cern.colt.matrix.tdouble.algo.decomposition

Class CSparseDoubleLUDecomposition

java.lang.Object

cern.colt.matrix.tdouble.algo.decomposition.CSparseDoubleLUDecomposition

All Implemented Interfaces:

SparseDoubleLUDecomposition

public class CSparseDoubleLUDecomposition
extends Object
implements SparseDoubleLUDecomposition

LU decomposition implemented using CSparseJ.

Author:

Piotr Wendykier (piotr.wendykier@gmail.com)

Constructor Summary

Constructors

Constructor and Description
CSparseDoubleLUDecomposition(DoubleMatrix2D A, int order, boolean checkIfSingular) Constructs and returns a new LU Decomposition object; The decomposed matrices can be retrieved via instance methods of the returned decomposition object.

Method Summary

Methods

Modifier and Type	Method and Description
double	det() Returns the determinant, det(A).
DoubleMatrix2D	getL() Returns the lower triangular factor, L.
int[]	getPivot() Returns a copy of the pivot permutation vector.
edu.emory.mathcs.csparsej.tdouble.Dcs_common.Dcss	getSymbolicAnalysis() Returns a copy of the symbolic LU analysis object
DoubleMatrix2D	getU() Returns the upper triangular factor, U.
boolean	isNonsingular() Returns whether the matrix is nonsingular (has an inverse).
void	solve(DoubleMatrix1D b) Solves A*x = b(in-place).

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

CSparseDoubleLUDecomposition

public CSparseDoubleLUDecomposition(DoubleMatrix2D A,
                            int order,
                            boolean checkIfSingular)

Constructs and returns a new LU Decomposition object; The decomposed matrices can be retrieved via instance methods of the returned decomposition object.

Parameters:

A - Square matrix

order - ordering option (0 to 3); 0: natural ordering, 1: amd(A+A'), 2: amd(S'*S), 3: amd(A'*A)

checkIfSingular - if true, then the singularity test (based on Dulmage-Mendelsohn decomposition) is performed.

Throws:

IllegalArgumentException - if A is not square or is not sparse.

IllegalArgumentException - if order is not in [0,3]

Method Detail

det

public double det()

Description copied from interface: SparseDoubleLUDecomposition

Returns the determinant, det(A).

Specified by:

det in interface SparseDoubleLUDecomposition

getL

public DoubleMatrix2D getL()

Description copied from interface: SparseDoubleLUDecomposition

Returns the lower triangular factor, L.

Specified by:

getL in interface SparseDoubleLUDecomposition

Returns:

L

getPivot

public int[] getPivot()

Description copied from interface: SparseDoubleLUDecomposition

Returns a copy of the pivot permutation vector.

Specified by:

getPivot in interface SparseDoubleLUDecomposition

Returns:

piv

getU

public DoubleMatrix2D getU()

Description copied from interface: SparseDoubleLUDecomposition

Returns the upper triangular factor, U.

Specified by:

getU in interface SparseDoubleLUDecomposition

Returns:

U

getSymbolicAnalysis

public edu.emory.mathcs.csparsej.tdouble.Dcs_common.Dcss getSymbolicAnalysis()

Description copied from interface: SparseDoubleLUDecomposition

Returns a copy of the symbolic LU analysis object

Specified by:

getSymbolicAnalysis in interface SparseDoubleLUDecomposition

Returns:

symbolic LU analysis

isNonsingular

public boolean isNonsingular()

Description copied from interface: SparseDoubleLUDecomposition

Returns whether the matrix is nonsingular (has an inverse).

Specified by:

isNonsingular in interface SparseDoubleLUDecomposition

Returns:

true if U, and hence A, is nonsingular; false otherwise.

solve

public void solve(DoubleMatrix1D b)

Description copied from interface: SparseDoubleLUDecomposition

Solves A*x = b(in-place). Upon return b is overridden with the result x.

Specified by:

solve in interface SparseDoubleLUDecomposition

Parameters:

b - A vector with of size A.rows();