List of usage examples for org.jfree.data.time RegularTimePeriod next
public abstract RegularTimePeriod next();
null if some limit has been reached. From source file:info.financialecology.finance.utilities.datastruct.VersatileTimeSeriesCollection.java
/** * Add a new time series to the collection. * <p>/*from w ww. j a v a 2 s . co m*/ * Creates a new {@link VersatileTimeSeries}, populates it with the values from the * {@link DoubleTimeSeries} {@code dts}, and insert it into the collection. * <p> * Uses the parameter {@code startTime} to set the time at which the time series starts. * Use {@code setStartTime()} and {@code overrideStartTime()} to change the start time. * <p> * * @param dts the {@link DoubleTimeSeries} from which we obtain the values to populate the * new time series * @param name the name of the time series variable */ public void add(DoubleTimeSeries dts) { String newKey = dts.getId(); Assertion.assertOrKill(getSeries(newKey) == null, "A time series with the key '" + newKey + "' already exists in the collection"); VersatileTimeSeries vts = new VersatileTimeSeries(newKey); RegularTimePeriod time = internalParams.getStartTime(); for (int t = 0; t < dts.size(); t++) { vts.add(time, dts.getValue(t)); time = time.next(); } addSeries(vts); Assertion.assertOrKill(checkConsistency(), "The time series '" + dts.getId() + "' added to " + "the collection is not consistent with the already existing time series"); }
From source file:info.financialecology.finance.utilities.datastruct.VersatileTimeSeriesCollection.java
/** * Create a new {@link VersatileTimeSeries}, populate it with values of a * {@link DoubleTimeSeries}, and insert into the collection. The run index * has to be provided while the dimension indices are optional. The key of * the new time series is constructed using the <code>name</code> and the * run and dimension indices provided as parameters. * <p>//from w w w . ja v a 2 s . co m * The sequence of the method arguments is a bit of a hack, to facilitate * passing an arbitrary list of dimension indices. * <p> * Uses the internal parameters <code>startTime</code> and <code>indexSeparator</code>. * <p> * @param dts the {@link DoubleTimeSeries} from which we obtain the values to populate the * new time series * @param run the run index * @param name the name of the time series variable * @param indices the dimension indices (may be empty) */ public void populateSeries(int run, String name, DoubleTimeSeries dts, int... indices) { String newKey = name + internalParams.getIndexSeparator(); Assertion.assertStrict(run >= 0, Assertion.Level.ERR, "Run index has to be positive"); for (int i : indices) { Assertion.assertStrict(i >= 0, Assertion.Level.ERR, "Dimension indices have to be positive"); newKey += Integer.toString(i) + internalParams.getIndexSeparator(); } newKey += "r" + Integer.toString(run); VersatileTimeSeries ats = new VersatileTimeSeries(newKey); addSeries(ats); RegularTimePeriod time = internalParams.getStartTime(); for (int i = 0; i < dts.size(); i++) { ats.add(time, dts.getValue(i)); time = time.next(); } }
From source file:info.financialecology.finance.utilities.datastruct.VersatileTimeSeriesCollection.java
/** * Create a new {@link VersatileTimeSeries}, populate it with values of a {@link DoubleTimeSeries}, * and insert into the collection. Experiment and run indices have to be provided while * the dimension indices are optional. The key of the new time series is constructed using * the <code>name</code> and the experiment, run, and dimension indices provided as parameters. * <p>//from w w w. j a v a2s. c om * The sequence of the method arguments is a bit of a hack, to facilitate passing an arbitrary list of * dimension indices. * <p> * Uses the internal parameters <code>startTime</code> and <code>indexSeparator</code>. * <p> * @param dts the {@link DoubleTimeSeries} from which we obtain the values to populate the * new time series * @param exp the experiment index * @param run the run index * @param name the name of the time series variable * @param indices the dimension indices (may be empty) */ public void populateSeries(int exp, int run, String name, DoubleTimeSeries dts, int... indices) { String newKey = name + internalParams.getIndexSeparator(); Assertion.assertStrict((exp >= 0) && (run >= 0), Assertion.Level.ERR, "Run and experiment index have to be positive"); for (int i : indices) { Assertion.assertStrict(i >= 0, Assertion.Level.ERR, "Dimension indices have to be positive"); newKey += Integer.toString(i) + internalParams.getIndexSeparator(); } newKey += "r" + Integer.toString(run) + internalParams.getIndexSeparator() + "e" + Integer.toString(exp); VersatileTimeSeries ats = new VersatileTimeSeries(newKey); addSeries(ats); RegularTimePeriod time = internalParams.getStartTime(); for (int i = 0; i < dts.size(); i++) { ats.add(time, dts.getValue(i)); time = time.next(); } }
