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

Example 1 with ICovarianceMatrix

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

the class MimbuildEditor method getIndTestParamBox.

/**
 * Factory to return the correct param editor for independence test params.
 * This will go in a little box in the search editor.
 */
private JComponent getIndTestParamBox(Parameters params) {
    if (params == null) {
        throw new NullPointerException();
    }
    if (params instanceof Parameters) {
        MimRunner runner = getMimRunner();
        params.set("varNames", runner.getParams().get("varNames", null));
        DataModel dataModel = runner.getData();
        if (dataModel instanceof DataSet) {
            DataSet data = (DataSet) runner.getData();
            boolean discrete = data.isDiscrete();
            return new BuildPureClustersIndTestParamsEditor2(params, discrete);
        } else if (dataModel instanceof ICovarianceMatrix) {
            return new BuildPureClustersIndTestParamsEditor2(params, false);
        }
    }
    if (params instanceof Parameters) {
        MimRunner runner = getMimRunner();
        params.set("varNames", runner.getParams().get("varNames", null));
        boolean discreteData = false;
        if (runner.getData() instanceof DataSet) {
            discreteData = ((DataSet) runner.getData()).isDiscrete();
        }
        return new PurifyIndTestParamsEditor(params, discreteData);
    }
    if (params instanceof Parameters) {
        MimRunner runner = getMimRunner();
        params.set("varNames", runner.getParams().get("varNames", null));
        return new MimBuildIndTestParamsEditor(params);
    }
    throw new IllegalArgumentException("Unrecognized Parameters: " + params.getClass());
}

Example 2 with ICovarianceMatrix

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

the class SemEstimatorEditor method reestimate.

private void reestimate() {
    SemOptimizer optimizer;
    String type = wrapper.getSemOptimizerType();
    switch(type) {
        case "Regression":
            optimizer = new SemOptimizerRegression();
            break;
        case "EM":
            optimizer = new SemOptimizerEm();
            break;
        case "Powell":
            optimizer = new SemOptimizerPowell();
            break;
        case "Random Search":
            optimizer = new SemOptimizerScattershot();
            break;
        case "RICF":
            optimizer = new SemOptimizerRicf();
            break;
        default:
            throw new IllegalArgumentException("Unexpected optimizer type: " + type);
    }
    int numRestarts = wrapper.getNumRestarts();
    optimizer.setNumRestarts(numRestarts);
    java.util.List<SemEstimator> estimators = wrapper.getMultipleResultList();
    java.util.List<SemEstimator> newEstimators = new ArrayList<>();
    estimators.forEach(estimator -> {
        SemPm semPm = estimator.getSemPm();
        DataSet dataSet = estimator.getDataSet();
        ICovarianceMatrix covMatrix = estimator.getCovMatrix();
        SemEstimator newEstimator;
        if (dataSet != null) {
            newEstimator = new SemEstimator(dataSet, semPm, optimizer);
            newEstimator.setNumRestarts(numRestarts);
            newEstimator.setScoreType(wrapper.getScoreType());
        } else if (covMatrix != null) {
            newEstimator = new SemEstimator(covMatrix, semPm, optimizer);
            newEstimator.setNumRestarts(numRestarts);
            newEstimator.setScoreType(wrapper.getScoreType());
        } else {
            throw new IllegalStateException("Only continuous rectangular" + " data sets and covariance matrices can be processed.");
        }
        newEstimator.estimate();
        newEstimators.add(newEstimator);
    });
    wrapper.setSemEstimator(newEstimators.get(0));
    wrapper.setMultipleResultList(newEstimators);
    resetSemImEditor();
}

Example 3 with ICovarianceMatrix

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

the class PurifyParamsEditor method setVarNames.

private boolean setVarNames(Object[] parentModels, Parameters params) {
    DataModel dataModel = null;
    for (Object parentModel : parentModels) {
        if (parentModel instanceof DataWrapper) {
            DataWrapper dataWrapper = (DataWrapper) parentModel;
            dataModel = dataWrapper.getSelectedDataModel();
        }
    }
    boolean discreteModel;
    if (dataModel instanceof ICovarianceMatrix) {
        discreteModel = false;
    } else {
        DataSet dataSet = (DataSet) dataModel;
        assert dataSet != null;
        discreteModel = dataSet.isDiscrete();
    // try {
    // new DataSet((DataSet) dataModel);
    // discreteModel = true;
    // }
    // catch (IllegalArgumentException e) {
    // discreteModel = false;
    // }
    }
    getParams().set("varNames", params.get("varNames", null));
    return discreteModel;
}

Example 4 with ICovarianceMatrix

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

the class MimSearchEditor2 method getIndTestParamBox.

/**
 * Factory to return the correct param editor for independence test params.
 * This will go in a little box in the search editor.
 */
private JComponent getIndTestParamBox(Parameters params) {
    if (params == null) {
        throw new NullPointerException();
    }
    if (params instanceof Parameters) {
        MimRunner runner = getMimRunner();
        params.set("varNames", runner.getParams().get("varNames", null));
        DataModel dataModel = runner.getData();
        if (dataModel instanceof DataSet) {
            DataSet data = (DataSet) runner.getData();
            boolean discrete = data.isDiscrete();
            return new BuildPureClustersIndTestParamsEditor2(params, discrete);
        } else if (dataModel instanceof ICovarianceMatrix) {
            return new BuildPureClustersIndTestParamsEditor2(params, false);
        }
    }
    if (params instanceof Parameters) {
        MimRunner runner = getMimRunner();
        params.set("varNames", runner.getParams().get("varNames", null));
        boolean discreteData = false;
        if (runner.getData() instanceof DataSet) {
            discreteData = ((DataSet) runner.getData()).isDiscrete();
        }
        return new PurifyIndTestParamsEditor(params, discreteData);
    }
    if (params instanceof Parameters) {
        MimRunner runner = getMimRunner();
        params.set("varNames", runner.getParams().get("varNames", null));
        return new MimBuildIndTestParamsEditor(params);
    }
    throw new IllegalArgumentException("Unrecognized Parameters: " + params.getClass());
}

Example 5 with ICovarianceMatrix

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

the class IndTestCramerT method indTestSubset.

// ==========================PUBLIC METHODS=============================//
/**
 * Creates a new IndTestCramerT instance for a subset of the variables.
 */
public IndependenceTest indTestSubset(List<Node> vars) {
    if (vars.isEmpty()) {
        throw new IllegalArgumentException("Subset may not be empty.");
    }
    for (Node var : vars) {
        if (!variables.contains(var)) {
            throw new IllegalArgumentException("All vars must be original vars");
        }
    }
    int[] indices = new int[vars.size()];
    for (int i = 0; i < indices.length; i++) {
        indices[i] = variables.indexOf(vars.get(i));
    }
    ICovarianceMatrix newCorrMatrix = covMatrix.getSubmatrix(indices);
    double alphaNew = getAlpha();
    return new IndTestCramerT(newCorrMatrix, alphaNew);
}