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

Example 6 with CombinationGenerator

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

the class SampleVcpcFast method search.

/**
 * Runs PC starting with a fully connected graph over all of the variables in the domain of the independence test.
 * See PC for caveats. The number of possible cycles and bidirected edges is far less with CPC than with PC.
 */
// public final Graph search() {
// return search(independenceTest.getVariable());
// }
// //    public Graph search(List<Node> nodes) {
// //
// ////        return search(new FasICov2(getIndependenceTest()), nodes);
// ////        return search(new Fas(getIndependenceTest()), nodes);
// //        return search(new Fas(getIndependenceTest()), nodes);
// }
// modified FAS into VCFAS; added in definitelyNonadjacencies set of edges.
public Graph search() {
    this.logger.log("info", "Starting VCCPC algorithm");
    this.logger.log("info", "Independence test = " + getIndependenceTest() + ".");
    this.allTriples = new HashSet<>();
    this.ambiguousTriples = new HashSet<>();
    this.colliderTriples = new HashSet<>();
    this.noncolliderTriples = new HashSet<>();
    Vcfas fas = new Vcfas(getIndependenceTest());
    definitelyNonadjacencies = new HashSet<>();
    markovInAllPatterns = new HashSet<>();
    // this.logger.log("info", "Variables " + independenceTest.getVariable());
    long startTime = System.currentTimeMillis();
    if (getIndependenceTest() == null) {
        throw new NullPointerException();
    }
    List<Node> allNodes = getIndependenceTest().getVariables();
    // if (!allNodes.containsAll(nodes)) {
    // throw new IllegalArgumentException("All of the given nodes must " +
    // "be in the domain of the independence test provided.");
    // }
    // Fas fas = new Fas(graph, getIndependenceTest());
    // FasStableConcurrent fas = new FasStableConcurrent(graph, getIndependenceTest());
    // Fas6 fas = new Fas6(graph, getIndependenceTest());
    // fas = new FasICov(graph, (IndTestFisherZ) getIndependenceTest());
    fas.setKnowledge(getKnowledge());
    fas.setDepth(getDepth());
    fas.setVerbose(verbose);
    // Note that we are ignoring the sepset map returned by this method
    // on purpose; it is not used in this search.
    graph = fas.search();
    apparentlyNonadjacencies = fas.getApparentlyNonadjacencies();
    if (isDoOrientation()) {
        if (verbose) {
            System.out.println("CPC orientation...");
        }
        SearchGraphUtils.pcOrientbk(knowledge, graph, allNodes);
        orientUnshieldedTriples(knowledge, getIndependenceTest(), getDepth());
        // orientUnshieldedTriplesConcurrent(knowledge, getIndependenceTest(), getMaxIndegree());
        MeekRules meekRules = new MeekRules();
        meekRules.setAggressivelyPreventCycles(this.aggressivelyPreventCycles);
        meekRules.setKnowledge(knowledge);
        meekRules.orientImplied(graph);
    }
    List<Triple> ambiguousTriples = new ArrayList(graph.getAmbiguousTriples());
    int[] dims = new int[ambiguousTriples.size()];
    for (int i = 0; i < ambiguousTriples.size(); i++) {
        dims[i] = 2;
    }
    List<Graph> patterns = new ArrayList<>();
    Map<Graph, List<Triple>> newColliders = new IdentityHashMap<>();
    Map<Graph, List<Triple>> newNonColliders = new IdentityHashMap<>();
    // Using combination generator to generate a list of combinations of ambiguous triples dismabiguated into colliders
    // and non-colliders. The combinations are added as graphs to the list patterns. The graphs are then subject to
    // basic rules to ensure consistent patterns.
    CombinationGenerator generator = new CombinationGenerator(dims);
    int[] combination;
    while ((combination = generator.next()) != null) {
        Graph _graph = new EdgeListGraph(graph);
        newColliders.put(_graph, new ArrayList<Triple>());
        newNonColliders.put(_graph, new ArrayList<Triple>());
        for (Graph graph : newColliders.keySet()) {
        // System.out.println("$$$ " + newColliders.get(graph));
        }
        for (int k = 0; k < combination.length; k++) {
            // System.out.println("k = " + combination[k]);
            Triple triple = ambiguousTriples.get(k);
            _graph.removeAmbiguousTriple(triple.getX(), triple.getY(), triple.getZ());
            if (combination[k] == 0) {
                newColliders.get(_graph).add(triple);
                // System.out.println(newColliders.get(_graph));
                Node x = triple.getX();
                Node y = triple.getY();
                Node z = triple.getZ();
                _graph.setEndpoint(x, y, Endpoint.ARROW);
                _graph.setEndpoint(z, y, Endpoint.ARROW);
            }
            if (combination[k] == 1) {
                newNonColliders.get(_graph).add(triple);
            }
        }
        patterns.add(_graph);
    }
    List<Graph> _patterns = new ArrayList<>(patterns);
    GRAPH: for (Graph graph : new ArrayList<>(patterns)) {
        // _graph = new EdgeListGraph(graph);
        // System.out.println("graph = " + graph + " in keyset? " + newColliders.containsKey(graph));
        // 
        List<Triple> colliders = newColliders.get(graph);
        List<Triple> nonColliders = newNonColliders.get(graph);
        for (Triple triple : colliders) {
            Node x = triple.getX();
            Node y = triple.getY();
            Node z = triple.getZ();
            if (graph.getEdge(x, y).pointsTowards(x) || (graph.getEdge(y, z).pointsTowards(z))) {
                patterns.remove(graph);
                continue GRAPH;
            }
        }
        for (Triple triple : colliders) {
            Node x = triple.getX();
            Node y = triple.getY();
            Node z = triple.getZ();
            graph.setEndpoint(x, y, Endpoint.ARROW);
            graph.setEndpoint(z, y, Endpoint.ARROW);
        }
        for (Triple triple : nonColliders) {
            Node x = triple.getX();
            Node y = triple.getY();
            Node z = triple.getZ();
            if (graph.getEdge(x, y).pointsTowards(y)) {
                graph.removeEdge(y, z);
                graph.addDirectedEdge(y, z);
            }
            if (graph.getEdge(y, z).pointsTowards(y)) {
                graph.removeEdge(x, y);
                graph.addDirectedEdge(y, x);
            }
        }
        for (Edge edge : graph.getEdges()) {
            Node x = edge.getNode1();
            Node y = edge.getNode2();
            if (Edges.isBidirectedEdge(edge)) {
                graph.removeEdge(x, y);
                graph.addUndirectedEdge(x, y);
            }
        }
        // for (Edge edge : graph.getEdges()) {
        // if (Edges.isBidirectedEdge(edge)) {
        // patterns.remove(graph);
        // continue Graph;
        // }
        // }
        MeekRules rules = new MeekRules();
        rules.orientImplied(graph);
        if (graph.existsDirectedCycle()) {
            patterns.remove(graph);
            continue GRAPH;
        }
    }
    MARKOV: for (Edge edge : apparentlyNonadjacencies.keySet()) {
        Node x = edge.getNode1();
        Node y = edge.getNode2();
        for (Graph _graph : new ArrayList<>(patterns)) {
            List<Node> boundaryX = new ArrayList<>(boundary(x, _graph));
            List<Node> boundaryY = new ArrayList<>(boundary(y, _graph));
            List<Node> futureX = new ArrayList<>(future(x, _graph));
            List<Node> futureY = new ArrayList<>(future(y, _graph));
