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https://github.com/triqs/dft_tools
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change del to with when reading hdf
This commit is contained in:
Manuel
parent
85c8c2b58c
commit
a8c7569830
@ -1,147 +0,0 @@
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import pytriqs.utility.mpi as mpi
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from pytriqs.operators.util import *
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from pytriqs.archive import HDFArchive
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from triqs_cthyb import *
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from pytriqs.gf import *
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from triqs_dft_tools.sumk_dft import *
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from triqs_dft_tools.converters.wien2k_converter import *
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dft_filename='Gd_fcc'
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U = 9.6
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J = 0.8
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beta = 40
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loops = 10 # Number of DMFT sc-loops
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sigma_mix = 1.0 # Mixing factor of Sigma after solution of the AIM
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delta_mix = 1.0 # Mixing factor of Delta as input for the AIM
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dc_type = 0 # DC type: 0 FLL, 1 Held, 2 AMF
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use_blocks = True # use bloc structure from DFT input
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prec_mu = 0.0001
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h_field = 0.0
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# Solver parameters
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p = {}
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p["max_time"] = -1
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p["length_cycle"] = 50
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p["n_warmup_cycles"] = 50
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p["n_cycles"] = 5000
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Converter = Wien2kConverter(filename=dft_filename, repacking=True)
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Converter.convert_dft_input()
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mpi.barrier()
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previous_runs = 0
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previous_present = False
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if mpi.is_master_node():
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f = HDFArchive(dft_filename+'.h5','a')
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if 'dmft_output' in f:
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ar = f['dmft_output']
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if 'iterations' in ar:
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previous_present = True
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previous_runs = ar['iterations']
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else:
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f.create_group('dmft_output')
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del f
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previous_runs = mpi.bcast(previous_runs)
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previous_present = mpi.bcast(previous_present)
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SK=SumkDFT(hdf_file=dft_filename+'.h5',use_dft_blocks=use_blocks,h_field=h_field)
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n_orb = SK.corr_shells[0]['dim']
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l = SK.corr_shells[0]['l']
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spin_names = ["up","down"]
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orb_names = [i for i in range(n_orb)]
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# Use GF structure determined by DFT blocks
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gf_struct = [(block, indices) for block, indices in SK.gf_struct_solver[0].iteritems()]
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# Construct U matrix for density-density calculations
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Umat, Upmat = U_matrix_kanamori(n_orb=n_orb, U_int=U, J_hund=J)
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# Construct Hamiltonian and solver
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h_int = h_int_density(spin_names, orb_names, map_operator_structure=SK.sumk_to_solver[0], U=Umat, Uprime=Upmat, H_dump="H.txt")
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S = Solver(beta=beta, gf_struct=gf_struct)
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if previous_present:
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chemical_potential = 0
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dc_imp = 0
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dc_energ = 0
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if mpi.is_master_node():
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S.Sigma_iw << HDFArchive(dft_filename+'.h5','a')['dmft_output']['Sigma_iw']
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chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
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S.Sigma_iw << mpi.bcast(S.Sigma_iw)
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chemical_potential = mpi.bcast(chemical_potential)
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dc_imp = mpi.bcast(dc_imp)
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dc_energ = mpi.bcast(dc_energ)
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SK.set_mu(chemical_potential)
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SK.set_dc(dc_imp,dc_energ)
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for iteration_number in range(1,loops+1):
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if mpi.is_master_node(): print "Iteration = ", iteration_number
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SK.symm_deg_gf(S.Sigma_iw,orb=0) # symmetrise Sigma
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SK.set_Sigma([ S.Sigma_iw ]) # set Sigma into the SumK class
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chemical_potential = SK.calc_mu( precision = prec_mu ) # find the chemical potential for given density
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S.G_iw << SK.extract_G_loc()[0] # calc the local Green function
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mpi.report("Total charge of Gloc : %.6f"%S.G_iw.total_density())
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# Init the DC term and the real part of Sigma, if no previous runs found:
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if (iteration_number==1 and previous_present==False):
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dm = S.G_iw.density()
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SK.calc_dc(dm, U_interact = U, J_hund = J, orb = 0, use_dc_formula = dc_type)
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S.Sigma_iw << SK.dc_imp[0]['up'][0,0]
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# Calculate new G0_iw to input into the solver:
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if mpi.is_master_node():
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# We can do a mixing of Delta in order to stabilize the DMFT iterations:
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S.G0_iw << S.Sigma_iw + inverse(S.G_iw)
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ar = HDFArchive(dft_filename+'.h5','a')['dmft_output']
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if (iteration_number>1 or previous_present):
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mpi.report("Mixing input Delta with factor %s"%delta_mix)
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Delta = (delta_mix * delta(S.G0_iw)) + (1.0-delta_mix) * ar['Delta_iw']
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S.G0_iw << S.G0_iw + delta(S.G0_iw) - Delta
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ar['Delta_iw'] = delta(S.G0_iw)
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S.G0_iw << inverse(S.G0_iw)
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del ar
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S.G0_iw << mpi.bcast(S.G0_iw)
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# Solve the impurity problem:
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S.solve(h_int=h_int, **p)
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# Solved. Now do post-processing:
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mpi.report("Total charge of impurity problem : %.6f"%S.G_iw.total_density())
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# Now mix Sigma and G with factor sigma_mix, if wanted:
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if (iteration_number>1 or previous_present):
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if mpi.is_master_node():
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ar = HDFArchive(dft_filename+'.h5','a')['dmft_output']
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mpi.report("Mixing Sigma and G with factor %s"%sigma_mix)
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S.Sigma_iw << sigma_mix * S.Sigma_iw + (1.0-sigma_mix) * ar['Sigma_iw']
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S.G_iw << sigma_mix * S.G_iw + (1.0-sigma_mix) * ar['G_iw']
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del ar
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S.G_iw << mpi.bcast(S.G_iw)
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S.Sigma_iw << mpi.bcast(S.Sigma_iw)
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# Write the final Sigma and G to the hdf5 archive:
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if mpi.is_master_node():
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ar = HDFArchive(dft_filename+'.h5','a')['dmft_output']
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if previous_runs: iteration_number += previous_runs
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ar['iterations'] = iteration_number
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ar['G_tau'] = S.G_tau
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ar['G_iw'] = S.G_iw
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ar['Sigma_iw'] = S.Sigma_iw
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ar['G0-%s'%(iteration_number)] = S.G0_iw
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ar['G-%s'%(iteration_number)] = S.G_iw
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ar['Sigma-%s'%(iteration_number)] = S.Sigma_iw
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del ar
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# Set the new double counting:
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dm = S.G_iw.density() # compute the density matrix of the impurity problem
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SK.calc_dc(dm, U_interact = U, J_hund = J, orb = 0, use_dc_formula = dc_type)
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# Save stuff into the dft_output group of hdf5 archive in case of rerun:
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SK.save(['chemical_potential','dc_imp','dc_energ'])
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if mpi.is_master_node():
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ar = HDFArchive("dftdmft.h5",'w')
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ar["G_tau"] = S.G_tau
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ar["G_iw"] = S.G_iw
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ar["Sigma_iw"] = S.Sigma_iw
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@ -40,8 +40,8 @@ If required, we have to load and initialise the real-frequency self energy. Most
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you have your self energy already stored as a real-frequency :class:`BlockGf <pytriqs.gf.BlockGf>` object
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in a hdf5 file::
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ar = HDFArchive('case.h5', 'a')
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SigmaReFreq = ar['dmft_output']['Sigma_w']
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with HDFArchive('case.h5', 'r') as ar:
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SigmaReFreq = ar['dmft_output']['Sigma_w']
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You may also have your self energy stored in text files. For this case the :ref:`TRIQS <triqslibs:welcome>` library offers
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the function :meth:`read_gf_from_txt`, which is able to load the data from text files of one Green function block
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@ -73,7 +73,6 @@ and additionally set the chemical potential and the double counting correction f
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chemical_potential, dc_imp, dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
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SK.set_mu(chemical_potential)
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SK.set_dc(dc_imp,dc_energ)
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del ar
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.. _dos_wannier:
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@ -106,15 +106,15 @@ are present, or if the calculation should start from scratch::
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previous_runs = 0
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previous_present = False
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if mpi.is_master_node():
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f = HDFArchive(dft_filename+'.h5','a')
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if 'dmft_output' in f:
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ar = f['dmft_output']
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if 'iterations' in ar:
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previous_present = True
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previous_runs = ar['iterations']
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with HDFArchive(dft_filename+'.h5','a') as f:
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if 'dmft_output' in f:
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ar = f['dmft_output']
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if 'iterations' in ar:
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previous_present = True
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previous_runs = ar['iterations']
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else:
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f.create_group('dmft_output')
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del f
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previous_runs = mpi.bcast(previous_runs)
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previous_present = mpi.bcast(previous_present)
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@ -126,9 +126,8 @@ double counting values of the last iteration::
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if previous_present:
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if mpi.is_master_node():
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ar = HDFArchive(dft_filename+'.h5','a')
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S.Sigma_iw << ar['dmft_output']['Sigma_iw']
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del ar
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with HDFArchive(dft_filename+'.h5','r') as ar:
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S.Sigma_iw << ar['dmft_output']['Sigma_iw']
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S.Sigma_iw << mpi.bcast(S.Sigma_iw)
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chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
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@ -153,11 +152,10 @@ functions) can be necessary in order to ensure convergence::
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mix = 0.8 # mixing factor
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if (iteration_number>1 or previous_present):
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if mpi.is_master_node():
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ar = HDFArchive(dft_filename+'.h5','a')
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mpi.report("Mixing Sigma and G with factor %s"%mix)
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S.Sigma_iw << mix * S.Sigma_iw + (1.0-mix) * ar['dmft_output']['Sigma_iw']
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S.G_iw << mix * S.G_iw + (1.0-mix) * ar['dmft_output']['G_iw']
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del ar
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with HDFArchive(dft_filename+'.h5','r') as ar:
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mpi.report("Mixing Sigma and G with factor %s"%mix)
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S.Sigma_iw << mix * S.Sigma_iw + (1.0-mix) * ar['dmft_output']['Sigma_iw']
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S.G_iw << mix * S.G_iw + (1.0-mix) * ar['dmft_output']['G_iw']
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S.G_iw << mpi.bcast(S.G_iw)
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S.Sigma_iw << mpi.bcast(S.Sigma_iw)
