void EncodingGraph::encode() {
- if (solver->getTuner()->getTunable(ENCODINGGRAPHOPT, &offon) == 0)
+ if (solver->isUnSAT() || solver->getTuner()->getTunable(ENCODINGGRAPHOPT, &offon) == 0)
return;
buildGraph();
SetIteratorEncodingSubGraph *itesg = subgraphs.iterator();
newSize = (leftSize > newSize) ? leftSize : newSize;
newSize = (rightSize > newSize) ? rightSize : newSize;
min = rightSize > leftSize ? leftSize : rightSize;
-// model_print("Merge=%s\tsimilarity=%f\n", max==newSize?"TRUE":"FALSE", left->measureSimilarity(right));
merge = leftGraph->measureSimilarity(right) > 1.5 || min == newSize;
+// model_print("Merge=%s\tsimilarity=%f\n", merge?"TRUE":"FALSE", leftGraph->measureSimilarity(right));
} else {
//Neither are null
leftSize = convertSize(leftGraph->numValues());
newSize = (leftSize > newSize) ? leftSize : newSize;
newSize = (rightSize > newSize) ? rightSize : newSize;
min = rightSize > leftSize ? leftSize : rightSize;
-// model_print("Merge=%s\tsimilarity=%f\n", max==newSize?"TRUE":"FALSE", leftGraph->measureSimilarity(right));
merge = leftGraph->measureSimilarity(rightGraph) > 1.5 || min == newSize;
+// model_print("Merge=%s\tsimilarity=%f\n", merge?"TRUE":"FALSE", leftGraph->measureSimilarity(rightGraph));
}
if (merge) {
//add the edge