001/* ===========================================================
002 * JFreeChart : a free chart library for the Java(tm) platform
003 * ===========================================================
004 *
005 * (C) Copyright 2000-2014, by Object Refinery Limited and Contributors.
006 *
007 * Project Info:  http://www.jfree.org/jfreechart/index.html
008 *
009 * This library is free software; you can redistribute it and/or modify it
010 * under the terms of the GNU Lesser General Public License as published by
011 * the Free Software Foundation; either version 2.1 of the License, or
012 * (at your option) any later version.
013 *
014 * This library is distributed in the hope that it will be useful, but
015 * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
016 * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public
017 * License for more details.
018 *
019 * You should have received a copy of the GNU Lesser General Public
020 * License along with this library; if not, write to the Free Software
021 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301,
022 * USA.
023 *
024 * [Oracle and Java are registered trademarks of Oracle and/or its affiliates. 
025 * Other names may be trademarks of their respective owners.]
026 *
027 * ---------------
028 * Statistics.java
029 * ---------------
030 * (C) Copyright 2000-2014, by Matthew Wright and Contributors.
031 *
032 * Original Author:  Matthew Wright;
033 * Contributor(s):   David Gilbert (for Object Refinery Limited);
034 *
035 * Changes (from 08-Nov-2001)
036 * --------------------------
037 * 08-Nov-2001 : Added standard header and tidied Javadoc comments (DG);
038 *               Moved from JFreeChart to package com.jrefinery.data.* in
039 *               JCommon class library (DG);
040 * 24-Jun-2002 : Removed unnecessary local variable (DG);
041 * 07-Oct-2002 : Fixed errors reported by Checkstyle (DG);
042 * 26-May-2004 : Moved calculateMean() method from BoxAndWhiskerCalculator (DG);
043 * 02-Jun-2004 : Fixed bug in calculateMedian() method (DG);
044 * 11-Jan-2005 : Removed deprecated code in preparation for the 1.0.0
045 *               release (DG);
046 * 02-Jul-2013 : Use ParamChecks (DG);
047 *
048 */
049
050package org.jfree.data.statistics;
051
052import java.util.ArrayList;
053import java.util.Collection;
054import java.util.Collections;
055import java.util.Iterator;
056import java.util.List;
057import org.jfree.chart.util.ParamChecks;
058
059/**
060 * A utility class that provides some common statistical functions.
061 */
062public abstract class Statistics {
063
064    /**
065     * Returns the mean of an array of numbers.  This is equivalent to calling
066     * {@code calculateMean(values, true)}.
067     *
068     * @param values  the values ({@code null} not permitted).
069     *
070     * @return The mean.
071     */
072    public static double calculateMean(Number[] values) {
073        return calculateMean(values, true);
074    }
075
076    /**
077     * Returns the mean of an array of numbers.
078     *
079     * @param values  the values ({@code null} not permitted).
080     * @param includeNullAndNaN  a flag that controls whether or not
081     *     {@code null} and {@code Double.NaN} values are included
082     *     in the calculation (if either is present in the array, the result is
083     *     {@link Double#NaN}).
084     *
085     * @return The mean.
086     *
087     * @since 1.0.3
088     */
089    public static double calculateMean(Number[] values,
090            boolean includeNullAndNaN) {
091
092        ParamChecks.nullNotPermitted(values, "values");
093        double sum = 0.0;
094        double current;
095        int counter = 0;
096        for (int i = 0; i < values.length; i++) {
097            // treat nulls the same as NaNs
098            if (values[i] != null) {
099                current = values[i].doubleValue();
100            }
101            else {
102                current = Double.NaN;
103            }
104            // calculate the sum and count
105            if (includeNullAndNaN || !Double.isNaN(current)) {
106                sum = sum + current;
107                counter++;
108            }
109        }
110        double result = (sum / counter);
111        return result;
112    }
113
114    /**
115     * Returns the mean of a collection of {@code Number} objects.
116     *
117     * @param values  the values ({@code null} not permitted).
118     *
119     * @return The mean.
120     */
121    public static double calculateMean(Collection values) {
122        return calculateMean(values, true);
123    }
124
125    /**
126     * Returns the mean of a collection of {@code Number} objects.
127     *
128     * @param values  the values ({@code null} not permitted).
129     * @param includeNullAndNaN  a flag that controls whether or not
130     *     {@code null} and {@code Double.NaN} values are included
131     *     in the calculation (if either is present in the array, the result is
132     *     {@link Double#NaN}).
133     *
134     * @return The mean.
135     *
136     * @since 1.0.3
137     */
138    public static double calculateMean(Collection values,
139            boolean includeNullAndNaN) {
140
141        ParamChecks.nullNotPermitted(values, "values");
142        int count = 0;
143        double total = 0.0;
144        Iterator iterator = values.iterator();
145        while (iterator.hasNext()) {
146            Object object = iterator.next();
147            if (object == null) {
148                if (includeNullAndNaN) {
149                    return Double.NaN;
150                }
151            }
152            else {
153                if (object instanceof Number) {
154                    Number number = (Number) object;
155                    double value = number.doubleValue();
156                    if (Double.isNaN(value)) {
157                        if (includeNullAndNaN) {
158                            return Double.NaN;
159                        }
160                    }
161                    else {
162                        total = total + number.doubleValue();
163                        count = count + 1;
164                    }
165                }
166            }
167        }
168        return total / count;
169    }
170
171    /**
172     * Calculates the median for a list of values ({@code Number} objects).