            if (y == x) {
                continue;
            }
            if (boundaryX.contains(y) || boundaryY.contains(x)) {
                continue;
            }
            IndependenceTest test = independenceTest;
            if (!futureX.contains(y)) {
                if (!test.isIndependent(x, y, boundaryX)) {
                    continue MARKOV;
                }
            }
            if (!futureY.contains(x)) {
                if (!test.isIndependent(y, x, boundaryY)) {
                    continue MARKOV;
                }
            }
        }
        definitelyNonadjacencies.add(edge);
    // apparentlyNonadjacencies.remove(edge);
    }
    for (Edge edge : definitelyNonadjacencies) {
        if (apparentlyNonadjacencies.keySet().contains(edge)) {
            apparentlyNonadjacencies.keySet().remove(edge);
        }
    }
    setSemIm(semIm);
    // semIm.getSemPm().getGraph();
    // System.out.println(semIm.getEdgeCoef());
    // graph = DataGraphUtils.replaceNodes(graph, semIm.getVariableNodes());
    // System.out.println(semIm.getEdgeCoef());
    // System.out.println(sampleRegress.entrySet());
    List<Double> squaredDifference = new ArrayList<>();
    int numNullEdges = 0;
    // //Edge Estimation Alg I
    Regression sampleRegression = new RegressionDataset(dataSet);
    System.out.println(sampleRegression.getGraph());
    graph = GraphUtils.replaceNodes(graph, dataSet.getVariables());
    Map<Edge, double[]> sampleRegress = new HashMap<>();
    Map<Edge, Double> edgeCoefs = new HashMap<>();
    ESTIMATION: for (Node z : graph.getNodes()) {
        Set<Edge> adj = getAdj(z, graph);
        for (Edge edge : apparentlyNonadjacencies.keySet()) {
            if (z == edge.getNode1() || z == edge.getNode2()) {
                for (Edge adjacency : adj) {
                    // return Unknown and go to next Z
                    sampleRegress.put(adjacency, null);
                    Node a = adjacency.getNode1();
                    Node b = adjacency.getNode2();
                    if (semIm.existsEdgeCoef(a, b)) {
                        Double c = semIm.getEdgeCoef(a, b);
                        edgeCoefs.put(adjacency, c);
                    } else {
                        edgeCoefs.put(adjacency, 0.0);
                    }
                }
                continue ESTIMATION;
            }
        }
        for (Edge nonadj : definitelyNonadjacencies) {
            if (nonadj.getNode1() == z || nonadj.getNode2() == z) {
                // return 0 for e
                double[] d = { 0, 0 };
                sampleRegress.put(nonadj, d);
                Node a = nonadj.getNode1();
                Node b = nonadj.getNode2();
                if (semIm.existsEdgeCoef(a, b)) {
                    Double c = semIm.getEdgeCoef(a, b);
                    edgeCoefs.put(nonadj, c);
                } else {
                    edgeCoefs.put(nonadj, 0.0);
                }
            }
        }
        Set<Edge> parentsOfZ = new HashSet<>();
        Set<Edge> _adj = getAdj(z, graph);
        for (Edge _adjacency : _adj) {
            if (!_adjacency.isDirected()) {
                for (Edge adjacency : adj) {
                    sampleRegress.put(adjacency, null);
                    Node a = adjacency.getNode1();
                    Node b = adjacency.getNode2();
                    if (semIm.existsEdgeCoef(a, b)) {
                        Double c = semIm.getEdgeCoef(a, b);
                        edgeCoefs.put(adjacency, c);
                    } else {
                        edgeCoefs.put(adjacency, 0.0);
                    }
                }
            }
            if (_adjacency.pointsTowards(z)) {
                parentsOfZ.add(_adjacency);
            }
        }
        for (Edge edge : parentsOfZ) {
            if (edge.pointsTowards(edge.getNode2())) {
                RegressionResult result = sampleRegression.regress(edge.getNode2(), edge.getNode1());
                System.out.println(result);
                double[] d = result.getCoef();
                sampleRegress.put(edge, d);
                Node a = edge.getNode1();
                Node b = edge.getNode2();
                if (semIm.existsEdgeCoef(a, b)) {
                    Double c = semIm.getEdgeCoef(a, b);
                    edgeCoefs.put(edge, c);
                } else {
                    edgeCoefs.put(edge, 0.0);
                }
            }
        // if (edge.pointsTowards(edge.getNode2())) {
        // RegressionResult result = sampleRegression.regress(edge.getNode2(), edge.getNode1());
        // double[] d = result.getCoef();
        // sampleRegress.put(edge, d);
        // 
        // Node a = edge.getNode1();
        // Node b = edge.getNode2();
        // if (semIm.existsEdgeCoef(a, b)) {
        // Double c = semIm.getEdgeCoef(a, b);
        // edgeCoefs.put(edge, c);
        // } else { edgeCoefs.put(edge, 0.0); }
        // }
        }
    }
    System.out.println("All IM: " + semIm + "Finish");
    System.out.println("Just IM coefs: " + semIm.getEdgeCoef());
    System.out.println("IM Coef Map: " + edgeCoefs);
    System.out.println("Regress Coef Map: " + sampleRegress);
    // 
    for (Edge edge : sampleRegress.keySet()) {
        System.out.println(" Sample Regression: " + edge + Arrays.toString(sampleRegress.get(edge)));
    }
    for (Edge edge : graph.getEdges()) {
        // if (edge.isDirected()) {
        // System.out.println("IM edge: " + semIm.getEdgeCoef(edge));
        // }
        System.out.println("Sample edge: " + Arrays.toString(sampleRegress.get(edge)));
    }
    // 
    // 
    System.out.println("Sample VCPC:");
    System.out.println("# of patterns: " + patterns.size());
    long endTime = System.currentTimeMillis();
    this.elapsedTime = endTime - startTime;
    System.out.println("Search Time (seconds):" + (elapsedTime) / 1000 + " s");
    System.out.println("Search Time (milli):" + elapsedTime + " ms");
    System.out.println("# of Apparent Nonadj: " + apparentlyNonadjacencies.size());
    System.out.println("# of Definite Nonadj: " + definitelyNonadjacencies.size());
    // System.out.println("Definitely Nonadjacencies:");
    // 
    // for (Edge edge : definitelyNonadjacencies) {
    // System.out.println(edge);
    // }
    // 
    // System.out.println("markov in all patterns:" + markovInAllPatterns);
    // System.out.println("patterns:" + patterns);
    // System.out.println("Apparently Nonadjacencies:");
    // 
    // for (Edge edge : apparentlyNonadjacencies.keySet()) {
    // System.out.println(edge);
    // }
    // System.out.println("Definitely Nonadjacencies:");
    // 
    // 
    // for (Edge edge : definitelyNonadjacencies) {
    // System.out.println(edge);
    // }
    TetradLogger.getInstance().log("apparentlyNonadjacencies", "\n Apparent Non-adjacencies" + apparentlyNonadjacencies);
    TetradLogger.getInstance().log("definitelyNonadjacencies", "\n Definite Non-adjacencies" + definitelyNonadjacencies);
    TetradLogger.getInstance().log("patterns", "Disambiguated Patterns: " + patterns);
    TetradLogger.getInstance().log("graph", "\nReturning this graph: " + graph);
    TetradLogger.getInstance().log("info", "Elapsed time = " + (elapsedTime) / 1000. + " s");
    TetradLogger.getInstance().log("info", "Finishing CPC algorithm.");
    logTriples();
    TetradLogger.getInstance().flush();
    // SearchGraphUtils.verifySepsetIntegrity(Map<Edge, List<Node>>, graph);
    return graph;
}

