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[WIP] Refactor NDStructures

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This commit is contained in:
Alexander Nozik 2021-01-22 23:22:24 +03:00
parent d10ae66e58
commit 061398b009
66 changed files with 889 additions and 1330 deletions
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1
CHANGELOG.md
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@ -35,6 +35,7 @@
- Matrix LUP `inverse` renamed to `inverseWithLUP`
- `NumericAlgebra` moved outside of regular algebra chain (`Ring` no longer implements it).
- Features moved to NDStructure and became transparent.
- Refactored `NDStructure` algebra to be more simple, preferring under-the-hood conversion to explicit NDStructure types
### Deprecated

2
README.md
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@ -114,7 +114,7 @@ submit a feature request if you want something to be implemented first.
>
> **Features:**
> - [algebras](kmath-core/src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt) : Algebraic structures: contexts and elements
> - [nd](kmath-core/src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt) : Many-dimensional structures
> - [nd](kmath-core/src/commonMain/kotlin/kscience/kmath/nd/NDStructure.kt) : Many-dimensional structures
> - [buffers](kmath-core/src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
> - [expressions](kmath-core/src/commonMain/kotlin/kscience/kmath/expressions) : Functional Expressions
> - [domains](kmath-core/src/commonMain/kotlin/kscience/kmath/domains) : Domains

2
build.gradle.kts
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@ -4,7 +4,7 @@ plugins {
id("ru.mipt.npm.project")
}
internal val kmathVersion: String by extra("0.2.0-dev-5")
internal val kmathVersion: String by extra("0.2.0-dev-6")
internal val bintrayRepo: String by extra("kscience")
internal val githubProject: String by extra("kmath")

4
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/DotBenchmark.kt
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@ -3,14 +3,12 @@ package kscience.kmath.benchmarks
import kotlinx.benchmark.Benchmark
import kscience.kmath.commons.linear.CMMatrixContext
import kscience.kmath.ejml.EjmlMatrixContext
import kscience.kmath.linear.BufferMatrixContext
import kscience.kmath.linear.RealMatrixContext
import kscience.kmath.linear.real
import kscience.kmath.nd.Matrix
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.Matrix
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import kotlin.random.Random

1
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/LinearAlgebraBenchmark.kt
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@ -8,7 +8,6 @@ import kscience.kmath.commons.linear.inverse
import kscience.kmath.ejml.EjmlMatrixContext
import kscience.kmath.ejml.inverse
import kscience.kmath.operations.invoke
import kscience.kmath.structures.Matrix
import org.openjdk.jmh.annotations.Scope
import org.openjdk.jmh.annotations.State
import kotlin.random.Random

9
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/NDFieldBenchmark.kt
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@ -1,5 +1,8 @@
package kscience.kmath.benchmarks
import kscience.kmath.nd.AbstractNDBuffer
import kscience.kmath.nd.NDField
import kscience.kmath.nd.RealNDField
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
import kscience.kmath.structures.*
@ -12,7 +15,7 @@ internal class NDFieldBenchmark {
@Benchmark
fun autoFieldAdd() {
bufferedField {
var res: NDBuffer<Double> = one
var res: AbstractNDBuffer<Double> = one
repeat(n) { res += one }
}
}
@ -26,7 +29,7 @@ internal class NDFieldBenchmark {
@Benchmark
fun specializedFieldAdd() {
specializedField {
var res: NDBuffer<Double> = one
var res: AbstractNDBuffer<Double> = one
repeat(n) { res += 1.0 }
}
}
@ -35,7 +38,7 @@ internal class NDFieldBenchmark {
@Benchmark
fun boxingFieldAdd() {
genericField {
var res: NDBuffer<Double> = one
var res: AbstractNDBuffer<Double> = one
repeat(n) { res += one }
}
}

4
examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ViktorBenchmark.kt
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@ -1,10 +1,10 @@
package kscience.kmath.benchmarks
import kscience.kmath.nd.NDField
import kscience.kmath.nd.RealNDField
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
import kscience.kmath.structures.BufferedNDField
import kscience.kmath.structures.NDField
import kscience.kmath.structures.RealNDField
import kscience.kmath.viktor.ViktorNDField
import org.jetbrains.bio.viktor.F64Array
import org.openjdk.jmh.annotations.Benchmark

3
examples/src/main/kotlin/kscience/kmath/operations/ComplexDemo.kt
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@ -1,8 +1,7 @@
package kscience.kmath.operations
import kscience.kmath.nd.NDField
import kscience.kmath.structures.NDElement
import kscience.kmath.structures.NDField
import kscience.kmath.structures.complex
fun main() {
// 2d element

13
examples/src/main/kotlin/kscience/kmath/structures/ComplexND.kt
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@ -1,6 +1,7 @@
package kscience.kmath.structures
import kscience.kmath.linear.transpose
import kscience.kmath.nd.*
import kscience.kmath.operations.Complex
import kscience.kmath.operations.ComplexField
import kscience.kmath.operations.invoke
@ -10,12 +11,12 @@ fun main() {
val dim = 1000
val n = 1000
val realField = NDField.real(dim, dim)
val complexField: ComplexNDField = NDField.complex(dim, dim)
val realField = NDAlgebra.real(dim, dim)
val complexField: ComplexNDField = NDAlgebra.complex(dim, dim)
val realTime = measureTimeMillis {
realField {
var res: NDBuffer<Double> = one
var res: NDStructure<Double> = one
repeat(n) {
res += 1.0
}
@ -26,8 +27,10 @@ fun main() {
val complexTime = measureTimeMillis {
complexField {
var res: NDBuffer<Complex> = one
repeat(n) { res += 1.0 }
var res: NDStructure<Complex> = one
repeat(n) {
res += 1.0
}
}
}

17
examples/src/main/kotlin/kscience/kmath/structures/NDField.kt
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@ -1,6 +1,7 @@
package kscience.kmath.structures
import kotlinx.coroutines.GlobalScope
import kscience.kmath.nd.*
import kscience.kmath.nd4j.Nd4jArrayField
import kscience.kmath.operations.RealField
import kscience.kmath.operations.invoke
@ -22,29 +23,29 @@ fun main() {
val n = 1000
// automatically build context most suited for given type.
val autoField = NDField.auto(RealField, dim, dim)
val autoField = NDAlgebra.field(RealField, Buffer.Companion::auto, dim, dim)
// specialized nd-field for Double. It works as generic Double field as well
val specializedField = NDField.real(dim, dim)
val specializedField = NDAlgebra.real(dim, dim)
//A generic boxing field. It should be used for objects, not primitives.
val genericField = NDField.boxing(RealField, dim, dim)
val boxingField = NDAlgebra.field(RealField, Buffer.Companion::boxing, dim, dim)
// Nd4j specialized field.
val nd4jField = Nd4jArrayField.real(dim, dim)
measureAndPrint("Automatic field addition") {
autoField {
var res: NDBuffer<Double> = one
var res: NDStructure<Double> = one
repeat(n) { res += 1.0 }
}
}
measureAndPrint("Element addition") {
var res = genericField.one
var res: NDStructure<Double> = boxingField.one
repeat(n) { res += 1.0 }
}
measureAndPrint("Specialized addition") {
specializedField {
var res: NDBuffer<Double> = one
var res: NDStructure<Double> = one
repeat(n) { res += 1.0 }
}
}
@ -70,8 +71,8 @@ fun main() {
measureAndPrint("Generic addition") {
//genericField.run(action)
genericField {
var res: NDBuffer<Double> = one
boxingField {
var res: NDStructure<Double> = one
repeat(n) {
res += 1.0 // couldn't avoid using `one` due to resolution ambiguity }
}

4
examples/src/main/kotlin/kscience/kmath/structures/StructureReadBenchmark.kt
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@ -1,5 +1,7 @@
package kscience.kmath.structures
import kscience.kmath.nd.DefaultStrides
import kscience.kmath.nd.NDBuffer
import kotlin.system.measureTimeMillis
fun main() {
@ -7,7 +9,7 @@ fun main() {
val array = DoubleArray(n * n) { 1.0 }
val buffer = RealBuffer(array)
val strides = DefaultStrides(intArrayOf(n, n))
val structure = BufferNDStructure(strides, buffer)
val structure = NDBuffer(strides, buffer)
measureTimeMillis {
var res = 0.0

2
examples/src/main/kotlin/kscience/kmath/structures/StructureWriteBenchmark.kt
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@ -1,5 +1,7 @@
package kscience.kmath.structures
import kscience.kmath.nd.NDStructure
import kscience.kmath.nd.mapToBuffer
import kotlin.system.measureTimeMillis
fun main() {

3
kmath-commons/src/main/kotlin/kscience/kmath/commons/linear/CMMatrix.kt
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@ -3,9 +3,8 @@ package kscience.kmath.commons.linear
import kscience.kmath.linear.DiagonalFeature
import kscience.kmath.linear.MatrixContext
import kscience.kmath.linear.Point
import kscience.kmath.linear.origin
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.structures.Matrix
import kscience.kmath.nd.Matrix
import org.apache.commons.math3.linear.*
import kotlin.reflect.KClass
import kotlin.reflect.cast

2
kmath-commons/src/main/kotlin/kscience/kmath/commons/linear/CMSolver.kt
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@ -1,7 +1,7 @@
package kscience.kmath.commons.linear
import kscience.kmath.linear.Point
import kscience.kmath.structures.Matrix
import kscience.kmath.nd.Matrix
import org.apache.commons.math3.linear.*
public enum class CMDecomposition {

2
kmath-core/README.md
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@ -3,7 +3,7 @@
The core features of KMath:
- [algebras](src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt) : Algebraic structures: contexts and elements
- [nd](src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt) : Many-dimensional structures
- [nd](src/commonMain/kotlin/kscience/kmath/nd/NDStructure.kt) : Many-dimensional structures
- [buffers](src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt) : One-dimensional structure
- [expressions](src/commonMain/kotlin/kscience/kmath/expressions) : Functional Expressions
- [domains](src/commonMain/kotlin/kscience/kmath/domains) : Domains

2
kmath-core/src/commonMain/kotlin/kscience/kmath/expressions/SymbolIndexer.kt
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@ -1,8 +1,8 @@
package kscience.kmath.expressions
import kscience.kmath.linear.Point
import kscience.kmath.nd.Structure2D
import kscience.kmath.structures.BufferFactory
import kscience.kmath.structures.Structure2D
/**
* An environment to easy transform indexed variables to symbols and back.

13
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/BufferMatrix.kt
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@ -1,7 +1,18 @@
package kscience.kmath.linear
import kscience.kmath.nd.NDStructure
import kscience.kmath.nd.Structure2D
import kscience.kmath.operations.Ring
import kscience.kmath.structures.*
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.BufferFactory
import 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]

1
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/LinearAlgebra.kt
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@ -1,7 +1,6 @@
package kscience.kmath.linear
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.VirtualBuffer
public typealias Point<T> = Buffer<T>

1
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/LupDecomposition.kt
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@ -1,6 +1,7 @@
package kscience.kmath.linear
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.nd.getFeature
import kscience.kmath.operations.*
import kscience.kmath.structures.*

9
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixBuilder.kt
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@ -1,6 +1,9 @@
package kscience.kmath.linear
import kscience.kmath.structures.*
import kscience.kmath.nd.Structure2D
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.BufferFactory
import kscience.kmath.structures.asBuffer
public class MatrixBuilder(public val rows: Int, public val columns: Int) {
public operator fun <T : Any> invoke(vararg elements: T): Matrix<T> {
@ -22,7 +25,7 @@ public fun <T : Any> Structure2D.Companion.row(vararg values: T): Matrix<T> {
public inline fun <reified T : Any> Structure2D.Companion.row(
size: Int,
factory: BufferFactory<T> = Buffer.Companion::auto,
noinline builder: (Int) -> T
noinline builder: (Int) -> T,
): Matrix<T> {
val buffer = factory(size, builder)
return BufferMatrix(1, size, buffer)
@ -36,7 +39,7 @@ public fun <T : Any> Structure2D.Companion.column(vararg values: T): Matrix<T> {
public inline fun <reified T : Any> Structure2D.Companion.column(
size: Int,
factory: BufferFactory<T> = Buffer.Companion::auto,
noinline builder: (Int) -> T
noinline builder: (Int) -> T,
): Matrix<T> {
val buffer = factory(size, builder)
return BufferMatrix(size, 1, buffer)

1
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixContext.kt
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@ -6,7 +6,6 @@ import kscience.kmath.operations.invoke
import kscience.kmath.operations.sum
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.BufferFactory
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.asSequence
/**

2
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixFeatures.kt
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@ -1,7 +1,5 @@
package kscience.kmath.linear
import kscience.kmath.structures.Matrix
/**
* A marker interface representing some properties of matrices or additional transformations of them. Features are used
* to optimize matrix operations performance in some cases or retrieve the APIs.

