X-Git-Url: https://ruin.nu/git/?a=blobdiff_plain;f=src%2Fmain.cpp;h=d9bce2f37ba2f901c38470a0d0b59ab1f2e323b3;hb=dcd966c5fca7dca53ca1f605f70f13f019d29771;hp=1c6a85ecc85790716e6a8559e1ea86117d716922;hpb=90e2c43b99205b0d7a300209011231cd8d11f7a0;p=germs.git

diff --git a/src/main.cpp b/src/main.cpp
index 1c6a85e..d9bce2f 100644
--- a/src/main.cpp
+++ b/src/main.cpp
@@ -12,28 +12,29 @@ using namespace std;
 #include "modelidentifier.h"
 #include "genesorter.h"
 #include "sortaction.h"
-
-typedef pair<ModelIdentifier::Model,double> modelpair;
-
-struct ScoreCmp {
-	template<typename T>
-	bool operator()(T s1, T s2){
-		return s1.first < s2.first;
-	}
-};
+#include "genealgorithms.h"
+#include "model.h"
 
 int main(int argc, char** argv){
 
 	string ann = "default.ann";
+	Model model(0);
+	bool detectModel = true;
 
+	//Parse command line arguments
 	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
@@ -47,6 +48,7 @@ int main(int argc, char** argv){
 		}
 	}
 
+	//Open file, or stdin
 	istream* in;
 	ifstream file;
 	if (optind == argc || *argv[optind] == '-'){
@@ -59,31 +61,40 @@ int main(int argc, char** argv){
 		}
 		in = &file;
 	}
-	//TODO: Parse
+
+	//Parse the gene order permutation
 	vector<Gene> g;
 	copy(istream_iterator<int>(*in), istream_iterator<int>(),
-		     back_inserter(g));   
+	     back_inserter(g));
 	GeneOrder go(g.begin(),g.end());
 
-	//TODO: Identify
+	//Identify the model
 	ModelIdentifier mi(ann);
-	map<ModelIdentifier::Model,double> scores = mi.identify(go);
-	priority_queue<pair<double,ModelIdentifier::Model>,vector<pair<double,ModelIdentifier::Model> >, ScoreCmp > pq;
-	for (map<ModelIdentifier::Model,double>::iterator m = scores.begin();
-			m != scores.end(); ++m){
-		if (m->second > 0){
-			pq.push(pair<double,ModelIdentifier::Model>(m->second,m->first));
-		}
+	priority_queue<pair<double,Model> > pq = mi.identify(go);
+	if (detectModel){
+		model = pq.top().second;
 	}
 	while (pq.size() > 0){
-		cout << "Model: " << mi.modelName(pq.top().second) << " score: " << pq.top().first << endl;
+		cout << "Model: " << pq.top().second.name() << " score: " << pq.top().first << endl;
 		pq.pop();
 	}
+	cout << "Using model: " << model.name() << endl;
+
+	cout << "Distance: " << inversionDistance(go) << endl;
+	//copy(go.begin(), go.end(), ostream_iterator<int>(cout, " "));
+	//cout << endl;
 
-	//TODO: Chose a sorter
+	//Sort
 	GeneSorter so;
-	//TODO: Sort
-	GeneSorter::ActionList al = so.sort(go);
-	//TODO: Print result
+	GeneSorter::ActionList al = so.sort(go,model);
+
+	//Print the result
+	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;
+
 	return EXIT_SUCCESS;
 }