def run_sapt():
if ddlow.name() == 'SCF':
dimer_wfn = ddlow
else:
dimer_wfn = ddlow.reference_wavefunction()
aux_basis = core.BasisSet.build(
dimer_wfn.molecule(), "DF_BASIS_SAPT",
core.get_global_option("DF_BASIS_SAPT"), "RIFIT",
core.get_global_option("BASIS"))
dimer_wfn.set_basisset("DF_BASIS_SAPT", aux_basis)
dimer_wfn.set_basisset("DF_BASIS_ELST", aux_basis)
core.sapt(dimer_wfn, m1mlow, m2mlow)
return {
k: core.variable(k)
for k in (
'SAPT ELST10,R ENERGY',
'SAPT EXCH10 ENERGY',
'SAPT EXCH10(S^2) ENERGY',
'SAPT IND20,R ENERGY',
'SAPT EXCH-IND20,R ENERGY',
'SAPT EXCH-DISP20 ENERGY',
'SAPT DISP20 ENERGY',
'SAPT SAME-SPIN EXCH-DISP20 ENERGY',
'SAPT SAME-SPIN DISP20 ENERGY',
'SAPT HF TOTAL ENERGY',
)
}
def compare_csx():
"""Function to validate energies in CSX files against PSIvariables. Only
active if write_csx flag on.
"""
warnings.warn(
"Using `psi4.driver.p4util.compare_csx` is deprecated (silently in 1.2), and in 1.3 it will stop working\n",
category=FutureWarning,
stacklevel=2)
if 'csx4psi' in sys.modules.keys():
if core.get_global_option('WRITE_CSX'):
enedict = csx2endict()
compare_integers(len(enedict) >= 2, True, 'CSX harvested')
for pv, en in enedict.items():
compare_values(core.variable(pv), en, 6, 'CSX ' + pv + ' ' + str(round(en, 4)))
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 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 compute_nbody_components(func, method_string, metadata):
"""Computes requested N-body components.
Performs requested computations for psi4::Molecule object `molecule` according to
`compute_list` with function `func` at `method_string` level of theory.
Parameters
----------
func : {'energy', 'gradient', 'hessian'}
Function object to be called within N-Body procedure.
method_string : str
Indicates level of theory to be passed to function `func`.
metadata : dict of str
Dictionary of N-body metadata.
Required ``'key': value`` pairs:
``'compute_list'``: dict of int: set
List of computations to perform. Keys indicate body-levels, e.g,. `compute_list[2]` is the
list of all 2-body computations required.
``'kwargs'``: dict
Arbitrary keyword arguments to be passed to function `func`.
Returns
-------
dict of str: dict
Dictionary containing computed N-body components.
Contents:
``'energies'``: dict of set: float64
Dictionary containing all energy components required for given N-body procedure.
``'ptype'``: dict of set: float64 or dict of set: psi4.Matrix
Dictionary of returned quantities from calls of function `func` during N-body computations
``'intermediates'``: dict of str: float64
Dictionary of psivars for intermediate N-body computations to be set at the end of the
N-body procedure.
"""
# Get required metadata
kwargs = metadata['kwargs']
molecule = metadata['molecule']
#molecule = core.get_active_molecule()
compute_list = metadata['compute_dict']['all']
# Now compute the energies
energies_dict = {}
gradients_dict = {}
ptype_dict = {}
intermediates_dict = {}
if kwargs.get('charge_method', False) and not metadata['embedding_charges']:
metadata['embedding_charges'] = driver_nbody_helper.compute_charges(kwargs['charge_method'],
kwargs.get('charge_type', 'MULLIKEN_CHARGES').upper(), molecule)
for count, n in enumerate(compute_list.keys()):
core.print_out("\n ==> N-Body: Now computing %d-body complexes <==\n\n" % n)
total = len(compute_list[n])
for num, pair in enumerate(compute_list[n]):
core.print_out(
"\n N-Body: Computing complex (%d/%d) with fragments %s in the basis of fragments %s.\n\n" %
(num + 1, total, str(pair[0]), str(pair[1])))
ghost = list(set(pair[1]) - set(pair[0]))
current_mol = molecule.extract_subsets(list(pair[0]), ghost)
current_mol.set_name("%s_%i_%i" % (current_mol.name(), count, num))
if metadata['embedding_charges']: driver_nbody_helper.electrostatic_embedding(metadata, pair=pair)
# Save energies info
ptype_dict[pair], wfn = func(method_string, molecule=current_mol, return_wfn=True, **kwargs)
core.set_global_option_python('EXTERN', None)
energies_dict[pair] = core.variable("CURRENT ENERGY")
gradients_dict[pair] = wfn.gradient()
var_key = "N-BODY (%s)@(%s) TOTAL ENERGY" % (', '.join([str(i) for i in pair[0]]), ', '.join(
[str(i) for i in pair[1]]))
intermediates_dict[var_key] = core.variable("CURRENT ENERGY")
core.print_out("\n N-Body: Complex Energy (fragments = %s, basis = %s: %20.14f)\n" % (str(
pair[0]), str(pair[1]), energies_dict[pair]))
# Flip this off for now, needs more testing
#if 'cp' in bsse_type_list and (len(bsse_type_list) == 1):
# core.set_global_option('DF_INTS_IO', 'LOAD')
core.clean()
return {
'energies': energies_dict,
'gradients': gradients_dict,
'ptype': ptype_dict,
'intermediates': intermediates_dict
}
def compute_nbody_components(func, method_string, metadata):
"""Computes requested N-body components.
Performs requested computations for psi4::Molecule object `molecule` according to
`compute_list` with function `func` at `method_string` level of theory.
Parameters
----------
func : str
{'energy', 'gradient', 'hessian'}
Function object to be called within N-Body procedure.
method_string : str
Indicates level of theory to be passed to function `func`.
metadata : dict of str
Dictionary of N-body metadata.
Required ``'key': value`` pairs:
``'compute_list'``: dict of int: set
List of computations to perform. Keys indicate body-levels, e.g,. `compute_list[2]` is the
list of all 2-body computations required.
``'kwargs'``: dict
Arbitrary keyword arguments to be passed to function `func`.
Returns
-------
dict of str: dict
Dictionary containing computed N-body components.
Contents:
``'energies'``: dict of set: float64
Dictionary containing all energy components required for given N-body procedure.
``'ptype'``: dict of set: float64 or dict of set: psi4.Matrix
Dictionary of returned quantities from calls of function `func` during N-body computations
``'intermediates'``: dict of str: float64
Dictionary of psivars for intermediate N-body computations to be set at the end of the
N-body procedure.
