Examples with RandomForward edu.cmu.tetrad.algcomparison.graph.RandomForward used on opensource projects

Example 6 with RandomForward

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

the class ExampleSave method main.

public static void main(String... args) {
    Parameters parameters = new Parameters();
    parameters.set("numRuns", 10);
    parameters.set("numMeasures", 100);
    parameters.set("avgDegree", 4);
    parameters.set("sampleSize", 100, 500, 1000);
    Simulation simulation = new SemSimulation(new RandomForward());
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.saveToFiles("comparison", simulation, parameters);
}

Example 7 with RandomForward

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

the class Save method main.

public static void main(String... args) {
    Parameters parameters = new Parameters();
    parameters.set("numRuns", 10);
    parameters.set("numMeasures", 50, 100);
    parameters.set("avgDegree", 4);
    parameters.set("sampleSize", 100, 500);
    parameters.set("numCategories", 3);
    parameters.set("percentDiscrete", 50);
    parameters.set("differentGraphs", true);
    Simulation simulation = new LeeHastieSimulation(new RandomForward());
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.saveToFiles("comparison", simulation, parameters);
}

Example 8 with RandomForward

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

the class ExampleSave method main.

public static void main(String... args) {
    Parameters parameters = new Parameters();
    parameters.set("numRuns", 10);
    parameters.set("numMeasures", 50, 100, 500);
    parameters.set("avgDegree", 2, 4, 6);
    parameters.set("sampleSize", 100, 500, 1000);
    parameters.set("differentGraphs", true);
    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("coefSymmetric", true);
    parameters.set("varLow", 1);
    parameters.set("varHigh", 3);
    parameters.set("randomizeColumns", true);
    NumberFormatUtil.getInstance().setNumberFormat(new DecimalFormat("0.000000"));
    Simulation simulation = new SemSimulation(new RandomForward());
    Comparison comparison = new Comparison();
    comparison.saveToFiles("/Users/user/comparison-data/condition_2", simulation, parameters);
}

Example 9 with RandomForward

use of edu.cmu.tetrad.algcomparison.graph.RandomForward 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 10 with RandomForward

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

the class TestFges method main.

public static void main(String... args) {
    if (args.length > 0) {
        int numMeasures = Integer.parseInt(args[0]);
        int avgDegree = Integer.parseInt(args[1]);
        Parameters parameters = new Parameters();
        parameters.set("numMeasures", numMeasures);
        parameters.set("numLatents", 0);
        parameters.set("avgDegree", avgDegree);
        parameters.set("maxDegree", 20);
        parameters.set("maxIndegree", 20);
        parameters.set("maxOutdegree", 20);
        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("numRuns", 1);
        parameters.set("percentDiscrete", 0);
        parameters.set("numCategories", 3);
        parameters.set("differentGraphs", true);
        parameters.set("sampleSize", 1000);
        parameters.set("intervalBetweenShocks", 10);
        parameters.set("intervalBetweenRecordings", 10);
        parameters.set("fisherEpsilon", 0.001);
        parameters.set("randomizeColumns", true);
        RandomGraph graph = new RandomForward();
        LinearFisherModel sim = new LinearFisherModel(graph);
        sim.createData(parameters);
        ScoreWrapper score = new FisherZScore();
        Algorithm alg = new edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges(score);
        parameters.set("alpha", 1e-8);
        for (int i = 0; i < 5; i++) {
            Graph out1 = alg.search(sim.getDataModel(0), parameters);
            System.out.println(out1);
        }
    } else {
        new TestFges().test9();
    }
}