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):
"""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 == '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):
"""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)