List of usage examples for org.jfree.data.xy XYIntervalSeries XYIntervalSeries
public XYIntervalSeries(Comparable key)
From source file:org.esa.snap.rcp.statistics.ProfilePlotPanel.java
private void updateDataSet() { if (!isInitialized) { return;/* w w w .j a va2 s .c om*/ } dataset.removeAllSeries(); double dx = 0.5 * dataSourceConfig.boxSize; if (profileData != null) { final float[] sampleValues = profileData.getSampleValues(); final float[] sampleSigmas = profileData.getSampleSigmas(); XYIntervalSeries series = new XYIntervalSeries( getRaster() != null ? getRaster().getName() : DEFAULT_SAMPLE_DATASET_NAME); for (int x = 0; x < sampleValues.length; x++) { final float y = sampleValues[x]; final float dy = sampleSigmas[x]; series.add(x, x - dx, x + dx, y, y - dy, y + dy); } dataset.addSeries(series); if (dataSourceConfig.useCorrelativeData && dataSourceConfig.pointDataSource != null && dataSourceConfig.dataField != null) { XYIntervalSeries corrSeries = new XYIntervalSeries(StatisticChartStyling .getCorrelativeDataLabel(dataSourceConfig.pointDataSource, dataSourceConfig.dataField)); int[] shapeVertexIndexes = profileData.getShapeVertexIndexes(); SimpleFeature[] simpleFeatures = dataSourceConfig.pointDataSource.getFeatureCollection() .toArray(new SimpleFeature[0]); if (shapeVertexIndexes.length == simpleFeatures.length) { int fieldIndex = getAttributeIndex(dataSourceConfig.pointDataSource, dataSourceConfig.dataField); if (fieldIndex != -1) { for (int i = 0; i < simpleFeatures.length; i++) { Number attribute = (Number) simpleFeatures[i].getAttribute(fieldIndex); if (attribute != null) { final double x = shapeVertexIndexes[i]; final double y = attribute.doubleValue(); corrSeries.add(x, x, x, y, y, y); } } dataset.addSeries(corrSeries); } } else { System.out.println("Weird things happened:"); System.out.println(" shapeVertexIndexes.length = " + shapeVertexIndexes.length); System.out.println(" simpleFeatures.length = " + simpleFeatures.length); } } profilePlotDisplay.restoreAutoBounds(); xAxisRangeControl.getBindingContext().setComponentsEnabled(PROPERTY_NAME_MARK_SEGMENTS, profileData.getShapeVertices().length > 2); } }
From source file:org.esa.beam.visat.toolviews.stat.ProfilePlotPanel.java
private void updateDataSet() { if (!isInitialized) { return;/*from ww w .j av a 2 s .c om*/ } dataset.removeAllSeries(); double dx = 0.5 * dataSourceConfig.boxSize; if (profileData != null) { final float[] sampleValues = profileData.getSampleValues(); final float[] sampleSigmas = profileData.getSampleSigmas(); XYIntervalSeries series = new XYIntervalSeries( getRaster() != null ? getRaster().getName() : DEFAULT_SAMPLE_DATASET_NAME); for (int x = 0; x < sampleValues.length; x++) { final float y = sampleValues[x]; final float dy = sampleSigmas[x]; series.add(x, x - dx, x + dx, y, y - dy, y + dy); } dataset.addSeries(series); if (dataSourceConfig.useCorrelativeData && dataSourceConfig.pointDataSource != null && dataSourceConfig.dataField != null) { XYIntervalSeries corrSeries = new XYIntervalSeries( getCorrelativeDataLabel(dataSourceConfig.pointDataSource, dataSourceConfig.dataField)); int[] shapeVertexIndexes = profileData.getShapeVertexIndexes(); SimpleFeature[] simpleFeatures = dataSourceConfig.pointDataSource.getFeatureCollection() .toArray(new SimpleFeature[0]); if (shapeVertexIndexes.length == simpleFeatures.length) { int fieldIndex = getAttributeIndex(dataSourceConfig.pointDataSource, dataSourceConfig.dataField); if (fieldIndex != -1) { for (int i = 0; i < simpleFeatures.length; i++) { Number attribute = (Number) simpleFeatures[i].getAttribute(fieldIndex); if (attribute != null) { final double x = shapeVertexIndexes[i]; final double y = attribute.doubleValue(); corrSeries.add(x, x, x, y, y, y); } } dataset.addSeries(corrSeries); } } else { System.out.println("Weird things happened:"); System.out.println(" shapeVertexIndexes.length = " + shapeVertexIndexes.length); System.out.println(" simpleFeatures.length = " + simpleFeatures.length); } } profilePlotDisplay.restoreAutoBounds(); xAxisRangeControl.getBindingContext().setComponentsEnabled(PROPERTY_NAME_MARK_SEGMENTS, profileData.getShapeVertices().length > 2); } }
