/*
 * Copyright (c) 2009-2015, 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.alg.dense.decompose.chol;


import org.ejml.data.CDenseMatrix64F;
import org.ejml.data.Complex64F;
import org.ejml.interfaces.decomposition.CholeskyDecomposition;
import org.ejml.ops.CCommonOps;


/**
 *
 * 

* This is an abstract class for a Cholesky decomposition. It provides the solvers, but the actual * decomposition is provided in other classes. *

* * @see org.ejml.interfaces.decomposition.CholeskyDecomposition * @author Peter Abeles */ public abstract class CholeskyDecompositionCommon_CD64 implements CholeskyDecomposition { // width and height of the matrix protected int n; // the decomposed matrix protected CDenseMatrix64F T; protected double[] t; // is it a lower triangular matrix or an upper triangular matrix protected boolean lower; // storage for the determinant protected Complex64F det = new Complex64F(); /** * Specifies if a lower or upper variant should be constructed. * * @param lower should a lower or upper triangular matrix be used. */ public CholeskyDecompositionCommon_CD64(boolean lower) { this.lower = lower; } /** * {@inheritDoc} */ @Override public boolean isLower() { return lower; } /** * {@inheritDoc} */ @Override public boolean decompose( CDenseMatrix64F mat ) { if( mat.numRows != mat.numCols ) { throw new IllegalArgumentException("Must be a square matrix."); } n = mat.numRows; T = mat; t = T.data; if(lower) { return decomposeLower(); } else { return decomposeUpper(); } } @Override public boolean inputModified() { return true; } /** * Performs an lower triangular decomposition. * * @return true if the matrix was decomposed. */ protected abstract boolean decomposeLower(); /** * Performs an upper triangular decomposition. * * @return true if the matrix was decomposed. */ protected abstract boolean decomposeUpper(); @Override public CDenseMatrix64F getT( CDenseMatrix64F T ) { // see if it needs to declare a new matrix or not if( T == null ) { T = new CDenseMatrix64F(n,n); } else { if( T.numRows != n || T.numCols != n ) throw new IllegalArgumentException("Unexpected matrix dimension for T."); CCommonOps.fill(T, 0,0); } // write the values to T if( lower ) { for( int i = 0; i < n; i++ ) { int index = i*n*2; for( int j = 0; j <= i; j++ ) { T.data[index] = this.T.data[index]; index++; T.data[index] = this.T.data[index]; index++; } } } else { for( int i = 0; i < n; i++ ) { int index = (i*n + i)*2; for( int j = i; j < n; j++ ) { T.data[index] = this.T.data[index]; index++; T.data[index] = this.T.data[index]; index++; } } } return T; } /** * Returns the raw decomposed matrix. * * @return A lower or upper triangular matrix. */ public CDenseMatrix64F _getT() { return T; } @Override public Complex64F computeDeterminant() { double prod = 1; // take advantage of the diagonal elements all being real int total = n*n*2; for( int i = 0; i < total; i += 2*(n + 1) ) { prod *= t[i]; } det.real = prod*prod; det.imaginary = 0; return det; } }

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