示例#1
0
  private Graph condense(Graph mimStructure, Graph mimbuildStructure) {
    //        System.out.println("Uncondensed: " + mimbuildStructure);

    Map<Node, Node> substitutions = new HashMap<Node, Node>();

    for (Node node : mimbuildStructure.getNodes()) {
      for (Node _node : mimStructure.getNodes()) {
        if (node.getName().startsWith(_node.getName())) {
          substitutions.put(node, _node);
          break;
        }

        substitutions.put(node, node);
      }
    }

    HashSet<Node> nodes = new HashSet<Node>(substitutions.values());
    Graph graph = new EdgeListGraph(new ArrayList<Node>(nodes));

    for (Edge edge : mimbuildStructure.getEdges()) {
      Node node1 = substitutions.get(edge.getNode1());
      Node node2 = substitutions.get(edge.getNode2());

      if (node1 == node2) continue;

      if (graph.isAdjacentTo(node1, node2)) continue;

      graph.addEdge(new Edge(node1, node2, edge.getEndpoint1(), edge.getEndpoint2()));
    }

    //        System.out.println("Condensed: " + graph);

    return graph;
  }
示例#2
0
文件: Lofs.java 项目: jdramsey/tetrad
  public Graph orient() {
    Graph skeleton = GraphUtils.undirectedGraph(getPattern());
    Graph graph = new EdgeListGraph(skeleton.getNodes());

    List<Node> nodes = skeleton.getNodes();
    //        Collections.shuffle(nodes);

    if (isR1Done()) {
      ruleR1(skeleton, graph, nodes);
    }

    for (Edge edge : skeleton.getEdges()) {
      if (!graph.isAdjacentTo(edge.getNode1(), edge.getNode2())) {
        graph.addUndirectedEdge(edge.getNode1(), edge.getNode2());
      }
    }

    if (isR2Done()) {
      ruleR2(skeleton, graph);
    }

    if (isMeekDone()) {
      new MeekRules().orientImplied(graph);
    }

    return graph;
  }
示例#3
0
  // Cannot be done if the graph changes.
  public void setInitialGraph(Graph initialGraph) {
    initialGraph = GraphUtils.replaceNodes(initialGraph, variables);

    out.println("Initial graph variables: " + initialGraph.getNodes());
    out.println("Data set variables: " + variables);

    if (!new HashSet<Node>(initialGraph.getNodes()).equals(new HashSet<Node>(variables))) {
      throw new IllegalArgumentException("Variables aren't the same.");
    }

    this.initialGraph = initialGraph;
  }
示例#4
0
  ////////////////////////////////////////////////
  // collect in rTupleList all unshielded tuples
  ////////////////////////////////////////////////
  private List<Node[]> getRTuples() {
    List<Node[]> rTuples = new ArrayList<Node[]>();
    List<Node> nodes = graph.getNodes();

    for (Node j : nodes) {
      List<Node> adjacentNodes = graph.getAdjacentNodes(j);

      if (adjacentNodes.size() < 2) {
        continue;
      }

      ChoiceGenerator cg = new ChoiceGenerator(adjacentNodes.size(), 2);
      int[] combination;

      while ((combination = cg.next()) != null) {
        Node i = adjacentNodes.get(combination[0]);
        Node k = adjacentNodes.get(combination[1]);

        // Skip triples that are shielded.
        if (!graph.isAdjacentTo(i, k)) {
          Node[] newTuple = {i, j, k};
          rTuples.add(newTuple);
        }
      }
    }

    return (rTuples);
  }
示例#5
0
文件: PcMax.java 项目: renjiey/tetrad
  public List<Triple> getUnshieldedCollidersFromGraph(Graph graph) {
    List<Triple> colliders = new ArrayList<>();

    List<Node> nodes = graph.getNodes();

    for (Node b : nodes) {
      List<Node> adjacentNodes = graph.getAdjacentNodes(b);

      if (adjacentNodes.size() < 2) {
        continue;
      }

      ChoiceGenerator cg = new ChoiceGenerator(adjacentNodes.size(), 2);
      int[] combination;

      while ((combination = cg.next()) != null) {
        Node a = adjacentNodes.get(combination[0]);
        Node c = adjacentNodes.get(combination[1]);