From source file:weka.gui.beans.JFreeChartOffscreenChartRenderer.java
/** * Render an XY scatter plot/*from w ww .jav a 2 s. c o m*/ * * @param width the width of the resulting chart in pixels * @param height the height of the resulting chart in pixels * @param series a list of Instances - one for each series to be plotted * @param xAxis the name of the attribute for the x-axis (all series Instances * are expected to have an attribute of the same type with this name) * @param yAxis the name of the attribute for the y-axis (all series Instances * are expected to have an attribute of the same type with this name) * @param optionalArgs optional arguments to the renderer (may be null) * * @return a BufferedImage containing the chart * @throws Exception if there is a problem rendering the chart */ public BufferedImage renderXYScatterPlot(int width, int height, List<Instances> series, String xAxis, String yAxis, List<String> optionalArgs) throws Exception { String plotTitle = "Scatter Plot"; String userTitle = getOption(optionalArgs, "-title"); plotTitle = (userTitle != null) ? userTitle : plotTitle; String colorAtt = getOption(optionalArgs, "-color"); if (series.size() == 1 && colorAtt != null && colorAtt.length() > 0) { int colIndex = getIndexOfAttribute(series.get(0), colorAtt); if (colIndex >= 0 && series.get(0).attribute(colIndex).isNominal()) { // split single series out into multiple instances objects - one // per class series = splitToClasses(series.get(0), colIndex); for (Instances insts : series) { insts.setClassIndex(colIndex); } } } Instances masterInstances = series.get(0); int xAx = getIndexOfAttribute(masterInstances, xAxis); int yAx = getIndexOfAttribute(masterInstances, yAxis); if (xAx < 0) { xAx = 0; } if (yAx < 0) { yAx = 0; } // Set the axis names just in case we've been supplied with // /first, /last or /<num> xAxis = masterInstances.attribute(xAx).name(); yAxis = masterInstances.attribute(yAx).name(); // look for an additional attribute that stores the // shape sizes - could be either nominal or numeric errors. // We only use numeric error information String shapeSize = getOption(optionalArgs, "-shapeSize"); boolean nominalClass = (masterInstances.classIndex() >= 0 && masterInstances.classAttribute().isNominal()); int shapeSizeI = -1; if (shapeSize != null && shapeSize.length() > 0) { shapeSizeI = getIndexOfAttribute(masterInstances, shapeSize); } AbstractIntervalXYDataset xyDataset = null; if (shapeSizeI < 0 || nominalClass) { xyDataset = new XYSeriesCollection(); } else { xyDataset = new XYIntervalSeriesCollection(); } // add master series Series master = null; if (shapeSizeI < 0 || nominalClass) { master = new XYSeries(masterInstances.relationName()); } else { master = new XYIntervalSeries(masterInstances.relationName()); } AttributeStats xStats = masterInstances.attributeStats(xAx); AttributeStats yStats = masterInstances.attributeStats(yAx); double sizeRange = 0; double sizeMin = 0; if (shapeSizeI >= 0 && !nominalClass) { AttributeStats sStats = masterInstances.attributeStats(shapeSizeI); sizeRange = sStats.numericStats.max - sStats.numericStats.min; sizeMin = sStats.numericStats.min; } double xRange = 0; if (masterInstances.attribute(xAx).isNominal()) { xRange = masterInstances.attribute(xAx).numValues(); } else { xRange = xStats.numericStats.max - xStats.numericStats.min; } double yRange = 0; if (masterInstances.attribute(yAx).isNominal()) { xRange = masterInstances.attribute(yAx).numValues(); } else { yRange = yStats.numericStats.max - yStats.numericStats.min; } for (int i = 0; i < masterInstances.numInstances(); i++) { Instance