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| """ | |
| RMSD matrix module. | |
| This module calculates of the RMSD matrix between all the models | |
| generated in the previous step. | |
| As all the pairwise RMSD calculations are independent, the module distributes | |
| them over all the available cores in an optimal way. | |
| Once created, the RMSD matrix is saved in text form in the current `rmsdmatrix` | |
| folder. The path to this file is then shared with the following step of the | |
| workflow by means of the json file `rmsd_matrix.json`. | |
| The module accepts two parameters in input, namely: | |
| * `max_models` (default = 10000) | |
| * `resdic_` : an expandable parameter to specify which residues must be | |
| considered for the alignment and the RMSD calculation. If there are | |
| two proteins denoted by chain IDs A and B, then the user can operate | |
| such selection in the following way inside the configuration file | |
| resdic_A = [1,2,3,4] | |
| resdic_B = [2,3,4] | |
| thus telling the module to consider residues from 1 to 4 of chain A and from 2 | |
| to 4 of chain B for the alignment and RMSD calculation. | |
| For more details about this module, please `refer to the haddock3 user manual | |
| <https://www.bonvinlab.org/haddock3-user-manual/modules/analysis.html#rmsdmatrix-module>`_ | |
| """ | |
| import contextlib | |
| import os | |
| from pathlib import Path | |
| from haddock import RMSD_path, log | |
| from haddock.core.defaults import FAST_RMSDMATRIX_EXEC, MODULE_DEFAULT_YAML | |
| from haddock.core.typing import Any, AtomsDict, FilePath | |
| from haddock.libs.libalign import check_common_atoms, rearrange_xyz_files | |
| from haddock.libs.libontology import ModuleIO, RMSDFile | |
| from haddock.libs.libparallel import get_index_list | |
| from haddock.libs.libutil import parse_ncores | |
| from haddock.modules import BaseHaddockModule, get_engine | |
| from haddock.modules.analysis import ( | |
| confirm_resdic_chainid_length, | |
| get_analysis_exec_mode, | |
| ) | |
| from haddock.modules.analysis.rmsdmatrix.rmsd import ( | |
| RMSDJob, | |
| XYZWriter, | |
| XYZWriterJob, | |
| rmsd_dispatcher, | |
| ) | |
| RECIPE_PATH = Path(__file__).resolve().parent | |
| DEFAULT_CONFIG = Path(RECIPE_PATH, MODULE_DEFAULT_YAML) | |
| EXEC_PATH = FAST_RMSDMATRIX_EXEC | |
| class HaddockModule(BaseHaddockModule): | |
| """HADDOCK3 module for clustering with RMSD.""" | |
| name = RECIPE_PATH.name | |
| def __init__( | |
| self, order: int, path: Path, initial_params: FilePath = DEFAULT_CONFIG | |
| ) -> None: | |
| super().__init__(order, path, initial_params) | |
| def confirm_installation(cls) -> None: | |
| """Confirm if fast-rmsdmatrix is installed and available.""" | |
| if not os.access(EXEC_PATH, mode=os.F_OK): | |
| raise Exception( | |
| f"Required {str(EXEC_PATH)} file does not exist.{os.linesep}" | |
| "Old HADDOCK3 installation? Please follow the new installation instructions at https://github.com/haddocking/haddock3/blob/main/docs/pages/INSTALL.md" | |
| ) | |
| if not os.access(EXEC_PATH, mode=os.X_OK): | |
| raise Exception(f"Required {str(EXEC_PATH)} file is not executable") | |
| return | |
| def _rearrange_output( | |
| self, output_name: FilePath, path: FilePath, ncores: int | |
| ) -> None: | |
| """Combine different rmsd outputs in a single file.""" | |
| output_fname = Path(path, output_name) | |
| self.log(f"rearranging output files into {output_fname}") | |
| # Combine files | |
| with open(output_fname, "w") as out_file: | |
| for core in range(ncores): | |
| tmp_file = Path(path, "rmsd_" + str(core) + ".matrix") | |
| with open(tmp_file) as infile: | |
| out_file.write(infile.read()) | |
| log.debug(f"File number {core} written") | |
| tmp_file.unlink() | |
| log.info("Completed reconstruction of rmsd files.") | |
| log.info(f"{output_fname} created.") | |
| def update_params(self, *args: Any, **kwargs: Any) -> None: | |
| """Update parameters.""" | |
