26,7 @@ dependencies {
```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
mavenCentral()
}
dependencies {

8
kmath-ejml/build.gradle.kts
View File

@ -4,7 +4,7 @@ plugins {
}
dependencies {
api("org.ejml:ejml-simple:0.40")
api("org.ejml:ejml-ddense:0.40")
api(project(":kmath-core"))
}
@ -14,19 +14,19 @@ readme {
feature(
id = "ejml-vector",
description = "The Point implementation using SimpleMatrix.",
description = "Point implementations.",
ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt"
)
feature(
id = "ejml-matrix",
description = "The Matrix implementation using SimpleMatrix.",
description = "Matrix implementation.",
ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt"
)
feature(
id = "ejml-linear-space",
description = "The LinearSpace implementation using SimpleMatrix.",
description = "LinearSpace implementations.",
ref = "src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt"
)
}

223
kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt
View File

@ -5,45 +5,71 @@
package space.kscience.kmath.ejml
import org.ejml.data.DMatrix
import org.ejml.data.DMatrixD1
import org.ejml.data.DMatrixRMaj
import org.ejml.dense.row.CommonOps_DDRM
import org.ejml.dense.row.factory.DecompositionFactory_DDRM
import org.ejml.simple.SimpleMatrix
import space.kscience.kmath.linear.*
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.StructureFeature
import space.kscience.kmath.nd.getFeature
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.Ring
import space.kscience.kmath.structures.DoubleBuffer
import kotlin.reflect.KClass
import kotlin.reflect.cast
/**
* Represents context of basic operations operating with [EjmlMatrix].
* [LinearSpace] implementation specialized for a certain EJML type.
*
* @param T the type of items in the matrices.
* @param A the element context type.
* @param M the EJML matrix type.
* @author Iaroslav Postovalov
*/
public abstract class EjmlLinearSpace<T : Any, out A : Ring<T>, M : org.ejml.data.Matrix> : LinearSpace<T, A> {
/**
* Converts this matrix to EJML one.
*/
public abstract fun Matrix<T>.toEjml(): EjmlMatrix<T, M>
/**
* Converts this vector to EJML one.
*/
public abstract fun Point<T>.toEjml(): EjmlVector<T, M>
public abstract override fun buildMatrix(
rows: Int,
columns: Int,
initializer: A.(i: Int, j: Int) -> T,
): EjmlMatrix<T, M>
public abstract override fun buildVector(size: Int, initializer: A.(Int) -> T): EjmlVector<T, M>
}
/**
* [EjmlLinearSpace] implementation based on [CommonOps_DDRM], [DecompositionFactory_DDRM] operations and
* [DMatrixRMaj] matrices.
*
* @author Iaroslav Postovalov
* @author Alexander Nozik
*/
public object EjmlLinearSpace : LinearSpace<Double, DoubleField> {
public object EjmlLinearSpaceDDRM : EjmlLinearSpace<Double, DoubleField, DMatrixRMaj>() {
/**
* The [DoubleField] reference.
*/
public override val elementAlgebra: DoubleField get() = DoubleField
/**
* Converts this matrix to EJML one.
*/
@OptIn(UnstableKMathAPI::class)
public fun Matrix<Double>.toEjml(): EjmlMatrix = when (val matrix = origin) {
is EjmlMatrix -> matrix
@Suppress("UNCHECKED_CAST")
public override fun Matrix<Double>.toEjml(): EjmlDoubleMatrix<DMatrixRMaj> = when {
this is EjmlDoubleMatrix<*> && origin is DMatrixRMaj -> this as EjmlDoubleMatrix<DMatrixRMaj>
else -> buildMatrix(rowNum, colNum) { i, j -> get(i, j) }
}
/**
* Converts this vector to EJML one.
