def scf_set_reference_local(name):
"""
Figures out the correct SCF reference to set locally
"""
optstash = p4util.OptionsState(
['SCF', 'DFT_FUNCTIONAL'],
['SCF', 'SCF_TYPE'],
['SCF', 'REFERENCE'])
# Alter default algorithm
if not core.has_option_changed('SCF', 'SCF_TYPE'):
core.set_local_option('SCF', 'SCF_TYPE', 'DF')
if name == 'hf':
if core.get_option('SCF','REFERENCE') == 'RKS':
core.set_local_option('SCF','REFERENCE','RHF')
elif core.get_option('SCF','REFERENCE') == 'UKS':
core.set_local_option('SCF','REFERENCE','UHF')
elif name == 'scf':
if core.get_option('SCF','REFERENCE') == 'RKS':
if (len(core.get_option('SCF', 'DFT_FUNCTIONAL')) > 0) or core.get_option('SCF', 'DFT_CUSTOM_FUNCTIONAL') is not None:
pass
else:
core.set_local_option('SCF','REFERENCE','RHF')
elif core.get_option('SCF','REFERENCE') == 'UKS':
if (len(core.get_option('SCF', 'DFT_FUNCTIONAL')) > 0) or core.get_option('SCF', 'DFT_CUSTOM_FUNCTIONAL') is not None:
pass
else:
core.set_local_option('SCF','REFERENCE','UHF')
return optstash
def scf_set_reference_local(name, is_dft=False):
"""
Figures out the correct SCF reference to set locally
"""
optstash = p4util.OptionsState(
['SCF_TYPE'],
['SCF', 'REFERENCE'])
# Alter default algorithm
if not core.has_global_option_changed('SCF_TYPE'):
core.set_global_option('SCF_TYPE', 'DF')
# Alter reference name if needed
user_ref = core.get_option('SCF', 'REFERENCE')
sup = build_superfunctional_from_dictionary(functionals[name], 1, 1, True)[0]
if sup.needs_xc() or is_dft:
if (user_ref == 'RHF'):
core.set_local_option('SCF', 'REFERENCE', 'RKS')
elif (user_ref == 'UHF'):
core.set_local_option('SCF', 'REFERENCE', 'UKS')
elif (user_ref == 'ROHF'):
raise ValidationError('ROHF reference for DFT is not available.')
elif (user_ref == 'CUHF'):
raise ValidationError('CUHF reference for DFT is not available.')
# else we are doing HF and nothing needs to be overloaded
return optstash
def set_module_options(module, options_dict):
"""
Sets Psi4 module options from a module specification and input dictionary.
"""
for k, v, in options_dict.items():
core.set_local_option(module.upper(), k.upper(), v)
def restore(self):
core.set_global_option(self.option, self.value_global)
if not self.haschanged_global:
core.revoke_global_option_changed(self.option)
if self.module:
core.set_local_option(self.module, self.option, self.value_local)
if not self.haschanged_local:
core.revoke_local_option_changed(self.module, self.option)
def df_mp2_sapt_dispersion(dimer_wfn, wfn_A, wfn_B, primary_basis, aux_basis, cache, do_print=True):
if do_print:
core.print_out("\n ==> E20 Dispersion (MP2) <== \n\n")
optstash = p4util.OptionsState(['SAPT', 'SAPT0_E10'], ['SAPT', 'SAPT0_E20IND'], ['SAPT', 'SAPT0_E20DISP'],
['SAPT', 'SAPT_QUIET'])
core.set_local_option("SAPT", "SAPT0_E10", False)
core.set_local_option("SAPT", "SAPT0_E20IND", False)
core.set_local_option("SAPT", "SAPT0_E20DISP", True)
core.set_local_option("SAPT", "SAPT_QUIET", True)
if core.get_option('SCF', 'REFERENCE') == 'RHF':
core.IO.change_file_namespace(psif.PSIF_SAPT_MONOMERA, 'monomerA', 'dimer')
core.IO.change_file_namespace(psif.PSIF_SAPT_MONOMERB, 'monomerB', 'dimer')
core.IO.set_default_namespace('dimer')
dimer_wfn.set_basisset("DF_BASIS_SAPT", aux_basis)
dimer_wfn.set_basisset("DF_BASIS_ELST", aux_basis)
e_sapt = core.sapt(dimer_wfn, wfn_A, wfn_B)
optstash.restore()
svars = dimer_wfn.variables()
core.print_out("\n")
core.print_out(print_sapt_var("Disp20 (MP2)", svars["E DISP20"], short=True) + "\n")
core.print_out(print_sapt_var("Exch-Disp20,u", svars["E EXCH-DISP20"], short=True) + "\n")
ret = {}
ret["Exch-Disp20,u"] = svars["E EXCH-DISP20"]
ret["Disp20,u"] = svars["E DISP20"]
return ret
def dft_set_reference_local(name):
"""
Figures out the correct DFT reference to set locally
"""
optstash = p4util.OptionsState(
['SCF', 'DFT_FUNCTIONAL'],
['SCF', 'REFERENCE'],
['SCF', 'SCF_TYPE'],
['DF_BASIS_MP2'],
['DFMP2', 'MP2_OS_SCALE'],
['DFMP2', 'MP2_SS_SCALE'])
# Alter default algorithm
if not core.has_option_changed('SCF', 'SCF_TYPE'):
core.set_local_option('SCF', 'SCF_TYPE', 'DF')
core.set_local_option('SCF', 'DFT_FUNCTIONAL', name)
user_ref = core.get_option('SCF', 'REFERENCE')
if (user_ref == 'RHF'):
core.set_local_option('SCF', 'REFERENCE', 'RKS')
elif (user_ref == 'UHF'):
core.set_local_option('SCF', 'REFERENCE', 'UKS')
elif (user_ref == 'ROHF'):
raise ValidationError('ROHF reference for DFT is not available.')
elif (user_ref == 'CUHF'):
raise ValidationError('CUHF reference for DFT is not available.')
return optstash
def set_cholesky_from(mtd_type):
type_val = core.get_global_option(mtd_type)
if type_val == 'CD':
core.set_local_option('GPU_DFCC', 'DF_BASIS_CC', 'CHOLESKY')
# Alter default algorithm
if not core.has_global_option_changed('SCF_TYPE'):
optstash.add_option(['SCF_TYPE'])
core.set_global_option('SCF_TYPE', 'CD')
core.print_out(""" SCF Algorithm Type (re)set to CD.\n""")
elif type_val in ['DF', 'DISK_DF']:
if core.get_option('GPU_DFCC', 'DF_BASIS_CC') == 'CHOLESKY':
core.set_local_option('GPU_DFCC', 'DF_BASIS_CC', '')
proc_util.check_disk_df(name.upper(), optstash)
else:
raise ValidationError("""Invalid type '%s' for DFCC""" % type_val)
def set_options(options_dict, verbose=1):
"""Sets Psi4 options from an input dictionary.
Parameters
----------
options_dict : dict
Dictionary where keys are "option_name" for global options or
"module_name__option_name" (double underscore separation) for
option local to "module_name". Values are the option value. All
are case insensitive.
verbose : int, optional
Control print volume.
Returns
-------
None
"""
optionre = re.compile(r'\A(?P<module>\w+__)?(?P<option>\w+)\Z', re.IGNORECASE)
rejected = {}
for k, v, in options_dict.items():
mobj = optionre.match(k)
module = mobj.group('module').upper()[:-2] if mobj.group('module') else None
option = mobj.group('option').upper()
if module:
if (module, option, v) not in [('SCF', 'GUESS', 'READ')]:
# TODO guess/read exception is for distributed driver. should be handled differently.
try:
core.set_local_option(module, option, v)
except RuntimeError as err:
rejected[k] = (v, err)
if verbose > 1:
print('Setting: core.set_local_option', module, option, v)
else:
try:
core.set_global_option(option, v)
except RuntimeError as err:
rejected[k] = (v, err)
if verbose > 1:
print('Setting: core.set_global_option', option, v)
if rejected:
raise ValidationError(f'Error setting options: {rejected}')
def pcm_helper(block):
"""
Passes multiline string *block* to PCMSolver parser.
Parameters
----------
block: multiline string with PCM input in PCMSolver syntax.
"""
suffix = str(os.getpid()) + '.' + str(uuid.uuid4())[:8]
pcmsolver_fname = 'pcmsolver.' + suffix + '.inp'
with open(pcmsolver_fname, 'w') as handle:
handle.write(block)
import pcmsolver
parsed_pcm = pcmsolver.parse_pcm_input(pcmsolver_fname)
os.remove(pcmsolver_fname)
pcmsolver_parsed_fname = '@pcmsolver.' + suffix
with open(pcmsolver_parsed_fname, 'w') as tmp:
tmp.write(parsed_pcm)
core.set_local_option('PCM', 'PCMSOLVER_PARSED_FNAME', '{}'.format(pcmsolver_parsed_fname))
def process_option(spaces, module, key, value, line):
"""Function to process a line with set or in a set block
into global/local domain and keyword/value.
"""
module = module.upper()
key = key.upper()
isbasis = True if 'BASIS' in key else False
value = quotify(value.strip(), isbasis=isbasis)
if module == "GLOBALS" or module == "GLOBAL" or module == "" or module.isspace():
# If it's really a global, we need slightly different syntax
if runalso:
core.set_global_option(key, dequotify(value))
return "%score.set_global_option(\"%s\", %s)\n" % (spaces, key, value)
else:
# It's a local option, so we need the module name in there too
if runalso:
core.set_local_option(module, key, dequotify(value))
return "%score.set_local_option(\"%s\", \"%s\", %s)\n" % (spaces, module, key, value)
def pcm_helper(block):
"""
Passes multiline string *block* to PCMSolver parser.
Parameters
----------
block: multiline string with PCM input in PCMSolver syntax.
"""
suffix = str(os.getpid()) + '.' + str(uuid.uuid4())[:8]
pcmsolver_fname = 'pcmsolver.' + suffix + '.inp'
with open(pcmsolver_fname, 'w') as handle:
handle.write(block)
import pcmsolver
parsed_pcm = pcmsolver.parse_pcm_input(pcmsolver_fname)
os.remove(pcmsolver_fname)
pcmsolver_parsed_fname = '@pcmsolver.' + suffix
with open(pcmsolver_parsed_fname, 'w') as tmp:
tmp.write(parsed_pcm)
core.set_local_option('PCM', 'PCMSOLVER_PARSED_FNAME',
'{}'.format(pcmsolver_parsed_fname))
def scf_set_reference_local(name, is_dft=False):
"""
Figures out the correct SCF reference to set locally
"""
optstash = p4util.OptionsState(
['SCF', 'SCF_TYPE'],
['SCF', 'REFERENCE'])
# Alter default algorithm
if not core.has_option_changed('SCF', 'SCF_TYPE'):
core.set_local_option('SCF', 'SCF_TYPE', 'DF')
# Alter reference name if needed
user_ref = core.get_option('SCF', 'REFERENCE')
if (name not in dft_funcs.superfunctional_noxc_names) or (is_dft):
if (user_ref == 'RHF'):
core.set_local_option('SCF', 'REFERENCE', 'RKS')
elif (user_ref == 'UHF'):
core.set_local_option('SCF', 'REFERENCE', 'UKS')
elif (user_ref == 'ROHF'):
raise ValidationError('ROHF reference for DFT is not available.')
elif (user_ref == 'CUHF'):
raise ValidationError('CUHF reference for DFT is not available.')
# else we are doing HF and nothing needs to be overloaded
return optstash
def scf_set_reference_local(name, is_dft=False):
"""
Figures out the correct SCF reference to set locally
"""
optstash = p4util.OptionsState(['SCF', 'SCF_TYPE'], ['SCF', 'REFERENCE'])
# Alter default algorithm
if not core.has_option_changed('SCF', 'SCF_TYPE'):
core.set_local_option('SCF', 'SCF_TYPE', 'DF')
# Alter reference name if needed
user_ref = core.get_option('SCF', 'REFERENCE')
sup = build_superfunctional_from_dictionary(functionals[name], 1, 1,
True)[0]
if sup.needs_xc() or is_dft:
if (user_ref == 'RHF'):
core.set_local_option('SCF', 'REFERENCE', 'RKS')
elif (user_ref == 'UHF'):
core.set_local_option('SCF', 'REFERENCE', 'UKS')
elif (user_ref == 'ROHF'):
raise ValidationError('ROHF reference for DFT is not available.')
elif (user_ref == 'CUHF'):
raise ValidationError('CUHF reference for DFT is not available.')
# else we are doing HF and nothing needs to be overloaded
return optstash
def _init_addghost_C(self, oldcalc, calc):
# print('Adding ghost %s->%s' % (oldcalc, calc))
old_filename = self._fmt_mo_fn(oldcalc)
data = np.load(old_filename)
Ca_occ = core.Matrix.np_read(data, "Ca_occ")
Cb_occ = core.Matrix.np_read(data, "Cb_occ")
m1_nso = self.wfn_cache[('m1', 'm', oldcalc.Z)].nso()
m2_nso = self.wfn_cache[('m2', 'm', oldcalc.Z)].nso()
m1_nalpha = self.wfn_cache[('m1', 'm', oldcalc.Z)].nalpha()
m2_nalpha = self.wfn_cache[('m2', 'm', oldcalc.Z)].nalpha()
m1_nbeta = self.wfn_cache[('m1', 'm', oldcalc.Z)].nbeta()
m2_nbeta = self.wfn_cache[('m2', 'm', oldcalc.Z)].nbeta()
if calc.V == 'm1':
Ca_occ_d = core.Matrix('Ca_occ', (m1_nso + m2_nso), m1_nalpha)
Ca_occ_d.np[:m1_nso, :] = Ca_occ.np[:, :]
Cb_occ_d = core.Matrix('Cb_occ', (m1_nso + m2_nso), m1_nbeta)
Cb_occ_d.np[:m1_nso, :] = Cb_occ.np[:, :]
elif calc.V == 'm2':
Ca_occ_d = core.Matrix('Ca_occ', (m1_nso + m2_nso), m2_nalpha)
Ca_occ_d.np[-m2_nso:, :] = Ca_occ.np[:, :]
Cb_occ_d = core.Matrix('Cb_occ', (m1_nso + m2_nso), m2_nbeta)
Cb_occ_d.np[-m2_nso:, :] = Cb_occ.np[:, :]
data_dict = dict(data)
data_dict.update(Ca_occ_d.np_write(prefix='Ca_occ'))
data_dict.update(Cb_occ_d.np_write(prefix='Cb_occ'))
psi_scratch = core.IOManager.shared_object().get_default_path()
write_filename = os.path.join(
psi_scratch,
os.path.split(
os.path.abspath(core.get_writer_file_prefix(
self.fmt_ns(calc))))[1] + ".180.npz")
np.savez(write_filename, **data_dict)
extras.register_numpy_file(write_filename)
core.set_local_option('SCF', 'GUESS', 'READ')
def process_option(spaces, module, key, value, line):
"""Function to process a line with set or in a set block
into global/local domain and keyword/value.
