playground.johannes.sna.math.DescriptivePiStatistics.java Source code

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Here is the source code for playground.johannes.sna.math.DescriptivePiStatistics.java

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/* *********************************************************************** *
 * project: org.matsim.*
 * DescriptivePiStatistics.java
 *                                                                         *
 * *********************************************************************** *
 *                                                                         *
 * copyright       : (C) 2010 by the members listed in the COPYING,        *
 *                   LICENSE and WARRANTY file.                            *
 * email           : info at matsim dot org                                *
 *                                                                         *
 * *********************************************************************** *
 *                                                                         *
 *   This program is free software; you can redistribute it and/or modify  *
 *   it under the terms of the GNU General Public License as published by  *
 *   the Free Software Foundation; either version 2 of the License, or     *
 *   (at your option) any later version.                                   *
 *   See also COPYING, LICENSE and WARRANTY file                           *
 *                                                                         *
 * *********************************************************************** */
package playground.johannes.sna.math;

import org.apache.commons.math.stat.descriptive.DescriptiveStatistics;
import org.apache.commons.math.stat.descriptive.UnivariateStatistic;
import org.apache.commons.math.stat.descriptive.rank.Max;
import org.apache.commons.math.stat.descriptive.rank.Min;
import org.apache.commons.math.stat.descriptive.rank.Percentile;
import org.apache.commons.math.util.ResizableDoubleArray;

/**
 * Descriptive statistics object where each sample has a pi-value assigned.
 * 
 * @author illenberger
 * 
 */
public class DescriptivePiStatistics extends DescriptiveStatistics {

    private ResizableDoubleArray piValues = new ResizableDoubleArray();

    private static final long serialVersionUID = 552953838961616624L;

    /**
     * Creates a new descriptive statistics object initialized with dummy
     * implementations that return {@link Double#NaN} (except
     * min/max-implementations).
     */
    public DescriptivePiStatistics() {
        DummyPiStatistics dummyStats = new DummyPiStatistics();
        setMeanImpl(dummyStats);
        setGeometricMeanImpl(dummyStats);
        setKurtosisImpl(dummyStats);
        setMaxImpl(new StatisticsWrapper(new Max()));
        setMinImpl(new StatisticsWrapper(new Min()));
        setPercentileImpl(new DummyPiPercentile());
        setSkewnessImpl(dummyStats);
        setVarianceImpl(dummyStats);
        setSumsqImpl(dummyStats);
        setSumImpl(dummyStats);
    }

    /**
     * Adds a sample with pi=1.0.
     */
    @Override
    public void addValue(double v) {
        addValue(v, 1.0);
    }

    /**
     * Adds a sample with a pi-value.
     * 
     * @param v
     *            a sample
     * @param pi
     *            the sample's pi-value
     */
    public void addValue(double v, double pi) {
        if (windowSize != INFINITE_WINDOW) {
            if (getN() == windowSize) {
                piValues.addElementRolling(pi);
            } else if (getN() < windowSize) {
                piValues.addElement(pi);
            }
        } else {
            piValues.addElement(pi);
        }

        super.addValue(v);
    }

    /**
     * Returns the pi-values (insertion-ordered).
     * 
     * @return the pi-values.
     */
    public double[] getPiValues() {
        return piValues.getElements();
    }

    /**
     * @see {@link DescriptiveStatistics#apply(UnivariateStatistic)}.
     */
    @Override
    public double apply(UnivariateStatistic stat) {
        ((UnivariatePiStatistic) stat).setPiValues(piValues.getInternalValues());
        return super.apply(stat);
    }

    /**
     * @see {@link DescriptiveStatistics#clear()}.
     */
    @Override
    public void clear() {
        piValues.clear();
        super.clear();
    }

    /**
     * @see {@link DescriptiveStatistics#removeMostRecentValue()}.
     */
    @Override
    public void removeMostRecentValue() {
        piValues.discardMostRecentElements(1);
        super.removeMostRecentValue();
    }

    private static class DummyPiStatistics implements UnivariatePiStatistic {

        @Override
        public void setPiValues(double[] piValues) {
            // does nothing
        }

        @Override
        public UnivariateStatistic copy() {
            return new DummyPiStatistics();
        }

        @Override
        public double evaluate(double[] values) {
            return Double.NaN;
        }

        @Override
        public double evaluate(double[] values, int begin, int length) {
            return Double.NaN;
        }
    }

    private static class StatisticsWrapper implements UnivariatePiStatistic {

        private UnivariateStatistic delegate;

        public StatisticsWrapper(UnivariateStatistic delegate) {
            this.delegate = delegate;
        }

        @Override
        public void setPiValues(double[] piValues) {
            // does nothing
        }

        @Override
        public UnivariateStatistic copy() {
            return new StatisticsWrapper(delegate);
        }

        @Override
        public double evaluate(double[] values) {
            return delegate.evaluate(values);
        }

        @Override
        public double evaluate(double[] values, int begin, int length) {
            return delegate.evaluate(values, begin, length);
        }
    }

    private static class DummyPiPercentile extends Percentile implements UnivariatePiStatistic {

        private static final long serialVersionUID = 3778314678555629077L;

        @Override
        public void setPiValues(double[] piValues) {
        }

        @Override
        public Percentile copy() {
            return new DummyPiPercentile();
        }

        @Override
        public double evaluate(double[] values, double p) {
            return Double.NaN;
        }

        @Override
        public double evaluate(double[] values, int begin, int length, double p) {
            return Double.NaN;
        }

        @Override
        public double evaluate(double[] values, int start, int length) {
            return Double.NaN;
        }

        @Override
        public double getQuantile() {
            return Double.NaN;
        }

        @Override
        public double evaluate(double[] values) {
            return Double.NaN;
        }

    }
}