Examples with SemBicScore edu.cmu.tetrad.algcomparison.score.SemBicScore used on opensource projects

Example 6 with SemBicScore

use of edu.cmu.tetrad.algcomparison.score.SemBicScore in project tetrad by cmu-phil.

the class Condition1 method generateTetradResults.

public void generateTetradResults() {
    Parameters parameters = new Parameters();
    parameters.set("alpha", 0.001);
    parameters.set("numRuns", 10);
    // parameters.set("penaltyDiscount", 4);
    parameters.set("useMaxPOrientationHeuristic", true);
    parameters.set("maxPOrientationMaxPathLength", 3);
    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.add(new PercentBidirectedEdges());
    // statistics.add(new NumAmbiguousTriples());
    statistics.setWeight("AP", 1.0);
    statistics.setWeight("AR", 0.5);
    statistics.setWeight("AHP", 1.0);
    statistics.setWeight("AHR", 0.5);
    Algorithms algorithms = new Algorithms();
    // algorithms.add(new Pc(new FisherZ()));
    // algorithms.add(new PcStable(new FisherZ()));
    // algorithms.add(new PcStableMax(new FisherZ(), false));
    // algorithms.add(new Cpc(new FisherZ()));
    // algorithms.add(new CpcStable(new FisherZ()));
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(true);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(true);
    comparison.setSaveGraphs(true);
    // comparison.compareFromFiles("/Users/user/comparison-data/condition_1",
    // "/Users/user/causal-comparisons/condition_1",
    // algorithms, statistics, parameters);
    // 
    // algorithms = new Algorithms();
    // 
    // parameters.set("alpha", 0.001, 0.0001, 1e-8);
    // parameters.set("faithfulnessAssumed", true);
    // //
    // algorithms.add(new Fges(new FisherZScore()));
    // 
    // comparison.compareFromFiles("/Users/user/comparison-data/condition_1",
    // "/Users/user/causal-comparisons/condition_1",
    // algorithms, statistics, parameters);
    // 
    // algorithms = new Algorithms();
    parameters.set("penaltyDiscount", 4);
    // 
    algorithms.add(new Fges(new SemBicScore()));
    comparison.compareFromFiles("/Users/user/comparison-data/condition_1", "/Users/user/causal-comparisons/condition_1", algorithms, statistics, parameters);
}

Example 7 with SemBicScore

use of edu.cmu.tetrad.algcomparison.score.SemBicScore 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);
}

Example 8 with SemBicScore

use of edu.cmu.tetrad.algcomparison.score.SemBicScore in project tetrad by cmu-phil.

the class TestSimulatedFmri method testTough.

// @Test
public void testTough() {
    Parameters parameters = new Parameters();
    parameters.set("penaltyDiscount", 2);
    parameters.set("depth", 5);
    parameters.set("twoCycleAlpha", .01);
    parameters.set("numRuns", 1);
    parameters.set("randomSelectionSize", 10);
    parameters.set("Structure", "Placeholder");
    Statistics statistics = new Statistics();
    statistics.add(new ParameterColumn("Structure"));
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    statistics.add(new MathewsCorrAdj());
    statistics.add(new ArrowheadPrecision());
    statistics.add(new ArrowheadRecall());
    statistics.add(new TwoCyclePrecision());
    statistics.add(new TwoCycleRecall());
    statistics.add(new TwoCycleFalsePositive());
    statistics.add(new TwoCycleFalseNegative());
    statistics.add(new TwoCycleTruePositive());
    statistics.add(new ElapsedTime());
    statistics.setWeight("AP", 1.0);
    statistics.setWeight("AR", 1.0);
    statistics.setWeight("AHP", 1.0);
    statistics.setWeight("AHR", 1.0);
    statistics.setWeight("2CP", 1.0);
    statistics.setWeight("2CR", 1.0);
    statistics.setWeight("2CFP", 1.0);
    Simulations simulations = new Simulations();
    String dir = "/Users/jdramsey/Downloads/";
    String subdir = "data_fslfilter";
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Markov_dist_thresh36", subdir));
    Algorithms algorithms = new Algorithms();
    // algorithms.add(new FasLofs(Lofs2.Rule.R1));
    // algorithms.add(new FasLofs(Lofs2.Rule.R2));
    // algorithms.add(new FasLofs(Lofs2.Rule.R3));
    // algorithms.add(new FasLofs(Lofs2.Rule.Patel));
    // algorithms.add(new FasLofs(Lofs2.Rule.Skew));
    // algorithms.add(new FasLofs(Lofs2.Rule.RSkew));
    // 
    // algorithms.add(new FgesConcatenated(new edu.cmu.tetrad.algcomparison.score.SemBicScore(), true));
    // algorithms.add(new PcStableMaxConcatenated(new SemBicTest(), true));
    algorithms.add(new FaskConcatenated(new SemBicScore()));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.R1));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.R2));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.R3));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.Patel));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.Skew));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.RSkew));
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(true);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(false);
    comparison.setParallelized(false);
    comparison.setSaveGraphs(false);
    comparison.setTabDelimitedTables(false);
    comparison.compareFromSimulations("comparison", simulations, algorithms, statistics, parameters);
}

Example 9 with SemBicScore

use of edu.cmu.tetrad.algcomparison.score.SemBicScore in project tetrad by cmu-phil.

the class TestSimulatedFmri method task2.

