Пример #1
0
  private boolean existsUnblockedSemiDirectedPath(Node from, Node to, List<Node> cond, Graph G) {
    Queue<Node> Q = new LinkedList<Node>();
    Set<Node> V = new HashSet<Node>();
    Q.offer(from);
    V.add(from);

    while (!Q.isEmpty()) {
      Node t = Q.remove();
      if (t == to) return true;

      for (Node u : G.getAdjacentNodes(t)) {
        Edge edge = G.getEdge(t, u);
        Node c = Edges.traverseSemiDirected(t, edge);
        if (c == null) continue;
        if (cond.contains(c)) continue;
        if (c == to) return true;

        if (!V.contains(c)) {
          V.add(c);
          Q.offer(c);
        }
      }
    }

    return false;
  }
Пример #2
0
  /**
   * Forward equivalence search.
   *
   * @param graph The graph in the state prior to the forward equivalence search.
   */
  private void fes(Graph graph, List<Node> nodes) {
    TetradLogger.getInstance().log("info", "** FORWARD EQUIVALENCE SEARCH");

    lookupArrows = new HashMap<OrderedPair, Set<Arrow>>();

    initializeArrowsForward(nodes);

    while (!sortedArrows.isEmpty()) {
      Arrow arrow = sortedArrows.first();
      sortedArrows.remove(arrow);

      Node x = arrow.getX();
      Node y = arrow.getY();

      clearArrow(x, y);

      if (graph.isAdjacentTo(x, y)) {
        continue;
      }

      if (!validInsert(x, y, arrow.getHOrT(), arrow.getNaYX(), graph)) {
        continue;
      }

      List<Node> t = arrow.getHOrT();
      double bump = arrow.getBump();

      Set<Edge> edges = graph.getEdges();

      insert(x, y, t, graph, bump);
      score += bump;
      rebuildPattern(graph);

      // Try to avoid duplicating scoring calls. First clear out all of the edges that need to be
      // changed,
      // then change them, checking to see if they're already been changed. I know, roundabout, but
      // there's
      // a performance boost.
      for (Edge edge : graph.getEdges()) {
        if (!edges.contains(edge)) {
          reevaluateForward(graph, nodes, edge.getNode1(), edge.getNode2());
        }
      }

      storeGraph(graph);
    }
  }
  private boolean pure(Set<Integer> quartet, List<Integer> variables) {
    if (quartetVanishes(quartet)) {
      for (int o : variables) {
        if (quartet.contains(o)) continue;

        for (int p : quartet) {
          Set<Integer> _quartet = new HashSet<Integer>(quartet);
          _quartet.remove(p);
          _quartet.add(o);

          if (!quartetVanishes(_quartet)) {
            return false;
          }
        }
      }

      return significant(new ArrayList<Integer>(quartet));
    }

    return false;
  }
Пример #4
0
  public void setNodeExpression(Node node, String expressionString) throws ParseException {
    if (node == null) {
      throw new NullPointerException("Node was null.");
    }

    if (expressionString == null) {
      //            return;
      throw new NullPointerException("Expression string was null.");
    }

    // Parse the expression. This could throw an ParseException, but that exception needs to handed
    // up the
    // chain, because the interface will need it.
    ExpressionParser parser = new ExpressionParser();
    Expression expression = parser.parseExpression(expressionString);
    List<String> parameterNames = parser.getParameters();

    // Make a list of parent names.
    List<Node> parents = this.graph.getParents(node);
    List<String> parentNames = new LinkedList<>();

    for (Node parent : parents) {
      parentNames.add(parent.getName());
    }

    //        List<String> _params = new ArrayList<String>(parameterNames);
    //        _params.retainAll(variableNames);
    //        _params.removeAll(parentNames);
    //
    //        if (!_params.isEmpty()) {
    //            throw new IllegalArgumentException("Conditioning on a variable other than the
    // parents: " + node);
    //        }

