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generalize fit() for non Ia applications #56

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merged 3 commits into from
Oct 30, 2024
Merged

generalize fit() for non Ia applications #56

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88b3ba9
generalize fit() for non Ia applications
AmandaWasserman Oct 18, 2024
0cdf1aa
Update src/resspect/fit_lightcurves.py
AmandaWasserman Oct 25, 2024
2ae74b1
Merge branch 'main' into generalize-features
drewoldag Oct 30, 2024
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45 changes: 34 additions & 11 deletions src/resspect/fit_lightcurves.py
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Original file line number Diff line number Diff line change
Expand Up @@ -309,7 +309,7 @@ def fit_TOM(data_dic: dict, output_features_file: str,
logging.info("Features have been saved to: %s", output_features_file)

def _sample_fit(
obj_dic: dict, feature_extractor: str, filters: list, type: str, Ia_code: list,
obj_dic: dict, feature_extractor: str, filters: list, type: str, one_code: list,
additional_info: list):
"""
Reads general file and performs fit.
Expand All @@ -328,29 +328,32 @@ def _sample_fit(
light_curve_data.id = obj_dic['objectid']
light_curve_data.redshift = obj_dic['redshift']
light_curve_data.sncode = obj_dic['sncode']
if light_curve_data.sncode in Ia_code:
light_curve_data.sntype = 'Ia'
if light_curve_data.sncode in one_code:
light_curve_data.sntype = 'Ia' #just labeling all positive classes as Ia
#unsure what changing this might affect in database.py
else:
light_curve_data.sntype = 'other'
light_curve_data.sample = type
light_curve_data.additional_info = additional_info

light_curve_data.additional_info = []
for info in additional_info:
light_curve_data.additional_info.append(obj_dic[info])
light_curve_data.fit_all()

return light_curve_data

def fit(data_dic: dict, output_features_file: str,
number_of_processors: int = MAX_NUMBER_OF_PROCESSES,
feature_extractor: str = 'bazin', filters: list = ['SNPCC'],
features: list = [], type: str = 'unspecified', Ia_code: list = [10],
features: list = [], type: str = 'unspecified', one_code: list = [10],
additional_info: list = []):
"""
Perform fit to all objects from a generalized dataset.

Parameters
----------
data_dic: str
Dictionary containing the photometry for all light curves.
data_dic: list
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Suggested change
data_dic: list
data_dic: list[dict]

Minor point - doesn't need to be fixed in this PR - but since data_dic is now expected to be a list, it might make sense to simply call it data.

List of dictionaries containing the photometry for each light
curve. Example provided below.
output_features_file: str
Path to output file where results should be stored.
number_of_processors: int, default 1
Expand All @@ -364,12 +367,32 @@ def fit(data_dic: dict, output_features_file: str,
the feature extractor.
type: str
Type of data: train, test, validation, pool
Ia_code: list
List of Ia codes to be used. Default is 10 from ELAsTiCC.
one_code: list
List of codes to be used to define a positive class.
Default is 10 from ELAsTiCC type Ia SN.
additional_info: list
List of additional header information to be used in other classifiers.
For example, RA and dec for GHOST feature extraction

Example of a data_dic element:
------------------------------
Required keys
'objectid'
object id
'photometry'
dictionary containing keys ''mjd', 'band', 'flux', 'fluxerr'.
each entry contains a list of mjd, band, flux, fluxerr for
each observation
'redshift'
redshift of the object if known, 'unknown' otherwise
'sncode'
number to delineate what type of transient the object is.
one_code will translate this into '1'/'0' for positive/negative

Optional keys; anything you might need for your classifier.
Need to specify the keys as a list in 'additional_info'. For example
'RA'
'dec'
"""
if feature_extractor == 'bazin':
header = TOM_FEATURES_HEADER
Expand Down Expand Up @@ -409,7 +432,7 @@ def fit(data_dic: dict, output_features_file: str,
for light_curve_data in multi_process.starmap(
_sample_fit, zip(
data_dic, repeat(feature_extractor), repeat(filters), repeat(type),
repeat(Ia_code), repeat(additional_info))):
repeat(one_code), repeat(additional_info))):
if 'None' not in light_curve_data.features:
write_features_to_output_file(
light_curve_data, features_file)
Expand Down
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