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@ -96,12 +96,11 @@ The converter :meth:`convert_transport_input <dft.converters.wien2k_converter.Wi
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reads the required data of the Wien2k output and stores it in the `dft_transp_input` subgroup of your hdf file.
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Additionally we need to read and set the self energy, the chemical potential and the double counting::
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ar = HDFArchive('case.h5', 'a')
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SK.set_Sigma([ar['dmft_output']['Sigma_w']])
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chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
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SK.set_mu(chemical_potential)
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SK.set_dc(dc_imp,dc_energ)
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del ar
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with HDFArchive('case.h5', 'r') as ar:
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SK.set_Sigma([ar['dmft_output']['Sigma_w']])
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chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
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SK.set_mu(chemical_potential)
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SK.set_dc(dc_imp,dc_energ)
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As next step we can calculate the transport distribution :math:`\Gamma_{\alpha\beta}(\omega)`::
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@ -22,15 +22,14 @@ mpi.barrier()
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previous_runs = 0
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previous_present = False
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if mpi.is_master_node():
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f = HDFArchive(dft_filename+'.h5','a')
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if 'dmft_output' in f:
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ar = f['dmft_output']
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if 'iterations' in ar:
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previous_present = True
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previous_runs = ar['iterations']
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else:
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f.create_group('dmft_output')
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del f
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with HDFArchive(dft_filename+'.h5','a') as f:
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if 'dmft_output' in f:
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ar = f['dmft_output']
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if 'iterations' in ar:
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previous_present = True
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previous_runs = ar['iterations']
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else:
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f.create_group('dmft_output')
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previous_runs = mpi.bcast(previous_runs)
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previous_present = mpi.bcast(previous_present)
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@ -47,9 +46,8 @@ chemical_potential=chemical_potential_init
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# load previous data: old self-energy, chemical potential, DC correction
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if previous_present:
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if mpi.is_master_node():
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ar = HDFArchive(dft_filename+'.h5','a')
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S.Sigma << ar['dmft_output']['Sigma']
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del ar
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with HDFArchive(dft_filename+'.h5','r') as ar:
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S.Sigma << ar['dmft_output']['Sigma']
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SK.chemical_potential,SK.dc_imp,SK.dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
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S.Sigma << mpi.bcast(S.Sigma)
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SK.chemical_potential = mpi.bcast(SK.chemical_potential)
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@ -87,11 +85,10 @@ for iteration_number in range(1,Loops+1):
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# Now mix Sigma and G with factor Mix, if wanted:
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if (iteration_number>1 or previous_present):
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if (mpi.is_master_node() and (mixing<1.0)):
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ar = HDFArchive(dft_filename+'.h5','a')
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mpi.report("Mixing Sigma and G with factor %s"%mixing)
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S.Sigma << mixing * S.Sigma + (1.0-mixing) * ar['dmft_output']['Sigma']
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S.G << mixing * S.G + (1.0-mixing) * ar['dmft_output']['G']
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del ar
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with HDFArchive(dft_filename+'.h5','r') as ar:
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mpi.report("Mixing Sigma and G with factor %s"%mixing)
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S.Sigma << mixing * S.Sigma + (1.0-mixing) * ar['dmft_output']['Sigma']
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S.G << mixing * S.G + (1.0-mixing) * ar['dmft_output']['G']
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S.G << mpi.bcast(S.G)
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S.Sigma << mpi.bcast(S.Sigma)
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@ -106,11 +103,10 @@ for iteration_number in range(1,Loops+1):
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# store the impurity self-energy, GF as well as correlation energy in h5
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if mpi.is_master_node():
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ar = HDFArchive(dft_filename+'.h5','a')
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ar['dmft_output']['iterations'] = iteration_number + previous_runs
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ar['dmft_output']['G'] = S.G
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ar['dmft_output']['Sigma'] = S.Sigma
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del ar
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with HDFArchive(dft_filename+'.h5','a') as ar:
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ar['dmft_output']['iterations'] = iteration_number + previous_runs
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ar['dmft_output']['G'] = S.G
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ar['dmft_output']['Sigma'] = S.Sigma
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#Save essential SumkDFT data:
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SK.save(['chemical_potential','dc_imp','dc_energ','correnerg'])
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@ -38,15 +38,15 @@ p["fit_max_n"] = 60
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previous_runs = 0
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previous_present = False
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if mpi.is_master_node():
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f = HDFArchive(dft_filename+'.h5','a')
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if 'dmft_output' in f:
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ar = f['dmft_output']
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if 'iterations' in ar:
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previous_present = True
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previous_runs = ar['iterations']
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else:
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f.create_group('dmft_output')
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del f
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with HDFArchive(dft_filename+'.h5','a') as f:
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if 'dmft_output' in f:
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ar = f['dmft_output']
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if 'iterations' in ar:
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previous_present = True
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previous_runs = ar['iterations']
