ENH: Enhanced info messages

src/LearningMethods/ParticleSwarm.cpp

@@ -203,9 +203,11 @@ void ParticleSwarm::optimize( double gamma, double epsilon, double delta) {
     double max_velocity;
     double max_vel_step = 0;
     double prev_max_vel_step;
+    double euclidean_dist;
 
     while( outer_it < this->iter_max ) {
         max_velocity = 0;
+        euclidean_dist = 0;
 
         //////////////////////////////////////////////////
         // Clustering algorithm - termination condition //
@@ -237,7 +239,12 @@ void ParticleSwarm::optimize( double gamma, double epsilon, double delta) {
                 }
 
                 /* Looking for nearby particles */
-                printf("iter: %d, pi: %d, euclidean dist: %f\n", outer_it, pi, this->get_euclidean_distance(particle->get_coordinate(), coords, this->func_dim));
+                //printf("iter: %d, pi: %d, euclidean dist: %f\n", outer_it, pi, this->get_euclidean_distance(particle->get_coordinate(), coords, this->func_dim));
+
+                // TODO - only in verbose mode
+                // only for info purposes
+                euclidean_dist += this->get_euclidean_distance(particle->get_coordinate(), coords, this->func_dim);
+
                 if(this->get_euclidean_distance(particle->get_coordinate(), coords, this->func_dim) < epsilon) {
                     cluster.insert(particle);
                 }
@@ -248,22 +255,33 @@ void ParticleSwarm::optimize( double gamma, double epsilon, double delta) {
         max_vel_step = max_velocity - prev_max_velocity;
 
         /* Check if the particles are near to each other AND the maximal velocity is less than 'gamma' */
-//        printf("cluster size: %ld, n particles: %d, %f\n", cluster.size(), this->n_particles, double(cluster.size())/this->n_particles);
-        printf("cluster: %f\n", double(cluster.size())/this->n_particles);
-        printf("real gamma: %f\n", std::abs(prev_max_vel_step/max_vel_step));
         if(double(cluster.size())/this->n_particles > delta && std::abs(prev_max_vel_step/max_vel_step) > gamma) {
             break;
         }
 
+        //TODO only in verbose mode
+        euclidean_dist /= this->n_particles*5.;
+        printf("Iteration %d, avg euclidean distance: %f\n", outer_it, euclidean_dist);
+
         outer_it++;
 //        this->w *= 0.99;
     }
 
-    printf("Found optimum in %6d iterations: %10.8f at coordinate: ", outer_it, optimal_value);
-    for(unsigned int i = 0; i < this->func_dim - 1; ++i){
-        printf("%10.8f, ", p_min_glob[i]);
+    if(outer_it < this->iter_max) {
+        /* Convergence reached */
+
+        printf("Found optimum in %d iterations: %10.8f at coordinates: \n", outer_it, optimal_value);
+        for (unsigned int i = 0; i <= this->func_dim - 1; ++i) {
+            printf("%10.8f \n", p_min_glob[i]);
+        }
+    } else {
+        /* Maximal number of iterations reached */
+
+        printf("Max number of iterations reached (%d)! Found value %10.8f at coordinates: \n", outer_it, optimal_value);
+        for (unsigned int i = 0; i <= this->func_dim - 1; ++i) {
+            printf("\t%10.8f \n", p_min_glob[i]);
+        }
     }
-    printf("%10.8f\n", p_min_glob[this->func_dim - 1]);
 
     delete [] p_min_glob;
     delete [] coords;