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private void myMethod () {Charset c =
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protected boolean useLogarithmicProblemScale(List<XYSeries> seriesList) { NavigableSet<Double> xValueSet = new TreeSet<>(); int xValueListSize = 0; for (XYSeries series : seriesList) { for (XYDataItem dataItem : (List<XYDataItem>) series.getItems()) { xValueSet.add(dataItem.getXValue()); xValueListSize++; } } if (xValueListSize < LOG_SCALE_MIN_DATASETS_COUNT) { return false; } // If 60% of the points are in 20% of the value space, use a logarithmic scale double threshold = 0.2 * (xValueSet.last() - xValueSet.first()); int belowThresholdCount = xValueSet.headSet(threshold).size(); return belowThresholdCount >= (0.6 * xValueSet.size()); }
private XYPlot createPeriodCostPlot(TangoColorFactory tangoColorFactory, CheapTimeSolution solution) { XYSeries series = new XYSeries("Power price"); for (PeriodPowerPrice periodPowerPrice : solution.getPeriodPowerPriceList()) { series.add((double) periodPowerPrice.getPowerPriceMicros() / 1000000.0, periodPowerPrice.getPeriod()); } XYSeriesCollection seriesCollection = new XYSeriesCollection(); seriesCollection.addSeries(series); XYItemRenderer renderer = new StandardXYItemRenderer(StandardXYItemRenderer.SHAPES); renderer.setSeriesPaint(0, TangoColorFactory.ORANGE_1); renderer.setSeriesShape(0, ShapeUtilities.createDiamond(2.0F)); NumberAxis domainAxis = new NumberAxis("Power price"); return new XYPlot(seriesCollection, domainAxis, null, renderer); }
k -> new XYSeries(point.getConstraintName() + " weight")); if (levelValues[i] != ((weightSeries.getItemCount() == 0) ? 0.0 : weightSeries.getY(weightSeries.getItemCount() - 1).doubleValue())) { weightSeries.add(timeMillisSpent, levelValues[i]); for (Iterator<Map.Entry<String, XYSeries>> it = constraintIdToWeightSeriesMap.entrySet().iterator(); it.hasNext(); ) { XYSeries weightSeries = it.next().getValue(); if (weightSeries.getItemCount() == 0) { weightSeries.add(timeMillisSpent, weightSeries.getY(weightSeries.getItemCount() - 1).doubleValue()); XYSeriesCollection seriesCollection = new XYSeriesCollection(); for (XYSeries series : constraintIdToWeightSeriesMapList.get(scoreLevelIndex).values()) { seriesCollection.addSeries(series);
for (int i = 0; i < levelValues.length && i < BenchmarkReport.CHARTED_SCORE_LEVEL_SIZE; i++) { if (i >= seriesList.size()) { seriesList.add(new XYSeries( singleBenchmarkResult.getSolverBenchmarkResult().getNameWithFavoriteSuffix())); seriesList.get(i).add(timeMillisSpent, levelValues[i]); plotList.add(createPlot(benchmarkReport, i)); plotList.get(i).setDataset(seriesIndex, new XYSeriesCollection(seriesList.get(i))); plotList.get(i).setRenderer(seriesIndex, renderer);
private void writeScoreCalculationSpeedSummaryChart() { List<XYSeries> seriesList = new ArrayList<>(plannerBenchmarkResult.getSolverBenchmarkResultList().size()); for (SolverBenchmarkResult solverBenchmarkResult : plannerBenchmarkResult.getSolverBenchmarkResultList()) { String solverLabel = solverBenchmarkResult.getNameWithFavoriteSuffix(); XYSeries series = new XYSeries(solverLabel); for (SingleBenchmarkResult singleBenchmarkResult : solverBenchmarkResult.getSingleBenchmarkResultList()) { if (singleBenchmarkResult.hasAllSuccess()) { long problemScale = singleBenchmarkResult.getProblemBenchmarkResult().getProblemScale(); long scoreCalculationSpeed = singleBenchmarkResult.getScoreCalculationSpeed(); series.add((Long) problemScale, (Long) scoreCalculationSpeed); } } seriesList.add(series); } XYPlot plot = createScalabilityPlot(seriesList, "Problem scale", NumberFormat.getInstance(locale), "Score calculation speed per second", NumberFormat.getInstance(locale)); JFreeChart chart = new JFreeChart("Score calculation speed summary (higher is better)", JFreeChart.DEFAULT_TITLE_FONT, plot, true); scoreCalculationSpeedSummaryChartFile = writeChartToImageFile(chart, "scoreCalculationSpeedSummary"); }