"""
# Get required metadata
kwargs = metadata['kwargs']
molecule = metadata['molecule']
#molecule = core.get_active_molecule()
compute_list = metadata['compute_dict']['all']
# Now compute the energies
energies_dict = {}
gradients_dict = {}
ptype_dict = {}
intermediates_dict = {}
if kwargs.get('charge_method',
False) and not metadata['embedding_charges']:
metadata['embedding_charges'] = driver_nbody_helper.compute_charges(
kwargs['charge_method'],
kwargs.get('charge_type', 'MULLIKEN_CHARGES').upper(), molecule)
for count, n in enumerate(compute_list.keys()):
core.print_out(
"\n ==> N-Body: Now computing %d-body complexes <==\n\n" % n)
total = len(compute_list[n])
for num, pair in enumerate(compute_list[n]):
core.print_out(
"\n N-Body: Computing complex (%d/%d) with fragments %s in the basis of fragments %s.\n\n"
% (num + 1, total, str(pair[0]), str(pair[1])))
ghost = list(set(pair[1]) - set(pair[0]))
current_mol = molecule.extract_subsets(list(pair[0]), ghost)
current_mol.set_name("%s_%i_%i" % (current_mol.name(), count, num))
if metadata['embedding_charges']:
driver_nbody_helper.electrostatic_embedding(metadata,
pair=pair)
# Save energies info
ptype_dict[pair], wfn = func(method_string,
molecule=current_mol,
return_wfn=True,
**kwargs)
core.set_global_option_python('EXTERN', None)
energies_dict[pair] = core.variable("CURRENT ENERGY")
gradients_dict[pair] = wfn.gradient()
var_key = "N-BODY (%s)@(%s) TOTAL ENERGY" % (', '.join(
[str(i)
for i in pair[0]]), ', '.join([str(i) for i in pair[1]]))
intermediates_dict[var_key] = core.variable("CURRENT ENERGY")
core.print_out(
"\n N-Body: Complex Energy (fragments = %s, basis = %s: %20.14f)\n"
% (str(pair[0]), str(pair[1]), energies_dict[pair]))
# Flip this off for now, needs more testing
#if 'cp' in bsse_type_list and (len(bsse_type_list) == 1):
# core.set_global_option('DF_INTS_IO', 'LOAD')
core.clean()
return {
'energies': energies_dict,
'gradients': gradients_dict,
'ptype': ptype_dict,
'intermediates': intermediates_dict
}
def mcscf_solver(ref_wfn):
# Build CIWavefunction
core.prepare_options_for_module("DETCI")
ciwfn = core.CIWavefunction(ref_wfn)
# Hush a lot of CI output
ciwfn.set_print(0)
# Begin with a normal two-step
step_type = 'Initial CI'
total_step = core.Matrix("Total step", ciwfn.get_dimension('OA'),
ciwfn.get_dimension('AV'))
start_orbs = ciwfn.get_orbitals("ROT").clone()
ciwfn.set_orbitals("ROT", start_orbs)
# Grab da options
mcscf_orb_grad_conv = core.get_option("DETCI", "MCSCF_R_CONVERGENCE")
mcscf_e_conv = core.get_option("DETCI", "MCSCF_E_CONVERGENCE")
mcscf_max_macroiteration = core.get_option("DETCI", "MCSCF_MAXITER")
mcscf_type = core.get_option("DETCI", "MCSCF_TYPE")
mcscf_d_file = core.get_option("DETCI", "CI_FILE_START") + 3
mcscf_nroots = core.get_option("DETCI", "NUM_ROOTS")
mcscf_wavefunction_type = core.get_option("DETCI", "WFN")
mcscf_ndet = ciwfn.ndet()
mcscf_nuclear_energy = ciwfn.molecule().nuclear_repulsion_energy()
mcscf_steplimit = core.get_option("DETCI", "MCSCF_MAX_ROT")
mcscf_rotate = core.get_option("DETCI", "MCSCF_ROTATE")
# DIIS info
mcscf_diis_start = core.get_option("DETCI", "MCSCF_DIIS_START")
mcscf_diis_freq = core.get_option("DETCI", "MCSCF_DIIS_FREQ")
mcscf_diis_error_type = core.get_option("DETCI", "MCSCF_DIIS_ERROR_TYPE")
mcscf_diis_max_vecs = core.get_option("DETCI", "MCSCF_DIIS_MAX_VECS")
# One-step info
mcscf_target_conv_type = core.get_option("DETCI", "MCSCF_ALGORITHM")
mcscf_so_start_grad = core.get_option("DETCI", "MCSCF_SO_START_GRAD")
mcscf_so_start_e = core.get_option("DETCI", "MCSCF_SO_START_E")
mcscf_current_step_type = 'Initial CI'
# Start with SCF energy and other params
scf_energy = ciwfn.variable("HF TOTAL ENERGY")
eold = scf_energy
norb_iter = 1
converged = False
ah_step = False
qc_step = False
approx_integrals_only = True
# Fake info to start with the initial diagonalization
ediff = 1.e-4
orb_grad_rms = 1.e-3
# Grab needed objects
diis_obj = solvers.DIIS(mcscf_diis_max_vecs)
mcscf_obj = ciwfn.mcscf_object()
# Execute the rotate command
for rot in mcscf_rotate:
if len(rot) != 4:
raise p4util.PsiException(
"Each element of the MCSCF rotate command requires 4 arguements (irrep, orb1, orb2, theta)."
)
irrep, orb1, orb2, theta = rot
if irrep > ciwfn.Ca().nirrep():
raise p4util.PsiException(
"MCSCF_ROTATE: Expression %s irrep number is larger than the number of irreps"
% (str(rot)))
if max(orb1, orb2) > ciwfn.Ca().coldim()[irrep]:
raise p4util.PsiException(
"MCSCF_ROTATE: Expression %s orbital number exceeds number of orbitals in irrep"
% (str(rot)))
theta = np.deg2rad(theta)
x = ciwfn.Ca().nph[irrep][:, orb1].copy()
y = ciwfn.Ca().nph[irrep][:, orb2].copy()
xp = np.cos(theta) * x - np.sin(theta) * y
yp = np.sin(theta) * x + np.cos(theta) * y
ciwfn.Ca().nph[irrep][:, orb1] = xp
ciwfn.Ca().nph[irrep][:, orb2] = yp
# Limited RAS functionality
if core.get_local_option(
"DETCI", "WFN") == "RASSCF" and mcscf_target_conv_type != "TS":
core.print_out(
"\n Warning! Only the TS algorithm for RASSCF wavefunction is currently supported.\n"
)
core.print_out(" Switching to the TS algorithm.\n\n")
mcscf_target_conv_type = "TS"
# Print out headers
if mcscf_type == "CONV":
mtype = " @MCSCF"
core.print_out("\n ==> Starting MCSCF iterations <==\n\n")
core.print_out(
" Iter Total Energy Delta E Orb RMS CI RMS NCI NORB\n"
)
elif mcscf_type == "DF":
mtype = " @DF-MCSCF"
core.print_out("\n ==> Starting DF-MCSCF iterations <==\n\n")
core.print_out(
" Iter Total Energy Delta E Orb RMS CI RMS NCI NORB\n"
)
else:
mtype = " @AO-MCSCF"
core.print_out("\n ==> Starting AO-MCSCF iterations <==\n\n")
core.print_out(
" Iter Total Energy Delta E Orb RMS CI RMS NCI NORB\n"
)
# Iterate !
for mcscf_iter in range(1, mcscf_max_macroiteration + 1):
# Transform integrals, diagonalize H
ciwfn.transform_mcscf_integrals(approx_integrals_only)
nci_iter = ciwfn.diag_h(abs(ediff) * 1.e-2, orb_grad_rms * 1.e-3)
# After the first diag we need to switch to READ
ciwfn.set_ci_guess("DFILE")
ciwfn.form_opdm()
ciwfn.form_tpdm()
ci_grad_rms = core.variable("DETCI AVG DVEC NORM")
# Update MCSCF object
Cocc = ciwfn.get_orbitals("DOCC")
Cact = ciwfn.get_orbitals("ACT")
Cvir = ciwfn.get_orbitals("VIR")
opdm = ciwfn.get_opdm(-1, -1, "SUM", False)
tpdm = ciwfn.get_tpdm("SUM", True)
mcscf_obj.update(Cocc, Cact, Cvir, opdm, tpdm)
current_energy = core.variable("MCSCF TOTAL ENERGY")
orb_grad_rms = mcscf_obj.gradient_rms()
ediff = current_energy - eold
# Print iterations
print_iteration(mtype, mcscf_iter, current_energy, ediff, orb_grad_rms,
ci_grad_rms, nci_iter, norb_iter,
mcscf_current_step_type)
eold = current_energy
if mcscf_current_step_type == 'Initial CI':
mcscf_current_step_type = 'TS'
# Check convergence
if (orb_grad_rms < mcscf_orb_grad_conv) and (abs(ediff) < abs(mcscf_e_conv)) and\
(mcscf_iter > 3) and not qc_step:
core.print_out("\n %s has converged!\n\n" % mtype)