"""
module = module.upper()
key = key.upper()
isbasis = True if 'BASIS' in key else False
value = quotify(value.strip(), isbasis=isbasis)
if module == "GLOBALS" or module == "GLOBAL" or module == "" or module.isspace(
):
# If it's really a global, we need slightly different syntax
if runalso:
core.set_global_option(key, dequotify(value))
return "%score.set_global_option(\"%s\", %s)\n" % (spaces, key, value)
else:
# It's a local option, so we need the module name in there too
if runalso:
core.set_local_option(module, key, dequotify(value))
return "%score.set_local_option(\"%s\", \"%s\", %s)\n" % (
spaces, module, key, value)
def df_mp2_sapt_dispersion(dimer_wfn,
wfn_A,
wfn_B,
primary_basis,
aux_basis,
cache,
do_print=True):
if do_print:
core.print_out("\n ==> E20 Dispersion (MP2) <== \n\n")
optstash = p4util.OptionsState(['SAPT', 'SAPT0_E10'],
['SAPT', 'SAPT0_E20IND'],
['SAPT', 'SAPT0_E20DISP'],
['SAPT', 'SAPT_QUIET'])
core.set_local_option("SAPT", "SAPT0_E10", False)
core.set_local_option("SAPT", "SAPT0_E20IND", False)
core.set_local_option("SAPT", "SAPT0_E20DISP", True)
core.set_local_option("SAPT", "SAPT_QUIET", True)
if core.get_option('SCF', 'REFERENCE') == 'RHF':
core.IO.change_file_namespace(psif.PSIF_SAPT_MONOMERA, 'monomerA',
'dimer')
core.IO.change_file_namespace(psif.PSIF_SAPT_MONOMERB, 'monomerB',
'dimer')
core.IO.set_default_namespace('dimer')
dimer_wfn.set_basisset("DF_BASIS_SAPT", aux_basis)
dimer_wfn.set_basisset("DF_BASIS_ELST", aux_basis)
e_sapt = core.sapt(dimer_wfn, wfn_A, wfn_B)
optstash.restore()
svars = dimer_wfn.variables()
core.print_out("\n")
core.print_out(
print_sapt_var("Disp20 (MP2)", svars["E DISP20"], short=True) + "\n")
core.print_out(
print_sapt_var("Exch-Disp20,u", svars["E EXCH-DISP20"], short=True) +
"\n")
ret = {}
ret["Exch-Disp20,u"] = svars["E EXCH-DISP20"]
ret["Disp20,u"] = svars["E DISP20"]
return ret
def _reset_pe_options(pofm: Dict):
"""Acts on ``Process::environment.options`` to clear it, then set it to state encoded in **pofm**.
Parameters
----------
pofm
Result of :py:func:`psi4.driver.p4util.prepare_options_for_modules(changedOnly=True, commandsInsteadDict=False, stateInsteadMediated=True)`
Returns
-------
None
"""
core.clean_options()
for go, dgo in pofm['GLOBALS'].items():
if dgo['has_changed']:
core.set_global_option(go, dgo['value'])
for module in _modules:
for lo, dlo in pofm[module].items():
if dlo['has_changed']:
core.set_local_option(module, lo, dlo['value'])
def reset_pe_options(pofm):
"""Acts on Process::environment.options to clear it, the set it to state encoded in `pofm`.
Parameters
----------
pofm : dict
Result of psi4.driver.p4util.prepare_options_for_modules(changedOnly=True, commandsInsteadDict=False)
Returns
-------
None
"""
core.clean_options()
for go, dgo in pofm['GLOBALS'].items():
if dgo['has_changed']:
core.set_global_option(go, dgo['value'])
for module in _modules:
for lo, dlo in pofm[module].items():
if dlo['has_changed']:
core.set_local_option(module, lo, dlo['value'])
def reset_pe_options(pofm):
"""Acts on Process::environment.options to clear it, the set it to state encoded in `pofm`.
Parameters
----------
pofm : dict
Result of psi4.driver.p4util.prepare_options_for_modules(changedOnly=True, commandsInsteadDict=False)
Returns
-------
None
"""
core.clean_options()
for go, dgo in pofm['GLOBALS'].items():
if dgo['has_changed']:
core.set_global_option(go, dgo['value'])
for module in _modules:
for lo, dlo in pofm[module].items():
if dlo['has_changed']:
core.set_local_option(module, lo, dlo['value'])
def run_sapt_dft(name, **kwargs):
optstash = p4util.OptionsState(['SCF_TYPE'], ['SCF', 'REFERENCE'],
['SCF', 'DFT_GRAC_SHIFT'],
['SCF', 'SAVE_JK'])
core.tstart()
# Alter default algorithm
if not core.has_global_option_changed('SCF_TYPE'):
core.set_global_option('SCF_TYPE', 'DF')
core.prepare_options_for_module("SAPT")
# Get the molecule of interest
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
sapt_dimer = kwargs.pop('molecule', core.get_active_molecule())
else:
core.print_out(
'Warning! SAPT argument "ref_wfn" is only able to use molecule information.'
)
sapt_dimer = ref_wfn.molecule()
sapt_dimer, monomerA, monomerB = proc_util.prepare_sapt_molecule(
sapt_dimer, "dimer")
# Grab overall settings
mon_a_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_A")
mon_b_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_B")
do_delta_hf = core.get_option("SAPT", "SAPT_DFT_DO_DHF")
sapt_dft_functional = core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL")
# Print out the title and some information
core.print_out("\n")
core.print_out(
" ---------------------------------------------------------\n")
core.print_out(" " + "SAPT(DFT) Procedure".center(58) + "\n")
core.print_out("\n")
core.print_out(" " + "by Daniel G. A. Smith".center(58) + "\n")
core.print_out(
" ---------------------------------------------------------\n")
core.print_out("\n")
core.print_out(
" !!! WARNING: SAPT(DFT) capability is in beta. Please use with caution. !!!\n\n"
)
core.print_out(" ==> Algorithm <==\n\n")
core.print_out(" SAPT DFT Functional %12s\n" %
str(sapt_dft_functional))
core.print_out(" Monomer A GRAC Shift %12.6f\n" % mon_a_shift)
core.print_out(" Monomer B GRAC Shift %12.6f\n" % mon_b_shift)
core.print_out(" Delta HF %12s\n" %
("True" if do_delta_hf else "False"))
core.print_out(" JK Algorithm %12s\n" %
core.get_global_option("SCF_TYPE"))
core.print_out("\n")
core.print_out(" Required computations:\n")
if (do_delta_hf):
core.print_out(" HF (Dimer)\n")
core.print_out(" HF (Monomer A)\n")
core.print_out(" HF (Monomer B)\n")
core.print_out(" DFT (Monomer A)\n")
core.print_out(" DFT (Monomer B)\n")
core.print_out("\n")
if (sapt_dft_functional != "HF") and ((mon_a_shift == 0.0) or
(mon_b_shift == 0.0)):
raise ValidationError(
'SAPT(DFT): must set both "SAPT_DFT_GRAC_SHIFT_A" and "B".')
if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
raise ValidationError(
'SAPT(DFT) currently only supports restricted references.')
core.IO.set_default_namespace('dimer')
data = {}
if (core.get_global_option('SCF_TYPE') == 'DF'):
# core.set_global_option('DF_INTS_IO', 'LOAD')
core.set_global_option('DF_INTS_IO', 'SAVE')
# # Compute dimer wavefunction
hf_wfn_dimer = None
if do_delta_hf:
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.set_global_option('DF_INTS_IO', 'SAVE')
core.timer_on("SAPT(DFT): Dimer SCF")
hf_data = {}
hf_wfn_dimer = scf_helper("SCF",
molecule=sapt_dimer,
banner="SAPT(DFT): delta HF Dimer",
**kwargs)
hf_data["HF DIMER"] = core.variable("CURRENT ENERGY")
core.timer_off("SAPT(DFT): Dimer SCF")
core.timer_on("SAPT(DFT): Monomer A SCF")
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'dimer', 'monomerA')
hf_wfn_A = scf_helper("SCF",
molecule=monomerA,
banner="SAPT(DFT): delta HF Monomer A",
**kwargs)
hf_data["HF MONOMER A"] = core.variable("CURRENT ENERGY")
core.timer_off("SAPT(DFT): Monomer A SCF")
core.timer_on("SAPT(DFT): Monomer B SCF")
core.set_global_option("SAVE_JK", True)
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
hf_wfn_B = scf_helper("SCF",
molecule=monomerB,
banner="SAPT(DFT): delta HF Monomer B",
**kwargs)
hf_data["HF MONOMER B"] = core.variable("CURRENT ENERGY")
core.set_global_option("SAVE_JK", False)
core.timer_off("SAPT(DFT): Monomer B SCF")
# Grab JK object and set to A (so we do not save many JK objects)
sapt_jk = hf_wfn_B.jk()
hf_wfn_A.set_jk(sapt_jk)
core.set_global_option("SAVE_JK", False)
# Move it back to monomer A
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerB', 'dimer')
core.print_out("\n")
core.print_out(
" ---------------------------------------------------------\n"
)
core.print_out(" " + "SAPT(DFT): delta HF Segment".center(58) +
"\n")
core.print_out("\n")
core.print_out(" " +
"by Daniel G. A. Smith and Rob Parrish".center(58) +
"\n")
core.print_out(
" ---------------------------------------------------------\n"
)
core.print_out("\n")
# Build cache
hf_cache = sapt_jk_terms.build_sapt_jk_cache(hf_wfn_A, hf_wfn_B,
sapt_jk, True)
# Electrostatics
core.timer_on("SAPT(DFT):SAPT:elst")
elst = sapt_jk_terms.electrostatics(hf_cache, True)
hf_data.update(elst)
core.timer_off("SAPT(DFT):SAPT:elst")
# Exchange
core.timer_on("SAPT(DFT):SAPT:exch")
exch = sapt_jk_terms.exchange(hf_cache, sapt_jk, True)
hf_data.update(exch)
core.timer_off("SAPT(DFT):SAPT:exch")
# Induction
core.timer_on("SAPT(DFT):SAPT:ind")
ind = sapt_jk_terms.induction(
hf_cache,
sapt_jk,
True,
maxiter=core.get_option("SAPT", "MAXITER"),
conv=core.get_option("SAPT", "D_CONVERGENCE"),
Sinf=core.get_option("SAPT", "DO_IND_EXCH_SINF"))
hf_data.update(ind)
core.timer_off("SAPT(DFT):SAPT:ind")
dhf_value = hf_data["HF DIMER"] - hf_data["HF MONOMER A"] - hf_data[
"HF MONOMER B"]
core.print_out("\n")
core.print_out(
print_sapt_hf_summary(hf_data, "SAPT(HF)", delta_hf=dhf_value))
data["Delta HF Correction"] = core.variable("SAPT(DFT) Delta HF")
sapt_jk.finalize()
del hf_wfn_A, hf_wfn_B, sapt_jk
if hf_wfn_dimer is None:
dimer_wfn = core.Wavefunction.build(sapt_dimer,
core.get_global_option("BASIS"))
else:
dimer_wfn = hf_wfn_dimer
# Set the primary functional
core.set_local_option('SCF', 'REFERENCE', 'RKS')
# Compute Monomer A wavefunction
core.timer_on("SAPT(DFT): Monomer A DFT")
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'dimer', 'monomerA')
if mon_a_shift:
core.set_global_option("DFT_GRAC_SHIFT", mon_a_shift)
core.IO.set_default_namespace('monomerA')
wfn_A = scf_helper(sapt_dft_functional,
post_scf=False,
molecule=monomerA,
banner="SAPT(DFT): DFT Monomer A",
**kwargs)
data["DFT MONOMERA"] = core.variable("CURRENT ENERGY")
core.set_global_option("DFT_GRAC_SHIFT", 0.0)
core.timer_off("SAPT(DFT): Monomer A DFT")
# Compute Monomer B wavefunction
core.timer_on("SAPT(DFT): Monomer B DFT")
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
if mon_b_shift:
core.set_global_option("DFT_GRAC_SHIFT", mon_b_shift)
core.set_global_option("SAVE_JK", True)
core.IO.set_default_namespace('monomerB')
wfn_B = scf_helper(sapt_dft_functional,
post_scf=False,
molecule=monomerB,
banner="SAPT(DFT): DFT Monomer B",
**kwargs)
data["DFT MONOMERB"] = core.variable("CURRENT ENERGY")
# Save JK object
sapt_jk = wfn_B.jk()
wfn_A.set_jk(sapt_jk)
core.set_global_option("SAVE_JK", False)
core.set_global_option("DFT_GRAC_SHIFT", 0.0)
core.timer_off("SAPT(DFT): Monomer B DFT")
# Write out header
scf_alg = core.get_global_option("SCF_TYPE")
sapt_dft_header(sapt_dft_functional, mon_a_shift, mon_b_shift,
bool(do_delta_hf), scf_alg)
# Call SAPT(DFT)
sapt_jk = wfn_B.jk()
sapt_dft(dimer_wfn,
wfn_A,
wfn_B,
sapt_jk=sapt_jk,
data=data,
print_header=False)
# Copy data back into globals
for k, v in data.items():
core.set_variable(k, v)
core.tstop()
return dimer_wfn
def run_sapt_dft(name, **kwargs):
optstash = p4util.OptionsState(['SCF', 'SCF_TYPE'], ['SCF', 'REFERENCE'],
['SCF', 'DFT_FUNCTIONAL'],
['SCF', 'DFT_GRAC_SHIFT'],
['SCF', 'SAVE_JK'])
core.tstart()
# Alter default algorithm
if not core.has_option_changed('SCF', 'SCF_TYPE'):
core.set_local_option('SCF', 'SCF_TYPE', 'DF')
core.prepare_options_for_module("SAPT")
# Get the molecule of interest
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
sapt_dimer = kwargs.pop('molecule', core.get_active_molecule())
else:
core.print_out(
'Warning! SAPT argument "ref_wfn" is only able to use molecule information.'
