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

Example 51 with DiscreteVariable

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

the class BayesPm method copyAvailableInformationFromOldBayesPm.

// =========================PRIVATE METHODS=============================//
private void copyAvailableInformationFromOldBayesPm(BayesPm oldbayesPm, int lowerBound, int upperBound) {
    Graph newGraph = getDag();
    Graph oldGraph = oldbayesPm.getDag();
    for (Node node1 : newGraph.getNodes()) {
        if (oldGraph.containsNode(node1)) {
            copyOldValues(oldbayesPm, node1, node1, lowerBound, upperBound);
        } else {
            setNewValues(node1, lowerBound, upperBound);
        }
    }
    for (Node node2 : newGraph.getNodes()) {
        if (oldGraph.containsNode(node2)) {
            Node _node2 = dag.getNode(node2.getName());
            DiscreteVariable oldNode2 = oldbayesPm.nodesToVariables.get(_node2);
            oldNode2.setNodeType(node2.getNodeType());
            oldNode2.setName(node2.getName());
            this.nodesToVariables.put(_node2, oldNode2);
        } else {
            setNewValues(node2, lowerBound, upperBound);
        }
    }
}

Example 52 with DiscreteVariable

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

the class MlBayesImObs method simulateTimeSeries.

private DataSet simulateTimeSeries(int sampleSize) {
    TimeLagGraph timeSeriesGraph = getBayesPm().getDag().getTimeLagGraph();
    List<Node> variables = new ArrayList<>();
    for (Node node : timeSeriesGraph.getLag0Nodes()) {
        variables.add(new DiscreteVariable(timeSeriesGraph.getNodeId(node).getName()));
    }
    List<Node> lag0Nodes = timeSeriesGraph.getLag0Nodes();
    DataSet fullData = new ColtDataSet(sampleSize, variables);
    Graph contemporaneousDag = timeSeriesGraph.subgraph(lag0Nodes);
    List<Node> tierOrdering = contemporaneousDag.getCausalOrdering();
    int[] tiers = new int[tierOrdering.size()];
    for (int i = 0; i < tierOrdering.size(); i++) {
        tiers[i] = getNodeIndex(tierOrdering.get(i));
    }
    // Construct the sample.
    int[] combination = new int[tierOrdering.size()];
    for (int i = 0; i < sampleSize; i++) {
        int[] point = new int[nodes.length];
        for (int nodeIndex : tiers) {
            double cutoff = RandomUtil.getInstance().nextDouble();
            for (int k = 0; k < getNumParents(nodeIndex); k++) {
                combination[k] = point[getParent(nodeIndex, k)];
            }
            int rowIndex = getRowIndex(nodeIndex, combination);
            double sum = 0.0;
            for (int k = 0; k < getNumColumns(nodeIndex); k++) {
                double probability = getProbability(nodeIndex, rowIndex, k);
                if (Double.isNaN(probability)) {
                    throw new IllegalStateException("Some probability " + "values in the BayesIm are not filled in; " + "cannot simulate data.");
                }
                sum += probability;
                if (sum >= cutoff) {
                    point[nodeIndex] = k;
                    break;
                }
            }
        }
    }
    return fullData;
}

Example 53 with DiscreteVariable

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

the class MlBayesImObs method simulateDataHelper.

/**
 * Constructs a random sample using the given already allocated data set, to
 * avoid allocating more memory.
 */
private DataSet simulateDataHelper(DataSet dataSet, boolean latentDataSaved) {
    if (dataSet.getNumColumns() != nodes.length) {
        throw new IllegalArgumentException("When rewriting the old data set, " + "number of variables in data set must equal number of variables " + "in Bayes net.");
    }
    int sampleSize = dataSet.getNumRows();
    int numMeasured = 0;
    int[] map = new int[nodes.length];
    List<Node> variables = new LinkedList<>();
    for (int j = 0; j < nodes.length; j++) {
        if (!latentDataSaved && nodes[j].getNodeType() != NodeType.MEASURED) {
            continue;
        }
        int numCategories = bayesPm.getNumCategories(nodes[j]);
        List<String> categories = new LinkedList<>();
        for (int k = 0; k < numCategories; k++) {
            categories.add(bayesPm.getCategory(nodes[j], k));
        }
        DiscreteVariable var = new DiscreteVariable(nodes[j].getName(), categories);
        variables.add(var);
        int index = ++numMeasured - 1;
        map[index] = j;
    }
    for (int i = 0; i < variables.size(); i++) {
        Node node = dataSet.getVariable(i);
        Node _node = variables.get(i);
        dataSet.changeVariable(node, _node);
    }
    constructSample(sampleSize, numMeasured, dataSet, map);
    return dataSet;
}

Example 54 with DiscreteVariable

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

the class BayesXmlRenderer method getVariablesElement.

private static Element getVariablesElement(BayesIm bayesIm) {
    Element element = new Element("bnVariables");
    for (int i = 0; i < bayesIm.getNumNodes(); i++) {
        Node node = bayesIm.getNode(i);
        BayesPm bayesPm = bayesIm.getBayesPm();
        DiscreteVariable variable = (DiscreteVariable) bayesPm.getVariable(node);
        Element element1 = new Element("discreteVariable");
        element1.addAttribute(new Attribute("name", variable.getName()));
        element1.addAttribute(new Attribute("index", "" + i));
        boolean latent = node.getNodeType() == NodeType.LATENT;
        if (latent) {
            element1.addAttribute(new Attribute("latent", "yes"));
        }
        element1.addAttribute(new Attribute("x", "" + node.getCenterX()));
        element1.addAttribute(new Attribute("y", "" + node.getCenterY()));
        for (int j = 0; j < variable.getNumCategories(); j++) {
            Element category = new Element("category");
            category.addAttribute(new Attribute("name", variable.getCategory(j)));
            category.addAttribute(new Attribute("index", "" + j));
            element1.appendChild(category);
        }
        element.appendChild(element1);
    }
    return element;
}

Example 55 with DiscreteVariable

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

the class IndTestMixedMultipleTTest 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());
    // first category is reference
    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;
}