LocalConfig

class gaitmap_challenges.config.LocalConfig(tmp_dir: Optional[Path] = None, cache_dir: Optional[Path] = None, results_dir: Optional[Path] = None, n_jobs: Union[int, str] = 1, datasets: Optional[DatasetsConfig] = None)

Local config for challenges.

This config can be set and modified using the set_config method. See this method for more details.

Parameters:

tmp_dirOptional[Path], optional

Path to the temporary directory that can be used by challenges/algorithms

cache_dirOptional[Path], optional

Path to the cache directory that can be used by challenges/algorithms (e.g. by joblib). Compared to the tmp_dir, there is an expectation that the cache_dir is persistent.

results_dirOptional[Path], optional

Path to the directory where results should be stored.

n_jobsUnion[int, str], optional

A recommendation for the number of jobs the current system can handle.

datasetsOptional[DatasetsConfig], optional

Config for the datasets. In particular the paths to the datasets can be specified here. For more details see the gaitmap_datasets package.

Attributes:

cache_dir

datasets

results_dir

tmp_dir

Methods

from_json_file(config_file)	Get config data from json file.
to_json_dict([path_relative_to])	Get the config as json-serializable dict.

__init__(tmp_dir: Optional[Path] = None, cache_dir: Optional[Path] = None, results_dir: Optional[Path] = None, n_jobs: Union[int, str] = 1, datasets: Optional[DatasetsConfig] = None) → None

classmethod from_json_file(config_file: Union[str, Path])

Get config data from json file.

to_json_dict(path_relative_to: Optional[Path] = None) → Dict[str, Any]

Get the config as json-serializable dict.

Note: This is not meant for round-trip serialization!