From source file:info.financialecology.finance.utilities.datastruct.VersatileTimeSeriesCollection.java
/** * Create a new {@link VersatileTimeSeries}, populate it with values of a {@link DoubleTimeSeries}, * and insert into the collection. Experiment, run, and asset indices have to be provided while * the dimension indices are optional. The key of the new time series is constructed using * the <code>name</code> and the experiment, run, asset, and dimension indices provided as parameters. * <p>//from www . j a va 2 s. c o m * The sequence of the method arguments is a bit of a hack, to facilitate passing an arbitrary list of * dimension indices. * <p> * Uses the internal parameters <code>startTime</code> and <code>indexSeparator</code>. * <p> * @param dts the {@link DoubleTimeSeries} from which we obtain the values to populate the * new time series * @param exp the experiment index * @param run the run index * @param assset the asset index * @param name the name of the time series variable * @param indices the dimension indices (may be empty) */ public void populateSeries(int exp, int run, String secId, String name, DoubleTimeSeries dts, int... indices) { String newKey = name + internalParams.getIndexSeparator(); Assertion.assertStrict((exp >= 0) && (run >= 0), Assertion.Level.ERR, "Run and experiment index have to be positive"); for (int i : indices) { Assertion.assertStrict(i >= 0, Assertion.Level.ERR, "Dimension indices have to be positive"); newKey += Integer.toString(i) + internalParams.getIndexSeparator(); } newKey += secId + internalParams.getIndexSeparator() + "r" + Integer.toString(run) + internalParams.getIndexSeparator() + "e" + Integer.toString(exp); VersatileTimeSeries ats = new VersatileTimeSeries(newKey); addSeries(ats); RegularTimePeriod time = internalParams.getStartTime(); for (int i = 0; i < dts.size(); i++) { ats.add(time, dts.getValue(i)); time = time.next(); } }
From source file:info.financialecology.finance.utilities.datastruct.VersatileTimeSeriesCollection.java
/** * Create a new set of {@link VersatileTimeSeries}, populate them with * values of {@link DoubleTimeSeries} from a {@link DoubleTimeSeriesList}, * and insert them into this collection. The run index has to be provided * together with the index at which the dimension index starts. The keys * of the new time series are constructed using the <code>name</code> and * the run index provided as parameters. * <p>//from w ww . j a va 2s . c o m * <b>Note:</b> This currently works only for series with a single dimension * index. * <p> * Uses the internal parameters <code>startTime</code> and <code>indexSeparator</code>. * <p> * @param dtl the {@link DoubleTimeSeriesList} from which we obtain the values to * populate the new time series * @param run the run index * @param name the name of the time series variable * @param startIndex the value at which the dimension index starts */ public void populateSeries(int run, String name, DoubleTimeSeriesList dtl, int startIndex) { Assertion.assertStrict((run >= 0) && (startIndex >= 0), Assertion.Level.ERR, "Start index and experiment index have to be positive"); for (int i = 0; i < dtl.size(); i++) { String newKey = name + internalParams.getIndexSeparator() + Integer.toString(i + startIndex) + internalParams.getIndexSeparator() + "r" + Integer.toString(run); VersatileTimeSeries ats = new VersatileTimeSeries(newKey); addSeries(ats); RegularTimePeriod time = internalParams.getStartTime(); for (int j = 0; j < dtl.get(i).size(); j++) { ats.add(time, dtl.get(i).getValue(j)); time = time.next(); } } }
From source file:info.financialecology.finance.utilities.datastruct.VersatileTimeSeriesCollection.java
