org.ejml.interfaces.decomposition.CholeskyLDLDecomposition Maven / Gradle / Ivy
/*
* Copyright (c) 2009-2017, Peter Abeles. All Rights Reserved.
*
* This file is part of Efficient Java Matrix Library (EJML).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.ejml.interfaces.decomposition;
import org.ejml.data.Matrix;
/**
*
* Cholesky LDLT decomposition.
*
*
* A Cholesky LDL decomposition decomposes positive-definite symmetric matrices into:
*
* L*D*LT=A
*
* where L is a lower triangular matrix and D is a diagonal matrix. The main advantage of LDL versus LL or RR Cholesky is that
* it avoid a square root operation.
*
*
* @author Peter Abeles
*/
public interface CholeskyLDLDecomposition
extends DecompositionInterface {
/**
*
* Returns the lower triangular matrix from the decomposition.
*
*
*
* If an input is provided that matrix is used to write the results to.
* Otherwise a new matrix is created and the results written to it.
*
*
* @param L If not null then the decomposed matrix is written here.
* @return A lower triangular matrix.
*/
MatrixType getL(MatrixType L);
/**
*
* Returns the diagonal matrixfrom the decomposition.
*
*
*
* If an input is provided that matrix is used to write the results to.
* Otherwise a new matrix is created and the results written to it.
*
*
* @param D If not null it will be used to store the diagonal matrix
* @return D Square diagonal matrix
*/
MatrixType getD(MatrixType D);
}