mirror of
https://github.com/triqs/dft_tools
synced 2024-12-22 20:34:38 +01:00
remove gf_struct_flatten function and replace with triqs version
This commit is contained in:
Alexander Hampel
parent
d28fe3c1ef
commit
320b2d2dfd
@ -23,11 +23,11 @@ DFTTools Version 3.1.0 is a release that
|
||||
* bugfix: This fix makes the function find_rot_mat() safer to use in case there are errors in finding the correct mapping. The converter will now abort if the agreement in mapping is below a user-definable threshold.
|
||||
|
||||
### Change in gf_struct
|
||||
* In line with TRIQS 3.1.x, the form of the Green's function's structure (`gf_struct`) has been modified
|
||||
* In line with TRIQS 3.1.x, the form of the Green's function's structure (`gf_struct`) has been modified (see [triqs changelog](https://triqs.github.io/triqs/latest/ChangeLog.html#change-in-gf-struct-objects) for more information)
|
||||
* Instead of `gf_struct = [("up", [0, 1]), ("down", [0, 1])]`, the new convention uses `gf_struct = [("up", 2), ("down", 2)]`
|
||||
* This modifies the form of `gf_struct_solver` (and `sumk`) in `block_structure` and `SumkDFT` as well.
|
||||
* Backwards-compatibility with old, stored `block_structure` objects is given, however a warning is issued.
|
||||
* A helper-function `block_structure.gf_struct_flatten(...)` is provided to manually bring `gf_struct`s to the new form.
|
||||
* A helper-function `triqs.gf.block_gf.fix_gf_struct_type(gf_struct_old)` is provided in triqs to manually bring `gf_struct`s to the new form.
|
||||
|
||||
### Documentation
|
||||
* change to read the docs sphinx theme
|
||||
|
||||
@ -6,7 +6,6 @@ from triqs.gf import *
|
||||
import sys, triqs.version as triqs_version
|
||||
from triqs_dft_tools.sumk_dft import *
|
||||
from triqs_dft_tools.sumk_dft_tools import *
|
||||
from triqs_dft_tools.block_structure import gf_struct_flatten
|
||||
from triqs.operators.util.hamiltonians import *
|
||||
from triqs.operators.util.U_matrix import *
|
||||
from triqs_cthyb import *
|
||||
@ -20,8 +19,8 @@ filename = 'nio'
|
||||
|
||||
SK = SumkDFT(hdf_file = filename+'.h5', use_dft_blocks = False)
|
||||
|
||||
beta = 5.0
|
||||
|
||||
beta = 5.0
|
||||
|
||||
Sigma = SK.block_structure.create_gf(beta=beta)
|
||||
SK.put_Sigma([Sigma])
|
||||
G = SK.extract_G_loc()
|
||||
@ -41,7 +40,7 @@ spin_names = ['up','down']
|
||||
orb_names = [i for i in range(0,n_orb)]
|
||||
|
||||
#gf_struct = set_operator_structure(spin_names, orb_names, orb_hyb)
|
||||
gf_struct = gf_struct_flatten(SK.gf_struct_solver[0])
|
||||
gf_struct = SK.gf_struct_solver_list[0]
|
||||
mpi.report('Sumk to Solver: %s'%SK.sumk_to_solver)
|
||||
mpi.report('GF struct sumk: %s'%SK.gf_struct_sumk)
|
||||
mpi.report('GF struct solver: %s'%SK.gf_struct_solver)
|
||||
@ -49,7 +48,7 @@ mpi.report('GF struct solver: %s'%SK.gf_struct_solver)
|
||||
S = Solver(beta=beta, gf_struct=gf_struct)
|
||||
|
||||
# Construct the Hamiltonian and save it in Hamiltonian_store.txt
|
||||
H = Operator()
|
||||
H = Operator()
|
||||
U = 8.0
|
||||
J = 1.0
|
||||
|
||||
@ -130,14 +129,14 @@ mpi.report('%s DMFT cycles requested. Starting with iteration %s.'%(n_iterations
|
||||
|
||||
# The infamous DMFT self consistency cycle
|
||||
for it in range(iteration_offset, iteration_offset + n_iterations):
|
||||
|
||||
|
||||
