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;
}
/**
* 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 Set<Integer> triple(int n1, int n2, int n3) {
Set<Integer> triple = new HashSet<Integer>();
triple.add(n1);
triple.add(n2);
triple.add(n3);
if (triple.size() < 3)
throw new IllegalArgumentException(
"Triple elements must be unique: <" + n1 + ", " + n2 + ", " + n3 + ">");
return triple;
}
private Set<Integer> quartet(int x, int y, int z, int w) {
Set<Integer> set = new HashSet<Integer>();
set.add(x);
set.add(y);
set.add(z);
set.add(w);
if (set.size() < 4)
throw new IllegalArgumentException(
"Quartet elements must be unique: <" + x + ", " + y + ", " + z + ", " + w + ">");
return set;
}
/** Get a graph and direct only the unshielded colliders. */
public static void basicPattern(Graph graph) {
Set<Edge> undirectedEdges = new HashSet<Edge>();
NEXT_EDGE:
for (Edge edge : graph.getEdges()) {
Node head = null, tail = null;
if (edge.getEndpoint1() == Endpoint.ARROW && edge.getEndpoint2() == Endpoint.TAIL) {
head = edge.getNode1();
tail = edge.getNode2();
} else if (edge.getEndpoint2() == Endpoint.ARROW && edge.getEndpoint1() == Endpoint.TAIL) {
head = edge.getNode2();
tail = edge.getNode1();
}
if (head != null) {
for (Node node : graph.getParents(head)) {
if (node != tail && !graph.isAdjacentTo(tail, node)) {
continue NEXT_EDGE;
}
}
undirectedEdges.add(edge);
}
}
for (Edge nextUndirected : undirectedEdges) {
Node node1 = nextUndirected.getNode1(), node2 = nextUndirected.getNode2();
graph.removeEdge(nextUndirected);
graph.addUndirectedEdge(node1, node2);
}
}
/** Adds the given variable name to knowledge. Duplicates are ignored. */
public void addVariable(String varName) {
if (!namesToVars.containsKey(varName) && checkVarName(varName)) {
MyNode e = new MyNode(varName);
myNodes.add(e);
namesToVars.put(varName, e);
}
}
public Set<Edge> getAdjacencies() {
Set<Edge> adjacencies = new HashSet<Edge>();
for (Edge edge : graph.getEdges()) {
adjacencies.add(edge);
}
return adjacencies;
}
private Set<List<Set<Integer>>> combineClusters(
Set<Set<Integer>> ESeeds, List<Set<Integer>> CSeeds) {
Set<Set<Integer>> EClusters = finishESeeds(ESeeds);
Set<Integer> Cs = new HashSet();
for (int i = 0; i < variables.size(); i++) Cs.add(i);
Set<Integer> Es = new HashSet();
for (Set<Integer> ECluster : EClusters) Es.addAll(ECluster);
Cs.removeAll(Es);
List<List<Set<Integer>>> Clusters = new ArrayList();
for (Set<Integer> ECluster : EClusters) {
List<Set<Integer>> newCluster = new ArrayList<Set<Integer>>();
newCluster.add(1, ECluster);
Clusters.add(newCluster);
}
List<Set<Integer>> EClustersArray = new ArrayList<Set<Integer>>();
for (Set<Integer> ECluster : EClusters) EClustersArray.add(ECluster);
for (Integer c : Cs) {
int match = -1;
int overlap = 0;
boolean pass = false;
for (int i = 0; i < EClusters.size(); i++) {
Set<Integer> ECluster = EClustersArray.get(i);
Set<Integer> intersection = ECluster;
intersection.retainAll(CSeeds.get(c));
int _overlap = intersection.size();
if (_overlap > overlap) {
overlap = _overlap;
match = i;
if (overlap / ECluster.size() > CIparameter) {
pass = true;
}
}
}
if (pass) {
List<Set<Integer>> modCluster = new ArrayList<Set<Integer>>();
Set<Integer> newCs = Clusters.get(match).get(0);
newCs.add(c);
modCluster.add(newCs);
modCluster.add(EClustersArray.get(match));
Clusters.set(match, modCluster);
}
}
Set<List<Set<Integer>>> ClusterSet = new HashSet<List<Set<Integer>>>(Clusters);
return ClusterSet;
}
/** Evaluate the Insert(X, Y, T) operator (Definition 12 from Chickering, 2002). */
private double insertEval(Node x, Node y, List<Node> t, List<Node> naYX, Graph graph) {
Set<Node> set1 = new HashSet<Node>(naYX);
set1.addAll(t);
List<Node> paY = graph.getParents(y);
set1.addAll(paY);
Set<Node> set2 = new HashSet<Node>(set1);
set1.add(x);
return scoreGraphChange(y, set1, set2);
}
/**
* @param node the node doing the referencing.
