/*
* Copyright (c) 2009-2013, 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 mikera.matrixx.decompose;
import mikera.matrixx.AMatrix;
/**
* <p>
* Interface for results of Cholesky Decomposition
* <p>
* <p>
* A Cholesky decomposition decomposes positive-definite symmetric matrices into either upper or
* lower triangles:<br>
* <br>
* L*L<sup>T</sup>=A<br>
* R<sup>T</sup>*R=A<br>
* <br>
* where L is a lower triangular matrix and R is an upper triangular matrix. This is typically
* used to invert matrices, such as a covariance matrix.<br>
* </p>
*
*
* @author Peter Abeles
*/
public interface ICholeskyResult {
/**
* <p>
* Returns the lower triangular matrix from the decomposition.
* </p>
* @return A lower triangular matrix.
*/
public AMatrix getL();
/**
* <p>
* Returns the upper triangular matrix from the decomposition.
*
* The Upper triangular matrix is the transpose of the lower triangular matrix
* in the Cholesky decomposition.
* </p>
* @return A upper triangular matrix.
*/
public AMatrix getU();
}