edu.cmu.tetradapp.model.BayesImWrapper Maven / Gradle / Ivy
///////////////////////////////////////////////////////////////////////////////
// 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, //
// 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 //
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// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA //
///////////////////////////////////////////////////////////////////////////////
package edu.cmu.tetradapp.model;
import edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation;
import edu.cmu.tetrad.bayes.BayesIm;
import edu.cmu.tetrad.bayes.BayesPm;
import edu.cmu.tetrad.bayes.MlBayesIm;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.Node;
import edu.cmu.tetrad.session.SessionModel;
import edu.cmu.tetrad.util.Memorable;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.TetradSerializableUtils;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.Serial;
import java.util.ArrayList;
import java.util.List;
/**
* Wraps a Bayes Pm for use in the Tetrad application.
*
* @author josephramsey
*/
public class BayesImWrapper implements SessionModel, Memorable {
@Serial
private static final long serialVersionUID = 23L;
// The number of models in the simulation.
private int numModels = 1;
// The index of the model to be used.
private int modelIndex;
// The name of the model source.
private String modelSourceName;
// The name of the Bayes IM.
private String name;
// The Bayes IM.
private List bayesIms;
//===========================CONSTRUCTORS===========================//
/**
* Constructs a new BayesImWrapper.
*
* @param bayesPmWrapper the Bayes Pm wrapper
* @param oldBayesImwrapper the old Bayes Im wrapper
* @param params the parameters
*/
public BayesImWrapper(BayesPmWrapper bayesPmWrapper, BayesImWrapper oldBayesImwrapper, Parameters params) {
if (bayesPmWrapper == null) {
throw new NullPointerException("BayesPmWrapper must not be null.");
}
if (params == null) {
throw new NullPointerException("Parameters must not be null.");
}
BayesPm bayesPm = new BayesPm(bayesPmWrapper.getBayesPm());
BayesIm oldBayesIm = oldBayesImwrapper.getBayesIm();
if (params.getString("initializationMode", "manualRetain").equals("manualRetain")) {
setBayesIm(bayesPm, oldBayesIm, MlBayesIm.MANUAL);
} else if (params.getString("initializationMode", "manualRetain").equals("randomRetain")) {
setBayesIm(bayesPm, oldBayesIm, MlBayesIm.RANDOM);
} else if (params.getString("initializationMode", "manualRetain").equals("randomOverwrite")) {
setBayesIm(new MlBayesIm(bayesPm, MlBayesIm.RANDOM));
}
}
/**
* Constructs a new BayesImWrapper.
*
* @param simulation the simulation
*/
public BayesImWrapper(Simulation simulation) {
List bayesIms = null;
if (simulation == null) {
throw new NullPointerException("The Simulation box does not contain a simulation.");
}
edu.cmu.tetrad.algcomparison.simulation.Simulation _simulation = simulation.getSimulation();
if (_simulation == null) {
throw new NullPointerException("No data sets have been simulated.");
}
if (!(_simulation instanceof BayesNetSimulation)) {
throw new IllegalArgumentException("That was not a discrete Bayes net simulation.");
}
bayesIms = ((BayesNetSimulation) _simulation).getBayesIms();
if (bayesIms == null) {
throw new NullPointerException("It looks like you have not done a simulation.");
}
this.bayesIms = bayesIms;
this.numModels = simulation.getDataModelList().size();
this.modelIndex = 0;
this.modelSourceName = simulation.getName();
}
/**
* Constructs a new BayesImWrapper for a RowSummingExactUpdaterWrapper.
*
* @param wrapper the wrapper
* @param parameters the parameters
*/
public BayesImWrapper(RowSummingExactWrapper wrapper, Parameters parameters) {
if (wrapper == null) {
throw new NullPointerException();
}
setBayesIm(wrapper.getBayesUpdater().getUpdatedBayesIm());
}
/**
* Constructs a new BayesImWrapper for a CptInvariantUpdaterWrapper.