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else:
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f.create_group('dmft_output')
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previous_runs = mpi.bcast(previous_runs)
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previous_present = mpi.bcast(previous_present)
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@ -72,9 +72,8 @@ if previous_present:
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dc_imp = 0
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dc_energ = 0
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if mpi.is_master_node():
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ar = HDFArchive(dft_filename+'.h5','a')
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S.Sigma_iw << ar['dmft_output']['Sigma_iw']
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del ar
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with HDFArchive(dft_filename+'.h5','r') as ar:
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S.Sigma_iw << ar['dmft_output']['Sigma_iw']
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chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
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S.Sigma_iw << mpi.bcast(S.Sigma_iw)
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chemical_potential = mpi.bcast(chemical_potential)
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@ -103,14 +102,13 @@ for iteration_number in range(1,loops+1):
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# We can do a mixing of Delta in order to stabilize the DMFT iterations:
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S.G0_iw << S.Sigma_iw + inverse(S.G_iw)
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# The following lines are uncommented until issue #98 is fixed in TRIQS
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# ar = HDFArchive(dft_filename+'.h5','a')
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# if (iteration_number>1 or previous_present):
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# mpi.report("Mixing input Delta with factor %s"%delta_mix)
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# Delta = (delta_mix * delta(S.G0_iw)) + (1.0-delta_mix) * ar['dmft_output']['Delta_iw']
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# S.G0_iw << S.G0_iw + delta(S.G0_iw) - Delta
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# ar['dmft_output']['Delta_iw'] = delta(S.G0_iw)
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# with HDFArchive(dft_filename+'.h5','a') as ar:
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# if (iteration_number>1 or previous_present):
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# mpi.report("Mixing input Delta with factor %s"%delta_mix)
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# Delta = (delta_mix * delta(S.G0_iw)) + (1.0-delta_mix) * ar['dmft_output']['Delta_iw']
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# S.G0_iw << S.G0_iw + delta(S.G0_iw) - Delta
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# ar['dmft_output']['Delta_iw'] = delta(S.G0_iw)
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S.G0_iw << inverse(S.G0_iw)
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# del ar
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S.G0_iw << mpi.bcast(S.G0_iw)
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@ -123,25 +121,24 @@ for iteration_number in range(1,loops+1):
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# Now mix Sigma and G with factor sigma_mix, if wanted:
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if (iteration_number>1 or previous_present):
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if mpi.is_master_node():
|
||||
ar = HDFArchive(dft_filename+'.h5','a')
|
||||
mpi.report("Mixing Sigma and G with factor %s"%sigma_mix)
|
||||
S.Sigma_iw << sigma_mix * S.Sigma_iw + (1.0-sigma_mix) * ar['dmft_output']['Sigma_iw']
|
||||
S.G_iw << sigma_mix * S.G_iw + (1.0-sigma_mix) * ar['dmft_output']['G_iw']
|
||||
del ar
|
||||
with HDFArchive(dft_filename+'.h5','r') as ar:
|
||||
mpi.report("Mixing Sigma and G with factor %s"%sigma_mix)
|
||||
S.Sigma_iw << sigma_mix * S.Sigma_iw + (1.0-sigma_mix) * ar['dmft_output']['Sigma_iw']
|
||||
S.G_iw << sigma_mix * S.G_iw + (1.0-sigma_mix) * ar['dmft_output']['G_iw']
|
||||
|
||||
S.G_iw << mpi.bcast(S.G_iw)
|
||||
S.Sigma_iw << mpi.bcast(S.Sigma_iw)
|
||||
|
||||
# Write the final Sigma and G to the hdf5 archive:
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(dft_filename+'.h5','a')
|
||||
ar['dmft_output']['iterations'] = iteration_number + previous_runs
|
||||
ar['dmft_output']['G_tau'] = S.G_tau
|
||||
ar['dmft_output']['G_iw'] = S.G_iw
|
||||
ar['dmft_output']['Sigma_iw'] = S.Sigma_iw
|
||||
ar['dmft_output']['G0-%s'%(iteration_number)] = S.G0_iw
|
||||
ar['dmft_output']['G-%s'%(iteration_number)] = S.G_iw
|
||||
ar['dmft_output']['Sigma-%s'%(iteration_number)] = S.Sigma_iw
|
||||
del ar
|
||||
with ar = HDFArchive(dft_filename+'.h5','a') as ar:
|
||||
ar['dmft_output']['iterations'] = iteration_number + previous_runs
|
||||
ar['dmft_output']['G_tau'] = S.G_tau
|
||||
ar['dmft_output']['G_iw'] = S.G_iw
|
||||
ar['dmft_output']['Sigma_iw'] = S.Sigma_iw
|
||||
ar['dmft_output']['G0-%s'%(iteration_number)] = S.G0_iw
|
||||
ar['dmft_output']['G-%s'%(iteration_number)] = S.G_iw
|
||||
ar['dmft_output']['Sigma-%s'%(iteration_number)] = S.Sigma_iw
|
||||
|
||||
# Set the new double counting:
|
||||
dm = S.G_iw.density() # compute the density matrix of the impurity problem
|
||||
|
||||
@ -39,15 +39,14 @@ p["fit_max_n"] = 60
|
||||
previous_runs = 0
|
||||
previous_present = False
|
||||
if mpi.is_master_node():
|
||||
f = HDFArchive(dft_filename+'.h5','a')
|
||||
if 'dmft_output' in f:
|
||||
ar = f['dmft_output']
|
||||
if 'iterations' in ar:
|
||||
previous_present = True
|
||||
previous_runs = ar['iterations']
|
||||
else:
|
||||
f.create_group('dmft_output')
|
||||
del f
|
||||
with HDFArchive(dft_filename+'.h5','a') as f:
|
||||
if 'dmft_output' in f:
|
||||
ar = f['dmft_output']
|
||||
if 'iterations' in ar:
|
||||
previous_present = True
|
||||
previous_runs = ar['iterations']
|
||||
else:
|
||||
f.create_group('dmft_output')
|
||||
previous_runs = mpi.bcast(previous_runs)
|
||||
previous_present = mpi.bcast(previous_present)
|
||||
|
||||
@ -75,9 +74,8 @@ if previous_present:
|
||||
dc_imp = 0
|
||||
dc_energ = 0
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(dft_filename+'.h5','a')
|
||||
S.Sigma_iw << ar['dmft_output']['Sigma_iw']
|
||||
del ar
|
||||
with HDFArchive(dft_filename+'.h5','r') as ar:
|
||||
S.Sigma_iw << ar['dmft_output']['Sigma_iw']
|
||||
chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
|
||||
S.Sigma_iw << mpi.bcast(S.Sigma_iw)
|
||||
chemical_potential = mpi.bcast(chemical_potential)
|
||||
@ -106,14 +104,13 @@ for iteration_number in range(1,loops+1):
|
||||
# We can do a mixing of Delta in order to stabilize the DMFT iterations:
|
||||
S.G0_iw << S.Sigma_iw + inverse(S.G_iw)
|
||||
# The following lines are uncommented until issue #98 is fixed in TRIQS
|
||||
# ar = HDFArchive(dft_filename+'.h5','a')
|
||||
# if (iteration_number>1 or previous_present):
|
||||
# mpi.report("Mixing input Delta with factor %s"%delta_mix)
|
||||
# Delta = (delta_mix * delta(S.G0_iw)) + (1.0-delta_mix) * ar['dmft_output']['Delta_iw']
|
||||
# S.G0_iw << S.G0_iw + delta(S.G0_iw) - Delta
|
||||
# ar['dmft_output']['Delta_iw'] = delta(S.G0_iw)
|
||||
# with HDFArchive(dft_filename+'.h5','a') as ar:
|
||||
# if (iteration_number>1 or previous_present):
|
||||
# mpi.report("Mixing input Delta with factor %s"%delta_mix)
|
||||
# Delta = (delta_mix * delta(S.G0_iw)) + (1.0-delta_mix) * ar['dmft_output']['Delta_iw']
|
||||
# S.G0_iw << S.G0_iw + delta(S.G0_iw) - Delta
|
||||
# ar['dmft_output']['Delta_iw'] = delta(S.G0_iw)
|
||||
S.G0_iw << inverse(S.G0_iw)
|
||||
# del ar
|
||||
|
||||
S.G0_iw << mpi.bcast(S.G0_iw)
|
||||
|
||||
@ -126,25 +123,23 @@ for iteration_number in range(1,loops+1):
|
||||
# Now mix Sigma and G with factor sigma_mix, if wanted:
|
||||
if (iteration_number>1 or previous_present):
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(dft_filename+'.h5','a')
|
||||
mpi.report("Mixing Sigma and G with factor %s"%sigma_mix)
|
||||
S.Sigma_iw << sigma_mix * S.Sigma_iw + (1.0-sigma_mix) * ar['dmft_output']['Sigma_iw']
|
||||
S.G_iw << sigma_mix * S.G_iw + (1.0-sigma_mix) * ar['dmft_output']['G_iw']
|
||||
del ar
|
||||
with HDFArchive(dft_filename+'.h5','r') as ar:
|
||||
mpi.report("Mixing Sigma and G with factor %s"%sigma_mix)
|
||||
S.Sigma_iw << sigma_mix * S.Sigma_iw + (1.0-sigma_mix) * ar['dmft_output']['Sigma_iw']
|
||||
S.G_iw << sigma_mix * S.G_iw + (1.0-sigma_mix) * ar['dmft_output']['G_iw']
|
||||
S.G_iw << mpi.bcast(S.G_iw)
|
||||
S.Sigma_iw << mpi.bcast(S.Sigma_iw)
|
||||
|
||||
