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Merge branch 'dev' into feature/integration

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Alexander Nozik 2021-03-16 09:47:40 +03:00
commit b2df860381
71 changed files with 1348 additions and 1438 deletions
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40
.github/workflows/pages.yml vendored Normal file
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@ -0,0 +1,40 @@
name: Dokka publication
on:
push:
branches:
- master
jobs:
build:
runs-on: ubuntu-20.04
steps:
- name: Checkout the repo
uses: actions/checkout@v2
- name: Set up JDK 11
uses: actions/setup-java@v1
with:
java-version: 11
- name: Cache gradle
uses: actions/cache@v2
with:
path: ~/.gradle/caches
key: ubuntu-20.04-gradle-${{ hashFiles('*.gradle.kts') }}
restore-keys: |
ubuntu-20.04-gradle-
- name: Cache konan
uses: actions/cache@v2
with:
path: ~/.konan
key: ${{ runner.os }}-gradle-${{ hashFiles('*.gradle.kts') }}
restore-keys: |
${{ runner.os }}-gradle-
- name: Build
run: |
./gradlew dokkaHtmlMultiModule --no-daemon --no-parallel --stacktrace
mv build/dokka/htmlMultiModule/-modules.html build/dokka/htmlMultiModule/index.html
- name: Deploy to GitHub Pages
uses: JamesIves/github-pages-deploy-action@4.1.0
with:
branch: gh-pages
folder: build/dokka/htmlMultiModule

1
CHANGELOG.md
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@ -9,6 +9,7 @@
- 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
### Deprecated

8
README.md
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@ -3,9 +3,7 @@
![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg)
Bintray: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-core/_latestVersion)
Bintray-dev: [ ![Download](https://api.bintray.com/packages/mipt-npm/dev/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/dev/kmath-core/_latestVersion)
[![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22%20AND%20a:%22kmath-core%22)
# KMath
@ -256,8 +254,8 @@ repositories {
}
dependencies {
api("kscience.kmath:kmath-core:() -> kotlin.Any")
// api("kscience.kmath:kmath-core-jvm:() -> kotlin.Any") for jvm-specific version
api("space.kscience:kmath-core:0.3.0-dev-2")
// api("kscience.kmath:kmath-core-jvm:0.3.0-dev-2") for jvm-specific version
}
```

2
build.gradle.kts
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@ -20,7 +20,7 @@ allprojects {
}
group = "space.kscience"
version = "0.3.0"
version = "0.3.0-dev-2"
}
subprojects {

6
docs/templates/ARTIFACT-TEMPLATE.md vendored
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@ -13,9 +13,6 @@
> 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
>// Uncomment if repo.kotlin.link is unavailable
>// maven { url 'https://dl.bintray.com/mipt-npm/kscience' }
>// maven { url 'https://dl.bintray.com/mipt-npm/dev' }
> }
>
> dependencies {
@ -29,9 +26,6 @@
> 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
>// Uncomment if repo.kotlin.link is unavailable
>// maven("https://dl.bintray.com/mipt-npm/kscience")
>// maven("https://dl.bintray.com/mipt-npm/dev")
> }
>
> dependencies {

6
docs/templates/README-TEMPLATE.md vendored
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@ -3,9 +3,7 @@
![Gradle build](https://github.com/mipt-npm/kmath/workflows/Gradle%20build/badge.svg)
Bintray: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-core/_latestVersion)
Bintray-dev: [ ![Download](https://api.bintray.com/packages/mipt-npm/dev/kmath-core/images/download.svg) ](https://bintray.com/mipt-npm/dev/kmath-core/_latestVersion)
[![Maven Central](https://img.shields.io/maven-central/v/space.kscience/kmath-core.svg?label=Maven%20Central)](https://search.maven.org/search?q=g:%22space.kscience%22%20AND%20a:%22kmath-core%22)
# KMath
@ -106,7 +104,7 @@ repositories {
}
dependencies {
api("kscience.kmath:kmath-core:$version")
api("${group}:kmath-core:$version")
// api("kscience.kmath:kmath-core-jvm:$version") for jvm-specific version
}
```

8
examples/build.gradle.kts
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@ -92,6 +92,14 @@ benchmark {
iterationTimeUnit = "ms" // time unity for iterationTime, default is seconds
include("ExpressionsInterpretersBenchmark")
}
configurations.register("matrixInverse") {
warmups = 1 // number of warmup iterations
iterations = 3 // number of iterations
iterationTime = 500 // time in seconds per iteration
iterationTimeUnit = "ms" // time unity for iterationTime, default is seconds
include("MatrixInverseBenchmark")
}
}
kotlin.sourceSets.all {

33
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt
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@ -4,14 +4,11 @@ import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.commons.linear.CMMatrixContext
import space.kscience.kmath.ejml.EjmlMatrixContext
import space.kscience.kmath.linear.BufferMatrixContext
import space.kscience.kmath.linear.Matrix
import space.kscience.kmath.linear.RealMatrixContext
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.invoke
import space.kscience.kmath.structures.Buffer
import kotlin.random.Random
@State(Scope.Benchmark)
@ -21,47 +18,47 @@ internal class DotBenchmark {
const val dim = 1000
//creating invertible matrix
val matrix1 = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val matrix2 = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val matrix1 = LinearSpace.real.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val matrix2 = LinearSpace.real.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val cmMatrix1 = CMMatrixContext { matrix1.toCM() }
val cmMatrix2 = CMMatrixContext { matrix2.toCM() }
val cmMatrix1 = CMLinearSpace { matrix1.toCM() }
val cmMatrix2 = CMLinearSpace { matrix2.toCM() }
val ejmlMatrix1 = EjmlMatrixContext { matrix1.toEjml() }
val ejmlMatrix2 = EjmlMatrixContext { matrix2.toEjml() }
val ejmlMatrix1 = EjmlLinearSpace { matrix1.toEjml() }
val ejmlMatrix2 = EjmlLinearSpace { matrix2.toEjml() }
}
@Benchmark
fun cmDot(blackhole: Blackhole) {
CMMatrixContext {
CMLinearSpace.run {
blackhole.consume(cmMatrix1 dot cmMatrix2)
}
}
@Benchmark
fun ejmlDot(blackhole: Blackhole) {
EjmlMatrixContext {
EjmlLinearSpace {
blackhole.consume(ejmlMatrix1 dot ejmlMatrix2)
}
}
@Benchmark
fun ejmlDotWithConversion(blackhole: Blackhole) {
EjmlMatrixContext {
EjmlLinearSpace {
blackhole.consume(matrix1 dot matrix2)
}
}
@Benchmark
fun bufferedDot(blackhole: Blackhole) {
BufferMatrixContext(RealField, Buffer.Companion::real).invoke {
LinearSpace.auto(RealField).invoke {
blackhole.consume(matrix1 dot matrix2)
}
}
@Benchmark
fun realDot(blackhole: Blackhole) {
RealMatrixContext {
LinearSpace.real {
blackhole.consume(matrix1 dot matrix2)
}
}

4
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt
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@ -30,7 +30,7 @@ internal class ExpressionsInterpretersBenchmark {
fun mstExpression(blackhole: Blackhole) {
val expr = algebra.mstInField {
val x = bindSymbol(x)
x * 2.0 + 2.0 / x - 16.0
x * 2.0 + number(2.0) / x - 16.0
}
invokeAndSum(expr, blackhole)
@ -40,7 +40,7 @@ internal class ExpressionsInterpretersBenchmark {
fun asmExpression(blackhole: Blackhole) {
val expr = algebra.mstInField {
val x = bindSymbol(x)
x * 2.0 + 2.0 / x - 16.0
x * 2.0 + number(2.0) / x - 16.0
}.compile()
invokeAndSum(expr, blackhole)

26
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/LinearAlgebraBenchmark.kt → examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/MatrixInverseBenchmark.kt
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@ -4,44 +4,44 @@ import kotlinx.benchmark.Benchmark
import kotlinx.benchmark.Blackhole
import kotlinx.benchmark.Scope
import kotlinx.benchmark.State
import space.kscience.kmath.commons.linear.CMMatrixContext
import space.kscience.kmath.commons.linear.CMMatrixContext.dot
import space.kscience.kmath.commons.linear.CMLinearSpace
import space.kscience.kmath.commons.linear.inverse
import space.kscience.kmath.ejml.EjmlMatrixContext
import space.kscience.kmath.ejml.EjmlLinearSpace
import space.kscience.kmath.ejml.inverse
import space.kscience.kmath.linear.Matrix
import space.kscience.kmath.linear.MatrixContext
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.inverseWithLup
import space.kscience.kmath.linear.real
import space.kscience.kmath.linear.invoke
import kotlin.random.Random
@State(Scope.Benchmark)
internal class LinearAlgebraBenchmark {
internal class MatrixInverseBenchmark {
companion object {
val random = Random(1224)
const val dim = 100
private val space = LinearSpace.real
//creating invertible matrix
val u = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val l = Matrix.real(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
val matrix = l dot u
val u = space.buildMatrix(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
val l = space.buildMatrix(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
val matrix = space { l dot u }
}
@Benchmark
fun kmathLupInversion(blackhole: Blackhole) {
blackhole.consume(MatrixContext.real.inverseWithLup(matrix))
blackhole.consume(LinearSpace.real.inverseWithLup(matrix))
}
@Benchmark
fun cmLUPInversion(blackhole: Blackhole) {
with(CMMatrixContext) {
with(CMLinearSpace) {
blackhole.consume(inverse(matrix))
}
}
@Benchmark
fun ejmlInverse(blackhole: Blackhole) {
with(EjmlMatrixContext) {
with(EjmlLinearSpace) {
blackhole.consume(inverse(matrix))
}
}

4
examples/src/benchmarks/kotlin/space/kscience/kmath/benchmarks/ViktorLogBenchmark.kt
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@ -15,7 +15,7 @@ import space.kscience.kmath.viktor.ViktorNDField
internal class ViktorLogBenchmark {
@Benchmark
fun realFieldLog(blackhole: Blackhole) {
with(realField) {
with(realNdField) {
val fortyTwo = produce { 42.0 }
var res = one
repeat(n) { res = ln(fortyTwo) }
@ -47,7 +47,7 @@ internal class ViktorLogBenchmark {
// 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 realNdField = NDAlgebra.real(dim, dim)
private val viktorField = ViktorNDField(intArrayOf(dim, dim))
}
}

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

2
examples/src/main/kotlin/space/kscience/kmath/structures/StructureWriteBenchmark.kt
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@ -7,7 +7,7 @@ import kotlin.system.measureTimeMillis
@Suppress("UNUSED_VARIABLE")
fun main() {
val n = 6000
val structure = NDStructure.build(intArrayOf(n, n), Buffer.Companion::auto) { 1.0 }
val structure = NDStructure.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")

4
examples/src/main/kotlin/space/kscience/kmath/structures/typeSafeDimensions.kt
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@ -5,7 +5,7 @@ import space.kscience.kmath.dimensions.D3
import space.kscience.kmath.dimensions.DMatrixContext
import space.kscience.kmath.dimensions.Dimension
private fun DMatrixContext<Double>.simple() {
private fun DMatrixContext<Double, *>.simple() {
val m1 = produce<D2, D3> { i, j -> (i + j).toDouble() }
val m2 = produce<D3, D2> { i, j -> (i + j).toDouble() }
@ -17,7 +17,7 @@ private object D5 : Dimension {
override val dim: UInt = 5u
}
private fun DMatrixContext<Double>.custom() {
private fun DMatrixContext<Double, *>.custom() {
val m1 = produce<D2, D5> { i, j -> (i + j).toDouble() }
val m2 = produce<D5, D2> { i, j -> (i - j).toDouble() }
val m3 = produce<D2, D2> { i, j -> (i - j).toDouble() }

8
gradle.properties
View File

@ -1,10 +1,8 @@
kotlin.code.style=official
kotlin.mpp.enableGranularSourceSetsMetadata=true
kotlin.mpp.stability.nowarn=true
kotlin.native.enableDependencyPropagation=false
kotlin.parallel.tasks.in.project=true
org.gradle.configureondemand=true
org.gradle.jvmargs=-XX:MaxMetaspaceSize=512m
org.gradle.jvmargs=-XX:MaxMetaspaceSize=2G
org.gradle.parallel=true
kotlin.mpp.enableGranularSourceSetsMetadata=true
kotlin.native.enableDependencyPropagation=false

6
kmath-ast/README.md
View File

@ -12,7 +12,7 @@ This subproject implements the following features:
> #### Artifact:
>
> This module artifact: `space.kscience:kmath-ast:0.2.0`.
> 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)
>
@ -31,7 +31,7 @@ This subproject implements the following features:
> }
>
> dependencies {
> implementation 'space.kscience:kmath-ast:0.2.0'
> implementation 'space.kscience:kmath-ast:0.3.0-dev-2'
> }
> ```
> **Gradle Kotlin DSL:**
@ -47,7 +47,7 @@ This subproject implements the following features:
> }
>
> dependencies {
> implementation("space.kscience:kmath-ast:0.2.0")
> implementation("space.kscience:kmath-ast:0.3.0-dev-2")
> }
> ```

6
kmath-ast/src/commonMain/kotlin/space/kscience/kmath/ast/MstAlgebra.kt
View File

@ -54,7 +54,7 @@ public object MstRing : Ring<MST>, NumbersAddOperations<MST>, ScaleOperations<MS
public override val one: MST.Numeric = number(1.0)
public override fun number(value: Number): MST.Numeric = MstGroup.number(value)
public override fun bindSymbol(value: String): MST.Symbolic = MstGroup.bindSymbol(value)
public override fun bindSymbol(value: String): MST.Symbolic = MstAlgebra.bindSymbol(value)
public override fun add(a: MST, b: MST): MST.Binary = MstGroup.add(a, b)
public override fun scale(a: MST, value: Double): MST.Binary =
@ -83,7 +83,7 @@ public object MstField : Field<MST>, NumbersAddOperations<MST>, ScaleOperations<
public override val one: MST.Numeric get() = MstRing.one
public override fun bindSymbol(value: String): MST.Symbolic = MstRing.bindSymbol(value)
public override fun bindSymbol(value: String): MST.Symbolic = MstAlgebra.bindSymbol(value)
public override fun number(value: Number): MST.Numeric = MstRing.number(value)
public override fun add(a: MST, b: MST): MST.Binary = MstRing.add(a, b)
@ -112,7 +112,7 @@ public object MstExtendedField : ExtendedField<MST>, NumericAlgebra<MST> {
public override val zero: MST.Numeric get() = MstField.zero
public override val one: MST.Numeric get() = MstField.one
public override fun bindSymbol(value: String): MST.Symbolic = MstField.bindSymbol(value)
public override fun bindSymbol(value: String): MST.Symbolic = MstAlgebra.bindSymbol(value)
public override fun number(value: Number): MST.Numeric = MstRing.number(value)
public override fun sin(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.SIN_OPERATION)(arg)
public override fun cos(arg: MST): MST.Unary = unaryOperationFunction(TrigonometricOperations.COS_OPERATION)(arg)

166
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMMatrix.kt
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@ -3,16 +3,108 @@ 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 kotlin.reflect.KClass
import kotlin.reflect.cast
public inline class CMMatrix(public val origin: RealMatrix) : Matrix<Double> {
public class CMMatrix(public val origin: RealMatrix) : Matrix<Double> {
public override val rowNum: Int get() = origin.rowDimension
public override val colNum: Int get() = origin.columnDimension
public override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
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 override val size: Int get() = origin.dimension
public override operator fun get(index: Int): Double = origin.getEntry(index)
public override operator fun iterator(): Iterator<Double> = origin.toArray().iterator()
}
public fun RealVector.toPoint(): CMVector = CMVector(this)
public object CMLinearSpace : LinearSpace<Double, RealField> {
override val elementAlgebra: RealField get() = RealField
public override fun buildMatrix(
rows: Int,
columns: Int,
initializer: RealField.(i: Int, j: Int) -> Double,
): CMMatrix {
val array = Array(rows) { i -> DoubleArray(columns) { j -> RealField.initializer(i, j) } }
return CMMatrix(Array2DRowRealMatrix(array))
}
@OptIn(UnstableKMathAPI::class)
public fun Matrix<Double>.toCM(): CMMatrix = when (val matrix = origin) {
is CMMatrix -> matrix
else -> {
//TODO add feature analysis
val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
Array2DRowRealMatrix(array).wrap()
}
}
public fun Point<Double>.toCM(): CMVector = if (this is CMVector) this else {
val array = DoubleArray(size) { this[it] }
ArrayRealVector(array).wrap()
}
internal fun RealMatrix.wrap(): CMMatrix = CMMatrix(this)
internal fun RealVector.wrap(): CMVector = CMVector(this)
override fun buildVector(size: Int, initializer: RealField.(Int) -> Double): Point<Double> =
ArrayRealVector(DoubleArray(size) { RealField.initializer(it) }).wrap()
override fun Matrix<Double>.plus(other: Matrix<Double>): CMMatrix =
toCM().origin.add(other.toCM().origin).wrap()
override fun Point<Double>.plus(other: Point<Double>): CMVector =
toCM().origin.add(other.toCM().origin).wrap()
override fun Point<Double>.minus(other: Point<Double>): CMVector =
toCM().origin.subtract(other.toCM().origin).wrap()
public override fun Matrix<Double>.dot(other: Matrix<Double>): CMMatrix =
toCM().origin.multiply(other.toCM().origin).wrap()
public override fun Matrix<Double>.dot(vector: Point<Double>): CMVector =
toCM().origin.preMultiply(vector.toCM().origin).wrap()
public override operator fun Matrix<Double>.minus(other: Matrix<Double>): CMMatrix =
toCM().origin.subtract(other.toCM().origin).wrap()
public override operator fun Matrix<Double>.times(value: Double): CMMatrix =
toCM().origin.scalarMultiply(value).wrap()
override fun Double.times(m: Matrix<Double>): CMMatrix =
m * this
override fun Point<Double>.times(value: Double): CMVector =
toCM().origin.mapMultiply(value).wrap()
override fun Double.times(v: Point<Double>): CMVector =
v * this
@UnstableKMathAPI
override fun <T : Any> getFeature(type: KClass<T>): T? = when (type) {
override fun <F : Any> getFeature(structure: Matrix<Double>, type: KClass<F>): F? {
//Return the feature if it is intrinsic to the structure
structure.getFeature(type)?.let { return it }
val origin = structure.toCM().origin
return when (type) {
DiagonalFeature::class -> if (origin is DiagonalMatrix) DiagonalFeature else null
DeterminantFeature::class, LupDecompositionFeature::class -> object :
@ -45,77 +137,13 @@ public inline class CMMatrix(public val origin: RealMatrix) : Matrix<Double> {
override val v: Matrix<Double> by lazy { CMMatrix(sv.v) }
override val singularValues: Point<Double> by lazy { RealBuffer(sv.singularValues) }
}
else -> null
}?.let(type::cast)
public override operator fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
}
public fun RealMatrix.asMatrix(): CMMatrix = CMMatrix(this)
public class CMVector(public val origin: RealVector) : Point<Double> {
public override val size: Int get() = origin.dimension
public override operator fun get(index: Int): Double = origin.getEntry(index)
public override operator fun iterator(): Iterator<Double> = origin.toArray().iterator()
}
public fun Point<Double>.toCM(): CMVector = if (this is CMVector) this else {
val array = DoubleArray(size) { this[it] }
CMVector(ArrayRealVector(array))
}
public fun RealVector.toPoint(): CMVector = CMVector(this)
public object CMMatrixContext : MatrixContext<Double, CMMatrix> {
public override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> Double): CMMatrix {
val array = Array(rows) { i -> DoubleArray(columns) { j -> initializer(i, j) } }
return CMMatrix(Array2DRowRealMatrix(array))
}
@OptIn(UnstableKMathAPI::class)
public fun Matrix<Double>.toCM(): CMMatrix = when (val matrix = origin) {
is CMMatrix -> matrix
else -> {
//TODO add feature analysis
val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }
CMMatrix(Array2DRowRealMatrix(array))
}
}
override fun scale(a: Matrix<Double>, value: Double): Matrix<Double> = a.toCM().times(value)
public operator fun CMMatrix.plus(other: CMMatrix): CMMatrix = CMMatrix(origin.add(other.origin))
public operator fun CMMatrix.minus(other: CMMatrix): CMMatrix = CMMatrix(origin.subtract(other.origin))
public override fun Matrix<Double>.dot(other: Matrix<Double>): CMMatrix =
CMMatrix(toCM().origin.multiply(other.toCM().origin))
public override fun Matrix<Double>.dot(vector: Point<Double>): CMVector =
CMVector(toCM().origin.preMultiply(vector.toCM().origin))
public override operator fun Matrix<Double>.unaryMinus(): CMMatrix =
produce(rowNum, colNum) { i, j -> -get(i, j) }
public override fun add(a: Matrix<Double>, b: Matrix<Double>): CMMatrix =
CMMatrix(a.toCM().origin.multiply(b.toCM().origin))
public override operator fun Matrix<Double>.minus(b: Matrix<Double>): CMMatrix =
CMMatrix(toCM().origin.subtract(b.toCM().origin))
// public override fun multiply(a: Matrix<Double>, k: Number): CMMatrix =
// CMMatrix(a.toCM().origin.scalarMultiply(k.toDouble()))
public override operator fun Matrix<Double>.times(value: Double): CMMatrix =
produce(rowNum, colNum) { i, j -> get(i, j) * value }
}
public operator fun CMMatrix.plus(other: CMMatrix): CMMatrix =
CMMatrix(origin.add(other.origin))
public operator fun CMMatrix.minus(other: CMMatrix): CMMatrix =
CMMatrix(origin.subtract(other.origin))
public infix fun CMMatrix.dot(other: CMMatrix): CMMatrix =
CMMatrix(origin.multiply(other.origin))
public infix fun CMMatrix.dot(other: CMMatrix): CMMatrix = CMMatrix(origin.multiply(other.origin))

