Source code for dmft_tools.results_to_archive
################################################################################
#
# solid_dmft - A versatile python wrapper to perform DFT+DMFT calculations
# utilizing the TRIQS software library
#
# Copyright (C) 2018-2020, ETH Zurich
# Copyright (C) 2021, The Simons Foundation
# authors: A. Hampel, M. Merkel, and S. Beck
#
# solid_dmft is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# solid_dmft is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE. See the GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along with
# solid_dmft (in the file COPYING.txt in this directory). If not, see
# <http://www.gnu.org/licenses/>.
#
################################################################################
import os
from h5 import HDFArchive
import triqs.utility.mpi as mpi
[docs]
def _compile_information(sum_k, general_params, solver_params, solvers, map_imp_solver, solver_type_per_imp,
previous_mu, density_mat_pre, density_mat, deltaN, dens):
""" Collects all results in a dictonary. """
write_to_h5 = {'chemical_potential_post': sum_k.chemical_potential,
'chemical_potential_pre': previous_mu,
'DC_pot': sum_k.dc_imp,
'DC_energ': sum_k.dc_energ,
'dens_mat_pre': density_mat_pre,
'dens_mat_post': density_mat,
}
if deltaN is not None:
write_to_h5['deltaN'] = deltaN
if dens is not None:
write_to_h5['deltaN_trace'] = dens
if any(str(entry) in ('crpa_dynamic') for entry in general_params['dc_type']):
write_to_h5['DC_pot_dyn'] = sum_k.dc_imp_dyn
for icrsh in range(sum_k.n_inequiv_shells):
isolvsec = map_imp_solver[icrsh]
if solver_type_per_imp[icrsh] in ['cthyb', 'hubbardI']:
write_to_h5['Delta_time_{}'.format(icrsh)] = solvers[icrsh].Delta_time
# Write the full density matrix to last_iter only - it is large
if solver_params[isolvsec]['measure_density_matrix']:
write_to_h5['full_dens_mat_{}'.format(icrsh)] = solvers[icrsh].density_matrix
write_to_h5['h_loc_diag_{}'.format(icrsh)] = solvers[icrsh].h_loc_diagonalization
if solver_type_per_imp[icrsh] in ('cthyb','hubbardI'):
write_to_h5['Sigma_moments_{}'.format(icrsh)] = solvers[icrsh].Sigma_moments
write_to_h5['G_moments_{}'.format(icrsh)] = solvers[icrsh].G_moments
write_to_h5['Sigma_Hartree_{}'.format(icrsh)] = solvers[icrsh].Sigma_Hartree
write_to_h5['orbital_occupations_{}'.format(icrsh)] = solvers[icrsh].orbital_occupations
elif solver_type_per_imp[icrsh] == 'ftps':
write_to_h5['Delta_freq_{}'.format(icrsh)] = solvers[icrsh].Delta_freq
write_to_h5['Gimp_time_{}'.format(icrsh)] = solvers[icrsh].G_time
write_to_h5['G0_freq_{}'.format(icrsh)] = solvers[icrsh].G0_freq
write_to_h5['Gimp_freq_{}'.format(icrsh)] = solvers[icrsh].G_freq
write_to_h5['Sigma_freq_{}'.format(icrsh)] = solvers[icrsh].Sigma_freq
if solver_type_per_imp[icrsh] == 'cthyb':
if solver_params[isolvsec]['measure_pert_order']:
write_to_h5['pert_order_imp_{}'.format(icrsh)] = solvers[icrsh].perturbation_order
write_to_h5['pert_order_total_imp_{}'.format(icrsh)] = solvers[icrsh].perturbation_order_total
if solver_params[isolvsec]['measure_chi'] is not None:
write_to_h5['O_{}_time_{}'.format(solver_params[isolvsec]['measure_chi'], icrsh)] = solvers[icrsh].O_time
# if legendre was set, that we have both now!
if (solver_params[isolvsec]['measure_G_l']
or not solver_params[isolvsec]['perform_tail_fit'] and solver_params[isolvsec]['legendre_fit']):
write_to_h5['G_time_orig_{}'.format(icrsh)] = solvers[icrsh].G_time_orig
write_to_h5['Gimp_l_{}'.format(icrsh)] = solvers[icrsh].G_l
if solver_params[isolvsec]['crm_dyson_solver']:
write_to_h5['G_time_dlr_{}'.format(icrsh)] = solvers[icrsh].G_time_dlr
write_to_h5['Sigma_dlr_{}'.format(icrsh)] = solvers[icrsh].Sigma_dlr
if solver_type_per_imp[icrsh] == 'ctint' and solver_params[isolvsec]['measure_pert_order']:
write_to_h5['pert_order_imp_{}'.format(icrsh)] = solvers[icrsh].perturbation_order
if solver_type_per_imp[icrsh] == 'hubbardI':
write_to_h5['G0_Refreq_{}'.format(icrsh)] = solvers[icrsh].G0_Refreq
write_to_h5['Gimp_Refreq_{}'.format(icrsh)] = solvers[icrsh].G_Refreq
write_to_h5['Sigma_Refreq_{}'.format(icrsh)] = solvers[icrsh].Sigma_Refreq
if solver_params[isolvsec]['measure_G_l']:
write_to_h5['Gimp_l_{}'.format(icrsh)] = solvers[icrsh].G_l
if solver_type_per_imp[icrsh] == 'hartree':
write_to_h5['Sigma_Refreq_{}'.format(icrsh)] = solvers[icrsh].Sigma_Refreq
if solver_type_per_imp[icrsh] == 'ctseg':
