def next_loop(self):
"""returns the DMFT loop nr. of the next loop"""
archive = HDFArchive(self.archive, 'r')
if archive.is_group('results'):
nl = archive['results']['n_dmft_loops']
else:
nl = 0
del archive
return nl
def run_dmft_loops(self, n_dmft_loops = 1):
"""runs the DMFT calculation"""
clp = p = CleanLoopParameters(self.get_parameters())
report = Reporter(**clp)
report('Parameters:', clp)
scheme = Scheme(**clp)
dmft = DMFTObjects(**clp)
raw_dmft = DMFTObjects(**clp)
g_0_c_iw, g_c_iw, sigma_c_iw, dmu = dmft.get_dmft_objs() # ref, ref, ref, value
report('Initializing...')
if clp['nambu']:
transf = NambuTransformation(**clp)
scheme.set_pretransf(transf.pretransformation(), transf.pretransformation_inverse())
raw_transf = NambuTransformation(**clp)
else:
transf = ClustersiteTransformation(g_loc = scheme.g_local(sigma_c_iw, dmu), **clp)
clp.update({'g_transf_struct': transf.get_g_struct()})
raw_transf = ClustersiteTransformation(**clp)
transf.set_hamiltonian(**clp)
report('Transformation ready')
report('New basis:', transf.get_g_struct())
impurity = Solver(beta = clp['beta'], gf_struct = dict(transf.get_g_struct()),
n_tau = clp['n_tau'], n_iw = clp['n_iw'], n_l = clp['n_legendre'])
impurity.Delta_tau.name = '$\\tilde{\\Delta}_c$'
rnames = random_generator_names_list()
report('H = ', transf.hamiltonian)
report('Impurity solver ready')
report('')
for loop_nr in range(self.next_loop(), self.next_loop() + n_dmft_loops):
report('DMFT-loop nr. %s'%loop_nr)
if mpi.is_master_node(): duration = time()
report('Calculating dmu...')
dmft.find_dmu(scheme, **clp)
g_0_c_iw, g_c_iw, sigma_c_iw, dmu = dmft.get_dmft_objs()
report('dmu = %s'%dmu)
report('Calculating local Greenfunction...')
g_c_iw << scheme.g_local(sigma_c_iw, dmu)
g_c_iw << addExtField(g_c_iw, p['ext_field'])
if mpi.is_master_node() and p['verbosity'] > 1: checksym_plot(g_c_iw, p['archive'][0:-3] + 'Gchecksym' + str(loop_nr) + '.pdf')
report('Calculating Weiss-field...')
g_0_c_iw << inverse(inverse(g_c_iw) + sigma_c_iw)
dmft.make_g_0_iw_with_delta_tau_real()
report('Changing basis...')
transf.set_dmft_objs(*dmft.get_dmft_objs())
if mpi.is_master_node() and p['verbosity'] > 1:
checktransf_plot(transf.get_g_iw(), p['archive'][0:-3] + 'Gchecktransf' + str(loop_nr) + '.pdf')
checktransf_plot(g_0_c_iw, p['archive'][0:-3] + 'Gweisscheck' + str(loop_nr) + '.pdf')
checksym_plot(inverse(transf.g_0_iw), p['archive'][0:-3] + 'invGweisscheckconst' + str(loop_nr) + '.pdf')
#checksym_plot(inverse(transf.get_g_iw()), p['archive'][0:-3] + 'invGsymcheckconst' + str(loop_nr) + '.pdf')
if not clp['random_name']: clp.update({'random_name': rnames[int((loop_nr + mpi.rank) % len(rnames))]}) # TODO move
if not clp['random_seed']: clp.update({'random_seed': 862379 * mpi.rank + 12563 * self.next_loop()})
impurity.G0_iw << transf.get_g_0_iw()
report('Solving impurity problem...')
mpi.barrier()
impurity.solve(h_int = transf.get_hamiltonian(), **clp.get_cthyb_parameters())
if mpi.is_master_node() and p['verbosity'] > 1:
checksym_plot(inverse(impurity.G0_iw), p['archive'][0:-3] + 'invGweisscheckconstsolver' + str(loop_nr) + '.pdf')
report('Postprocessing measurements...')
if clp['measure_g_l']:
for ind, g in transf.get_g_iw(): g << LegendreToMatsubara(impurity.G_l[ind])
else:
for ind, g in transf.get_g_iw(): g.set_from_fourier(impurity.G_tau[ind])
raw_transf.set_dmft_objs(transf.get_g_0_iw(),
transf.get_g_iw(),
inverse(transf.get_g_0_iw()) - inverse(transf.get_g_iw()))
if clp['measure_g_tau'] and clp['fit_tail']:
for ind, g in transf.get_g_iw():
for tind in transf.get_g_struct():
if tind[0] == ind: block_inds = tind[1]
fixed_moments = TailGf(len(block_inds), len(block_inds), 1, 1)
fixed_moments[1] = identity(len(block_inds))
g.fit_tail(fixed_moments, 3, clp['tail_start'], clp['n_iw'] - 1)
if mpi.is_master_node() and p['verbosity'] > 1: checksym_plot(inverse(transf.get_g_iw()), p['archive'][0:-3] + 'invGsymcheckconstsolver' + str(loop_nr) + '.pdf')
report('Backtransforming...')
