def _update_queryable_if_get_cost(self, light_curve_data: LightCurve,
telescope_names: list,
telescope_sizes: list,
spectroscopic_snr: int,
**kwargs) -> LightCurve:
"""
Updates time required to take a spectra calc_exp_time() method of
LightCurve class
Parameters
----------
light_curve_data
An instance of LightCurve class
telescope_names
Names of the telescopes under consideration for spectroscopy.
Only used if "get_cost == True".
Default is ["4m", "8m"].
telescope_sizes
Primary mirrors diameters of potential spectroscopic telescopes.
Only used if "get_cost == True".
Default is [4, 8].
spectroscopic_snr
SNR required for spectroscopic follow-up. Default is 10.
kwargs
Any input required by ExpTimeCalc.findexptime function.
"""
for index in range(self._number_of_telescopes):
light_curve_data.calc_exp_time(
telescope_diam=telescope_sizes[index],
telescope_name=telescope_names[index],
SNR=spectroscopic_snr,
**kwargs)
return light_curve_data
def _get_features_to_write(self, light_curve_data_day: LightCurve,
get_cost: bool, telescope_names: list) -> list:
"""
Returns features list to write
Parameters
----------
light_curve_data_day
fitted light curve data of current snid
get_cost
if cost of taking a spectra is computed
telescope_names
Names of the telescopes under consideration for spectroscopy.
Only used if "get_cost == True".
Default is ["4m", "8m"].
"""
light_curve_data_day.sntype = PLASTICC_TARGET_TYPES[
light_curve_data_day.sncode]
light_curve_data_day.sample = 'pool'
features_list = [
light_curve_data_day.id, light_curve_data_day.redshift,
light_curve_data_day.sntype, light_curve_data_day.sncode,
light_curve_data_day.sample, light_curve_data_day.queryable,
light_curve_data_day.last_mag
]
if get_cost:
for index in range(self._number_of_telescopes):
features_list.append(
str(light_curve_data_day.exp_time[telescope_names[index]]))
features_list.extend(light_curve_data_day.bazin_features)
return features_list
def _load_plasticc_data(self,
raw_data_dir: str,
volume: int,
snid: int,
sample='test') -> LightCurve:
"""
Loads PLAsTiCC dataset files to LightCurve class
Parameters
----------
raw_data_dir
Complete path to all PLAsTiCC zenodo files.
snid: int
Object id for the transient to be fitted.
vol: int (optional)
Index of the original PLAsTiCC zenodo light curve
files where the photometry for this object is stored.
sample: str (optional)
Sample to load, 'train' or 'test'. Default is 'test'.
"""
light_curve_data = LightCurve()
if sample == 'test':
file_name = os.path.join(raw_data_dir,
self._file_list_dict['test'][volume - 1])
else:
file_name = os.path.join(raw_data_dir,
self._file_list_dict['train'][0])
light_curve_data.load_plasticc_lc(file_name, snid)
return light_curve_data
def get_lim_mjds(self, raw_data_dir: str) -> list:
"""
Get minimum and maximum MJD for complete sample.
This function is not necessary if you are working with
SNPCC data. The values are hard coded in the class.
Parameters
----------
raw_data_dir: str
Complete path to raw data directory.
Returns
-------
limits: list
List of extreme MJDs for entire sample: [min_MJD, max_MJD].
"""
files_list = _get_files_list(raw_data_dir, 'DES_SN')
# store MJDs
min_day = []
max_day = []
for each_file in progressbar.progressbar(files_list):
light_curve_data = LightCurve()
light_curve_data.load_snpcc_lc(
os.path.join(raw_data_dir, each_file))
min_day.append(min(light_curve_data.photometry['mjd'].values))
max_day.append(max(light_curve_data.photometry['mjd'].values))
self.min_epoch = min(min_day)
self.max_epoch = max(max_day)
return [min(min_day), max(max_day)]
def _update_light_curve_meta_data(self, light_curve_data_day: LightCurve,
snid: int) -> Union[LightCurve, None]:
"""
Loads light curve data of the given SNID
Parameters
----------
light_curve_data_day
An instance of LightCurve class instance of the data
snid
Object id for the transient to be fitted.
Returns
-------
light_curve_data_day
LightCurve class data for the given SNID
"""
if light_curve_data_day is not None:
snid_mask = self.metadata['object_id'].values == snid
if np.sum(snid_mask) > 0:
light_curve_data_day.redshift = self.metadata['true_z'].values[
snid_mask][0]
light_curve_data_day.sncode = (
self.metadata['true_target'].values[snid_mask][0])
light_curve_data_day.id = snid
return light_curve_data_day
return None
def _process_current_day(
self, light_curve_data_day: LightCurve, queryable_criteria: int,
days_since_last_observation: int, telescope_names: list,
telescope_sizes: list, spectroscopic_snr: int,
min_available_points: int = 4, **kwargs):
"""
Processes data for current day
Parameters
----------
light_curve_data_day
An instance of LightCurve class
queryable_criteria
Criteria to determine if an obj is queryable.
1 -> r-band cut on last measured photometric point.
2 -> last obs was further than a given limit,
use Bazin estimate of flux today. Otherwise, use
the last observed point.
days_since_last_observation
Day since last observation to consider for spectroscopic
follow-up without the need to extrapolate light curve.
telescope_names
Names of the telescopes under consideration for spectroscopy.
Only used if "get_cost == True".
telescope_sizes
Primary mirrors diameters of potential spectroscopic telescopes.
