diff --git a/few/lib/epsilon_lexicase.h b/few/lib/epsilon_lexicase.h
index e54e6b3..6c8d0a3 100644
--- a/few/lib/epsilon_lexicase.h
+++ b/few/lib/epsilon_lexicase.h
@@ -96,56 +96,28 @@ void epsilon_lexicase(const ExtMat & F, int n, int d,
   for (int i = 0; i<epsilon.size(); ++i)
     epsilon(i) = mad(F.col(i));
 
-  /*vector<int> ind_locs;
- if(lex_size){
-    //randomly select a size from sizes
-    int max_index = sizes.size();
-    int random_index = rand() % max_index;
-
-
-    // individual locations
-    vector<int> ind_locs_temp(sizes[random_index]);
-    ind_locs = ind_locs_temp;
-    //ind_locs.reserve(sizes[random_index]);
-  }
-  else{
-    // individual locations
-    vector<int> ind_locs_temp(n);
-    ind_locs = ind_locs_temp;
-    //ind_locs.reserve(n);
-  }*/
-
-  vector<int> ind_locs;
- if(lex_size){
+vector<int> ind_locs(n);
+if(lex_size){
     char message[200];
-    PyOS_snprintf(message, sizeof(message),"lex_size");
     //randomly select a size from sizes
     int max_index = sizes.size();
     int random_index = rand() % max_index;
-    vector<int> ind_locs_temp(n);
 
     // individual locations
     int j=0;
     for(int i=0;i<max_index;i++){
-      if(sizes[i]==random_index)
-        ind_locs_temp[j++] = i;
-    }
-    ind_locs.reserve(j);
-    for(int k=0;k<j;k++){
-        ind_locs[k] = ind_locs_temp[k];
+      if(sizes[i]<=sizes[random_index])
+        ind_locs.push_back(i);
     }
     
   }
   else{
     // individual locations
-    ind_locs.reserve(n);
     iota(ind_locs.begin(),ind_locs.end(),0);
   }
 
-
   // temporary winner pool
   vector<int> winner;
-
   for (int i = 0; i<num_selections; ++i){
     //cout << "selection " << i << "\n";
     // perform selection
diff --git a/few/selection.py b/few/selection.py
index 79f6509..cbf9471 100644
--- a/few/selection.py
+++ b/few/selection.py
@@ -26,16 +26,11 @@ def survival(self,parents,offspring,elite=None,elite_index=None,X=None,F=None,F_
         elif self.sel == 'epsilon_lexicase':
             # survivors, survivor_index = self.epsilon_lexicase(parents + offspring, num_selections = len(parents), survival = True)
             if self.lex_size:
-                print(parents + offspring)
                 sizes = [len(i.stack) for i in (parents + offspring)]
-                print(sizes)
-                print("--")
                 survivor_index = self.epsilon_lexicase(np.vstack((F,F_offspring)), sizes, num_selections = F.shape[0], survival = True)
-                print(survivor_index)
                 survivors = [(parents+ offspring)[s] for s in survivor_index]
             else:
                 survivor_index = self.epsilon_lexicase(np.vstack((F,F_offspring)), [], num_selections = F.shape[0], survival = True)
-                print(survivor_index)
                 survivors = [(parents+ offspring)[s] for s in survivor_index]
         elif self.sel == 'deterministic_crowding':
             survivors, survivor_index = self.deterministic_crowding(parents,offspring,X,X_offspring)