*/
public fun Point<Double>.toEjml(): EjmlVector = when (this) {
is EjmlVector -> this
else -> EjmlVector(SimpleMatrix(size, 1).also {
(0 until it.numRows()).forEach { row -> it[row, 0] = get(row) }
@Suppress("UNCHECKED_CAST")
public override fun Point<Double>.toEjml(): EjmlDoubleVector<DMatrixRMaj> = when {
this is EjmlDoubleVector<*> && origin is DMatrixRMaj -> this as EjmlDoubleVector<DMatrixRMaj>
else -> EjmlDoubleVector(DMatrixRMaj(size, 1).also {
(0 until it.numRows).forEach { row -> it[row, 0] = get(row) }
})
}
@ -51,159 +77,178 @@ public object EjmlLinearSpace : LinearSpace<Double, DoubleField> {
rows: Int,
columns: Int,
initializer: DoubleField.(i: Int, j: Int) -> Double,
): EjmlMatrix = EjmlMatrix(SimpleMatrix(rows, columns).also {
): EjmlDoubleMatrix<DMatrixRMaj> = EjmlDoubleMatrix(DMatrixRMaj(rows, columns).also {
(0 until rows).forEach { row ->
(0 until columns).forEach { col -> it[row, col] = DoubleField.initializer(row, col) }
(0 until columns).forEach { col -> it[row, col] = elementAlgebra.initializer(row, col) }
}
})
public override fun buildVector(size: Int, initializer: DoubleField.(Int) -> Double): Point<Double> =
EjmlVector(SimpleMatrix(size, 1).also {
(0 until it.numRows()).forEach { row -> it[row, 0] = DoubleField.initializer(row) }
public override fun buildVector(
size: Int,
initializer: DoubleField.(Int) -> Double,
): EjmlDoubleVector<DMatrixRMaj> = EjmlDoubleVector(DMatrixRMaj(size, 1).also {
(0 until it.numRows).forEach { row -> it[row, 0] = elementAlgebra.initializer(row) }
})
private fun SimpleMatrix.wrapMatrix() = EjmlMatrix(this)
private fun SimpleMatrix.wrapVector() = EjmlVector(this)
private fun <T : DMatrix> T.wrapMatrix() = EjmlDoubleMatrix(this)
private fun <T : DMatrixD1> T.wrapVector() = EjmlDoubleVector(this)
public override fun Matrix<Double>.unaryMinus(): Matrix<Double> = this * (-1.0)
public override fun Matrix<Double>.dot(other: Matrix<Double>): EjmlMatrix =
EjmlMatrix(toEjml().origin.mult(other.toEjml().origin))
public override fun Matrix<Double>.dot(other: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> {
val out = DMatrixRMaj(1, 1)
CommonOps_DDRM.mult(toEjml().origin, other.toEjml().origin, out)
return out.wrapMatrix()
}
public override fun Matrix<Double>.dot(vector: Point<Double>): EjmlVector =
EjmlVector(toEjml().origin.mult(vector.toEjml().origin))
public override fun Matrix<Double>.dot(vector: Point<Double>): EjmlDoubleVector<DMatrixRMaj> {
val out = DMatrixRMaj(1, 1)
CommonOps_DDRM.mult(toEjml().origin, vector.toEjml().origin, out)
return out.wrapVector()
}
public override operator fun Matrix<Double>.minus(other: Matrix<Double>): EjmlMatrix =
(toEjml().origin - other.toEjml().origin).wrapMatrix()
public override operator fun Matrix<Double>.minus(other: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> {
val out = DMatrixRMaj(1, 1)
CommonOps_DDRM.subtract(toEjml().origin, other.toEjml().origin, out)
return out.wrapMatrix()
}
public override operator fun Matrix<Double>.times(value: Double): EjmlMatrix =
toEjml().origin.scale(value).wrapMatrix()
public override operator fun Matrix<Double>.times(value: Double): EjmlDoubleMatrix<DMatrixRMaj> {
val res = this.toEjml().origin.copy()
CommonOps_DDRM.scale(value, res)
return res.wrapMatrix()
}
public override fun Point<Double>.unaryMinus(): EjmlVector =
toEjml().origin.negative().wrapVector()