transf.set_sigma_iw(inverse(transf.get_g_0_iw()) - inverse(transf.get_g_iw()))
dmft.set_dmft_objs(*transf.get_backtransformed_dmft_objs())
dmft.set_dmu(dmu)
raw_dmft.set_dmft_objs(*raw_transf.get_backtransformed_dmft_objs())
raw_dmft.set_dmu(dmu)
if clp['mix']: dmft.mix()
if clp['impose_paramagnetism']: dmft.paramagnetic()
if clp['impose_afm']: dmft.afm()
if clp['site_symmetries']: dmft.site_symmetric(clp['site_symmetries'])
density = scheme.apply_pretransf_inv(dmft.get_g_iw(), True).total_density()
report('Saving results...')
if mpi.is_master_node():
a = HDFArchive(p['archive'], 'a')
if not a.is_group('results'):
a.create_group('results')
a_r = a['results']
a_r.create_group(str(loop_nr))
a_l = a_r[str(loop_nr)]
a_l['g_c_iw'] = dmft.get_g_iw()
a_l['g_c_iw_raw'] = raw_dmft.get_g_iw()
a_l['g_transf_iw'] = transf.get_g_iw()
a_l['g_transf_iw_raw'] = raw_transf.get_g_iw()
a_l['sigma_c_iw'] = dmft.get_sigma_iw()
a_l['sigma_c_iw_raw'] = raw_dmft.get_sigma_iw()
a_l['sigma_transf_iw'] = transf.get_sigma_iw()
a_l['sigma_transf_iw_raw'] = raw_transf.get_sigma_iw()
a_l['g_0_c_iw'] = dmft.get_g_0_iw()
a_l['g_0_c_iw_raw'] = raw_dmft.get_g_0_iw()
a_l['g_0_transf_iw'] = transf.get_g_0_iw()
a_l['g_0_transf_iw_raw'] = raw_transf.get_g_0_iw()
a_l['dmu'] = dmft.get_dmu()
a_l['density'] = density
a_l['loop_time'] = {'seconds': time() - duration,
'hours': (time() - duration)/3600.,
'days': (time() - duration)/3600./24.}
a_l['n_cpu'] = mpi.size
a_l['cdmft_code_version'] = CDmft._version
clp_dict = dict()
clp_dict.update(clp)
a_l['parameters'] = clp_dict
a_l['triqs_code_version'] = version
a_l['delta_transf_tau'] = impurity.Delta_tau
if clp['measure_g_l']: a_l['g_transf_l'] = impurity.G_l
if clp['measure_g_tau']: a_l['g_transf_tau'] = impurity.G_tau
a_l['sign'] = impurity.average_sign
if clp['measure_density_matrix']: a_l['density_matrix'] = impurity.density_matrix
a_l['g_atomic_tau'] = impurity.atomic_gf
a_l['h_loc_diagonalization'] = impurity.h_loc_diagonalization
if a_r.is_data('n_dmft_loops'):
a_r['n_dmft_loops'] += 1
else:
a_r['n_dmft_loops'] = 1
del a_l, a_r, a
report('Loop done')
report('')
mpi.barrier()
import sys, numpy as np, os
from mpltotex import PRLPlotConf
from pytriqs.gf.local import GfReFreq, GfImTime, GfLegendre, GfImFreq
from pytriqs.archive import HDFArchive
from pytriqs.statistics.histograms import Histogram
mplcfg = PRLPlotConf(add_ax=False)
fig = mplcfg.fig
plt = mplcfg.plt
for archive_name in sys.argv[1:]:
archive = HDFArchive(archive_name, 'r')
if not archive.is_group('g_w'):
print 'g_w of ' + archive_name + ' not found'
continue
try:
histos = archive['histograms']
except:
print 'couldn\'t load histos of ' + archive_name
continue
ax0 = fig.add_axes([.17, .15 + .5, .82, .82 - .5])
hist = histos[0]
dx = (hist.limits[1] - hist.limits[0]) / len(hist)
x = np.linspace(hist.limits[0], hist.limits[1], len(hist.data))
y = hist.data
i_max = 0
for i, yi in enumerate(y):
if not np.allclose(yi, 0):
i_max = i
ax0.bar(x, y, dx, color='gray', linewidth=0.1)
#ax0.hist(hist.data, 20)
ax0.set_xlabel("$D$")
