def compute_energy(self, molecule: 'psi4.core.Molecule', wfn: 'psi4.core.Wavefunction' = None) -> float:
"""Compute dispersion energy based on engine, dispersion level, and parameters in `self`.
Parameters
----------
molecule : psi4.core.Molecule
System for which to compute empirical dispersion correction.
wfn :
Location to set QCVariables
Returns
-------
float
Dispersion energy [Eh].
Notes
-----
DISPERSION CORRECTION ENERGY
Disp always set. Overridden in SCF finalization, but that only changes for "-3C" methods.
self.fctldash + DISPERSION CORRECTION ENERGY
Set if `fctldash` nonempty.
"""
if self.engine in ['dftd3', 'mp2d']:
resi = ResultInput(
**{
'driver': 'energy',
'model': {
'method': self.fctldash,
'basis': '(auto)',
},
'keywords': {
'level_hint': self.dashlevel,
'params_tweaks': self.dashparams,
'dashcoeff_supplement': self.dashcoeff_supplement,
'verbose': 1,
},
'molecule': molecule.to_schema(dtype=2),
'provenance': p4util.provenance_stamp(__name__),
})
jobrec = qcng.compute(resi, self.engine, raise_error=True)
dashd_part = float(jobrec.extras['qcvars']['DISPERSION CORRECTION ENERGY'])
if wfn is not None:
for k, qca in jobrec.extras['qcvars'].items():
if 'CURRENT' not in k:
wfn.set_variable(k, p4util.plump_qcvar(qca, k))
if self.fctldash in ['hf3c', 'pbeh3c']:
gcp_part = gcp.run_gcp(molecule, self.fctldash, verbose=False, dertype=0)
dashd_part += gcp_part
return dashd_part
else:
ene = self.disp.compute_energy(molecule)
core.set_variable('DISPERSION CORRECTION ENERGY', ene)
if self.fctldash:
core.set_variable('{} DISPERSION CORRECTION ENERGY'.format(self.fctldash), ene)
return ene
def compute_energy(self, molecule):
"""Compute dispersion energy based on engine, dispersion level, and parameters in `self`.
Parameters
----------
molecule : psi4.core.Molecule
System for which to compute empirical dispersion correction.
Returns
-------
float
Dispersion energy [Eh].
Notes
-----
DISPERSION CORRECTION ENERGY
Disp always set. Overridden in SCF finalization, but that only changes for "-3C" methods.
self.fctldash + DISPERSION CORRECTION ENERGY
Set if `fctldash` nonempty.
"""
if self.engine in ['dftd3', 'mp2d']:
resinp = {
'schema_name': 'qcschema_input',
'schema_version': 1,
'molecule': molecule.to_schema(dtype=2),
'driver': 'energy',
'model': {
'method': self.fctldash,
'basis': '(auto)',
},
'keywords': {
'level_hint': self.dashlevel,
'params_tweaks': self.dashparams,
'dashcoeff_supplement': self.dashcoeff_supplement,
'verbose': 1,
},
}
jobrec = qcng.compute(resinp, self.engine, raise_error=True)
jobrec = jobrec.dict()
dashd_part = float(jobrec['extras']['qcvars']['DISPERSION CORRECTION ENERGY'])
for k, qca in jobrec['extras']['qcvars'].items():
if not isinstance(qca, (list, np.ndarray)):
core.set_variable(k, qca)
if self.fctldash in ['hf3c', 'pbeh3c']:
gcp_part = gcp.run_gcp(molecule, self.fctldash, verbose=False, dertype=0)
dashd_part += gcp_part
return dashd_part
else:
ene = self.disp.compute_energy(molecule)
core.set_variable('DISPERSION CORRECTION ENERGY', ene)
if self.fctldash:
core.set_variable('{} DISPERSION CORRECTION ENERGY'.format(self.fctldash), ene)
return ene
def compute_energy(self, molecule):
"""Compute dispersion energy based on engine, dispersion level, and parameters in `self`.
Parameters
----------
molecule : psi4.core.Molecule
System for which to compute empirical dispersion correction.
Returns
-------
float
Dispersion energy [Eh].
Notes
-----
DISPERSION CORRECTION ENERGY
Disp always set. Overridden in SCF finalization, but that only changes for "-3C" methods.
self.fctldash + DISPERSION CORRECTION ENERGY
Set if `fctldash` nonempty.