)
sapt_dimer = ref_wfn.molecule()
# Shifting to C1 so we need to copy the active molecule
if sapt_dimer.schoenflies_symbol() != 'c1':
core.print_out(
' SAPT does not make use of molecular symmetry, further calculations in C1 point group.\n'
)
# Make sure the geometry doesnt shift or rotate
sapt_dimer = sapt_dimer.clone()
sapt_dimer.reset_point_group('c1')
sapt_dimer.fix_orientation(True)
sapt_dimer.fix_com(True)
sapt_dimer.update_geometry()
# Grab overall settings
mon_a_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_A")
mon_b_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_B")
do_delta_hf = core.get_option("SAPT", "SAPT_DFT_DO_DHF")
sapt_dft_functional = core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL")
# Print out the title and some information
core.print_out("\n")
core.print_out(
" ---------------------------------------------------------\n")
core.print_out(" " + "SAPT(DFT) Procedure".center(58) + "\n")
core.print_out("\n")
core.print_out(" " + "by Daniel G. A. Smith".center(58) + "\n")
core.print_out(
" ---------------------------------------------------------\n")
core.print_out("\n")
core.print_out(" ==> Algorithm <==\n\n")
core.print_out(" SAPT DFT Functional %12s\n" %
str(sapt_dft_functional))
core.print_out(" Monomer A GRAC Shift %12.6f\n" % mon_a_shift)
core.print_out(" Monomer B GRAC Shift %12.6f\n" % mon_b_shift)
core.print_out(" Delta HF %12s\n" %
("True" if do_delta_hf else "False"))
core.print_out(" JK Algorithm %12s\n" %
core.get_option("SCF", "SCF_TYPE"))
core.print_out("\n")
core.print_out(" Required computations:\n")
if (do_delta_hf):
core.print_out(" HF (Dimer)\n")
core.print_out(" HF (Monomer A)\n")
core.print_out(" HF (Monomer B)\n")
core.print_out(" DFT (Monomer A)\n")
core.print_out(" DFT (Monomer B)\n")
core.print_out("\n")
if (mon_a_shift == 0.0) or (mon_b_shift == 0.0):
raise ValidationError(
'SAPT(DFT): must set both "SAPT_DFT_GRAC_SHIFT_A" and "B".')
if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
raise ValidationError(
'SAPT(DFT) currently only supports restricted references.')
nfrag = sapt_dimer.nfragments()
if nfrag != 2:
raise ValidationError(
'SAPT requires active molecule to have 2 fragments, not %s.' %
(nfrag))
monomerA = sapt_dimer.extract_subsets(1, 2)
monomerA.set_name('monomerA')
monomerB = sapt_dimer.extract_subsets(2, 1)
monomerB.set_name('monomerB')
core.IO.set_default_namespace('dimer')
data = {}
core.set_global_option("SAVE_JK", True)
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
# core.set_global_option('DF_INTS_IO', 'LOAD')
core.set_global_option('DF_INTS_IO', 'SAVE')
# # Compute dimer wavefunction
hf_cache = {}
hf_wfn_dimer = None
if do_delta_hf:
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.set_global_option('DF_INTS_IO', 'SAVE')
hf_data = {}
hf_wfn_dimer = scf_helper("SCF",
molecule=sapt_dimer,
banner="SAPT(DFT): delta HF Dimer",
**kwargs)
hf_data["HF DIMER"] = core.get_variable("CURRENT ENERGY")
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'dimer', 'monomerA')
hf_wfn_A = scf_helper("SCF",
molecule=monomerA,
banner="SAPT(DFT): delta HF Monomer A",
**kwargs)
hf_data["HF MONOMER A"] = core.get_variable("CURRENT ENERGY")
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
hf_wfn_B = scf_helper("SCF",
molecule=monomerB,
banner="SAPT(DFT): delta HF Monomer B",
**kwargs)
hf_data["HF MONOMER B"] = core.get_variable("CURRENT ENERGY")
# Move it back to monomer A
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerB', 'dimer')
core.print_out("\n")
core.print_out(
" ---------------------------------------------------------\n"
)
core.print_out(" " +
"SAPT(DFT): delta HF Segement".center(58) + "\n")
core.print_out("\n")
core.print_out(" " +
"by Daniel G. A. Smith and Rob Parrish".center(58) +
"\n")
core.print_out(
" ---------------------------------------------------------\n"
)
core.print_out("\n")
# Build cache and JK
sapt_jk = hf_wfn_B.jk()
hf_cache = sapt_jk_terms.build_sapt_jk_cache(hf_wfn_A, hf_wfn_B,
sapt_jk, True)
# Electostatics
elst = sapt_jk_terms.electrostatics(hf_cache, True)
hf_data.update(elst)
# Exchange
exch = sapt_jk_terms.exchange(hf_cache, sapt_jk, True)
hf_data.update(exch)
# Induction
ind = sapt_jk_terms.induction(
hf_cache,
sapt_jk,
True,
maxiter=core.get_option("SAPT", "MAXITER"),
conv=core.get_option("SAPT", "D_CONVERGENCE"))
hf_data.update(ind)
dhf_value = hf_data["HF DIMER"] - hf_data["HF MONOMER A"] - hf_data[
"HF MONOMER B"]
core.print_out("\n")
core.print_out(
print_sapt_hf_summary(hf_data, "SAPT(HF)", delta_hf=dhf_value))
data["Delta HF Correction"] = core.get_variable("SAPT(DFT) Delta HF")
if hf_wfn_dimer is None:
dimer_wfn = core.Wavefunction.build(sapt_dimer,
core.get_global_option("BASIS"))
else:
dimer_wfn = hf_wfn_dimer
# Set the primary functional
core.set_global_option("DFT_FUNCTIONAL",
core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL"))
core.set_local_option('SCF', 'REFERENCE', 'RKS')
# Compute Monomer A wavefunction
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'dimer', 'monomerA')
if mon_a_shift:
core.set_global_option("DFT_GRAC_SHIFT", mon_a_shift)
# Save the JK object
core.IO.set_default_namespace('monomerA')
wfn_A = scf_helper("SCF",
molecule=monomerA,
banner="SAPT(DFT): DFT Monomer A",
**kwargs)
data["DFT MONOMERA"] = core.get_variable("CURRENT ENERGY")
core.set_global_option("DFT_GRAC_SHIFT", 0.0)
# Compute Monomer B wavefunction
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
if mon_b_shift:
core.set_global_option("DFT_GRAC_SHIFT", mon_b_shift)
core.IO.set_default_namespace('monomerB')
wfn_B = scf_helper("SCF",
molecule=monomerB,
banner="SAPT(DFT): DFT Monomer B",
**kwargs)
data["DFT MONOMERB"] = core.get_variable("CURRENT ENERGY")
core.set_global_option("DFT_GRAC_SHIFT", 0.0)
# Print out the title and some information
core.print_out("\n")
core.print_out(
" ---------------------------------------------------------\n")
core.print_out(" " +
"SAPT(DFT): Intermolecular Interaction Segment".center(58) +
"\n")
core.print_out("\n")
core.print_out(" " +
"by Daniel G. A. Smith and Rob Parrish".center(58) + "\n")
core.print_out(
" ---------------------------------------------------------\n")
core.print_out("\n")
core.print_out(" ==> Algorithm <==\n\n")
core.print_out(" SAPT DFT Functional %12s\n" %
str(sapt_dft_functional))
core.print_out(" Monomer A GRAC Shift %12.6f\n" % mon_a_shift)
core.print_out(" Monomer B GRAC Shift %12.6f\n" % mon_b_shift)
core.print_out(" Delta HF %12s\n" %
("True" if do_delta_hf else "False"))
core.print_out(" JK Algorithm %12s\n" %
core.get_option("SCF", "SCF_TYPE"))
# Build cache and JK
sapt_jk = wfn_B.jk()
cache = sapt_jk_terms.build_sapt_jk_cache(wfn_A, wfn_B, sapt_jk, True)
# Electostatics
elst = sapt_jk_terms.electrostatics(cache, True)
data.update(elst)
# Exchange
exch = sapt_jk_terms.exchange(cache, sapt_jk, True)
data.update(exch)
# Induction
ind = sapt_jk_terms.induction(cache,
sapt_jk,
True,
maxiter=core.get_option("SAPT", "MAXITER"),
conv=core.get_option("SAPT",
"D_CONVERGENCE"))
data.update(ind)
# Dispersion
primary_basis = wfn_A.basisset()
core.print_out("\n")
aux_basis = core.BasisSet.build(sapt_dimer, "DF_BASIS_MP2",
core.get_option("DFMP2", "DF_BASIS_MP2"),
"RIFIT", core.get_global_option('BASIS'))
fdds_disp = sapt_mp2_terms.df_fdds_dispersion(primary_basis, aux_basis,
cache)
data.update(fdds_disp)
if core.get_option("SAPT", "SAPT_DFT_MP2_DISP_ALG") == "FISAPT":
mp2_disp = sapt_mp2_terms.df_mp2_fisapt_dispersion(wfn_A,
primary_basis,
aux_basis,
cache,
do_print=True)
else:
mp2_disp = sapt_mp2_terms.df_mp2_sapt_dispersion(dimer_wfn,
wfn_A,
wfn_B,
primary_basis,
aux_basis,
cache,
do_print=True)
data.update(mp2_disp)
# Print out final data
core.print_out("\n")
core.print_out(print_sapt_dft_summary(data, "SAPT(DFT)"))
core.tstop()
return dimer_wfn
def run_sapt_dft(name, **kwargs):
optstash = p4util.OptionsState(['SCF_TYPE'], ['SCF', 'REFERENCE'], ['SCF', 'DFT_GRAC_SHIFT'],
['SCF', 'SAVE_JK'])
core.tstart()
# Alter default algorithm
if not core.has_global_option_changed('SCF_TYPE'):
core.set_global_option('SCF_TYPE', 'DF')
core.prepare_options_for_module("SAPT")
# Get the molecule of interest
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
sapt_dimer = kwargs.pop('molecule', core.get_active_molecule())
else:
core.print_out('Warning! SAPT argument "ref_wfn" is only able to use molecule information.')
sapt_dimer = ref_wfn.molecule()
sapt_dimer, monomerA, monomerB = proc_util.prepare_sapt_molecule(sapt_dimer, "dimer")
# Grab overall settings
mon_a_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_A")
mon_b_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_B")
do_delta_hf = core.get_option("SAPT", "SAPT_DFT_DO_DHF")
sapt_dft_functional = core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL")
# Print out the title and some information
core.print_out("\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out(" " + "SAPT(DFT) Procedure".center(58) + "\n")
core.print_out("\n")
core.print_out(" " + "by Daniel G. A. Smith".center(58) + "\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out("\n")
core.print_out(" !!! WARNING: SAPT(DFT) capability is in beta. Please use with caution. !!!\n\n")
core.print_out(" ==> Algorithm <==\n\n")
core.print_out(" SAPT DFT Functional %12s\n" % str(sapt_dft_functional))
core.print_out(" Monomer A GRAC Shift %12.6f\n" % mon_a_shift)
core.print_out(" Monomer B GRAC Shift %12.6f\n" % mon_b_shift)
core.print_out(" Delta HF %12s\n" % ("True" if do_delta_hf else "False"))
core.print_out(" JK Algorithm %12s\n" % core.get_global_option("SCF_TYPE"))
core.print_out("\n")
core.print_out(" Required computations:\n")
if (do_delta_hf):
core.print_out(" HF (Dimer)\n")
core.print_out(" HF (Monomer A)\n")
core.print_out(" HF (Monomer B)\n")
core.print_out(" DFT (Monomer A)\n")
core.print_out(" DFT (Monomer B)\n")
core.print_out("\n")
if (sapt_dft_functional != "HF") and ((mon_a_shift == 0.0) or (mon_b_shift == 0.0)):
raise ValidationError('SAPT(DFT): must set both "SAPT_DFT_GRAC_SHIFT_A" and "B".')
if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
raise ValidationError('SAPT(DFT) currently only supports restricted references.')
core.IO.set_default_namespace('dimer')
data = {}
if (core.get_global_option('SCF_TYPE') == 'DF'):
# core.set_global_option('DF_INTS_IO', 'LOAD')
core.set_global_option('DF_INTS_IO', 'SAVE')
# # Compute dimer wavefunction
hf_wfn_dimer = None
if do_delta_hf:
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.set_global_option('DF_INTS_IO', 'SAVE')
hf_data = {}
hf_wfn_dimer = scf_helper("SCF", molecule=sapt_dimer, banner="SAPT(DFT): delta HF Dimer", **kwargs)
hf_data["HF DIMER"] = core.get_variable("CURRENT ENERGY")
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'dimer', 'monomerA')
hf_wfn_A = scf_helper("SCF", molecule=monomerA, banner="SAPT(DFT): delta HF Monomer A", **kwargs)
hf_data["HF MONOMER A"] = core.get_variable("CURRENT ENERGY")
core.set_global_option("SAVE_JK", True)
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
hf_wfn_B = scf_helper("SCF", molecule=monomerB, banner="SAPT(DFT): delta HF Monomer B", **kwargs)
hf_data["HF MONOMER B"] = core.get_variable("CURRENT ENERGY")
core.set_global_option("SAVE_JK", False)
# Grab JK object and set to A (so we do not save many JK objects)
sapt_jk = hf_wfn_B.jk()
hf_wfn_A.set_jk(sapt_jk)
core.set_global_option("SAVE_JK", False)
# Move it back to monomer A
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerB', 'dimer')
core.print_out("\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out(" " + "SAPT(DFT): delta HF Segement".center(58) + "\n")
core.print_out("\n")
core.print_out(" " + "by Daniel G. A. Smith and Rob Parrish".center(58) + "\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out("\n")
# Build cache
hf_cache = sapt_jk_terms.build_sapt_jk_cache(hf_wfn_A, hf_wfn_B, sapt_jk, True)
# Electostatics
elst = sapt_jk_terms.electrostatics(hf_cache, True)
hf_data.update(elst)
# Exchange
exch = sapt_jk_terms.exchange(hf_cache, sapt_jk, True)
hf_data.update(exch)
# Induction
ind = sapt_jk_terms.induction(
hf_cache,
sapt_jk,
True,
maxiter=core.get_option("SAPT", "MAXITER"),
conv=core.get_option("SAPT", "D_CONVERGENCE"),
Sinf=core.get_option("SAPT", "DO_IND_EXCH_SINF"))
hf_data.update(ind)
dhf_value = hf_data["HF DIMER"] - hf_data["HF MONOMER A"] - hf_data["HF MONOMER B"]
core.print_out("\n")
core.print_out(print_sapt_hf_summary(hf_data, "SAPT(HF)", delta_hf=dhf_value))
data["Delta HF Correction"] = core.get_variable("SAPT(DFT) Delta HF")
sapt_jk.finalize()
del hf_wfn_A, hf_wfn_B, sapt_jk
if hf_wfn_dimer is None:
dimer_wfn = core.Wavefunction.build(sapt_dimer, core.get_global_option("BASIS"))
else:
dimer_wfn = hf_wfn_dimer
# Set the primary functional
core.set_local_option('SCF', 'REFERENCE', 'RKS')
# Compute Monomer A wavefunction
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'dimer', 'monomerA')
if mon_a_shift:
core.set_global_option("DFT_GRAC_SHIFT", mon_a_shift)
# Save the JK object
core.IO.set_default_namespace('monomerA')
wfn_A = scf_helper(
sapt_dft_functional, post_scf=False, molecule=monomerA, banner="SAPT(DFT): DFT Monomer A", **kwargs)
data["DFT MONOMERA"] = core.get_variable("CURRENT ENERGY")
core.set_global_option("DFT_GRAC_SHIFT", 0.0)
# Compute Monomer B wavefunction
if (core.get_global_option('SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
if mon_b_shift:
core.set_global_option("DFT_GRAC_SHIFT", mon_b_shift)
core.set_global_option("SAVE_JK", True)
core.IO.set_default_namespace('monomerB')
wfn_B = scf_helper(
sapt_dft_functional, post_scf=False, molecule=monomerB, banner="SAPT(DFT): DFT Monomer B", **kwargs)
data["DFT MONOMERB"] = core.get_variable("CURRENT ENERGY")
# Save JK object
sapt_jk = wfn_B.jk()
wfn_A.set_jk(sapt_jk)
core.set_global_option("SAVE_JK", False)
core.set_global_option("DFT_GRAC_SHIFT", 0.0)
# Write out header
scf_alg = core.get_global_option("SCF_TYPE")
sapt_dft_header(sapt_dft_functional, mon_a_shift, mon_b_shift, bool(do_delta_hf), scf_alg)
# Call SAPT(DFT)
sapt_jk = wfn_B.jk()
sapt_dft(dimer_wfn, wfn_A, wfn_B, sapt_jk=sapt_jk, data=data, print_header=False)
# Copy data back into globals
for k, v in data.items():
core.set_variable(k, v)
core.tstop()
return dimer_wfn
def ip_fitting(name,
omega_l=0.05,
omega_r=2.5,
omega_convergence=1.0e-3,
maxiter=20,
**kwargs):
"""Optimize DFT omega parameter for molecular system.