/** * Create a new set of {@link VersatileTimeSeries}, populate them with * values of {@link DoubleTimeSeries} from a {@link DoubleTimeSeriesList}, * and insert them into this collection. The experiment and run indices * have to be provided together with the index at which the dimension index * starts. The keys of the new time series are constructed using the * <code>name</code> and the experiment and run indices provided as parameters. * <p>/*from w ww . j a v a 2 s . co m*/ * <b>Note:</b> This currently works only for series with a single dimension * index. * <p> * Uses the internal parameters <code>startTime</code> and <code>indexSeparator</code>. * <p> * @param dtl the {@link DoubleTimeSeriesList} from which we obtain the values to * populate the new time series * @param exp the experiment index * @param run the run index * @param name the name of the time series variable * @param startIndex the value at which the dimension index starts */ public void populateSeries(int exp, int run, String name, DoubleTimeSeriesList dtl, int startIndex) { Assertion.assertStrict((exp >= 0) && (run >= 0) && (startIndex >= 0), Assertion.Level.ERR, "Start index and run and experiment indices have to be positive"); for (int i = 0; i < dtl.size(); i++) { String newKey = name + internalParams.getIndexSeparator() + Integer.toString(i + startIndex) + internalParams.getIndexSeparator() + "r" + Integer.toString(run) + internalParams.getIndexSeparator() + "e" + Integer.toString(exp); VersatileTimeSeries ats = new VersatileTimeSeries(newKey); addSeries(ats); RegularTimePeriod time = internalParams.getStartTime(); for (int j = 0; j < dtl.get(i).size(); j++) { ats.add(time, dtl.get(i).getValue(j)); time = time.next(); } } }
From source file:fmiquerytest.Coordinates.java
static String drawTempRainChart(List<stepWeather> stepDataBase, Map routeWeather) { //First, fetch the real data List<Double> times = new ArrayList<>(); List<Double> temps = new ArrayList<>(); List<Double> rains = new ArrayList<>(); List<Double> lights = new ArrayList<>(); for (int i = 0; i < stepDataBase.size(); ++i) { stepWeather step = stepDataBase.get(i); stepWeather nextstep = step;/*from www . jav a2 s . c o m*/ if (i < stepDataBase.size() - 1) { nextstep = stepDataBase.get(i + 1); } times.add(step.timeAsDouble); temps.add(getParameterAverage(routeWeather, step, nextstep, "Temperature")); rains.add(getParameterAverage(routeWeather, step, nextstep, "Precipitation1h")); lights.add(Math.pow(Math.abs(step.timeAsDouble % 24 - ((step.sunRise + step.sunSet) / 2)) / ((step.sunSet - step.sunRise) / 2), 5)); } double zeroPoint = times.get(0); // Make first dataset final TimeSeriesCollection dataset = new TimeSeriesCollection(); final TimeSeries s1 = new TimeSeries("Temperature C", Minute.class); // Make second dataset final TimeSeriesCollection dataset2 = new TimeSeriesCollection(); final TimeSeries s2 = new TimeSeries("Rain (mm)", Minute.class); // Make third dataset //final TimeSeriesCollection dataset3 = new TimeSeriesCollection(); final TimeSeries s3 = new TimeSeries("Darkness", Minute.class); // Show data per minute RegularTimePeriod start = new Minute(new Date(FmiQueryTest.startTimeMillis)); for (int i = 0; i < times.size() - 1; ++i) { double time = times.get(i); double nexttime = times.get(i + 1); int firstMinute = intValue((time - zeroPoint) * 60); int currentMinute = firstMinute; int lastMinute = intValue((nexttime - zeroPoint) * 60); while (currentMinute < lastMinute) { s1.add(start, temps.get(i) + ((double) currentMinute - firstMinute) / (lastMinute - firstMinute) * (temps.get(i + 1) - temps.get(i))); s2.add(start, (rains.get(i) + rains.get(i + 1)) / 2); //+((double)currentMinute-firstMinute)/(lastMinute-firstMinute)*(rains.get(i+1)-rains.get(i))); s3.add(start, lights.get(i) + ((double) currentMinute - firstMinute) / (lastMinute - firstMinute) * (lights.get(i + 1) - lights.get(i))); ++currentMinute; start = start.next(); } } dataset.addSeries(s1); dataset2.addSeries(s3); dataset2.addSeries(s2); // Initialize chart final JFreeChart chart = ChartFactory.createTimeSeriesChart("Temperature and rain", "Time", "Temperature C", dataset, true, // legend? true, // tooltips? false // URLs? ); final XYPlot plot = chart.getXYPlot(); plot.getDomainAxis().setLowerMargin(0.0); plot.getDomainAxis().setUpperMargin(0.0); // configure the range axis to display first dataset... final ValueAxis rangeAxis = (ValueAxis) plot.getRangeAxis(); rangeAxis.setRange(-30, 30); final TickUnits units = new TickUnits(); units.add(new NumberTickUnit(10.0)); units.add(new NumberTickUnit(1.0)); units.add(new NumberTickUnit(0.1)); rangeAxis.setStandardTickUnits(units); //rangeAxis.setTickLabelFont(new Font("SansSerif", Font.BOLD, 16)); // add the secondary dataset/renderer/axis plot.setRangeAxis(rangeAxis); final XYItemRenderer