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

LinearSpace

interface LinearSpace<T, out A : Ring<T>>

Basic operations on matrices and vectors.

Parameters

the type of items in the matrices.

the type of ring over T.

Types

Companion

object Companion

Functions

buildMatrix

abstract fun buildMatrix(rows: Int, columns: Int, initializer: A.(i: Int, j: Int) -> T): Matrix<T>

Produces a matrix with this context and given dimensions.

buildVector

abstract fun buildVector(size: Int, initializer: A.(Int) -> T): Point<T>

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

computeFeature

@UnstableKMathAPI

open fun <F : StructureFeature> computeFeature(structure: Matrix<T>, type: KClass<out F>): F?

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

dot

open infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T>

Computes the dot product of this matrix and another one.

open infix fun Matrix<T>.dot(vector: Point<T>): Point<T>

Computes the dot product of this matrix and a vector.

minus

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

Matrix subtraction

open operator fun Point<T>.minus(other: Point<T>): Point<T>

Vector subtraction

plus

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

Matrix sum

open operator fun Point<T>.plus(other: Point<T>): Point<T>

Vector sum

times

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

Multiplies an element by a matrix of it.

open operator fun T.times(v: Point<T>): Point<T>

Multiplies an element by a vector of it.

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

Multiplies a matrix by its element.

open operator fun Point<T>.times(value: T): Point<T>

Multiplies a vector by its element.

unaryMinus

open operator fun Matrix<T>.unaryMinus(): Matrix<T>

open operator fun Point<T>.unaryMinus(): Point<T>

Properties

elementAlgebra

abstract val elementAlgebra: A

Inheritors

BufferedLinearSpace

DoubleLinearSpace

Extensions

column

inline fun <T : Any> LinearSpace<T, Ring<T>>.column(size: Int, crossinline builder: (Int) -> T): Matrix<T>

fun <T : Any> LinearSpace<T, Ring<T>>.column(vararg values: T): Matrix<T>

computeFeature

@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.

contentEquals

@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.

lup

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.

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>

lupSolver

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

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

matrix

@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

one

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.

row

inline fun <T : Any> LinearSpace<T, Ring<T>>.row(size: Int, crossinline builder: (Int) -> T): Matrix<T>

fun <T : Any> LinearSpace<T, Ring<T>>.row(vararg values: T): Matrix<T>

vector

@UnstableKMathAPI

fun <T : Any> LinearSpace<T, Ring<T>>.vector(vararg elements: T): Point<T>

zero

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

A virtual matrix of zeroes

Sources

common source