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.- interaction_signs_df – A pandas