8
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixWrapper.kt
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@ -1,11 +1,10 @@
package kscience.kmath.linear
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.nd.Structure2D
import kscience.kmath.nd.getFeature
import kscience.kmath.operations.Ring
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.Structure2D
import kscience.kmath.structures.asBuffer
import kscience.kmath.structures.getFeature
import kotlin.math.sqrt
import kotlin.reflect.KClass
import kotlin.reflect.safeCast
@ -39,7 +38,8 @@ public class MatrixWrapper<T : Any> internal constructor(
* Origin does not necessary store all features.
*/
@UnstableKMathAPI
public val <T : Any> Matrix<T>.origin: Matrix<T> get() = (this as? MatrixWrapper)?.origin ?: this
public val <T : Any> Matrix<T>.origin: Matrix<T>
get() = (this as? MatrixWrapper)?.origin ?: this
/**
* Add a single feature to a [Matrix]

1
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/RealMatrixContext.kt
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@ -1,6 +1,5 @@
package kscience.kmath.linear
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.RealBuffer
@Suppress("OVERRIDE_BY_INLINE")

2
kmath-core/src/commonMain/kotlin/kscience/kmath/linear/VirtualMatrix.kt
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@ -1,7 +1,5 @@
package kscience.kmath.linear
import kscience.kmath.structures.Matrix
public class VirtualMatrix<T : Any>(
override val rowNum: Int,
override val colNum: Int,

128
kmath-core/src/commonMain/kotlin/kscience/kmath/nd/BufferNDAlgebra.kt Normal file
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@ -0,0 +1,128 @@
package kscience.kmath.nd
import kscience.kmath.nd.*
import kscience.kmath.operations.*
import kscience.kmath.structures.BufferFactory
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
public interface BufferNDAlgebra<T, C> : NDAlgebra<T, C> {
public val strides: Strides
public val bufferFactory: BufferFactory<T>
override fun produce(initializer: C.(IntArray) -> T): NDBuffer<T> = NDBuffer(
strides,
bufferFactory(strides.linearSize) { offset ->
elementContext.initializer(strides.index(offset))
}
)
public val NDStructure<T>.ndBuffer: NDBuffer<T>
get() = when {
!shape.contentEquals(this@BufferNDAlgebra.shape) -> throw ShapeMismatchException(
this@BufferNDAlgebra.shape,
shape
)
this is NDBuffer && this.strides == this@BufferNDAlgebra.strides -> this
else -> produce { this@ndBuffer[it] }
}
override fun map(arg: NDStructure<T>, transform: C.(T) -> T): NDBuffer<T> {
val argAsBuffer = arg.ndBuffer
val buffer = bufferFactory(strides.linearSize) { offset ->
elementContext.transform(argAsBuffer.buffer[offset])
}
return NDBuffer(strides, buffer)
}
override fun mapIndexed(arg: NDStructure<T>, transform: C.(index: IntArray, T) -> T): NDStructure<T> {
val argAsBuffer = arg.ndBuffer
val buffer = bufferFactory(strides.linearSize) { offset ->
elementContext.transform(
strides.index(offset),
argAsBuffer[offset]
)
}
return NDBuffer(strides, buffer)
}
override fun combine(a: NDStructure<T>, b: NDStructure<T>, transform: C.(T, T) -> T): NDStructure<T> {
val aBuffer = a.ndBuffer
val bBuffer = b.ndBuffer
val buffer = bufferFactory(strides.linearSize) { offset ->
elementContext.transform(aBuffer.buffer[offset], bBuffer[offset])
}
return NDBuffer(strides, buffer)
}
}
public open class BufferedNDSpace<T, R : Space<T>>(
final override val shape: IntArray,
final override val elementContext: R,
final override val bufferFactory: BufferFactory<T>,
) : NDSpace<T, R>, BufferNDAlgebra<T, R> {
override val strides: Strides = DefaultStrides(shape)
override val zero: NDBuffer<T> by lazy { produce { zero } }
}
public open class BufferedNDRing<T, R : Ring<T>>(
shape: IntArray,
elementContext: R,
bufferFactory: BufferFactory<T>,
) : BufferedNDSpace<T, R>(shape, elementContext, bufferFactory), NDRing<T, R> {
override val one: NDBuffer<T> by lazy { produce { one } }
}
public open class BufferedNDField<T, R : Field<T>>(
shape: IntArray,
elementContext: R,
bufferFactory: BufferFactory<T>,
) : BufferedNDRing<T, R>(shape, elementContext, bufferFactory), NDField<T, R>
// space factories
public fun <T, A : Space<T>> NDAlgebra.Companion.space(
space: A,
bufferFactory: BufferFactory<T>,
vararg shape: Int,
): BufferedNDSpace<T, A> = BufferedNDSpace(shape, space, bufferFactory)
public inline fun <T, A : Space<T>, R> A.nd(
noinline bufferFactory: BufferFactory<T>,
vararg shape: Int,
action: BufferedNDSpace<T, A>.() -> R,
): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return NDAlgebra.space(this, bufferFactory, *shape).run(action)
}
//ring factories
public fun <T, A : Ring<T>> NDAlgebra.Companion.ring(
ring: A,
bufferFactory: BufferFactory<T>,
vararg shape: Int,
): BufferedNDRing<T, A> = BufferedNDRing(shape, ring, bufferFactory)
public inline fun <T, A : Ring<T>, R> A.nd(
noinline bufferFactory: BufferFactory<T>,
vararg shape: Int,
action: BufferedNDRing<T, A>.() -> R,
): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return NDAlgebra.ring(this, bufferFactory, *shape).run(action)
}
//field factories
public fun <T, A : Field<T>> NDAlgebra.Companion.field(
field: A,
bufferFactory: BufferFactory<T>,
vararg shape: Int,
): BufferedNDField<T, A> = BufferedNDField(shape, field, bufferFactory)
public inline fun <T, A : Field<T>, R> A.nd(
noinline bufferFactory: BufferFactory<T>,
vararg shape: Int,
action: BufferedNDField<T, A>.() -> R,
): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return NDAlgebra.field(this, bufferFactory, *shape).run(action)
}

113
kmath-core/src/commonMain/kotlin/kscience/kmath/nd/ComplexNDField.kt Normal file
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@ -0,0 +1,113 @@
package kscience.kmath.nd
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.operations.*
import kscience.kmath.structures.Buffer
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
/**
* An optimized nd-field for complex numbers
*/
@OptIn(UnstableKMathAPI::class)
public open class ComplexNDField(
shape: IntArray,
) : BufferedNDField<Complex, ComplexField>(shape, ComplexField, Buffer.Companion::complex),
RingWithNumbers<NDStructure<Complex>>,
ExtendedField<NDStructure<Complex>> {
override val zero: NDBuffer<Complex> by lazy { produce { zero } }
override val one: NDBuffer<Complex> by lazy { produce { one } }
override fun number(value: Number): NDBuffer<Complex> {
val d = value.toComplex() // minimize conversions
return produce { d }
}
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun map(
// arg: AbstractNDBuffer<Double>,
// transform: RealField.(Double) -> Double,
// ): RealNDElement {
// check(arg)
// val array = RealBuffer(arg.strides.linearSize) { offset -> RealField.transform(arg.buffer[offset]) }
// return BufferedNDFieldElement(this, array)
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun produce(initializer: RealField.(IntArray) -> Double): RealNDElement {
// val array = RealBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) }
// return BufferedNDFieldElement(this, array)
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun mapIndexed(
// arg: AbstractNDBuffer<Double>,
// transform: RealField.(index: IntArray, Double) -> Double,
// ): RealNDElement {
// check(arg)
// return BufferedNDFieldElement(
// this,
// RealBuffer(arg.strides.linearSize) { offset ->
// elementContext.transform(
// arg.strides.index(offset),
// arg.buffer[offset]
// )
// })
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun combine(
// a: AbstractNDBuffer<Double>,
// b: AbstractNDBuffer<Double>,
// transform: RealField.(Double, Double) -> Double,
// ): RealNDElement {
// check(a, b)
// val buffer = RealBuffer(strides.linearSize) { offset ->
// elementContext.transform(a.buffer[offset], b.buffer[offset])
// }
// return BufferedNDFieldElement(this, buffer)
// }
override fun power(arg: NDStructure<Complex>, pow: Number): NDBuffer<Complex> = map(arg) { power(it, pow) }
override fun exp(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { exp(it) }
override fun ln(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { ln(it) }
override fun sin(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { sin(it) }
override fun cos(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { cos(it) }
override fun tan(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { tan(it) }
override fun asin(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { asin(it) }
override fun acos(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { acos(it) }
override fun atan(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { atan(it) }
override fun sinh(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { sinh(it) }
override fun cosh(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { cosh(it) }
override fun tanh(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { tanh(it) }
override fun asinh(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { asinh(it) }
override fun acosh(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { acosh(it) }
override fun atanh(arg: NDStructure<Complex>): NDBuffer<Complex> = map(arg) { atanh(it) }
}
/**
* Fast element production using function inlining
*/
public inline fun BufferedNDField<Complex, ComplexField>.produceInline(initializer: ComplexField.(Int) -> Complex): NDBuffer<Complex> {
contract { callsInPlace(initializer, InvocationKind.EXACTLY_ONCE) }
val buffer = Buffer.complex(strides.linearSize) { offset -> ComplexField.initializer(offset) }
return NDBuffer(strides, buffer)
}
public fun NDAlgebra.Companion.complex(vararg shape: Int): ComplexNDField = ComplexNDField(shape)
/**
* Produce a context for n-dimensional operations inside this real field
*/
public inline fun <R> ComplexField.nd(vararg shape: Int, action: ComplexNDField.() -> R): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return ComplexNDField(shape).action()
}

262
kmath-core/src/commonMain/kotlin/kscience/kmath/nd/NDAlgebra.kt Normal file
View File

@ -0,0 +1,262 @@
package kscience.kmath.nd
import kscience.kmath.operations.Field
import kscience.kmath.operations.Ring
import kscience.kmath.operations.Space
import kscience.kmath.structures.*
/**
* An exception is thrown when the expected ans actual shape of NDArray differs.
*
* @property expected the expected shape.
* @property actual the actual shape.
*/
public class ShapeMismatchException(public val expected: IntArray, public val actual: IntArray) :
RuntimeException("Shape ${actual.contentToString()} doesn't fit in expected shape ${expected.contentToString()}.")
/**
* The base interface for all ND-algebra implementations.
*
* @param T the type of ND-structure element.
* @param C the type of the element context.
* @param N the type of the structure.
*/
public interface NDAlgebra<T, C> {
/**
* The shape of ND-structures this algebra operates on.
*/
public val shape: IntArray
/**
* The algebra over elements of ND structure.
*/
public val elementContext: C
/**
* Produces a new [N] structure using given initializer function.
*/
public fun produce(initializer: C.(IntArray) -> T): NDStructure<T>
/**
* Maps elements from one structure to another one by applying [transform] to them.
*/
public fun map(arg: NDStructure<T>, transform: C.(T) -> T): NDStructure<T>
/**
* Maps elements from one structure to another one by applying [transform] to them alongside with their indices.
*/
public fun mapIndexed(arg: NDStructure<T>, transform: C.(index: IntArray, T) -> T): NDStructure<T>
/**
* Combines two structures into one.
*/
public fun combine(a: NDStructure<T>, b: NDStructure<T>, transform: C.(T, T) -> T): NDStructure<T>
/**
* Element-wise invocation of function working on [T] on a [NDStructure].
*/
public operator fun Function1<T, T>.invoke(structure: NDStructure<T>): NDStructure<T> =
map(structure) { value -> this@invoke(value) }
public companion object
}
/**
* 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> 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) }
?: structures
/**
* Checks if given element is consistent with this context.
*
* @param element the structure to check.
* @return the valid structure.
*/
internal fun <T, C> NDAlgebra<T, C>.checkShape(element: NDStructure<T>): NDStructure<T> {
if (!element.shape.contentEquals(shape)) throw ShapeMismatchException(shape, element.shape)
return element
}
/**
* Space of [NDStructure].
*
* @param T the type of the element contained in ND structure.
* @param N the type of ND structure.
* @param S the type of space of structure elements.
*/
public interface NDSpace<T, S : Space<T>> : Space<NDStructure<T>>, NDAlgebra<T, S> {
/**
* Element-wise addition.
*
* @param a the addend.
* @param b the augend.
* @return the sum.
*/
public override fun add(a: NDStructure<T>, b: NDStructure<T>): NDStructure<T> =
combine(a, b) { aValue, bValue -> add(aValue, bValue) }
/**
* Element-wise multiplication by scalar.
*
* @param a the multiplicand.
* @param k the multiplier.
* @return the product.
*/
public override fun multiply(a: NDStructure<T>, k: Number): NDStructure<T> = map(a) { multiply(it, k) }
// TODO move to extensions after KEEP-176
/**
* Adds an ND structure to an element of it.
*
* @receiver the addend.
* @param arg the augend.
* @return the sum.
*/
public operator fun NDStructure<T>.plus(arg: T): NDStructure<T> = map(this) { value -> add(arg, value) }
/**
* Subtracts an element from ND structure of it.
*
* @receiver the dividend.
* @param arg the divisor.
* @return the quotient.
*/
public operator fun NDStructure<T>.minus(arg: T): NDStructure<T> = map(this) { value -> add(arg, -value) }
/**
* Adds an element to ND structure of it.
*
* @receiver the addend.
* @param arg the augend.
* @return the sum.
*/
public operator fun T.plus(arg: NDStructure<T>): NDStructure<T> = map(arg) { value -> add(this@plus, value) }
/**
* Subtracts an ND structure from an element of it.
*
* @receiver the dividend.
* @param arg the divisor.
* @return the quotient.
*/
public operator fun T.minus(arg: NDStructure<T>): NDStructure<T> = map(arg) { value -> add(-this@minus, value) }
public companion object
}
/**
* Ring of [NDStructure].
*
* @param T the type of the element contained in ND structure.
* @param N the type of ND structure.
* @param R the type of ring of structure elements.
*/
public interface NDRing<T, R : Ring<T>> : Ring<NDStructure<T>>, NDSpace<T, R> {
/**
* Element-wise multiplication.
*
* @param a the multiplicand.
* @param b the multiplier.
* @return the product.
*/
public override fun multiply(a: NDStructure<T>, b: NDStructure<T>): NDStructure<T> =
combine(a, b) { aValue, bValue -> multiply(aValue, bValue) }
//TODO move to extensions after KEEP-176
/**
* Multiplies an ND structure by an element of it.
*
* @receiver the multiplicand.
* @param arg the multiplier.
* @return the product.
*/
public operator fun NDStructure<T>.times(arg: T): NDStructure<T> = map(this) { value -> multiply(arg, value) }
/**
* Multiplies an element by a ND structure of it.
*
* @receiver the multiplicand.
* @param arg the multiplier.
* @return the product.
*/
public operator fun T.times(arg: NDStructure<T>): NDStructure<T> = map(arg) { value -> multiply(this@times, value) }
public companion object
}
/**
* Field of [NDStructure].
*
* @param T the type of the element contained in ND structure.
* @param N the type of ND structure.
* @param F the type field of structure elements.
*/
public interface NDField<T, F : Field<T>> : Field<NDStructure<T>>, NDRing<T, F> {
/**
* Element-wise division.
*
* @param a the dividend.
* @param b the divisor.
* @return the quotient.
*/
public override fun divide(a: NDStructure<T>, b: NDStructure<T>): NDStructure<T> =
combine(a, b) { aValue, bValue -> divide(aValue, bValue) }
//TODO move to extensions after KEEP-176
/**
* Divides an ND structure by an element of it.
*
* @receiver the dividend.
* @param arg the divisor.
* @return the quotient.
*/
public operator fun NDStructure<T>.div(arg: T): NDStructure<T> = map(this) { value -> divide(arg, value) }
/**
* Divides an element by an ND structure of it.
*
* @receiver the dividend.
* @param arg the divisor.
* @return the quotient.
*/
public operator fun T.div(arg: NDStructure<T>): NDStructure<T> = map(arg) { divide(it, this@div) }
// @ThreadLocal
// public companion object {
// private val realNDFieldCache: MutableMap<IntArray, RealNDField> = hashMapOf()
//
// /**
// * Create a nd-field for [Double] values or pull it from cache if it was created previously.
// */
// public fun real(vararg shape: Int): RealNDField = realNDFieldCache.getOrPut(shape) { RealNDField(shape) }
//
// /**
// * Create an ND field with boxing generic buffer.
// */
// public fun <T : Any, F : Field<T>> boxing(
// field: F,
// vararg shape: Int,
// bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
// ): BufferedNDField<T, F> = BufferedNDField(shape, field, bufferFactory)
//
// /**
// * Create a most suitable implementation for nd-field using reified class.
// */
// @Suppress("UNCHECKED_CAST")
// public inline fun <reified T : Any, F : Field<T>> auto(field: F, vararg shape: Int): NDField<T, F> =
// when {
// T::class == Double::class -> real(*shape) as NDField<T, F>
// T::class == Complex::class -> complex(*shape) as BufferedNDField<T, F>
// else -> BoxingNDField(shape, field, Buffer.Companion::auto)
// }
// }
}