Example 7 with CombinationGenerator

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

the class TimeoutComparison method compareFromSimulations.

/**
 * Compares algorithms.
 *
 * @param resultsPath Path to the file where the output should be printed.
 * @param simulations The list of simulationWrapper that is used to generate
 * graphs and data for the comparison.
 * @param algorithms The list of algorithms to be compared.
 * @param statistics The list of statistics on which to compare the
 * algorithm, and their utility weights.
 */
public void compareFromSimulations(String resultsPath, Simulations simulations, String outputFileName, Algorithms algorithms, Statistics statistics, Parameters parameters, long timeout, TimeUnit unit) {
    this.resultsPath = resultsPath;
    // Create output file.
    try {
        File dir = new File(resultsPath);
        dir.mkdirs();
        File file = new File(dir, outputFileName);
        this.out = new PrintStream(new FileOutputStream(file));
    } catch (Exception e) {
        throw new RuntimeException(e);
    }
    out.println(new Date());
    // Set up simulations--create data and graphs, read in parameters. The parameters
    // are set in the parameters object.
    List<SimulationWrapper> simulationWrappers = new ArrayList<>();
    int numRuns = parameters.getInt("numRuns");
    for (Simulation simulation : simulations.getSimulations()) {
        List<SimulationWrapper> wrappers = getSimulationWrappers(simulation, parameters);
        for (SimulationWrapper wrapper : wrappers) {
            wrapper.createData(wrapper.getSimulationSpecificParameters());
            simulationWrappers.add(wrapper);
        }
    }
    // Set up the algorithms.
    List<AlgorithmWrapper> algorithmWrappers = new ArrayList<>();
    for (Algorithm algorithm : algorithms.getAlgorithms()) {
        List<Integer> _dims = new ArrayList<>();
        List<String> varyingParameters = new ArrayList<>();
        final List<String> parameters1 = algorithm.getParameters();
        for (String name : parameters1) {
            if (parameters.getNumValues(name) > 1) {
                _dims.add(parameters.getNumValues(name));
                varyingParameters.add(name);
            }
        }
        if (varyingParameters.isEmpty()) {
            algorithmWrappers.add(new AlgorithmWrapper(algorithm, parameters));
        } else {
            int[] dims = new int[_dims.size()];
            for (int i = 0; i < _dims.size(); i++) {
                dims[i] = _dims.get(i);
            }
            CombinationGenerator gen = new CombinationGenerator(dims);
            int[] choice;
            while ((choice = gen.next()) != null) {
                AlgorithmWrapper wrapper = new AlgorithmWrapper(algorithm, parameters);
                for (int h = 0; h < dims.length; h++) {
                    String parameter = varyingParameters.get(h);
                    Object[] values = parameters.getValues(parameter);
                    Object value = values[choice[h]];
                    wrapper.setValue(parameter, value);
                }
                algorithmWrappers.add(wrapper);
            }
        }
    }
    // Create the algorithm-simulation wrappers for every combination of algorithm and
    // simulation.
    List<AlgorithmSimulationWrapper> algorithmSimulationWrappers = new ArrayList<>();
    for (SimulationWrapper simulationWrapper : simulationWrappers) {
        for (AlgorithmWrapper algorithmWrapper : algorithmWrappers) {
            DataType algDataType = algorithmWrapper.getDataType();
            DataType simDataType = simulationWrapper.getDataType();
            if (!(algDataType == DataType.Mixed || (algDataType == simDataType))) {
                System.out.println("Type mismatch: " + algorithmWrapper.getDescription() + " / " + simulationWrapper.getDescription());
            }
            if (algorithmWrapper.getAlgorithm() instanceof ExternalAlgorithm) {
                ExternalAlgorithm external = (ExternalAlgorithm) algorithmWrapper.getAlgorithm();
                // external.setSimulation(simulationWrapper.getSimulation());
                // external.setPath(dirs.get(simulationWrappers.indexOf(simulationWrapper)));
                // external.setPath(resultsPath);
                external.setSimIndex(simulationWrappers.indexOf(external.getSimulation()));
            }
            algorithmSimulationWrappers.add(new AlgorithmSimulationWrapper(algorithmWrapper, simulationWrapper));
        }
    }
    // Run all of the algorithms and compile statistics.
    double[][][][] allStats = calcStats(algorithmSimulationWrappers, algorithmWrappers, simulationWrappers, statistics, numRuns, timeout, unit);
    // Print out the preliminary information for statistics types, etc.
    if (allStats != null) {
        out.println();
        out.println("Statistics:");
        out.println();
        for (Statistic stat : statistics.getStatistics()) {
            out.println(stat.getAbbreviation() + " = " + stat.getDescription());
        }
    }
    out.println();
    // out.println();
    if (allStats != null) {
        int numTables = allStats.length;
        int numStats = allStats[0][0].length - 1;
        double[][][] statTables = calcStatTables(allStats, Mode.Average, numTables, algorithmSimulationWrappers, numStats, statistics);
        double[] utilities = calcUtilities(statistics, algorithmSimulationWrappers, statTables[0]);
        // Add utilities to table as the last column.
        for (int u = 0; u < numTables; u++) {
            for (int t = 0; t < algorithmSimulationWrappers.size(); t++) {
                statTables[u][t][numStats] = utilities[t];
            }
        }
        int[] newOrder;
        if (isSortByUtility()) {
            newOrder = sort(algorithmSimulationWrappers, utilities);
        } else {
            newOrder = new int[algorithmSimulationWrappers.size()];
            for (int q = 0; q < algorithmSimulationWrappers.size(); q++) {
                newOrder[q] = q;
            }
        }
        out.println("Simulations:");
        out.println();
        // if (simulationWrappers.size() == 1) {
        // out.println(simulationWrappers.get(0).getDescription());
        // } else {
        int i = 0;
        for (SimulationWrapper simulation : simulationWrappers) {
            out.print("Simulation " + (++i) + ": ");
            out.println(simulation.getDescription());
            out.println();
            printParameters(simulation.getParameters(), simulation.getSimulationSpecificParameters(), out);
            // for (String param : simulation.getParameters()) {
            // out.println(param + " = " + simulation.getValue(param));
            // }
            out.println();
        }
        // }
        out.println("Algorithms:");
        out.println();
        for (int t = 0; t < algorithmSimulationWrappers.size(); t++) {
            AlgorithmSimulationWrapper wrapper = algorithmSimulationWrappers.get(t);
            if (wrapper.getSimulationWrapper() == simulationWrappers.get(0)) {
                out.println((t + 1) + ". " + wrapper.getAlgorithmWrapper().getDescription());
            }
        }
        if (isSortByUtility()) {
            out.println();
            out.println("Sorting by utility, high to low.");
        }
        if (isShowUtilities()) {
            out.println();
            out.println("Weighting of statistics:");
            out.println();
            out.println("U = ");
            for (Statistic stat : statistics.getStatistics()) {
                String statName = stat.getAbbreviation();
                double weight = statistics.getWeight(stat);
                if (weight != 0.0) {
                    out.println("    " + weight + " * f(" + statName + ")");
                }
            }
            out.println();
            out.println("...normed to range between 0 and 1.");
            out.println();
            out.println("Note that f for each statistic is a function that maps the statistic to the ");
            out.println("interval [0, 1], with higher being better.");
        }
        out.println();
        out.println("Graphs are being compared to the " + comparisonGraph.toString().replace("_", " ") + ".");
        out.println();
        // Add utilities to table as the last column.
        for (int u = 0; u < numTables; u++) {
            for (int t = 0; t < algorithmSimulationWrappers.size(); t++) {
                statTables[u][t][numStats] = utilities[t];
            }
        }
        // Print all of the tables.
        printStats(statTables, statistics, Mode.Average, newOrder, algorithmSimulationWrappers, algorithmWrappers, simulationWrappers, utilities, parameters);
        statTables = calcStatTables(allStats, Mode.StandardDeviation, numTables, algorithmSimulationWrappers, numStats, statistics);
        printStats(statTables, statistics, Mode.StandardDeviation, newOrder, algorithmSimulationWrappers, algorithmWrappers, simulationWrappers, utilities, parameters);
        statTables = calcStatTables(allStats, Mode.WorstCase, numTables, algorithmSimulationWrappers, numStats, statistics);
        // Add utilities to table as the last column.
        for (int u = 0; u < numTables; u++) {
            for (int t = 0; t < algorithmSimulationWrappers.size(); t++) {
                statTables[u][t][numStats] = utilities[t];
            }
        }
        printStats(statTables, statistics, Mode.WorstCase, newOrder, algorithmSimulationWrappers, algorithmWrappers, simulationWrappers, utilities, parameters);
    }
    out.close();
}

Example 8 with CombinationGenerator

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

the class VcpcAlt method search.