inst = masterInstances.instance(i); if (!inst.isMissing(xAx) && !inst.isMissing(yAx)) { if (shapeSizeI < 0 || nominalClass) { ((XYSeries) master).add(inst.value(xAx), inst.value(yAx)); } else { double xBar = (inst.value(shapeSizeI) - sizeMin) / sizeRange; xBar *= (xRange / 5.0); // max of 1/5th the x range double yBar = (inst.value(shapeSizeI) - sizeMin) / sizeRange; yBar *= (yRange / 5.0); double x = inst.value(xAx); double y = inst.value(yAx); ((XYIntervalSeries) master).add(x, x - (xBar / 2.0), x + (xBar / 2.0), y, y - (yBar / 2.0), y + (yBar / 2.0)); } } } if (shapeSizeI < 0 || nominalClass) { ((XYSeriesCollection) xyDataset).addSeries((XYSeries) master); } else { ((XYIntervalSeriesCollection) xyDataset).addSeries((XYIntervalSeries) master); } // remaining series for (int i = 1; i < series.size(); i++) { Instances aSeriesI = series.get(i); Series aSeriesJ = null; if (shapeSizeI < 0 || nominalClass) { aSeriesJ = new XYSeries(aSeriesI.relationName()); } else { aSeriesJ = new XYIntervalSeries(aSeriesI.relationName()); } for (int j = 0; j < aSeriesI.numInstances(); j++) { Instance inst = aSeriesI.instance(j); if (!inst.isMissing(xAx) && !inst.isMissing(yAx)) { if (shapeSizeI < 0 || nominalClass) { ((XYSeries) aSeriesJ).add(inst.value(xAx), inst.value(yAx)); } else { double xBar = (inst.value(shapeSizeI) - sizeMin) / sizeRange; xBar *= (xRange / 5.0); // max of 1/10th the x range double yBar = (inst.value(shapeSizeI) - sizeMin) / sizeRange; yBar *= (yRange / 5.0); double x = inst.value(xAx); double y = inst.value(yAx); ((XYIntervalSeries) aSeriesJ).add(x, x - (xBar / 2.0), x + (xBar / 2.0), y, y - (yBar / 2.0), y + (yBar / 2.0)); } } } if (shapeSizeI < 0 || nominalClass) { ((XYSeriesCollection) xyDataset).addSeries((XYSeries) aSeriesJ); } else { ((XYIntervalSeriesCollection) xyDataset).addSeries((XYIntervalSeries) aSeriesJ); } } JFreeChart chart = ChartFactory.createXYLineChart(plotTitle, xAxis, yAxis, xyDataset, PlotOrientation.VERTICAL, true, false, false); chart.setBackgroundPaint(java.awt.Color.white); XYPlot plot = (XYPlot) chart.getPlot(); if (shapeSizeI < 0 || nominalClass) { XYLineAndShapeRenderer renderer = new XYLineAndShapeRenderer(false, true); renderer.setBaseShapesFilled(false); plot.setRenderer(renderer); } else { XYErrorRenderer renderer = new XYErrorRenderer(); renderer.setDrawXError(true); renderer.setDrawYError(true); renderer.setBaseLinesVisible(false); plot.setRenderer(renderer); } BufferedImage image = chart.createBufferedImage(width, height); return image; }
From source file:jhplot.HChart.java
/** * Add a H1D histogram to the chart. Call update() method to view it. * //from ww w. j a v a2 s . co m * @param h1 * H1D histogram */ public void add(H1D h1) { IAxis axis = h1.get().axis(); XYIntervalSeriesCollection c = new XYIntervalSeriesCollection(); XYIntervalSeries SerData = new XYIntervalSeries(h1.getTitle()); int ibins = axis.bins(); for (int i = 0; i < ibins; i++) { SerData.add(h1.binMean(i), axis.binLowerEdge(i), axis.binUpperEdge(i), h1.binHeight(i), 0, h1.binHeight(i)); } c.addSeries(SerData); xyplot[N1][N2].setDataset(indexdat[N1][N2], c); XYBarRenderer render = new XYBarRenderer(); LinePars lpp = h1.getDrawOption(); Color cfill = lpp.getFillColor(); float width = (float) lpp.getPenWidth(); int style = h1.getLineStyle(); float dash = lpp.getDashLength(); StandardXYBarPainter paint = new StandardXYBarPainter(); render.setBarPainter(paint); render.setDrawBarOutline(true); render.setShadowVisible(false); render.setBaseStroke(getStrokes(style, width, dash)); render.setBasePaint(cfill); render.setBaseOutlinePaint(h1.getColor()); render.setBaseOutlineStroke(getStrokes(style, width, dash)); render.setSeriesStroke(0, getStrokes(style, width, dash)); render.setSeriesPaint(0, cfill); render.setSeriesOutlinePaint(0, h1.getColor()); if (h1.isFilled()) { render.setSeriesFillPaint(0, cfill); } // System.out.println(render.toString()); // System.out.println(rdat[N1][N2]); rdat[N1][N2].add(render); type[N1][N2].put(new Integer(indexdat[N1][N2]), "h"); indexdat[N1][N2]++; }
