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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.data.*;
import edu.cmu.tetrad.graph.Graph;
import edu.cmu.tetrad.graph.LayoutUtil;
import edu.cmu.tetrad.graph.Node;
import edu.cmu.tetrad.search.MimbuildTrek;
import edu.cmu.tetrad.search.utils.ClusterUtils;
import edu.cmu.tetrad.search.utils.MimUtils;
import edu.cmu.tetrad.sem.ReidentifyVariables;
import edu.cmu.tetrad.sem.SemPm;
import edu.cmu.tetrad.util.Parameters;
import edu.cmu.tetrad.util.TetradLogger;
import edu.cmu.tetrad.util.TetradSerializableUtils;
import java.io.Serial;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
/**
* Extends AbstractAlgorithmRunner to produce a wrapper for the MIMBuild algorithm.
*
* @author Ricardo Silva
* @version $Id: $Id
*/
public class MimBuildTrekRunner extends AbstractMimRunner implements GraphSource {
@Serial
private static final long serialVersionUID = 23L;
/**
* The data set.
*/
private final DataSet dataSet;
/**
* The full graph.
*/
private Graph fullGraph;
/**
* The covariance matrix.
*/
private ICovarianceMatrix covMatrix;
//============================CONSTRUCTORS===========================//
/**
* Constructor for MimBuildTrekRunner.
*
* @param dataWrapper a {@link edu.cmu.tetradapp.model.DataWrapper} object
* @param mmWrapper a {@link edu.cmu.tetradapp.model.MeasurementModelWrapper} object
* @param params a {@link edu.cmu.tetrad.util.Parameters} object
*/
public MimBuildTrekRunner(DataWrapper dataWrapper,
MeasurementModelWrapper mmWrapper,
Parameters params) {
super(dataWrapper, mmWrapper.getClusters(), params);
this.dataSet = (DataSet) getData();
setClusters(mmWrapper.getClusters());
params.set("clusters", mmWrapper.getClusters());
}
/**
* Constructor for MimBuildTrekRunner.
*
* @param dataWrapper a {@link edu.cmu.tetradapp.model.DataWrapper} object
* @param mmWrapper a {@link edu.cmu.tetradapp.model.BuildPureClustersRunner} object
* @param params a {@link edu.cmu.tetrad.util.Parameters} object
*/
public MimBuildTrekRunner(DataWrapper dataWrapper,
BuildPureClustersRunner mmWrapper,
Parameters params) {
super(dataWrapper, mmWrapper.getClusters(), params);
this.dataSet = (DataSet) getData();
setClusters(mmWrapper.getClusters());
params.set("clusters", mmWrapper.getClusters());
}
/**
* Constructor for MimBuildTrekRunner.
*
* @param dataWrapper a {@link edu.cmu.tetradapp.model.DataWrapper} object
* @param mmWrapper a {@link edu.cmu.tetradapp.model.MeasurementModelWrapper} object
* @param params a {@link edu.cmu.tetrad.util.Parameters} object
* @param knowledgeBoxModel a {@link edu.cmu.tetradapp.model.KnowledgeBoxModel} object
*/
public MimBuildTrekRunner(DataWrapper dataWrapper,
MeasurementModelWrapper mmWrapper,
Parameters params,
KnowledgeBoxModel knowledgeBoxModel) {
super(dataWrapper, mmWrapper.getClusters(), params);
this.dataSet = (DataSet) getData();
setClusters(mmWrapper.getClusters());
params.set("clusters", mmWrapper.getClusters());
params.set("knowledge", knowledgeBoxModel.getKnowledge());
}
/**
* Constructor for MimBuildTrekRunner.
*
* @param mmWrapper a {@link edu.cmu.tetradapp.model.MeasurementModelWrapper} object
* @param dataWrapper a {@link edu.cmu.tetradapp.model.DataWrapper} object
* @param params a {@link edu.cmu.tetrad.util.Parameters} object
*/
public MimBuildTrekRunner(MeasurementModelWrapper mmWrapper,
DataWrapper dataWrapper,
Parameters params) {
super(mmWrapper, mmWrapper.getClusters(), params);
this.dataSet = (DataSet) dataWrapper.getDataModelList().get(0);
setClusters(mmWrapper.getClusters());
params.set("clusters", mmWrapper.getClusters());
}
/**
* Constructor for MimBuildTrekRunner.
*
* @param runner a {@link edu.cmu.tetradapp.model.MimBuildTrekRunner} object
* @param params a {@link edu.cmu.tetrad.util.Parameters} object
*/
public MimBuildTrekRunner(MimBuildTrekRunner runner, Parameters params) {
super(runner, params);
this.dataSet = (DataSet) getData();
setClusters((Clusters) params.get("clusters", null));
}
/**
* Constructor for MimBuildTrekRunner.
