Extreme Optimization™: Complexity made simple.

Math and Statistics
Libraries for .NET

  • Home
  • Features
    • Math Library
    • Vector and Matrix Library
    • Statistics Library
    • Performance
    • Usability
  • Documentation
    • Introduction
    • Math Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Reference
  • Resources
    • Downloads
    • QuickStart Samples
    • Sample Applications
    • Frequently Asked Questions
    • Technical Support
  • Blog
  • Order
  • Company
    • About us
    • Testimonials
    • Customers
    • Press Releases
    • Careers
    • Partners
    • Contact us
Introduction
Deployment Guide
Configuration
Using Parallelism
Expand Mathematics Library User's GuideMathematics Library User's Guide
Expand Vector and Matrix Library User's GuideVector and Matrix Library User's Guide
Expand Data Analysis Library User's GuideData Analysis Library User's Guide
Expand Statistics Library User's GuideStatistics Library User's Guide
Expand Data Access Library User's GuideData Access Library User's Guide
Expand ReferenceReference
  • Extreme Optimization
    • Features
    • Solutions
    • Documentation
    • QuickStart Samples
    • Sample Applications
    • Downloads
    • Technical Support
    • Download trial
    • How to buy
    • Blog
    • Company
    • Resources
  • Documentation
    • Introduction
    • Deployment Guide
    • Configuration
    • Using Parallelism
    • Mathematics Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Data Access Library User's Guide
    • Reference
  • Reference
    • Extreme
    • Extreme.Collections
    • Extreme.Data
    • Extreme.Data.Json
    • Extreme.Data.Matlab
    • Extreme.Data.R
    • Extreme.Data.Stata
    • Extreme.Data.Text
    • Extreme.DataAnalysis
    • Extreme.DataAnalysis.Linq
    • Extreme.Mathematics
    • Extreme.Mathematics.Algorithms
    • Extreme.Mathematics.Calculus
    • Extreme.Mathematics.Calculus.OrdinaryDifferentialEquations
    • Extreme.Mathematics.Curves
    • Extreme.Mathematics.Curves.Nonlinear
    • Extreme.Mathematics.Distributed
    • Extreme.Mathematics.Distributed.Cuda
    • Extreme.Mathematics.EquationSolvers
    • Extreme.Mathematics.FSharp
    • Extreme.Mathematics.Generic
    • Extreme.Mathematics.Generic.LinearAlgebra
    • Extreme.Mathematics.Generic.LinearAlgebra.Implementation
    • Extreme.Mathematics.Generic.LinearAlgebra.Providers
    • Extreme.Mathematics.Generic.SignalProcessing
    • Extreme.Mathematics.Implementation
    • Extreme.Mathematics.LinearAlgebra
    • Extreme.Mathematics.LinearAlgebra.Complex
    • Extreme.Mathematics.LinearAlgebra.Complex.Decompositions
    • Extreme.Mathematics.LinearAlgebra.Implementation
    • Extreme.Mathematics.LinearAlgebra.IO
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers.Preconditioners
    • Extreme.Mathematics.LinearAlgebra.Providers
    • Extreme.Mathematics.LinearAlgebra.Sparse
    • Extreme.Mathematics.Optimization
    • Extreme.Mathematics.Optimization.Genetic
    • Extreme.Mathematics.Optimization.LineSearches
    • Extreme.Mathematics.Random
    • Extreme.Mathematics.SignalProcessing
    • Extreme.Numerics.FSharp
    • Extreme.Statistics
    • Extreme.Statistics.Distributions
    • Extreme.Statistics.IO
    • Extreme.Statistics.Linq
    • Extreme.Statistics.Multivariate
    • Extreme.Statistics.Random
    • Extreme.Statistics.Tests
    • Extreme.Statistics.TimeSeriesAnalysis
  • Extreme.Mathematics.LinearAlgebra.Implementation
    • DecompositionOperations(T) Class
    • DecompositionOperations(TReal, TComplex) Class
    • GenericDecompositionOperations(T) Class
    • GenericLinearAlgebraOperations(T) Class
    • GenericSparseLinearAlgebraOperations(T) Class
    • IArrayFunctions(T, TShape, TArray) Interface
    • ILinearAlgebraOperations(T) Interface
    • ILinearAlgebraOperations(T, TVector, TMatrix) Interface
    • ISparseLinearAlgebraOperations(T) Interface
    • IVectorFunctions(T) Interface
    • LinearAlgebraOperations(T) Class
    • ManagedArrayFunctions Class
    • ManagedArrayFunctions(T) Class
    • ManagedArrayFunctionsOfSingle Class
    • ManagedLapack Class
    • ManagedLapackOfSingle Class
    • ManagedLinearAlgebraOperations Class
    • ManagedLinearAlgebraOperationsOfSingle Class
    • ManagedSparseLinearAlgebraOperations Class
    • ManagedSparseLinearAlgebraOperationsOfSingle Class
    • SparseLinearAlgebraOperations Class
    • SparseLinearAlgebraOperations(T) Class
    • SparseLinearAlgebraOperationsOfSingle Class
  • ManagedLapack Class
    • Properties
    • Methods
  • Methods
    • BandCholeskyDecompose Method Overloads
    • BandCholeskyEstimateCondition Method Overloads
    • BandCholeskySolve Method Overloads
    • BandLUDecompose Method Overloads
    • BandLUEstimateCondition Method Overloads
    • BandLUSolve Method Overloads
    • BandTriangularSolve Method
    • CholeskyDecompose Method Overloads
    • CholeskyEstimateCondition Method Overloads
    • CholeskyInvert Method Overloads
    • CholeskySolve Method Overloads
    • EigenvalueDecompose Method Overloads
    • GeneralizedEigenvalueDecompose Method Overloads
    • GeneralizedSingularValueDecompose Method Overloads
    • HermitianDecompose Method Overloads
    • HermitianEigenvalueDecompose Method Overloads
    • HermitianEstimateCondition Method Overloads
    • HermitianGeneralizedEigenvalueDecompose Method
    • HermitianInvert Method Overloads
    • HermitianSolve Method Overloads
    • LQDecompose Method Overloads
    • LQOrthogonalMultiply Method
    • LQUnitaryMultiply Method
    • LUDecompose Method Overloads
    • LUEstimateCondition Method Overloads
    • LUInvert Method Overloads
    • LUSolve Method Overloads
    • QLDecompose Method Overloads
    • QLOrthogonalMultiply Method
    • QLUnitaryMultiply Method
    • QRDecompose Method Overloads
    • QROrthogonalMultiply Method
    • QRUnitaryMultiply Method Overloads
    • RQDecompose Method Overloads
    • RQOrthogonalMultiply Method
    • RQUnitaryMultiply Method
    • SingularValueDecompose Method Overloads
    • SymmetricDecompose Method
    • SymmetricEigenvalueDecompose Method
    • SymmetricEstimateCondition Method
    • SymmetricGeneralizedEigenvalueDecompose Method
    • SymmetricInvert Method
    • SymmetricSolve Method
    • TriangularEstimateCondition Method Overloads
    • TriangularInvert Method Overloads
    • TriangularSolve Method Overloads
  • LUDecompose Method Overloads
    • LUDecompose Method (Int32, Int32, Array2D(Complex(Double)), Array1D(Int32), Int32)
    • LUDecompose Method (Int32, Int32, Array2D(Double), Array1D(Int32), Int32)
    • LUDecompose Method (Int32, Int32, Array2D(DoubleComplex), Array1D(Int32), Int32)
  • LUDecompose Method (Int32, Int32, Array2D(Complex(Double)), Array1D(Int32), Int32)
ManagedLapackLUDecompose Method (Int32, Int32, Array2DComplexDouble, Array1DInt32, Int32)Extreme Optimization Numerical Libraries for .NET Professional
ZGETRF computes an LU decomposition of a general M-by-N matrix A using partial pivoting with row interchanges.

