@Override
public Graph search(DataSet dataSet, Parameters parameters) {
edu.cmu.tetrad.search.Mbfs search =
new edu.cmu.tetrad.search.Mbfs(
test.getTest(dataSet, parameters), parameters.getInt("depth"));
search.setKnowledge(knowledge);
this.targetName = parameters.getString("targetName");
Node target = dataSet.getVariable(targetName);
return search.search(target);
}
/**
* Executes the algorithm, producing (at least) a result workbench. Must be implemented in the
* extending class.
*/
public void execute() {
IKnowledge knowledge = (IKnowledge) getParams().get("knowledge", new Knowledge2());
Parameters searchParams = getParams();
Parameters params = searchParams;
Graph graph;
IndependenceTest independenceTest = getIndependenceTest();
Score score = new ScoredIndTest(independenceTest);
if (independenceTest instanceof IndTestDSep) {
final DagToPag dagToPag = new DagToPag(((IndTestDSep) independenceTest).getGraph());
dagToPag.setCompleteRuleSetUsed(params.getBoolean("completeRuleSetUsed", false));
graph = dagToPag.convert();
} else {
GFci fci = new GFci(independenceTest, score);
fci.setKnowledge(knowledge);
fci.setCompleteRuleSetUsed(params.getBoolean("completeRuleSetUsed", false));
fci.setMaxPathLength(params.getInt("maxReachablePathLength", -1));
fci.setMaxDegree(params.getInt("maxIndegree"));
fci.setCompleteRuleSetUsed(false);
fci.setFaithfulnessAssumed(params.getBoolean("faithfulnessAssumed", true));
graph = fci.search();
}
if (getSourceGraph() != null) {
GraphUtils.arrangeBySourceGraph(graph, getSourceGraph());
} else if (knowledge.isDefaultToKnowledgeLayout()) {
SearchGraphUtils.arrangeByKnowledgeTiers(graph, knowledge);
} else {
GraphUtils.circleLayout(graph, 200, 200, 150);
}
setResultGraph(graph);
}