use of edu.cmu.tetrad.search.SemBicScoreImages in project tetrad by cmu-phil.
the class TsImages method search.
@Override
public Graph search(List<DataModel> dataSets, Parameters parameters) {
List<DataModel> dataModels = new ArrayList<>();
for (DataModel dataSet : dataSets) {
dataModels.add(dataSet);
}
TsGFci search;
if (score instanceof SemBicScore) {
SemBicScoreImages gesScore = new SemBicScoreImages(dataModels);
gesScore.setPenaltyDiscount(parameters.getDouble("penaltyDiscount"));
IndependenceTest test = new IndTestScore(gesScore);
search = new TsGFci(test, gesScore);
} else if (score instanceof BdeuScore) {
double samplePrior = parameters.getDouble("samplePrior", 1);
double structurePrior = parameters.getDouble("structurePrior", 1);
BdeuScoreImages score = new BdeuScoreImages(dataModels);
score.setSamplePrior(samplePrior);
score.setStructurePrior(structurePrior);
IndependenceTest test = new IndTestScore(score);
search = new TsGFci(test, score);
} else {
throw new IllegalStateException("Sorry, data must either be all continuous or all discrete.");
}
IKnowledge knowledge = dataModels.get(0).getKnowledge();
search.setKnowledge(knowledge);
return search.search();
}
use of edu.cmu.tetrad.search.SemBicScoreImages in project tetrad by cmu-phil.
the class ImagesSemBic method search.
@Override
public Graph search(List<DataModel> dataSets, Parameters parameters) {
if (parameters.getInt("bootstrapSampleSize") < 1) {
final SemBicScoreImages score = new SemBicScoreImages(dataSets);
score.setPenaltyDiscount(parameters.getDouble("penaltyDiscount"));
edu.cmu.tetrad.search.Fges search = new edu.cmu.tetrad.search.Fges(score);
search.setKnowledge(knowledge);
return search.search();
} else {
ImagesSemBic imagesSemBic = new ImagesSemBic();
// imagesSemBic.setKnowledge(knowledge);
List<DataSet> datasets = new ArrayList<>();
for (DataModel dataModel : dataSets) {
datasets.add((DataSet) dataModel);
}
GeneralBootstrapTest search = new GeneralBootstrapTest(datasets, imagesSemBic, parameters.getInt("bootstrapSampleSize"));
search.setKnowledge(knowledge);
BootstrapEdgeEnsemble edgeEnsemble = BootstrapEdgeEnsemble.Highest;
switch(parameters.getInt("bootstrapEnsemble", 1)) {
case 0:
edgeEnsemble = BootstrapEdgeEnsemble.Preserved;
break;
case 1:
edgeEnsemble = BootstrapEdgeEnsemble.Highest;
break;
case 2:
edgeEnsemble = BootstrapEdgeEnsemble.Majority;
}
search.setEdgeEnsemble(edgeEnsemble);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean("verbose"));
return search.search();
}
}
use of edu.cmu.tetrad.search.SemBicScoreImages in project tetrad by cmu-phil.
the class TsImagesSemBic method search.
@Override
public Graph search(List<DataModel> dataModels, Parameters parameters) {
if (parameters.getInt("bootstrapSampleSize") < 1) {
List<DataSet> dataSets = new ArrayList<>();
for (DataModel dataModel : dataModels) {
dataSets.add((DataSet) dataModel);
}
edu.cmu.tetrad.search.TsGFci search = new edu.cmu.tetrad.search.TsGFci(new IndTestScore(new SemBicScoreImages(dataModels)), new SemBicScoreImages(dataModels));
search.setFaithfulnessAssumed(true);
search.setKnowledge(knowledge);
return search.search();
} else {
TsImagesSemBic tsImagesSemBic = new TsImagesSemBic();
// tsImagesSemBic.setKnowledge(knowledge);
List<DataSet> datasets = new ArrayList<>();
for (DataModel dataModel : dataModels) {
datasets.add((DataSet) dataModel);
}
GeneralBootstrapTest search = new GeneralBootstrapTest(datasets, tsImagesSemBic, parameters.getInt("bootstrapSampleSize"));
search.setKnowledge(knowledge);
BootstrapEdgeEnsemble edgeEnsemble = BootstrapEdgeEnsemble.Highest;
switch(parameters.getInt("bootstrapEnsemble", 1)) {
case 0:
edgeEnsemble = BootstrapEdgeEnsemble.Preserved;
break;
case 1:
edgeEnsemble = BootstrapEdgeEnsemble.Highest;
break;
case 2:
edgeEnsemble = BootstrapEdgeEnsemble.Majority;
}
search.setEdgeEnsemble(edgeEnsemble);
search.setParameters(parameters);
search.setVerbose(parameters.getBoolean("verbose"));
return search.search();
}
}
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