/* * 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(); }