X-Git-Url: https://ruin.nu/git/?a=blobdiff_plain;f=src%2Fmain.cpp;h=2e074957b459fbd72c3b5b2ada38fd7ca96753bb;hb=5202e2201f0d303478cefb4c365306d146189b45;hp=94109b4e4cce83e47329ce482186e44b740722f7;hpb=d7c119fefaf9cce07974afbefb4b6a017689a961;p=germs.git

diff --git a/src/main.cpp b/src/main.cpp
index 94109b4..2e07495 100644
--- a/src/main.cpp
+++ b/src/main.cpp
@@ -18,15 +18,22 @@ using namespace std;
 int main(int argc, char** argv){
 
 	string ann = "default.ann";
+	Model model(0);
+	bool detectModel = true;
 
 	int opt;
-	while ((opt = getopt(argc, argv, "n:h")) != -1) {
+	while ((opt = getopt(argc, argv, "m:n:h")) != -1) {
 		switch (opt) {
+			case 'm':
+				model = Model::modelFactory(optarg);
+				detectModel = false;
+				break;
 			case 'n':
 				ann = optarg;
 				break;
 			case 'h':
 				cout << "Usage: " << argv[0] << " [OPTION] [FILE]" << endl
+					<< endl << "  -m <model> Specifies which model to use for sorting: Whirl, X, Zipper, FatX or Cloud "
 					<< endl << "  -n <ann>   Specifies which artificial neural network to use for identification. '" << ann << "' is used by default"
 					<< endl << "  -h         Prints this help message"
 					<< endl << endl
@@ -61,24 +68,30 @@ int main(int argc, char** argv){
 	//TODO: Identify
 	ModelIdentifier mi(ann);
 	priority_queue<pair<double,Model> > pq = mi.identify(go);
-	Model model = pq.top().second;
-	//while (pq.size() > 0){
-	cout << "Model: " << model.name() << " score: " << pq.top().first << endl;
-		//pq.pop();
-	//}
+	if (detectModel){
+		model = pq.top().second;
+	}
+	while (pq.size() > 0){
+		cout << "Model: " << pq.top().second.name() << " score: " << pq.top().first << endl;
+		pq.pop();
+	}
+	cout << "Using model: " << model.name() << endl;
 
-	cout << "Distance: " << inversionDistance(go) << " : ";
-	copy(go.begin(), go.end(), ostream_iterator<int>(cout, " "));
-	cout << endl;
+	cout << "Distance: " << inversionDistance(go) << endl;
+	//copy(go.begin(), go.end(), ostream_iterator<int>(cout, " "));
+	//cout << endl;
 
 	//TODO: Chose a sorter
 	GeneSorter so;
 	//TODO: Sort
 	GeneSorter::ActionList al = so.sort(go,model);
 
+	double score = 0;
 	for (GeneSorter::ActionList::iterator sa = al.begin(); sa != al.end(); ++sa){
 		cout << "Action: " << sa->toString() << " model score: " << model.score(*sa,go) << endl;
+		score += model.score(*sa,go);
 	}
+	cout << "Avg score: " << score / al.size() << endl;
 	//TODO: Print result
 	return EXIT_SUCCESS;
 }