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;
}
/**
* 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;
}
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);
}
@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;
}
