Gets the gaussian pdf value log. - Java java.lang

Java examples for java.lang:Math Calculation

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Description

Gets the gaussian pdf value log.

Demo Code

/**// w ww  .j  a  va 2  s .  c o m
 * Copyright 2004-2006 DFKI GmbH.
 * All Rights Reserved.  Use is subject to license terms.
 * 
 * Permission is hereby granted, free of charge, to use and distribute
 * this software and its documentation without restriction, including
 * without limitation the rights to use, copy, modify, merge, publish,
 * distribute, sublicense, and/or sell copies of this work, and to
 * permit persons to whom this work is furnished to do so, subject to
 * the following conditions:
 * 
 * 1. The code must retain the above copyright notice, this list of
 *    conditions and the following disclaimer.
 * 2. Any modifications must be clearly marked as such.
 * 3. Original authors' names are not deleted.
 * 4. The authors' names are not used to endorse or promote products
 *    derived from this software without specific prior written
 *    permission.
 *
 * DFKI GMBH AND THE CONTRIBUTORS TO THIS WORK DISCLAIM ALL WARRANTIES WITH
 * REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF
 * MERCHANTABILITY AND FITNESS, IN NO EVENT SHALL DFKI GMBH NOR THE
 * CONTRIBUTORS BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL
 * DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR
 * PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
 * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
 * THIS SOFTWARE.
 */
//package com.java2s;

public class Main {
    /**
     * Gets the gaussian pdf value log.
     *
     * @param x the x
     * @param meanVector the mean vector
     * @param covarianceMatrix the covariance matrix
     * @param constantTermLog the constant term log
     * @return the gaussian pdf value log
     */
    public static double getGaussianPdfValueLog(double[] x,
            double[] meanVector, double[] covarianceMatrix,
            double constantTermLog) {
        double P = Double.MIN_VALUE;
        int i;
        double z;

        for (i = 0; i < x.length; i++) {
            z = (x[i] - meanVector[i]) * (x[i] - meanVector[i]);
            P = logAdd(P, Math.log(z) - Math.log(covarianceMatrix[i]));
        }

        P *= -0.5;

        P = constantTermLog + P;

        return P;
    }

    /**
     * Log add.
     *
     * @param x the x
     * @param y the y
     * @return the double
     */
    public static double logAdd(double x, double y) {
        if (y > x) {
            double temp = x;
            x = y;
            y = temp;
        }

        if (x == Double.NEGATIVE_INFINITY)
            return x;

        double negDiff = y - x;
        if (negDiff < -20)
            return x;

        return x + Math.log(1.0 + Math.exp(negDiff));
    }

    /**
     * Log.
     *
     * @param a the a
     * @return the double[]
     */
    public static double[] log(double[] a) {
        double[] c = new double[a.length];
        for (int i = 0; i < a.length; i++) {
            c[i] = Math.log(a[i]);
        }
        return c;
    }

    /**
     * Log.
     *
     * @param a the a
     * @param minimumValue the minimum value
     * @param fixedValue the fixed value
     * @return the double[]
     */
    public static double[] log(double[] a, double minimumValue,
            double fixedValue) {
        double[] c = new double[a.length];
        for (int i = 0; i < a.length; i++) {
            if (a[i] > minimumValue)
                c[i] = Math.log(a[i]);
            else
                c[i] = fixedValue;
        }
        return c;
    }

    /**
     * Exp.
     *
     * @param a the a
     * @return the double[]
     */
    public static double[] exp(double[] a) {
        double[] c = new double[a.length];
        for (int i = 0; i < a.length; i++) {
            c[i] = Math.exp(a[i]);
        }
        return c;
    }
}

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