From source file:jhplot.HChart.java
/** * Draw data from a P1D. Drawing updated automatically. 1st level errors are * shown if the dimension is above 5. Otherwise show X and Y. If you set * setChartPolar() before,m you can also show polar coordinates. * /*from w ww .ja v a2s . c om*/ * @param d * input P1D container */ public void add(P1D d) { if (cdatPolar[N1][N2] != null) { XYSeries SerData = new XYSeries(d.getTitle()); for (int i = 0; i < d.size(); i++) SerData.add(d.getX(i), d.getY(i)); cdatPolar[N1][N2].addSeries(SerData); return; // return if this is polar chart } // assume XY chart // System.out.println(d.dimension()); LinePars lpp = d.getDrawOption(); float width = (float) lpp.getPenWidth(); int style = d.getLineStyle(); float dash = lpp.getDashLength(); int symbol = lpp.getSymbol(); Shape shape = getShape(symbol, lpp.getSymbolSize()); // setSeriesShapesFilled(int series, java.lang.Boolean flag) // setShapesFilled(boolean filled) if (d.dimension() > 5) { XYIntervalSeriesCollection c = new XYIntervalSeriesCollection(); XYIntervalSeries SerData = new XYIntervalSeries(d.getTitle()); for (int i = 0; i < d.size(); i++) SerData.add(d.getX(i), d.getX(i) - d.getXleft(i), d.getX(i) + d.getXright(i), d.getY(i), d.getY(i) - d.getYlower(i), d.getY(i) + d.getYupper(i)); c.addSeries(SerData); xyplot[N1][N2].setDataset(indexdat[N1][N2], c); XYErrorRenderer xyerrorrenderer = new XYErrorRenderer(); xyerrorrenderer.setSeriesStroke(0, getStrokes(style, width, dash)); xyerrorrenderer.setSeriesPaint(0, d.getColor()); xyerrorrenderer.setSeriesOutlinePaint(0, d.getColor()); xyerrorrenderer.setSeriesFillPaint(0, lpp.getFillColor()); xyerrorrenderer.setSeriesShape(0, shape); if (symbol > 0 && symbol < 4) xyerrorrenderer.setSeriesShapesFilled(0, false); if (symbol > 3) xyerrorrenderer.setSeriesShapesFilled(0, true); rdat[N1][N2].add(xyerrorrenderer); type[N1][N2].put(new Integer(indexdat[N1][N2]), "pe"); indexdat[N1][N2]++; } else if (d.dimension() == 4) { XYIntervalSeriesCollection c = new XYIntervalSeriesCollection(); XYIntervalSeries SerData = new XYIntervalSeries(d.getTitle()); for (int i = 0; i < d.size(); i++) SerData.add(d.getX(i), d.getX(i), d.getX(i), d.getY(i), d.getY(i) - d.getYlower(i), d.getY(i) + d.getYupper(i)); c.addSeries(SerData); xyplot[N1][N2].setDataset(indexdat[N1][N2], c); XYErrorRenderer xyerrorrenderer = new XYErrorRenderer(); xyerrorrenderer.setSeriesStroke(0, getStrokes(style, width, dash)); xyerrorrenderer.setSeriesPaint(0, d.getColor()); xyerrorrenderer.setSeriesOutlinePaint(0, d.getColor()); xyerrorrenderer.setSeriesFillPaint(0, lpp.getFillColor()); xyerrorrenderer.setSeriesShape(0, shape); if (symbol > 0 && symbol < 4) xyerrorrenderer.setSeriesShapesFilled(0, false); if (symbol > 3) xyerrorrenderer.setSeriesShapesFilled(0, true); rdat[N1][N2].add(xyerrorrenderer); type[N1][N2].put(new Integer(indexdat[N1][N2]), "pe"); indexdat[N1][N2]++; } else if (d.dimension() == 3) { XYIntervalSeriesCollection c = new XYIntervalSeriesCollection(); XYIntervalSeries SerData = new XYIntervalSeries(d.getTitle()); for (int i = 0; i < d.size(); i++) SerData.add(d.getX(i), d.getX(i), d.getX(i), d.getY(i), d.getY(i) - d.getYupper(i), d.getY(i) + d.getYupper(i)); c.addSeries(SerData); xyplot[N1][N2].setDataset(indexdat[N1][N2], c); XYErrorRenderer xyerrorrenderer = new XYErrorRenderer(); xyerrorrenderer.setSeriesStroke(0, getStrokes(style, width, dash)); xyerrorrenderer.setSeriesPaint(0, d.getColor()); xyerrorrenderer.setSeriesOutlinePaint(0, d.getColor()); xyerrorrenderer.setSeriesFillPaint(0, lpp.getFillColor()); xyerrorrenderer.setSeriesShape(0, shape); if (symbol > 0 && symbol < 4) xyerrorrenderer.setSeriesShapesFilled(0, false); if (symbol > 