Parameters
----------
name : string or function
DFT functional string name or function defining functional
whose omega is to be optimized.
omega_l : float, optional
Minimum omega to be considered during fitting.
omega_r : float, optional
Maximum omega to be considered during fitting.
molecule : :ref:`molecule <op_py_molecule>`, optional
Target molecule (neutral) for which omega is to be tuned, if not last defined.
omega_convergence : float, optional
Threshold below which to consider omega converged. (formerly omega_tolerance)
maxiter : int, optional
Maximum number of iterations towards omega convergence.
Returns
-------
float
Optimal omega parameter.
"""
optstash = p4util.OptionsState(['SCF', 'REFERENCE'], ['SCF', 'GUESS'],
['SCF', 'DF_INTS_IO'], ['SCF', 'DFT_OMEGA'],
['DOCC'], ['SOCC'])
kwargs = p4util.kwargs_lower(kwargs)
# By default, do not read previous 180 orbitals file
read = False
read180 = ''
if 'read' in kwargs:
read = True
read180 = kwargs['read']
if core.get_option('SCF', 'REFERENCE') != 'UKS':
core.print_out(
""" Requested procedure `ip_fitting` runs further calculations with UKS reference.\n"""
)
core.set_local_option('SCF', 'REFERENCE', 'UKS')
# Make sure the molecule the user provided is the active one, and neutral
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
if molecule.molecular_charge() != 0:
raise ValidationError(
"""IP Fitting requires neutral molecule to start.""")
if molecule.schoenflies_symbol() != 'c1':
core.print_out(
""" Requested procedure `ip_fitting` does not make use of molecular symmetry: """
"""further calculations in C1 point group.\n""")
molecule = molecule.clone()
molecule.reset_point_group('c1')
molecule.update_geometry()
charge0 = molecule.molecular_charge()
mult0 = molecule.multiplicity()
# How many electrons are there?
N = 0
for A in range(molecule.natom()):
N += molecule.Z(A)
N -= charge0
N = int(N)
Nb = int((N - mult0 + 1) / 2)
Na = int(N - Nb)
# Work in the ot namespace for this procedure
core.IO.set_default_namespace("ot")
# Burn in to determine orbital eigenvalues
if read:
core.set_local_option("SCF", "GUESS", "READ")
copy_file_to_scratch(read180, 'psi', 'ot', 180)
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
E, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
banner='IP Fitting SCF: Burn-in',
**kwargs)
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
if not wfn.functional().is_x_lrc():
raise ValidationError(
"""Not sensible to optimize omega for non-long-range-correction functional."""
)
# Determine H**O, to determine mult1
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Na == Nb:
H**O = -Nb
elif Nb == 0:
H**O = Na
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
if E_a >= E_b:
H**O = Na
else:
H**O = -Nb
Na1 = Na
Nb1 = Nb
if H**O > 0:
Na1 -= 1
else:
Nb1 -= 1
charge1 = charge0 + 1
mult1 = Na1 - Nb1 + 1
omegas = []
E0s = []
E1s = []
kIPs = []
IPs = []
types = []
# Right endpoint
core.set_local_option('SCF', 'DFT_OMEGA', omega_r)
# Neutral
if read:
core.set_local_option("SCF", "GUESS", "READ")
p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
E0r, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
banner='IP Fitting SCF: Neutral, Right Endpoint',
**kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
E_HOMOr = E_HOMO
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
if read:
core.set_local_option("SCF", "GUESS", "READ")
p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
E1r = driver.energy('scf',
dft_functional=name,
molecule=molecule,
banner='IP Fitting SCF: Cation, Right Endpoint',
**kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IPr = E1r - E0r
kIPr = -E_HOMOr
delta_r = IPr - kIPr
if IPr > kIPr:
raise ValidationError(
"""\n***IP Fitting Error: Right Omega limit should have kIP > IP: {} !> {}"""
.format(kIPr, IPr))
omegas.append(omega_r)
types.append('Right Limit')
E0s.append(E0r)
E1s.append(E1r)
IPs.append(IPr)
kIPs.append(kIPr)
# Use previous orbitals from here out
core.set_local_option("SCF", "GUESS", "READ")
# Left endpoint
core.set_local_option('SCF', 'DFT_OMEGA', omega_l)
# Neutral
core.IO.change_file_namespace(180, "neutral", "ot")
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
core.set_global_option("DOCC", [Nb])
core.set_global_option("SOCC", [Na - Nb])
E0l, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
banner='IP Fitting SCF: Neutral, Left Endpoint',
**kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
E_HOMOl = E_HOMO
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
core.IO.change_file_namespace(180, "cation", "ot")
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
core.set_global_option("DOCC", [Nb1])
core.set_global_option("SOCC", [Na1 - Nb1])
E1l = driver.energy('scf',
dft_functional=name,
molecule=molecule,
banner='IP Fitting SCF: Cation, Left Endpoint',
**kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IPl = E1l - E0l
kIPl = -E_HOMOl
delta_l = IPl - kIPl
if IPl < kIPl:
raise ValidationError(
"""\n***IP Fitting Error: Left Omega limit should have kIP < IP: {} !< {}"""
.format(kIPl, IPl))
omegas.append(omega_l)
types.append('Left Limit')
E0s.append(E0l)
E1s.append(E1l)
IPs.append(IPl)
kIPs.append(kIPl)
converged = False
repeat_l = 0
repeat_r = 0
for step in range(maxiter):
# Regula Falsi (modified)
if repeat_l > 1:
delta_l /= 2.0
if repeat_r > 1:
delta_r /= 2.0
omega = -(omega_r - omega_l) / (delta_r - delta_l) * delta_l + omega_l
core.set_local_option('SCF', 'DFT_OMEGA', omega)
# Neutral
core.IO.change_file_namespace(180, "neutral", "ot")
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
core.set_global_option("DOCC", [Nb])
core.set_global_option("SOCC", [Na - Nb])
E0, wfn = driver.energy(
'scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
banner='IP Fitting SCF: Neutral, Omega = {:11.3E}'.format(omega),
**kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
core.IO.change_file_namespace(180, "cation", "ot")
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
core.set_global_option("DOCC", [Nb1])
core.set_global_option("SOCC", [Na1 - Nb1])
E1 = driver.energy(
'scf',
dft_functional=name,
molecule=molecule,
banner='IP Fitting SCF: Cation, Omega = {:11.3E}'.format(omega),
**kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IP = E1 - E0
kIP = -E_HOMO
delta = IP - kIP
if kIP > IP:
omega_r = omega
E0r = E0
E1r = E1
IPr = IP
kIPr = kIP
delta_r = delta
repeat_r = 0
repeat_l += 1
else:
omega_l = omega
E0l = E0
E1l = E1
IPl = IP
kIPl = kIP
delta_l = delta
repeat_l = 0
repeat_r += 1
omegas.append(omega)
types.append('Regula-Falsi')
E0s.append(E0)
E1s.append(E1)
IPs.append(IP)
kIPs.append(kIP)
# Termination
if abs(omega_l - omega_r) < omega_convergence:
converged = True
break
core.IO.set_default_namespace("")
core.print_out("""\n ==> IP Fitting Results <==\n\n""")
core.print_out(""" => Occupation Determination <= \n\n""")
core.print_out(""" %6s %6s %6s %6s %6s %6s\n""" %
('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
core.print_out(""" Neutral: %6d %6d %6d %6d %6d %6d\n""" %
(N, Na, Nb, charge0, mult0, H**O))
core.print_out(""" Cation: %6d %6d %6d %6d %6d\n\n""" %
(N - 1, Na1, Nb1, charge1, mult1))
core.print_out(""" => Regula Falsi Iterations <=\n\n""")
core.print_out(""" %3s %11s %14s %14s %14s %s\n""" %
('N', 'Omega', 'IP', 'kIP', 'Delta', 'Type'))
for k in range(len(omegas)):
core.print_out(
""" %3d %11.3E %14.6E %14.6E %14.6E %s\n""" %
(k + 1, omegas[k], IPs[k], kIPs[k], IPs[k] - kIPs[k], types[k]))
optstash.restore()
if converged:
core.print_out("""\n IP Fitting Converged\n""")
core.print_out(""" Final omega = %14.6E\n""" %
((omega_l + omega_r) / 2))
core.print_out(
"""\n "M,I. does the dying. Fleet just does the flying."\n""")
core.print_out(""" -Starship Troopers\n""")
else:
raise ConvergenceError("""IP Fitting """, step + 1)
return ((omega_l + omega_r) / 2)
def frac_traverse(name, **kwargs):
"""Scan electron occupancy from +1 electron to -1.
Parameters
----------
name : string or function
DFT functional string name or function defining functional
whose omega is to be optimized.
molecule : :ref:`molecule <op_py_molecule>`, optional
Target molecule (neutral) for which omega is to be tuned, if not last defined.
cation_mult : int, optional
Multiplicity of cation, if not neutral multiplicity + 1.
anion_mult : int, optional
Multiplicity of anion, if not neutral multiplicity + 1.
frac_start : int, optional
Iteration at which to start frac procedure when not reading previous
guess. Defaults to 25.
HOMO_occs : list, optional
Occupations to step through for cation, by default `[1 - 0.1 * x for x in range(11)]`.
LUMO_occs : list, optional
Occupations to step through for anion, by default `[1 - 0.1 * x for x in range(11)]`.
H**O : int, optional
Index of H**O.
LUMO : int, optional
Index of LUMO.
frac_diis : bool, optional
Do use DIIS for non-1.0-occupied points?
neutral_guess : bool, optional
Do use neutral orbitals as guess for the anion?
hf_guess: bool, optional
Do use UHF guess before UKS?
continuous_guess : bool, optional
Do carry along guess rather than reguessing at each occupation?
filename : str, optional
Result filename, if not name of molecule.
Returns
-------
dict
Dictionary associating SCF energies with occupations.
"""
optstash = p4util.OptionsState(
['SCF', 'GUESS'],
['SCF', 'DF_INTS_IO'],
['SCF', 'REFERENCE'],
["SCF", "FRAC_START"],
["SCF", "FRAC_RENORMALIZE"],
#["SCF", "FRAC_LOAD"],
["SCF", "FRAC_OCC"],
["SCF", "FRAC_VAL"],
["SCF", "FRAC_DIIS"])
kwargs = p4util.kwargs_lower(kwargs)
# Make sure the molecule the user provided is the active one, and neutral
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
if molecule.molecular_charge() != 0:
raise ValidationError(
"""frac_traverse requires neutral molecule to start.""")
if molecule.schoenflies_symbol() != 'c1':
core.print_out(
""" Requested procedure `frac_traverse` does not make use of molecular symmetry: """
"""further calculations in C1 point group.\n""")
molecule = molecule.clone()
molecule.reset_point_group('c1')
molecule.update_geometry()
charge0 = molecule.molecular_charge()
mult0 = molecule.multiplicity()
chargep = charge0 + 1
chargem = charge0 - 1
multp = kwargs.get('cation_mult', mult0 + 1)
multm = kwargs.get('anion_mult', mult0 + 1)
# By default, we start the frac procedure on the 25th iteration
# when not reading a previous guess
frac_start = kwargs.get('frac_start', 25)
# By default, we occupy by tenths of electrons
HOMO_occs = kwargs.get(
'HOMO_occs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])
LUMO_occs = kwargs.get(
'LUMO_occs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])
# By default, H**O and LUMO are both in alpha
Z = 0
for A in range(molecule.natom()):
Z += molecule.Z(A)
Z -= charge0
H**O = kwargs.get('H**O', (Z / 2 + 1 if (Z % 2) else Z / 2))
LUMO = kwargs.get('LUMO', H**O + 1)
# By default, DIIS in FRAC (1.0 occupation is always DIIS'd)
frac_diis = kwargs.get('frac_diis', True)
# By default, use the neutral orbitals as a guess for the anion
neutral_guess = kwargs.get('neutral_guess', True)
# By default, burn-in with UHF first, if UKS
hf_guess = False
if core.get_local_option('SCF', 'REFERENCE') == 'UKS':
hf_guess = kwargs.get('hf_guess', True)
# By default, re-guess at each N
continuous_guess = kwargs.get('continuous_guess', False)
# By default, drop the files to the molecule's name
root = kwargs.get('filename', molecule.name())
traverse_filename = root + '.traverse.dat'
# => Traverse <= #
occs = []
energies = []
potentials = []
convs = []
# => Run the neutral for its orbitals, if requested <= #
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
old_guess = core.get_local_option("SCF", "GUESS")
if (neutral_guess):
if (hf_guess):
core.set_local_option("SCF", "REFERENCE", "UHF")
driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
core.set_local_option("SCF", "GUESS", "READ")
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
# => Run the anion first <= #
molecule.set_molecular_charge(chargem)
molecule.set_multiplicity(multm)
# => Burn the anion in with hf, if requested <= #
if hf_guess:
core.set_local_option("SCF", "REFERENCE", "UHF")
driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
core.set_local_option("SCF", "REFERENCE", "UKS")
core.set_local_option("SCF", "GUESS", "READ")
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
core.set_local_option("SCF", "FRAC_START", frac_start)
core.set_local_option("SCF", "FRAC_RENORMALIZE", True)
# NYI core.set_local_option("SCF", "FRAC_LOAD", False)
for occ in LUMO_occs:
core.set_local_option("SCF", "FRAC_OCC", [LUMO])
core.set_local_option("SCF", "FRAC_VAL", [occ])
E, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
**kwargs)
C = 1
if E == 0.0:
E = core.variable('SCF ITERATION ENERGY')
C = 0
if LUMO > 0:
eps = wfn.epsilon_a()
potentials.append(eps.get(int(LUMO) - 1))
else:
eps = wfn.epsilon_b()
potentials.append(eps.get(-int(LUMO) - 1))
occs.append(occ)
energies.append(E)
convs.append(C)
core.set_local_option("SCF", "FRAC_START", 2)
#core.set_local_option("SCF", "FRAC_LOAD", True)
core.set_local_option("SCF", "GUESS", "READ")
core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
# => Run the neutral next <= #
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
# Burn the neutral in with hf, if requested <= #
if not continuous_guess:
core.set_local_option("SCF", "GUESS", old_guess)
if hf_guess:
core.set_local_option("SCF", "FRAC_START", 0)
core.set_local_option("SCF", "REFERENCE", "UHF")
driver.energy('scf',
dft_functional=name,
molecule=molecule,
**kwargs)
core.set_local_option("SCF", "REFERENCE", "UKS")
core.set_local_option("SCF", "GUESS", "READ")
# NYI core.set_local_option("SCF", "FRAC_LOAD", False)
core.set_local_option("SCF", "FRAC_START", frac_start)
core.set_local_option("SCF", "FRAC_RENORMALIZE", True)
for occ in HOMO_occs:
core.set_local_option("SCF", "FRAC_OCC", [H**O])
core.set_local_option("SCF", "FRAC_VAL", [occ])
E, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
**kwargs)
C = 1
if E == 0.0:
E = core.variable('SCF ITERATION ENERGY')
C = 0
if LUMO > 0:
eps = wfn.epsilon_a()
potentials.append(eps.get(int(H**O) - 1))
else:
eps = wfn.epsilon_b()
potentials.append(eps.get(-int(H**O) - 1))
occs.append(occ - 1.0)
energies.append(E)
convs.append(C)
core.set_local_option("SCF", "FRAC_START", 2)
# NYI core.set_local_option("SCF", "FRAC_LOAD", True)
core.set_local_option("SCF", "GUESS", "READ")
core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
# => Print the results out <= #
E = {}
core.print_out(
"""\n ==> Fractional Occupation Traverse Results <==\n\n""")
core.print_out(""" %-11s %-24s %-24s %11s\n""" %
('N', 'Energy', 'H**O Energy', 'Converged'))
for k in range(len(occs)):
core.print_out(""" %11.3E %24.16E %24.16E %11d\n""" %
(occs[k], energies[k], potentials[k], convs[k]))
E[occs[k]] = energies[k]
core.print_out("""
You trying to be a hero Watkins?
