def run_cis(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
cis can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('cis')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
psi4.core.set_local_option('MYPLUGIN', 'PRINT', 1)
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
print('Attention! This SCF may be density-fitted.')
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Ensure IWL files have been written when not using DF/CD
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option('SCF', 'SCF_TYPE'), ref_wfn)
# Call the Psi4 plugin
# Please note that setting the reference wavefunction in this way is ONLY for plugins
cis_wfn = psi4.core.plugin('cis.so', ref_wfn)
return cis_wfn
def run_mydft(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
mydft can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('mydft')
"""
#lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
scf_wfn = kwargs.get('ref_wfn', None)
if scf_wfn is None:
func = psi4.core.get_option('MYDFT', 'FUNCTIONAL')
scf_molecule = kwargs.get('molecule', psi4.core.get_active_molecule())
base_wfn = psi4.core.Wavefunction.build(
scf_molecule, psi4.core.get_global_option('BASIS'))
scf_wfn = proc.scf_wavefunction_factory(
func, base_wfn, psi4.core.get_option('SCF', 'REFERENCE'))
# Ensure IWL files have been written when not using DF/CD
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option('SCF', 'SCF_TYPE'), scf_wfn)
# Call the Psi4 plugin
# Please note that setting the reference wavefunction in this way is ONLY for plugins
mydft_wfn = psi4.core.plugin('mydft.so', scf_wfn)
return mydft_wfn
def run_cct3(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
cct3 can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('cct3')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
optstash = p4util.OptionsState(['CCT3', 'CALC_TYPE'])
# Your plugin's psi4 run sequence goes here
if lowername == "cct3":
pass
elif lowername == "ccsd":
psi4.core.set_local_option("CCT3", "CALC_TYPE", "CCSD")
elif lowername == "cr-cc(2,3)":
psi4.core.set_local_option("CCT3", "CALC_TYPE", "CR-CC")
elif lowername == "ccsd_lct": # CCSDt
psi4.core.set_local_option("CCT3", "CALC_TYPE", "CCSD3A")
elif lowername == "cc(t;3)":
psi4.core.set_local_option("CCT3", "CALC_TYPE", "CCT3")
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Ensure IWL files have been written when not using DF/CD
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option('SCF', 'SCF_TYPE'), ref_wfn)
# Call the Psi4 plugin
# Please note that setting the reference wavefunction in this way is ONLY for plugins
cct3_wfn = psi4.core.plugin('cct3.so', ref_wfn)
try:
cct3_wfn.set_module("cct3")
except AttributeError:
pass # pre-July 2020 psi4
# Shove variables into global space
for k, v in cct3_wfn.variables().items():
psi4.core.set_variable(k, v)
optstash.restore()
return cct3_wfn
def run_mcpdft(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
mcpdft can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('mcpdft')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
psi4.core.set_local_option('SCF', 'DF_INTS_IO', 'SAVE')
v2rdm_wfn = kwargs.get('ref_wfn', None)
if v2rdm_wfn is None:
raise ValidationError(
"""Error: %s requires a reference wave function (v2rdm-casscf)."""
% name)
psi4.core.set_variable("V2RDM TOTAL ENERGY", v2rdm_wfn.energy())
if ((psi4.core.get_option('MCPDFT', 'MCPDFT_METHOD') == '1DH_MCPDFT') or
(psi4.core.get_option('MCPDFT', 'MCPDFT_METHOD') == 'LS1DH_MCPDFT')):
proc.run_dfmp2('mp2', **kwargs)
if ('WBLYP' == psi4.core.get_option('MCPDFT', 'MCPDFT_FUNCTIONAL')):
func = 'BLYP'
else:
func = psi4.core.get_option('MCPDFT', 'MCPDFT_FUNCTIONAL')
ref_molecule = kwargs.get('molecule', psi4.core.get_active_molecule())
base_wfn = psi4.core.Wavefunction.build(
ref_molecule, psi4.core.get_global_option('BASIS'))
ref_wfn = proc.scf_wavefunction_factory(
func, base_wfn, psi4.core.get_option('MCPDFT', 'REFERENCE'))
# push v2rdm-casscf orbitals onto reference
for irrep in range(0, v2rdm_wfn.Ca().nirrep()):
ref_wfn.Ca().nph[irrep][:, :] = v2rdm_wfn.Ca().nph[irrep][:, :]
ref_wfn.Cb().nph[irrep][:, :] = v2rdm_wfn.Cb().nph[irrep][:, :]
# push v2rdm-casscf energies onto reference
for irrep in range(0, v2rdm_wfn.epsilon_a().nirrep()):
ref_wfn.epsilon_a().nph[irrep][:] = v2rdm_wfn.epsilon_a().nph[irrep][:]
ref_wfn.epsilon_b().nph[irrep][:] = v2rdm_wfn.epsilon_b().nph[irrep][:]
# Call the Psi4 plugin
# Please note that setting the reference wavefunction in this way is ONLY for plugins
mcpdft_wfn = psi4.core.plugin('mcpdft.so', ref_wfn)
return mcpdft_wfn
def run_scf_plug(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
scf_plug can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('scf_plug')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
psi4.core.set_local_option('MYPLUGIN', 'PRINT', 1)
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
print('Attention! This SCF may be density-fitted.')
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Ensure IWL files have been written when not using DF/CD
# proc_util.check_iwl_file_from_scf_type(psi4.core.get_option('SCF', 'SCF_TYPE'), ref_wfn)
# analytic derivatives do not work with scf_type df/cd
scf_type = psi4.core.get_option('SCF', 'SCF_TYPE')
if ( scf_type == 'CD' or scf_type == 'DF' ):
raise ValidationError("""Error: analytic gradients not implemented for scf_type %s.""" % scf_type)
# Call the Psi4 plugin
# Please note that setting the reference wavefunction in this way is ONLY for plugins
scf_plug_wfn = psi4.core.plugin('scf_plug.so', ref_wfn)
print(scf_plug_wfn)
print(ref_wfn)
derivobj = psi4.core.Deriv(scf_plug_wfn)
derivobj.set_deriv_density_backtransformed(True)
derivobj.set_ignore_reference(True)
grad = derivobj.compute()
scf_plug_wfn.set_gradient(grad)
return scf_plug_wfn
def run_rhf_dlmg2b(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
rhf_dlmg2b can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('rhf_dlmg2b')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
psi4.core.set_local_option('MYPLUGIN', 'PRINT', 1)
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
print('Attention! This SCF may be density-fitted.')
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Ensure IWL files have been written when not using DF/CD
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option('SCF', 'SCF_TYPE'), ref_wfn)
# Call the Psi4 plugin
psi4.core.set_global_option('GUESS', 'READ')
optstash = p4util.OptionsState(['E_CONVERGENCE'])
psi4.core.set_global_option('E_CONVERGENCE', 1492.)
# Please note that setting the reference wavefunction in this way is ONLY for plugins
vac_wfn = psi4.core.plugin('rhf_dlmg2b.so', ref_wfn)
# Vacuum wfn has been returned. Start solvent calc
psi4.core.set_local_option('RHF_DLMG2B', 'eps',
psi4.core.get_option('RHF_DLMG2B', 'eps_sol'))
# If eps_sol set to zero, return vacuum wfn
test_eps = psi4.core.get_option('RHF_DLMG2B', 'eps_sol')
optstash.restore()
if (test_eps == 0.0):
print("Vac_wfn being returned now")
return vac_wfn
# Do solvent scf
sol_wfn = psi4.core.plugin('rhf_dlmg2b.so', vac_wfn)
kwargs['ref_wfn'] = sol_wfn
return sol_wfn
def run_v2rdm_casscf_gradient(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
v2rdm_casscf can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> gradient('v2rdm_casscf')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
optstash = p4util.OptionsState(
['GLOBALS', 'DERTYPE'], ['V2RDM_CASSCF', 'OPTIMIZE_ORBITALS'],
['V2RDM_CASSCF', 'SEMICANONICALIZE_ORBITALS'],
['V2RDM_CASSCF', 'ORBOPT_ACTIVE_ACTIVE_ROTATIONS'],
['V2RDM_CASSCF', 'RESTART_FROM_CHECKPOINT_FILE'],
['V2RDM_CASSCF', 'WRITE_CHECKPOINT_FILE'])
psi4.core.set_global_option('DERTYPE', 'FIRST')
psi4.core.set_local_option("V2RDM_CASSCF", "OPTIMIZE_ORBITALS", True)
psi4.core.set_local_option("V2RDM_CASSCF",
"ORBOPT_ACTIVE_ACTIVE_ROTATIONS", True)
psi4.core.set_local_option("V2RDM_CASSCF", "SEMICANONICALIZE_ORBITALS",
False)
psi4.core.set_local_option("V2RDM_CASSCF", "RESTART_FROM_CHECKPOINT_FILE",
"DUMMY")
psi4.core.set_local_option("V2RDM_CASSCF", "WRITE_CHECKPOINT_FILE", True)
# analytic derivatives do not work with scf_type df/cd
scf_type = psi4.core.get_option('SCF', 'SCF_TYPE')
if (scf_type == 'CD' or scf_type == 'DF'):
raise ValidationError(
"""Error: analytic v2RDM-CASSCF gradients not implemented for scf_type %s."""
% scf_type)
v2rdm_wfn = run_v2rdm_casscf(name, **kwargs)
derivobj = psi4.core.Deriv(v2rdm_wfn)
derivobj.set_deriv_density_backtransformed(True)
derivobj.set_ignore_reference(True)
grad = derivobj.compute()
v2rdm_wfn.set_gradient(grad)
optstash.restore()
return v2rdm_wfn
def run_mean_field_cqed(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
mean_field_cqed can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('mean_field_cqed')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
mean_field_cqed_wfn = psi4.core.plugin('mean_field_cqed.so', ref_wfn)
return mean_field_cqed_wfn
def run_fcidump(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
fcidump can be called via :py:func:`~driver.energy`.
>>> energy('fcidump')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
proc_util.check_iwl_file_from_scf_type(psi4.core.get_option('SCF', 'SCF_TYPE'), ref_wfn)
test_wfn = psi4.core.plugin('fcidump.so', ref_wfn)
return test_wfn
def run_v2rdm_casscf(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
v2rdm_casscf can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('v2rdm_casscf')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
optstash = p4util.OptionsState(['SCF', 'DF_INTS_IO'])
psi4.core.set_local_option('SCF', 'DF_INTS_IO', 'SAVE')
# Your plugin's psi4 run sequence goes here
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# if restarting from a checkpoint file, this file
# needs to be in scratch with the correct name
filename = psi4.core.get_option("V2RDM_CASSCF",
"RESTART_FROM_CHECKPOINT_FILE")
# todo PSIF_V2RDM_CHECKPOINT should be definied in psifiles.h
if (filename != "" and psi4.core.get_global_option('DERTYPE') != 'FIRST'):
molname = psi4.wavefunction().molecule().name()
p4util.copy_file_to_scratch(filename, 'psi', molname, 269, False)
# Ensure IWL files have been written when not using DF/CD
scf_type = psi4.core.get_option('SCF', 'SCF_TYPE')
if (scf_type == 'PK' or scf_type == 'DIRECT'):
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option('SCF', 'SCF_TYPE'), ref_wfn)
returnvalue = psi4.core.plugin('v2rdm_casscf.so', ref_wfn)
optstash.restore()
return returnvalue
def run_erpa(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
erpa can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('erpa')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
optstash = p4util.OptionsState(['SCF', 'DF_INTS_IO'])
# psi4.core.set_local_option('SCF', 'DF_INTS_IO', 'SAVE')
erpa_corr_global = psi4.core.get_option('ERPA', 'ERPA_CORRELATION')
erpa_corr_local = psi4.core.get_global_option('ERPA_CORRELATION')
if not erpa_corr_global and not erpa_corr_local:
nat_orbs_global = psi4.core.get_option('V2RDM_CASSCF', 'NAT_ORBS')
nat_orbs_local = psi4.core.get_global_option('NAT_ORBS')
if not nat_orbs_global and not nat_orbs_local:
raise psi4.ValidationError(
"""ERPA requires that the V2RDM_CASSCF option "nat_orbs" be set to true."""
)
# Your plugin's psi4 run sequence goes here
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Ensure IWL files have been written when not using DF/CD
scf_type = psi4.core.get_option('SCF', 'SCF_TYPE')
if (scf_type == 'PK' or scf_type == 'DIRECT'):
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option('SCF', 'SCF_TYPE'), ref_wfn)
returnvalue = psi4.core.plugin('erpa.so', ref_wfn)
# optstash.restore()
return returnvalue
def run_ugacc(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
ugacc can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('ugacc')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
if ('wfn' in kwargs):
if (kwargs['wfn'] == 'ccsd'):
psi4.core.set_global_option('WFN', 'CCSD')
elif (kwargs['wfn'] == 'ccsd(t)'):
psi4.core.set_global_option('WFN', 'CCSD_T')
scf_wfn = kwargs.get('ref_wfn', None)
if scf_wfn is None:
scf_wfn = psi4.driver.scf_helper(name, **kwargs)
proc_util.check_iwl_file_from_scf_type(psi4.core.get_option('SCF', 'SCF_TYPE'), scf_wfn)
return psi4.core.plugin('ugacc.so', scf_wfn)
def run_libresponse_psi4(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
libresponse_psi4 can be called via :py:func:`~driver.energy`. For post-scf
plugins.
>>> energy('libresponse_psi4')
"""
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
psi4.core.set_local_option("MYPLUGIN", "PRINT", 1)
# The response density is asymmetric; need to build generalized
# J/K.
proc_util.check_non_symmetric_jk_density("libresponse")
# Disable symmetry, even for passed-in wavefunctions.
molecule = kwargs.get("molecule", None)
if molecule is None:
molecule = psi4.core.get_active_molecule()
molecule = disable_symmetry(molecule)
kwargs["molecule"] = molecule
# Compute a SCF reference, a wavefunction is return which holds the
# molecule used, orbitals Fock matrices, and more
ref_wfn = kwargs.get("ref_wfn", None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Ensure IWL files have been written when not using DF/CD
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option("SCF", "SCF_TYPE"), ref_wfn)
# Call the Psi4 plugin
# Please note that setting the reference wavefunction in this way is ONLY for plugins
libresponse_psi4_wfn = psi4.core.plugin("libresponse_psi4.so", ref_wfn)
return libresponse_psi4_wfn
def run_ccreorg(name, **kwargs):
"""Function encoding sequence of PSI module and plugin calls so that
ccreorg can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('ccreorg')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
if ('wfn' in kwargs):
if (kwargs['wfn'] == 'ccsd'):
psi4.core.set_global_option('WFN', 'CCSD')
elif (kwargs['wfn'] == 'ccsd(t)'):
psi4.core.set_global_option('WFN', 'CCSD_T')
scf_wfn = kwargs.get('ref_wfn', None)
if scf_wfn is None:
scf_wfn = psi4.driver.scf_helper(name, **kwargs)
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option('SCF', 'SCF_TYPE'), scf_wfn)
return psi4.core.plugin('ccreorg.so', scf_wfn)
def run_forte(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
forte can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('forte')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
psi4.core.set_local_option('MYPLUGIN', 'PRINT', 1)
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
if ('DF' in psi4.core.get_option('FORTE', 'INT_TYPE')):
aux_basis = psi4.core.BasisSet.build(
ref_wfn.molecule(), 'DF_BASIS_MP2',
psi4.core.get_global_option('DF_BASIS_MP2'), 'RIFIT',
psi4.core.get_global_option('BASIS'))
ref_wfn.set_basisset('DF_BASIS_MP2', aux_basis)
if (psi4.core.get_option('FORTE', 'MINAO_BASIS')):
minao_basis = psi4.core.BasisSet.build(
ref_wfn.molecule(), 'MINAO_BASIS',
psi4.core.get_option('FORTE', 'MINAO_BASIS'))
ref_wfn.set_basisset('MINAO_BASIS', minao_basis)
# Call the Psi4 plugin
# Please note that setting the reference wavefunction in this way is ONLY for plugins
forte_wfn = psi4.core.plugin('forte.so', ref_wfn)
return forte_wfn
def run_gpu_dfcc(name, **kwargs):
"""Function encoding sequence of PSI module calls for
a GPU-accelerated DF-CCSD(T) computation.
>>> energy('df-ccsd(t)')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# stash user options
optstash = p4util.OptionsState(['GPU_DFCC', 'COMPUTE_TRIPLES'],
['GPU_DFCC', 'DFCC'],
['GPU_DFCC', 'NAT_ORBS'],
['SCF', 'DF_INTS_IO'], ['SCF', 'SCF_TYPE'],
['GPU_DFCC', 'CC_TYPE'])
psi4.core.set_local_option('GPU_DFCC', 'DFCC', True)
psi4.core.set_local_option('GPU_DFCC', 'CC_TYPE', 'DF')
# throw an exception for open-shells
if (psi4.core.get_option('SCF', 'REFERENCE') != 'RHF'):
raise ValidationError("Error: %s requires \"reference rhf\"." %
lowername)
def set_cholesky_from(mtd_type):
type_val = core.get_global_option(mtd_type)
if type_val == 'CD':
core.set_local_option('GPU_DFCC', 'DF_BASIS_CC', 'CHOLESKY')
# Alter default algorithm
if not core.has_global_option_changed('SCF_TYPE'):
optstash.add_option(['SCF_TYPE'])
core.set_global_option('SCF_TYPE', 'CD')
core.print_out(""" SCF Algorithm Type (re)set to CD.\n""")
elif type_val == 'DF':
if core.get_option('GPU_DFCC', 'DF_BASIS_CC') == 'CHOLESKY':
core.set_local_option('GPU_DFCC', 'DF_BASIS_CC', '')
proc_util.check_disk_df(name.upper(), optstash)
else:
raise ValidationError("""Invalid type '%s' for DFCC""" % type_val)
# triples?
if (lowername == 'gpu-df-ccsd'):
psi4.core.set_local_option('GPU_DFCC', 'COMPUTE_TRIPLES', False)
set_cholesky_from('CC_TYPE')
if (lowername == 'gpu-df-ccsd(t)'):
psi4.core.set_local_option('GPU_DFCC', 'COMPUTE_TRIPLES', True)
set_cholesky_from('CC_TYPE')
if psi4.core.get_global_option('SCF_TYPE') not in ['CD', 'DISK_DF']:
raise ValidationError("""Invalid scf_type for DFCC.""")
