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.Vector;
034import gov.sandia.cognition.math.matrix.mtj.DenseMatrixFactoryMTJ;
035
036/**
037 * Given a matrix considered its "current value" this init strategy takes the current value
038 * and averages the columns (creating the mean row). This row is used as the value for
039 * all the rows in the initialise matrix
040 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
041 *
042 */
043public abstract class CurrentValueMean extends AbstractContextAwareInitStrategy<Matrix, Matrix>{
044
045        @Override
046        public Matrix init(int rows, int cols) {
047                Matrix currentValues = getCurrentValues();
048                Vector mean = currentValues.sumOfRows().scale(1f/currentValues.getNumRows());
049                Matrix m = DenseMatrixFactoryMTJ.INSTANCE.createMatrix(rows, cols);
050                for (int r = 0; r < m.getNumRows(); r++) {
051                        m.setRow(r, mean);
052                }
053
054                return m;
055        }
056
057        /**
058         * @return the matrix treated as the current value
059         */
060        public abstract Matrix getCurrentValues() ;
061
062}