Just trying to kill some bugs sir!
-Starship Troopers""")
# Drop the files out
with open(traverse_filename, 'w') as fh:
fh.write(""" %-11s %-24s %-24s %11s\n""" %
('N', 'Energy', 'H**O Energy', 'Converged'))
for k in range(len(occs)):
fh.write(""" %11.3E %24.16E %24.16E %11d\n""" %
(occs[k], energies[k], potentials[k], convs[k]))
optstash.restore()
return E
def frac_nuke(name, **kwargs):
"""Pull all the electrons out, one at a time"""
optstash = p4util.OptionsState(
['SCF', 'GUESS'],
['SCF', 'DF_INTS_IO'],
["SCF", "FRAC_START"],
["SCF", "FRAC_RENORMALIZE"],
# NYI ["SCF", "FRAC_LOAD"],
["SCF", "FRAC_OCC"],
["SCF", "FRAC_VAL"],
["SCF", "FRAC_DIIS"])
kwargs = p4util.kwargs_lower(kwargs)
# Make sure the molecule the user provided is the active one, and neutral
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
if molecule.molecular_charge() != 0:
raise ValidationError(
"""frac_nuke requires neutral molecule to start.""")
if molecule.schoenflies_symbol() != 'c1':
core.print_out(
""" Requested procedure `frac_nuke` does not make use of molecular symmetry: """
"""further calculations in C1 point group.\n""")
molecule = molecule.clone()
molecule.reset_point_group('c1')
molecule.update_geometry()
charge0 = molecule.molecular_charge()
mult0 = molecule.multiplicity()
# By default, we start the frac procedure on the 25th iteration
# when not reading a previous guess
frac_start = kwargs.get('frac_start', 25)
# By default, we occupy by tenths of electrons
foccs = kwargs.get('foccs',
[1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])
# By default, H**O and LUMO are both in alpha
N = 0
for A in range(molecule.natom()):
N += molecule.Z(A)
N -= charge0
N = int(N)
Nb = int((N - mult0 + 1) / 2)
Na = int(N - Nb)
charge = charge0
mult = mult0
# By default, nuke all the electrons
Nmin = 0
if 'nmax' in kwargs:
Nmin = N - int(kwargs['nmax'])
# By default, DIIS in FRAC (1.0 occupation is always DIIS'd)
frac_diis = kwargs.get('frac_diis', True)
# By default, drop the files to the molecule's name
root = kwargs.get('filename', molecule.name())
traverse_filename = root + '.traverse.dat'
stats_filename = root + '.stats.dat'
# => Traverse <= #
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
Ns = []
energies = []
potentials = []
convs = []
stats = []
# Run one SCF to burn things in
E, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
**kwargs)
# Determine H**O
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
eps_a.print_out()
if Na == Nb:
H**O = -Nb
elif Nb == 0:
H**O = Na
else:
E_a = eps_a.get(int(Na - 1))
E_b = eps_b.get(int(Nb - 1))
if E_a >= E_b:
H**O = Na
else:
H**O = -Nb
stats.append(""" %6d %6d %6d %6d %6d %6d\n""" %
(N, Na, Nb, charge, mult, H**O))
if H**O > 0:
Na -= 1
else:
Nb -= 1
charge += 1
mult = Na - Nb + 1
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
core.set_local_option("SCF", "FRAC_START", frac_start)
core.set_local_option("SCF", "FRAC_RENORMALIZE", True)
# Nuke 'em Rico!
for Nintegral in range(N, Nmin, -1):
# Nuke the current H**O
for occ in foccs:
core.set_local_option("SCF", "FRAC_OCC", [H**O])
core.set_local_option("SCF", "FRAC_VAL", [occ])
E, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
**kwargs)
C = 1
if E == 0.0:
E = core.variable('SCF ITERATION ENERGY')
C = 0
if H**O > 0:
eps = wfn.epsilon_a()
potentials.append(eps.np[H**O - 1])
else:
eps = wfn.epsilon_b()
potentials.append(eps.np[-H**O - 1])
Ns.append(Nintegral + occ - 1.0)
energies.append(E)
convs.append(C)
core.set_local_option("SCF", "FRAC_START", 2)
# NYI core.set_local_option("SCF", "FRAC_LOAD", True)
core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
core.set_local_option("SCF", "GUESS", "READ")
# Set the next charge/mult
molecule.set_molecular_charge(charge)
molecule.set_multiplicity(mult)
# Determine H**O
print('DGAS: What ref should this point to?')
#ref = core.legacy_wavefunction()
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Na == Nb:
H**O = -Nb
elif Nb == 0:
H**O = Na
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
if E_a >= E_b:
H**O = Na
else:
H**O = -Nb
stats.append(""" %6d %6d %6d %6d %6d %6d\n""" %
(Nintegral - 1, Na, Nb, charge, mult, H**O))
if H**O > 0:
Na -= 1
else:
Nb -= 1
charge += 1
mult = Na - Nb + 1
core.set_local_option("SCF", "DF_INTS_IO", "NONE")
# => Print the results out <= #
E = {}
core.print_out("""\n ==> Fractional Occupation Nuke Results <==\n\n""")
core.print_out(""" %-11s %-24s %-24s %11s\n""" %
('N', 'Energy', 'H**O Energy', 'Converged'))
for k in range(len(Ns)):
core.print_out(""" %11.3E %24.16E %24.16E %11d\n""" %
(Ns[k], energies[k], potentials[k], convs[k]))
E[Ns[k]] = energies[k]
core.print_out('\n')
core.print_out(""" %6s %6s %6s %6s %6s %6s\n""" %
('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
for line in stats:
core.print_out(line)
core.print_out(
'\n "You shoot a nuke down a bug hole, you got a lot of dead bugs"\n'
)
core.print_out(' -Starship Troopers\n')
# Drop the files out
with open(traverse_filename, 'w') as fh:
fh.write(""" %-11s %-24s %-24s %11s\n""" %
('N', 'Energy', 'H**O Energy', 'Converged'))
for k in range(len(Ns)):
fh.write(""" %11.3E %24.16E %24.16E %11d\n""" %
(Ns[k], energies[k], potentials[k], convs[k]))
with open(stats_filename, 'w') as fh:
fh.write(""" %6s %6s %6s %6s %6s %6s\n""" %
('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
for line in stats:
fh.write(line)
optstash.restore()
return E
def write_zmat(name, dertype, molecule):
"""Returns string with contents of Cfour ZMAT file as gathered from
active molecule, current keyword settings, and cfour {...} block.
"""
# Handle memory
mem = int(0.000001 * core.get_memory())
if mem == 524:
memcmd, memkw = '', {}
else:
memcmd, memkw = qcdb.cfour.muster_memory(mem)
# Handle molecule and basis set
if molecule.name() == 'blank_molecule_psi4_yo':
molcmd, molkw = '', {}
bascmd, baskw = '', {}
core.set_local_option('CFOUR', 'TRANSLATE_PSI4', False)
else:
molecule.update_geometry()
#print(molecule.create_psi4_string_from_molecule())
qcdbmolecule = qcdb.Molecule(
molecule.create_psi4_string_from_molecule())
qcdbmolecule.tagline = molecule.name()
molcmd, molkw = qcdbmolecule.format_molecule_for_cfour()
if core.get_global_option('BASIS') in ["", "(AUTO)"]:
bascmd, baskw = '', {}
else:
user_pg = molecule.schoenflies_symbol()
molecule.reset_point_group(
'c1') # need basis printed for *every* atom
qbs = core.BasisSet.build(molecule, "BASIS",
core.get_global_option('BASIS'))
if qbs.has_ECP():
raise ValidationError("""ECPs not hooked up for Cfour""")
with open('GENBAS', 'w') as cfour_basfile:
cfour_basfile.write(qbs.genbas())
core.print_out(
' GENBAS loaded from Psi4 LibMints for basis %s\n' %
(core.get_global_option('BASIS')))
molecule.reset_point_group(user_pg)
molecule.update_geometry()
bascmd, baskw = qcdbmolecule.format_basis_for_cfour(
qbs.has_puream())
# Handle psi4 keywords implying cfour keyword values
if core.get_option('CFOUR', 'TRANSLATE_PSI4'):
psicmd, psikw = qcdb.cfour.muster_psi4options(
p4util.prepare_options_for_modules(changedOnly=True))
else:
psicmd, psikw = '', {}
# Handle calc type and quantum chemical method
mdccmd, mdckw = qcdb.cfour.muster_modelchem(name, dertype)
# Handle calc type and quantum chemical method
mdccmd, mdckw = qcdb.cfour.muster_modelchem(name, dertype)
# Handle driver vs input/default keyword reconciliation
userkw = p4util.prepare_options_for_modules()
userkw = qcdb.options.reconcile_options(userkw, memkw)
userkw = qcdb.options.reconcile_options(userkw, molkw)
userkw = qcdb.options.reconcile_options(userkw, baskw)
userkw = qcdb.options.reconcile_options(userkw, psikw)
userkw = qcdb.options.reconcile_options(userkw, mdckw)
# Handle conversion of psi4 keyword structure into cfour format
optcmd = qcdb.options.prepare_options_for_cfour(userkw)
# Handle text to be passed untouched to cfour
litcmd = core.get_global_option('LITERAL_CFOUR')
# Assemble ZMAT pieces
zmat = memcmd + molcmd + optcmd + mdccmd + psicmd + bascmd + litcmd
if len(re.findall(r'^\*(ACES2|CFOUR|CRAPS)\(', zmat, re.MULTILINE)) != 1:
core.print_out('\n Faulty ZMAT constructed:\n%s' % (zmat))
raise ValidationError("""
Multiple *CFOUR(...) blocks in input. This usually arises
because molecule or options are specified both the psi4 way through
molecule {...} and set ... and the cfour way through cfour {...}.""")
return zmat
def run_gaussian_2(name, **kwargs):
# throw an exception for open-shells
if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
raise ValidationError("""g2 computations require "reference rhf".""")
# stash user options:
optstash = p4util.OptionsState(['FNOCC', 'COMPUTE_TRIPLES'],
['FNOCC', 'COMPUTE_MP4_TRIPLES'], ['BASIS'],
['FREEZE_CORE'], ['MP2_TYPE'], ['SCF_TYPE'])
# override default scf_type
core.set_global_option('SCF_TYPE', 'PK')
# optimize geometry at scf level
core.clean()
core.set_global_option('BASIS', "6-31G(D)")
driver.optimize('scf')
core.clean()
# scf frequencies for zpe
# NOTE This line should not be needed, but without it there's a seg fault
scf_e, ref = driver.frequency('scf', return_wfn=True)
# thermodynamic properties
du = core.variable('THERMAL ENERGY CORRECTION')
dh = core.variable('ENTHALPY CORRECTION')
dg = core.variable('GIBBS FREE ENERGY CORRECTION')
freqs = ref.frequencies()
nfreq = freqs.dim(0)
freqsum = 0.0
for i in range(0, nfreq):
freqsum += freqs.get(i)
zpe = freqsum / constants.hartree2wavenumbers * 0.8929 * 0.5
core.clean()
# optimize geometry at mp2 (no frozen core) level
# note: freeze_core isn't an option in MP2
core.set_global_option('FREEZE_CORE', "FALSE")
core.set_global_option('MP2_TYPE', 'CONV')
driver.optimize('mp2')
core.clean()
# qcisd(t)
core.set_local_option('FNOCC', 'COMPUTE_MP4_TRIPLES', "TRUE")
core.set_global_option('FREEZE_CORE', "TRUE")
core.set_global_option('BASIS', "6-311G(D_P)")
ref = driver.proc.run_fnocc('qcisd(t)', return_wfn=True, **kwargs)
# HLC: high-level correction based on number of valence electrons
nirrep = ref.nirrep()
frzcpi = ref.frzcpi()
nfzc = 0
for i in range(0, nirrep):
nfzc += frzcpi[i]
nalpha = ref.nalpha() - nfzc
nbeta = ref.nbeta() - nfzc
# hlc of gaussian-2
hlc = -0.00481 * nalpha - 0.00019 * nbeta
# hlc of gaussian-1
hlc1 = -0.00614 * nalpha
eqci_6311gdp = core.variable("QCISD(T) TOTAL ENERGY")
emp4_6311gd = core.variable("MP4 TOTAL ENERGY")
emp2_6311gd = core.variable("MP2 TOTAL ENERGY")
core.clean()
# correction for diffuse functions
core.set_global_option('BASIS', "6-311+G(D_P)")
driver.energy('mp4')
emp4_6311pg_dp = core.variable("MP4 TOTAL ENERGY")
emp2_6311pg_dp = core.variable("MP2 TOTAL ENERGY")
core.clean()
# correction for polarization functions
core.set_global_option('BASIS', "6-311G(2DF_P)")
driver.energy('mp4')
emp4_6311g2dfp = core.variable("MP4 TOTAL ENERGY")
emp2_6311g2dfp = core.variable("MP2 TOTAL ENERGY")
core.clean()
# big basis mp2
core.set_global_option('BASIS', "6-311+G(3DF_2P)")
#run_fnocc('_mp2',**kwargs)
driver.energy('mp2')
emp2_big = core.variable("MP2 TOTAL ENERGY")
core.clean()
eqci = eqci_6311gdp
e_delta_g2 = emp2_big + emp2_6311gd - emp2_6311g2dfp - emp2_6311pg_dp
e_plus = emp4_6311pg_dp - emp4_6311gd
e_2df = emp4_6311g2dfp - emp4_6311gd
eg2 = eqci + e_delta_g2 + e_plus + e_2df
eg2_mp2_0k = eqci + (emp2_big - emp2_6311gd) + hlc + zpe
core.print_out('\n')
core.print_out(' ==> G1/G2 Energy Components <==\n')
core.print_out('\n')
core.print_out(' QCISD(T): %20.12lf\n' % eqci)
core.print_out(' E(Delta): %20.12lf\n' % e_delta_g2)
core.print_out(' E(2DF): %20.12lf\n' % e_2df)
core.print_out(' E(+): %20.12lf\n' % e_plus)
core.print_out(' E(G1 HLC): %20.12lf\n' % hlc1)
core.print_out(' E(G2 HLC): %20.12lf\n' % hlc)
core.print_out(' E(ZPE): %20.12lf\n' % zpe)
core.print_out('\n')
core.print_out(' ==> 0 Kelvin Results <==\n')
core.print_out('\n')
eg2_0k = eg2 + zpe + hlc
core.print_out(' G1: %20.12lf\n' %
(eqci + e_plus + e_2df + hlc1 + zpe))
core.print_out(' G2(MP2): %20.12lf\n' % eg2_mp2_0k)
core.print_out(' G2: %20.12lf\n' % eg2_0k)
core.set_variable("G1 TOTAL ENERGY", eqci + e_plus + e_2df + hlc1 + zpe)
core.set_variable("G2 TOTAL ENERGY", eg2_0k)
core.set_variable("G2(MP2) TOTAL ENERGY", eg2_mp2_0k)
core.print_out('\n')
T = core.get_global_option('T')
core.print_out(' ==> %3.0lf Kelvin Results <==\n' % T)
core.print_out('\n')
internal_energy = eg2_mp2_0k + du - zpe / 0.8929
enthalpy = eg2_mp2_0k + dh - zpe / 0.8929
gibbs = eg2_mp2_0k + dg - zpe / 0.8929
core.print_out(' G2(MP2) energy: %20.12lf\n' % internal_energy)
core.print_out(' G2(MP2) enthalpy: %20.12lf\n' % enthalpy)
core.print_out(' G2(MP2) free energy: %20.12lf\n' % gibbs)
core.print_out('\n')
core.set_variable("G2(MP2) INTERNAL ENERGY", internal_energy)
core.set_variable("G2(MP2) ENTHALPY", enthalpy)
core.set_variable("G2(MP2) FREE ENERGY", gibbs)
internal_energy = eg2_0k + du - zpe / 0.8929
enthalpy = eg2_0k + dh - zpe / 0.8929
gibbs = eg2_0k + dg - zpe / 0.8929
core.print_out(' G2 energy: %20.12lf\n' % internal_energy)
core.print_out(' G2 enthalpy: %20.12lf\n' % enthalpy)
core.print_out(' G2 free energy: %20.12lf\n' % gibbs)
core.set_variable("CURRENT ENERGY", eg2_0k)
core.set_variable("G2 INTERNAL ENERGY", internal_energy)
core.set_variable("G2 ENTHALPY", enthalpy)
core.set_variable("G2 FREE ENERGY", gibbs)
core.clean()
optstash.restore()
# return 0K g2 results
return eg2_0k
def frac_traverse(name, **kwargs):
"""Scan electron occupancy from +1 electron to -1.