converged = True
break
# Which orbital convergence are we doing?
if ah_step:
converged, norb_iter, step = ah_iteration(mcscf_obj,
print_micro=False)
norb_iter += 1
if converged:
mcscf_current_step_type = 'AH'
else:
core.print_out(
" !Warning. Augmented Hessian did not converge. Taking an approx step.\n"
)
step = mcscf_obj.approx_solve()
mcscf_current_step_type = 'TS, AH failure'
else:
step = mcscf_obj.approx_solve()
step_type = 'TS'
maxstep = step.absmax()
if maxstep > mcscf_steplimit:
core.print_out(
' Warning! Maxstep = %4.2f, scaling to %4.2f\n' %
(maxstep, mcscf_steplimit))
step.scale(mcscf_steplimit / maxstep)
xstep = total_step.clone()
total_step.add(step)
# Do or add DIIS
if (mcscf_iter >= mcscf_diis_start) and ("TS"
in mcscf_current_step_type):
# Figure out DIIS error vector
if mcscf_diis_error_type == "GRAD":
error = core.Matrix.triplet(ciwfn.get_orbitals("OA"),
mcscf_obj.gradient(),
ciwfn.get_orbitals("AV"), False,
False, True)
else:
error = step
diis_obj.add(total_step, error)
if not (mcscf_iter % mcscf_diis_freq):
total_step = diis_obj.extrapolate()
mcscf_current_step_type = 'TS, DIIS'
# Build the rotation by continuous updates
if mcscf_iter == 1:
totalU = mcscf_obj.form_rotation_matrix(total_step)
else:
xstep.axpy(-1.0, total_step)
xstep.scale(-1.0)
Ustep = mcscf_obj.form_rotation_matrix(xstep)
totalU = core.Matrix.doublet(totalU, Ustep, False, False)
# Build the rotation directly (not recommended)
# orbs_mat = mcscf_obj.Ck(start_orbs, total_step)
# Finally rotate and set orbitals
orbs_mat = core.Matrix.doublet(start_orbs, totalU, False, False)
ciwfn.set_orbitals("ROT", orbs_mat)
# Figure out what the next step should be
if (orb_grad_rms < mcscf_so_start_grad) and (abs(ediff) < abs(mcscf_so_start_e)) and\
(mcscf_iter >= 2):
if mcscf_target_conv_type == 'AH':
approx_integrals_only = False
ah_step = True
elif mcscf_target_conv_type == 'OS':
approx_integrals_only = False
mcscf_current_step_type = 'OS, Prep'
break
else:
continue
#raise p4util.PsiException("")
# If we converged do not do onestep
if converged or (mcscf_target_conv_type != 'OS'):
one_step_iters = []
# If we are not converged load in Dvec and build iters array
else:
one_step_iters = range(mcscf_iter + 1, mcscf_max_macroiteration + 1)
dvec = ciwfn.D_vector()
dvec.init_io_files(True)
dvec.read(0, 0)
dvec.symnormalize(1.0, 0)
ci_grad = ciwfn.new_civector(1, mcscf_d_file + 1, True, True)
ci_grad.set_nvec(1)
ci_grad.init_io_files(True)
# Loop for onestep
for mcscf_iter in one_step_iters:
# Transform integrals and update the MCSCF object
ciwfn.transform_mcscf_integrals(ciwfn.H(), False)
ciwfn.form_opdm()
ciwfn.form_tpdm()
# Update MCSCF object
Cocc = ciwfn.get_orbitals("DOCC")
Cact = ciwfn.get_orbitals("ACT")
Cvir = ciwfn.get_orbitals("VIR")
opdm = ciwfn.get_opdm(-1, -1, "SUM", False)
tpdm = ciwfn.get_tpdm("SUM", True)
mcscf_obj.update(Cocc, Cact, Cvir, opdm, tpdm)
orb_grad_rms = mcscf_obj.gradient_rms()
# Warning! Does not work for SA-MCSCF
current_energy = mcscf_obj.current_total_energy()
current_energy += mcscf_nuclear_energy
core.set_variable("CI ROOT %d TOTAL ENERGY" % 1, current_energy)
core.set_variable("CURRENT ENERGY", current_energy)
docc_energy = mcscf_obj.current_docc_energy()
ci_energy = mcscf_obj.current_ci_energy()
# Compute CI gradient
ciwfn.sigma(dvec, ci_grad, 0, 0)
ci_grad.scale(2.0, 0)
ci_grad.axpy(-2.0 * ci_energy, dvec, 0, 0)
ci_grad_rms = ci_grad.norm(0)
orb_grad_rms = mcscf_obj.gradient().rms()
ediff = current_energy - eold
print_iteration(mtype, mcscf_iter, current_energy, ediff, orb_grad_rms,
ci_grad_rms, nci_iter, norb_iter,
mcscf_current_step_type)
mcscf_current_step_type = 'OS'
eold = current_energy
if (orb_grad_rms < mcscf_orb_grad_conv) and (abs(ediff) <
abs(mcscf_e_conv)):
core.print_out("\n %s has converged!\n\n" % mtype)
converged = True
break
# Take a step
converged, norb_iter, nci_iter, step = qc_iteration(
dvec, ci_grad, ciwfn, mcscf_obj)
# Rotate integrals to new frame
total_step.add(step)
orbs_mat = mcscf_obj.Ck(ciwfn.get_orbitals("ROT"), step)
ciwfn.set_orbitals("ROT", orbs_mat)
core.print_out(mtype + " Final Energy: %20.15f\n" % current_energy)
# Die if we did not converge
if (not converged):
if core.get_global_option("DIE_IF_NOT_CONVERGED"):
raise p4util.PsiException("MCSCF: Iterations did not converge!")
else:
core.print_out("\nWarning! MCSCF iterations did not converge!\n\n")
# Print out CI vector information
if mcscf_target_conv_type == 'OS':
dvec.close_io_files()
ci_grad.close_io_files()
# For orbital invariant methods we transform the orbitals to the natural or
# semicanonical basis. Frozen doubly occupied and virtual orbitals are not
# modified.
if core.get_option("DETCI", "WFN") == "CASSCF":
# Do we diagonalize the opdm?
if core.get_option("DETCI", "NAT_ORBS"):
ciwfn.ci_nat_orbs()
else:
ciwfn.semicanonical_orbs()
# Retransform intragrals and update CI coeffs., OPDM, and TPDM
ciwfn.transform_mcscf_integrals(approx_integrals_only)
nci_iter = ciwfn.diag_h(abs(ediff) * 1.e-2, orb_grad_rms * 1.e-3)
ciwfn.set_ci_guess("DFILE")
ciwfn.form_opdm()
ciwfn.form_tpdm()
proc_util.print_ci_results(ciwfn,
"MCSCF",
scf_energy,
current_energy,
print_opdm_no=True)
# Set final energy
core.set_variable("CURRENT ENERGY", core.variable("MCSCF TOTAL ENERGY"))
# What do we need to cleanup?
if core.get_option("DETCI", "MCSCF_CI_CLEANUP"):
ciwfn.cleanup_ci()
if core.get_option("DETCI", "MCSCF_DPD_CLEANUP"):
ciwfn.cleanup_dpd()
del diis_obj
del mcscf_obj
return ciwfn
def mcscf_solver(ref_wfn):
# Build CIWavefunction
core.prepare_options_for_module("DETCI")
ciwfn = core.CIWavefunction(ref_wfn)
# Hush a lot of CI output
ciwfn.set_print(0)
# Begin with a normal two-step
step_type = 'Initial CI'
total_step = core.Matrix("Total step", ciwfn.get_dimension('OA'), ciwfn.get_dimension('AV'))
start_orbs = ciwfn.get_orbitals("ROT").clone()
ciwfn.set_orbitals("ROT", start_orbs)
# Grab da options
mcscf_orb_grad_conv = core.get_option("DETCI", "MCSCF_R_CONVERGENCE")
mcscf_e_conv = core.get_option("DETCI", "MCSCF_E_CONVERGENCE")
mcscf_max_macroiteration = core.get_option("DETCI", "MCSCF_MAXITER")
mcscf_type = core.get_option("DETCI", "MCSCF_TYPE")
mcscf_d_file = core.get_option("DETCI", "CI_FILE_START") + 3
mcscf_nroots = core.get_option("DETCI", "NUM_ROOTS")
mcscf_wavefunction_type = core.get_option("DETCI", "WFN")
mcscf_ndet = ciwfn.ndet()
mcscf_nuclear_energy = ciwfn.molecule().nuclear_repulsion_energy()
mcscf_steplimit = core.get_option("DETCI", "MCSCF_MAX_ROT")
mcscf_rotate = core.get_option("DETCI", "MCSCF_ROTATE")
# DIIS info
mcscf_diis_start = core.get_option("DETCI", "MCSCF_DIIS_START")
mcscf_diis_freq = core.get_option("DETCI", "MCSCF_DIIS_FREQ")
mcscf_diis_error_type = core.get_option("DETCI", "MCSCF_DIIS_ERROR_TYPE")
mcscf_diis_max_vecs = core.get_option("DETCI", "MCSCF_DIIS_MAX_VECS")
# One-step info
mcscf_target_conv_type = core.get_option("DETCI", "MCSCF_ALGORITHM")
mcscf_so_start_grad = core.get_option("DETCI", "MCSCF_SO_START_GRAD")
mcscf_so_start_e = core.get_option("DETCI", "MCSCF_SO_START_E")
mcscf_current_step_type = 'Initial CI'
# Start with SCF energy and other params
scf_energy = ciwfn.variable("HF TOTAL ENERGY")
eold = scf_energy
norb_iter = 1
converged = False
ah_step = False
qc_step = False
approx_integrals_only = True
# Fake info to start with the initial diagonalization
ediff = 1.e-4
orb_grad_rms = 1.e-3
# Grab needed objects
diis_obj = solvers.DIIS(mcscf_diis_max_vecs)
mcscf_obj = ciwfn.mcscf_object()
# Execute the rotate command
for rot in mcscf_rotate:
if len(rot) != 4:
raise p4util.PsiException("Each element of the MCSCF rotate command requires 4 arguements (irrep, orb1, orb2, theta).")