/**
 * Runs PC starting with a fully connected graph over all of the variables in the domain of the independence test.
 * See PC for caveats. The number of possible cycles and bidirected edges is far less with CPC than with PC.
 */
// public final Graph search() {
// return search(independenceTest.getVariable());
// }
// //    public Graph search(List<Node> nodes) {
// //
// ////        return search(new FasICov2(getIndependenceTest()), nodes);
// ////        return search(new Fas(getIndependenceTest()), nodes);
// //        return search(new Fas(getIndependenceTest()), nodes);
// }
// modified FAS into VCFAS; added in definitelyNonadjacencies set of edges.
public Graph search() {
    this.logger.log("info", "Starting VCCPC algorithm");
    this.logger.log("info", "Independence test = " + getIndependenceTest() + ".");
    this.allTriples = new HashSet<>();
    this.ambiguousTriples = new HashSet<>();
    this.colliderTriples = new HashSet<>();
    this.noncolliderTriples = new HashSet<>();
    Vcfas fas = new Vcfas(getIndependenceTest());
    definitelyNonadjacencies = new HashSet<>();
    markovInAllPatterns = new HashSet<>();
    // this.logger.log("info", "Variables " + independenceTest.getVariable());
    long startTime = System.currentTimeMillis();
    if (getIndependenceTest() == null) {
        throw new NullPointerException();
    }
    List<Node> allNodes = getIndependenceTest().getVariables();
    // if (!allNodes.containsAll(nodes)) {
    // throw new IllegalArgumentException("All of the given nodes must " +
    // "be in the domain of the independence test provided.");
    // }
    // Fas fas = new Fas(graph, getIndependenceTest());
    // FasStableConcurrent fas = new FasStableConcurrent(graph, getIndependenceTest());
    // Fas6 fas = new Fas6(graph, getIndependenceTest());
    // fas = new FasICov(graph, (IndTestFisherZ) getIndependenceTest());
    fas.setKnowledge(getKnowledge());
    fas.setDepth(getDepth());
    fas.setVerbose(verbose);
    // Note that we are ignoring the sepset map returned by this method
    // on purpose; it is not used in this search.
    graph = fas.search();
    apparentlyNonadjacencies = fas.getApparentlyNonadjacencies();
    if (isDoOrientation()) {
        if (verbose) {
            System.out.println("CPC orientation...");
        }
        SearchGraphUtils.pcOrientbk(knowledge, graph, allNodes);
        orientUnshieldedTriples(knowledge, getIndependenceTest(), getDepth());
        // orientUnshieldedTriplesConcurrent(knowledge, getIndependenceTest(), getMaxIndegree());
        MeekRules meekRules = new MeekRules();
        meekRules.setAggressivelyPreventCycles(this.aggressivelyPreventCycles);
        meekRules.setKnowledge(knowledge);
        meekRules.orientImplied(graph);
    }
    List<Triple> ambiguousTriples = new ArrayList(graph.getAmbiguousTriples());
    int[] dims = new int[ambiguousTriples.size()];
    for (int i = 0; i < ambiguousTriples.size(); i++) {
        dims[i] = 2;
    }
    List<Graph> patterns = new ArrayList<>();
    Map<Graph, List<Triple>> newColliders = new IdentityHashMap<>();
    Map<Graph, List<Triple>> newNonColliders = new IdentityHashMap<>();
    // Using combination generator to generate a list of combinations of ambiguous triples dismabiguated into colliders
    // and non-colliders. The combinations are added as graphs to the list patterns. The graphs are then subject to
    // basic rules to ensure consistent patterns.
    CombinationGenerator generator = new CombinationGenerator(dims);
    int[] combination;
    while ((combination = generator.next()) != null) {
        Graph _graph = new EdgeListGraph(graph);
        newColliders.put(_graph, new ArrayList<Triple>());
        newNonColliders.put(_graph, new ArrayList<Triple>());
        for (Graph graph : newColliders.keySet()) {
        // System.out.println("$$$ " + newColliders.get(graph));
        }
        for (int k = 0; k < combination.length; k++) {
            // System.out.println("k = " + combination[k]);
            Triple triple = ambiguousTriples.get(k);
            _graph.removeAmbiguousTriple(triple.getX(), triple.getY(), triple.getZ());
            if (combination[k] == 0) {
                newColliders.get(_graph).add(triple);
                // System.out.println(newColliders.get(_graph));
                Node x = triple.getX();
                Node y = triple.getY();
                Node z = triple.getZ();
                _graph.setEndpoint(x, y, Endpoint.ARROW);
                _graph.setEndpoint(z, y, Endpoint.ARROW);
            }
            if (combination[k] == 1) {
                newNonColliders.get(_graph).add(triple);
            }
        }
        patterns.add(_graph);
    }
    List<Graph> _patterns = new ArrayList<>(patterns);
    GRAPH: for (Graph graph : new ArrayList<>(patterns)) {
        // _graph = new EdgeListGraph(graph);
        // System.out.println("graph = " + graph + " in keyset? " + newColliders.containsKey(graph));
        // 
        List<Triple> colliders = newColliders.get(graph);
        List<Triple> nonColliders = newNonColliders.get(graph);
        for (Triple triple : colliders) {
            Node x = triple.getX();
            Node y = triple.getY();
            Node z = triple.getZ();
            if (graph.getEdge(x, y).pointsTowards(x) || (graph.getEdge(y, z).pointsTowards(z))) {
                patterns.remove(graph);
                continue GRAPH;
            }
        }
        for (Triple triple : colliders) {
            Node x = triple.getX();
            Node y = triple.getY();
            Node z = triple.getZ();
            graph.setEndpoint(x, y, Endpoint.ARROW);
            graph.setEndpoint(z, y, Endpoint.ARROW);
        }
        for (Triple triple : nonColliders) {
            Node x = triple.getX();
            Node y = triple.getY();
            Node z = triple.getZ();