3) xyerrorrenderer.setSeriesShapesFilled(0, true); rdat[N1][N2].add(xyerrorrenderer); type[N1][N2].put(new Integer(indexdat[N1][N2]), "pe"); indexdat[N1][N2]++; } else { XYSeriesCollection c = new XYSeriesCollection(); XYSeries SerData = new XYSeries(d.getTitle()); for (int i = 0; i < d.size(); i++) SerData.add(d.getX(i), d.getY(i)); c.addSeries(SerData); xyplot[N1][N2].setDataset(indexdat[N1][N2], c); XYLineAndShapeRenderer xyerrorrenderer = new XYLineAndShapeRenderer(false, true); xyerrorrenderer.setSeriesStroke(0, getStrokes(style, width, dash)); xyerrorrenderer.setSeriesPaint(0, d.getColor()); xyerrorrenderer.setSeriesOutlinePaint(0, d.getColor()); xyerrorrenderer.setSeriesFillPaint(0, lpp.getFillColor()); xyerrorrenderer.setSeriesShape(0, shape); if (symbol > 0 && symbol < 4) xyerrorrenderer.setSeriesShapesFilled(0, false); if (symbol > 3) xyerrorrenderer.setSeriesShapesFilled(0, true); rdat[N1][N2].add(xyerrorrenderer); type[N1][N2].put(new Integer(indexdat[N1][N2]), "p"); indexdat[N1][N2]++; } }
From source file:org.esa.snap.rcp.statistics.ScatterPlotPanel.java
private void compute(final Mask selectedMask) { final RasterDataNode raster = getRaster(); final AttributeDescriptor dataField = scatterPlotModel.dataField; if (raster == null || dataField == null) { return;/*from ww w .j a v a2s .co m*/ } SwingWorker<ComputedData[], Object> swingWorker = new SwingWorker<ComputedData[], Object>() { @Override protected ComputedData[] doInBackground() throws Exception { SystemUtils.LOG.finest("start computing scatter plot data"); final List<ComputedData> computedDataList = new ArrayList<>(); final FeatureCollection<SimpleFeatureType, SimpleFeature> collection = scatterPlotModel.pointDataSource .getFeatureCollection(); final SimpleFeature[] features = collection.toArray(new SimpleFeature[collection.size()]); final int boxSize = scatterPlotModel.boxSize; final Rectangle sceneRect = new Rectangle(raster.getRasterWidth(), raster.getRasterHeight()); final GeoCoding geoCoding = raster.getGeoCoding(); final AffineTransform imageToModelTransform; imageToModelTransform = Product.findImageToModelTransform(geoCoding); for (SimpleFeature feature : features) { final Point point = (Point) feature.getDefaultGeometryProperty().getValue(); Point2D modelPos = new Point2D.Float((float) point.getX(), (float) point.getY()); final Point2D imagePos = imageToModelTransform.inverseTransform(modelPos, null); if (!sceneRect.contains(imagePos)) { continue; } final float imagePosX = (float) imagePos.getX(); final float imagePosY = (float) imagePos.getY(); final Rectangle imageRect = sceneRect.intersection(new Rectangle( ((int) imagePosX) - boxSize / 2, ((int) imagePosY) - boxSize / 2, boxSize, boxSize)); if (imageRect.isEmpty()) { continue; } final double[] rasterValues = new double[imageRect.width * imageRect.height]; raster.readPixels(imageRect.x, imageRect.y, imageRect.width, imageRect.height, rasterValues); final int[] maskBuffer = new int[imageRect.width * imageRect.height]; Arrays.fill(maskBuffer, 1); if (selectedMask != null) { selectedMask.readPixels(imageRect.x, imageRect.y, imageRect.width, imageRect.height, maskBuffer); } final int centerIndex = imageRect.width * (imageRect.height / 2) + (imageRect.width / 2); if (maskBuffer[centerIndex] == 0) { continue; } double sum = 0; double sumSqr = 0; int n = 0; boolean valid = false; for (int y = 0; y < imageRect.height; y++) { for (int x = 0; x < imageRect.width; x++) { final int index = y * imageRect.height + x; if (raster.isPixelValid(x + imageRect.x, y + imageRect.y) && maskBuffer[index] != 0) { final double rasterValue = rasterValues[index]; sum += rasterValue; sumSqr += rasterValue * rasterValue; n++; valid = true; } } } if (!valid) { continue; } double rasterMean = sum / n; double rasterSigma = n > 1 ? Math.sqrt((sumSqr - (sum * sum) / n) / (n - 1)) : 0.0; String localName = dataField.getLocalName(); Number