Laboratoire ICAR » Plateforme TXM

import java.util.List;

import org.eclipse.osgi.util.NLS;

import org.txm.ca.core.messages.CACoreMessages;

import org.txm.ca.core.preferences.CAPreferences;

import org.txm.ca.core.statsengine.r.functions.FactoMineRCA;

	protected boolean __compute(TXMProgressMonitor monitor) throws Exception {

		try {

				Log.warning("** Empty Lexical table. Computing aborted.");

				return false;

			}

			this.rowtitles = null;

			this.rowtabledata = null;

			try {

				if (this.getCA() != null) {

					RWorkspace.getRWorkspaceInstance().removeVariableFromWorkspace(this.getCA().getSymbol());

	 */

	public String[] getColNames() throws StatException {

		if (colnames == null) {

		}

		return colnames;

	}

	 * Gets the number of columns.

	 * 

	 * @return the number of columns

	 */

		return this.r_ca.getColumnsCount();

	}

	 * Gets the col all infos as Array of arrays.

	 *

	 * @return the col infos

	 */

		if (coltabledata != null) {

			return coltabledata.toArray();

	 * Gets the number of rows.

	 * 

	 * @return the number of rows

	 */

		return this.r_ca.getRowsCount();

	}

	 *

	 * @return the singular values

	 * @throws StatException the stat exception

	 */

		return r_ca.getSingularValues();

	}

	 * Get the singular values infos as List of Lists

	 *

	 * @return the singular values infos

	 */

		List<List<Object>> svtabledata = new ArrayList<>();

		double[] sv = null;

	 *

	 * @return the valeurs propres

	 * @throws StatException the stat exception

	 */

		return r_ca.getEigenvalues();

	}

	 *

	 * @return the valeurs propres sum

	 * @throws StatException the stat exception

	 */

		double sum = 0;

		for (double d : getValeursPropres()) {

			sum += d;

import org.jfree.chart.plot.PlotOrientation;

import org.jfree.chart.plot.XYPlot;

import org.jfree.chart.ui.TextAnchor;

import org.txm.ca.core.chartsengine.base.CAChartCreator;

import org.txm.ca.core.chartsengine.base.Utils;

import org.txm.ca.core.chartsengine.jfreechart.datasets.CAXYDataset;

 *

 */

public class JFCCAChartCreator extends JFCChartCreator implements CAChartCreator {

	@Override

	public JFreeChart createChart(ChartResult result) {

		CA ca = (CA) result;

		try {

					CAPreferences.getInstance().getBoolean(ChartsEnginePreferences.SHOW_LEGEND), false, false);

			// Custom renderer

			chart.getXYPlot().setRenderer(new CAItemSelectionRenderer(ca, chart));

		}

			Log.severe("Can't create CA factorial map scatter plot" + e);

			return null;

		}

	}

	@Override

	public void updateChart(ChartResult result) {

		CA ca = (CA) result;

		// freeze rendering while computing

		chart.setNotify(false);

		try {

			chart.getXYPlot().setDataset(new CAXYDataset(ca));

		}

			e.printStackTrace();

		}

		renderer.setSeriesVisible(0, ca.isShowVariables());

		renderer.setSeriesVisible(1, ca.isShowIndividuals());

		// Create the limits border

		this.createCAFactorialMapChartLimitsBorder(chart);

		this.updateChartCAFactorialMapSetDimensions(ca);

		super.updateChart(result);

	}

	/**

	 * Add some borders to the limits of the specified XY plot.