# if legendre was set, that we have both now!
write_to_h5['orbital_occupations_{}'.format(icrsh)] = solvers[icrsh].orbital_occupations
write_to_h5['Sigma_Hartree_{}'.format(icrsh)] = solvers[icrsh].Sigma_Hartree
write_to_h5['Sigma_moments_{}'.format(icrsh)] = solvers[icrsh].Sigma_moments
if (solver_params[isolvsec]['legendre_fit']):
write_to_h5['G_time_orig_{}'.format(icrsh)] = solvers[icrsh].G_time_orig
write_to_h5['Gimp_l_{}'.format(icrsh)] = solvers[icrsh].G_l
if solver_params[isolvsec]['improved_estimator']:
write_to_h5['F_freq_{}'.format(icrsh)] = solvers[icrsh].F_freq
write_to_h5['F_time_{}'.format(icrsh)] = solvers[icrsh].F_time
if solver_params[isolvsec]['measure_pert_order']:
write_to_h5['pert_order_histo_imp_{}'.format(icrsh)] = solvers[icrsh].perturbation_order_histo
write_to_h5['avg_order_imp_{}.format(icrsh)'] = solvers[icrsh].avg_pert_order
if solver_params[isolvsec]['measure_nn_tau']:
write_to_h5['O_NN_{}'.format(icrsh)] = solvers[icrsh].triqs_solver.results.nn_tau
if solver_params[isolvsec]['measure_state_hist']:
write_to_h5['state_hist_{}'.format(icrsh)] = solvers[icrsh].state_histogram
if solver_params[isolvsec]['crm_dyson_solver']:
write_to_h5['G_time_dlr_{}'.format(icrsh)] = solvers[icrsh].G_time_dlr
write_to_h5['Sigma_dlr_{}'.format(icrsh)] = solvers[icrsh].Sigma_dlr
if general_params['h_int_type'][icrsh] == 'dyn_density_density':
write_to_h5['D0_time_{}'.format(icrsh)] = solvers[icrsh].triqs_solver.D0_tau
write_to_h5['Jperp_time_{}'.format(icrsh)] = solvers[icrsh].triqs_solver.Jperp_tau
return write_to_h5
[docs]
def write(archive, sum_k, general_params, solver_params, solvers, map_imp_solver, solver_type_per_imp, it, is_sampling,
previous_mu, density_mat_pre, density_mat, deltaN=None, dens=None):
"""
Collects and writes results to archive.
"""
if not mpi.is_master_node():
return
write_to_h5 = _compile_information(sum_k, general_params, solver_params, solvers, map_imp_solver, solver_type_per_imp,
previous_mu, density_mat_pre, density_mat, deltaN, dens)
# Saves the results to last_iter
with HDFArchive(archive, 'a') as ar:
ar['DMFT_results']['iteration_count'] = it
for key, value in write_to_h5.items():
ar['DMFT_results/last_iter'][key] = value
# Permanently saves to h5 archive every h5_save_freq iterations
if ((not is_sampling and it % general_params['h5_save_freq'] == 0)
or (is_sampling and it % general_params['sampling_h5_save_freq'] == 0)):
ar['DMFT_results'].create_group('it_{}'.format(it))
for key, value in write_to_h5.items():
# Full density matrix only written to last_iter - it is large
if 'full_dens_mat_' not in key and 'h_loc_diag_' not in key:
ar['DMFT_results/it_{}'.format(it)][key] = value
# Saves CSC input
if general_params['csc']:
for dft_var in ['dft_update', 'dft_input', 'dft_misc_input']:
if dft_var in ar:
ar['DMFT_results/it_{}'.format(it)].create_group(dft_var)
for key, value in ar[dft_var].items():
# do only store changing elements
if key not in ['symm_kpath', 'kpts_cart']:
ar['DMFT_results/it_{}'.format(it)][dft_var][key] = value
for band_elem in ['_bands.dat', '_bands.dat.gnu', '_bands.projwfc_up', '_band.dat']:
if os.path.isfile('./{}{}'.format(general_params['seedname'], band_elem)):
os.rename('./{}{}'.format(general_params['seedname'], band_elem),
'./{}{}_it{}'.format(general_params['seedname'], band_elem, it))
for w90_elem in ['_hr.dat', '.wout']:
if os.path.isfile('./{}{}'.format(general_params['seedname'], w90_elem)):
os.rename('./{}{}'.format(general_params['seedname'], w90_elem),
'./{}_it{}{}'.format(general_params['seedname'], it, w90_elem))