mpi.report('Doing iteration: %s'%it)
|
||||
|
||||
|
||||
# Get G0
|
||||
S.G0_iw << inverse(S.Sigma_iw + inverse(S.G_iw))
|
||||
# Solve the impurity problem
|
||||
S.solve(h_int = H, **p)
|
||||
if mpi.is_master_node():
|
||||
if mpi.is_master_node():
|
||||
ar['DMFT_input']['Iterations']['solver_dict_it'+str(it)] = p
|
||||
ar['DMFT_results']['Iterations']['Gimp_it'+str(it)] = S.G_iw
|
||||
ar['DMFT_results']['Iterations']['Gtau_it'+str(it)] = S.G_tau
|
||||
@ -150,13 +149,13 @@ for it in range(iteration_offset, iteration_offset + n_iterations):
|
||||
SK.put_Sigma(Sigma_imp=[S.Sigma_iw])
|
||||
SK.calc_mu(precision=0.01)
|
||||
S.G_iw << SK.extract_G_loc()[0]
|
||||
|
||||
|
||||
# print densities
|
||||
for sig,gf in S.G_iw:
|
||||
mpi.report("Orbital %s density: %.6f"%(sig,dm[sig][0,0]))
|
||||
mpi.report('Total charge of Gloc : %.6f'%S.G_iw.total_density())
|
||||
|
||||
if mpi.is_master_node():
|
||||
if mpi.is_master_node():
|
||||
ar['DMFT_results']['iteration_count'] = it
|
||||
ar['DMFT_results']['Iterations']['Sigma_it'+str(it)] = S.Sigma_iw
|
||||
ar['DMFT_results']['Iterations']['Gloc_it'+str(it)] = S.G_iw
|
||||
|
||||
@ -6,7 +6,6 @@ from triqs.gf import *
|
||||
import sys, triqs.version as triqs_version
|
||||
from triqs_dft_tools.sumk_dft import *
|
||||
from triqs_dft_tools.sumk_dft_tools import *
|
||||
from triqs_dft_tools.block_structure import gf_struct_flatten
|
||||
from triqs.operators.util.hamiltonians import *
|
||||
from triqs.operators.util.U_matrix import *
|
||||
from triqs_cthyb import *
|
||||
@ -21,14 +20,14 @@ warnings.filterwarnings("ignore", category=FutureWarning)
|
||||
|
||||
def dmft_cycle():
|
||||
filename = 'nio'
|
||||
|
||||
|
||||
Converter = VaspConverter(filename=filename)
|
||||
Converter.convert_dft_input()
|
||||
|
||||
|
||||
SK = SumkDFT(hdf_file = filename+'.h5', use_dft_blocks = False)
|
||||
|
||||
beta = 5.0
|
||||
|
||||
|
||||
beta = 5.0
|
||||
|
||||
Sigma = SK.block_structure.create_gf(beta=beta)
|
||||
SK.put_Sigma([Sigma])
|
||||
G = SK.extract_G_loc()
|
||||
@ -40,38 +39,38 @@ def dmft_cycle():
|
||||
mpi.report('block {0:d} consists of orbitals:'.format(iblock))
|
||||
for keys in list(SK.deg_shells[i_sh][iblock].keys()):
|
||||
mpi.report(' '+keys)
|
||||
|
||||
|
||||
# Setup CTQMC Solver
|
||||
|
||||
|
||||
n_orb = SK.corr_shells[0]['dim']
|
||||
spin_names = ['up','down']
|
||||
orb_names = [i for i in range(0,n_orb)]
|
||||
|
||||
|
||||
#gf_struct = set_operator_structure(spin_names, orb_names, orb_hyb)
|
||||
gf_struct = SK.gf_struct_solver[0]
|
||||
gf_struct = SK.gf_struct_solver_list[0]
|
||||
mpi.report('Sumk to Solver: %s'%SK.sumk_to_solver)
|
||||
mpi.report('GF struct sumk: %s'%SK.gf_struct_sumk)
|
||||
mpi.report('GF struct solver: %s'%SK.gf_struct_solver)
|
||||
|
||||
|
||||
S = Solver(beta=beta, gf_struct=gf_struct)
|
||||
|
||||
|
||||
# Construct the Hamiltonian and save it in Hamiltonian_store.txt
|
||||
H = Operator()
|
||||
H = Operator()
|
||||
U = 8.0
|
||||
J = 1.0
|
||||
|
||||
|
||||
|
||||
|
||||
U_sph = U_matrix(l=2, U_int=U, J_hund=J)
|
||||
U_cubic = transform_U_matrix(U_sph, spherical_to_cubic(l=2, convention=''))
|
||||
Umat, Upmat = reduce_4index_to_2index(U_cubic)
|
||||
|
||||
|
||||
H = h_int_density(spin_names, orb_names, map_operator_structure=SK.sumk_to_solver[0], U=Umat, Uprime=Upmat)
