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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 //
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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.data.*;
import edu.cmu.tetrad.graph.Dag;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.Node;
import edu.cmu.tetrad.graph.NodeType;
import edu.cmu.tetrad.sem.*;
import edu.cmu.tetrad.util.*;
import edu.cmu.tetradapp.session.SessionModel;
import javax.swing.*;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.io.Serial;
import java.util.LinkedList;
import java.util.List;
/**
* Wraps a SemEstimator for use in the Tetrad application.
*
* @author josephramsey
* @version $Id: $Id
*/
public class SemEstimatorWrapper implements SessionModel {
@Serial
private static final long serialVersionUID = 23L;
/**
* The parameters for the estimator.
*/
private final Parameters params;
/**
* The SEM PM for the estimator.
*/
private final SemPm semPm;
/**
* The name of the estimator.
*/
private String name;
/**
* The estimator itself.
*/
private SemEstimator semEstimator;
//==============================CONSTRUCTORS==========================//
/**
* Private constructor for serialization only. Problem is, for the real constructors, I'd like to call the degrees
* of freedom check, which pops up a dialog. This is irritating when running unit tests. jdramsey 8/29/07
*
* @param dataModel a {@link edu.cmu.tetrad.data.DataModel} object
* @param semPm a {@link edu.cmu.tetrad.sem.SemPm} object
* @param params a {@link edu.cmu.tetrad.util.Parameters} object
*/
public SemEstimatorWrapper(DataModel dataModel, SemPm semPm, Parameters params) {
this.params = params;
this.semPm = semPm;
if (dataModel instanceof DataSet dataSet) {
SemEstimator estimator = new SemEstimator(dataSet, semPm, getOptimizer());
estimator.setNumRestarts(getParams().getInt("numRestarts", 1));
estimator.setScoreType((ScoreType) getParams().get("scoreType", ScoreType.Fgls));
estimator.estimate();
if (!degreesOfFreedomCheck(semPm)) {
throw new IllegalArgumentException("Cannot proceed.");
}
this.semEstimator = estimator;
} else if (dataModel instanceof ICovarianceMatrix) {
ICovarianceMatrix covMatrix = new CovarianceMatrix((ICovarianceMatrix) dataModel);
SemEstimator estimator = new SemEstimator(covMatrix, semPm, getOptimizer());
estimator.setNumRestarts(getParams().getInt("numRestarts", 1));
estimator.setScoreType((ScoreType) getParams().get("scoreType", ScoreType.Fml));
estimator.estimate();
if (!degreesOfFreedomCheck(semPm)) {
throw new IllegalArgumentException("Cannot proceed.");
}
this.semEstimator = estimator;
} else {
throw new IllegalArgumentException("Data must consist of continuous data sets or covariance matrices.");
}
}
/**
* Constructor for SemEstimatorWrapper.
*
* @param dataWrapper a {@link edu.cmu.tetradapp.model.DataWrapper} object
* @param semPmWrapper a {@link edu.cmu.tetradapp.model.SemPmWrapper} object
* @param params a {@link edu.cmu.tetrad.util.Parameters} object
*/
public SemEstimatorWrapper(DataWrapper dataWrapper, SemPmWrapper semPmWrapper, Parameters params) {
this(dataWrapper.getSelectedDataModel(), semPmWrapper.getSemPm(), params);
log();
}
/**
* Constructs a SemEstimatorWrapper object.
*
* @param simulation a Simulation object
* @param semPmWrapper a SemPmWrapper object
* @param parameters a Parameters object
*/
public SemEstimatorWrapper(Simulation simulation, SemPmWrapper semPmWrapper, Parameters parameters) {
this(new DataWrapper(simulation, parameters), semPmWrapper, parameters);
}
/**
* Generates a simple exemplar of this class to test serialization.
*
* @return a {@link edu.cmu.tetradapp.model.SemEstimatorWrapper} object
* @see TetradSerializableUtils
*/
public static SemEstimatorWrapper serializableInstance() {
List variables = new LinkedList<>();
ContinuousVariable x = new ContinuousVariable("X");
variables.add(x);
DataSet dataSet = new BoxDataSet(new VerticalDoubleDataBox(10, variables.size()), variables);
for (int i = 0; i < dataSet.getNumRows(); i++) {
for (int j = 0; j < dataSet.getNumColumns(); j++) {
dataSet.setDouble(i, j, RandomUtil.getInstance().nextDouble());
}
}
Dag dag = new Dag();
dag.addNode(x);
SemPm pm = new SemPm(dag);
Parameters params1 = new Parameters();
return new SemEstimatorWrapper(dataSet, pm, params1);
}
private static boolean containsCovarParam(SemPm semPm) {
boolean containsCovarParam = false;
List params = semPm.getParameters();
for (Parameter param : params) {
if (param.getType() == ParamType.COVAR) {
containsCovarParam = true;
break;
}
}
return containsCovarParam;
}
private boolean degreesOfFreedomCheck(SemPm semPm) {
if (semPm.getDof() < 1) {
int ret = JOptionPane.showConfirmDialog(JOptionUtils.centeringComp(), "This model has non-positive degrees of freedom (DOF = " + semPm.getDof() + "). " + "\nEstimation will be uninformative. Are you sure you want to proceed?", "Please confirm", JOptionPane.YES_NO_OPTION, JOptionPane.WARNING_MESSAGE);
return ret == JOptionPane.YES_OPTION;
}
return true;
}
//============================PUBLIC METHODS=========================//
/**
* Getter for the field semEstimator.