Parameters
----------
name : string or function
DFT functional string name or function defining functional
whose omega is to be optimized.
molecule : :ref:`molecule <op_py_molecule>`, optional
Target molecule (neutral) for which omega is to be tuned, if not last defined.
cation_mult : int, optional
Multiplicity of cation, if not neutral multiplicity + 1.
anion_mult : int, optional
Multiplicity of anion, if not neutral multiplicity + 1.
frac_start : int, optional
Iteration at which to start frac procedure when not reading previous
guess. Defaults to 25.
HOMO_occs : list, optional
Occupations to step through for cation, by default `[1 - 0.1 * x for x in range(11)]`.
LUMO_occs : list, optional
Occupations to step through for anion, by default `[1 - 0.1 * x for x in range(11)]`.
H**O : int, optional
Index of H**O.
LUMO : int, optional
Index of LUMO.
frac_diis : bool, optional
Do use DIIS for non-1.0-occupied points?
neutral_guess : bool, optional
Do use neutral orbitals as guess for the anion?
hf_guess: bool, optional
Do use UHF guess before UKS?
continuous_guess : bool, optional
Do carry along guess rather than reguessing at each occupation?
filename : str, optional
Result filename, if not name of molecule.
Returns
-------
dict
Dictionary associating SCF energies with occupations.
"""
optstash = p4util.OptionsState(
['SCF', 'GUESS'],
['SCF', 'DF_INTS_IO'],
['SCF', 'REFERENCE'],
["SCF", "FRAC_START"],
["SCF", "FRAC_RENORMALIZE"],
#["SCF", "FRAC_LOAD"],
["SCF", "FRAC_OCC"],
["SCF", "FRAC_VAL"],
["SCF", "FRAC_DIIS"])
kwargs = p4util.kwargs_lower(kwargs)
# Make sure the molecule the user provided is the active one, and neutral
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
if molecule.molecular_charge() != 0:
raise ValidationError("""frac_traverse requires neutral molecule to start.""")
if molecule.schoenflies_symbol() != 'c1':
core.print_out(""" Requested procedure `frac_traverse` does not make use of molecular symmetry: """
"""further calculations in C1 point group.\n""")
molecule = molecule.clone()
molecule.reset_point_group('c1')
molecule.update_geometry()
charge0 = molecule.molecular_charge()
mult0 = molecule.multiplicity()
chargep = charge0 + 1
chargem = charge0 - 1
multp = kwargs.get('cation_mult', mult0 + 1)
multm = kwargs.get('anion_mult', mult0 + 1)
# By default, we start the frac procedure on the 25th iteration
# when not reading a previous guess
frac_start = kwargs.get('frac_start', 25)
# By default, we occupy by tenths of electrons
HOMO_occs = kwargs.get('HOMO_occs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])
LUMO_occs = kwargs.get('LUMO_occs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])
# By default, H**O and LUMO are both in alpha
Z = 0
for A in range(molecule.natom()):
Z += molecule.Z(A)
Z -= charge0
H**O = kwargs.get('H**O', (Z / 2 + 1 if (Z % 2) else Z / 2))
LUMO = kwargs.get('LUMO', H**O + 1)
# By default, DIIS in FRAC (1.0 occupation is always DIIS'd)
frac_diis = kwargs.get('frac_diis', True)
# By default, use the neutral orbitals as a guess for the anion
neutral_guess = kwargs.get('neutral_guess', True)
# By default, burn-in with UHF first, if UKS
hf_guess = False
if core.get_local_option('SCF', 'REFERENCE') == 'UKS':
hf_guess = kwargs.get('hf_guess', True)
# By default, re-guess at each N
continuous_guess = kwargs.get('continuous_guess', False)
# By default, drop the files to the molecule's name
root = kwargs.get('filename', molecule.name())
traverse_filename = root + '.traverse.dat'
# => Traverse <= #
occs = []
energies = []
potentials = []
convs = []
# => Run the neutral for its orbitals, if requested <= #
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
old_guess = core.get_local_option("SCF", "GUESS")
if (neutral_guess):
if (hf_guess):
core.set_local_option("SCF", "REFERENCE", "UHF")
driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
core.set_local_option("SCF", "GUESS", "READ")
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
# => Run the anion first <= #
molecule.set_molecular_charge(chargem)
molecule.set_multiplicity(multm)
# => Burn the anion in with hf, if requested <= #
if hf_guess:
core.set_local_option("SCF", "REFERENCE","UHF")
driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
core.set_local_option("SCF", "REFERENCE", "UKS")
core.set_local_option("SCF", "GUESS", "READ")
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
core.set_local_option("SCF", "FRAC_START", frac_start)
core.set_local_option("SCF", "FRAC_RENORMALIZE", True)
# NYI core.set_local_option("SCF", "FRAC_LOAD", False)
for occ in LUMO_occs:
core.set_local_option("SCF", "FRAC_OCC", [LUMO])
core.set_local_option("SCF", "FRAC_VAL", [occ])
E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule, **kwargs)
C = 1
if E == 0.0:
E = core.variable('SCF ITERATION ENERGY')
C = 0
if LUMO > 0:
eps = wfn.epsilon_a()
potentials.append(eps.get(int(LUMO) - 1))
else:
eps = wfn.epsilon_b()
potentials.append(eps.get(-int(LUMO) - 1))
occs.append(occ)
energies.append(E)
convs.append(C)
core.set_local_option("SCF", "FRAC_START", 2)
#core.set_local_option("SCF", "FRAC_LOAD", True)
core.set_local_option("SCF", "GUESS", "READ")
core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
# => Run the neutral next <= #
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
# Burn the neutral in with hf, if requested <= #
if not continuous_guess:
core.set_local_option("SCF", "GUESS", old_guess)
if hf_guess:
core.set_local_option("SCF", "FRAC_START", 0)
core.set_local_option("SCF", "REFERENCE", "UHF")
driver.energy('scf', dft_functional=name, molecule=molecule, **kwargs)
core.set_local_option("SCF", "REFERENCE", "UKS")
core.set_local_option("SCF", "GUESS", "READ")
# NYI core.set_local_option("SCF", "FRAC_LOAD", False)
core.set_local_option("SCF", "FRAC_START", frac_start)
core.set_local_option("SCF", "FRAC_RENORMALIZE", True)
for occ in HOMO_occs:
core.set_local_option("SCF", "FRAC_OCC", [H**O])
core.set_local_option("SCF", "FRAC_VAL", [occ])
E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule, **kwargs)
C = 1
if E == 0.0:
E = core.variable('SCF ITERATION ENERGY')
C = 0
if LUMO > 0:
eps = wfn.epsilon_a()
potentials.append(eps.get(int(H**O) - 1))
else:
eps = wfn.epsilon_b()
potentials.append(eps.get(-int(H**O) - 1))
occs.append(occ - 1.0)
energies.append(E)
convs.append(C)
core.set_local_option("SCF", "FRAC_START", 2)
# NYI core.set_local_option("SCF", "FRAC_LOAD", True)
core.set_local_option("SCF", "GUESS", "READ")
core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
# => Print the results out <= #
E = {}
core.print_out("""\n ==> Fractional Occupation Traverse Results <==\n\n""")
core.print_out(""" %-11s %-24s %-24s %11s\n""" % ('N', 'Energy', 'H**O Energy', 'Converged'))
for k in range(len(occs)):
core.print_out(""" %11.3E %24.16E %24.16E %11d\n""" % (occs[k], energies[k], potentials[k], convs[k]))
E[occs[k]] = energies[k]
core.print_out("""
You trying to be a hero Watkins?
Just trying to kill some bugs sir!
-Starship Troopers""")
# Drop the files out
with open(traverse_filename, 'w') as fh:
fh.write(""" %-11s %-24s %-24s %11s\n""" % ('N', 'Energy', 'H**O Energy', 'Converged'))
for k in range(len(occs)):
fh.write(""" %11.3E %24.16E %24.16E %11d\n""" % (occs[k], energies[k], potentials[k], convs[k]))
optstash.restore()
return E
def _set_convergence_criterion(ptype, method_name, scf_Ec, pscf_Ec, scf_Dc, pscf_Dc, gen_Ec, verbose=1):
r"""
This function will set local SCF and global energy convergence criterion
to the defaults listed at:
http://www.psicode.org/psi4manual/master/scf.html#convergence-and-
algorithm-defaults. SCF will be converged more tightly if a post-SCF
method is select (pscf_Ec, and pscf_Dc) else the looser (scf_Ec, and
scf_Dc convergence criterion will be used).
ptype - Procedure type (energy, gradient, etc). Nearly always test on
procedures['energy'] since that's guaranteed to exist for a method.
method_name - Name of the method
scf_Ec - E convergence criterion for scf target method
pscf_Ec - E convergence criterion for scf of post-scf target method
scf_Dc - D convergence criterion for scf target method
pscf_Dc - D convergence criterion for scf of post-scf target method
gen_Ec - E convergence criterion for post-scf target method
"""
optstash = p4util.OptionsState(
['SCF', 'E_CONVERGENCE'],
['SCF', 'D_CONVERGENCE'],
['E_CONVERGENCE'])
# Kind of want to move this out of here
_method_exists(ptype, method_name)
if verbose >= 2:
print(' Setting convergence', end=' ')
# Set method-dependent scf convergence criteria, check against energy routines
if not core.has_option_changed('SCF', 'E_CONVERGENCE'):
if procedures['energy'][method_name] == proc.run_scf:
core.set_local_option('SCF', 'E_CONVERGENCE', scf_Ec)
if verbose >= 2:
print(scf_Ec, end=' ')
else:
core.set_local_option('SCF', 'E_CONVERGENCE', pscf_Ec)
if verbose >= 2:
print(pscf_Ec, end=' ')
else:
if verbose >= 2:
print('CUSTOM', core.get_option('SCF', 'E_CONVERGENCE'), end=' ')
if not core.has_option_changed('SCF', 'D_CONVERGENCE'):
if procedures['energy'][method_name] == proc.run_scf:
core.set_local_option('SCF', 'D_CONVERGENCE', scf_Dc)
if verbose >= 2:
print(scf_Dc, end=' ')
else:
core.set_local_option('SCF', 'D_CONVERGENCE', pscf_Dc)
if verbose >= 2:
print(pscf_Dc, end=' ')
else:
if verbose >= 2:
print('CUSTOM', core.get_option('SCF', 'D_CONVERGENCE'), end=' ')
# Set post-scf convergence criteria (global will cover all correlated modules)
if not core.has_global_option_changed('E_CONVERGENCE'):
if procedures['energy'][method_name] != proc.run_scf:
core.set_global_option('E_CONVERGENCE', gen_Ec)
if verbose >= 2:
print(gen_Ec, end=' ')
else:
if procedures['energy'][method_name] != proc.run_scf:
if verbose >= 2:
print('CUSTOM', core.get_global_option('E_CONVERGENCE'), end=' ')
if verbose >= 2:
print('')
return optstash
def _set_convergence_criterion(ptype,
method_name,
scf_Ec,
pscf_Ec,
scf_Dc,
pscf_Dc,
gen_Ec,
verbose=1):
r"""
This function will set local SCF and global energy convergence criterion
to the defaults listed at:
http://www.psicode.org/psi4manual/master/scf.html#convergence-and-
algorithm-defaults. SCF will be converged more tightly if a post-SCF
method is select (pscf_Ec, and pscf_Dc) else the looser (scf_Ec, and
scf_Dc convergence criterion will be used).
ptype - Procedure type (energy, gradient, etc). Nearly always test on
procedures['energy'] since that's guaranteed to exist for a method.
method_name - Name of the method
scf_Ec - E convergence criterion for scf target method
pscf_Ec - E convergence criterion for scf of post-scf target method
scf_Dc - D convergence criterion for scf target method
pscf_Dc - D convergence criterion for scf of post-scf target method
gen_Ec - E convergence criterion for post-scf target method
"""
optstash = p4util.OptionsState(['SCF', 'E_CONVERGENCE'],
['SCF', 'D_CONVERGENCE'], ['E_CONVERGENCE'])
# Kind of want to move this out of here
_method_exists(ptype, method_name)
if verbose >= 2:
print(' Setting convergence', end=' ')
# Set method-dependent scf convergence criteria, check against energy routines
if not core.has_option_changed('SCF', 'E_CONVERGENCE'):
if procedures['energy'][method_name] == proc.run_scf:
core.set_local_option('SCF', 'E_CONVERGENCE', scf_Ec)
if verbose >= 2:
print(scf_Ec, end=' ')
else:
core.set_local_option('SCF', 'E_CONVERGENCE', pscf_Ec)
if verbose >= 2:
print(pscf_Ec, end=' ')
else:
if verbose >= 2:
print('CUSTOM', core.get_option('SCF', 'E_CONVERGENCE'), end=' ')
if not core.has_option_changed('SCF', 'D_CONVERGENCE'):
if procedures['energy'][method_name] == proc.run_scf:
core.set_local_option('SCF', 'D_CONVERGENCE', scf_Dc)
if verbose >= 2:
print(scf_Dc, end=' ')
else:
core.set_local_option('SCF', 'D_CONVERGENCE', pscf_Dc)
if verbose >= 2:
print(pscf_Dc, end=' ')
else:
if verbose >= 2:
print('CUSTOM', core.get_option('SCF', 'D_CONVERGENCE'), end=' ')
# Set post-scf convergence criteria (global will cover all correlated modules)
if not core.has_global_option_changed('E_CONVERGENCE'):
if procedures['energy'][method_name] != proc.run_scf:
core.set_global_option('E_CONVERGENCE', gen_Ec)
if verbose >= 2:
print(gen_Ec, end=' ')
else:
if procedures['energy'][method_name] != proc.run_scf:
if verbose >= 2:
print('CUSTOM',
core.get_global_option('E_CONVERGENCE'),
end=' ')
if verbose >= 2:
print('')
return optstash
def run_gaussian_2(name, **kwargs):
# throw an exception for open-shells
if (core.get_option('SCF','REFERENCE') != 'RHF' ):
raise ValidationError("""g2 computations require "reference rhf".""")
