/**
* Executes the algorithm, producing (at least) a result workbench. Must be implemented in the
* extending class.
*/
public void execute() {
IKnowledge knowledge = getParams().getKnowledge();
SearchParams searchParams = getParams();
FciIndTestParams indTestParams = (FciIndTestParams) searchParams.getIndTestParams();
// Cfci fciSearch =
// new Cfci(getIndependenceTest(), knowledge);
// fciSearch.setMaxIndegree(indTestParams.depth());
// Graph graph = fciSearch.search();
//
// if (knowledge.isDefaultToKnowledgeLayout()) {
// SearchGraphUtils.arrangeByKnowledgeTiers(graph, knowledge);
// }
//
// setResultGraph(graph);
Graph graph;
if (indTestParams.isRFCI_Used()) {
Rfci fci = new Rfci(getIndependenceTest());
fci.setKnowledge(knowledge);
fci.setCompleteRuleSetUsed(indTestParams.isCompleteRuleSetUsed());
fci.setMaxPathLength(indTestParams.getMaxReachablePathLength());
fci.setDepth(indTestParams.getDepth());
graph = fci.search();
} else {
Fci fci = new Fci(getIndependenceTest());
fci.setKnowledge(knowledge);
fci.setCompleteRuleSetUsed(indTestParams.isCompleteRuleSetUsed());
fci.setPossibleDsepSearchDone(indTestParams.isPossibleDsepDone());
fci.setMaxPathLength(indTestParams.getMaxReachablePathLength());
fci.setDepth(indTestParams.getDepth());
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);
}
/**
* Executes the algorithm, producing (at least) a result workbench. Must be implemented in the
* extending class.
*/
public void execute() {
IKnowledge knowledge = getParams().getKnowledge();
SearchParams searchParams = getParams();
FciGesIndTestParams indTestParams = (FciGesIndTestParams) searchParams.getIndTestParams();
// Cfci fciSearch =
// new Cfci(getIndependenceTest(), knowledge);
// fciSearch.setDepth(indTestParams.depth());
// Graph graph = fciSearch.search();
//
// if (knowledge.isDefaultToKnowledgeLayout()) {
// SearchGraphUtils.arrangeByKnowledgeTiers(graph, knowledge);
// }
//
// setResultGraph(graph);
Graph graph;
TFciGes fci = new TFciGes(getIndependenceTest());
fci.setKnowledge(knowledge);
fci.setCompleteRuleSetUsed(indTestParams.isCompleteRuleSetUsed());
fci.setPossibleDsepSearchDone(indTestParams.isPossibleDsepDone());
fci.setMaxPathLength(indTestParams.getMaxReachablePathLength());
fci.setDepth(indTestParams.getDepth());
fci.setPenaltyDiscount(indTestParams.getPenaltyDiscount());
fci.setSamplePrior(indTestParams.getSamplePrior());
fci.setStructurePrior(indTestParams.getStructurePrior());
fci.setCompleteRuleSetUsed(false);
fci.setPenaltyDiscount(indTestParams.getPenaltyDiscount());
fci.setFaithfulnessAssumed(indTestParams.isFaithfulnessAssumed());
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);
}
public void execute() {
IKnowledge knowledge = getParams().getKnowledge();
PcSearchParams searchParams = (PcSearchParams) getParams();
PcIndTestParams indTestParams = (PcIndTestParams) searchParams.getIndTestParams();
VcpcAlt VcpcAlt = new VcpcAlt(getIndependenceTest());
VcpcAlt.setKnowledge(knowledge);
VcpcAlt.setAggressivelyPreventCycles(this.isAggressivelyPreventCycles());
VcpcAlt.setDepth(indTestParams.getDepth());
Graph graph = VcpcAlt.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);
}
/**
* 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);
}
/**
* Executes the algorithm, producing (at least) a result workbench. Must be implemented in the
* extending class.
*/
public void execute() {
Object source = dataWrapper.getSelectedDataModel();
DataModel dataModel = (DataModel) source;
IKnowledge knowledge = params2.getKnowledge();
if (initialGraph == null) {
initialGraph = new EdgeListGraph(dataModel.getVariables());
}
Graph graph2 = new EdgeListGraph(initialGraph);
graph2 = GraphUtils.replaceNodes(graph2, dataModel.getVariables());
Bff search;
if (dataModel instanceof DataSet) {
DataSet dataSet = (DataSet) dataModel;
if (getAlgorithmType() == AlgorithmType.BEAM) {
search = new BffBeam(graph2, dataSet, knowledge);
} else if (getAlgorithmType() == AlgorithmType.GES) {
search = new BffGes(graph2, dataSet);
search.setKnowledge(knowledge);
} else {
throw new IllegalStateException();
}
} else if (dataModel instanceof CovarianceMatrix) {
CovarianceMatrix covarianceMatrix = (CovarianceMatrix) dataModel;
if (getAlgorithmType() == AlgorithmType.BEAM) {
search = new BffBeam(graph2, covarianceMatrix, knowledge);
} else if (getAlgorithmType() == AlgorithmType.GES) {
throw new IllegalArgumentException(
"GES method requires a dataset; a covariance matrix was provided.");
// search = new BffGes(graph2, covarianceMatrix);
// search.setKnowledge(knowledge);
} else {
throw new IllegalStateException();
}
} else {
throw new IllegalStateException();
}
PcIndTestParams indTestParams = (PcIndTestParams) getParams().getIndTestParams();
search.setAlpha(indTestParams.getAlpha());
search.setBeamWidth(indTestParams.getBeamWidth());
search.setHighPValueAlpha(indTestParams.getZeroEdgeP());
this.graph = search.search();
// this.graph = search.getNewSemIm().getSemPm().getGraph();
setOriginalSemIm(search.getOriginalSemIm());
this.newSemIm = search.getNewSemIm();
fireGraphChange(graph);
if (getSourceGraph() != null) {
GraphUtils.arrangeBySourceGraph(graph, getSourceGraph());
} else if (knowledge.isDefaultToKnowledgeLayout()) {
SearchGraphUtils.arrangeByKnowledgeTiers(graph, knowledge);
} else {
GraphUtils.circleLayout(graph, 200, 200, 150);
}
setResultGraph(SearchGraphUtils.patternForDag(graph, knowledge));
}