private XYPlot createScalabilityPlot(List<XYSeries> seriesList, String xAxisLabel, NumberFormat xAxisNumberFormat, String yAxisLabel, NumberFormat yAxisNumberFormat) { NumberAxis xAxis; if (useLogarithmicProblemScale(seriesList)) { LogarithmicAxis logarithmicAxis = new LogarithmicAxis(xAxisLabel + " (logarithmic)"); logarithmicAxis.setAllowNegativesFlag(true); xAxis = logarithmicAxis; } else { xAxis = new NumberAxis(xAxisLabel); } xAxis.setNumberFormatOverride(xAxisNumberFormat); NumberAxis yAxis = new NumberAxis(yAxisLabel); yAxis.setNumberFormatOverride(yAxisNumberFormat); XYPlot plot = new XYPlot(null, xAxis, yAxis, null); int seriesIndex = 0; for (XYSeries series : seriesList) { XYSeriesCollection seriesCollection = new XYSeriesCollection(); seriesCollection.addSeries(series); plot.setDataset(seriesIndex, seriesCollection); XYItemRenderer renderer = createScalabilityPlotRenderer(yAxisNumberFormat); plot.setRenderer(seriesIndex, renderer); seriesIndex++; } plot.setOrientation(PlotOrientation.VERTICAL); return plot; }
k -> new XYIntervalSeries(moveType)); double yValue = levelValues[i]; series.add(timeMillisSpent, timeMillisSpent, timeMillisSpent, yValue, (yValue > 0.0) ? 0.0 : yValue, (yValue > 0.0) ? yValue : 0.0); XYItemRenderer renderer = new YIntervalRenderer(); plot.setRenderer(renderer); XYIntervalSeriesCollection seriesCollection = new XYIntervalSeriesCollection(); for (XYIntervalSeries series : moveTypeToSeriesMapList.get(scoreLevelIndex).values()) { seriesCollection.addSeries(series);
private JFreeChart createChart(Schedule schedule) { YIntervalSeriesCollection seriesCollection = new YIntervalSeriesCollection(); Map<Project, YIntervalSeries> projectSeriesMap = new LinkedHashMap<>( schedule.getProjectList().size()); int seriesIndex = 0; for (Project project : schedule.getProjectList()) { YIntervalSeries projectSeries = new YIntervalSeries(project.getLabel()); seriesCollection.addSeries(projectSeries); projectSeriesMap.put(project, projectSeries); renderer.setSeriesShape(seriesIndex, new Rectangle()); int endDate = allocation.getEndDate(); YIntervalSeries projectSeries = projectSeriesMap.get(allocation.getProject()); projectSeries.add(allocation.getId(), (startDate + endDate) / 2.0, startDate, endDate); maximumEndDate = Math.max(maximumEndDate, endDate);
int rows = 20; double[][] values = new double[cols][rows]; XYSeriesCollection xySeriesCollection = new XYSeriesCollection(); XYSeries series = new XYSeries("Random"); Random rand = new Random(); for (int i = 0; i < values.length; i++) { double x = rand.nextGaussian(); double y = rand.nextGaussian(); series.add(x, y); xySeriesCollection.addSeries(series); return xySeriesCollection;
k -> new XYSeries(point.getConstraintName() + " weight")); if (levelValues[i] != ((weightSeries.getItemCount() == 0) ? 0.0 : weightSeries.getY(weightSeries.getItemCount() - 1).doubleValue())) { weightSeries.add(timeMillisSpent, levelValues[i]); for (Iterator<Map.Entry<String, XYSeries>> it = constraintIdToWeightSeriesMap.entrySet().iterator(); it.hasNext(); ) { XYSeries weightSeries = it.next().getValue(); if (weightSeries.getItemCount() == 0) { weightSeries.add(timeMillisSpent, weightSeries.getY(weightSeries.getItemCount() - 1).doubleValue()); XYSeriesCollection seriesCollection = new XYSeriesCollection(); for (XYSeries series : constraintIdToWeightSeriesMapList.get(scoreLevelIndex).values()) { seriesCollection.addSeries(series);
int seriesIndex = 0; for (SingleBenchmarkResult singleBenchmarkResult : problemBenchmarkResult.getSingleBenchmarkResultList()) { XYSeries series = new XYSeries(singleBenchmarkResult.getSolverBenchmarkResult().getNameWithFavoriteSuffix()); XYItemRenderer renderer = new XYLineAndShapeRenderer(); if (singleBenchmarkResult.hasAllSuccess()) { long timeMillisSpent = point.getTimeMillisSpent(); long scoreCalculationSpeed = point.getScoreCalculationSpeed(); series.add(timeMillisSpent, scoreCalculationSpeed); plot.setDataset(seriesIndex, new XYSeriesCollection(series));
k -> new XYIntervalSeries(moveType)); double yValue = levelValues[i]; series.add(timeMillisSpent, timeMillisSpent, timeMillisSpent, yValue, (yValue > 0.0) ? 0.0 : yValue, (yValue > 0.0) ? yValue : 0.0); XYItemRenderer renderer = new YIntervalRenderer(); plot.setRenderer(renderer); XYIntervalSeriesCollection seriesCollection = new XYIntervalSeriesCollection(); for (XYIntervalSeries series : moveTypeToSeriesMapList.get(scoreLevelIndex).values()) { seriesCollection.addSeries(series);
