plt.cla()
ax.plot(best_e, best_lndos, ':', color='0.5')
for suffix_index in range(len(suffixes)):
suffix = suffixes[suffix_index]
basename = dataformat % (suffix, frame * skipby)
try:
e, lndos, ps, lndostm = readnew.e_lndos_ps_lndostm(basename)
colors.plot(e, lndos, method=suffix)
#if lndostm is not None and suffix[:2] != 'sa':
# colors.plot(e, lndostm, method=suffix+'-tm')
datname = basename + '-lndos.dat'
min_T = readnew.minT(datname)
too_lo, too_hi = readnew.too_low_high_energy(datname)
ax.axvline(-readnew.max_entropy_state(datname),
color='r',
linestyle=':')
min_important_energy = int(readnew.min_important_energy(datname))
ax.axvline(-min_important_energy, color='b', linestyle=':')
if too_lo is not None and suffix[:3] == 'sad':
ax.axvline(-too_lo, color='b', linestyle='--')
if too_lo is not None and suffix[:3] == 'sad':
ax.axvline(-too_hi, color='r', linestyle='--')
# Uncomment the following to plot a line at the
# min_important_energy with slope determined by min_T
# ax.plot(e, (e+min_important_energy)/min_T + lndos[min_important_energy], colors[suffix_index]+'--')
# ax.axvline(-readnew.converged_state(datname), color=colors.color(suffix), linestyle=':')
# Uncomment the following to plot the lnw along with the lndos
# e, lnw = readnew.e_lnw(basename)
# ax.plot(e, -lnw, colors[suffix_index]+':')
all_methods = ['-tmi3', '-tmi2', '-tmi', '-toe', '-tmmc']
methods = []
prettymethods = []
T = []
u = []
energy = []
lndos = []
ps = []
hist = []
fref = 'data/lv/ww%.2f-ff%.2f-%gx%g-tmi3-dos.dat' % (ww, ff, lenx, lenyz)
energy_ref, lndos_ref = readnew.e_lndos(fref)
max_entropy_state = readnew.max_entropy_state(fref)
for method in all_methods:
try:
fbase = 'data/lv/ww%.2f-ff%.2f-%gx%g%s-movie/%s' % (
ww, ff, lenx, lenyz, method, number)
myT, myu, mycv, mys, myminT = readnew.T_u_cv_s_minT(fbase)
myenergy, mylndos, myps = readnew.e_lndos_ps(fbase)
_, myhist = readnew.e_hist(fbase)
except:
continue
energy.append(myenergy[:len(lndos_ref)])
lndos.append(mylndos[:len(lndos_ref)])
ps.append(myps[:len(lndos_ref)])
newhist = np.zeros_like(lndos_ref)
for j in range(len(split2)):
methods.append('-%s' % split2[j])
# For SAMC compatibility with LVMC
lvextra1 = glob('data/%s-samc*-movie' % filebase)
split3 = [i.split('%s-' % filebase, 1)[-1] for i in lvextra1]
split4 = [i.split('-m', 1)[0] for i in split3]
for j in range(len(split4)):
methods.append('-%s' % split4[j])
print methods
ref = reference
if ref[:len('data/')] != 'data/':
ref = 'data/' + ref
maxref = int(readnew.max_entropy_state(ref))
minref = int(readnew.min_important_energy(ref))
n_energies = int(minref - maxref + 1)
print maxref, minref
try:
eref, lndosref, Nrt_ref = readnew.e_lndos_ps(ref)
except:
eref, lndosref = readnew.e_lndos(ref)
for method in methods:
dirname = 'data/comparison/%s%s' % (filebase, method)
dirnametm = 'data/comparison/%s%s-tm' % (filebase, method)
try:
r = glob('data/%s%s-movie/*lndos.dat' % (filebase, method))
if len(r) == 0:
# print(" ... but it has no data in data/%s%s-movie/*lndos.dat" % (filebase,method))
plt.cla()
