Examples with DiscreteVariable edu.cmu.tetrad.data.DiscreteVariable used on opensource projects

Example 41 with DiscreteVariable

use of edu.cmu.tetrad.data.DiscreteVariable in project tetrad by cmu-phil.

the class DataCellRenderer method getTableCellRendererComponent.

public Component getTableCellRendererComponent(JTable table, Object value, boolean isSelected, boolean hasFocus, int row, int col) {
    // Have to set the alignment here, since this is the only place the col
    // index of the component is available...
    Component c = super.getTableCellRendererComponent(table, value, isSelected, hasFocus, row, col);
    DefaultTableCellRenderer renderer = (DefaultTableCellRenderer) c;
    if (dataSet.getNumColumns() > 0 && col >= getNumLeadingCols() && col < dataSet.getNumColumns() + getNumLeadingCols()) {
        int dataCol = col - getNumLeadingCols();
        Node variable = dataSet.getVariable(dataCol);
        if (variable instanceof DiscreteVariable) {
            renderer.setHorizontalAlignment(JLabel.RIGHT);
        } else {
            renderer.setHorizontalAlignment(JLabel.RIGHT);
        }
    }
    return renderer;
}

Example 42 with DiscreteVariable

use of edu.cmu.tetrad.data.DiscreteVariable in project tetrad by cmu-phil.

the class SubsetDiscreteVariablesAction method actionPerformed.

/**
 * Performs the action of loading a session from a file.
 */
public void actionPerformed(ActionEvent e) {
    DataModel selectedDataModel = getDataEditor().getSelectedDataModel();
    if (selectedDataModel instanceof DataSet) {
        DataSet dataSet = (DataSet) selectedDataModel;
        for (int i = dataSet.getNumColumns(); i >= 0; i--) {
            if (dataSet.getVariable(i) instanceof DiscreteVariable) {
                dataSet.removeColumn(i);
            }
        }
        DataModelList list = new DataModelList();
        list.add(dataSet);
        getDataEditor().reset(list);
        getDataEditor().selectFirstTab();
    } else {
        JOptionPane.showMessageDialog(JOptionUtils.centeringComp(), "Requires a tabular data set.");
    }
}

Example 43 with DiscreteVariable

use of edu.cmu.tetrad.data.DiscreteVariable in project tetrad by cmu-phil.

the class TabularDataTable method swapDiscreteColumnForContinuous.

private Node swapDiscreteColumnForContinuous(int col) {
    Node variable = dataSet.getVariable(col - getNumLeadingCols());
    if (variable == null) {
        throw new NullPointerException();
    }
    if (!isEmpty(dataSet, col - getNumLeadingCols())) {
        throw new IllegalArgumentException("Old column not empty.");
    }
    String name = variable.getName();
    DiscreteVariable var = new DiscreteVariable(name);
    var.setCategoryNamesDisplayed(true);
    dataSet.removeColumn(col - getNumLeadingCols());
    dataSet.addVariable(col - getNumLeadingCols(), var);
    pcs.firePropertyChange("modelChanged", null, null);
    return var;
}

Example 44 with DiscreteVariable

use of edu.cmu.tetrad.data.DiscreteVariable in project tetrad by cmu-phil.

the class TimeoutComparison method getSubgraph.

private Graph getSubgraph(Graph graph, boolean discrete1, boolean discrete2, DataModel DataModel) {
    if (discrete1 && discrete2) {
        Graph newGraph = new EdgeListGraph(graph.getNodes());
        for (Edge edge : graph.getEdges()) {
            Node node1 = DataModel.getVariable(edge.getNode1().getName());
            Node node2 = DataModel.getVariable(edge.getNode2().getName());
            if (node1 instanceof DiscreteVariable && node2 instanceof DiscreteVariable) {
                newGraph.addEdge(edge);
            }
        }
        return newGraph;
    } else if (!discrete1 && !discrete2) {
        Graph newGraph = new EdgeListGraph(graph.getNodes());
        for (Edge edge : graph.getEdges()) {
            Node node1 = DataModel.getVariable(edge.getNode1().getName());
            Node node2 = DataModel.getVariable(edge.getNode2().getName());
            if (node1 instanceof ContinuousVariable && node2 instanceof ContinuousVariable) {
                newGraph.addEdge(edge);
            }
        }
        return newGraph;
    } else {
        Graph newGraph = new EdgeListGraph(graph.getNodes());
        for (Edge edge : graph.getEdges()) {
            Node node1 = DataModel.getVariable(edge.getNode1().getName());
            Node node2 = DataModel.getVariable(edge.getNode2().getName());
            if (node1 instanceof DiscreteVariable && node2 instanceof ContinuousVariable) {
                newGraph.addEdge(edge);
            }
            if (node1 instanceof ContinuousVariable && node2 instanceof DiscreteVariable) {
                newGraph.addEdge(edge);
            }
        }
        return newGraph;
    }
}

Example 45 with DiscreteVariable

use of edu.cmu.tetrad.data.DiscreteVariable in project tetrad by cmu-phil.

the class DescriptiveStats method generateDescriptiveStats.

/**
 * Constructs a readable table of normality test results
 */
public static String generateDescriptiveStats(DataSet dataSet, Node variable) {
    NumberFormat nf = NumberFormatUtil.getInstance().getNumberFormat();
    int col = dataSet.getColumn(variable);
    double[] data = new double[dataSet.getNumRows()];
    boolean continuous = false;
    if (variable instanceof ContinuousVariable) {
        continuous = true;
        for (int i = 0; i < dataSet.getNumRows(); i++) {
            data[i] = dataSet.getDouble(i, col);
        }
    } else {
        try {
            for (int i = 0; i < dataSet.getNumRows(); i++) {
                DiscreteVariable var = (DiscreteVariable) variable;
                String category = var.getCategory(dataSet.getInt(i, col));
                int value = Integer.parseInt(category);
                data[i] = value;
            }
        } catch (NumberFormatException e) {
            return "Not a numerical discrete column.";
        }
    }
    String result = "Descriptive Statistics for: " + variable.getName() + "\n";
    result += "------------------------------------\n\n";
    double[] normalValues = normalParams(data);
    result += "Sample Size:\t\t" + dataSet.getNumRows() + "\n";
    result += "Mean:\t\t\t" + nf.format(normalValues[0]) + "\nStandard Deviation:\t" + nf.format(normalValues[1]) + "\nVariance:\t\t" + nf.format(normalValues[2]) + "\n";
    result += "Skewness:\t\t" + nf.format(StatUtils.skewness(data)) + "\n";
    result += "Excess Kurtosis:\t" + nf.format(StatUtils.kurtosis(data)) + "\n";
    if (continuous) {
        result += "SE Mean:\t\t" + nf.format(standardErrorMean(normalValues[1], dataSet.getNumRows())) + "\n";
    }
    double[] median = median(data);
    result += "Median:\t\t\t" + nf.format(median[0]) + "\n";
    if (continuous) {
        result += "Minimum Value:\t\t" + nf.format(median[1]) + "\nMaximum Value:\t\t" + nf.format(median[2]);
    }
    return result;
}