12
kmath-commons/src/main/kotlin/space/kscience/kmath/commons/linear/CMSolver.kt
View File

@ -12,7 +12,7 @@ public enum class CMDecomposition {
CHOLESKY
}
public fun CMMatrixContext.solver(
public fun CMLinearSpace.solver(
a: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): DecompositionSolver = when (decomposition) {
@ -23,19 +23,19 @@ public fun CMMatrixContext.solver(
CMDecomposition.CHOLESKY -> CholeskyDecomposition(a.toCM().origin).solver
}
public fun CMMatrixContext.solve(
public fun CMLinearSpace.solve(
a: Matrix<Double>,
b: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).asMatrix()
): CMMatrix = solver(a, decomposition).solve(b.toCM().origin).wrap()
public fun CMMatrixContext.solve(
public fun CMLinearSpace.solve(
a: Matrix<Double>,
b: Point<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMVector = solver(a, decomposition).solve(b.toCM().origin).toPoint()
public fun CMMatrixContext.inverse(
public fun CMLinearSpace.inverse(
a: Matrix<Double>,
decomposition: CMDecomposition = CMDecomposition.LUP
): CMMatrix = solver(a, decomposition).inverse.asMatrix()
): CMMatrix = solver(a, decomposition).inverse.wrap()

6
kmath-complex/README.md
View File

@ -8,7 +8,7 @@ Complex and hypercomplex number systems in KMath:
> #### Artifact:
>
> This module artifact: `space.kscience:kmath-complex:0.2.0`.
> 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)
>
@ -27,7 +27,7 @@ Complex and hypercomplex number systems in KMath:
> }
>
> dependencies {
> implementation 'space.kscience:kmath-complex:0.2.0'
> implementation 'space.kscience:kmath-complex:0.3.0-dev-2'
> }
> ```
> **Gradle Kotlin DSL:**
@ -43,6 +43,6 @@ Complex and hypercomplex number systems in KMath:
> }
>
> dependencies {
> implementation("space.kscience:kmath-complex:0.2.0")
> implementation("space.kscience:kmath-complex:0.3.0-dev-2")
> }
> ```

55
kmath-core/README.md Normal file
View File

@ -0,0 +1,55 @@
# The Core Module (`kmath-core`)
The core features 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
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
> #### 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
>// Uncomment if repo.kotlin.link is unavailable
>// maven { url 'https://dl.bintray.com/mipt-npm/kscience' }
>// maven { url 'https://dl.bintray.com/mipt-npm/dev' }
> }
>
> 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
>// Uncomment if repo.kotlin.link is unavailable
>// maven("https://dl.bintray.com/mipt-npm/kscience")
>// maven("https://dl.bintray.com/mipt-npm/dev")
> }
>
> dependencies {
> implementation("space.kscience:kmath-core:0.3.0-dev-2")
> }
> ```

