Examples with DepthChoiceGenerator edu.cmu.tetrad.util.DepthChoiceGenerator used on opensource projects

Example 26 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class Nlo method fullOrient4.

public Graph fullOrient4(Graph graph) {
    graph = GraphUtils.undirectedGraph(graph);
    graph = GraphUtils.replaceNodes(graph, dataSet.getVariables());
    Map<Node, List<Node>> cond = new HashMap<>();
    for (Node Y : graph.getNodes()) {
        System.out.println("Y = " + Y);
        double maxQ = 0.0;
        List<Node> adjNodes = graph.getAdjacentNodes(Y);
        DepthChoiceGenerator gen = new DepthChoiceGenerator(adjNodes.size(), 6);
        int[] choice;
        List<Node> parents = new ArrayList<>();
        while ((choice = gen.next()) != null) {
            List<Node> W = GraphUtils.asList(choice, adjNodes);
            if (W.isEmpty())
                continue;
            double[] r = new double[0];
            try {
                r = cci.residuals(name(Y), names(W));
            } catch (Exception e) {
                e.printStackTrace();
                continue;
            }
            boolean indep = testIndependence(W, r);
            System.out.println("\tW = " + W + " indep = " + (indep) + " q = " + q);
            if (indep) {
                for (Node x : W) {
                    if (!parents.contains(x)) {
                        parents.add(x);
                    }
                }
            }
        }
        cond.put(Y, parents);
    }
    // Don't orient bidirected edges.
    for (Node Y : graph.getNodes()) {
        System.out.println("Y = " + Y + " cond = " + cond.get(Y));
        for (Node X : cond.get(Y)) {
            System.out.println("\tcond " + X + " = " + cond.get(X));
            boolean contains = cond.get(X).contains(Y);
            if (contains) {
                System.out.println("\t\t" + cond.get(X) + " contains " + Y + " ... not orienting.");
            }
            if (!contains) {
                graph.setEndpoint(X, Y, Endpoint.ARROW);
            }
        }
    }
    return graph;
}

Example 27 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class PcStableMaxLocal method reorientNode2.

private void reorientNode2(Node y) {
    List<Node> adjy = graph.getAdjacentNodes(y);
    adjy.removeAll(graph.getChildren(y));
    DepthChoiceGenerator gen = new DepthChoiceGenerator(adjy.size(), adjy.size());
    int[] choice;
    double maxScore = Double.NEGATIVE_INFINITY;
    List<Node> maxParents = new ArrayList<>();
    unorientAdjacents(y);
    while ((choice = gen.next()) != null) {
        List<Node> parents = GraphUtils.asList(choice, adjy);
        Iterator<Node> pi = parents.iterator();
        int[] parentIndices = new int[parents.size()];
        int count = 0;
        while (pi.hasNext()) {
            Node nextParent = pi.next();
            parentIndices[count++] = hashIndices.get(nextParent);
        }
        int yIndex = hashIndices.get(y);
        double _score = score.localScore(yIndex, parentIndices);
        if (_score > maxScore) {
            maxScore = _score;
            maxParents = parents;
        }
    }
    for (Node v : maxParents) {
        graph.removeEdge(v, y);
        graph.addDirectedEdge(v, y);
    }
}

Example 28 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class SemBicScoreImages method printMinimalLinearlyDependentSet.

// Prints a smallest subset of parents that causes a singular matrix exception.
private void printMinimalLinearlyDependentSet(int[] parents, ICovarianceMatrix cov) {
    List<Node> _parents = new ArrayList<>();
    for (int p : parents) _parents.add(variables.get(p));
    DepthChoiceGenerator gen = new DepthChoiceGenerator(_parents.size(), _parents.size());
    int[] choice;
    while ((choice = gen.next()) != null) {
        int[] sel = new int[choice.length];
        List<Node> _sel = new ArrayList<>();
        for (int m = 0; m < choice.length; m++) {
            sel[m] = parents[m];
            _sel.add(variables.get(sel[m]));
        }
        TetradMatrix m = cov.getSelection(sel, sel);
        try {
            m.inverse();
        } catch (Exception e2) {
            out.println("### Linear dependence among variables: " + _sel);
        }
    }
}

