use of edu.cmu.tetrad.algcomparison.algorithm.FirstInflection in project tetrad by cmu-phil.
the class ExampleFirstInflection method main.
public static void main(String... args) {
Parameters parameters = new Parameters();
parameters.set("numMeasures", 40, 100);
parameters.set("avgDegree", 2);
parameters.set("sampleSize", 400, 800);
parameters.set("numRuns", 10);
parameters.set("differentGraphs", true);
parameters.set("numLatents", 0);
parameters.set("maxDegree", 100);
parameters.set("maxIndegree", 100);
parameters.set("maxOutdegree", 100);
parameters.set("connected", false);
parameters.set("coefLow", 0.2);
parameters.set("coefHigh", 0.9);
parameters.set("varLow", 1);
parameters.set("varHigh", 3);
parameters.set("verbose", false);
parameters.set("coefSymmetric", true);
parameters.set("percentDiscrete", 0);
parameters.set("numCategories", 3);
parameters.set("differentGraphs", true);
parameters.set("intervalBetweenShocks", 10);
parameters.set("intervalBetweenRecordings", 10);
parameters.set("fisherEpsilon", 0.001);
parameters.set("randomizeColumns", true);
parameters.set("alpha", 1e-8);
parameters.set("depth", -1);
parameters.set("penaltyDiscount", 4);
parameters.set("useMaxPOrientationHeuristic", false);
parameters.set("maxPOrientationMaxPathLength", 3);
parameters.set("verbose", false);
parameters.set("scaleFreeAlpha", 0.00001);
parameters.set("scaleFreeBeta", 0.4);
parameters.set("scaleFreeDeltaIn", .1);
parameters.set("scaleFreeDeltaOut", 3);
parameters.set("symmetricFirstStep", false);
parameters.set("faithfulnessAssumed", true);
parameters.set("maxDegree", 100);
// parameters.set("logScale", true);
Statistics statistics = new Statistics();
statistics.add(new ParameterColumn("numMeasures"));
statistics.add(new ParameterColumn("avgDegree"));
statistics.add(new ParameterColumn("sampleSize"));
statistics.add(new AdjacencyPrecision());
statistics.add(new AdjacencyRecall());
statistics.add(new ArrowheadPrecision());
statistics.add(new ArrowheadRecall());
statistics.add(new ElapsedTime());
statistics.setWeight("AP", 0.25);
statistics.setWeight("AR", 0.25);
statistics.setWeight("AHP", 0.25);
statistics.setWeight("AHR", 0.25);
Algorithms algorithms = new Algorithms();
Algorithm fges = new Fges(new SemBicScore());
// algorithms.add(new FirstInflection(fges, "alpha", -7, -2, -.5));
algorithms.add(new FirstInflection(fges, "penaltyDiscount", 0.7, 5, 1));
Simulations simulations = new Simulations();
simulations.add(new LinearFisherModel(new RandomForward()));
Comparison comparison = new Comparison();
comparison.setShowAlgorithmIndices(true);
comparison.setShowSimulationIndices(true);
comparison.setSortByUtility(false);
comparison.setShowUtilities(false);
comparison.setParallelized(true);
comparison.setComparisonGraph(Comparison.ComparisonGraph.Pattern_of_the_true_DAG);
comparison.compareFromSimulations("first.inflection", simulations, algorithms, statistics, parameters);
}
use of edu.cmu.tetrad.algcomparison.algorithm.FirstInflection in project tetrad by cmu-phil.
the class ExampleStARS method main.
public static void main(String... args) {
Parameters parameters = new Parameters();
// parameters.set("numMeasures", 100);
// parameters.set("avgDegree", 2, 4);
// parameters.set("sampleSize", 100, 500);
// parameters.set("numRuns", 5);
parameters.set("numMeasures", 200);
parameters.set("avgDegree", 2, 4, 6);
parameters.set("sampleSize", 100, 500);
parameters.set("numRuns", 2);
parameters.set("differentGraphs", true);
parameters.set("numLatents", 0);
parameters.set("maxDegree", 100);
parameters.set("maxIndegree", 100);
parameters.set("maxOutdegree", 100);
parameters.set("connected", false);
parameters.set("coefLow", 0.2);
parameters.set("coefHigh", 0.9);
parameters.set("varLow", 1);
parameters.set("varHigh", 3);
parameters.set("verbose", false);
parameters.set("coefSymmetric", true);
parameters.set("percentDiscrete", 0);
parameters.set("numCategories", 3);
parameters.set("differentGraphs", true);
parameters.set("intervalBetweenShocks", 10);
parameters.set("intervalBetweenRecordings", 10);
parameters.set("fisherEpsilon", 0.001);
parameters.set("randomizeColumns", true);
parameters.set("alpha", 0.01);
parameters.set("depth", -1);
parameters.set("penaltyDiscount", 2);
parameters.set("useMaxPOrientationHeuristic", false);
parameters.set("maxPOrientationMaxPathLength", 3);
parameters.set("verbose", false);
parameters.set("scaleFreeAlpha", 0.00001);
parameters.set("scaleFreeBeta", 0.4);
parameters.set("scaleFreeDeltaIn", .1);
parameters.set("scaleFreeDeltaOut", 3);
parameters.set("symmetricFirstStep", false);
parameters.set("faithfulnessAssumed", true);
parameters.set("maxDegree", 100);
parameters.set("StARS.tolerance", .5);
parameters.set("StARS.cutoff", .05);
parameters.set("numSubsamples", 7);
parameters.set("percentSubsampleSize", .5);
parameters.set("percentStability", .5);
Statistics statistics = new Statistics();
statistics.add(new ParameterColumn("numMeasures"));
statistics.add(new ParameterColumn("avgDegree"));
statistics.add(new ParameterColumn("sampleSize"));
statistics.add(new AdjacencyPrecision());
statistics.add(new AdjacencyRecall());
statistics.add(new ArrowheadPrecision());
statistics.add(new ArrowheadRecall());
statistics.add(new ElapsedTime());
statistics.setWeight("AP", 0.25);
statistics.setWeight("AR", 0.25);
statistics.setWeight("AHP", 0.25);
statistics.setWeight("AHR", 0.25);
Algorithms algorithms = new Algorithms();
parameters.set("logScale", false);
algorithms.add(new StabilitySelection(new Fges(new SemBicScore())));
algorithms.add(new StARS(new Fges(new SemBicScore()), "penaltyDiscount", 1, 5));
algorithms.add(new FirstInflection(new Fges(new SemBicScore()), "penaltyDiscount", 1, 5, .1));
// parameters.set("penaltyDiscount", 5, 11, 15);
// algorithms.add(new Fges(new SemBicScore()));
// parameters.set("logScale", true);
// Algorithm fges = new Fges(new FisherZScore());
// algorithms.add(new StARS(fges, "alpha", -10, -2, -8));
// algorithms.add(new FirstInflection(fges, "alpha", -10, -2, -3));
Simulations simulations = new Simulations();
simulations.add(new LinearFisherModel(new RandomForward()));
Comparison comparison = new Comparison();
comparison.setShowAlgorithmIndices(true);
comparison.setShowSimulationIndices(true);
comparison.setSortByUtility(false);
comparison.setShowUtilities(false);
comparison.setParallelized(true);
comparison.setComparisonGraph(Comparison.ComparisonGraph.Pattern_of_the_true_DAG);
comparison.compareFromSimulations("first.inflection", simulations, algorithms, statistics, parameters);
}
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