            if (graph.getEdge(x, y).pointsTowards(y)) {
                graph.removeEdge(y, z);
                graph.addDirectedEdge(y, z);
            }
            if (graph.getEdge(y, z).pointsTowards(y)) {
                graph.removeEdge(x, y);
                graph.addDirectedEdge(y, x);
            }
        }
        for (Edge edge : graph.getEdges()) {
            if (Edges.isBidirectedEdge(edge)) {
                patterns.remove(graph);
                continue GRAPH;
            }
        }
        MeekRules rules = new MeekRules();
        rules.orientImplied(graph);
        if (graph.existsDirectedCycle()) {
            patterns.remove(graph);
            continue GRAPH;
        }
    }
    MARKOV: for (Edge edge : apparentlyNonadjacencies.keySet()) {
        Node x = edge.getNode1();
        Node y = edge.getNode2();
        for (Graph _graph : new ArrayList<>(patterns)) {
            List<Node> boundaryX = new ArrayList<>(boundary(x, _graph));
            List<Node> boundaryY = new ArrayList<>(boundary(y, _graph));
            List<Node> futureX = new ArrayList<>(future(x, _graph));
            List<Node> futureY = new ArrayList<>(future(y, _graph));
            if (y == x) {
                continue;
            }
            if (boundaryX.contains(y) || boundaryY.contains(x)) {
                continue;
            }
            IndependenceTest test = independenceTest;
            if (!futureX.contains(y)) {
                if (test.isIndependent(x, y, boundaryX)) {
                    if (!futureY.contains(x)) {
                        if (test.isIndependent(y, x, boundaryY)) {
                            definitelyNonadjacencies.add(edge);
                            continue MARKOV;
                        }
                    }
                }
            }
        }
    }
    for (Edge edge : definitelyNonadjacencies) {
        if (apparentlyNonadjacencies.keySet().contains(edge)) {
            apparentlyNonadjacencies.keySet().remove(edge);
        }
    }
    // MARKOV:
    // 
    // for (Edge edge : apparentlyNonadjacencies.keySet()) {
    // Node x = edge.getNode1();
    // Node y = edge.getNode2();
    // 
    // for (Graph _graph : new ArrayList<Graph>(patterns)) {
    // 
    // List<Node> boundaryX = new ArrayList<Node>(boundary(x, _graph));
    // List<Node> boundaryY = new ArrayList<Node>(boundary(y, _graph));
    // List<Node> futureX = new ArrayList<Node>(future(x, _graph));
    // List<Node> futureY = new ArrayList<Node>(future(y, _graph));
    // if (y == x) {
    // continue;
    // }
    // if (futureX.contains(y) || futureY.contains(x)) {
    // continue;
    // }
    // if (boundaryX.contains(y) || boundaryY.contains(x)) {
    // continue;
    // }
    // 
    // System.out.println(_graph);
    // IndependenceTest test = new IndTestDSep(_graph);
    // if (!test.isIndependent(x, y, boundaryX)) {
    // continue;
    // }
    // if (!test.isIndependent(y, x, boundaryY)) {
    // continue;
    // }
    // 
    // definitelyNonadjacencies.add(edge);
    // continue MARKOV;
    // }
    // 
    // //            apparentlyNonadjacencies.remove(edge);
    // 
    // }
    // 
    // for (Edge edge : definitelyNonadjacencies) {
    // if (apparentlyNonadjacencies.keySet().contains(edge)) {
    // apparentlyNonadjacencies.keySet().remove(edge);
    // }
    // }
    // Step V5. For each consistent disambiguation of the ambiguous triples
    // we test whether the resulting pattern satisfies Markov. If
    // every pattern does, then mark all the apparently non-adjacent
    // pairs as definitely non-adjacent.
    // NODES:
    // 
    // for (Node node : graph.getNodes()) {
    // for (Graph _graph : new ArrayList<Graph>(patterns)) {
    // System.out.println("boundary of" + node + boundary(node, _graph));
    // System.out.println("future of" + node + future(node, _graph));
    // if (!isMarkov(node, _graph)) {
    // continue NODES;
    // }
    // }
    // markovInAllPatterns.add(node);
    // continue NODES;
    // }
    // 
    // Graph g = new EdgeListGraph(graph.getNodes());
    // for (Edge edge : apparentlyNonadjacencies.keySet()) {
    // g.addEdge(edge);
    // }
    // 
    // List<Edge> _edges = g.getEdges();
    // 
    // for (Edge edge : _edges) {
    // Node x = edge.getNode1();
    // Node y = edge.getNode2();
    // 
    // if (markovInAllPatterns.contains(x) &&
    // markovInAllPatterns.contains(y)) {
    // definitelyNonadjacencies.add(edge);
    // }
    // }
    System.out.println("Definitely Nonadjacencies:");
    for (Edge edge : definitelyNonadjacencies) {
        System.out.println(edge);
    }
    System.out.println("markov in all patterns:" + markovInAllPatterns);
    System.out.println("patterns:" + patterns);
    System.out.println("Apparently Nonadjacencies:");
    for (Edge edge : apparentlyNonadjacencies.keySet()) {
        System.out.println(edge);
    }
    System.out.println("Definitely Nonadjacencies:");
    for (Edge edge : definitelyNonadjacencies) {
        System.out.println(edge);
    }
    TetradLogger.getInstance().log("apparentlyNonadjacencies", "\n Apparent Non-adjacencies" + apparentlyNonadjacencies);
    TetradLogger.getInstance().log("definitelyNonadjacencies", "\n Definite Non-adjacencies" + definitelyNonadjacencies);
    TetradLogger.getInstance().log("patterns", "Disambiguated Patterns: " + patterns);
    TetradLogger.getInstance().log("graph", "\nReturning this graph: " + graph);
    long endTime = System.currentTimeMillis();
    this.elapsedTime = endTime - startTime;
    TetradLogger.getInstance().log("info", "Elapsed time = " + (elapsedTime) / 1000. + " s");
    TetradLogger.getInstance().log("info", "Finishing CPC algorithm.");
    logTriples();
    TetradLogger.getInstance().flush();
    // SearchGraphUtils.verifySepsetIntegrity(Map<Edge, List<Node>>, graph);
    return graph;
}

