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BUG: fix function names after rename #194

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Dec 19, 2023
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BUG: fix function names after rename #194

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38 changes: 19 additions & 19 deletions light_curves/code_src/sample_lc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,8 +9,8 @@
from gaia_functions import Gaia_get_lightcurve
from HCV_functions import HCV_get_lightcurves
from heasarc_functions import HEASARC_get_lightcurves
from icecube_functions import icecube_get_lightcurve
from panstarrs import panstarrs_get_lightcurves
from icecube_functions import Icecube_get_lightcurve
from panstarrs import Panstarrs_get_lightcurves
from sample_selection import (clean_sample, get_green_sample, get_hon_sample, get_lamassa_sample,
get_lopeznavas_sample, get_lyu_sample, get_macleod16_sample, get_macleod19_sample, get_paper_sample,
get_ruan_sample, get_SDSS_sample, get_sheng_sample, get_yang_sample, nonunique_sample)
Expand All @@ -22,10 +22,10 @@

def build_sample():
'''Putting together a sample of SDSS quasars, WISE variable AGNs,
TDEs, Changing look AGNs, .. coordinates from different
TDEs, Changing look AGNs, .. coordinates from different
papers.'''
coords =[]

coords = []
labels = []

get_lamassa_sample(coords, labels) #2015ApJ...800..144L
Expand All @@ -44,38 +44,38 @@ def build_sample():
vagn_coords = [SkyCoord(ra, dec, frame='icrs', unit='deg') for ra, dec in zip(VAGN['SDSS_RA'], VAGN['SDSS_Dec'])]
vagn_labels = ['WISE-Variable' for ra in VAGN['SDSS_RA']]
coords.extend(vagn_coords)
labels.extend(vagn_labels)
labels.extend(vagn_labels)

#now get some "normal" QSOs for use in the classifier
#there are ~500K of these, so choose the number based on
#a balance between speed of running the light curves and whatever
#a balance between speed of running the light curves and whatever
#the ML algorithms would like to have
num_normal_QSO = 2000
get_SDSS_sample(coords, labels, num_normal_QSO)

## ADD TDEs to the sample, manually copied the TDE ZTF names from Hammerstein et al. 2023
#tde_names = ['ZTF18aabtxvd','ZTF18aahqkbt','ZTF18abxftqm','ZTF18acaqdaa','ZTF18acpdvos','ZTF18actaqdw','ZTF19aabbnzo','ZTF18acnbpmd','ZTF19aakiwze','ZTF19aakswrb','ZTF17aaazdba','ZTF19aapreis','ZTF19aarioci','ZTF19abhejal','ZTF19abhhjcc','ZTF19abidbya','ZTF19abzrhgq','ZTF19accmaxo','ZTF20aabqihu','ZTF19acspeuw','ZTF20aamqmfk','ZTF18aakelin','ZTF20abjwvae','ZTF20abfcszi','ZTF20abefeab','ZTF20abowque','ZTF20abrnwfc','ZTF20acitpfz','ZTF20acqoiyt', 'ZTF20abnorit']
#TDE_id2coord(tde_names,coords,labels)


get_paper_sample('2015ApJ...810...14A','FermiBL',coords,labels)
get_paper_sample('2019A&A...627A..33D','Cicco19',coords,labels)
get_paper_sample('2022ApJ...933...37W','Galex variable 22',coords,labels)
get_paper_sample('2020ApJ...896...10B','Palomar variable 20',coords,labels)

#To remove duplicates from the list if combining multiple references clean_sample can be used
#To remove duplicates from the list if combining multiple references clean_sample can be used
# the call below with nonunique_sample just changes the structure to mimic the output of clean sample
coords_list, labels_list = nonunique_sample(coords, labels)
coords_list, labels_list = nonunique_sample(coords, labels)
print('final sample: ',len(coords))
return coords_list,labels_list


def parallel_lc(coords_list,labels_list,parquet_savename = '../output/df_lc_.parquet'):
''' Check all the archives for the light curve data of the
list of coordinates given in input in parallel and return a
''' Check all the archives for the light curve data of the
list of coordinates given in input in parallel and return a
muldidimensional lightcurve dataframe.'''
max_fermi_error_radius = str(1.0)

max_fermi_error_radius = str(1.0)
max_sax_error_radius = str(3.0)
heasarc_cat = ["FERMIGTRIG", "SAXGRBMGRB"]
error_radius = [max_fermi_error_radius , max_sax_error_radius]
Expand Down Expand Up @@ -109,10 +109,10 @@ def parallel_lc(coords_list,labels_list,parquet_savename = '../output/df_lc_.par
HCV_get_lightcurves, (coords_list, labels_list, hcv_radius), callback=callback
)
pool.apply_async(
icecube_get_lightcurve, (coords_list, labels_list, 3, "../data/", 1), callback=callback
Icecube_get_lightcurve, (coords_list, labels_list, 3, "../data/", 1), callback=callback
)
pool.apply_async(
panstarrs_get_lightcurves, (coords_list, labels_list, panstarrs_radius), callback=callback
Panstarrs_get_lightcurves, (coords_list, labels_list, panstarrs_radius), callback=callback
)
pool.apply_async(
TESS_Kepler_get_lightcurves, (coords_list, labels_list, lk_radius), callback=callback
Expand All @@ -129,7 +129,7 @@ def parallel_lc(coords_list,labels_list,parquet_savename = '../output/df_lc_.par

parallel_endtime = time.time()
print('parallel processing took', parallel_endtime - parallel_starttime, 's')

# # Save the data for future use with ML notebook
parallel_df_lc.data.to_parquet(parquet_savename)
print("file saved!")
Expand All @@ -139,6 +139,6 @@ def main():
c,l = build_sample()
dflc = parallel_lc(c,l,parquet_savename = '../output/df_lc_smalltest.parquet')
# Unify for ML and save

if __name__ == "__main__":
main()