use of edu.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest in project tetrad by cmu-phil.
the class FgesConcatenated 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);
}
DataSet dataSet = DataUtils.concatenate(dataSets);
Graph initial = null;
if (initialGraph != null) {
initial = initialGraph.search(dataSet, parameters);
}
edu.cmu.tetrad.search.Fges search = new edu.cmu.tetrad.search.Fges(score.getScore(dataSet, parameters));
search.setFaithfulnessAssumed(parameters.getBoolean("faithfulnessAssumed"));
search.setKnowledge(knowledge);
search.setVerbose(parameters.getBoolean("verbose"));
search.setMaxDegree(parameters.getInt("maxDegree"));
Object obj = parameters.get("printStedu.cmream");
if (obj instanceof PrintStream) {
search.setOut((PrintStream) obj);
}
if (initial != null) {
search.setInitialGraph(initial);
}
return search.search();
} else {
FgesConcatenated fgesConcatenated = new FgesConcatenated(score, initialGraph);
fgesConcatenated.setCompareToTrue(compareToTrue);
// fgesConcatenated.setKnowledge(knowledge);
List<DataSet> datasets = new ArrayList<>();
for (DataModel dataModel : dataModels) {
datasets.add((DataSet) dataModel);
}
GeneralBootstrapTest search = new GeneralBootstrapTest(datasets, fgesConcatenated, 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.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest in project tetrad by cmu-phil.
the class ImagesCcd method search.
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (!parameters.getBoolean("bootstrapping")) {
return search(Collections.singletonList((DataModel) DataUtils.getContinuousDataSet(dataSet)), parameters);
} else {
ImagesCcd imagesCcd = new ImagesCcd();
imagesCcd.setKnowledge(knowledge);
List<DataSet> dataSets = Collections.singletonList(DataUtils.getContinuousDataSet(dataSet));
GeneralBootstrapTest search = new GeneralBootstrapTest(dataSets, imagesCcd, parameters.getInt("bootstrapSampleSize"));
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.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest in project tetrad by cmu-phil.
the class ImagesCcd 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);
}
SemBicScoreImages score = new SemBicScoreImages(dataModels);
score.setPenaltyDiscount(parameters.getDouble("penaltyDiscount"));
IndependenceTest test = new IndTestScore(score);
edu.cmu.tetrad.search.CcdMax search = new edu.cmu.tetrad.search.CcdMax(test);
search.setCollapseTiers(parameters.getBoolean("collapseTiers"));
search.setOrientConcurrentFeedbackLoops(parameters.getBoolean("orientVisibleFeedbackLoops"));
search.setDoColliderOrientations(parameters.getBoolean("doColliderOrientation"));
search.setUseHeuristic(parameters.getBoolean("useMaxPOrientationHeuristic"));
search.setMaxPathLength(parameters.getInt("maxPOrientationMaxPathLength"));
search.setDepth(parameters.getInt("depth"));
search.setApplyOrientAwayFromCollider(parameters.getBoolean("applyR1"));
search.setUseOrientTowardDConnections(parameters.getBoolean("orientTowardDConnections"));
search.setKnowledge(knowledge);
search.setDepth(parameters.getInt("depth"));
return search.search();
} else {
ImagesCcd imagesCcd = new ImagesCcd();
// imagesCcd.setKnowledge(knowledge);
List<DataSet> datasets = new ArrayList<>();
for (DataModel dataModel : dataModels) {
datasets.add((DataSet) dataModel);
}
GeneralBootstrapTest search = new GeneralBootstrapTest(datasets, imagesCcd, 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.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest in project tetrad by cmu-phil.
the class ImagesSemBic method search.
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (!parameters.getBoolean("bootstrapping")) {
return search(Collections.singletonList((DataModel) DataUtils.getContinuousDataSet(dataSet)), parameters);
} else {
ImagesSemBic imagesSemBic = new ImagesSemBic();
imagesSemBic.setKnowledge(knowledge);
List<DataSet> dataSets = Collections.singletonList(DataUtils.getContinuousDataSet(dataSet));
GeneralBootstrapTest search = new GeneralBootstrapTest(dataSets, imagesSemBic, parameters.getInt("bootstrapSampleSize"));
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.pitt.dbmi.algo.bootstrap.GeneralBootstrapTest in project tetrad by cmu-phil.
the class Fofc method search.
@Override
public Graph search(DataModel dataSet, Parameters parameters) {
if (parameters.getInt("bootstrapSampleSize") < 1) {
ICovarianceMatrix cov = DataUtils.getCovMatrix(dataSet);
double alpha = parameters.getDouble("alpha");
boolean wishart = parameters.getBoolean("useWishart", true);
TestType testType;
if (wishart) {
testType = TestType.TETRAD_WISHART;
} else {
testType = TestType.TETRAD_DELTA;
}
boolean gap = parameters.getBoolean("useGap", true);
FindOneFactorClusters.Algorithm algorithm;
if (gap) {
algorithm = FindOneFactorClusters.Algorithm.GAP;
} else {
algorithm = FindOneFactorClusters.Algorithm.SAG;
}
edu.cmu.tetrad.search.FindOneFactorClusters search = new edu.cmu.tetrad.search.FindOneFactorClusters(cov, testType, algorithm, alpha);
search.setVerbose(parameters.getBoolean("verbose"));
return search.search();
} else {
Fofc algorithm = new Fofc();
// algorithm.setKnowledge(knowledge);
// if (initialGraph != null) {
// algorithm.setInitialGraph(initialGraph);
// }
DataSet data = (DataSet) dataSet;
GeneralBootstrapTest search = new GeneralBootstrapTest(data, algorithm, 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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