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JFreeChart is a class library, written in Java, for generating charts. Utilising the Java2D APIs, it currently supports bar charts, pie charts, line charts, XY-plots and time series plots.

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/* ===========================================================
 * JFreeChart : a free chart library for the Java(tm) platform
 * ===========================================================
 *
 * (C) Copyright 2000-2013, 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.]
 *
 * ----------------------------------
 * DefaultBoxAndWhiskerXYDataset.java
 * ----------------------------------
 * (C) Copyright 2003-2008, by David Browning and Contributors.
 *
 * Original Author:  David Browning (for Australian Institute of Marine
 *                   Science);
 * Contributor(s):   David Gilbert (for Object Refinery Limited);
 *
 * Changes
 * -------
 * 05-Aug-2003 : Version 1, contributed by David Browning (DG);
 * 08-Aug-2003 : Minor changes to comments (DB)
 *               Allow average to be null  - average is a perculiar AIMS
 *               requirement which probably should be stripped out and overlaid
 *               if required...
 *               Added a number of methods to allow the max and min non-outlier
 *               and non-farout values to be calculated
 * 12-Aug-2003   Changed the getYValue to return the highest outlier value
 *               Added getters and setters for outlier and farout coefficients
 * 27-Aug-2003 : Renamed DefaultBoxAndWhiskerDataset
 *               --> DefaultBoxAndWhiskerXYDataset (DG);
 * 06-May-2004 : Now extends AbstractXYDataset (DG);
 * 15-Jul-2004 : Switched getX() with getXValue() and getY() with
 *               getYValue() (DG);
 * 18-Nov-2004 : Updated for changes in RangeInfo interface (DG);
 * 11-Jan-2005 : Removed deprecated code in preparation for the 1.0.0
 *               release (DG);
 * ------------- JFREECHART 1.0.x ---------------------------------------------
 * 02-Feb-2007 : Removed author tags from all over JFreeChart sources (DG);
 * 12-Nov-2007 : Implemented equals() and clone() (DG);
 *
 */

package org.jfree.data.statistics;

import java.util.ArrayList;
import java.util.Date;
import java.util.List;

import org.jfree.data.Range;
import org.jfree.data.RangeInfo;
import org.jfree.data.general.DatasetChangeEvent;
import org.jfree.data.xy.AbstractXYDataset;
import org.jfree.util.ObjectUtilities;

/**
 * A simple implementation of the {@link BoxAndWhiskerXYDataset} interface.
 * This dataset implementation can hold only one series.
 */
public class DefaultBoxAndWhiskerXYDataset extends AbstractXYDataset
            implements BoxAndWhiskerXYDataset, RangeInfo {

    /** The series key. */
    private Comparable seriesKey;

    /** Storage for the dates. */
    private List dates;

    /** Storage for the box and whisker statistics. */
    private List items;

    /** The minimum range value. */
    private Number minimumRangeValue;

    /** The maximum range value. */
    private Number maximumRangeValue;

    /** The range of values. */
    private Range rangeBounds;

    /**
     * The coefficient used to calculate outliers. Tukey's default value is
     * 1.5 (see EDA) Any value which is greater than Q3 + (interquartile range
     * * outlier coefficient) is considered to be an outlier.  Can be altered
     * if the data is particularly skewed.
     */
    private double outlierCoefficient = 1.5;

    /**
     * The coefficient used to calculate farouts. Tukey's default value is 2
     * (see EDA) Any value which is greater than Q3 + (interquartile range *
     * farout coefficient) is considered to be a farout.  Can be altered if the
     * data is particularly skewed.
     */
    private double faroutCoefficient = 2.0;