96
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/NDStructure.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/nd/NDStructure.kt
View File

@ -1,6 +1,10 @@
package kscience.kmath.structures
package kscience.kmath.nd
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.BufferFactory
import kscience.kmath.structures.MutableBuffer
import kscience.kmath.structures.asSequence
import kotlin.jvm.JvmName
import kotlin.native.concurrent.ThreadLocal
import kotlin.reflect.KClass
@ -74,8 +78,8 @@ public interface NDStructure<T> {
strides: Strides,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
initializer: (IntArray) -> T,
): BufferNDStructure<T> =
BufferNDStructure(strides, bufferFactory(strides.linearSize) { i -> initializer(strides.index(i)) })
): NDBuffer<T> =
NDBuffer(strides, bufferFactory(strides.linearSize) { i -> initializer(strides.index(i)) })
/**
* Inline create NDStructure with non-boxing buffer implementation if it is possible
@ -83,40 +87,40 @@ public interface NDStructure<T> {
public inline fun <reified T : Any> auto(
strides: Strides,
crossinline initializer: (IntArray) -> T,
): BufferNDStructure<T> =
BufferNDStructure(strides, Buffer.auto(strides.linearSize) { i -> initializer(strides.index(i)) })
): NDBuffer<T> =
NDBuffer(strides, Buffer.auto(strides.linearSize) { i -> initializer(strides.index(i)) })
public inline fun <T : Any> auto(
type: KClass<T>,
strides: Strides,
crossinline initializer: (IntArray) -> T,
): BufferNDStructure<T> =
BufferNDStructure(strides, Buffer.auto(type, strides.linearSize) { i -> initializer(strides.index(i)) })
): NDBuffer<T> =
NDBuffer(strides, Buffer.auto(type, strides.linearSize) { i -> initializer(strides.index(i)) })
public fun <T> build(
shape: IntArray,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
initializer: (IntArray) -> T,
): BufferNDStructure<T> = build(DefaultStrides(shape), bufferFactory, initializer)
): NDBuffer<T> = build(DefaultStrides(shape), bufferFactory, initializer)
public inline fun <reified T : Any> auto(
shape: IntArray,
crossinline initializer: (IntArray) -> T,
): BufferNDStructure<T> =
): NDBuffer<T> =
auto(DefaultStrides(shape), initializer)
@JvmName("autoVarArg")
public inline fun <reified T : Any> auto(
vararg shape: Int,
crossinline initializer: (IntArray) -> T,
): BufferNDStructure<T> =
): NDBuffer<T> =
auto(DefaultStrides(shape), initializer)
public inline fun <T : Any> auto(
type: KClass<T>,
vararg shape: Int,
crossinline initializer: (IntArray) -> T,
): BufferNDStructure<T> =
): NDBuffer<T> =
auto(type, DefaultStrides(shape), initializer)
}
}
@ -156,7 +160,7 @@ public inline fun <T> MutableNDStructure<T>.mapInPlace(action: (IntArray, T) ->
*/
public interface Strides {
/**
* Shape of NDstructure
* Shape of NDStructure
*/
public val shape: IntArray
@ -185,7 +189,9 @@ public interface Strides {
/**
* Iterate over ND indices in a natural order
*/
public fun indices(): Sequence<IntArray> = (0 until linearSize).asSequence().map { index(it) }
public fun indices(): Sequence<IntArray> = (0 until linearSize).asSequence().map {
index(it)
}
}
/**
@ -211,7 +217,7 @@ public class DefaultStrides private constructor(override val shape: IntArray) :
}
override fun offset(index: IntArray): Int = index.mapIndexed { i, value ->
if (value < 0 || value >= this.shape[i])
if (value < 0 || value >= shape[i])
throw IndexOutOfBoundsException("Index $value out of shape bounds: (0,${this.shape[i]})")
value * strides[i]
@ -256,23 +262,29 @@ public class DefaultStrides private constructor(override val shape: IntArray) :
* Represents [NDStructure] over [Buffer].
*
* @param T the type of items.
* @param strides The strides to access elements of [Buffer] by linear indices.
* @param buffer The underlying buffer.
*/
public abstract class NDBuffer<T> : NDStructure<T> {
/**
* The underlying buffer.
*/
public abstract val buffer: Buffer<T>
public open class NDBuffer<T>(
public val strides: Strides,
buffer: Buffer<T>,
) : NDStructure<T> {
/**
* The strides to access elements of [Buffer] by linear indices.
*/
public abstract val strides: Strides
init {
if (strides.linearSize != buffer.size) {
error("Expected buffer side of ${strides.linearSize}, but found ${buffer.size}")
}
}
public open val buffer: Buffer<T> = buffer
override operator fun get(index: IntArray): T = buffer[strides.offset(index)]
override val shape: IntArray get() = strides.shape
override fun elements(): Sequence<Pair<IntArray, T>> = strides.indices().map { it to this[it] }
override fun elements(): Sequence<Pair<IntArray, T>> = strides.indices().map {
it to this[it]
}
override fun equals(other: Any?): Boolean {
return NDStructure.contentEquals(this, other as? NDStructure<*> ?: return false)
@ -297,46 +309,30 @@ public abstract class NDBuffer<T> : NDStructure<T> {
}
return "NDBuffer(shape=${shape.contentToString()}, buffer=$bufferRepr)"
}
}
/**
* Boxing generic [NDStructure]
*/
public class BufferNDStructure<T>(
override val strides: Strides,
override val buffer: Buffer<T>,
) : NDBuffer<T>() {
init {
if (strides.linearSize != buffer.size) {
error("Expected buffer side of ${strides.linearSize}, but found ${buffer.size}")
}
}
}
/**
* Transform structure to a new structure using provided [BufferFactory] and optimizing if argument is [BufferNDStructure]
* Transform structure to a new structure using provided [BufferFactory] and optimizing if argument is [NDBuffer]
*/
public inline fun <T, reified R : Any> NDStructure<T>.mapToBuffer(
factory: BufferFactory<R> = Buffer.Companion::auto,
crossinline transform: (T) -> R,
): BufferNDStructure<R> {
return if (this is BufferNDStructure<T>)
BufferNDStructure(this.strides, factory.invoke(strides.linearSize) { transform(buffer[it]) })
): NDBuffer<R> {
return if (this is NDBuffer<T>)
NDBuffer(this.strides, factory.invoke(strides.linearSize) { transform(buffer[it]) })
else {
val strides = DefaultStrides(shape)
BufferNDStructure(strides, factory.invoke(strides.linearSize) { transform(get(strides.index(it))) })
NDBuffer(strides, factory.invoke(strides.linearSize) { transform(get(strides.index(it))) })
}
}
/**
* Mutable ND buffer based on linear [MutableBuffer].
*/
public class MutableBufferNDStructure<T>(
override val strides: Strides,
override val buffer: MutableBuffer<T>,
) : NDBuffer<T>(), MutableNDStructure<T> {
public class MutableNDBuffer<T>(
strides: Strides,
buffer: MutableBuffer<T>,
) : NDBuffer<T>(strides,buffer), MutableNDStructure<T> {
init {
require(strides.linearSize == buffer.size) {
@ -344,6 +340,8 @@ public class MutableBufferNDStructure<T>(
}
}
override val buffer: MutableBuffer<T> = super.buffer as MutableBuffer<T>
override operator fun set(index: IntArray, value: T): Unit = buffer.set(strides.offset(index), value)
}

111
kmath-core/src/commonMain/kotlin/kscience/kmath/nd/RealNDField.kt Normal file
View File

@ -0,0 +1,111 @@
package kscience.kmath.nd
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.operations.ExtendedField
import kscience.kmath.operations.RealField
import kscience.kmath.operations.RingWithNumbers
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.RealBuffer
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@OptIn(UnstableKMathAPI::class)
public open class RealNDField(
shape: IntArray,
) : BufferedNDField<Double, RealField>(shape, RealField, Buffer.Companion::real),
RingWithNumbers<NDStructure<Double>>,
ExtendedField<NDStructure<Double>> {
override val zero: NDBuffer<Double> by lazy { produce { zero } }
override val one: NDBuffer<Double> by lazy { produce { one } }
override fun number(value: Number): NDBuffer<Double> {
val d = value.toDouble() // minimize conversions
return produce { d }
}
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun map(
// arg: AbstractNDBuffer<Double>,
// transform: RealField.(Double) -> Double,
// ): RealNDElement {
// check(arg)
// val array = RealBuffer(arg.strides.linearSize) { offset -> RealField.transform(arg.buffer[offset]) }
// return BufferedNDFieldElement(this, array)
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun produce(initializer: RealField.(IntArray) -> Double): RealNDElement {
// val array = RealBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) }
// return BufferedNDFieldElement(this, array)
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun mapIndexed(
// arg: AbstractNDBuffer<Double>,
// transform: RealField.(index: IntArray, Double) -> Double,
// ): RealNDElement {
// check(arg)
// return BufferedNDFieldElement(
// this,
// RealBuffer(arg.strides.linearSize) { offset ->
// elementContext.transform(
// arg.strides.index(offset),
// arg.buffer[offset]
// )
// })
// }
//
// @Suppress("OVERRIDE_BY_INLINE")
// override inline fun combine(
// a: AbstractNDBuffer<Double>,
// b: AbstractNDBuffer<Double>,
// transform: RealField.(Double, Double) -> Double,
// ): RealNDElement {
// check(a, b)
// val buffer = RealBuffer(strides.linearSize) { offset ->
// elementContext.transform(a.buffer[offset], b.buffer[offset])
// }
// return BufferedNDFieldElement(this, buffer)
// }
override fun power(arg: NDStructure<Double>, pow: Number): NDBuffer<Double> = map(arg) { power(it, pow) }
override fun exp(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { exp(it) }
override fun ln(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { ln(it) }
override fun sin(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { sin(it) }
override fun cos(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { cos(it) }
override fun tan(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { tan(it) }
override fun asin(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { asin(it) }
override fun acos(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { acos(it) }
override fun atan(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { atan(it) }
override fun sinh(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { sinh(it) }
override fun cosh(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { cosh(it) }
override fun tanh(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { tanh(it) }
override fun asinh(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { asinh(it) }
override fun acosh(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { acosh(it) }
override fun atanh(arg: NDStructure<Double>): NDBuffer<Double> = map(arg) { atanh(it) }
}
/**
* Fast element production using function inlining
*/
public inline fun BufferedNDField<Double, RealField>.produceInline(crossinline initializer: RealField.(Int) -> Double): NDBuffer<Double> {
contract { callsInPlace(initializer, InvocationKind.EXACTLY_ONCE) }
val array = DoubleArray(strides.linearSize) { offset -> RealField.initializer(offset) }
return NDBuffer(strides, RealBuffer(array))
}
public fun NDAlgebra.Companion.real(vararg shape: Int): RealNDField = RealNDField(shape)
/**
* Produce a context for n-dimensional operations inside this real field
*/
public inline fun <R> RealField.nd(vararg shape: Int, action: RealNDField.() -> R): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return RealNDField(shape).run(action)
}