irrep, orb1, orb2, theta = rot
if irrep > ciwfn.Ca().nirrep():
raise p4util.PsiException("MCSCF_ROTATE: Expression %s irrep number is larger than the number of irreps" %
(str(rot)))
if max(orb1, orb2) > ciwfn.Ca().coldim()[irrep]:
raise p4util.PsiException("MCSCF_ROTATE: Expression %s orbital number exceeds number of orbitals in irrep" %
(str(rot)))
theta = np.deg2rad(theta)
x = ciwfn.Ca().nph[irrep][:, orb1].copy()
y = ciwfn.Ca().nph[irrep][:, orb2].copy()
xp = np.cos(theta) * x - np.sin(theta) * y
yp = np.sin(theta) * x + np.cos(theta) * y
ciwfn.Ca().nph[irrep][:, orb1] = xp
ciwfn.Ca().nph[irrep][:, orb2] = yp
# Limited RAS functionality
if core.get_local_option("DETCI", "WFN") == "RASSCF" and mcscf_target_conv_type != "TS":
core.print_out("\n Warning! Only the TS algorithm for RASSCF wavefunction is currently supported.\n")
core.print_out(" Switching to the TS algorithm.\n\n")
mcscf_target_conv_type = "TS"
# Print out headers
if mcscf_type == "CONV":
mtype = " @MCSCF"
core.print_out("\n ==> Starting MCSCF iterations <==\n\n")
core.print_out(" Iter Total Energy Delta E Orb RMS CI RMS NCI NORB\n")
elif mcscf_type == "DF":
mtype = " @DF-MCSCF"
core.print_out("\n ==> Starting DF-MCSCF iterations <==\n\n")
core.print_out(" Iter Total Energy Delta E Orb RMS CI RMS NCI NORB\n")
else:
mtype = " @AO-MCSCF"
core.print_out("\n ==> Starting AO-MCSCF iterations <==\n\n")
core.print_out(" Iter Total Energy Delta E Orb RMS CI RMS NCI NORB\n")
# Iterate !
for mcscf_iter in range(1, mcscf_max_macroiteration + 1):
# Transform integrals, diagonalize H
ciwfn.transform_mcscf_integrals(approx_integrals_only)
nci_iter = ciwfn.diag_h(abs(ediff) * 1.e-2, orb_grad_rms * 1.e-3)
# After the first diag we need to switch to READ
ciwfn.set_ci_guess("DFILE")
ciwfn.form_opdm()
ciwfn.form_tpdm()
ci_grad_rms = core.variable("DETCI AVG DVEC NORM")
# Update MCSCF object
Cocc = ciwfn.get_orbitals("DOCC")
Cact = ciwfn.get_orbitals("ACT")
Cvir = ciwfn.get_orbitals("VIR")
opdm = ciwfn.get_opdm(-1, -1, "SUM", False)
tpdm = ciwfn.get_tpdm("SUM", True)
mcscf_obj.update(Cocc, Cact, Cvir, opdm, tpdm)
current_energy = core.variable("MCSCF TOTAL ENERGY")
orb_grad_rms = mcscf_obj.gradient_rms()
ediff = current_energy - eold
# Print iterations
print_iteration(mtype, mcscf_iter, current_energy, ediff, orb_grad_rms, ci_grad_rms,
nci_iter, norb_iter, mcscf_current_step_type)
eold = current_energy
if mcscf_current_step_type == 'Initial CI':
mcscf_current_step_type = 'TS'
# Check convergence
if (orb_grad_rms < mcscf_orb_grad_conv) and (abs(ediff) < abs(mcscf_e_conv)) and\
(mcscf_iter > 3) and not qc_step:
core.print_out("\n %s has converged!\n\n" % mtype);
converged = True
break
# Which orbital convergence are we doing?
if ah_step:
converged, norb_iter, step = ah_iteration(mcscf_obj, print_micro=False)
norb_iter += 1
if converged:
mcscf_current_step_type = 'AH'
else:
core.print_out(" !Warning. Augmented Hessian did not converge. Taking an approx step.\n")
step = mcscf_obj.approx_solve()
mcscf_current_step_type = 'TS, AH failure'
else:
step = mcscf_obj.approx_solve()
step_type = 'TS'
maxstep = step.absmax()
if maxstep > mcscf_steplimit:
core.print_out(' Warning! Maxstep = %4.2f, scaling to %4.2f\n' % (maxstep, mcscf_steplimit))
step.scale(mcscf_steplimit / maxstep)
xstep = total_step.clone()
total_step.add(step)
# Do or add DIIS
if (mcscf_iter >= mcscf_diis_start) and ("TS" in mcscf_current_step_type):
# Figure out DIIS error vector
if mcscf_diis_error_type == "GRAD":
error = core.triplet(ciwfn.get_orbitals("OA"),
mcscf_obj.gradient(),
ciwfn.get_orbitals("AV"),
False, False, True)
else:
error = step
diis_obj.add(total_step, error)
if not (mcscf_iter % mcscf_diis_freq):
total_step = diis_obj.extrapolate()
mcscf_current_step_type = 'TS, DIIS'
# Build the rotation by continuous updates
if mcscf_iter == 1:
totalU = mcscf_obj.form_rotation_matrix(total_step)
else:
xstep.axpy(-1.0, total_step)
xstep.scale(-1.0)
Ustep = mcscf_obj.form_rotation_matrix(xstep)
totalU = core.doublet(totalU, Ustep, False, False)
# Build the rotation directly (not recommended)
# orbs_mat = mcscf_obj.Ck(start_orbs, total_step)
# Finally rotate and set orbitals
orbs_mat = core.doublet(start_orbs, totalU, False, False)
ciwfn.set_orbitals("ROT", orbs_mat)
# Figure out what the next step should be
if (orb_grad_rms < mcscf_so_start_grad) and (abs(ediff) < abs(mcscf_so_start_e)) and\
(mcscf_iter >= 2):
if mcscf_target_conv_type == 'AH':
approx_integrals_only = False
ah_step = True
elif mcscf_target_conv_type == 'OS':
approx_integrals_only = False
mcscf_current_step_type = 'OS, Prep'
break
else:
continue
#raise p4util.PsiException("")
# If we converged do not do onestep
if converged or (mcscf_target_conv_type != 'OS'):
one_step_iters = []
# If we are not converged load in Dvec and build iters array
else:
one_step_iters = range(mcscf_iter + 1, mcscf_max_macroiteration + 1)
dvec = ciwfn.D_vector()
dvec.init_io_files(True)
dvec.read(0, 0)
dvec.symnormalize(1.0, 0)
ci_grad = ciwfn.new_civector(1, mcscf_d_file + 1, True, True)
ci_grad.set_nvec(1)
ci_grad.init_io_files(True)
# Loop for onestep
for mcscf_iter in one_step_iters:
# Transform integrals and update the MCSCF object
ciwfn.transform_mcscf_integrals(ciwfn.H(), False)
ciwfn.form_opdm()
ciwfn.form_tpdm()
# Update MCSCF object
Cocc = ciwfn.get_orbitals("DOCC")
Cact = ciwfn.get_orbitals("ACT")
Cvir = ciwfn.get_orbitals("VIR")
opdm = ciwfn.get_opdm(-1, -1, "SUM", False)
tpdm = ciwfn.get_tpdm("SUM", True)
mcscf_obj.update(Cocc, Cact, Cvir, opdm, tpdm)
orb_grad_rms = mcscf_obj.gradient_rms()
# Warning! Does not work for SA-MCSCF
current_energy = mcscf_obj.current_total_energy()
current_energy += mcscf_nuclear_energy
core.set_variable("CI ROOT %d TOTAL ENERGY" % 1, current_energy)
core.set_variable("CURRENT ENERGY", current_energy)
docc_energy = mcscf_obj.current_docc_energy()
ci_energy = mcscf_obj.current_ci_energy()
# Compute CI gradient
ciwfn.sigma(dvec, ci_grad, 0, 0)
ci_grad.scale(2.0, 0)
ci_grad.axpy(-2.0 * ci_energy, dvec, 0, 0)
ci_grad_rms = ci_grad.norm(0)
orb_grad_rms = mcscf_obj.gradient().rms()
ediff = current_energy - eold
print_iteration(mtype, mcscf_iter, current_energy, ediff, orb_grad_rms, ci_grad_rms,
nci_iter, norb_iter, mcscf_current_step_type)
mcscf_current_step_type = 'OS'
eold = current_energy
if (orb_grad_rms < mcscf_orb_grad_conv) and (abs(ediff) < abs(mcscf_e_conv)):
core.print_out("\n %s has converged!\n\n" % mtype);
converged = True
break
# Take a step
converged, norb_iter, nci_iter, step = qc_iteration(dvec, ci_grad, ciwfn, mcscf_obj)
# Rotate integrals to new frame
total_step.add(step)
orbs_mat = mcscf_obj.Ck(ciwfn.get_orbitals("ROT"), step)
ciwfn.set_orbitals("ROT", orbs_mat)
core.print_out(mtype + " Final Energy: %20.15f\n" % current_energy)
# Die if we did not converge
if (not converged):
if core.get_global_option("DIE_IF_NOT_CONVERGED"):
raise p4util.PsiException("MCSCF: Iterations did not converge!")
