001/* ===========================================================
002 * JFreeChart : a free chart library for the Java(tm) platform
003 * ===========================================================
004 *
005 * (C) Copyright 2000-present, by David Gilbert 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 * MovingAverage.java
029 * ------------------
030 * (C) Copyright 2003-present, by David Gilbert.
031 *
032 * Original Author:  David Gilbert;
033 * Contributor(s):   Benoit Xhenseval;
034 *
035 */
036
037package org.jfree.data.time;
038
039import org.jfree.chart.util.Args;
040import org.jfree.data.xy.XYDataset;
041import org.jfree.data.xy.XYSeries;
042import org.jfree.data.xy.XYSeriesCollection;
043
044/**
045 * A utility class for calculating moving averages of time series data.
046 */
047public class MovingAverage {
048
049    /**
050     * Creates a new {@link TimeSeriesCollection} containing a moving average
051     * series for each series in the source collection.
052     *
053     * @param source  the source collection.
054     * @param suffix  the suffix added to each source series name to create the
055     *                corresponding moving average series name.
056     * @param periodCount  the number of periods in the moving average
057     *                     calculation.
058     * @param skip  the number of initial periods to skip.
059     *
060     * @return A collection of moving average time series.
061     */
062    public static TimeSeriesCollection createMovingAverage(
063            TimeSeriesCollection source, String suffix, int periodCount,
064            int skip) {
065
066        Args.nullNotPermitted(source, "source");
067        if (periodCount < 1) {
068            throw new IllegalArgumentException("periodCount must be greater "
069                    + "than or equal to 1.");
070        }
071
072        TimeSeriesCollection result = new TimeSeriesCollection();
073        for (int i = 0; i < source.getSeriesCount(); i++) {
074            TimeSeries sourceSeries = source.getSeries(i);
075            TimeSeries maSeries = createMovingAverage(sourceSeries,
076                    sourceSeries.getKey() + suffix, periodCount, skip);
077            result.addSeries(maSeries);
078        }
079        return result;
080
081    }
082
083    /**
084     * Creates a new {@link TimeSeries} containing moving average values for
085     * the given series.  If the series is empty (contains zero items), the
086     * result is an empty series.
087     *
088     * @param source  the source series.
089     * @param name  the name of the new series.
090     * @param periodCount  the number of periods used in the average
091     *                     calculation.
092     * @param skip  the number of initial periods to skip.
093     *
094     * @return The moving average series.
095     */
096    public static TimeSeries createMovingAverage(TimeSeries source,
097            String name, int periodCount, int skip) {
098
099        Args.nullNotPermitted(source, "source");
100        if (periodCount < 1) {
101            throw new IllegalArgumentException("periodCount must be greater " 
102                    + "than or equal to 1.");
103        }
104
105        TimeSeries result = new TimeSeries(name);
106
107        if (source.getItemCount() > 0) {
108
109            // if the initial averaging period is to be excluded, then
110            // calculate the index of the
111            // first data item to have an average calculated...
112            long firstSerial = source.getTimePeriod(0).getSerialIndex() + skip;
113
114            for (int i = source.getItemCount() - 1; i >= 0; i--) {
115
116                // get the current data item...
117                RegularTimePeriod period = source.getTimePeriod(i);
118                long serial = period.getSerialIndex();
119
120                if (serial >= firstSerial) {
121                    // work out the average for the earlier values...
122                    int n = 0;
123                    double sum = 0.0;
124                    long serialLimit = period.getSerialIndex() - periodCount;
125                    int offset = 0;
126                    boolean finished = false;
127
128                    while ((offset < periodCount) && (!finished)) {
129                        if ((i - offset) >= 0) {
130                            TimeSeriesDataItem item = source.getRawDataItem(
131                                    i - offset);
132                            RegularTimePeriod p = item.getPeriod();
133                            Number v = item.getValue();
134                            long currentIndex = p.getSerialIndex();
135                            if (currentIndex > serialLimit) {
136                                if (v != null) {
137                                    sum = sum + v.doubleValue();
138                                    n = n + 1;
139                                }
140                            }
141                            else {
142                                finished = true;
143                            }
144                        }
145                        offset = offset + 1;
146                    }
147                    if (n > 0) {
148                        result.add(period, sum / n);
149                    }
150                    else {
151                        result.add(period, null);
152                    }
153                }
154
155            }
156        }
157
158        return result;
159
160    }
161
162    /**
163     * Creates a new {@link TimeSeries} containing moving average values for
164     * the given series, calculated by number of points (irrespective of the
165     * 'age' of those points).  If the series is empty (contains zero items),
166     * the result is an empty series.
167     * <p>
168     * Developed by Benoit Xhenseval (www.ObjectLab.co.uk).
169     *
170     * @param source  the source series.
171     * @param name  the name of the new series.
172     * @param pointCount  the number of POINTS used in the average calculation
173     *                    (not periods!)