36
kmath-core/src/commonMain/kotlin/kscience/kmath/nd/ShortNDRing.kt Normal file
View File

@ -0,0 +1,36 @@
package kscience.kmath.nd
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.operations.RingWithNumbers
import kscience.kmath.operations.ShortRing
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.ShortBuffer
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
@OptIn(UnstableKMathAPI::class)
public open class ShortNDRing(
shape: IntArray,
) : BufferedNDRing<Short, ShortRing>(shape, ShortRing, Buffer.Companion::auto),
RingWithNumbers<NDStructure<Short>> {
override val zero: NDBuffer<Short> by lazy { produce { zero } }
override val one: NDBuffer<Short> by lazy { produce { one } }
override fun number(value: Number): NDBuffer<Short> {
val d = value.toShort() // minimize conversions
return produce { d }
}
}
/**
* Fast element production using function inlining.
*/
public inline fun BufferedNDRing<Short, ShortRing>.produceInline(crossinline initializer: ShortRing.(Int) -> Short): NDBuffer<Short> {
return NDBuffer(strides, ShortBuffer(ShortArray(strides.linearSize) { offset -> ShortRing.initializer(offset) }))
}
public inline fun <R> ShortRing.nd(vararg shape: Int, action: ShortNDRing.() -> R): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return ShortNDRing(shape).run(action)
}

7
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/Structure1D.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/nd/Structure1D.kt
View File

@ -1,4 +1,7 @@
package kscience.kmath.structures
package kscience.kmath.nd
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.asSequence
/**
* A structure that is guaranteed to be one-dimensional
@ -34,7 +37,7 @@ private inline class Buffer1DWrapper<T>(val buffer: Buffer<T>) : Structure1D<T>
override val size: Int get() = buffer.size
override fun elements(): Sequence<Pair<IntArray, T>> =
asSequence().mapIndexed { index, value -> intArrayOf(index) to value }
buffer.asSequence().mapIndexed { index, value -> intArrayOf(index) to value }
override operator fun get(index: Int): T = buffer[index]
}

12
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/Structure2D.kt → kmath-core/src/commonMain/kotlin/kscience/kmath/nd/Structure2D.kt
View File

@ -1,4 +1,7 @@
package kscience.kmath.structures
package kscience.kmath.nd
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.VirtualBuffer
/**
* A structure that is guaranteed to be two-dimensional.
@ -73,10 +76,3 @@ 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")
/**
* Alias for [Structure2D] with more familiar name.
*
* @param T the type of items.
*/
public typealias Matrix<T> = Structure2D<T>

1
kmath-core/src/commonMain/kotlin/kscience/kmath/operations/BigInt.kt
View File

@ -1,6 +1,7 @@
package kscience.kmath.operations
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.nd.NDAlgebra
import kscience.kmath.operations.BigInt.Companion.BASE
import kscience.kmath.operations.BigInt.Companion.BASE_SIZE
import kscience.kmath.structures.*

81
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BoxingNDField.kt
View File

@ -1,81 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.operations.Field
import kscience.kmath.operations.FieldElement
public class BoxingNDField<T, F : Field<T>>(
public override val shape: IntArray,
public override val elementContext: F,
public val bufferFactory: BufferFactory<T>
) : BufferedNDField<T, F> {
public override val zero: BufferedNDFieldElement<T, F> by lazy { produce { zero } }
public override val one: BufferedNDFieldElement<T, F> by lazy { produce { one } }
public override val strides: Strides = DefaultStrides(shape)
public fun buildBuffer(size: Int, initializer: (Int) -> T): Buffer<T> =
bufferFactory(size, initializer)
public override fun check(vararg elements: NDBuffer<T>): Array<out NDBuffer<T>> {
require(elements.all { it.strides == strides }) { "Element strides are not the same as context strides" }
return elements
}
public override fun produce(initializer: F.(IntArray) -> T): BufferedNDFieldElement<T, F> =
BufferedNDFieldElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) })
public override fun map(arg: NDBuffer<T>, transform: F.(T) -> T): BufferedNDFieldElement<T, F> {
check(arg)
return BufferedNDFieldElement(
this,
buildBuffer(arg.strides.linearSize) { offset -> elementContext.transform(arg.buffer[offset]) })
// val buffer = arg.buffer.transform { _, value -> elementContext.transform(value) }
// return BufferedNDFieldElement(this, buffer)
}
public override fun mapIndexed(
arg: NDBuffer<T>,
transform: F.(index: IntArray, T) -> T
): BufferedNDFieldElement<T, F> {
check(arg)
return BufferedNDFieldElement(
this,
buildBuffer(arg.strides.linearSize) { offset ->
elementContext.transform(
arg.strides.index(offset),
arg.buffer[offset]
)
})
// val buffer =
// arg.buffer.transform { offset, value -> elementContext.transform(arg.strides.index(offset), value) }
// return BufferedNDFieldElement(this, buffer)
}
public override fun combine(
a: NDBuffer<T>,
b: NDBuffer<T>,
transform: F.(T, T) -> T
): BufferedNDFieldElement<T, F> {
check(a, b)
return BufferedNDFieldElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.transform(a.buffer[offset], b.buffer[offset]) })
}
public override fun NDBuffer<T>.toElement(): FieldElement<NDBuffer<T>, *, out BufferedNDField<T, F>> =
BufferedNDFieldElement(this@BoxingNDField, buffer)
}
public inline fun <T : Any, F : Field<T>, R> F.nd(
noinline bufferFactory: BufferFactory<T>,
vararg shape: Int,
action: NDField<T, F, *>.() -> R
): R {
val ndfield = NDField.boxing(this, *shape, bufferFactory = bufferFactory)
return ndfield.action()
}

71
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BoxingNDRing.kt
View File

@ -1,71 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.operations.Ring
import kscience.kmath.operations.RingElement
public class BoxingNDRing<T, R : Ring<T>>(
override val shape: IntArray,
override val elementContext: R,
public val bufferFactory: BufferFactory<T>
) : BufferedNDRing<T, R> {
override val strides: Strides = DefaultStrides(shape)
override val zero: BufferedNDRingElement<T, R> by lazy { produce { zero } }
override val one: BufferedNDRingElement<T, R> by lazy { produce { one } }
public fun buildBuffer(size: Int, initializer: (Int) -> T): Buffer<T> = bufferFactory(size, initializer)
override fun check(vararg elements: NDBuffer<T>): Array<out NDBuffer<T>> {
if (!elements.all { it.strides == this.strides }) error("Element strides are not the same as context strides")
return elements
}
override fun produce(initializer: R.(IntArray) -> T): BufferedNDRingElement<T, R> =
BufferedNDRingElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) })
override fun map(arg: NDBuffer<T>, transform: R.(T) -> T): BufferedNDRingElement<T, R> {
check(arg)
return BufferedNDRingElement(
this,
buildBuffer(arg.strides.linearSize) { offset -> elementContext.transform(arg.buffer[offset]) })
// val buffer = arg.buffer.transform { _, value -> elementContext.transform(value) }
// return BufferedNDFieldElement(this, buffer)
}
override fun mapIndexed(
arg: NDBuffer<T>,
transform: R.(index: IntArray, T) -> T
): BufferedNDRingElement<T, R> {
check(arg)
return BufferedNDRingElement(
this,
buildBuffer(arg.strides.linearSize) { offset ->
elementContext.transform(
arg.strides.index(offset),
arg.buffer[offset]
)
})
// val buffer =
// arg.buffer.transform { offset, value -> elementContext.transform(arg.strides.index(offset), value) }
// return BufferedNDFieldElement(this, buffer)
}
override fun combine(
a: NDBuffer<T>,
b: NDBuffer<T>,
transform: R.(T, T) -> T
): BufferedNDRingElement<T, R> {
check(a, b)
return BufferedNDRingElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.transform(a.buffer[offset], b.buffer[offset]) })
}
override fun NDBuffer<T>.toElement(): RingElement<NDBuffer<T>, *, out BufferedNDRing<T, R>> =
BufferedNDRingElement(this@BoxingNDRing, buffer)
}

5
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BufferAccessor2D.kt
View File

@ -1,5 +1,10 @@
package kscience.kmath.structures
import kscience.kmath.nd.DefaultStrides
import kscience.kmath.nd.NDStructure
import kscience.kmath.nd.Structure2D
import kscience.kmath.nd.as2D
/**
* A context that allows to operate on a [MutableBuffer] as on 2d array
*/

43
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BufferedNDAlgebra.kt
View File

@ -1,43 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.operations.*
public interface BufferedNDAlgebra<T, C> : NDAlgebra<T, C, NDBuffer<T>> {
public val strides: Strides
public override fun check(vararg elements: NDBuffer<T>): Array<out NDBuffer<T>> {
require(elements.all { it.strides == strides }) { "Strides mismatch" }
return elements
}
/**
* Convert any [NDStructure] to buffered structure using strides from this context.
* If the structure is already [NDBuffer], conversion is free. If not, it could be expensive because iteration over
* indices.
*
* If the argument is [NDBuffer] with different strides structure, the new element will be produced.
*/
public fun NDStructure<T>.toBuffer(): NDBuffer<T> =
if (this is NDBuffer<T> && this.strides == this@BufferedNDAlgebra.strides)
this
else
produce { index -> this@toBuffer[index] }
/**
* Convert a buffer to element of this algebra
*/
public fun NDBuffer<T>.toElement(): MathElement<out BufferedNDAlgebra<T, C>>
}
public interface BufferedNDSpace<T, S : Space<T>> : NDSpace<T, S, NDBuffer<T>>, BufferedNDAlgebra<T, S> {
public override fun NDBuffer<T>.toElement(): SpaceElement<NDBuffer<T>, *, out BufferedNDSpace<T, S>>
}
public interface BufferedNDRing<T, R : Ring<T>> : NDRing<T, R, NDBuffer<T>>, BufferedNDSpace<T, R> {
override fun NDBuffer<T>.toElement(): RingElement<NDBuffer<T>, *, out BufferedNDRing<T, R>>
}
public interface BufferedNDField<T, F : Field<T>> : NDField<T, F, NDBuffer<T>>, BufferedNDRing<T, F> {
override fun NDBuffer<T>.toElement(): FieldElement<NDBuffer<T>, *, out BufferedNDField<T, F>>
}

86
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/BufferedNDElement.kt
View File

@ -1,86 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.operations.*
/**
* Base class for an element with context, containing strides
*/
public abstract class BufferedNDElement<T, C> : NDBuffer<T>(), NDElement<T, C, NDBuffer<T>> {
abstract override val context: BufferedNDAlgebra<T, C>
override val strides: Strides get() = context.strides
override val shape: IntArray get() = context.shape
}
public class BufferedNDSpaceElement<T, S : Space<T>>(
override val context: BufferedNDSpace<T, S>,
override val buffer: Buffer<T>
) : BufferedNDElement<T, S>(), SpaceElement<NDBuffer<T>, BufferedNDSpaceElement<T, S>, BufferedNDSpace<T, S>> {
override fun unwrap(): NDBuffer<T> = this
override fun NDBuffer<T>.wrap(): BufferedNDSpaceElement<T, S> {
context.check(this)
return BufferedNDSpaceElement(context, buffer)
}
}
public class BufferedNDRingElement<T, R : Ring<T>>(
override val context: BufferedNDRing<T, R>,
override val buffer: Buffer<T>
) : BufferedNDElement<T, R>(), RingElement<NDBuffer<T>, BufferedNDRingElement<T, R>, BufferedNDRing<T, R>> {
override fun unwrap(): NDBuffer<T> = this
override fun NDBuffer<T>.wrap(): BufferedNDRingElement<T, R> {
context.check(this)
return BufferedNDRingElement(context, buffer)
}
}
public class BufferedNDFieldElement<T, F : Field<T>>(
override val context: BufferedNDField<T, F>,
override val buffer: Buffer<T>
) : BufferedNDElement<T, F>(), FieldElement<NDBuffer<T>, BufferedNDFieldElement<T, F>, BufferedNDField<T, F>> {
override fun unwrap(): NDBuffer<T> = this
override fun NDBuffer<T>.wrap(): BufferedNDFieldElement<T, F> {
context.check(this)
return BufferedNDFieldElement(context, buffer)
}
}
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy.
*/
public operator fun <T : Any, F : Field<T>> Function1<T, T>.invoke(ndElement: BufferedNDElement<T, F>): MathElement<out BufferedNDAlgebra<T, F>> =
ndElement.context.run { map(ndElement) { invoke(it) }.toElement() }
/* plus and minus */
/**
* Summation operation for [BufferedNDElement] and single element
*/
public operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.plus(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it + arg }.wrap()
/**
* Subtraction operation between [BufferedNDElement] and single element
*/
public operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.minus(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it - arg }.wrap()
/* prod and div */
/**
* Product operation for [BufferedNDElement] and single element
*/
public operator fun <T : Any, F : Ring<T>> BufferedNDElement<T, F>.times(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it * arg }.wrap()
/**
* Division operation between [BufferedNDElement] and single element
*/
public operator fun <T : Any, F : Field<T>> BufferedNDElement<T, F>.div(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it / arg }.wrap()

