diff --git a/RotTable.py b/RotTable.py
index efdebce4cf42480c3be6c111f39fcce5c4cfa90e..e3486c1b21452cfed789090694fdb3d372884c98 100644
--- a/RotTable.py
+++ b/RotTable.py
@@ -63,7 +63,7 @@ class RotTable:
###################
-table1 = RotTable()
-print(table1.orta())
+# table1 = RotTable()
+# print(table1.orta())
-print(table1.rot_table["AA"])
+# print(table1.rot_table["AA"])
diff --git a/croisement.py b/croisement.py
index a59546f35101170f94063bcc93992754ca4c402a..48a399f3e03e49d46867b53a1695e99657f13c67 100644
--- a/croisement.py
+++ b/croisement.py
@@ -1,5 +1,6 @@
import numpy
from RotTable import RotTable
+from individu import Individu
ROT_TABLE = {\
"AA": [35.62, 7.2, -154, 0.06, 0.6, 0],\
@@ -22,17 +23,17 @@ ROT_TABLE = {\
def croisement_un_point(parent1, parent2):
- enfant1 = RotTable()
- enfant2 = RotTable()
+ enfant1 = Individu(RotTable())
+ enfant2 = Individu(RotTable())
comp = 0
point_crois= numpy.random.random_integers(0,16)
for doublet in ROT_TABLE:
if comp < point_crois:
- enfant1.rot_table[doublet] = parent1.rot_table[doublet]
- enfant2.rot_table[doublet] = parent2.rot_table[doublet]
+ enfant1.table.rot_table[doublet] = parent1.table.rot_table[doublet]
+ enfant2.table.rot_table[doublet] = parent2.table.rot_table[doublet]
else :
- enfant1.rot_table[doublet] = parent2.rot_table[doublet]
- enfant2.rot_table[doublet] = parent1.rot_table[doublet]
+ enfant1.table.rot_table[doublet] = parent2.table.rot_table[doublet]
+ enfant2.table.rot_table[doublet] = parent1.table.rot_table[doublet]
comp += 1
return enfant1, enfant2
diff --git a/individu.py b/individu.py
index 88b9dc13f204b0ff18f866208e40ed8b8e3eab31..0bc68e4926298da3172bec0b670ea360435d13ca 100644
--- a/individu.py
+++ b/individu.py
@@ -24,7 +24,7 @@ class Individu():
first_name = brin[0]
last_name = brin[-1]
- rot_computed = self.table.Rot_Table[last_name+first_name]
+ rot_computed = self.table.rot_table[last_name+first_name]
rot_traj = first_nucleotide - last_nucleotide
# print(rot_traj)
# print(rot_computed)
diff --git a/population.py b/population.py
index 69e6bd8d9ec53803fc22e6753efb9996d0c0a7a5..f3daad1c6d133392c6474d0923951837dfe7c6fb 100644
--- a/population.py
+++ b/population.py
@@ -1,53 +1,69 @@
import random
+from random import random, randint, randrange
+from individu import Individu
+from RotTable import RotTable
+from croisement import *
class Population:
def __init__(self,n):
- self.indiv=[Individu(rot_table.alea) for k in range (n)]
+ self.indiv=[Individu(RotTable()) for k in range (n)]
self.n = n
-
- def selection_duel_pondere(self,p=(self.n)//2):
+
+ def modifier_population(self, liste_individus):
+ """Fonction qui renvoie une nouvelle instance de population a partir d'une liste d'individus"""
+ self.n = len(liste_individus)
+ self.indiv = liste_individus
+ return self
+
+ def selection_duel_pondere(self,p=None):
+ if p == None :
+ p = (self.n)//2
newself=[]
- vu={}
- m=None
- t=None #méthode des duels pondérée: si x=10 et y=1, y a une chance sur 11 de passer
+ vu=set()
+ m=randrange(0,self.n)
+ t=randrange(0,self.n) #méthode des duels pondérée: si x=10 et y=1, y a une chance sur 11 de passer
while len(newself)<p:
while m in vu:
- m=random.randrange(0,len(self))
+ m=randrange(0,self.n)
while t in vu:
- t=random.randrange(0,len(self))
- x=self[m]
- y=self[t]
+ t=randrange(0,self.n)
+ x=self.indiv[m]
+ y=self.indiv[t]
vu.add(t)
vu.add(m)
- p=uniform(0,1)
+ p=random()
if p>x.score/(x.score+y.score):
newself.append(y)
else:
newself.append(x)
- return(newself)
+ self = self.modifier_population(newself)
- def selection_duel(self,p=(self.n)//2):
+ def selection_duel(self,p=None):
+ if p == None :
+ p = (self.n)//2
newself=[]
- vu={}
- t=None
- m=None
+ vu=set()
+ t=randrange(0,self.n)
+ m=randrange(0,self.n)
while len(newself)<p:
while m in vu:
- m=random.randrange(0,len(self))
+ m=randrange(0,self.n)
while t in vu:
- t=random.randrange(0,len(self))
- x=self[m]
- y=self[t]
+ t=randrange(0,self.n)
+ x=self.indiv[m]
+ y=self.indiv[t]
vu.add(t)
vu.add(m)
if x.score<=y.score:
newself.append(x)
else:
newself.append(y)
- return(newself)
+ self = self.modifier_population(newself)