public override fun Point<Double>.unaryMinus(): EjmlDoubleVector<DMatrixRMaj> {
val out = toEjml().origin.copy()
CommonOps_DDRM.changeSign(out)
return out.wrapVector()
}
public override fun Matrix<Double>.plus(other: Matrix<Double>): EjmlMatrix =
(toEjml().origin + other.toEjml().origin).wrapMatrix()
public override fun Matrix<Double>.plus(other: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> {
val out = DMatrixRMaj(1, 1)
CommonOps_DDRM.add(toEjml().origin, other.toEjml().origin, out)
return out.wrapMatrix()
}
public override fun Point<Double>.plus(other: Point<Double>): EjmlVector =
(toEjml().origin + other.toEjml().origin).wrapVector()
public override fun Point<Double>.plus(other: Point<Double>): EjmlDoubleVector<DMatrixRMaj> {
val out = DMatrixRMaj(1, 1)
CommonOps_DDRM.add(toEjml().origin, other.toEjml().origin, out)
return out.wrapVector()
}
public override fun Point<Double>.minus(other: Point<Double>): EjmlVector =
(toEjml().origin - other.toEjml().origin).wrapVector()
public override fun Point<Double>.minus(other: Point<Double>): EjmlDoubleVector<DMatrixRMaj> {
val out = DMatrixRMaj(1, 1)
CommonOps_DDRM.subtract(toEjml().origin, other.toEjml().origin, out)
return out.wrapVector()
}
public override fun Double.times(m: Matrix<Double>): EjmlMatrix =
m.toEjml().origin.scale(this).wrapMatrix()
public override fun Double.times(m: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> = m * this
public override fun Point<Double>.times(value: Double): EjmlVector =
toEjml().origin.scale(value).wrapVector()
public override fun Point<Double>.times(value: Double): EjmlDoubleVector<DMatrixRMaj> {
val res = this.toEjml().origin.copy()
CommonOps_DDRM.scale(value, res)
return res.wrapVector()
}
public override fun Double.times(v: Point<Double>): EjmlVector =
v.toEjml().origin.scale(this).wrapVector()
public override fun Double.times(v: Point<Double>): EjmlDoubleVector<DMatrixRMaj> = v * this
@UnstableKMathAPI
public override fun <F : StructureFeature> getFeature(structure: Matrix<Double>, type: KClass<out F>): F? {
//Return the feature if it is intrinsic to the structure
// Return the feature if it is intrinsic to the structure
structure.getFeature(type)?.let { return it }
val origin = structure.toEjml().origin
return when (type) {
InverseMatrixFeature::class -> object : InverseMatrixFeature<Double> {
override val inverse: Matrix<Double> by lazy { EjmlMatrix(origin.invert()) }
override val inverse: Matrix<Double> by lazy {
val res = origin.copy()
CommonOps_DDRM.invert(res)
EjmlDoubleMatrix(res)
}
}
DeterminantFeature::class -> object : DeterminantFeature<Double> {
override val determinant: Double by lazy(origin::determinant)
override val determinant: Double by lazy { CommonOps_DDRM.det(DMatrixRMaj(origin)) }
}
SingularValueDecompositionFeature::class -> object : SingularValueDecompositionFeature<Double> {
private val svd by lazy {
DecompositionFactory_DDRM.svd(origin.numRows(), origin.numCols(), true, true, false)
.apply { decompose(origin.ddrm.copy()) }
DecompositionFactory_DDRM.svd(origin.numRows, origin.numCols, true, true, false)
.apply { decompose(origin.copy()) }
}
override val u: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(svd.getU(null, false))) }
override val s: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(svd.getW(null))) }
override val v: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(svd.getV(null, false))) }