# save DF or CD ints generated by SCF for use in CC
psi4.core.set_local_option('SCF', 'DF_INTS_IO', 'SAVE')
# psi4 run sequence
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, use_c1=True,
**kwargs) # C1 certified
else:
if ref_wfn.molecule().schoenflies_symbol() != 'c1':
raise ValidationError(
""" GPU-DFCC does not make use of molecular symmetry: """
""" reference wavefunction must be C1.\n""")
scf_aux_basis = psi4.core.BasisSet.build(
ref_wfn.molecule(),
"DF_BASIS_SCF",
psi4.core.get_option("SCF", "DF_BASIS_SCF"),
"JKFIT",
psi4.core.get_global_option('BASIS'),
puream=ref_wfn.basisset().has_puream())
ref_wfn.set_basisset("DF_BASIS_SCF", scf_aux_basis)
aux_basis = psi4.core.BasisSet.build(
ref_wfn.molecule(), "DF_BASIS_CC",
psi4.core.get_global_option("DF_BASIS_CC"), "RIFIT",
psi4.core.get_global_option("BASIS"))
ref_wfn.set_basisset("DF_BASIS_CC", aux_basis)
returnvalue = psi4.core.plugin('gpu_dfcc.so', ref_wfn)
# restore options
optstash.restore()
return returnvalue
def run_v2rdm_casscf(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
v2rdm_casscf can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('v2rdm_casscf')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
optstash = p4util.OptionsState(['SCF', 'DF_INTS_IO'])
psi4.core.set_local_option('SCF', 'DF_INTS_IO', 'SAVE')
# Your plugin's psi4 run sequence goes here
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# if restarting from a checkpoint file, this file
# needs to be in scratch with the correct name
filename = psi4.core.get_option("V2RDM_CASSCF",
"RESTART_FROM_CHECKPOINT_FILE")
# Ensure IWL files have been written when not using DF/CD
scf_type = psi4.core.get_option('SCF', 'SCF_TYPE')
if (scf_type == 'PK' or scf_type == 'DIRECT'):
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option('SCF', 'SCF_TYPE'), ref_wfn)
# reorder wavefuntions based on user input
# apply a list of 2x2 rotation matrices to the orbitals in the form of [irrep, orbital1, orbital2, theta]
# where an angle of 0 would do nothing and an angle of 90 would switch the two orbitals.
# the indices of irreps and orbitals start from 0
reorder_orbitals = psi4.core.get_option("V2RDM_CASSCF", "MCSCF_ROTATE")
for orbord in reorder_orbitals:
if type(orbord) != list:
raise psi4.p4util.PsiException(
"Each element of the orbtial rotate list requires 4 arguements (irrep, orb1, orb2, theta)."
)
if len(orbord) != 4:
raise psi4.p4util.PsiException(
"Each element of the orbtial rotate list requires 4 arguements (irrep, orb1, orb2, theta)."
)
irrep, orb1, orb2, theta = orbord
if irrep > ref_wfn.Ca().nirrep():
raise psi4.p4util.PsiException(
"REORDER_ORBITALS: Expression %s irrep number is larger than the number of irreps"
% (str(orbord)))
if max(orb1, orb2) > ref_wfn.Ca().coldim()[irrep]:
raise psi4.p4util.PsiException(
"REORDER_ORBITALS: Expression %s orbital number exceeds number of orbitals in irrep"
% (str(orbord)))
theta = numpy.deg2rad(theta)
x_a = ref_wfn.Ca().nph[irrep][:, orb1].copy()
y_a = ref_wfn.Ca().nph[irrep][:, orb2].copy()
xp_a = numpy.cos(theta) * x_a - numpy.sin(theta) * y_a
yp_a = numpy.sin(theta) * x_a + numpy.cos(theta) * y_a
ref_wfn.Ca().nph[irrep][:, orb1] = xp_a
ref_wfn.Ca().nph[irrep][:, orb2] = yp_a
x_b = ref_wfn.Ca().nph[irrep][:, orb1].copy()
y_b = ref_wfn.Ca().nph[irrep][:, orb2].copy()
xp_b = numpy.cos(theta) * x_b - numpy.sin(theta) * y_b
yp_b = numpy.sin(theta) * x_b + numpy.cos(theta) * y_b
ref_wfn.Ca().nph[irrep][:, orb1] = xp_b
ref_wfn.Ca().nph[irrep][:, orb2] = yp_b
returnvalue = psi4.core.plugin('v2rdm_casscf.so', ref_wfn)
optstash.restore()
return returnvalue
def ip_fitting(name,
omega_l=0.05,
omega_r=2.5,
omega_convergence=1.0e-3,
maxiter=20,
**kwargs):
"""Optimize DFT omega parameter for molecular system.
Parameters
----------
name : string or function
DFT functional string name or function defining functional
whose omega is to be optimized.
omega_l : float, optional
Minimum omega to be considered during fitting.
omega_r : float, optional
Maximum omega to be considered during fitting.
molecule : :ref:`molecule <op_py_molecule>`, optional
Target molecule (neutral) for which omega is to be tuned, if not last defined.
omega_convergence : float, optional
Threshold below which to consider omega converged. (formerly omega_tolerance)
maxiter : int, optional
Maximum number of iterations towards omega convergence.
Returns
-------
float
Optimal omega parameter.
"""
optstash = p4util.OptionsState(['SCF', 'REFERENCE'], ['SCF', 'GUESS'],
['SCF', 'DF_INTS_IO'], ['SCF', 'DFT_OMEGA'],
['DOCC'], ['SOCC'])
kwargs = p4util.kwargs_lower(kwargs)
# By default, do not read previous 180 orbitals file
read = False
read180 = ''
if 'read' in kwargs:
read = True
read180 = kwargs['read']
if core.get_option('SCF', 'REFERENCE') != 'UKS':
core.print_out(
""" Requested procedure `ip_fitting` runs further calculations with UKS reference.\n"""
)
core.set_local_option('SCF', 'REFERENCE', 'UKS')
# Make sure the molecule the user provided is the active one, and neutral
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
if molecule.molecular_charge() != 0:
raise ValidationError(
"""IP Fitting requires neutral molecule to start.""")
if molecule.schoenflies_symbol() != 'c1':
core.print_out(
""" Requested procedure `ip_fitting` does not make use of molecular symmetry: """
"""further calculations in C1 point group.\n""")
molecule = molecule.clone()
molecule.reset_point_group('c1')
molecule.update_geometry()
charge0 = molecule.molecular_charge()
mult0 = molecule.multiplicity()
# How many electrons are there?
N = 0
for A in range(molecule.natom()):
N += molecule.Z(A)
N -= charge0
N = int(N)
Nb = int((N - mult0 + 1) / 2)
Na = int(N - Nb)
# Work in the ot namespace for this procedure
core.IO.set_default_namespace("ot")
# Burn in to determine orbital eigenvalues
if read:
core.set_local_option("SCF", "GUESS", "READ")
copy_file_to_scratch(read180, 'psi', 'ot', 180)
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
E, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
banner='IP Fitting SCF: Burn-in',
**kwargs)
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
if not wfn.functional().is_x_lrc():
raise ValidationError(
"""Not sensible to optimize omega for non-long-range-correction functional."""
)
# Determine H**O, to determine mult1
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Na == Nb:
H**O = -Nb
elif Nb == 0:
H**O = Na
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
if E_a >= E_b:
H**O = Na
else:
H**O = -Nb
Na1 = Na
Nb1 = Nb
if H**O > 0:
Na1 -= 1
else:
Nb1 -= 1
charge1 = charge0 + 1
mult1 = Na1 - Nb1 + 1
omegas = []
E0s = []
E1s = []
kIPs = []
IPs = []
types = []
# Right endpoint
core.set_local_option('SCF', 'DFT_OMEGA', omega_r)
# Neutral
if read:
core.set_local_option("SCF", "GUESS", "READ")
p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
E0r, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
banner='IP Fitting SCF: Neutral, Right Endpoint',
**kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
E_HOMOr = E_HOMO
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
if read:
core.set_local_option("SCF", "GUESS", "READ")
p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
E1r = driver.energy('scf',
dft_functional=name,
molecule=molecule,
banner='IP Fitting SCF: Cation, Right Endpoint',
**kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IPr = E1r - E0r
kIPr = -E_HOMOr
delta_r = IPr - kIPr
if IPr > kIPr:
raise ValidationError(
"""\n***IP Fitting Error: Right Omega limit should have kIP > IP: {} !> {}"""
.format(kIPr, IPr))
omegas.append(omega_r)
types.append('Right Limit')
E0s.append(E0r)
E1s.append(E1r)
IPs.append(IPr)
kIPs.append(kIPr)
# Use previous orbitals from here out
core.set_local_option("SCF", "GUESS", "READ")
# Left endpoint
core.set_local_option('SCF', 'DFT_OMEGA', omega_l)
# Neutral
core.IO.change_file_namespace(180, "neutral", "ot")
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
core.set_global_option("DOCC", [Nb])
core.set_global_option("SOCC", [Na - Nb])
E0l, wfn = driver.energy('scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
banner='IP Fitting SCF: Neutral, Left Endpoint',
**kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
E_HOMOl = E_HOMO
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
core.IO.change_file_namespace(180, "cation", "ot")
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
core.set_global_option("DOCC", [Nb1])
core.set_global_option("SOCC", [Na1 - Nb1])
E1l = driver.energy('scf',
dft_functional=name,
molecule=molecule,
banner='IP Fitting SCF: Cation, Left Endpoint',
**kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IPl = E1l - E0l
kIPl = -E_HOMOl
delta_l = IPl - kIPl
if IPl < kIPl:
raise ValidationError(
"""\n***IP Fitting Error: Left Omega limit should have kIP < IP: {} !< {}"""
.format(kIPl, IPl))
omegas.append(omega_l)
types.append('Left Limit')
E0s.append(E0l)
E1s.append(E1l)
IPs.append(IPl)
kIPs.append(kIPl)
converged = False
repeat_l = 0
repeat_r = 0
for step in range(maxiter):
# Regula Falsi (modified)
if repeat_l > 1:
delta_l /= 2.0
if repeat_r > 1:
delta_r /= 2.0
omega = -(omega_r - omega_l) / (delta_r - delta_l) * delta_l + omega_l
core.set_local_option('SCF', 'DFT_OMEGA', omega)
# Neutral
core.IO.change_file_namespace(180, "neutral", "ot")
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
core.set_global_option("DOCC", [Nb])
core.set_global_option("SOCC", [Na - Nb])
E0, wfn = driver.energy(
'scf',
dft_functional=name,
return_wfn=True,
molecule=molecule,
banner='IP Fitting SCF: Neutral, Omega = {:11.3E}'.format(omega),
**kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
core.IO.change_file_namespace(180, "cation", "ot")
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
core.set_global_option("DOCC", [Nb1])
core.set_global_option("SOCC", [Na1 - Nb1])
E1 = driver.energy(
'scf',
dft_functional=name,
molecule=molecule,
banner='IP Fitting SCF: Cation, Omega = {:11.3E}'.format(omega),
**kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IP = E1 - E0
kIP = -E_HOMO
delta = IP - kIP
if kIP > IP:
omega_r = omega
E0r = E0
E1r = E1
IPr = IP
kIPr = kIP
delta_r = delta
repeat_r = 0
repeat_l += 1
else:
omega_l = omega
E0l = E0
E1l = E1
IPl = IP
kIPl = kIP
delta_l = delta
repeat_l = 0
repeat_r += 1
omegas.append(omega)
types.append('Regula-Falsi')
E0s.append(E0)
E1s.append(E1)
IPs.append(IP)
kIPs.append(kIP)
# Termination
if abs(omega_l - omega_r) < omega_convergence:
converged = True
break
core.IO.set_default_namespace("")
core.print_out("""\n ==> IP Fitting Results <==\n\n""")
core.print_out(""" => Occupation Determination <= \n\n""")
core.print_out(""" %6s %6s %6s %6s %6s %6s\n""" %
('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
core.print_out(""" Neutral: %6d %6d %6d %6d %6d %6d\n""" %
(N, Na, Nb, charge0, mult0, H**O))
core.print_out(""" Cation: %6d %6d %6d %6d %6d\n\n""" %
(N - 1, Na1, Nb1, charge1, mult1))
core.print_out(""" => Regula Falsi Iterations <=\n\n""")
core.print_out(""" %3s %11s %14s %14s %14s %s\n""" %
('N', 'Omega', 'IP', 'kIP', 'Delta', 'Type'))
for k in range(len(omegas)):
core.print_out(
""" %3d %11.3E %14.6E %14.6E %14.6E %s\n""" %
(k + 1, omegas[k], IPs[k], kIPs[k], IPs[k] - kIPs[k], types[k]))
optstash.restore()
if converged:
core.print_out("""\n IP Fitting Converged\n""")
core.print_out(""" Final omega = %14.6E\n""" %
((omega_l + omega_r) / 2))
core.print_out(
"""\n "M,I. does the dying. Fleet just does the flying."\n""")
core.print_out(""" -Starship Troopers\n""")
else:
raise ConvergenceError("""IP Fitting """, step + 1)
return ((omega_l + omega_r) / 2)
def frac_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 run_forte(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
forte can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('forte')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Get the option object
options = psi4.core.get_options()
options.set_current_module('FORTE')
forte.forte_options.update_psi_options(options)
if ('DF' in options.get_str('INT_TYPE')):
aux_basis = psi4.core.BasisSet.build(ref_wfn.molecule(), 'DF_BASIS_MP2',
psi4.core.get_global_option('DF_BASIS_MP2'),
'RIFIT', psi4.core.get_global_option('BASIS'))
ref_wfn.set_basisset('DF_BASIS_MP2', aux_basis)
if (options.get_str('MINAO_BASIS')):
minao_basis = psi4.core.BasisSet.build(ref_wfn.molecule(), 'MINAO_BASIS',
options.get_str('MINAO_BASIS'))
ref_wfn.set_basisset('MINAO_BASIS', minao_basis)
# Start Forte, initialize ambit
my_proc_n_nodes = forte.startup()
my_proc, n_nodes = my_proc_n_nodes
# Print the banner
forte.banner()
# Create the MOSpaceInfo object
mo_space_info = forte.make_mo_space_info(ref_wfn, forte.forte_options)
# Call methods that project the orbitals (AVAS, embedding)
orbital_projection(ref_wfn, options)
state = forte.make_state_info_from_psi_wfn(ref_wfn)
scf_info = forte.SCFInfo(ref_wfn)
state_weights_map = forte.make_state_weights_map(forte.forte_options,ref_wfn)
# Run a method
job_type = options.get_str('JOB_TYPE')
energy = 0.0
if job_type == 'NONE':
forte.cleanup()
return ref_wfn
start = timeit.timeit()
# Make an integral object
ints = forte.make_forte_integrals(ref_wfn, options, mo_space_info)
# Rotate orbitals before computation
orb_type = options.get_str("ORBITAL_TYPE")
if orb_type != 'CANONICAL':
orb_t = forte.make_orbital_transformation(orb_type, scf_info, forte.forte_options, ints, mo_space_info)
orb_t.compute_transformation()
Ua = orb_t.get_Ua()
Ub = orb_t.get_Ub()
ints.rotate_orbitals(Ua,Ub)
# Run a method
if (job_type == 'NEWDRIVER'):
energy = forte_driver(state_weights_map, scf_info, forte.forte_options, ints, mo_space_info)
else:
energy = forte.forte_old_methods(ref_wfn, options, ints, mo_space_info)
end = timeit.timeit()
#print('\n\n Your calculation took ', (end - start), ' seconds');
# Close ambit, etc.
forte.cleanup()
psi4.core.set_scalar_variable('CURRENT ENERGY', energy)
return ref_wfn
def run_psi4fockci(name, molecule, **kwargs):
"""
A method to run a RAS-nSF-IP/EA calculation.
This runs a RAS-nSF-IP/EA calculation using Psi4's DETCI module. The
number of spin-flips and IP/EA is determined based on setting the
``new_charge`` and ``new_multiplicity`` of the desired target state.
Additional excitations are included by setting the ``conf_space``
keyword; excitations through the CISDT level are currently supported.
Parameters
----------
name : str
Name of method (for Psi4 interfacing)
molecule : psi4.core.Molecule
Molecule to run the calculation on.
new_charge : int
Target charge of the molecule.
new_multiplicity : int
Target multiplicity of the molecule.
conf_space : str ("")
Option for including additional excitations outside of the CAS space.
Defaults to CAS-nSF-IP/EA. Valid options include:
* ``""`` CAS-nSF-IP/EA
* ``"h"`` RAS(h)-nSF-IP/EA
* ``"p"`` RAS(p)-nSF-IP/EA
* ``"1x"`` RAS(h,p)-nSF-IP/EA
* ``"S"`` RAS(S)-nSF-IP/EA
* ``"SD"`` RAS(SD)-nSF-IP/EA
* ``"SDT"`` RAS(SDT)-nSF-IP/EA
add_opts : dict ({})
Additional options to pass into Psi4.
return_ci_wfn : bool (False)
Whether to return the CI wavefunction object.
return_rohf_wfn : bool (False)
Whether to return the ROHF wavefunction object.
return_rohf_e : bool (False)
Whether to return the ROHF energy.
read_rohf_wfn : bool (False)
Whether to read a Psi4 ROHF wavefunction.
rohf_wfn_in : psi4.core.Wavefunction
The Psi4 ROHF reference wavefunction (pre-computed).
write_rohf_wfn : str ("")
Name of file (.npz) to write
localize : bool (False)
Perform BOYS localization on the RAS 2 space before DETCI call?