        // Skip triples that are shielded.
        if (graph.isAdjacentTo(a, c)) {
          continue;
        }

        if (graph.isDefCollider(a, b, c)) {
          colliders.add(new Triple(a, b, c));
        }
      }
    }

    return colliders;
  }
  /**
   * Double checks a sepset map against a pattern to make sure that X is adjacent to Y in the
   * pattern iff {X, Y} is not in the domain of the sepset map.
   *
   * @param sepset a sepset map, over variables V.
   * @param pattern a pattern over variables W, V subset of W.
   * @return true if the sepset map is consistent with the pattern.
   */
  public static boolean verifySepsetIntegrity(SepsetMap sepset, Graph pattern) {
    for (Node x : pattern.getNodes()) {
      for (Node y : pattern.getNodes()) {
        if (x == y) {
          continue;
        }

        if ((pattern.isAdjacentTo(y, x)) != (sepset.get(x, y) == null)) {
          System.out.println("Sepset not consistent with graph for {" + x + ", " + y + "}");
          return false;
        }
      }
    }

    return true;
  }
示例#7
0
  public TimeLagGraphWrapper(GraphWrapper graphWrapper) {
    if (graphWrapper == null) {
      throw new NullPointerException("No graph wrapper.");
    }

    TimeLagGraph graph = new TimeLagGraph();

    Graph _graph = graphWrapper.getGraph();

    for (Node node : _graph.getNodes()) {
      Node _node = node.like(node.getName() + ":0");
      _node.setNodeType(node.getNodeType());
      graph.addNode(_node);
    }

    for (Edge edge : _graph.getEdges()) {
      if (!Edges.isDirectedEdge(edge)) {
        throw new IllegalArgumentException();
      }

      Node from = edge.getNode1();
      Node to = edge.getNode2();

      Node _from = graph.getNode(from.getName(), 1);
      Node _to = graph.getNode(to.getName(), 0);

      graph.addDirectedEdge(_from, _to);
    }

    this.graph = graph;
  }
示例#8
0
  // ===========================SCORING METHODS===================//
  public double scoreDag(Graph graph) {
    Graph dag = new EdgeListGraphSingleConnections(graph);
    buildIndexing(graph);

    double score = 0.0;

    for (Node y : dag.getNodes()) {
      Set<Node> parents = new HashSet<Node>(dag.getParents(y));
      int nextIndex = -1;
      for (int i = 0; i < getVariables().size(); i++) {
        nextIndex = hashIndices.get(variables.get(i));
      }
      int parentIndices[] = new int[parents.size()];
      Iterator<Node> pi = parents.iterator();
      int count = 0;
      while (pi.hasNext()) {
        Node nextParent = pi.next();
        parentIndices[count++] = hashIndices.get(nextParent);
      }

      if (this.isDiscrete()) {
        score += localDiscreteScore(nextIndex, parentIndices);
      } else {
        score += localSemScore(nextIndex, parentIndices);
      }
    }
    return score;
  }
示例#9
0
  private Graph changeLatentNames(Graph full, Clusters measurements, List<String> latentVarList) {
    Graph g2 = null;

    try {
      g2 = (Graph) new MarshalledObject(full).get();
    } catch (IOException e) {
      e.printStackTrace();
    } catch (ClassNotFoundException e) {
      e.printStackTrace();
    }

    for (int i = 0; i < measurements.getNumClusters(); i++) {
      List<String> d = measurements.getCluster(i);
      String latentName = latentVarList.get(i);

      for (Node node : full.getNodes()) {
        if (!(node.getNodeType() == NodeType.LATENT)) {
          continue;
        }

        List<Node> _children = full.getChildren(node);

        _children.removeAll(ReidentifyVariables.getLatents(full));

        List<String> childNames = getNames(_children);

        if (new HashSet<String>(childNames).equals(new HashSet<String>(d))) {
          g2.getNode(node.getName()).setName(latentName);
        }
      }
    }

    return g2;
  }
  /**
   * Constructs a new on-the-fly BayesIM that will calculate conditional probabilities on the fly
   * from the given discrete data set, for the given Bayes PM.
   *
   * @param bayesPm the given Bayes PM, which specifies a directed acyclic graph for a Bayes net and
   *     parametrization for the Bayes net, but not actual values for the parameters.
   * @param dataSet the discrete data set from which conditional probabilities should be estimated
   *     on the fly.
   */
  public OnTheFlyMarginalCalculator(BayesPm bayesPm, DataSet dataSet)
      throws IllegalArgumentException {
    if (bayesPm == null) {
      throw new NullPointerException();
    }

    if (dataSet == null) {
      throw new NullPointerException();
    }

    // Make sure all of the variables in the PM are in the data set;
    // otherwise, estimation is impossible.
    BayesUtils.ensureVarsInData(bayesPm.getVariables(), dataSet);
    //        DataUtils.ensureVariablesExist(bayesPm, dataSet);

    this.bayesPm = new BayesPm(bayesPm);

    // Get the nodes from the BayesPm. This fixes the order of the nodes
    // in the BayesIm, independently of any change to the BayesPm.
    // (This order must be maintained.)
    Graph graph = bayesPm.getDag();
    this.nodes = graph.getNodes().toArray(new Node[0]);

    // Initialize.
    initialize();