override val u: Matrix<Double> by lazy { EjmlDoubleMatrix(svd.getU(null, false)) }
override val s: Matrix<Double> by lazy { EjmlDoubleMatrix(svd.getW(null)) }
override val v: Matrix<Double> by lazy { EjmlDoubleMatrix(svd.getV(null, false)) }
override val singularValues: Point<Double> by lazy { DoubleBuffer(svd.singularValues) }
}
QRDecompositionFeature::class -> object : QRDecompositionFeature<Double> {
private val qr by lazy {
DecompositionFactory_DDRM.qr().apply { decompose(origin.ddrm.copy()) }
DecompositionFactory_DDRM.qr().apply { decompose(origin.copy()) }
}
override val q: Matrix<Double> by lazy {
EjmlMatrix(SimpleMatrix(qr.getQ(null, false))) + OrthogonalFeature
EjmlDoubleMatrix(qr.getQ(null, false)) + OrthogonalFeature
}
override val r: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(qr.getR(null, false))) + UFeature }
override val r: Matrix<Double> by lazy { EjmlDoubleMatrix(qr.getR(null, false)) + UFeature }
}
CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<Double> {
override val l: Matrix<Double> by lazy {
val cholesky =
DecompositionFactory_DDRM.chol(structure.rowNum, true).apply { decompose(origin.ddrm.copy()) }
DecompositionFactory_DDRM.chol(structure.rowNum, true).apply { decompose(origin.copy()) }
EjmlMatrix(SimpleMatrix(cholesky.getT(null))) + LFeature
EjmlDoubleMatrix(cholesky.getT(null)) + LFeature
}
}
LupDecompositionFeature::class -> object : LupDecompositionFeature<Double> {
private val lup by lazy {
DecompositionFactory_DDRM.lu(origin.numRows(), origin.numCols())
.apply { decompose(origin.ddrm.copy()) }
DecompositionFactory_DDRM.lu(origin.numRows, origin.numCols).apply { decompose(origin.copy()) }
}
override val l: Matrix<Double> by lazy {
EjmlMatrix(SimpleMatrix(lup.getLower(null))) + LFeature
EjmlDoubleMatrix(lup.getLower(null)) + LFeature
}
override val u: Matrix<Double> by lazy {
EjmlMatrix(SimpleMatrix(lup.getUpper(null))) + UFeature
EjmlDoubleMatrix(lup.getUpper(null)) + UFeature
}
override val p: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(lup.getRowPivot(null))) }
override val p: Matrix<Double> by lazy { EjmlDoubleMatrix(lup.getRowPivot(null)) }
}
else -> null
}?.let(type::cast)
}
}
/**
/**
* Solves for *x* in the following equation: *x = [a] <sup>-1</sup> &middot; [b]*.
*
* @param a the base matrix.
* @param b n by p matrix.
* @return the solution for 'x' that is n by p.
* @author Iaroslav Postovalov
*/
public fun EjmlLinearSpace.solve(a: Matrix<Double>, b: Matrix<Double>): EjmlMatrix =
EjmlMatrix(a.toEjml().origin.solve(b.toEjml().origin))
public fun solve(a: Matrix<Double>, b: Matrix<Double>): EjmlDoubleMatrix<DMatrixRMaj> {
val res = DMatrixRMaj(1, 1)
CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res)
return EjmlDoubleMatrix(res)
}
/**
/**
* Solves for *x* in the following equation: *x = [a] <sup>-1</sup> &middot; [b]*.
*
* @param a the base matrix.
* @param b n by p vector.
* @return the solution for 'x' that is n by p.
* @author Iaroslav Postovalov
*/
public fun EjmlLinearSpace.solve(a: Matrix<Double>, b: Point<Double>): EjmlVector =
EjmlVector(a.toEjml().origin.solve(b.toEjml().origin))
/**
* Inverts this matrix.
*
* @author Alexander Nozik
*/
@OptIn(UnstableKMathAPI::class)
public fun EjmlMatrix.inverted(): EjmlMatrix = getFeature<InverseMatrixFeature<Double>>()!!.inverse as EjmlMatrix
/**
* Inverts the given matrix.