    // Make a list of parameter names, by removing from the parser's list of freeParameters any that
    // correspond
    // to parent variables. If there are any variable names (including error terms) that are not
    // among the list of
    // parents, that's a time to throw an exception. We must respect the graph! (We will not
    // complain if any parents
    // are missing.)
    parameterNames.removeAll(variableNames);

    for (Node variable : nodes) {
      if (parameterNames.contains(variable.getName())) {
        parameterNames.remove(variable.getName());
        //                throw new IllegalArgumentException("The list of parameter names may not
        // include variables: " + variable.getName());
      }
    }

    // Remove old parameter references.
    List<String> parametersToRemove = new LinkedList<>();

    for (String parameter : this.referencedParameters.keySet()) {
      Set<Node> nodes = this.referencedParameters.get(parameter);

      if (nodes.contains(node)) {
        nodes.remove(node);
      }

      if (nodes.isEmpty()) {
        parametersToRemove.add(parameter);
      }
    }

    for (String parameter : parametersToRemove) {
      this.referencedParameters.remove(parameter);
      this.parameterExpressions.remove(parameter);
      this.parameterExpressionStrings.remove(parameter);
      this.parameterEstimationInitializationExpressions.remove(parameter);
      this.parameterEstimationInitializationExpressionStrings.remove(parameter);
    }

    // Add new parameter references.
    for (String parameter : parameterNames) {
      if (this.referencedParameters.get(parameter) == null) {
        this.referencedParameters.put(parameter, new HashSet<Node>());
      }

      Set<Node> nodes = this.referencedParameters.get(parameter);
      nodes.add(node);

      setSuitableParameterDistribution(parameter);
    }

    // Remove old node references.
    List<Node> nodesToRemove = new LinkedList<>();

    for (Node _node : this.referencedNodes.keySet()) {
      Set<Node> nodes = this.referencedNodes.get(_node);

      if (nodes.contains(node)) {
        nodes.remove(node);
      }

      if (nodes.isEmpty()) {
        nodesToRemove.add(_node);
      }
    }

    for (Node _node : nodesToRemove) {
      this.referencedNodes.remove(_node);
    }

    // Add new freeParameters.
    for (String variableString : variableNames) {
      Node _node = getNode(variableString);

      if (this.referencedNodes.get(_node) == null) {
        this.referencedNodes.put(_node, new HashSet<Node>());
      }

      for (String s : parentNames) {
        if (s.equals(variableString)) {
          Set<Node> nodes = this.referencedNodes.get(_node);
          nodes.add(node);
        }
      }
    }

    // Finally, save the parsed expression and the original string that the user entered. No need to
    // annoy
    // the user by changing spacing.
    nodeExpressions.put(node, expression);
    nodeExpressionStrings.put(node, expressionString);
  }
Пример #5
0
  @Test
  public void test1() {
    GeneralizedSemPm pm = makeTypicalPm();

    print(pm);

    Node x1 = pm.getNode("X1");
    Node x2 = pm.getNode("X2");
    Node x3 = pm.getNode("X3");
    Node x4 = pm.getNode("X4");
    Node x5 = pm.getNode("X5");

    SemGraph graph = pm.getGraph();

    List<Node> variablesNodes = pm.getVariableNodes();
    print(variablesNodes);

    List<Node> errorNodes = pm.getErrorNodes();
    print(errorNodes);

    try {
      pm.setNodeExpression(x1, "cos(B1) + E_X1");
      print(pm);

      String b1 = "B1";
      String b2 = "B2";
      String b3 = "B3";

      Set<Node> nodes = pm.getReferencingNodes(b1);

      assertTrue(nodes.contains(x1));
      assertTrue(!nodes.contains(x2) && !nodes.contains(x2));

      Set<String> referencedParameters = pm.getReferencedParameters(x3);

      print("Parameters referenced by X3 are: " + referencedParameters);

      assertTrue(referencedParameters.contains(b1) && referencedParameters.contains(b2));
      assertTrue(!(referencedParameters.contains(b1) && referencedParameters.contains(b3)));