174     *
175     * @return The moving average series.
176     */
177    public static TimeSeries createPointMovingAverage(TimeSeries source,
178            String name, int pointCount) {
179
180        Args.nullNotPermitted(source, "source");
181        if (pointCount < 2) {
182            throw new IllegalArgumentException("periodCount must be greater " 
183                    + "than or equal to 2.");
184        }
185
186        TimeSeries result = new TimeSeries(name);
187        double rollingSumForPeriod = 0.0;
188        for (int i = 0; i < source.getItemCount(); i++) {
189            // get the current data item...
190            TimeSeriesDataItem current = source.getRawDataItem(i);
191            RegularTimePeriod period = current.getPeriod();
192            // FIXME: what if value is null on next line?
193            rollingSumForPeriod += current.getValue().doubleValue();
194
195            if (i > pointCount - 1) {
196                // remove the point i-periodCount out of the rolling sum.
197                TimeSeriesDataItem startOfMovingAvg = source.getRawDataItem(
198                        i - pointCount);
199                rollingSumForPeriod -= startOfMovingAvg.getValue()
200                        .doubleValue();
201                result.add(period, rollingSumForPeriod / pointCount);
202            }
203            else if (i == pointCount - 1) {
204                result.add(period, rollingSumForPeriod / pointCount);
205            }
206        }
207        return result;
208    }
209
210    /**
211     * Creates a new {@link XYDataset} containing the moving averages of each
212     * series in the {@code source} dataset.
213     *
214     * @param source  the source dataset.
215     * @param suffix  the string to append to source series names to create
216     *                target series names.
217     * @param period  the averaging period.
218     * @param skip  the length of the initial skip period.
219     *
220     * @return The dataset.
221     */
222    public static XYDataset createMovingAverage(XYDataset source, String suffix,
223            long period, long skip) {
224
225        return createMovingAverage(source, suffix, (double) period,
226                (double) skip);
227
228    }
229
230
231    /**
232     * Creates a new {@link XYDataset} containing the moving averages of each
233     * series in the {@code source} dataset.
234     *
235     * @param source  the source dataset.
236     * @param suffix  the string to append to source series names to create
237     *                target series names.
238     * @param period  the averaging period.
239     * @param skip  the length of the initial skip period.
240     *
241     * @return The dataset.
242     */
243    public static XYDataset createMovingAverage(XYDataset source,
244            String suffix, double period, double skip) {
245
246        Args.nullNotPermitted(source, "source");
247        XYSeriesCollection result = new XYSeriesCollection();
248        for (int i = 0; i < source.getSeriesCount(); i++) {
249            XYSeries s = createMovingAverage(source, i, source.getSeriesKey(i)
250                    + suffix, period, skip);
251            result.addSeries(s);
252        }
253        return result;
254    }
255
256    /**
257     * Creates a new {@link XYSeries} containing the moving averages of one
258     * series in the {@code source} dataset.
259     *
260     * @param source  the source dataset.
261     * @param series  the series index (zero based).
262     * @param name  the name for the new series.
263     * @param period  the averaging period.
264     * @param skip  the length of the initial skip period.
265     *
266     * @return The dataset.
267     */
268    public static XYSeries createMovingAverage(XYDataset source,
269            int series, String name, double period, double skip) {
270
271        Args.nullNotPermitted(source, "source");
272        if (period < Double.MIN_VALUE) {
273            throw new IllegalArgumentException("period must be positive.");
274        }
275        if (skip < 0.0) {
276            throw new IllegalArgumentException("skip must be >= 0.0.");
277        }
278
279        XYSeries result = new XYSeries(name);
280
281        if (source.getItemCount(series) > 0) {
282
283            // if the initial averaging period is to be excluded, then
284            // calculate the lowest x-value to have an average calculated...
285            double first = source.getXValue(series, 0) + skip;
286
287            for (int i = source.getItemCount(series) - 1; i >= 0; i--) {
288
289                // get the current data item...
290                double x = source.getXValue(series, i);
291
292                if (x >= first) {
293                    // work out the average for the earlier values...
294                    int n = 0;
295                    double sum = 0.0;
296                    double limit = x - period;
297                    int offset = 0;
298                    boolean finished = false;
299
300                    while (!finished) {
301                        if ((i - offset) >= 0) {
302                            double xx = source.getXValue(series, i - offset);
303                            Number yy = source.getY(series, i - offset);
304                            if (xx > limit) {
305                                if (yy != null) {
306                                    sum = sum + yy.doubleValue();
307                                    n = n + 1;
308                                }
309                            }
310                            else {
311                                finished = true;
312                            }
313                        }
314                        else {
315                            finished = true;
316                        }
317                        offset = offset + 1;
318                    }
319                    if (n > 0) {
320                        result.add(x, sum / n);
321                    }
322                    else {
323                        result.add(x, null);
324                    }
325                }
326
327            }
328        }
329
330        return result;
331
332    }
333
334}