def geneticAlgorithm(populationSize, maxCost, nbFights, **kwargs):
if 'initChampions' in kwargs:
population = kwargs['initChampions']
population += [createRandomShip(maxCost) for _ in range(populationSize-len(kwargs['initChampions']))]
else:
population = [createRandomShip(maxCost) for _ in range(populationSize)]
tournamentResult = tournament(population, nbFights)
nbChampions = 2
if 'nbChampions' in kwargs:
nbChampions = kwargs['nbChampions']
nbGeneration = 2
if 'nbGeneration' in kwargs:
nbChampions = kwargs['nbGeneration']
nbMutations = 2
if 'nbMutations' in kwargs:
nbChampions = kwargs['nbMutations']
for nbG in range(nbGeneration):
# Determine the parents
champions = [(population[i], tournamentResult[population[i]]) for i in range(len(population[:nbChampions]))]
for shipResult in tournamentResult:
mini = min([result[1] for result in champions])
if tournamentResult[shipResult] > mini:
for indexR in range(len(champions)):
if champions[indexR] == mini:
champions[indexR] = (shipResult, tournamentResult[shipResult])
break
# Create new population with crossovers of the parents
for shipD in population:
if shipD not in [champ[0] for champ in champions]:
deleteShip(shipD)
population = [shipC[0] for shipC in champions]
for cantFindName in range(populationSize-len(champions)):
parent1 = randrange(nbChampions)
# We'll assume that there's at least 2 champions
parent2 = randrange(nbChampions)
while parent2 == parent1:
parent2 = randrange(nbChampions)
population += [crossover(population[parent1], population[parent2], maxCost)]
# Mutation
for nbM in range(nbMutations):
population[randrange(len(population))] = mutation(population[randrange(len(population))], maxCost)
# Determine the fitness of the population
tournamentResult = tournament(population, nbFights)
bestIndividual = population[0]
for key in tournamentResult:
if tournamentResult[key] > tournamentResult[bestIndividual]:
bestIndividual = key
return bestIndividual
async def tournament(ctx, *args):
global currentTournaments
if len(args) == 0:
if len(currentTournaments) == 0:
currentTournaments = tournament()
else:
ctx.send("There is always a game night")
else:
if args[0] == "clear":
if int(args[1]).isDigit():
try:
currentTournaments.remove(int(args[1]) - 1)
except IndexError:
ctx.send("Index out of bounds")
elif args[1] == "all":
currentTournaments = None
else:
ctx.send(f"Cannot clear {args[1]}")
elif len(args) > 4:
del args[4:] #truncate args
newTournament = tournament.tournament(args)
currentTournaments.append(newTournament)
ctx.send(newTournament.getAnnouncement())
else:
newGamesNight = gamesnight.gamesnight(args)
currentTournaments.append(newGamesNight)
ctx.send(newGamesNight.getAnnouncement())
def autoStopGeneticAlgorithm(populationSize, maxCost, nbFights, **kwargs):
"""
Stops when then champions aren't really differents from the rest of the population.
"""
champions = []
oldChampions = []
minGenerations = 5
if keepMemoryOfShipsGAlgo:
ls = os.listdir()
nameF = 'shipsGAlgo'
while nameF in ls:
nameF += '2'
resMemory = ''
def handler(signum, _):
if signum == signal.SIGTERM:
print('\033[32m'+str(champions)+'\033[0m')
signal.signal(signal.SIGTERM, handler)
def muchDifferences(championsL):
victoriesPoints = [ch[1] for ch in championsL]
for x in victoriesPoints:
if x > (populationSize-1) * (2/3):
return True
return False
if 'initChampions' in kwargs:
population = kwargs['initChampions']
population += [createRandomShip(maxCost) for _ in range(populationSize-len(kwargs['initChampions']))]
else:
population = [createRandomShip(maxCost) for _ in range(populationSize)]
tournamentResult = tournament(population, nbFights)
nbChampions = 2
if 'nbChampions' in kwargs:
nbChampions = kwargs['nbChampions']
nbMutations = 2
if 'nbMutations' in kwargs:
nbChampions = kwargs['nbMutations']
nbGenerations = 0
if keepMemoryOfShipsGAlgo:
for shipM in population:
resMemory += shipM + ' '
resMemory += '\n'
while (minGenerations > nbGenerations or muchDifferences(champions)) and nbGenerations < 30:
# Determine the parents
champions = [(population[i], tournamentResult[population[i]]) for i in range(len(population[:nbChampions]))]
for shipResult in tournamentResult:
mini = min([result[1] for result in champions])
if tournamentResult[shipResult] > mini:
for indexR in range(len(champions)):
if champions[indexR] == mini:
champions[indexR] = (shipResult, tournamentResult[shipResult])
break
oldChampions += [c[0] for c in champions if c[0] not in oldChampions]
# Create new population with crossovers of the parents
# for shipD in population:
# if shipD not in [champ[0] for champ in champions]:
# deleteShip(shipD)
population = [shipC[0] for shipC in champions]
for cantFindName in range(populationSize-len(champions)):
parent1 = randrange(nbChampions)
# We'll assume that there's at least 2 champions
parent2 = randrange(nbChampions)
while parent2 == parent1:
parent2 = randrange(nbChampions)
population += [crossover(population[parent1], population[parent2], maxCost)]
# Mutation
for nbM in range(nbMutations):
population[randrange(len(population)-nbChampions)+nbChampions] = mutation(population[randrange(len(population))], maxCost)
# Determine the fitness of the population
tournamentResult = tournament(population, nbFights)
nbGenerations += 1
if keepMemoryOfShipsGAlgo:
for shipM in population:
resMemory += shipM + ' '
resMemory += '\n'
if keepMemoryOfShipsGAlgo:
with open(nameF, 'w') as keepMemory:
keepMemory.write(resMemory)
bestIndividual = population[0]
for key in tournamentResult:
if tournamentResult[key] > tournamentResult[bestIndividual]:
bestIndividual = key
print('\033[32m'+'Best individual : '+bestIndividual+'\033[0m')
champions = [(population[i], tournamentResult[population[i]]) for i in range(len(population[:nbChampions]))]
for shipResult in tournamentResult:
mini = min([result[1] for result in champions])
if tournamentResult[shipResult] > mini:
for indexR in range(len(champions)):
if champions[indexR][1] == mini:
champions[indexR] = (shipResult, tournamentResult[shipResult])
break
oldChampions += [c[0] for c in champions if c[0] not in oldChampions]
resChamps = [bestIndividual] + [champs[0] for champs in champions if champs != bestIndividual]
return resChamps, [badShip for badShip in population if badShip not in resChamps], oldChampions