*
* @param wrapper the wrapper
* @param parameters the parameters
*/
public BayesImWrapper(CptInvariantUpdaterWrapper wrapper, Parameters parameters) {
if (wrapper == null) {
throw new NullPointerException();
}
setBayesIm(wrapper.getBayesUpdater().getUpdatedBayesIm());
}
public BayesImWrapper(ApproximateUpdaterWrapper wrapper, Parameters parameters) {
if (wrapper == null) {
throw new NullPointerException();
}
setBayesIm(wrapper.getBayesUpdater().getUpdatedBayesIm());
}
public BayesImWrapper(BayesPmWrapper bayesPmWrapper, Parameters params) {
if (bayesPmWrapper == null) {
throw new NullPointerException("BayesPmWrapper must not be null.");
}
if (params == null) {
throw new NullPointerException("Parameters must not be null.");
}
BayesPm bayesPm = new BayesPm(bayesPmWrapper.getBayesPm());
if (params.getString("initializationMode", "manualRetain").equals("manualRetain")) {
setBayesIm(new MlBayesIm(bayesPm));
} else if (params.getString("initializationMode", "manualRetain").equals("randomRetain")) {
setBayesIm(new MlBayesIm(bayesPm, MlBayesIm.RANDOM));
} else if (params.getString("initializationMode", "manualRetain").equals("randomOverwrite")) {
setBayesIm(new MlBayesIm(bayesPm, MlBayesIm.RANDOM));
}
}
/**
* Constructs a new BayesImWrapper for a BayesIm.
*
* @param bayesIm the BayesIm
*/
public BayesImWrapper(BayesIm bayesIm) {
if (bayesIm == null) {
throw new NullPointerException("Bayes IM must not be null.");
}
setBayesIm(new MlBayesIm(bayesIm));
}
/**
* Generates a simple exemplar of this class to test serialization.
*
* @see TetradSerializableUtils
*/
public static BayesImWrapper serializableInstance() {
return new BayesImWrapper(BayesPmWrapper.serializableInstance(),
new Parameters());
}
/**
* Returns the BayesIm.
*
* @return the BayesIm
*/
public BayesIm getBayesIm() {
return this.bayesIms.get(getModelIndex());
}
/**
* Sets the BayesIm.
*
* @param bayesIm the BayesIm
*/
public void setBayesIm(BayesIm bayesIm) {
this.bayesIms = new ArrayList<>();
this.bayesIms.add(bayesIm);
}
/**
* Returns the graph.
*
* @return the graph
*/
public Graph getGraph() {
return getBayesIm().getBayesPm().getDag();
}
/**
* Returns the name of the BayesIm.
*
* @return the name of the BayesIm
*/
public String getName() {
return this.name;
}
/**
* Sets the name of the BayesIm.
*
* @param name the name of the BayesIm
*/
public void setName(String name) {
this.name = name;
}
/**
* Returns the source graph.
*
* @return the source graph
*/
public Graph getSourceGraph() {
return getGraph();
}
/**
* Returns the result graph.
*
* @return the result graph
*/
public Graph getResultGraph() {
return getGraph();
}
/**
* Returns the variable names.
*
* @return the variable names
*/
public List getVariableNames() {
return getGraph().getNodeNames();
}
/**
* Returns the variables.
*
* @return the variables
*/
public List getVariables() {
return getGraph().getNodes();
}
/**
* Returns the number of models.
*
* @return the number of models
*/
public int getNumModels() {
return this.numModels;
}
/**
* Returns the index of the model to be used.
*
* @return the index of the model to be used
*/
public int getModelIndex() {
return this.modelIndex;
}
/**
* Sets the index of the model to be used.
*
* @param modelIndex the index of the model to be used
*/
public void setModelIndex(int modelIndex) {
this.modelIndex = modelIndex;
}
/**
* Returns the name of the model source.
*
* @return the name of the model source
*/
public String getModelSourceName() {
return this.modelSourceName;
}
//============================== private methods ============================//
private void setBayesIm(BayesPm bayesPm, BayesIm oldBayesIm, int manual) {
this.bayesIms = new ArrayList<>();
this.bayesIms.add(new MlBayesIm(bayesPm, oldBayesIm, manual));
}
/**
* Adds semantic checks to the default deserialization method. This method must have the standard signature for a
* readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any
* semantic checks can be specified and do not need to stay the same from version to version. A readObject method of
* this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the
* class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for
* help.
*/
@Serial
private void readObject(ObjectInputStream s)
throws IOException, ClassNotFoundException {
s.defaultReadObject();
}
}
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