/* ===========================================================
 * JFreeChart : a free chart library for the Java(tm) platform
 * ===========================================================
 *
 * (C) Copyright 2000-2011, by Object Refinery Limited and Contributors.
 *
 * Project Info:  http://www.jfree.org/jfreechart/index.html
 *
 * This library is free software; you can redistribute it and/or modify it
 * under the terms of the GNU Lesser General Public License as published by
 * the Free Software Foundation; either version 2.1 of the License, or
 * (at your option) any later version.
 *
 * This library 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. See the GNU Lesser General Public
 * License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this library; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301,
 * USA.
 *
 * [Oracle and Java are registered trademarks of Oracle and/or its affiliates.
 * Other names may be trademarks of their respective owners.]
 *
 * ----------------------------
 * BoxAndWhiskerCalculator.java
 * ----------------------------
 * (C) Copyright 2003-2008,  by Object Refinery Limited and Contributors.
 *
 * Original Author:  David Gilbert (for Object Refinery Limited);
 * Contributor(s):   -;
 *
 * Changes
 * -------
 * 28-Aug-2003 : Version 1 (DG);
 * 17-Nov-2003 : Fixed bug in calculations of outliers and median (DG);
 * 10-Jan-2005 : Removed deprecated methods in preparation for 1.0.0
 *               release (DG);
 * ------------- JFREECHART 1.0.x ---------------------------------------------
 * 15-Nov-2006 : Cleaned up handling of null arguments, and null or NaN items
 *               in the list (DG);
 *
 */

package org.jfree.data.statistics;

import org.jfree.chart.axis.NumberComparator;

import java.util.ArrayList;
import java.util.Collections;
import java.util.List;

/**
 * A utility class that calculates the mean, median, quartiles Q1 and Q3, plus
 * a list of outlier values...all from an arbitrary list of
 * <code>Number</code> objects.
 */
public abstract class BoxAndWhiskerCalculator {

    /**
     * Calculates the statistics required for a {@link BoxAndWhiskerItem}
     * from a list of <code>Number</code> objects.  Any items in the list
     * that are <code>null</code>, not an instance of <code>Number</code>, or
     * equivalent to <code>Double.NaN</code>, will be ignored.
     *
     * @param values  a list of numbers (a <code>null</code> list is not
     *                permitted).
     *
     * @return A box-and-whisker item.
     */
    public static BoxAndWhiskerItem calculateBoxAndWhiskerStatistics(
                                        List<Number> values) {
        return calculateBoxAndWhiskerStatistics(values, true);
    }

    /**
     * Calculates the statistics required for a {@link BoxAndWhiskerItem}
     * from a list of <code>Number</code> objects.  Any items in the list
     * that are <code>null</code>, not an instance of <code>Number</code>, or
     * equivalent to <code>Double.NaN</code>, will be ignored.
     *
     * @param values  a list of numbers (a <code>null</code> list is not
     *                permitted).
     * @param stripNullAndNaNItems  a flag that controls the handling of null
     *     and NaN items.
     *
     * @return A box-and-whisker item.
     *
     * @since 1.0.3
     */
    public static BoxAndWhiskerItem calculateBoxAndWhiskerStatistics(
            List<Number> values, boolean stripNullAndNaNItems) {

        if (values == null) {
            throw new IllegalArgumentException("Null 'values' argument.");
        }

        List<Number> vlist;
        if (stripNullAndNaNItems) {
            vlist = new ArrayList<Number>(values.size());
            for (Number n : values) {
                double v = n.doubleValue();
                if (!Double.isNaN(v)) {
                    vlist.add(n);
                }
            }
        }
        else {
            vlist = values;
        }
        Collections.sort(vlist, new NumberComparator());

        double mean = Statistics.calculateMean(vlist, false);
        double median = Statistics.calculateMedian(vlist, false);
        double q1 = calculateQ1(vlist);
        double q3 = calculateQ3(vlist);

        double interQuartileRange = q3 - q1;

        double upperOutlierThreshold = q3 + (interQuartileRange * 1.5);
        double lowerOutlierThreshold = q1 - (interQuartileRange * 1.5);

        double upperFaroutThreshold = q3 + (interQuartileRange * 2.0);
        double lowerFaroutThreshold = q1 - (interQuartileRange * 2.0);

        double minRegularValue = Double.POSITIVE_INFINITY;
        double maxRegularValue = Double.NEGATIVE_INFINITY;
        double minOutlier = Double.POSITIVE_INFINITY;
        double maxOutlier = Double.NEGATIVE_INFINITY;
        List<Number> outliers = new ArrayList<Number>();

        for (Number number : vlist) {
            double value = number.doubleValue();
            if (value > upperOutlierThreshold) {
                outliers.add(number);
                if (value > maxOutlier && value <= upperFaroutThreshold) {
                    maxOutlier = value;
                }
            } else if (value < lowerOutlierThreshold) {
                outliers.add(number);
                if (value < minOutlier && value >= lowerFaroutThreshold) {
                    minOutlier = value;
                }
            } else {
                minRegularValue = Math.min(minRegularValue, value);
                maxRegularValue = Math.max(maxRegularValue, value);
            }
            minOutlier = Math.min(minOutlier, minRegularValue);
            maxOutlier = Math.max(maxOutlier, maxRegularValue);
        }

        return new BoxAndWhiskerItem(mean, median,
                q1, q3, minRegularValue,
                maxRegularValue, minOutlier,
                maxOutlier, outliers);

    }

    /**
     * Calculates the first quartile for a list of numbers in ascending order.
     * If the items in the list are not in ascending order, the result is
     * unspecified.  If the list contains items that are <code>null</code>, not
     * an instance of <code>Number</code>, or equivalent to
     * <code>Double.NaN</code>, the result is unspecified.
     *
     * @param values  the numbers in ascending order (<code>null</code> not
     *     permitted).
     *
     * @return The first quartile.
     */
    public static double calculateQ1(List<Number> values) {
        if (values == null) {
            throw new IllegalArgumentException("Null 'values' argument.");
        }

        double result = Double.NaN;
        int count = values.size();
        if (count > 0) {
            if (count % 2 == 1) {
                if (count > 1) {
                    result = Statistics.calculateMedian(values, 0, count / 2);
                }
                else {
                    result = Statistics.calculateMedian(values, 0, 0);
                }
            }
            else {
                result = Statistics.calculateMedian(values, 0, count / 2 - 1);
            }

        }
        return result;
    }

    /**
     * Calculates the third quartile for a list of numbers in ascending order.
     * If the items in the list are not in ascending order, the result is
     * unspecified.  If the list contains items that are <code>null</code>, not
     * an instance of <code>Number</code>, or equivalent to
     * <code>Double.NaN</code>, the result is unspecified.
     *
     * @param values  the list of values (<code>null</code> not permitted).
     *
     * @return The third quartile.
     */
    public static double calculateQ3(List<Number> values) {
        if (values == null) {
            throw new IllegalArgumentException("Null 'values' argument.");
        }
        double result = Double.NaN;
        int count = values.size();
        if (count > 0) {
            if (count % 2 == 1) {
                if (count > 1) {
                    result = Statistics.calculateMedian(values, count / 2,
                            count - 1);
                }
                else {
                    result = Statistics.calculateMedian(values, 0, 0);
                }
            }
            else {
                result = Statistics.calculateMedian(values, count / 2,
                        count - 1);
            }
        }
        return result;
    }

}