    // Create a subset of the data set with the variables of the IM, in
    // the order of the IM.
    List<Node> variables = getVariables();
    this.dataSet = dataSet.subsetColumns(variables);

    // Create a tautologous proposition for evidence.
    this.evidence = new Evidence(Proposition.tautology(this));
  }
示例#11
0
文件: PcMax.java 项目: renjiey/tetrad
  /**
   * Step C of PC; orients colliders using specified sepset. That is, orients x *-* y *-* z as x *->
   * y <-* z just in case y is in Sepset({x, z}).
   */
  public Map<Triple, Double> findCollidersUsingSepsets(
      SepsetProducer sepsetProducer, Graph graph, boolean verbose, IKnowledge knowledge) {
    TetradLogger.getInstance().log("details", "Starting Collider Orientation:");
    Map<Triple, Double> colliders = new HashMap<>();

    System.out.println("Looking for colliders");

    List<Node> nodes = graph.getNodes();

    for (Node b : nodes) {
      List<Node> adjacentNodes = graph.getAdjacentNodes(b);

      if (adjacentNodes.size() < 2) {
        continue;
      }

      ChoiceGenerator cg = new ChoiceGenerator(adjacentNodes.size(), 2);
      int[] combination;

      while ((combination = cg.next()) != null) {
        Node a = adjacentNodes.get(combination[0]);
        Node c = adjacentNodes.get(combination[1]);

        // Skip triples that are shielded.
        if (graph.isAdjacentTo(a, c)) {
          continue;
        }

        List<Node> sepset = sepsetProducer.getSepset(a, c);

        if (sepset == null) continue;

        //                if (sepsetProducer.getPValue() < 0.5) continue;

        if (!sepset.contains(b)) {
          if (verbose) {
            //                        boolean dsep = this.dsep.isIndependent(a, c);
            //                        System.out.println("QQQ p = " + independenceTest.getPValue() +
            // " " + dsep);

            System.out.println(
                "\nCollider orientation <" + a + ", " + b + ", " + c + "> sepset = " + sepset);
          }

          colliders.put(new Triple(a, b, c), sepsetProducer.getPValue());

          TetradLogger.getInstance()
              .log("colliderOrientations", SearchLogUtils.colliderOrientedMsg(a, b, c, sepset));
        }
      }
    }

    TetradLogger.getInstance().log("details", "Finishing Collider Orientation.");

    System.out.println("Done finding colliders");

    return colliders;
  }
  /**
   * Transforms a maximally directed pattern (PDAG) represented in graph <code>g</code> into an
   * arbitrary DAG by modifying <code>g</code> itself. Based on the algorithm described in
   * Chickering (2002) "Optimal structure identification with greedy search" Journal of Machine
   * Learning Research. R. Silva, June 2004
   */
  public static void pdagToDag(Graph g) {
    Graph p = new EdgeListGraph(g);
    List<Edge> undirectedEdges = new ArrayList<Edge>();

    for (Edge edge : g.getEdges()) {
      if (edge.getEndpoint1() == Endpoint.TAIL
          && edge.getEndpoint2() == Endpoint.TAIL
          && !undirectedEdges.contains(edge)) {
        undirectedEdges.add(edge);
      }
    }
    g.removeEdges(undirectedEdges);
    List<Node> pNodes = p.getNodes();

    do {
      Node x = null;

      for (Node pNode : pNodes) {
        x = pNode;

        if (p.getChildren(x).size() > 0) {
          continue;
        }

        Set<Node> neighbors = new HashSet<Node>();

        for (Edge edge : p.getEdges()) {
          if (edge.getNode1() == x || edge.getNode2() == x) {
            if (edge.getEndpoint1() == Endpoint.TAIL && edge.getEndpoint2() == Endpoint.TAIL) {
              if (edge.getNode1() == x) {
                neighbors.add(edge.getNode2());
              } else {
                neighbors.add(edge.getNode1());
              }
            }
          }
        }
        if (neighbors.size() > 0) {
          Collection<Node> parents = p.getParents(x);
          Set<Node> all = new HashSet<Node>(neighbors);
          all.addAll(parents);
          if (!GraphUtils.isClique(all, p)) {
            continue;
          }
        }

        for (Node neighbor : neighbors) {
          Node node1 = g.getNode(neighbor.getName());
          Node node2 = g.getNode(x.getName());

          g.addDirectedEdge(node1, node2);
        }
        p.removeNode(x);
        break;
      }
      pNodes.remove(x);
    } while (pNodes.size() > 0);
  }
 private List<String> measuredNames(Graph graph) {
   List<String> names = new ArrayList<>();
   for (Node node : graph.getNodes()) {
     if (node.getNodeType() == NodeType.MEASURED) {
       names.add(node.getName());
     }
   }
   return names;
 }
  public static boolean meekR1Locally2(
      Graph graph, Knowledge knowledge, IndependenceTest test, int depth) {
    List<Node> nodes = graph.getNodes();
    boolean changed = true;

    while (changed) {
      changed = false;

      for (Node a : nodes) {
        List<Node> adjacentNodes = graph.getAdjacentNodes(a);

        if (adjacentNodes.size() < 2) {
          continue;
        }

        ChoiceGenerator cg = new ChoiceGenerator(adjacentNodes.size(), 2);
        int[] combination;

        while ((combination = cg.next()) != null) {
          Node b = adjacentNodes.get(combination[0]);
          Node c = adjacentNodes.get(combination[1]);