      Node e_x3 = pm.getNode("E_X3");
      //
      for (Node node : pm.getNodes()) {
        Set<Node> referencingNodes = pm.getReferencingNodes(node);
        print("Nodes referencing " + node + " are: " + referencingNodes);
      }

      for (Node node : pm.getVariableNodes()) {
        Set<Node> referencingNodes = pm.getReferencedNodes(node);
        print("Nodes referenced by " + node + " are: " + referencingNodes);
      }

      Set<Node> referencingX3 = pm.getReferencingNodes(x3);
      assertTrue(referencingX3.contains(x4));
      assertTrue(!referencingX3.contains(x5));

      Set<Node> referencedByX3 = pm.getReferencedNodes(x3);
      assertTrue(
          referencedByX3.contains(x1)
              && referencedByX3.contains(x2)
              && referencedByX3.contains(e_x3)
              && !referencedByX3.contains(x4));

      pm.setNodeExpression(x5, "a * E^X2 + X4 + E_X5");

      Node e_x5 = pm.getErrorNode(x5);

      graph.setShowErrorTerms(true);
      assertTrue(e_x5.equals(graph.getExogenous(x5)));

      pm.setNodeExpression(e_x5, "Beta(3, 5)");

      print(pm);

      assertEquals("Split(-1.5,-.5,.5,1.5)", pm.getParameterExpressionString(b1));
      pm.setParameterExpression(b1, "N(0, 2)");
      assertEquals("N(0, 2)", pm.getParameterExpressionString(b1));

      GeneralizedSemIm im = new GeneralizedSemIm(pm);

      print(im);

      DataSet dataSet = im.simulateDataAvoidInfinity(10, false);

      print(dataSet);

    } catch (ParseException e) {
      e.printStackTrace();
    }
  }
  private Set<Set<Integer>> finishESeeds(Set<Set<Integer>> ESeeds) {
    log("Growing Effect Seeds.", true);
    Set<Set<Integer>> grown = new HashSet<Set<Integer>>();

    List<Integer> _variables = new ArrayList<Integer>();
    for (int i = 0; i < variables.size(); i++) _variables.add(i);

    // Lax grow phase with speedup.
    if (algType == AlgType.lax) {
      Set<Integer> t = new HashSet<Integer>();
      int count = 0;
      int total = ESeeds.size();

      do {
        if (!ESeeds.iterator().hasNext()) {
          break;
        }

        Set<Integer> cluster = ESeeds.iterator().next();
        Set<Integer> _cluster = new HashSet<Integer>(cluster);

        if (extraShuffle) {
          Collections.shuffle(_variables);
        }

        for (int o : _variables) {
          if (_cluster.contains(o)) continue;

          List<Integer> _cluster2 = new ArrayList<Integer>(_cluster);
          int rejected = 0;
          int accepted = 0;

          ChoiceGenerator gen = new ChoiceGenerator(_cluster2.size(), 2);
          int[] choice;

          while ((choice = gen.next()) != null) {
            int n1 = _cluster2.get(choice[0]);
            int n2 = _cluster2.get(choice[1]);

            t.clear();
            t.add(n1);
            t.add(n2);
            t.add(o);

            if (!ESeeds.contains(t)) {
              rejected++;
            } else {
              accepted++;
            }
          }

          if (rejected > accepted) {
            continue;
          }

          _cluster.add(o);

          //                    if (!(avgSumLnP(new ArrayList<Integer>(_cluster)) > -10)) {
          //                        _cluster.remove(o);
          //                    }
        }

        // This takes out all pure clusters that are subsets of _cluster.
        ChoiceGenerator gen2 = new ChoiceGenerator(_cluster.size(), 3);
        int[] choice2;
        List<Integer> _cluster3 = new ArrayList<Integer>(_cluster);

        while ((choice2 = gen2.next()) != null) {
          int n1 = _cluster3.get(choice2[0]);
          int n2 = _cluster3.get(choice2[1]);
          int n3 = _cluster3.get(choice2[2]);

          t.clear();
          t.add(n1);
          t.add(n2);
          t.add(n3);