"""
if self.engine == 'dftd3':
jobrec = intf_dftd3.run_dftd3_from_arrays(
molrec=molecule.to_dict(np_out=False),
name_hint=self.fctldash,
level_hint=self.dashlevel,
param_tweaks=self.dashparams,
dashcoeff_supplement=self.dashcoeff_supplement,
ptype='energy',
verbose=1)
dashd_part = float(
jobrec['qcvars']['DISPERSION CORRECTION ENERGY'].data)
for k, qca in jobrec['qcvars'].items():
if not isinstance(qca.data, np.ndarray):
core.set_variable(k, qca.data)
if self.fctldash in ['hf3c', 'pbeh3c']:
gcp_part = gcp.run_gcp(molecule,
self.fctldash,
verbose=False,
dertype=0)
dashd_part += gcp_part
return dashd_part
else:
ene = self.disp.compute_energy(molecule)
core.set_variable('DISPERSION CORRECTION ENERGY', ene)
if self.fctldash:
core.set_variable(
'{} DISPERSION CORRECTION ENERGY'.format(self.fctldash),
ene)
return ene
def compute_energy(self, molecule):
if self.disp_type == 'gr':
if self.alias in ['HF3C', 'PBEH3C']:
dashd_part = dftd3.run_dftd3(molecule, dashlvl=self.dtype.lower().replace('-', ''),
dashparam=self.dash_params, verbose=False, dertype=0)
gcp_part = gcp.run_gcp(molecule, self.alias.lower(), verbose=False, dertype=0)
return dashd_part + gcp_part
else:
return dftd3.run_dftd3(molecule, dashlvl=self.dtype.lower().replace('-', ''),
dashparam=self.dash_params, verbose=False, dertype=0)
else:
return self.disp.compute_energy(molecule)
def compute_gradient(self, molecule: 'psi4.core.Molecule',
wfn: 'psi4.core.Wavefunction' = None) -> 'psi4.core.Matrix':
"""Compute dispersion gradient based on engine, dispersion level, and parameters in `self`.
Parameters
----------
molecule : psi4.core.Molecule
System for which to compute empirical dispersion correction.
wfn :
Location to set QCVariables
Returns
-------
psi4.core.Matrix
(nat, 3) dispersion gradient [Eh/a0].
"""
if self.engine in ['dftd3', 'mp2d']:
resi = AtomicInput(
**{
'driver': 'gradient',
'model': {
'method': self.fctldash,
'basis': '(auto)',
},
'keywords': {
'level_hint': self.dashlevel,
'params_tweaks': self.dashparams,
'dashcoeff_supplement': self.dashcoeff_supplement,
'verbose': 1,
},
'molecule': molecule.to_schema(dtype=2),
'provenance': p4util.provenance_stamp(__name__),
})
jobrec = qcng.compute(resi, self.engine, raise_error=True,
local_options={"scratch_directory": core.IOManager.shared_object().get_default_path()})
dashd_part = core.Matrix.from_array(
np.array(jobrec.extras['qcvars']['DISPERSION CORRECTION GRADIENT']).reshape(-1, 3))
if wfn is not None:
for k, qca in jobrec.extras['qcvars'].items():
if 'CURRENT' not in k:
wfn.set_variable(k, p4util.plump_qcvar(qca, k))
if self.fctldash in ['hf3c', 'pbeh3c']:
gcp_part = gcp.run_gcp(molecule, self.fctldash, verbose=False, dertype=1)
dashd_part.add(gcp_part)
return dashd_part
else:
return self.disp.compute_gradient(molecule)
def compute_energy(self, molecule):
"""Compute dispersion energy based on engine, dispersion level, and parameters in `self`.
Parameters
----------
molecule : psi4.core.Molecule
System for which to compute empirical dispersion correction.
Returns
-------
float
Dispersion energy [Eh].
Notes
-----
DISPERSION CORRECTION ENERGY
Disp always set. Overridden in SCF finalization, but that only changes for "-3C" methods.
self.fctldash + DISPERSION CORRECTION ENERGY
Set if `fctldash` nonempty.