private static final String title = "Scatter Add Demo"; private static final Random rand = new Random(); private XYSeries added = new XYSeries("Added"); public void actionPerformed(ActionEvent e) { for (int i = 0; i < N; i++) { added.add(rand.nextDouble(), rand.nextDouble()); XYSeriesCollection xySeriesCollection = new XYSeriesCollection(); XYSeries series = new XYSeries("Random"); for (int i = 0; i < N * N; i++) { double x = rand.nextDouble(); double y = rand.nextDouble(); series.add(x, y); xySeriesCollection.addSeries(series); xySeriesCollection.addSeries(added); return xySeriesCollection;
int seriesIndex = 0; for (SingleBenchmarkResult singleBenchmarkResult : problemBenchmarkResult.getSingleBenchmarkResultList()) { XYIntervalSeries series = new XYIntervalSeries(singleBenchmarkResult.getSolverBenchmarkResult().getNameWithFavoriteSuffix()); XYItemRenderer renderer = new YIntervalRenderer(); if (singleBenchmarkResult.hasAllSuccess()) { double yValue = mutationCount; series.add(timeMillisSpent, timeMillisSpent, timeMillisSpent, yValue, (yValue > 0.0) ? 0.0 : yValue, (yValue > 0.0) ? yValue : 0.0); XYIntervalSeriesCollection dataset = new XYIntervalSeriesCollection(); dataset.addSeries(series); plot.setDataset(seriesIndex, dataset);
XYSeriesCollection seriesCollection = new XYSeriesCollection(); XYItemRenderer renderer = new StandardXYItemRenderer(StandardXYItemRenderer.SHAPES); int seriesIndex = 0; for (Machine machine : solution.getMachineList()) { XYSeries machineSeries = new XYSeries(machine.getLabel()); for (MachineCapacity machineCapacity : machine.getMachineCapacityList()) { List<Integer> machineAvailableList = availableMap.get(machineCapacity); for (int period = 0; period < solution.getGlobalPeriodRangeTo(); period++) { int available = machineAvailableList.get(period); machineSeries.add(available, period); seriesCollection.addSeries(machineSeries); renderer.setSeriesPaint(seriesIndex, tangoColorFactory.pickColor(machine)); renderer.setSeriesShape(seriesIndex, ShapeUtilities.createDiamond(1.5F));
private void writeTimeSpentScalabilitySummaryChart() { List<XYSeries> seriesList = new ArrayList<>(plannerBenchmarkResult.getSolverBenchmarkResultList().size()); for (SolverBenchmarkResult solverBenchmarkResult : plannerBenchmarkResult.getSolverBenchmarkResultList()) { String solverLabel = solverBenchmarkResult.getNameWithFavoriteSuffix(); XYSeries series = new XYSeries(solverLabel); for (SingleBenchmarkResult singleBenchmarkResult : solverBenchmarkResult.getSingleBenchmarkResultList()) { if (singleBenchmarkResult.hasAllSuccess()) { long problemScale = singleBenchmarkResult.getProblemBenchmarkResult().getProblemScale(); long timeMillisSpent = singleBenchmarkResult.getTimeMillisSpent(); series.add((Long) problemScale, (Long) timeMillisSpent); } } seriesList.add(series); } XYPlot plot = createScalabilityPlot(seriesList, "Problem scale", NumberFormat.getInstance(locale), "Time spent", new MillisecondsSpentNumberFormat(locale)); JFreeChart chart = new JFreeChart("Time spent scalability summary (lower is better)", JFreeChart.DEFAULT_TITLE_FONT, plot, true); timeSpentScalabilitySummaryChartFile = writeChartToImageFile(chart, "timeSpentScalabilitySummary"); }
XYSeries acceptedSeries = new XYSeries( singleBenchmarkResult.getSolverBenchmarkResult().getNameWithFavoriteSuffix() + " accepted"); XYSeries selectedSeries = new XYSeries( singleBenchmarkResult.getSolverBenchmarkResult().getNameWithFavoriteSuffix() + " selected"); XYItemRenderer renderer = new XYLineAndShapeRenderer(true, false); long acceptedMoveCount = point.getMoveCountPerStepMeasurement().getAcceptedMoveCount(); long selectedMoveCount = point.getMoveCountPerStepMeasurement().getSelectedMoveCount(); acceptedSeries.add(timeMillisSpent, acceptedMoveCount); selectedSeries.add(timeMillisSpent, selectedMoveCount); XYSeriesCollection seriesCollection = new XYSeriesCollection(); seriesCollection.addSeries(acceptedSeries); seriesCollection.addSeries(selectedSeries); plot.setDataset(seriesIndex, seriesCollection);
int seriesIndex = 0; for (SingleBenchmarkResult singleBenchmarkResult : problemBenchmarkResult.getSingleBenchmarkResultList()) { XYSeries usedSeries = new XYSeries( singleBenchmarkResult.getSolverBenchmarkResult().getNameWithFavoriteSuffix() + " used"); long timeMillisSpent = point.getTimeMillisSpent(); MemoryUseMeasurement memoryUseMeasurement = point.getMemoryUseMeasurement(); usedSeries.add(timeMillisSpent, memoryUseMeasurement.getUsedMemory()); XYSeriesCollection seriesCollection = new XYSeriesCollection(); seriesCollection.addSeries(usedSeries);