          ESeeds.remove(t);
        }

        if (verbose) {
          System.out.println(
              "Grown "
                  + (++count)
                  + " of "
                  + total
                  + ": "
                  + variablesForIndices(new ArrayList<Integer>(_cluster)));
        }
        grown.add(_cluster);
      } while (!ESeeds.isEmpty());
    }

    // Lax grow phase without speedup.
    if (algType == AlgType.laxWithSpeedup) {
      int count = 0;
      int total = ESeeds.size();

      // Optimized lax version of grow phase.
      for (Set<Integer> cluster : new HashSet<Set<Integer>>(ESeeds)) {
        Set<Integer> _cluster = new HashSet<Integer>(cluster);

        if (extraShuffle) {
          Collections.shuffle(_variables);
        }

        for (int o : _variables) {
          if (_cluster.contains(o)) continue;

          List<Integer> _cluster2 = new ArrayList<Integer>(_cluster);
          int rejected = 0;
          int accepted = 0;
          //
          ChoiceGenerator gen = new ChoiceGenerator(_cluster2.size(), 2);
          int[] choice;

          while ((choice = gen.next()) != null) {
            int n1 = _cluster2.get(choice[0]);
            int n2 = _cluster2.get(choice[1]);

            Set<Integer> triple = triple(n1, n2, o);

            if (!ESeeds.contains(triple)) {
              rejected++;
            } else {
              accepted++;
            }
          }
          //
          if (rejected > accepted) {
            continue;
          }

          //                    System.out.println("Adding " + o  + " to " + cluster);
          _cluster.add(o);
        }

        for (Set<Integer> c : new HashSet<Set<Integer>>(ESeeds)) {
          if (_cluster.containsAll(c)) {
            ESeeds.remove(c);
          }
        }

        if (verbose) {
          System.out.println("Grown " + (++count) + " of " + total + ": " + _cluster);
        }

        grown.add(_cluster);
      }
    }

    // Strict grow phase.
    if (algType == AlgType.strict) {
      Set<Integer> t = new HashSet<Integer>();
      int count = 0;
      int total = ESeeds.size();

      do {
        if (!ESeeds.iterator().hasNext()) {
          break;
        }

        Set<Integer> cluster = ESeeds.iterator().next();
        Set<Integer> _cluster = new HashSet<Integer>(cluster);

        if (extraShuffle) {
          Collections.shuffle(_variables);
        }

        VARIABLES:
        for (int o : _variables) {
          if (_cluster.contains(o)) continue;

          List<Integer> _cluster2 = new ArrayList<Integer>(_cluster);

          ChoiceGenerator gen = new ChoiceGenerator(_cluster2.size(), 2);
          int[] choice;

          while ((choice = gen.next()) != null) {
            int n1 = _cluster2.get(choice[0]);
            int n2 = _cluster2.get(choice[1]);

            t.clear();
            t.add(n1);
            t.add(n2);
            t.add(o);

            if (!ESeeds.contains(t)) {
              continue VARIABLES;
            }

            //                        if (avgSumLnP(new ArrayList<Integer>(t)) < -10) continue
            // CLUSTER;
          }

          _cluster.add(o);
        }

        // This takes out all pure clusters that are subsets of _cluster.
        ChoiceGenerator gen2 = new ChoiceGenerator(_cluster.size(), 3);
        int[] choice2;
        List<Integer> _cluster3 = new ArrayList<Integer>(_cluster);

        while ((choice2 = gen2.next()) != null) {
          int n1 = _cluster3.get(choice2[0]);
          int n2 = _cluster3.get(choice2[1]);
          int n3 = _cluster3.get(choice2[2]);

          t.clear();
          t.add(n1);
          t.add(n2);
          t.add(n3);

          ESeeds.remove(t);
        }

        if (verbose) {
          System.out.println("Grown " + (++count) + " of " + total + ": " + _cluster);
        }
        grown.add(_cluster);
      } while (!ESeeds.isEmpty());
    }

