def __init__(self, shape, T):
self.shape = shape
self.T = T
n, m = shape
tests = []
for i in range(T):
perc = Percolation((n, m))
while not perc.percolates():
lin = random.randint(0, n - 1)
col = random.randint(0, m - 1)
if not perc.is_open(lin, col):
perc.open(lin, col)
tests.append(perc.no_open())
testes = np.array(tests)
self.testes = testes / (n * m)
def __init__(self, n, t):
if n <= 0 or t <= 0:
raise ValueError("N and T should be greater than 0")
self._vals = []
self._t = t
for _ in range(t):
p = Percolation(n)
count = 0.0
while not p.percolates():
x = np.random.random_integers(1, n)
y = np.random.random_integers(1, n)
if p.is_open(x, y):
continue
else:
p.open(x, y)
count += 1
ans = count / (n * n)
self._vals.append(ans)
def __init__(self, shape, T):
grade = Percolation(shape)
self.grade = Percolation(shape)
self.T = T
self.x = [] #inicia a lista de armazena os limiares de percolação
self.numsitios = grade.op #guarda o numero de sitios da grade
for i in range(T):
contagem = 0 #reinicia a contagem de sitios abertos
while grade.percolates() == False:
valorlinha = random.randint(
0, grade.lin - 1
) #produz um valor inteiro aleatorio dentro do shape da grade
valorcoluna = random.randint(0, grade.col - 1)
if grade.is_open(
valorlinha, valorcoluna
) == False: #caso não seja BLOCKED abre o ponto da grade
grade.open(valorlinha,
valorcoluna) #e adiciona +1 na contagem
contagem += 1
self.x.append(
contagem /
self.numsitios) #adiciona um valor de limiar na lista
grade = Percolation(shape) #refaz a grade
import random
from percolation import Percolation
parser = argparse.ArgumentParser(description='Calculate the percolation ratio')
parser.add_argument('-n', action='store', dest='n', type=int,
help='The grid size n * n')
parser.add_argument('-t', action='store', dest='t', type=int,
help='How often should the experiment be executed.')
results = parser.parse_args()
n = results.n
t = results.t
percolation_results = []
for i in range(0, results.t):
perc = Percolation(n)
open_sites = 0
while not perc.percolates():
row = random.randint(1, n)
column = random.randint(1, n)
if not perc.is_open(row, column):
perc.open(row, column)
open_sites += 1
percolation = (open_sites * 1.0) / (n * n)
print percolation
percolation_results.append(percolation)
mean = sum(percolation_results) / len(percolation_results)
print "Mean: ", mean
