mirror of
https://github.com/triqs/dft_tools
synced 2024-06-02 19:35:32 +02:00
70 lines
2.1 KiB
Python
70 lines
2.1 KiB
Python
from pytriqs.applications.dft.sumk_dft_tools import *
|
|
from pytriqs.applications.dft.converters.wien2k_converter import *
|
|
from pytriqs.applications.impurity_solvers.hubbard_I.hubbard_solver import Solver
|
|
|
|
# Creates the data directory, cd into it:
|
|
#Prepare_Run_Directory(DirectoryName = "Ce-Gamma")
|
|
dft_filename = 'Ce-gamma'
|
|
Beta = 40
|
|
U_int = 6.00
|
|
J_hund = 0.70
|
|
DC_type = 0 # 0...FLL, 1...Held, 2... AMF, 3...Lichtenstein
|
|
load_previous = True # load previous results
|
|
useBlocs = False # use bloc structure from DFT input
|
|
useMatrix = True # use the U matrix calculated from Slater coefficients instead of (U+2J, U, U-J)
|
|
ommin=-4.0
|
|
ommax=6.0
|
|
N_om=2001
|
|
broadening = 0.02
|
|
|
|
HDFfilename = dft_filename+'.h5'
|
|
|
|
# Convert DMFT input:
|
|
# Can be commented after the first run
|
|
Converter = Wien2kConverter(filename=dft_filename,repacking=True)
|
|
Converter.convert_dft_input()
|
|
Converter.convert_parproj_input()
|
|
|
|
#check if there are previous runs:
|
|
previous_runs = 0
|
|
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
|
|
|
|
mpi.barrier()
|
|
previous_runs = mpi.bcast(previous_runs)
|
|
previous_present = mpi.bcast(previous_present)
|
|
|
|
# if previous runs are present, no need for recalculating the bloc structure
|
|
# It has to be commented, if you run this script for the first time, starting
|
|
# from a converted h5 archive.
|
|
|
|
# Init the SumK class
|
|
SK = SumkDFTTools(hdf_file=dft_filename+'.h5',use_dft_blocks=False)
|
|
|
|
|
|
if (mpi.is_master_node()):
|
|
print 'DC after reading SK: ',SK.dc_imp[SK.invshellmap[0]]
|
|
|
|
N = SK.corr_shells[0]['dim']
|
|
l = SK.corr_shells[0]['l']
|
|
|
|
# Init the Solver:
|
|
S = Solver(beta = Beta, l = l)
|
|
S.Nmoments= 8
|
|
|
|
# set atomic levels:
|
|
eal = SK.eff_atomic_levels()[0]
|
|
S.set_atomic_levels( eal = eal )
|
|
S.GF_realomega(ommin=ommin, ommax = ommax, N_om=N_om,U_int=U_int,J_hund=J_hund)
|
|
SK.put_Sigma(Sigma_imp = [S.Sigma])
|
|
SK.dos_partial(broadening=broadening)
|