# stash user options:
optstash = p4util.OptionsState(
['FNOCC','COMPUTE_TRIPLES'],
['FNOCC','COMPUTE_MP4_TRIPLES'],
['FREEZE_CORE'],
['MP2_TYPE'],
['SCF','SCF_TYPE'])
# override default scf_type
core.set_local_option('SCF','SCF_TYPE','PK')
# optimize geometry at scf level
core.clean()
core.set_global_option('BASIS',"6-31G(D)")
driver.optimize('scf')
core.clean()
# scf frequencies for zpe
# NOTE This line should not be needed, but without it there's a seg fault
scf_e, ref = driver.frequency('scf', return_wfn=True)
# thermodynamic properties
du = core.get_variable('INTERNAL ENERGY CORRECTION')
dh = core.get_variable('ENTHALPY CORRECTION')
dg = core.get_variable('GIBBS FREE ENERGY CORRECTION')
freqs = ref.frequencies()
nfreq = freqs.dim(0)
freqsum = 0.0
for i in range(0, nfreq):
freqsum += freqs.get(i)
zpe = freqsum / p4const.psi_hartree2wavenumbers * 0.8929 * 0.5
core.clean()
# optimize geometry at mp2 (no frozen core) level
# note: freeze_core isn't an option in MP2
core.set_global_option('FREEZE_CORE',"FALSE")
core.set_global_option('MP2_TYPE', 'CONV')
driver.optimize('mp2')
core.clean()
# qcisd(t)
core.set_local_option('FNOCC','COMPUTE_MP4_TRIPLES',"TRUE")
core.set_global_option('FREEZE_CORE',"TRUE")
core.set_global_option('BASIS',"6-311G(D_P)")
ref = driver.proc.run_fnocc('qcisd(t)', return_wfn=True, **kwargs)
# HLC: high-level correction based on number of valence electrons
nirrep = ref.nirrep()
frzcpi = ref.frzcpi()
nfzc = 0
for i in range (0,nirrep):
nfzc += frzcpi[i]
nalpha = ref.nalpha() - nfzc
nbeta = ref.nbeta() - nfzc
# hlc of gaussian-2
hlc = -0.00481 * nalpha -0.00019 * nbeta
# hlc of gaussian-1
hlc1 = -0.00614 * nalpha
eqci_6311gdp = core.get_variable("QCISD(T) TOTAL ENERGY")
emp4_6311gd = core.get_variable("MP4 TOTAL ENERGY")
emp2_6311gd = core.get_variable("MP2 TOTAL ENERGY")
core.clean()
# correction for diffuse functions
core.set_global_option('BASIS',"6-311+G(D_P)")
driver.energy('mp4')
emp4_6311pg_dp = core.get_variable("MP4 TOTAL ENERGY")
emp2_6311pg_dp = core.get_variable("MP2 TOTAL ENERGY")
core.clean()
# correction for polarization functions
core.set_global_option('BASIS',"6-311G(2DF_P)")
driver.energy('mp4')
emp4_6311g2dfp = core.get_variable("MP4 TOTAL ENERGY")
emp2_6311g2dfp = core.get_variable("MP2 TOTAL ENERGY")
core.clean()
# big basis mp2
core.set_global_option('BASIS',"6-311+G(3DF_2P)")
#run_fnocc('_mp2',**kwargs)
driver.energy('mp2')
emp2_big = core.get_variable("MP2 TOTAL ENERGY")
core.clean()
eqci = eqci_6311gdp
e_delta_g2 = emp2_big + emp2_6311gd - emp2_6311g2dfp - emp2_6311pg_dp
e_plus = emp4_6311pg_dp - emp4_6311gd
e_2df = emp4_6311g2dfp - emp4_6311gd
eg2 = eqci + e_delta_g2 + e_plus + e_2df
eg2_mp2_0k = eqci + (emp2_big - emp2_6311gd) + hlc + zpe
core.print_out('\n')
core.print_out(' ==> G1/G2 Energy Components <==\n')
core.print_out('\n')
core.print_out(' QCISD(T): %20.12lf\n' % eqci)
core.print_out(' E(Delta): %20.12lf\n' % e_delta_g2)
core.print_out(' E(2DF): %20.12lf\n' % e_2df)
core.print_out(' E(+): %20.12lf\n' % e_plus)
core.print_out(' E(G1 HLC): %20.12lf\n' % hlc1)
core.print_out(' E(G2 HLC): %20.12lf\n' % hlc)
core.print_out(' E(ZPE): %20.12lf\n' % zpe)
core.print_out('\n')
core.print_out(' ==> 0 Kelvin Results <==\n')
core.print_out('\n')
eg2_0k = eg2 + zpe + hlc
core.print_out(' G1: %20.12lf\n' % (eqci + e_plus + e_2df + hlc1 + zpe))
core.print_out(' G2(MP2): %20.12lf\n' % eg2_mp2_0k)
core.print_out(' G2: %20.12lf\n' % eg2_0k)
core.set_variable("G1 TOTAL ENERGY",eqci + e_plus + e_2df + hlc1 + zpe)
core.set_variable("G2 TOTAL ENERGY",eg2_0k)
core.set_variable("G2(MP2) TOTAL ENERGY",eg2_mp2_0k)
core.print_out('\n')
T = core.get_global_option('T')
core.print_out(' ==> %3.0lf Kelvin Results <==\n'% T)
core.print_out('\n')
internal_energy = eg2_mp2_0k + du - zpe / 0.8929
enthalpy = eg2_mp2_0k + dh - zpe / 0.8929
gibbs = eg2_mp2_0k + dg - zpe / 0.8929
core.print_out(' G2(MP2) energy: %20.12lf\n' % internal_energy )
core.print_out(' G2(MP2) enthalpy: %20.12lf\n' % enthalpy)
core.print_out(' G2(MP2) free energy: %20.12lf\n' % gibbs)
core.print_out('\n')
core.set_variable("G2(MP2) INTERNAL ENERGY",internal_energy)
core.set_variable("G2(MP2) ENTHALPY",enthalpy)
core.set_variable("G2(MP2) FREE ENERGY",gibbs)
internal_energy = eg2_0k + du - zpe / 0.8929
enthalpy = eg2_0k + dh - zpe / 0.8929
gibbs = eg2_0k + dg - zpe / 0.8929
core.print_out(' G2 energy: %20.12lf\n' % internal_energy )
core.print_out(' G2 enthalpy: %20.12lf\n' % enthalpy)
core.print_out(' G2 free energy: %20.12lf\n' % gibbs)
core.set_variable("CURRENT ENERGY",eg2_0k)
core.set_variable("G2 INTERNAL ENERGY",internal_energy)
core.set_variable("G2 ENTHALPY",enthalpy)
core.set_variable("G2 FREE ENERGY",gibbs)
core.clean()
optstash.restore()
# return 0K g2 results
return eg2_0k
def run_sapt_dft(name, **kwargs):
optstash = p4util.OptionsState(['SCF', 'SCF_TYPE'],
['SCF', 'REFERENCE'],
['SCF', 'DFT_FUNCTIONAL'],
['SCF', 'DFT_GRAC_SHIFT'],
['SCF', 'SAVE_JK'])
core.tstart()
# Alter default algorithm
if not core.has_option_changed('SCF', 'SCF_TYPE'):
core.set_local_option('SCF', 'SCF_TYPE', 'DF')
core.prepare_options_for_module("SAPT")
# Get the molecule of interest
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
sapt_dimer = kwargs.pop('molecule', core.get_active_molecule())
else:
core.print_out('Warning! SAPT argument "ref_wfn" is only able to use molecule information.')
sapt_dimer = ref_wfn.molecule()
sapt_dimer, monomerA, monomerB = proc_util.prepare_sapt_molecule(sapt_dimer, "dimer")
# Grab overall settings
mon_a_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_A")
mon_b_shift = core.get_option("SAPT", "SAPT_DFT_GRAC_SHIFT_B")
do_delta_hf = core.get_option("SAPT", "SAPT_DFT_DO_DHF")
sapt_dft_functional = core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL")
# Print out the title and some information
core.print_out("\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out(" " + "SAPT(DFT) Procedure".center(58) + "\n")
core.print_out("\n")
core.print_out(" " + "by Daniel G. A. Smith".center(58) + "\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out("\n")
core.print_out(" ==> Algorithm <==\n\n")
core.print_out(" SAPT DFT Functional %12s\n" % str(sapt_dft_functional))
core.print_out(" Monomer A GRAC Shift %12.6f\n" % mon_a_shift)
core.print_out(" Monomer B GRAC Shift %12.6f\n" % mon_b_shift)
core.print_out(" Delta HF %12s\n" % ("True" if do_delta_hf else "False"))
core.print_out(" JK Algorithm %12s\n" % core.get_option("SCF", "SCF_TYPE"))
core.print_out("\n")
core.print_out(" Required computations:\n")
if (do_delta_hf):
core.print_out(" HF (Dimer)\n")
core.print_out(" HF (Monomer A)\n")
core.print_out(" HF (Monomer B)\n")
core.print_out(" DFT (Monomer A)\n")
core.print_out(" DFT (Monomer B)\n")
core.print_out("\n")
if (sapt_dft_functional != "HF") and ((mon_a_shift == 0.0) or (mon_b_shift == 0.0)):
raise ValidationError('SAPT(DFT): must set both "SAPT_DFT_GRAC_SHIFT_A" and "B".')
if (core.get_option('SCF', 'REFERENCE') != 'RHF'):
raise ValidationError('SAPT(DFT) currently only supports restricted references.')
core.IO.set_default_namespace('dimer')
data = {}
core.set_global_option("SAVE_JK", True)
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
# core.set_global_option('DF_INTS_IO', 'LOAD')
core.set_global_option('DF_INTS_IO', 'SAVE')
# # Compute dimer wavefunction
hf_cache = {}
hf_wfn_dimer = None
if do_delta_hf:
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.set_global_option('DF_INTS_IO', 'SAVE')
hf_data = {}
hf_wfn_dimer = scf_helper(
"SCF", molecule=sapt_dimer, banner="SAPT(DFT): delta HF Dimer", **kwargs)
hf_data["HF DIMER"] = core.get_variable("CURRENT ENERGY")
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'dimer', 'monomerA')
hf_wfn_A = scf_helper(
"SCF", molecule=monomerA, banner="SAPT(DFT): delta HF Monomer A", **kwargs)
hf_data["HF MONOMER A"] = core.get_variable("CURRENT ENERGY")
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
hf_wfn_B = scf_helper(
"SCF", molecule=monomerB, banner="SAPT(DFT): delta HF Monomer B", **kwargs)
hf_data["HF MONOMER B"] = core.get_variable("CURRENT ENERGY")
# Move it back to monomer A
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerB', 'dimer')
core.print_out("\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out(" " + "SAPT(DFT): delta HF Segement".center(58) + "\n")
core.print_out("\n")
core.print_out(" " + "by Daniel G. A. Smith and Rob Parrish".center(58) + "\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out("\n")
# Build cache and JK
sapt_jk = hf_wfn_B.jk()
hf_cache = sapt_jk_terms.build_sapt_jk_cache(hf_wfn_A, hf_wfn_B, sapt_jk, True)
# Electostatics
elst = sapt_jk_terms.electrostatics(hf_cache, True)
hf_data.update(elst)
# Exchange
exch = sapt_jk_terms.exchange(hf_cache, sapt_jk, True)
hf_data.update(exch)
# Induction
ind = sapt_jk_terms.induction(
hf_cache,
sapt_jk,
True,
maxiter=core.get_option("SAPT", "MAXITER"),
conv=core.get_option("SAPT", "D_CONVERGENCE"))
hf_data.update(ind)
dhf_value = hf_data["HF DIMER"] - hf_data["HF MONOMER A"] - hf_data["HF MONOMER B"]
core.print_out("\n")
core.print_out(print_sapt_hf_summary(hf_data, "SAPT(HF)", delta_hf=dhf_value))
data["Delta HF Correction"] = core.get_variable("SAPT(DFT) Delta HF")
if hf_wfn_dimer is None:
dimer_wfn = core.Wavefunction.build(sapt_dimer, core.get_global_option("BASIS"))
else:
dimer_wfn = hf_wfn_dimer
# Set the primary functional
core.set_global_option("DFT_FUNCTIONAL", core.get_option("SAPT", "SAPT_DFT_FUNCTIONAL"))
core.set_local_option('SCF', 'REFERENCE', 'RKS')
# Compute Monomer A wavefunction
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'dimer', 'monomerA')
if mon_a_shift:
core.set_global_option("DFT_GRAC_SHIFT", mon_a_shift)
# Save the JK object
core.IO.set_default_namespace('monomerA')
wfn_A = scf_helper("SCF", molecule=monomerA, banner="SAPT(DFT): DFT Monomer A", **kwargs)
data["DFT MONOMERA"] = core.get_variable("CURRENT ENERGY")
core.set_global_option("DFT_GRAC_SHIFT", 0.0)
# Compute Monomer B wavefunction
if (core.get_option('SCF', 'SCF_TYPE') == 'DF'):
core.IO.change_file_namespace(97, 'monomerA', 'monomerB')
if mon_b_shift:
core.set_global_option("DFT_GRAC_SHIFT", mon_b_shift)
core.IO.set_default_namespace('monomerB')
wfn_B = scf_helper("SCF", molecule=monomerB, banner="SAPT(DFT): DFT Monomer B", **kwargs)
data["DFT MONOMERB"] = core.get_variable("CURRENT ENERGY")
core.set_global_option("DFT_GRAC_SHIFT", 0.0)
# Print out the title and some information
core.print_out("\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out(" " + "SAPT(DFT): Intermolecular Interaction Segment".center(58) + "\n")
core.print_out("\n")
core.print_out(" " + "by Daniel G. A. Smith and Rob Parrish".center(58) + "\n")
core.print_out(" ---------------------------------------------------------\n")
core.print_out("\n")
core.print_out(" ==> Algorithm <==\n\n")
core.print_out(" SAPT DFT Functional %12s\n" % str(sapt_dft_functional))
core.print_out(" Monomer A GRAC Shift %12.6f\n" % mon_a_shift)
core.print_out(" Monomer B GRAC Shift %12.6f\n" % mon_b_shift)
core.print_out(" Delta HF %12s\n" % ("True" if do_delta_hf else "False"))
core.print_out(" JK Algorithm %12s\n" % core.get_option("SCF", "SCF_TYPE"))
# Build cache and JK
sapt_jk = wfn_B.jk()
cache = sapt_jk_terms.build_sapt_jk_cache(wfn_A, wfn_B, sapt_jk, True)
# Electostatics
elst = sapt_jk_terms.electrostatics(cache, True)
data.update(elst)
# Exchange
exch = sapt_jk_terms.exchange(cache, sapt_jk, True)
data.update(exch)
# Induction
ind = sapt_jk_terms.induction(
cache,
sapt_jk,
True,
maxiter=core.get_option("SAPT", "MAXITER"),
conv=core.get_option("SAPT", "D_CONVERGENCE"))
data.update(ind)
# Dispersion
primary_basis = wfn_A.basisset()
core.print_out("\n")
aux_basis = core.BasisSet.build(sapt_dimer, "DF_BASIS_MP2",
core.get_option("DFMP2", "DF_BASIS_MP2"), "RIFIT",
core.get_global_option('BASIS'))
fdds_disp = sapt_mp2_terms.df_fdds_dispersion(primary_basis, aux_basis, cache)
data.update(fdds_disp)
if core.get_option("SAPT", "SAPT_DFT_MP2_DISP_ALG") == "FISAPT":
mp2_disp = sapt_mp2_terms.df_mp2_fisapt_dispersion(wfn_A, primary_basis, aux_basis, cache, do_print=True)
else:
mp2_disp = sapt_mp2_terms.df_mp2_sapt_dispersion(
dimer_wfn, wfn_A, wfn_B, primary_basis, aux_basis, cache, do_print=True)
data.update(mp2_disp)
# Print out final data
core.print_out("\n")
core.print_out(print_sapt_dft_summary(data, "SAPT(DFT)"))
# Copy data back into globals
for k, v in data.items():
core.set_variable(k, v)
core.tstop()
return dimer_wfn
def frac_nuke(name, **kwargs):
"""Pull all the electrons out, one at a time"""
optstash = p4util.OptionsState(
['SCF', 'GUESS'],
['SCF', 'DF_INTS_IO'],
["SCF", "FRAC_START"],
["SCF", "FRAC_RENORMALIZE"],
# NYI ["SCF", "FRAC_LOAD"],
["SCF", "FRAC_OCC"],
["SCF", "FRAC_VAL"],
["SCF", "FRAC_DIIS"])
kwargs = p4util.kwargs_lower(kwargs)
# Make sure the molecule the user provided is the active one, and neutral
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
if molecule.molecular_charge() != 0:
raise ValidationError("""frac_nuke requires neutral molecule to start.""")
