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

Example 6 with DiscreteVariable

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

the class Mgm method search.

@Override
public Graph search(DataModel ds, Parameters parameters) {
    // Notify the user that you need at least one continuous and one discrete variable to run MGM
    List<Node> variables = ds.getVariables();
    boolean hasContinuous = false;
    boolean hasDiscrete = false;
    for (Node node : variables) {
        if (node instanceof ContinuousVariable) {
            hasContinuous = true;
        }
        if (node instanceof DiscreteVariable) {
            hasDiscrete = true;
        }
    }
    if (!hasContinuous || !hasDiscrete) {
        throw new IllegalArgumentException("You need at least one continuous and one discrete variable to run MGM.");
    }
    if (parameters.getInt("bootstrapSampleSize") < 1) {
        DataSet _ds = DataUtils.getMixedDataSet(ds);
        double mgmParam1 = parameters.getDouble("mgmParam1");
        double mgmParam2 = parameters.getDouble("mgmParam2");
        double mgmParam3 = parameters.getDouble("mgmParam3");
        double[] lambda = { mgmParam1, mgmParam2, mgmParam3 };
        MGM m = new MGM(_ds, lambda);
        return m.search();
    } else {
        Mgm algorithm = new Mgm();
        DataSet data = (DataSet) ds;
        GeneralBootstrapTest search = new GeneralBootstrapTest(data, algorithm, parameters.getInt("bootstrapSampleSize"));
        BootstrapEdgeEnsemble edgeEnsemble = BootstrapEdgeEnsemble.Highest;
        switch(parameters.getInt("bootstrapEnsemble", 1)) {
            case 0:
                edgeEnsemble = BootstrapEdgeEnsemble.Preserved;
                break;
            case 1:
                edgeEnsemble = BootstrapEdgeEnsemble.Highest;
                break;
            case 2:
                edgeEnsemble = BootstrapEdgeEnsemble.Majority;
        }
        search.setEdgeEnsemble(edgeEnsemble);
        search.setParameters(parameters);
        search.setVerbose(parameters.getBoolean("verbose"));
        return search.search();
    }
}

Example 7 with DiscreteVariable

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

the class IndTestMultinomialLogisticRegression method expandVariable.

private List<Node> expandVariable(DataSet dataSet, Node node) {
    if (node instanceof ContinuousVariable) {
        return Collections.singletonList(node);
    }
    if (node instanceof DiscreteVariable && ((DiscreteVariable) node).getNumCategories() < 3) {
        return Collections.singletonList(node);
    }
    if (!(node instanceof DiscreteVariable)) {
        throw new IllegalArgumentException();
    }
    List<String> varCats = new ArrayList<>(((DiscreteVariable) node).getCategories());
    varCats.remove(0);
    List<Node> variables = new ArrayList<>();
    for (String cat : varCats) {
        Node newVar;
        do {
            String newVarName = node.getName() + "MULTINOM" + "." + cat;
            newVar = new DiscreteVariable(newVarName, 2);
        } while (dataSet.getVariable(newVar.getName()) != null);
        variables.add(newVar);
        dataSet.addVariable(newVar);
        int newVarIndex = dataSet.getColumn(newVar);
        int numCases = dataSet.getNumRows();
        for (int l = 0; l < numCases; l++) {
            Object dataCell = dataSet.getObject(l, dataSet.getColumn(node));
            int dataCellIndex = ((DiscreteVariable) node).getIndex(dataCell.toString());
            if (dataCellIndex == ((DiscreteVariable) node).getIndex(cat))
                dataSet.setInt(l, newVarIndex, 1);
            else
                dataSet.setInt(l, newVarIndex, 0);
        }
    }
    return variables;
}

Example 8 with DiscreteVariable

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

the class BayesPmEditorWizard method copyCategories.

private void copyCategories() {
    Node node = (Node) variableChooser.getSelectedItem();
    DiscreteVariable variable = (DiscreteVariable) bayesPm.getVariable(node);
    this.copiedCategories = variable.getCategories();
}

Example 9 with DiscreteVariable

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

the class BayesUpdaterClassifierEditor method doClassify.

private void doClassify() {
    DiscreteVariable variable = (DiscreteVariable) getVariableDropdown().getSelectedItem();
    String varName = variable.getName();
    String category = (String) getCategoryDropdown().getSelectedItem();
    int catIndex = variable.getIndex(category);
    getClassifier().setTarget(varName, catIndex);
    getClassifier().classify();
}

Example 10 with DiscreteVariable

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

the class BayesUpdaterClassifierEditor method showConfusionMatrix.

private void showConfusionMatrix() {
    int tabIndex = -1;
    for (int i = 0; i < getTabbedPane().getTabCount(); i++) {
        if ("Confusion Matrix".equals(getTabbedPane().getTitleAt(i))) {
            getTabbedPane().remove(i);
            tabIndex = i;
        }
    }
    StringBuilder buf = new StringBuilder();
    int[][] crossTabs = getClassifier().crossTabulation();
    // this case, don't put the confusion matrix back in.
    if (crossTabs == null) {
        return;
    }
    DiscreteVariable targetVariable = getClassifier().getTargetVariable();
    int nvalues = targetVariable.getNumCategories();
    int ncases = getClassifier().getNumCases();
    int ntot = getClassifier().getTotalUsableCases();
    // System.out.println("Number correct = " + numCorrect);
    // buf.append("<html><pre>");
    buf.append("Total number of usable cases = ");
    buf.append(ntot);
    buf.append(" out of ");
    buf.append(ncases);
    buf.append("\n\nTarget Variable ");
    buf.append(targetVariable);
    buf.append("\n\t\tEstimated\t");
    buf.append("\nObserved\t");
    for (int i = 0; i < nvalues - 1; i++) {
        buf.append(targetVariable.getCategory(i));
        buf.append("\t");
    }
    buf.append(targetVariable.getCategory(nvalues - 1));
    for (int i = 0; i < nvalues; i++) {
        buf.append("\n");
        buf.append(targetVariable.getCategory(i));
        buf.append("\t");
        for (int j = 0; j < nvalues - 1; j++) {
            buf.append(crossTabs[i][j]);
            buf.append("\t");
        }
        buf.append(crossTabs[i][nvalues - 1]);
    }
    buf.append("\n\nPercentage correctly classified:  ");
    buf.append(getClassifier().getPercentCorrect());
    // buf.append("</pre></html>");
    JTextArea label = new JTextArea(buf.toString());
    // label.setFocusable(false);
    label.setFont(new Font("SansSerif", Font.PLAIN, 14));
    JPanel panel = new JPanel();
    panel.setLayout(new BorderLayout());
    panel.setBackground(Color.WHITE);
    Box b1 = Box.createVerticalBox();
    Box b2 = Box.createHorizontalBox();
    b2.add(Box.createHorizontalStrut(5));
    b2.add(label);
    b2.add(Box.createHorizontalGlue());
    b1.add(b2);
    b1.add(Box.createVerticalGlue());
    b1.add(Box.createVerticalGlue());
    panel.add(b1, BorderLayout.CENTER);
    JScrollPane scroll = new JScrollPane(panel);
    if (tabIndex == -1) {
        getTabbedPane().add("Confusion Matrix", scroll);
    } else {
        getTabbedPane().add(scroll, tabIndex);
        getTabbedPane().setTitleAt(tabIndex, "Confusion Matrix");
    }
}