Only used if "get_cost == True".
spectroscopic_snr
SNR required for spectroscopic follow-up.
kwargs
Any input required by ExpTimeCalc.findexptime function.
min_available_points
minimum number of survived points
"""
photo_flag = (
light_curve_data_day.photometry['mjd'].values <= self._today)
if np.sum(photo_flag) > min_available_points:
light_curve_data_day.photometry = light_curve_data_day.photometry[
photo_flag]
light_curve_data_day.fit_bazin_all()
if (len(light_curve_data_day.bazin_features) > 0 and
'None' not in light_curve_data_day.bazin_features):
light_curve_data_day.queryable = self._check_queryable(
light_curve_data_day, queryable_criteria,
days_since_last_observation)
light_curve_data_day = self._update_queryable_if_get_cost(
light_curve_data_day, telescope_names, telescope_sizes,
spectroscopic_snr, **kwargs)
light_curve_data_day.queryable = bool(sum(get_query_flags(
light_curve_data_day, telescope_names
)))
return light_curve_data_day
return None
def _process_each_light_curve(
self,
light_curve_data: LightCurve,
queryable_criteria: int,
days_since_last_observation: int,
telescope_names: list,
telescope_sizes: list,
spectroscopic_snr: int,
kwargs: dict,
min_available_points: int = 5) -> Union[LightCurve, None]:
"""
Processes each light curve files.
Parameters
----------
light_curve_data: resspect.LightCurve
An instance of LightCurve class
queryable_criteria: int
Criteria to determine if an obj is queryable.
1 -> r-band cut on last measured photometric point.
2 -> last obs was further than a given limit,
use Bazin estimate of flux today. Otherwise, use
the last observed point.
days_since_last_observation: int
Day since last observation to consider for spectroscopic
follow-up without the need to extrapolate light curve.
telescope_names: list
Names of the telescopes under consideration for spectroscopy.
Only used if "get_cost == True".
telescope_sizes: list
Primary mirrors diameters of potential spectroscopic telescopes.
Only used if "get_cost == True".
spectroscopic_snr: int
SNR required for spectroscopic follow-up.
kwargs: dict (optional)
Any input required by ExpTimeCalc.findexptime function.
min_available_points: int (optional)
minimum number of survived points. Default is 5.
"""
photo_flag = light_curve_data.photometry['mjd'].values <= self._today
if sum(photo_flag) >= min_available_points:
light_curve_data.photometry = light_curve_data.photometry[
photo_flag]
light_curve_data.fit_bazin_all()
if (len(light_curve_data.bazin_features) > 0
and 'None' not in light_curve_data.bazin_features):
light_curve_data.queryable = self._check_queryable(
light_curve_data, queryable_criteria,
days_since_last_observation)
light_curve_data = self._update_queryable_if_get_cost(
light_curve_data, telescope_names, telescope_sizes,
spectroscopic_snr, kwargs)
light_curve_data.queryable = bool(
sum(get_query_flags(light_curve_data, telescope_names)))
return light_curve_data
return None
def _check_queryable(self, light_curve_data: LightCurve,
queryable_criteria: int,
days_since_last_observation: int) -> bool:
"""
Applies check_queryable method of LightCurve class
Parameters
----------
light_curve_data
An instance of LightCurve class
queryable_criteria: [1 or 2]
Criteria to determine if an obj is queryable.
1 -> r-band cut on last measured photometric point.
2 -> last obs was further than a given limit,
use Bazin estimate of flux today. Otherwise, use
the last observed point.
Default is 1.
days_since_last_observation
Day since last observation to consider for spectroscopic
follow-up without the need to extrapolate light curve.
"""
return light_curve_data.check_queryable(
mjd=self._today,
filter_lim=self.rmag_lim,
criteria=queryable_criteria,
days_since_last_obs=days_since_last_observation)
def _update_light_curve_meta_data(self, light_curve_data_day: LightCurve,
snid: int) -> Union[LightCurve, None]:
""" Add docstring!!!
"""
if light_curve_data_day is not None:
snid_mask = self.metadata['object_id'].values == snid
if np.sum(snid_mask) > 0:
light_curve_data_day.redshift = self.metadata['true_z'].values[
snid_mask][0]
light_curve_data_day.sncode = (
self.metadata['true_target'].values[snid_mask][0])
light_curve_data_day.id = snid
return light_curve_data_day
return None
def _get_current_sample_features(self, file_name: str, raw_data_dir: str,
queryable_criteria: int,
days_since_observation: int,
telescope_names: list,
telescope_sizes: list,
spec_SNR: int) -> LightCurve:
"""
Reads a SNPCC file and updates time domain features
Parameters
----------
file_name
SNPCC file name
raw_data_dir: str
Complete path to raw data directory
queryable_criteria: int [1 or 2] (optional)
Criteria to determine if an obj is queryable.
1 -> r-band cut on last measured photometric point.
2 -> last obs was further than a given limit,
use Bazin estimate of flux today. Otherwise, use
the last observed point.
Default is 1.
days_since_observation: int (optional)
Day since last observation to consider for spectroscopic
follow-up without the need to extrapolate light curve.
Only used if "queryable_criteria == 2". Default is 2.
telescope_names: list (optional)
Names of the telescopes under consideration for spectroscopy.
Only used if "get_cost == True".
Default is ["4m", "8m"].
telescope_sizes: list (optional)
Primary mirrors diameters of potential spectroscopic telescopes.
Only used if "get_cost == True".
Default is [4, 8].
spec_SNR: float (optional)
SNR required for spectroscopic follow-up. Default is 10.
"""
light_curve_data = LightCurve()
light_curve_data.load_snpcc_lc(os.path.join(raw_data_dir, file_name))
light_curve_data = self._process_each_light_curve(
light_curve_data, queryable_criteria, days_since_observation,
telescope_names, telescope_sizes, spec_SNR, self._kwargs)
return light_curve_data