org.ejml.factory

Class DecompositionFactory

java.lang.Object

org.ejml.factory.DecompositionFactory

public class DecompositionFactory
extends Object

Contains operations related to creating and evaluating the quality of common matrix decompositions. Except in specialized situations, matrix decompositions should be instantiated from this factory instead of being directly constructed. Low level implementations are more prone to changes and new algorithms will be automatically placed here.

Several functions are also provided to evaluate the quality of a decomposition. This is provided as a way to sanity check a decomposition. Often times a significant error in a decomposition will result in a poor (larger) quality value. Typically a quality value of around 1e-15 means it is within machine precision.

Author:

Peter Abeles

Constructor Summary

Constructors

Constructor and Description
DecompositionFactory()

Method Summary

Methods

Modifier and Type	Method and Description
static CholeskyDecomposition<DenseMatrix64F>	chol(int matrixSize, boolean lower) Returns a CholeskyDecomposition that has been optimized for the specified matrix size.
static CholeskyDecompositionLDL	cholLDL(int matrixSize) Returns a CholeskyDecompositionLDL that has been optimized for the specified matrix size.
static <T extends Matrix64F> boolean	decomposeSafe(DecompositionInterface<T> decomp, T M) A simple convinience function that decomposes the matrix but automatically checks the input ti make sure is not being modified.
static EigenDecomposition<DenseMatrix64F>	eig(int matrixSize, boolean needVectors) Returns an EigenDecomposition that has been optimized for the specified matrix size.
static EigenDecomposition<DenseMatrix64F>	eig(int matrixSize, boolean computeVectors, boolean isSymmetric) Returns an EigenDecomposition which is specialized for symmetric matrices or the general problem.
static LUDecomposition<DenseMatrix64F>	lu(int numRows, int numCol) Returns a LUDecomposition that has been optimized for the specified matrix size.
static QRDecomposition<DenseMatrix64F>	qr(int numRows, int numCols) Returns a QRDecomposition that has been optimized for the specified matrix size.
static QRPDecomposition<DenseMatrix64F>	qrp(int numRows, int numCols) Returns a QRPDecomposition that has been optimized for the specified matrix size.
static double	quality(DenseMatrix64F orig, DenseMatrix64F U, DenseMatrix64F W, DenseMatrix64F Vt)
static double	quality(DenseMatrix64F orig, EigenDecomposition<DenseMatrix64F> eig) Computes a metric which measures the the quality of an eigen value decomposition.
static double	quality(DenseMatrix64F orig, SingularValueDecomposition<DenseMatrix64F> svd) Computes a metric which measures the the quality of a singular value decomposition.
static SingularValueDecomposition<DenseMatrix64F>	svd(int numRows, int numCols, boolean needU, boolean needV, boolean compact) Returns a SingularValueDecomposition that has been optimized for the specified matrix size.
static TridiagonalSimilarDecomposition<DenseMatrix64F>	tridiagonal(int matrixSize) Checks to see if the passed in tridiagonal decomposition is of the appropriate type for the matrix of the provided size.

Methods inherited from class java.lang.Object

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

Constructor Detail

DecompositionFactory

public DecompositionFactory()

Method Detail

chol

public static CholeskyDecomposition<DenseMatrix64F> chol(int matrixSize,
                                         boolean lower)

Returns a CholeskyDecomposition that has been optimized for the specified matrix size.

Parameters:

matrixSize - Number of rows and columns that the returned decomposition is optimized for.

lower - should a lower or upper triangular matrix be used. If not sure set to true.

Returns:

A new CholeskyDecomposition.

cholLDL

public static CholeskyDecompositionLDL cholLDL(int matrixSize)

Returns a CholeskyDecompositionLDL that has been optimized for the specified matrix size.

Parameters:

matrixSize - Number of rows and columns that the returned decomposition is optimized for.

Returns:

CholeskyDecompositionLDL

lu

public static LUDecomposition<DenseMatrix64F> lu(int numRows,
                                 int numCol)

Returns a LUDecomposition that has been optimized for the specified matrix size.

Returns:

LUDecomposition

svd

public static SingularValueDecomposition<DenseMatrix64F> svd(int numRows,
                                             int numCols,
                                             boolean needU,
                                             boolean needV,
                                             boolean compact)

Returns a SingularValueDecomposition that has been optimized for the specified matrix size. For improved performance only the portion of the decomposition that the user requests will be computed.

