def qcdb_post_parse_output(self, input_model: AtomicInput,
output_model: "AtomicResult") -> "AtomicResult":
dqcvars = PreservingDict(copy.deepcopy(output_model.extras["qcvars"]))
for k in list(dqcvars.keys()):
if k in ["DETCI AVG DVEC NORM", "MCSCF TOTAL ENERGY"]:
dqcvars.pop(k)
qcvars.build_out(dqcvars)
calcinfo = qcvars.certify_and_datumize(
dqcvars, plump=True, nat=len(output_model.molecule.symbols))
output_model.extras["qcdb:qcvars"] = calcinfo
return output_model
def qcdb_post_parse_output(self, input_model: AtomicInput,
output_model: "AtomicResult") -> "AtomicResult":
progvars = PreservingDict(copy.deepcopy(output_model.extras["qcvars"]))
ropts = input_model.extras["qcdb:options"]
# badly placed
# if "MP2 OPPOSITE-SPIN CORRELATION ENERGY" in progvars and "MP2 SAME-SPIN CORRELATION ENERGY" in progvars:
# oss_opt = ropts.scroll['QCDB']['MP2_OS_SCALE']
# sss_opt = ropts.scroll['QCDB']['MP2_SS_SCALE']
# custom_scsmp2_corl = \
# Decimal(oss_opt.value) * progvars["MP2 OPPOSITE-SPIN CORRELATION ENERGY"] + \
# Decimal(sss_opt.value) * progvars["MP2 SAME-SPIN CORRELATION ENERGY"]
# if "MP2 SINGLES ENERGY" in progvars:
# custom_scsmp2_corl += progvars["MP2 SINGLES ENERGY"]
# progvars["CUSTOM SCS-MP2 CORRELATION ENERGY"] = custom_scsmp2_corl
#
# if "CCSD OPPOSITE-SPIN CORRELATION ENERGY" in progvars and "CCSD SAME-SPIN CORRELATION ENERGY" in progvars:
# oss_opt = ropts.scroll['QCDB']['CCSD_OS_SCALE']
# sss_opt = ropts.scroll['QCDB']['CCSD_SS_SCALE']
# custom_scsmp2_corl = \
# Decimal(oss_opt.value) * progvars["CCSD OPPOSITE-SPIN CORRELATION ENERGY"] + \
# Decimal(sss_opt.value) * progvars["CCSD SAME-SPIN CORRELATION ENERGY"]
# # TODO check on validity of CCSD SINGLES ENERGY
# if "CCSD SINGLES ENERGY" in progvars:
# custom_scsccsd_corl += progvars["CCSD SINGLES ENERGY"]
# progvars["CUSTOM SCS-CCSD CORRELATION ENERGY"] = custom_scsccsd_corl
qcvars.build_out(progvars)
calcinfo = qcvars.certify_and_datumize(
progvars, plump=True, nat=len(output_model.molecule.symbols))
output_model.extras["qcdb:qcvars"] = calcinfo
return output_model
def qcdb_post_parse_output(self, input_model: 'ResultInput',
output_model: 'Result') -> 'Result':
dqcvars = PreservingDict(copy.deepcopy(output_model.extras['qcvars']))
# badly placed
# Cfour's SCS-MP2 is non adjustible and only valid for UHF
# ROMP2 doesn't print SS & OS
if "MP2 OPPOSITE-SPIN CORRELATION ENERGY" in dqcvars and "MP2 SAME-SPIN CORRELATION ENERGY" in dqcvars:
oss_opt = input_model.extras['qcdb:options'].scroll['QCDB'][
'MP2_OS_SCALE']
sss_opt = input_model.extras['qcdb:options'].scroll['QCDB'][
'MP2_SS_SCALE']
custom_scsmp2_corl = \
Decimal(oss_opt.value) * dqcvars["MP2 OPPOSITE-SPIN CORRELATION ENERGY"] + \
Decimal(sss_opt.value) * dqcvars["MP2 SAME-SPIN CORRELATION ENERGY"]
if "MP2 SINGLES ENERGY" in dqcvars:
custom_scsmp2_corl += dqcvars["MP2 SINGLES ENERGY"]
dqcvars["CUSTOM SCS-MP2 CORRELATION ENERGY"] = custom_scsmp2_corl
qcvars.build_out(dqcvars)
calcinfo = qcvars.certify(dqcvars,
plump=True,
nat=len(output_model.molecule.symbols))
output_model.extras['qcdb:qcvars'] = calcinfo
return output_model
def qcdb_post_parse_output(self, input_model: AtomicInput,
output_model: "AtomicResult") -> "AtomicResult":
dqcvars = PreservingDict(copy.deepcopy(output_model.extras["qcvars"]))
# badly placed
# Cfour's SCS-MP2 is non adjustible and only valid for UHF
# ROMP2 doesn't print SS & OS
# if "MP2 OPPOSITE-SPIN CORRELATION ENERGY" in dqcvars and "MP2 SAME-SPIN CORRELATION ENERGY" in dqcvars:
# oss_opt = input_model.extras['qcdb:options'].scroll['QCDB']['MP2_OS_SCALE']
# sss_opt = input_model.extras['qcdb:options'].scroll['QCDB']['MP2_SS_SCALE']
# custom_scsmp2_corl = \
# Decimal(oss_opt.value) * dqcvars["MP2 OPPOSITE-SPIN CORRELATION ENERGY"] + \
# Decimal(sss_opt.value) * dqcvars["MP2 SAME-SPIN CORRELATION ENERGY"]
# if "MP2 SINGLES ENERGY" in dqcvars:
# custom_scsmp2_corl += dqcvars["MP2 SINGLES ENERGY"]
# dqcvars["CUSTOM SCS-MP2 CORRELATION ENERGY"] = custom_scsmp2_corl
try:
qcvars.build_out(dqcvars)
except ValueError:
raise InputError(
error_stamp(output_model.native_files["input"],
output_model.stdout, output_model.stderr))
calcinfo = qcvars.certify_and_datumize(
dqcvars, plump=True, nat=len(output_model.molecule.symbols))
output_model.extras["qcdb:qcvars"] = calcinfo
return output_model
def qcdb_post_parse_output(self, input_model: AtomicInput,
output_model: "AtomicResult") -> "AtomicResult":
dqcvars = PreservingDict(copy.deepcopy(output_model.extras["qcvars"]))
qcvars.build_out(dqcvars)
calcinfo = qcvars.certify_and_datumize(
dqcvars, plump=True, nat=len(output_model.molecule.symbols))
output_model.extras["qcdb:qcvars"] = calcinfo
return output_model
def qcdb_post_parse_output(self, input_model: 'ResultInput',
output_model: 'Result') -> 'Result':
dqcvars = PreservingDict(copy.deepcopy(output_model.extras['qcvars']))
qcvars.build_out(dqcvars)
calcinfo = qcvars.certify(dqcvars,
plump=True,
nat=len(output_model.molecule.symbols))
output_model.extras['qcdb:qcvars'] = calcinfo
return output_model
def dftd3_harvest(jobrec, dftd3rec):
"""Processes raw results from read-only `dftd3rec` into QCAspect fields in returned `jobrec`."""
try:
jobrec["molecule"]["real"]
jobrec["do_gradient"]
except KeyError as err:
raise KeyError("Required fields missing from ({})".format(
jobrec.keys())) from err
try:
dftd3rec["stdout"]
if jobrec["do_gradient"] is True:
dftd3rec["dftd3_gradient"]
except KeyError as err:
raise KeyError("Required fields missing from ({})".format(
dftd3rec.keys())) from err
# parse energy output (could go further and break into E6, E8, E10 and Cn coeff)
for ln in dftd3rec["stdout"].splitlines():
if re.search("DFTD3 V", ln):
version = ln.replace("DFTD3", "").replace("|", "").strip().lower()
elif re.match(" Edisp /kcal,au", ln):
# ene = float(ln.split()[3])
ene = Decimal(ln.split()[3])
elif re.match(" normal termination of dftd3", ln):
break
else:
raise Dftd3Error(
"Unsuccessful run. Possibly -D variant not available in dftd3 version."
)
# parse gradient output
if "dftd3_gradient" in dftd3rec:
real = np.array(jobrec["molecule"]["real"])
fnat = real.shape[0]
rnat = np.sum(real)
srealgrad = dftd3rec["dftd3_gradient"].replace("D", "E")
realgrad = np.fromstring(srealgrad, count=3 * rnat, sep=" ").reshape(
(-1, 3))
ireal = np.argwhere(real).reshape((-1))
fullgrad = np.zeros((fnat, 3))
fullgrad[ireal, :] = realgrad
# TODO if dftd3rec['do_gradient']: raise Dftd3Error
# QCAspect = collections.namedtuple('QCAspect', 'lbl unit data comment')
# calcinfo = []
# calcinfo.append(QCAspect('DISPERSION CORRECTION ENERGY', '[Eh]', ene, ''))
# calcinfo.append(
# QCAspect('DISPERSION CORRECTION GRADIENT', '[Eh/a0]', fullgrad, ''))
# calcinfo = {info.lbl: info for info in calcinfo}
# pprint.pprint(jobrec)
# import sys
# sys.exit()
formal = {
"d2p4": "d2",
"d2gr": "d2",
"d3zero": "d3",
"d3bj": "d3(bj)",
"d3mzero": "d3m",
"d3mbj": "d3m(bj)"
}
dash = formal[jobrec["dashlevel"]]
if jobrec["functional"] == "":
qcvkey = " ".join(["custom", dash]).upper()
else:
fctl = jobrec["functional"]
if fctl.endswith("-d"):
fctl = fctl[:-2]
elif fctl == "lcwpbe":
fctl = "wpbe"
qcvkey = "-".join([fctl, dash]).upper()
dftd3var = {}
dftd3var["DISPERSION CORRECTION ENERGY"] = ene
dftd3var["{} DISPERSION CORRECTION ENERGY".format(qcvkey)] = ene
if "dftd3_gradient" in dftd3rec:
dftd3var["DISPERSION CORRECTION GRADIENT"] = fullgrad
dftd3var["{} DISPERSION CORRECTION GRADIENT".format(qcvkey)] = fullgrad
progvars = PreservingDict(dftd3var)
qcvars.build_out(progvars)
calcinfo = qcvars.certify_and_datumize(progvars)
# amalgamate output
text = dftd3rec["stdout"]
text += "\n <<< DFTD3 {} {} Results >>>".format(
"", "") # name.lower(), calledby.capitalize())) # banner()
text += print_variables(calcinfo)
jobrec["raw_output"] = text
jobrec["qcvars"] = calcinfo
prov = {}
prov["creator"] = "DFTD3"
prov["routine"] = sys._getframe().f_code.co_name
prov["version"] = version
jobrec["provenance"].append(prov)
return jobrec