Can help with visualization and analysis of orbitals.
frozen_docc : int (0)
Number of frozen core orbitals.
frozen_vir : int (0)
Number of frozen virtual orbitals.
Returns
-------
return_ci_wfn : psi4.core.Wavefunction
The SF-CAS([conf_space]) wavefunction.
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
optstash = p4util.OptionsState(['SCF', 'SCF_TYPE'], ['BASIS'],
['SCF', 'MAXITER'], ['DETCI', 'CI_MAXITER'])
new_charge = kwargs.get('new_charge')
new_multiplicity = kwargs.get('new_multiplicity')
ref_mol = molecule
if (not 'new_charge' in kwargs):
print("ERROR: Please designate a target charge!")
exit()
if (not 'new_multiplicity' in kwargs):
print("ERROR: Please designate a target multiplicity!")
exit()
conf_space = kwargs.get('conf_space', "")
add_opts = kwargs.get('add_opts', {})
read_rohf_wfn = kwargs.get('read_rohf_wfn', False)
wfn_rohf_in = kwargs.get('wfn_rohf_in', None)
write_rohf_wfn = kwargs.get('write_rohf_wfn', "")
write_ci_vects = kwargs.get('write_ci_vects', False)
localize = kwargs.get('localize', False)
frozen_docc = kwargs.get('frozen_docc', 0)
frozen_uocc = kwargs.get('frozen_vir', 0)
print("Starting Psi4FockCI...\n")
# default options for Psi4
opts = {
'scf_type': 'pk',
'reference': 'rohf',
'mixed': False,
'maxiter': 1000,
'ci_maxiter': 50
}
opts.update(add_opts) # add additional options from user
# run ROHF calculation on reference state or read it in
psi4.core.clean()
psi4.set_options(opts)
mol = ref_mol.clone() # clone molecule so original isn't modified
# read in ROHF guess wavefunction if provided
if (read_rohf_wfn):
# set up options and run
psi4.set_options(opts)
print("Using ROHF from reference...")
wfn_rohf = wfn_rohf_in
e_rohf = wfn_rohf.energy()
# else, run ROHF on reference state
else:
print("Running reference...")
# TODO: Change to scf_helper call
e_rohf, wfn_rohf = psi4.energy('scf',
molecule=mol,
return_wfn=True,
options=opts)
print("SCF (%i %i): %6.12f" %
(mol.molecular_charge(), mol.multiplicity(), e_rohf))
# saving npz file of wavefunction if needed
if (write_rohf_wfn != ""):
wfn_rohf.to_file(write_rohf_wfn)
# update molecular charge and multiplicity
mol.set_molecular_charge(new_charge)
mol.set_multiplicity(new_multiplicity)
# set up reference wfn to pass into detci
# save orbital values from reference calculation
doccpi = wfn_rohf.doccpi()[0]
soccpi = wfn_rohf.soccpi()[0]
nmo = wfn_rohf.nmo()
# calculate soccpi and doccpi
new_soccpi = mol.multiplicity() - 1
del_electrons = ref_mol.molecular_charge() - mol.molecular_charge()
n_total = wfn_rohf.nalpha() + wfn_rohf.nbeta() + del_electrons
# set orbital occupations
wfn_rohf.force_soccpi(psi4.core.Dimension([new_soccpi]))
wfn_rohf.force_doccpi(
psi4.core.Dimension([(int)((n_total - new_soccpi) / 2)]))
# set up RAS1, RAS2, RAS3 spaces
ras1 = doccpi
ras2 = soccpi
ras3 = nmo - soccpi - doccpi
# add/remove orbitals to active space
if ('add_orbs_ras1' in kwargs):
ras1 = ras1 - kwargs['add_orbs_ras1']
ras2 = ras2 + kwargs['add_orbs_ras1']
if ('add_orbs_ras3' in kwargs):
ras3 = ras3 - kwargs['add_orbs_ras3']
ras2 = ras2 + kwargs['add_orbs_ras3']
# if we need to localize...
if (localize):
C = psi4.core.Matrix.to_array(wfn_rohf.Ca(), copy=True)
ras1_C = C[:, :doccpi]
ras2_C = C[:, doccpi:doccpi + soccpi]
ras3_C = C[:, doccpi + soccpi:]
loc = psi4.core.Localizer.build('BOYS', wfn_rohf.basisset(),
psi4.core.Matrix.from_array(ras2_C))
loc.localize()
ras2_localized = psi4.core.Matrix.to_array(loc.L, copy=True)
localized_orbs = np.column_stack((ras1_C, ras2_localized, ras3_C))
new_Ca = psi4.core.Matrix.from_array(localized_orbs, name="Ca")
new_Cb = psi4.core.Matrix.from_array(localized_orbs, name="Cb")
wfn_rohf.Ca().copy(new_Ca)
wfn_rohf.Cb().copy(new_Cb)
# change charge and multiplicity to new target values
n_sf = (ref_mol.multiplicity() - abs(del_electrons) - new_multiplicity) / 2
print("\nRunning RAS-SF-IP/EA...")
print(" New Charge/Mult: (%i %i)" % (new_charge, new_multiplicity))
print(" Spin-Flips: %i" % n_sf)
print(" Electron Count: %i" % del_electrons)
# set active space and docc space based on configuration space input
# Regular CAS configuration space
# includes only active space configurations
if (conf_space == "" or conf_space == "CAS"):
opts.update({'frozen_docc': [doccpi]})
opts.update({'ras1': [0]})
opts.update({'ras2': [ras2]})
opts.update({'ras3': [0]})
opts.update({'ras4': [0]})
# just (h) excitations
elif (conf_space == "h"):
opts.update({'ex_level': 0})
opts.update({'val_ex_level': 1})
opts.update({'ras3_max': 0})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [ras1 - frozen_docc]})
opts.update({'ras2': [ras2]})
opts.update({'ras3': [0]})
opts.update({'ras4': [0]})
# just (p) excitations
elif (conf_space == "p"):
opts.update({'ex_level': 0})
opts.update({'val_ex_level': 0})
opts.update({'ras3_max': 1})
opts.update({'frozen_docc': [doccpi]})
opts.update({'ras1': [0]})
opts.update({'ras2': [ras2]})
opts.update({'ras3': [ras3 - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
# 1x configuration space
# includes (h, p) excitations
elif (conf_space == "1x" or conf_space == "h,p"):
opts.update({'frozen_docc': [0]})
opts.update({'ex_level': 0})
opts.update({'val_ex_level': 1})
opts.update({'ras3_max': 1})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [ras1 - frozen_docc]})
opts.update({'ras2': [ras2]})
opts.update({'ras3': [ras3 - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
# S configuration space
# includes (h, p, hp) excitations
elif (conf_space == "s"):
opts.update({'ex_level': 1})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [ras1 - frozen_docc]})
opts.update({'ras2': [ras2]})
opts.update({'ras3': [ras3 - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
elif (conf_space == "sd"):
opts.update({'frozen_docc': [0]})
opts.update({'ex_level': 2})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [ras1 - frozen_docc]})
opts.update({'ras2': [ras2]})
opts.update({'ras3': [ras3 - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
elif (conf_space == "sdt"):
opts.update({'frozen_docc': [0]})
opts.update({'ex_level': 3})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [ras1 - frozen_docc]})
opts.update({'ras2': [ras2]})
opts.update({'ras3': [ras3 - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
# Other configuration spaces aren't supported yet
else:
print("Configuration space %s not supported. Exiting..." % conf_space)
exit()
# run cas
psi4.set_options(opts)
e_cas, wfn_cas = psi4.energy('detci',
ref_wfn=wfn_rohf,
return_wfn=True,
molecule=mol)
# printing useful info
print("\n Root\tEnergy")
print("-----------------------------------")
n = 0
while (psi4.core.has_variable("CI ROOT %i TOTAL ENERGY" % n)):
n_str = "CI ROOT %i TOTAL ENERGY" % n
e_n = psi4.core.variable(n_str)
print(" %4i\t%6.12f" % (n, e_n))
n = n + 1
print("-----------------------------------\n")
psi4.core.print_variables() # printing Psi4 variables
# obtain eigenvectors if needed
# partly based on Daniel Smith's answer on Psi4 forums
if (write_ci_vects):
wfn_cas_2 = psi4.core.CIWavefunction(wfn_rohf)
C = np.zeros((wfn_cas_2.ndet(), n_roots))
for i in range(n_roots):
dvec = wfn_cas_2.new_civector(i + 1, 53, True, True)
dvec.set_nvec(i + 1)
dvec.init_io_files(True)
dvec.read(i, 0)
C[:, i] = np.array(dvec)
np.savetxt('ci_vect.txt', C)
optstash.restore()
print("Psi4FockCI complete. Have a good day!")
return wfn_cas
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 <db_nameDATABASEMEANSIGNEDDEVIATION>`
* :psivar:`db_name DATABASE MEAN ABSOLUTE DEVIATION <db_nameDATABASEMEANABSOLUTEDEVIATION>`
* :psivar:`db_name DATABASE ROOT-MEAN-SQUARE DEVIATION <db_nameDATABASEROOT-MEAN-SQUARESIGNEDDEVIATION>`
* 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:`share/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: string
: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:`~driver.energy`.
:type db_name: string
: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: string
: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 :py:func:`~wrappers.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: string
: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: array of strings
: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: string or array of strings
: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 `Available Databases`_ 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
def run_gpu_dfcc(name, **kwargs):
"""Function encoding sequence of PSI module calls for
a GPU-accelerated DF-CCSD(T) computation.
>>> energy('df-ccsd(t)')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# stash user options
optstash = p4util.OptionsState(
['GPU_DFCC','COMPUTE_TRIPLES'],
['GPU_DFCC','DFCC'],
['GPU_DFCC','NAT_ORBS'],
['SCF','DF_INTS_IO'],
['GPU_DFCC','CC_TYPE'])
psi4.core.set_local_option('GPU_DFCC','DFCC', True)
psi4.core.set_local_option('GPU_DFCC','CC_TYPE', 'DF')
# throw an exception for open-shells
if (psi4.core.get_option('SCF','REFERENCE') != 'RHF' ):
raise ValidationError("Error: %s requires \"reference rhf\"." % lowername)
def set_cholesky_from(mtd_type):
type_val = core.get_global_option(mtd_type)
if type_val == 'CD':
core.set_local_option('GPU_DFCC', 'DF_BASIS_CC', 'CHOLESKY')
# Alter default algorithm
if not core.has_global_option_changed('SCF_TYPE'):
optstash.add_option(['SCF_TYPE'])
core.set_global_option('SCF_TYPE', 'CD')
core.print_out(""" SCF Algorithm Type (re)set to CD.\n""")
elif type_val in ['DF', 'DISK_DF']:
if core.get_option('GPU_DFCC', 'DF_BASIS_CC') == 'CHOLESKY':
core.set_local_option('GPU_DFCC', 'DF_BASIS_CC', '')
proc_util.check_disk_df(name.upper(), optstash)
else:
raise ValidationError("""Invalid type '%s' for DFCC""" % type_val)
# triples?
if (lowername == 'gpu-df-ccsd'):
psi4.core.set_local_option('GPU_DFCC','COMPUTE_TRIPLES', False)
set_cholesky_from('CC_TYPE')
if (lowername == 'gpu-df-ccsd(t)'):
psi4.core.set_local_option('GPU_DFCC','COMPUTE_TRIPLES', True)
set_cholesky_from('CC_TYPE')
if psi4.core.get_global_option('SCF_TYPE') not in ['CD', 'DISK_DF']:
raise ValidationError("""Invalid scf_type for DFCC.""")
# save DF or CD ints generated by SCF for use in CC
psi4.core.set_local_option('SCF', 'DF_INTS_IO', 'SAVE')
# psi4 run sequence
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, use_c1=True, **kwargs) # C1 certified
else:
if ref_wfn.molecule().schoenflies_symbol() != 'c1':
raise ValidationError(""" GPU-DFCC does not make use of molecular symmetry: """
""" reference wavefunction must be C1.\n""")
scf_aux_basis = psi4.core.BasisSet.build(ref_wfn.molecule(), "DF_BASIS_SCF",
psi4.core.get_option("SCF", "DF_BASIS_SCF"),
"JKFIT", psi4.core.get_global_option('BASIS'),
puream=ref_wfn.basisset().has_puream())
ref_wfn.set_basisset("DF_BASIS_SCF", scf_aux_basis)
aux_basis = psi4.core.BasisSet.build(ref_wfn.molecule(), "DF_BASIS_CC",
psi4.core.get_global_option("DF_BASIS_CC"),
"RIFIT", psi4.core.get_global_option("BASIS"))
ref_wfn.set_basisset("DF_BASIS_CC", aux_basis)
returnvalue = psi4.core.plugin('gpu_dfcc.so',ref_wfn)
# restore options
optstash.restore()
return returnvalue
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 <db_nameDATABASEMEANSIGNEDDEVIATION>`
* :psivar:`db_name DATABASE MEAN ABSOLUTE DEVIATION <db_nameDATABASEMEANABSOLUTEDEVIATION>`
* :psivar:`db_name DATABASE ROOT-MEAN-SQUARE DEVIATION <db_nameDATABASEROOT-MEAN-SQUARESIGNEDDEVIATION>`
* 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:`share/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: string
: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:`~driver.energy`.
:type db_name: string
: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: string
: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 :py:func:`~wrappers.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: string
: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: array of strings
: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: string or array of strings
: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 `Available Databases`_ 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
def run_n_body(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
n_body can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('n_body')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# print("START run_n_body()")
# Your plugin's psi4 run sequence goes here
psi4.core.set_local_option('MYPLUGIN', 'PRINT', 1)
##### BEGIN TAYLOR'S run_n_body() FUNCTION #####
# Only energy and properties are implemented for now, not sure others even
# make sense anyways.
db = shelve.open('database', writeback=True)
# print(db)
# Initialize database
if not 'initialized' in db:
n_body.initialize_database(db, kwargs)
db['initialized'] = True
elif not db['initialized']:
n_body.initialize_database(db, kwargs)
db['initialized'] = True
# Remove n_body_func, it's being tracked in the database and we don't want to propagate it
if 'n_body_func' in kwargs:
kwargs.pop('n_body_func')
# Process user requested options
n_body_options = n_body.process_options(name, db, kwargs.pop('n_body'))
# Compare database options to n_body_options
if 'distributed' in n_body_options:
db['distributed'] = n_body_options['distributed']
if not db['distributed']:
raise Exception(
"Currently n_body jobs must be run in distributed mode"
" use the n_body wrapper instead.\n")
if 'cutoff' in n_body_options:
db['cutoff'] = n_body_options['cutoff']
if 'num_threads' in n_body_options:
db['num_threads'] = n_body_options['num_threads']
if 'bsse' in n_body_options:
db['bsse'] = n_body_options['bsse']
if 'pcm' in n_body_options:
db['pcm'] = n_body_options['pcm']
if 'solute' in n_body_options:
db['solute'] = n_body_options['solute']
if 'timing' in n_body_options:
db['timing'] = n_body_options['timing']
if 'harvest' in n_body_options:
db['harvest'] = n_body_options['harvest']
if 'cook' in n_body_options:
db['cook'] = n_body_options['cook']
# methods consistency check
if 'methods' in n_body_options:
for key, val in n_body_options['methods'].items():
if key in db['methods'].keys():
# requested n_body_max smaller than previously requested
if val < db['methods'][key]:
raise Exception('n_body_max for {} has '
'decreased.'.format(key))
# requested n_body_max has increased
elif val > db['methods'][key]:
# save requested n_body_max
db['methods'][key] = val
# update database entries
n_body.extend_database(db, kwargs)
# set flag to regenerate inputs
db['inputs_generated'] = False
else: # method not already in database
# add method and n_body_max to database
db['methods'][key] = val
# update database entries
n_body.extend_database(db, kwargs)
# set flag to regenerate inputs
db['inputs_generated'] = False
# Get complete system
molecule = psi4.core.get_active_molecule()
# Determine interacting fragments
if db['cutoff']:
i_pairs = n_body.interacting_pairs(db['cutoff'])
i_clusters = []
if not db['inputs_generated']:
# Create method directories
for method, n_body_max in db['methods'].items():
try:
os.makedirs(method)
except:
if os.path.isdir(method):
print(method)
pass
else:
raise Exception('Attempt to create {} directory '
'failed.'.format(method))
# Create n_body_level directories
for n in range(1, n_body_max + 1):
directory = '{}/{}'.format(method, n_body.n_body_dir(n))
try:
os.makedirs(directory)
except:
if os.path.isdir(directory):
print(directory)
pass
else:
raise Exception('Attempt to create {} directory '
'failed.'.format(directory))
# Create job input files
# Grab all ghost functions if SSFC
# Else, get all possible clusters without ghost atoms
if db['bsse'] == 'ssfc':
clusters = psi4.extract_clusters(molecule, True, n)
else:
clusters = psi4.extract_clusters(molecule, False, n)
# Flip distance-dropoff off for now
#if db['bsse'] == 'radius'
#clusters = extract_clusters(molecule, False, n)
#clusters = n_body.expand_basis(clusters, db['basis_cutoff'])
# Get list of fragments involved in clusters
indexes = psi4.extract_cluster_indexing(molecule, n)
print('Length of index array = {}'.format(len(indexes)))
# Testing for extension to inclusion of nearby atoms (ghosted)
#cluster_string = clusters[0].save_string_xyz_g09()
#print(cluster_string)
#cluster_string += molecule.extract_subsets(2).save_string_xyz_g09()
#print(molecule.extract_subsets(2).save_string_xyz_g09())
#print(clusters[0].save_string_xyz_g09())
#print(cluster_string)
#cluster_string = ''
# Get interacting clusters
if db['cutoff']:
if n == 1:
# Generate all inputs
pass
elif n == 2:
# generate inputs for i_pairs only
for k in range(len(clusters) - 1, -1, -1):
clus = indexes[k]
if clus in i_pairs:
i_clusters.append(clus)
else:
# Remove non-interacting clusters from lists
clusters.pop(k)
indexes.pop(k)
elif n > 2:
prev_clusters = copy.deepcopy(i_clusters)
i_clusters = []
for k in range(len(clusters) - 1, -1, -1):
# Check if interacting cluster
clus = indexes[k]
for p_clus in prev_clusters:
# previous cluster is contained within current cluster
if set(p_clus).issubset(set(clus)):
# Get remaining frag number
if len(set(clus).difference(
set(p_clus))) == 1:
l = set(clus).difference(
set(p_clus)).pop()
else:
raise Exception(
'Length of difference '
'set is greater than 1')
for m in p_clus:
# Is this an interacting pair?
if sorted([l, m],
reverse=True) in i_pairs:
i_clusters.append(clus)
# Don't check anymore pairs
break
if clus in i_clusters:
break
else:
# Remove non-interacting clusters from lists
clusters.pop(k)
indexes.pop(k)
# Create input files
db[method][n]['total_num_jobs'] = len(clusters)
print('n = {}'.format(n))
print('Number of jobs created = {}'.format(len(clusters)))
for k in range(len(clusters)):
psi4.activate(clusters[k])
cluster = psi4.core.get_active_molecule()
# db[method][n]['MW'][job] = value
### Set-up things for input generation
# Get list of combinations to ghost
# MBCP
if db['bsse'] == 'mbcp' and n > 1:
mbcp = list(itertools.combinations(indexes[k], n - 1))
for ghost in mbcp:
directory = '{}/{}/{}'.format(
method, n_body.n_body_dir(n),
n_body.ghost_dir(indexes[k], ghost))
cluster.set_ghost_fragments(list(ghost))
cluster.update_geometry()
cluster.set_name('{}_{}'.format(
molecule.name(),
n_body.ghost_dir(indexes[k], ghost)))
n_body.plant(cluster, db, kwargs, method,
directory)
# Update job_status dict
n_basis = n
n_real = n - len(ghost)
ghost_jobs = '{}-{}r'.format(n_basis, n_real)
# db[method][ghost_jobs]['total_num_jobs'] = len(mbcp) * len(clusters)
# db[method][ghost_jobs]['job_status'].update({n_body.ghost_dir(indexes[k],ghost):
# 'not_started'})
db[method][n]['total_num_jobs'] = len(mbcp) * len(
clusters)
db[method][n]['job_status'].update({
n_body.ghost_dir(indexes[k], ghost):
'not_started'
})
# Calculate molecular weight
totalmass = sum(
mol2.mass(i) for i in range(mol2.natom())
if mol2.Z(i))
totmass = sum(
cluster.mass(i) for i in range(cluster.natom())
if cluster.Z(i))
db[method][n]['MW'].update(
{n_body.ghost_dir(indexes[k], ghost): totmass})
# Reactivate fragments for next round
cluster.set_active_fragments(list(ghost))
cluster.update_geometry()
# VMFC
elif db['bsse'] == 'vmfc':
vmfc = []
for n_ghost in range(n - 1, 0, -1):
vmfc.extend(
list(
itertools.combinations(
indexes[k], n_ghost)))
for ghost in vmfc:
directory = '{}/{}/{}'.format(
method, n_body.n_body_dir(n),
n_body.ghost_dir(indexes[k], ghost))
cluster.set_ghost_fragments(list(ghost))
cluster.update_geometry()
cluster.set_name('{}_{}'.format(
molecule.name(),
n_body.ghost_dir(indexes[k], ghost)))
n_body.plant(cluster, db, kwargs, method,
directory)
# Update job_status dict
n_basis = n
n_real = n - len(ghost)
ghost_jobs = '{}-{}r'.format(n_basis, n_real)
#db[method][ghost_jobs]['total_num_jobs'] = len(vmfc) * len(clusters)
# db[method][ghost_jobs]['total_num_jobs'] = len(list(itertools.combinations(range(0,n),n_real))) * len(clusters)
# db[method][ghost_jobs]['job_status'].update({n_body.ghost_dir(indexes[k],ghost):
# 'not_started'})
db[method][n]['total_num_jobs'] = len(
list(
itertools.combinations(
range(0, n), n_real))) * len(clusters)
db[method][n]['job_status'].update({
n_body.ghost_dir(indexes[k], ghost):
'not_started'
})
# Calculate molecular weight
totmass = sum(
cluster.mass(i) for i in range(cluster.natom())
if cluster.Z(i))
db[method][n]['MW'].update(
{n_body.ghost_dir(indexes[k], ghost): totmass})
# Reactivate fragments for next round
cluster.set_active_fragments(list(ghost))
cluster.update_geometry()
# SSFC or no BSSE
else:
cluster.set_name('{}_{}'.format(
molecule.name(), n_body.cluster_dir(indexes[k])))
#molecule.set_name('{}_{}'.format(molecule.name(),cluster_dir(indexes[k])))
directory = '{}/{}/{}'.format(
method, n_body.n_body_dir(n),
n_body.cluster_dir(indexes[k]))
n_body.plant(cluster, db, kwargs, method, directory)
# Update database job_status dict
db[method][n]['job_status'].update(
{n_body.cluster_dir(indexes[k]): 'not_started'})
# Calculate molecular weight
totmass = sum(
cluster.mass(i) for i in range(cluster.natom())
if cluster.Z(i))
db[method][n]['MW'].update(
{n_body.cluster_dir(indexes[k]): totmass})
# Check for zero jobs (happens occasionally due to cutoff)
for method in db['methods']:
for n in range(1, db[method]['n_body_max'] + 1):
if db[method][n]['total_num_jobs'] == 0:
db[method]['n_body_max'] = n - 1
break
# Inputs successfully generated
db['inputs_generated'] = True
# For now open and close database frequently, until I figure out atexit
db.close()
db = shelve.open('database', writeback=True)
# Check status of jobs
if not db['jobs_complete']:
n_incomplete = 0
# Check all methods
for method in db['methods'].keys():
#### NOTE: dft_methods is defunct #####
# if method in n_body.dft_methods:
# outname = 'input.log'
# complete_message = 'Normal termination of Gaussian'
# if (method == 'b3lyp'):
if method in n_body.dft_methods:
outname = 'input.log'
complete_message = 'Normal termination of Gaussian'
error_message = 'Error termination'
else:
outname = 'output.dat'
complete_message = 'Psi4 exiting successfully'
error_message = 'Psi4 encountered an error'
# Check all n_body_levels
print('Before job checking:')
for field in db[method]['farm']:
num_fin = db[method][field]['num_jobs_complete']
tot_num = db[method][field]['total_num_jobs']
print('{}/{} {}-body jobs finished'.format(
num_fin, tot_num, field))
n_complete = num_fin
if num_fin != tot_num:
db_stat = db[method][field]['job_status']
n_complete = 0
for job, status in db_stat.items():
if status == 'complete':
n_complete += 1
elif status in ('not_started', 'running', 'error'):
try:
outfile = open('{}/{}/{}/{}'.format(
method, n_body.n_body_dir(field), job,
outname))
for line in outfile:
if complete_message in line:
# This actually marks the job complete as soon as
# the first route section is complete in the case
# of g09, not when the job is totally finished.
db_stat[job] = 'complete'
n_complete += 1
break
elif error_message in line:
db_stat[job] = 'error'
break
else:
db_stat[job] = 'running'
n_incomplete += 1
except:
# this print statement is super annoying, muting it for now
# print('Exception: probably could not open file for {}'.format(job))
n_incomplete += 1
db[method][field]['num_jobs_complete'] = n_complete
if n_incomplete == 0:
db['jobs_complete'] = True
db.close()
db = shelve.open('database', writeback=True)
# Gather results
if not db['results_computed']:
for method in db['methods'].keys():
print('\nAfter job checking:')
for field in db[method]['farm']:
num_fin = db[method][field]['num_jobs_complete']
tot_num = db[method][field]['total_num_jobs']
print('{}/{} {}-body jobs finished'.format(
num_fin, tot_num, field))
if (db[method][field]['num_jobs_complete'] == db[method][field]
['total_num_jobs']):
if db['harvest']:
if method in n_body.dft_methods:
n_body.harvest_g09(db, method, field)
else:
n_body.harvest_data(db, method, field)
if not db['harvest']:
print("Data harvesting has been disabled.")
elif not db['cook']:
print("Data cooking has been disabled.")
else:
for field in db[method]['farm']:
if (db[method][field]['num_jobs_complete'] == db[method]
[field]['total_num_jobs']):
n_body.cook_data(db, method, field)
# #if db['bsse'] == 'vmfc' and field > 1:
# # n_body.vmfc_cook(db, method, field)
# # n_body.mbcp_cook(db, method, field)
# if db['bsse'] == 'vmfc':
# n_body.vmfc_cook(db, method, field)
# if field > 1:
# n_body.mbcp_cook(db, method, field)
# elif db['bsse'] == 'mbcp' and field > 1:
# n_body.mbcp_cook(db,method,field)
# # Future location of an if check for mass adjust or not
# if 'rotation' in db[method]['results']:
# n_body.mass_adjust_rotations(db,method,field)
db.close()
db = shelve.open('database', writeback=True)
# Print banner to output file including user options
n_body.banner(db)
db.close()
pass
def run_psixas(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
psixas can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('psixas')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
#print the banner
printBanner()
mol = kwargs["molecule"]
func = kwargs["functional"]
tmp = psi4.core.get_local_option("PSIXAS", "MODE")
mode = tmp.split("+")
if not (all([x in ["GS", "LOC", "EX", "SPEC"] for x in mode])):
raise Exception("Wrong mode, possible values are GS, LOC, EX, SPEC.")
if "GS" in mode:
DFTGroundState(mol,
func,
PREFIX=psi4.core.get_local_option("PSIXAS", "PREFIX"))
if "LOC" in mode:
loc_sub = np.array(psi4.core.get_local_option("PSIXAS", "LOC_SUB"),
dtype=np.int)
wfn = psi4.core.Wavefunction.build(
mol, psi4.core.get_global_option('BASIS'))
nbf = wfn.nso()
sup = psi4.driver.dft.build_superfunctional(func, False)[0]
sup.set_deriv(2)
sup.allocate()
uhf = psi4.core.UHF(wfn, sup)
prefix = psi4.core.get_local_option("PSIXAS", "PREFIX")
Ca = np.load(prefix + "_gsorbs.npz")["Ca"]
Cb = np.load(prefix + "_gsorbs.npz")["Cb"]
occa = np.load(prefix + "_gsorbs.npz")["occa"]
occb = np.load(prefix + "_gsorbs.npz")["occb"]
epsa = np.load(prefix + "_gsorbs.npz")["epsa"]
epsb = np.load(prefix + "_gsorbs.npz")["epsb"]
locCa = psi4.core.Matrix(wfn.nso(), len(loc_sub))
locCb = psi4.core.Matrix(wfn.nso(), len(loc_sub))
locCa.np[:] = np.copy(Ca[:, loc_sub])
locCb.np[:] = np.copy(Cb[:, loc_sub])
LocalA = psi4.core.Localizer.build("PIPEK_MEZEY", wfn.basisset(),
locCa)
LocalB = psi4.core.Localizer.build("PIPEK_MEZEY", wfn.basisset(),
locCb)
LocalA.localize()
LocalB.localize()
Ca[:, loc_sub] = LocalA.L
Cb[:, loc_sub] = LocalB.L
np.savez(prefix + '_gsorbs', Ca=Ca, Cb=Cb, occa=occa, occb=occb)
psi4.core.print_out("Localized Orbitals written")
OCCA = psi4.core.Vector(nbf)
OCCB = psi4.core.Vector(nbf)
OCCA.np[:] = occa
OCCB.np[:] = occb
uhf.Ca().np[:] = Ca
uhf.Cb().np[:] = Cb
uhf.epsilon_a().np[:] = epsa
uhf.epsilon_b().np[:] = epsb
uhf.occupation_a().np[:] = occa
uhf.occupation_b().np[:] = occb
mw = psi4.core.MoldenWriter(uhf)
mw.write(prefix + '_loc.molden', uhf.Ca(), uhf.Cb(), uhf.epsilon_a(),
uhf.epsilon_b(), OCCA, OCCB, True)
psi4.core.print_out("Moldenfile written\n")
print("Localize subset")
print(loc_sub)
orbitals = []
if ("EX" in mode):
orbs = psi4.core.get_local_option("PSIXAS", "ORBS")
occs = psi4.core.get_local_option("PSIXAS", "OCCS")
freeze = psi4.core.get_local_option("PSIXAS", "FREEZE")
spin = psi4.core.get_local_option("PSIXAS", "SPIN")
ovl = psi4.core.get_local_option("PSIXAS", "OVL")
lens = [len(x) for x in [orbs, occs, freeze, spin, ovl]]
if len(list((set(lens)))) > 1:
raise Exception("Input arrays have inconsistent length" +
" ".join(str(lens)))
for i in range(len(orbs)):
orbitals.append({
"orb": orbs[i],
"spin": spin[i].lower(),
"occ": occs[i],
"frz": freeze[i] == "T",
"DoOvl": ovl[i] == "T"
})
DFTExcitedState(mol, func, orbitals)
if ("SPEC" in mode):
CalcSpec(mol, func)
#psixas_wfn = psi4.core.plugin('psixas.so', wfn)
return 0 #psixas_wfn
def nbody_gufunc(func, method_string, **kwargs):
"""
Computes the nbody interaction energy, gradient, or Hessian depending on input.
This is a generalized univeral function for computing interaction quantities.
:returns: *return type of func* |w--w| The interaction data.
:returns: (*float*, :py:class:`~psi4.core.Wavefunction`) |w--w| interaction data and wavefunction with energy/gradient/hessian set appropriately when **return_wfn** specified.
:type func: function
:param func: ``energy`` || etc.
Python function that accepts method_string and a molecule. Returns a
energy, gradient, or Hessian as requested.
:type method_string: string
:param method_string: ``'scf'`` || ``'mp2'`` || ``'ci5'`` || etc.
First argument, lowercase and usually unlabeled. Indicates the computational
method to be passed to func.
:type molecule: :ref:`molecule <op_py_molecule>`
:param molecule: ``h2o`` || etc.
The target molecule, if not the last molecule defined.
:type return_wfn: :ref:`boolean <op_py_boolean>`
:param return_wfn: ``'on'`` || |dl| ``'off'`` |dr|
Indicate to additionally return the :py:class:`~psi4.core.Wavefunction`
calculation result as the second element of a tuple.
:type bsse_type: string or list
:param bsse_type: ``'cp'`` || ``['nocp', 'vmfc']`` || |dl| ``None`` |dr| || etc.
Type of BSSE correction to compute: CP, NoCP, or VMFC. The first in this
list is returned by this function. By default, this function is not called.
:type max_nbody: int
:param max_nbody: ``3`` || etc.
Maximum n-body to compute, cannot exceed the number of fragments in the moleucle.
:type ptype: string
:param ptype: ``'energy'`` || ``'gradient'`` || ``'hessian'``
Type of the procedure passed in.
:type return_total_data: :ref:`boolean <op_py_boolean>`
:param return_total_data: ``'on'`` || |dl| ``'off'`` |dr|
If True returns the total data (energy/gradient/etc) of the system,
otherwise returns interaction data.
