neighbormodels.interactions.compute_model_coefficients

compute_model_coefficients(interaction_signs_df: pandas.core.frame.DataFrame, neighbor_data: neighbormodels.neighbors.NeighborData, distance_filter: Optional[Dict[str, List[float]]]) → pandas.core.frame.DataFrame[source]

Computes the model coefficients by aggregating over the dot product of the neighbor counts and interaction signs.

Parameters:
  • interaction_signs_df – A pandas DataFrame of the signs of the pairwise interactions.
  • neighbor_data

    A named tuple with three field names:

    neighbor_count
    A pandas DataFrame of neighbor counts aggregated over site-index pairs and separation distances.
    sublattice_pairs
    A pandas DataFrame of neighbor distances mapped to unique bin intervals.
    structure
    A copy of the Structure object defining the crystal structure.
  • distance_filter – A dictionary that defines pair distances to keep in the model. Any pair not found int he dictionary is filtered out. The dictionary keys define named groups of pair distances to keep, which subsequently are used for naming the interaction parameters.
Returns:

A pandas DataFrame of the model coefficients.