haddock.modules.analysis.seletopclusts.seletopclusts module

Set of functions related to the selection of top clusters.

haddock.modules.analysis.seletopclusts.seletopclusts.map_clusters_models(models: list[PDBFile]) → dict[int, list[PDBFile]][source]

Group models by clusters.

Parameters:

models (list[PDBFile]) – List of PDBfiles models to be grouped.

Returns:

by_clusters (dict[int, list[PDBFile]]) – _description_

haddock.modules.analysis.seletopclusts.seletopclusts.rank_clust_order(by_clusters: dict[int, list[PDBFile]]) → list[int][source]

Select best clusters based on structures scores.

Parameters:

  • models_to_select (list[PDBFile]) – List of input models on which selection must be performed.

  • top_clusters (int) – Number of best clusters to take into account.

  • top_models (int) – Number of best models in each cluster to take into account.

Returns:

  • models_to_export (list[PDBFile]) – List of PDBfiles to export.

  • notes (list[str]) – List of notes to be printed.

haddock.modules.analysis.seletopclusts.seletopclusts.select_top_clusts_models(sortby: str, models_to_select: list[PDBFile], top_clusters: int, top_models: int | float) → tuple[list[PDBFile], list[str]][source]

Select best clusters based on structures scores.

Parameters:

  • sortby (str) – How to order clusters: by score or by size.

  • models_to_select (list[PDBFile]) – List of input models on which selection must be performed.

  • top_clusters (int) – Number of best clusters to take into account.

  • top_models (int) – Number of best models in each cluster to take into account.

Returns:

  • models_to_export (list[PDBFile]) – List of PDBfiles to export.

  • notes (list[str]) – List of notes to be printed.

haddock.modules.analysis.seletopclusts.seletopclusts.size_clust_order(by_clusters: dict[int, list[PDBFile]]) → list[int][source]

Select best clusters based on structures scores.

Parameters:

  • models_to_select (list[PDBFile]) – List of input models on which selection must be performed.

  • top_clusters (int) – Number of best clusters to take into account.

  • top_models (int) – Number of best models in each cluster to take into account.

Returns:

  • models_to_export (list[PDBFile]) – List of PDBfiles to export.

  • notes (list[str]) – List of notes to be printed.

haddock.modules.analysis.seletopclusts.seletopclusts.sort_models(models: list[PDBFile]) → tuple[list[PDBFile], None | str][source]

Sort models based on their rank in cluster.

Parameters:

models (list[PDBFile]) – List of input models on which ordering must be performed.

Returns:

sorted_mdls (list[PDBFile]) – List of sorted models.

haddock.modules.analysis.seletopclusts.seletopclusts.write_selected_models(output_path: str | Path, models: list[PDBFile], module_path: str | Path) → list[PDBFile][source]

Dump selected models and new names in a file.

Parameters:

  • output_path (Union[str, Path]) – Name of tne file to create.

  • models (list[PDBFile]) – List of PDBfiles of selected models.

  • module_path (Union[str, Path]) – Path of the module.

Returns:

models (list[PDBFile]) – Updated list of selected models.