Parameters:

numRows - Number of rows the returned decomposition is optimized for.

numCols - Number of columns that the returned decomposition is optimized for.

needU - Should it compute the U matrix. If not sure set to true.

needV - Should it compute the V matrix. If not sure set to true.

compact - Should it compute the SVD in compact form. If not sure set to false.

Returns:

qr

public static QRDecomposition<DenseMatrix64F> qr(int numRows,
                                 int numCols)

Returns a QRDecomposition that has been optimized for the specified matrix size.

Parameters:

numRows - Number of rows the returned decomposition is optimized for.

numCols - Number of columns that the returned decomposition is optimized for.

Returns:

QRDecomposition

qrp

public static QRPDecomposition<DenseMatrix64F> qrp(int numRows,
                                   int numCols)

Returns a QRPDecomposition that has been optimized for the specified matrix size.

Parameters:

numRows - Number of rows the returned decomposition is optimized for.

numCols - Number of columns that the returned decomposition is optimized for.

Returns:

QRPDecomposition

eig

public static EigenDecomposition<DenseMatrix64F> eig(int matrixSize,
                                     boolean needVectors)

Returns an EigenDecomposition that has been optimized for the specified matrix size. If the input matrix is symmetric within tolerance then the symmetric algorithm will be used, otherwise a general purpose eigenvalue decomposition is used.

Parameters:

matrixSize - Number of rows and columns that the returned decomposition is optimized for.

needVectors - Should eigenvectors be computed or not. If not sure set to true.

Returns:

A new EigenDecomposition

eig

public static EigenDecomposition<DenseMatrix64F> eig(int matrixSize,
                                     boolean computeVectors,
                                     boolean isSymmetric)

Returns an EigenDecomposition which is specialized for symmetric matrices or the general problem.

Parameters:

matrixSize - Number of rows and columns that the returned decomposition is optimized for.

computeVectors - Should it compute the eigenvectors or just eigenvalues.

isSymmetric - If true then the returned algorithm is specialized only for symmetric matrices, if false then a general purpose algorithm is returned.

Returns:

EVD for any matrix.

quality

public static double quality(DenseMatrix64F orig,
             SingularValueDecomposition<DenseMatrix64F> svd)

Computes a metric which measures the the quality of a singular value decomposition. If a value is returned that is close to or smaller than 1e-15 then it is within machine precision.

SVD quality is defined as:

Quality = || A - U W V^T|| / || A ||
where A is the original matrix , U W V is the decomposition, and ||A|| is the norm-f of A.

Parameters:

orig - The original matrix which was decomposed. Not modified.

svd - The decomposition after processing 'orig'. Not modified.

Returns:

The quality of the decomposition.

quality

public static double quality(DenseMatrix64F orig,
             DenseMatrix64F U,
             DenseMatrix64F W,
             DenseMatrix64F Vt)

quality

public static double quality(DenseMatrix64F orig,
             EigenDecomposition<DenseMatrix64F> eig)

Computes a metric which measures the the quality of an eigen value decomposition. If a value is returned that is close to or smaller than 1e-15 then it is within machine precision.

EVD quality is defined as:

Quality = ||A*V - V*D|| / ||A*V||.

Parameters:

orig - The original matrix. Not modified.

eig - EVD of the original matrix. Not modified.

Returns:

The quality of the decomposition.

tridiagonal

public static TridiagonalSimilarDecomposition<DenseMatrix64F> tridiagonal(int matrixSize)

Checks to see if the passed in tridiagonal decomposition is of the appropriate type for the matrix of the provided size. Returns the same instance or a new instance.

Parameters:

matrixSize - Number of rows and columns that the returned decomposition is optimized for.

decomposeSafe

public static <T extends Matrix64F> boolean decomposeSafe(DecompositionInterface<T> decomp,
                                          T M)

A simple convinience function that decomposes the matrix but automatically checks the input ti make sure is not being modified.

Type Parameters:

T - Matrix type.

Parameters:

decomp - Decomposition which is being wrapped

M - THe matrix being decomposed.

Returns:

If the decomposition was successful or not.