renderer2 = new XYAreaRenderer(); final ValueAxis axis2 = new NumberAxis("Rain (mm) "); axis2.setRange(0, 2); axis2.setStandardTickUnits(units); //axis2.setTickLabelFont(new Font("SansSerif", Font.BOLD, 16)); renderer2.setSeriesPaint(0, new Color(0, 0, 255, 128)); plot.setDataset(1, dataset2); plot.setRenderer(1, renderer2); plot.setRangeAxis(1, axis2); plot.mapDatasetToRangeAxis(1, 1); final XYItemRenderer renderer3 = new XYAreaRenderer(); renderer3.setSeriesPaint(0, new Color(0, 0, 0, 64)); //plot.setDataset(1, dataset2); plot.setRenderer(1, renderer3); plot.setRangeAxis(1, axis2); plot.mapDatasetToRangeAxis(1, 1); chart.setBackgroundPaint(Color.white); //plot.setBackgroundPaint(Color.lightGray); plot.setBackgroundPaint(Color.white); plot.setDomainGridlinesVisible(true); plot.setDomainGridlinePaint(Color.black); plot.setRangeGridlinesVisible(true); plot.setRangeGridlinePaint(Color.black); // final TextTitle subtitle = new TextTitle("An area chart demonstration. We use this " // + "subtitle as an example of what happens when you get a really long title or " // + "subtitle."); // subtitle.setFont(new Font("SansSerif", Font.PLAIN, 12)); // subtitle.setPosition(RectangleEdge.TOP); //// subtitle.setSpacer(new Spacer(Spacer.RELATIVE, 0.05, 0.05, 0.05, 0.05)); // subtitle.setVerticalAlignment(VerticalAlignment.BOTTOM); // chart.addSubtitle(subtitle); // Produce chart // ChartFrame frame = new ChartFrame("Tamperature and rain", chart); // frame.pack(); // RefineryUtilities.centerFrameOnScreen(frame); // frame.setVisible(true); ByteArrayOutputStream bas = new ByteArrayOutputStream(); try { ChartUtilities.writeChartAsPNG(bas, chart, 600, 400); } catch (IOException ex) { Logger.getLogger(WeatherTools.class.getName()).log(Level.SEVERE, null, ex); } byte[] byteArray = bas.toByteArray(); String baseCode = Base64.encode(byteArray); return "<img width=\"480\" alt=\"Temperature and rain\" src=\"data:image/png;base64," + baseCode.trim() + "\" />"; }
From source file:info.financialecology.finance.utilities.datastruct.VersatileTimeSeries.java
/** * Creates a new time series by applying the integral operator to this time series. * The value of a data point in the new time series is equal to the sum of the values * up to that point in time. This can be used for instance to compute the current asset * position as the sum of all prior orders. * /*w ww . j a v a 2 s . c o m*/ * @param name the label of the new time series * @return a new time series with the difference values */ public VersatileTimeSeries operatorCumulative(String name) { VersatileTimeSeries ats = new VersatileTimeSeries(name); RegularTimePeriod currentTime = getTimePeriod(0); ats.add(new TimeSeriesDataItem(currentTime, this.getValue(0))); for (int i = 1; i < this.getItemCount(); i++) { currentTime = currentTime.next(); ats.add(currentTime, ats.getValue(i - 1).doubleValue() + this.getValue(i).doubleValue()); } return ats; }
From source file:info.financialecology.finance.utilities.datastruct.VersatileTimeSeries.java
/** * Creates a new time series with the absolute values of each data point of this time * series. This can be used for instance to calculate trading volume from total * orders. // w w w . java2s. c om * * @param name the label of the new time series * @return a new time series with the absolute values */ public VersatileTimeSeries operatorAbs(String name) { VersatileTimeSeries ats = new VersatileTimeSeries(name); RegularTimePeriod currentTime = getTimePeriod(0); for (int i = 0; i < this.getItemCount(); i++) { ats.add(currentTime, Math.abs(this.getValue(i).doubleValue())); currentTime = currentTime.next(); } return ats; }
From source file:info.financialecology.finance.utilities.datastruct.VersatileTimeSeries.java
/** * Creates a new time series with the exponential values of each data point of this time * series. Since many models work with log prices, this method can be used to calculate * the corresponding prices, which are easier to interpret when inspecting the results. * /*from w w w. ja va2 s . c o m*/ * @param name the label of the new time series * @return a new time series with the exponential values */ public VersatileTimeSeries operatorExp(String name) { VersatileTimeSeries ats = new VersatileTimeSeries(name); RegularTimePeriod currentTime = getTimePeriod(0); for (int i = 0; i < this.getItemCount(); i++) { ats.add(currentTime, Math.exp(this.getValue(i).doubleValue())); currentTime = currentTime.next(); } return ats; }