387
kmath-core/api/kmath-core.api
View File

@ -432,106 +432,23 @@ public final class space/kscience/kmath/expressions/SymbolIndexerKt {
public static final fun withSymbols ([Lspace/kscience/kmath/expressions/Symbol;Lkotlin/jvm/functions/Function1;)Ljava/lang/Object;
}
public final class space/kscience/kmath/linear/BufferMatrix : space/kscience/kmath/nd/Structure2D {
public fun <init> (IILspace/kscience/kmath/structures/Buffer;)V
public fun elements ()Lkotlin/sequences/Sequence;
public fun equals (Ljava/lang/Object;)Z
public fun get (II)Ljava/lang/Object;
public fun get ([I)Ljava/lang/Object;
public final fun getBuffer ()Lspace/kscience/kmath/structures/Buffer;
public fun getColNum ()I
public fun getColumns ()Lspace/kscience/kmath/structures/Buffer;
public fun getDimension ()I
public fun getRowNum ()I
public fun getRows ()Lspace/kscience/kmath/structures/Buffer;
public fun getShape ()[I
public fun hashCode ()I
public fun toString ()Ljava/lang/String;
}
public final class space/kscience/kmath/linear/BufferMatrixContext : space/kscience/kmath/linear/GenericMatrixContext {
public static final field Companion Lspace/kscience/kmath/linear/BufferMatrixContext$Companion;
public final class space/kscience/kmath/linear/BufferedLinearSpace : space/kscience/kmath/linear/LinearSpace {
public fun <init> (Lspace/kscience/kmath/operations/Ring;Lkotlin/jvm/functions/Function2;)V
public synthetic fun add (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun add (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun add (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun binaryOperation (Ljava/lang/String;Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun binaryOperation (Ljava/lang/String;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2;
public synthetic fun bindSymbol (Ljava/lang/String;)Ljava/lang/Object;
public fun bindSymbol (Ljava/lang/String;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun div (Ljava/lang/Object;Ljava/lang/Number;)Ljava/lang/Object;
public fun div (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Number;)Lspace/kscience/kmath/nd/Structure2D;
public fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun buildMatrix (IILkotlin/jvm/functions/Function3;)Lspace/kscience/kmath/nd/Structure2D;
public fun buildVector (ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/structures/Buffer;
public fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public fun getElementContext ()Lspace/kscience/kmath/operations/Ring;
public synthetic fun minus (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun minus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun minus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public final fun one (II)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun plus (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun plus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun point (ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/structures/Buffer;
public fun produce (IILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun produce (IILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun scale (Ljava/lang/Object;D)Ljava/lang/Object;
public fun scale (Lspace/kscience/kmath/nd/Structure2D;D)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun times (Ljava/lang/Number;Ljava/lang/Object;)Ljava/lang/Object;
public fun times (Ljava/lang/Number;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun times (Ljava/lang/Object;Ljava/lang/Number;)Ljava/lang/Object;
public fun times (Ljava/lang/Object;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun times (Ljava/lang/Object;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun times (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Number;)Lspace/kscience/kmath/nd/Structure2D;
public fun times (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Object;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun times (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun unaryMinus (Ljava/lang/Object;)Ljava/lang/Object;
public fun unaryMinus (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun unaryMinus (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun unaryOperation (Ljava/lang/String;Ljava/lang/Object;)Ljava/lang/Object;
public fun unaryOperation (Ljava/lang/String;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun unaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function1;
public synthetic fun unaryPlus (Ljava/lang/Object;)Ljava/lang/Object;
public fun unaryPlus (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
}
public final class space/kscience/kmath/linear/BufferMatrixContext$Companion {
}
public final class space/kscience/kmath/linear/BufferVectorSpace : space/kscience/kmath/linear/VectorSpace {
public fun <init> (ILspace/kscience/kmath/operations/Group;Lkotlin/jvm/functions/Function2;)V
public synthetic fun add (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun add (Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public synthetic fun binaryOperation (Ljava/lang/String;Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun binaryOperation (Ljava/lang/String;Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2;
public synthetic fun bindSymbol (Ljava/lang/String;)Ljava/lang/Object;
public fun bindSymbol (Ljava/lang/String;)Lspace/kscience/kmath/structures/Buffer;
public synthetic fun div (Ljava/lang/Object;Ljava/lang/Number;)Ljava/lang/Object;
public fun div (Lspace/kscience/kmath/structures/Buffer;Ljava/lang/Number;)Lspace/kscience/kmath/structures/Buffer;
public fun getAlgebra ()Lspace/kscience/kmath/operations/Group;
public final fun getBufferFactory ()Lkotlin/jvm/functions/Function2;
public fun getSize ()I
public synthetic fun getZero ()Ljava/lang/Object;
public fun getZero ()Lspace/kscience/kmath/structures/Buffer;
public synthetic fun minus (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun getElementAlgebra ()Lspace/kscience/kmath/operations/Ring;
public fun minus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun minus (Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public synthetic fun plus (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun plus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun plus (Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public fun produce (Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/structures/Buffer;
public synthetic fun scale (Ljava/lang/Object;D)Ljava/lang/Object;
public fun scale (Lspace/kscience/kmath/structures/Buffer;D)Lspace/kscience/kmath/structures/Buffer;
public synthetic fun times (Ljava/lang/Number;Ljava/lang/Object;)Ljava/lang/Object;
public fun times (Ljava/lang/Number;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public synthetic fun times (Ljava/lang/Object;Ljava/lang/Number;)Ljava/lang/Object;
public fun times (Lspace/kscience/kmath/structures/Buffer;Ljava/lang/Number;)Lspace/kscience/kmath/structures/Buffer;
public synthetic fun unaryMinus (Ljava/lang/Object;)Ljava/lang/Object;
public fun times (Ljava/lang/Object;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun times (Ljava/lang/Object;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public fun times (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public fun times (Lspace/kscience/kmath/structures/Buffer;Ljava/lang/Object;)Lspace/kscience/kmath/structures/Buffer;
public fun unaryMinus (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun unaryMinus (Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public synthetic fun unaryOperation (Ljava/lang/String;Ljava/lang/Object;)Ljava/lang/Object;
public fun unaryOperation (Ljava/lang/String;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public fun unaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function1;
public synthetic fun unaryPlus (Ljava/lang/Object;)Ljava/lang/Object;
public fun unaryPlus (Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
}
public abstract interface class space/kscience/kmath/linear/CholeskyDecompositionFeature : space/kscience/kmath/linear/MatrixFeature {
@ -549,37 +466,6 @@ public abstract interface class space/kscience/kmath/linear/DiagonalFeature : sp
public final class space/kscience/kmath/linear/DiagonalFeature$Companion : space/kscience/kmath/linear/DiagonalFeature {
}
public abstract interface class space/kscience/kmath/linear/GenericMatrixContext : space/kscience/kmath/linear/MatrixContext {
public abstract fun add (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun getElementContext ()Lspace/kscience/kmath/operations/Ring;
public abstract fun minus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun times (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun unaryMinus (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
}
public final class space/kscience/kmath/linear/GenericMatrixContext$DefaultImpls {
public static fun add (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun binaryOperation (Lspace/kscience/kmath/linear/GenericMatrixContext;Ljava/lang/String;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun binaryOperationFunction (Lspace/kscience/kmath/linear/GenericMatrixContext;Ljava/lang/String;)Lkotlin/jvm/functions/Function2;
public static fun bindSymbol (Lspace/kscience/kmath/linear/GenericMatrixContext;Ljava/lang/String;)Lspace/kscience/kmath/nd/Structure2D;
public static fun div (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Number;)Lspace/kscience/kmath/nd/Structure2D;
public static fun dot (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun dot (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun minus (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun plus (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun point (Lspace/kscience/kmath/linear/GenericMatrixContext;ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/structures/Buffer;
public static fun times (Lspace/kscience/kmath/linear/GenericMatrixContext;Ljava/lang/Number;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun times (Lspace/kscience/kmath/linear/GenericMatrixContext;Ljava/lang/Object;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun times (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Number;)Lspace/kscience/kmath/nd/Structure2D;
public static fun times (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public static fun unaryMinus (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun unaryOperation (Lspace/kscience/kmath/linear/GenericMatrixContext;Ljava/lang/String;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun unaryOperationFunction (Lspace/kscience/kmath/linear/GenericMatrixContext;Ljava/lang/String;)Lkotlin/jvm/functions/Function1;
public static fun unaryPlus (Lspace/kscience/kmath/linear/GenericMatrixContext;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
}
public abstract interface class space/kscience/kmath/linear/InverseMatrixFeature : space/kscience/kmath/linear/MatrixFeature {
public abstract fun getInverse ()Lspace/kscience/kmath/nd/Structure2D;
}
@ -588,11 +474,6 @@ public final class space/kscience/kmath/linear/LFeature : space/kscience/kmath/l
public static final field INSTANCE Lspace/kscience/kmath/linear/LFeature;
}
public final class space/kscience/kmath/linear/LinearAlgebraKt {
public static final fun asMatrix (Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/linear/VirtualMatrix;
public static final fun asPoint (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/structures/Buffer;
}
public abstract interface class space/kscience/kmath/linear/LinearSolver {
public abstract fun inverse (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun solve (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
@ -603,9 +484,58 @@ public final class space/kscience/kmath/linear/LinearSolver$DefaultImpls {
public static fun solve (Lspace/kscience/kmath/linear/LinearSolver;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
}
public final class space/kscience/kmath/linear/LinearSolverKt {
public static final fun asMatrix (Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/linear/VirtualMatrix;
public static final fun asVector (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/structures/Buffer;
}
public abstract interface class space/kscience/kmath/linear/LinearSpace {
public static final field Companion Lspace/kscience/kmath/linear/LinearSpace$Companion;
public abstract fun buildMatrix (IILkotlin/jvm/functions/Function3;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun buildVector (ILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun getElementAlgebra ()Lspace/kscience/kmath/operations/Ring;
public abstract fun minus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun minus (Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun plus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun plus (Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun times (Ljava/lang/Object;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun times (Ljava/lang/Object;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun times (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun times (Lspace/kscience/kmath/structures/Buffer;Ljava/lang/Object;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun unaryMinus (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun unaryMinus (Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
}
public final class space/kscience/kmath/linear/LinearSpace$Companion {
public final fun buffered (Lspace/kscience/kmath/operations/Ring;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/linear/LinearSpace;
public static synthetic fun buffered$default (Lspace/kscience/kmath/linear/LinearSpace$Companion;Lspace/kscience/kmath/operations/Ring;Lkotlin/jvm/functions/Function2;ILjava/lang/Object;)Lspace/kscience/kmath/linear/LinearSpace;
public final fun getReal ()Lspace/kscience/kmath/linear/LinearSpace;
}
public final class space/kscience/kmath/linear/LinearSpace$DefaultImpls {
public static fun dot (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun dot (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun minus (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun minus (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun plus (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun plus (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun times (Lspace/kscience/kmath/linear/LinearSpace;Ljava/lang/Object;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun times (Lspace/kscience/kmath/linear/LinearSpace;Ljava/lang/Object;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun times (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public static fun times (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/structures/Buffer;Ljava/lang/Object;)Lspace/kscience/kmath/structures/Buffer;
public static fun unaryMinus (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun unaryMinus (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
}
public final class space/kscience/kmath/linear/LinearSpaceKt {
public static final fun invoke (Lspace/kscience/kmath/linear/LinearSpace;Lkotlin/jvm/functions/Function1;)Ljava/lang/Object;
}
public final class space/kscience/kmath/linear/LupDecomposition : space/kscience/kmath/linear/DeterminantFeature, space/kscience/kmath/linear/LupDecompositionFeature {
public fun <init> (Lspace/kscience/kmath/linear/MatrixContext;Lspace/kscience/kmath/operations/Field;Lspace/kscience/kmath/nd/Structure2D;[IZ)V
public final fun getContext ()Lspace/kscience/kmath/linear/MatrixContext;
public fun <init> (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/operations/Field;Lspace/kscience/kmath/nd/Structure2D;[IZ)V
public final fun getContext ()Lspace/kscience/kmath/linear/LinearSpace;
public fun getDeterminant ()Ljava/lang/Object;
public final fun getElementContext ()Lspace/kscience/kmath/operations/Field;
public fun getL ()Lspace/kscience/kmath/nd/Structure2D;
@ -622,57 +552,27 @@ public abstract interface class space/kscience/kmath/linear/LupDecompositionFeat
}
public final class space/kscience/kmath/linear/LupDecompositionKt {
public static final fun abs (Lspace/kscience/kmath/linear/GenericMatrixContext;Ljava/lang/Comparable;)Ljava/lang/Comparable;
public static final fun inverseWithLup (Lspace/kscience/kmath/linear/RealMatrixContext;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun lup (Lspace/kscience/kmath/linear/MatrixContext;Lkotlin/jvm/functions/Function2;Lspace/kscience/kmath/operations/Field;Lspace/kscience/kmath/nd/Structure2D;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/linear/LupDecomposition;
public static final fun lup (Lspace/kscience/kmath/linear/MatrixContext;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/LupDecomposition;
public static final fun abs (Lspace/kscience/kmath/linear/LinearSpace;Ljava/lang/Comparable;)Ljava/lang/Comparable;
public static final fun inverseWithLup (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun lup (Lspace/kscience/kmath/linear/LinearSpace;Lkotlin/jvm/functions/Function2;Lspace/kscience/kmath/nd/Structure2D;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/linear/LupDecomposition;
public static final fun lup (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/LupDecomposition;
public static final fun solveWithLup (Lspace/kscience/kmath/linear/LinearSpace;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun solveWithLup (Lspace/kscience/kmath/linear/LupDecomposition;Lkotlin/jvm/functions/Function2;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun solveWithLup (Lspace/kscience/kmath/linear/RealMatrixContext;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
}
public final class space/kscience/kmath/linear/MatrixBuilder {
public fun <init> (II)V
public fun <init> (Lspace/kscience/kmath/linear/LinearSpace;II)V
public final fun getColumns ()I
public final fun getLinearSpace ()Lspace/kscience/kmath/linear/LinearSpace;
public final fun getRows ()I
public final fun invoke ([Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
}
public final class space/kscience/kmath/linear/MatrixBuilderKt {
public static final fun build (Lspace/kscience/kmath/nd/Structure2D$Companion;II)Lspace/kscience/kmath/linear/MatrixBuilder;
public static final fun column (Lspace/kscience/kmath/nd/Structure2D$Companion;[Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun row (Lspace/kscience/kmath/nd/Structure2D$Companion;[Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
}
public abstract interface class space/kscience/kmath/linear/MatrixContext : space/kscience/kmath/operations/GroupOperations, space/kscience/kmath/operations/ScaleOperations {
public static final field Companion Lspace/kscience/kmath/linear/MatrixContext$Companion;
public abstract fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2;
public abstract fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun point (ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun produce (IILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun times (Ljava/lang/Object;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public abstract fun times (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
}
public final class space/kscience/kmath/linear/MatrixContext$Companion {
public final fun buffered (Lspace/kscience/kmath/operations/Ring;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/linear/GenericMatrixContext;
public static synthetic fun buffered$default (Lspace/kscience/kmath/linear/MatrixContext$Companion;Lspace/kscience/kmath/operations/Ring;Lkotlin/jvm/functions/Function2;ILjava/lang/Object;)Lspace/kscience/kmath/linear/GenericMatrixContext;
}
public final class space/kscience/kmath/linear/MatrixContext$DefaultImpls {
public static fun binaryOperation (Lspace/kscience/kmath/linear/MatrixContext;Ljava/lang/String;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun binaryOperationFunction (Lspace/kscience/kmath/linear/MatrixContext;Ljava/lang/String;)Lkotlin/jvm/functions/Function2;
public static fun bindSymbol (Lspace/kscience/kmath/linear/MatrixContext;Ljava/lang/String;)Lspace/kscience/kmath/nd/Structure2D;
public static fun div (Lspace/kscience/kmath/linear/MatrixContext;Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Number;)Lspace/kscience/kmath/nd/Structure2D;
public static fun minus (Lspace/kscience/kmath/linear/MatrixContext;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun plus (Lspace/kscience/kmath/linear/MatrixContext;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun point (Lspace/kscience/kmath/linear/MatrixContext;ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/structures/Buffer;
public static fun times (Lspace/kscience/kmath/linear/MatrixContext;Ljava/lang/Number;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun times (Lspace/kscience/kmath/linear/MatrixContext;Ljava/lang/Object;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun times (Lspace/kscience/kmath/linear/MatrixContext;Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Number;)Lspace/kscience/kmath/nd/Structure2D;
public static fun unaryOperation (Lspace/kscience/kmath/linear/MatrixContext;Ljava/lang/String;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static fun unaryOperationFunction (Lspace/kscience/kmath/linear/MatrixContext;Ljava/lang/String;)Lkotlin/jvm/functions/Function1;
public static fun unaryPlus (Lspace/kscience/kmath/linear/MatrixContext;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun column (Lspace/kscience/kmath/linear/LinearSpace;ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun column (Lspace/kscience/kmath/linear/LinearSpace;[Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun row (Lspace/kscience/kmath/linear/LinearSpace;ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun row (Lspace/kscience/kmath/linear/LinearSpace;[Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
}
public abstract interface class space/kscience/kmath/linear/MatrixFeature {
@ -688,12 +588,12 @@ public final class space/kscience/kmath/linear/MatrixWrapper : space/kscience/km
public fun get (II)Ljava/lang/Object;
public fun get ([I)Ljava/lang/Object;
public fun getColNum ()I
public fun getColumns ()Lspace/kscience/kmath/structures/Buffer;
public fun getColumns ()Ljava/util/List;
public fun getDimension ()I
public final fun getFeatures ()Ljava/util/Set;
public final fun getOrigin ()Lspace/kscience/kmath/nd/Structure2D;
public fun getRowNum ()I
public fun getRows ()Lspace/kscience/kmath/structures/Buffer;
public fun getRows ()Ljava/util/List;
public fun getShape ()[I
public fun hashCode ()I
public fun toString ()Ljava/lang/String;
@ -701,12 +601,11 @@ public final class space/kscience/kmath/linear/MatrixWrapper : space/kscience/km
public final class space/kscience/kmath/linear/MatrixWrapperKt {
public static final fun getOrigin (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun one (Lspace/kscience/kmath/linear/GenericMatrixContext;II)Lspace/kscience/kmath/nd/Structure2D;
public static final fun one (Lspace/kscience/kmath/linear/LinearSpace;II)Lspace/kscience/kmath/nd/Structure2D;
public static final fun plus (Lspace/kscience/kmath/nd/Structure2D;Ljava/util/Collection;)Lspace/kscience/kmath/linear/MatrixWrapper;
public static final fun plus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/linear/MatrixFeature;)Lspace/kscience/kmath/linear/MatrixWrapper;
public static final fun square (Lspace/kscience/kmath/nd/Structure2D$Companion;[Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun transpose (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public static final fun zero (Lspace/kscience/kmath/linear/GenericMatrixContext;II)Lspace/kscience/kmath/nd/Structure2D;
public static final fun zero (Lspace/kscience/kmath/linear/LinearSpace;II)Lspace/kscience/kmath/nd/Structure2D;
}
public final class space/kscience/kmath/linear/OrthogonalFeature : space/kscience/kmath/linear/MatrixFeature {
@ -718,52 +617,6 @@ public abstract interface class space/kscience/kmath/linear/QRDecompositionFeatu
public abstract fun getR ()Lspace/kscience/kmath/nd/Structure2D;
}
public final class space/kscience/kmath/linear/RealMatrixContext : space/kscience/kmath/linear/MatrixContext, space/kscience/kmath/operations/ScaleOperations {
public static final field INSTANCE Lspace/kscience/kmath/linear/RealMatrixContext;
public synthetic fun add (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun add (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun binaryOperation (Ljava/lang/String;Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun binaryOperation (Ljava/lang/String;Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun binaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function2;
public synthetic fun bindSymbol (Ljava/lang/String;)Ljava/lang/Object;
public fun bindSymbol (Ljava/lang/String;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun div (Ljava/lang/Object;Ljava/lang/Number;)Ljava/lang/Object;
public fun div (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Number;)Lspace/kscience/kmath/nd/Structure2D;
public fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun dot (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public synthetic fun minus (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun minus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public final fun one (II)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun plus (Ljava/lang/Object;Ljava/lang/Object;)Ljava/lang/Object;
public fun plus (Lspace/kscience/kmath/nd/Structure2D;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun point (ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/structures/Buffer;
public fun produce (IILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun produce (IILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun scale (Ljava/lang/Object;D)Ljava/lang/Object;
public fun scale (Lspace/kscience/kmath/nd/Structure2D;D)Lspace/kscience/kmath/linear/BufferMatrix;
public fun times (DLspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun times (Ljava/lang/Number;Ljava/lang/Object;)Ljava/lang/Object;
public fun times (Ljava/lang/Number;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun times (Ljava/lang/Object;Ljava/lang/Number;)Ljava/lang/Object;
public synthetic fun times (Ljava/lang/Object;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun times (Lspace/kscience/kmath/nd/Structure2D;D)Lspace/kscience/kmath/linear/BufferMatrix;
public fun times (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Number;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun times (Lspace/kscience/kmath/nd/Structure2D;Ljava/lang/Object;)Lspace/kscience/kmath/nd/Structure2D;
public final fun toBufferMatrix (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/linear/BufferMatrix;
public synthetic fun unaryMinus (Ljava/lang/Object;)Ljava/lang/Object;
public fun unaryMinus (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public synthetic fun unaryOperation (Ljava/lang/String;Ljava/lang/Object;)Ljava/lang/Object;
public fun unaryOperation (Ljava/lang/String;Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
public fun unaryOperationFunction (Ljava/lang/String;)Lkotlin/jvm/functions/Function1;
public synthetic fun unaryPlus (Ljava/lang/Object;)Ljava/lang/Object;
public fun unaryPlus (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/nd/Structure2D;
}
public final class space/kscience/kmath/linear/RealMatrixContextKt {
public static final fun getReal (Lspace/kscience/kmath/linear/MatrixContext$Companion;)Lspace/kscience/kmath/linear/RealMatrixContext;
}
public abstract interface class space/kscience/kmath/linear/SingularValueDecompositionFeature : space/kscience/kmath/linear/MatrixFeature {
public abstract fun getS ()Lspace/kscience/kmath/nd/Structure2D;
public abstract fun getSingularValues ()Lspace/kscience/kmath/structures/Buffer;
@ -784,41 +637,6 @@ public final class space/kscience/kmath/linear/UnitFeature : space/kscience/kmat
public static final field INSTANCE Lspace/kscience/kmath/linear/UnitFeature;
}
public abstract interface class space/kscience/kmath/linear/VectorSpace : space/kscience/kmath/operations/Group, space/kscience/kmath/operations/ScaleOperations {
public static final field Companion Lspace/kscience/kmath/linear/VectorSpace$Companion;
public abstract fun add (Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun getAlgebra ()Lspace/kscience/kmath/operations/Group;
public abstract fun getSize ()I
public abstract fun getZero ()Lspace/kscience/kmath/structures/Buffer;
public abstract fun produce (Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/structures/Buffer;
public abstract fun scale (Lspace/kscience/kmath/structures/Buffer;D)Lspace/kscience/kmath/structures/Buffer;
public abstract fun unaryMinus (Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
}
public final class space/kscience/kmath/linear/VectorSpace$Companion {
public final fun buffered (ILspace/kscience/kmath/operations/Group;Lkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/linear/BufferVectorSpace;
public static synthetic fun buffered$default (Lspace/kscience/kmath/linear/VectorSpace$Companion;ILspace/kscience/kmath/operations/Group;Lkotlin/jvm/functions/Function2;ILjava/lang/Object;)Lspace/kscience/kmath/linear/BufferVectorSpace;
public final fun real (I)Lspace/kscience/kmath/linear/BufferVectorSpace;
}
public final class space/kscience/kmath/linear/VectorSpace$DefaultImpls {
public static fun add (Lspace/kscience/kmath/linear/VectorSpace;Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun binaryOperation (Lspace/kscience/kmath/linear/VectorSpace;Ljava/lang/String;Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun binaryOperationFunction (Lspace/kscience/kmath/linear/VectorSpace;Ljava/lang/String;)Lkotlin/jvm/functions/Function2;
public static fun bindSymbol (Lspace/kscience/kmath/linear/VectorSpace;Ljava/lang/String;)Lspace/kscience/kmath/structures/Buffer;
public static fun div (Lspace/kscience/kmath/linear/VectorSpace;Lspace/kscience/kmath/structures/Buffer;Ljava/lang/Number;)Lspace/kscience/kmath/structures/Buffer;
public static fun getZero (Lspace/kscience/kmath/linear/VectorSpace;)Lspace/kscience/kmath/structures/Buffer;
public static fun minus (Lspace/kscience/kmath/linear/VectorSpace;Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun plus (Lspace/kscience/kmath/linear/VectorSpace;Lspace/kscience/kmath/structures/Buffer;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun scale (Lspace/kscience/kmath/linear/VectorSpace;Lspace/kscience/kmath/structures/Buffer;D)Lspace/kscience/kmath/structures/Buffer;
public static fun times (Lspace/kscience/kmath/linear/VectorSpace;Ljava/lang/Number;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun times (Lspace/kscience/kmath/linear/VectorSpace;Lspace/kscience/kmath/structures/Buffer;Ljava/lang/Number;)Lspace/kscience/kmath/structures/Buffer;
public static fun unaryMinus (Lspace/kscience/kmath/linear/VectorSpace;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun unaryOperation (Lspace/kscience/kmath/linear/VectorSpace;Ljava/lang/String;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static fun unaryOperationFunction (Lspace/kscience/kmath/linear/VectorSpace;Ljava/lang/String;)Lkotlin/jvm/functions/Function1;
public static fun unaryPlus (Lspace/kscience/kmath/linear/VectorSpace;Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
}
public final class space/kscience/kmath/linear/VirtualMatrix : space/kscience/kmath/nd/Structure2D {
public fun <init> (IILkotlin/jvm/functions/Function2;)V
public fun elements ()Lkotlin/sequences/Sequence;
@ -826,11 +644,11 @@ public final class space/kscience/kmath/linear/VirtualMatrix : space/kscience/km
public fun get (II)Ljava/lang/Object;
public fun get ([I)Ljava/lang/Object;
public fun getColNum ()I
public fun getColumns ()Lspace/kscience/kmath/structures/Buffer;
public fun getColumns ()Ljava/util/List;
public fun getDimension ()I
public final fun getGenerator ()Lkotlin/jvm/functions/Function2;
public fun getRowNum ()I
public fun getRows ()Lspace/kscience/kmath/structures/Buffer;
public fun getRows ()Ljava/util/List;
public fun getShape ()[I
public fun hashCode ()I
}
@ -882,11 +700,11 @@ public final class space/kscience/kmath/nd/BufferNDAlgebra$DefaultImpls {
public final class space/kscience/kmath/nd/BufferNDAlgebraKt {
public static final fun field (Lspace/kscience/kmath/nd/NDAlgebra$Companion;Lspace/kscience/kmath/operations/Field;Lkotlin/jvm/functions/Function2;[I)Lspace/kscience/kmath/nd/BufferedNDField;
public static final fun group (Lspace/kscience/kmath/nd/NDAlgebra$Companion;Lspace/kscience/kmath/operations/Group;Lkotlin/jvm/functions/Function2;[I)Lspace/kscience/kmath/nd/BufferedNDGroup;
public static final fun ndField (Lspace/kscience/kmath/operations/Field;Lkotlin/jvm/functions/Function2;[ILkotlin/jvm/functions/Function1;)Ljava/lang/Object;
public static final fun ndGroup (Lspace/kscience/kmath/operations/Group;Lkotlin/jvm/functions/Function2;[ILkotlin/jvm/functions/Function1;)Ljava/lang/Object;
public static final fun ndRing (Lspace/kscience/kmath/operations/Ring;Lkotlin/jvm/functions/Function2;[ILkotlin/jvm/functions/Function1;)Ljava/lang/Object;
public static final fun ndSpace (Lspace/kscience/kmath/operations/Group;Lkotlin/jvm/functions/Function2;[ILkotlin/jvm/functions/Function1;)Ljava/lang/Object;
public static final fun ring (Lspace/kscience/kmath/nd/NDAlgebra$Companion;Lspace/kscience/kmath/operations/Ring;Lkotlin/jvm/functions/Function2;[I)Lspace/kscience/kmath/nd/BufferedNDRing;
public static final fun space (Lspace/kscience/kmath/nd/NDAlgebra$Companion;Lspace/kscience/kmath/operations/Group;Lkotlin/jvm/functions/Function2;[I)Lspace/kscience/kmath/nd/BufferedNDGroup;
}
public class space/kscience/kmath/nd/BufferedNDField : space/kscience/kmath/nd/BufferedNDRing, space/kscience/kmath/nd/NDField {
@ -1147,10 +965,10 @@ public abstract interface class space/kscience/kmath/nd/NDStructure {
public final class space/kscience/kmath/nd/NDStructure$Companion {
public final fun auto (Lkotlin/reflect/KClass;Lspace/kscience/kmath/nd/Strides;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/NDBuffer;
public final fun auto (Lkotlin/reflect/KClass;[ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/NDBuffer;
public final fun build (Lspace/kscience/kmath/nd/Strides;Lkotlin/jvm/functions/Function2;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/NDBuffer;
public final fun build ([ILkotlin/jvm/functions/Function2;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/NDBuffer;
public static synthetic fun build$default (Lspace/kscience/kmath/nd/NDStructure$Companion;Lspace/kscience/kmath/nd/Strides;Lkotlin/jvm/functions/Function2;Lkotlin/jvm/functions/Function1;ILjava/lang/Object;)Lspace/kscience/kmath/nd/NDBuffer;
public static synthetic fun build$default (Lspace/kscience/kmath/nd/NDStructure$Companion;[ILkotlin/jvm/functions/Function2;Lkotlin/jvm/functions/Function1;ILjava/lang/Object;)Lspace/kscience/kmath/nd/NDBuffer;
public final fun buffered (Lspace/kscience/kmath/nd/Strides;Lkotlin/jvm/functions/Function2;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/NDBuffer;
public final fun buffered ([ILkotlin/jvm/functions/Function2;Lkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/nd/NDBuffer;
public static synthetic fun buffered$default (Lspace/kscience/kmath/nd/NDStructure$Companion;Lspace/kscience/kmath/nd/Strides;Lkotlin/jvm/functions/Function2;Lkotlin/jvm/functions/Function1;ILjava/lang/Object;)Lspace/kscience/kmath/nd/NDBuffer;
public static synthetic fun buffered$default (Lspace/kscience/kmath/nd/NDStructure$Companion;[ILkotlin/jvm/functions/Function2;Lkotlin/jvm/functions/Function1;ILjava/lang/Object;)Lspace/kscience/kmath/nd/NDBuffer;
public final fun contentEquals (Lspace/kscience/kmath/nd/NDStructure;Lspace/kscience/kmath/nd/NDStructure;)Z
}
@ -1307,22 +1125,21 @@ public abstract interface class space/kscience/kmath/nd/Structure2D : space/ksci
public abstract fun get (II)Ljava/lang/Object;
public abstract fun get ([I)Ljava/lang/Object;
public abstract fun getColNum ()I
public abstract fun getColumns ()Lspace/kscience/kmath/structures/Buffer;
public abstract fun getColumns ()Ljava/util/List;
public abstract fun getRowNum ()I
public abstract fun getRows ()Lspace/kscience/kmath/structures/Buffer;
public abstract fun getRows ()Ljava/util/List;
public abstract fun getShape ()[I
}
public final class space/kscience/kmath/nd/Structure2D$Companion {
public final fun real (IILkotlin/jvm/functions/Function2;)Lspace/kscience/kmath/linear/BufferMatrix;
}
public final class space/kscience/kmath/nd/Structure2D$DefaultImpls {
public static fun elements (Lspace/kscience/kmath/nd/Structure2D;)Lkotlin/sequences/Sequence;
public static fun get (Lspace/kscience/kmath/nd/Structure2D;[I)Ljava/lang/Object;
public static fun getColumns (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/structures/Buffer;
public static fun getColumns (Lspace/kscience/kmath/nd/Structure2D;)Ljava/util/List;
public static fun getDimension (Lspace/kscience/kmath/nd/Structure2D;)I
public static fun getRows (Lspace/kscience/kmath/nd/Structure2D;)Lspace/kscience/kmath/structures/Buffer;
public static fun getRows (Lspace/kscience/kmath/nd/Structure2D;)Ljava/util/List;
public static fun getShape (Lspace/kscience/kmath/nd/Structure2D;)[I
}
@ -2298,7 +2115,6 @@ public abstract interface class space/kscience/kmath/structures/Buffer {
public final class space/kscience/kmath/structures/Buffer$Companion {
public final fun auto (Lkotlin/reflect/KClass;ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/structures/Buffer;
public final fun boxing (ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/structures/Buffer;
public final fun real-8hrHhI4 (ILkotlin/jvm/functions/Function1;)[D
}
public final class space/kscience/kmath/structures/Buffer$DefaultImpls {
@ -2306,13 +2122,16 @@ public final class space/kscience/kmath/structures/Buffer$DefaultImpls {
}
public final class space/kscience/kmath/structures/BufferKt {
public static final fun ListBuffer (ILkotlin/jvm/functions/Function1;)Ljava/util/List;
public static final fun asBuffer (Ljava/util/List;)Ljava/util/List;
public static final fun asBuffer ([Ljava/lang/Object;)Lspace/kscience/kmath/structures/ArrayBuffer;
public static final fun asIterable (Lspace/kscience/kmath/structures/Buffer;)Ljava/lang/Iterable;
public static final fun asMutableBuffer (Ljava/util/List;)Ljava/util/List;
public static final fun asReadOnly (Lspace/kscience/kmath/structures/Buffer;)Lspace/kscience/kmath/structures/Buffer;
public static final fun asSequence (Lspace/kscience/kmath/structures/Buffer;)Lkotlin/sequences/Sequence;
public static final fun getIndices (Lspace/kscience/kmath/structures/Buffer;)Lkotlin/ranges/IntRange;
}
public final class space/kscience/kmath/structures/BufferOperationKt {
public static final fun asIterable (Lspace/kscience/kmath/structures/Buffer;)Ljava/lang/Iterable;
public static final fun asSequence (Lspace/kscience/kmath/structures/Buffer;)Lkotlin/sequences/Sequence;
public static final fun toList (Lspace/kscience/kmath/structures/Buffer;)Ljava/util/List;
}
@ -2376,7 +2195,7 @@ public final class space/kscience/kmath/structures/FloatBufferKt {
public static final fun FloatBuffer (ILkotlin/jvm/functions/Function1;)[F
public static final fun FloatBuffer ([F)[F
public static final fun asBuffer ([F)[F
public static final fun getArray (Lspace/kscience/kmath/structures/MutableBuffer;)[F
public static final fun toFloatArray (Lspace/kscience/kmath/structures/Buffer;)[F
}
public final class space/kscience/kmath/structures/IntBuffer : space/kscience/kmath/structures/MutableBuffer {
@ -2412,7 +2231,7 @@ public final class space/kscience/kmath/structures/IntBufferKt {
public static final fun IntBuffer (ILkotlin/jvm/functions/Function1;)[I
public static final fun IntBuffer ([I)[I
public static final fun asBuffer ([I)[I
public static final fun getArray (Lspace/kscience/kmath/structures/MutableBuffer;)[I
public static final fun toIntArray (Lspace/kscience/kmath/structures/Buffer;)[I
}
public final class space/kscience/kmath/structures/ListBuffer : space/kscience/kmath/structures/Buffer {
@ -2470,7 +2289,7 @@ public final class space/kscience/kmath/structures/LongBufferKt {
public static final fun LongBuffer (ILkotlin/jvm/functions/Function1;)[J
public static final fun LongBuffer ([J)[J
public static final fun asBuffer ([J)[J
public static final fun getArray (Lspace/kscience/kmath/structures/MutableBuffer;)[J
public static final fun toLongArray (Lspace/kscience/kmath/structures/Buffer;)[J
}
public class space/kscience/kmath/structures/MemoryBuffer : space/kscience/kmath/structures/Buffer {
@ -2498,7 +2317,11 @@ public abstract interface class space/kscience/kmath/structures/MutableBuffer :
public final class space/kscience/kmath/structures/MutableBuffer$Companion {
public final fun auto (Lkotlin/reflect/KClass;ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/structures/MutableBuffer;
public final fun boxing (ILkotlin/jvm/functions/Function1;)Lspace/kscience/kmath/structures/MutableBuffer;
public final fun float-YxruXGw (ILkotlin/jvm/functions/Function1;)[F
public final fun int-Ye6GY2U (ILkotlin/jvm/functions/Function1;)[I
public final fun long-BuQOeTY (ILkotlin/jvm/functions/Function1;)[J
public final fun real-8hrHhI4 (ILkotlin/jvm/functions/Function1;)[D
public final fun short-1yRgbGw (ILkotlin/jvm/functions/Function1;)[S
}
public final class space/kscience/kmath/structures/MutableBuffer$DefaultImpls {
@ -2749,7 +2572,7 @@ public final class space/kscience/kmath/structures/RealBufferKt {
public static final fun RealBuffer ([D)[D
public static final fun asBuffer ([D)[D
public static final fun contentEquals-2uVC2J0 ([D[D)Z
public static final fun getArray (Lspace/kscience/kmath/structures/MutableBuffer;)[D
public static final fun toDoubleArray (Lspace/kscience/kmath/structures/Buffer;)[D
}
public final class space/kscience/kmath/structures/ShortBuffer : space/kscience/kmath/structures/MutableBuffer {
@ -2785,7 +2608,7 @@ public final class space/kscience/kmath/structures/ShortBufferKt {
public static final fun ShortBuffer (ILkotlin/jvm/functions/Function1;)[S
public static final fun ShortBuffer ([S)[S
public static final fun asBuffer ([S)[S
public static final fun getArray (Lspace/kscience/kmath/structures/MutableBuffer;)[S
public static final fun toShortArray (Lspace/kscience/kmath/structures/Buffer;)[S
}
public final class space/kscience/kmath/structures/ValueFlag : java/lang/Enum {

