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;
}