mlapfds

PsoLars.py

@@ -20,15 +20,16 @@ def pso (n, pop, sample, c1=1/3, c2=1/3, c3=1/3, abort = 50):
     population = list()
     
     # create pop-many particle
-    
+
     for i in range(pop):
         new_particle = part.Particle(n)
         population.append(new_particle)
         for p in population:
             p.local_attractor=p.position
             p.local_attractor_cost = pl.cost_function(sample,p.local_attractor)
-        
+
             if(p.local_attractor_cost < global_attractor_cost):
+              
                 global_attractor = p.position
                 global_attractor_cost = p.local_attractor_cost
     
@@ -58,6 +59,6 @@ def pso (n, pop, sample, c1=1/3, c2=1/3, c3=1/3, abort = 50):
             if(p.cost<global_attractor_cost):
                 global_attractor=p.position
                 global_attractor_cost = p.cost
-      
+
     return test_array