"""
# Initialize dictionaries for easy data passing
metadata, component_results, nbody_results = {}, {}, {}
# Parse some kwargs
kwargs = p4util.kwargs_lower(kwargs)
metadata['ptype'] = kwargs.pop('ptype', None)
metadata['return_wfn'] = kwargs.pop('return_wfn', False)
metadata['return_total_data'] = kwargs.pop('return_total_data', False)
metadata['molecule'] = kwargs.pop('molecule', core.get_active_molecule())
metadata['molecule'].update_geometry()
metadata['kwargs'] = kwargs
core.clean_variables()
if metadata['ptype'] not in ['energy', 'gradient', 'hessian']:
raise ValidationError("""N-Body driver: The ptype '%s' is not regonized.""" % metadata['ptype'])
# Parse bsse_type, raise exception if not provided or unrecognized
metadata['bsse_type_list'] = kwargs.pop('bsse_type')
if metadata['bsse_type_list'] is None:
raise ValidationError("N-Body GUFunc: Must pass a bsse_type")
if not isinstance(metadata['bsse_type_list'], list):
metadata['bsse_type_list'] = [metadata['bsse_type_list']]
for num, btype in enumerate(metadata['bsse_type_list']):
metadata['bsse_type_list'][num] = btype.lower()
if btype.lower() not in ['cp', 'nocp', 'vmfc']:
raise ValidationError("N-Body GUFunc: bsse_type '%s' is not recognized" % btype.lower())
metadata['max_nbody'] = kwargs.get('max_nbody', -1)
metadata['max_frag'] = metadata['molecule'].nfragments()
if metadata['max_nbody'] == -1:
metadata['max_nbody'] = metadata['molecule'].nfragments()
else:
metadata['max_nbody'] = min(metadata['max_nbody'], metadata['max_frag'])
# Flip this off for now, needs more testing
# If we are doing CP lets save them integrals
#if 'cp' in bsse_type_list and (len(bsse_type_list) == 1):
# # Set to save RI integrals for repeated full-basis computations
# ri_ints_io = core.get_global_option('DF_INTS_IO')
# # inquire if above at all applies to dfmp2 or just scf
# core.set_global_option('DF_INTS_IO', 'SAVE')
# psioh = core.IOManager.shared_object()
# psioh.set_specific_retention(97, True)
bsse_str = metadata['bsse_type_list'][0]
if len(metadata['bsse_type_list']) > 1:
bsse_str = str(metadata['bsse_type_list'])
core.print_out("\n\n")
core.print_out(" ===> N-Body Interaction Abacus <===\n")
core.print_out(" BSSE Treatment: %s\n" % bsse_str)
# Get compute list
metadata = build_nbody_compute_list(metadata)
# Compute N-Body components
component_results = compute_nbody_components(func, method_string, metadata)
# Assemble N-Body quantities
nbody_results = assemble_nbody_components(metadata, component_results)
# Figure out returns
if metadata['ptype'] != 'energy':
if metadata['return_total_data']:
np_final_ptype = nbody_results['ptype_body_dict'][metadata['max_nbody']].copy()
else:
np_final_ptype = nbody_results['ptype_body_dict'][metadata['max_nbody']].copy()
np_final_ptype -= ptype_body_dict[1]
nbody_results['ret_ptype'] = core.Matrix.from_array(np_final_ptype)
else:
nbody_results['ret_ptype'] = nbody_results['ret_energy']
# Build wfn and bind variables
wfn = core.Wavefunction.build(metadata['molecule'], 'def2-svp')
dicts = ['energies', 'ptype', 'intermediates', 'energy_body_dict', 'ptype_body_dict', 'nbody']
for r in [component_results, nbody_results]:
for d in r:
if d in dicts:
for var, value in r[d].items():
wfn.set_variable(str(var), value)
core.set_variable(str(var), value)
if metadata['ptype'] == 'gradient':
wfn.set_gradient(ret_ptype)
elif metadata['ptype'] == 'hessian':
wfn.set_hessian(ret_ptype)
core.set_variable("CURRENT ENERGY", nbody_results['ret_energy'])
wfn.set_variable("CURRENT ENERGY", nbody_results['ret_energy'])
if metadata['return_wfn']:
return (nbody_results['ret_ptype'], wfn)
else:
return nbody_results['ret_ptype']
def run_forte(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
forte can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('forte')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Get the option object
options = psi4.core.get_options()
options.set_current_module('FORTE')
forte.forte_options.update_psi_options(options)
if ('DF' in options.get_str('INT_TYPE')):
aux_basis = psi4.core.BasisSet.build(
ref_wfn.molecule(), 'DF_BASIS_MP2',
psi4.core.get_global_option('DF_BASIS_MP2'), 'RIFIT',
psi4.core.get_global_option('BASIS'))
ref_wfn.set_basisset('DF_BASIS_MP2', aux_basis)
if (options.get_str('MINAO_BASIS')):
minao_basis = psi4.core.BasisSet.build(ref_wfn.molecule(),
'MINAO_BASIS',
options.get_str('MINAO_BASIS'))
ref_wfn.set_basisset('MINAO_BASIS', minao_basis)
# Start Forte, initialize ambit
my_proc_n_nodes = forte.startup()
my_proc, n_nodes = my_proc_n_nodes
# Print the banner
forte.banner()
# Create the MOSpaceInfo object
mo_space_info = forte.make_mo_space_info(ref_wfn, forte.forte_options)
# Create the AO subspace projector
ps = forte.make_aosubspace_projector(ref_wfn, options)
state = forte.make_state_info_from_psi_wfn(ref_wfn)
scf_info = forte.SCFInfo(ref_wfn)
state_weights_map = forte.make_state_weights_map(forte.forte_options,
ref_wfn)
# Run a method
job_type = options.get_str('JOB_TYPE')
energy = 0.0
if job_type != 'NONE':
start = timeit.timeit()
# Make an integral object
ints = forte.make_forte_integrals(ref_wfn, options, mo_space_info)
# Rotate orbitals before computation
orb_type = options.get_str("ORBITAL_TYPE")
if orb_type != 'CANONICAL':
orb_t = forte.make_orbital_transformation(orb_type, scf_info,
forte.forte_options,
ints, mo_space_info)
orb_t.compute_transformation()
Ua = orb_t.get_Ua()
Ub = orb_t.get_Ub()
ints.rotate_orbitals(Ua, Ub)
# Run a method
if (job_type == 'NEWDRIVER'):
energy = forte_driver(state_weights_map, scf_info,
forte.forte_options, ints, mo_space_info)
else:
energy = forte.forte_old_methods(ref_wfn, options, ints,
mo_space_info)
end = timeit.timeit()
#print('\n\n Your calculation took ', (end - start), ' seconds');
# Close ambit, etc.
forte.cleanup()
psi4.core.set_scalar_variable('CURRENT ENERGY', energy)
return ref_wfn
def prepare_psi4_ref_wfn(options, **kwargs):
"""
Prepare a Psi4 Wavefunction as reference for Forte.
:param options: a ForteOptions object for options
:param kwargs: named arguments associated with Psi4
:return: (the processed Psi4 Wavefunction, a Forte MOSpaceInfo object)
Notes:
We will create a new Psi4 Wavefunction (wfn_new) if necessary.
1. For an empty ref_wfn, wfn_new will come from Psi4 SCF or MCSCF.
2. For a valid ref_wfn, we will test the orbital orthonormality against molecule.
If the orbitals from ref_wfn are consistent with the active geometry,
wfn_new will simply be a link to ref_wfn.
If not, we will rerun a Psi4 SCF and orthogonalize orbitals, where
wfn_new comes from this new Psi4 SCF computation.
"""
p4print = psi4.core.print_out
# grab reference Wavefunction and Molecule from kwargs
kwargs = p4util.kwargs_lower(kwargs)
ref_wfn = kwargs.get('ref_wfn', None)
molecule = kwargs.pop('molecule', psi4.core.get_active_molecule())
point_group = molecule.point_group().symbol()
# try to read orbitals from file
Ca = read_orbitals() if options.get_bool('READ_ORBITALS') else None
need_orbital_check = True
fresh_ref_wfn = True if ref_wfn is None else False
if ref_wfn is None:
ref_type = options.get_str('REF_TYPE')
p4print('\n No reference wave function provided for Forte.'
f' Computing {ref_type} orbitals using Psi4 ...\n')
# no warning printing for MCSCF
job_type = options.get_str('JOB_TYPE')
do_mcscf = (job_type in ["CASSCF", "MCSCF_TWO_STEP"]
or options.get_bool("CASSCF_REFERENCE"))
# run Psi4 SCF or MCSCF
ref_wfn = run_psi4_ref(ref_type, molecule, not do_mcscf, **kwargs)
need_orbital_check = False if Ca is None else True
else:
# Ca from file has higher priority than that of ref_wfn
Ca = ref_wfn.Ca().clone() if Ca is None else Ca
# build Forte MOSpaceInfo
nmopi = ref_wfn.nmopi()
mo_space_info = forte.make_mo_space_info(nmopi, point_group, options)
# do we need to check MO overlap?
if not need_orbital_check:
wfn_new = ref_wfn
else:
# test if input Ca has the correct dimension
if Ca.rowdim() != nmopi or Ca.coldim() != nmopi:
raise ValueError(
"Invalid orbitals: different basis set / molecule")
new_S = psi4.core.Wavefunction.build(molecule,
options.get_str("BASIS")).S()
if check_MO_orthonormality(new_S, Ca):
wfn_new = ref_wfn
wfn_new.Ca().copy(Ca)
else:
if fresh_ref_wfn:
wfn_new = ref_wfn
wfn_new.Ca().copy(ortho_orbs_forte(wfn_new, mo_space_info, Ca))
else:
p4print("\n Perform new SCF at current geometry ...\n")
kwargs_copy = {
k: v
for k, v in kwargs.items() if k != 'ref_wfn'
}
wfn_new = run_psi4_ref('scf', molecule, False, **kwargs_copy)
# orthonormalize orbitals
wfn_new.Ca().copy(ortho_orbs_forte(wfn_new, mo_space_info, Ca))
# copy wfn_new to ref_wfn
ref_wfn.shallow_copy(wfn_new)
# set DF and MINAO basis
if 'DF' in options.get_str('INT_TYPE'):
aux_basis = psi4.core.BasisSet.build(molecule, 'DF_BASIS_MP2',
options.get_str('DF_BASIS_MP2'),
'RIFIT', options.get_str('BASIS'))
wfn_new.set_basisset('DF_BASIS_MP2', aux_basis)
if options.get_str('MINAO_BASIS'):
minao_basis = psi4.core.BasisSet.build(molecule, 'MINAO_BASIS',
options.get_str('MINAO_BASIS'))
wfn_new.set_basisset('MINAO_BASIS', minao_basis)
return wfn_new, mo_space_info
def gradient_forte(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
forte can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> gradient('forte')
available for : CASSCF
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Get the psi4 option object
optstash = p4util.OptionsState(['GLOBALS', 'DERTYPE'])
psi4_options = psi4.core.get_options()
psi4_options.set_current_module('FORTE')
# Get the forte option object
options = forte.forte_options
options.get_options_from_psi4(psi4_options)
if ('DF' in options.get_str('INT_TYPE')):
raise Exception('analytic gradient is not implemented for density fitting')
if (options.get_str('MINAO_BASIS')):
minao_basis = psi4.core.BasisSet.build(ref_wfn.molecule(), 'MINAO_BASIS',
options.get_str('MINAO_BASIS'))
ref_wfn.set_basisset('MINAO_BASIS', minao_basis)
# Start Forte, initialize ambit
my_proc_n_nodes = forte.startup()
my_proc, n_nodes = my_proc_n_nodes
# Print the banner
forte.banner()
# Create the MOSpaceInfo object
mo_space_info = forte.make_mo_space_info(ref_wfn, options)
# Call methods that project the orbitals (AVAS, embedding)
mo_space_info = orbital_projection(ref_wfn, options, mo_space_info)
state = forte.make_state_info_from_psi_wfn(ref_wfn)
scf_info = forte.SCFInfo(ref_wfn)
state_weights_map = forte.make_state_weights_map(options,ref_wfn)
# Run a method
job_type = options.get_str('JOB_TYPE')
energy = 0.0
if not job_type == 'CASSCF':
raise Exception('analytic gradient is only implemented for CASSCF')
start = time.time()
# Make an integral object
ints = forte.make_forte_integrals(ref_wfn, options, mo_space_info)
# Rotate orbitals before computation
orb_type = options.get_str("ORBITAL_TYPE")
if orb_type != 'CANONICAL':
orb_t = forte.make_orbital_transformation(orb_type, scf_info, options, ints, mo_space_info)
orb_t.compute_transformation()
Ua = orb_t.get_Ua()
Ub = orb_t.get_Ub()
ints.rotate_orbitals(Ua,Ub)
# Run gradient computation
energy = forte.forte_old_methods(ref_wfn, options, ints, mo_space_info)
derivobj = psi4.core.Deriv(ref_wfn)
derivobj.set_deriv_density_backtransformed(True)
derivobj.set_ignore_reference(True)
grad = derivobj.compute() #psi4.core.DerivCalcType.Correlated
ref_wfn.set_gradient(grad)
optstash.restore()
end = time.time()
#print('\n\n Your calculation took ', (end - start), ' seconds');
# Close ambit, etc.
forte.cleanup()
return ref_wfn
def nbody_gufunc(func, method_string, **kwargs):
"""
Computes the nbody interaction energy, gradient, or Hessian depending on input.
This is a generalized univeral function for computing interaction quantities.
:returns: *return type of func* |w--w| The interaction data.
:returns: (*float*, :ref:`Wavefunction<sec:psimod_Wavefunction>`) |w--w| interaction data and wavefunction with energy/gradient/hessian set appropriately when **return_wfn** specified.
:type func: function
:param func: ``energy`` || etc.
Python function that accepts method_string and a molecule. Returns a
energy, gradient, or Hessian as requested.
:type method_string: string
:param method_string: ``'scf'`` || ``'mp2'`` || ``'ci5'`` || etc.
First argument, lowercase and usually unlabeled. Indicates the computational
method to be passed to func.
:type molecule: :ref:`molecule <op_py_molecule>`
:param molecule: ``h2o`` || etc.
The target molecule, if not the last molecule defined.
:type return_wfn: :ref:`boolean <op_py_boolean>`
:param return_wfn: ``'on'`` || |dl| ``'off'`` |dr|
Indicate to additionally return the :ref:`Wavefunction<sec:psimod_Wavefunction>`
calculation result as the second element of a tuple.
:type bsse_type: string or list
:param bsse_type: ``'cp'`` || ``['nocp', 'vmfc']`` || |dl| ``None`` |dr| || etc.
Type of BSSE correction to compute: CP, NoCP, or VMFC. The first in this
list is returned by this function. By default, this function is not called.
:type max_nbody: int
:param max_nbody: ``3`` || etc.
Maximum n-body to compute, cannot exceed the number of fragments in the moleucle.
:type ptype: string
:param ptype: ``'energy'`` || ``'gradient'`` || ``'hessian'``
Type of the procedure passed in.
:type return_total_data: :ref:`boolean <op_py_boolean>`
:param return_total_data: ``'on'`` || |dl| ``'off'`` |dr|
If True returns the total data (energy/gradient/etc) of the system,
otherwise returns interaction data.
"""
### ==> Parse some kwargs <==
kwargs = p4util.kwargs_lower(kwargs)
return_wfn = kwargs.pop('return_wfn', False)
ptype = kwargs.pop('ptype', None)
return_total_data = kwargs.pop('return_total_data', False)
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
core.clean_variables()
if ptype not in ['energy', 'gradient', 'hessian']:
raise ValidationError(
"""N-Body driver: The ptype '%s' is not regonized.""" % ptype)
# Figure out BSSE types
do_cp = False
do_nocp = False
do_vmfc = False
return_method = False
# Must be passed bsse_type
bsse_type_list = kwargs.pop('bsse_type')
if bsse_type_list is None:
raise ValidationError("N-Body GUFunc: Must pass a bsse_type")
if not isinstance(bsse_type_list, list):
bsse_type_list = [bsse_type_list]
for num, btype in enumerate(bsse_type_list):
if btype.lower() == 'cp':
do_cp = True
if (num == 0): return_method = 'cp'
elif btype.lower() == 'nocp':
do_nocp = True
if (num == 0): return_method = 'nocp'
elif btype.lower() == 'vmfc':
do_vmfc = True
if (num == 0): return_method = 'vmfc'
else:
raise ValidationError(
"N-Body GUFunc: bsse_type '%s' is not recognized" %
btype.lower())
max_nbody = kwargs.get('max_nbody', -1)
max_frag = molecule.nfragments()
if max_nbody == -1:
max_nbody = molecule.nfragments()
else:
max_nbody = min(max_nbody, max_frag)