    /**
     * Constructs a new box and whisker dataset.
     * 

* The current implementation allows only one series in the dataset. * This may be extended in a future version. * * @param seriesKey the key for the series. */ public DefaultBoxAndWhiskerXYDataset(Comparable seriesKey) { this.seriesKey = seriesKey; this.dates = new ArrayList(); this.items = new ArrayList(); this.minimumRangeValue = null; this.maximumRangeValue = null; this.rangeBounds = null; } /** * Returns the value used as the outlier coefficient. The outlier * coefficient gives an indication of the degree of certainty in an * unskewed distribution. Increasing the coefficient increases the number * of values included. Currently only used to ensure farout coefficient is * greater than the outlier coefficient * * @return A double representing the value used to calculate * outliers. * * @see #setOutlierCoefficient(double) */ @Override public double getOutlierCoefficient() { return this.outlierCoefficient; } /** * Sets the value used as the outlier coefficient * * @param outlierCoefficient being a double representing the * value used to calculate outliers. * * @see #getOutlierCoefficient() */ public void setOutlierCoefficient(double outlierCoefficient) { this.outlierCoefficient = outlierCoefficient; } /** * Returns the value used as the farout coefficient. The farout coefficient * allows the calculation of which values will be off the graph. * * @return A double representing the value used to calculate * farouts. * * @see #setFaroutCoefficient(double) */ @Override public double getFaroutCoefficient() { return this.faroutCoefficient; } /** * Sets the value used as the farouts coefficient. The farout coefficient * must b greater than the outlier coefficient. * * @param faroutCoefficient being a double representing the * value used to calculate farouts. * * @see #getFaroutCoefficient() */ public void setFaroutCoefficient(double faroutCoefficient) { if (faroutCoefficient > getOutlierCoefficient()) { this.faroutCoefficient = faroutCoefficient; } else { throw new IllegalArgumentException("Farout value must be greater " + "than the outlier value, which is currently set at: (" + getOutlierCoefficient() + ")"); } } /** * Returns the number of series in the dataset. *

* This implementation only allows one series. * * @return The number of series. */ @Override public int getSeriesCount() { return 1; } /** * Returns the number of items in the specified series. * * @param series the index (zero-based) of the series. * * @return The number of items in the specified series. */ @Override public int getItemCount(int series) { return this.dates.size(); } /** * Adds an item to the dataset and sends a {@link DatasetChangeEvent} to * all registered listeners. * * @param date the date (null not permitted). * @param item the item (null not permitted). */ public void add(Date date, BoxAndWhiskerItem item) { this.dates.add(date); this.items.add(item); if (this.minimumRangeValue == null) { this.minimumRangeValue = item.getMinRegularValue(); } else { if (item.getMinRegularValue().doubleValue() < this.minimumRangeValue.doubleValue()) { this.minimumRangeValue = item.getMinRegularValue(); } } if (this.maximumRangeValue == null) { this.maximumRangeValue = item.getMaxRegularValue(); } else { if (item.getMaxRegularValue().doubleValue() > this.maximumRangeValue.doubleValue()) { this.maximumRangeValue = item.getMaxRegularValue(); } } this.rangeBounds = new Range(this.minimumRangeValue.doubleValue(), this.maximumRangeValue.doubleValue()); fireDatasetChanged(); } /** * Returns the name of the series stored in this dataset. * * @param i the index of the series. Currently ignored. * * @return The name of this series. */ @Override public Comparable getSeriesKey(int i) { return this.seriesKey; } /** * Return an item from within the dataset. * * @param series the series index (ignored, since this dataset contains * only one series). * @param item the item within the series (zero-based index) * * @return The item. */ public BoxAndWhiskerItem getItem(int series, int item) { return (BoxAndWhiskerItem) this.items.get(item); } /** * Returns the x-value for one item in a series. *

* The value returned is a Long object generated from the underlying Date * object. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The x-value. */ @Override public Number getX(int series, int item) { return new Long(((Date) this.dates.get(item)).getTime()); } /** * Returns the x-value for one item in a series, as a Date. *

* This method is provided for convenience only. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The x-value as a Date. */ public Date getXDate(int series, int item) { return (Date) this.dates.get(item); } /** * Returns the y-value for one item in a series. *

