torchref.base.scattering.itc92 module

ITC92 atomic scattering factor calculations.

Functions for computing atomic scattering factors using the International Tables for Crystallography Volume C (1992) parameterization.

torchref.base.scattering.itc92.get_scattering_factors_unique(atoms, s)[source]

Compute unique scattering factors for a set of atoms.

Parameters:

  • atoms (DataFrame-like) – Atoms with ‘element’ and ‘charge’ attributes.

  • s (array-like) – Scattering vector magnitudes.

Returns:

Dictionary mapping element symbols to scattering factors.

Return type:

dict

torchref.base.scattering.itc92.get_scattering_factors(scattering_dict, elements)[source]

Get scattering factors from a pre-computed dictionary.

Parameters:

  • scattering_dict (dict) – Dictionary of scattering factors by element.

  • elements (list) – List of element symbols.

Returns:

Concatenated scattering factors.

Return type:

torch.Tensor

torchref.base.scattering.itc92.linear_interpolation(x, x0, x1, y0, y1)[source]

Perform linear interpolation.

Parameters:

  • x (array-like) – Query points.

  • x0 (array-like) – Lower bound x values.

  • x1 (array-like) – Upper bound x values.

  • y0 (array-like) – Lower bound y values.

  • y1 (array-like) – Upper bound y values.

Returns:

Interpolated y values.

Return type:

array-like

torchref.base.scattering.itc92.get_scattering_itc92(df, s)[source]

Get ITC92 scattering factors using gemmi.

Parameters:

  • df (DataFrame) – DataFrame with ‘element’ column.

  • s (torch.Tensor) – Scattering vector magnitudes.

Returns:

Scattering factors for all atoms.

Return type:

torch.Tensor

torchref.base.scattering.itc92.calc_scattering_factors_paramtetrization(parametrization, s, atom_list)[source]

Calculate scattering factors from ITC92 parametrization.

Parameters:

  • parametrization (dict) – Dictionary of (A, B, C) tuples by element.

  • s (torch.Tensor) – Scattering vector magnitudes.

  • atom_list (list) – List of atom symbols.

Returns:

Scattering factors.

Return type:

torch.Tensor

torchref.base.scattering.itc92.get_parameterization(df)[source]

Get ITC92 parametrization for atoms in a DataFrame.

Parameters:

df (DataFrame) – DataFrame with ‘element’ and ‘charge’ columns.

Returns:

Dictionary of parametrization by element.

Return type:

dict

torchref.base.scattering.itc92.get_parameterization_extended(df)[source]

Extended parametrization function that handles all atoms in a DataFrame.

Creates a dictionary mapping element symbols (and optionally charges) to their ITC92 parameters (A, B, C). This is optimized for FT-based calculations where we need fast access to parametrization without scattering vectors.

Parameters:

df (pandas.DataFrame) – DataFrame with ‘element’ and ‘charge’ columns

Returns:

dict – A: torch.Tensor, shape (1, 4) - amplitude coefficients B: torch.Tensor, shape (1, 4) - width coefficients (Ų) C: torch.Tensor, shape (1,) - constant term

Return type:

{element_str: (A, B, C)}

torchref.base.scattering.itc92.get_parametrization_for_elements(elements, charges=None)[source]

Get ITC92 parametrization for a list of elements.

Useful for getting parametrization for specific atoms without a full DataFrame.

Parameters:

  • elements (list of str) – Element symbols (e.g., [‘C’, ‘N’, ‘O’])

  • charges (list of int, optional) – Charges for each element (default: all zeros)

Returns:

dict

Return type:

{element: (A, B, C)}

torchref.base.scattering.itc92.get_parametrization_atom(charge, atom)[source]

Get ITC92 parametrization for a single atom.

Parameters:

  • charge (int) – Atomic charge.

  • atom (str) – Element symbol.

Returns:

[A, B] tensors for the atom.

Return type:

list