mirror of
https://github.com/triqs/dft_tools
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60 lines
2.7 KiB
Python
60 lines
2.7 KiB
Python
################################################################################
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#
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# TRIQS: a Toolbox for Research in Interacting Quantum Systems
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#
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# Copyright (C) 2011 by M. Aichhorn, L. Pourovskii, V. Vildosola
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# Copyright (c) 2022-2023 Simons Foundation
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#
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# TRIQS is free software: you can redistribute it and/or modify it under the
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# terms of the GNU General Public License as published by the Free Software
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# Foundation, either version 3 of the License, or (at your option) any later
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# version.
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#
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# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
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# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
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# details.
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#
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# You should have received a copy of the GNU General Public License along with
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# TRIQS. If not, see <http://www.gnu.org/licenses/>.
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#
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# Authors: M. Aichhorn, S. Beck, A. Hampel, L. Pourovskii, V. Vildosola
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################################################################################
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from numpy import *
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from h5 import HDFArchive
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from triqs_dft_tools.converters.wien2k import *
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from triqs_dft_tools.sumk_dft import *
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from triqs_dft_tools.sumk_dft_tools import *
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from triqs_dft_tools.sumk_dft_transport import transport_distribution, init_spectroscopy, conductivity_and_seebeck, write_output_to_hdf
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from triqs.utility.comparison_tests import *
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from triqs.utility import h5diff
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beta = 40
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Converter = Wien2kConverter(filename='SrVO3', repacking=True)
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Converter.convert_dft_input()
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Converter.convert_transport_input()
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with HDFArchive('SrVO3_Sigma_transport.h5', 'r') as ar:
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Sigma = ar['dmft_transp_input']['Sigma_w']
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SK = SumkDFTTools(hdf_file='SrVO3.ref.h5', mesh=Sigma.mesh, use_dft_blocks=True)
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SK.set_Sigma([Sigma])
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SK.chemical_potential = ar['dmft_transp_input']['chemical_potential']
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SK.dc_imp = ar['dmft_transp_input']['dc_imp']
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SK = init_spectroscopy(SK, code='wien2k')
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Gamma_w, omega, Om_mesh = transport_distribution(SK, directions=['xx'], broadening=0.0, energy_window=[-0.3,0.3],
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Om_mesh=[0.00, 0.02], beta=beta, with_Sigma=True, code='wien2k')
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# SK.save(['Gamma_w','Om_meshr','omega','directions'])
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# SK.load(['Gamma_w','Om_meshr','omega','directions'])
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optic_cond, seebeck, kappa = conductivity_and_seebeck(Gamma_w, omega, Om_mesh, SK.SP, ['xx'], beta=beta)
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output_dict = {'seebeck': seebeck, 'optic_cond': optic_cond, 'kappa': kappa}
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# comparison of the output transport data
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if mpi.is_master_node():
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write_output_to_hdf(SK, output_dict, 'transp_output')
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out = HDFArchive('SrVO3.ref.h5','r')
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ref = HDFArchive('srvo3_transp.ref.h5', 'r')
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h5diff.compare('', out['transp_output'], ref['transp_output'], 0, 1e-8) |