Example 9 with CombinationGenerator

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

the class SampleVcpc method search.

/**
 * Runs PC starting with a fully connected graph over all of the variables in the domain of the independence test.
 * See PC for caveats. The number of possible cycles and bidirected edges is far less with CPC than with PC.
 */
// public final Graph search() {
// return search(independenceTest.getVariable());
// }
// //    public Graph search(List<Node> nodes) {
// //
// ////        return search(new FasICov2(getIndependenceTest()), nodes);
// ////        return search(new Fas(getIndependenceTest()), nodes);
// //        return search(new Fas(getIndependenceTest()), nodes);
// }
// modified FAS into VCFAS; added in definitelyNonadjacencies set of edges.
public Graph search() {
    this.logger.log("info", "Starting VCCPC algorithm");
    this.logger.log("info", "Independence test = " + getIndependenceTest() + ".");
    this.allTriples = new HashSet<>();
    this.ambiguousTriples = new HashSet<>();
    this.colliderTriples = new HashSet<>();
    this.noncolliderTriples = new HashSet<>();
    Vcfas fas = new Vcfas(getIndependenceTest());
    definitelyNonadjacencies = new HashSet<>();
    markovInAllPatterns = new HashSet<>();
    // this.logger.log("info", "Variables " + independenceTest.getVariable());
    long startTime = System.currentTimeMillis();
    if (getIndependenceTest() == null) {
        throw new NullPointerException();
    }
    List<Node> allNodes = getIndependenceTest().getVariables();
    // if (!allNodes.containsAll(nodes)) {
    // throw new IllegalArgumentException("All of the given nodes must " +
    // "be in the domain of the independence test provided.");
    // }
    // Fas fas = new Fas(graph, getIndependenceTest());
    // FasStableConcurrent fas = new FasStableConcurrent(graph, getIndependenceTest());
    // Fas6 fas = new Fas6(graph, getIndependenceTest());
    // fas = new FasICov(graph, (IndTestFisherZ) getIndependenceTest());
    fas.setKnowledge(getKnowledge());
    fas.setDepth(getDepth());
    fas.setVerbose(verbose);
    // Note that we are ignoring the sepset map returned by this method
    // on purpose; it is not used in this search.
    graph = fas.search();
    apparentlyNonadjacencies = fas.getApparentlyNonadjacencies();
    if (isDoOrientation()) {
        if (verbose) {
            System.out.println("CPC orientation...");
        }
        SearchGraphUtils.pcOrientbk(knowledge, graph, allNodes);
        orientUnshieldedTriples(knowledge, getIndependenceTest(), getDepth());
        // orientUnshieldedTriplesConcurrent(knowledge, getIndependenceTest(), getMaxIndegree());
        MeekRules meekRules = new MeekRules();
        meekRules.setAggressivelyPreventCycles(this.aggressivelyPreventCycles);
        meekRules.setKnowledge(knowledge);
        meekRules.orientImplied(graph);
    }
    List<Triple> ambiguousTriples = new ArrayList(graph.getAmbiguousTriples());
    int[] dims = new int[ambiguousTriples.size()];
    for (int i = 0; i < ambiguousTriples.size(); i++) {
        dims[i] = 2;
    }
    List<Graph> patterns = new ArrayList<>();
    Map<Graph, List<Triple>> newColliders = new IdentityHashMap<>();
    Map<Graph, List<Triple>> newNonColliders = new IdentityHashMap<>();
    // Using combination generator to generate a list of combinations of ambiguous triples dismabiguated into colliders
    // and non-colliders. The combinations are added as graphs to the list patterns. The graphs are then subject to
    // basic rules to ensure consistent patterns.
    CombinationGenerator generator = new CombinationGenerator(dims);
    int[] combination;
    while ((combination = generator.next()) != null) {
        Graph _graph = new EdgeListGraph(graph);
        newColliders.put(_graph, new ArrayList<Triple>());
        newNonColliders.put(_graph, new ArrayList<Triple>());
        for (Graph graph : newColliders.keySet()) {
        // System.out.println("$$$ " + newColliders.get(graph));
        }
        for (int k = 0; k < combination.length; k++) {
            // System.out.println("k = " + combination[k]);
            Triple triple = ambiguousTriples.get(k);
            _graph.removeAmbiguousTriple(triple.getX(), triple.getY(), triple.getZ());
            if (combination[k] == 0) {
                newColliders.get(_graph).add(triple);
                // System.out.println(newColliders.get(_graph));
                Node x = triple.getX();
                Node y = triple.getY();
                Node z = triple.getZ();
                _graph.setEndpoint(x, y, Endpoint.ARROW);
                _graph.setEndpoint(z, y, Endpoint.ARROW);
            }
            if (combination[k] == 1) {
                newNonColliders.get(_graph).add(triple);
            }
        }
        patterns.add(_graph);
    }
    List<Graph> _patterns = new ArrayList<>(patterns);
    GRAPH: for (Graph graph : new ArrayList<>(patterns)) {
        // _graph = new EdgeListGraph(graph);
        // System.out.println("graph = " + graph + " in keyset? " + newColliders.containsKey(graph));
