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.linear.learner.init;
031
032import gov.sandia.cognition.math.matrix.Matrix;
033import gov.sandia.cognition.math.matrix.MatrixFactory;
034import gov.sandia.cognition.math.matrix.mtj.SparseMatrix;
035
036import java.util.Random;
037
038public class SparseRowRandomInitStrategy implements InitStrategy {
039        MatrixFactory<? extends Matrix> smf = MatrixFactory.getSparseDefault();
040        private double min;
041        private double max;
042        private Random random;
043        private double sparcity;
044
045        public SparseRowRandomInitStrategy(double min, double max, double sparcity, Random random) {
046                this.min = min;
047                this.max = max;
048                this.random = random;
049                this.sparcity = sparcity;
050        }
051
052        @Override
053        public Matrix init(int rows, int cols) {
054                final SparseMatrix rand = (SparseMatrix) smf.createUniformRandom(rows, cols, min, max, random);
055                final Matrix ret = smf.createMatrix(rows, cols);
056                for (int i = 0; i < rows; i++) {
057                        if (this.random.nextDouble() > sparcity) {
058                                ret.setRow(i, rand.getRow(i));
059                        }
060                }
061                return ret;
062        }
063}