else:
core.print_out("\nWarning! MCSCF iterations did not converge!\n\n")
# Print out CI vector information
if mcscf_target_conv_type == 'OS':
dvec.close_io_files()
ci_grad.close_io_files()
# For orbital invariant methods we transform the orbitals to the natural or
# semicanonical basis. Frozen doubly occupied and virtual orbitals are not
# modified.
if core.get_option("DETCI", "WFN") == "CASSCF":
# Do we diagonalize the opdm?
if core.get_option("DETCI", "NAT_ORBS"):
ciwfn.ci_nat_orbs()
else:
ciwfn.semicanonical_orbs()
# Retransform intragrals and update CI coeffs., OPDM, and TPDM
ciwfn.transform_mcscf_integrals(approx_integrals_only)
nci_iter = ciwfn.diag_h(abs(ediff) * 1.e-2, orb_grad_rms * 1.e-3)
ciwfn.set_ci_guess("DFILE")
ciwfn.form_opdm()
ciwfn.form_tpdm()
proc_util.print_ci_results(ciwfn, "MCSCF", scf_energy, current_energy, print_opdm_no=True)
# Set final energy
core.set_variable("CURRENT ENERGY", core.variable("MCSCF TOTAL ENERGY"))
# What do we need to cleanup?
if core.get_option("DETCI", "MCSCF_CI_CLEANUP"):
ciwfn.cleanup_ci()
if core.get_option("DETCI", "MCSCF_DPD_CLEANUP"):
ciwfn.cleanup_dpd()
del diis_obj
del mcscf_obj
return ciwfn
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 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 print_ci_results(ciwfn, rname, scf_e, ci_e, print_opdm_no=False):
"""
Printing for all CI Wavefunctions
"""
# Print out energetics
core.print_out("\n ==> Energetics <==\n\n")
core.print_out(" SCF energy = %20.15f\n" % scf_e)
if "CI" in rname:
core.print_out(" Total CI energy = %20.15f\n" % ci_e)
elif "MP" in rname:
core.print_out(" Total MP energy = %20.15f\n" % ci_e)
elif "ZAPT" in rname:
core.print_out(" Total ZAPT energy = %20.15f\n" % ci_e)
else:
core.print_out(" Total MCSCF energy = %20.15f\n" % ci_e)
# Nothing to be done for ZAPT or MP
if ("MP" in rname) or ("ZAPT" in rname):
core.print_out("\n")
return
# Initial info
ci_nroots = core.get_option("DETCI", "NUM_ROOTS")
irrep_labels = ciwfn.molecule().irrep_labels()
# Grab the D-vector
dvec = ciwfn.D_vector()
dvec.init_io_files(True)
for root in range(ci_nroots):
core.print_out("\n ==> %s root %d information <==\n\n" %
(rname, root))
# Print total energy
root_e = core.variable("CI ROOT %d TOTAL ENERGY" % (root))
core.print_out(" %s Root %d energy = %20.15f\n" %
(rname, root, root_e))
# Print natural occupations
if print_opdm_no:
core.print_out("\n Active Space Natural occupation numbers:\n\n")
occs_list = []
r_opdm = ciwfn.get_opdm(root, root, "SUM", False)
for h in range(len(r_opdm.nph)):
if 0 in r_opdm.nph[h].shape:
continue
nocc, rot = np.linalg.eigh(r_opdm.nph[h])
for e in nocc:
occs_list.append((e, irrep_labels[h]))
occs_list.sort(key=lambda x: -x[0])
cnt = 0
for value, label in occs_list:
value, label = occs_list[cnt]
core.print_out(" %4s % 8.6f" % (label, value))
cnt += 1
if (cnt % 3) == 0:
core.print_out("\n")
if (cnt % 3):
core.print_out("\n")
# Print CIVector information
ciwfn.print_vector(dvec, root)
# True to keep the file
dvec.close_io_files(True)
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_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 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()
optstash.restore()
return dimer_wfn
def sapt_empirical_dispersion(name, dimer_wfn, **kwargs):
sapt_dimer = dimer_wfn.molecule()
sapt_dimer, monomerA, monomerB = prepare_sapt_molecule(sapt_dimer, "dimer")
disp_name = name.split("-")[1]
# Get the names right between SAPT0 and FISAPT0
saptd_name = name.split('-')[0].upper()
if saptd_name == "SAPT0":
sapt0_name = "SAPT0"
else:
sapt0_name = "SAPT"
save_pair = (saptd_name == "FISAPT0")
from .proc import build_disp_functor
_, _disp_functor = build_disp_functor('hf-' + disp_name,
restricted=True,
save_pairwise_disp=save_pair,
**kwargs)
## Dimer dispersion
dimer_disp_energy = _disp_functor.compute_energy(dimer_wfn.molecule(),
dimer_wfn)
## Monomer dispersion
mon_disp_energy = _disp_functor.compute_energy(monomerA)
mon_disp_energy += _disp_functor.compute_energy(monomerB)
disp_interaction_energy = dimer_disp_energy - mon_disp_energy
core.set_variable(saptd_name + "-D DISP ENERGY", disp_interaction_energy)
core.set_variable("SAPT DISP ENERGY", disp_interaction_energy)
core.set_variable("DISPERSION CORRECTION ENERGY", disp_interaction_energy)
core.set_variable(saptd_name + "DISPERSION CORRECTION ENERGY",
disp_interaction_energy)
## Set SAPT0-D3 variables
total = disp_interaction_energy
saptd_en = {}
saptd_en['DISP'] = disp_interaction_energy
for term in ['ELST', 'EXCH', 'IND']:
en = core.variable(' '.join([sapt0_name, term, 'ENERGY']))
saptd_en[term] = en
core.set_variable(' '.join([saptd_name + '-D', term, 'ENERGY']), en)
core.set_variable(' '.join(['SAPT', term, 'ENERGY']), en)
total += en
core.set_variable(saptd_name + '-D TOTAL ENERGY', total)
core.set_variable('SAPT TOTAL ENERGY', total)
core.set_variable('CURRENT ENERGY', total)
## Print Energy Summary
units = (1000.0, constants.hartree2kcalmol, constants.hartree2kJmol)
core.print_out(f" => {saptd_name +'-D'} Energy Summary <=\n")
core.print_out(" " + "-" * 104 + "\n")
core.print_out(
" %-25s % 16.8f [mEh] % 16.8f [kcal/mol] % 16.8f [kJ/mol]\n" %
("Electrostatics", saptd_en['ELST'] * units[0],
saptd_en['ELST'] * units[1], saptd_en['ELST'] * units[2]))
core.print_out(
" %-25s % 16.8f [mEh] % 16.8f [kcal/mol] % 16.8f [kJ/mol]\n" %
("Exchange", saptd_en['EXCH'] * units[0], saptd_en['EXCH'] * units[1],
saptd_en['EXCH'] * units[2]))
core.print_out(
" %-25s % 16.8f [mEh] % 16.8f [kcal/mol] % 16.8f [kJ/mol]\n" %
("Induction", saptd_en['IND'] * units[0], saptd_en['IND'] * units[1],
saptd_en['IND'] * units[2]))
core.print_out(
" %-25s % 16.8f [mEh] % 16.8f [kcal/mol] % 16.8f [kJ/mol]\n" %
("Dispersion", saptd_en['DISP'] * units[0],
saptd_en['DISP'] * units[1], saptd_en['DISP'] * units[2]))
core.print_out(
" %-27s % 16.8f [mEh] % 16.8f [kcal/mol] % 16.8f [kJ/mol]\n" %
("Total " + saptd_name + "-D", total * units[0], total * units[1],
total * units[2]))
core.print_out(" " + "-" * 104 + "\n")
if saptd_name == "FISAPT0":
pw_disp = dimer_wfn.variable("PAIRWISE DISPERSION CORRECTION ANALYSIS")
pw_disp.name = 'Empirical_Disp'
filepath = core.get_option("FISAPT", "FISAPT_FSAPT_FILEPATH")
fisapt_proc._drop(pw_disp, filepath)
return dimer_wfn
def print_ci_results(ciwfn, rname, scf_e, ci_e, print_opdm_no=False):
"""
Printing for all CI Wavefunctions
"""
# Print out energetics
core.print_out("\n ==> Energetics <==\n\n")
core.print_out(" SCF energy = %20.15f\n" % scf_e)
if "CI" in rname:
core.print_out(" Total CI energy = %20.15f\n" % ci_e)
elif "MP" in rname:
core.print_out(" Total MP energy = %20.15f\n" % ci_e)
elif "ZAPT" in rname:
core.print_out(" Total ZAPT energy = %20.15f\n" % ci_e)
else:
core.print_out(" Total MCSCF energy = %20.15f\n" % ci_e)
# Nothing to be done for ZAPT or MP
if ("MP" in rname) or ("ZAPT" in rname):
core.print_out("\n")
return
# Initial info
ci_nroots = core.get_option("DETCI", "NUM_ROOTS")
irrep_labels = ciwfn.molecule().irrep_labels()
# Grab the D-vector
dvec = ciwfn.D_vector()
dvec.init_io_files(True)
for root in range(ci_nroots):
core.print_out("\n ==> %s root %d information <==\n\n" % (rname, root))
# Print total energy
root_e = core.variable("CI ROOT %d TOTAL ENERGY" % (root))
core.print_out(" %s Root %d energy = %20.15f\n" % (rname, root, root_e))
# Print natural occupations
if print_opdm_no:
core.print_out("\n Active Space Natural occupation numbers:\n\n")
occs_list = []
r_opdm = ciwfn.get_opdm(root, root, "SUM", False)
for h in range(len(r_opdm.nph)):
if 0 in r_opdm.nph[h].shape:
continue
nocc, rot = np.linalg.eigh(r_opdm.nph[h])
for e in nocc:
occs_list.append((e, irrep_labels[h]))
occs_list.sort(key=lambda x: -x[0])
cnt = 0
for value, label in occs_list:
value, label = occs_list[cnt]
core.print_out(" %4s % 8.6f" % (label, value))
cnt += 1
if (cnt % 3) == 0:
core.print_out("\n")
if (cnt % 3):
core.print_out("\n")
# Print CIVector information
ciwfn.print_vector(dvec, root)
# True to keep the file
dvec.close_io_files(True)
def database(name, db_name, **kwargs):
r"""Function to access the molecule objects and reference energies of
popular chemical databases.
:aliases: db()
:returns: (*float*) Mean absolute deviation of the database in kcal/mol
:PSI variables:
.. hlist::
:columns: 1
* :psivar:`db_name DATABASE MEAN SIGNED DEVIATION`
* :psivar:`db_name DATABASE MEAN ABSOLUTE DEVIATION`
* :psivar:`db_name DATABASE ROOT-MEAN-SQUARE DEVIATION`
* Python dictionaries of results accessible as ``DB_RGT`` and ``DB_RXN``.
.. note:: It is very easy to make a database from a collection of xyz files
using the script :source:`psi4/share/psi4/scripts/ixyz2database.py`.
See :ref:`sec:createDatabase` for details.
.. caution:: Some features are not yet implemented. Buy a developer some coffee.
- In sow/reap mode, use only global options (e.g., the local option set by ``set scf scf_type df`` will not be respected).
.. note:: To access a database that is not embedded in a |PSIfour|
distribution, add the path to the directory containing the database
to the environment variable :envvar:`PYTHONPATH`.
:type name: str
:param name: ``'scf'`` || ``'sapt0'`` || ``'ccsd(t)'`` || etc.
First argument, usually unlabeled. Indicates the computational method
to be applied to the database. May be any valid argument to
:py:func:`psi4.driver.energy`.
:type db_name: str
:param db_name: ``'BASIC'`` || ``'S22'`` || ``'HTBH'`` || etc.
Second argument, usually unlabeled. Indicates the requested database
name, matching (case insensitive) the name of a python file in
``psi4/share/databases`` or :envvar:`PYTHONPATH`. Consult that
directory for available databases and literature citations.
:type func: :ref:`function <op_py_function>`
:param func: |dl| ``energy`` |dr| || ``optimize`` || ``cbs``
Indicates the type of calculation to be performed on each database
member. The default performs a single-point ``energy('name')``, while
``optimize`` perfoms a geometry optimization on each reagent, and
``cbs`` performs a compound single-point energy. If a nested series
of python functions is intended (see :ref:`sec:intercalls`), use
keyword ``db_func`` instead of ``func``.
:type mode: str
:param mode: |dl| ``'continuous'`` |dr| || ``'sow'`` || ``'reap'``
Indicates whether the calculations required to complete the
database are to be run in one file (``'continuous'``) or are to be
farmed out in an embarrassingly parallel fashion
(``'sow'``/``'reap'``). For the latter, run an initial job with
``'sow'`` and follow instructions in its output file.
:type cp: :ref:`boolean <op_py_boolean>`
:param cp: ``'on'`` || |dl| ``'off'`` |dr|
Indicates whether counterpoise correction is employed in computing
interaction energies. Use this option and NOT the ``bsse_type="cp"``
function for BSSE correction in database(). Option available
(See :ref:`sec:availableDatabases`) only for databases of bimolecular complexes.
:type rlxd: :ref:`boolean <op_py_boolean>`
:param rlxd: ``'on'`` || |dl| ``'off'`` |dr|
Indicates whether correction for deformation energy is
employed in computing interaction energies. Option available
(See :ref:`sec:availableDatabases`) only for databases of bimolecular complexes
with non-frozen monomers, e.g., HBC6.
:type symm: :ref:`boolean <op_py_boolean>`
:param symm: |dl| ``'on'`` |dr| || ``'off'``
Indicates whether the native symmetry of the database reagents is
employed (``'on'``) or whether it is forced to :math:`C_1` symmetry
(``'off'``). Some computational methods (e.g., SAPT) require no
symmetry, and this will be set by database().
:type zpe: :ref:`boolean <op_py_boolean>`
:param zpe: ``'on'`` || |dl| ``'off'`` |dr|
Indicates whether zero-point-energy corrections are appended to
single-point energy values. Option valid only for certain
thermochemical databases. Disabled until Hessians ready.
:type benchmark: str
:param benchmark: |dl| ``'default'`` |dr| || ``'S22A'`` || etc.
Indicates whether a non-default set of reference energies, if
available (See :ref:`sec:availableDatabases`), are employed for the
calculation of error statistics.
:type tabulate: List[str]
:param tabulate: |dl| ``[]`` |dr| || ``['scf total energy', 'natom']`` || etc.
Indicates whether to form tables of variables other than the
primary requested energy. Available for any PSI variable.
:type subset: Union[str, List[str]]
:param subset:
Indicates a subset of the full database to run. This is a very
flexible option and can be used in three distinct ways, outlined
below. Note that two take a string and the last takes an array.
See :ref:`sec:availableDatabases` for available values.
* ``'small'`` || ``'large'`` || ``'equilibrium'``
Calls predefined subsets of the requested database, either
``'small'``, a few of the smallest database members,
``'large'``, the largest of the database members, or
``'equilibrium'``, the equilibrium geometries for a database
composed of dissociation curves.
* ``'BzBz_S'`` || ``'FaOOFaON'`` || ``'ArNe'`` || ``'HB'`` || etc.
For databases composed of dissociation curves, or otherwise
divided into subsets, individual curves and subsets can be
called by name. Consult the database python files for available
molecular systems (case insensitive).
* ``[1,2,5]`` || ``['1','2','5']`` || ``['BzMe-3.5', 'MeMe-5.0']`` || etc.
Specify a list of database members to run. Consult the
database python files for available molecular systems. This
is the only portion of database input that is case sensitive;
choices for this keyword must match the database python file.
