def parse_atom_range(geom, value):
if value.lower() in ("all", ":"):
return np.arange(geom.no), "all"
value = ",".join( # ensure only single commas (no space between them)
"".join( # ensure no empty whitespaces
",".join( # join different lines with a comma
value.splitlines()).split()).split(","))
# Sadly many shell interpreters does not
# allow simple [] because they are expansion tokens
# in the shell.
# We bypass this by allowing *, [, {
# * will "only" fail if files are named accordingly, else
# it will be passed as-is.
# { [ *
sep = ['c', 'b', '*']
failed = True
while failed and len(sep) > 0:
try:
ranges = lstranges(
strmap(int, value, 0, len(geom), sep.pop()))
failed = False
except Exception:
pass
if failed:
print(value)
raise ValueError("Could not parse the atomic/orbital ranges")
# we have only a subset of the orbitals
orbs = []
no = 0
for atoms in ranges:
if isinstance(atoms, list):
# Get atoms and orbitals
ob = geom.a2o(atoms[0] - 1, True)
# We normalize for the total number of orbitals
# on the requested atoms.
# In this way the user can compare directly the DOS
# for same atoms with different sets of orbitals and the
# total will add up.
no += len(ob)
ob = ob[asarrayi(atoms[1]) - 1]
else:
ob = geom.a2o(atoms - 1, True)
no += len(ob)
orbs.append(ob)
if len(orbs) == 0:
print('Available atoms:')
print(f' 1-{len(geometry)}')
print('Input atoms:')
print(' ', value)
raise ValueError(
'Atomic/Orbital requests are not fully included in the device region.'
)
# Add one to make the c-index equivalent to the f-index
return np.concatenate(orbs).flatten(), value
def __call__(self, parser, ns, value, option_string=None):
value = (value
.replace("s", 0)
.replace("p", 1)
.replace("d", 2)
.replace("f", 3)
.replace("g", 4)
)
ns._l = strmap(int, value)[0]
def categorize(self, geometry, *args, **kwargs):
# Now that we have the geometry, we know what is the end index
# and we can finally safely convert the sequence to indices.
indices_map = strmap(int, self._seq, start=0, end=geometry.na - 1)
indices = lstranges(
self._sanitize_negs(indices_map, end=geometry.na - 1))
# Initialize the machinery of AtomIndex
super().__init__(indices)
self.set_name(self._seq)
# Finally categorize
return super().categorize(geometry, *args, **kwargs)
def __call__(self, parser, ns, value, option_string=None):
E = ns._E
Emap = strmap(float, value, E.min(), E.max())
def Eindex(e):
return np.abs(E - e).argmin()
# Convert to actual indices
E = []
for begin, end in Emap:
if begin is None and end is None:
ns._Erng = None
return
elif begin is None:
E.append(range(Eindex(end)+1))
elif end is None:
E.append(range(Eindex(begin), len(E)))
else:
E.append(range(Eindex(begin), Eindex(end)+1))
# Issuing unique also sorts the entries
ns._Erng = np.unique(arrayi(E).flatten())
def __call__(self, parser, ns, value, option_string=None):
ns._Emap = strmap(float, value)[0]
def __call__(self, parser, ns, value, option_string=None):
ns._Emap = strmap(float, value)[0]
def __call__(self, parser, ns, value, option_string=None):
ns._n = strmap(int, value)[0]