*
* @param runner a {@link edu.cmu.tetradapp.model.MimBuildTrekRunner} object
* @param knowledgeBox a {@link edu.cmu.tetradapp.model.KnowledgeBoxModel} object
* @param params a {@link edu.cmu.tetrad.util.Parameters} object
*/
public MimBuildTrekRunner(MimBuildTrekRunner runner, KnowledgeBoxModel knowledgeBox, Parameters params) {
super(runner, params);
this.dataSet = (DataSet) getData();
setClusters((Clusters) params.get("clusters", null));
params.set("knowledge", knowledgeBox.getKnowledge());
}
/**
* 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();
}
/**
* Getter for the field covMatrix.
*
* @return a {@link edu.cmu.tetrad.data.ICovarianceMatrix} object
*/
public ICovarianceMatrix getCovMatrix() {
return this.covMatrix;
}
//===================PUBLIC METHODS OVERRIDING ABSTRACT================//
/**
* Executes the algorithm, producing (at least) a result workbench. Must be implemented in the extending class.
*
* @throws java.lang.Exception if any.
*/
public void execute() throws Exception {
DataSet data = this.dataSet;
MimbuildTrek mimbuild = new MimbuildTrek();
mimbuild.setAlpha(getParams().getDouble("alpha", 0.001));
mimbuild.setKnowledge((Knowledge) getParams().get("knowledge", new Knowledge()));
if (getParams().getBoolean("includeThreeClusters", true)) {
mimbuild.setMinClusterSize(3);
} else {
mimbuild.setMinClusterSize(4);
}
Clusters clusters = (Clusters) getParams().get("clusters", null);
List> partition = ClusterUtils.clustersToPartition(clusters, data.getVariables());
List latentNames = new ArrayList<>();
for (int i = 0; i < clusters.getNumClusters(); i++) {
latentNames.add(clusters.getClusterName(i));
}
CovarianceMatrix cov = new CovarianceMatrix(data);
Graph structureGraph = mimbuild.search(partition, latentNames, cov);
LayoutUtil.defaultLayout(structureGraph);
LayoutUtil.fruchtermanReingoldLayout(structureGraph);
ICovarianceMatrix latentsCov = mimbuild.getLatentsCov();
TetradLogger.getInstance().log("Latent covs = \n" + latentsCov);
Graph fullGraph = mimbuild.getFullGraph();
LayoutUtil.defaultLayout(fullGraph);
LayoutUtil.fruchtermanReingoldLayout(fullGraph);
setResultGraph(fullGraph);
setFullGraph(fullGraph);
setClusters(MimUtils.convertToClusters(structureGraph));
setClusters(ClusterUtils.partitionToClusters(mimbuild.getClustering()));
setStructureGraph(structureGraph);
getParams().set("latentVariableNames", new ArrayList<>(latentNames));
this.covMatrix = latentsCov;
double p = mimbuild.getpValue();
TetradLogger.getInstance().log("\nStructure graph = " + structureGraph);
TetradLogger.getInstance().log(getLatentClustersString(fullGraph).toString());
TetradLogger.getInstance().log("P = " + p);
if (getParams().getBoolean("showMaxP", false)) {
if (p > getParams().getDouble("maxP", 1.0)) {
getParams().set("maxP", p);
getParams().set("maxStructureGraph", structureGraph);
getParams().set("maxClusters", getClusters());
getParams().set("maxFullGraph", fullGraph);
getParams().set("maxAlpha", getParams().getDouble("alpha", 0.001));
}
setStructureGraph((Graph) getParams().get("maxStructureGraph", null));
setFullGraph((Graph) getParams().get("maxFullGraph", null));
if (getParams().get("maxClusters", null) != null) {
setClusters((Clusters) getParams().get("maxClusters", null));
}
setResultGraph((Graph) getParams().get("maxFullGraph", null));
String message1 = "\nMAX Graph = " + getParams().get("maxStructureGraph", null);
TetradLogger.getInstance().log(message1);
TetradLogger.getInstance().log(getLatentClustersString((Graph) getParams().get("maxFullGraph", null)).toString());
String message = "MAX P = " + getParams().getDouble("maxP", 1.0);
TetradLogger.getInstance().log(message);
}
}
private StringBuilder getLatentClustersString(Graph graph) {
StringBuilder builder = new StringBuilder();
builder.append("Latent Clusters:\n");
List latents = ReidentifyVariables.getLatents(graph);
Collections.sort(latents);
for (Node latent : latents) {
List children = graph.getChildren(latent);
latents.forEach(children::remove);
// Collections.sort(children);
builder.append(latent.getName()).append(": ");
for (Node child : children) {
builder.append(child).append(" ");
}
builder.append("\n");
}
return builder;
}
/**
* getGraph.
*
* @return a {@link edu.cmu.tetrad.graph.Graph} object
*/
public Graph getGraph() {
return getResultGraph();
}
//===========================PRIVATE METHODS==========================//
/**
* getSemPm.
*
* @return a {@link edu.cmu.tetrad.sem.SemPm} object
*/
public SemPm getSemPm() {
Graph graph = getResultGraph();
return new SemPm(graph);
}
/**
* Getter for the field fullGraph.
*
* @return a {@link edu.cmu.tetrad.graph.Graph} object
*/
public Graph getFullGraph() {
return this.fullGraph;
}
private void setFullGraph(Graph fullGraph) {
this.fullGraph = fullGraph;
}
}
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