# Write the final Sigma and G to the hdf5 archive:
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(dft_filename+'.h5','a')
|
||||
ar['dmft_output']['iterations'] = iteration_number + previous_runs
|
||||
ar['dmft_output']['G_tau'] = S.G_tau
|
||||
ar['dmft_output']['G_iw'] = S.G_iw
|
||||
ar['dmft_output']['Sigma_iw'] = S.Sigma_iw
|
||||
ar['dmft_output']['G0-%s'%(iteration_number)] = S.G0_iw
|
||||
ar['dmft_output']['G-%s'%(iteration_number)] = S.G_iw
|
||||
ar['dmft_output']['Sigma-%s'%(iteration_number)] = S.Sigma_iw
|
||||
del ar
|
||||
with HDFArchive(dft_filename+'.h5','a') as ar:
|
||||
ar['dmft_output']['iterations'] = iteration_number + previous_runs
|
||||
ar['dmft_output']['G_tau'] = S.G_tau
|
||||
ar['dmft_output']['G_iw'] = S.G_iw
|
||||
ar['dmft_output']['Sigma_iw'] = S.Sigma_iw
|
||||
ar['dmft_output']['G0-%s'%(iteration_number)] = S.G0_iw
|
||||
ar['dmft_output']['G-%s'%(iteration_number)] = S.G_iw
|
||||
ar['dmft_output']['Sigma-%s'%(iteration_number)] = S.Sigma_iw
|
||||
|
||||
# Set the new double counting:
|
||||
dm = S.G_iw.density() # compute the density matrix of the impurity problem
|
||||
|
||||
@ -205,23 +205,21 @@ some additional refinements::
|
||||
# Now mix Sigma and G with factor mix, if wanted:
|
||||
if (iteration_number>1 or previous_present):
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(dft_filename+'.h5','a')
|
||||
mpi.report("Mixing Sigma and G with factor %s"%mix)
|
||||
S.Sigma_iw << mix * S.Sigma_iw + (1.0-mix) * ar['dmft_output']['Sigma_iw']
|
||||
S.G_iw << mix * S.G_iw + (1.0-mix) * ar['dmft_output']['G_iw']
|
||||
del ar
|
||||
with HDFArchive(dft_filename+'.h5','r') as ar:
|
||||
mpi.report("Mixing Sigma and G with factor %s"%mix)
|
||||
S.Sigma_iw << mix * S.Sigma_iw + (1.0-mix) * ar['dmft_output']['Sigma_iw']
|
||||
S.G_iw << mix * S.G_iw + (1.0-mix) * ar['dmft_output']['G_iw']
|
||||
S.G_iw << mpi.bcast(S.G_iw)
|
||||
S.Sigma_iw << mpi.bcast(S.Sigma_iw)
|
||||
|
||||
# Write the final Sigma and G to the hdf5 archive:
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(dft_filename+'.h5','a')
|
||||
ar['dmft_output']['iterations'] = iteration_number
|
||||
ar['dmft_output']['G_0'] = S.G0_iw
|
||||
ar['dmft_output']['G_tau'] = S.G_tau
|
||||
ar['dmft_output']['G_iw'] = S.G_iw
|
||||
ar['dmft_output']['Sigma_iw'] = S.Sigma_iw
|
||||
del ar
|
||||
with HDFArchive(dft_filename+'.h5','a') as ar:
|
||||
ar['dmft_output']['iterations'] = iteration_number
|
||||
ar['dmft_output']['G_0'] = S.G0_iw
|
||||
ar['dmft_output']['G_tau'] = S.G_tau
|
||||
ar['dmft_output']['G_iw'] = S.G_iw
|
||||
ar['dmft_output']['Sigma_iw'] = S.Sigma_iw
|
||||
|
||||
# Set the new double counting:
|
||||
dm = S.G_iw.density() # compute the density matrix of the impurity problem
|
||||
|
||||
@ -260,13 +260,12 @@ class HkConverter(ConverterTools):
|
||||
R.close()
|
||||
|
||||
# Save to the HDF5:
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
if not (self.dft_subgrp in ar):
|
||||
ar.create_group(self.dft_subgrp)
|
||||
things_to_save = ['energy_unit', 'n_k', 'k_dep_projection', 'SP', 'SO', 'charge_below', 'density_required',
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
if not (self.dft_subgrp in ar):
|
||||
ar.create_group(self.dft_subgrp)
|
||||
things_to_save = ['energy_unit', 'n_k', 'k_dep_projection', 'SP', 'SO', 'charge_below', 'density_required',
|
||||
'symm_op', 'n_shells', 'shells', 'n_corr_shells', 'corr_shells', 'use_rotations', 'rot_mat',
|
||||
'rot_mat_time_inv', 'n_reps', 'dim_reps', 'T', 'n_orbitals', 'proj_mat', 'bz_weights', 'hopping',
|
||||
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr']
|
||||
for it in things_to_save:
|
||||
ar[self.dft_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
for it in things_to_save:
|
||||
ar[self.dft_subgrp][it] = locals()[it]
|
||||
|
||||
@ -44,10 +44,9 @@ class TestSumkDFT(SumkDFT):
|
||||
fermi_weights = 0
|
||||
band_window = 0
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(self.hdf_file,'r')
|
||||
fermi_weights = ar['dft_misc_input']['dft_fermi_weights']
|
||||
band_window = ar['dft_misc_input']['band_window']
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file,'r') as ar:
|
||||
fermi_weights = ar['dft_misc_input']['dft_fermi_weights']
|
||||
band_window = ar['dft_misc_input']['band_window']
|
||||
fermi_weights = mpi.bcast(fermi_weights)
|
||||
band_window = mpi.bcast(band_window)
|
||||
|
||||
@ -184,10 +183,9 @@ class TestSumkDFT(SumkDFT):
|
||||
fermi_weights = 0
|
||||
band_window = 0
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(self.hdf_file,'r')
|
||||
fermi_weights = ar['dft_misc_input']['dft_fermi_weights']
|
||||
band_window = ar['dft_misc_input']['band_window']
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file,'r') as ar:
|
||||
fermi_weights = ar['dft_misc_input']['dft_fermi_weights']
|
||||
band_window = ar['dft_misc_input']['band_window']
|
||||
fermi_weights = mpi.bcast(fermi_weights)
|
||||
band_window = mpi.bcast(band_window)
|
||||
|
||||
@ -282,14 +280,13 @@ def dmft_cycle():
|
||||
previous_present = False
|
||||
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(HDFfilename,'a')
|
||||
if 'iterations' in ar:
|
||||
previous_present = True
|
||||
previous_runs = ar['iterations']
|
||||
else:
|
||||
previous_runs = 0
|
||||
previous_present = False
|
||||
del ar
|
||||
with HDFArchive(HDFfilename,'a') as ar:
|
||||
if 'iterations' in ar:
|
||||
previous_present = True
|
||||
previous_runs = ar['iterations']
|
||||
else:
|
||||
previous_runs = 0
|
||||
previous_present = False
|
||||
|
||||
mpi.barrier()
|
||||
previous_runs = mpi.bcast(previous_runs)
|
||||
@ -315,9 +312,8 @@ def dmft_cycle():
|
||||
if (previous_present):
|
||||
mpi.report("Using stored data for initialisation")
|
||||
if (mpi.is_master_node()):
|
||||
ar = HDFArchive(HDFfilename,'a')
|
||||
S.Sigma <<= ar['SigmaF']
|
||||
del ar
|
||||
with HDFArchive(HDFfilename,'a') as ar:
|
||||
S.Sigma <<= ar['SigmaF']
|
||||
things_to_load=['chemical_potential','dc_imp']
|
||||
old_data=SK.load(things_to_load)
|
||||
chemical_potential=old_data[0]
|
||||
@ -365,13 +361,12 @@ def dmft_cycle():
|
||||
# Now mix Sigma and G:
|
||||
if ((itn>1)or(previous_present)):
|
||||
if (mpi.is_master_node()and (Mix<1.0)):
|
||||
ar = HDFArchive(HDFfilename,'r')
|
||||
mpi.report("Mixing Sigma and G with factor %s"%Mix)
|
||||
if ('SigmaF' in ar):
|
||||
S.Sigma <<= Mix * S.Sigma + (1.0-Mix) * ar['SigmaF']
|
||||
if ('GF' in ar):
|
||||
S.G <<= Mix * S.G + (1.0-Mix) * ar['GF']
|
||||
del ar
|
||||
with HDFArchive(HDFfilename,'r') as ar:
|
||||
mpi.report("Mixing Sigma and G with factor %s"%Mix)
|
||||
if ('SigmaF' in ar):
|
||||
S.Sigma <<= Mix * S.Sigma + (1.0-Mix) * ar['SigmaF']
|
||||
if ('GF' in ar):
|
||||
S.G <<= Mix * S.G + (1.0-Mix) * ar['GF']
|
||||
S.G = mpi.bcast(S.G)
|
||||
S.Sigma = mpi.bcast(S.Sigma)
|
||||
|
||||
@ -386,14 +381,13 @@ def dmft_cycle():
|
||||
|
||||
# store the impurity self-energy, GF as well as correlation energy in h5
|
||||
if (mpi.is_master_node()):
|
||||
ar = HDFArchive(HDFfilename,'a')
|
||||
ar['iterations'] = itn
|
||||
ar['chemical_cotential%s'%itn] = chemical_potential
|
||||
ar['SigmaF'] = S.Sigma
|
||||
ar['GF'] = S.G
|
||||
ar['correnerg%s'%itn] = correnerg
|
||||
ar['DCenerg%s'%itn] = SK.dc_energ
|
||||
del ar
|
||||
with HDFArchive(HDFfilename,'a') as ar:
|
||||
ar['iterations'] = itn
|
||||
ar['chemical_cotential%s'%itn] = chemical_potential
|
||||
ar['SigmaF'] = S.Sigma
|
||||
ar['GF'] = S.G
|
||||
ar['correnerg%s'%itn] = correnerg
|
||||
ar['DCenerg%s'%itn] = SK.dc_energ
|
||||
|
||||
#Save essential SumkDFT data:
|
||||
things_to_save=['chemical_potential','dc_energ','dc_imp']
|
||||
@ -428,11 +422,10 @@ def dmft_cycle():
|
||||
|
||||
# store correlation energy contribution to be read by Wien2ki and then included to DFT+DMFT total energy
|
||||
if (mpi.is_master_node()):
|
||||
ar = HDFArchive(HDFfilename)
|
||||
itn = ar['iterations']
|
||||
correnerg = ar['correnerg%s'%itn]
|
||||
DCenerg = ar['DCenerg%s'%itn]
|
||||
del ar
|
||||
with HDFArchive(HDFfilename) as ar:
|
||||
itn = ar['iterations']
|
||||
correnerg = ar['correnerg%s'%itn]
|
||||
DCenerg = ar['DCenerg%s'%itn]
|
||||
correnerg -= DCenerg[0]
|
||||
f=open(lda_filename+'.qdmft','a')
|
||||
f.write("%.16f\n"%correnerg)
|
||||
|
||||
@ -269,22 +269,23 @@ class VaspConverter(ConverterTools):
|
||||
|
||||
|
||||
# Save it to the HDF:
|
||||
ar = HDFArchive(self.hdf_file,'a')
|
||||
if not (self.dft_subgrp in ar): ar.create_group(self.dft_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is created. If it exists, the data is overwritten!
|
||||
things_to_save = ['energy_unit','n_k','k_dep_projection','SP','SO','charge_below','density_required',
|
||||
with HDFArchive(self.hdf_file,'a') as ar:
|
||||
if not (self.dft_subgrp in ar): ar.create_group(self.dft_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is created. If it exists, the data is overwritten!