        // 
        List<Triple> colliders = newColliders.get(graph);
        List<Triple> nonColliders = newNonColliders.get(graph);
        for (Triple triple : colliders) {
            Node x = triple.getX();
            Node y = triple.getY();
            Node z = triple.getZ();
            if (graph.getEdge(x, y).pointsTowards(x) || (graph.getEdge(y, z).pointsTowards(z))) {
                patterns.remove(graph);
                continue GRAPH;
            }
        }
        for (Triple triple : colliders) {
            Node x = triple.getX();
            Node y = triple.getY();
            Node z = triple.getZ();
            graph.setEndpoint(x, y, Endpoint.ARROW);
            graph.setEndpoint(z, y, Endpoint.ARROW);
        }
        for (Triple triple : nonColliders) {
            Node x = triple.getX();
            Node y = triple.getY();
            Node z = triple.getZ();
            if (graph.getEdge(x, y).pointsTowards(y)) {
                graph.removeEdge(y, z);
                graph.addDirectedEdge(y, z);
            }
            if (graph.getEdge(y, z).pointsTowards(y)) {
                graph.removeEdge(x, y);
                graph.addDirectedEdge(y, x);
            }
        }
        for (Edge edge : graph.getEdges()) {
            Node x = edge.getNode1();
            Node y = edge.getNode2();
            if (Edges.isBidirectedEdge(edge)) {
                graph.removeEdge(x, y);
                graph.addUndirectedEdge(x, y);
            }
        }
        // for (Edge edge : graph.getEdges()) {
        // if (Edges.isBidirectedEdge(edge)) {
        // patterns.remove(graph);
        // continue Graph;
        // }
        // }
        MeekRules rules = new MeekRules();
        rules.orientImplied(graph);
        if (graph.existsDirectedCycle()) {
            patterns.remove(graph);
            continue GRAPH;
        }
    }
    MARKOV: for (Edge edge : apparentlyNonadjacencies.keySet()) {
        Node x = edge.getNode1();
        Node y = edge.getNode2();
        for (Graph _graph : new ArrayList<>(patterns)) {
            List<Node> boundaryX = new ArrayList<>(boundary(x, _graph));
            List<Node> boundaryY = new ArrayList<>(boundary(y, _graph));
            List<Node> futureX = new ArrayList<>(future(x, _graph));
            List<Node> futureY = new ArrayList<>(future(y, _graph));
            if (y == x) {
                continue;
            }
            if (boundaryX.contains(y) || boundaryY.contains(x)) {
                continue;
            }
            IndependenceTest test = independenceTest;
            if (!futureX.contains(y)) {
                if (!test.isIndependent(x, y, boundaryX)) {
                    continue MARKOV;
                }
            }
            if (!futureY.contains(x)) {
                if (!test.isIndependent(y, x, boundaryY)) {
                    continue MARKOV;
                }
            }
        }
        definitelyNonadjacencies.add(edge);
    // apparentlyNonadjacencies.remove(edge);
    }
    for (Edge edge : definitelyNonadjacencies) {
        if (apparentlyNonadjacencies.keySet().contains(edge)) {
            apparentlyNonadjacencies.keySet().remove(edge);
        }
    }
    setSemIm(semIm);
    // semIm.getSemPm().getGraph();
    System.out.println(semIm.getEdgeCoef());
    // graph = DataGraphUtils.replaceNodes(graph, semIm.getVariableNodes());
    // System.out.println(semIm.getEdgeCoef());
    // System.out.println(sampleRegress.entrySet());
    List<Double> squaredDifference = new ArrayList<>();
    int numNullEdges = 0;
    // //Edge Estimation Alg I
    Regression sampleRegression = new RegressionDataset(dataSet);
    System.out.println(sampleRegression.getGraph());
    graph = GraphUtils.replaceNodes(graph, dataSet.getVariables());
    Map<Edge, double[]> sampleRegress = new HashMap<>();
    Map<Edge, Double> edgeCoefs = new HashMap<>();
    ESTIMATION: for (Node z : graph.getNodes()) {
        Set<Edge> adj = getAdj(z, graph);
        for (Edge edge : apparentlyNonadjacencies.keySet()) {
            if (z == edge.getNode1() || z == edge.getNode2()) {
                for (Edge adjacency : adj) {
                    // return Unknown and go to next Z
                    sampleRegress.put(adjacency, null);
                    Node a = adjacency.getNode1();
                    Node b = adjacency.getNode2();
                    if (semIm.existsEdgeCoef(a, b)) {
                        Double c = semIm.getEdgeCoef(a, b);
                        edgeCoefs.put(adjacency, c);
                    } else {
                        edgeCoefs.put(adjacency, 0.0);
                    }
                }
                continue ESTIMATION;
            }
        }
        for (Edge nonadj : definitelyNonadjacencies) {
            if (nonadj.getNode1() == z || nonadj.getNode2() == z) {
                // return 0 for e
                double[] d = { 0, 0 };
                sampleRegress.put(nonadj, d);
                Node a = nonadj.getNode1();
                Node b = nonadj.getNode2();
                if (semIm.existsEdgeCoef(a, b)) {