    // Optimized pick phase.
    log("Choosing among grown Effect Clusters.", true);

    for (Set<Integer> l : grown) {
      ArrayList<Integer> _l = new ArrayList<Integer>(l);
      Collections.sort(_l);
      if (verbose) {
        log("Grown: " + variablesForIndices(_l), false);
      }
    }

    Set<Set<Integer>> out = new HashSet<Set<Integer>>();

    List<Set<Integer>> list = new ArrayList<Set<Integer>>(grown);

    //        final Map<Set<Integer>, Double> pValues = new HashMap<Set<Integer>, Double>();
    //
    //        for (Set<Integer> o : grown) {
    //            pValues.put(o, getP(new ArrayList<Integer>(o)));
    //        }

    Collections.sort(
        list,
        new Comparator<Set<Integer>>() {
          @Override
          public int compare(Set<Integer> o1, Set<Integer> o2) {
            //                if (o1.size() == o2.size()) {
            //                    double chisq1 = pValues.get(o1);
            //                    double chisq2 = pValues.get(o2);
            //                    return Double.compare(chisq2, chisq1);
            //                }

            return o2.size() - o1.size();
          }
        });

    //        for (Set<Integer> o : list) {
    //            if (pValues.get(o) < alpha) continue;
    //            System.out.println(variablesForIndices(new ArrayList<Integer>(o)) + "  p = " +
    // pValues.get(o));
    //        }

    Set<Integer> all = new HashSet<Integer>();

    CLUSTER:
    for (Set<Integer> cluster : list) {
      //            if (pValues.get(cluster) < alpha) continue;

      for (Integer i : cluster) {
        if (all.contains(i)) continue CLUSTER;
      }

      out.add(cluster);

      //            if (getPMulticluster(out) < alpha) {
      //                out.remove(cluster);
      //                continue;
      //            }

      all.addAll(cluster);
    }

    return out;
  }
  private Void findSeeds() {
    Tetrad tetrad = null;
    List<Node> empty = new ArrayList();
    if (variables.size() < 4) {
      Set<Set<Integer>> ESeeds = new HashSet<Set<Integer>>();
    }

    Map<Node, Set<Node>> adjacencies;

    if (depth == -2) {
      adjacencies = new HashMap<Node, Set<Node>>();

      for (Node node : variables) {
        HashSet<Node> _nodes = new HashSet<Node>(variables);
        _nodes.remove(node);
        adjacencies.put(node, _nodes);
      }
    } else {
      //            System.out.println("Running PC adjacency search...");
      Graph graph = new EdgeListGraph(variables);
      Fas fas = new Fas(graph, indTest);
      fas.setVerbose(false);
      fas.setDepth(depth); // 1?
      adjacencies = fas.searchMapOnly();
      //            System.out.println("...done.");
    }

    List<Integer> allVariables = new ArrayList<Integer>();
    for (int i = 0; i < variables.size(); i++) allVariables.add(i);

    log("Finding seeds.", true);

    ChoiceGenerator gen = new ChoiceGenerator(allVariables.size(), 3);
    int[] choice;
    CHOICE:
    while ((choice = gen.next()) != null) {
      int n1 = allVariables.get(choice[0]);
      int n2 = allVariables.get(choice[1]);
      int n3 = allVariables.get(choice[2]);
      Node v1 = variables.get(choice[0]);
      Node v2 = variables.get(choice[1]);
      Node v3 = variables.get(choice[2]);

      Set<Integer> triple = triple(n1, n2, n3);

      if (!clique(triple, adjacencies)) {
        continue;
      }

      boolean EPure = true;
      boolean CPure1 = true;
      boolean CPure2 = true;
      boolean CPure3 = true;

      for (int o : allVariables) {
        if (triple.contains(o)) {
          continue;
        }