* @return the freeParameters referenced by the given variable (variable node or error node).
*/
public Set<String> getReferencedParameters(Node node) {
Set<String> parameters = new HashSet<>();
for (String parameter : this.referencedParameters.keySet()) {
if (this.referencedParameters.get(parameter).contains(node)) {
parameters.add(parameter);
}
}
return parameters;
}
/**
* @param node the node doing the referencing.
* @return the variables referenced by the expression for the given node (variable node or error
* node.
*/
public Set<Node> getReferencedNodes(Node node) {
Set<Node> nodes = new HashSet<>();
for (Node _node : this.referencedNodes.keySet()) {
if (this.referencedNodes.get(_node).contains(node)) {
nodes.add(_node);
}
}
return nodes;
}
private void addLookupArrow(Node i, Node j, Arrow arrow) {
OrderedPair<Node> pair = new OrderedPair<Node>(i, j);
Set<Arrow> arrows = lookupArrows.get(pair);
if (arrows == null) {
arrows = new HashSet<Arrow>();
lookupArrows.put(pair, arrows);
}
arrows.add(arrow);
}
private Set<String> split(String spec) {
String[] tokens = spec.split(",");
Set<String> _tokens = new HashSet<>();
for (String _token : tokens) {
if (!_token.trim().equals("")) {
_tokens.add(_token);
}
}
return _tokens;
}
public static List<Set<Node>> powerSet(List<Node> nodes) {
List<Set<Node>> subsets = new ArrayList<Set<Node>>();
int total = (int) Math.pow(2, nodes.size());
for (int i = 0; i < total; i++) {
Set<Node> newSet = new HashSet<Node>();
String selection = Integer.toBinaryString(i);
for (int j = selection.length() - 1; j >= 0; j--) {
if (selection.charAt(j) == '1') {
newSet.add(nodes.get(selection.length() - j - 1));
}
}
subsets.add(newSet);
}
return subsets;
}
private Graph convertToGraph(Set<Set<Integer>> allClusters) {
Set<Set<Node>> _clustering = new HashSet<Set<Node>>();
for (Set<Integer> cluster : allClusters) {
Set<Node> nodes = new HashSet<Node>();
for (int i : cluster) {
nodes.add(variables.get(i));
}
_clustering.add(nodes);
}
return convertSearchGraphNodes(_clustering);
}
/** Iterator over the KnowledgeEdge's representing required edges. */
public final Iterator<KnowledgeEdge> requiredEdgesIterator() {
Set<KnowledgeEdge> edges = new HashSet<>();
for (OrderedPair<Set<MyNode>> o : requiredRulesSpecs) {
final Set<MyNode> first = o.getFirst();
for (MyNode s1 : first) {
final Set<MyNode> second = o.getSecond();
for (MyNode s2 : second) {
if (!s1.equals(s2)) {
edges.add(new KnowledgeEdge(s1.getName(), s2.getName()));
}
}
}
}
return edges.iterator();
}
private Set<MyNode> getExtent(String spec) {
Set<String> split = split(spec);
Set<MyNode> matches = new HashSet<>();
for (String _spec : split) {
_spec = _spec.replace("*", ".*");
java.util.regex.Pattern pattern = java.util.regex.Pattern.compile(_spec);
for (MyNode var : myNodes) {
Matcher matcher = pattern.matcher(var.getName());
if (matcher.matches()) {
matches.add(var);
}
}
}
return matches;
}
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;
}
/** Iterator over the knowledge's explicitly forbidden edges. */
public final Iterator<KnowledgeEdge> explicitlyForbiddenEdgesIterator() {
Set<OrderedPair<Set<MyNode>>> copy = new HashSet<>(forbiddenRulesSpecs);
copy.removeAll(forbiddenTierRules());
for (KnowledgeGroup group : knowledgeGroups) {
copy.remove(knowledgeGroupRules.get(group));
}
Set<KnowledgeEdge> edges = new HashSet<>();
for (OrderedPair<Set<MyNode>> o : copy) {
final Set<MyNode> first = o.getFirst();
for (MyNode s1 : first) {
final Set<MyNode> second = o.getSecond();
for (MyNode s2 : second) {
edges.add(new KnowledgeEdge(s1.getName(), s2.getName()));
}
}
}
return edges.iterator();
}
/**
* Constructs a new FCI search for the given independence test and background knowledge and a list
* of variables to search over.