          // Skip triples that are shielded.
          if (graph.isAdjacentTo(b, c)) {
            continue;
          }

          if (graph.getEndpoint(b, a) == Endpoint.ARROW && graph.isUndirectedFromTo(a, c)) {
            if (existsLocalSepsetWithoutDet(b, a, c, test, graph, depth)) {
              continue;
            }

            if (isArrowpointAllowed(a, c, knowledge)) {
              graph.setEndpoint(a, c, Endpoint.ARROW);
              TetradLogger.getInstance()
                  .edgeOriented(SearchLogUtils.edgeOrientedMsg("Meek R1", graph.getEdge(a, c)));
              changed = true;
            }
          } else if (graph.getEndpoint(c, a) == Endpoint.ARROW && graph.isUndirectedFromTo(a, b)) {
            if (existsLocalSepsetWithoutDet(b, a, c, test, graph, depth)) {
              continue;
            }

            if (isArrowpointAllowed(a, b, knowledge)) {
              graph.setEndpoint(a, b, Endpoint.ARROW);
              TetradLogger.getInstance()
                  .edgeOriented(SearchLogUtils.edgeOrientedMsg("Meek R1", graph.getEdge(a, b)));
              changed = true;
            }
          }
        }
      }
    }

    return changed;
  }
  /**
   * Performs step C of the algorithm, as indicated on page xxx of CPS, with the modification that
   * X--W--Y is oriented as X-->W<--Y if W is *determined by* the sepset of (X, Y), rather than W
   * just being *in* the sepset of (X, Y).
   */
  public static void pcdOrientC(
      SepsetMap set, IndependenceTest test, Knowledge knowledge, Graph graph) {
    TetradLogger.getInstance().log("info", "Staring Collider Orientation:");

    List<Node> nodes = graph.getNodes();

    for (Node y : nodes) {
      List<Node> adjacentNodes = graph.getAdjacentNodes(y);

      if (adjacentNodes.size() < 2) {
        continue;
      }

      ChoiceGenerator cg = new ChoiceGenerator(adjacentNodes.size(), 2);
      int[] combination;

      while ((combination = cg.next()) != null) {
        Node x = adjacentNodes.get(combination[0]);
        Node z = adjacentNodes.get(combination[1]);

        // Skip triples that are shielded.
        if (graph.isAdjacentTo(x, z)) {
          continue;
        }

        List<Node> sepset = set.get(x, z);

        if (sepset == null) {
          continue;
        }

        List<Node> augmentedSet = new LinkedList<Node>(sepset);
        augmentedSet.add(y);

        if (test.determines(sepset, y)) {
          continue;
        }
        //
        if (!test.splitDetermines(sepset, x, z) && test.splitDetermines(augmentedSet, x, z)) {
          continue;
        }

        if (!isArrowpointAllowed(x, y, knowledge) || !isArrowpointAllowed(z, y, knowledge)) {
          continue;
        }

        graph.setEndpoint(x, y, Endpoint.ARROW);
        graph.setEndpoint(z, y, Endpoint.ARROW);

        TetradLogger.getInstance()
            .log("colliderOriented", SearchLogUtils.colliderOrientedMsg(x, y, z));
      }
    }

    TetradLogger.getInstance().log("info", "Finishing Collider Orientation.");
  }
  /**
   * Provides methods for estimating a Bayes IM from an existing BayesIM and a discrete dataset
   * using EM (Expectation Maximization). The data columns in the given data must be equal to a
   * variable in the given Bayes IM but the latter may contain variables which don't occur in the
   * dataset (latent variables). The first argument of the constructoris the BayesPm whose graph
   * contains latent and observed variables. The second is the dataset of observed variables;
   * missing value codes may be present.
   */
  public EmBayesEstimator(BayesPm bayesPm, DataSet dataSet) {

    if (bayesPm == null) {
      throw new NullPointerException();
    }

    if (dataSet == null) {
      throw new NullPointerException();
    }

    List<Node> observedVars = new ArrayList<Node>();

    this.bayesPm = bayesPm;
    this.dataSet = dataSet;