|
||||
things_to_save = ['energy_unit','n_k','k_dep_projection','SP','SO','charge_below','density_required',
|
||||
'symm_op','n_shells','shells','n_corr_shells','corr_shells','use_rotations','rot_mat',
|
||||
'rot_mat_time_inv','n_reps','dim_reps','T','n_orbitals','proj_mat','bz_weights','hopping',
|
||||
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr']
|
||||
for it in things_to_save: ar[self.dft_subgrp][it] = locals()[it]
|
||||
for it in things_to_save: ar[self.dft_subgrp][it] = locals()[it]
|
||||
|
||||
# Store Fermi weights to 'dft_misc_input'
|
||||
if not (self.misc_subgrp in ar): ar.create_group(self.misc_subgrp)
|
||||
ar[self.misc_subgrp]['dft_fermi_weights'] = f_weights
|
||||
ar[self.misc_subgrp]['band_window'] = band_window
|
||||
del ar
|
||||
# Store Fermi weights to 'dft_misc_input'
|
||||
if not (self.misc_subgrp in ar): ar.create_group(self.misc_subgrp)
|
||||
ar[self.misc_subgrp]['dft_fermi_weights'] = f_weights
|
||||
ar[self.misc_subgrp]['band_window'] = band_window
|
||||
|
||||
# Symmetries are used, so now convert symmetry information for *correlated* orbitals:
|
||||
self.convert_symmetry_input(ctrl_head, orbits=self.corr_shells, symm_subgrp=self.symmcorr_subgrp)
|
||||
|
||||
# TODO: Implement misc_input
|
||||
# self.convert_misc_input(bandwin_file=self.bandwin_file,struct_file=self.struct_file,outputs_file=self.outputs_file,
|
||||
# misc_subgrp=self.misc_subgrp,SO=self.SO,SP=self.SP,n_k=self.n_k)
|
||||
@ -381,10 +382,9 @@ class VaspConverter(ConverterTools):
|
||||
raise "convert_misc_input: reading file %s failed" %self.outputs_file
|
||||
|
||||
# Save it to the HDF:
|
||||
ar=HDFArchive(self.hdf_file,'a')
|
||||
if not (misc_subgrp in ar): ar.create_group(misc_subgrp)
|
||||
for it in things_to_save: ar[misc_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file,'a') as ar:
|
||||
if not (misc_subgrp in ar): ar.create_group(misc_subgrp)
|
||||
for it in things_to_save: ar[misc_subgrp][it] = locals()[it]
|
||||
|
||||
|
||||
def convert_symmetry_input(self, ctrl_head, orbits, symm_subgrp):
|
||||
@ -405,10 +405,8 @@ class VaspConverter(ConverterTools):
|
||||
mat_tinv = [numpy.identity(1)]
|
||||
|
||||
# Save it to the HDF:
|
||||
ar=HDFArchive(self.hdf_file,'a')
|
||||
if not (symm_subgrp in ar): ar.create_group(symm_subgrp)
|
||||
things_to_save = ['n_symm','n_atoms','perm','orbits','SO','SP','time_inv','mat','mat_tinv']
|
||||
for it in things_to_save:
|
||||
# print "%s:"%(it), locals()[it]
|
||||
ar[symm_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file,'a') as ar:
|
||||
if not (symm_subgrp in ar): ar.create_group(symm_subgrp)
|
||||
things_to_save = ['n_symm','n_atoms','perm','orbits','SO','SP','time_inv','mat','mat_tinv']
|
||||
for it in things_to_save:
|
||||
ar[symm_subgrp][it] = locals()[it]
|
||||
|
||||
@ -345,18 +345,17 @@ class Wannier90Converter(ConverterTools):
|
||||
iorb += norb
|
||||
|
||||
# Finally, save all required data into the HDF archive:
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
if not (self.dft_subgrp in ar):
|
||||
ar.create_group(self.dft_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!
|
||||
things_to_save = ['energy_unit', 'n_k', 'k_dep_projection', 'SP', 'SO', 'charge_below', 'density_required',
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
if not (self.dft_subgrp in ar):
|
||||
ar.create_group(self.dft_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!
|
||||
things_to_save = ['energy_unit', 'n_k', 'k_dep_projection', 'SP', 'SO', 'charge_below', 'density_required',
|
||||
'symm_op', 'n_shells', 'shells', 'n_corr_shells', 'corr_shells', 'use_rotations', 'rot_mat',
|
||||
'rot_mat_time_inv', 'n_reps', 'dim_reps', 'T', 'n_orbitals', 'proj_mat', 'bz_weights', 'hopping',
|
||||
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr']
|
||||
for it in things_to_save:
|
||||
ar[self.dft_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
for it in things_to_save:
|
||||
ar[self.dft_subgrp][it] = locals()[it]
|
||||
|
||||
def read_wannier90hr(self, hr_filename="wannier_hr.dat"):
|
||||
"""
|
||||
|
||||
@ -258,18 +258,17 @@ class Wien2kConverter(ConverterTools):
|
||||
# Reading done!
|
||||
|
||||
# Save it to the HDF:
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
if not (self.dft_subgrp in ar):
|
||||
ar.create_group(self.dft_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!
|
||||
things_to_save = ['energy_unit', 'n_k', 'k_dep_projection', 'SP', 'SO', 'charge_below', 'density_required',
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
if not (self.dft_subgrp in ar):
|
||||
ar.create_group(self.dft_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!
|
||||
things_to_save = ['energy_unit', 'n_k', 'k_dep_projection', 'SP', 'SO', 'charge_below', 'density_required',
|
||||
'symm_op', 'n_shells', 'shells', 'n_corr_shells', 'corr_shells', 'use_rotations', 'rot_mat',
|
||||
'rot_mat_time_inv', 'n_reps', 'dim_reps', 'T', 'n_orbitals', 'proj_mat', 'bz_weights', 'hopping',
|
||||
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr']
|
||||
for it in things_to_save:
|
||||
ar[self.dft_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
for it in things_to_save:
|
||||
ar[self.dft_subgrp][it] = locals()[it]
|
||||
|
||||
# Symmetries are used, so now convert symmetry information for
|
||||
# *correlated* orbitals:
|
||||
@ -292,15 +291,14 @@ class Wien2kConverter(ConverterTools):
|
||||
return
|
||||
|
||||
# get needed data from hdf file
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
things_to_read = ['SP', 'SO', 'n_shells',
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
things_to_read = ['SP', 'SO', 'n_shells',
|
||||
'n_k', 'n_orbitals', 'shells']
|
||||
|
||||
for it in things_to_read:
|
||||
if not hasattr(self, it):
|
||||
setattr(self, it, ar[self.dft_subgrp][it])
|
||||
self.n_spin_blocs = self.SP + 1 - self.SO
|
||||
del ar
|
||||
for it in things_to_read:
|
||||
if not hasattr(self, it):
|
||||
setattr(self, it, ar[self.dft_subgrp][it])
|
||||
self.n_spin_blocs = self.SP + 1 - self.SO
|
||||
|
||||
mpi.report("Reading input from %s..." % self.parproj_file)
|
||||
|
||||
@ -368,16 +366,15 @@ class Wien2kConverter(ConverterTools):
|
||||
# Reading done!
|
||||
|
||||
# Save it to the HDF:
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
if not (self.parproj_subgrp in ar):
|
||||
ar.create_group(self.parproj_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!
