edu.umn.msi.tropix.proteomics.itraqquantitation.impl.RUtils.java Source code

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/********************************************************************************
 * Copyright (c) 2009 Regents of the University of Minnesota
 *
 * This Software was written at the Minnesota Supercomputing Institute
 * http://msi.umn.edu
 *
 * All rights reserved. The following statement of license applies
 * only to this file, and and not to the other files distributed with it
 * or derived therefrom.  This file is made available under the terms of
 * the Eclipse Public License v1.0 which accompanies this distribution,
 * and is available at http://www.eclipse.org/legal/epl-v10.html
 *
 * Contributors:
 * Minnesota Supercomputing Institute - initial API and implementation
 *******************************************************************************/

package edu.umn.msi.tropix.proteomics.itraqquantitation.impl;

import org.apache.commons.math.MathException;
import org.apache.commons.math.distribution.NormalDistributionImpl;
import org.apache.commons.math.stat.StatUtils;
import org.apache.commons.math.stat.descriptive.rank.Median;

class RUtils {
    private static NormalDistributionImpl standardNormalDistribution = new NormalDistributionImpl();
    private static Median median = new Median();

    public static double pnorm(final double x) {
        try {
            return standardNormalDistribution.cumulativeProbability(x);
        } catch (final MathException e) {
            throw new RuntimeException(e);
        }
    }

    public static double median(final double[] x) {
        return median.evaluate(x);
    }

    public static double sd(final double[] x) {
        return Math.sqrt(StatUtils.variance(x));
    }

    /**
     * Implements wtd.mean from the Hmisc R library.
     * 
     * @param x
     * @param w
     * @return
     */
    public static double weightedMean(final double[] x, final double[] weights) {
        double weightedSum = 0.0, sumOfWeights = 0.0;
        for (int i = 0; i < x.length; i++) {
            weightedSum += x[i] * weights[i];
            sumOfWeights += weights[i];
        }
        return weightedSum / sumOfWeights;
    }

    /**
     * Implements wtd.var from the Hmisc R library.
     * 
     * @param x
     * @param weights
     * @return
     */
    public static double weightedVariance(final double[] x, final double[] weights) {
        final double xBar = weightedMean(x, weights);
        double weightedSumDiff = 0.0, sumOfWeights = 0.0;
        for (int i = 0; i < x.length; i++) {
            final double diff = x[i] - xBar;
            weightedSumDiff += weights[i] * diff * diff;
            sumOfWeights += weights[i];
        }
        return weightedSumDiff / (sumOfWeights - 1);
    }

}