144
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferMatrix.kt
View File

@ -1,144 +0,0 @@
package space.kscience.kmath.linear
import space.kscience.kmath.nd.NDStructure
import space.kscience.kmath.nd.Structure2D
import space.kscience.kmath.operations.Ring
import space.kscience.kmath.operations.ScaleOperations
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.BufferFactory
import space.kscience.kmath.structures.asSequence
/**
* Alias for [Structure2D] with more familiar name.
*
* @param T the type of items.
*/
public typealias Matrix<T> = Structure2D<T>
/**
* Basic implementation of Matrix space based on [NDStructure]
*/
public class BufferMatrixContext<T : Any, A>(
public override val elementContext: A,
private val bufferFactory: BufferFactory<T>,
) : GenericMatrixContext<T, A, BufferMatrix<T>> where A : Ring<T>, A : ScaleOperations<T> {
public override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): BufferMatrix<T> {
val buffer = bufferFactory(rows * columns) { offset -> initializer(offset / columns, offset % columns) }
return BufferMatrix(rows, columns, buffer)
}
override fun scale(a: Matrix<T>, value: Double): Matrix<T> = elementContext {
produce(a.rowNum, a.colNum) { i, j ->
a[i, j] * value
}
}
public override fun point(size: Int, initializer: (Int) -> T): Point<T> = bufferFactory(size, initializer)
private fun Matrix<T>.toBufferMatrix(): BufferMatrix<T> = if (this is BufferMatrix) this else {
produce(rowNum, colNum) { i, j -> get(i, j) }
}
public fun one(rows: Int, columns: Int): Matrix<Double> = VirtualMatrix(rows, columns) { i, j ->
if (i == j) 1.0 else 0.0
} + DiagonalFeature
public override infix fun Matrix<T>.dot(other: Matrix<T>): BufferMatrix<T> {
require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
val bufferMatrix = toBufferMatrix()
val otherBufferMatrix = other.toBufferMatrix()
return elementContext {
produce(rowNum, other.colNum) { i, j ->
var res = one
for (l in 0 until colNum) {
res += bufferMatrix[i, l] * otherBufferMatrix[l, j]
}
res
}
}
}
public override infix fun Matrix<T>.dot(vector: Point<T>): Point<T> {
require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" }
val bufferMatrix = toBufferMatrix()
return elementContext {
bufferFactory(rowNum) { i ->
var res = one
for (j in 0 until colNum) {
res += bufferMatrix[i, j] * vector[j]
}
res
}
}
}
override fun add(a: Matrix<T>, b: Matrix<T>): BufferMatrix<T> {
require(a.rowNum == b.rowNum) { "Row number mismatch in matrix addition. Left side: ${a.rowNum}, right side: ${b.rowNum}" }
require(a.colNum == b.colNum) { "Column number mismatch in matrix addition. Left side: ${a.colNum}, right side: ${b.colNum}" }
val aBufferMatrix = a.toBufferMatrix()
val bBufferMatrix = b.toBufferMatrix()
return elementContext {
produce(a.rowNum, a.colNum) { i, j ->
aBufferMatrix[i, j] + bBufferMatrix[i, j]
}
}
}
// override fun multiply(a: Matrix<T>, k: Number): BufferMatrix<T> {
// val aBufferMatrix = a.toBufferMatrix()
// return elementContext {
// produce(a.rowNum, a.colNum) { i, j -> aBufferMatrix[i, j] * k.toDouble() }
// }
// }
public companion object
}
public class BufferMatrix<T : Any>(
public override val rowNum: Int,
public override val colNum: Int,
public val buffer: Buffer<T>,
) : Matrix<T> {
init {
require(buffer.size == rowNum * colNum) { "Dimension mismatch for matrix structure" }
}
override val shape: IntArray get() = intArrayOf(rowNum, colNum)
public override operator fun get(index: IntArray): T = get(index[0], index[1])
public override operator fun get(i: Int, j: Int): T = buffer[i * colNum + j]
public override fun elements(): Sequence<Pair<IntArray, T>> = sequence {
for (i in 0 until rowNum) for (j in 0 until colNum) yield(intArrayOf(i, j) to get(i, j))
}
public override fun equals(other: Any?): Boolean {
if (this === other) return true
return when (other) {
is NDStructure<*> -> NDStructure.contentEquals(this, other)
else -> false
}
}
override fun hashCode(): Int {
var result = rowNum
result = 31 * result + colNum
result = 31 * result + buffer.hashCode()
return result
}
public override fun toString(): String {
return if (rowNum <= 5 && colNum <= 5)
"Matrix(rowsNum = $rowNum, colNum = $colNum)\n" +
rows.asSequence().joinToString(prefix = "(", postfix = ")", separator = "\n ") { buffer ->
buffer.asSequence().joinToString(separator = "\t") { it.toString() }
}
else "Matrix(rowsNum = $rowNum, colNum = $colNum)"
}
}

83
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt Normal file
View File

@ -0,0 +1,83 @@
package space.kscience.kmath.linear
import space.kscience.kmath.nd.*
import space.kscience.kmath.operations.Ring
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.BufferFactory
import space.kscience.kmath.structures.VirtualBuffer
import space.kscience.kmath.structures.indices
public class BufferedLinearSpace<T : Any, A : Ring<T>>(
override val elementAlgebra: A,
private val bufferFactory: BufferFactory<T>,
) : LinearSpace<T, A> {
private fun ndRing(
rows: Int,
cols: Int,
): BufferedNDRing<T, A> = NDAlgebra.ring(elementAlgebra, bufferFactory, rows, cols)
override fun buildMatrix(rows: Int, columns: Int, initializer: A.(i: Int, j: Int) -> T): Matrix<T> =
ndRing(rows, columns).produce { (i, j) -> elementAlgebra.initializer(i, j) }.as2D()
override fun buildVector(size: Int, initializer: A.(Int) -> T): Point<T> =
bufferFactory(size) { elementAlgebra.initializer(it) }
override fun Matrix<T>.unaryMinus(): Matrix<T> = ndRing(rowNum, colNum).run {
unwrap().map { -it }.as2D()
}
override fun Matrix<T>.plus(other: Matrix<T>): Matrix<T> = ndRing(rowNum, colNum).run {
require(shape.contentEquals(other.shape)) { "Shape mismatch on Matrix::plus. Expected $shape but found ${other.shape}" }
unwrap().plus(other.unwrap()).as2D()
}
override fun Matrix<T>.minus(other: Matrix<T>): Matrix<T> = ndRing(rowNum, colNum).run {
require(shape.contentEquals(other.shape)) { "Shape mismatch on Matrix::minus. Expected $shape but found ${other.shape}" }
unwrap().minus(other.unwrap()).as2D()
}
private fun Buffer<T>.linearize() = if (this is VirtualBuffer) {
buildVector(size) { get(it) }
} else {
this
}
override fun Matrix<T>.dot(other: Matrix<T>): Matrix<T> {
require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
return elementAlgebra {
val rows = this@dot.rows.map { it.linearize() }
val columns = other.columns.map { it.linearize() }
buildMatrix(rowNum, other.colNum) { i, j ->
val r = rows[i]
val c = columns[j]
var res = zero
for (l in r.indices) {
res += r[l] * c[l]
}
res
}
}
}
override fun Matrix<T>.dot(vector: Point<T>): Point<T> {
require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" }
return elementAlgebra {
val rows = this@dot.rows.map { it.linearize() }
buildVector(rowNum) { i ->
val r = rows[i]
var res = zero
for (j in r.indices) {
res += r[j] * vector[j]
}
res
}
}
}
override fun Matrix<T>.times(value: T): Matrix<T> = ndRing(rowNum, colNum).run {
unwrap().map { it * value }.as2D()
}
}

24
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearAlgebra.kt → kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSolver.kt
View File

@ -1,25 +1,33 @@
package space.kscience.kmath.linear
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.VirtualBuffer
public typealias Point<T> = Buffer<T>
import space.kscience.kmath.nd.as1D
/**
* A group of methods to resolve equation A dot X = B, where A and B are matrices or vectors
*/
public interface LinearSolver<T : Any> {
/**
* Solve a dot x = b matrix equation and return x
*/
public fun solve(a: Matrix<T>, b: Matrix<T>): Matrix<T>
public fun solve(a: Matrix<T>, b: Point<T>): Point<T> = solve(a, b.asMatrix()).asPoint()
public fun inverse(a: Matrix<T>): Matrix<T>
/**
* Solve a dot x = b vector equation and return b
*/
public fun solve(a: Matrix<T>, b: Point<T>): Point<T> = solve(a, b.asMatrix()).asVector()
/**
* Get inverse of a matrix
*/
public fun inverse(matrix: Matrix<T>): Matrix<T>
}
/**
* Convert matrix to vector if it is possible
*/
public fun <T : Any> Matrix<T>.asPoint(): Point<T> =
public fun <T : Any> Matrix<T>.asVector(): Point<T> =
if (this.colNum == 1)
VirtualBuffer(rowNum) { get(it, 0) }
as1D()
else
error("Can't convert matrix with more than one column to vector")

202
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt Normal file
View File

@ -0,0 +1,202 @@
package space.kscience.kmath.linear
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.*
import space.kscience.kmath.operations.*
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.BufferFactory
import space.kscience.kmath.structures.RealBuffer
import kotlin.reflect.KClass
/**
* Alias for [Structure2D] with more familiar name.
*
* @param T the type of items.
*/
public typealias Matrix<T> = Structure2D<T>
/**
* Alias or using [Buffer] as a point/vector in a many-dimensional space.
*/
public typealias Point<T> = Buffer<T>
/**
* Basic operations on matrices and vectors. Operates on [Matrix].
*
* @param T the type of items in the matrices.
* @param M the type of operated matrices.
*/
public interface LinearSpace<T : Any, out A : Ring<T>> {
public val elementAlgebra: A
/**
* Produces a matrix with this context and given dimensions.
*/
public fun buildMatrix(rows: Int, columns: Int, initializer: A.(i: Int, j: Int) -> T): Matrix<T>
/**
* Produces a point compatible with matrix space (and possibly optimized for it).
*/
public fun buildVector(size: Int, initializer: A.(Int) -> T): Point<T>
public operator fun Matrix<T>.unaryMinus(): Matrix<T> = buildMatrix(rowNum, colNum) { i, j ->
-get(i, j)
}
public operator fun Point<T>.unaryMinus(): Point<T> = buildVector(size) {
-get(it)
}
/**
* Matrix sum
*/
public operator fun Matrix<T>.plus(other: Matrix<T>): Matrix<T> = buildMatrix(rowNum, colNum) { i, j ->
get(i, j) + other[i, j]
}
/**
* Vector sum
*/
public operator fun Point<T>.plus(other: Point<T>): Point<T> = buildVector(size) {
get(it) + other[it]
}
/**
* Matrix subtraction
*/
public operator fun Matrix<T>.minus(other: Matrix<T>): Matrix<T> = buildMatrix(rowNum, colNum) { i, j ->
get(i, j) - other[i, j]
}
/**
* Vector subtraction
*/
public operator fun Point<T>.minus(other: Point<T>): Point<T> = buildVector(size) {
get(it) - other[it]
}
/**
* Computes the dot product of this matrix and another one.
*
* @receiver the multiplicand.
* @param other the multiplier.
* @return the dot product.
*/
public infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T> {
require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
return elementAlgebra {
buildMatrix(rowNum, other.colNum) { i, j ->
var res = zero
for (l in 0 until colNum) {
res += this@dot[i, l] * other[l, j]
}
res
}
}
}
/**
* Computes the dot product of this matrix and a vector.
*
* @receiver the multiplicand.
* @param vector the multiplier.
* @return the dot product.
*/
public infix fun Matrix<T>.dot(vector: Point<T>): Point<T> {
require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" }
return elementAlgebra {
buildVector(rowNum) { i ->
var res = one
for (j in 0 until colNum) {
res += this@dot[i, j] * vector[j]
}
res
}
}
}
/**
* Multiplies a matrix by its element.
*
* @receiver the multiplicand.
* @param value the multiplier.
* @receiver the product.
*/
public operator fun Matrix<T>.times(value: T): Matrix<T> =
buildMatrix(rowNum, colNum) { i, j -> get(i, j) * value }
/**
* Multiplies an element by a matrix of it.
*
* @receiver the multiplicand.
* @param m the multiplier.
* @receiver the product.
*/
public operator fun T.times(m: Matrix<T>): Matrix<T> = m * this
/**
* Multiplies a vector by its element.
*
* @receiver the multiplicand.
* @param value the multiplier.
* @receiver the product.
*/
public operator fun Point<T>.times(value: T): Point<T> =
buildVector(size) { i -> get(i) * value }
/**
* Multiplies an element by a vector of it.
*
* @receiver the multiplicand.
* @param v the multiplier.
* @receiver the product.
*/
public operator fun T.times(v: Point<T>): Point<T> = v * this
/**
* Get a feature of the structure in this scope. Structure features take precedence other context features
*
* @param F the type of feature.
* @param structure the structure.
* @param type the [KClass] instance of [F].
* @return a feature object or `null` if it isn't present.
*/
@UnstableKMathAPI
public fun <F : Any> getFeature(structure: Matrix<T>, type: KClass<F>): F? = structure.getFeature(type)
public companion object {
/**
* A structured matrix with custom buffer
*/
public fun <T : Any, A : Ring<T>> buffered(
algebra: A,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
): LinearSpace<T, A> = BufferedLinearSpace(algebra, bufferFactory)
public val real: LinearSpace<Double, RealField> = buffered(RealField, ::RealBuffer)
/**
* Automatic buffered matrix, unboxed if it is possible
*/
public inline fun <reified T : Any, A : Ring<T>> auto(ring: A): LinearSpace<T, A> =
buffered(ring, Buffer.Companion::auto)
}
}
/**
* Get a feature of the structure in this scope. Structure features take precedence other context features
*
* @param T the type of items in the matrices.
* @param F the type of feature.
* @return a feature object or `null` if it isn't present.
*/
@UnstableKMathAPI
public inline fun <T : Any, reified F : Any> LinearSpace<T, *>.getFeature(structure: Matrix<T>): F? =
getFeature(structure, F::class)
public operator fun <LS : LinearSpace<*, *>, R> LS.invoke(block: LS.() -> R): R = run(block)

39
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt
View File

@ -3,16 +3,16 @@ package space.kscience.kmath.linear
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.getFeature
import space.kscience.kmath.operations.*
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.BufferAccessor2D
import space.kscience.kmath.structures.MutableBuffer
import space.kscience.kmath.structures.MutableBufferFactory
import space.kscience.kmath.structures.RealBuffer
/**
* Common implementation of [LupDecompositionFeature].
*/
public class LupDecomposition<T : Any>(
public val context: MatrixContext<T, Matrix<T>>,
public val context: LinearSpace<T, *>,
public val elementContext: Field<T>,
public val lu: Matrix<T>,
public val pivot: IntArray,
@ -62,15 +62,14 @@ public class LupDecomposition<T : Any>(
}
@PublishedApi
internal fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F, *>.abs(value: T): T =
if (value > elementContext.zero) value else elementContext { -value }
internal fun <T : Comparable<T>> LinearSpace<T, Ring<T>>.abs(value: T): T =
if (value > elementAlgebra.zero) value else elementAlgebra { -value }
/**
* Create a lup decomposition of generic matrix.
*/
public fun <T : Comparable<T>> MatrixContext<T, Matrix<T>>.lup(
public fun <T : Comparable<T>> LinearSpace<T, Field<T>>.lup(
factory: MutableBufferFactory<T>,
elementContext: Field<T>,
matrix: Matrix<T>,
checkSingular: (T) -> Boolean,
): LupDecomposition<T> {
@ -80,7 +79,7 @@ public fun <T : Comparable<T>> MatrixContext<T, Matrix<T>>.lup(
//TODO just waits for KEEP-176
BufferAccessor2D(matrix.rowNum, matrix.colNum, factory).run {
elementContext {
elementAlgebra {
val lu = create(matrix)
// Initialize permutation array and parity
@ -142,18 +141,18 @@ public fun <T : Comparable<T>> MatrixContext<T, Matrix<T>>.lup(
for (row in col + 1 until m) lu[row, col] /= luDiag
}
return LupDecomposition(this@lup, elementContext, lu.collect(), pivot, even)
return LupDecomposition(this@lup, elementAlgebra, lu.collect(), pivot, even)
}
}
}
public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F, Matrix<T>>.lup(
public inline fun <reified T : Comparable<T>> LinearSpace<T, Field<T>>.lup(
matrix: Matrix<T>,
noinline checkSingular: (T) -> Boolean,
): LupDecomposition<T> = lup(MutableBuffer.Companion::auto, elementContext, matrix, checkSingular)
): LupDecomposition<T> = lup(MutableBuffer.Companion::auto, matrix, checkSingular)
public fun MatrixContext<Double, Matrix<Double>>.lup(matrix: Matrix<Double>): LupDecomposition<Double> =
lup(Buffer.Companion::real, RealField, matrix) { it < 1e-11 }
public fun LinearSpace<Double, RealField>.lup(matrix: Matrix<Double>): LupDecomposition<Double> =
lup(::RealBuffer, matrix) { it < 1e-11 }
public fun <T : Any> LupDecomposition<T>.solveWithLup(
factory: MutableBufferFactory<T>,
@ -198,7 +197,7 @@ public fun <T : Any> LupDecomposition<T>.solveWithLup(
}
}
return context.produce(pivot.size, matrix.colNum) { i, j -> bp[i, j] }
return context.buildMatrix(pivot.size, matrix.colNum) { i, j -> bp[i, j] }
}
}
}
@ -210,18 +209,18 @@ public inline fun <reified T : Any> LupDecomposition<T>.solveWithLup(matrix: Mat
* Solves a system of linear equations *ax = b** using LUP decomposition.
*/
@OptIn(UnstableKMathAPI::class)
public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F, Matrix<T>>.solveWithLup(
public inline fun <reified T : Comparable<T>> LinearSpace<T, Field<T>>.solveWithLup(
a: Matrix<T>,
b: Matrix<T>,
noinline bufferFactory: MutableBufferFactory<T> = MutableBuffer.Companion::auto,
noinline checkSingular: (T) -> Boolean,
): Matrix<T> {
// Use existing decomposition if it is provided by matrix
val decomposition = a.getFeature() ?: lup(bufferFactory, elementContext, a, checkSingular)
val decomposition = a.getFeature() ?: lup(bufferFactory, a, checkSingular)
return decomposition.solveWithLup(bufferFactory, b)
}
public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F, Matrix<T>>.inverseWithLup(
public inline fun <reified T : Comparable<T>> LinearSpace<T, Field<T>>.inverseWithLup(
matrix: Matrix<T>,
noinline bufferFactory: MutableBufferFactory<T> = MutableBuffer.Companion::auto,
noinline checkSingular: (T) -> Boolean,
@ -229,15 +228,15 @@ public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext
@OptIn(UnstableKMathAPI::class)
public fun RealMatrixContext.solveWithLup(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> {
public fun LinearSpace<Double, RealField>.solveWithLup(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> {
// Use existing decomposition if it is provided by matrix
val bufferFactory: MutableBufferFactory<Double> = MutableBuffer.Companion::real
val decomposition: LupDecomposition<Double> = a.getFeature() ?: lup(bufferFactory, RealField, a) { it < 1e-11 }
val bufferFactory: MutableBufferFactory<Double> = ::RealBuffer
val decomposition: LupDecomposition<Double> = a.getFeature() ?: lup(bufferFactory, a) { it < 1e-11 }
return decomposition.solveWithLup(bufferFactory, b)
}
/**
* Inverses a square matrix using LUP decomposition. Non square matrix will throw a error.
*/
public fun RealMatrixContext.inverseWithLup(matrix: Matrix<Double>): Matrix<Double> =
public fun LinearSpace<Double, RealField>.inverseWithLup(matrix: Matrix<Double>): Matrix<Double> =
solveWithLup(matrix, one(matrix.rowNum, matrix.colNum))

57
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixBuilder.kt
View File

@ -1,46 +1,43 @@
package space.kscience.kmath.linear
import space.kscience.kmath.nd.Structure2D
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.BufferFactory
import space.kscience.kmath.structures.asBuffer
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.Ring
public class MatrixBuilder(public val rows: Int, public val columns: Int) {
public operator fun <T : Any> invoke(vararg elements: T): Matrix<T> {
public class MatrixBuilder<T : Any, A : Ring<T>>(
public val linearSpace: LinearSpace<T, A>,
public val rows: Int,
public val columns: Int,
) {
public operator fun invoke(vararg elements: T): Matrix<T> {
require(rows * columns == elements.size) { "The number of elements ${elements.size} is not equal $rows * $columns" }
val buffer = elements.asBuffer()
return BufferMatrix(rows, columns, buffer)
return linearSpace.buildMatrix(rows, columns) { i, j -> elements[i * columns + j] }
}
//TODO add specific matrix builder functions like diagonal, etc
}
public fun Structure2D.Companion.build(rows: Int, columns: Int): MatrixBuilder = MatrixBuilder(rows, columns)
/**
* Create a matrix builder with given number of rows and columns
*/
@UnstableKMathAPI
public fun <T : Any, A : Ring<T>> LinearSpace<T, A>.matrix(rows: Int, columns: Int): MatrixBuilder<T, A> =
MatrixBuilder(this, rows, columns)
public fun <T : Any> Structure2D.Companion.row(vararg values: T): Matrix<T> {
val buffer = values.asBuffer()
return BufferMatrix(1, values.size, buffer)
@UnstableKMathAPI
public fun <T : Any> LinearSpace<T, Ring<T>>.vector(vararg elements: T): Point<T> {
return buildVector(elements.size) { elements[it] }
}
public inline fun <reified T : Any> Structure2D.Companion.row(
public inline fun <T : Any> LinearSpace<T, Ring<T>>.row(
size: Int,
factory: BufferFactory<T> = Buffer.Companion::auto,
noinline builder: (Int) -> T,
): Matrix<T> {
val buffer = factory(size, builder)
return BufferMatrix(1, size, buffer)
}
crossinline builder: (Int) -> T,
): Matrix<T> = buildMatrix(1, size) { _, j -> builder(j) }
public fun <T : Any> Structure2D.Companion.column(vararg values: T): Matrix<T> {
val buffer = values.asBuffer()
return BufferMatrix(values.size, 1, buffer)
}
public fun <T : Any> LinearSpace<T, Ring<T>>.row(vararg values: T): Matrix<T> = row(values.size, values::get)
public inline fun <reified T : Any> Structure2D.Companion.column(
public inline fun <T : Any> LinearSpace<T, Ring<T>>.column(
size: Int,
factory: BufferFactory<T> = Buffer.Companion::auto,
noinline builder: (Int) -> T,
): Matrix<T> {
val buffer = factory(size, builder)
return BufferMatrix(size, 1, buffer)
}
crossinline builder: (Int) -> T,
): Matrix<T> = buildMatrix(size, 1) { i, _ -> builder(i) }
public fun <T : Any> LinearSpace<T, Ring<T>>.column(vararg values: T): Matrix<T> = column(values.size, values::get)

