Examples with Node edu.cmu.tetrad.graph.Node used on opensource projects

Example 86 with Node

use of edu.cmu.tetrad.graph.Node in project tetrad by cmu-phil.

the class FtfcRunner method getVariables.

public List<Node> getVariables() {
    List<Node> latents = new ArrayList<>();
    for (String name : getVariableNames()) {
        Node node = new ContinuousVariable(name);
        node.setNodeType(NodeType.LATENT);
        latents.add(node);
    }
    return latents;
}

Example 87 with Node

use of edu.cmu.tetrad.graph.Node in project tetrad by cmu-phil.

the class GlassoRunner method execute.

// ===================PUBLIC METHODS OVERRIDING ABSTRACT================//
public void execute() {
    Object dataModel = getDataModel();
    Parameters params = getParams();
    if (dataModel instanceof DataSet) {
        DataSet dataSet = (DataSet) dataModel;
        DoubleMatrix2D cov = new DenseDoubleMatrix2D(dataSet.getCovarianceMatrix().toArray());
        Glasso glasso = new Glasso(cov);
        glasso.setMaxit((int) params.get("maxit", 10000));
        glasso.setIa(params.getBoolean("ia", false));
        glasso.setIs(params.getBoolean("is", false));
        glasso.setItr(params.getBoolean("itr", false));
        glasso.setIpen(params.getBoolean("ipen", false));
        glasso.setThr(params.getDouble("thr", 1e-4));
        glasso.setRhoAllEqual(1.0);
        Glasso.Result result = glasso.search();
        TetradMatrix wwi = new TetradMatrix(result.getWwi().toArray());
        List<Node> variables = dataSet.getVariables();
        Graph resultGraph = new EdgeListGraph(variables);
        for (int i = 0; i < variables.size(); i++) {
            for (int j = i + 1; j < variables.size(); j++) {
                if (wwi.get(i, j) != 0.0 && wwi.get(i, j) != 0.0) {
                    resultGraph.addUndirectedEdge(variables.get(i), variables.get(j));
                }
            }
        }
        setResultGraph(resultGraph);
    }
}

Example 88 with Node

use of edu.cmu.tetrad.graph.Node in project tetrad by cmu-phil.

the class SemEstimatorWrapper method serializableInstance.

// public SemEstimatorWrapper(DataWrapper dataWrapper,
// SemPmWrapper semPmWrapper,
// SemImWrapper semImWrapper,
// Parameters params) {
// if (dataWrapper == null) {
// throw new NullPointerException();
// }
// 
// if (semPmWrapper == null) {
// throw new NullPointerException();
// }
// 
// if (semImWrapper == null) {
// throw new NullPointerException();
// }
// 
// DataSet dataSet =
// (DataSet) dataWrapper.getSelectedDataModel();
// SemPm semPm = semPmWrapper.getSemPm();
// SemIm semIm = semImWrapper.getSemIm();
// 
// this.semEstimator = new SemEstimator(dataSet, semPm, getOptimizer());
// if (!degreesOfFreedomCheck(semPm)) return;
// this.semEstimator.setTrueSemIm(semIm);
// this.semEstimator.setNumRestarts(getParams().getInt("numRestarts", 1));
// this.semEstimator.estimate();
// 
// this.params = params;
// 
// log();
// }
/**
 * Generates a simple exemplar of this class to test serialization.
 *
 * @see TetradSerializableUtils
 */
public static SemEstimatorWrapper serializableInstance() {
    List<Node> variables = new LinkedList<>();
    ContinuousVariable x = new ContinuousVariable("X");
    variables.add(x);
    DataSet dataSet = new ColtDataSet(10, variables);
    for (int i = 0; i < dataSet.getNumRows(); i++) {
        for (int j = 0; j < dataSet.getNumColumns(); j++) {
            dataSet.setDouble(i, j, RandomUtil.getInstance().nextDouble());
        }
    }
    Dag dag = new Dag();
    dag.addNode(x);
    SemPm pm = new SemPm(dag);
    Parameters params1 = new Parameters();
    return new SemEstimatorWrapper(dataSet, pm, params1);
}

Example 89 with Node

use of edu.cmu.tetrad.graph.Node in project tetrad by cmu-phil.

the class BayesEstimatorWrapper method estimate.

private void estimate(DataSet dataSet, BayesPm bayesPm) {
    Graph graph = bayesPm.getDag();
    for (Object o : graph.getNodes()) {
        Node node = (Node) o;
        if (node.getNodeType() == NodeType.LATENT) {
            throw new IllegalArgumentException("Estimation of Bayes IM's " + "with latents is not supported.");
        }
    }
    if (DataUtils.containsMissingValue(dataSet)) {
        throw new IllegalArgumentException("Please remove or impute missing values.");
    }
    try {
        MlBayesEstimator estimator = new MlBayesEstimator();
        this.bayesIm = estimator.estimate(bayesPm, dataSet);
    } catch (ArrayIndexOutOfBoundsException e) {
        e.printStackTrace();
        throw new RuntimeException("Value assignments between Bayes PM " + "and discrete data set do not match.");
    }
}

Example 90 with Node

use of edu.cmu.tetrad.graph.Node in project tetrad by cmu-phil.

the class IdentifiabilityWrapper method setup.

// ===============================PRIVATE METHODS======================//
private void setup(BayesIm bayesIm, Parameters params) {
    TetradLogger.getInstance().setConfigForClass(this.getClass());
    this.params = params;
    if (params.get("evidence", null) == null || ((Evidence) params.get("evidence", null)).isIncompatibleWith(bayesIm)) {
        bayesUpdater = new Identifiability(bayesIm);
    } else {
        bayesUpdater = new Identifiability(bayesIm, (Evidence) params.get("evidence", null));
    }
    Node node = (Node) getParams().get("variable", null);
    if (node != null) {
        NumberFormat nf = NumberFormatUtil.getInstance().getNumberFormat();
        TetradLogger.getInstance().log("info", "\nIdentifiability");
        String nodeName = node.getName();
        int nodeIndex = bayesIm.getNodeIndex(bayesIm.getNode(nodeName));
        double[] priors = getBayesUpdater().calculatePriorMarginals(nodeIndex);
        double[] marginals = getBayesUpdater().calculateUpdatedMarginals(nodeIndex);
        TetradLogger.getInstance().log("details", "\nVariable = " + nodeName);
        TetradLogger.getInstance().log("details", "\nEvidence:");
        Evidence evidence = (Evidence) getParams().get("evidence", null);
        Proposition proposition = evidence.getProposition();
        for (int i = 0; i < proposition.getNumVariables(); i++) {
            Node variable = proposition.getVariableSource().getVariables().get(i);
            int category = proposition.getSingleCategory(i);
            if (category != -1) {
                TetradLogger.getInstance().log("details", "\t" + variable + " = " + category);
            }
        }
        TetradLogger.getInstance().log("details", "\nCat.\tPrior\tMarginal");
        for (int i = 0; i < priors.length; i++) {
            TetradLogger.getInstance().log("details", category(evidence, nodeName, i) + "\t" + nf.format(priors[i]) + "\t" + nf.format(marginals[i]));
        }
    }
    TetradLogger.getInstance().reset();
}