vibeqc.SolventResult¶

class vibeqc.SolventResult(scf, energy, e_solv, e_gas, epsilon, solvent_name, solvent_variant, cavity, cpcm, n_macro_iter, macro_history=<factory>, converged=False, screening=None, z_eff=None, direct_feedback=None, gradient_symmetry_tol_bohr=0.0, all_scf_traces=<factory>)[source]¶

Bases: object

Outcome of a CPCM-coupled SCF run.

Carries the original SCF result type (RHFResult / UHFResult / RKSResult / UKSResult) on .scf plus the converged solvation diagnostics.

Parameters:

scf (Any)
energy (float)
e_solv (float)
e_gas (float | None)
epsilon (float)
solvent_name (str)
solvent_variant (str)
cavity (CavityTessellation)
cpcm (CPCMResult)
n_macro_iter (int)
macro_history (list[dict[str, float]])
converged (bool)
screening (ScreeningModel | None)
z_eff (ndarray | None)
direct_feedback (Any | None)
gradient_symmetry_tol_bohr (float)
all_scf_traces (list[Any])

__init__(scf, energy, e_solv, e_gas, epsilon, solvent_name, solvent_variant, cavity, cpcm, n_macro_iter, macro_history=<factory>, converged=False, screening=None, z_eff=None, direct_feedback=None, gradient_symmetry_tol_bohr=0.0, all_scf_traces=<factory>)¶

Parameters:

scf (Any)
energy (float)
e_solv (float)
e_gas (float | None)
epsilon (float)
solvent_name (str)
solvent_variant (str)
cavity (CavityTessellation)
cpcm (CPCMResult)
n_macro_iter (int)
macro_history (list[dict[str, float]])
converged (bool)
screening (ScreeningModel | None)
z_eff (ndarray | None)
direct_feedback (Any | None)
gradient_symmetry_tol_bohr (float)
all_scf_traces (list[Any])

Return type:

None

Methods

__init__(scf, energy, e_solv, e_gas, ...[, ...])

Attributes

`converged`
`direct_feedback`
`gradient_symmetry_tol_bohr`
`screening`
`z_eff`
`scf`
`energy`
`e_solv`
`e_gas`
`epsilon`
`solvent_name`
`solvent_variant`
`cavity`
`cpcm`
`n_macro_iter`
`macro_history`
`all_scf_traces`

scf: Any¶

energy: float¶

e_solv: float¶

e_gas: float | None¶

epsilon: float¶

solvent_name: str¶

solvent_variant: str¶

cavity: CavityTessellation¶

cpcm: CPCMResult¶

n_macro_iter: int¶

macro_history: list[dict[str, float]]¶

converged: bool = False¶

screening: ScreeningModel | None = None¶

z_eff: ndarray | None = None¶

direct_feedback: Any | None = None¶

gradient_symmetry_tol_bohr: float = 0.0¶

all_scf_traces: list[Any]¶