*/
public Rfci(IndependenceTest independenceTest, List<Node> searchVars) {
if (independenceTest == null || knowledge == null) {
throw new NullPointerException();
}
this.independenceTest = independenceTest;
this.variables.addAll(independenceTest.getVariables());
Set<Node> remVars = new HashSet<Node>();
for (Node node1 : this.variables) {
boolean search = false;
for (Node node2 : searchVars) {
if (node1.getName().equals(node2.getName())) {
search = true;
}
}
if (!search) {
remVars.add(node1);
}
}
this.variables.removeAll(remVars);
}
// Finds clusters of size 3.
private Set<Set<Integer>> findMixedClusters(
List<Integer> remaining, Set<Integer> unionPure, Map<Node, Set<Node>> adjacencies) {
Set<Set<Integer>> threeClusters = new HashSet<Set<Integer>>();
if (unionPure.isEmpty()) {
return new HashSet<Set<Integer>>();
}
REMAINING:
while (true) {
if (remaining.size() < 3) break;
ChoiceGenerator gen = new ChoiceGenerator(remaining.size(), 3);
int[] choice;
while ((choice = gen.next()) != null) {
int y = remaining.get(choice[0]);
int z = remaining.get(choice[1]);
int w = remaining.get(choice[2]);
Set<Integer> cluster = new HashSet<Integer>();
cluster.add(y);
cluster.add(z);
cluster.add(w);
// if (!allVariablesDependent(cluster)) {
// continue;
// }
if (!clique(cluster, adjacencies)) {
continue;
}
// Check all x as a cross check; really only one should be necessary.
boolean allX = true;
for (int x : unionPure) {
Set<Integer> _cluster = new HashSet<Integer>(cluster);
_cluster.add(x);
if (!quartetVanishes(_cluster) || !significant(new ArrayList<Integer>(_cluster))) {
allX = false;
break;
}
}
if (allX) {
threeClusters.add(cluster);
unionPure.addAll(cluster);
remaining.removeAll(cluster);
System.out.println(
"3-cluster found: " + variablesForIndices(new ArrayList<Integer>(cluster)));
continue REMAINING;
}
}
break;
}
return threeClusters;
}
// 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;
}
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;
}
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);
}
public GeneralizedSemPm(SemPm semPm) {
this(semPm.getGraph());
// Write down equations.
