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())