    // this.variables = Collections.unmodifiableList(vars);
    graph = bayesPm.getDag();
    this.nodes = new Node[graph.getNumNodes()];

    Iterator<Node> it = graph.getNodes().iterator();

    for (int i = 0; i < this.nodes.length; i++) {
      this.nodes[i] = it.next();
      // System.out.println("node " + i + " " + nodes[i]);
    }

    for (int i = 0; i < this.nodes.length; i++) {
      if (nodes[i].getNodeType() == NodeType.MEASURED) {
        observedVars.add(bayesPm.getVariable(nodes[i]));
      }
    }

    // Make sure variables in dataset are measured variables in the BayesPM
    //        for (Node dataSetVariable : this.dataSet.getVariables()) {
    //            if (!observedVars.contains(dataSetVariable)) {
    //                throw new IllegalArgumentException(
    //                        "Some var in the dataset is not a " +
    //                                "measured variable in the Bayes net");
    //            }
    //        }

    // Make sure all measured variables in the BayesPm are in the discrete dataset
    for (Node observedVar : observedVars) {
      try {
        this.dataSet.getVariable(observedVar.getName());
      } catch (Exception e) {
        throw new IllegalArgumentException(
            "Some observed var in the Bayes net " + "is not in the dataset: " + observedVar);
      }
    }

    findBayesNetObserved(); // Sets bayesPmObs

    initialize();
  }
示例#17
0
  private Graph structure(Graph mim) {
    List<Node> latents = new ArrayList<Node>();

    for (Node node : mim.getNodes()) {
      if (node.getNodeType() == NodeType.LATENT) {
        latents.add(node);
      }
    }

    return mim.subgraph(latents);
  }
示例#18
0
  private Graph restrictToEmpiricalLatents(Graph mimStructure, Graph mimbuildStructure) {
    Graph _mim = new EdgeListGraph(mimStructure);

    for (Node node : mimbuildStructure.getNodes()) {
      if (!mimbuildStructure.containsNode(node)) {
        _mim.removeNode(node);
      }
    }

    return _mim;
  }
  /** Meek's rule R3. If a--b, a--c, a--d, c-->b, c-->b, then orient a-->b. */
  public static boolean meekR3(Graph graph, Knowledge knowledge) {

    List<Node> nodes = graph.getNodes();
    boolean changed = false;

    for (Node a : nodes) {
      List<Node> adjacentNodes = graph.getAdjacentNodes(a);

      if (adjacentNodes.size() < 3) {
        continue;
      }

      for (Node b : adjacentNodes) {
        List<Node> otherAdjacents = new LinkedList<Node>(adjacentNodes);
        otherAdjacents.remove(b);

        if (!graph.isUndirectedFromTo(a, b)) {
          continue;
        }

        ChoiceGenerator cg = new ChoiceGenerator(otherAdjacents.size(), 2);
        int[] combination;

        while ((combination = cg.next()) != null) {
          Node c = otherAdjacents.get(combination[0]);
          Node d = otherAdjacents.get(combination[1]);

          if (graph.isAdjacentTo(c, d)) {
            continue;
          }

          if (!graph.isUndirectedFromTo(a, c)) {
            continue;
          }

          if (!graph.isUndirectedFromTo(a, d)) {
            continue;
          }

          if (graph.isDirectedFromTo(c, b) && graph.isDirectedFromTo(d, b)) {
            if (isArrowpointAllowed(a, b, knowledge)) {
              graph.setEndpoint(a, b, Endpoint.ARROW);
              TetradLogger.getInstance()
                  .edgeOriented(SearchLogUtils.edgeOrientedMsg("Meek R3", graph.getEdge(a, b)));
              changed = true;
              break;
            }
          }
        }
      }
    }

    return changed;
  }
示例#20
0
  public List<Node> findMb(String targetName) {
    Node target = getVariableForName(targetName);

    Pc search = new Pc(test);
    search.setDepth(depth);
    Graph graph = search.search();
    MbUtils.trimToMbNodes(graph, target, false);
    List<Node> mbVariables = graph.getNodes();
    mbVariables.remove(target);

    return mbVariables;
  }
  public static void arrangeByKnowledgeTiers(Graph graph, Knowledge knowledge) {
    if (knowledge.getNumTiers() == 0) {
      throw new IllegalArgumentException("There are no Tiers to arrange.");
    }