ax.plot(best_e, best_lndos, ':', color='0.5')
for suffix_index in range(len(suffixes)):
suffix = suffixes[suffix_index]
basename = dataformat % (suffix, frame*skipby)
try:
e, lndos, ps, lndostm = readnew.e_lndos_ps_lndostm(basename)
colors.plot(e, lndos, method=suffix)
#if lndostm is not None and suffix[:2] != 'sa':
# colors.plot(e, lndostm, method=suffix+'-tm')
datname = basename+'-lndos.dat'
min_T = readnew.minT(datname)
too_lo, too_hi = readnew.too_low_high_energy(datname)
ax.axvline(-readnew.max_entropy_state(datname), color='r', linestyle=':')
min_important_energy = int(readnew.min_important_energy(datname))
ax.axvline(-min_important_energy, color='b', linestyle=':')
if too_lo is not None and suffix[:3] == 'sad':
ax.axvline(-too_lo, color='b', linestyle='--')
if too_lo is not None and suffix[:3] == 'sad':
ax.axvline(-too_hi, color='r', linestyle='--')
# Uncomment the following to plot a line at the
# min_important_energy with slope determined by min_T
# ax.plot(e, (e+min_important_energy)/min_T + lndos[min_important_energy], colors[suffix_index]+'--')
# ax.axvline(-readnew.converged_state(datname), color=colors.color(suffix), linestyle=':')
# Uncomment the following to plot the lnw along with the lndos
# e, lnw = readnew.e_lnw(basename)
# ax.plot(e, -lnw, colors[suffix_index]+':')
except (KeyboardInterrupt, SystemExit):
raise
for j in range(len(split2)):
methods.append('-%s' %split2[j])
# For SAMC compatibility with LVMC
lvextra1 = glob('data/%s-samc*-movie' % filebase)
split3 = [i.split('%s-'%filebase, 1)[-1] for i in lvextra1]
split4 = [i.split('-m', 1)[0] for i in split3]
for j in range(len(split4)):
methods.append('-%s' %split4[j])
print methods
ref = reference
if ref[:len('data/')] != 'data/':
ref = 'data/' + ref
maxref = int(readnew.max_entropy_state(ref))
minref = int(readnew.min_important_energy(ref))
n_energies = int(minref - maxref+1)
print maxref, minref
try:
eref, lndosref, Nrt_ref = readnew.e_lndos_ps(ref)
except:
eref, lndosref = readnew.e_lndos(ref)
for method in methods:
dirname = 'data/comparison/%s%s' % (filebase,method)
dirnametm = 'data/comparison/%s%s-tm' % (filebase,method)
try:
r = glob('data/%s%s-movie/*lndos.dat' % (filebase,method))
if len(r)==0:
# print(" ... but it has no data in data/%s%s-movie/*lndos.dat" % (filebase,method))
all_methods = [ '-tmi3', '-tmi2', '-tmi', '-toe', '-tmmc']
methods = []
prettymethods = []
T = []
u = []
energy = []
lndos = []
ps = []
hist = []
fref = 'data/lv/ww%.2f-ff%.2f-%gx%g-tmi3-dos.dat' % (ww,ff,lenx,lenyz)
energy_ref,lndos_ref = readnew.e_lndos(fref)
max_entropy_state = readnew.max_entropy_state(fref)
for method in all_methods:
try:
fbase = 'data/lv/ww%.2f-ff%.2f-%gx%g%s-movie/%s' % (ww,ff,lenx,lenyz,method,number)
myT,myu,mycv,mys,myminT = readnew.T_u_cv_s_minT(fbase)
myenergy,mylndos,myps = readnew.e_lndos_ps(fbase)
_, myhist = readnew.e_hist(fbase)
except:
continue
energy.append(myenergy[:len(lndos_ref)])
lndos.append(mylndos[:len(lndos_ref)])
ps.append(myps[:len(lndos_ref)])
newhist = np.zeros_like(lndos_ref)
newhist[:len(myhist)] = myhist