attribute = (Number) feature.getAttribute(localName); final Collection<org.opengis.feature.Property> featureProperties = feature.getProperties(); final float correlativeData = attribute.floatValue(); final GeoPos geoPos = new GeoPos(); if (geoCoding.canGetGeoPos()) { final PixelPos pixelPos = new PixelPos(imagePosX, imagePosY); geoCoding.getGeoPos(pixelPos, geoPos); } else { geoPos.setInvalid(); } computedDataList.add( new ComputedData(imagePosX, imagePosY, (float) geoPos.getLat(), (float) geoPos.getLon(), (float) rasterMean, (float) rasterSigma, correlativeData, featureProperties)); } return computedDataList.toArray(new ComputedData[computedDataList.size()]); } @Override public void done() { try { final ValueAxis xAxis = getPlot().getDomainAxis(); final ValueAxis yAxis = getPlot().getRangeAxis(); xAxis.setAutoRange(false); yAxis.setAutoRange(false); scatterpointsDataset.removeAllSeries(); acceptableDeviationDataset.removeAllSeries(); regressionDataset.removeAllSeries(); getPlot().removeAnnotation(r2Annotation); computedDatas = null; final ComputedData[] data = get(); if (data.length == 0) { return; } computedDatas = data; final XYIntervalSeries scatterValues = new XYIntervalSeries(getCorrelativeDataName()); for (ComputedData computedData : computedDatas) { final float rasterMean = computedData.rasterMean; final float rasterSigma = computedData.rasterSigma; final float correlativeData = computedData.correlativeData; scatterValues.add(correlativeData, correlativeData, correlativeData, rasterMean, rasterMean - rasterSigma, rasterMean + rasterSigma); } computingData = true; scatterpointsDataset.addSeries(scatterValues); xAxis.setAutoRange(true); yAxis.setAutoRange(true); xAxis.setAutoRange(false); yAxis.setAutoRange(false); xAutoRangeAxisRange = new Range(xAxis.getLowerBound(), xAxis.getUpperBound()); yAutoRangeAxisRange = new Range(yAxis.getLowerBound(), yAxis.getUpperBound()); if (xAxisRangeControl.isAutoMinMax()) { xAxisRangeControl.adjustComponents(xAxis, 3); } else { xAxisRangeControl.adjustAxis(xAxis, 3); } if (yAxisRangeControl.isAutoMinMax()) { yAxisRangeControl.adjustComponents(yAxis, 3); } else { yAxisRangeControl.adjustAxis(yAxis, 3); } computeRegressionAndAcceptableDeviationData(); computingData = false; } catch (InterruptedException | CancellationException e) { SystemUtils.LOG.log(Level.WARNING, "Failed to compute correlative plot.", e); Dialogs.showMessage(CHART_TITLE, "Failed to compute correlative plot.\n" + "Calculation canceled.", JOptionPane.ERROR_MESSAGE, null); } catch (ExecutionException e) { SystemUtils.LOG.log(Level.WARNING, "Failed to compute correlative plot.", e); Dialogs.showMessage(CHART_TITLE, "Failed to compute correlative plot.\n" + "An error occurred:\n" + e.getCause().getMessage(), JOptionPane.ERROR_MESSAGE, null); } } }; swingWorker.execute(); }
From source file:org.esa.beam.visat.toolviews.stat.ScatterPlotPanel.java
private void compute(final Mask selectedMask) { final RasterDataNode raster = getRaster(); final AttributeDescriptor dataField = scatterPlotModel.dataField; if (raster == null || dataField == null) { return;// w w w. j ava2 s . c o m } SwingWorker<ComputedData[], Object> swingWorker = new SwingWorker<ComputedData[], Object>() { @Override protected ComputedData[] doInBackground() throws Exception { BeamLogManager.getSystemLogger().finest("start computing scatter plot data"); final List<ComputedData> computedDataList = new ArrayList<>(); final FeatureCollection<SimpleFeatureType, SimpleFeature> collection = scatterPlotModel.pointDataSource .getFeatureCollection(); final SimpleFeature[] features = collection.toArray(new SimpleFeature[collection.size()]); final int boxSize = scatterPlotModel.boxSize; final Rectangle sceneRect = new Rectangle(raster.getSceneRasterWidth(), raster.getSceneRasterHeight()); final GeoCoding geoCoding = raster.getGeoCoding(); final AffineTransform