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A project for various tests that don't quite constitute demos but might be useful to look at.

There is a newer version: 1.3.10

/**
 * Copyright (c) 2011, The University of Southampton and the individual contributors.
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification,
 * are permitted provided that the following conditions are met:
 *
 *   * 	Redistributions of source code must retain the above copyright notice,
 * 	this list of conditions and the following disclaimer.
 *
 *   *	Redistributions in binary form must reproduce the above copyright notice,
 * 	this list of conditions and the following disclaimer in the documentation
 * 	and/or other materials provided with the distribution.
 *
 *   *	Neither the name of the University of Southampton nor the names of its
 * 	contributors may be used to endorse or promote products derived from this
 * 	software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */
package org.openimaj.ml.benchmark;

import org.openimaj.math.matrix.MatlibMatrixUtils;
import org.openimaj.math.matrix.MeanVector;
import org.openimaj.time.Timer;

import ch.akuhn.matrix.SparseMatrix;
/**
 *
 * @author Sina Samangooei ([email protected])
 */
public class MatlibMatrixMultiplyBenchmark {
	
	public static void main(String[] args) {
		SparseMatrix a = SparseMatrix.sparse(4, 1118);
		MatlibMatrixUtils.plusInplace(a, 1);
		SparseMatrix xtrow = MatlibMatrixUtils.transpose(SparseMatrix.random(1118,22917,1 - 0.9998818947086253));
		
		System.out.println("xtrow sparsity: " + MatlibMatrixUtils.sparsity(xtrow));
		
		MeanVector mv = new MeanVector();
		System.out.println("doing: a . xtrow");
		for (int i = 0; i < 10; i++) {
			Timer t = Timer.timer();
			MatlibMatrixUtils.dotProductTranspose(a, xtrow);
			
			mv.update(new double[]{t.duration()});
			System.out.println("time: " + mv.vec()[0]);
		}
		
	}
}