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

Example 1 with RandomGraph

use of edu.cmu.tetrad.algcomparison.graph.RandomGraph 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();
    }
}

Example 2 with RandomGraph

use of edu.cmu.tetrad.algcomparison.graph.RandomGraph 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())));
}

Example 3 with RandomGraph

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

the class TestFges method clarkTest.

@Test
public void clarkTest() {
    RandomGraph randomGraph = new RandomForward();
    Simulation simulation = new LinearFisherModel(randomGraph);
    Parameters parameters = new Parameters();
    parameters.set("numMeasures", 100);
    parameters.set("numLatents", 0);
    parameters.set("coefLow", 0.2);
    parameters.set("coefHigh", 0.8);
    parameters.set("avgDegree", 2);
    parameters.set("maxDegree", 100);
    parameters.set("maxIndegree", 100);
    parameters.set("maxOutdegree", 100);
    parameters.set("connected", false);
    parameters.set("numRuns", 1);
    parameters.set("differentGraphs", false);
    parameters.set("sampleSize", 1000);
    parameters.set("faithfulnessAssumed", false);
    parameters.set("maxDegree", -1);
    parameters.set("verbose", false);
    parameters.set("alpha", 0.01);
    simulation.createData(parameters);
    DataSet dataSet = (DataSet) simulation.getDataModel(0);
    Graph trueGraph = simulation.getTrueGraph(0);
    // trueGraph = SearchGraphUtils.patternForDag(trueGraph);
    ScoreWrapper score = new edu.cmu.tetrad.algcomparison.score.SemBicScore();
    IndependenceWrapper test = new FisherZ();
    Algorithm fges = new edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges(score, false);
    Graph fgesGraph = fges.search(dataSet, parameters);
    clarkTestForAlpha(0.05, parameters, dataSet, trueGraph, fgesGraph, test);
    clarkTestForAlpha(0.01, parameters, dataSet, trueGraph, fgesGraph, test);
}

Example 4 with RandomGraph

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

the class TestFges method test9.

public void test9() {
    Parameters parameters = new Parameters();
    parameters.set("numMeasures", 50);
    parameters.set("numLatents", 0);
    parameters.set("avgDegree", 2);
    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", 500);
    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);
    Graph previous = null;
    int prevDiff = Integer.MAX_VALUE;
    // for (int l = 7; l >= 1; l--) {
    for (int i = 2; i <= 20; i++) {
        parameters.set("penaltyDiscount", i / (double) 10);
        // parameters.set("alpha", Double.parseDouble("1E-" + l));
        // ScoreWrapper score = new edu.cmu.tetrad.algcomparison.score.SemBicScore();
        // Algorithm alg = new edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges(score);
        IndependenceWrapper test = new SemBicTest();
        // IndependenceWrapper test = new FisherZ();
        Algorithm alg = new edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Cpc(test);
        Graph out = alg.search(sim.getDataModel(0), parameters);
        // Graph out = GraphUtils.undirectedGraph(alg.search(sim.getDataModel(0), parameters));
        Set<Edge> edges1 = out.getEdges();
        int numEdges = edges1.size();
        if (previous != null) {
            Set<Edge> edges2 = previous.getEdges();
            edges2.removeAll(edges1);
            int diff = edges2.size();
            // 
            System.out.println("Penalty discount =" + parameters.getDouble("penaltyDiscount") + " # edges = " + numEdges + " # additional = " + diff);
            previous = out;
            if (diff > prevDiff)
                break;
            prevDiff = diff;
        } else {
            previous = out;
        }
    }
    Graph estGraph = previous;
    Graph trueGraph = sim.getTrueGraph(0);
    estGraph = GraphUtils.replaceNodes(estGraph, trueGraph.getNodes());
    Statistic ap = new AdjacencyPrecision();
    Statistic ar = new AdjacencyRecall();
    Statistic ahp = new ArrowheadPrecision();
    Statistic ahr = new ArrowheadRecall();
    System.out.println("AP = " + ap.getValue(trueGraph, estGraph));
    System.out.println("AR = " + ar.getValue(trueGraph, estGraph));
    System.out.println("AHP = " + ahp.getValue(trueGraph, estGraph));
    System.out.println("AHR = " + ahr.getValue(trueGraph, estGraph));
}