| super().update_params(*args, **kwargs) | |
| with contextlib.suppress(KeyError): | |
| self.params.pop("resdic_") | |
| confirm_resdic_chainid_length(self._params) | |
| def _run(self) -> None: | |
| """Execute module.""" | |
| # Get the models generated in previous step | |
| models = self.previous_io.retrieve_models(individualize=True) | |
| nmodels = len(models) | |
| if nmodels > self.params["max_models"]: | |
| # too many input models : RMSD matrix would be too big => Abort! | |
| raise Exception("Too many models for RMSD matrix calculation") | |
| # index_list for the jobs with linear scaling | |
| ncores = parse_ncores(n=self.params["ncores"], njobs=len(models)) | |
| index_list = get_index_list(nmodels, ncores) | |
| traj_filename = Path("traj.xyz") | |
| filter_resdic = { | |
| key[-1]: value | |
| for key, value in self.params.items() | |
| if key.startswith("resdic") | |
| } | |
| # check common atoms | |
| n_atoms, common_keys = check_common_atoms( | |
| models, | |
| filter_resdic, | |
| self.params["allatoms"], | |
| self.params["atom_similarity"], | |
| ) | |
| xyzwriter_jobs: list[XYZWriterJob] = [] | |
| for core in range(ncores): | |
| output_name = Path("traj_" + str(core) + ".xyz") | |
| # init RMSDJobFast | |
| xyzwriter_obj = XYZWriter( | |
| model_list=models[index_list[core] : index_list[core + 1]], | |
| output_name=output_name, | |
| core=core, | |
| n_atoms=n_atoms, | |
| common_keys=common_keys, | |
| filter_resdic=filter_resdic, | |
| allatoms=self.params["allatoms"], | |
| ) | |
| # job_f = output_name | |
| job = XYZWriterJob( | |
| xyzwriter_obj, | |
| ) | |
| xyzwriter_jobs.append(job) | |
| # run jobs | |
| exec_mode = get_analysis_exec_mode(self.params["mode"]) | |
| Engine = get_engine(exec_mode, self.params) | |
| engine = Engine(xyzwriter_jobs) | |
| engine.run() | |
| rearrange_xyz_files(traj_filename, path=Path("."), ncores=ncores) | |
| # Parallelisation : optimal dispatching of models | |
| tot_npairs = nmodels * (nmodels - 1) // 2 | |
| log.info(f"total number of pairs {tot_npairs}") | |
| ncores = parse_ncores(n=self.params["ncores"], njobs=tot_npairs) | |
| npairs, ref_structs, mod_structs = rmsd_dispatcher(nmodels, tot_npairs, ncores) | |
| # Calculate the rmsd for each set of models | |
| rmsd_jobs: list[RMSDJob] = [] | |
| self.log(f"running RmsdFast Jobs with {ncores} cores") | |
| for core in range(ncores): | |
| output_name = Path("rmsd_" + str(core) + ".out") | |
| # init RMSDJobFast | |
| job = RMSDJob( | |
| traj_filename, | |
| output_name, | |
| EXEC_PATH, | |
| core, | |
| npairs[core], | |
| ref_structs[core], | |
| mod_structs[core], | |
| len(models), | |
| n_atoms, | |
| ) | |
| rmsd_jobs.append(job) | |
| engine = Engine(rmsd_jobs) | |
| engine.run() | |
| rmsd_file_l: list[str] = [] | |
| not_found: list[str] = [] | |
| for job in rmsd_jobs: | |
| if not job.output.exists(): | |
| # NOTE: If there is no output, most likely the RMSD calculation | |
| # timed out | |
| not_found.append(job.output.name) | |
| wrn = f"Rmsd results were not calculated for {job.output.name}" | |
| log.warning(wrn) | |
| else: | |
| rmsd_file_l.append(str(job.output)) | |
| if not_found: | |
| # Not all distances were calculated, cannot create the full matrix | |
| self.finish_with_error(f"Several files were not generated: {not_found}") | |
| # Post-processing : single file | |
| final_output_name = "rmsd.matrix" | |
| self._rearrange_output(final_output_name, path=Path("."), ncores=ncores) | |
| # Delete the trajectory file | |
| if traj_filename.exists(): | |
| os.unlink(traj_filename) | |
| # Sending models to the next step of the workflow | |
| self.output_models = models | |
| self.export_io_models() | |
| # Sending matrix path to the next step of the workflow | |
| matrix_io = ModuleIO() | |
| rmsd_matrix_file = RMSDFile(final_output_name, npairs=tot_npairs) | |
| matrix_io.add(rmsd_matrix_file) | |
| matrix_io.save(filename="rmsd_matrix.json") | |