run
- ZenoWrapper.run(start: int = None, stop: int = None, step: int = None, frames: Iterable = None, verbose: bool = None, n_workers: int = None, n_parts: int = None, backend: str | BackendBase = None, *, unsupported_backend: bool = False, progressbar_kwargs=None)
Perform the calculation
- Parameters:
start (int, optional) – start frame of analysis
stop (int, optional) – stop frame of analysis
step (int, optional) – number of frames to skip between each analysed frame
frames (array_like, optional) – array of integers or booleans to slice trajectory;
framescan only be used instead ofstart,stop, andstep. Setting bothframesand at least one ofstart,stop,stepto a non-default value will raise aValueError.Added in version 2.2.0.
verbose (bool, optional) – Turn on verbosity
progressbar_kwargs (dict, optional) – ProgressBar keywords with custom parameters regarding progress bar position, etc; see
MDAnalysis.lib.log.ProgressBarfor full list. Available only forbackend='serial'backend (Union[str, BackendBase], optional) – By default, performs calculations in a serial fashion. Otherwise, user can choose a backend:
stris matched to a builtin backend (one ofserial,multiprocessinganddask), or aMDAnalysis.analysis.results.BackendBasesubclass.Added in version 2.8.0.
n_workers (int) – positive integer with number of workers (processes, in case of built-in backends) to split the work between
Added in version 2.8.0.
n_parts (int, optional) – number of parts to split computations across. Can be more than number of workers.
Added in version 2.8.0.
unsupported_backend (bool, optional) – if you want to run your custom backend on a parallelizable class that has not been tested by developers, by default False
Added in version 2.8.0.
Changed in version 2.2.0: Added ability to analyze arbitrary frames by passing a list of frame indices in the frames keyword argument.
Changed in version 2.5.0: Add progressbar_kwargs parameter, allowing to modify description, position etc of tqdm progressbars
Changed in version 2.8.0: Introduced
backend,n_workers,n_partsandunsupported_backendkeywords, and refactored the method logic to support parallelizable execution.