The decomposition has the form

A = P * L * U

where P is a permutation matrix, L is lower triangular with unit diagonal elements (lower trapezoidal if m > n), and U is upper triangular (upper trapezoidal if m < n).

This is the right-looking Level 3 BLAS version of the algorithm.

Namespace: Extreme.Mathematics.LinearAlgebra.Implementation
Assembly: Extreme.Numerics.Net40 (in Extreme.Numerics.Net40.dll) Version: 6.0.16073.0 (6.0.16312.0)
Syntax

C#
VB
C++
F#
Copy
public override void LUDecompose(
	int m,
	int n,
	Array2D<Complex<double>> a,
	Array1D<int> ipiv,
	out int info
)
Public Overrides Sub LUDecompose ( 
	m As Integer,
	n As Integer,
	a As Array2D(Of Complex(Of Double)),
	ipiv As Array1D(Of Integer),
	<OutAttribute> ByRef info As Integer
)
public:
virtual void LUDecompose(
	int m, 
	int n, 
	Array2D<Complex<double>> a, 
	Array1D<int> ipiv, 
	[OutAttribute] int% info
) override
abstract LUDecompose : 
        m : int * 
        n : int * 
        a : Array2D<Complex<float>> * 
        ipiv : Array1D<int> * 
        info : int byref -> unit 
override LUDecompose : 
        m : int * 
        n : int * 
        a : Array2D<Complex<float>> * 
        ipiv : Array1D<int> * 
        info : int byref -> unit 

Parameters

m
Type: SystemInt32
An integer specifying the number of rows of the matrix a. Must be greater than or equal to zero.
n
Type: SystemInt32
An integer specifying the number of columns of the matrix a. Must be greater than or equal to zero.
a
Type: Extreme.CollectionsArray2DComplexDouble
complex double-precision array specifying the m-by-n matrix to be factored. On exit, the factors L and U from the decomposition A = P*L*U; the unit diagonal elements of L are not stored.
ipiv
Type: Extreme.CollectionsArray1DInt32
Integer array of length min(m,n) that will hold the pivot indexes. Row i of the matrix was interchanged with row ipiv[i].
info
Type: SystemInt32
Reference to an integer containing a result code. Zero indicates success. Greater than zero indicates U(i,i) is exactly zero. The decomposition has been completed, but the factor U is exactly singular, and division by zero will occur if it is used to solve a system of equations.
Version Information

Numerical Libraries

Supported in: 6.0
See Also

Reference

ManagedLapack Class
LUDecompose Overload
Extreme.Mathematics.LinearAlgebra.Implementation Namespace

Copyright (c) 2004-2016 ExoAnalytics Inc.

Send comments on this topic to support@extremeoptimization.com

Copyright © 2004-2018, Extreme Optimization. All rights reserved.
Extreme Optimization, Complexity made simple, M#, and M Sharp are trademarks of ExoAnalytics Inc.
Microsoft, Visual C#, Visual Basic, Visual Studio, Visual Studio.NET, and the Optimized for Visual Studio logo
are registered trademarks of Microsoft Corporation.