org.jblas

Class Decompose

• public class Decompose
extends Object
Matrix which collects all kinds of decompositions.
• Constructor Detail

• Decompose

public Decompose()
• Method Detail

• lu

public static Decompose.LUDecomposition<DoubleMatrix> lu(DoubleMatrix A)
Compute LU Decomposition of a general matrix. Computes the LU decomposition using GETRF. Returns three matrices L, U, P, where L is lower diagonal, U is upper diagonal, and P is a permutation matrix such that A = P * L * U.
Parameters:
A - general matrix
Returns:
An LUDecomposition object.
• cholesky

public static FloatMatrix cholesky(FloatMatrix A)
if (info ) Compute Cholesky decomposition of A
Parameters:
A - symmetric, positive definite matrix (only upper half is used)
Returns:
upper triangular matrix U such that A = U' * U
• lu

public static Decompose.LUDecomposition<FloatMatrix> lu(FloatMatrix A)
Compute LU Decomposition of a general matrix. Computes the LU decomposition using GETRF. Returns three matrices L, U, P, where L is lower diagonal, U is upper diagonal, and P is a permutation matrix such that A = P * L * U.
Parameters:
A - general matrix
Returns:
An LUDecomposition object.
• cholesky

public static DoubleMatrix cholesky(DoubleMatrix A)
Compute Cholesky decomposition of A
Parameters:
A - symmetric, positive definite matrix (only upper half is used)
Returns:
upper triangular matrix U such that A = U' * U
• qr

public static Decompose.QRDecomposition<DoubleMatrix> qr(DoubleMatrix A)
QR decomposition. Decomposes (m,n) matrix A into a (m,m) matrix Q and an (m,n) matrix R such that Q is orthogonal, R is upper triangular and Q * R = A Note that if A has more rows than columns, then the lower rows of R will contain only zeros, such that the corresponding later columns of Q do not enter the computation at all. For some reason, LAPACK does not properly normalize those columns.
Parameters:
A - matrix
Returns:
QR decomposition
• qr

public static Decompose.QRDecomposition<FloatMatrix> qr(FloatMatrix A)
QR decomposition. Decomposes (m,n) matrix A into a (m,m) matrix Q and an (m,n) matrix R such that Q is orthogonal, R is upper triangular and Q * R = A
Parameters:
A - matrix
Returns:
QR decomposition