Joseph94m

def sample(n):
    game_results = np.random.choice([1, -1, 0], size=n, p=[0.2, 0.15, 0.65])
    return game_results

Joseph94m

SIZE = [12,24,48,96,128,192,256,384,512,768,1024,1256,1536,1768,2000]
ITERATIONS = 10000

winnings_best=[]
winnings_worst=[]
draw=[]

for k in range(len(SIZE)):
    best_guy_wins=0
    worst_guy_wins=0

Joseph94m

class Game:
    def __init__(self, initial_state, rules,max_size):
        self.initial_state = initial_state
        self.rules = rules
        self.max_size = max_size
    def run_game(self, it):
        state = self.initial_state
        previous_state = None
        progression = []
        i = 0

Joseph94m

class SparseSetState(State):
    def __init__(self, grid):
        self.grid = grid

    def copy(self):
        return SparseSetState(copy(self.grid))
    
    def get_neighbours(self, elem, max_size):
        #Returns the neighbours of a live cell if they lie within the bounds of the grid specified by max_size
        l = []

Joseph94m

class SparseSetRules(Rule):
    def apply_rules(self, grid, max_size,get_neighbours):
        #grid = state.grid
        counter = {}
        for elem in grid:
            if elem not in counter:
                counter[elem]=0
            nb = get_neighbours(elem, max_size)
            for n in nb:
                if n not in counter:

Joseph94m

MAX_ITER = 1500
MAX_SIZE = 80
board = {(39, 40),(39, 41),(40, 39),(40, 40),(41, 40)}
rules = SparseSetRules()
game = Game(SparseSetState(board), rules,MAX_SIZE)
t = time.time()
rw = game.run_game(MAX_ITER)
print(time.time()-t)