*
* @return a {@link edu.cmu.tetrad.sem.SemEstimator} object
*/
public SemEstimator getSemEstimator() {
return this.semEstimator;
}
/**
* Setter for the field semEstimator.
*
* @param semEstimator a {@link edu.cmu.tetrad.sem.SemEstimator} object
*/
public void setSemEstimator(SemEstimator semEstimator) {
this.semEstimator = semEstimator;
}
/**
* getEstimatedSemIm.
*
* @return a {@link edu.cmu.tetrad.sem.SemIm} object
*/
public SemIm getEstimatedSemIm() {
return this.semEstimator.getEstimatedSem();
}
/**
* getSemOptimizerType.
*
* @return a {@link java.lang.String} object
*/
public String getSemOptimizerType() {
return getParams().getString("semOptimizerType", "Regression");
}
/**
* setSemOptimizerType.
*
* @param type a {@link java.lang.String} object
*/
public void setSemOptimizerType(String type) {
getParams().set("semOptimizerType", type);
}
/**
* getGraph.
*
* @return a {@link edu.cmu.tetrad.graph.Graph} object
*/
public Graph getGraph() {
return this.semEstimator.getEstimatedSem().getSemPm().getGraph();
}
/**
* 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 =======================//
private void log() {
TetradLogger.getInstance().log("SEM Estimator:");
String message3 = "" + getEstimatedSemIm();
TetradLogger.getInstance().log(message3);
String message2 = "ChiSq = " + getEstimatedSemIm().getChiSquare();
TetradLogger.getInstance().log(message2);
String message1 = "DOF = " + getEstimatedSemIm().getSemPm().getDof();
TetradLogger.getInstance().log(message1);
String message = "P = " + getEstimatedSemIm().getPValue();
TetradLogger.getInstance().log(message);
}
/**
* 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 params.
*
* @return a {@link edu.cmu.tetrad.util.Parameters} object
*/
public Parameters getParams() {
return this.params;
}
private SemOptimizer getOptimizer() {
SemOptimizer optimizer;
String type = getParams().getString("semOptimizerType", "Regression");
if ("Regression".equals(type)) {
SemOptimizer defaultOptimization = getDefaultOptimization();
if (!(defaultOptimization instanceof SemOptimizerRegression)) {
optimizer = defaultOptimization;
type = getType(defaultOptimization);
getParams().set("semOptimizerType", type);
} else {
optimizer = new SemOptimizerRegression();
}
} else if ("EM".equals(type)) {
optimizer = new SemOptimizerEm();
} else if ("Powell".equals(type)) {
optimizer = new SemOptimizerPowell();
} else if ("Random Search".equals(type)) {
optimizer = new SemOptimizerScattershot();
} else if ("RICF".equals(type)) {
optimizer = new SemOptimizerRicf();
} else {
if (this.semPm != null) {
optimizer = getDefaultOptimization();
String _type = getType(optimizer);
if (_type != null) {
getParams().set("semOptimizerType", _type);
}
} else {
optimizer = null;
}
}
return optimizer;
}
private String getType(SemOptimizer optimizer) {
String _type = null;
if (optimizer instanceof SemOptimizerRegression) {
_type = "Regression";
} else if (optimizer instanceof SemOptimizerEm) {
_type = "EM";
} else if (optimizer instanceof SemOptimizerPowell) {
_type = "Powell";
} else if (optimizer instanceof SemOptimizerScattershot) {
_type = "Random Search";
} else if (optimizer instanceof SemOptimizerRicf) {
_type = "RICF";
}
return _type;
}
private boolean containsFixedParam(SemPm semPm) {
return new SemIm(semPm).getNumFixedParams() > 0;
}
/**
* getScoreType.
*
* @return a {@link edu.cmu.tetrad.sem.ScoreType} object
*/
public ScoreType getScoreType() {
return (ScoreType) this.params.get("scoreType", ScoreType.SemBic);
}
/**
* setScoreType.
*
* @param scoreType a {@link edu.cmu.tetrad.sem.ScoreType} object
*/
public void setScoreType(ScoreType scoreType) {
this.params.set("scoreType", scoreType);
}
/**
* getNumRestarts.
*
* @return a int
*/
public int getNumRestarts() {
return getParams().getInt("numRestarts", 1);
}
/**
* setNumRestarts.
*
* @param numRestarts a int
*/
public void setNumRestarts(int numRestarts) {
getParams().set("numRestarts", numRestarts);
}
private SemOptimizer getDefaultOptimization() {
if (this.semPm == null) {
throw new NullPointerException("Sorry, I didn't see a SEM PM as parent to the estimator; perhaps the parents are wrong.");
}
boolean containsLatent = false;
for (Node node : this.semPm.getGraph().getNodes()) {
if (node.getNodeType() == NodeType.LATENT) {
containsLatent = true;
break;
}
}
SemOptimizer optimizer;
if (containsFixedParam(this.semPm) || this.semPm.getGraph().paths().existsDirectedCycle() || SemEstimatorWrapper.containsCovarParam(this.semPm)) {
optimizer = new SemOptimizerPowell();
} else if (containsLatent) {
optimizer = new SemOptimizerEm();
} else {
optimizer = new SemOptimizerRegression();
}
optimizer.setNumRestarts(getParams().getInt("numRestarts", 1));
return optimizer;
}
}
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