*
* @author Alexander Nozik
*/
public fun EjmlLinearSpace.inverse(matrix: Matrix<Double>): Matrix<Double> = matrix.toEjml().inverted()
public fun solve(a: Matrix<Double>, b: Point<Double>): EjmlDoubleVector<DMatrixRMaj> {
val res = DMatrixRMaj(1, 1)
CommonOps_DDRM.solve(DMatrixRMaj(a.toEjml().origin), DMatrixRMaj(b.toEjml().origin), res)
return EjmlDoubleVector(res)
}
}

24
kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt
View File

@ -5,18 +5,28 @@
package space.kscience.kmath.ejml
import org.ejml.simple.SimpleMatrix
import space.kscience.kmath.linear.Matrix
import org.ejml.data.DMatrix
import org.ejml.data.Matrix
import space.kscience.kmath.nd.Structure2D
/**
* The matrix implementation over EJML [SimpleMatrix].
* [space.kscience.kmath.linear.Matrix] implementation based on EJML [Matrix].
*
* @property origin the underlying [SimpleMatrix].
* @param T the type of elements contained in the buffer.
* @param M the type of EJML matrix.
* @property origin The underlying EJML matrix.
* @author Iaroslav Postovalov
*/
public class EjmlMatrix(public val origin: SimpleMatrix) : Matrix<Double> {
public override val rowNum: Int get() = origin.numRows()
public override val colNum: Int get() = origin.numCols()
public abstract class EjmlMatrix<T, out M : Matrix>(public open val origin: M) : Structure2D<T> {
public override val rowNum: Int get() = origin.numRows
public override val colNum: Int get() = origin.numCols
}
/**
* [EjmlMatrix] specialization for [Double].
*
* @author Iaroslav Postovalov
*/
public class EjmlDoubleMatrix<out M : DMatrix>(public override val origin: M) : EjmlMatrix<Double, M>(origin) {
public override operator fun get(i: Int, j: Int): Double = origin[i, j]
}

36
kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlVector.kt
View File

@ -5,35 +5,41 @@
package space.kscience.kmath.ejml
import org.ejml.simple.SimpleMatrix
import org.ejml.data.DMatrixD1
import org.ejml.data.Matrix
import space.kscience.kmath.linear.Point
/**
* Represents point over EJML [SimpleMatrix].
* [Point] implementation based on EJML [Matrix].
*
* @property origin the underlying [SimpleMatrix].
* @param T the type of elements contained in the buffer.
* @param M the type of EJML matrix.
* @property origin The underlying matrix.
* @author Iaroslav Postovalov
*/
public class EjmlVector internal constructor(public val origin: SimpleMatrix) : Point<Double> {
public abstract class EjmlVector<out T, out M : Matrix>(public open val origin: M) : Point<T> {
public override val size: Int
get() = origin.numRows()
get() = origin.numRows
init {
require(origin.numCols() == 1) { "Only single column matrices are allowed" }
}
public override operator fun get(index: Int): Double = origin[index]
public override operator fun iterator(): Iterator<Double> = object : Iterator<Double> {
public override operator fun iterator(): Iterator<T> = object : Iterator<T> {
private var cursor: Int = 0
override fun next(): Double {
override fun next(): T {
cursor += 1
return origin[cursor - 1]
return this@EjmlVector[cursor - 1]
}
override fun hasNext(): Boolean = cursor < origin.numCols() * origin.numRows()
override fun hasNext(): Boolean = cursor < origin.numCols * origin.numRows
}
public override fun toString(): String = "EjmlVector(origin=$origin)"
}
/**
* [EjmlVector] specialization for [Double].
