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Similarities for Feature Vectors and Time Series thereof, such as Cosine and Dynamic Time Warping.
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/*
 * Maltcms, modular application toolkit for chromatography-mass spectrometry.
 * Copyright (C) 2008-2014, The authors of Maltcms. All rights reserved.
 *
 * Project website: http://maltcms.sf.net
 *
 * Maltcms may be used under the terms of either the
 *
 * GNU Lesser General Public License (LGPL)
 * http://www.gnu.org/licenses/lgpl.html
 *
 * or the
 *
 * Eclipse Public License (EPL)
 * http://www.eclipse.org/org/documents/epl-v10.php
 *
 * As a user/recipient of Maltcms, you may choose which license to receive the code
 * under. Certain files or entire directories may not be covered by this
 * dual license, but are subject to licenses compatible to both LGPL and EPL.
 * License exceptions are explicitly declared in all relevant files or in a
 * LICENSE file in the relevant directories.
 *
 * Maltcms is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
 * FOR A PARTICULAR PURPOSE. Please consult the relevant license documentation
 * for details.
 */
package maltcms.math.functions.similarities;

import lombok.Data;
import maltcms.math.functions.IArraySimilarity;
import maltcms.tools.ArrayTools;
import maltcms.tools.ArrayTools2;
import net.jcip.annotations.NotThreadSafe;
import ucar.ma2.Array;
import ucar.ma2.ArrayDouble;
import ucar.ma2.IndexIterator;

/**
 * Calculates the dotmap, but instead of the weighting by mz bin this class uses
 * the standard deviation.
 *
 * @author Mathias Wilhelm
 * 
 */
@Data
//@ServiceProvider(service = IArraySimilarity.class)
@NotThreadSafe
public class ArrayDotMap implements IArraySimilarity {

    private ArrayDouble.D1 std;
    private IArraySimilarity score = new ArrayCos();

    /** {@inheritDoc} */
    @Override
    public double apply(final Array t1, final Array t2) {

        IndexIterator iter1 = t1.getIndexIterator();
        IndexIterator iter2 = t2.getIndexIterator();
        IndexIterator iter3 = this.std.getIndexIterator();
        double sum1 = 0.0d;
        double sum2 = 0.0d;
        double lstd = 0.0d;
        double c = 0.0d;
        while (iter1.hasNext() && iter2.hasNext() && iter3.hasNext()) {
            lstd = iter3.getDoubleNext();
            sum1 += Math.sqrt(iter1.getDoubleNext()) * lstd * c;
            sum2 += Math.sqrt(iter2.getDoubleNext()) * lstd * c;
            c++;
        }

        final Array t1s = ArrayTools.mult(ArrayTools2.sqrt(t1), 1.0d / sum1);
        final Array t2s = ArrayTools.mult(ArrayTools2.sqrt(t2), 1.0d / sum2);

        iter1 = t1s.getIndexIterator();
        iter2 = t2s.getIndexIterator();
        iter3 = this.std.getIndexIterator();
        double s1, s2, sum = 0.0d;
        c = 0;
        while (iter1.hasNext() && iter2.hasNext() && iter3.hasNext()) {
            lstd = iter3.getDoubleNext();
            s1 = iter1.getDoubleNext() * lstd * c;
            s2 = iter2.getDoubleNext() * lstd * c;
            sum += s1 * s2;
            c++;
        }

        return sum + this.score.apply(t1, t2);
    }

    /**
     * Setter.
     *
     * @param stdArray variance for each mass bin
     */
    public void setStdArray(final ArrayDouble.D1 stdArray) {
        this.std = (ArrayDouble.D1) stdArray.copy();
    }

    /** {@inheritDoc} */
    @Override
    public IArraySimilarity copy() {
        ArrayDotMap ac = new ArrayDotMap();
        ac.setScore(getScore());
        ac.setStdArray(getStd());
        return ac;
    }
}