# Librairie du projet en version orientée objet

import random

def min_i(array: list[int]) -> int:
	min_val = array[0]
	min_i = 0
	for i in range(len(array)):
		if array[i] < min_val:
			min_val = array[i]
			min_i = i 
	return min_i

def max_i(array: list[int]) -> int:
	max_val = array[0]
	max_i = 0
	for i in range(len(array)):
		if array[i] > max_val:
			max_val = array[i]
			max_i = i 
	return max_i

class Population:
	"""
	Classe qui représente notre population d'individuts
	"""
	def __init__(self, pm, ng, n, ts, tm):
		self.individuals = [Individual() for _ in range(n)]
		for individual in self.individuals: 
			individual.randomize(len(pm))
		self.pm = pm
		self.ng = ng
		self.l = len(pm)
		self.n = n
		self.ts = ts
		self.tm = tm

	def select(self) -> None:
		fitness_list = [] 
		for individual in self.individuals:
			fitness_list.append(individual.fitness(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:
		new = []
		while len(self.individuals) + len(new) != self.n:
			cut = random.randint(int(self.l / 3), int(2 * self.l / 3))
			indivi_1 = self.individuals[random.randint(0, len(self.individuals) - 1)]
			indivi_2 = self.individuals[random.randint(0, len(self.individuals) - 1)]
			while indivi_1 == indivi_2:
				indivi_2 = self.individuals[random.randint(0, len(self.individuals) - 1)]
			new_chromozome = indivi_1.getChromozome()[:cut] + indivi_2.getChromozome()[cut:]
			child = Individual()
			child.setChromozome(new_chromozome)
			new.append(child)
		self.individuals += new

	def mutate(self) -> None:
		mutated = []
		for i in range(int(self.tm * self.n)):
			to_mutate = random.randint(0, self.n - 1)
			while to_mutate in mutated:
				to_mutate = random.randint(0, self.n - 1)
			self.individuals[to_mutate].mutate()
			mutated.append(to_mutate)

	def print_best(self) -> None:
		fitness_list = []
		for individual in self.individuals:
			fitness_list.append(individual.fitness(self.pm))
		print(self.individuals[max_i(fitness_list)].getChromozome())

	def run(self) -> None:
		for i in range(self.ng):
			self.select()
			self.reproduct()
			self.mutate()
		self.print_best()

class Individual:
	"""
	Classe qui représente les individuts de la population (les solutions potentielles)
	"""
	def __init__(self):
		self.chromozome = ""

	def setChromozome(self, c: str) -> None:
		self.chromozome = c
	
	def getChromozome(self) -> str:
		return self.chromozome

	def randomize(self, l) -> None:
		new = ""
		for i in range(l):
			new += chr(random.randint(0, 255))
		self.chromozome = new

	def fitness(self, pm) -> int:
		sum = 0
		for i in range(len(self.chromozome)):
			sum += abs(ord(self.chromozome[i]) - ord(pm[i]))
		return -sum

	def mutate(self) -> None:
		new = list(self.chromozome)
		new[random.randint(0, len(new) - 1)] = chr(random.randint(0, 255))
		self.chromozome = "".join(new)