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TimeSeriesCollection tsc = new TimeSeriesCollection(); tsc.addSeries(createSeries("Projected", 200)); tsc.addSeries(createSeries("Actual", 100)); return tsc; TimeSeries series = new TimeSeries(name); for (int i = 0; i < 6; i++) { series.add(new Year(2005 + i), Math.pow(2, i) * scale);
/** * Reduce a given dataset to only contain a specified number of columns * * @param dataset The dataset to reduce * @param rowKeysToKeep The rows to keep * @return A reduced dataset copy. */ public static TimeSeriesCollection reduceDataset(TimeSeriesCollection dataset, List rowKeysToKeep) { final TimeSeriesCollection newDataSet = new TimeSeriesCollection(); @SuppressWarnings("unchecked") final List<TimeSeries> timeSerieses = new ArrayList<TimeSeries>(dataset.getSeries()); for (TimeSeries timeSeries : timeSerieses) { if (rowKeysToKeep.contains(timeSeries.getKey())) { newDataSet.addSeries(timeSeries); } } return newDataSet; }
/** * Returns a series. * * @param series the index of the series (zero-based). * * @return The series. */ public TimeSeries getSeries(int series) { if ((series < 0) || (series >= getSeriesCount())) { throw new IllegalArgumentException( "The 'series' argument is out of bounds (" + series + ")."); } return (TimeSeries) this.data.get(series); }
/** * Removes a series from the collection. * * @param index the series index (zero-based). */ public void removeSeries(int index) { TimeSeries series = getSeries(index); if (series != null) { removeSeries(series); } }
private XYDataset getResponseDataset( TimeSeries averageSeries, TimeSeries percentileseries ) { TimeSeriesCollection dataset = new TimeSeriesCollection(); dataset.addSeries( averageSeries ); dataset.addSeries( percentileseries ); return dataset; } }
TimeSeriesCollection dataset = new TimeSeriesCollection(); TimeSeries series = new TimeSeries("Basal", Second.class); for (BasalRate basal : pInsulin.basals) { Second lSecond = new Second(basal.getTime()); series.addOrUpdate(lSecond, basal.getValue()); } dataset.addSeries(series);
TimeSeriesCollection otherDataSet = new TimeSeriesCollection(); TimeSeries ts1 = new TimeSeries("Series 1"); otherDataSet.addSeries(ts1); TimeSeries ts2 = new TimeSeries("Series 2"); otherDataSet.addSeries(ts2); TimeSeries ts3 = new TimeSeries("Series 2"); otherDataSet.addSeries(ts3);
/** * Creates a TimeSeriesCollection which represents the cumulative values of a given TimeSeriesCollection. * * @param collection collection * @return TimeSeriesCollection */ public static TimeSeriesCollection makeCumulative(TimeSeriesCollection collection) { TimeSeriesCollection result = new TimeSeriesCollection(); for (int i = 0; i < collection.getSeriesCount(); i++) { TimeSeries oldSeries = collection.getSeries(i); TimeSeries cumulativeSeries = new TimeSeries(oldSeries.getKey(), oldSeries.getTimePeriodClass()); int cumulativeValue = 0; for (int j = 0; j < oldSeries.getItemCount(); j++) { cumulativeValue += oldSeries.getValue(j).intValue(); cumulativeSeries.add(oldSeries.getTimePeriod(j), Integer.valueOf(cumulativeValue)); } result.addSeries(cumulativeSeries); } return result; }
for (int i = 0; i < t.getSeriesCount(); i++) { TimeSeries s = t.getSeries(i); s.add(now, Math.abs(r.nextGaussian())); now = (Day) now.next(); TimeSeriesCollection tsc = new TimeSeriesCollection(); TimeSeries ts = new TimeSeries(title); tsc.addSeries(ts); return tsc;
return null; TimeSeriesCollection dataset = new TimeSeriesCollection(); for (Iterator<String> en = s.keySet().iterator(); en.hasNext();) { String groupName = en.next(); List<TestStepInstance> stps = s.get(groupName); TimeSeries pop = new TimeSeries(groupName); for (Iterator<TestStepInstance> it = stps.iterator(); it.hasNext();) { TestStepInstance step = it.next(); switch (chartMode) { case STEP_TIME: pop.addOrUpdate(RegularTimePeriod.createInstance(Millisecond.class, new Date(step.getStartTime()), TimeZone.getDefault()), num); break; case SEQUENCE_TIME: pop.addOrUpdate(RegularTimePeriod.createInstance(Millisecond.class, new Date(step.getTestSequenceInstance().getCreateTime()), TimeZone.getDefault()), num); break; dataset.addSeries(pop); String groupName = it.next(); Color c = ChartCategories.getColor(i); for (int j = 0; j < dataset.getSeriesCount(); j++) { TimeSeries ts = dataset.getSeries(j); if (ts.getKey().equals(groupName)) { renderer5.setSeriesPaint(j, c);
int sercnt = dataset.getSeriesCount(); Integer sernum = (Integer)seriesmap.get(seriesname); if(sernum!=null) if(seriesname!=null) series = new TimeSeries(seriesname, time); if(maxitemcnt!=null) series.setMaximumItemCount(maxitemcnt.intValue()); seriesmap.put(seriesname, Integer.valueOf(j)); series = new TimeSeries(Integer.valueOf(j), time); if(maxitemcnt!=null) series.setMaximumItemCount(maxitemcnt.intValue()); seriesmap.put(Integer.valueOf(j), Integer.valueOf(j)); dataset.addSeries(series); TimeSeries ser = dataset.getSeries(seriesnum);