2
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/Buffers.kt
View File

@ -43,7 +43,7 @@ public interface Buffer<T> {
* Checks content equality with another buffer.
*/
public fun contentEquals(other: Buffer<*>): Boolean =
asSequence().mapIndexed { index, value -> value == other[index] }.all { it }
kscience.kmath.nd.mapIndexed { index, value -> value == other[index] }.all { it }
public companion object {
/**

158
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/ComplexNDField.kt
View File

@ -1,158 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.operations.*
import kotlin.contracts.InvocationKind
import kotlin.contracts.contract
public typealias ComplexNDElement = BufferedNDFieldElement<Complex, ComplexField>
/**
* An optimized nd-field for complex numbers
*/
@OptIn(UnstableKMathAPI::class)
public class ComplexNDField(override val shape: IntArray) :
BufferedNDField<Complex, ComplexField>,
ExtendedNDField<Complex, ComplexField, NDBuffer<Complex>>,
RingWithNumbers<NDBuffer<Complex>>{
override val strides: Strides = DefaultStrides(shape)
override val elementContext: ComplexField get() = ComplexField
override val zero: ComplexNDElement by lazy { produce { zero } }
override val one: ComplexNDElement by lazy { produce { one } }
override fun number(value: Number): NDBuffer<Complex> {
val c = value.toComplex()
return produce { c }
}
public inline fun buildBuffer(size: Int, crossinline initializer: (Int) -> Complex): Buffer<Complex> =
Buffer.complex(size) { initializer(it) }
/**
* Inline transform an NDStructure to another structure
*/
override fun map(
arg: NDBuffer<Complex>,
transform: ComplexField.(Complex) -> Complex,
): ComplexNDElement {
check(arg)
val array = buildBuffer(arg.strides.linearSize) { offset -> ComplexField.transform(arg.buffer[offset]) }
return BufferedNDFieldElement(this, array)
}
override fun produce(initializer: ComplexField.(IntArray) -> Complex): ComplexNDElement {
val array = buildBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) }
return BufferedNDFieldElement(this, array)
}
override fun mapIndexed(
arg: NDBuffer<Complex>,
transform: ComplexField.(index: IntArray, Complex) -> Complex,
): ComplexNDElement {
check(arg)
return BufferedNDFieldElement(
this,
buildBuffer(arg.strides.linearSize) { offset ->
elementContext.transform(
arg.strides.index(offset),
arg.buffer[offset]
)
})
}
override fun combine(
a: NDBuffer<Complex>,
b: NDBuffer<Complex>,
transform: ComplexField.(Complex, Complex) -> Complex,
): ComplexNDElement {
check(a, b)
return BufferedNDFieldElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.transform(a.buffer[offset], b.buffer[offset]) })
}
override fun NDBuffer<Complex>.toElement(): FieldElement<NDBuffer<Complex>, *, out BufferedNDField<Complex, ComplexField>> =
BufferedNDFieldElement(this@ComplexNDField, buffer)
override fun power(arg: NDBuffer<Complex>, pow: Number): ComplexNDElement =
map(arg) { power(it, pow) }
override fun exp(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { exp(it) }
override fun ln(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { ln(it) }
override fun sin(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { sin(it) }
override fun cos(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { cos(it) }
override fun tan(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { tan(it) }
override fun asin(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { asin(it) }
override fun acos(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { acos(it) }
override fun atan(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { atan(it) }
override fun sinh(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { sinh(it) }
override fun cosh(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { cosh(it) }
override fun tanh(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { tanh(it) }
override fun asinh(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { asinh(it) }
override fun acosh(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { acosh(it) }
override fun atanh(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { atanh(it) }
}
/**
* Fast element production using function inlining
*/
public inline fun BufferedNDField<Complex, ComplexField>.produceInline(initializer: ComplexField.(Int) -> Complex): ComplexNDElement {
val buffer = Buffer.complex(strides.linearSize) { offset -> ComplexField.initializer(offset) }
return BufferedNDFieldElement(this, buffer)
}
/**
* Map one [ComplexNDElement] using function with indices.
*/
public inline fun ComplexNDElement.mapIndexed(transform: ComplexField.(index: IntArray, Complex) -> Complex): ComplexNDElement =
context.produceInline { offset -> transform(strides.index(offset), buffer[offset]) }
/**
* Map one [ComplexNDElement] using function without indices.
*/
public inline fun ComplexNDElement.map(transform: ComplexField.(Complex) -> Complex): ComplexNDElement {
val buffer = Buffer.complex(strides.linearSize) { offset -> ComplexField.transform(buffer[offset]) }
return BufferedNDFieldElement(context, buffer)
}
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy
*/
public operator fun Function1<Complex, Complex>.invoke(ndElement: ComplexNDElement): ComplexNDElement =
ndElement.map { this@invoke(it) }
/* plus and minus */
/**
* Summation operation for [BufferedNDElement] and single element
*/
public operator fun ComplexNDElement.plus(arg: Complex): ComplexNDElement = map { it + arg }
/**
* Subtraction operation between [BufferedNDElement] and single element
*/
public operator fun ComplexNDElement.minus(arg: Complex): ComplexNDElement = map { it - arg }
public operator fun ComplexNDElement.plus(arg: Double): ComplexNDElement = map { it + arg }
public operator fun ComplexNDElement.minus(arg: Double): ComplexNDElement = map { it - arg }
public fun NDField.Companion.complex(vararg shape: Int): ComplexNDField = ComplexNDField(shape)
public fun NDElement.Companion.complex(
vararg shape: Int,
initializer: ComplexField.(IntArray) -> Complex,
): ComplexNDElement = NDField.complex(*shape).produce(initializer)
/**
* Produce a context for n-dimensional operations inside this real field
*/
public inline fun <R> ComplexField.nd(vararg shape: Int, action: ComplexNDField.() -> R): R {
contract { callsInPlace(action, InvocationKind.EXACTLY_ONCE) }
return NDField.complex(*shape).action()
}

44
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/ExtendedNDField.kt
View File

@ -1,44 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.operations.ExtendedField
/**
* [ExtendedField] over [NDStructure].
*
* @param T the type of the element contained in ND structure.
* @param N the type of ND structure.
* @param F the extended field of structure elements.
*/
public interface ExtendedNDField<T : Any, F : ExtendedField<T>, N : NDStructure<T>> : NDField<T, F, N>, ExtendedField<N>
///**
// * NDField that supports [ExtendedField] operations on its elements
// */
//class ExtendedNDFieldWrapper<T : Any, F : ExtendedField<T>, N : NDStructure<T>>(private val ndField: NDField<T, F, N>) :
// ExtendedNDField<T, F, N>, NDField<T, F, N> by ndField {
//
// override val shape: IntArray get() = ndField.shape
// override val elementContext: F get() = ndField.elementContext
//
// override fun produce(initializer: F.(IntArray) -> T) = ndField.produce(initializer)
//
// override fun power(arg: N, pow: Double): N {
// return produce { with(elementContext) { power(arg[it], pow) } }
// }
//
// override fun exp(arg: N): N {
// return produce { with(elementContext) { exp(arg[it]) } }
// }
//
// override fun ln(arg: N): N {
// return produce { with(elementContext) { ln(arg[it]) } }
// }
//
// override fun sin(arg: N): N {
// return produce { with(elementContext) { sin(arg[it]) } }
// }
//
// override fun cos(arg: N): N {
// return produce { with(elementContext) { cos(arg[it]) } }
// }
//}

2
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/FlaggedBuffer.kt
View File

@ -60,7 +60,7 @@ public class FlaggedRealBuffer(public val values: DoubleArray, public val flags:
override operator fun get(index: Int): Double? = if (isValid(index)) values[index] else null
override operator fun iterator(): Iterator<Double?> = values.indices.asSequence().map {
override operator fun iterator(): Iterator<Double?> = kscience.kmath.nd.map {
if (isValid(it)) values[it] else null
}.iterator()
}

2
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/MemoryBuffer.kt
View File

@ -15,7 +15,7 @@ public open class MemoryBuffer<T : Any>(protected val memory: Memory, protected
private val reader: MemoryReader = memory.reader()
override operator fun get(index: Int): T = reader.read(spec, spec.objectSize * index)
override operator fun iterator(): Iterator<T> = (0 until size).asSequence().map { get(it) }.iterator()
override operator fun iterator(): Iterator<T> = kscience.kmath.nd.map { get(it) }.iterator()
public companion object {
public fun <T : Any> create(spec: MemorySpec<T>, size: Int): MemoryBuffer<T> =

259
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/NDAlgebra.kt
View File

@ -1,259 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.operations.Complex
import kscience.kmath.operations.Field
import kscience.kmath.operations.Ring
import kscience.kmath.operations.Space
import kotlin.native.concurrent.ThreadLocal
/**
* An exception is thrown when the expected ans actual shape of NDArray differs.
*
* @property expected the expected shape.
* @property actual the actual shape.
*/
public class ShapeMismatchException(public val expected: IntArray, public val actual: IntArray) :
RuntimeException("Shape ${actual.contentToString()} doesn't fit in expected shape ${expected.contentToString()}.")
/**
* The base interface for all ND-algebra implementations.
*
* @param T the type of ND-structure element.
* @param C the type of the element context.
* @param N the type of the structure.
*/
public interface NDAlgebra<T, C, N : NDStructure<T>> {
/**
* The shape of ND-structures this algebra operates on.
*/
public val shape: IntArray
/**
* The algebra over elements of ND structure.
*/
public val elementContext: C
/**
* Produces a new [N] structure using given initializer function.
*/
public fun produce(initializer: C.(IntArray) -> T): N
/**
* Maps elements from one structure to another one by applying [transform] to them.
*/
public fun map(arg: N, transform: C.(T) -> T): N
/**
* Maps elements from one structure to another one by applying [transform] to them alongside with their indices.
*/
public fun mapIndexed(arg: N, transform: C.(index: IntArray, T) -> T): N
/**
* Combines two structures into one.
*/
public fun combine(a: N, b: N, transform: C.(T, T) -> T): N
/**
* Checks if given element is consistent with this context.
*
* @param element the structure to check.
* @return the valid structure.
*/
public fun check(element: N): N {
if (!element.shape.contentEquals(shape)) throw ShapeMismatchException(shape, element.shape)
return element
}
/**
* Checks if given elements are consistent with this context.
*
* @param elements the structures to check.
* @return the array of valid structures.
*/
public fun check(vararg elements: N): Array<out N> = elements
.map(NDStructure<T>::shape)
.singleOrNull { !shape.contentEquals(it) }
?.let<IntArray, Array<out N>> { throw ShapeMismatchException(shape, it) }
?: elements
/**
* Element-wise invocation of function working on [T] on a [NDStructure].
*/
public operator fun Function1<T, T>.invoke(structure: N): N = map(structure) { value -> this@invoke(value) }
public companion object
}
/**
* Space of [NDStructure].
*
* @param T the type of the element contained in ND structure.
* @param N the type of ND structure.
* @param S the type of space of structure elements.
*/
public interface NDSpace<T, S : Space<T>, N : NDStructure<T>> : Space<N>, NDAlgebra<T, S, N> {
/**
* Element-wise addition.
*
* @param a the addend.
* @param b the augend.
* @return the sum.
*/
public override fun add(a: N, b: N): N = combine(a, b) { aValue, bValue -> add(aValue, bValue) }
/**
* Element-wise multiplication by scalar.
*
* @param a the multiplicand.
* @param k the multiplier.
* @return the product.
*/
public override fun multiply(a: N, k: Number): N = map(a) { multiply(it, k) }
// TODO move to extensions after KEEP-176
/**
* Adds an ND structure to an element of it.
*
* @receiver the addend.
* @param arg the augend.
* @return the sum.
*/
public operator fun N.plus(arg: T): N = map(this) { value -> add(arg, value) }
/**
* Subtracts an element from ND structure of it.
*
* @receiver the dividend.
* @param arg the divisor.
* @return the quotient.
*/
public operator fun N.minus(arg: T): N = map(this) { value -> add(arg, -value) }
/**
* Adds an element to ND structure of it.
*
* @receiver the addend.
* @param arg the augend.
* @return the sum.
*/
public operator fun T.plus(arg: N): N = map(arg) { value -> add(this@plus, value) }
/**
* Subtracts an ND structure from an element of it.
*
* @receiver the dividend.
* @param arg the divisor.
* @return the quotient.
*/
public operator fun T.minus(arg: N): N = map(arg) { value -> add(-this@minus, value) }
public companion object
}
/**
* Ring of [NDStructure].
*
* @param T the type of the element contained in ND structure.
* @param N the type of ND structure.
* @param R the type of ring of structure elements.
*/
public interface NDRing<T, R : Ring<T>, N : NDStructure<T>> : Ring<N>, NDSpace<T, R, N> {
/**
* Element-wise multiplication.
*
* @param a the multiplicand.
* @param b the multiplier.
* @return the product.
*/
public override fun multiply(a: N, b: N): N = combine(a, b) { aValue, bValue -> multiply(aValue, bValue) }
//TODO move to extensions after KEEP-176
/**
* Multiplies an ND structure by an element of it.
*
* @receiver the multiplicand.
* @param arg the multiplier.
* @return the product.
*/
public operator fun N.times(arg: T): N = map(this) { value -> multiply(arg, value) }
/**
* Multiplies an element by a ND structure of it.
*
* @receiver the multiplicand.
* @param arg the multiplier.
* @return the product.
*/
public operator fun T.times(arg: N): N = map(arg) { value -> multiply(this@times, value) }
public companion object
}
/**
* Field of [NDStructure].
*
* @param T the type of the element contained in ND structure.
* @param N the type of ND structure.
* @param F the type field of structure elements.
*/
public interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N>, NDRing<T, F, N> {
/**
* Element-wise division.
*
* @param a the dividend.
* @param b the divisor.
* @return the quotient.
*/
public override fun divide(a: N, b: N): N = combine(a, b) { aValue, bValue -> divide(aValue, bValue) }
//TODO move to extensions after KEEP-176
/**
* Divides an ND structure by an element of it.
*
* @receiver the dividend.
* @param arg the divisor.
* @return the quotient.
*/
public operator fun N.div(arg: T): N = map(this) { value -> divide(arg, value) }
/**
* Divides an element by an ND structure of it.
*
* @receiver the dividend.
* @param arg the divisor.
* @return the quotient.
*/
public operator fun T.div(arg: N): N = map(arg) { divide(it, this@div) }
@ThreadLocal
public companion object {
private val realNDFieldCache: MutableMap<IntArray, RealNDField> = hashMapOf()
/**
* Create a nd-field for [Double] values or pull it from cache if it was created previously.
*/
public fun real(vararg shape: Int): RealNDField = realNDFieldCache.getOrPut(shape) { RealNDField(shape) }
/**
* Create an ND field with boxing generic buffer.
*/
public fun <T : Any, F : Field<T>> boxing(
field: F,
vararg shape: Int,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing
): BoxingNDField<T, F> = BoxingNDField(shape, field, bufferFactory)
/**
* Create a most suitable implementation for nd-field using reified class.
*/
@Suppress("UNCHECKED_CAST")
public inline fun <reified T : Any, F : Field<T>> auto(field: F, vararg shape: Int): BufferedNDField<T, F> =
when {
T::class == Double::class -> real(*shape) as BufferedNDField<T, F>
T::class == Complex::class -> complex(*shape) as BufferedNDField<T, F>
else -> BoxingNDField(shape, field, Buffer.Companion::auto)
}
}
}