// @Test
public void task2() {
    Parameters parameters = new Parameters();
    parameters.set("penaltyDiscount", 1);
    parameters.set("depth", -1);
    parameters.set("twoCycleAlpha", 0);
    parameters.set("faskDelta", -.1);
    parameters.set("numRuns", 10);
    parameters.set("randomSelectionSize", 2);
    parameters.set("Structure", "Placeholder");
    Statistics statistics = new Statistics();
    statistics.add(new ParameterColumn("Structure"));
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    // statistics.add(new MathewsCorrAdj());
    statistics.add(new ArrowheadPrecision());
    statistics.add(new ArrowheadRecall());
    statistics.add(new TwoCyclePrecision());
    statistics.add(new TwoCycleRecall());
    statistics.add(new TwoCycleFalsePositive());
    statistics.add(new TwoCycleFalseNegative());
    statistics.add(new TwoCycleTruePositive());
    statistics.add(new ElapsedTime());
    statistics.setWeight("AHR", 1.0);
    statistics.setWeight("2CP", 1.0);
    statistics.setWeight("2CR", 1.0);
    statistics.setWeight("2CFP", 1.0);
    Simulations simulations = new Simulations();
    Algorithms algorithms = new Algorithms();
    for (int i = 1; i <= 28; i++) {
        // if (i == 21) continue;
        simulations.add(new LoadContinuousDataSmithSim("/Users/user/Downloads/smithsim/", i));
    // simulations.add(new LoadContinuousDataPwdd7("/Users/user/Downloads/pwdd7/", i, "50_BOLDdemefilt1"));
    // simulations.add(new LoadContinuousDataPwdd7("/Users/user/Downloads/pwdd7/", i, "50_BOLDnoise"));
    }
    // algorithms.add(new LofsConcatenated(Lofs2.Rule.FASKLR));
    // algorithms.add(new LofsConcatenated(Lofs2.Rule.R1));
    // algorithms.add(new LofsConcatenated(Lofs2.Rule.R3));
    // algorithms.add(new LofsConcatenated(Lofs2.Rule.RSkew));
    // algorithms.add(new LofsConcatenated(Lofs2.Rule.RSkewE));
    // algorithms.add(new LofsConcatenated(Lofs2.Rule.Skew));
    // algorithms.add(new LofsConcatenated(Lofs2.Rule.SkewE));
    // algorithms.add(new LofsConcatenated(Lofs2.Rule.Patel));
    algorithms.add(new FaskConcatenated(new SemBicScore()));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.R1));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.R3));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.RSkew));
    // algorithms.add(new FasLofsConfcatenated(Lofs2.Rule.RSkewE));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.Skew));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.SkewE));
    // algorithms.add(new FasLofsConcatenated(Lofs2.Rule.Patel));
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(true);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(false);
    comparison.setParallelized(false);
    comparison.setSaveGraphs(false);
    comparison.setTabDelimitedTables(false);
    comparison.setSaveGraphs(true);
    String directory = "smithsim";
    comparison.compareFromSimulations(directory, simulations, algorithms, statistics, parameters);
}

Example 10 with SemBicScore

use of edu.cmu.tetrad.algcomparison.score.SemBicScore in project tetrad by cmu-phil.

the class TestKunMeasurementError method TestCycles_Data_fMRI_FASK.

public void TestCycles_Data_fMRI_FASK() {
    Parameters parameters = new Parameters();
    parameters.set("numRuns", 20);
    parameters.set("penaltyDiscount", 1);
    parameters.set("depth", -1);
    parameters.set("determinismThreshold", .1);
    parameters.set("verbose", true);
    parameters.set("symmetricFirstStep", false);
    parameters.set("faithfulnessAssumed", false);
    parameters.set("maxDegree", 100);
    Statistics statistics = new Statistics();
    // statistics.add(new ParameterColumn("determinismThreshold"));
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    statistics.add(new ArrowheadPrecision());
    statistics.add(new ArrowheadRecall());
    Simulations simulations = new Simulations();
    // String dir = "/Users/user/Downloads/Simul1_T500";
    String dir = "/Users/user/Downloads/Simul1_T2000";
    // String dir = "/Users/user/Downloads/Simul2_T500";
    // String dir = "/Users/user/Downloads/Simul2_T2000";
    simulations.add(new LoadContinuousDataAndSingleGraphKun(dir, "Cov_X"));
    simulations.add(new LoadContinuousDataAndSingleGraphKun(dir, "Cov_tilde"));
    simulations.add(new LoadContinuousDataAndSingleGraphKun(dir, "Cov_tilde_hat"));
    // 
    Algorithms algorithms = new Algorithms();
    IndependenceWrapper test = new SemBicTest();
    ScoreWrapper score = new SemBicScore();
    algorithms.add(new Pc(test));
    algorithms.add(new Fges(score));
    algorithms.add(new Pcd());
    algorithms.add(new FgesD());
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(true);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(false);
    comparison.setParallelized(false);
    comparison.setSaveGraphs(false);
    comparison.setTabDelimitedTables(false);
    comparison.compareFromSimulations("comparison", simulations, algorithms, statistics, parameters);
}