atomate.vasp.analysis package

Submodules

atomate.vasp.analysis.linear_response module

atomate.vasp.analysis.linear_response.chi_inverse(chi, chi_err, method='full')

Function to compute inverse of response matrix and associated element-wise uncertainty for point-wise, atom-wise, and full matrix inversion

atomate.vasp.analysis.linear_response.compute_u_pointwise(site_index, f_matrix, f_matrix_err)

Function to compute Hubbard U value using point-wise (diagonal) inversion, in addition to the associated uncertainty value - based on the study by Linscott et. al.

atomate.vasp.analysis.linear_response.compute_uj_scaled_two_by_two(site_index, f_matrix, f_matrix_err, chi_matrix_scf, chi_scf_err, chi_matrix_nscf, chi_nscf_err, chi_scf_inv_jacobs, chi_nscf_inv_jacobs)

Function to compute Hubbard U and Hund J values using scaled 2x2 formula, in addition to the associated uncertainty values - based on the study by Linscott et. al.

atomate.vasp.analysis.linear_response.compute_uj_simple_two_by_two(site_index, f_matrix, f_matrix_err)

Function to compute Hubbard U and Hund J values using simple 2x2 formula, in addition to the associated uncertainty values - based on the study by Linscott et. al.

atomate.vasp.analysis.linear_response.inverse_matrix_uncertainty(matrix, matrix_covar)

Function to compute the element-wise error propagation in matrix inversion

atomate.vasp.analysis.linear_response.obtain_response_matrices(n_response, spin_polarized, response_dict, keys)

Function to compute self-consistent (SCF) and non-self-consistent (NSCF) linear response “chi” matrices; In addition to using linear regression to compute slopes about zero potential, the uncertainty associated with these values are also stored for subsequent error quantification. Returns: chi_matrix_nscf, chi_matrix_scf, chi_nscf_err, chi_scf_err

atomate.vasp.analysis.linear_response.procure_response_dict(struct_final, num_perturb_sites, incar_dict, outcar_dict, inv_block_dict, response_dict, perturb_dict, rkey, ldaul_vals, analyzer_gs, calcs_skipped)

Function to gather response data, in preparation for linear regression. This data is organized into response_dict.

atomate.vasp.analysis.linear_response.response_fit(x, y)

Function for fitting to response data. Returns: slope and associated error

atomate.vasp.analysis.linear_response.response_fit_stepped(x, y, tol=1e-06)

Function for fitting to response data - includes the “slope ~ zero” case for stepped data due to low precision Returns: slope and associated error

atomate.vasp.analysis.phonopy module

atomate.vasp.analysis.phonopy.get_phonopy_gibbs(energies, volumes, force_constants, structure, t_min, t_step, t_max, mesh, eos, pressure=0)

Compute QHA gibbs free energy using the phonopy interface.

Args:

energies (list): volumes (list): force_constants (list): structure (Structure): t_min (float): min temperature t_step (float): temperature step t_max (float): max temperature mesh (list/tuple): reciprocal space density eos (str): equation of state used for fitting the energies and the volumes.

options supported by phonopy: vinet, murnaghan, birch_murnaghan

pressure (float): in GPa, optional.

Returns:

(numpy.ndarray, numpy.ndarray): Gibbs free energy, Temperature

atomate.vasp.analysis.phonopy.get_phonopy_qha(energies, volumes, force_constants, structure, t_min, t_step, t_max, mesh, eos, pressure=0)

Return phonopy QHA interface.

Args:

energies (list): volumes (list): force_constants (list): structure (Structure): t_min (float): min temperature t_step (float): temperature step t_max (float): max temperature mesh (list/tuple): reciprocal space density eos (str): equation of state used for fitting the energies and the volumes.

options supported by phonopy: vinet, murnaghan, birch_murnaghan

pressure (float): in GPa, optional.

Returns:

PhonopyQHA

atomate.vasp.analysis.phonopy.get_phonopy_thermal_expansion(energies, volumes, force_constants, structure, t_min, t_step, t_max, mesh, eos, pressure=0)

Compute QHA thermal expansion coefficient using the phonopy interface.

Args:

energies (list): volumes (list): force_constants (list): structure (Structure): t_min (float): min temperature t_step (float): temperature step t_max (float): max temperature mesh (list/tuple): reciprocal space density eos (str): equation of state used for fitting the energies and the volumes.

options supported by phonopy: vinet, murnaghan, birch_murnaghan

pressure (float): in GPa, optional.

Returns:

(numpy.ndarray, numpy.ndarray): thermal expansion coefficient, Temperature

Module contents