Examples with Comparison edu.cmu.tetrad.algcomparison.Comparison used on opensource projects

Example 11 with Comparison

use of edu.cmu.tetrad.algcomparison.Comparison 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 12 with Comparison

use of edu.cmu.tetrad.algcomparison.Comparison 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 13 with Comparison

use of edu.cmu.tetrad.algcomparison.Comparison 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 14 with Comparison

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

the class TestSimulatedFmr3 method TestCycles_Data_fMRI_FASK.

public void TestCycles_Data_fMRI_FASK() {
    Parameters parameters = new Parameters();
    parameters.set("penaltyDiscount", 4);
    parameters.set("depth", -1);
    parameters.set("twoCycleAlpha", .001);
    parameters.set("thresholdForReversing", 1);
    parameters.set("numRuns", 60);
    // parameters.set("randomSelectionSize", 10);
    // parameters.set("penaltyDiscount", 6);
    // parameters.set("depth", -1);
    // parameters.set("twoCycleAlpha", 1e-15);
    // 
    // parameters.set("numRuns", 10);
    // For automatically generated concatenations if you're doing them.
    // parameters.set("randomSelectionSize", 5);
    parameters.set("Structure", "Placeholder");
    Statistics statistics = new Statistics();
    statistics.add(new ParameterColumn("Structure"));
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    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/user/Downloads/Cycles_Data_fMRI_Training/";
    String dir = "/Users/user/Downloads/CyclesTestingData/";
    String subdir = "data_fslfilter_concat";
    // String subdir = "data_fslfilter";
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network1_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network2_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network3_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network4_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_cont_p3n7", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network5_cont_p7n3", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network6_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network6_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network7_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network7_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_amp_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_amp_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network8_cont_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_amp_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_amp_cont", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Network9_cont_amp", subdir));
    simulations.add(new LoadContinuousDataAndSingleGraph(dir + "Diamond", subdir));
    // simulations.add(new LoadContinuousDataAndSingleGraph(
    // dir + "Markov_Complex_1", subdir));
    Algorithms algorithms = new Algorithms();
    algorithms.add(new Fask());
    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 15 with Comparison

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

the class TestSimulatedFmr3 method TestMadelynDAta.

public void TestMadelynDAta() {
    Parameters parameters = new Parameters();
    parameters.set("penaltyDiscount", 10);
    parameters.set("depth", -1);
    parameters.set("twoCycleAlpha", 1e-12);
    parameters.set("thresholdForReversing", 1);
    parameters.set("numRuns", 10);
    parameters.set("randomSelectionSize", 10);
    // parameters.set("penaltyDiscount", 6);
    // parameters.set("depth", -1);
    // parameters.set("twoCycleAlpha", 1e-15);
    // 
    // parameters.set("numRuns", 10);
    // For automatically generated concatenations if you're doing them.
    // parameters.set("randomSelectionSize", 5);
    parameters.set("Structure", "Placeholder");
    Statistics statistics = new Statistics();
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    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);
    String dir = "/Users/user/Downloads/SimulatedData_2/";
    String[] dirs = new String[] { "AllNegative", "AllPositive", "TwoCycleNegative", "XYNegative", "XYPositive", "XZNegative", "XZPositive", "YZNegative", "YZPositive" };
    String[] suffixes = new String[] { "allneg", "allpos", "twocycleneg", "XYneg", "XYpos", "XZneg", "XZpos", "YZneg", "YZpos" };
    for (int i = 0; i < dirs.length; i++) {
        System.out.println("Directory " + dirs[i]);
        Simulations simulations = new Simulations();
        simulations.add(new LoadMadelynData(dir + dirs[i], suffixes[i], 1));
        simulations.add(new LoadMadelynData(dir + dirs[i], suffixes[i], 2));
        simulations.add(new LoadMadelynData(dir + dirs[i], suffixes[i], 3));
        simulations.add(new LoadMadelynData(dir + dirs[i], suffixes[i], 4));
        simulations.add(new LoadMadelynData(dir + dirs[i], suffixes[i], 5));
        simulations.add(new LoadMadelynData(dir + dirs[i], suffixes[i], 6));
        simulations.add(new LoadMadelynData(dir + dirs[i], suffixes[i], 7));
        Algorithms algorithms = new Algorithms();
        algorithms.add(new FaskConcatenated());
        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.setComparisonGraph(Comparison.ComparisonGraph.true_DAG);
        comparison.compareFromSimulations("comparison_" + dirs[i], simulations, algorithms, statistics, parameters);
    }
}