TimeSeriesCollection timeSeries = new TimeSeriesCollection(); TimeSeries product1 = new TimeSeries("product1"); new JDBCTemplate("query", params, new ResultSetExtractor<Void>() { public Void extractData(ResultSet rs) throws SQLException { product1.addOrUpdate(new FixedMillisecond(rs.getLong(1)), rs.getDouble(2)); return null; } } <other products to follow>
String seriesKey = getFullText((Element) columnIterator.header()); series = collection.getSeries(seriesKey); if (series == null) { series = new TimeSeries(seriesKey, timePeriodClass); collection.addSeries(series); series.add(RegularTimePeriod.createInstance(timePeriodClass, toDate(key), TimeZone.getDefault()), toNumber(value));
/** * This method adds the specified stream elements to the timeSeries of the * appropriate plot. * * @param streamElement */ public synchronized void addData ( StreamElement streamElement ) { for ( int i = 0 ; i < streamElement.getFieldNames( ).length ; i++ ) { TimeSeries timeSeries = dataForTheChart.get( streamElement.getFieldNames( )[ i ] ); if ( timeSeries == null ) { dataForTheChart.put( streamElement.getFieldNames( )[ i ] , timeSeries = new TimeSeries( streamElement.getFieldNames( )[ i ] , org.jfree.data.time.FixedMillisecond.class ) ); if(isTimeBased){ timeSeries.setMaximumItemAge(historySize); }else{ timeSeries.setMaximumItemCount(historySize); } dataCollectionForTheChart.addSeries( timeSeries ); } try { timeSeries.addOrUpdate( new FixedMillisecond( new Date( streamElement.getTimeStamp( ) ) ) , Double.parseDouble( streamElement.getData( )[ i ].toString( ) ) ); } catch ( SeriesException e ) { logger.warn( e.getMessage( ) , e ); } } changed = true; }
private static TimeSeriesCollection addSubPlot(CombinedDomainXYPlot plot, String label) { final TimeSeriesCollection seriesCollection = new TimeSeriesCollection(new TimeSeries(label, Millisecond.class)); NumberAxis rangeAxis = new NumberAxis(); rangeAxis.setAutoRangeIncludesZero(false); XYPlot subplot = new XYPlot(seriesCollection, null, rangeAxis, new StandardXYItemRenderer()); subplot.setBackgroundPaint(Color.lightGray); subplot.setDomainGridlinePaint(Color.white); subplot.setRangeGridlinePaint(Color.white); plot.add(subplot); return seriesCollection; }
private TimeSeriesCollection createTimeseriesCollection(Data<QuantityValue> referenceData, StyleProperties style) { TimeSeriesCollection timeseriesCollection = new TimeSeriesCollection(); timeseriesCollection.addSeries(createDiscreteTimeseries(referenceData, style)); timeseriesCollection.setGroup(new DatasetGroup(chartId)); return timeseriesCollection; }
private void buildTimeSeries(final Map theDates, final Map theErrors, final boolean withAverage, final List availableTypes, final TimeSeriesCollection series) { final Iterator typeIter = theDates.entrySet().iterator(); final Date max = findMaxDate(theDates); final Calendar cal = Calendar.getInstance(); cal.setTime(max); cal.add(Calendar.HOUR_OF_DAY, NUM_HOURS_BEFORE_LAST_DATE); // no stats over the last 28h final Date zeroDeadline = cal.getTime(); // no stats over the last 28h while (typeIter.hasNext()) { final Map.Entry pairTypeDates = (Map.Entry) typeIter.next(); final String type = (String) pairTypeDates.getKey(); availableTypes.add(type); final TimeSeries ts = new TimeSeries(type, "bla", "bli", FixedMillisecond.class); final List typeDates = (List) pairTypeDates.getValue(); final List typeErrors = (List) theErrors.get(type); if ((typeDates != null) && (typeErrors != null)) { addDataToTimeSeries(zeroDeadline, ts, typeDates, typeErrors); } series.addSeries(ts); if (withAverage && (getMovingAverage() > 0)) { series.addSeries(MovingAverage.createPointMovingAverage(ts, type + " " + getMovingAverage() + "-run Moving Average", getMovingAverage())); } } }
public static void normaliseDateRange(TimeSeriesCollection collection, RegularTimePeriod[] range) { if (collection.getSeriesCount() == 0) return; // find earliest date, then move it forwards until we hit now RegularTimePeriod earliest = range[0]; RegularTimePeriod latest = range[1]; RegularTimePeriod cursor = earliest; for (int i = 0; i < collection.getSeriesCount(); i++) { TimeSeries series = collection.getSeries(i); while (cursor.compareTo(latest) != 1) { if (series.getValue(cursor) == null) series.add(cursor, Integer.valueOf(0)); cursor = cursor.next(); } cursor = earliest; } } }
private static final String titles[] = { "Zone A", "Zone B", "Zone C", "Zone S", "Zone SH", "Zone W"}; private final TimeSeriesCollection all = new TimeSeriesCollection();