From 162737f0728e8b08532613eec97002966e2a605d Mon Sep 17 00:00:00 2001
From: Martin Beseda <martinbeseda@seznam.cz>
Date: Wed, 25 Jul 2018 16:15:13 +0200
Subject: [PATCH] ENH: Enhanced info messages
---
src/LearningMethods/ParticleSwarm.cpp | 34 ++++++++++++++++++++-------
1 file changed, 26 insertions(+), 8 deletions(-)
diff --git a/src/LearningMethods/ParticleSwarm.cpp b/src/LearningMethods/ParticleSwarm.cpp
index 20c79490..8d9702c2 100644
--- a/src/LearningMethods/ParticleSwarm.cpp
+++ b/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;
--
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