gs_optimization_overlap_cutoff: float
default_energy_cutoff: float
bad_alpha_limit: float
bad_scaling_limit: float

__init__(self, coords, alphas, transformations=None, *, momenta=None, poly_coeffs=None, kinetic_options=None, logger=None, parallelizer=None): 

@property
overlap_data(self): 

get_S(self, return_prefactor=False): 

get_T(self): 

optimize(self, optimizer_options, potential_function=None, logger=None, **opts): 

take_gaussian_selection(self, full_good_pos): 

@classmethod
construct(cls, coords, alphas, *, potential_expansion=None, potential_function=None, transformations=None, masses=None, atoms=None, modes=None, kinetic_options=None, internals=None, coordinate_selection=None, cartesians=None, gmat_function=None, momenta=None, poly_coeffs=None, logger=None, pairwise_potential_functions=None, parallelizer=None): 

@classmethod
get_normal_modes(cls, coords, potential_function, masses=None, atoms=None, internals=None, gmat_function=None, reference_structure=None, stationary_point_norm=0.01, project_transrot=True): 

@classmethod
get_reaction_path_transformations(cls, coords, potential_function, gmat_function, stationary_point_norm=0.0001, sort_alphas=True): 

@classmethod
get_hessian_diagonalizing_transformations(cls, coords, potential_function, gmat_function, *, masses=None, project_transrot=True): 

@classmethod
dispatch_get_alphas(self, alphas, centers, **extra_opts): 

@classmethod
get_mass_alphas(cls, centers, *, masses, scaling=10, use_mean=False): 

@classmethod
get_min_distance_alphas(cls, masses, centers, scaling=0.25, use_mean=False): 

@classmethod
get_virial_alphas(cls, coords, *, potential_function, gmat_function, transformations, scaling=0.5): 

@classmethod
canonicalize_poly_coeffs(cls, coeffs, alphas): 

@property
transformations(self): 

@classmethod
canonicalize_transforms(self, coords, tfs): 

@property
prefactor(self): 

@property
S(self): 

@property
T(self): 

marginalize_out(self, indices, *, bad_alpha_limit=None, bad_scaling_limit=None): 

as_cartesians(self): 

plot_centers(self, figure=None, xyz_sel=None, **plot_styles):