134
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/NDElement.kt
View File

@ -1,134 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.operations.Field
import kscience.kmath.operations.RealField
import kscience.kmath.operations.Ring
import kscience.kmath.operations.Space
/**
* The root for all [NDStructure] based algebra elements. Does not implement algebra element root because of problems with recursive self-types
* @param T the type of the element of the structure
* @param C the type of the context for the element
* @param N the type of the underlying [NDStructure]
*/
public interface NDElement<T, C, N : NDStructure<T>> : NDStructure<T> {
public val context: NDAlgebra<T, C, N>
public fun unwrap(): N
public fun N.wrap(): NDElement<T, C, N>
public companion object {
/**
* Create a optimized NDArray of doubles
*/
public fun real(shape: IntArray, initializer: RealField.(IntArray) -> Double = { 0.0 }): RealNDElement =
NDField.real(*shape).produce(initializer)
public inline fun real1D(dim: Int, crossinline initializer: (Int) -> Double = { _ -> 0.0 }): RealNDElement =
real(intArrayOf(dim)) { initializer(it[0]) }
public inline fun real2D(
dim1: Int,
dim2: Int,
crossinline initializer: (Int, Int) -> Double = { _, _ -> 0.0 }
): RealNDElement = real(intArrayOf(dim1, dim2)) { initializer(it[0], it[1]) }
public inline fun real3D(
dim1: Int,
dim2: Int,
dim3: Int,
crossinline initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }
): RealNDElement = real(intArrayOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
/**
* Simple boxing NDArray
*/
public fun <T : Any, F : Field<T>> boxing(
shape: IntArray,
field: F,
initializer: F.(IntArray) -> T
): BufferedNDElement<T, F> {
val ndField = BoxingNDField(shape, field, Buffer.Companion::boxing)
return ndField.produce(initializer)
}
public inline fun <reified T : Any, F : Field<T>> auto(
shape: IntArray,
field: F,
noinline initializer: F.(IntArray) -> T
): BufferedNDFieldElement<T, F> {
val ndField = NDField.auto(field, *shape)
return BufferedNDFieldElement(ndField, ndField.produce(initializer).buffer)
}
}
}
public fun <T, C, N : NDStructure<T>> NDElement<T, C, N>.mapIndexed(transform: C.(index: IntArray, T) -> T): NDElement<T, C, N> =
context.mapIndexed(unwrap(), transform).wrap()
public fun <T, C, N : NDStructure<T>> NDElement<T, C, N>.map(transform: C.(T) -> T): NDElement<T, C, N> =
context.map(unwrap(), transform).wrap()
/**
* Element by element application of any operation on elements to the whole [NDElement]
*/
public operator fun <T, C, N : NDStructure<T>> Function1<T, T>.invoke(ndElement: NDElement<T, C, N>): NDElement<T, C, N> =
ndElement.map { value -> this@invoke(value) }
/* plus and minus */
/**
* Summation operation for [NDElement] and single element
*/
public operator fun <T, S : Space<T>, N : NDStructure<T>> NDElement<T, S, N>.plus(arg: T): NDElement<T, S, N> =
map { value -> arg + value }
/**
* Subtraction operation between [NDElement] and single element
*/
public operator fun <T, S : Space<T>, N : NDStructure<T>> NDElement<T, S, N>.minus(arg: T): NDElement<T, S, N> =
map { value -> arg - value }
/* prod and div */
/**
* Product operation for [NDElement] and single element
*/
public operator fun <T, R : Ring<T>, N : NDStructure<T>> NDElement<T, R, N>.times(arg: T): NDElement<T, R, N> =
map { value -> arg * value }
/**
* Division operation between [NDElement] and single element
*/
public operator fun <T, F : Field<T>, N : NDStructure<T>> NDElement<T, F, N>.div(arg: T): NDElement<T, F, N> =
map { value -> arg / value }
// /**
// * Reverse sum operation
// */
// operator fun T.plus(arg: NDStructure<T>): NDElement<T, F> = produce { index ->
// field.run { this@plus + arg[index] }
// }
//
// /**
// * Reverse minus operation
// */
// operator fun T.minus(arg: NDStructure<T>): NDElement<T, F> = produce { index ->
// field.run { this@minus - arg[index] }
// }
//
// /**
// * Reverse product operation
// */
// operator fun T.times(arg: NDStructure<T>): NDElement<T, F> = produce { index ->
// field.run { this@times * arg[index] }
// }
//
// /**
// * Reverse division operation
// */
// operator fun T.div(arg: NDStructure<T>): NDElement<T, F> = produce { index ->
// field.run { this@div / arg[index] }
// }

140
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/RealNDField.kt
View File

@ -1,140 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.operations.FieldElement
import kscience.kmath.operations.RealField
import kscience.kmath.operations.RingWithNumbers
public typealias RealNDElement = BufferedNDFieldElement<Double, RealField>
@OptIn(UnstableKMathAPI::class)
public class RealNDField(override val shape: IntArray) :
BufferedNDField<Double, RealField>,
ExtendedNDField<Double, RealField, NDBuffer<Double>>,
RingWithNumbers<NDBuffer<Double>> {
override val strides: Strides = DefaultStrides(shape)
override val elementContext: RealField get() = RealField
override val zero: RealNDElement by lazy { produce { zero } }
override val one: RealNDElement by lazy { produce { one } }
override fun number(value: Number): NDBuffer<Double> {
val d = value.toDouble()
return produce { d }
}
@Suppress("OVERRIDE_BY_INLINE")
override inline fun map(
arg: NDBuffer<Double>,
transform: RealField.(Double) -> Double,
): RealNDElement {
check(arg)
val array = RealBuffer(arg.strides.linearSize) { offset -> RealField.transform(arg.buffer[offset]) }
return BufferedNDFieldElement(this, array)
}
@Suppress("OVERRIDE_BY_INLINE")
override inline fun produce(initializer: RealField.(IntArray) -> Double): RealNDElement {
val array = RealBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) }
return BufferedNDFieldElement(this, array)
}
@Suppress("OVERRIDE_BY_INLINE")
override inline fun mapIndexed(
arg: NDBuffer<Double>,
transform: RealField.(index: IntArray, Double) -> Double,
): RealNDElement {
check(arg)
return BufferedNDFieldElement(
this,
RealBuffer(arg.strides.linearSize) { offset ->
elementContext.transform(
arg.strides.index(offset),
arg.buffer[offset]
)
})
}
@Suppress("OVERRIDE_BY_INLINE")
override inline fun combine(
a: NDBuffer<Double>,
b: NDBuffer<Double>,
transform: RealField.(Double, Double) -> Double,
): RealNDElement {
check(a, b)
val buffer = RealBuffer(strides.linearSize) { offset ->
elementContext.transform(a.buffer[offset], b.buffer[offset])
}
return BufferedNDFieldElement(this, buffer)
}
override fun NDBuffer<Double>.toElement(): FieldElement<NDBuffer<Double>, *, out BufferedNDField<Double, RealField>> =
BufferedNDFieldElement(this@RealNDField, buffer)
override fun power(arg: NDBuffer<Double>, pow: Number): RealNDElement = map(arg) { power(it, pow) }
override fun exp(arg: NDBuffer<Double>): RealNDElement = map(arg) { exp(it) }
override fun ln(arg: NDBuffer<Double>): RealNDElement = map(arg) { ln(it) }
override fun sin(arg: NDBuffer<Double>): RealNDElement = map(arg) { sin(it) }
override fun cos(arg: NDBuffer<Double>): RealNDElement = map(arg) { cos(it) }
override fun tan(arg: NDBuffer<Double>): RealNDElement = map(arg) { tan(it) }
override fun asin(arg: NDBuffer<Double>): RealNDElement = map(arg) { asin(it) }
override fun acos(arg: NDBuffer<Double>): RealNDElement = map(arg) { acos(it) }
override fun atan(arg: NDBuffer<Double>): RealNDElement = map(arg) { atan(it) }
override fun sinh(arg: NDBuffer<Double>): RealNDElement = map(arg) { sinh(it) }
override fun cosh(arg: NDBuffer<Double>): RealNDElement = map(arg) { cosh(it) }
override fun tanh(arg: NDBuffer<Double>): RealNDElement = map(arg) { tanh(it) }
override fun asinh(arg: NDBuffer<Double>): RealNDElement = map(arg) { asinh(it) }
override fun acosh(arg: NDBuffer<Double>): RealNDElement = map(arg) { acosh(it) }
override fun atanh(arg: NDBuffer<Double>): RealNDElement = map(arg) { atanh(it) }
}
/**
* Fast element production using function inlining
*/
public inline fun BufferedNDField<Double, RealField>.produceInline(crossinline initializer: RealField.(Int) -> Double): RealNDElement {
val array = DoubleArray(strides.linearSize) { offset -> RealField.initializer(offset) }
return BufferedNDFieldElement(this, RealBuffer(array))
}
/**
* Map one [RealNDElement] using function with indices.
*/
public inline fun RealNDElement.mapIndexed(crossinline transform: RealField.(index: IntArray, Double) -> Double): RealNDElement =
context.produceInline { offset -> transform(strides.index(offset), buffer[offset]) }
/**
* Map one [RealNDElement] using function without indices.
*/
public inline fun RealNDElement.map(crossinline transform: RealField.(Double) -> Double): RealNDElement {
val array = DoubleArray(strides.linearSize) { offset -> RealField.transform(buffer[offset]) }
return BufferedNDFieldElement(context, RealBuffer(array))
}
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy.
*/
public operator fun Function1<Double, Double>.invoke(ndElement: RealNDElement): RealNDElement =
ndElement.map { this@invoke(it) }
/* plus and minus */
/**
* Summation operation for [BufferedNDElement] and single element
*/
public operator fun RealNDElement.plus(arg: Double): RealNDElement = map { it + arg }
/**
* Subtraction operation between [BufferedNDElement] and single element
*/
public operator fun RealNDElement.minus(arg: Double): RealNDElement = map { it - arg }
/**
* Produce a context for n-dimensional operations inside this real field
*/
public inline fun <R> RealField.nd(vararg shape: Int, action: RealNDField.() -> R): R = NDField.real(*shape).run(action)

93
kmath-core/src/commonMain/kotlin/kscience/kmath/structures/ShortNDRing.kt
View File

