Examples with Edge edu.cmu.tetrad.graph.Edge used on opensource projects

Example 1 with Edge

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

the class TestAutisticClassification method printFiles.

private void printFiles(List<Graph> _graphs, List<Boolean> types, int i, List<List<Edge>> ret) {
    try {
        List<Edge> sublist = ret.get(4);
        File dir2 = new File("/Users/jdramsey/Downloads/alldata");
        dir2.mkdirs();
        PrintStream out = new PrintStream(new File(dir2, "data" + (i + 1) + ".txt"));
        for (int j = 0; j < sublist.size(); j++) {
            out.print("X" + (j + 1) + "\t");
        }
        out.println("T");
        for (int k = 0; k < _graphs.size(); k++) {
            for (Edge edge : sublist) {
                out.print(_graphs.get(k).containsEdge(edge) ? "1\t" : "0\t");
            }
            out.println(types.get(k) ? "1" : "0");
        }
        out.close();
        File dir3 = new File("/Users/jdramsey/Downloads/allkeys");
        dir3.mkdirs();
        PrintStream keyOut = new PrintStream(new File(dir3, "key" + (i + 1) + ".txt"));
        for (int j = 0; j < sublist.size(); j++) {
            keyOut.println("X" + (j + 1) + ". " + sublist.get(j));
        }
    } catch (FileNotFoundException e) {
        e.printStackTrace();
    }
}

Example 2 with Edge

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

the class TestAutisticClassification method train.

private List<List<Edge>> train(List<Graph> trainingGraphs, List<Edge> allEdges, List<Boolean> types) {
    double[] truth = getTruth(trainingGraphs, types);
    List<Edge> forAutismIfPresent = new ArrayList<>();
    List<Edge> forAutismIfAbsent = new ArrayList<>();
    List<Edge> forTypicalIfPresent = new ArrayList<>();
    List<Edge> forTypicalIfAbsent = new ArrayList<>();
    for (Edge edge : allEdges) {
        double[] est = getEst(trainingGraphs, edge);
        if (cond(est, truth, 1, 1, cutoffPresent)) {
            forAutismIfPresent.add(edge);
        }
        if (cond(est, truth, 0, 1, cutoffAbsent)) {
            forAutismIfAbsent.add(edge);
        }
        if (cond(est, truth, 1, 0, cutoffPresent)) {
            forTypicalIfPresent.add(edge);
        }
        if (cond(est, truth, 0, 0, cutoffAbsent)) {
            forTypicalIfAbsent.add(edge);
        }
    }
    Set<Edge> sublist = new HashSet<>();
    sublist.addAll(forAutismIfPresent);
    sublist.addAll(forAutismIfAbsent);
    sublist.addAll(forTypicalIfPresent);
    sublist.addAll(forTypicalIfAbsent);
    List<Edge> _sublist = new ArrayList<>(sublist);
    // return from train.
    List<List<Edge>> ret = new ArrayList<>();
    ret.add(forAutismIfPresent);
    ret.add(forAutismIfAbsent);
    ret.add(forTypicalIfPresent);
    ret.add(forTypicalIfAbsent);
    ret.add(_sublist);
    return ret;
}

Example 3 with Edge

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

the class TestAutisticClassification method getAllEdges.

private List<Edge> getAllEdges(List<Graph> _graphs, List<Boolean> types, List<Graph> trainingGraphs) {
    Map<Edge, Double> autisticEdgeCount = new HashMap<>();
    Map<Edge, Double> typicalEdgeCount = new HashMap<>();
    Set<Edge> allEdgesSet = new HashSet<>();
    for (int k = 0; k < trainingGraphs.size(); k++) {
        for (Edge edge : trainingGraphs.get(k).getEdges()) {
            if (types.get(k)) {
                countEdge(autisticEdgeCount, edge);
            } else {
                countEdge(typicalEdgeCount, edge);
            }
        }
        allEdgesSet.addAll(_graphs.get(k).getEdges());
    }
    return new ArrayList<>(allEdgesSet);
}

Example 4 with Edge

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

the class TestAutisticClassification method leaveOneOut.

private void leaveOneOut(FaskGraphs train) {
    int numTp = 0;
    int numFp = 0;
    int numUnclassified = 0;
    for (int i = 0; i < train.getGraphs().size(); i++) {
        List<Graph> trainingGraphs = new ArrayList<>(train.getGraphs());
        trainingGraphs.remove(train.getGraphs().get(i));
        List<Edge> allEdges = getAllEdges(train.getGraphs(), train.getTypes(), trainingGraphs);
        List<List<Edge>> ret = train(trainingGraphs, allEdges, train.getTypes());
        int _class = test(i, train.getFilenames(), train.getGraphs(), train.getTypes(), ret);
        if (_class == 1)
            numTp++;
        if (_class == -1)
            numFp++;
        if (_class == 0)
            numUnclassified++;
        printFiles(train.getGraphs(), train.getTypes(), i, ret);
    }
    System.out.println();
    System.out.println("# TP = " + numTp);
    System.out.println("# FP = " + numFp);
    System.out.println("# Unclassified = " + numUnclassified);
    NumberFormat nf = new DecimalFormat("0.00");
    System.out.println("Precision = " + nf.format((numTp / (double) (numTp + numFp))));
    System.out.println();
}

Example 5 with Edge

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

the class SessionEditor method getSelectedModelComponents.

/**
 * @return a list of all the SessionNodeWrappers (TetradNodes) and
 * SessionNodeEdges that are model components for the respective
 * SessionNodes and SessionEdges selected in the workbench. Note that the
 * workbench, not the SessionEditorNodes themselves, keeps track of the
 * selection.
 */
public List getSelectedModelComponents() {
    List selectedComponents = getWorkbench().getSelectedComponents();
    List selectedModelComponents = new ArrayList();
    for (Object comp : selectedComponents) {
        if (comp instanceof SessionEditorNode) {
            SessionEditorNode editorNode = (SessionEditorNode) comp;
            Node modelNode = editorNode.getModelNode();
            selectedModelComponents.add(modelNode);
        } else if (comp instanceof SessionEditorEdge) {
            SessionEditorEdge editorEdge = (SessionEditorEdge) comp;
            Edge modelEdge = getWorkbench().getModelEdge(editorEdge);
            selectedModelComponents.add(modelEdge);
        }
    }
    return selectedModelComponents;
}