    List<Node> nodes = graph.getNodes();
    List<String> varNames = new ArrayList<String>();
    int ySpace = 500 / knowledge.getNumTiers();
    ySpace = ySpace < 50 ? 50 : ySpace;

    for (Node node1 : nodes) {
      varNames.add(node1.getName());
    }

    List<String> notInTier = knowledge.getVarsNotInTier(varNames);

    int x = 0;
    int y = 50 - ySpace;

    if (notInTier.size() > 0) {
      y += ySpace;

      for (String name : notInTier) {
        x += 90;
        Node node = graph.getNode(name);

        if (node != null) {
          node.setCenterX(x);
          node.setCenterY(y);
        }
      }
    }

    for (int i = 0; i < knowledge.getNumTiers(); i++) {
      List<String> tier = knowledge.getTier(i);
      y += ySpace;
      x = -25;

      for (String name : tier) {
        x += 90;
        Node node = graph.getNode(name);

        if (node != null) {
          node.setCenterX(x);
          node.setCenterY(y);
        }
      }
    }
  }
示例#22
0
  private static double characteristicPathLength(Graph g) {
    List<Node> nodes = g.getNodes();
    int total = 0;
    int count = 0;

    for (int i = 0; i < nodes.size(); i++) {
      for (int j = i; j < nodes.size(); j++) {
        int shortest = shortestPath(nodes.get(i), nodes.get(j), g);
        total += shortest;
        count++;
      }
    }

    return total / (double) count;
  }
示例#23
0
  public void testAlternativeGraphs() {

    //        UniformGraphGenerator gen = new UniformGraphGenerator(UniformGraphGenerator.ANY_DAG);
    //        gen.setNumNodes(100);
    //        gen.setMaxEdges(200);
    //        gen.setMaxDegree(30);
    //        gen.setMaxInDegree(30);
    //        gen.setMaxOutDegree(30);
    ////        gen.setNumIterations(3000000);
    //        gen.setResamplingDegree(10);
    //
    //        gen.generate();
    //
    //        Graph graph = gen.getDag();

    Graph graph = weightedRandomGraph(250, 400);

    List<Integer> degreeCounts = new ArrayList<Integer>();
    Map<Integer, Integer> degreeCount = new HashMap<Integer, Integer>();

    for (Node node : graph.getNodes()) {
      int degree = graph.getNumEdges(node);
      degreeCounts.add(degree);

      if (degreeCount.get(degree) == null) {
        degreeCount.put(degree, 0);
      }

      degreeCount.put(degree, degreeCount.get(degree) + 1);
    }

    Collections.sort(degreeCounts);
    System.out.println(degreeCounts);
    List<Integer> _degrees = new ArrayList<Integer>(degreeCount.keySet());
    Collections.sort(_degrees);

    for (int i : _degrees) {
      int j = degreeCount.get(i);
      //            System.out.println(i + " " + j);
      System.out.println(log(i + 1) + " " + log(j));
    }

    System.out.println("\nCPL = " + characteristicPathLength(graph));

    Graph erGraph = erdosRenyiGraph(200, 200);
    System.out.println("\n ER CPL = " + characteristicPathLength(erGraph));
  }
  /**
   * Step C of PC; orients colliders using specified sepset. That is, orients x *-* y *-* z as x *->
   * y <-* z just in case y is in Sepset({x, z}).
   */
  public static void orientCollidersUsingSepsets(SepsetMap set, Knowledge knowledge, Graph graph) {
    TetradLogger.getInstance().log("info", "Starting Collider Orientation:");

    //        verifySepsetIntegrity(set, graph);

    List<Node> nodes = graph.getNodes();

    for (Node a : nodes) {
      List<Node> adjacentNodes = graph.getAdjacentNodes(a);

      if (adjacentNodes.size() < 2) {
        continue;
      }

      ChoiceGenerator cg = new ChoiceGenerator(adjacentNodes.size(), 2);
      int[] combination;

      while ((combination = cg.next()) != null) {
        Node b = adjacentNodes.get(combination[0]);
        Node c = adjacentNodes.get(combination[1]);

        // Skip triples that are shielded.
        if (graph.isAdjacentTo(b, c)) {
          continue;
        }

        List<Node> sepset = set.get(b, c);
        if (sepset != null
            && !sepset.contains(a)
            && isArrowpointAllowed(b, a, knowledge)
            && isArrowpointAllowed(c, a, knowledge)) {
          graph.setEndpoint(b, a, Endpoint.ARROW);
          graph.setEndpoint(c, a, Endpoint.ARROW);
          TetradLogger.getInstance()
              .log("colliderOriented", SearchLogUtils.colliderOrientedMsg(b, a, c, sepset));
        }
      }
    }

