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1   /**
2    * Copyright (c) 2011, The University of Southampton and the individual contributors.
3    * All rights reserved.
4    *
5    * Redistribution and use in source and binary forms, with or without modification,
6    * are permitted provided that the following conditions are met:
7    *
8    *   * 	Redistributions of source code must retain the above copyright notice,
9    * 	this list of conditions and the following disclaimer.
10   *
11   *   *	Redistributions in binary form must reproduce the above copyright notice,
12   * 	this list of conditions and the following disclaimer in the documentation
13   * 	and/or other materials provided with the distribution.
14   *
15   *   *	Neither the name of the University of Southampton nor the names of its
16   * 	contributors may be used to endorse or promote products derived from this
17   * 	software without specific prior written permission.
18   *
19   * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
20   * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
21   * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
22   * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
23   * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
24   * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
25   * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
26   * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
27   * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
28   * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
29   */
30  package org.openimaj.ml.benchmark;
31  
32  import java.util.Random;
33  
34  import org.openimaj.math.matrix.CFMatrixUtils;
35  import org.openimaj.math.matrix.MeanVector;
36  import org.openimaj.time.Timer;
37  
38  import no.uib.cipr.matrix.sparse.FlexCompRowMatrix;
39  import gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix;
40  import gov.sandia.cognition.math.matrix.mtj.SparseMatrix;
41  import gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ;
42  import gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix;
43  
44  /**
45   *
46   * @author Sina Samangooei (ss@ecs.soton.ac.uk)
47   */
48  public class CFMatrixMultiplyBenchmark {
49  	
50  	public static void main(String[] args) {
51  		SparseMatrix a = SparseMatrixFactoryMTJ.INSTANCE.copyMatrix(SparseMatrixFactoryMTJ.INSTANCE.createWrapper(new FlexCompRowMatrix(4, 1118)));
52  		CFMatrixUtils.plusInplace(a, 1);
53  		SparseRowMatrix xtrow = CFMatrixUtils.randomSparseRow(1118,22917,0d,1d,1 - 0.9998818947086253, new Random(1));
54  		SparseColumnMatrix xtcol = CFMatrixUtils.randomSparseCol(1118,22917,0d,1d,1 - 0.9998818947086253, new Random(1));
55  		
56  		System.out.println("xtrow sparsity: " + CFMatrixUtils.sparsity(xtrow));
57  		System.out.println("xtcol sparsity: " + CFMatrixUtils.sparsity(xtcol));
58  		System.out.println("Equal: " + CFMatrixUtils.fastsparsedot(a,xtcol).equals(a.times(xtcol), 0));
59  		MeanVector mv = new MeanVector();
60  		System.out.println("doing: a . xtcol");
61  		for (int i = 0; i < 10; i++) {
62  			Timer t = Timer.timer();
63  			CFMatrixUtils.fastsparsedot(a,xtcol);
64  			mv.update(new double[]{t.duration()});
65  			System.out.println("time: " + mv.vec()[0]);
66  		}
67  		
68  		
69  		mv.reset();
70  		System.out.println("doing: a . xtcol");
71  		for (int i = 0; i < 10; i++) {
72  			Timer t = Timer.timer();
73  			a.times(xtcol);
74  			mv.update(new double[]{t.duration()});
75  			System.out.println("time: " + mv.vec()[0]);
76  		}
77  		mv.reset();
78  		System.out.println("doing: a . xtrow");
79  		for (int i = 0; i < 10; i++) {
80  			Timer t = Timer.timer();
81  			a.times(xtrow);
82  			mv.update(new double[]{t.duration()});
83  			System.out.println("time: " + mv.vec()[0]);
84  		}
85  	}
86  }