	 * @param plot

	 */

		XYPlot plot = chart.getXYPlot();

		// Remove all existent annotations

		plot.clearAnnotations();

		double minX = 0, maxX = 0, minY = 0, maxY = 0;

		// FIXME: new version

		// FIXME: old version, to remove when new version will be validated

		// Rows

		}

		// Cols

				minX = tmpMinX;

			}

		}

		// Rows

		}

		// Cols

				maxX = tmpMaxX;

			}

		}

		// Rows

		}

		// Cols

				minY = tmpMinY;

			}

		}

		// Rows

		}

		// Cols

				maxY = tmpMaxY;

			}

		}

		// Add some margins to the border

		// FIXME : to compute according to the real series shape dimensions

		// The code below doesn't work

		double shapeHalfWidth = 0.02;

		minX -= shapeHalfWidth;

		maxX += shapeHalfWidth;

		minY -= shapeHalfWidth;

		maxY += shapeHalfWidth;

		// Create the border

		XYLineAnnotation annotation;

		Color borderColor = Color.GRAY;

		// Left border

		annotation = new XYLineAnnotation(minX, minY, minX, maxY, dashedStroke, borderColor);

		annotation = new XYLineAnnotation(maxX, minY, maxX, maxY, dashedStroke, borderColor);

		// Bottom border

		annotation = new XYLineAnnotation(minX, minY, maxX, minY, dashedStroke, borderColor);

		annotation = new XYLineAnnotation(minX, maxY, maxX, maxY, dashedStroke, borderColor);

	}

	@Override

	public void updateChartCAFactorialMapHighlightPoints(Object chart, boolean rows, String[] labels) {

		// Rows

		int series = 0;

		// Columns

			series = 1;

		}

		selector.removeAllSelectedItems(series);

			selector.addSelectedItem(series, items[i]);

		}

	}

	@Override

		JFreeChart chart = (JFreeChart) ca.getChart();

			// the code below doesn't neither center the view nor update the axes ticks of the new chart, continue tests

			// Update the limits border

		}

			// TODO Auto-generated catch block

			e.printStackTrace();

		}

	@Override

	public ArrayList<String> getCAFactorialMapChartSelectedPoints(Object chart, int series) {

			CAXYDataset dataset = (CAXYDataset) ((JFreeChart) chart).getXYPlot().getDataset();

			int[] selectedItems = selector.getSelectedItems(series);

				pointLabels.add(dataset.getLabel(series, selectedItems[i]));

			}

		}

		return pointLabels;

	}

	@Override

	public void updateChartCAFactorialMapSetLabelItemsSelectionOrder(Object chart, String[] rowLabels, String[] colLabels) {

	}

	/**

	 * Gets a map where the values of the dataset are ordered according to the specified label arrays, keeping the order of these arrays and flatten but grouped by series.

	 * @param dataset

	 * @return

	 */

		int[] rowIndices = dataset.getOrderedLabelIndices(0, rowLabels);

		int[] colIndices = dataset.getOrderedLabelIndices(1, colLabels);

		int i = 0;

			itemData.add(0); // series

			itemData.add(rowIndices[i]); // item

			orderedValues.put(i, itemData);

		}

			itemData.add(1); // series

			itemData.add(colIndices[j]); // item

			orderedValues.put(j + i, itemData);

		}

		return orderedValues;

	}

	public Class getResultDataClass() {

		return CA.class;

	}

import org.jfree.chart.axis.NumberAxis;

import org.jfree.data.category.DefaultCategoryDataset;

import org.jfree.data.general.DatasetUtils;

import org.txm.ca.core.chartsengine.jfreechart.themes.highcharts.renderers.CAEigenvaluesItemSelectionRenderer;

import org.txm.ca.core.functions.CA;

import org.txm.ca.core.functions.Eigenvalues;

 *

 */

public class JFCEigenvaluesChartCreator extends JFCChartCreator {

	@Override

	public Object createChart(ChartResult result) {

		JFreeChart chart = null;

		// Creates the empty dataset

		DefaultCategoryDataset dataset = new DefaultCategoryDataset();

		// Create the chart

		chart = this.getChartsEngine().createCategoryBarChart(dataset, CACoreMessages.eigenvalues, CACoreMessages.axis, CACoreMessages.eigenvalue, false, false, false);

		// Custom renderer

		chart.getCategoryPlot().setRenderer(new CAEigenvaluesItemSelectionRenderer(ca));

		return chart;

