@staticmethod
get_log_values(log_file, keys=('StandardCartesianCoordinates', 'ScanEnergies')): 

@classmethod
from_log_file(cls, log_file, coord_transf, keys=('StandardCartesianCoordinates', 'ScanEnergies'), tol=0.001, **opts): 

Loads dipoles from a Gaussian log file and builds a potential surface by interpolating. Obviously this only really works if we have a subset of “scan” coordinates, so at this stage the user is obligated to furnish a function that’ll take a set of Cartesian coordinates and convert them to “scan” coordinates. Coordinerds can be helpful with this, as it provides a convenient syntax for Cartesian <-> ZMatrix conversions.

• log_file: str

  a Gaussian log file to pull from

• :returns: _

@classmethod
from_fchk_file(cls, fchk_file, ref=None, **opts): 

Loads potential from a Gaussian formatted checkpoint file and builds a potential surface via a quartic approximation

• fchk_file: Any

  a Gaussian fchk file to pull from

• log_file: str

• :returns: _

@classmethod
from_mol(cls, mol, expansion=None, center=None, transforms=None, transformed_derivatives=False, use_internals=True, **opts): 

@classmethod
from_derivatives(cls, expansion, center=None, ref=None, transforms=None, transformed_derivatives=False, **opts): 

__call__(self, gridpoints, **opts): 

Explicitly overrides the Surface-level evaluation because we know the Taylor surface needs us to flatten our gridpoints

• gridpoints: Any

• opts: Any

• :returns: _