flags[f5] = 0
# Add alerts caught by ZTF already from MPC
if ssdistnr is not None:
# alerts should be at max 5'' away from MPC object
f_distance1 = ssdistnr >= 0.0
f_distance2 = ssdistnr < 5.0
# Distance to Panstarrs object should be bigger than distance to MPC object
f_relative_distance = (abs(distpsnr1) - ssdistnr) > 0.0
# Not seen many times with the same objectId
f_ndethist = ndethist <= 2
mask_roid = f_distance1 & f_distance2 & f_relative_distance & f_ndethist
flags[mask_roid] = 3
return pd.Series(flags)
if __name__ == "__main__":
""" Execute the test suite """
globs = globals()
path = os.path.dirname(__file__)
ztf_alert_sample = 'file://{}/data/alerts/datatest'.format(path)
globs["ztf_alert_sample"] = ztf_alert_sample
# Run the test suite
spark_unit_tests(globs)
np.array(catalog_matches, dtype=np.int64),
'match':
True
})
pdf_merge = pd.merge(pdf, pdf_matches, how='left', on='candid')
m = pdf_merge['match'].apply(lambda x: x is True)
# Now get types for these
catalog_ztf_merge = SkyCoord(
ra=np.array(pdf_merge.loc[m, 'ra'].values, dtype=np.float) * u.degree,
dec=np.array(pdf_merge.loc[m, 'dec'].values, dtype=np.float) *
u.degree)
# cross-match
idx2, d2d2, d3d2 = catalog_ztf_merge.match_to_catalog_sky(catalog_other)
pdf_merge['Type'] = 'Unknown'
pdf_merge.loc[m, 'Type'] = [
str(i).strip() for i in type2.astype(str).values[idx2]
]
return pdf_merge['Type']
if __name__ == "__main__":
""" Execute the test suite """
# Run the test suite
spark_unit_tests(globals())