                    Double c = semIm.getEdgeCoef(a, b);
                    edgeCoefs.put(nonadj, c);
                } else {
                    edgeCoefs.put(nonadj, 0.0);
                }
            }
        }
        Set<Edge> parentsOfZ = new HashSet<>();
        Set<Edge> _adj = getAdj(z, graph);
        for (Edge _adjacency : _adj) {
            if (!_adjacency.isDirected()) {
                for (Edge adjacency : adj) {
                    sampleRegress.put(adjacency, null);
                    Node a = adjacency.getNode1();
                    Node b = adjacency.getNode2();
                    if (semIm.existsEdgeCoef(a, b)) {
                        Double c = semIm.getEdgeCoef(a, b);
                        edgeCoefs.put(adjacency, c);
                    } else {
                        edgeCoefs.put(adjacency, 0.0);
                    }
                }
            }
            if (_adjacency.pointsTowards(z)) {
                parentsOfZ.add(_adjacency);
            }
        }
        for (Edge edge : parentsOfZ) {
            if (edge.pointsTowards(edge.getNode2())) {
                RegressionResult result = sampleRegression.regress(edge.getNode2(), edge.getNode1());
                System.out.println(result);
                double[] d = result.getCoef();
                sampleRegress.put(edge, d);
                Node a = edge.getNode1();
                Node b = edge.getNode2();
                if (semIm.existsEdgeCoef(a, b)) {
                    Double c = semIm.getEdgeCoef(a, b);
                    edgeCoefs.put(edge, c);
                } else {
                    edgeCoefs.put(edge, 0.0);
                }
            }
        // if (edge.pointsTowards(edge.getNode2())) {
        // RegressionResult result = sampleRegression.regress(edge.getNode2(), edge.getNode1());
        // double[] d = result.getCoef();
        // sampleRegress.put(edge, d);
        // 
        // Node a = edge.getNode1();
        // Node b = edge.getNode2();
        // if (semIm.existsEdgeCoef(a, b)) {
        // Double c = semIm.getEdgeCoef(a, b);
        // edgeCoefs.put(edge, c);
        // } else { edgeCoefs.put(edge, 0.0); }
        // }
        }
    }
    System.out.println("All IM: " + semIm + "Finish");
    System.out.println("Just IM coefs: " + semIm.getEdgeCoef());
    System.out.println("IM Coef Map: " + edgeCoefs);
    System.out.println("Regress Coef Map: " + sampleRegress);
    // 
    for (Edge edge : sampleRegress.keySet()) {
        System.out.println(" Sample Regression: " + edge + java.util.Arrays.toString(sampleRegress.get(edge)));
    }
    for (Edge edge : graph.getEdges()) {
        // if (edge.isDirected()) {
        // System.out.println("IM edge: " + semIm.getEdgeCoef(edge));
        // }
        System.out.println("Sample edge: " + java.util.Arrays.toString(sampleRegress.get(edge)));
    }
    // 
    // 
    System.out.println("Sample VCPC:");
    System.out.println("# of patterns: " + patterns.size());
    long endTime = System.currentTimeMillis();
    this.elapsedTime = endTime - startTime;
    System.out.println("Search Time (seconds):" + (elapsedTime) / 1000 + " s");
    System.out.println("Search Time (milli):" + elapsedTime + " ms");
    System.out.println("# of Apparent Nonadj: " + apparentlyNonadjacencies.size());
    System.out.println("# of Definite Nonadj: " + definitelyNonadjacencies.size());
    // System.out.println("Definitely Nonadjacencies:");
    // 
    // for (Edge edge : definitelyNonadjacencies) {
    // System.out.println(edge);
    // }
    // 
    // System.out.println("markov in all patterns:" + markovInAllPatterns);
    // System.out.println("patterns:" + patterns);
    // System.out.println("Apparently Nonadjacencies:");
    // 
    // for (Edge edge : apparentlyNonadjacencies.keySet()) {
    // System.out.println(edge);
    // }
    // System.out.println("Definitely Nonadjacencies:");
    // 
    // 
    // for (Edge edge : definitelyNonadjacencies) {
    // System.out.println(edge);
    // }
    TetradLogger.getInstance().log("apparentlyNonadjacencies", "\n Apparent Non-adjacencies" + apparentlyNonadjacencies);
    TetradLogger.getInstance().log("definitelyNonadjacencies", "\n Definite Non-adjacencies" + definitelyNonadjacencies);
    TetradLogger.getInstance().log("patterns", "Disambiguated Patterns: " + patterns);
    TetradLogger.getInstance().log("graph", "\nReturning this graph: " + graph);
    TetradLogger.getInstance().log("info", "Elapsed time = " + (elapsedTime) / 1000. + " s");
    TetradLogger.getInstance().log("info", "Finishing CPC algorithm.");
    logTriples();
    TetradLogger.getInstance().flush();
    // SearchGraphUtils.verifySepsetIntegrity(Map<Edge, List<Node>>, graph);
    return graph;
}

Example 10 with CombinationGenerator

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

the class TestCombinationGenerator method test1.

@Test
public void test1() {
    CombinationGenerator gen = new CombinationGenerator(new int[] { 5, 3 });
    int count = 0;
    while (gen.next() != null) {
        count++;
    }
    assertEquals(15, count);
}