173
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixContext.kt
View File

@ -1,173 +0,0 @@
package space.kscience.kmath.linear
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.*
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.BufferFactory
import space.kscience.kmath.structures.asSequence
import kotlin.reflect.KClass
/**
* Basic operations on matrices. Operates on [Matrix].
*
* @param T the type of items in the matrices.
* @param M the type of operated matrices.
*/
public interface MatrixContext<T : Any, out M : Matrix<T>> : GroupOperations<Matrix<T>>, ScaleOperations<Matrix<T>> {
/**
* Produces a matrix with this context and given dimensions.
*/
public fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): M
/**
* Produces a point compatible with matrix space (and possibly optimized for it).
*/
public fun point(size: Int, initializer: (Int) -> T): Point<T> = Buffer.boxing(size, initializer)
@Suppress("UNCHECKED_CAST")
public override fun binaryOperationFunction(operation: String): (left: Matrix<T>, right: Matrix<T>) -> M =
when (operation) {
"dot" -> { left, right -> left dot right }
else -> super<GroupOperations>.binaryOperationFunction(operation) as (Matrix<T>, Matrix<T>) -> M
}
/**
* Computes the dot product of this matrix and another one.
*
* @receiver the multiplicand.
* @param other the multiplier.
* @return the dot product.
*/
public infix fun Matrix<T>.dot(other: Matrix<T>): M
/**
* Computes the dot product of this matrix and a vector.
*
* @receiver the multiplicand.
* @param vector the multiplier.
* @return the dot product.
*/
public infix fun Matrix<T>.dot(vector: Point<T>): Point<T>
/**
* Multiplies a matrix by its element.
*
* @receiver the multiplicand.
* @param value the multiplier.
* @receiver the product.
*/
public operator fun Matrix<T>.times(value: T): M
/**
* Multiplies an element by a matrix of it.
*
* @receiver the multiplicand.
* @param m the multiplier.
* @receiver the product.
*/
public operator fun T.times(m: Matrix<T>): M = m * this
/**
* Gets a feature from the matrix. This function may return some additional features to
* [kscience.kmath.nd.NDStructure.getFeature].
*
* @param F the type of feature.
* @param m the matrix.
* @param type the [KClass] instance of [F].
* @return a feature object or `null` if it isn't present.
*/
@UnstableKMathAPI
public fun <F : Any> getFeature(m: Matrix<T>, type: KClass<F>): F? = m.getFeature(type)
public companion object {
/**
* A structured matrix with custom buffer
*/
public fun <T : Any, A> buffered(
ring: A,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
): GenericMatrixContext<T, A, BufferMatrix<T>> where A : Ring<T>, A: ScaleOperations<T> = BufferMatrixContext(ring, bufferFactory)
/**
* Automatic buffered matrix, unboxed if it is possible
*/
public inline fun <reified T : Any, A> auto(ring: A): GenericMatrixContext<T, A, BufferMatrix<T>> where A : Ring<T>, A: ScaleOperations<T> =
buffered(ring, Buffer.Companion::auto)
}
}
/**
* Gets a feature from the matrix. This function may return some additional features to
* [kscience.kmath.nd.NDStructure.getFeature].
*
* @param T the type of items in the matrices.
* @param M the type of operated matrices.
* @param F the type of feature.
* @receiver the [MatrixContext] of [T].
* @param m the matrix.
* @return a feature object or `null` if it isn't present.
*/
@UnstableKMathAPI
public inline fun <T : Any, reified F : Any> MatrixContext<T, *>.getFeature(m: Matrix<T>): F? =
getFeature(m, F::class)
/**
* Partial implementation of [MatrixContext] for matrices of [Ring].
*
* @param T the type of items in the matrices.
* @param A the type of ring of matrix elements.
* @param M the type of operated matrices.
*/
public interface GenericMatrixContext<T : Any, A, out M : Matrix<T>> : MatrixContext<T, M> where A : Ring<T>, A : ScaleOperations<T>{
/**
* The ring over matrix elements.
*/
public val elementContext: A
public override infix fun Matrix<T>.dot(other: Matrix<T>): M {
//TODO add typed error
require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
return produce(rowNum, other.colNum) { i, j ->
val row = rows[i]
val column = other.columns[j]
elementContext { sum(row.asSequence().zip(column.asSequence(), ::multiply)) }
}
}
public override infix fun Matrix<T>.dot(vector: Point<T>): Point<T> {
//TODO add typed error
require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" }
return point(rowNum) { i ->
val row = rows[i]
elementContext { sum(row.asSequence().zip(vector.asSequence(), ::multiply)) }
}
}
public override operator fun Matrix<T>.unaryMinus(): M =
produce(rowNum, colNum) { i, j -> elementContext { -get(i, j) } }
public override fun add(a: Matrix<T>, b: Matrix<T>): M {
require(a.rowNum == b.rowNum && a.colNum == b.colNum) {
"Matrix operation dimension mismatch. [${a.rowNum},${a.colNum}] + [${b.rowNum},${b.colNum}]"
}
return produce(a.rowNum, a.colNum) { i, j -> elementContext { a[i, j] + b[i, j] } }
}
public override operator fun Matrix<T>.minus(b: Matrix<T>): M {
require(rowNum == b.rowNum && colNum == b.colNum) {
"Matrix operation dimension mismatch. [$rowNum,$colNum] - [${b.rowNum},${b.colNum}]"
}
return produce(rowNum, colNum) { i, j -> elementContext { get(i, j) + b[i, j] } }
}
//
// public override fun multiply(a: Matrix<T>, k: Number): M =
// produce(a.rowNum, a.colNum) { i, j -> elementContext { a[i, j] * k } }
public override operator fun Matrix<T>.times(value: T): M =
produce(rowNum, colNum) { i, j -> elementContext { get(i, j) * value } }
}

30
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/MatrixWrapper.kt
View File

@ -1,14 +1,9 @@
package space.kscience.kmath.linear
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.Structure2D
import space.kscience.kmath.nd.getFeature
import space.kscience.kmath.operations.Ring
import space.kscience.kmath.operations.ScaleOperations
import space.kscience.kmath.structures.asBuffer
import kotlin.math.sqrt
import kotlin.reflect.KClass
import kotlin.reflect.safeCast
/**
* A [Matrix] that holds [MatrixFeature] objects.
@ -24,7 +19,8 @@ public class MatrixWrapper<T : Any> internal constructor(
* Get the first feature matching given class. Does not guarantee that matrix has only one feature matching the criteria
*/
@UnstableKMathAPI
override fun <T : Any> getFeature(type: KClass<T>): T? = type.safeCast(features.find { type.isInstance(it) })
@Suppress("UNCHECKED_CAST")
override fun <T : Any> getFeature(type: KClass<T>): T? = features.singleOrNull { type.isInstance(it) } as? T
?: origin.getFeature(type)
override fun equals(other: Any?): Boolean = origin == other
@ -61,35 +57,25 @@ public operator fun <T : Any> Matrix<T>.plus(newFeatures: Collection<MatrixFeatu
MatrixWrapper(this, newFeatures.toSet())
}
/**
* Build a square matrix from given elements.
*/
public fun <T : Any> Structure2D.Companion.square(vararg elements: T): Matrix<T> {
val size: Int = sqrt(elements.size.toDouble()).toInt()
require(size * size == elements.size) { "The number of elements ${elements.size} is not a full square" }
val buffer = elements.asBuffer()
return BufferMatrix(size, size, buffer)
}
/**
* Diagonal matrix of ones. The matrix is virtual no actual matrix is created
*/
public fun <T : Any, A> GenericMatrixContext<T, A, *>.one(
public fun <T : Any> LinearSpace<T, Ring<T>>.one(
rows: Int,
columns: Int,
): Matrix<T> where A : Ring<T>, A : ScaleOperations<T> = VirtualMatrix(rows, columns) { i, j ->
if (i == j) elementContext.one else elementContext.zero
): Matrix<T> = VirtualMatrix(rows, columns) { i, j ->
if (i == j) elementAlgebra.one else elementAlgebra.zero
} + UnitFeature
/**
* A virtual matrix of zeroes
*/
public fun <T : Any, A> GenericMatrixContext<T, A, *>.zero(
public fun <T : Any> LinearSpace<T, Ring<T>>.zero(
rows: Int,
columns: Int,
): Matrix<T> where A : Ring<T>, A : ScaleOperations<T> = VirtualMatrix(rows, columns) { _, _ ->
elementContext.zero
): Matrix<T> = VirtualMatrix(rows, columns) { _, _ ->
elementAlgebra.zero
} + ZeroFeature
public class TransposedFeature<T : Any>(public val original: Matrix<T>) : MatrixFeature

85
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/RealMatrixContext.kt
View File

@ -1,85 +0,0 @@
package space.kscience.kmath.linear
import space.kscience.kmath.operations.ScaleOperations
import space.kscience.kmath.structures.RealBuffer
public object RealMatrixContext : MatrixContext<Double, BufferMatrix<Double>>, ScaleOperations<Matrix<Double>> {
public override fun produce(
rows: Int,
columns: Int,
initializer: (i: Int, j: Int) -> Double,
): BufferMatrix<Double> {
val buffer = RealBuffer(rows * columns) { offset -> initializer(offset / columns, offset % columns) }
return BufferMatrix(rows, columns, buffer)
}
public fun Matrix<Double>.toBufferMatrix(): BufferMatrix<Double> = if (this is BufferMatrix) this else {
produce(rowNum, colNum) { i, j -> get(i, j) }
}
public fun one(rows: Int, columns: Int): Matrix<Double> = VirtualMatrix(rows, columns) { i, j ->
if (i == j) 1.0 else 0.0
} + DiagonalFeature
override fun Matrix<Double>.unaryMinus(): Matrix<Double> = produce(rowNum, colNum) { i, j -> -get(i, j) }
public override infix fun Matrix<Double>.dot(other: Matrix<Double>): BufferMatrix<Double> {
require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
val bufferMatrix = toBufferMatrix()
val otherBufferMatrix = other.toBufferMatrix()
return produce(rowNum, other.colNum) { i, j ->
var res = 0.0
for (l in 0 until colNum) {
res += bufferMatrix[i, l] * otherBufferMatrix[l, j]
}
res
}
}
public override infix fun Matrix<Double>.dot(vector: Point<Double>): Point<Double> {
require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" }
val bufferMatrix = toBufferMatrix()
return RealBuffer(rowNum) { i ->
var res = 0.0
for (j in 0 until colNum) {
res += bufferMatrix[i, j] * vector[j]
}
res
}
}
override fun add(a: Matrix<Double>, b: Matrix<Double>): BufferMatrix<Double> {
require(a.rowNum == b.rowNum) { "Row number mismatch in matrix addition. Left side: ${a.rowNum}, right side: ${b.rowNum}" }
require(a.colNum == b.colNum) { "Column number mismatch in matrix addition. Left side: ${a.colNum}, right side: ${b.colNum}" }
val aBufferMatrix = a.toBufferMatrix()
val bBufferMatrix = b.toBufferMatrix()
return produce(a.rowNum, a.colNum) { i, j ->
aBufferMatrix[i, j] + bBufferMatrix[i, j]
}
}
override fun scale(a: Matrix<Double>, value: Double): BufferMatrix<Double> {
val bufferMatrix = a.toBufferMatrix()
return produce(a.rowNum, a.colNum) { i, j -> bufferMatrix[i, j] * value }
}
override fun Matrix<Double>.times(value: Double): BufferMatrix<Double> = scale(this, value)
//
// override fun multiply(a: Matrix<Double>, k: Number): BufferMatrix<Double> {
// val aBufferMatrix = a.toBufferMatrix()
// return produce(a.rowNum, a.colNum) { i, j -> aBufferMatrix[i, j] * k.toDouble() }
// }
//
// override fun divide(a: Matrix<Double>, k: Number): BufferMatrix<Double> {
// val aBufferMatrix = a.toBufferMatrix()
// return produce(a.rowNum, a.colNum) { i, j -> aBufferMatrix[i, j] / k.toDouble() }
// }
}
/**
* Partially optimized real-valued matrix
*/
public val MatrixContext.Companion.real: RealMatrixContext get() = RealMatrixContext

72
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VectorSpace.kt
View File

@ -1,72 +0,0 @@
package space.kscience.kmath.linear
import space.kscience.kmath.operations.Group
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.ScaleOperations
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.BufferFactory
/**
* A linear space for vectors.
* Could be used on any point-like structure
*/
public interface VectorSpace<T : Any, A> : Group<Point<T>>, ScaleOperations<Point<T>>
where A : Group<T>, A : ScaleOperations<T> {
public val size: Int
public val algebra: A
override val zero: Point<T> get() = produce { algebra.zero }
public fun produce(initializer: A.(Int) -> T): Point<T>
override fun add(a: Point<T>, b: Point<T>): Point<T> = produce { algebra { a[it] + b[it] } }
override fun scale(a: Point<T>, value: Double): Point<T> = produce { algebra.scale(a[it], value) }
override fun Point<T>.unaryMinus(): Point<T> = produce { -get(it) }
//TODO add basis
public companion object {
private val realSpaceCache: MutableMap<Int, BufferVectorSpace<Double, RealField>> = hashMapOf()
/**
* Non-boxing double vector space
*/
public fun real(size: Int): BufferVectorSpace<Double, RealField> = realSpaceCache.getOrPut(size) {
BufferVectorSpace(
size,
RealField,
Buffer.Companion::auto
)
}
/**
* A structured vector space with custom buffer
*/
public fun <T : Any, A> buffered(
size: Int,
space: A,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
): BufferVectorSpace<T, A> where A : Group<T>, A : ScaleOperations<T> =
BufferVectorSpace(size, space, bufferFactory)
/**
* Automatic buffered vector, unboxed if it is possible
*/
public inline fun <reified T : Any, A> auto(
size: Int,
space: A,
): VectorSpace<T, A> where A : Group<T>, A : ScaleOperations<T> =
buffered(size, space, Buffer.Companion::auto)
}
}
public class BufferVectorSpace<T : Any, A>(
override val size: Int,
override val algebra: A,
public val bufferFactory: BufferFactory<T>,
) : VectorSpace<T, A> where A : Group<T>, A : ScaleOperations<T> {
override fun produce(initializer: A.(Int) -> T): Buffer<T> = bufferFactory(size) { algebra.initializer(it) }
}

14
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt
View File

@ -1,5 +1,7 @@
package space.kscience.kmath.linear
import space.kscience.kmath.nd.NDStructure
/**
* The matrix where each element is evaluated each time when is being accessed.
*
@ -8,7 +10,7 @@ package space.kscience.kmath.linear
public class VirtualMatrix<T : Any>(
override val rowNum: Int,
override val colNum: Int,
public val generator: (i: Int, j: Int) -> T
public val generator: (i: Int, j: Int) -> T,
) : Matrix<T> {
override val shape: IntArray get() = intArrayOf(rowNum, colNum)
@ -17,12 +19,8 @@ public class VirtualMatrix<T : Any>(
override fun equals(other: Any?): Boolean {
if (this === other) return true
if (other !is Matrix<*>) return false
if (rowNum != other.rowNum) return false
if (colNum != other.colNum) return false
return elements().all { (index, value) -> value == other[index] }
if (other !is NDStructure<*>) return false
return NDStructure.contentEquals(this, other)
}
override fun hashCode(): Int {
@ -31,6 +29,4 @@ public class VirtualMatrix<T : Any>(
result = 31 * result + generator.hashCode()
return result
}
}

8
kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/BufferNDAlgebra.kt
View File

@ -79,20 +79,20 @@ public open class BufferedNDField<T, R : Field<T>>(
override fun scale(a: NDStructure<T>, value: Double): NDStructure<T> = a.map { it * value }
}
// space factories
public fun <T, A : Group<T>> NDAlgebra.Companion.space(
// group factories
public fun <T, A : Group<T>> NDAlgebra.Companion.group(
space: A,
bufferFactory: BufferFactory<T>,
vararg shape: Int,
): BufferedNDGroup<T, A> = BufferedNDGroup(shape, space, bufferFactory)
public inline fun <T, A : Group<T>, R> A.ndSpace(
public inline fun <T, A : Group<T>, R> A.ndGroup(
noinline bufferFactory: BufferFactory<T>,
vararg shape: Int,
action: BufferedNDGroup<T, A>.() -> R,
): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return NDAlgebra.space(this, bufferFactory, *shape).run(action)
return NDAlgebra.group(this, bufferFactory, *shape).run(action)
}
//ring factories

28
kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/NDAlgebra.kt
View File

@ -1,7 +1,9 @@
package space.kscience.kmath.nd
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.*
import space.kscience.kmath.structures.*
import kotlin.reflect.KClass
/**
* An exception is thrown when the expected ans actual shape of NDArray differs.
@ -56,16 +58,40 @@ public interface NDAlgebra<T, C: Algebra<T>> {
public operator fun Function1<T, T>.invoke(structure: NDStructure<T>): NDStructure<T> =
structure.map { value -> this@invoke(value) }
/**
* Get a feature of the structure in this scope. Structure features take precedence other context features
*
* @param F the type of feature.
* @param structure the structure.
* @param type the [KClass] instance of [F].
* @return a feature object or `null` if it isn't present.
*/
@UnstableKMathAPI
public fun <F : Any> getFeature(structure: NDStructure<T>, type: KClass<F>): F? = structure.getFeature(type)
public companion object
}
/**
* Get a feature of the structure in this scope. Structure features take precedence other context features
*
* @param T the type of items in the matrices.
* @param F the type of feature.
* @return a feature object or `null` if it isn't present.
*/
@UnstableKMathAPI
public inline fun <T : Any, reified F : Any> NDAlgebra<T, *>.getFeature(structure: NDStructure<T>): F? =
getFeature(structure, F::class)
/**
* Checks if given elements are consistent with this context.
*
* @param structures the structures to check.
* @return the array of valid structures.
*/
internal fun <T, C: Algebra<T>> NDAlgebra<T, C>.checkShape(vararg structures: NDStructure<T>): Array<out NDStructure<T>> = structures
internal fun <T, C : Algebra<T>> NDAlgebra<T, C>.checkShape(vararg structures: NDStructure<T>): Array<out NDStructure<T>> =
structures
.map(NDStructure<T>::shape)
.singleOrNull { !shape.contentEquals(it) }
?.let<IntArray, Array<out NDStructure<T>>> { throw ShapeMismatchException(shape, it) }

12
kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/NDStructure.kt
View File

@ -48,11 +48,11 @@ public interface NDStructure<T> {
public override fun hashCode(): Int
/**
* Feature is additional property or hint that does not directly affect the structure, but could in some cases help
* optimize operations and performance. If the feature is not present, null is defined.
* Feature is some additional strucure information which allows to access it special properties or hints.
* If the feature is not present, null is returned.
*/
@UnstableKMathAPI
public fun <T : Any> getFeature(type: KClass<T>): T? = null
public fun <F : Any> getFeature(type: KClass<F>): F? = null
public companion object {
/**
@ -74,7 +74,7 @@ public interface NDStructure<T> {
*
* Strides should be reused if possible.
*/
public fun <T> build(
public fun <T> buffered(
strides: Strides,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
initializer: (IntArray) -> T,
@ -94,11 +94,11 @@ public interface NDStructure<T> {
crossinline initializer: (IntArray) -> T,
): NDBuffer<T> = NDBuffer(strides, Buffer.auto(type, strides.linearSize) { i -> initializer(strides.index(i)) })
public fun <T> build(
public fun <T> buffered(
shape: IntArray,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
initializer: (IntArray) -> T,
): NDBuffer<T> = build(DefaultStrides(shape), bufferFactory, initializer)
): NDBuffer<T> = buffered(DefaultStrides(shape), bufferFactory, initializer)
public inline fun <reified T : Any> auto(
shape: IntArray,

