ibllib.pipes.dynamic_pipeline

Task pipeline creation from an acquisition description.

The principal function here is make_pipeline which reads an _ibl_experiment.description.yaml file and determines the set of tasks required to preprocess the session.

Functions

acquisition_description_legacy_session

From a legacy session create a dictionary corresponding to the acquisition description.

get_acquisition_description

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load_pipeline_dict

make_pipeline

Creates a pipeline of extractor tasks from a session's experiment description file.

make_pipeline_dict

acquisition_description_legacy_session(session_path, save=False)[source]

From a legacy session create a dictionary corresponding to the acquisition description.

Parameters:
  • session_path (str, pathlib.Path) – A path to a session to describe.

  • save (bool) – If true, saves the acquisition description file to _ibl_experiment.description.yaml.

Returns:

The legacy acquisition description.

Return type:

dict

get_acquisition_description(protocol)[source]

” This is a set of example acquisition descriptions for experiments - choice_world_recording - choice_world_biased - choice_world_training - choice_world_habituation - choice_world_passive That are part of the IBL pipeline

make_pipeline(session_path, **pkwargs)[source]

Creates a pipeline of extractor tasks from a session’s experiment description file.

Parameters:
  • session_path (str, Path) – The absolute session path, i.e. ‘/path/to/subject/yyyy-mm-dd/nnn’.

  • **pkwargs – Optional arguments passed to the ibllib.pipes.tasks.Pipeline constructor.

Returns:

A task pipeline object.

Return type:

ibllib.pipes.tasks.Pipeline

make_pipeline_dict(pipeline, save=True)[source]
load_pipeline_dict(path)[source]