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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. //
// //
// 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.DataModelList;
import edu.cmu.tetrad.data.DataSet;
import edu.cmu.tetrad.data.DataUtils;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.sem.*;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.TetradLogger;
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;
/**
* Compares a target workbench with a reference workbench by counting errors of omission and commission. (for edge
* presence only, not orientation).
*
* @author josephramsey
* @author Erin Korber (added remove latents functionality July 2004)
* @version $Id: $Id
*/
public final class CPDAGFitModel implements SessionModel {
@Serial
private static final long serialVersionUID = 23L;
/**
* The parameters for the check.
*/
private final Parameters parameters;
/**
* The data models to be checked.
*/
private final DataModelList dataModelList;
/**
* The name of the model.
*/
private String name;
/**
* The Bayes IMs to be checked.
*/
private List bayesIms;
/**
* The Bayes PMs to be checked.
*/
private List bayesPms;
/**
* The SEM PMs to be checked.
*/
private List referenceGraphs;
/**
* The SEM PMs to be checked.
*/
private List semPms;
//=============================CONSTRUCTORS==========================//
/**
* Compares the results of a PC to a reference workbench by counting errors of omission and commission. The counts
* can be retrieved using the methods
* countOmissionErrors and countCommissionErrors.
*
* @param simulation a {@link edu.cmu.tetradapp.model.Simulation} object
* @param algorithmRunner a {@link edu.cmu.tetradapp.model.GeneralAlgorithmRunner} object
* @param params a {@link edu.cmu.tetrad.util.Parameters} object
*/
public CPDAGFitModel(Simulation simulation, GeneralAlgorithmRunner algorithmRunner, Parameters params) {
if (params == null) {
throw new NullPointerException("Parameters must not be null");
}
this.parameters = params;
DataModelList dataModels = simulation.getDataModelList();
this.dataModelList = dataModels;
List graphs = algorithmRunner.getGraphs();
if (dataModels.size() != graphs.size()) {
throw new IllegalArgumentException("Sorry, I was expecting the same number of data sets as result graphs.");
}
if (dataModels.get(0).isDiscrete()) {
this.bayesPms = new ArrayList<>();
this.bayesIms = new ArrayList<>();
for (int i = 0; i < dataModels.size(); i++) {
DataSet dataSet = (DataSet) dataModels.get(0);
Graph dag = GraphTransforms.dagFromCpdag(graphs.get(0), null);
BayesPm pm = new BayesPmWrapper(dag, new DataWrapper(dataSet)).getBayesPm();
this.bayesPms.add(pm);
this.bayesIms.add(estimate(dataSet, pm));
}
} else if (dataModels.get(0).isContinuous()) {
this.semPms = new ArrayList<>();
List semIms = new ArrayList<>();
for (int i = 0; i < dataModels.size(); i++) {
DataSet dataSet = (DataSet) dataModels.get(0);
Graph dag = GraphTransforms.dagFromCpdag(graphs.get(0), null);
try {
SemPm pm = new SemPm(dag);
this.semPms.add(pm);
semIms.add(estimate(dataSet, pm));
} catch (Exception e) {
e.printStackTrace();
Graph mag = GraphTransforms.zhangMagFromPag(graphs.get(0));
// Ricf.RicfResult result = estimatePag(dataSet, mag);
SemGraph graph = new SemGraph(mag);
graph.setShowErrorTerms(false);
SemPm pm = new SemPm(graph);
this.semPms.add(pm);
semIms.add(estimatePag(dataSet, pm));
}
}
}
}
private BayesIm 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.");
}
double prior = parameters.getDouble("bayesEstimatorCellPrior", 1.0);
try {
MlBayesEstimator estimator = new MlBayesEstimator(prior);
return estimator.estimate(bayesPm, dataSet);
} catch (ArrayIndexOutOfBoundsException e) {
e.printStackTrace();
throw new RuntimeException("Value assignments between Bayes PM " +
"and discrete data set do not match.");
}
}
private SemIm estimate(DataSet dataSet, SemPm semPm) {
Graph graph = semPm.getGraph();
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 {
SemEstimator estimator = new SemEstimator(dataSet, semPm);
return estimator.estimate();
} catch (ArrayIndexOutOfBoundsException e) {
e.printStackTrace();
throw new RuntimeException("Value assignments between Bayes PM " +
"and discrete data set do not match.");
}
}
private SemIm estimatePag(DataSet dataSet, SemPm pm) {
SemGraph graph = pm.getGraph();
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 {
SemOptimizer optimizer = new SemOptimizerRicf();
SemEstimator estimator = new SemEstimator(dataSet, pm, optimizer);
return estimator.estimate();
} catch (ArrayIndexOutOfBoundsException e) {
e.printStackTrace();
throw new RuntimeException("Value assignments between Bayes PM " +
"and discrete data set do not match.");
}
}
//==============================PUBLIC METHODS========================//
/**
* 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;
}
/**
* getBayesIm.
*
* @param i a int
* @return a {@link edu.cmu.tetrad.bayes.BayesIm} object
*/
public BayesIm getBayesIm(int i) {
return this.bayesIms.get(i);
}
/**
* 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;
}
}
/**
* Getter for the field referenceGraphs.
*
* @return a {@link java.util.List} object
*/
public List getReferenceGraphs() {
return this.referenceGraphs;
}
/**
* Getter for the field bayesIms.
*
* @return a {@link java.util.List} object
*/
public List getBayesIms() {
return this.bayesIms;
}
/**
* Getter for the field dataModelList.
*
* @return a {@link edu.cmu.tetrad.data.DataModelList} object
*/
public DataModelList getDataModelList() {
return this.dataModelList;
}
/**
* Getter for the field bayesPms.
*
* @return a {@link java.util.List} object
*/
public List getBayesPms() {
return this.bayesPms;
}
/**
* Getter for the field semPms.
*
* @return a {@link java.util.List} object
*/
public List getSemPms() {
return this.semPms;
}
/**
* getParams.
*
* @return a {@link edu.cmu.tetrad.util.Parameters} object
*/
public Parameters getParams() {
return this.parameters;
}
}
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