3
kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/RealNDField.kt
View File

@ -5,7 +5,6 @@ import space.kscience.kmath.operations.ExtendedField
import space.kscience.kmath.operations.NumbersAddOperations
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.ScaleOperations
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.RealBuffer
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@ -13,7 +12,7 @@ import kotlin.contracts.contract
@OptIn(UnstableKMathAPI::class)
public class RealNDField(
shape: IntArray,
) : BufferedNDField<Double, RealField>(shape, RealField, Buffer.Companion::real),
) : BufferedNDField<Double, RealField>(shape, RealField, ::RealBuffer),
NumbersAddOperations<NDStructure<Double>>,
ScaleOperations<NDStructure<Double>>,
ExtendedField<NDStructure<Double>> {

19
kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt
View File

@ -45,12 +45,23 @@ private inline class Buffer1DWrapper<T>(val buffer: Buffer<T>) : Structure1D<T>
/**
* Represent a [NDStructure] as [Structure1D]. Throw error in case of dimension mismatch
*/
public fun <T> NDStructure<T>.as1D(): Structure1D<T> = if (shape.size == 1) {
if (this is NDBuffer) Buffer1DWrapper(this.buffer) else Structure1DWrapper(this)
} else
error("Can't create 1d-structure from ${shape.size}d-structure")
public fun <T> NDStructure<T>.as1D(): Structure1D<T> = this as? Structure1D<T> ?: if (shape.size == 1) {
when (this) {
is NDBuffer -> Buffer1DWrapper(this.buffer)
else -> Structure1DWrapper(this)
}
} else error("Can't create 1d-structure from ${shape.size}d-structure")
/**
* Represent this buffer as 1D structure
*/
public fun <T> Buffer<T>.asND(): Structure1D<T> = Buffer1DWrapper(this)
/**
* Expose inner buffer of this [Structure1D] if possible
*/
internal fun <T : Any> Structure1D<T>.unwrap(): Buffer<T> = when {
this is Buffer1DWrapper<T> -> buffer
this is Structure1DWrapper && structure is NDBuffer<T> -> structure.buffer
else -> this
}

47
kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure2D.kt
View File

@ -1,9 +1,9 @@
package space.kscience.kmath.nd
import space.kscience.kmath.linear.BufferMatrix
import space.kscience.kmath.linear.RealMatrixContext
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.VirtualBuffer
import kotlin.reflect.KClass
/**
* A structure that is guaranteed to be two-dimensional.
@ -26,14 +26,14 @@ public interface Structure2D<T> : NDStructure<T> {
/**
* The buffer of rows of this structure. It gets elements from the structure dynamically.
*/
public val rows: Buffer<Buffer<T>>
get() = VirtualBuffer(rowNum) { i -> VirtualBuffer(colNum) { j -> get(i, j) } }
public val rows: List<Buffer<T>>
get() = List(rowNum) { i -> VirtualBuffer(colNum) { j -> get(i, j) } }
/**
* The buffer of columns of this structure. It gets elements from the structure dynamically.
*/
public val columns: Buffer<Buffer<T>>
get() = VirtualBuffer(colNum) { j -> VirtualBuffer(rowNum) { i -> get(i, j) } }
public val columns: List<Buffer<T>>
get() = List(colNum) { j -> VirtualBuffer(rowNum) { i -> get(i, j) } }
/**
* Retrieves an element from the structure by two indices.
@ -54,21 +54,13 @@ public interface Structure2D<T> : NDStructure<T> {
for (j in 0 until colNum) yield(intArrayOf(i, j) to get(i, j))
}
public companion object {
public inline fun real(
rows: Int,
columns: Int,
crossinline init: (i: Int, j: Int) -> Double,
): BufferMatrix<Double> = RealMatrixContext.produce(rows,columns) { i, j ->
init(i, j)
}
}
public companion object
}
/**
* A 2D wrapper for nd-structure
*/
private inline class Structure2DWrapper<T>(val structure: NDStructure<T>) : Structure2D<T> {
private class Structure2DWrapper<T>(val structure: NDStructure<T>) : Structure2D<T> {
override val shape: IntArray get() = structure.shape
override val rowNum: Int get() = shape[0]
@ -76,20 +68,27 @@ private inline class Structure2DWrapper<T>(val structure: NDStructure<T>) : Stru
override operator fun get(i: Int, j: Int): T = structure[i, j]
@UnstableKMathAPI
override fun <F : Any> getFeature(type: KClass<F>): F? = structure.getFeature(type)
override fun elements(): Sequence<Pair<IntArray, T>> = structure.elements()
override fun equals(other: Any?): Boolean = structure == other
override fun hashCode(): Int = structure.hashCode()
}
/**
* Represent a [NDStructure] as [Structure1D]. Throw error in case of dimension mismatch
*/
public fun <T> NDStructure<T>.as2D(): Structure2D<T> = if (shape.size == 2)
Structure2DWrapper(this)
else
error("Can't create 2d-structure from ${shape.size}d-structure")
public fun <T> NDStructure<T>.as2D(): Structure2D<T> = this as? Structure2D<T> ?: when (shape.size) {
2 -> Structure2DWrapper(this)
else -> error("Can't create 2d-structure from ${shape.size}d-structure")
}
/**
* Alias for [Structure2D] with more familiar name.
*
* @param T the type of items in the matrix.
* Expose inner [NDStructure] if possible
*/
public typealias Matrix<T> = Structure2D<T>
internal fun <T> Structure2D<T>.unwrap(): NDStructure<T> =
if (this is Structure2DWrapper) structure
else this

130
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/Buffer.kt
View File

@ -44,21 +44,12 @@ public interface Buffer<out T> {
asSequence().mapIndexed { index, value -> value == other[index] }.all { it }
public companion object {
/**
* Creates a [RealBuffer] with the specified [size], where each element is calculated by calling the specified
* [initializer] function.
*/
public inline fun real(size: Int, initializer: (Int) -> Double): RealBuffer =
RealBuffer(size) { initializer(it) }
/**
* Creates a [ListBuffer] of given type [T] with given [size]. Each element is calculated by calling the
* specified [initializer] function.
*/
public inline fun <T> boxing(size: Int, initializer: (Int) -> T): Buffer<T> =
ListBuffer(List(size, initializer))
// TODO add resolution based on Annotation or companion resolution
List(size, initializer).asBuffer()
/**
* Creates a [Buffer] of given [type]. If the type is primitive, specialized buffers are used ([IntBuffer],
@ -69,11 +60,11 @@ public interface Buffer<out T> {
@Suppress("UNCHECKED_CAST")
public inline fun <T : Any> auto(type: KClass<T>, size: Int, initializer: (Int) -> T): Buffer<T> =
when (type) {
Double::class -> RealBuffer(size) { initializer(it) as Double } as Buffer<T>
Short::class -> ShortBuffer(size) { initializer(it) as Short } as Buffer<T>
Int::class -> IntBuffer(size) { initializer(it) as Int } as Buffer<T>
Long::class -> LongBuffer(size) { initializer(it) as Long } as Buffer<T>
Float::class -> FloatBuffer(size) { initializer(it) as Float } as Buffer<T>
Double::class -> MutableBuffer.real(size) { initializer(it) as Double } as Buffer<T>
Short::class -> MutableBuffer.short(size) { initializer(it) as Short } as Buffer<T>
Int::class -> MutableBuffer.int(size) { initializer(it) as Int } as Buffer<T>
Long::class -> MutableBuffer.long(size) { initializer(it) as Long } as Buffer<T>
Float::class -> MutableBuffer.float(size) { initializer(it) as Float } as Buffer<T>
else -> boxing(size, initializer)
}
@ -89,21 +80,6 @@ public interface Buffer<out T> {
}
}
/**
* Creates a sequence that returns all elements from this [Buffer].
*/
public fun <T> Buffer<T>.asSequence(): Sequence<T> = Sequence(::iterator)
/**
* Creates an iterable that returns all elements from this [Buffer].
*/
public fun <T> Buffer<T>.asIterable(): Iterable<T> = Iterable(::iterator)
/**
* Converts this [Buffer] to a new [List]
*/
public fun <T> Buffer<T>.toList(): List<T> = asSequence().toList()
/**
* Returns an [IntRange] of the valid indices for this [Buffer].
*/
@ -126,6 +102,44 @@ public interface MutableBuffer<T> : Buffer<T> {
public fun copy(): MutableBuffer<T>
public companion object {
/**
* Creates a [RealBuffer] with the specified [size], where each element is calculated by calling the specified
* [initializer] function.
*/
public inline fun real(size: Int, initializer: (Int) -> Double): RealBuffer =
RealBuffer(size, initializer)
/**
* Creates a [ShortBuffer] with the specified [size], where each element is calculated by calling the specified
* [initializer] function.
*/
public inline fun short(size: Int, initializer: (Int) -> Short): ShortBuffer =
ShortBuffer(size, initializer)
/**
* Creates a [IntBuffer] with the specified [size], where each element is calculated by calling the specified
* [initializer] function.
*/
public inline fun int(size: Int, initializer: (Int) -> Int): IntBuffer =
IntBuffer(size, initializer)
/**
* Creates a [LongBuffer] with the specified [size], where each element is calculated by calling the specified
* [initializer] function.
*/
public inline fun long(size: Int, initializer: (Int) -> Long): LongBuffer =
LongBuffer(size, initializer)
/**
* Creates a [FloatBuffer] with the specified [size], where each element is calculated by calling the specified
* [initializer] function.
*/
public inline fun float(size: Int, initializer: (Int) -> Float): FloatBuffer =
FloatBuffer(size, initializer)
/**
* Create a boxing mutable buffer of given type
*/
@ -141,11 +155,11 @@ public interface MutableBuffer<T> : Buffer<T> {
@Suppress("UNCHECKED_CAST")
public inline fun <T : Any> auto(type: KClass<out T>, size: Int, initializer: (Int) -> T): MutableBuffer<T> =
when (type) {
Double::class -> RealBuffer(size) { initializer(it) as Double } as MutableBuffer<T>
Short::class -> ShortBuffer(size) { initializer(it) as Short } as MutableBuffer<T>
Int::class -> IntBuffer(size) { initializer(it) as Int } as MutableBuffer<T>
Float::class -> FloatBuffer(size) { initializer(it) as Float } as MutableBuffer<T>
Long::class -> LongBuffer(size) { initializer(it) as Long } as MutableBuffer<T>
Double::class -> real(size) { initializer(it) as Double } as MutableBuffer<T>
Short::class -> short(size) { initializer(it) as Short } as MutableBuffer<T>
Int::class -> int(size) { initializer(it) as Int } as MutableBuffer<T>
Float::class -> float(size) { initializer(it) as Float } as MutableBuffer<T>
Long::class -> long(size) { initializer(it) as Long } as MutableBuffer<T>
else -> boxing(size, initializer)
}
@ -158,13 +172,6 @@ public interface MutableBuffer<T> : Buffer<T> {
@Suppress("UNCHECKED_CAST")
public inline fun <reified T : Any> auto(size: Int, initializer: (Int) -> T): MutableBuffer<T> =
auto(T::class, size, initializer)
/**
* Creates a [RealBuffer] with the specified [size], where each element is calculated by calling the specified
* [initializer] function.
*/
public inline fun real(size: Int, initializer: (Int) -> Double): RealBuffer =
RealBuffer(size) { initializer(it) }
}
}
@ -187,15 +194,6 @@ public inline class ListBuffer<T>(public val list: List<T>) : Buffer<T> {
*/
public fun <T> List<T>.asBuffer(): ListBuffer<T> = ListBuffer(this)
/**
* Creates a new [ListBuffer] with the specified [size], where each element is calculated by calling the specified
* [init] function.
*
* The function [init] is called for each array element sequentially starting from the first one.
* It should return the value for an array element given its index.
*/
public inline fun <T> ListBuffer(size: Int, init: (Int) -> T): ListBuffer<T> = List(size, init).asBuffer()
/**
* [MutableBuffer] implementation over [MutableList].
*
@ -216,16 +214,20 @@ public inline class MutableListBuffer<T>(public val list: MutableList<T>) : Muta
override fun copy(): MutableBuffer<T> = MutableListBuffer(ArrayList(list))
}
/**
* Returns an [ListBuffer] that wraps the original list.
*/
public fun <T> MutableList<T>.asMutableBuffer(): MutableListBuffer<T> = MutableListBuffer(this)
/**
* [MutableBuffer] implementation over [Array].
*
* @param T the type of elements contained in the buffer.
* @property array The underlying array.
*/
public class ArrayBuffer<T>(private val array: Array<T>) : MutableBuffer<T> {
public class ArrayBuffer<T>(internal val array: Array<T>) : MutableBuffer<T> {
// Can't inline because array is invariant
override val size: Int
get() = array.size
override val size: Int get() = array.size
override operator fun get(index: Int): T = array[index]
@ -243,16 +245,6 @@ public class ArrayBuffer<T>(private val array: Array<T>) : MutableBuffer<T> {
*/
public fun <T> Array<T>.asBuffer(): ArrayBuffer<T> = ArrayBuffer(this)
/**
* Creates a new [ArrayBuffer] with the specified [size], where each element is calculated by calling the specified
* [init] function.
*
* The function [init] is called for each array element sequentially starting from the first one.
* It should return the value for an array element given its index.
*/
public inline fun <reified T> ArrayBuffer(size: Int, init: (Int) -> T): ArrayBuffer<T> =
Array(size) { i -> init(i) }.asBuffer()
/**
* Immutable wrapper for [MutableBuffer].
*
@ -294,13 +286,3 @@ public class VirtualBuffer<T>(override val size: Int, private val generator: (In
* Convert this buffer to read-only buffer.
*/
public fun <T> Buffer<T>.asReadOnly(): Buffer<T> = if (this is MutableBuffer) ReadOnlyBuffer(this) else this
/**
* Typealias for buffer transformations.
*/
public typealias BufferTransform<T, R> = (Buffer<T>) -> Buffer<R>
/**
* Typealias for buffer transformations with suspend function.
*/
public typealias SuspendBufferTransform<T, R> = suspend (Buffer<T>) -> Buffer<R>

6
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt
View File

@ -13,10 +13,10 @@ internal class BufferAccessor2D<T : Any>(
public val colNum: Int,
val factory: MutableBufferFactory<T>,
) {
public operator fun Buffer<T>.get(i: Int, j: Int): T = get(i + colNum * j)
public operator fun Buffer<T>.get(i: Int, j: Int): T = get(i * colNum + j)
public operator fun MutableBuffer<T>.set(i: Int, j: Int, value: T) {
set(i + colNum * j, value)
set(i * colNum + j, value)
}
public inline fun create(crossinline init: (i: Int, j: Int) -> T): MutableBuffer<T> =
@ -25,7 +25,7 @@ internal class BufferAccessor2D<T : Any>(
public fun create(mat: Structure2D<T>): MutableBuffer<T> = create { i, j -> mat[i, j] }
//TODO optimize wrapper
public fun MutableBuffer<T>.collect(): Structure2D<T> = NDStructure.build(
public fun MutableBuffer<T>.collect(): Structure2D<T> = NDStructure.buffered(
DefaultStrides(intArrayOf(rowNum, colNum)),
factory
) { (i, j) ->

8
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FloatBuffer.kt
View File

@ -36,10 +36,12 @@ public inline fun FloatBuffer(size: Int, init: (Int) -> Float): FloatBuffer = Fl
public fun FloatBuffer(vararg floats: Float): FloatBuffer = FloatBuffer(floats)
/**
* Returns a [FloatArray] containing all of the elements of this [MutableBuffer].
* Returns a new [FloatArray] containing all of the elements of this [Buffer].
*/
public val MutableBuffer<out Float>.array: FloatArray
get() = (if (this is FloatBuffer) array else FloatArray(size) { get(it) })
public fun Buffer<Float>.toFloatArray(): FloatArray = when (this) {
is FloatBuffer -> array.copyOf()
else -> FloatArray(size, ::get)
}
/**
* Returns [FloatBuffer] over this array.

8
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/IntBuffer.kt
View File

@ -35,10 +35,12 @@ public inline fun IntBuffer(size: Int, init: (Int) -> Int): IntBuffer = IntBuffe
public fun IntBuffer(vararg ints: Int): IntBuffer = IntBuffer(ints)
/**
* Returns a [IntArray] containing all of the elements of this [MutableBuffer].
* Returns a new [IntArray] containing all of the elements of this [Buffer].
*/
public val MutableBuffer<out Int>.array: IntArray
get() = (if (this is IntBuffer) array else IntArray(size) { get(it) })
public fun Buffer<Int>.toIntArray(): IntArray = when (this) {
is IntBuffer -> array.copyOf()
else -> IntArray(size, ::get)
}
/**
* Returns [IntBuffer] over this array.

8
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/LongBuffer.kt
View File

@ -35,10 +35,12 @@ public inline fun LongBuffer(size: Int, init: (Int) -> Long): LongBuffer = LongB
public fun LongBuffer(vararg longs: Long): LongBuffer = LongBuffer(longs)
/**
* Returns a [IntArray] containing all of the elements of this [MutableBuffer].
* Returns a new [LongArray] containing all of the elements of this [Buffer].
*/
public val MutableBuffer<out Long>.array: LongArray
get() = (if (this is LongBuffer) array else LongArray(size) { get(it) })
public fun Buffer<Long>.toLongArray(): LongArray = when (this) {
is LongBuffer -> array.copyOf()
else -> LongArray(size, ::get)
}
/**
* Returns [LongBuffer] over this array.

4
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt
View File

@ -24,7 +24,7 @@ public open class MemoryBuffer<T : Any>(protected val memory: Memory, protected
public inline fun <T : Any> create(
spec: MemorySpec<T>,
size: Int,
initializer: (Int) -> T
initializer: (Int) -> T,
): MemoryBuffer<T> = MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
(0 until size).forEach { buffer[it] = initializer(it) }
}
@ -53,7 +53,7 @@ public class MutableMemoryBuffer<T : Any>(memory: Memory, spec: MemorySpec<T>) :
public inline fun <T : Any> create(
spec: MemorySpec<T>,
size: Int,
initializer: (Int) -> T
initializer: (Int) -> T,
): MutableMemoryBuffer<T> = MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
(0 until size).forEach { buffer[it] = initializer(it) }
}

8
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/RealBuffer.kt
View File

@ -40,10 +40,12 @@ public fun RealBuffer(vararg doubles: Double): RealBuffer = RealBuffer(doubles)
public fun RealBuffer.contentEquals(vararg doubles: Double): Boolean = array.contentEquals(doubles)
/**
* Returns a [DoubleArray] containing all of the elements of this [MutableBuffer].
* Returns a new [DoubleArray] containing all of the elements of this [Buffer].
*/
public val MutableBuffer<out Double>.array: DoubleArray
get() = (if (this is RealBuffer) array else DoubleArray(size) { get(it) })
public fun Buffer<Double>.toDoubleArray(): DoubleArray = when (this) {
is RealBuffer -> array.copyOf()
else -> DoubleArray(size, ::get)
}
/**
* Returns [RealBuffer] over this array.

8
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt
View File

@ -33,10 +33,12 @@ public inline fun ShortBuffer(size: Int, init: (Int) -> Short): ShortBuffer = Sh
public fun ShortBuffer(vararg shorts: Short): ShortBuffer = ShortBuffer(shorts)
/**
* Returns a [ShortArray] containing all of the elements of this [MutableBuffer].
* Returns a new [ShortArray] containing all of the elements of this [Buffer].
*/
public val MutableBuffer<out Short>.array: ShortArray
get() = (if (this is ShortBuffer) array else ShortArray(size) { get(it) })
public fun Buffer<Short>.toShortArray(): ShortArray = when (this) {
is ShortBuffer -> array.copyOf()
else -> ShortArray(size, ::get)
}
/**
* Returns [ShortBuffer] over this array.