	}

	@Override

	public void updateChart(ChartResult result) {

		JFreeChart chart = (JFreeChart) result.getChart();

		// freeze rendering while computing

		chart.setNotify(false);

		// update the dataset

		try {

			DefaultCategoryDataset dataset = (DefaultCategoryDataset) chart.getCategoryPlot().getDataset();

			dataset.clear();

			double[] singularValues = ca.getValeursPropres();

				dataset.setValue(singularValues[i], CACoreMessages.eigenvalue, String.valueOf(i + 1));

			}

		}

			Log.severe(NLS.bind(CACoreMessages.cantCreateBarChartOfTheCASingularValuesP0, e));

			Log.printStackTrace(e);

		}

		super.updateChart(result);

		chart.getCategoryPlot().setDomainGridlinesVisible(false);

	}

	public Class getResultDataClass() {

		return Eigenvalues.class;

	}

import org.jfree.chart.labels.CategoryToolTipGenerator;

import org.jfree.data.category.CategoryDataset;

import org.jfree.data.category.DefaultCategoryDataset;

import org.txm.ca.core.functions.CA;

import org.txm.ca.core.messages.CACoreMessages;

import org.txm.chartsengine.core.ChartsEngine;

/**

 * Renderer providing item selection system and drawing features for selected item and custom rendering for CA eigenvalues bar charts.

 * @author sjacquot

 *

 */

public class CAEigenvaluesItemSelectionRenderer extends ItemSelectionCategoryBarRenderer {

	/**

	 * Percent values number format.

	 */

	protected DecimalFormat percentValuesNumberFormat;

	/**

	 * Creates a renderer dedicated to CA charts.

	 */

		this.mouseOverItemSelector.setResult(ca);

		this.percentValuesNumberFormat = new DecimalFormat("#.00");

	}

	@Override

		this.setDefaultToolTipGenerator(new CategoryToolTipGenerator() {

			@Override

			public String generateToolTip(CategoryDataset dataset, int row, int column) {

				// Hexadecimal color

				Color color = (Color) getSeriesPaint(row);

				String hex = "#" + Integer.toHexString(color.getRGB()).substring(2);

				DefaultCategoryDataset catDataset = (DefaultCategoryDataset) dataset;

				Number value = catDataset.getValue(row, column);

				CA ca = (CA) getItemsSelector().getResult();

				return CustomHTMLToolTip.getDefaultHTMLBody(renderer, hex) + "<p>#" + catDataset.getColumnKey(column) + "</p>"

						+ "<p><span style=\"color: " + hex + ";\">" + catDataset.getRowKey(row) + ChartsEngineCoreMessages.EMPTY

						+ "<p><span style=\"color: " + hex + ";\">" + CACoreMessages.percent + ChartsEngineCoreMessages.EMPTY

						+ "<p><span style=\"color: " + hex + ";\">" + CACoreMessages.charts_singularValues_tooltipSum + CACoreMessages.percent

						+ "</body><html>";

			}

		});

	}

import org.txm.ca.core.messages.CACoreMessages;

import org.txm.lexicaltable.core.statsengine.data.ILexicalTable;

import org.txm.statsengine.core.StatException;

import org.txm.statsengine.r.core.RWorkspace;

import org.txm.statsengine.r.core.data.QuantitativeDataStructureImpl;

import org.txm.statsengine.r.core.exceptions.RWorkspaceException;

/**

 *

 * @author mdecorde

 */

public class FactoMineRCA implements ICA {

	/** The singular values. */

	private double[] eigenvalues = null;

	/** The singular values2. */

	private double[] singularValues = null;

	/** The rowmass. */

	private double[] rowmass = null;

	/** The colinertia. */

	private double[] colinertia = null;

	/** The rowcos2. */

	private double[][] rowcos2 = null;

	/** The colcontrib. */

	private double[][] colcontrib = null;

	/** The rw. */

	private final RWorkspace rw = RWorkspace.getRWorkspaceInstance();

	/** The symbol. */

	private final String symbol = QuantitativeDataStructureImpl.createSymbole(FactoMineRCA.class);

	/** The rowscoords. */

	private double[][] rowscoords;

	/** The colscoords. */

	private double[][] colscoords;

	/**

	 * Create a correspondence analysis on the given table. The correspondence analysis is computed as soon as the object is created.