* This method (from the XYDataset interface) is mapped to the * getMeanValue() method. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The y-value. */ @Override public Number getY(int series, int item) { return getMeanValue(series, item); } /** * Returns the mean for the specified series and item. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The mean for the specified series and item. */ @Override public Number getMeanValue(int series, int item) { Number result = null; BoxAndWhiskerItem stats = (BoxAndWhiskerItem) this.items.get(item); if (stats != null) { result = stats.getMean(); } return result; } /** * Returns the median-value for the specified series and item. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The median-value for the specified series and item. */ @Override public Number getMedianValue(int series, int item) { Number result = null; BoxAndWhiskerItem stats = (BoxAndWhiskerItem) this.items.get(item); if (stats != null) { result = stats.getMedian(); } return result; } /** * Returns the Q1 median-value for the specified series and item. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The Q1 median-value for the specified series and item. */ @Override public Number getQ1Value(int series, int item) { Number result = null; BoxAndWhiskerItem stats = (BoxAndWhiskerItem) this.items.get(item); if (stats != null) { result = stats.getQ1(); } return result; } /** * Returns the Q3 median-value for the specified series and item. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The Q3 median-value for the specified series and item. */ @Override public Number getQ3Value(int series, int item) { Number result = null; BoxAndWhiskerItem stats = (BoxAndWhiskerItem) this.items.get(item); if (stats != null) { result = stats.getQ3(); } return result; } /** * Returns the min-value for the specified series and item. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The min-value for the specified series and item. */ @Override public Number getMinRegularValue(int series, int item) { Number result = null; BoxAndWhiskerItem stats = (BoxAndWhiskerItem) this.items.get(item); if (stats != null) { result = stats.getMinRegularValue(); } return result; } /** * Returns the max-value for the specified series and item. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The max-value for the specified series and item. */ @Override public Number getMaxRegularValue(int series, int item) { Number result = null; BoxAndWhiskerItem stats = (BoxAndWhiskerItem) this.items.get(item); if (stats != null) { result = stats.getMaxRegularValue(); } return result; } /** * Returns the minimum value which is not a farout. * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return A Number representing the maximum non-farout value. */ @Override public Number getMinOutlier(int series, int item) { Number result = null; BoxAndWhiskerItem stats = (BoxAndWhiskerItem) this.items.get(item); if (stats != null) { result = stats.getMinOutlier(); } return result; } /** * Returns the maximum value which is not a farout, ie Q3 + (interquartile * range * farout coefficient). * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return A Number representing the maximum non-farout value. */ @Override public Number getMaxOutlier(int series, int item) { Number result = null; BoxAndWhiskerItem stats = (BoxAndWhiskerItem) this.items.get(item); if (stats != null) { result = stats.getMaxOutlier(); } return result; } /** * Returns a list of outliers for the specified series and item. * * @param series the series (zero-based index). * @param item the item (zero-based index). * * @return The list of outliers for the specified series and item * (possibly null). */ @Override public List getOutliers(int series, int item) { List result = null; BoxAndWhiskerItem stats = (BoxAndWhiskerItem) this.items.get(item); if (stats != null) { result = stats.getOutliers(); } return result; } /** * Returns the minimum y-value in the dataset. * * @param includeInterval a flag that determines whether or not the * y-interval is taken into account. * * @return The minimum value. */ @Override public double getRangeLowerBound(boolean includeInterval) { double result = Double.NaN; if (this.minimumRangeValue != null) { result = this.minimumRangeValue.doubleValue(); } return result; } /** * Returns the maximum y-value in the dataset. * * @param includeInterval a flag that determines whether or not the * y-interval is taken into account. * * @return The maximum value. */ @Override public double getRangeUpperBound(boolean includeInterval) { double result = Double.NaN; if (this.maximumRangeValue != null) { result = this.maximumRangeValue.doubleValue(); } return result; } /** * Returns the range of the values in this dataset's range. * * @param includeInterval a flag that determines whether or not the * y-interval is taken into account. * * @return The range. */ @Override public Range getRangeBounds(boolean includeInterval) { return this.rangeBounds; } /** * Tests this dataset for equality with an arbitrary object. * * @param obj the object (null permitted). * * @return A boolean. */ @Override public boolean equals(Object obj) { if (obj == this) { return true; } if (!(obj instanceof DefaultBoxAndWhiskerXYDataset)) { return false; } DefaultBoxAndWhiskerXYDataset that = (DefaultBoxAndWhiskerXYDataset) obj; if (!ObjectUtilities.equal(this.seriesKey, that.seriesKey)) { return false; } if (!this.dates.equals(that.dates)) { return false; } if (!this.items.equals(that.items)) { return false; } return true; } /** * Returns a clone of the plot. * * @return A clone. * * @throws CloneNotSupportedException if the cloning is not supported. */ @Override public Object clone() throws CloneNotSupportedException { DefaultBoxAndWhiskerXYDataset clone = (DefaultBoxAndWhiskerXYDataset) super.clone(); clone.dates = new java.util.ArrayList(this.dates); clone.items = new java.util.ArrayList(this.items); return clone; } }





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