# What levels do we need?
nbody_range = range(1, max_nbody + 1)
fragment_range = range(1, max_frag + 1)
# Flip this off for now, needs more testing
# If we are doing CP lets save them integrals
#if 'cp' in bsse_type_list and (len(bsse_type_list) == 1):
# # Set to save RI integrals for repeated full-basis computations
# ri_ints_io = core.get_global_option('DF_INTS_IO')
# # inquire if above at all applies to dfmp2 or just scf
# core.set_global_option('DF_INTS_IO', 'SAVE')
# psioh = core.IOManager.shared_object()
# psioh.set_specific_retention(97, True)
bsse_str = bsse_type_list[0]
if len(bsse_type_list) > 1:
bsse_str = str(bsse_type_list)
core.print_out("\n\n")
core.print_out(" ===> N-Body Interaction Abacus <===\n")
core.print_out(" BSSE Treatment: %s\n" %
bsse_str)
cp_compute_list = {x: set() for x in nbody_range}
nocp_compute_list = {x: set() for x in nbody_range}
vmfc_compute_list = {x: set() for x in nbody_range}
vmfc_level_list = {x: set()
for x in nbody_range
} # Need to sum something slightly different
# Build up compute sets
if do_cp:
# Everything is in dimer basis
basis_tuple = tuple(fragment_range)
for nbody in nbody_range:
for x in it.combinations(fragment_range, nbody):
cp_compute_list[nbody].add((x, basis_tuple))
if do_nocp:
# Everything in monomer basis
for nbody in nbody_range:
for x in it.combinations(fragment_range, nbody):
nocp_compute_list[nbody].add((x, x))
if do_vmfc:
# Like a CP for all combinations of pairs or greater
for nbody in nbody_range:
for cp_combos in it.combinations(fragment_range, nbody):
basis_tuple = tuple(cp_combos)
for interior_nbody in nbody_range:
for x in it.combinations(cp_combos, interior_nbody):
combo_tuple = (x, basis_tuple)
vmfc_compute_list[interior_nbody].add(combo_tuple)
vmfc_level_list[len(basis_tuple)].add(combo_tuple)
# Build a comprehensive compute_range
compute_list = {x: set() for x in nbody_range}
for n in nbody_range:
compute_list[n] |= cp_compute_list[n]
compute_list[n] |= nocp_compute_list[n]
compute_list[n] |= vmfc_compute_list[n]
core.print_out(" Number of %d-body computations: %d\n" %
(n, len(compute_list[n])))
# Build size and slices dictionaries
fragment_size_dict = {
frag: molecule.extract_subsets(frag).natom()
for frag in range(1, max_frag + 1)
}
start = 0
fragment_slice_dict = {}
for k, v in fragment_size_dict.items():
fragment_slice_dict[k] = slice(start, start + v)
start += v
molecule_total_atoms = sum(fragment_size_dict.values())
# Now compute the energies
energies_dict = {}
ptype_dict = {}
for n in compute_list.keys():
core.print_out(
"\n ==> N-Body: Now computing %d-body complexes <==\n\n" % n)
print("\n ==> N-Body: Now computing %d-body complexes <==\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)
ptype_dict[pair] = func(method_string,
molecule=current_mol,
**kwargs)
energies_dict[pair] = core.get_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()
# Final dictionaries
cp_energy_by_level = {n: 0.0 for n in nbody_range}
nocp_energy_by_level = {n: 0.0 for n in nbody_range}
cp_energy_body_dict = {n: 0.0 for n in nbody_range}
nocp_energy_body_dict = {n: 0.0 for n in nbody_range}
vmfc_energy_body_dict = {n: 0.0 for n in nbody_range}
# Build out ptype dictionaries if needed
if ptype != 'energy':
if ptype == 'gradient':
arr_shape = (molecule_total_atoms, 3)
elif ptype == 'hessian':
arr_shape = (molecule_total_atoms * 3, molecule_total_atoms * 3)
else:
raise KeyError("N-Body: ptype '%s' not recognized" % ptype)
cp_ptype_by_level = {n: np.zeros(arr_shape) for n in nbody_range}
nocp_ptype_by_level = {n: np.zeros(arr_shape) for n in nbody_range}
vmfc_ptype_by_level = {n: np.zeros(arr_shape) for n in nbody_range}
cp_ptype_body_dict = {n: np.zeros(arr_shape) for n in nbody_range}
nocp_ptype_body_dict = {n: np.zeros(arr_shape) for n in nbody_range}
vmfc_ptype_body_dict = {n: np.zeros(arr_shape) for n in nbody_range}
else:
cp_ptype_by_level, cp_ptype_body_dict = None, None
nocp_ptype_by_level, nocp_ptype_body_dict = None, None
vmfc_ptype_body_dict = None
# Sum up all of the levels
for n in nbody_range:
# Energy
cp_energy_by_level[n] = sum(energies_dict[v]
for v in cp_compute_list[n])
nocp_energy_by_level[n] = sum(energies_dict[v]
for v in nocp_compute_list[n])
# Special vmfc case
if n > 1:
vmfc_energy_body_dict[n] = vmfc_energy_body_dict[n - 1]
for tup in vmfc_level_list[n]:
vmfc_energy_body_dict[n] += (
(-1)**(n - len(tup[0]))) * energies_dict[tup]
# Do ptype
if ptype != 'energy':
_sum_cluster_ptype_data(ptype, ptype_dict, cp_compute_list[n],
fragment_slice_dict, fragment_size_dict,
cp_ptype_by_level[n])
_sum_cluster_ptype_data(ptype, ptype_dict, nocp_compute_list[n],
fragment_slice_dict, fragment_size_dict,
nocp_ptype_by_level[n])
_sum_cluster_ptype_data(ptype,
ptype_dict,
vmfc_level_list[n],
fragment_slice_dict,
fragment_size_dict,
vmfc_ptype_by_level[n],
vmfc=True)
# Compute cp energy and ptype
if do_cp:
for n in nbody_range:
if n == max_frag:
cp_energy_body_dict[n] = cp_energy_by_level[n]
if ptype != 'energy':
cp_ptype_body_dict[n][:] = cp_ptype_by_level[n]
continue
for k in range(1, n + 1):
take_nk = nCr(max_frag - k - 1, n - k)
sign = ((-1)**(n - k))
value = cp_energy_by_level[k]
cp_energy_body_dict[n] += take_nk * sign * value
if ptype != 'energy':
value = cp_ptype_by_level[k]
cp_ptype_body_dict[n] += take_nk * sign * value
_print_nbody_energy(cp_energy_body_dict, "Counterpoise Corrected (CP)")
cp_interaction_energy = cp_energy_body_dict[
max_nbody] - cp_energy_body_dict[1]
core.set_variable('Counterpoise Corrected Total Energy',
cp_energy_body_dict[max_nbody])
core.set_variable('Counterpoise Corrected Interaction Energy',
cp_interaction_energy)
for n in nbody_range[1:]:
var_key = 'CP-CORRECTED %d-BODY INTERACTION ENERGY' % n
core.set_variable(var_key,
cp_energy_body_dict[n] - cp_energy_body_dict[1])
# Compute nocp energy and ptype
if do_nocp:
for n in nbody_range:
if n == max_frag:
nocp_energy_body_dict[n] = nocp_energy_by_level[n]
if ptype != 'energy':
nocp_ptype_body_dict[n][:] = nocp_ptype_by_level[n]
continue
for k in range(1, n + 1):
take_nk = nCr(max_frag - k - 1, n - k)
sign = ((-1)**(n - k))
value = nocp_energy_by_level[k]
nocp_energy_body_dict[n] += take_nk * sign * value
if ptype != 'energy':
value = nocp_ptype_by_level[k]
nocp_ptype_body_dict[n] += take_nk * sign * value
_print_nbody_energy(nocp_energy_body_dict,
"Non-Counterpoise Corrected (NoCP)")
nocp_interaction_energy = nocp_energy_body_dict[
max_nbody] - nocp_energy_body_dict[1]
core.set_variable('Non-Counterpoise Corrected Total Energy',
nocp_energy_body_dict[max_nbody])
core.set_variable('Non-Counterpoise Corrected Interaction Energy',
nocp_interaction_energy)
for n in nbody_range[1:]:
var_key = 'NOCP-CORRECTED %d-BODY INTERACTION ENERGY' % n
core.set_variable(
var_key, nocp_energy_body_dict[n] - nocp_energy_body_dict[1])
# Compute vmfc energy and ptype
if do_vmfc:
_print_nbody_energy(vmfc_energy_body_dict,
"Valiron-Mayer Function Couterpoise (VMFC)")
vmfc_interaction_energy = vmfc_energy_body_dict[
max_nbody] - vmfc_energy_body_dict[1]
core.set_variable('Valiron-Mayer Function Couterpoise Total Energy',
vmfc_energy_body_dict[max_nbody])
core.set_variable(
'Valiron-Mayer Function Couterpoise Interaction Energy',
vmfc_interaction_energy)
for n in nbody_range[1:]:
var_key = 'VMFC-CORRECTED %d-BODY INTERACTION ENERGY' % n
core.set_variable(
var_key, vmfc_energy_body_dict[n] - vmfc_energy_body_dict[1])
if return_method == 'cp':
ptype_body_dict = cp_ptype_body_dict
energy_body_dict = cp_energy_body_dict
elif return_method == 'nocp':
ptype_body_dict = nocp_ptype_body_dict
energy_body_dict = nocp_energy_body_dict
elif return_method == 'vmfc':
ptype_body_dict = vmfc_ptype_body_dict
energy_body_dict = vmfc_energy_body_dict
else:
raise ValidationError(
"N-Body Wrapper: Invalid return type. Should never be here, please post this error on github."
)
# Figure out and build return types
if return_total_data:
ret_energy = energy_body_dict[max_nbody]
else:
ret_energy = energy_body_dict[max_nbody]
ret_energy -= energy_body_dict[1]
if ptype != 'energy':
if return_total_data:
np_final_ptype = ptype_body_dict[max_nbody].copy()
else:
np_final_ptype = ptype_body_dict[max_nbody].copy()
np_final_ptype -= ptype_body_dict[1]
ret_ptype = core.Matrix.from_array(np_final_ptype)
else:
ret_ptype = ret_energy
# Build and set a wavefunction
wfn = core.Wavefunction.build(molecule, 'sto-3g')
wfn.cdict["nbody_energy"] = energies_dict
wfn.cdict["nbody_ptype"] = ptype_dict
wfn.cdict["nbody_body_energy"] = energy_body_dict
wfn.cdict["nbody_body_ptype"] = ptype_body_dict
if ptype == 'gradient':
wfn.set_gradient(ret_ptype)
elif ptype == 'hessian':
wfn.set_hessian(ret_ptype)
core.set_variable("CURRENT ENERGY", ret_energy)
if return_wfn:
return (ret_ptype, wfn)
else:
return ret_ptype
def run_efp_gamess(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
efp_gamess can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('efp_gamess')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Your plugin's psi4 run sequence goes here
psi4.core.set_local_option('MYPLUGIN', 'PRINT', 1)
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
print('Attention! This SCF may be density-fitted.')
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Ensure IWL files have been written when not using DF/CD
proc_util.check_iwl_file_from_scf_type(
psi4.core.get_option('SCF', 'SCF_TYPE'), ref_wfn)
# Call the Psi4 plugin
# Please note that setting the reference wavefunction in this way is ONLY for plugins
# This prints a bound python method
print("\nPrinting ref_wfn.Fa")
print(ref_wfn.Fa)
# This defines a psi4.core.Matrix object and prints it
print("\nPrinting np.asarray(ref_wfn.Fa())")
print(np.asarray(ref_wfn.Fa()))
#Farray=np.asarray(ref_wfn.Fa())
Farray = ref_wfn.Fa().to_array()
print("\nPrinting Farray, which is np.asarray(ref_wfn.Fa())")
print(Farray)
print("\nPrinting Farray asarray")
print(np.asarray(Farray))
# I think this does nothing different from the above
Fa = ref_wfn.Fa()
print("\nPrinting Fa=ref_wfn.Fa()")
print(Fa)
print("\nPrinting np.asarray(Fa)")
print(np.asarray(Fa))
# This prints to the output the matrix values
#Fa.print_out()
# This actually changes Fa and the ref_wfn Fa value
#Fa.set(0,0,0.0)
#Fa.print_out()
#ref_wfn.Fa=Fa
# Tests my previous assertion about ref_wfn changes
#Fa_zeroed=ref_wfn.Fa()
#Fa_zeroed.print_out()
# Change return name to the trans matrix I'm trying to send back
#efp_gamess_wfn = psi4.core.plugin('efp_gamess.so', ref_wfn)
psi4.core.set_local_option('efp_gamess', 'coleman', 0)
trans_mat_c = psi4.core.plugin('efp_gamess.so', ref_wfn)
print("\nPrinting C transformation matrix")
print(trans_mat_c)
print("\nPrinting C transformation matrix (as array)")
print(np.asarray(trans_mat_c))
trans_mat_c.print_out()
psi4.core.print_out("\nalright coleman H coming now")
psi4.core.set_local_option('efp_gamess', 'coleman', 1)
trans_mat_h = psi4.core.plugin('efp_gamess.so', ref_wfn)
print("\nPrinting H transformation matrix")
print(trans_mat_h)
print("\nPrinting H transformation matrix (as array)")
print(np.asarray(trans_mat_h))
trans_mat_h.print_out()
# Define hdf5 file
f = h5py.File("form.h5", "r")
group = f["EFPcalc"]
print("\nListing dataset in h5 file EFPcalc group")
print(list(group.keys()))
fock_dset = group['CONVERGED TOTAL FOCK MATRIX']
fock_np = np.array(fock_dset)
print("\nGAMESS Fock matrix as numpy array")
print(fock_np)
mo_dset = group['MO_coeff']
mo_np = np.array(mo_dset)
print("\nGAMESS MO coeficients")
print(mo_np)
print("\nPSI4 MO coefficients")
print("\nTransforming MO coefficients")
psi4_C = np.matmul(trans_mat_c, np.transpose(mo_np))
print("\nTransformed MO coefficients")
print(psi4_C)
# Test adding these together
#print("Adding np.asarray(trans_mat_h)+np.asarray(trans_mat_c)\n")
#test_sum=np.asarray(trans_mat_h)+np.asarray(trans_mat_c)
#print(test_sum)
#test_sum2=np.asarray(Fa)+np.asarray(trans_mat_c)
#print(test_sum2)
#test_sum.print_out()
# Find out what trans_mat is (it's like the others)
#print(trans_mat)
# print actual values
#trans_mat.print_out()
# Change return to original ref_wfn, hopefully changed
#return efp_gamess_wfn
return ref_wfn
def nbody_gufunc(func: Union[str, Callable], method_string: str, **kwargs):
"""
Computes the nbody interaction energy, gradient, or Hessian depending on input.
This is a generalized univeral function for computing interaction and total quantities.
:returns: *return type of func* |w--w| The data.
:returns: (*float*, :py:class:`~psi4.core.Wavefunction`) |w--w| data and wavefunction with energy/gradient/hessian set appropriately when **return_wfn** specified.
:type func: Callable
:param func: ``energy`` || etc.
Python function that accepts method_string and a molecule. Returns a
energy, gradient, or Hessian as requested.
:type method_string: str
:param method_string: ``'scf'`` || ``'mp2'`` || ``'ci5'`` || etc.
First argument, lowercase and usually unlabeled. Indicates the computational
method to be passed to func.
:type molecule: :ref:`molecule <op_py_molecule>`
:param molecule: ``h2o`` || etc.
The target molecule, if not the last molecule defined.
:type return_wfn: :ref:`boolean <op_py_boolean>`
:param return_wfn: ``'on'`` || |dl| ``'off'`` |dr|
Indicate to additionally return the :py:class:`~psi4.core.Wavefunction`
calculation result as the second element of a tuple.
:type bsse_type: str or list
:param bsse_type: ``'cp'`` || ``['nocp', 'vmfc']`` || |dl| ``None`` |dr| || etc.
Type of BSSE correction to compute: CP, NoCP, or VMFC. The first in this
list is returned by this function. By default, this function is not called.
:type max_nbody: int
:param max_nbody: ``3`` || etc.
Maximum n-body to compute, cannot exceed the number of fragments in the moleucle.
:type ptype: str
:param ptype: ``'energy'`` || ``'gradient'`` || ``'hessian'``
Type of the procedure passed in.
:type return_total_data: :ref:`boolean <op_py_boolean>`
:param return_total_data: ``'on'`` || |dl| ``'off'`` |dr|
If True returns the total data (energy/gradient/etc) of the system,
otherwise returns interaction data.
:type levels: dict
:param levels: ``{1: 'ccsd(t)', 2: 'mp2', 'supersystem': 'scf'}`` || ``{1: 2, 2: 'ccsd(t)', 3: 'mp2'}`` || etc
Dictionary of different levels of theory for different levels of expansion
Note that method_string is not used in this case.
supersystem computes all higher order n-body effects up to nfragments.
:type embedding_charges: dict
:param embedding_charges: ``{1: [-0.834, 0.417, 0.417], ..}``
Dictionary of atom-centered point charges. keys: 1-based index of fragment, values: list of charges for each fragment.
:type charge_method: str
:param charge_method: ``scf/6-31g`` || ``b3lyp/6-31g*`` || etc
Method to compute point charges for monomers. Overridden by embedding_charges if both are provided.
:type charge_type: str
:param charge_type: ``MULLIKEN_CHARGES`` || ``LOWDIN_CHARGES``
Default is ``MULLIKEN_CHARGES``
"""
# Initialize dictionaries for easy data passing
metadata, component_results, nbody_results = {}, {}, {}
# Parse some kwargs
kwargs = p4util.kwargs_lower(kwargs)
if kwargs.get('levels', False):
return driver_nbody_helper.multi_level(func, **kwargs)
metadata['ptype'] = kwargs.pop('ptype', None)
metadata['return_wfn'] = kwargs.pop('return_wfn', False)
metadata['return_total_data'] = kwargs.pop('return_total_data', False)
metadata['molecule'] = kwargs.pop('molecule', core.get_active_molecule())
metadata['molecule'].update_geometry()
metadata['molecule'].fix_com(True)
metadata['molecule'].fix_orientation(True)
metadata['embedding_charges'] = kwargs.get('embedding_charges', False)
metadata['kwargs'] = kwargs
core.clean_variables()
if metadata['ptype'] not in ['energy', 'gradient', 'hessian']:
raise ValidationError(
"""N-Body driver: The ptype '%s' is not regonized.""" %
metadata['ptype'])
# Parse bsse_type, raise exception if not provided or unrecognized
metadata['bsse_type_list'] = kwargs.pop('bsse_type')
if metadata['bsse_type_list'] is None:
raise ValidationError("N-Body GUFunc: Must pass a bsse_type")
if not isinstance(metadata['bsse_type_list'], list):
metadata['bsse_type_list'] = [metadata['bsse_type_list']]
for num, btype in enumerate(metadata['bsse_type_list']):
metadata['bsse_type_list'][num] = btype.lower()
if btype.lower() not in ['cp', 'nocp', 'vmfc']:
raise ValidationError(
"N-Body GUFunc: bsse_type '%s' is not recognized" %
btype.lower())
metadata['max_nbody'] = kwargs.get('max_nbody', -1)
if metadata['molecule'].nfragments() == 1:
raise ValidationError(
"N-Body requires active molecule to have more than 1 fragment.")
metadata['max_frag'] = metadata['molecule'].nfragments()
if metadata['max_nbody'] == -1:
metadata['max_nbody'] = metadata['molecule'].nfragments()
else:
metadata['max_nbody'] = min(metadata['max_nbody'],
metadata['max_frag'])
# Flip this off for now, needs more testing
# If we are doing CP lets save them integrals
#if 'cp' in bsse_type_list and (len(bsse_type_list) == 1):
# # Set to save RI integrals for repeated full-basis computations
# ri_ints_io = core.get_global_option('DF_INTS_IO')
# # inquire if above at all applies to dfmp2 or just scf
# core.set_global_option('DF_INTS_IO', 'SAVE')
# psioh = core.IOManager.shared_object()
# psioh.set_specific_retention(97, True)
bsse_str = metadata['bsse_type_list'][0]
if len(metadata['bsse_type_list']) > 1:
bsse_str = str(metadata['bsse_type_list'])
core.print_out("\n\n")
core.print_out(" ===> N-Body Interaction Abacus <===\n")
core.print_out(" BSSE Treatment: %s\n" %
bsse_str)
# Get compute list
metadata = build_nbody_compute_list(metadata)
# Compute N-Body components
component_results = compute_nbody_components(func, method_string, metadata)
# Assemble N-Body quantities
nbody_results = assemble_nbody_components(metadata, component_results)
# Build wfn and bind variables
wfn = core.Wavefunction.build(metadata['molecule'], 'def2-svp')
dicts = [
'energies', 'ptype', 'intermediates', 'energy_body_dict',
'gradient_body_dict', 'hessian_body_dict', 'nbody',
'cp_energy_body_dict', 'nocp_energy_body_dict', 'vmfc_energy_body_dict'
]
if metadata['ptype'] == 'gradient':
wfn.set_gradient(nbody_results['ret_ptype'])
nbody_results['gradient_body_dict'] = nbody_results['ptype_body_dict']
elif metadata['ptype'] == 'hessian':
nbody_results['hessian_body_dict'] = nbody_results['ptype_body_dict']
wfn.set_hessian(nbody_results['ret_ptype'])
component_results_gradient = component_results.copy()
component_results_gradient['ptype'] = component_results_gradient[
'gradients']
metadata['ptype'] = 'gradient'
nbody_results_gradient = assemble_nbody_components(
metadata, component_results_gradient)
wfn.set_gradient(nbody_results_gradient['ret_ptype'])
nbody_results['gradient_body_dict'] = nbody_results_gradient[
'ptype_body_dict']
for r in [component_results, nbody_results]:
for d in r:
if d in dicts:
for var, value in r[d].items():
try:
wfn.set_scalar_variable(str(var), value)
core.set_scalar_variable(str(var), value)
except:
wfn.set_array_variable(
d.split('_')[0].upper() + ' ' + str(var),
core.Matrix.from_array(value))
core.set_variable("CURRENT ENERGY", nbody_results['ret_energy'])
wfn.set_variable("CURRENT ENERGY", nbody_results['ret_energy'])
if metadata['ptype'] == 'gradient':
core.set_variable("CURRENT GRADIENT", nbody_results['ret_ptype'])
elif metadata['ptype'] == 'hessian':
core.set_variable("CURRENT HESSIAN", nbody_results['ret_ptype'])
if metadata['return_wfn']:
return (nbody_results['ret_ptype'], wfn)
else:
return nbody_results['ret_ptype']
def nbody_gufunc(func, method_string, **kwargs):
"""
Computes the nbody interaction energy, gradient, or Hessian depending on input.