if molecule.schoenflies_symbol() != 'c1':
core.print_out(""" Requested procedure `frac_nuke` does not make use of molecular symmetry: """
"""further calculations in C1 point group.\n""")
molecule = molecule.clone()
molecule.reset_point_group('c1')
molecule.update_geometry()
charge0 = molecule.molecular_charge()
mult0 = molecule.multiplicity()
# By default, we start the frac procedure on the 25th iteration
# when not reading a previous guess
frac_start = kwargs.get('frac_start', 25)
# By default, we occupy by tenths of electrons
foccs = kwargs.get('foccs', [1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])
# By default, H**O and LUMO are both in alpha
N = 0
for A in range(molecule.natom()):
N += molecule.Z(A)
N -= charge0
N = int(N)
Nb = int((N - mult0 + 1) / 2)
Na = int(N - Nb)
charge = charge0
mult = mult0
# By default, nuke all the electrons
Nmin = 0
if 'nmax' in kwargs:
Nmin = N - int(kwargs['nmax'])
# By default, DIIS in FRAC (1.0 occupation is always DIIS'd)
frac_diis = kwargs.get('frac_diis', True)
# By default, drop the files to the molecule's name
root = kwargs.get('filename', molecule.name())
traverse_filename = root + '.traverse.dat'
stats_filename = root + '.stats.dat'
# => Traverse <= #
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
Ns = []
energies = []
potentials = []
convs = []
stats = []
# Run one SCF to burn things in
E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule, **kwargs)
# Determine H**O
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
eps_a.print_out()
if Na == Nb:
H**O = -Nb
elif Nb == 0:
H**O = Na
else:
E_a = eps_a.get(int(Na - 1))
E_b = eps_b.get(int(Nb - 1))
if E_a >= E_b:
H**O = Na
else:
H**O = -Nb
stats.append(""" %6d %6d %6d %6d %6d %6d\n""" % (N, Na, Nb, charge, mult, H**O))
if H**O > 0:
Na -= 1
else:
Nb -= 1
charge += 1
mult = Na - Nb + 1
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
core.set_local_option("SCF", "FRAC_START", frac_start)
core.set_local_option("SCF", "FRAC_RENORMALIZE", True)
# Nuke 'em Rico!
for Nintegral in range(N, Nmin, -1):
# Nuke the current H**O
for occ in foccs:
core.set_local_option("SCF", "FRAC_OCC", [H**O])
core.set_local_option("SCF", "FRAC_VAL", [occ])
E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule, **kwargs)
C = 1
if E == 0.0:
E = core.variable('SCF ITERATION ENERGY')
C = 0
if H**O > 0:
eps = wfn.epsilon_a()
potentials.append(eps.np[H**O - 1])
else:
eps = wfn.epsilon_b()
potentials.append(eps.np[-H**O - 1])
Ns.append(Nintegral + occ - 1.0)
energies.append(E)
convs.append(C)
core.set_local_option("SCF", "FRAC_START", 2)
# NYI core.set_local_option("SCF", "FRAC_LOAD", True)
core.set_local_option("SCF", "FRAC_DIIS", frac_diis)
core.set_local_option("SCF", "GUESS", "READ")
# Set the next charge/mult
molecule.set_molecular_charge(charge)
molecule.set_multiplicity(mult)
# Determine H**O
print('DGAS: What ref should this point to?')
#ref = core.legacy_wavefunction()
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Na == Nb:
H**O = -Nb
elif Nb == 0:
H**O = Na
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
if E_a >= E_b:
H**O = Na
else:
H**O = -Nb
stats.append(""" %6d %6d %6d %6d %6d %6d\n""" % (Nintegral-1, Na, Nb, charge, mult, H**O))
if H**O > 0:
Na -= 1
else:
Nb -= 1
charge += 1
mult = Na - Nb + 1
core.set_local_option("SCF", "DF_INTS_IO", "NONE")
# => Print the results out <= #
E = {}
core.print_out("""\n ==> Fractional Occupation Nuke Results <==\n\n""")
core.print_out(""" %-11s %-24s %-24s %11s\n""" % ('N', 'Energy', 'H**O Energy', 'Converged'))
for k in range(len(Ns)):
core.print_out(""" %11.3E %24.16E %24.16E %11d\n""" % (Ns[k], energies[k], potentials[k], convs[k]))
E[Ns[k]] = energies[k]
core.print_out('\n')
core.print_out(""" %6s %6s %6s %6s %6s %6s\n""" % ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
for line in stats:
core.print_out(line)
core.print_out('\n "You shoot a nuke down a bug hole, you got a lot of dead bugs"\n')
core.print_out(' -Starship Troopers\n')
# Drop the files out
with open(traverse_filename, 'w') as fh:
fh.write(""" %-11s %-24s %-24s %11s\n""" % ('N', 'Energy', 'H**O Energy', 'Converged'))
for k in range(len(Ns)):
fh.write(""" %11.3E %24.16E %24.16E %11d\n""" % (Ns[k], energies[k], potentials[k], convs[k]))
with open(stats_filename, 'w') as fh:
fh.write(""" %6s %6s %6s %6s %6s %6s\n""" % ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
for line in stats:
fh.write(line)
optstash.restore()
return E
def ip_fitting(name, omega_l=0.05, omega_r=2.5, omega_convergence=1.0e-3, maxiter=20, **kwargs):
"""Optimize DFT omega parameter for molecular system.
Parameters
----------
name : string or function
DFT functional string name or function defining functional
whose omega is to be optimized.
omega_l : float, optional
Minimum omega to be considered during fitting.
omega_r : float, optional
Maximum omega to be considered during fitting.
molecule : :ref:`molecule <op_py_molecule>`, optional
Target molecule (neutral) for which omega is to be tuned, if not last defined.
omega_convergence : float, optional
Threshold below which to consider omega converged. (formerly omega_tolerance)
maxiter : int, optional
Maximum number of iterations towards omega convergence.
Returns
-------
float
Optimal omega parameter.
"""
optstash = p4util.OptionsState(
['SCF', 'REFERENCE'],
['SCF', 'GUESS'],
['SCF', 'DF_INTS_IO'],
['SCF', 'DFT_OMEGA'],
['DOCC'],
['SOCC'])
kwargs = p4util.kwargs_lower(kwargs)
# By default, do not read previous 180 orbitals file
read = False
read180 = ''
if 'read' in kwargs:
read = True
read180 = kwargs['read']
if core.get_option('SCF', 'REFERENCE') != 'UKS':
core.print_out(""" Requested procedure `ip_fitting` runs further calculations with UKS reference.\n""")
core.set_local_option('SCF', 'REFERENCE', 'UKS')
# Make sure the molecule the user provided is the active one, and neutral
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
if molecule.molecular_charge() != 0:
raise ValidationError("""IP Fitting requires neutral molecule to start.""")
if molecule.schoenflies_symbol() != 'c1':
core.print_out(""" Requested procedure `ip_fitting` does not make use of molecular symmetry: """
"""further calculations in C1 point group.\n""")
molecule = molecule.clone()
molecule.reset_point_group('c1')
molecule.update_geometry()
charge0 = molecule.molecular_charge()
mult0 = molecule.multiplicity()
# How many electrons are there?
N = 0
for A in range(molecule.natom()):
N += molecule.Z(A)
N -= charge0
N = int(N)
Nb = int((N - mult0 + 1) / 2)
Na = int(N - Nb)
# Work in the ot namespace for this procedure
core.IO.set_default_namespace("ot")
# Burn in to determine orbital eigenvalues
if read:
core.set_local_option("SCF", "GUESS", "READ")
copy_file_to_scratch(read180, 'psi', 'ot', 180)
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
banner='IP Fitting SCF: Burn-in', **kwargs)
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
if not wfn.functional().is_x_lrc():
raise ValidationError("""Not sensible to optimize omega for non-long-range-correction functional.""")
# Determine H**O, to determine mult1
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Na == Nb:
H**O = -Nb
elif Nb == 0:
H**O = Na
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
if E_a >= E_b:
H**O = Na
else:
H**O = -Nb
Na1 = Na
Nb1 = Nb
if H**O > 0:
Na1 -= 1
else:
Nb1 -= 1
charge1 = charge0 + 1
mult1 = Na1 - Nb1 + 1
omegas = []
E0s = []
E1s = []
kIPs = []
IPs = []
types = []
# Right endpoint
core.set_local_option('SCF', 'DFT_OMEGA', omega_r)
# Neutral
if read:
core.set_local_option("SCF", "GUESS", "READ")
p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
E0r, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
banner='IP Fitting SCF: Neutral, Right Endpoint', **kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
E_HOMOr = E_HOMO
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
if read:
core.set_local_option("SCF", "GUESS", "READ")
p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
E1r = driver.energy('scf', dft_functional=name, molecule=molecule,
banner='IP Fitting SCF: Cation, Right Endpoint', **kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IPr = E1r - E0r
kIPr = -E_HOMOr
delta_r = IPr - kIPr
if IPr > kIPr:
raise ValidationError("""\n***IP Fitting Error: Right Omega limit should have kIP > IP: {} !> {}""".format(kIPr, IPr))
omegas.append(omega_r)
types.append('Right Limit')
E0s.append(E0r)
E1s.append(E1r)
IPs.append(IPr)
kIPs.append(kIPr)
# Use previous orbitals from here out
core.set_local_option("SCF", "GUESS", "READ")
# Left endpoint
core.set_local_option('SCF', 'DFT_OMEGA', omega_l)
# Neutral
core.IO.change_file_namespace(180, "neutral", "ot")
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
core.set_global_option("DOCC", [Nb])
core.set_global_option("SOCC", [Na - Nb])
E0l, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
banner='IP Fitting SCF: Neutral, Left Endpoint', **kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
E_HOMOl = E_HOMO
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
core.IO.change_file_namespace(180, "cation", "ot")
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
core.set_global_option("DOCC", [Nb1])
core.set_global_option("SOCC", [Na1 - Nb1])
E1l = driver.energy('scf', dft_functional=name, molecule=molecule,
banner='IP Fitting SCF: Cation, Left Endpoint', **kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IPl = E1l - E0l
kIPl = -E_HOMOl
delta_l = IPl - kIPl
if IPl < kIPl:
raise ValidationError("""\n***IP Fitting Error: Left Omega limit should have kIP < IP: {} !< {}""".format(kIPl, IPl))
omegas.append(omega_l)
types.append('Left Limit')
E0s.append(E0l)
E1s.append(E1l)
IPs.append(IPl)
kIPs.append(kIPl)
converged = False
repeat_l = 0
repeat_r = 0
for step in range(maxiter):
# Regula Falsi (modified)
if repeat_l > 1:
delta_l /= 2.0
if repeat_r > 1:
delta_r /= 2.0
omega = - (omega_r - omega_l) / (delta_r - delta_l) * delta_l + omega_l
core.set_local_option('SCF', 'DFT_OMEGA', omega)
# Neutral
core.IO.change_file_namespace(180, "neutral", "ot")
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
core.set_global_option("DOCC", [Nb])
core.set_global_option("SOCC", [Na - Nb])
E0, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
banner='IP Fitting SCF: Neutral, Omega = {:11.3E}'.format(omega), **kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
core.IO.change_file_namespace(180, "cation", "ot")
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
core.set_global_option("DOCC", [Nb1])
core.set_global_option("SOCC", [Na1 - Nb1])
E1 = driver.energy('scf', dft_functional=name, molecule=molecule,
banner='IP Fitting SCF: Cation, Omega = {:11.3E}'.format(omega), **kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IP = E1 - E0
kIP = -E_HOMO
delta = IP - kIP
if kIP > IP:
omega_r = omega
E0r = E0
E1r = E1
IPr = IP
kIPr = kIP
delta_r = delta
repeat_r = 0
repeat_l += 1
else:
omega_l = omega
E0l = E0
E1l = E1
IPl = IP
kIPl = kIP
delta_l = delta
repeat_l = 0
repeat_r += 1
omegas.append(omega)
types.append('Regula-Falsi')
E0s.append(E0)
E1s.append(E1)
IPs.append(IP)
kIPs.append(kIP)
# Termination
if abs(omega_l - omega_r) < omega_convergence:
converged = True
break
core.IO.set_default_namespace("")
core.print_out("""\n ==> IP Fitting Results <==\n\n""")
core.print_out(""" => Occupation Determination <= \n\n""")
core.print_out(""" %6s %6s %6s %6s %6s %6s\n""" % ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
core.print_out(""" Neutral: %6d %6d %6d %6d %6d %6d\n""" % (N, Na, Nb, charge0, mult0, H**O))
core.print_out(""" Cation: %6d %6d %6d %6d %6d\n\n""" % (N - 1, Na1, Nb1, charge1, mult1))
core.print_out(""" => Regula Falsi Iterations <=\n\n""")
core.print_out(""" %3s %11s %14s %14s %14s %s\n""" % ('N','Omega','IP','kIP','Delta','Type'))
for k in range(len(omegas)):
core.print_out(""" %3d %11.3E %14.6E %14.6E %14.6E %s\n""" %
(k + 1, omegas[k], IPs[k], kIPs[k], IPs[k] - kIPs[k], types[k]))
optstash.restore()
if converged:
core.print_out("""\n IP Fitting Converged\n""")
core.print_out(""" Final omega = %14.6E\n""" % ((omega_l + omega_r) / 2))
core.print_out("""\n "M,I. does the dying. Fleet just does the flying."\n""")
core.print_out(""" -Starship Troopers\n""")
else:
raise ConvergenceError("""IP Fitting """, step + 1)
return ((omega_l + omega_r) / 2)