    TetradLogger.getInstance().log("info", "Finishing Collider Orientation.");
  }
  /** If */
  public static boolean meekR2(Graph graph, Knowledge knowledge) {
    List<Node> nodes = graph.getNodes();
    boolean changed = false;

    for (Node a : nodes) {
      List<Node> adjacentNodes = graph.getAdjacentNodes(a);

      if (adjacentNodes.size() < 2) {
        continue;
      }

      ChoiceGenerator cg = new ChoiceGenerator(adjacentNodes.size(), 2);
      int[] combination;

      while ((combination = cg.next()) != null) {
        Node b = adjacentNodes.get(combination[0]);
        Node c = adjacentNodes.get(combination[1]);

        if (graph.isDirectedFromTo(b, a)
            && graph.isDirectedFromTo(a, c)
            && graph.isUndirectedFromTo(b, c)) {
          if (isArrowpointAllowed(b, c, knowledge)) {
            graph.setEndpoint(b, c, Endpoint.ARROW);
            TetradLogger.getInstance()
                .edgeOriented(SearchLogUtils.edgeOrientedMsg("Meek R2", graph.getEdge(b, c)));
          }
        } else if (graph.isDirectedFromTo(c, a)
            && graph.isDirectedFromTo(a, b)
            && graph.isUndirectedFromTo(c, b)) {
          if (isArrowpointAllowed(c, b, knowledge)) {
            graph.setEndpoint(c, b, Endpoint.ARROW);
            TetradLogger.getInstance()
                .edgeOriented(SearchLogUtils.edgeOrientedMsg("Meek R2", graph.getEdge(c, b)));
          }
        }
      }
    }

    return changed;
  }
  public static void orientCollidersLocally(
      Knowledge knowledge, Graph graph, IndependenceTest test, int depth, Set<Node> nodesToVisit) {
    TetradLogger.getInstance().log("info", "Starting Collider Orientation:");

    if (nodesToVisit == null) {
      nodesToVisit = new HashSet<Node>(graph.getNodes());
    }

    for (Node a : nodesToVisit) {
      List<Node> adjacentNodes = graph.getAdjacentNodes(a);

      if (adjacentNodes.size() < 2) {
        continue;
      }

      ChoiceGenerator cg = new ChoiceGenerator(adjacentNodes.size(), 2);
      int[] combination;

      while ((combination = cg.next()) != null) {
        Node b = adjacentNodes.get(combination[0]);
        Node c = adjacentNodes.get(combination[1]);

        // Skip triples that are shielded.
        if (graph.isAdjacentTo(b, c)) {
          continue;
        }

        if (isArrowpointAllowed1(b, a, knowledge) && isArrowpointAllowed1(c, a, knowledge)) {
          if (!existsLocalSepsetWith(b, a, c, test, graph, depth)) {
            graph.setEndpoint(b, a, Endpoint.ARROW);
            graph.setEndpoint(c, a, Endpoint.ARROW);
            TetradLogger.getInstance()
                .log("colliderOriented", SearchLogUtils.colliderOrientedMsg(b, a, c));
          }
        }
      }
    }

    TetradLogger.getInstance().log("info", "Finishing Collider Orientation.");
  }
示例#27
0
  private void correlateExogenousVariables() {
    Graph graph = getWorkbench().getGraph();

    if (graph instanceof Dag) {
      JOptionPane.showMessageDialog(
          JOptionUtils.centeringComp(), "Cannot add bidirected edges to DAG's.");
      return;
    }

    List<Node> nodes = graph.getNodes();

    List<Node> exoNodes = new LinkedList<Node>();

    for (int i = 0; i < nodes.size(); i++) {
      Node node = nodes.get(i);
      if (graph.isExogenous(node)) {
        exoNodes.add(node);
      }
    }

    for (int i = 0; i < exoNodes.size(); i++) {

      loop:
      for (int j = i + 1; j < exoNodes.size(); j++) {
        Node node1 = exoNodes.get(i);
        Node node2 = exoNodes.get(j);
        List<Edge> edges = graph.getEdges(node1, node2);

        for (int k = 0; k < edges.size(); k++) {
          Edge edge = edges.get(k);
          if (Edges.isBidirectedEdge(edge)) {
            continue loop;
          }
        }

        graph.addBidirectedEdge(node1, node2);
      }
    }
  }
示例#28
0
  /**
   * Greedy equivalence search: Start from the empty graph, add edges till model is significant.
   * Then start deleting edges till a minimum is achieved.
   *
   * @return the resulting Pattern.
   */
  public Graph search() {

    Graph graph;

    if (initialGraph == null) {
      graph = new EdgeListGraphSingleConnections(getVariables());
    } else {
      graph = new EdgeListGraphSingleConnections(initialGraph);
    }

    fireGraphChange(graph);
    buildIndexing(graph);
    addRequiredEdges(graph);

    topGraphs.clear();

    storeGraph(graph);

    List<Node> nodes = graph.getNodes();

    long start = System.currentTimeMillis();
    score = 0.0;

    // Do forward search.
    fes(graph, nodes);

