def from_directory(input_dir):
"""
Read in a set of FEFF input files from a directory, which is
useful when existing FEFF input needs some adjustment.
"""
sub_d = {}
for fname, ftype in [("HEADER", Header), ("PARAMETERS", Tags)]:
fullzpath = zpath(os.path.join(input_dir, fname))
sub_d[fname.lower()] = ftype.from_file(fullzpath)
# Generation of FEFFDict set requires absorbing atom, need to search
# the index of absorption atom in the structure according to the
# distance matrix and shell species information contained in feff.inp
absorber_index = []
radius = None
feffinp = zpath(os.path.join(input_dir, 'feff.inp'))
if "RECIPROCAL" not in sub_d["parameters"]:
input_atoms = Atoms.cluster_from_file(feffinp)
shell_species = np.array([x.species_string for x in input_atoms])
# First row of distance matrix represents the distance from the absorber to
# the rest atoms
distance_matrix = input_atoms.distance_matrix[0, :]
# Get radius value
from math import ceil
radius = int(ceil(input_atoms.get_distance(input_atoms.index(input_atoms[0]),
input_atoms.index(input_atoms[-1]))))
for site_index, site in enumerate(sub_d['header'].struct):
if site.specie == input_atoms[0].specie:
site_atoms = Atoms(sub_d['header'].struct, absorbing_atom=site_index,
radius=radius)
site_distance = np.array(site_atoms.get_lines())[:, 5].astype(np.float64)
site_shell_species = np.array(site_atoms.get_lines())[:, 4]
shell_overlap = min(shell_species.shape[0], site_shell_species.shape[0])
if np.allclose(distance_matrix[:shell_overlap], site_distance[:shell_overlap]) and \
np.all(site_shell_species[:shell_overlap] == shell_species[:shell_overlap]):
absorber_index.append(site_index)
if "RECIPROCAL" in sub_d["parameters"]:
absorber_index = sub_d["parameters"]["TARGET"]
absorber_index[0] = int(absorber_index[0]) - 1
# Generate the input set
if 'XANES' in sub_d["parameters"]:
CONFIG = loadfn(os.path.join(MODULE_DIR, "MPXANESSet.yaml"))
if radius is None:
radius = 10
return FEFFDictSet(absorber_index[0], sub_d['header'].struct, radius=radius,
config_dict=CONFIG, edge=sub_d["parameters"]["EDGE"],
nkpts=1000, user_tag_settings=sub_d["parameters"])
def from_directory(input_dir):
"""
Read in a set of FEFF input files from a directory, which is
useful when existing FEFF input needs some adjustment.
"""
sub_d = {}
for fname, ftype in [("HEADER", Header), ("PARAMETERS", Tags)]:
fullzpath = zpath(os.path.join(input_dir, fname))
sub_d[fname.lower()] = ftype.from_file(fullzpath)
# Generation of FEFFDict set requires absorbing atom, need to search
# the index of absorption atom in the structure according to the
# distance matrix and shell species information contained in feff.inp
absorber_index = []
radius = None
feffinp = zpath(os.path.join(input_dir, 'feff.inp'))
if "RECIPROCAL" not in sub_d["parameters"]:
input_atoms = Atoms.cluster_from_file(feffinp)
shell_species = np.array([x.species_string for x in input_atoms])
# First row of distance matrix represents the distance from the absorber to
# the rest atoms
distance_matrix = input_atoms.distance_matrix[0, :]
# Get radius value
from math import ceil
radius = int(ceil(input_atoms.get_distance(input_atoms.index(input_atoms[0]),
input_atoms.index(input_atoms[-1]))))
for site_index, site in enumerate(sub_d['header'].struct):
if site.specie == input_atoms[0].specie:
site_atoms = Atoms(sub_d['header'].struct, absorbing_atom=site_index,
radius=radius)
site_distance = np.array(site_atoms.get_lines())[:, 5].astype(np.float64)
site_shell_species = np.array(site_atoms.get_lines())[:, 4]
shell_overlap = min(shell_species.shape[0], site_shell_species.shape[0])
if np.allclose(distance_matrix[:shell_overlap], site_distance[:shell_overlap]) and \
np.all(site_shell_species[:shell_overlap] == shell_species[:shell_overlap]):
absorber_index.append(site_index)
if "RECIPROCAL" in sub_d["parameters"]:
absorber_index = sub_d["parameters"]["TARGET"]
absorber_index[0] = int(absorber_index[0]) - 1
# Generate the input set
if 'XANES' in sub_d["parameters"]:
CONFIG = loadfn(os.path.join(MODULE_DIR, "MPXANESSet.yaml"))
if radius is None:
radius = 10
return FEFFDictSet(absorber_index[0], sub_d['header'].struct, radius=radius,
config_dict=CONFIG, edge=sub_d["parameters"]["EDGE"],
nkpts=1000, user_tag_settings=sub_d["parameters"])
sg=186, lattice=zno_lattice_init,
species=[Element('Zn'), Element('O')],
coords=[
[1 / 3, 2 / 3, 0.00000],
[1 / 3, 2 / 3, 0.37780],
],
coords_are_cartesian=False,
tol=1e-9,
)
print(zno_structure)
print(zno_structure.get_space_group_info())
out_file_name = '/home/yugin/PycharmProjects/neurons/data/src/feff.inp.new2'
file_name = '/home/yugin/PycharmProjects/neurons/data/src/feff.inp.old'
atoms_obj = Atoms(zno_structure, 'O', 12)
pprint(atoms_obj.struct.cart_coords)
pprint(atoms_obj.get_lines())
header_obj = Header(struct=zno_structure)
pot_obj = Potential(zno_structure, 'O')
tags_obj = Tags().from_file(filename=file_name)
pprint(tags_obj.as_dict())
pot_obj.pot_string_from_file(filename=file_name)
pprint(pot_obj)
atoms_obj.atoms_string_from_file(filename=file_name)
pprint(atoms_obj.as_dict())
header_obj.write_file(out_file_name)
tags_obj.write_file(out_file_name)
