T_start = 2.0
T_stop = 2.4
T_step = 0.01 # 0.02
MCcycles = 1000000
initial_state = "Random"
for L in [20, 40, 60, 80, 100]:
if doItAgain:
doit()
for L in [20, 40, 60, 80, 100]:
filename = Filename(L, T_start, T_stop, T_step, MCcycles, initial_state)
data = lesfil(filename)
plt.figure(0)
plt.subplot(211)
plotfil(filename, 0, 1, label="$L=%i$" % L)
plt.subplot(212)
plotfil(filename, 0, 2, label="$L=%i$" % L)
plt.figure(2)
plt.subplot(211)
plotfil(filename, 0, 3, label="$L=%i$" % L)
plt.subplot(212)
plotfil(filename, 0, 4, label="$L=%i$" % L)
plt.figure(0)
plt.subplot(211)
plt.plot((2.269, 2.269), (-1.8, -1.1), "k")
# plt.xlabel(mathrm('Temperature')+'$T$')
doit()
## Temperature T=2.4
T = 2.4
doit()
### Now plot things:
## Uniform start
filename1 = Filename(1, MCcycles, 'Uniform')
filename2 = Filename(2.4, MCcycles, 'Uniform')
# <E>
plt.subplot(211)
plt.title(mathrm('Uniform'))
plotfil(filename1, 0, 1, label='$T=1$') # T=1
plotfil(filename2, 0, 1, label='$T=2.4$') # T=2.4
plt.ylim([-2.1, -1.1])
plt.legend(loc='best')
plt.ylabel('$\langle E \\rangle$ ')
# <|M|>
plt.subplot(212)
plotfil(filename1, 0, 2, label='$T=1$') # T=1
plotfil(filename2, 0, 2, label='$T=2.4$') # T=2.4
plt.ylim([0.4, 1.1])
plt.legend(loc='best')
plt.xlabel(mathrm('Number of monte carlo cycles'))
plt.ylabel('$\langle |M| \\rangle$')
plt.savefig('task_c_averages_uniform.pdf')