84
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferOperation.kt Normal file
View File

@ -0,0 +1,84 @@
package space.kscience.kmath.structures
import space.kscience.kmath.misc.UnstableKMathAPI
/**
* Typealias for buffer transformations.
*/
public typealias BufferTransform<T, R> = (Buffer<T>) -> Buffer<R>
/**
* Typealias for buffer transformations with suspend function.
*/
public typealias SuspendBufferTransform<T, R> = suspend (Buffer<T>) -> Buffer<R>
/**
* Creates a sequence that returns all elements from this [Buffer].
*/
public fun <T> Buffer<T>.asSequence(): Sequence<T> = Sequence(::iterator)
/**
* Creates an iterable that returns all elements from this [Buffer].
*/
public fun <T> Buffer<T>.asIterable(): Iterable<T> = Iterable(::iterator)
/**
* Returns a new [List] containing all elements of this buffer.
*/
public fun <T> Buffer<T>.toList(): List<T> = when (this) {
is ArrayBuffer<T> -> array.toList()
is ListBuffer<T> -> list.toList()
is MutableListBuffer<T> -> list.toList()
else -> asSequence().toList()
}
/**
* Returns a new [MutableList] filled with all elements of this buffer.
* **NOTE:** this method uses a protective copy, so it should not be used in performance-critical code.
*/
@UnstableKMathAPI
public fun <T> Buffer<T>.toMutableList(): MutableList<T> = when (this) {
is ArrayBuffer<T> -> array.toMutableList()
is ListBuffer<T> -> list.toMutableList()
is MutableListBuffer<T> -> list.toMutableList()
else -> MutableList(size, ::get)
}
/**
* Returns a new [Array] containing all elements of this buffer.
* **NOTE:** this method uses a protective copy, so it should not be used in performance-critical code.
*/
@UnstableKMathAPI
public inline fun <reified T> Buffer<T>.toTypedArray(): Array<T> = Array(size, ::get)
/**
* Create a new buffer from this one with the given mapping function.
* Provided [BufferFactory] is used to construct the new buffer.
*/
public inline fun <T : Any, reified R : Any> Buffer<T>.map(
bufferFactory: BufferFactory<R> = Buffer.Companion::auto,
crossinline block: (T) -> R,
): Buffer<R> = bufferFactory(size) { block(get(it)) }
/**
* Create a new buffer from this one with the given indexed mapping function.
* Provided [BufferFactory] is used to construct the new buffer.
*/
public inline fun <T : Any, reified R : Any> Buffer<T>.mapIndexed(
bufferFactory: BufferFactory<R> = Buffer.Companion::auto,
crossinline block: (index: Int, value: T) -> R,
): Buffer<R> = bufferFactory(size) { block(it, get(it)) }
/**
* Zip two buffers using given [transform].
*/
@UnstableKMathAPI
public inline fun <T1 : Any, T2 : Any, reified R : Any> Buffer<T1>.zip(
other: Buffer<T2>,
bufferFactory: BufferFactory<R> = Buffer.Companion::auto,
crossinline transform: (T1, T2) -> R,
): Buffer<R> {
require(size == other.size) { "Buffer size mismatch in zip: expected $size but found ${other.size}" }
return bufferFactory(size) { transform(get(it), other[it]) }
}

11
kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt
View File

@ -1,23 +1,24 @@
package space.kscience.kmath.linear
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.NDStructure
import space.kscience.kmath.nd.as2D
import space.kscience.kmath.operations.invoke
import kotlin.test.Test
import kotlin.test.assertEquals
@UnstableKMathAPI
@Suppress("UNUSED_VARIABLE")
class MatrixTest {
@Test
fun testTranspose() {
val matrix = MatrixContext.real.one(3, 3)
val matrix = LinearSpace.real.one(3, 3)
val transposed = matrix.transpose()
assertEquals(matrix, transposed)
}
@Test
fun testBuilder() {
val matrix = Matrix.build(2, 3)(
val matrix = LinearSpace.real.matrix(2, 3)(
1.0, 0.0, 0.0,
0.0, 1.0, 2.0
)
@ -39,7 +40,7 @@ class MatrixTest {
infix fun Matrix<Double>.pow(power: Int): Matrix<Double> {
var res = this
repeat(power - 1) {
res = RealMatrixContext.invoke { res dot this@pow }
res = LinearSpace.real.run { res dot this@pow }
}
return res
}
@ -52,7 +53,7 @@ class MatrixTest {
val firstMatrix = NDStructure.auto(2, 3) { (i, j) -> (i + j).toDouble() }.as2D()
val secondMatrix = NDStructure.auto(3, 2) { (i, j) -> (i + j).toDouble() }.as2D()
MatrixContext.real.run {
LinearSpace.real.run {
// val firstMatrix = produce(2, 3) { i, j -> (i + j).toDouble() }
// val secondMatrix = produce(3, 2) { i, j -> (i + j).toDouble() }
val result = firstMatrix dot secondMatrix

20
kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/RealLUSolverTest.kt
View File

@ -1,29 +1,31 @@
package space.kscience.kmath.linear
import space.kscience.kmath.misc.UnstableKMathAPI
import kotlin.test.Test
import kotlin.test.assertEquals
@UnstableKMathAPI
class RealLUSolverTest {
@Test
fun testInvertOne() {
val matrix = MatrixContext.real.one(2, 2)
val inverted = MatrixContext.real.inverseWithLup(matrix)
val matrix = LinearSpace.real.one(2, 2)
val inverted = LinearSpace.real.inverseWithLup(matrix)
assertEquals(matrix, inverted)
}
@Test
fun testDecomposition() {
val matrix = Matrix.square(
LinearSpace.real.run {
val matrix = matrix(2, 2)(
3.0, 1.0,
1.0, 3.0
2.0, 3.0
)
MatrixContext.real.run {
val lup = lup(matrix)
//Check determinant
assertEquals(8.0, lup.determinant)
assertEquals(7.0, lup.determinant)
assertEquals(lup.p dot matrix, lup.l dot lup.u)
}
@ -31,14 +33,14 @@ class RealLUSolverTest {
@Test
fun testInvert() {
val matrix = Matrix.square(
val matrix = LinearSpace.real.matrix(2, 2)(
3.0, 1.0,
1.0, 3.0
)
val inverted = MatrixContext.real.inverseWithLup(matrix)
val inverted = LinearSpace.real.inverseWithLup(matrix)
val expected = Matrix.square(
val expected = LinearSpace.real.matrix(2, 2)(
0.375, -0.125,
-0.125, 0.375
)

5
kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt
View File

@ -1,5 +1,6 @@
package space.kscience.kmath.structures
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.nd.*
import space.kscience.kmath.operations.Norm
import space.kscience.kmath.operations.invoke
@ -33,7 +34,9 @@ class NumberNDFieldTest {
@Test
fun testGeneration() {
val array = Structure2D.real(3, 3) { i, j -> (i * 10 + j).toDouble() }
val array = LinearSpace.real.buildMatrix(3, 3) { i, j ->
(i * 10 + j).toDouble()
}
for (i in 0..2) {
for (j in 0..2) {

35
kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt
View File

@ -2,7 +2,8 @@ package space.kscience.kmath.dimensions
import space.kscience.kmath.linear.*
import space.kscience.kmath.nd.Structure2D
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.operations.Ring
/**
* A matrix with compile-time controlled dimension
@ -77,7 +78,7 @@ public inline class DPointWrapper<T, D : Dimension>(public val point: Point<T>)
/**
* Basic operations on dimension-safe matrices. Operates on [Matrix]
*/
public inline class DMatrixContext<T : Any>(public val context: MatrixContext<T, Matrix<T>>) {
public inline class DMatrixContext<T : Any, out A : Ring<T>>(public val context: LinearSpace<T, A>) {
public inline fun <reified R : Dimension, reified C : Dimension> Matrix<T>.coerce(): DMatrix<T, R, C> {
require(rowNum == Dimension.dim<R>().toInt()) {
"Row number mismatch: expected ${Dimension.dim<R>()} but found $rowNum"
@ -93,17 +94,19 @@ public inline class DMatrixContext<T : Any>(public val context: MatrixContext<T,
/**
* Produce a matrix with this context and given dimensions
*/
public inline fun <reified R : Dimension, reified C : Dimension> produce(noinline initializer: (i: Int, j: Int) -> T): DMatrix<T, R, C> {
public inline fun <reified R : Dimension, reified C : Dimension> produce(
noinline initializer: A.(i: Int, j: Int) -> T
): DMatrix<T, R, C> {
val rows = Dimension.dim<R>()
val cols = Dimension.dim<C>()
return context.produce(rows.toInt(), cols.toInt(), initializer).coerce<R, C>()
return context.buildMatrix(rows.toInt(), cols.toInt(), initializer).coerce<R, C>()
}
public inline fun <reified D : Dimension> point(noinline initializer: (Int) -> T): DPoint<T, D> {
public inline fun <reified D : Dimension> point(noinline initializer: A.(Int) -> T): DPoint<T, D> {
val size = Dimension.dim<D>()
return DPoint.coerceUnsafe(
context.point(
context.buildVector(
size.toInt(),
initializer
)
@ -112,31 +115,31 @@ public inline class DMatrixContext<T : Any>(public val context: MatrixContext<T,
public inline infix fun <reified R1 : Dimension, reified C1 : Dimension, reified C2 : Dimension> DMatrix<T, R1, C1>.dot(
other: DMatrix<T, C1, C2>,
): DMatrix<T, R1, C2> = context { this@dot dot other }.coerce()
): DMatrix<T, R1, C2> = context.run { this@dot dot other }.coerce()
public inline infix fun <reified R : Dimension, reified C : Dimension> DMatrix<T, R, C>.dot(vector: DPoint<T, C>): DPoint<T, R> =
DPoint.coerceUnsafe(context { this@dot dot vector })
DPoint.coerceUnsafe(context.run { this@dot dot vector })
public inline operator fun <reified R : Dimension, reified C : Dimension> DMatrix<T, R, C>.times(value: T): DMatrix<T, R, C> =
context { this@times.times(value) }.coerce()
context.run { this@times.times(value) }.coerce()
public inline operator fun <reified R : Dimension, reified C : Dimension> T.times(m: DMatrix<T, R, C>): DMatrix<T, R, C> =
m * this
public inline operator fun <reified R : Dimension, reified C : Dimension> DMatrix<T, C, R>.plus(other: DMatrix<T, C, R>): DMatrix<T, C, R> =
context { this@plus + other }.coerce()
context.run { this@plus + other }.coerce()
public inline operator fun <reified R : Dimension, reified C : Dimension> DMatrix<T, C, R>.minus(other: DMatrix<T, C, R>): DMatrix<T, C, R> =
context { this@minus + other }.coerce()
context.run { this@minus + other }.coerce()
public inline operator fun <reified R : Dimension, reified C : Dimension> DMatrix<T, C, R>.unaryMinus(): DMatrix<T, C, R> =
context { this@unaryMinus.unaryMinus() }.coerce()
context.run { this@unaryMinus.unaryMinus() }.coerce()
public inline fun <reified R : Dimension, reified C : Dimension> DMatrix<T, C, R>.transpose(): DMatrix<T, R, C> =
context { (this@transpose as Matrix<T>).transpose() }.coerce()
context.run { (this@transpose as Matrix<T>).transpose() }.coerce()
public companion object {
public val real: DMatrixContext<Double> = DMatrixContext(MatrixContext.real)
public val real: DMatrixContext<Double, RealField> = DMatrixContext(LinearSpace.real)
}
}
@ -144,11 +147,11 @@ public inline class DMatrixContext<T : Any>(public val context: MatrixContext<T,
/**
* A square unit matrix
*/
public inline fun <reified D : Dimension> DMatrixContext<Double>.one(): DMatrix<Double, D, D> = produce { i, j ->
public inline fun <reified D : Dimension> DMatrixContext<Double, RealField>.one(): DMatrix<Double, D, D> = produce { i, j ->
if (i == j) 1.0 else 0.0
}
public inline fun <reified R : Dimension, reified C : Dimension> DMatrixContext<Double>.zero(): DMatrix<Double, R, C> =
public inline fun <reified R : Dimension, reified C : Dimension> DMatrixContext<Double, RealField>.zero(): DMatrix<Double, R, C> =
produce { _, _ ->
0.0
}

187
kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt Normal file
View File

@ -0,0 +1,187 @@
package space.kscience.kmath.ejml
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.getFeature
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.structures.RealBuffer
import kotlin.reflect.KClass
import kotlin.reflect.cast
/**
* Represents context of basic operations operating with [EjmlMatrix].
*
* @author Iaroslav Postovalov
*/
public object EjmlLinearSpace : LinearSpace<Double, RealField> {
override val elementAlgebra: RealField get() = RealField
/**
* Converts this matrix to EJML one.
*/
@OptIn(UnstableKMathAPI::class)
public fun Matrix<Double>.toEjml(): EjmlMatrix = when (val matrix = origin) {
is EjmlMatrix -> matrix
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) }
})
}
override fun buildMatrix(rows: Int, columns: Int, initializer: RealField.(i: Int, j: Int) -> Double): EjmlMatrix =
EjmlMatrix(SimpleMatrix(rows, columns).also {
(0 until rows).forEach { row ->
(0 until columns).forEach { col -> it[row, col] = RealField.initializer(row, col) }
}
})
override fun buildVector(size: Int, initializer: RealField.(Int) -> Double): Point<Double> =
EjmlVector(SimpleMatrix(size, 1).also {
(0 until it.numRows()).forEach { row -> it[row, 0] = RealField.initializer(row) }
})
private fun SimpleMatrix.wrapMatrix() = EjmlMatrix(this)
private fun SimpleMatrix.wrapVector() = EjmlVector(this)
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(vector: Point<Double>): EjmlVector =
EjmlVector(toEjml().origin.mult(vector.toEjml().origin))
public override operator fun Matrix<Double>.minus(other: Matrix<Double>): EjmlMatrix =
(toEjml().origin - other.toEjml().origin).wrapMatrix()
public override operator fun Matrix<Double>.times(value: Double): EjmlMatrix =
toEjml().origin.scale(value).wrapMatrix()
override fun Point<Double>.unaryMinus(): EjmlVector =
toEjml().origin.negative().wrapVector()
override fun Matrix<Double>.plus(other: Matrix<Double>): EjmlMatrix =
(toEjml().origin + other.toEjml().origin).wrapMatrix()
override fun Point<Double>.plus(other: Point<Double>): EjmlVector =
(toEjml().origin + other.toEjml().origin).wrapVector()
override fun Point<Double>.minus(other: Point<Double>): EjmlVector =
(toEjml().origin - other.toEjml().origin).wrapVector()
override fun Double.times(m: Matrix<Double>): EjmlMatrix =
m.toEjml().origin.scale(this).wrapMatrix()
override fun Point<Double>.times(value: Double): EjmlVector =
toEjml().origin.scale(value).wrapVector()
override fun Double.times(v: Point<Double>): EjmlVector =
v.toEjml().origin.scale(this).wrapVector()
@UnstableKMathAPI
override fun <F : Any> getFeature(structure: Matrix<Double>, type: KClass<F>): F? {
//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()) }
}
DeterminantFeature::class -> object : DeterminantFeature<Double> {
override val determinant: Double by lazy(origin::determinant)
}
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()) }
}
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 singularValues: Point<Double> by lazy { RealBuffer(svd.singularValues) }
}
QRDecompositionFeature::class -> object : QRDecompositionFeature<Double> {
private val qr by lazy {
DecompositionFactory_DDRM.qr().apply { decompose(origin.ddrm.copy()) }
}
override val q: Matrix<Double> by lazy {
EjmlMatrix(SimpleMatrix(qr.getQ(null, false))) + OrthogonalFeature
}
override val r: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(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()) }
EjmlMatrix(SimpleMatrix(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()) }
}
override val l: Matrix<Double> by lazy {
EjmlMatrix(SimpleMatrix(lup.getLower(null))) + LFeature
}
override val u: Matrix<Double> by lazy {
EjmlMatrix(SimpleMatrix(lup.getUpper(null))) + UFeature
}
override val p: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(lup.getRowPivot(null))) }
}
else -> null
}?.let(type::cast)
}
}
/**
* Solves for X in the following equation: x = a^-1*b, where 'a' is base matrix and 'b' is an n by p matrix.
*
* @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))
/**
* Solves for X in the following equation: x = a^(-1)*b, where 'a' is base matrix and 'b' is an n by p matrix.
*
* @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))
@OptIn(UnstableKMathAPI::class)
public fun EjmlMatrix.inverted(): EjmlMatrix = getFeature<InverseMatrixFeature<Double>>()!!.inverse as EjmlMatrix
public fun EjmlLinearSpace.inverse(matrix: Matrix<Double>): Matrix<Double> = matrix.toEjml().inverted()

71
kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrix.kt
View File

@ -1,13 +1,8 @@
package space.kscience.kmath.ejml
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.linear.Matrix
import space.kscience.kmath.nd.NDStructure
import space.kscience.kmath.structures.RealBuffer
import kotlin.reflect.KClass
import kotlin.reflect.cast
/**
* Represents featured matrix over EJML [SimpleMatrix].
@ -19,73 +14,11 @@ 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()
@UnstableKMathAPI
public override fun <T : Any> getFeature(type: KClass<T>): T? = when (type) {
InverseMatrixFeature::class -> object : InverseMatrixFeature<Double> {
override val inverse: Matrix<Double> by lazy { EjmlMatrix(origin.invert()) }
}
DeterminantFeature::class -> object : DeterminantFeature<Double> {
override val determinant: Double by lazy(origin::determinant)
}
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()) }
}
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 singularValues: Point<Double> by lazy { RealBuffer(svd.singularValues) }
}
QRDecompositionFeature::class -> object : QRDecompositionFeature<Double> {
private val qr by lazy {
DecompositionFactory_DDRM.qr().apply { decompose(origin.ddrm.copy()) }
}
override val q: Matrix<Double> by lazy {
EjmlMatrix(SimpleMatrix(qr.getQ(null, false))) + OrthogonalFeature
}
override val r: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(qr.getR(null, false))) + UFeature }
}
CholeskyDecompositionFeature::class -> object : CholeskyDecompositionFeature<Double> {
override val l: Matrix<Double> by lazy {
val cholesky =
DecompositionFactory_DDRM.chol(rowNum, true).apply { decompose(origin.ddrm.copy()) }
EjmlMatrix(SimpleMatrix(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()) }
}
override val l: Matrix<Double> by lazy {
EjmlMatrix(SimpleMatrix(lup.getLower(null))) + LFeature
}
override val u: Matrix<Double> by lazy {
EjmlMatrix(SimpleMatrix(lup.getUpper(null))) + UFeature
}
override val p: Matrix<Double> by lazy { EjmlMatrix(SimpleMatrix(lup.getRowPivot(null))) }
}
else -> null
}?.let(type::cast)
public override operator fun get(i: Int, j: Int): Double = origin[i, j]
override fun equals(other: Any?): Boolean {
if (this === other) return true
if (other !is Matrix<*>) return false
if (other !is NDStructure<*>) return false
return NDStructure.contentEquals(this, other)
}

92
kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlMatrixContext.kt
View File

@ -1,92 +0,0 @@
package space.kscience.kmath.ejml
import org.ejml.simple.SimpleMatrix
import space.kscience.kmath.linear.*
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.getFeature
import space.kscience.kmath.operations.ScaleOperations
/**
* Represents context of basic operations operating with [EjmlMatrix].
*
* @author Iaroslav Postovalov
*/
public object EjmlMatrixContext : MatrixContext<Double, EjmlMatrix>, ScaleOperations<Matrix<Double>> {
/**
* Converts this matrix to EJML one.
*/
@OptIn(UnstableKMathAPI::class)
public fun Matrix<Double>.toEjml(): EjmlMatrix = when (val matrix = origin) {
is EjmlMatrix -> matrix
else -> produce(rowNum, colNum) { i, j -> get(i, j) }
}
/**
* Converts this vector to EJML one.
*/
public fun Point<Double>.toEjml(): EjmlVector =
if (this is EjmlVector) this else EjmlVector(SimpleMatrix(size, 1).also {
(0 until it.numRows()).forEach { row -> it[row, 0] = get(row) }
})
override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> Double): EjmlMatrix =
EjmlMatrix(SimpleMatrix(rows, columns).also {
(0 until rows).forEach { row ->
(0 until columns).forEach { col -> it[row, col] = initializer(row, col) }
}
})
override fun point(size: Int, initializer: (Int) -> Double): Point<Double> =
EjmlVector(SimpleMatrix(size, 1).also {
(0 until it.numRows()).forEach { row -> it[row, 0] = initializer(row) }
})
override fun Matrix<Double>.unaryMinus(): Matrix<Double> = this*(-1)
public override fun Matrix<Double>.dot(other: Matrix<Double>): EjmlMatrix =
EjmlMatrix(toEjml().origin.mult(other.toEjml().origin))
public override fun Matrix<Double>.dot(vector: Point<Double>): EjmlVector =
EjmlVector(toEjml().origin.mult(vector.toEjml().origin))
public override fun add(a: Matrix<Double>, b: Matrix<Double>): EjmlMatrix =
EjmlMatrix(a.toEjml().origin + b.toEjml().origin)
public override operator fun Matrix<Double>.minus(b: Matrix<Double>): EjmlMatrix =
EjmlMatrix(toEjml().origin - b.toEjml().origin)
public override fun scale(a: Matrix<Double>, value: Double): EjmlMatrix =
produce(a.rowNum, a.colNum) { i, j -> a[i, j] * value }
public override operator fun Matrix<Double>.times(value: Double): EjmlMatrix =
EjmlMatrix(toEjml().origin.scale(value))
}
/**
* Solves for X in the following equation: x = a^-1*b, where 'a' is base matrix and 'b' is an n by p matrix.
*
* @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 EjmlMatrixContext.solve(a: Matrix<Double>, b: Matrix<Double>): EjmlMatrix =
EjmlMatrix(a.toEjml().origin.solve(b.toEjml().origin))
/**
* Solves for X in the following equation: x = a^(-1)*b, where 'a' is base matrix and 'b' is an n by p matrix.
*
* @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 EjmlMatrixContext.solve(a: Matrix<Double>, b: Point<Double>): EjmlVector =
EjmlVector(a.toEjml().origin.solve(b.toEjml().origin))
@OptIn(UnstableKMathAPI::class)
public fun EjmlMatrix.inverted(): EjmlMatrix = getFeature<InverseMatrixFeature<Double>>()!!.inverse as EjmlMatrix
public fun EjmlMatrixContext.inverse(matrix: Matrix<Double>): Matrix<Double> = matrix.toEjml().inverted()