|
||||
things_to_save = ['dens_mat_below', 'n_parproj',
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
if not (self.parproj_subgrp in ar):
|
||||
ar.create_group(self.parproj_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!
|
||||
things_to_save = ['dens_mat_below', 'n_parproj',
|
||||
'proj_mat_all', 'rot_mat_all', 'rot_mat_all_time_inv']
|
||||
for it in things_to_save:
|
||||
ar[self.parproj_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
for it in things_to_save:
|
||||
ar[self.parproj_subgrp][it] = locals()[it]
|
||||
|
||||
# Symmetries are used, so now convert symmetry information for *all*
|
||||
# orbitals:
|
||||
@ -395,15 +392,14 @@ class Wien2kConverter(ConverterTools):
|
||||
|
||||
try:
|
||||
# get needed data from hdf file
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
things_to_read = ['SP', 'SO', 'n_corr_shells',
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
things_to_read = ['SP', 'SO', 'n_corr_shells',
|
||||
'n_shells', 'corr_shells', 'shells', 'energy_unit']
|
||||
|
||||
for it in things_to_read:
|
||||
if not hasattr(self, it):
|
||||
setattr(self, it, ar[self.dft_subgrp][it])
|
||||
self.n_spin_blocs = self.SP + 1 - self.SO
|
||||
del ar
|
||||
for it in things_to_read:
|
||||
if not hasattr(self, it):
|
||||
setattr(self, it, ar[self.dft_subgrp][it])
|
||||
self.n_spin_blocs = self.SP + 1 - self.SO
|
||||
|
||||
mpi.report("Reading input from %s..." % self.band_file)
|
||||
R = ConverterTools.read_fortran_file(
|
||||
@ -482,16 +478,15 @@ class Wien2kConverter(ConverterTools):
|
||||
# Reading done!
|
||||
|
||||
# Save it to the HDF:
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
if not (self.bands_subgrp in ar):
|
||||
ar.create_group(self.bands_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!
|
||||
things_to_save = ['n_k', 'n_orbitals', 'proj_mat',
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
if not (self.bands_subgrp in ar):
|
||||
ar.create_group(self.bands_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!
|
||||
things_to_save = ['n_k', 'n_orbitals', 'proj_mat',
|
||||
'hopping', 'n_parproj', 'proj_mat_all']
|
||||
for it in things_to_save:
|
||||
ar[self.bands_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
for it in things_to_save:
|
||||
ar[self.bands_subgrp][it] = locals()[it]
|
||||
|
||||
def convert_misc_input(self):
|
||||
"""
|
||||
@ -510,13 +505,12 @@ class Wien2kConverter(ConverterTools):
|
||||
return
|
||||
|
||||
# Check if SP, SO and n_k are already in h5
|
||||
ar = HDFArchive(self.hdf_file, 'r')
|
||||
if not (self.dft_subgrp in ar):
|
||||
raise IOError, "convert_misc_input: No %s subgroup in hdf file found! Call convert_dft_input first." % self.dft_subgrp
|
||||
SP = ar[self.dft_subgrp]['SP']
|
||||
SO = ar[self.dft_subgrp]['SO']
|
||||
n_k = ar[self.dft_subgrp]['n_k']
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file, 'r') as ar:
|
||||
if not (self.dft_subgrp in ar):
|
||||
raise IOError, "convert_misc_input: No %s subgroup in hdf file found! Call convert_dft_input first." % self.dft_subgrp
|
||||
SP = ar[self.dft_subgrp]['SP']
|
||||
SO = ar[self.dft_subgrp]['SO']
|
||||
n_k = ar[self.dft_subgrp]['n_k']
|
||||
|
||||
things_to_save = []
|
||||
|
||||
@ -612,12 +606,11 @@ class Wien2kConverter(ConverterTools):
|
||||
raise IOError, "convert_misc_input: reading file %s failed" % self.outputs_file
|
||||
|
||||
# Save it to the HDF:
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
if not (self.misc_subgrp in ar):
|
||||
ar.create_group(self.misc_subgrp)
|
||||
for it in things_to_save:
|
||||
ar[self.misc_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
if not (self.misc_subgrp in ar):
|
||||
ar.create_group(self.misc_subgrp)
|
||||
for it in things_to_save:
|
||||
ar[self.misc_subgrp][it] = locals()[it]
|
||||
|
||||
def convert_transport_input(self):
|
||||
"""
|
||||
@ -633,13 +626,12 @@ class Wien2kConverter(ConverterTools):
|
||||
return
|
||||
|
||||
# Check if SP, SO and n_k are already in h5
|
||||
ar = HDFArchive(self.hdf_file, 'r')
|
||||
if not (self.dft_subgrp in ar):
|
||||
raise IOError, "convert_transport_input: No %s subgroup in hdf file found! Call convert_dft_input first." % self.dft_subgrp
|
||||
SP = ar[self.dft_subgrp]['SP']
|
||||
SO = ar[self.dft_subgrp]['SO']
|
||||
n_k = ar[self.dft_subgrp]['n_k']
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file, 'r') as ar:
|
||||
if not (self.dft_subgrp in ar):
|
||||
raise IOError, "convert_transport_input: No %s subgroup in hdf file found! Call convert_dft_input first." % self.dft_subgrp
|
||||
SP = ar[self.dft_subgrp]['SP']
|
||||
SO = ar[self.dft_subgrp]['SO']
|
||||
n_k = ar[self.dft_subgrp]['n_k']
|
||||
|
||||
# Read relevant data from .pmat/up/dn files
|
||||
###########################################
|
||||
@ -691,15 +683,14 @@ class Wien2kConverter(ConverterTools):
|
||||
R.close() # Reading done!
|
||||
|
||||
# Put data to HDF5 file
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
if not (self.transp_subgrp in ar):
|
||||
ar.create_group(self.transp_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!!!
|
||||
things_to_save = ['band_window_optics', 'velocities_k']
|
||||
for it in things_to_save:
|
||||
ar[self.transp_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
if not (self.transp_subgrp in ar):
|
||||
ar.create_group(self.transp_subgrp)
|
||||
# The subgroup containing the data. If it does not exist, it is
|
||||
# created. If it exists, the data is overwritten!!!
|
||||
things_to_save = ['band_window_optics', 'velocities_k']
|
||||
for it in things_to_save:
|
||||
ar[self.transp_subgrp][it] = locals()[it]
|
||||
|
||||
def convert_symmetry_input(self, orbits, symm_file, symm_subgrp, SO, SP):
|
||||
"""
|
||||
@ -781,11 +772,10 @@ class Wien2kConverter(ConverterTools):
