/**
 * 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
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 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */
package org.openimaj.math.statistics.normalisation;

import org.openimaj.math.util.DoubleArrayStatsUtils;
import org.openimaj.util.array.ArrayUtils;

/**
 * Subtract the mean of each example vector from itself to normalise the vector.
 * <p>
 * Only use if the data is stationary (i.e., the statistics for each data
 * dimension follow the same distribution).
 *
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 */
public class PerExampleMeanCenter implements Normaliser {
        @Override
        public double[] normalise(double[] vector) {
                final double mean = DoubleArrayStatsUtils.mean(vector);
                vector = ArrayUtils.subtract(vector, mean);
                return vector;
        }

        @Override
        public double[][] normalise(double[][] data) {
                final double[][] out = new double[data.length][];
                for (int c = 0; c < out.length; c++)
                        out[c] = normalise(data[c]);
                return out;
        }
}