def MC(temperature, spins, MCc,
MSpins): # Temperature, Number of Spins, Number of cycles
PBC = lambda idx, lim, add: (idx + lim + add) % lim
E = 0.
Eavr = 0.
M = 0.
Mavr = 0.
lMl = 0.
VE = np.zeros(MCc + 1)
VM = np.zeros(MCc + 1)
# Sampling rule
w = np.zeros(17, np.float64)
for de in range(-8, 9, 4):
w[de + 8] = math.exp(-de / temperature)
# Initial energy and magnetization
M = MSpins.sum()
for ii in range(spins):
for jj in range(spins):
E -= MSpins[ii, jj] * (MSpins[PBC(ii, spins, -1), jj] +
MSpins[ii, PBC(jj, spins, 1)])
VE[0] = E
VM[0] = M
#MC
for ii in range(MCc):
# print(ii)
for ss in range(spins**2):
x = int(nrand() * spins)
y = int(nrand() * spins)
# print(x,y)
dE = 2 * MSpins[x, y] * (
MSpins[PBC(x, spins, -1), y] + MSpins[PBC(x, spins, 1), y] +
MSpins[x, PBC(y, spins, -1)] + MSpins[x, PBC(y, spins, 1)])
# print(dE)
if nrand() <= w[dE + 8]:
MSpins[x, y] *= -1
M += 2 * MSpins[x, y]
E += dE
Eavr += E
VE[ii + 1] = Eavr / (ii + 1)
lMl += int(math.fabs(M))
VM[ii + 1] = lMl / (ii + 1)
#Eavr /= float(MCc* spins**2)
#Mavr /= float(MCc)
#lMl /= float(MCc * spins**2)
VE /= float(spins**2)
VM /= float(spins**2)
return (VE, VM)
def sim(self, arm):
""" Draw a sample from given arm """
self.nsamples += 1
self.sample_size[arm] += 1
if self.dist == 'bernoulli':
if random.random() > self.mean_list[arm]:
return 0
else:
return 1
else:
return nrand(self.mean_list[arm], 0.25)
def MCC(MCc, spins, MSpins, E, M, Eavr, E2av, Mavr, M2av, lMl, w):
for ii in range(MCc):
for ss in range(spins**2):
x = int(nrand() * spins) #Pick up a spin
y = int(nrand() * spins) #Pick up a spin
dE = 2 * MSpins[x, y] * (
MSpins[PBC(x, spins, -1), y] + MSpins[PBC(x, spins, 1), y] +
MSpins[x, PBC(y, spins, -1)] + MSpins[x, PBC(y, spins, 1)])
# Metropolis
if nrand() <= w[dE + 8]:
MSpins[x, y] *= -1
M += 2 * MSpins[x, y]
E += dE
Eavr += E
E2av += E**2
Mavr += M
M2av += M**2
lMl += int(math.fabs(M))
return (Eavr, E2av, Mavr, M2av, lMl)
print(len(output_error))
f_in = open(input, 'r')
f_out_raw = open(output_raw, 'w')
f_out_error = []
for e in output_error:
f_out_error.append(open(e, 'w'))
lines = f_in.readlines()
for l in lines:
seq = l.rstrip().split(" ")
for data in seq:
f_out_raw.write(data + ":" + data + ":" + '0' + " ")
for j in range(1, 11):
stddev = 0.2 * j
error = nrand(data, stddev)
f_out_error[j-1].write(data + ":" + str(error) + ":" + str(stddev) + " ")
f_out_raw.write("\n")
for e in f_out_error:
e.write("\n")
f_in.close()
f_out_raw.close()
for e in f_out_error:
e.close()