This is a generalized univeral function for computing interaction quantities.
:returns: *return type of func* |w--w| The interaction data.
:returns: (*float*, :py:class:`~psi4.core.Wavefunction`) |w--w| interaction data and wavefunction with energy/gradient/hessian set appropriately when **return_wfn** specified.
:type func: function
:param func: ``energy`` || etc.
Python function that accepts method_string and a molecule. Returns a
energy, gradient, or Hessian as requested.
:type method_string: string
:param method_string: ``'scf'`` || ``'mp2'`` || ``'ci5'`` || etc.
First argument, lowercase and usually unlabeled. Indicates the computational
method to be passed to func.
:type molecule: :ref:`molecule <op_py_molecule>`
:param molecule: ``h2o`` || etc.
The target molecule, if not the last molecule defined.
:type return_wfn: :ref:`boolean <op_py_boolean>`
:param return_wfn: ``'on'`` || |dl| ``'off'`` |dr|
Indicate to additionally return the :py:class:`~psi4.core.Wavefunction`
calculation result as the second element of a tuple.
:type bsse_type: string or list
:param bsse_type: ``'cp'`` || ``['nocp', 'vmfc']`` || |dl| ``None`` |dr| || etc.
Type of BSSE correction to compute: CP, NoCP, or VMFC. The first in this
list is returned by this function. By default, this function is not called.
:type max_nbody: int
:param max_nbody: ``3`` || etc.
Maximum n-body to compute, cannot exceed the number of fragments in the moleucle.
:type ptype: string
:param ptype: ``'energy'`` || ``'gradient'`` || ``'hessian'``
Type of the procedure passed in.
:type return_total_data: :ref:`boolean <op_py_boolean>`
:param return_total_data: ``'on'`` || |dl| ``'off'`` |dr|
If True returns the total data (energy/gradient/etc) of the system,
otherwise returns interaction data.
"""
### ==> Parse some kwargs <==
kwargs = p4util.kwargs_lower(kwargs)
return_wfn = kwargs.pop('return_wfn', False)
ptype = kwargs.pop('ptype', None)
return_total_data = kwargs.pop('return_total_data', False)
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
core.clean_variables()
if ptype not in ['energy', 'gradient', 'hessian']:
raise ValidationError("""N-Body driver: The ptype '%s' is not regonized.""" % ptype)
# Figure out BSSE types
do_cp = False
do_nocp = False
do_vmfc = False
return_method = False
# Must be passed bsse_type
bsse_type_list = kwargs.pop('bsse_type')
if bsse_type_list is None:
raise ValidationError("N-Body GUFunc: Must pass a bsse_type")
if not isinstance(bsse_type_list, list):
bsse_type_list = [bsse_type_list]
for num, btype in enumerate(bsse_type_list):
if btype.lower() == 'cp':
do_cp = True
if (num == 0): return_method = 'cp'
elif btype.lower() == 'nocp':
do_nocp = True
if (num == 0): return_method = 'nocp'
elif btype.lower() == 'vmfc':
do_vmfc = True
if (num == 0): return_method = 'vmfc'
else:
raise ValidationError("N-Body GUFunc: bsse_type '%s' is not recognized" % btype.lower())
max_nbody = kwargs.get('max_nbody', -1)
max_frag = molecule.nfragments()
if max_nbody == -1:
max_nbody = molecule.nfragments()
else:
max_nbody = min(max_nbody, max_frag)
# What levels do we need?
nbody_range = range(1, max_nbody + 1)
fragment_range = range(1, max_frag + 1)
# Flip this off for now, needs more testing
# If we are doing CP lets save them integrals
#if 'cp' in bsse_type_list and (len(bsse_type_list) == 1):
# # Set to save RI integrals for repeated full-basis computations
# ri_ints_io = core.get_global_option('DF_INTS_IO')
# # inquire if above at all applies to dfmp2 or just scf
# core.set_global_option('DF_INTS_IO', 'SAVE')
# psioh = core.IOManager.shared_object()
# psioh.set_specific_retention(97, True)
bsse_str = bsse_type_list[0]
if len(bsse_type_list) >1:
bsse_str = str(bsse_type_list)
core.print_out("\n\n")
core.print_out(" ===> N-Body Interaction Abacus <===\n")
core.print_out(" BSSE Treatment: %s\n" % bsse_str)
cp_compute_list = {x:set() for x in nbody_range}
nocp_compute_list = {x:set() for x in nbody_range}
vmfc_compute_list = {x:set() for x in nbody_range}
vmfc_level_list = {x:set() for x in nbody_range} # Need to sum something slightly different
# Build up compute sets
if do_cp:
# Everything is in dimer basis
basis_tuple = tuple(fragment_range)
for nbody in nbody_range:
for x in it.combinations(fragment_range, nbody):
cp_compute_list[nbody].add( (x, basis_tuple) )
if do_nocp:
# Everything in monomer basis
for nbody in nbody_range:
for x in it.combinations(fragment_range, nbody):
nocp_compute_list[nbody].add( (x, x) )
if do_vmfc:
# Like a CP for all combinations of pairs or greater
for nbody in nbody_range:
for cp_combos in it.combinations(fragment_range, nbody):
basis_tuple = tuple(cp_combos)
for interior_nbody in nbody_range:
for x in it.combinations(cp_combos, interior_nbody):
combo_tuple = (x, basis_tuple)
vmfc_compute_list[interior_nbody].add( combo_tuple )
vmfc_level_list[len(basis_tuple)].add( combo_tuple )
# Build a comprehensive compute_range
compute_list = {x:set() for x in nbody_range}
for n in nbody_range:
compute_list[n] |= cp_compute_list[n]
compute_list[n] |= nocp_compute_list[n]
compute_list[n] |= vmfc_compute_list[n]
core.print_out(" Number of %d-body computations: %d\n" % (n, len(compute_list[n])))
# Build size and slices dictionaries
fragment_size_dict = {frag: molecule.extract_subsets(frag).natom() for
frag in range(1, max_frag+1)}
start = 0
fragment_slice_dict = {}
for k, v in fragment_size_dict.items():
fragment_slice_dict[k] = slice(start, start + v)
start += v
molecule_total_atoms = sum(fragment_size_dict.values())
# Now compute the energies
energies_dict = {}
ptype_dict = {}
for n in 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)
ptype_dict[pair] = func(method_string, molecule=current_mol, **kwargs)
energies_dict[pair] = core.get_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()
# Final dictionaries
cp_energy_by_level = {n: 0.0 for n in nbody_range}
nocp_energy_by_level = {n: 0.0 for n in nbody_range}
cp_energy_body_dict = {n: 0.0 for n in nbody_range}
nocp_energy_body_dict = {n: 0.0 for n in nbody_range}
vmfc_energy_body_dict = {n: 0.0 for n in nbody_range}
# Build out ptype dictionaries if needed
if ptype != 'energy':
if ptype == 'gradient':
arr_shape = (molecule_total_atoms, 3)
elif ptype == 'hessian':
arr_shape = (molecule_total_atoms * 3, molecule_total_atoms * 3)
else:
raise KeyError("N-Body: ptype '%s' not recognized" % ptype)
cp_ptype_by_level = {n: np.zeros(arr_shape) for n in nbody_range}
nocp_ptype_by_level = {n: np.zeros(arr_shape) for n in nbody_range}
vmfc_ptype_by_level = {n: np.zeros(arr_shape) for n in nbody_range}
cp_ptype_body_dict = {n: np.zeros(arr_shape) for n in nbody_range}
nocp_ptype_body_dict = {n: np.zeros(arr_shape) for n in nbody_range}
vmfc_ptype_body_dict = {n: np.zeros(arr_shape) for n in nbody_range}
else:
cp_ptype_by_level, cp_ptype_body_dict = None, None
nocp_ptype_by_level, nocp_ptype_body_dict = None, None
vmfc_ptype_body_dict = None
# Sum up all of the levels
for n in nbody_range:
# Energy
cp_energy_by_level[n] = sum(energies_dict[v] for v in cp_compute_list[n])
nocp_energy_by_level[n] = sum(energies_dict[v] for v in nocp_compute_list[n])
# Special vmfc case
if n > 1:
vmfc_energy_body_dict[n] = vmfc_energy_body_dict[n - 1]
for tup in vmfc_level_list[n]:
vmfc_energy_body_dict[n] += ((-1) ** (n - len(tup[0]))) * energies_dict[tup]
# Do ptype
if ptype != 'energy':
_sum_cluster_ptype_data(ptype, ptype_dict, cp_compute_list[n],
fragment_slice_dict, fragment_size_dict,
cp_ptype_by_level[n])
_sum_cluster_ptype_data(ptype, ptype_dict, nocp_compute_list[n],
fragment_slice_dict, fragment_size_dict,
nocp_ptype_by_level[n])
_sum_cluster_ptype_data(ptype, ptype_dict, vmfc_level_list[n],
fragment_slice_dict, fragment_size_dict,
vmfc_ptype_by_level[n], vmfc=True)
# Compute cp energy and ptype
if do_cp:
for n in nbody_range:
if n == max_frag:
cp_energy_body_dict[n] = cp_energy_by_level[n]
if ptype != 'energy':
cp_ptype_body_dict[n][:] = cp_ptype_by_level[n]
continue
for k in range(1, n + 1):
take_nk = nCr(max_frag - k - 1, n - k)
sign = ((-1) ** (n - k))
value = cp_energy_by_level[k]
cp_energy_body_dict[n] += take_nk * sign * value
if ptype != 'energy':
value = cp_ptype_by_level[k]
cp_ptype_body_dict[n] += take_nk * sign * value
_print_nbody_energy(cp_energy_body_dict, "Counterpoise Corrected (CP)")
cp_interaction_energy = cp_energy_body_dict[max_nbody] - cp_energy_body_dict[1]
core.set_variable('Counterpoise Corrected Total Energy', cp_energy_body_dict[max_nbody])
core.set_variable('Counterpoise Corrected Interaction Energy', cp_interaction_energy)
for n in nbody_range[1:]:
var_key = 'CP-CORRECTED %d-BODY INTERACTION ENERGY' % n
core.set_variable(var_key, cp_energy_body_dict[n] - cp_energy_body_dict[1])
# Compute nocp energy and ptype
if do_nocp:
for n in nbody_range:
if n == max_frag:
nocp_energy_body_dict[n] = nocp_energy_by_level[n]
if ptype != 'energy':
nocp_ptype_body_dict[n][:] = nocp_ptype_by_level[n]
continue
for k in range(1, n + 1):
take_nk = nCr(max_frag - k - 1, n - k)
sign = ((-1) ** (n - k))
value = nocp_energy_by_level[k]
nocp_energy_body_dict[n] += take_nk * sign * value
if ptype != 'energy':
value = nocp_ptype_by_level[k]
nocp_ptype_body_dict[n] += take_nk * sign * value
_print_nbody_energy(nocp_energy_body_dict, "Non-Counterpoise Corrected (NoCP)")
nocp_interaction_energy = nocp_energy_body_dict[max_nbody] - nocp_energy_body_dict[1]
core.set_variable('Non-Counterpoise Corrected Total Energy', nocp_energy_body_dict[max_nbody])
core.set_variable('Non-Counterpoise Corrected Interaction Energy', nocp_interaction_energy)
for n in nbody_range[1:]:
var_key = 'NOCP-CORRECTED %d-BODY INTERACTION ENERGY' % n
core.set_variable(var_key, nocp_energy_body_dict[n] - nocp_energy_body_dict[1])
# Compute vmfc energy and ptype
if do_vmfc:
_print_nbody_energy(vmfc_energy_body_dict, "Valiron-Mayer Function Couterpoise (VMFC)")
vmfc_interaction_energy = vmfc_energy_body_dict[max_nbody] - vmfc_energy_body_dict[1]
core.set_variable('Valiron-Mayer Function Couterpoise Total Energy', vmfc_energy_body_dict[max_nbody])
core.set_variable('Valiron-Mayer Function Couterpoise Interaction Energy', vmfc_interaction_energy)
for n in nbody_range[1:]:
var_key = 'VMFC-CORRECTED %d-BODY INTERACTION ENERGY' % n
core.set_variable(var_key, vmfc_energy_body_dict[n] - vmfc_energy_body_dict[1])
if return_method == 'cp':
ptype_body_dict = cp_ptype_body_dict
energy_body_dict = cp_energy_body_dict
elif return_method == 'nocp':
ptype_body_dict = nocp_ptype_body_dict
energy_body_dict = nocp_energy_body_dict
elif return_method == 'vmfc':
ptype_body_dict = vmfc_ptype_body_dict
energy_body_dict = vmfc_energy_body_dict
else:
raise ValidationError("N-Body Wrapper: Invalid return type. Should never be here, please post this error on github.")
# Figure out and build return types
if return_total_data:
ret_energy = energy_body_dict[max_nbody]
else:
ret_energy = energy_body_dict[max_nbody]
ret_energy -= energy_body_dict[1]
if ptype != 'energy':
if return_total_data:
np_final_ptype = ptype_body_dict[max_nbody].copy()
else:
np_final_ptype = ptype_body_dict[max_nbody].copy()
np_final_ptype -= ptype_body_dict[1]
ret_ptype = core.Matrix.from_array(np_final_ptype)
else:
ret_ptype = ret_energy
# Build and set a wavefunction
wfn = core.Wavefunction.build(molecule, 'sto-3g')
wfn.nbody_energy = energies_dict
wfn.nbody_ptype = ptype_dict
wfn.nbody_body_energy = energy_body_dict
wfn.nbody_body_ptype = ptype_body_dict
if ptype == 'gradient':
wfn.set_gradient(ret_ptype)
elif ptype == 'hessian':
wfn.set_hessian(ret_ptype)
core.set_variable("CURRENT ENERGY", ret_energy)
if return_wfn:
return (ret_ptype, wfn)
else:
return ret_ptype
def nbody_gufunc(func, method_string, **kwargs):
"""
Computes the nbody interaction energy, gradient, or Hessian depending on input.
This is a generalized univeral function for computing interaction and total quantities.
:returns: *return type of func* |w--w| The data.
:returns: (*float*, :py:class:`~psi4.core.Wavefunction`) |w--w| data and wavefunction with energy/gradient/hessian set appropriately when **return_wfn** specified.
:type func: function
:param func: ``energy`` || etc.
Python function that accepts method_string and a molecule. Returns a
energy, gradient, or Hessian as requested.
:type method_string: string
:param method_string: ``'scf'`` || ``'mp2'`` || ``'ci5'`` || etc.
First argument, lowercase and usually unlabeled. Indicates the computational
method to be passed to func.
:type molecule: :ref:`molecule <op_py_molecule>`
:param molecule: ``h2o`` || etc.
The target molecule, if not the last molecule defined.
:type return_wfn: :ref:`boolean <op_py_boolean>`
:param return_wfn: ``'on'`` || |dl| ``'off'`` |dr|
Indicate to additionally return the :py:class:`~psi4.core.Wavefunction`
calculation result as the second element of a tuple.
:type bsse_type: string or list
:param bsse_type: ``'cp'`` || ``['nocp', 'vmfc']`` || |dl| ``None`` |dr| || etc.
Type of BSSE correction to compute: CP, NoCP, or VMFC. The first in this
list is returned by this function. By default, this function is not called.
:type max_nbody: int
:param max_nbody: ``3`` || etc.
Maximum n-body to compute, cannot exceed the number of fragments in the moleucle.
:type ptype: string
:param ptype: ``'energy'`` || ``'gradient'`` || ``'hessian'``
Type of the procedure passed in.
:type return_total_data: :ref:`boolean <op_py_boolean>`
:param return_total_data: ``'on'`` || |dl| ``'off'`` |dr|
If True returns the total data (energy/gradient/etc) of the system,
otherwise returns interaction data.
:type levels: dict
:param levels: ``{1: 'ccsd(t)', 2: 'mp2', 'supersystem': 'scf'}`` || ``{1: 2, 2: 'ccsd(t)', 3: 'mp2'}`` || etc
Dictionary of different levels of theory for different levels of expansion
Note that method_string is not used in this case.
supersystem computes all higher order n-body effects up to nfragments.
:type embedding_charges: dict
:param embedding_charges: ``{1: [-0.834, 0.417, 0.417], ..}``
Dictionary of atom-centered point charges. keys: 1-based index of fragment, values: list of charges for each fragment.
:type charge_method: string
:param charge_method: ``scf/6-31g`` || ``b3lyp/6-31g*`` || etc
Method to compute point charges for monomers. Overridden by embedding_charges if both are provided.