*
* @author Iaroslav Postovalov
*/
public class EjmlDoubleVector<out M : DMatrixD1>(public override val origin: M) : EjmlVector<Double, M>(origin) {
public override operator fun get(index: Int): Double = origin[index]
}

53
kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt
View File

@ -5,12 +5,15 @@
package space.kscience.kmath.ejml
import org.ejml.data.DMatrixRMaj
import org.ejml.dense.row.CommonOps_DDRM
import org.ejml.dense.row.RandomMatrices_DDRM
import org.ejml.dense.row.factory.DecompositionFactory_DDRM
import org.ejml.simple.SimpleMatrix
import space.kscience.kmath.linear.*
import space.kscience.kmath.linear.DeterminantFeature
import space.kscience.kmath.linear.LupDecompositionFeature
import space.kscience.kmath.linear.getFeature
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.StructureND
import space.kscience.kmath.nd.getFeature
import kotlin.random.Random
import kotlin.random.asJavaRandom
import kotlin.test.*
@ -22,65 +25,59 @@ fun <T : Any> assertMatrixEquals(expected: StructureND<T>, actual: StructureND<T
internal class EjmlMatrixTest {
private val random = Random(0)
private val randomMatrix: SimpleMatrix
private val randomMatrix: DMatrixRMaj
get() {
val s = random.nextInt(2, 100)
return SimpleMatrix.random_DDRM(s, s, 0.0, 10.0, random.asJavaRandom())
val d = DMatrixRMaj(s, s)
RandomMatrices_DDRM.fillUniform(d, random.asJavaRandom())
return d
}
@Test
fun rowNum() {
val m = randomMatrix
assertEquals(m.numRows(), EjmlMatrix(m).rowNum)
assertEquals(m.numRows, EjmlDoubleMatrix(m).rowNum)
}
@Test
fun colNum() {
val m = randomMatrix
assertEquals(m.numCols(), EjmlMatrix(m).rowNum)
assertEquals(m.numCols, EjmlDoubleMatrix(m).rowNum)
}
@Test
fun shape() {
val m = randomMatrix
val w = EjmlMatrix(m)
assertEquals(listOf(m.numRows(), m.numCols()), w.shape.toList())
val w = EjmlDoubleMatrix(m)
assertContentEquals(intArrayOf(m.numRows, m.numCols), w.shape)
}
@OptIn(UnstableKMathAPI::class)
@Test
fun features() {
val m = randomMatrix
val w = EjmlMatrix(m)
val det: DeterminantFeature<Double> = EjmlLinearSpace.getFeature(w) ?: fail()
assertEquals(m.determinant(), det.determinant)
val lup: LupDecompositionFeature<Double> = EjmlLinearSpace.getFeature(w) ?: fail()
val w = EjmlDoubleMatrix(m)
val det: DeterminantFeature<Double> = EjmlLinearSpaceDDRM.getFeature(w) ?: fail()
assertEquals(CommonOps_DDRM.det(m), det.determinant)
val lup: LupDecompositionFeature<Double> = EjmlLinearSpaceDDRM.getFeature(w) ?: fail()
val ludecompositionF64 = DecompositionFactory_DDRM.lu(m.numRows(), m.numCols())
.also { it.decompose(m.ddrm.copy()) }
val ludecompositionF64 = DecompositionFactory_DDRM.lu(m.numRows, m.numCols)
.also { it.decompose(m.copy()) }
assertMatrixEquals(EjmlMatrix(SimpleMatrix(ludecompositionF64.getLower(null))), lup.l)
assertMatrixEquals(EjmlMatrix(SimpleMatrix(ludecompositionF64.getUpper(null))), lup.u)
assertMatrixEquals(EjmlMatrix(SimpleMatrix(ludecompositionF64.getRowPivot(null))), lup.p)
}
private object SomeFeature : MatrixFeature {}
@OptIn(UnstableKMathAPI::class)
@Test
fun suggestFeature() {
assertNotNull((EjmlMatrix(randomMatrix) + SomeFeature).getFeature<SomeFeature>())
assertMatrixEquals(EjmlDoubleMatrix(ludecompositionF64.getLower(null)), lup.l)
assertMatrixEquals(EjmlDoubleMatrix(ludecompositionF64.getUpper(null)), lup.u)