imageToModelTransform; imageToModelTransform = ImageManager.getImageToModelTransform(geoCoding); for (SimpleFeature feature : features) { final Point point = (Point) feature.getDefaultGeometryProperty().getValue(); Point2D modelPos = new Point2D.Float((float) point.getX(), (float) point.getY()); final Point2D imagePos = imageToModelTransform.inverseTransform(modelPos, null); if (!sceneRect.contains(imagePos)) { continue; } final float imagePosX = (float) imagePos.getX(); final float imagePosY = (float) imagePos.getY(); final Rectangle imageRect = sceneRect.intersection(new Rectangle( ((int) imagePosX) - boxSize / 2, ((int) imagePosY) - boxSize / 2, boxSize, boxSize)); if (imageRect.isEmpty()) { continue; } final double[] rasterValues = new double[imageRect.width * imageRect.height]; raster.readPixels(imageRect.x, imageRect.y, imageRect.width, imageRect.height, rasterValues); final int[] maskBuffer = new int[imageRect.width * imageRect.height]; Arrays.fill(maskBuffer, 1); if (selectedMask != null) { selectedMask.readPixels(imageRect.x, imageRect.y, imageRect.width, imageRect.height, maskBuffer); } final int centerIndex = imageRect.width * (imageRect.height / 2) + (imageRect.width / 2); if (maskBuffer[centerIndex] == 0) { continue; } double sum = 0; double sumSqr = 0; int n = 0; boolean valid = false; for (int y = 0; y < imageRect.height; y++) { for (int x = 0; x < imageRect.width; x++) { final int index = y * imageRect.height + x; if (raster.isPixelValid(x + imageRect.x, y + imageRect.y) && maskBuffer[index] != 0) { final double rasterValue = rasterValues[index]; sum += rasterValue; sumSqr += rasterValue * rasterValue; n++; valid = true; } } } if (!valid) { continue; } double rasterMean = sum / n; double rasterSigma = n > 1 ? Math.sqrt((sumSqr - (sum * sum) / n) / (n - 1)) : 0.0; String localName = dataField.getLocalName(); Number attribute = (Number) feature.getAttribute(localName); final Collection<org.opengis.feature.Property> featureProperties = feature.getProperties(); final float correlativeData = attribute.floatValue(); final GeoPos geoPos = new GeoPos(); if (geoCoding.canGetGeoPos()) { final PixelPos pixelPos = new PixelPos(imagePosX, imagePosY); geoCoding.getGeoPos(pixelPos, geoPos); } else { geoPos.setInvalid(); } computedDataList.add(new ComputedData(imagePosX, imagePosY, geoPos.getLat(), geoPos.getLon(), (float) rasterMean, (float) rasterSigma, correlativeData, featureProperties)); } return computedDataList.toArray(new ComputedData[computedDataList.size()]); } @Override public void done() { try { final ValueAxis xAxis = getPlot().getDomainAxis(); final ValueAxis yAxis = getPlot().getRangeAxis(); xAxis.setAutoRange(false); yAxis.setAutoRange(false); scatterpointsDataset.removeAllSeries(); acceptableDeviationDataset.removeAllSeries(); regressionDataset.removeAllSeries(); getPlot().removeAnnotation(r2Annotation); computedDatas = null; final ComputedData[] data = get(); if (data.length == 0) { return; } computedDatas = data; final XYIntervalSeries scatterValues = new XYIntervalSeries(getCorrelativeDataName()); for (ComputedData computedData : computedDatas) { final float rasterMean = computedData.rasterMean; final float rasterSigma = computedData.rasterSigma; final float correlativeData = computedData.correlativeData; scatterValues.add(correlativeData, correlativeData, correlativeData, rasterMean, rasterMean - rasterSigma, rasterMean + rasterSigma); } computingData = true; scatterpointsDataset.addSeries(scatterValues); xAxis.setAutoRange(true); yAxis.setAutoRange(true); xAxis.setAutoRange(false); yAxis.setAutoRange(false); xAutoRangeAxisRange = new Range(xAxis.getLowerBound(), xAxis.getUpperBound()); yAutoRangeAxisRange = new Range(yAxis.getLowerBound(), yAxis.getUpperBound()); if (xAxisRangeControl.isAutoMinMax()) { xAxisRangeControl.adjustComponents(xAxis, 3); } else { xAxisRangeControl.adjustAxis(xAxis, 3); } if (yAxisRangeControl.isAutoMinMax()) { yAxisRangeControl.adjustComponents(yAxis, 3); } else { yAxisRangeControl.adjustAxis(yAxis, 3); } computeRegressionAndAcceptableDeviationData(); computingData = false; } catch (InterruptedException | CancellationException e) { BeamLogManager.getSystemLogger().log(Level.WARNING, "Failed to compute correlative plot.", e); JOptionPane.showMessageDialog(getParentDialogContentPane(), "Failed to compute correlative plot.