|
||||
# Reading done!
|
||||
|
||||
# Save it to the HDF:
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
if not (symm_subgrp in ar):
|
||||
ar.create_group(symm_subgrp)
|
||||
things_to_save = ['n_symm', 'n_atoms', 'perm',
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
if not (symm_subgrp in ar):
|
||||
ar.create_group(symm_subgrp)
|
||||
things_to_save = ['n_symm', 'n_atoms', 'perm',
|
||||
'orbits', 'SO', 'SP', 'time_inv', 'mat', 'mat_tinv']
|
||||
for it in things_to_save:
|
||||
ar[symm_subgrp][it] = locals()[it]
|
||||
del ar
|
||||
for it in things_to_save:
|
||||
ar[symm_subgrp][it] = locals()[it]
|
||||
|
||||
@ -187,23 +187,22 @@ class SumkDFT(object):
|
||||
subgroup_present = 0
|
||||
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(self.hdf_file, 'r')
|
||||
if subgrp in ar:
|
||||
subgroup_present = True
|
||||
# first read the necessary things:
|
||||
for it in things_to_read:
|
||||
if it in ar[subgrp]:
|
||||
setattr(self, it, ar[subgrp][it])
|
||||
else:
|
||||
mpi.report("Loading %s failed!" % it)
|
||||
value_read = False
|
||||
else:
|
||||
if (len(things_to_read) != 0):
|
||||
mpi.report(
|
||||
"Loading failed: No %s subgroup in hdf5!" % subgrp)
|
||||
subgroup_present = False
|
||||
value_read = False
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file, 'r') as ar:
|
||||
if subgrp in ar:
|
||||
subgroup_present = True
|
||||
# first read the necessary things:
|
||||
for it in things_to_read:
|
||||
if it in ar[subgrp]:
|
||||
setattr(self, it, ar[subgrp][it])
|
||||
else:
|
||||
mpi.report("Loading %s failed!" % it)
|
||||
value_read = False
|
||||
else:
|
||||
if (len(things_to_read) != 0):
|
||||
mpi.report(
|
||||
"Loading failed: No %s subgroup in hdf5!" % subgrp)
|
||||
subgroup_present = False
|
||||
value_read = False
|
||||
# now do the broadcasting:
|
||||
for it in things_to_read:
|
||||
setattr(self, it, mpi.bcast(getattr(self, it)))
|
||||
@ -226,18 +225,16 @@ class SumkDFT(object):
|
||||
|
||||
if not (mpi.is_master_node()):
|
||||
return # do nothing on nodes
|
||||
ar = HDFArchive(self.hdf_file, 'a')
|
||||
if not subgrp in ar:
|
||||
ar.create_group(subgrp)
|
||||
for it in things_to_save:
|
||||
if it in [ "gf_struct_sumk", "gf_struct_solver",
|
||||
"solver_to_sumk", "sumk_to_solver", "solver_to_sumk_block"]:
|
||||
warn("It is not recommended to save '{}' individually. Save 'block_structure' instead.".format(it))
|
||||
try:
|
||||
ar[subgrp][it] = getattr(self, it)
|
||||
except:
|
||||
mpi.report("%s not found, and so not saved." % it)
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file, 'a') as ar:
|
||||
if not subgrp in ar: ar.create_group(subgrp)
|
||||
for it in things_to_save:
|
||||
if it in [ "gf_struct_sumk", "gf_struct_solver",
|
||||
"solver_to_sumk", "sumk_to_solver", "solver_to_sumk_block"]:
|
||||
warn("It is not recommended to save '{}' individually. Save 'block_structure' instead.".format(it))
|
||||
try:
|
||||
ar[subgrp][it] = getattr(self, it)
|
||||
except:
|
||||
mpi.report("%s not found, and so not saved." % it)
|
||||
|
||||
def load(self, things_to_load, subgrp='user_data'):
|
||||
r"""
|
||||
@ -258,16 +255,15 @@ class SumkDFT(object):
|
||||
|
||||
if not (mpi.is_master_node()):
|
||||
return # do nothing on nodes
|
||||
ar = HDFArchive(self.hdf_file, 'r')
|
||||
if not subgrp in ar:
|
||||
mpi.report("Loading %s failed!" % subgrp)
|
||||
list_to_return = []
|
||||
for it in things_to_load:
|
||||
try:
|
||||
list_to_return.append(ar[subgrp][it])
|
||||
except:
|
||||
raise ValueError, "load: %s not found, and so not loaded." % it
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file, 'r') as ar:
|
||||
if not subgrp in ar:
|
||||
mpi.report("Loading %s failed!" % subgrp)
|
||||
list_to_return = []
|
||||
for it in things_to_load:
|
||||
try:
|
||||
list_to_return.append(ar[subgrp][it])
|
||||
except:
|
||||
raise ValueError, "load: %s not found, and so not loaded." % it
|
||||
return list_to_return
|
||||
|
||||
################
|
||||
@ -1822,10 +1818,9 @@ class SumkDFT(object):
|
||||
fermi_weights = 0
|
||||
band_window = 0
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(self.hdf_file,'r')
|
||||
fermi_weights = ar['dft_misc_input']['dft_fermi_weights']
|
||||
band_window = ar['dft_misc_input']['band_window']
|
||||
del ar
|
||||
with HDFArchive(self.hdf_file,'r') as ar:
|
||||
fermi_weights = ar['dft_misc_input']['dft_fermi_weights']
|
||||
band_window = ar['dft_misc_input']['band_window']
|
||||
fermi_weights = mpi.bcast(fermi_weights)
|
||||
band_window = mpi.bcast(band_window)
|
||||
|
||||
|
||||
@ -58,16 +58,15 @@ class Symmetry:
|
||||
|
||||
if mpi.is_master_node():
|
||||
# Read the stuff on master:
|
||||
ar = HDFArchive(hdf_file, 'r')
|
||||
if subgroup is None:
|
||||
ar2 = ar
|
||||
else:
|
||||
ar2 = ar[subgroup]
|
||||
with HDFArchive(hdf_file, 'r') as ar:
|
||||
if subgroup is None:
|
||||
ar2 = ar
|
||||
else:
|
||||
ar2 = ar[subgroup]
|
||||
|
||||
for it in things_to_read:
|
||||
setattr(self, it, ar2[it])
|
||||
for it in things_to_read:
|
||||
setattr(self, it, ar2[it])
|
||||
del ar2
|
||||
del ar
|
||||
|
||||
# Broadcasting
|
||||
for it in things_to_read:
|
||||
|
||||
@ -34,12 +34,11 @@ Converter.convert_transport_input()
|
||||
|
||||
SK = SumkDFTTools(hdf_file='SrVO3.h5', use_dft_blocks=True)
|
||||
|
||||
ar = HDFArchive('SrVO3_Sigma.h5', 'a')
|
||||
Sigma = ar['dmft_transp_input']['Sigma_w']
|
||||
SK.set_Sigma([Sigma])
|
||||
SK.chemical_potential = ar['dmft_transp_input']['chemical_potential']
|
||||
SK.dc_imp = ar['dmft_transp_input']['dc_imp']
|
||||
del ar
|
||||
with HDFArchive('SrVO3_Sigma.h5', 'a') as ar:
|
||||
Sigma = ar['dmft_transp_input']['Sigma_w']
|
||||
SK.set_Sigma([Sigma])
|
||||
SK.chemical_potential = ar['dmft_transp_input']['chemical_potential']
|
||||
SK.dc_imp = ar['dmft_transp_input']['dc_imp']
|
||||
|
||||
SK.transport_distribution(directions=['xx'], broadening=0.0, energy_window=[-0.3,0.3], Om_mesh=[0.00, 0.02] , beta=beta, with_Sigma=True)
|
||||
#SK.save(['Gamma_w','Om_meshr','omega','directions'])
|
||||
|
||||
Loading…
Reference in New Issue
Block a user