assertMatrixEquals(EjmlDoubleMatrix(ludecompositionF64.getRowPivot(null)), lup.p)
}
@Test
fun get() {
val m = randomMatrix
assertEquals(m[0, 0], EjmlMatrix(m)[0, 0])
assertEquals(m[0, 0], EjmlDoubleMatrix(m)[0, 0])
}
@Test
fun origin() {
val m = randomMatrix
assertSame(m, EjmlMatrix(m).origin)
assertSame(m, EjmlDoubleMatrix(m).origin)
}
}

23
kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlVectorTest.kt
View File

@ -5,7 +5,8 @@
package space.kscience.kmath.ejml
import org.ejml.simple.SimpleMatrix
import org.ejml.data.DMatrixRMaj
import org.ejml.dense.row.RandomMatrices_DDRM
import kotlin.random.Random
import kotlin.random.asJavaRandom
import kotlin.test.Test
@ -15,30 +16,34 @@ import kotlin.test.assertSame
internal class EjmlVectorTest {
private val random = Random(0)
private val randomMatrix: SimpleMatrix
get() = SimpleMatrix.random_DDRM(random.nextInt(2, 100), 1, 0.0, 10.0, random.asJavaRandom())
private val randomMatrix: DMatrixRMaj
get() {
val d = DMatrixRMaj(random.nextInt(2, 100), 1)
RandomMatrices_DDRM.fillUniform(d, random.asJavaRandom())
return d
}
@Test
fun size() {
val m = randomMatrix
val w = EjmlVector(m)
assertEquals(m.numRows(), w.size)
val w = EjmlDoubleVector(m)
assertEquals(m.numRows, w.size)
}
@Test
fun get() {
val m = randomMatrix
val w = EjmlVector(m)
val w = EjmlDoubleVector(m)
assertEquals(m[0, 0], w[0])
}
@Test
fun iterator() {
val m = randomMatrix
val w = EjmlVector(m)
val w = EjmlDoubleVector(m)
assertEquals(
m.iterator(true, 0, 0, m.numRows() - 1, 0).asSequence().toList(),
m.iterator(true, 0, 0, m.numRows - 1, 0).asSequence().toList(),
w.iterator().asSequence().toList()
)
}
@ -46,7 +51,7 @@ internal class EjmlVectorTest {
@Test
fun origin() {
val m = randomMatrix
val w = EjmlVector(m)
val w = EjmlDoubleVector(m)
assertSame(m, w.origin)
}
}

2
kmath-for-real/README.md
View File

@ -15,7 +15,6 @@ The Maven coordinates of this project are `space.kscience:kmath-for-real:0.3.0-d
```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
}
@ -28,7 +27,6 @@ dependencies {
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 {

2
kmath-functions/README.md
View File

@ -17,7 +17,6 @@ The Maven coordinates of this project are `space.kscience:kmath-functions:0.3.0-
```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
}
@ -30,7 +29,6 @@ dependencies {
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 {

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

@ -4,8 +4,8 @@ plugins {
}
dependencies {
implementation("com.github.breandan:kaliningraph:0.1.4")
implementation("com.github.breandan:kotlingrad:0.4.0")
api("com.github.breandan:kaliningraph:0.1.4")
api("com.github.breandan:kotlingrad:0.4.5")
api(project(":kmath-ast"))
}

6
kmath-nd4j/README.md
View File

@ -15,8 +15,7 @@ The Maven coordinates of this project are `space.kscience:kmath-nd4j:0.3.0-dev-7
```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
mavenCentral()
}
dependencies {
@ -27,8 +26,7 @@ dependencies {
```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
mavenCentral()
}
dependencies {

2
kmath-viktor/build.gradle.kts
View File

@ -7,7 +7,7 @@ description = "Binding for https://github.com/JetBrains-Research/viktor"
dependencies {
api(project(":kmath-core"))
api("org.jetbrains.bio:viktor:1.0.1")
api("org.jetbrains.bio:viktor:1.1.0")
}
readme {