Java DataTable.add方法代码示例

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
private Plotter getPlotter(Object renderable) {
	SVDModel model = (SVDModel) renderable;

	double[] cumulativeVariance = new double[model.getNumberOfComponents()];
	for (int i = 0; i < cumulativeVariance.length; i++) {
		cumulativeVariance[i] = model.getCumulativeSingularValue(i);
	}
	DataTable dataTable = new SimpleDataTable("Cumulative Proportion of Singular Values", new String[] {
			"Singular Value Vectors", "Cumulative Proportion of Singular Values" });
	dataTable.add(new SimpleDataTableRow(new double[] { 0.0d, 0.0d }));
	for (int i = 0; i < cumulativeVariance.length; i++) {
		dataTable.add(new SimpleDataTableRow(new double[] { i + 1, cumulativeVariance[i] }));
	}

	PlotterConfigurationModel settings = new PlotterConfigurationModel(
			PlotterConfigurationModel.WEIGHT_PLOTTER_SELECTION, dataTable);
	settings.setPlotter(PlotterConfigurationModel.LINES_PLOT);
	Plotter plotter = settings.getPlotter();
	settings.setAxis(0, 0);
	settings.enablePlotColumn(1);

	return plotter;
}
 

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
private Plotter getPlotter(Object renderable) {
	AbstractEigenvectorModel model = (AbstractEigenvectorModel) renderable;
	double[] cumulativeVariance = model.getCumulativeVariance();

	DataTable dataTable = new SimpleDataTable("Cumulative Proportion of Variance", new String[] {
			"Principal Components", "Cumulative Proportion of Variance" });
	dataTable.add(new SimpleDataTableRow(new double[] { 0.0d, 0.0d }));
	for (int i = 0; i < cumulativeVariance.length; i++) {
		dataTable.add(new SimpleDataTableRow(new double[] { i + 1, cumulativeVariance[i] }));
	}

	PlotterConfigurationModel settings = new PlotterConfigurationModel(
			PlotterConfigurationModel.WEIGHT_PLOTTER_SELECTION, dataTable);
	settings.setPlotter(PlotterConfigurationModel.LINES_PLOT);
	Plotter plotter = settings.getPlotter();
	settings.setAxis(0, 0);
	settings.enablePlotColumn(1);

	return plotter;
}
 

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
public DataTable createDataTable() {
	DataTable dataTable = new SimpleDataTable("Attribute Weights", new String[] { "attribute", "weight" });
	for (Map.Entry<String, AttributeWeight> entry : weightMap.entrySet()) {
		String attName = entry.getKey();
		AttributeWeight attWeight = entry.getValue();
		double index = dataTable.mapString(0, attName);
		double weightValue = attWeight.getWeight();
		double[] data = new double[] { index, weightValue };
		dataTable.add(new SimpleDataTableRow(data, attName));
	}
	return dataTable;
}
 

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
private DataTable createDataTable(ROCData data, boolean showSlope, boolean showThresholds) {
	DataTable dataTable = new SimpleDataTable("ROC Plot", new String[] { "FP/N", "TP/P", "Slope", "Threshold" });
	Iterator<ROCPoint> i = data.iterator();
	int pointCounter = 0;
	int eachPoint = Math.max(1, (int) Math.round((double) data.getNumberOfPoints() / (double) MAX_ROC_POINTS));
	while (i.hasNext()) {
		ROCPoint point = i.next();
		if ((pointCounter == 0) || ((pointCounter % eachPoint) == 0) || (!i.hasNext())) { // draw
																							// only
																							// MAX_ROC_POINTS
																							// points
			double fpRate = point.getFalsePositives() / data.getTotalNegatives();
			double tpRate = point.getTruePositives() / data.getTotalPositives();
			double threshold = point.getConfidence();
			dataTable.add(new SimpleDataTableRow(new double[] {
					fpRate, // x
					tpRate, // y1
					data.getBestIsometricsTPValue()
							+ (fpRate * slope * (data.getTotalNegatives() / data.getTotalPositives())), // y2:
																										// slope
					threshold // y3: threshold or confidence
					}));
		}
		pointCounter++;
	}
	return dataTable;
}
 

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
/** Creates a dialog containing a plotter for a given list of ROC data points. */
public void createLiftChartPlot(List<double[]> data) {
	// create data table
	DataTable dataTable = new SimpleDataTable("Lift Chart", new String[] { "Fraction", "Lift" });
	Iterator i = data.iterator();
	int pointCounter = 0;
	int eachPoint = Math.max(1, (int) Math.round((double) data.size() / (double) MAX_LIFT_POINTS));
	while (i.hasNext()) {
		double[] point = (double[]) i.next();
		if ((pointCounter == 0) || ((pointCounter % eachPoint) == 0) || (!i.hasNext())) {
			double fraction = point[0];
			double lift = point[1];
			if (Double.isNaN(lift)) {
				lift = this.maxLift;
			}
			dataTable.add(new SimpleDataTableRow(new double[] { fraction, lift }));
		}
		pointCounter++;
	}

	// create plotter
	SimplePlotterDialog plotter = new SimplePlotterDialog(dataTable);
	plotter.setXAxis(0);
	plotter.plotColumn(1, true);
	// plotter.setDrawRange(0.0d, 1.0d, 0.0d, 1.0d);
	plotter.setVisible(true);
}
 

import com.rapidminer.datatable.DataTable; //导入方法依赖的package包/类
private Plotter createHistogramPlotter(SimilarityMeasureObject sim, ExampleSet exampleSet) {
	DistanceMeasure measure = sim.getDistanceMeasure();
	DataTable dataTable = new SimpleDataTable("Histogram", new String[] { "Histogram" });
	double sampleRatio = Math.min(1.0d, 500.0d / exampleSet.size());

	Random random = new Random();
	int i = 0;
	for (Example example : exampleSet) {
		int j = 0;
		for (Example comExample : exampleSet) {
			if (j != i && random.nextDouble() < sampleRatio) {
				double simValue;
				if (measure.isDistance()) {
					simValue = measure.calculateDistance(example, comExample);
				} else {
					simValue = measure.calculateSimilarity(example, comExample);
				}
				dataTable.add(new SimpleDataTableRow(new double[] { simValue }));
			}
			j++;
		}
		i++;
	}
	PlotterConfigurationModel settings = new PlotterConfigurationModel(PlotterConfigurationModel.HISTOGRAM_PLOT,
			dataTable);

	settings.enablePlotColumn(0);
	settings.setParameterAsInt(HistogramChart.PARAMETER_NUMBER_OF_BINS, 100);

	return settings.getPlotter();
}