9
kmath-ejml/src/test/kotlin/space/kscience/kmath/ejml/EjmlMatrixTest.kt
View File

@ -2,10 +2,7 @@ package space.kscience.kmath.ejml
import org.ejml.dense.row.factory.DecompositionFactory_DDRM
import org.ejml.simple.SimpleMatrix
import space.kscience.kmath.linear.DeterminantFeature
import space.kscience.kmath.linear.LupDecompositionFeature
import space.kscience.kmath.linear.MatrixFeature
import space.kscience.kmath.linear.plus
import space.kscience.kmath.linear.*
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.nd.getFeature
import kotlin.random.Random
@ -45,9 +42,9 @@ internal class EjmlMatrixTest {
fun features() {
val m = randomMatrix
val w = EjmlMatrix(m)
val det = w.getFeature<DeterminantFeature<Double>>() ?: fail()
val det: DeterminantFeature<Double> = EjmlLinearSpace.getFeature(w) ?: fail()
assertEquals(m.determinant(), det.determinant)
val lup = w.getFeature<LupDecompositionFeature<Double>>() ?: fail()
val lup: LupDecompositionFeature<Double> = EjmlLinearSpace.getFeature(w) ?: fail()
val ludecompositionF64 = DecompositionFactory_DDRM.lu(m.numRows(), m.numCols())
.also { it.decompose(m.ddrm.copy()) }

6
kmath-for-real/README.md
View File

@ -7,7 +7,7 @@
> #### Artifact:
>
> This module artifact: `space.kscience:kmath-for-real:0.2.0`.
> This module artifact: `space.kscience:kmath-for-real:0.3.0-dev-2`.
>
> Bintray release version: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-for-real/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-for-real/_latestVersion)
>
@ -26,7 +26,7 @@
> }
>
> dependencies {
> implementation 'space.kscience:kmath-for-real:0.2.0'
> implementation 'space.kscience:kmath-for-real:0.3.0-dev-2'
> }
> ```
> **Gradle Kotlin DSL:**
@ -42,6 +42,6 @@
> }
>
> dependencies {
> implementation("space.kscience:kmath-for-real:0.2.0")
> implementation("space.kscience:kmath-for-real:0.3.0-dev-2")
> }
> ```

59
kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt
View File

@ -2,6 +2,7 @@ package space.kscience.kmath.real
import space.kscience.kmath.linear.*
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.RealField
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.RealBuffer
import space.kscience.kmath.structures.asIterable
@ -21,15 +22,19 @@ import kotlin.math.pow
public typealias RealMatrix = Matrix<Double>
public fun realMatrix(rowNum: Int, colNum: Int, initializer: (i: Int, j: Int) -> Double): RealMatrix =
MatrixContext.real.produce(rowNum, colNum, initializer)
public fun realMatrix(rowNum: Int, colNum: Int, initializer: RealField.(i: Int, j: Int) -> Double): RealMatrix =
LinearSpace.real.buildMatrix(rowNum, colNum, initializer)
@OptIn(UnstableKMathAPI::class)
public fun realMatrix(rowNum: Int, colNum: Int): MatrixBuilder<Double, RealField> =
LinearSpace.real.matrix(rowNum, colNum)
public fun Array<DoubleArray>.toMatrix(): RealMatrix {
return MatrixContext.real.produce(size, this[0].size) { row, col -> this[row][col] }
return LinearSpace.real.buildMatrix(size, this[0].size) { row, col -> this@toMatrix[row][col] }
}
public fun Sequence<DoubleArray>.toMatrix(): RealMatrix = toList().let {
MatrixContext.real.produce(it.size, it[0].size) { row, col -> it[row][col] }
LinearSpace.real.buildMatrix(it.size, it[0].size) { row, col -> it[row][col] }
}
public fun RealMatrix.repeatStackVertical(n: Int): RealMatrix =
@ -42,38 +47,38 @@ public fun RealMatrix.repeatStackVertical(n: Int): RealMatrix =
*/
public operator fun RealMatrix.times(double: Double): RealMatrix =
MatrixContext.real.produce(rowNum, colNum) { row, col ->
this[row, col] * double
LinearSpace.real.buildMatrix(rowNum, colNum) { row, col ->
get(row, col) * double
}
public operator fun RealMatrix.plus(double: Double): RealMatrix =
MatrixContext.real.produce(rowNum, colNum) { row, col ->
this[row, col] + double
LinearSpace.real.buildMatrix(rowNum, colNum) { row, col ->
get(row, col) + double
}
public operator fun RealMatrix.minus(double: Double): RealMatrix =
MatrixContext.real.produce(rowNum, colNum) { row, col ->
this[row, col] - double
LinearSpace.real.buildMatrix(rowNum, colNum) { row, col ->
get(row, col) - double
}
public operator fun RealMatrix.div(double: Double): RealMatrix =
MatrixContext.real.produce(rowNum, colNum) { row, col ->
this[row, col] / double
LinearSpace.real.buildMatrix(rowNum, colNum) { row, col ->
get(row, col) / double
}
public operator fun Double.times(matrix: RealMatrix): RealMatrix =
MatrixContext.real.produce(matrix.rowNum, matrix.colNum) { row, col ->
this * matrix[row, col]
LinearSpace.real.buildMatrix(matrix.rowNum, matrix.colNum) { row, col ->
this@times * matrix[row, col]
}
public operator fun Double.plus(matrix: RealMatrix): RealMatrix =
MatrixContext.real.produce(matrix.rowNum, matrix.colNum) { row, col ->
this + matrix[row, col]
LinearSpace.real.buildMatrix(matrix.rowNum, matrix.colNum) { row, col ->
this@plus + matrix[row, col]
}
public operator fun Double.minus(matrix: RealMatrix): RealMatrix =
MatrixContext.real.produce(matrix.rowNum, matrix.colNum) { row, col ->
this - matrix[row, col]
LinearSpace.real.buildMatrix(matrix.rowNum, matrix.colNum) { row, col ->
this@minus - matrix[row, col]
}
// TODO: does this operation make sense? Should it be 'this/matrix[row, col]'?
@ -87,29 +92,29 @@ public operator fun Double.minus(matrix: RealMatrix): RealMatrix =
@UnstableKMathAPI
public operator fun RealMatrix.times(other: RealMatrix): RealMatrix =
MatrixContext.real.produce(rowNum, colNum) { row, col -> this[row, col] * other[row, col] }
LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> this@times[row, col] * other[row, col] }
public operator fun RealMatrix.plus(other: RealMatrix): RealMatrix =
MatrixContext.real.add(this, other)
LinearSpace.real.run { this@plus + other }
public operator fun RealMatrix.minus(other: RealMatrix): RealMatrix =
MatrixContext.real.produce(rowNum, colNum) { row, col -> this[row, col] - other[row, col] }
LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> this@minus[row, col] - other[row, col] }
/*
* Operations on columns
*/
public inline fun RealMatrix.appendColumn(crossinline mapper: (Buffer<Double>) -> Double): RealMatrix =
MatrixContext.real.produce(rowNum, colNum + 1) { row, col ->
LinearSpace.real.buildMatrix(rowNum, colNum + 1) { row, col ->
if (col < colNum)
this[row, col]
get(row, col)
else
mapper(rows[row])
}
public fun RealMatrix.extractColumns(columnRange: IntRange): RealMatrix =
MatrixContext.real.produce(rowNum, columnRange.count()) { row, col ->
this[row, columnRange.first + col]
LinearSpace.real.buildMatrix(rowNum, columnRange.count()) { row, col ->
this@extractColumns[row, columnRange.first + col]
}
public fun RealMatrix.extractColumn(columnIndex: Int): RealMatrix =
@ -141,14 +146,14 @@ public fun RealMatrix.max(): Double? = elements().map { (_, value) -> value }.ma
public fun RealMatrix.average(): Double = elements().map { (_, value) -> value }.average()
public inline fun RealMatrix.map(crossinline transform: (Double) -> Double): RealMatrix =
MatrixContext.real.produce(rowNum, colNum) { i, j ->
LinearSpace.real.buildMatrix(rowNum, colNum) { i, j ->
transform(get(i, j))
}
/**
* Inverse a square real matrix using LUP decomposition
*/
public fun RealMatrix.inverseWithLup(): RealMatrix = MatrixContext.real.inverseWithLup(this)
public fun RealMatrix.inverseWithLup(): RealMatrix = LinearSpace.real.inverseWithLup(this)
//extended operations

18
kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealVector.kt
View File

@ -1,10 +1,13 @@
package space.kscience.kmath.real
import space.kscience.kmath.linear.Point
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.Norm
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.MutableBuffer.Companion.real
import space.kscience.kmath.structures.asBuffer
import space.kscience.kmath.structures.asIterable
import space.kscience.kmath.structures.indices
import kotlin.math.pow
import kotlin.math.sqrt
@ -19,15 +22,16 @@ public operator fun Buffer.Companion.invoke(vararg doubles: Double): RealVector
/**
* Fill the vector of given [size] with given [value]
*/
@UnstableKMathAPI
public fun Buffer.Companion.same(size: Int, value: Number): RealVector = real(size) { value.toDouble() }
// Transformation methods
public inline fun RealVector.map(transform: (Double) -> Double): RealVector =
Buffer.real(size) { transform(get(it)) }
real(size) { transform(get(it)) }
public inline fun RealVector.mapIndexed(transform: (index: Int, value: Double) -> Double): RealVector =
Buffer.real(size) { transform(it, get(it)) }
real(size) { transform(it, get(it)) }
public operator fun RealVector.plus(other: RealVector): RealVector {
require(size == other.size) { "Vector size $size expected but ${other.size} found" }
@ -88,3 +92,13 @@ public fun tan(vector: RealVector): RealVector = vector.map { kotlin.math.tan(it
public fun ln(vector: RealVector): RealVector = vector.map { kotlin.math.ln(it) }
public fun log10(vector: RealVector): RealVector = vector.map { kotlin.math.log10(it) }
// reductions methods
public fun RealVector.sum(): Double {
var res = 0.0
for (i in indices) {
res += get(i)
}
return res
}

27
kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt
View File

@ -1,31 +1,12 @@
package space.kscience.kmath.real
import space.kscience.kmath.linear.BufferMatrix
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.RealBuffer
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.Matrix
/**
* Optimized dot product for real matrices
*/
public infix fun BufferMatrix<Double>.dot(other: BufferMatrix<Double>): BufferMatrix<Double> {
require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
val resultArray = DoubleArray(this.rowNum * other.colNum)
//convert to array to insure there is no memory indirection
fun Buffer<Double>.unsafeArray() = if (this is RealBuffer)
this.array
else
DoubleArray(size) { get(it) }
val a = this.buffer.unsafeArray()
val b = other.buffer.unsafeArray()
for (i in (0 until rowNum))
for (j in (0 until other.colNum))
for (k in (0 until colNum))
resultArray[i * other.colNum + j] += a[i * colNum + k] * b[k * other.colNum + j]
val buffer = RealBuffer(resultArray)
return BufferMatrix(rowNum, other.colNum, buffer)
public infix fun Matrix<Double>.dot(other: Matrix<Double>): Matrix<Double> = LinearSpace.real.run{
this@dot dot other
}

39
kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/RealMatrixTest.kt
View File

@ -1,7 +1,7 @@
package kaceince.kmath.real
import space.kscience.kmath.linear.Matrix
import space.kscience.kmath.linear.build
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.matrix
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.real.*
import space.kscience.kmath.structures.contentEquals
@ -9,6 +9,7 @@ import kotlin.test.Test
import kotlin.test.assertEquals
import kotlin.test.assertTrue
@UnstableKMathAPI
internal class RealMatrixTest {
@Test
fun testSum() {
@ -30,11 +31,11 @@ internal class RealMatrixTest {
@Test
fun testRepeatStackVertical() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = realMatrix(2, 3)(
1.0, 0.0, 0.0,
0.0, 1.0, 2.0
)
val matrix2 = Matrix.build(6, 3)(
val matrix2 = realMatrix(6, 3)(
1.0, 0.0, 0.0,
0.0, 1.0, 2.0,
1.0, 0.0, 0.0,
@ -47,12 +48,12 @@ internal class RealMatrixTest {
@Test
fun testMatrixAndDouble() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = realMatrix(2, 3)(
1.0, 0.0, 3.0,
4.0, 6.0, 2.0
)
val matrix2 = (matrix1 * 2.5 + 1.0 - 2.0) / 2.0
val expectedResult = Matrix.build(2, 3)(
val expectedResult = LinearSpace.real.matrix(2, 3)(
0.75, -0.5, 3.25,
4.5, 7.0, 2.0
)
@ -61,13 +62,13 @@ internal class RealMatrixTest {
@Test
fun testDoubleAndMatrix() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = realMatrix(2, 3)(
1.0, 0.0, 3.0,
4.0, 6.0, 2.0
)
val matrix2 = 20.0 - (10.0 + (5.0 * matrix1))
//val matrix2 = 10.0 + (5.0 * matrix1)
val expectedResult = Matrix.build(2, 3)(
val expectedResult = realMatrix(2, 3)(
5.0, 10.0, -5.0,
-10.0, -20.0, 0.0
)
@ -76,15 +77,15 @@ internal class RealMatrixTest {
@Test
fun testSquareAndPower() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = realMatrix(2, 3)(
-1.0, 0.0, 3.0,
4.0, -6.0, -2.0
)
val matrix2 = Matrix.build(2, 3)(
val matrix2 = realMatrix(2, 3)(
1.0, 0.0, 9.0,
16.0, 36.0, 4.0
)
val matrix3 = Matrix.build(2, 3)(
val matrix3 = realMatrix(2, 3)(
-1.0, 0.0, 27.0,
64.0, -216.0, -8.0
)
@ -95,16 +96,16 @@ internal class RealMatrixTest {
@OptIn(UnstableKMathAPI::class)
@Test
fun testTwoMatrixOperations() {
val matrix1 = Matrix.build(2, 3)(
val matrix1 = realMatrix(2, 3)(
-1.0, 0.0, 3.0,
4.0, -6.0, 7.0
)
val matrix2 = Matrix.build(2, 3)(
val matrix2 = realMatrix(2, 3)(
1.0, 0.0, 3.0,
4.0, 6.0, -2.0
)
val result = matrix1 * matrix2 + matrix1 - matrix2
val expectedResult = Matrix.build(2, 3)(
val expectedResult = realMatrix(2, 3)(
-3.0, 0.0, 9.0,
16.0, -48.0, -5.0
)
@ -113,16 +114,16 @@ internal class RealMatrixTest {
@Test
fun testColumnOperations() {
val matrix1 = Matrix.build(2, 4)(
val matrix1 = realMatrix(2, 4)(
-1.0, 0.0, 3.0, 15.0,
4.0, -6.0, 7.0, -11.0
)
val matrix2 = Matrix.build(2, 5)(
val matrix2 = realMatrix(2, 5)(
-1.0, 0.0, 3.0, 15.0, -1.0,
4.0, -6.0, 7.0, -11.0, 4.0
)
val col1 = Matrix.build(2, 1)(0.0, -6.0)
val cols1to2 = Matrix.build(2, 2)(
val col1 = realMatrix(2, 1)(0.0, -6.0)
val cols1to2 = realMatrix(2, 2)(
0.0, 3.0,
-6.0, 7.0
)
@ -147,7 +148,7 @@ internal class RealMatrixTest {
@Test
fun testAllElementOperations() {
val matrix1 = Matrix.build(2, 4)(
val matrix1 = LinearSpace.real.matrix(2, 4)(
-1.0, 0.0, 3.0, 15.0,
4.0, -6.0, 7.0, -11.0
)

18
kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/RealVectorTest.kt
View File

@ -1,38 +1,36 @@
package kaceince.kmath.real
import space.kscience.kmath.linear.MatrixContext
import space.kscience.kmath.linear.LinearSpace
import space.kscience.kmath.linear.asMatrix
import space.kscience.kmath.linear.real
import space.kscience.kmath.linear.transpose
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.real.plus
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.RealBuffer
import kotlin.test.Test
import kotlin.test.assertEquals
internal class RealVectorTest {
@Test
fun testSum() {
val vector1 = Buffer.real(5) { it.toDouble() }
val vector2 = Buffer.real(5) { 5 - it.toDouble() }
val vector1 = RealBuffer(5) { it.toDouble() }
val vector2 = RealBuffer(5) { 5 - it.toDouble() }
val sum = vector1 + vector2
assertEquals(5.0, sum[2])
}
@Test
fun testVectorToMatrix() {
val vector = Buffer.real(5) { it.toDouble() }
val vector = RealBuffer(5) { it.toDouble() }
val matrix = vector.asMatrix()
assertEquals(4.0, matrix[4, 0])
}
@Test
fun testDot() {
val vector1 = Buffer.real(5) { it.toDouble() }
val vector2 = Buffer.real(5) { 5 - it.toDouble() }
val vector1 = RealBuffer(5) { it.toDouble() }
val vector2 = RealBuffer(5) { 5 - it.toDouble() }
val matrix1 = vector1.asMatrix()
val matrix2 = vector2.asMatrix().transpose()
val product = MatrixContext.real { matrix1 dot matrix2 }
val product = LinearSpace.real.run { matrix1 dot matrix2 }
assertEquals(5.0, product[1, 0])
assertEquals(6.0, product[2, 2])
}

6
kmath-functions/README.md
View File

@ -10,7 +10,7 @@ Functions and interpolations:
> #### Artifact:
>
> This module artifact: `space.kscience:kmath-functions:0.2.0`.
> This module artifact: `space.kscience:kmath-functions:0.3.0-dev-2`.
>
> Bintray release version: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-functions/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-functions/_latestVersion)
>
@ -29,7 +29,7 @@ Functions and interpolations:
> }
>
> dependencies {
> implementation 'space.kscience:kmath-functions:0.2.0'
> implementation 'space.kscience:kmath-functions:0.3.0-dev-2'
> }
> ```
> **Gradle Kotlin DSL:**
@ -45,6 +45,6 @@ Functions and interpolations:
> }
>
> dependencies {
> implementation("space.kscience:kmath-functions:0.2.0")
> implementation("space.kscience:kmath-functions:0.3.0-dev-2")
> }
> ```

4
kmath-histograms/src/commonMain/kotlin/space/kscience/kmath/histogram/Histogram.kt
View File

@ -2,8 +2,8 @@ package space.kscience.kmath.histogram
import space.kscience.kmath.domains.Domain
import space.kscience.kmath.linear.Point
import space.kscience.kmath.structures.ArrayBuffer
import space.kscience.kmath.structures.RealBuffer
import space.kscience.kmath.structures.asBuffer
/**
* The binned data element. Could be a histogram bin with a number of counts or an artificial construct
@ -40,7 +40,7 @@ public fun interface HistogramBuilder<T : Any> {
public fun <T : Any, B : Bin<T>> HistogramBuilder<T>.put(point: Point<out T>): Unit = putValue(point, 1.0)
public fun <T : Any> HistogramBuilder<T>.put(vararg point: T): Unit = put(ArrayBuffer(point))
public fun <T : Any> HistogramBuilder<T>.put(vararg point: T): Unit = put(point.asBuffer())
public fun HistogramBuilder<Double>.put(vararg point: Number): Unit =
put(RealBuffer(point.map { it.toDouble() }.toDoubleArray()))

6
kmath-nd4j/README.md
View File

@ -9,7 +9,7 @@ This subproject implements the following features:
> #### Artifact:
>
> This module artifact: `space.kscience:kmath-nd4j:0.2.0`.
> This module artifact: `space.kscience:kmath-nd4j:0.3.0-dev-2`.
>
> Bintray release version: [ ![Download](https://api.bintray.com/packages/mipt-npm/kscience/kmath-nd4j/images/download.svg) ](https://bintray.com/mipt-npm/kscience/kmath-nd4j/_latestVersion)
>
@ -28,7 +28,7 @@ This subproject implements the following features:
> }
>
> dependencies {
> implementation 'space.kscience:kmath-nd4j:0.2.0'
> implementation 'space.kscience:kmath-nd4j:0.3.0-dev-2'
> }
> ```
> **Gradle Kotlin DSL:**
@ -44,7 +44,7 @@ This subproject implements the following features:
> }
>
> dependencies {
> implementation("space.kscience:kmath-nd4j:0.2.0")
> implementation("space.kscience:kmath-nd4j:0.3.0-dev-2")
> }
> ```

3
kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Distribution.kt
View File

@ -4,6 +4,7 @@ import space.kscience.kmath.chains.Chain
import space.kscience.kmath.chains.collect
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.structures.BufferFactory
import space.kscience.kmath.structures.RealBuffer
public interface Sampler<T : Any> {
public fun sample(generator: RandomGenerator): Chain<T>
@ -74,4 +75,4 @@ public fun <T : Any> Sampler<T>.sampleBuffer(
* Generate a bunch of samples from real distributions
*/
public fun Sampler<Double>.sampleBuffer(generator: RandomGenerator, size: Int): Chain<Buffer<Double>> =
sampleBuffer(generator, size, Buffer.Companion::real)
sampleBuffer(generator, size, ::RealBuffer)