gen_sim_input.py

mlcg_tk.scripts.gen_sim_input.process_sim_input(dataset_name, raw_data_dir, save_dir, tag, pdb_fns, cg_atoms, embedding_map, embedding_func, skip_residues, copies, prior_tag, prior_builders, mass_scale=418.4, collection_cls=<class 'mlcg_tk.input_generator.raw_dataset.SampleCollection'>, smpl_loader=<class 'mlcg_tk.input_generator.raw_data_loader.SimInput_loader'>)[source]

Generates input AtomicData objects for coarse-grained simulations

Parameters:

  • dataset_name (str) – Name given to specific dataset

  • raw_data_dir (str) – Path to location of input structures

  • save_dir (str) – Path to directory in which output will be saved

  • tag (str) – Label given to all output files produced from dataset

  • pdb_fns (List[str]) – List of pdb filenames from which input will be generated

  • cg_atoms (List[str]) – List of atom names to preserve in coarse-grained resolution

  • embedding_map (CGEmbeddingMap) – Mapping object

  • embedding_func (Callable) – Function which will be used to apply CG mapping

  • skip_residues (List[str]) – List of residues to skip, can be None

  • copies (int) – Copies that will be produced of each structure listing in pdb_fns

  • prior_tag (str) – String identifying the specific combination of prior terms

  • prior_builders (List[PriorBuilder]) – List of PriorBuilder objects and their corresponding parameters

  • mass_scale (Optional[float]) – Optional scaling factor applied to atomic masses

  • collection_cls (Type[SampleCollection]) – Class type for sample collection

  • smpl_loader (Type[DatasetLoader]) – Loader class for dataset