@ -1,93 +0,0 @@
package kscience.kmath.structures
import kscience.kmath.operations.RingElement
import kscience.kmath.operations.ShortRing
public typealias ShortNDElement = BufferedNDRingElement<Short, ShortRing>
public class ShortNDRing(override val shape: IntArray) :
BufferedNDRing<Short, ShortRing> {
override val strides: Strides = DefaultStrides(shape)
override val elementContext: ShortRing get() = ShortRing
override val zero: ShortNDElement by lazy { produce { zero } }
override val one: ShortNDElement by lazy { produce { one } }
public inline fun buildBuffer(size: Int, crossinline initializer: (Int) -> Short): Buffer<Short> =
ShortBuffer(ShortArray(size) { initializer(it) })
/**
* Inline transform an NDStructure to
*/
override fun map(
arg: NDBuffer<Short>,
transform: ShortRing.(Short) -> Short
): ShortNDElement {
check(arg)
val array = buildBuffer(arg.strides.linearSize) { offset -> ShortRing.transform(arg.buffer[offset]) }
return BufferedNDRingElement(this, array)
}
override fun produce(initializer: ShortRing.(IntArray) -> Short): ShortNDElement {
val array = buildBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) }
return BufferedNDRingElement(this, array)
}
override fun mapIndexed(
arg: NDBuffer<Short>,
transform: ShortRing.(index: IntArray, Short) -> Short
): ShortNDElement {
check(arg)
return BufferedNDRingElement(
this,
buildBuffer(arg.strides.linearSize) { offset ->
elementContext.transform(
arg.strides.index(offset),
arg.buffer[offset]
)
})
}
override fun combine(
a: NDBuffer<Short>,
b: NDBuffer<Short>,
transform: ShortRing.(Short, Short) -> Short
): ShortNDElement {
check(a, b)
return BufferedNDRingElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.transform(a.buffer[offset], b.buffer[offset]) })
}
override fun NDBuffer<Short>.toElement(): RingElement<NDBuffer<Short>, *, out BufferedNDRing<Short, ShortRing>> =
BufferedNDRingElement(this@ShortNDRing, buffer)
}
/**
* Fast element production using function inlining.
*/
public inline fun BufferedNDRing<Short, ShortRing>.produceInline(crossinline initializer: ShortRing.(Int) -> Short): ShortNDElement =
BufferedNDRingElement(this, ShortBuffer(ShortArray(strides.linearSize) { offset -> ShortRing.initializer(offset) }))
/**
* Element by element application of any operation on elements to the whole array.
*/
public operator fun Function1<Short, Short>.invoke(ndElement: ShortNDElement): ShortNDElement =
ndElement.context.produceInline { i -> invoke(ndElement.buffer[i]) }
/* plus and minus */
/**
* Summation operation for [ShortNDElement] and single element.
*/
public operator fun ShortNDElement.plus(arg: Short): ShortNDElement =
context.produceInline { i -> (buffer[i] + arg).toShort() }
/**
* Subtraction operation between [ShortNDElement] and single element.
*/
public operator fun ShortNDElement.minus(arg: Short): ShortNDElement =
context.produceInline { i -> (buffer[i] - arg).toShort() }

5
kmath-core/src/commonTest/kotlin/kscience/kmath/linear/MatrixTest.kt
View File

@ -1,9 +1,8 @@
package kscience.kmath.linear
import kscience.kmath.nd.NDStructure
import kscience.kmath.nd.as2D
import kscience.kmath.operations.invoke
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.NDStructure
import kscience.kmath.structures.as2D
import kotlin.test.Test
import kotlin.test.assertEquals

1
kmath-core/src/commonTest/kotlin/kscience/kmath/linear/RealLUSolverTest.kt
View File

@ -1,6 +1,5 @@
package kscience.kmath.linear
import kscience.kmath.structures.Matrix
import kotlin.test.Test
import kotlin.test.assertEquals

1
kmath-core/src/commonTest/kotlin/kscience/kmath/structures/NDFieldTest.kt
View File

@ -1,5 +1,6 @@
package kscience.kmath.structures
import kscience.kmath.nd.NDField
import kscience.kmath.operations.internal.FieldVerifier
import kotlin.test.Test
import kotlin.test.assertEquals

3
kmath-core/src/commonTest/kotlin/kscience/kmath/structures/NumberNDFieldTest.kt
View File

@ -1,7 +1,8 @@
package kscience.kmath.structures
import kscience.kmath.nd.NDField
import kscience.kmath.nd.NDStructure
import kscience.kmath.operations.Norm
import kscience.kmath.operations.invoke
import kscience.kmath.structures.NDElement.Companion.real2D
import kotlin.math.abs
import kotlin.math.pow

4
kmath-coroutines/src/jvmMain/kotlin/kscience/kmath/structures/LazyNDStructure.kt
View File

@ -2,6 +2,8 @@ package kscience.kmath.structures
import kotlinx.coroutines.*
import kscience.kmath.coroutines.Math
import kscience.kmath.nd.DefaultStrides
import kscience.kmath.nd.NDStructure
public class LazyNDStructure<T>(
public val scope: CoroutineScope,
@ -19,7 +21,7 @@ public class LazyNDStructure<T>(
public override fun elements(): Sequence<Pair<IntArray, T>> {
val strides = DefaultStrides(shape)
val res = runBlocking { strides.indices().toList().map { index -> index to await(index) } }
val res = runBlocking { kscience.kmath.nd.map { index -> index to await(index) } }
return res.asSequence()
}

3
kmath-dimensions/src/commonMain/kotlin/kscience/kmath/dimensions/Wrappers.kt
View File

@ -1,9 +1,8 @@
package kscience.kmath.dimensions
import kscience.kmath.linear.*
import kscience.kmath.nd.Structure2D
import kscience.kmath.operations.invoke
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.Structure2D
/**
* A matrix with compile-time controlled dimension

3
kmath-ejml/src/main/kotlin/kscience/kmath/ejml/EjmlMatrix.kt
View File

@ -2,8 +2,7 @@ package kscience.kmath.ejml
import kscience.kmath.linear.*
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.NDStructure
import kscience.kmath.nd.NDStructure
import kscience.kmath.structures.RealBuffer
import org.ejml.dense.row.factory.DecompositionFactory_DDRM
import org.ejml.simple.SimpleMatrix

5
kmath-ejml/src/main/kotlin/kscience/kmath/ejml/EjmlMatrixContext.kt
View File

@ -3,10 +3,9 @@ package kscience.kmath.ejml
import kscience.kmath.linear.InverseMatrixFeature
import kscience.kmath.linear.MatrixContext
import kscience.kmath.linear.Point
import kscience.kmath.linear.origin
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.getFeature
import kscience.kmath.nd.Matrix
import kscience.kmath.nd.getFeature
import org.ejml.simple.SimpleMatrix
/**

2
kmath-ejml/src/test/kotlin/kscience/kmath/ejml/EjmlMatrixTest.kt
View File

@ -5,7 +5,7 @@ import kscience.kmath.linear.LupDecompositionFeature
import kscience.kmath.linear.MatrixFeature
import kscience.kmath.linear.plus
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.structures.getFeature
import kscience.kmath.nd.getFeature
import org.ejml.dense.row.factory.DecompositionFactory_DDRM
import org.ejml.simple.SimpleMatrix
import kotlin.random.Random

6
kmath-for-real/src/commonMain/kotlin/kscience/kmath/real/RealMatrix.kt
View File

@ -1,15 +1,11 @@
package kscience.kmath.real
import kscience.kmath.linear.MatrixContext
import kscience.kmath.linear.VirtualMatrix
import kscience.kmath.linear.inverseWithLUP
import kscience.kmath.linear.real
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.nd.Matrix
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.RealBuffer
import kscience.kmath.structures.asIterable
import kotlin.math.pow
/*
* Functions for convenient "numpy-like" operations with Double matrices.

31
kmath-for-real/src/commonMain/kotlin/kscience/kmath/real/realND.kt Normal file
View File

@ -0,0 +1,31 @@
package kscience.kmath.real
import kscience.kmath.nd.NDBuffer
import kscience.kmath.operations.RealField
import kscience.kmath.structures.RealBuffer
/**
* Map one [NDBuffer] using function without indices.
*/
public inline fun NDBuffer<Double>.mapInline(crossinline transform: RealField.(Double) -> Double): NDBuffer<Double> {
val array = DoubleArray(strides.linearSize) { offset -> RealField.transform(buffer[offset]) }
return NDBuffer(strides, RealBuffer(array))
}
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy.
*/
public operator fun Function1<Double, Double>.invoke(ndElement: NDBuffer<Double>): NDBuffer<Double> =
ndElement.mapInline { this@invoke(it) }
/* plus and minus */
/**
* Summation operation for [NDBuffer] and single element
*/
public operator fun NDBuffer<Double>.plus(arg: Double): NDBuffer<Double> = mapInline { it + arg }
/**
* Subtraction operation between [NDBuffer] and single element
*/
public operator fun NDBuffer<Double>.minus(arg: Double): NDBuffer<Double> = mapInline { it - arg }

4
kmath-for-real/src/commonTest/kotlin/kaceince/kmath/real/RealMatrixTest.kt
View File

@ -1,9 +1,7 @@
package kaceince.kmath.real
import kscience.kmath.linear.build
import kscience.kmath.nd.Matrix
import kscience.kmath.real.*
import kscience.kmath.structures.Matrix
import kscience.kmath.structures.contentEquals
import kotlin.test.Test
import kotlin.test.assertEquals
import kotlin.test.assertTrue

2
kmath-functions/src/commonMain/kotlin/kscience/kmath/interpolation/XYPointSet.kt
View File

@ -1,7 +1,7 @@
package kscience.kmath.interpolation
import kscience.kmath.nd.Structure2D
import kscience.kmath.structures.Buffer
import kscience.kmath.structures.Structure2D
public interface XYPointSet<X, Y> {
public val size: Int

8
kmath-histograms/src/commonMain/kotlin/kscience/kmath/histogram/RealHistogram.kt
View File

@ -1,6 +1,8 @@
package kscience.kmath.histogram
import kscience.kmath.linear.Point
import kscience.kmath.nd.DefaultStrides
import kscience.kmath.nd.NDStructure
import kscience.kmath.operations.SpaceOperations
import kscience.kmath.operations.invoke
import kscience.kmath.structures.*
@ -15,7 +17,7 @@ public data class BinDef<T : Comparable<T>>(
require(vector.size == center.size) { "Dimension mismatch for input vector. Expected ${center.size}, but found ${vector.size}" }
val upper = space { center + sizes / 2.0 }
val lower = space { center - sizes / 2.0 }
return vector.asSequence().mapIndexed { i, value -> value in lower[i]..upper[i] }.all { it }
return kscience.kmath.nd.mapIndexed { i, value -> value in lower[i]..upper[i] }.all { it }
}
}
@ -68,7 +70,7 @@ public class RealHistogram(
public fun getValue(point: Buffer<out Double>): Long = getValue(getIndex(point))
private fun getDef(index: IntArray): BinDef<Double> {
val center = index.mapIndexed { axis, i ->
val center = kscience.kmath.nd.mapIndexed { axis, i ->
when (i) {
0 -> Double.NEGATIVE_INFINITY
strides.shape[axis] - 1 -> Double.POSITIVE_INFINITY
@ -98,7 +100,7 @@ public class RealHistogram(
}
public override operator fun iterator(): Iterator<MultivariateBin<Double>> =
weights.elements().map { (index, value) -> MultivariateBin(getDef(index), value.sum()) }
kscience.kmath.nd.map { (index, value) -> MultivariateBin(getDef(index), value.sum()) }
.iterator()
/**