    // Do backward search.
    bes(graph);

    long endTime = System.currentTimeMillis();
    this.elapsedTime = endTime - start;
    this.logger.log("graph", "\nReturning this graph: " + graph);

    this.logger.log("info", "Elapsed time = " + (elapsedTime) / 1000. + " s");
    this.logger.flush();

    return graph;
  }
示例#29
0
 public List<Node> getNodes() {
   return graph.getNodes();
 }
  /**
   * Transforms a DAG represented in graph <code>graph</code> into a maximally directed pattern
   * (PDAG) by modifying <code>g</code> itself. Based on the algorithm described in Chickering
   * (2002) "Optimal structure identification with greedy search" Journal of Machine Learning
   * Research. It works for both BayesNets and SEMs. R. Silva, June 2004
   */
  public static void dagToPdag(Graph graph) {
    // do topological sort on the nodes
    Graph graphCopy = new EdgeListGraph(graph);
    Node orderedNodes[] = new Node[graphCopy.getNodes().size()];
    int count = 0;
    while (graphCopy.getNodes().size() > 0) {
      Set<Node> exogenousNodes = new HashSet<Node>();

      for (Node next : graphCopy.getNodes()) {
        if (graphCopy.isExogenous(next)) {
          exogenousNodes.add(next);
          orderedNodes[count++] = graph.getNode(next.getName());
        }
      }

      graphCopy.removeNodes(new ArrayList<Node>(exogenousNodes));
    }
    // ordered edges - improvised, inefficient implementation
    count = 0;
    Edge edges[] = new Edge[graph.getNumEdges()];
    boolean edgeOrdered[] = new boolean[graph.getNumEdges()];
    Edge orderedEdges[] = new Edge[graph.getNumEdges()];

    for (Edge edge : graph.getEdges()) {
      edges[count++] = edge;
    }

    for (int i = 0; i < edges.length; i++) {
      edgeOrdered[i] = false;
    }

    while (count > 0) {
      for (Node orderedNode : orderedNodes) {
        for (int k = orderedNodes.length - 1; k >= 0; k--) {
          for (int q = 0; q < edges.length; q++) {
            if (!edgeOrdered[q]
                && edges[q].getNode1() == orderedNodes[k]
                && edges[q].getNode2() == orderedNode) {
              edgeOrdered[q] = true;
              orderedEdges[orderedEdges.length - count] = edges[q];
              count--;
            }
          }
        }
      }
    }

    // label edges
    boolean compelledEdges[] = new boolean[graph.getNumEdges()];
    boolean reversibleEdges[] = new boolean[graph.getNumEdges()];
    for (int i = 0; i < graph.getNumEdges(); i++) {
      compelledEdges[i] = false;
      reversibleEdges[i] = false;
    }
    for (int i = 0; i < graph.getNumEdges(); i++) {
      if (compelledEdges[i] || reversibleEdges[i]) {
        continue;
      }
      Node x = orderedEdges[i].getNode1();
      Node y = orderedEdges[i].getNode2();
      for (int j = 0; j < orderedEdges.length; j++) {
        if (orderedEdges[j].getNode2() == x && compelledEdges[j]) {
          Node w = orderedEdges[j].getNode1();
          if (!graph.isParentOf(w, y)) {
            for (int k = 0; k < orderedEdges.length; k++) {
              if (orderedEdges[k].getNode2() == y) {
                compelledEdges[k] = true;
                break;
              }
            }
          } else {
            for (int k = 0; k < orderedEdges.length; k++) {
              if (orderedEdges[k].getNode1() == w && orderedEdges[k].getNode2() == y) {
                compelledEdges[k] = true;
                break;
              }
            }
          }
        }
        if (compelledEdges[i]) {
          break;
        }
      }
      if (compelledEdges[i]) {
        continue;
      }
      boolean foundZ = false;

      for (Edge orderedEdge : orderedEdges) {
        Node z = orderedEdge.getNode1();
        if (z != x && orderedEdge.getNode2() == y && !graph.isParentOf(z, x)) {
          compelledEdges[i] = true;
          for (int k = i + 1; k < graph.getNumEdges(); k++) {
            if (orderedEdges[k].getNode2() == y && !reversibleEdges[k]) {
              compelledEdges[k] = true;
            }
          }
          foundZ = true;
          break;
        }
      }

      if (!foundZ) {
        reversibleEdges[i] = true;

        for (int j = i + 1; j < orderedEdges.length; j++) {
          if (!compelledEdges[j] && orderedEdges[j].getNode2() == y) {
            reversibleEdges[j] = true;
          }
        }
      }
    }

    // undirect edges that are reversible
    for (int i = 0; i < reversibleEdges.length; i++) {
      if (reversibleEdges[i]) {
        graph.setEndpoint(orderedEdges[i].getNode1(), orderedEdges[i].getNode2(), Endpoint.TAIL);
        graph.setEndpoint(orderedEdges[i].getNode2(), orderedEdges[i].getNode1(), Endpoint.TAIL);
      }
    }
  }