Examples with LeeHastieSimulation edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation used on opensource projects

Example 1 with LeeHastieSimulation

use of edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation 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 2 with LeeHastieSimulation

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

the class TestGenerateMixedData method test1.

public void test1() {
    Parameters parameters = new Parameters();
    parameters.set("numRuns", 100);
    parameters.set("numMeasures", 100);
    parameters.set("avgDegree", 4);
    parameters.set("sampleSize", 5000);
    parameters.set("maxDegree", 8);
    parameters.set("minCategories", 2);
    parameters.set("maxCategories", 5);
    parameters.set("percentDiscrete", 50);
    parameters.set("intervalBetweenRecordings", 20);
    parameters.set("varLow", 1.);
    parameters.set("varHigh", 3.);
    parameters.set("coefLow", .1);
    parameters.set("coefHigh", 1.5);
    parameters.set("coefSymmetric", true);
    parameters.set("meanLow", -1);
    parameters.set("meanHigh", 1);
    final LeeHastieSimulation simulation = new LeeHastieSimulation(new RandomForward());
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(false);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(false);
    comparison.setParallelized(false);
    comparison.setSaveGraphs(true);
    comparison.setTabDelimitedTables(true);
    comparison.saveToFiles("mixed.lee.hastie.avg.degree.4", simulation, parameters);
}

Example 3 with LeeHastieSimulation

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

the class SimulationEditor method resetPanel.

private void resetPanel(Simulation simulation, String[] graphItems, String[] simulationItems, JTabbedPane tabbedPane) {
    RandomGraph randomGraph = (simulation.getSourceGraph() == null) ? new SingleGraph(new EdgeListGraph()) : new SingleGraph(simulation.getSourceGraph());
    if (!simulation.isFixedGraph()) {
        String graphItem = (String) graphsDropdown.getSelectedItem();
        simulation.getParams().set("graphsDropdownPreference", graphItem);
        if (graphItem.equals(graphItems[0])) {
            randomGraph = new RandomForward();
        } else if (graphItem.equals(graphItems[1])) {
            randomGraph = new ScaleFree();
        } else if (graphItem.equals(graphItems[2])) {
            randomGraph = new Cyclic();
        } else if (graphItem.equals(graphItems[3])) {
            randomGraph = new RandomSingleFactorMim();
        } else if (graphItem.equals(graphItems[4])) {
            randomGraph = new RandomTwoFactorMim();
        } else {
            throw new IllegalArgumentException("Unrecognized simulation type: " + graphItem);
        }
    }
    if (!simulation.isFixedSimulation()) {
        if (simulation.getSourceGraph() == null) {
            String simulationItem = (String) simulationsDropdown.getSelectedItem();
            simulation.getParams().set("simulationsDropdownPreference", simulationItem);
            simulation.setFixedGraph(false);
            if (randomGraph instanceof SingleGraph) {
                simulation.setFixedGraph(true);
            }
            if (simulationItem.equals(simulationItems[0])) {
                simulation.setSimulation(new BayesNetSimulation(randomGraph), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[1])) {
                simulation.setSimulation(new SemSimulation(randomGraph), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[2])) {
                simulation.setSimulation(new LinearFisherModel(randomGraph, simulation.getInputDataModelList()), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[3])) {
                simulation.setSimulation(new LeeHastieSimulation(randomGraph), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[4])) {
                simulation.setSimulation(new ConditionalGaussianSimulation(randomGraph), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[5])) {
                simulation.setSimulation(new TimeSeriesSemSimulation(randomGraph), simulation.getParams());
            } else {
                throw new IllegalArgumentException("Unrecognized simulation type: " + simulationItem);
            }
        } else {
            String simulationItem = (String) simulationsDropdown.getSelectedItem();
            simulation.getParams().set("simulationsDropdownPreference", simulationItem);
            simulation.setFixedGraph(false);
            if (randomGraph instanceof SingleGraph) {
                simulation.setFixedGraph(true);
            }
            if (simulationItem.equals(simulationItems[0])) {
                simulation.setSimulation(new BayesNetSimulation(randomGraph), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[1])) {
                simulation.setSimulation(new SemSimulation(randomGraph), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[2])) {
                simulation.setSimulation(new LinearFisherModel(randomGraph), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[3])) {
                simulation.setSimulation(new LeeHastieSimulation(randomGraph), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[4])) {
                simulation.setSimulation(new ConditionalGaussianSimulation(randomGraph), simulation.getParams());
            } else if (simulationItem.equals(simulationItems[5])) {
                simulation.setSimulation(new TimeSeriesSemSimulation(randomGraph), simulation.getParams());
            } else {
                throw new IllegalArgumentException("Unrecognized simulation type: " + simulationItem);
            }
        }
    }
    tabbedPane.setComponentAt(0, new PaddingPanel(getParameterPanel(simulation, simulation.getSimulation(), simulation.getParams())));
}