running

genetics.py

@@ -10,7 +10,7 @@ def genetic_selection(brains):
     # proportionnally to its relative fitness
     wheel = []
     for b in brains :
-        wheel += [b] * b.brains
+        wheel += [b] * b.fitness
 
     
     tot_fitness = len(wheel)
@@ -19,7 +19,11 @@ def genetic_selection(brains):
     # selection of pool/2 pair of parents to reproduce  
     parents_pool = []
     for _ in range(half_pop):
-        parents_pool.append([round(random.random()*tot_fitness), round(random.random()*tot_fitness)])
+        parents_pool.append([
+                wheel[round(random.random()*tot_fitness)], 
+                wheel[round(random.random()*tot_fitness)]
+                ])
+    return parents_pool
     
 
 def cross_mutate_genes(p1_gene, p2_gene):
@@ -28,15 +32,15 @@ def cross_mutate_genes(p1_gene, p2_gene):
     p2_gene = list(p1_gene)
     for idx,x in enumerate(p2_gene):
         if random.random() > 0.5 :
-            choice = p1_gene
+            choice = p1_gene[idx]
         else :
-            choice = p2_gene
+            choice = p2_gene[idx]
         # Mutation
         if random.random() < 0.005 :
-            choice[random.randint(0, len(choice - 1))] = random.random()
+            choice[random.randint(0, len(choice) - 1)] = random.random()
             print("Mutation !")
-        child.append(np.array(choice))
-    return child
+        child.append(choice)
+    return np.array(child)
 
 
 def genetic_reproduction(parents_pool):