|
||||
|
||||
|
||||
# Print some information on the master node
|
||||
mpi.report('Greens function structure is: %s '%gf_struct)
|
||||
mpi.report('U Matrix set to:\n%s'%Umat)
|
||||
mpi.report('Up Matrix set to:\n%s'%Upmat)
|
||||
|
||||
|
||||
# Parameters for the CTQMC Solver
|
||||
p = {}
|
||||
p["max_time"] = -1
|
||||
@ -84,14 +83,14 @@ def dmft_cycle():
|
||||
p["fit_min_n"] = 30
|
||||
p["fit_max_n"] = 50
|
||||
p["perform_tail_fit"] = True
|
||||
|
||||
|
||||
# Double Counting: 0 FLL, 1 Held, 2 AMF
|
||||
DC_type = 0
|
||||
DC_value = 59.0
|
||||
|
||||
|
||||
# Prepare hdf file and and check for previous iterations
|
||||
n_iterations = 1
|
||||
|
||||
|
||||
iteration_offset = 0
|
||||
if mpi.is_master_node():
|
||||
ar = HDFArchive(filename+'.h5','a')
|
||||
@ -119,33 +118,33 @@ def dmft_cycle():
|
||||
SK.dc_imp = mpi.bcast(SK.dc_imp)
|
||||
SK.dc_energ = mpi.bcast(SK.dc_energ)
|
||||
SK.chemical_potential = mpi.bcast(SK.chemical_potential)
|
||||
|
||||
|
||||
# Calc the first G0
|
||||
SK.symm_deg_gf(S.Sigma_iw, ish=0)
|
||||
SK.put_Sigma(Sigma_imp = [S.Sigma_iw])
|
||||
SK.calc_mu(precision=0.01)
|
||||
S.G_iw << SK.extract_G_loc()[0]
|
||||
SK.symm_deg_gf(S.G_iw, ish=0)
|
||||
|
||||
|
||||
#Init the DC term and the self-energy if no previous iteration was found
|
||||
if iteration_offset == 0:
|
||||
dm = S.G_iw.density()
|
||||
SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0, use_dc_formula=DC_type,use_dc_value=DC_value)
|
||||
S.Sigma_iw << SK.dc_imp[0]['up'][0,0]
|
||||
|
||||
|
||||
mpi.report('%s DMFT cycles requested. Starting with iteration %s.'%(n_iterations,iteration_offset))
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
# The infamous DMFT self consistency cycle
|
||||
for it in range(iteration_offset, iteration_offset + n_iterations):
|
||||
mpi.report('Doing iteration: %s'%it)
|
||||
|
||||
|
||||
# Get G0
|
||||
S.G0_iw << inverse(S.Sigma_iw + inverse(S.G_iw))
|
||||
# Solve the impurity problem
|
||||
S.solve(h_int = H, **p)
|
||||
if mpi.is_master_node():
|
||||
if mpi.is_master_node():
|
||||
ar['DMFT_input']['Iterations']['solver_dict_it'+str(it)] = p
|
||||
ar['DMFT_results']['Iterations']['Gimp_it'+str(it)] = S.G_iw
|
||||
ar['DMFT_results']['Iterations']['Gtau_it'+str(it)] = S.G_tau
|
||||
@ -158,13 +157,13 @@ def dmft_cycle():
|
||||
SK.put_Sigma(Sigma_imp=[S.Sigma_iw])
|
||||
SK.calc_mu(precision=0.01)
|
||||
S.G_iw << SK.extract_G_loc()[0]
|
||||
|
||||
|
||||
# print densities
|
||||
for sig,gf in S.G_iw:
|
||||
mpi.report("Orbital %s density: %.6f"%(sig,dm[sig][0,0]))
|
||||
mpi.report('Total charge of Gloc : %.6f'%S.G_iw.total_density())
|
||||
|
||||
if mpi.is_master_node():
|
||||
|
||||
if mpi.is_master_node():
|
||||
ar['DMFT_results']['iteration_count'] = it
|
||||
ar['DMFT_results']['Iterations']['Sigma_it'+str(it)] = S.Sigma_iw
|
||||
ar['DMFT_results']['Iterations']['Gloc_it'+str(it)] = S.G_iw
|
||||
@ -172,31 +171,31 @@ def dmft_cycle():
|
||||
ar['DMFT_results']['Iterations']['dc_imp'+str(it)] = SK.dc_imp
|
||||
ar['DMFT_results']['Iterations']['dc_energ'+str(it)] = SK.dc_energ
|
||||
ar['DMFT_results']['Iterations']['chemical_potential'+str(it)] = SK.chemical_potential
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
if mpi.is_master_node():
|
||||
print('calculating mu...')