:examples:
>>> # [1] Two-stage SCF calculation on short, equilibrium, and long helium dimer
>>> db('scf','RGC10',cast_up='sto-3g',subset=['HeHe-0.85','HeHe-1.0','HeHe-1.5'], tabulate=['scf total energy','natom'])
>>> # [2] Counterpoise-corrected interaction energies for three complexes in S22
>>> # Error statistics computed wrt an old benchmark, S22A
>>> database('mp2','S22',cp=1,subset=[16,17,8],benchmark='S22A')
>>> # [3] SAPT0 on the neon dimer dissociation curve
>>> db('sapt0',subset='NeNe',cp=0,symm=0,db_name='RGC10')
>>> # [4] Optimize system 1 in database S22, producing tables of scf and mp2 energy
>>> db('mp2','S22',db_func=optimize,subset=[1], tabulate=['mp2 total energy','current energy'])
>>> # [5] CCSD on the smallest systems of HTBH, a hydrogen-transfer database
>>> database('ccsd','HTBH',subset='small', tabulate=['ccsd total energy', 'mp2 total energy'])
"""
lowername = name #TODO
kwargs = p4util.kwargs_lower(kwargs)
# Wrap any positional arguments into kwargs (for intercalls among wrappers)
if not ('name' in kwargs) and name:
kwargs['name'] = name #.lower()
if not ('db_name' in kwargs) and db_name:
kwargs['db_name'] = db_name
# Establish function to call
func = kwargs.pop('db_func', kwargs.pop('func', energy))
kwargs['db_func'] = func
# Bounce to CP if bsse kwarg (someday)
if kwargs.get('bsse_type', None) is not None:
raise ValidationError(
"""Database: Cannot specify bsse_type for database. Use the cp keyword withing database instead."""
)
allowoptexceeded = kwargs.get('allowoptexceeded', False)
optstash = p4util.OptionsState(['WRITER_FILE_LABEL'], ['SCF', 'REFERENCE'])
# Wrapper wholly defines molecule. discard any passed-in
kwargs.pop('molecule', None)
# Paths to search for database files: here + PSIPATH + library + PYTHONPATH
db_paths = []
db_paths.append(os.getcwd())
db_paths.extend(os.environ.get('PSIPATH', '').split(os.path.pathsep))
db_paths.append(os.path.join(core.get_datadir(), 'databases'))
db_paths.append(os.path.dirname(__file__))
db_paths = list(map(os.path.abspath, db_paths))
sys.path[1:1] = db_paths
# TODO this should be modernized a la interface_cfour
# Define path and load module for requested database
database = p4util.import_ignorecase(db_name)
if database is None:
core.print_out('\nPython module for database %s failed to load\n\n' %
(db_name))
core.print_out('\nSearch path that was tried:\n')
core.print_out(", ".join(map(str, sys.path)))
raise ValidationError("Python module loading problem for database " +
str(db_name))
else:
dbse = database.dbse
HRXN = database.HRXN
ACTV = database.ACTV
RXNM = database.RXNM
BIND = database.BIND
TAGL = database.TAGL
GEOS = database.GEOS
try:
DATA = database.DATA
except AttributeError:
DATA = {}
user_writer_file_label = core.get_global_option('WRITER_FILE_LABEL')
user_reference = core.get_global_option('REFERENCE')
# Configuration based upon e_name & db_name options
# Force non-supramolecular if needed
if not hasattr(lowername, '__call__') and re.match(r'^.*sapt', lowername):
try:
database.ACTV_SA
except AttributeError:
raise ValidationError(
'Database %s not suitable for non-supramolecular calculation.'
% (db_name))
else:
ACTV = database.ACTV_SA
# Force open-shell if needed
openshell_override = 0
if user_reference in ['RHF', 'RKS']:
try:
database.isOS
except AttributeError:
pass
else:
if p4util.yes.match(str(database.isOS)):
openshell_override = 1
core.print_out(
'\nSome reagents in database %s require an open-shell reference; will be reset to UHF/UKS as needed.\n'
% (db_name))
# Configuration based upon database keyword options
# Option symmetry- whether symmetry treated normally or turned off (currently req'd for dfmp2 & dft)
db_symm = kwargs.get('symm', True)
symmetry_override = 0
if db_symm is False:
symmetry_override = 1
elif db_symm is True:
pass
else:
raise ValidationError("""Symmetry mode '%s' not valid.""" % (db_symm))
# Option mode of operation- whether db run in one job or files farmed out
db_mode = kwargs.pop('db_mode', kwargs.pop('mode', 'continuous')).lower()
kwargs['db_mode'] = db_mode
if db_mode == 'continuous':
pass
elif db_mode == 'sow':
pass
elif db_mode == 'reap':
db_linkage = kwargs.get('linkage', None)
if db_linkage is None:
raise ValidationError(
"""Database execution mode 'reap' requires a linkage option."""
)
else:
raise ValidationError("""Database execution mode '%s' not valid.""" %
(db_mode))
# Option counterpoise- whether for interaction energy databases run in bsse-corrected or not
db_cp = kwargs.get('cp', False)
if db_cp is True:
try:
database.ACTV_CP
except AttributeError:
raise ValidationError(
"""Counterpoise correction mode 'yes' invalid for database %s."""
% (db_name))
else:
ACTV = database.ACTV_CP
elif db_cp is False:
pass
else:
raise ValidationError(
"""Counterpoise correction mode '%s' not valid.""" % (db_cp))
# Option relaxed- whether for non-frozen-monomer interaction energy databases include deformation correction or not?
db_rlxd = kwargs.get('rlxd', False)
if db_rlxd is True:
if db_cp is True:
try:
database.ACTV_CPRLX
database.RXNM_CPRLX
except AttributeError:
raise ValidationError(
'Deformation and counterpoise correction mode \'yes\' invalid for database %s.'
% (db_name))
else:
ACTV = database.ACTV_CPRLX
RXNM = database.RXNM_CPRLX
elif db_cp is False:
try:
database.ACTV_RLX
except AttributeError:
raise ValidationError(
'Deformation correction mode \'yes\' invalid for database %s.'
% (db_name))
else:
ACTV = database.ACTV_RLX
elif db_rlxd is False:
#elif no.match(str(db_rlxd)):
pass
else:
raise ValidationError('Deformation correction mode \'%s\' not valid.' %
(db_rlxd))
# Option zero-point-correction- whether for thermochem databases jobs are corrected by zpe
db_zpe = kwargs.get('zpe', False)
if db_zpe is True:
raise ValidationError(
'Zero-point-correction mode \'yes\' not yet implemented.')
elif db_zpe is False:
pass
else:
raise ValidationError('Zero-point-correction \'mode\' %s not valid.' %
(db_zpe))
# Option benchmark- whether error statistics computed wrt alternate reference energies
db_benchmark = 'default'
if 'benchmark' in kwargs:
db_benchmark = kwargs['benchmark']
if db_benchmark.lower() == 'default':
pass
else:
BIND = p4util.getattr_ignorecase(database, 'BIND_' + db_benchmark)
if BIND is None:
raise ValidationError(
'Special benchmark \'%s\' not available for database %s.' %
(db_benchmark, db_name))
# Option tabulate- whether tables of variables other than primary energy method are formed
# TODO db(func=cbs,tabulate=[non-current-energy]) # broken
db_tabulate = []
if 'tabulate' in kwargs:
db_tabulate = kwargs['tabulate']
# Option subset- whether all of the database or just a portion is run
db_subset = HRXN
if 'subset' in kwargs:
db_subset = kwargs['subset']
if isinstance(db_subset, (str, bytes)):
if db_subset.lower() == 'small':
try:
database.HRXN_SM
except AttributeError:
raise ValidationError(
"""Special subset 'small' not available for database %s."""
% (db_name))
else:
HRXN = database.HRXN_SM
elif db_subset.lower() == 'large':
try:
database.HRXN_LG
except AttributeError:
raise ValidationError(
"""Special subset 'large' not available for database %s."""
% (db_name))
else:
HRXN = database.HRXN_LG
elif db_subset.lower() == 'equilibrium':
try:
database.HRXN_EQ
except AttributeError:
raise ValidationError(
"""Special subset 'equilibrium' not available for database %s."""
% (db_name))
else:
HRXN = database.HRXN_EQ
else:
HRXN = p4util.getattr_ignorecase(database, db_subset)
if HRXN is None:
HRXN = p4util.getattr_ignorecase(database, 'HRXN_' + db_subset)
if HRXN is None:
raise ValidationError(
"""Special subset '%s' not available for database %s."""