:type charge_type: string
:param charge_type: ``MULLIKEN_CHARGES`` || ``LOWDIN_CHARGES``
Default is ``MULLIKEN_CHARGES``
"""
# Initialize dictionaries for easy data passing
metadata, component_results, nbody_results = {}, {}, {}
# Parse some kwargs
kwargs = p4util.kwargs_lower(kwargs)
if kwargs.get('levels', False):
return driver_nbody_helper.multi_level(func, **kwargs)
metadata['ptype'] = kwargs.pop('ptype', None)
metadata['return_wfn'] = kwargs.pop('return_wfn', False)
metadata['return_total_data'] = kwargs.pop('return_total_data', False)
metadata['molecule'] = kwargs.pop('molecule', core.get_active_molecule())
metadata['molecule'].update_geometry()
metadata['molecule'].fix_com(True)
metadata['molecule'].fix_orientation(True)
metadata['embedding_charges'] = kwargs.get('embedding_charges', False)
metadata['kwargs'] = kwargs
core.clean_variables()
if metadata['ptype'] not in ['energy', 'gradient', 'hessian']:
raise ValidationError("""N-Body driver: The ptype '%s' is not regonized.""" % metadata['ptype'])
# Parse bsse_type, raise exception if not provided or unrecognized
metadata['bsse_type_list'] = kwargs.pop('bsse_type')
if metadata['bsse_type_list'] is None:
raise ValidationError("N-Body GUFunc: Must pass a bsse_type")
if not isinstance(metadata['bsse_type_list'], list):
metadata['bsse_type_list'] = [metadata['bsse_type_list']]
for num, btype in enumerate(metadata['bsse_type_list']):
metadata['bsse_type_list'][num] = btype.lower()
if btype.lower() not in ['cp', 'nocp', 'vmfc']:
raise ValidationError("N-Body GUFunc: bsse_type '%s' is not recognized" % btype.lower())
metadata['max_nbody'] = kwargs.get('max_nbody', -1)
metadata['max_frag'] = metadata['molecule'].nfragments()
if metadata['max_nbody'] == -1:
metadata['max_nbody'] = metadata['molecule'].nfragments()
else:
metadata['max_nbody'] = min(metadata['max_nbody'], metadata['max_frag'])
# Flip this off for now, needs more testing
# If we are doing CP lets save them integrals
#if 'cp' in bsse_type_list and (len(bsse_type_list) == 1):
# # Set to save RI integrals for repeated full-basis computations
# ri_ints_io = core.get_global_option('DF_INTS_IO')
# # inquire if above at all applies to dfmp2 or just scf
# core.set_global_option('DF_INTS_IO', 'SAVE')
# psioh = core.IOManager.shared_object()
# psioh.set_specific_retention(97, True)
bsse_str = metadata['bsse_type_list'][0]
if len(metadata['bsse_type_list']) > 1:
bsse_str = str(metadata['bsse_type_list'])
core.print_out("\n\n")
core.print_out(" ===> N-Body Interaction Abacus <===\n")
core.print_out(" BSSE Treatment: %s\n" % bsse_str)
# Get compute list
metadata = build_nbody_compute_list(metadata)
# Compute N-Body components
component_results = compute_nbody_components(func, method_string, metadata)
# Assemble N-Body quantities
nbody_results = assemble_nbody_components(metadata, component_results)
# Build wfn and bind variables
wfn = core.Wavefunction.build(metadata['molecule'], 'def2-svp')
dicts = [
'energies', 'ptype', 'intermediates', 'energy_body_dict', 'gradient_body_dict', 'hessian_body_dict', 'nbody',
'cp_energy_body_dict', 'nocp_energy_body_dict', 'vmfc_energy_body_dict'
]
if metadata['ptype'] == 'gradient':
wfn.set_gradient(nbody_results['ret_ptype'])
nbody_results['gradient_body_dict'] = nbody_results['ptype_body_dict']
elif metadata['ptype'] == 'hessian':
nbody_results['hessian_body_dict'] = nbody_results['ptype_body_dict']
wfn.set_hessian(nbody_results['ret_ptype'])
component_results_gradient = component_results.copy()
component_results_gradient['ptype'] = component_results_gradient['gradients']
metadata['ptype'] = 'gradient'
nbody_results_gradient = assemble_nbody_components(metadata, component_results_gradient)
wfn.set_gradient(nbody_results_gradient['ret_ptype'])
nbody_results['gradient_body_dict'] = nbody_results_gradient['ptype_body_dict']
for r in [component_results, nbody_results]:
for d in r:
if d in dicts:
for var, value in r[d].items():
try:
wfn.set_scalar_variable(str(var), value)
core.set_scalar_variable(str(var), value)
except:
wfn.set_array_variable(d.split('_')[0].upper() + ' ' + str(var), core.Matrix.from_array(value))
core.set_variable("CURRENT ENERGY", nbody_results['ret_energy'])
wfn.set_variable("CURRENT ENERGY", nbody_results['ret_energy'])
if metadata['return_wfn']:
return (nbody_results['ret_ptype'], wfn)
else:
return nbody_results['ret_ptype']
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 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_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 run_forte(name, **kwargs):
r"""Function encoding sequence of PSI module and plugin calls so that
forte can be called via :py:func:`~driver.energy`. For post-scf plugins.
>>> energy('forte')
"""
lowername = name.lower()
kwargs = p4util.kwargs_lower(kwargs)
# Compute a SCF reference, a wavefunction is return which holds the molecule used, orbitals
# Fock matrices, and more
ref_wfn = kwargs.get('ref_wfn', None)
if ref_wfn is None:
ref_wfn = psi4.driver.scf_helper(name, **kwargs)
# Get the option object
psi4_options = psi4.core.get_options()
psi4_options.set_current_module('FORTE')
# Get the forte option object
options = forte.forte_options
options.get_options_from_psi4(psi4_options)
if ('DF' in options.get_str('INT_TYPE')):
aux_basis = psi4.core.BasisSet.build(ref_wfn.molecule(), 'DF_BASIS_MP2',
options.get_str('DF_BASIS_MP2'),
'RIFIT', options.get_str('BASIS'))
ref_wfn.set_basisset('DF_BASIS_MP2', aux_basis)
if (options.get_str('MINAO_BASIS')):
minao_basis = psi4.core.BasisSet.build(ref_wfn.molecule(), 'MINAO_BASIS',
options.get_str('MINAO_BASIS'))
ref_wfn.set_basisset('MINAO_BASIS', minao_basis)
# Start Forte, initialize ambit
my_proc_n_nodes = forte.startup()
my_proc, n_nodes = my_proc_n_nodes
# Print the banner
forte.banner()
# Create the MOSpaceInfo object
mo_space_info = forte.make_mo_space_info(ref_wfn, options)
# Call methods that project the orbitals (AVAS, embedding)
mo_space_info = orbital_projection(ref_wfn, options, mo_space_info)
# Averaging spin multiplets if doing spin-adapted computation
if options.get_str('CORRELATION_SOLVER') == 'SA-MRDSRG':
options_dict = options.dict()
options_dict['SPIN_AVG_DENSITY']['value'] = True
options.set_dict(options_dict)
state = forte.make_state_info_from_psi_wfn(ref_wfn)
scf_info = forte.SCFInfo(ref_wfn)
state_weights_map = forte.make_state_weights_map(options,ref_wfn)
# Run a method
job_type = options.get_str('JOB_TYPE')
energy = 0.0
if job_type == 'NONE':
forte.cleanup()
return ref_wfn
start_pre_ints = time.time()
# Make an integral object
ints = forte.make_forte_integrals(ref_wfn, options, mo_space_info)
start = time.time()
# Rotate orbitals before computation (e.g. localization, MP2 natural orbitals, etc.)
orb_type = options.get_str("ORBITAL_TYPE")
if orb_type != 'CANONICAL':
orb_t = forte.make_orbital_transformation(orb_type, scf_info, options, ints, mo_space_info)
orb_t.compute_transformation()
Ua = orb_t.get_Ua()
Ub = orb_t.get_Ub()
ints.rotate_orbitals(Ua,Ub)
# Run a method
if (job_type == 'NEWDRIVER'):
energy = forte_driver(state_weights_map, scf_info, options, ints, mo_space_info)
else:
energy = forte.forte_old_methods(ref_wfn, options, ints, mo_space_info)
end = time.time()
# Close ambit, etc.
forte.cleanup()
psi4.core.set_scalar_variable('CURRENT ENERGY', energy)
psi4.core.print_out(f'\n\n Time to prepare integrals: {start - start_pre_ints:12.3f} seconds')
psi4.core.print_out(f'\n Time to run job : {end - start:12.3f} seconds')
psi4.core.print_out(f'\n Total : {end - start:12.3f} seconds')
return ref_wfn
def ip_fitting(name, omega_l=0.05, omega_r=2.5, omega_convergence=1.0e-3, maxiter=20, **kwargs):
"""Optimize DFT omega parameter for molecular system.
Parameters
----------
name : string or function
DFT functional string name or function defining functional
whose omega is to be optimized.
omega_l : float, optional
Minimum omega to be considered during fitting.
omega_r : float, optional
Maximum omega to be considered during fitting.
molecule : :ref:`molecule <op_py_molecule>`, optional
Target molecule (neutral) for which omega is to be tuned, if not last defined.
omega_convergence : float, optional
Threshold below which to consider omega converged. (formerly omega_tolerance)
maxiter : int, optional
Maximum number of iterations towards omega convergence.
Returns
-------
float
Optimal omega parameter.
"""
optstash = p4util.OptionsState(
['SCF', 'REFERENCE'],
['SCF', 'GUESS'],
['SCF', 'DF_INTS_IO'],
['SCF', 'DFT_OMEGA'],
['DOCC'],
['SOCC'])
kwargs = p4util.kwargs_lower(kwargs)
# By default, do not read previous 180 orbitals file
read = False
read180 = ''
if 'read' in kwargs:
read = True
read180 = kwargs['read']
if core.get_option('SCF', 'REFERENCE') != 'UKS':
core.print_out(""" Requested procedure `ip_fitting` runs further calculations with UKS reference.\n""")
core.set_local_option('SCF', 'REFERENCE', 'UKS')
# Make sure the molecule the user provided is the active one, and neutral
molecule = kwargs.pop('molecule', core.get_active_molecule())
molecule.update_geometry()
if molecule.molecular_charge() != 0:
raise ValidationError("""IP Fitting requires neutral molecule to start.""")
if molecule.schoenflies_symbol() != 'c1':
core.print_out(""" Requested procedure `ip_fitting` does not make use of molecular symmetry: """
"""further calculations in C1 point group.\n""")
molecule = molecule.clone()
molecule.reset_point_group('c1')
molecule.update_geometry()
charge0 = molecule.molecular_charge()
mult0 = molecule.multiplicity()
# How many electrons are there?
N = 0
for A in range(molecule.natom()):
N += molecule.Z(A)
N -= charge0
N = int(N)
Nb = int((N - mult0 + 1) / 2)
Na = int(N - Nb)
# Work in the ot namespace for this procedure
core.IO.set_default_namespace("ot")
# Burn in to determine orbital eigenvalues
if read:
core.set_local_option("SCF", "GUESS", "READ")
copy_file_to_scratch(read180, 'psi', 'ot', 180)
core.set_local_option("SCF", "DF_INTS_IO", "SAVE")
E, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
banner='IP Fitting SCF: Burn-in', **kwargs)
core.set_local_option("SCF", "DF_INTS_IO", "LOAD")
if not wfn.functional().is_x_lrc():
raise ValidationError("""Not sensible to optimize omega for non-long-range-correction functional.""")
# Determine H**O, to determine mult1
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Na == Nb:
H**O = -Nb
elif Nb == 0:
H**O = Na
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
if E_a >= E_b:
H**O = Na
else:
H**O = -Nb
Na1 = Na
Nb1 = Nb
if H**O > 0:
Na1 -= 1
else:
Nb1 -= 1
charge1 = charge0 + 1
mult1 = Na1 - Nb1 + 1
omegas = []
E0s = []
E1s = []
kIPs = []
IPs = []
types = []
# Right endpoint
core.set_local_option('SCF', 'DFT_OMEGA', omega_r)
# Neutral
if read:
core.set_local_option("SCF", "GUESS", "READ")
p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
E0r, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
banner='IP Fitting SCF: Neutral, Right Endpoint', **kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
E_HOMOr = E_HOMO
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
if read:
core.set_local_option("SCF", "GUESS", "READ")
p4util.copy_file_to_scratch(read180, 'psi', 'ot', 180)
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
E1r = driver.energy('scf', dft_functional=name, molecule=molecule,
banner='IP Fitting SCF: Cation, Right Endpoint', **kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IPr = E1r - E0r
kIPr = -E_HOMOr
delta_r = IPr - kIPr
if IPr > kIPr:
raise ValidationError("""\n***IP Fitting Error: Right Omega limit should have kIP > IP: {} !> {}""".format(kIPr, IPr))
omegas.append(omega_r)
types.append('Right Limit')
E0s.append(E0r)
E1s.append(E1r)
IPs.append(IPr)
kIPs.append(kIPr)
# Use previous orbitals from here out
core.set_local_option("SCF", "GUESS", "READ")
# Left endpoint
core.set_local_option('SCF', 'DFT_OMEGA', omega_l)
# Neutral
core.IO.change_file_namespace(180, "neutral", "ot")
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
core.set_global_option("DOCC", [Nb])
core.set_global_option("SOCC", [Na - Nb])
E0l, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
banner='IP Fitting SCF: Neutral, Left Endpoint', **kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
E_HOMOl = E_HOMO
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
core.IO.change_file_namespace(180, "cation", "ot")
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
core.set_global_option("DOCC", [Nb1])
core.set_global_option("SOCC", [Na1 - Nb1])
E1l = driver.energy('scf', dft_functional=name, molecule=molecule,
banner='IP Fitting SCF: Cation, Left Endpoint', **kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IPl = E1l - E0l
kIPl = -E_HOMOl
delta_l = IPl - kIPl
if IPl < kIPl:
raise ValidationError("""\n***IP Fitting Error: Left Omega limit should have kIP < IP: {} !< {}""".format(kIPl, IPl))
omegas.append(omega_l)
types.append('Left Limit')
E0s.append(E0l)
E1s.append(E1l)
IPs.append(IPl)
kIPs.append(kIPl)
converged = False
repeat_l = 0
repeat_r = 0
for step in range(maxiter):
# Regula Falsi (modified)
if repeat_l > 1:
delta_l /= 2.0
if repeat_r > 1:
delta_r /= 2.0
omega = - (omega_r - omega_l) / (delta_r - delta_l) * delta_l + omega_l
core.set_local_option('SCF', 'DFT_OMEGA', omega)
# Neutral
core.IO.change_file_namespace(180, "neutral", "ot")
molecule.set_molecular_charge(charge0)
molecule.set_multiplicity(mult0)
core.set_global_option("DOCC", [Nb])
core.set_global_option("SOCC", [Na - Nb])
E0, wfn = driver.energy('scf', dft_functional=name, return_wfn=True, molecule=molecule,
banner='IP Fitting SCF: Neutral, Omega = {:11.3E}'.format(omega), **kwargs)
eps_a = wfn.epsilon_a()
eps_b = wfn.epsilon_b()
if Nb == 0:
E_HOMO = eps_a.np[int(Na - 1)]
else:
E_a = eps_a.np[int(Na - 1)]
E_b = eps_b.np[int(Nb - 1)]
E_HOMO = max(E_a, E_b)
core.IO.change_file_namespace(180, "ot", "neutral")
# Cation
core.IO.change_file_namespace(180, "cation", "ot")
molecule.set_molecular_charge(charge1)
molecule.set_multiplicity(mult1)
core.set_global_option("DOCC", [Nb1])
core.set_global_option("SOCC", [Na1 - Nb1])
E1 = driver.energy('scf', dft_functional=name, molecule=molecule,
banner='IP Fitting SCF: Cation, Omega = {:11.3E}'.format(omega), **kwargs)
core.IO.change_file_namespace(180, "ot", "cation")
IP = E1 - E0
kIP = -E_HOMO
delta = IP - kIP
if kIP > IP:
omega_r = omega
E0r = E0
E1r = E1
IPr = IP
kIPr = kIP
delta_r = delta
repeat_r = 0
repeat_l += 1
else:
omega_l = omega
E0l = E0
E1l = E1
IPl = IP
kIPl = kIP
delta_l = delta
repeat_l = 0
repeat_r += 1
omegas.append(omega)
types.append('Regula-Falsi')
E0s.append(E0)
E1s.append(E1)
IPs.append(IP)
kIPs.append(kIP)
# Termination
if abs(omega_l - omega_r) < omega_convergence:
converged = True
break
core.IO.set_default_namespace("")
core.print_out("""\n ==> IP Fitting Results <==\n\n""")
core.print_out(""" => Occupation Determination <= \n\n""")
core.print_out(""" %6s %6s %6s %6s %6s %6s\n""" % ('N', 'Na', 'Nb', 'Charge', 'Mult', 'H**O'))
core.print_out(""" Neutral: %6d %6d %6d %6d %6d %6d\n""" % (N, Na, Nb, charge0, mult0, H**O))
core.print_out(""" Cation: %6d %6d %6d %6d %6d\n\n""" % (N - 1, Na1, Nb1, charge1, mult1))
core.print_out(""" => Regula Falsi Iterations <=\n\n""")
core.print_out(""" %3s %11s %14s %14s %14s %s\n""" % ('N','Omega','IP','kIP','Delta','Type'))
for k in range(len(omegas)):
core.print_out(""" %3d %11.3E %14.6E %14.6E %14.6E %s\n""" %
(k + 1, omegas[k], IPs[k], kIPs[k], IPs[k] - kIPs[k], types[k]))
optstash.restore()
if converged:
core.print_out("""\n IP Fitting Converged\n""")
core.print_out(""" Final omega = %14.6E\n""" % ((omega_l + omega_r) / 2))
core.print_out("""\n "M,I. does the dying. Fleet just does the flying."\n""")
core.print_out(""" -Starship Troopers\n""")
else:
raise ConvergenceError("""IP Fitting """, step + 1)
return ((omega_l + omega_r) / 2)