        Node v4 = variables.get(o);
        tetrad = new Tetrad(v1, v2, v3, v4);

        if (deltaTest.getPValue(tetrad) > alpha) {
          EPure = false;
          if (indTest.isDependent(v1, v4, empty)) {
            CPure1 = false;
          }
          if (indTest.isDependent(v2, v4, empty)) {
            CPure2 = false;
          }
        }
        tetrad = new Tetrad(v1, v3, v2, v4);
        if (deltaTest.getPValue(tetrad) > alpha) {
          EPure = false;
          if (indTest.isDependent(v3, v4, empty)) {
            CPure3 = false;
          }
        }

        if (!(EPure || CPure1 || CPure2 || CPure3)) {
          continue CHOICE;
        }
      }

      HashSet<Integer> _cluster = new HashSet<Integer>(triple);

      if (verbose) {
        log("++" + variablesForIndices(new ArrayList<Integer>(triple)), false);
      }

      if (EPure) {
        ESeeds.add(_cluster);
      }
      if (!EPure) {
        if (CPure1) {
          Set<Integer> _cluster1 = new HashSet<Integer>(n2, n3);
          _cluster1.addAll(CSeeds.get(n1));
          CSeeds.set(n1, _cluster1);
        }
        if (CPure2) {
          Set<Integer> _cluster2 = new HashSet<Integer>(n1, n3);
          _cluster2.addAll(CSeeds.get(n2));
          CSeeds.set(n2, _cluster2);
        }
        if (CPure3) {
          Set<Integer> _cluster3 = new HashSet<Integer>(n1, n2);
          _cluster3.addAll(CSeeds.get(n3));
          CSeeds.set(n3, _cluster3);
        }
      }
    }
    return null;
  }
  // Trying to optimize the search for 4-cliques a bit.
  private Set<Set<Integer>> findPureClusters2(
      List<Integer> _variables, Map<Node, Set<Node>> adjacencies) {
    System.out.println("Original variables = " + variables);

    Set<Set<Integer>> clusters = new HashSet<Set<Integer>>();
    List<Integer> allVariables = new ArrayList<Integer>();
    Set<Node> foundVariables = new HashSet<Node>();
    for (int i = 0; i < this.variables.size(); i++) allVariables.add(i);

    for (int x : _variables) {
      Node nodeX = variables.get(x);
      if (foundVariables.contains(nodeX)) continue;

      List<Node> adjX = new ArrayList<Node>(adjacencies.get(nodeX));
      adjX.removeAll(foundVariables);

      if (adjX.size() < 3) continue;

      for (Node nodeY : adjX) {
        if (foundVariables.contains(nodeY)) continue;

        List<Node> commonXY = new ArrayList<Node>(adjacencies.get(nodeY));
        commonXY.retainAll(adjX);
        commonXY.removeAll(foundVariables);

        for (Node nodeZ : commonXY) {
          if (foundVariables.contains(nodeZ)) continue;

          List<Node> commonXZ = new ArrayList<Node>(commonXY);
          commonXZ.retainAll(adjacencies.get(nodeZ));
          commonXZ.removeAll(foundVariables);

          for (Node nodeW : commonXZ) {
            if (foundVariables.contains(nodeW)) continue;

            if (!adjacencies.get(nodeY).contains(nodeW)) {
              continue;
            }

            int y = variables.indexOf(nodeY);
            int w = variables.indexOf(nodeW);
            int z = variables.indexOf(nodeZ);

            Set<Integer> cluster = quartet(x, y, z, w);

            // Note that purity needs to be assessed with respect to all of the variables in order
            // to
            // remove all latent-measure impurities between pairs of latents.
            if (pure(cluster, allVariables)) {

              O:
              for (int o : _variables) {
                if (cluster.contains(o)) continue;
                cluster.add(o);

                if (!clique(cluster, adjacencies)) {
                  cluster.remove(o);
                  continue O;
                }

                //                                if (!allVariablesDependent(cluster)) {
                //                                    cluster.remove(o);
                //                                    continue O;
                //                                }

                List<Integer> _cluster = new ArrayList<Integer>(cluster);

                ChoiceGenerator gen2 = new ChoiceGenerator(_cluster.size(), 4);
                int[] choice2;
                int count = 0;

                while ((choice2 = gen2.next()) != null) {
                  int x2 = _cluster.get(choice2[0]);
                  int y2 = _cluster.get(choice2[1]);
                  int z2 = _cluster.get(choice2[2]);
                  int w2 = _cluster.get(choice2[3]);