173     * The list of values will be copied, and the copy sorted, before
174     * calculating the median.  To avoid this step (if your list of values
175     * is already sorted), use the {@link #calculateMedian(List, boolean)}
176     * method.
177     *
178     * @param values  the values ({@code null} permitted).
179     *
180     * @return The median.
181     */
182    public static double calculateMedian(List values) {
183        return calculateMedian(values, true);
184    }
185
186    /**
187     * Calculates the median for a list of values ({@code Number} objects).
188     * If {@code copyAndSort} is {@code false}, the list is assumed
189     * to be presorted in ascending order by value.
190     *
191     * @param values  the values ({@code null} permitted).
192     * @param copyAndSort  a flag that controls whether the list of values is
193     *                     copied and sorted.
194     *
195     * @return The median.
196     */
197    public static double calculateMedian(List values, boolean copyAndSort) {
198
199        double result = Double.NaN;
200        if (values != null) {
201            if (copyAndSort) {
202                int itemCount = values.size();
203                List copy = new ArrayList(itemCount);
204                for (int i = 0; i < itemCount; i++) {
205                    copy.add(i, values.get(i));
206                }
207                Collections.sort(copy);
208                values = copy;
209            }
210            int count = values.size();
211            if (count > 0) {
212                if (count % 2 == 1) {
213                    if (count > 1) {
214                        Number value = (Number) values.get((count - 1) / 2);
215                        result = value.doubleValue();
216                    }
217                    else {
218                        Number value = (Number) values.get(0);
219                        result = value.doubleValue();
220                    }
221                }
222                else {
223                    Number value1 = (Number) values.get(count / 2 - 1);
224                    Number value2 = (Number) values.get(count / 2);
225                    result = (value1.doubleValue() + value2.doubleValue())
226                             / 2.0;
227                }
228            }
229        }
230        return result;
231    }
232
233    /**
234     * Calculates the median for a sublist within a list of values
235     * ({@code Number} objects).
236     *
237     * @param values  the values, in any order ({@code null} not permitted).
238     * @param start  the start index.
239     * @param end  the end index.
240     *
241     * @return The median.
242     */
243    public static double calculateMedian(List values, int start, int end) {
244        return calculateMedian(values, start, end, true);
245    }
246
247    /**
248     * Calculates the median for a sublist within a list of values
249     * ({@code Number} objects).  The entire list will be sorted if the
250     * {@code ascending} argument is {@code false}.
251     *
252     * @param values  the values ({@code null} not permitted).
253     * @param start  the start index.
254     * @param end  the end index.
255     * @param copyAndSort  a flag that that controls whether the list of values
256     *                     is copied and sorted.
257     *
258     * @return The median.
259     */
260    public static double calculateMedian(List values, int start, int end,
261                                         boolean copyAndSort) {
262
263        double result = Double.NaN;
264        if (copyAndSort) {
265            List working = new ArrayList(end - start + 1);
266            for (int i = start; i <= end; i++) {
267                working.add(values.get(i));
268            }
269            Collections.sort(working);
270            result = calculateMedian(working, false);
271        }
272        else {
273            int count = end - start + 1;
274            if (count > 0) {
275                if (count % 2 == 1) {
276                    if (count > 1) {
277                        Number value
278                            = (Number) values.get(start + (count - 1) / 2);
279                        result = value.doubleValue();
280                    }
281                    else {
282                        Number value = (Number) values.get(start);
283                        result = value.doubleValue();
284                    }
285                }
286                else {
287                    Number value1 = (Number) values.get(start + count / 2 - 1);
288                    Number value2 = (Number) values.get(start + count / 2);
289                    result
290                        = (value1.doubleValue() + value2.doubleValue()) / 2.0;
291                }
292            }
293        }
294        return result;
295
296    }
297
298    /**
299     * Returns the standard deviation of a set of numbers.
300     *
301     * @param data  the data ({@code null} or zero length array not
302     *     permitted).
303     *
304     * @return The standard deviation of a set of numbers.
305     */
306    public static double getStdDev(Number[] data) {
307        ParamChecks.nullNotPermitted(data, "data");
308        if (data.length == 0) {
309            throw new IllegalArgumentException("Zero length 'data' array.");
310        }
311        double avg = calculateMean(data);
312        double sum = 0.0;
313
314        for (int counter = 0; counter < data.length; counter++) {
315            double diff = data[counter].doubleValue() - avg;
316            sum = sum + diff * diff;
317        }
318        return Math.sqrt(sum / (data.length - 1));
319    }
320
321    /**
322     * Fits a straight line to a set of (x, y) data, returning the slope and
323     * intercept.
324     *
325     * @param xData  the x-data ({@code null} not permitted).