	 *

	 * @throws StatException the stat exception

	 */

	public FactoMineRCA(ILexicalTable table) throws StatException {

		loadLibrary();

		this.table = table;

	}

	public void compute() throws StatException {

		if (!rw.containsVariable(table.getSymbol())) {

			throw new StatException(CACoreMessages.error_lexicalTableNotFoundInWorkspace);

		}

		try {

			throw new StatException(NLS.bind(CACoreMessages.error_errorWhileComputingCAP0, e.getMessage()), e);

		}

	}

	 * @see org.txm.stat.engine.r.function.ICA#getColContrib()

	 */

	@Override

				REXP sv = rw.extractItemFromListByName(symbol, "col$contrib"); //$NON-NLS-1$

				colcontrib = sv.asDoubleMatrix();

				// Arrays.sort(rowdist);

				throw new StatException(NLS.bind(CACoreMessages.error_failedToGetContributionColumnP0, e.getMessage()), e);

				org.txm.utils.logger.Log.printStackTrace(e);

			}

		}

		return colcontrib;

	}

	 * @see org.txm.stat.engine.r.function.ICA#getColCos2()

	 */

	@Override

				REXP sv = rw.extractItemFromListByName(symbol, "col$cos2"); //$NON-NLS-1$

				colcos2 = sv.asDoubleMatrix();

				// Arrays.sort(rowdist);

				throw new StatException(NLS.bind(CACoreMessages.error_failedToGetCos2ColumnP0, e.getMessage()), e);

				org.txm.utils.logger.Log.printStackTrace(e);

			}

		}

		return colcos2;

	}

	/**

	 * Get the rows mass.

	 *

	 */

	@Override

	public double[] getColDist() throws StatException {

			double[][] colcoords = getColsCoords();

			coldist = new double[colcoords.length];

					coldist[i] += Math.pow(colcoords[i][c], 2);

		}

		return coldist;

	}

	 * @see org.txm.stat.engine.r.function.ICA#getColsCoords()

	 */

	@Override

			try {

				REXP exp = rw.extractItemFromListByName(symbol, "col$coord"); //$NON-NLS-1$

				colscoords = exp.asDoubleMatrix();

				// multiply coords by sv

				org.txm.utils.logger.Log.printStackTrace(e);

			}

		}

		return colscoords;

	}

	/**

	 * Get the rows mass.

	 *

				REXP sv = rw.extractItemFromListByName(symbol, "col$contrib"); //$NON-NLS-1$

				colinertia = RWorkspace.toDouble(sv);

				// Arrays.sort(colinertia);

				throw new StatException(CACoreMessages.bind(CACoreMessages.error_unableToExtractSingularValuesP0, e.getMessage()), e);

			}

		}

		return colinertia;

	}

	/**

	 * Get the rows mass.

	 *

				REXP sv = rw.extractItemFromListByName(symbol, "call$marge.col"); //$NON-NLS-1$

				colmass = RWorkspace.toDouble(sv);

				// Arrays.sort(colmass);

				throw new StatException(CACoreMessages.bind(CACoreMessages.error_unableToExtractSingularValuesP0, e.getMessage()), e);

			}

		}

		return colmass;

	}

	 * @see org.txm.stat.engine.r.function.ICA#getRowContrib()

	 */

	@Override

	public double[][] getRowContrib() throws StatException {

		if (rowcontrib == null) {

			try {

				REXP sv = rw.extractItemFromListByName(symbol, "row$contrib"); //$NON-NLS-1$

				rowcontrib = sv.asDoubleMatrix();