\n" + "Calculation canceled.", /*I18N*/ CHART_TITLE, /*I18N*/ JOptionPane.ERROR_MESSAGE); } catch (ExecutionException e) { BeamLogManager.getSystemLogger().log(Level.WARNING, "Failed to compute correlative plot.", e); JOptionPane.showMessageDialog(getParentDialogContentPane(), "Failed to compute correlative plot.\n" + "An error occurred:\n" + e.getCause().getMessage(), CHART_TITLE, /*I18N*/ JOptionPane.ERROR_MESSAGE); } } }; swingWorker.execute(); }
From source file:org.esa.snap.rcp.statistics.ScatterPlotPanel.java
private XYIntervalSeries computeRegressionData(double xStart, double xEnd) { if (scatterpointsDataset.getItemCount(0) > 1) { final double[] coefficients = Regression.getOLSRegression(scatterpointsDataset, 0); final Function2D curve = new LineFunction2D(coefficients[0], coefficients[1]); final XYSeries regressionData = DatasetUtilities.sampleFunction2DToSeries(curve, xStart, xEnd, 100, "regression line"); final XYIntervalSeries xyIntervalRegression = new XYIntervalSeries(regressionData.getKey()); for (int i = 0; i < regressionData.getItemCount(); i++) { XYDataItem item = regressionData.getDataItem(i); final double x = item.getXValue(); final double y = item.getYValue(); xyIntervalRegression.add(x, x, x, y, y, y); }/*from w w w. j a v a 2 s.c o m*/ return xyIntervalRegression; } else { JOptionPane.showMessageDialog(this, "Unable to compute regression line.\n" + "At least 2 values are needed to compute regression coefficients."); return null; } }
From source file:org.esa.beam.visat.toolviews.stat.ScatterPlotPanel.java
private XYIntervalSeries computeRegressionData(double xStart, double xEnd) { if (scatterpointsDataset.getItemCount(0) > 1) { final double[] coefficients = Regression.getOLSRegression(scatterpointsDataset, 0); final Function2D curve = new LineFunction2D(coefficients[0], coefficients[1]); final XYSeries regressionData = DatasetUtilities.sampleFunction2DToSeries(curve, xStart, xEnd, 100, "regression line"); final XYIntervalSeries xyIntervalRegression = new XYIntervalSeries(regressionData.getKey()); final List<XYDataItem> regressionDataItems = regressionData.getItems(); for (XYDataItem item : regressionDataItems) { final double x = item.getXValue(); final double y = item.getYValue(); xyIntervalRegression.add(x, x, x, y, y, y); }/* w w w . java 2 s .c o m*/ return xyIntervalRegression; } else { JOptionPane.showMessageDialog(this, "Unable to compute regression line.\n" + "At least 2 values are needed to compute regression coefficients."); return null; } }
From source file:org.esa.snap.rcp.statistics.ScatterPlotPanel.java
private XYIntervalSeries computeAcceptableDeviationData(double lowerBound, double upperBound) { final XYSeries identity = DatasetUtilities.sampleFunction2DToSeries(x -> x, lowerBound, upperBound, 100, "1:1 line"); final XYIntervalSeries xyIntervalSeries = new XYIntervalSeries(identity.getKey()); for (int i = 0; i < identity.getItemCount(); i++) { XYDataItem item = identity.getDataItem(i); final double x = item.getXValue(); final double y = item.getYValue(); if (scatterPlotModel.showAcceptableDeviation) { final double acceptableDeviation = scatterPlotModel.acceptableDeviationInterval; final double xOff = acceptableDeviation * x / 100; final double yOff = acceptableDeviation * y / 100; xyIntervalSeries.add(x, x - xOff, x + xOff, y, y - yOff, y + yOff); } else {//w w w. j av a 2s. c o m xyIntervalSeries.add(x, x, x, y, y, y); } } return xyIntervalSeries; }