326     * @param yData  the y-data ({@code null} not permitted).
327     *
328     * @return A double array with the intercept in [0] and the slope in [1].
329     */
330    public static double[] getLinearFit(Number[] xData, Number[] yData) {
331
332        ParamChecks.nullNotPermitted(xData, "xData");
333        ParamChecks.nullNotPermitted(yData, "yData");
334        if (xData.length != yData.length) {
335            throw new IllegalArgumentException(
336                "Statistics.getLinearFit(): array lengths must be equal.");
337        }
338
339        double[] result = new double[2];
340        // slope
341        result[1] = getSlope(xData, yData);
342        // intercept
343        result[0] = calculateMean(yData) - result[1] * calculateMean(xData);
344
345        return result;
346
347    }
348
349    /**
350     * Finds the slope of a regression line using least squares.
351     *
352     * @param xData  the x-values ({@code null} not permitted).
353     * @param yData  the y-values ({@code null} not permitted).
354     *
355     * @return The slope.
356     */
357    public static double getSlope(Number[] xData, Number[] yData) {
358        ParamChecks.nullNotPermitted(xData, "xData");
359        ParamChecks.nullNotPermitted(yData, "yData");
360        if (xData.length != yData.length) {
361            throw new IllegalArgumentException("Array lengths must be equal.");
362        }
363
364        // ********* stat function for linear slope ********
365        // y = a + bx
366        // a = ybar - b * xbar
367        //     sum(x * y) - (sum (x) * sum(y)) / n
368        // b = ------------------------------------
369        //     sum (x^2) - (sum(x)^2 / n
370        // *************************************************
371
372        // sum of x, x^2, x * y, y
373        double sx = 0.0, sxx = 0.0, sxy = 0.0, sy = 0.0;
374        int counter;
375        for (counter = 0; counter < xData.length; counter++) {
376            sx = sx + xData[counter].doubleValue();
377            sxx = sxx + Math.pow(xData[counter].doubleValue(), 2);
378            sxy = sxy + yData[counter].doubleValue()
379                      * xData[counter].doubleValue();
380            sy = sy + yData[counter].doubleValue();
381        }
382        return (sxy - (sx * sy) / counter) / (sxx - (sx * sx) / counter);
383
384    }
385
386    /**
387     * Calculates the correlation between two datasets.  Both arrays should
388     * contain the same number of items.  Null values are treated as zero.
389     * <P>
390     * Information about the correlation calculation was obtained from:
391     *
392     * http://trochim.human.cornell.edu/kb/statcorr.htm
393     *
394     * @param data1  the first dataset.
395     * @param data2  the second dataset.
396     *
397     * @return The correlation.
398     */
399    public static double getCorrelation(Number[] data1, Number[] data2) {
400        ParamChecks.nullNotPermitted(data1, "data1");
401        ParamChecks.nullNotPermitted(data2, "data2");
402        if (data1.length != data2.length) {
403            throw new IllegalArgumentException(
404                "'data1' and 'data2' arrays must have same length."
405            );
406        }
407        int n = data1.length;
408        double sumX = 0.0;
409        double sumY = 0.0;
410        double sumX2 = 0.0;
411        double sumY2 = 0.0;
412        double sumXY = 0.0;
413        for (int i = 0; i < n; i++) {
414            double x = 0.0;
415            if (data1[i] != null) {
416                x = data1[i].doubleValue();
417            }
418            double y = 0.0;
419            if (data2[i] != null) {
420                y = data2[i].doubleValue();
421            }
422            sumX = sumX + x;
423            sumY = sumY + y;
424            sumXY = sumXY + (x * y);
425            sumX2 = sumX2 + (x * x);
426            sumY2 = sumY2 + (y * y);
427        }
428        return (n * sumXY - sumX * sumY) / Math.pow((n * sumX2 - sumX * sumX)
429                * (n * sumY2 - sumY * sumY), 0.5);
430    }
431
432    /**
433     * Returns a data set for a moving average on the data set passed in.
434     *
435     * @param xData  an array of the x data.
436     * @param yData  an array of the y data.
437     * @param period  the number of data points to average
438     *
439     * @return A double[][] the length of the data set in the first dimension,
440     *         with two doubles for x and y in the second dimension
441     */
442    public static double[][] getMovingAverage(Number[] xData, Number[] yData,
443            int period) {
444
445        // check arguments...
446        if (xData.length != yData.length) {
447            throw new IllegalArgumentException("Array lengths must be equal.");
448        }
449
450        if (period > xData.length) {
451            throw new IllegalArgumentException(
452                "Period can't be longer than dataset.");
453        }
454
455        double[][] result = new double[xData.length - period][2];
456        for (int i = 0; i < result.length; i++) {
457            result[i][0] = xData[i + period].doubleValue();
458            // holds the moving average sum
459            double sum = 0.0;
460            for (int j = 0; j < period; j++) {
461                sum += yData[i + j].doubleValue();
462            }
463            sum = sum / period;
464            result[i][1] = sum;
465        }
466        return result;
467
468    }
469
470}