				// Arrays.sort(rowdist);

				throw new StatException(NLS.bind(CACoreMessages.error_failedToGetConstributionRowP0, e.getMessage()), e);

				org.txm.utils.logger.Log.printStackTrace(e);

			}

		}

		return rowcontrib;

	}

	 * @see org.txm.stat.engine.r.function.ICA#getRowCos2()

	 */

	@Override

				REXP sv = rw.extractItemFromListByName(symbol, "row$cos2"); //$NON-NLS-1$

				rowcos2 = sv.asDoubleMatrix();

				// Arrays.sort(rowdist);

				throw new StatException(NLS.bind(CACoreMessages.error_failedToGetCos2RowP0, e.getMessage()), e);

				org.txm.utils.logger.Log.printStackTrace(e);

			}

		}

		return rowcos2;

	}

	/**

	 * Get the rows mass.

	 *

	 */

	@Override

	public double[] getRowDist() throws StatException {

			double[][] rowcoords = getRowsCoords();

			rowdist = new double[rowcoords.length];

					rowdist[i] += Math.pow(rowcoords[i][c], 2);

		}

		return rowdist;

	}

	 * @see org.txm.stat.engine.r.function.ICA#getRowsCoords()

	 */

	@Override

				REXP sv = rw.extractItemFromListByName(symbol, "row$coord"); //$NON-NLS-1$

				rowscoords = sv.asDoubleMatrix();

				org.txm.utils.logger.Log.printStackTrace(e);

			}

		}

		return rowscoords;

	}

	/**

	 * Get the rows mass.

	 *

				REXP sv = rw.extractItemFromListByName(symbol, "row$contrib"); //$NON-NLS-1$

				rowinertia = RWorkspace.toDouble(sv);

				// Arrays.sort(rowinertia);

				throw new StatException(CACoreMessages.bind(CACoreMessages.error_unableToExtractSingularValuesP0, e.getMessage()), e);

			}

		}

		return rowinertia;

	}

	/**

	 * Get the rows mass.

	 *

				REXP sv = rw.extractItemFromListByName(symbol, "call$marge.row"); //$NON-NLS-1$

				rowmass = RWorkspace.toDouble(sv);

				// Arrays.sort(rowmass);

				throw new StatException(CACoreMessages.bind(CACoreMessages.error_unableToExtractSingularValuesP0, e.getMessage()), e);

			}

		}

		return rowmass;

	}

	/**

	 * Get the singular values.

	 *

	 * @return the singular values

	 * @throws StatException the stat exception

	 */

	@Override

		if (singularValues == null) {

			getEigenvalues();

			singularValues = new double[eigenvalues.length];

				singularValues[i] = Math.pow(eigenvalues[i], 0.5);

		}

		return singularValues;

	}

	 * @see org.txm.stat.engine.r.function.ICA#getSymbol()

	 */

	@Override

	public String getSymbol() {

		return symbol;

	}

	/**

	 * Gets the valeurs propres.

	 *

	 * @return the singular values pow 2

	 * @throws StatException the stat exception

	 */

	@Override

		if (eigenvalues == null) {

			}

		}

		return eigenvalues;

	 */

	@Override

	public String getEigenvaluesRSymbol() throws StatException {

	}

	 * @see org.txm.stat.engine.r.function.ICA#loadLibrary()

	 */

	@Override

		try {

			rw.voidEval("library(FactoMineR)"); //$NON-NLS-1$

			System.out.println(NLS.bind(CACoreMessages.error_canNotLoadCALibraryP0, e));

			return false;

		}

		return true;

	}

	/**

	 * Draw in the given file a plot of the factorial map.

	 *

	public boolean toTxt(File file, String encoding, String colseparator, String txtseparator) {

		try {

			RWorkspace rw = RWorkspace.getRWorkspaceInstance();

			rw.eval("sink()"); //$NON-NLS-1$

			org.txm.utils.logger.Log.printStackTrace(e);

			return false;

		}

		return true;

	}

	@Override

	}

	@Override