edu.cmu.tetradapp.model.BayesEstimatorWrapper Maven / Gradle / Ivy
The newest version!
///////////////////////////////////////////////////////////////////////////////
// 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. //
// //
// This program is distributed in the hope that it will be useful, //
// but WITHOUT ANY WARRANTY; without even the implied warranty of //
// 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 //
// along with this program; if not, write to the Free Software //
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA //
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.model;
import edu.cmu.tetrad.bayes.BayesIm;
import edu.cmu.tetrad.bayes.BayesPm;
import edu.cmu.tetrad.bayes.MlBayesEstimator;
import edu.cmu.tetrad.data.DataModel;
import edu.cmu.tetrad.data.DataModelList;
import edu.cmu.tetrad.data.DataSet;
import edu.cmu.tetrad.data.DataUtils;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.Node;
import edu.cmu.tetrad.graph.NodeType;
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;
import java.util.ArrayList;
import java.util.List;
/**
* Wraps a Bayes Pm for use in the Tetrad application.
*
* @author josephramsey
* @version $Id: $Id
*/
public class BayesEstimatorWrapper implements SessionModel {
@Serial
private static final long serialVersionUID = 23L;
/**
* The data wrapper.
*/
private final DataWrapper dataWrapper;
/**
* ' The estimated Bayes IM.
*/
private final List bayesIms = new ArrayList<>();
/**
* The private final parameters variable holds the parameters for the given instance.
* It is of type Parameters.
*/
private final Parameters parameters;
/**
* The name of the Bayes Pm.
*/
private String name;
/**
* The estimated Bayes IM.
*/
private BayesIm bayesIm;
/**
* The data set.
*/
private DataSet dataSet;
/**
* The number of models.
*/
private int numModels;
/**
* The model index.
*/
private int modelIndex;
//=================================CONSTRUCTORS========================//
/**
* Constructs a new BayesEstimatorWrapper object.
*
* @param simulation the Simulation object
* @param bayesPmWrapper the BayesPmWrapper object
* @param parameters the Parameters object
*/
public BayesEstimatorWrapper(Simulation simulation, BayesPmWrapper bayesPmWrapper, Parameters parameters) {
this(new DataWrapper(simulation, parameters), bayesPmWrapper, parameters);
}
/**
* Constructor for BayesEstimatorWrapper.
*
* @param dataWrapper a {@link edu.cmu.tetradapp.model.DataWrapper} object
* @param bayesPmWrapper a {@link edu.cmu.tetradapp.model.BayesPmWrapper} object
*/
public BayesEstimatorWrapper(DataWrapper dataWrapper,
BayesPmWrapper bayesPmWrapper, Parameters parameters) {
if (dataWrapper == null) {
throw new NullPointerException(
"BayesDataWrapper must not be null.");
}
this.dataWrapper = dataWrapper;
this.parameters = parameters;
if (bayesPmWrapper == null) {
throw new NullPointerException("BayesPmWrapper must not be null");
}
DataModelList dataModel = dataWrapper.getDataModelList();
if (dataModel != null) {
for (int i = 0; i < dataWrapper.getDataModelList().size(); i++) {
DataModel model = dataWrapper.getDataModelList().get(i);
DataSet dataSet = (DataSet) model;
bayesPmWrapper.setModelIndex(i);
BayesPm bayesPm = bayesPmWrapper.getBayesPm();
estimate(dataSet, bayesPm);
this.bayesIms.add(this.bayesIm);
}
this.bayesIm = this.bayesIms.get(0);
// log(this.bayesIm);
} else {
throw new IllegalArgumentException("Data must consist of discrete data sets.");
}
this.name = bayesPmWrapper.getName();
this.numModels = this.bayesIms.size();
this.modelIndex = 0;
this.bayesIm = this.bayesIms.get(this.modelIndex);
DataModel model = dataModel.get(this.modelIndex);
this.dataSet = (DataSet) model;
}
/**
* Constructor for BayesEstimatorWrapper.
*
* @param dataWrapper a {@link edu.cmu.tetradapp.model.DataWrapper} object
* @param bayesImWrapper a {@link edu.cmu.tetradapp.model.BayesImWrapper} object
*/
public BayesEstimatorWrapper(DataWrapper dataWrapper,
BayesImWrapper bayesImWrapper, Parameters parameters) {
this(dataWrapper, new BayesPmWrapper(bayesImWrapper), parameters);
}
/**
* 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========================//
/**
* getEstimatedBayesIm.
*
* @return a {@link edu.cmu.tetrad.bayes.BayesIm} object
*/
public BayesIm getEstimatedBayesIm() {
return this.bayesIm;
}
/**
* Setter for the field bayesIm.
*
* @param bayesIm a {@link edu.cmu.tetrad.bayes.BayesIm} object
*/
public void setBayesIm(BayesIm bayesIm) {
this.bayesIms.clear();
this.bayesIms.add(bayesIm);
}
/**
* Getter for the field dataSet.
*
* @return a {@link edu.cmu.tetrad.data.DataSet} object
*/
public DataSet getDataSet() {
return this.dataSet;
}
/**
* getGraph.
*
* @return a {@link edu.cmu.tetrad.graph.Graph} object
*/
public Graph getGraph() {
return this.bayesIm.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;
}
/**
* Returns the number of models.
*
* @return the number of models.
*/
public int getNumModels() {
return this.numModels;
}
/**
* Sets the number of models.
*
* @param numModels the number of models to be set.
*/
public void setNumModels(int numModels) {
this.numModels = numModels;
}
/**
* Retrieves the model index.
*
* @return the model index
*/
public int getModelIndex() {
return this.modelIndex;
}
/**
* Sets the model index.
*
* @param modelIndex the index of the model to be set.
*/
public void setModelIndex(int modelIndex) {
this.modelIndex = modelIndex;
this.bayesIm = this.bayesIms.get(modelIndex);
DataModelList dataModel = this.dataWrapper.getDataModelList();
this.dataSet = (DataSet) dataModel.get(modelIndex);
}
//======================== Private Methods ======================//
/**
* Writes the object to the specified ObjectOutputStream.
*
* @param out The ObjectOutputStream to write the object to.
* @throws IOException If an I/O error occurs.
*/
/**
* 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;
}
}
private void log(BayesIm im) {
TetradLogger.getInstance().log("ML estimated Bayes IM.");
String message = im.toString();
TetradLogger.getInstance().log(message);
}
private void estimate(DataSet dataSet, BayesPm bayesPm) {
Graph graph = bayesPm.getDag();
for (Node node : graph.getNodes()) {
if (node.getNodeType() == NodeType.LATENT) {
throw new IllegalArgumentException("Estimation of Bayes IMs "
+ "with latents is not supported.");
}
}
if (DataUtils.containsMissingValue(dataSet)) {
throw new IllegalArgumentException("Please remove or impute missing values.");
}
double prior = parameters.getDouble("bayesEstimatorCellPrior", 1.0);
try {
MlBayesEstimator estimator = new MlBayesEstimator(prior);
this.bayesIm = estimator.estimate(bayesPm, dataSet);
} catch (ArrayIndexOutOfBoundsException e) {
throw new RuntimeException("Value assignments between Bayes PM "
+ "and discrete data set do not match.");
}
}
}
© 2015 - 2025 Weber Informatics LLC | Privacy Policy