add function that unhardcodes features and filters #46
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drewoldag
reviewed
Oct 16, 2024
src/resspect/fit_lightcurves.py
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| def fit(data_dic: dict, output_features_file: str, | ||
| number_of_processors: int = 1, | ||
| feature_extractor: str = 'bazin', filters: list = ['SNPCC'], | ||
| features: list = None, type: str = 'unspecified', Ia_code: list = [10]): |
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Should type default to None?
drewoldag
reviewed
Oct 16, 2024
| List of Ia codes to be used. Default is 10 from ELAsTiCC. | ||
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| """ | ||
| if feature_extractor == 'bazin': |
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I might combine this if/else with the one on line 373.
drewoldag
reviewed
Oct 16, 2024
| header = make_features_header(filters, features) | ||
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| multi_process = multiprocessing.Pool(number_of_processors) | ||
| if feature_extractor != None: |
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Will feature_extractor ever be None? Would it make sense to do this check earlier in the function and raise an exception?
drewoldag
approved these changes
Oct 16, 2024
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Working to unhardcode features and filters. This may need to be workshopped down the line but this does what we need in the meantime basically combining
fit_snpccfit_plasticcandfit_TOM. Allows any filters to be used, may need to workshop the any features functionality.