- def selection_par_rang(self, p=(self.n)//2):
+ def selection_par_rang(self,p = None):
+ if p == None :
+ p = (self.n)//2
liste_individus = self.indiv
n = self.n
@@ -58,7 +74,11 @@ class Population:
echanger(tableau,debut,randint(debut,fin-1))
partition=debut
for i in range(debut+1,fin):
+<<<<<<< HEAD
#if tableau[i] < tableau[debut]:
+=======
+ # if tableau[i] < tableau[debut]:
+>>>>>>> ea595ada3becbb697c8735a8fbdc55f04e1606a2
if tableau[i].score<tableau[debut].score:
partition+=1
echanger(tableau,i,partition)
@@ -85,39 +105,62 @@ class Population:
j+=1
#on doit prendre l'individu avec le jème score
# print("individus selectionés", individus_selectionnes)
- individus_selectionnes.append(liste[j-1])
-
- def modifier_population(self, liste_individus):
- self.n = len(liste_individus)
- self.indiv = liste_individus
- return self
+ individus_selectionnes.append(liste_individus[j-1])
- self = modifier_population(self, individus_selectionnes)
+ self = self.modifier_population(individus_selectionnes)
- def selection_proportionelle(self,p=(self.n)//2):
+ def selection_proportionelle(self,p= None):
+ if p == None :
+ p = (self.n)//2
newself=[]
somme=0
- for indiv in self:
+ for indiv in self.indiv:
somme=somme+indiv.score
while len(newself)<p:
- m=m=random.randrange(0,len(self))
- x=self[m]
- p=uniform(0,1)
+ m=m=randrange(0, self.n)
+ x=self.indiv[m]
+ p=random()
if p<=x.score/somme:
newself.append(x)
- return(newself)
-
- def reproduction(self,selection=selection_duel,enfant=mixage,p=n//2):
- newself=selection(self,p)
- while len(newself)<self.n:
- m=random.randrange(0,len(newself))
- t=random.randrange(0,len(newself))
+ self = self.modifier_population(newself)
+
+ def reproduction(self,selection=None,enfant=croisement_un_point, p = None):
+ if selection == None :
+ selection = self.selection_duel
+ if p == None :
+ p = (self.n)//2
+ vieille_taille = self.n
+ selection(p)
+ newself = list(self.indiv)
+ while len(newself)<vieille_taille:
+ m=randrange(0,self.n)
+ t=randrange(0,self.n)
x=newself[m]
y=newself[t]
- newself.append(enfant(x,y))
- return(newself)
-
-
+ couple_enfant = enfant(x,y)
+ newself.append(couple_enfant[0])
+ newself.append(couple_enfant[1])
+ self = self.modifier_population(newself)
+
+def afficher(popu):
+ for individu in popu.indiv :
+ print("\n individu \n")
+ print(individu.table.rot_table)
+
+def test():
+ popu = Population(4)
+ print("\n POPULATION INITIALE \n")
+ for individu in popu.indiv :
+ individu.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
+ afficher(popu)
+ # popu.selection_par_rang()
+ # print("\n SELECTION PAR RANG \n")
+ # afficher(popu)
+ popu.reproduction(selection = popu.selection_proportionelle)
+ print("\n REPRODUCTION \n")
+ afficher(popu)
+
+test()
diff --git a/selection_par_rang.py b/selection_par_rang.py
deleted file mode 100644
index ded5567fe7094249e4e3f1e0222031f0010a0164..0000000000000000000000000000000000000000
--- a/selection_par_rang.py
+++ /dev/null
@@ -1,45 +0,0 @@
-from random import random
-
-def creer_population(self, liste_individus):
- self.n = len(liste_individus)
- self.indiv = set(liste_individus)
- return self
-
-def selection_par_rang(self, p = n//2):
- set_individus = self.indiv
- n = self.n
-
- def partitionner(tableau,debut,fin):
- echanger(tableau,debut,random.randint(debut,fin-1))
- partition=debut
- for i in range(debut+1,fin):
- if tableau[i].score<tableau[debut].score:
- partition+=1
- echanger(tableau,i,partition)
- echanger(tableau,debut,partition)
- return partition
-
- def tri_rapide_aux(tableau,debut,fin):
- if debut < fin-1:
- positionPivot=partitionner(tableau,debut,fin)
- tri_rapide_aux(tableau,debut,positionPivot)
- tri_rapide_aux(tableau,positionPivot+1,fin)
-
- def tri_rapide(tableau):
- tri_rapide_aux(tableau,0,len(tableau))
-
- liste = list(set_individus)
- tri_rapide(liste)
- individus_selectionnes = []
-
- for _ in range(p):
- curseur = random()*n*(n+1)/2
- j = 1
- while j*(j+1)/2 < curseur :
- j+=1
- #on doit prendre l'individu avec le jème score
- individus_selectionnes.append(liste[j])
- self = creer_population(self, liste_individus)
-
-
-
\ No newline at end of file