try {
List<Node> variableNodes = getVariableNodes();
for (int i = 0; i < variableNodes.size(); i++) {
Node node = variableNodes.get(i);
List<Node> parents = getVariableParents(node);
StringBuilder buf = new StringBuilder();
for (int j = 0; j < parents.size(); j++) {
if (!(variableNodes.contains(parents.get(j)))) {
continue;
}
Node parent = parents.get(j);
Parameter _parameter = semPm.getParameter(parent, node);
String parameter = _parameter.getName();
Set<Node> nodes = new HashSet<>();
nodes.add(node);
referencedParameters.put(parameter, nodes);
buf.append(parameter);
buf.append("*");
buf.append(parents.get(j).getName());
setParameterExpression(parameter, "Split(-1.5, -.5, .5, 1.5)");
setStartsWithParametersTemplate(parameter.substring(0, 1), "Split(-1.5, -.5, .5, 1.5)");
setStartsWithParametersEstimationInitializaationTemplate(
parameter.substring(0, 1), "Split(-1.5, -.5, .5, 1.5)");
if (j < parents.size() - 1) {
buf.append(" + ");
}
}
if (buf.toString().trim().length() != 0) {
buf.append(" + ");
}
buf.append(errorNodes.get(i));
setNodeExpression(node, buf.toString());
}
for (Node node : variableNodes) {
Parameter _parameter = semPm.getParameter(node, node);
String parameter = _parameter.getName();
String distributionFormula = "N(0," + parameter + ")";
setNodeExpression(getErrorNode(node), distributionFormula);
setParameterExpression(parameter, "U(0, 1)");
setStartsWithParametersTemplate(parameter.substring(0, 1), "U(0, 1)");
setStartsWithParametersEstimationInitializaationTemplate(
parameter.substring(0, 1), "U(0, 1)");
}
variableNames = new ArrayList<>();
for (Node _node : variableNodes) variableNames.add(_node.getName());
for (Node _node : errorNodes) variableNames.add(_node.getName());
} catch (ParseException e) {
throw new IllegalStateException("Parse error in constructing initial model.", e);
}
}
@Test
public void test4() {
// For X3
Map<String, String[]> templates = new HashMap<>();
templates.put(
"NEW(b) + NEW(b) + NEW(c) + NEW(c) + NEW(c)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("NEW(X1) + NEW(b) + NEW(c) + NEW(c) + NEW(c)", new String[] {});
templates.put("$", new String[] {});
templates.put("TSUM($)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TPROD($)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TPROD($) + X2", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TPROD($) + TSUM($)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("tan(TSUM(NEW(a)*$))", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("Normal(0, 1)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("Normal(m, s)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("Normal(NEW(m), s)", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("Normal(NEW(m), NEW(s)) + m1 + s6", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TSUM($) + a", new String[] {"X1", "X2", "X3", "X4", "X5"});
templates.put("TSUM($) + TSUM($) + TSUM($) + 1", new String[] {"X1", "X2", "X3", "X4", "X5"});
for (String template : templates.keySet()) {
GeneralizedSemPm semPm = makeTypicalPm();
print(semPm.getGraph().toString());
Set<Node> shouldWork = new HashSet<>();
for (String name : templates.get(template)) {
shouldWork.add(semPm.getNode(name));
}
Set<Node> works = new HashSet<>();
for (int i = 0; i < semPm.getNodes().size(); i++) {
print("-----------");
print(semPm.getNodes().get(i).toString());
print("Trying template: " + template);
String _template = template;
Node node = semPm.getNodes().get(i);
try {
_template = TemplateExpander.getInstance().expandTemplate(_template, semPm, node);
} catch (Exception e) {
print("Couldn't expand template: " + template);
continue;
}
try {
semPm.setNodeExpression(node, _template);
print("Set formula " + _template + " for " + node);
if (semPm.getVariableNodes().contains(node)) {
works.add(node);
}
} catch (Exception e) {
print("Couldn't set formula " + _template + " for " + node);
}
}
for (String parameter : semPm.getParameters()) {
print("-----------");
print(parameter);
print("Trying template: " + template);
String _template = template;
try {
_template = TemplateExpander.getInstance().expandTemplate(_template, semPm, null);
} catch (Exception e) {
print("Couldn't expand template: " + template);
continue;
}
try {
semPm.setParameterExpression(parameter, _template);
print("Set formula " + _template + " for " + parameter);
} catch (Exception e) {
print("Couldn't set formula " + _template + " for " + parameter);
}
}
assertEquals(shouldWork, works);
}
}
/**
* 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);
}
}
}
// 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;
}
