Saataa andagii !

This commit is contained in:
Lukian 2024-11-18 13:00:20 +01:00
parent b858033964
commit 788e5fdf5f
2 changed files with 71 additions and 7 deletions

View file

@ -1,6 +1,7 @@
# Librairie du projet en version orientée objet
import random
import Levenshtein
def min_i(array: list[int]) -> int:
min_val = array[0]
@ -24,7 +25,7 @@ class Population:
"""
Classe qui représente notre population d'individuts
"""
def __init__(self, pm, ng, n, ts, tm):
def __init__(self, pm, ng, n, ts, tm, alpha, fm):
self.individuals = [Individual() for _ in range(n)]
for individual in self.individuals:
individual.randomize(len(pm))
@ -34,17 +35,33 @@ class Population:
self.n = n
self.ts = ts
self.tm = tm
self.alpha = alpha
self.fitness_method = fm
def select(self) -> None:
"""
Methode qui sélectionne les meilleurs individus
"""
fitness_list = []
for individual in self.individuals:
fitness_list.append(individual.fitness(self.pm))
match self.fitness_method:
case 1:
fitness_list.append(individual.fitness1(self.pm))
case 2:
fitness_list.append(individual.fitness2(self.pm, self.alpha))
case 3:
fitness_list.append(individual.fitness3(self.pm))
case _:
fitness_list.append(individual.fitness1(self.pm))
for i in range(int((1 - self.ts) * self.n)):
least = min_i(fitness_list)
fitness_list.pop(least)
self.individuals.pop(least)
def reproduct(self) -> None:
"""
Methode qui reproduit les individus entre eux jusqu'à obtenir une population de taille N
"""
new = []
while len(self.individuals) + len(new) != self.n:
cut = random.randint(int(self.l / 3), int(2 * self.l / 3))
@ -59,6 +76,9 @@ class Population:
self.individuals += new
def mutate(self) -> None:
"""
Methode qui mute une partie de la population selon le taut de mutation
"""
mutated = []
for i in range(int(self.tm * self.n)):
to_mutate = random.randint(0, self.n - 1)
@ -68,12 +88,26 @@ class Population:
mutated.append(to_mutate)
def print_best(self) -> None:
"""
Methode qui affiche le meilleur individu de la population
"""
fitness_list = []
for individual in self.individuals:
fitness_list.append(individual.fitness(self.pm))
match self.fitness_method:
case 1:
fitness_list.append(individual.fitness1(self.pm))
case 2:
fitness_list.append(individual.fitness2(self.pm, self.alpha))
case 3:
fitness_list.append(individual.fitness3(self.pm))
case _:
fitness_list.append(individual.fitness1(self.pm))
print(self.individuals[max_i(fitness_list)].getChromozome())
def run(self) -> None:
"""
Boucle principale
"""
for i in range(self.ng):
self.select()
self.reproduct()
@ -94,18 +128,46 @@ class Individual:
return self.chromozome
def randomize(self, l) -> None:
"""
Methode qui change la valeur d'un chromozome pour une valeur aléatoire
"""
new = ""
for i in range(l):
new += chr(random.randint(0, 255))
self.chromozome = new
def fitness(self, pm) -> int:
def fitness1(self, pm) -> int:
"""
Première methode de fitness, fait la somme des différences entre les codages des caractères des deux chaînes.
"""
sum = 0
for i in range(len(self.chromozome)):
sum += abs(ord(self.chromozome[i]) - ord(pm[i]))
return -sum
def fitness2(self, pm, alpha) -> int:
"""
Deuxième methode de fitness qui compte les caractères bien placés et mal placés et qui renvoie un int pondéré par alpha
"""
match = 0
missed_placed = 0
for i in range(len(self.chromozome)):
if self.chromozome[i] == pm[i]:
match += 1
else:
missed_placed += 1
return match + alpha * missed_placed
def fitness3(self, pm) -> int:
"""
Troisième methode de fitness qui utilise la distance de Levenshtein
"""
return -Levenshtein.distance(self.chromozome, pm)
def mutate(self) -> None:
"""
Methode qui change un des caractères du chromozome
"""
new = list(self.chromozome)
new[random.randint(0, len(new) - 1)] = chr(random.randint(0, 255))
self.chromozome = "".join(new)

View file

@ -5,15 +5,17 @@ import lib.ultra_mastermind_obj as libobj
import lib.ultra_mastermind_imp as libomp
# constants
PM = "Saataa andagii !"
NG = 2000
PM = "Hello, world!"
NG = 1000
N = 400
TS = 0.5
TM = 0.01
ALPHA = 0.5
FITNESS_METHOD = 3
# main function
def main() -> None:
pop = libobj.Population(pm = PM, ng = NG, n = N, ts = TS, tm = TM)
pop = libobj.Population(pm = PM, ng = NG, n = N, ts = TS, tm = TM, alpha = ALPHA, fm = FITNESS_METHOD)
pop.run()
if __name__ == "__main__":