set_custom_sigma

autoplex.fitting.common.regularization.set_custom_sigma(atoms, reg_minmax, isolated_atom_energies=None, scheme='linear-hull', energy_name='REF_energy', force_name='REF_forces', virial_name='REF_virial', element_order=None, max_energy=20.0, config_type_override=None, retain_existing_sigma=False)

Handle automatic regularisation based on distance to convex hull, amongst other things.

TODO: Need to make sure this works for full multi-stoichiometry systems.

Parameters:

• atoms ((list of ase.Atoms)) – List of atoms objects to set reg. for. Usually fitting database

• reg_minmax ((list of tuples)) – List of tuples of (min, max) values for energy, force, virial sigmas

• scheme ((str)) – Method to use for regularization. Options are: linear_hull, volume-stoichiometry linear_hull: for single-composition system, use 2D convex hull (E, V) volume-stoichiometry: for multi-composition system, use 3D convex hull of (E, V, mole-fraction)

• energy_name ((str)) – Name of energy key in atoms.info

• force_name ((str)) – Name of force key in atoms.arrays

• virial_name ((str)) – Name of virial key in atoms.info

• isolated_atom_energies ((dict)) – Dictionary of isolated energies for each atomic number. Only needed for volume-x scheme e.g. {14: ‘-163.0’, 8:’-75.0’} for SiO2

• element_order ((list)) – List of atomic numbers in order of choice (e.g. [42, 16] for MoS2)

• max_energy ((float)) – Ignore any structures with energy above hull greater than this value (eV)

• config_type_override ((dict)) – Give custom regularization for specific configuration types

• retain_existing_sigma (bool) – Whether to keep the current sigma values for specific configuration types. If set to True, existing sigma values for specific configurations will remain unchanged.

• [(0.1 (e.g. reg_minmax =)

• 1)

• (0.001

• 0.1)

• (0.0316

• 0.316)

• (0.0632

• 0.632)]

• [(emin

• emax)

• (semin

• semax)

• (sfmin

• sfmax)

• (ssvmin

• svmax)]

Return type:

list[Atoms]