132
kmath-nd4j/src/main/kotlin/kscience.kmath.nd4j/Nd4jArrayAlgebra.kt
View File

@ -1,11 +1,9 @@
package kscience.kmath.nd4j
import kscience.kmath.misc.UnstableKMathAPI
import kscience.kmath.nd.*
import kscience.kmath.operations.*
import kscience.kmath.structures.NDAlgebra
import kscience.kmath.structures.NDField
import kscience.kmath.structures.NDRing
import kscience.kmath.structures.NDSpace
import kscience.kmath.structures.*
import org.nd4j.linalg.api.ndarray.INDArray
import org.nd4j.linalg.factory.Nd4j
@ -15,11 +13,22 @@ import org.nd4j.linalg.factory.Nd4j
* @param T the type of ND-structure element.
* @param C the type of the element context.
*/
public interface Nd4jArrayAlgebra<T, C> : NDAlgebra<T, C, Nd4jArrayStructure<T>> {
public interface Nd4jArrayAlgebra<T, C> : NDAlgebra<T, C> {
/**
* Wraps [INDArray] to [N].
*/
public fun INDArray.wrap(): Nd4jArrayStructure<T>
public val NDStructure<T>.ndArray: INDArray
get() = when {
!shape.contentEquals(this@Nd4jArrayAlgebra.shape) -> throw ShapeMismatchException(
this@Nd4jArrayAlgebra.shape,
shape
)
this is Nd4jArrayStructure -> ndArray //TODO check strides
else -> {
TODO()
}
}
public override fun produce(initializer: C.(IntArray) -> T): Nd4jArrayStructure<T> {
val struct = Nd4j.create(*shape)!!.wrap()
@ -27,29 +36,26 @@ public interface Nd4jArrayAlgebra<T, C> : NDAlgebra<T, C, Nd4jArrayStructure<T>>
return struct
}
public override fun map(arg: Nd4jArrayStructure<T>, transform: C.(T) -> T): Nd4jArrayStructure<T> {
check(arg)
public override fun map(arg: NDStructure<T>, transform: C.(T) -> T): Nd4jArrayStructure<T> {
val newStruct = arg.ndArray.dup().wrap()
newStruct.elements().forEach { (idx, value) -> newStruct[idx] = elementContext.transform(value) }
return newStruct
}
public override fun mapIndexed(
arg: Nd4jArrayStructure<T>,
arg: NDStructure<T>,
transform: C.(index: IntArray, T) -> T,
): Nd4jArrayStructure<T> {
check(arg)
val new = Nd4j.create(*shape).wrap()
new.indicesIterator().forEach { idx -> new[idx] = elementContext.transform(idx, arg[idx]) }
return new
}
public override fun combine(
a: Nd4jArrayStructure<T>,
b: Nd4jArrayStructure<T>,
a: NDStructure<T>,
b: NDStructure<T>,
transform: C.(T, T) -> T,
): Nd4jArrayStructure<T> {
check(a, b)
val new = Nd4j.create(*shape).wrap()
new.indicesIterator().forEach { idx -> new[idx] = elementContext.transform(a[idx], b[idx]) }
return new
@ -62,38 +68,32 @@ public interface Nd4jArrayAlgebra<T, C> : NDAlgebra<T, C, Nd4jArrayStructure<T>>
* @param T the type of the element contained in ND structure.
* @param S the type of space of structure elements.
*/
public interface Nd4jArraySpace<T, S : Space<T>> : NDSpace<T, S, Nd4jArrayStructure<T>>, Nd4jArrayAlgebra<T, S> {
public interface Nd4jArraySpace<T, S : Space<T>> : NDSpace<T, S>, Nd4jArrayAlgebra<T, S> {
public override val zero: Nd4jArrayStructure<T>
get() = Nd4j.zeros(*shape).wrap()
public override fun add(a: Nd4jArrayStructure<T>, b: Nd4jArrayStructure<T>): Nd4jArrayStructure<T> {
check(a, b)
public override fun add(a: NDStructure<T>, b: NDStructure<T>): Nd4jArrayStructure<T> {
return a.ndArray.add(b.ndArray).wrap()
}
public override operator fun Nd4jArrayStructure<T>.minus(b: Nd4jArrayStructure<T>): Nd4jArrayStructure<T> {
check(this, b)
public override operator fun NDStructure<T>.minus(b: NDStructure<T>): Nd4jArrayStructure<T> {
return ndArray.sub(b.ndArray).wrap()
}
public override operator fun Nd4jArrayStructure<T>.unaryMinus(): Nd4jArrayStructure<T> {
check(this)
public override operator fun NDStructure<T>.unaryMinus(): Nd4jArrayStructure<T> {
return ndArray.neg().wrap()
}
public override fun multiply(a: Nd4jArrayStructure<T>, k: Number): Nd4jArrayStructure<T> {
check(a)
public override fun multiply(a: NDStructure<T>, k: Number): Nd4jArrayStructure<T> {
return a.ndArray.mul(k).wrap()
}
public override operator fun Nd4jArrayStructure<T>.div(k: Number): Nd4jArrayStructure<T> {
check(this)
public override operator fun NDStructure<T>.div(k: Number): Nd4jArrayStructure<T> {
return ndArray.div(k).wrap()
}
public override operator fun Nd4jArrayStructure<T>.times(k: Number): Nd4jArrayStructure<T> {
check(this)
public override operator fun NDStructure<T>.times(k: Number): Nd4jArrayStructure<T> {
return ndArray.mul(k).wrap()
}
}
@ -105,13 +105,12 @@ public interface Nd4jArraySpace<T, S : Space<T>> : NDSpace<T, S, Nd4jArrayStruct
* @param R the type of ring of structure elements.
*/
@OptIn(UnstableKMathAPI::class)
public interface Nd4jArrayRing<T, R : Ring<T>> : NDRing<T, R, Nd4jArrayStructure<T>>, Nd4jArraySpace<T, R> {
public interface Nd4jArrayRing<T, R : Ring<T>> : NDRing<T, R>, Nd4jArraySpace<T, R> {
public override val one: Nd4jArrayStructure<T>
get() = Nd4j.ones(*shape).wrap()
public override fun multiply(a: Nd4jArrayStructure<T>, b: Nd4jArrayStructure<T>): Nd4jArrayStructure<T> {
check(a, b)
public override fun multiply(a: NDStructure<T>, b: NDStructure<T>): Nd4jArrayStructure<T> {
return a.ndArray.mul(b.ndArray).wrap()
}
//
@ -168,17 +167,12 @@ public interface Nd4jArrayRing<T, R : Ring<T>> : NDRing<T, R, Nd4jArrayStructure
* @param N the type of ND structure.
* @param F the type field of structure elements.
*/
public interface Nd4jArrayField<T, F : Field<T>> : NDField<T, F, Nd4jArrayStructure<T>>, Nd4jArrayRing<T, F> {
public interface Nd4jArrayField<T, F : Field<T>> : NDField<T, F>, Nd4jArrayRing<T, F> {
public override fun divide(a: Nd4jArrayStructure<T>, b: Nd4jArrayStructure<T>): Nd4jArrayStructure<T> {
check(a, b)
return a.ndArray.div(b.ndArray).wrap()
}
public override fun divide(a: NDStructure<T>, b: NDStructure<T>): Nd4jArrayStructure<T> =
a.ndArray.div(b.ndArray).wrap()
public override operator fun Number.div(b: Nd4jArrayStructure<T>): Nd4jArrayStructure<T> {
check(b)
return b.ndArray.rdiv(this).wrap()
}
public override operator fun Number.div(b: NDStructure<T>): Nd4jArrayStructure<T> = b.ndArray.rdiv(this).wrap()
public companion object {
@ -219,35 +213,29 @@ public class RealNd4jArrayField(public override val shape: IntArray) : Nd4jArray
public override val elementContext: RealField
get() = RealField
public override fun INDArray.wrap(): Nd4jArrayStructure<Double> = check(asRealStructure())
public override fun INDArray.wrap(): Nd4jArrayStructure<Double> = checkShape(asRealStructure())
public override operator fun Nd4jArrayStructure<Double>.div(arg: Double): Nd4jArrayStructure<Double> {
check(this)
public override operator fun NDStructure<Double>.div(arg: Double): Nd4jArrayStructure<Double> {
return ndArray.div(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Double>.plus(arg: Double): Nd4jArrayStructure<Double> {
check(this)
public override operator fun NDStructure<Double>.plus(arg: Double): Nd4jArrayStructure<Double> {
return ndArray.add(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Double>.minus(arg: Double): Nd4jArrayStructure<Double> {
check(this)
public override operator fun NDStructure<Double>.minus(arg: Double): Nd4jArrayStructure<Double> {
return ndArray.sub(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Double>.times(arg: Double): Nd4jArrayStructure<Double> {
check(this)
public override operator fun NDStructure<Double>.times(arg: Double): Nd4jArrayStructure<Double> {
return ndArray.mul(arg).wrap()
}
public override operator fun Double.div(arg: Nd4jArrayStructure<Double>): Nd4jArrayStructure<Double> {
check(arg)
public override operator fun Double.div(arg: NDStructure<Double>): Nd4jArrayStructure<Double> {
return arg.ndArray.rdiv(this).wrap()
}
public override operator fun Double.minus(arg: Nd4jArrayStructure<Double>): Nd4jArrayStructure<Double> {
check(arg)
public override operator fun Double.minus(arg: NDStructure<Double>): Nd4jArrayStructure<Double> {
return arg.ndArray.rsub(this).wrap()
}
}
@ -259,35 +247,29 @@ public class FloatNd4jArrayField(public override val shape: IntArray) : Nd4jArra
public override val elementContext: FloatField
get() = FloatField
public override fun INDArray.wrap(): Nd4jArrayStructure<Float> = check(asFloatStructure())
public override fun INDArray.wrap(): Nd4jArrayStructure<Float> = checkShape(asFloatStructure())
public override operator fun Nd4jArrayStructure<Float>.div(arg: Float): Nd4jArrayStructure<Float> {
check(this)
public override operator fun NDStructure<Float>.div(arg: Float): Nd4jArrayStructure<Float> {
return ndArray.div(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Float>.plus(arg: Float): Nd4jArrayStructure<Float> {
check(this)
public override operator fun NDStructure<Float>.plus(arg: Float): Nd4jArrayStructure<Float> {
return ndArray.add(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Float>.minus(arg: Float): Nd4jArrayStructure<Float> {
check(this)
public override operator fun NDStructure<Float>.minus(arg: Float): Nd4jArrayStructure<Float> {
return ndArray.sub(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Float>.times(arg: Float): Nd4jArrayStructure<Float> {
check(this)
public override operator fun NDStructure<Float>.times(arg: Float): Nd4jArrayStructure<Float> {
return ndArray.mul(arg).wrap()
}
public override operator fun Float.div(arg: Nd4jArrayStructure<Float>): Nd4jArrayStructure<Float> {
check(arg)
public override operator fun Float.div(arg: NDStructure<Float>): Nd4jArrayStructure<Float> {
return arg.ndArray.rdiv(this).wrap()
}
public override operator fun Float.minus(arg: Nd4jArrayStructure<Float>): Nd4jArrayStructure<Float> {
check(arg)
public override operator fun Float.minus(arg: NDStructure<Float>): Nd4jArrayStructure<Float> {
return arg.ndArray.rsub(this).wrap()
}
}
@ -301,23 +283,19 @@ public class IntNd4jArrayRing(public override val shape: IntArray) : Nd4jArrayRi
public override fun INDArray.wrap(): Nd4jArrayStructure<Int> = check(asIntStructure())
public override operator fun Nd4jArrayStructure<Int>.plus(arg: Int): Nd4jArrayStructure<Int> {
check(this)
public override operator fun NDStructure<Int>.plus(arg: Int): Nd4jArrayStructure<Int> {
return ndArray.add(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Int>.minus(arg: Int): Nd4jArrayStructure<Int> {
check(this)
public override operator fun NDStructure<Int>.minus(arg: Int): Nd4jArrayStructure<Int> {
return ndArray.sub(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Int>.times(arg: Int): Nd4jArrayStructure<Int> {
check(this)
public override operator fun NDStructure<Int>.times(arg: Int): Nd4jArrayStructure<Int> {
return ndArray.mul(arg).wrap()
}
public override operator fun Int.minus(arg: Nd4jArrayStructure<Int>): Nd4jArrayStructure<Int> {
check(arg)
public override operator fun Int.minus(arg: NDStructure<Int>): Nd4jArrayStructure<Int> {
return arg.ndArray.rsub(this).wrap()
}
}
@ -331,23 +309,19 @@ public class LongNd4jArrayRing(public override val shape: IntArray) : Nd4jArrayR
public override fun INDArray.wrap(): Nd4jArrayStructure<Long> = check(asLongStructure())
public override operator fun Nd4jArrayStructure<Long>.plus(arg: Long): Nd4jArrayStructure<Long> {
check(this)
public override operator fun NDStructure<Long>.plus(arg: Long): Nd4jArrayStructure<Long> {
return ndArray.add(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Long>.minus(arg: Long): Nd4jArrayStructure<Long> {
check(this)
public override operator fun NDStructure<Long>.minus(arg: Long): Nd4jArrayStructure<Long> {
return ndArray.sub(arg).wrap()
}
public override operator fun Nd4jArrayStructure<Long>.times(arg: Long): Nd4jArrayStructure<Long> {
check(this)
public override operator fun NDStructure<Long>.times(arg: Long): Nd4jArrayStructure<Long> {
return ndArray.mul(arg).wrap()
}
public override operator fun Long.minus(arg: Nd4jArrayStructure<Long>): Nd4jArrayStructure<Long> {
check(arg)
public override operator fun Long.minus(arg: NDStructure<Long>): Nd4jArrayStructure<Long> {
return arg.ndArray.rsub(this).wrap()
}
}

4
kmath-nd4j/src/main/kotlin/kscience.kmath.nd4j/Nd4jArrayStructure.kt
View File

@ -1,7 +1,7 @@
package kscience.kmath.nd4j
import kscience.kmath.structures.MutableNDStructure
import kscience.kmath.structures.NDStructure
import kscience.kmath.nd.MutableNDStructure
import kscience.kmath.nd.NDStructure
import org.nd4j.linalg.api.ndarray.INDArray
/**

2
kmath-nd4j/src/test/kotlin/kscience/kmath/nd4j/Nd4jArrayStructureTest.kt
View File

@ -1,6 +1,6 @@
package kscience.kmath.nd4j
import kscience.kmath.structures.get
import kscience.kmath.nd.get
import org.nd4j.linalg.factory.Nd4j
import kotlin.test.Test
import kotlin.test.assertEquals

8
kmath-viktor/src/main/kotlin/kscience/kmath/viktor/ViktorNDStructure.kt
View File

@ -1,10 +1,10 @@
package kscience.kmath.viktor
import kscience.kmath.nd.DefaultStrides
import kscience.kmath.nd.MutableNDStructure
import kscience.kmath.nd.NDField
import kscience.kmath.nd.Strides
import kscience.kmath.operations.RealField
import kscience.kmath.structures.DefaultStrides
import kscience.kmath.structures.MutableNDStructure
import kscience.kmath.structures.NDField
import kscience.kmath.structures.Strides
import org.jetbrains.bio.viktor.F64Array
@Suppress("OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")