mutations seulement sur les enfants

algogenetique.py

@@ -16,21 +16,22 @@ def main(N,tmax,pmutation, proportion,brin="plasmid_8k.fasta"):
 	brin = ''.join(lineList[1:])'''
     L=[]
     People=Population(N)
-    afficher(People)
+    # afficher(People)
     for i in range(tmax):
         print("\n \n NOUVELLE GENERATION \n \n")
         max=0
         best=None
         for individu in People.indiv:
             individu.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
-        People.reproduction(p = proportion)
-        for individu in People.indiv:
-            individu.mutation(pmutation)
+        People.reproduction(p = proportion, proba_mutation= pmutation)
+        # for individu in People.indiv:
+        #     individu.mutation(pmutation)
         for individu in People.indiv:
             individu.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
             if individu.score>max:
                 best=individu
                 max=individu.score
+        afficher(People)
         L.append(max)
         #print(L)
     plt.plot([i for i in range(tmax)], L)
@@ -38,7 +39,7 @@ def main(N,tmax,pmutation, proportion,brin="plasmid_8k.fasta"):
     return(best)
 
 
-main(100,50,0.015,50)
+main(10,50,0,5)
 
 
 

population.py

@@ -42,7 +42,12 @@ class Population:
     def selection_duel(self,p=None):
         if p == None :
             p = (self.n)//2
-        newself=[]
+        meilleur = self.indiv[0]
+        for individu in self.indiv :
+            if meilleur.score < individu.score:
+                meilleur = individu
+        newself = [meilleur]
+        print("\n \n \nmeilleur", meilleur.table.rot_table, "\n \nscore", meilleur.score)
         vu=set()                        
         t=randrange(0,self.n)
         m=randrange(0,self.n)             
@@ -120,7 +125,9 @@ class Population:
                 newself.append(x)
         self = self.modifier_population(newself)
 
-    def reproduction(self,selection=None,enfant=croisement_un_point, p = None):
+    def reproduction(self,proba_mutation = None, selection=None,enfant=croisement_un_point, p = None):
+        if proba_mutation == None :
+            proba_mutation = 0.001
         if selection == None :
             selection = self.selection_duel
         if p == None :
@@ -134,6 +141,8 @@ class Population:
             x=newself[m]
             y=newself[t]
             couple_enfant = enfant(x,y)
+            for child in couple_enfant :
+                child.mutation(proba_mutation)
             newself.append(couple_enfant[0])
             newself.append(couple_enfant[1])
         self = self.modifier_population(newself)