001/**
002 * Copyright (c) 2011, The University of Southampton and the individual contributors.
003 * All rights reserved.
004 *
005 * Redistribution and use in source and binary forms, with or without modification,
006 * are permitted provided that the following conditions are met:
007 *
008 *   *  Redistributions of source code must retain the above copyright notice,
009 *      this list of conditions and the following disclaimer.
010 *
011 *   *  Redistributions in binary form must reproduce the above copyright notice,
012 *      this list of conditions and the following disclaimer in the documentation
013 *      and/or other materials provided with the distribution.
014 *
015 *   *  Neither the name of the University of Southampton nor the names of its
016 *      contributors may be used to endorse or promote products derived from this
017 *      software without specific prior written permission.
018 *
019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
029 */
030package org.openimaj.ml.benchmark;
031
032import org.openimaj.math.matrix.MatlibMatrixUtils;
033import org.openimaj.math.matrix.MeanVector;
034import org.openimaj.time.Timer;
035
036import ch.akuhn.matrix.SparseMatrix;
037/**
038 *
039 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
040 */
041public class MatlibMatrixMultiplyBenchmark {
042        
043        public static void main(String[] args) {
044                SparseMatrix a = SparseMatrix.sparse(4, 1118);
045                MatlibMatrixUtils.plusInplace(a, 1);
046                SparseMatrix xtrow = MatlibMatrixUtils.transpose(SparseMatrix.random(1118,22917,1 - 0.9998818947086253));
047                
048                System.out.println("xtrow sparsity: " + MatlibMatrixUtils.sparsity(xtrow));
049                
050                MeanVector mv = new MeanVector();
051                System.out.println("doing: a . xtrow");
052                for (int i = 0; i < 10; i++) {
053                        Timer t = Timer.timer();
054                        MatlibMatrixUtils.dotProductTranspose(a, xtrow);
055                        
056                        mv.update(new double[]{t.duration()});
057                        System.out.println("time: " + mv.vec()[0]);
058                }
059                
060        }
061}