kmath-core/space.kscience.kmath.linear/DoubleLinearSpace

DoubleLinearSpace

object DoubleLinearSpace : LinearSpace<Double, DoubleField> (source)

Functions

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open override fun buildMatrix(rows: Int, columns: Int, initializer: DoubleField.(i: Int, j: Int) -> Double): Matrix<Double>

Produces a matrix with this context and given dimensions.

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open override fun buildVector(size: Int, initializer: DoubleField.(Int) -> Double): DoubleBuffer

Produces a point compatible with matrix space (and possibly optimized for it).

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fun <T : Any> LinearSpace<T, Ring<T>>.column(vararg values: T): Matrix<T>
inline fun <T : Any> LinearSpace<T, Ring<T>>.column(size: Int, crossinline builder: (Int) -> T): Matrix<T>
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@UnstableKMathAPI
open fun <F : StructureFeature> computeFeature(structure: Matrix<Double>, type: KClass<out F>): F?

Compute a feature of the structure in this scope. Structure features take precedence other context features.

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@UnstableKMathAPI
inline fun <T : Any, F : StructureFeature> LinearSpace<T, *>.computeFeature(structure: Matrix<T>): F?

Get a feature of the structure in this scope. Structure features take precedence other context features.

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@PerformancePitfall
fun <T : Comparable<T>> LinearSpace<T, Ring<T>>.contentEquals(st1: StructureND<T>, st2: StructureND<T>): Boolean

Indicates whether some StructureND is equal to another one.

@PerformancePitfall
fun <T : Comparable<T>> LinearSpace<T, Ring<T>>.contentEquals(st1: StructureND<T>, st2: StructureND<T>, absoluteTolerance: T): Boolean

Indicates whether some StructureND is equal to another one with absoluteTolerance.

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operator fun Point<Double>.div(value: Double): DoubleBuffer
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open infix override fun Matrix<Double>.dot(other: Matrix<Double>): Matrix<Double>

Computes the dot product of this matrix and another one.

open infix override fun Matrix<Double>.dot(vector: Point<Double>): DoubleBuffer

Computes the dot product of this matrix and a vector.

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inline fun <T : Comparable<T>> LinearSpace<T, Field<T>>.lup(matrix: Matrix<T>, noinline checkSingular: (T) -> Boolean): LupDecomposition<T>
fun LinearSpace<Double, DoubleField>.lup(matrix: Matrix<Double>, singularityThreshold: Double = 1.0E-11): LupDecomposition<Double>

fun <T : Comparable<T>> LinearSpace<T, Field<T>>.lup(factory: MutableBufferFactory<T>, matrix: Matrix<T>, checkSingular: (T) -> Boolean): LupDecomposition<T>

Create a lup decomposition of generic matrix.

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fun LinearSpace<Double, DoubleField>.lupSolver(singularityThreshold: Double = 1.0E-11): LinearSolver<Double>

fun <T : Comparable<T>, F : Field<T>> LinearSpace<T, F>.lupSolver(bufferFactory: MutableBufferFactory<T>, singularityCheck: (T) -> Boolean): LinearSolver<T>

Produce a generic solver based on LUP decomposition

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@UnstableKMathAPI
fun <T : Any, A : Ring<T>> LinearSpace<T, A>.matrix(rows: Int, columns: Int): MatrixBuilder<T, A>

Create a matrix builder with given number of rows and columns

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open operator override fun Matrix<Double>.minus(other: Matrix<Double>): Matrix<Double>

Matrix subtraction

open operator override fun Point<Double>.minus(other: Point<Double>): DoubleBuffer

Vector subtraction

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fun <T : Any> LinearSpace<T, Ring<T>>.one(rows: Int, columns: Int): Matrix<T>

Diagonal matrix of ones. The matrix is virtual no actual matrix is created.

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open operator override fun Matrix<Double>.plus(other: Matrix<Double>): Matrix<Double>

Matrix sum

open operator override fun Point<Double>.plus(other: Point<Double>): DoubleBuffer

Vector sum

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fun <T : Any> LinearSpace<T, Ring<T>>.row(vararg values: T): Matrix<T>
inline fun <T : Any> LinearSpace<T, Ring<T>>.row(size: Int, crossinline builder: (Int) -> T): Matrix<T>
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open operator override fun Double.times(v: Point<Double>): DoubleBuffer

Multiplies an element by a vector of it.

open operator override fun Matrix<Double>.times(value: Double): Matrix<Double>

Multiplies a matrix by its element.

open operator override fun Point<Double>.times(value: Double): DoubleBuffer

Multiplies a vector by its element.

open operator fun Double.times(m: Matrix<Double>): Matrix<Double>

Multiplies an element by a matrix of it.

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open operator override fun Matrix<Double>.unaryMinus(): Matrix<Double>
open operator fun Point<Double>.unaryMinus(): Point<Double>
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@UnstableKMathAPI
fun <T : Any> LinearSpace<T, Ring<T>>.vector(vararg elements: T): Point<T>
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fun <T : Any> LinearSpace<T, Ring<T>>.zero(rows: Int, columns: Int): Matrix<T>

A virtual matrix of zeroes

Properties

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open override val elementAlgebra: DoubleField