Example 29 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class HitonMb method hitonMb.

private List<Node> hitonMb(Node t) {
    // MB <- {}
    Set<Node> mb = new HashSet<>();
    Set<Node> _pcpc = new HashSet<>();
    for (Node node : getPc(t)) {
        List<Node> f = getPc(node);
        this.pc.put(node, f);
        _pcpc.addAll(f);
    }
    List<Node> pcpc = new LinkedList<>(_pcpc);
    Set<Node> currentMb = new HashSet<>(getPc(t));
    currentMb.addAll(pcpc);
    currentMb.remove(t);
    HashSet<Node> diff = new HashSet<>(currentMb);
    diff.removeAll(getPc(t));
    diff.remove(t);
    // for each x in PCPC \ PC
    for (Node x : diff) {
        List<Node> s = null;
        // Find an S such PC such that x _||_ t | S
        DepthChoiceGenerator generator = new DepthChoiceGenerator(pcpc.size(), depth);
        int[] choice;
        while ((choice = generator.next()) != null) {
            List<Node> _s = new LinkedList<>();
            for (int index : choice) {
                _s.add(pcpc.get(index));
            }
            numIndTests++;
            if (independenceTest.isIndependent(t, x, _s)) {
                s = _s;
                break;
            }
        }
        if (s == null) {
            System.out.println("S not found.");
            // mb.add(x);
            continue;
        }
        // y_set <- {y in PC(t) : x in PC(y)}
        Set<Node> ySet = new HashSet<>();
        for (Node y : getPc(t)) {
            if (this.pc.get(y).contains(x)) {
                ySet.add(y);
            }
        }
        // For each y in y_set
        for (Node y : ySet) {
            if (x == y)
                continue;
            List<Node> _s = new LinkedList<>(s);
            _s.add(y);
            // If x NOT _||_ t | S U {y}
            numIndTests++;
            if (!independenceTest.isIndependent(t, x, _s)) {
                mb.add(x);
                break;
            }
        }
    }
    mb.addAll(getPc(t));
    return new LinkedList<>(mb);
}

Example 30 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class SemBicScoreDeterministic method getMinimalLinearlyDependentSet.

private int[] getMinimalLinearlyDependentSet(int i, int[] parents, ICovarianceMatrix cov) {
    double small = getDeterminismThreshold();
    List<Node> _parents = new ArrayList<>();
    for (int p : parents) _parents.add(variables.get(p));
    DepthChoiceGenerator gen = new DepthChoiceGenerator(_parents.size(), _parents.size());
    int[] choice;
    while ((choice = gen.next()) != null) {
        int[] sel = new int[choice.length];
        List<Node> _sel = new ArrayList<>();
        for (int m = 0; m < choice.length; m++) {
            sel[m] = parents[m];
            _sel.add(variables.get(sel[m]));
        }
        TetradMatrix m = cov.getSelection(sel, sel);
        double s2 = getCovariances().getValue(i, i);
        TetradMatrix covxx = getSelection(getCovariances(), parents, parents);
        TetradVector covxy = getSelection(getCovariances(), parents, new int[] { i }).getColumn(0);
        s2 -= covxx.inverse().times(covxy).dotProduct(covxy);
        if (s2 <= small) {
            out.println("### Linear dependence among variables: " + _sel);
            out.println("### Removing " + _sel.get(0));
            return sel;
        }
        try {
            m.inverse();
        } catch (Exception e2) {
            // forbidden.add(sel[0]);
            out.println("### Linear dependence among variables: " + _sel);
            out.println("### Removing " + _sel.get(0));
            return sel;
        }
    }
    return new int[0];
}