|
||||
SK.chemical_potential = SK.calc_mu( precision = 0.000001 )
|
||||
|
||||
|
||||
if mpi.is_master_node():
|
||||
print('calculating GAMMA')
|
||||
SK.calc_density_correction(dm_type='vasp')
|
||||
|
||||
|
||||
if mpi.is_master_node():
|
||||
print('calculating energy corrections')
|
||||
|
||||
|
||||
correnerg = 0.5 * (S.G_iw * S.Sigma_iw).total_density()
|
||||
|
||||
|
||||
dm = S.G_iw.density() # compute the density matrix of the impurity problem
|
||||
SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0, use_dc_formula=DC_type,use_dc_value=DC_value)
|
||||
dc_energ = SK.dc_energ[0]
|
||||
|
||||
if mpi.is_master_node():
|
||||
|
||||
if mpi.is_master_node():
|
||||
ar['DMFT_results']['Iterations']['corr_energy_it'+str(it)] = correnerg
|
||||
ar['DMFT_results']['Iterations']['dc_energy_it'+str(it)] = dc_energ
|
||||
|
||||
|
||||
if mpi.is_master_node(): del ar
|
||||
|
||||
|
||||
return correnerg, dc_energ
|
||||
|
||||
@ -120,7 +120,7 @@ class BlockStructure(object):
|
||||
deg_shells=None,
|
||||
corr_to_inequiv = None,
|
||||
transformation=None):
|
||||
|
||||
|
||||
# Ensure backwards-compatibility with pre-3.1.x gf_structs
|
||||
show_gf_struct_warning = False
|
||||
if gf_struct_sumk != None:
|
||||
@ -625,7 +625,7 @@ class BlockStructure(object):
|
||||
for k in list(self.sumk_to_solver[ish].keys()):
|
||||
if not k in su2so:
|
||||
su2so[k] = (None, None)
|
||||
|
||||
|
||||
for new_block in gf_struct:
|
||||
assert all(np.sort(gf_struct[new_block]) == list(range(len(gf_struct[new_block])))) ,\
|
||||
"New gf_struct does not have valid 0-based indices!"
|
||||
@ -1190,45 +1190,5 @@ class BlockStructure(object):
|
||||
s += str(self.transformation)
|
||||
return s
|
||||
|
||||
def gf_struct_flatten(gf_struct):
|
||||
'''
|
||||
flattens gf_struct objecti
|
||||
|
||||
input gf_struct can looks like this:
|
||||
|
||||
[('up', [0, 1, 2]), ('down', [0, 1, 2])]
|
||||
|
||||
and will be returned as
|
||||
|
||||
[('up', 3), ('down', 3)]
|
||||
|
||||
Same for dict but replacing the values. This is for compatibility with the upcoming triqs releases.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
gf_struct: list of tuple or dict representing the Gf structure
|
||||
__Returns:__
|
||||
gf_struct_flat: flattens the values of the dict or the tuple representing the Gf indices by replacing them with the len of the list of indices
|
||||
|
||||
'''
|
||||
|
||||
if isinstance(gf_struct, list):
|
||||
# create a copy of the original list
|
||||
gf_struct_flat = gf_struct.copy()
|
||||
for idx, block in enumerate(gf_struct_flat):
|
||||
# exchange list of indices with length of list
|
||||
gf_struct_flat[idx] = (block[0], len(block[1]))
|
||||
elif isinstance(gf_struct, dict):
|
||||
# create a copy of the original dict
|
||||
gf_struct_flat = dict(gf_struct)
|
||||
for key, value in gf_struct_flat.items():
|
||||
# exchange list of indices with length of list
|
||||
gf_struct_flat[key] = len(value)
|
||||
else:
|
||||
raise Exception('gf_struct input needs to be list or dict')
|
||||
|
||||
|
||||
return gf_struct_flat
|
||||
|
||||
from h5.formats import register_class
|
||||
register_class(BlockStructure)
|
||||
|
||||
@ -3,7 +3,7 @@ from triqs.utility.h5diff import h5diff, compare, failures
|
||||
from triqs.gf import *
|
||||
from triqs.utility.comparison_tests import assert_block_gfs_are_close
|
||||
from scipy.linalg import expm
|
||||
from triqs_dft_tools.block_structure import BlockStructure, gf_struct_flatten
|
||||
from triqs_dft_tools.block_structure import BlockStructure
|
||||
import numpy as np
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user