                  Set<Integer> quartet = quartet(x2, y2, z2, w2);

                  // Optimizes for large clusters.
                  if (quartet.contains(o)) {
                    if (++count > 2) continue O;
                  }

                  if (quartet.contains(o) && !pure(quartet, allVariables)) {
                    cluster.remove(o);
                    continue O;
                  }
                }
              }

              System.out.println(
                  "Cluster found: " + variablesForIndices(new ArrayList<Integer>(cluster)));
              clusters.add(cluster);
              foundVariables.addAll(variablesForIndices(new ArrayList<Integer>(cluster)));
            }
          }
        }
      }
    }

    return clusters;
  }
  // Finds clusters of size 4 or higher.
  private Set<Set<Integer>> findPureClusters(
      List<Integer> _variables, Map<Node, Set<Node>> adjacencies) {
    //        System.out.println("Original variables = " + variables);

    Set<Set<Integer>> clusters = new HashSet<Set<Integer>>();
    List<Integer> allVariables = new ArrayList<Integer>();
    for (int i = 0; i < this.variables.size(); i++) allVariables.add(i);

    VARIABLES:
    while (!_variables.isEmpty()) {
      if (_variables.size() < 4) break;

      for (int x : _variables) {
        Node nodeX = variables.get(x);
        List<Node> adjX = new ArrayList<Node>(adjacencies.get(nodeX));
        adjX.retainAll(variablesForIndices(new ArrayList<Integer>(_variables)));

        for (Node node : new ArrayList<Node>(adjX)) {
          if (adjacencies.get(node).size() < 3) {
            adjX.remove(node);
          }
        }

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

        ChoiceGenerator gen = new ChoiceGenerator(adjX.size(), 3);
        int[] choice;

        while ((choice = gen.next()) != null) {
          Node nodeY = adjX.get(choice[0]);
          Node nodeZ = adjX.get(choice[1]);
          Node nodeW = adjX.get(choice[2]);

          int y = variables.indexOf(nodeY);
          int w = variables.indexOf(nodeW);
          int z = variables.indexOf(nodeZ);

          Set<Integer> cluster = quartet(x, y, z, w);

          if (!clique(cluster, adjacencies)) {
            continue;
          }

          // Note that purity needs to be assessed with respect to all of the variables in order to
          // remove all latent-measure impurities between pairs of latents.
          if (pure(cluster, allVariables)) {

            //                        Collections.shuffle(_variables);

            O:
            for (int o : _variables) {
              if (cluster.contains(o)) continue;
              cluster.add(o);
              List<Integer> _cluster = new ArrayList<Integer>(cluster);

              if (!clique(cluster, adjacencies)) {
                cluster.remove(o);
                continue O;
              }

              //                            if (!allVariablesDependent(cluster)) {
              //                                cluster.remove(o);
              //                                continue O;
              //                            }

              ChoiceGenerator gen2 = new ChoiceGenerator(_cluster.size(), 4);
              int[] choice2;
              int count = 0;

              while ((choice2 = gen2.next()) != null) {
                int x2 = _cluster.get(choice2[0]);
                int y2 = _cluster.get(choice2[1]);
                int z2 = _cluster.get(choice2[2]);
                int w2 = _cluster.get(choice2[3]);

                Set<Integer> quartet = quartet(x2, y2, z2, w2);

                // Optimizes for large clusters.
                if (quartet.contains(o)) {
                  if (++count > 50) continue O;
                }

                if (quartet.contains(o) && !pure(quartet, allVariables)) {
                  cluster.remove(o);
                  continue O;
                }
              }
            }

            System.out.println(
                "Cluster found: " + variablesForIndices(new ArrayList<Integer>(cluster)));
            clusters.add(cluster);
            _variables.removeAll(cluster);

            continue VARIABLES;
          }
        }
      }

      break;
    }

    return clusters;
  }