% (db_subset, db_name))
else:
temp = []
for rxn in db_subset:
if rxn in HRXN:
temp.append(rxn)
else:
raise ValidationError(
"""Subset element '%s' not a member of database %s.""" %
(str(rxn), db_name))
HRXN = temp
temp = []
for rxn in HRXN:
temp.append(ACTV['%s-%s' % (dbse, rxn)])
HSYS = p4util.drop_duplicates(sum(temp, []))
# Sow all the necessary reagent computations
core.print_out("\n\n")
p4util.banner(("Database %s Computation" % (db_name)))
core.print_out("\n")
# write index of calcs to output file
instructions = """\n The database single-job procedure has been selected through mode='continuous'.\n"""
instructions += """ Calculations for the reagents will proceed in the order below and will be followed\n"""
instructions += """ by summary results for the database.\n\n"""
for rgt in HSYS:
instructions += """ %-s\n""" % (rgt)
core.print_out(instructions)
# Loop through chemical systems
ERGT = {}
ERXN = {}
VRGT = {}
VRXN = {}
for rgt in HSYS:
VRGT[rgt] = {}
core.print_out('\n')
p4util.banner(' Database {} Computation: Reagent {} \n {}'.format(
db_name, rgt, TAGL[rgt]))
core.print_out('\n')
molecule = core.Molecule.from_dict(GEOS[rgt].to_dict())
molecule.set_name(rgt)
molecule.update_geometry()
if symmetry_override:
molecule.reset_point_group('c1')
molecule.fix_orientation(True)
molecule.fix_com(True)
molecule.update_geometry()
if (openshell_override) and (molecule.multiplicity() != 1):
if user_reference == 'RHF':
core.set_global_option('REFERENCE', 'UHF')
elif user_reference == 'RKS':
core.set_global_option('REFERENCE', 'UKS')
core.set_global_option(
'WRITER_FILE_LABEL', user_writer_file_label +
('' if user_writer_file_label == '' else '-') + rgt)
if allowoptexceeded:
try:
ERGT[rgt] = func(molecule=molecule, **kwargs)
except ConvergenceError:
core.print_out(f"Optimization exceeded cycles for {rgt}")
ERGT[rgt] = 0.0
else:
ERGT[rgt] = func(molecule=molecule, **kwargs)
core.print_variables()
core.print_out(" Database Contributions Map:\n {}\n".format('-' *
75))
for rxn in HRXN:
db_rxn = dbse + '-' + str(rxn)
if rgt in ACTV[db_rxn]:
core.print_out(
' reagent {} contributes by {:.4f} to reaction {}\n'.
format(rgt, RXNM[db_rxn][rgt], db_rxn))
core.print_out('\n')
for envv in db_tabulate:
VRGT[rgt][envv.upper()] = core.variable(envv)
core.set_global_option("REFERENCE", user_reference)
core.clean()
#core.opt_clean()
core.clean_variables()
# Reap all the necessary reaction computations
core.print_out("\n")
p4util.banner(("Database %s Results" % (db_name)))
core.print_out("\n")
maxactv = []
for rxn in HRXN:
maxactv.append(len(ACTV[dbse + '-' + str(rxn)]))
maxrgt = max(maxactv)
table_delimit = '-' * (62 + 20 * maxrgt)
tables = ''
# find any reactions that are incomplete
FAIL = collections.defaultdict(int)
for rxn in HRXN:
db_rxn = dbse + '-' + str(rxn)
for i in range(len(ACTV[db_rxn])):
if abs(ERGT[ACTV[db_rxn][i]]) < 1.0e-12:
if not allowoptexceeded:
FAIL[rxn] = 1
# tabulate requested process::environment variables
tables += """ For each VARIABLE requested by tabulate, a 'Reaction Value' will be formed from\n"""
tables += """ 'Reagent' values according to weightings 'Wt', as for the REQUESTED ENERGY below.\n"""
tables += """ Depending on the nature of the variable, this may or may not make any physical sense.\n"""
for rxn in HRXN:
db_rxn = dbse + '-' + str(rxn)
VRXN[db_rxn] = {}
for envv in db_tabulate:
envv = envv.upper()
tables += """\n ==> %s <==\n\n""" % (envv.title())
tables += _tblhead(maxrgt, table_delimit, 2)
for rxn in HRXN:
db_rxn = dbse + '-' + str(rxn)
if FAIL[rxn]:
tables += """\n%23s %8s %8s %8s %8s""" % (db_rxn, '', '****',
'', '')
for i in range(len(ACTV[db_rxn])):
tables += """ %16.8f %2.0f""" % (VRGT[
ACTV[db_rxn][i]][envv], RXNM[db_rxn][ACTV[db_rxn][i]])
else:
VRXN[db_rxn][envv] = 0.0
for i in range(len(ACTV[db_rxn])):
VRXN[db_rxn][envv] += VRGT[
ACTV[db_rxn][i]][envv] * RXNM[db_rxn][ACTV[db_rxn][i]]
tables += """\n%23s %16.8f """ % (
db_rxn, VRXN[db_rxn][envv])
for i in range(len(ACTV[db_rxn])):
tables += """ %16.8f %2.0f""" % (VRGT[
ACTV[db_rxn][i]][envv], RXNM[db_rxn][ACTV[db_rxn][i]])
tables += """\n %s\n""" % (table_delimit)
# tabulate primary requested energy variable with statistics
count_rxn = 0
minDerror = 100000.0
maxDerror = 0.0
MSDerror = 0.0
MADerror = 0.0
RMSDerror = 0.0
tables += """\n ==> %s <==\n\n""" % ('Requested Energy')
tables += _tblhead(maxrgt, table_delimit, 1)
for rxn in HRXN:
db_rxn = dbse + '-' + str(rxn)
if FAIL[rxn]:
tables += """\n%23s %8.4f %8s %10s %10s""" % (
db_rxn, BIND[db_rxn], '****', '****', '****')
for i in range(len(ACTV[db_rxn])):
tables += """ %16.8f %2.0f""" % (ERGT[ACTV[db_rxn][i]],
RXNM[db_rxn][ACTV[db_rxn][i]])
else:
ERXN[db_rxn] = 0.0
for i in range(len(ACTV[db_rxn])):
ERXN[db_rxn] += ERGT[ACTV[db_rxn][i]] * RXNM[db_rxn][
ACTV[db_rxn][i]]
error = constants.hartree2kcalmol * ERXN[db_rxn] - BIND[db_rxn]
tables += """\n%23s %8.4f %8.4f %10.4f %10.4f""" % (
db_rxn, BIND[db_rxn], constants.hartree2kcalmol * ERXN[db_rxn],
error, error * constants.cal2J)
for i in range(len(ACTV[db_rxn])):
tables += """ %16.8f %2.0f""" % (ERGT[ACTV[db_rxn][i]],
RXNM[db_rxn][ACTV[db_rxn][i]])
if abs(error) < abs(minDerror):
minDerror = error
if abs(error) > abs(maxDerror):
maxDerror = error
MSDerror += error
MADerror += abs(error)
RMSDerror += error * error
count_rxn += 1
tables += """\n %s\n""" % (table_delimit)
if count_rxn:
MSDerror /= float(count_rxn)
MADerror /= float(count_rxn)
RMSDerror = math.sqrt(RMSDerror / float(count_rxn))
tables += """%23s %19s %10.4f %10.4f\n""" % (
'Minimal Dev', '', minDerror, minDerror * constants.cal2J)
tables += """%23s %19s %10.4f %10.4f\n""" % (
'Maximal Dev', '', maxDerror, maxDerror * constants.cal2J)
tables += """%23s %19s %10.4f %10.4f\n""" % (
'Mean Signed Dev', '', MSDerror, MSDerror * constants.cal2J)
tables += """%23s %19s %10.4f %10.4f\n""" % (
'Mean Absolute Dev', '', MADerror, MADerror * constants.cal2J)
tables += """%23s %19s %10.4f %10.4f\n""" % (
'RMS Dev', '', RMSDerror, RMSDerror * constants.cal2J)
tables += """ %s\n""" % (table_delimit)
core.set_variable('%s DATABASE MEAN SIGNED DEVIATION' % (db_name),
MSDerror)
core.set_variable('%s DATABASE MEAN ABSOLUTE DEVIATION' % (db_name),
MADerror)
core.set_variable('%s DATABASE ROOT-MEAN-SQUARE DEVIATION' % (db_name),
RMSDerror)
core.print_out(tables)
finalenergy = MADerror
else:
finalenergy = 0.0
optstash.restore()
DB_RGT.clear()
DB_RGT.update(VRGT)
DB_RXN.clear()
DB_RXN.update(VRXN)
return finalenergy