def _parse(blines, optimize=False):
header_ln = blines.pop(0) # noqa: F841
nsets = int(blines.pop(0))
basis = []
for n in range(nsets):
comp = [int(p) for p in blines.pop(0).split()]
lmin, lmax, nexps, ncontractions = comp[1], comp[2], comp[3], comp[4:]
basis_n = [[l] for l in range(lmin,lmax+1)]
for nexp in range(nexps):
line = blines.pop(0)
dat = line.split()
try:
bfun = [float(x) for x in dat]
except ValueError:
if DISABLE_EVAL:
raise ValueError('Failed to parse basis %s' % line)
else:
bfun = eval(','.join(dat))
exp = bfun.pop(0)
for i,l in enumerate(range(lmin,lmax+1)):
cl = [exp]
for c in range(ncontractions[i]):
cl.append(bfun.pop(0))
basis_n[i].append(tuple(cl))
basis.extend(basis_n)
basis_sorted = []
for l in range(MAXL):
basis_sorted.extend([b for b in basis if b[0] == l])
if optimize:
basis_sorted = parse_nwchem.optimize_contraction(basis_sorted)
basis_sorted = parse_nwchem.remove_zero(basis_sorted)
return basis_sorted
def _parse(blines, optimize=False):
header_ln = blines.pop(0)
nsets = int(blines.pop(0))
basis = []
for n in range(nsets):
comp = [int(p) for p in blines.pop(0).split()]
n, lmin, lmax, nexps, ncontractions = comp[0], comp[1], comp[2], comp[3], comp[4:]
basis_n = [[l] for l in range(lmin,lmax+1)]
for nexp in range(nexps):
bfun = [float(x) for x in blines.pop(0).split()]
exp = bfun.pop(0)
for i,l in enumerate(range(lmin,lmax+1)):
cl = [exp]
for c in range(ncontractions[i]):
cl.append(bfun.pop(0))
basis_n[i].append(tuple(cl))
basis.extend(basis_n)
basis_sorted = []
for l in range(MAXL):
basis_sorted.extend([b for b in basis if b[0] == l])
if optimize:
basis_sorted = parse_nwchem.optimize_contraction(basis_sorted)
basis_sorted = parse_nwchem.remove_zero(basis_sorted)
return basis_sorted
def _parse(raw_basis, optimize=True):
basis_add = []
for line in raw_basis:
dat = line.strip()
if dat.startswith('!'):
continue
elif dat[0].isalpha():
key = dat.split()
if len(key) == 2:
# skip the line which has only two items. It's the line for
# element symbol
continue
elif key[0] == 'SP':
basis_add.append([0])
basis_add.append([1])
else:
basis_add.append([MAPSPDF[key[0]]])
else:
line = [float(x) for x in dat.replace('D','e').split()]
if key[0] == 'SP':
basis_add[-2].append([line[0], line[1]])
basis_add[-1].append([line[0], line[2]])
else:
basis_add[-1].append(line)
basis_sorted = []
for l in range(MAXL):
basis_sorted.extend([b for b in basis_add if b[0] == l])
if optimize:
basis_sorted = optimize_contraction(basis_sorted)
basis_sorted = remove_zero(basis_sorted)
return basis_sorted
def _parse(raw_basis, optimize=True):
# pass 1
basis_add = []
for dat in raw_basis:
dat = dat.upper()
if dat[0].isalpha():
if ' ' not in dat:
# Skip the line of comments
continue
status = dat
val = []
basis_add.append([status, val])
else:
val.append(dat)
raw_basis = [[k, ' '.join(v)] for k, v in basis_add]
# pass 2
basis_add = []
for status, valstring in raw_basis:
tmp = status.split(':')
key = tmp[0].split()
l = MAPSPDF[key[1].upper()]
#TODO if key[-1] == 'SV'
val = tmp[1].split()
np = int(val[0])
nc = int(val[1])
rawd = [float(x) for x in valstring.replace('D', 'e').split()]
if nc == 0:
for e in rawd:
basis_add.append([l, [e, 1.]])
else:
exps = numpy.array(rawd[:np])
coeff = numpy.zeros((np, nc))
p1 = np
for i in range(nc):
start, end = val[2 + i].split('.')
start, end = int(start), int(end)
nd = end - start + 1
p0, p1 = p1, p1 + nd
coeff[start - 1:end, i] = rawd[p0:p1]
bval = numpy.hstack((exps[:, None], coeff))
basis_add.append([l] + bval.tolist())
basis_sorted = []
for l in range(MAXL):
basis_sorted.extend([b for b in basis_add if b[0] == l])
if optimize:
basis_sorted = optimize_contraction(basis_sorted)
basis_sorted = remove_zero(basis_sorted)
return basis_sorted
def _parse(raw_basis, optimize=True):
# pass 1
basis_add = []
for dat in raw_basis:
dat = dat.upper()
if dat[0].isalpha():
if ' ' not in dat:
# Skip the line of comments
continue
status = dat
val = []
basis_add.append([status, val])
else:
val.append(dat)
raw_basis = [[k, ' '.join(v)] for k,v in basis_add]
# pass 2
basis_add = []
for status, valstring in raw_basis:
tmp = status.split(':')
key = tmp[0].split()
l = MAPSPDF[key[1].upper()]
#TODO if key[-1] == 'SV'
val = tmp[1].split()
np = int(val[0])
nc = int(val[1])
rawd = [float(x) for x in valstring.replace('D','e').split()]
if nc == 0:
for e in rawd:
basis_add.append([l, [e, 1.]])
else:
exps = numpy.array(rawd[:np])
coeff = numpy.zeros((np,nc))
p1 = np
for i in range(nc):
start, end = val[2+i].split('.')
start, end = int(start), int(end)
nd = end - start + 1
p0, p1 = p1, p1 + nd
coeff[start-1:end,i] = rawd[p0:p1]
bval = numpy.hstack((exps[:,None], coeff))
basis_add.append([l] + bval.tolist())
basis_sorted = []
for l in range(MAXL):
basis_sorted.extend([b for b in basis_add if b[0] == l])
if optimize:
basis_sorted = optimize_contraction(basis_sorted)
basis_sorted = remove_zero(basis_sorted)
return basis_sorted
def convert_to(data, elem_list=elements.IUPAC_LIST):
"""
Take a list of dicts containing the entries
atnum: atomic number
functions: list of dict with the keys:
angular_momentum Angular momentum of the function
coefficients List of contraction coefficients
exponents List of contraction exponents
and return a dictionary in the format expected by pscf.gto.Mole.
Example:
>>> from pyscf import gto
>>> from look4bas.basis_format.pyscf import convert_to
>>>
>>> mol = gto.Mole()
>>> mol.basis = convert_to(look4bas_data)
"""
ret = {}
for atom in data:
symbol = elem_list[atom["atnum"]]["symbol"]
bdef = []
for fun in sorted(atom["functions"],
key=lambda x: x["angular_momentum"]):
data_symbol = [fun["angular_momentum"]]
if len(fun["coefficients"]) != len(fun["exponents"]):
raise ValueError(
"Length of coefficients and length of exponents "
"in contraction specification need to agree")
for i, coeff in enumerate(fun["coefficients"]):
exp = fun["exponents"][i]
data_symbol.append([exp, coeff])
bdef.append(data_symbol)
bdef = optimize_contraction(bdef)
bdef = remove_zeros(bdef)
ret[symbol] = bdef
for atom in data:
if "ecp" in atom:
warn(convert_to.__name__ + " currently ignores any ECP "
"definitions parsed.")
break
return ret