"""
if self.engine == 'dftd3':
jobrec = intf_dftd3.run_dftd3_from_arrays(
molrec=molecule.to_dict(np_out=False),
name_hint=self.fctldash,
level_hint=self.dashlevel,
param_tweaks=self.dashparams,
dashcoeff_supplement=self.dashcoeff_supplement,
ptype='energy',
verbose=1)
dashd_part = float(jobrec['qcvars']['DISPERSION CORRECTION ENERGY'].data)
for k, qca in jobrec['qcvars'].items():
if not isinstance(qca.data, np.ndarray):
core.set_variable(k, qca.data)
if self.fctldash in ['hf3c', 'pbeh3c']:
gcp_part = gcp.run_gcp(molecule, self.fctldash, verbose=False, dertype=0)
dashd_part += gcp_part
return dashd_part
else:
ene = self.disp.compute_energy(molecule)
core.set_variable('DISPERSION CORRECTION ENERGY', ene)
if self.fctldash:
core.set_variable('{} DISPERSION CORRECTION ENERGY'.format(self.fctldash), ene)
return ene
def compute_gradient(self, molecule):
"""Compute dispersion gradient based on engine, dispersion level, and parameters in `self`.
Parameters
----------
molecule : psi4.core.Molecule
System for which to compute empirical dispersion correction.
Returns
-------
psi4.core.Matrix
(nat, 3) dispersion gradient [Eh/a0].
"""
if self.engine in ['dftd3', 'mp2d']:
resinp = {
'schema_name': 'qcschema_input',
'schema_version': 1,
'molecule': molecule.to_schema(dtype=2),
'driver': 'gradient',
'model': {
'method': self.fctldash,
'basis': '(auto)',
},
'keywords': {
'level_hint': self.dashlevel,
'params_tweaks': self.dashparams,
'dashcoeff_supplement': self.dashcoeff_supplement,
'verbose': 1,
},
}
jobrec = qcng.compute(resinp, self.engine, raise_error=True)
jobrec = jobrec.dict()
dashd_part = core.Matrix.from_array(np.array(jobrec['extras']['qcvars']['DISPERSION CORRECTION GRADIENT']).reshape(-1, 3))
for k, qca in jobrec['extras']['qcvars'].items():
if not isinstance(qca, (list, np.ndarray)):
core.set_variable(k, qca)
if self.fctldash in ['hf3c', 'pbeh3c']:
gcp_part = gcp.run_gcp(molecule, self.fctldash, verbose=False, dertype=1)
dashd_part.add(gcp_part)
return dashd_part
else:
return self.disp.compute_gradient(molecule)
def compute_gradient(self, molecule):
if self.disp_type == 'gr':
if self.alias in ['hf3c', 'pbeh3c']:
dashd_part = dftd3.run_dftd3(
molecule,
dashlvl=self.dtype.lower().replace('-', ''),
dashparam=self.dash_params,
verbose=False,
dertype=1)
gcp_part = gcp.run_gcp(molecule, self.alias.lower(), verbose=False, dertype=1)
dashd_part.add(gcp_part)
return dashd_part
else:
return dftd3.run_dftd3(
molecule,
dashlvl=self.dtype.lower().replace('-', ''),
dashparam=self.dash_params,
verbose=False,
dertype=1)
else:
return self.disp.compute_gradient(molecule)
def compute_gradient(self, molecule):
"""Compute dispersion gradient based on engine, dispersion level, and parameters in `self`.
Parameters
----------
molecule : psi4.core.Molecule
System for which to compute empirical dispersion correction.
Returns
-------
psi4.core.Matrix
(nat, 3) dispersion gradient [Eh/a0].
"""
if self.engine == 'dftd3':
jobrec = intf_dftd3.run_dftd3_from_arrays(
molrec=molecule.to_dict(np_out=False),
name_hint=self.fctldash,
level_hint=self.dashlevel,
param_tweaks=self.dashparams,
dashcoeff_supplement=self.dashcoeff_supplement,
ptype='gradient',
verbose=1)
dashd_part = core.Matrix.from_array(
jobrec['qcvars']['DISPERSION CORRECTION GRADIENT'].data)
for k, qca in jobrec['qcvars'].items():
if not isinstance(qca.data, np.ndarray):
core.set_variable(k, qca.data)
if self.fctldash in ['hf3c', 'pbeh3c']:
gcp_part = gcp.run_gcp(molecule,
self.fctldash,
verbose=False,
dertype=1)
dashd_part.add(gcp_part)
return dashd_part
else:
return self.disp.compute_gradient(molecule)
def compute_gradient(self, molecule):
if self.disp_type == 'gr':
if self.alias in ['hf3c', 'pbeh3c']:
dashd_part = dftd3.run_dftd3(
molecule,
dashlvl=self.dtype.lower().replace('-', ''),
dashparam=self.dash_params,
verbose=False,
dertype=1)
gcp_part = gcp.run_gcp(molecule,
self.alias.lower(),
verbose=False,
dertype=1)
dashd_part.add(gcp_part)
return dashd_part
else:
return dftd3.run_dftd3(molecule,
dashlvl=self.dtype.lower().replace(
'-', ''),
dashparam=self.dash_params,
verbose=False,
dertype=1)
else:
return self.disp.compute_gradient(molecule)
def compute_gradient(self, molecule):
"""Compute dispersion gradient based on engine, dispersion level, and parameters in `self`.
