private double scoreGraphChange(Node y, Set<Node> parents1, Set<Node> parents2) {
int yIndex = hashIndices.get(y);
double score1, score2;
int[] parentIndices1 = new int[parents1.size()];
int count = -1;
for (Node parent : parents1) {
parentIndices1[++count] = hashIndices.get(parent);
}
if (isDiscrete()) {
score1 = localDiscreteScore(yIndex, parentIndices1);
} else {
score1 = localSemScore(yIndex, parentIndices1);
}
int[] parentIndices2 = new int[parents2.size()];
int count2 = -1;
for (Node parent : parents2) {
parentIndices2[++count2] = hashIndices.get(parent);
}
if (isDiscrete()) {
score2 = localDiscreteScore(yIndex, parentIndices2);
} else {
score2 = localSemScore(yIndex, parentIndices2);
}
return score1 - score2;
}
// ===========================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;
}
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;
}
/** 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);
}
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);
}
/**
* 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);
}
}
// Can be done concurrently.
private double deleteEval(Node x, Node y, List<Node> h, List<Node> naYX, Graph graph) {
List<Node> paY = graph.getParents(y);
Set<Node> paYMinuxX = new HashSet<Node>(paY);
paYMinuxX.remove(x);
Set<Node> set1 = new HashSet<Node>(naYX);
set1.removeAll(h);
set1.addAll(paYMinuxX);
Set<Node> set2 = new HashSet<Node>(naYX);
set2.removeAll(h);
set2.addAll(paY);
return scoreGraphChange(y, set1, set2);
}