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///////////////////////////////////////////////////////////////////////////////
// For information as to what this class does, see the Javadoc, below.       //
// Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006,       //
// 2007, 2008, 2009, 2010, 2014, 2015, 2022 by Peter Spirtes, Richard        //
// Scheines, Joseph Ramsey, and Clark Glymour.                               //
//                                                                           //
// This program is free software; you can redistribute it and/or modify      //
// it under the terms of the GNU General Public License as published by      //
// the Free Software Foundation; either version 2 of the License, or         //
// (at your option) any later version.                                       //
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// This program is distributed in the hope that it will be useful,           //
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the             //
// GNU General Public License for more details.                              //
//                                                                           //
// You should have received a copy of the GNU General Public License         //
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// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA //
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package edu.cmu.tetradapp.model;

import edu.cmu.tetrad.bayes.BayesIm;
import edu.cmu.tetrad.bayes.BayesPm;
import edu.cmu.tetrad.bayes.EmBayesEstimator;
import edu.cmu.tetrad.data.DataSet;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.TetradLogger;
import edu.cmu.tetrad.util.TetradSerializableUtils;
import edu.cmu.tetradapp.session.SessionModel;

import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.io.Serial;

/**
 * Wraps a Bayes Pm for use in the Tetrad application.
 *
 * @author josephramsey
 * @author Frank Wimberly adapted for EM Bayes estimator and structural EM Bayes estimator
 * @version $Id: $Id
 */
public class EmBayesEstimatorWrapper implements SessionModel, GraphSource {
    @Serial
    private static final long serialVersionUID = 23L;

    /**
     * The name of the model.
     */
    private String name;

    /**
     * The data model.
     */
    private DataSet dataSet;

    /**
     * Contains the estimated BayesIm, or null if it hasn't been estimated yet.
     */
    private BayesIm estimateBayesIm;

    //============================CONSTRUCTORS==========================//

    /**
     * Initializes an instance of the EmBayesEstimatorWrapper class.
     *
     * @param simulation     The simulation used for estimation.
     * @param bayesPmWrapper The BayesPmWrapper used for estimation.
     * @param params         The parameters for the estimator.
     */
    public EmBayesEstimatorWrapper(Simulation simulation, BayesPmWrapper bayesPmWrapper, Parameters params) {
        this(new DataWrapper(simulation, params), bayesPmWrapper, params);
    }

    /**
     * 

Constructor for EmBayesEstimatorWrapper.

* * @param dataWrapper a {@link edu.cmu.tetradapp.model.DataWrapper} object * @param bayesPmWrapper a {@link edu.cmu.tetradapp.model.BayesPmWrapper} object * @param params a {@link edu.cmu.tetrad.util.Parameters} object */ public EmBayesEstimatorWrapper(DataWrapper dataWrapper, BayesPmWrapper bayesPmWrapper, Parameters params) { if (dataWrapper == null) { throw new NullPointerException(); } if (bayesPmWrapper == null) { throw new NullPointerException(); } if (params == null) { throw new NullPointerException(); } DataSet dataSet = (DataSet) dataWrapper.getSelectedDataModel(); BayesPm bayesPm = bayesPmWrapper.getBayesPm(); EmBayesEstimator estimator = new EmBayesEstimator(bayesPm, dataSet); this.dataSet = estimator.getMixedDataSet(); try { estimator.maximization(params.getDouble("tolerance", 0.0001)); this.estimateBayesIm = estimator.getEstimatedIm(); } catch (IllegalArgumentException e) { e.printStackTrace(); throw new RuntimeException( "Please specify the search tolerance first."); } TetradLogger.getInstance().log("EM-Estimated Bayes IM:"); TetradLogger.getInstance().log("" + this.estimateBayesIm); } /** * Generates a simple exemplar of this class to test serialization. * * @return a {@link edu.cmu.tetradapp.model.PcRunner} object * @see TetradSerializableUtils */ public static PcRunner serializableInstance() { return PcRunner.serializableInstance(); } //================================PUBLIC METHODS======================// /** *

Getter for the field estimateBayesIm.

* * @return a {@link edu.cmu.tetrad.bayes.BayesIm} object */ public BayesIm getEstimateBayesIm() { return this.estimateBayesIm; } private void estimate(DataSet dataSet, BayesPm bayesPm, double thresh) { try { EmBayesEstimator estimator = new EmBayesEstimator(bayesPm, dataSet); this.estimateBayesIm = estimator.maximization(thresh); this.dataSet = estimator.getMixedDataSet(); } catch (ArrayIndexOutOfBoundsException e) { e.printStackTrace(); throw new RuntimeException("Value assignments between Bayes PM " + "and discrete data set do not match."); } } /** *

Getter for the field dataSet.

* * @return a {@link edu.cmu.tetrad.data.DataSet} object */ public DataSet getDataSet() { return this.dataSet; } /** * Writes the object to the specified ObjectOutputStream. * * @param out The ObjectOutputStream to write the object to. * @throws IOException If an I/O error occurs. */ @Serial private void writeObject(ObjectOutputStream out) throws IOException { try { out.defaultWriteObject(); } catch (IOException e) { TetradLogger.getInstance().log("Failed to serialize object: " + getClass().getCanonicalName() + ", " + e.getMessage()); throw e; } } /** * Reads the object from the specified ObjectInputStream. This method is used during deserialization * to restore the state of the object. * * @param in The ObjectInputStream to read the object from. * @throws IOException If an I/O error occurs. * @throws ClassNotFoundException If the class of the serialized object cannot be found. */ @Serial private void readObject(ObjectInputStream in) throws IOException, ClassNotFoundException { try { in.defaultReadObject(); } catch (IOException e) { TetradLogger.getInstance().log("Failed to deserialize object: " + getClass().getCanonicalName() + ", " + e.getMessage()); throw e; } } /** *

getGraph.

* * @return a {@link edu.cmu.tetrad.graph.Graph} object */ public Graph getGraph() { return this.estimateBayesIm.getBayesPm().getDag(); } /** *

Getter for the field name.

* * @return a {@link java.lang.String} object */ public String getName() { return this.name; } /** * {@inheritDoc} */ public void setName(String name) { this.name = name; } //=============================== Private methods ==========================// }




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