Parameters
----------
molecule : psi4.core.Molecule
System for which to compute empirical dispersion correction.
Returns
-------
psi4.core.Matrix
(nat, 3) dispersion gradient [Eh/a0].
"""
if self.engine == 'dftd3':
jobrec = intf_dftd3.run_dftd3_from_arrays(
molrec=molecule.to_dict(np_out=False),
name_hint=self.fctldash,
level_hint=self.dashlevel,
param_tweaks=self.dashparams,
dashcoeff_supplement=self.dashcoeff_supplement,
ptype='gradient',
verbose=1)
dashd_part = core.Matrix.from_array(jobrec['qcvars']['DISPERSION CORRECTION GRADIENT'].data)
for k, qca in jobrec['qcvars'].items():
if not isinstance(qca.data, np.ndarray):
core.set_variable(k, qca.data)
if self.fctldash in ['hf3c', 'pbeh3c']:
gcp_part = gcp.run_gcp(molecule, self.fctldash, verbose=False, dertype=1)
dashd_part.add(gcp_part)
return dashd_part
else:
return self.disp.compute_gradient(molecule)
def compute_energy(self,
molecule: 'psi4.core.Molecule',
wfn: 'psi4.core.Wavefunction' = None) -> float:
"""Compute dispersion energy based on engine, dispersion level, and parameters in `self`.
Parameters
----------
molecule : psi4.core.Molecule
System for which to compute empirical dispersion correction.
wfn :
Location to set QCVariables
Returns
-------
float
Dispersion energy [Eh].
Notes
-----
DISPERSION CORRECTION ENERGY
Disp always set. Overridden in SCF finalization, but that only changes for "-3C" methods.
self.fctldash + DISPERSION CORRECTION ENERGY
Set if `fctldash` nonempty.
"""
if self.engine in ['dftd3', 'mp2d']:
resi = AtomicInput(
**{
'driver': 'energy',
'model': {
'method': self.fctldash,
'basis': '(auto)',
},
'keywords': {
'level_hint': self.dashlevel,
'params_tweaks': self.dashparams,
'dashcoeff_supplement': self.dashcoeff_supplement,
'save_pairwise_dispersion': self.save_pairwise_disp,
'verbose': 1,
},
'molecule': molecule.to_schema(dtype=2),
'provenance': p4util.provenance_stamp(__name__),
})
jobrec = qcng.compute(
resi,
self.engine,
raise_error=True,
local_options={
"scratch_directory":
core.IOManager.shared_object().get_default_path()
})
dashd_part = float(
jobrec.extras['qcvars']['DISPERSION CORRECTION ENERGY'])
if wfn is not None:
for k, qca in jobrec.extras['qcvars'].items():
# The pairwise dispersion analysis is already a nparray
# Do we always want to save it?
if ('CURRENT' not in k) and ('PAIRWISE' not in k):
wfn.set_variable(k, p4util.plump_qcvar(qca, k))
# Pass along the pairwise dispersion decomposition if we need it
if self.save_pairwise_disp is True:
wfn.set_variable(
"PAIRWISE DISPERSION CORRECTION ANALYSIS",
jobrec.extras['qcvars']
["PAIRWISE DISPERSION CORRECTION ANALYSIS"])
if self.fctldash in ['hf3c', 'pbeh3c']:
gcp_part = gcp.run_gcp(molecule,
self.fctldash,
verbose=False,
dertype=0)
dashd_part += gcp_part
return dashd_part
else:
ene = self.disp.compute_energy(molecule)
core.set_variable('DISPERSION CORRECTION ENERGY', ene)
if self.fctldash:
core.set_variable(
'{} DISPERSION CORRECTION ENERGY'.format(self.fctldash),
ene)
return ene
