BufferedLinearSpace
class BufferedLinearSpace<T, out A : Ring<T>>(bufferAlgebra: BufferAlgebra<T, A>) : LinearSpace<T, A> (source)
Functions
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Compute a feature of the structure in this scope. Structure features take precedence other context features.
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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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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.
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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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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Multiplies a matrix by its element.
Multiplies an element by a matrix of it.
Multiplies an element by a vector of it.
Multiplies a vector by its element.
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