def find_crossmatch_failures(survey): r = pd.read_hdf('/data/jls/GaiaDR2/spectro/%s_input.hdf5' % survey) # columns = ['parallax', 'parallax_error', # 'pmra', 'pmdec', # 'pmra_error', 'pmdec_error', # 'parallax_pmra_corr', 'parallax_pmdec_corr', 'pmra_pmdec_corr', # 'source_id', 'G', 'GBP', 'GRP', 'eG', 'eGRP', 'eGBP', # 'a_g_val', 'a_g_percentile_lower', 'a_g_percentile_upper'] # r = r.drop(columns, axis=1) if survey == 'GES': rx = load_ges() if survey == 'APOGEE': rx = load_apogee() if survey == 'RAVE': rx = load_rave(use_dr5=True) if survey == 'RAVEON': rx = load_rave(use_dr5=False) if survey == 'GALAH': rx = load_galah() if survey == 'LAMOST': rx = load_lamost() rx = format_columns(rx) rx = crossmatch_gaia_spectro(rx, no_proper_motion=False, dist_max=5.) print len(rx), np.count_nonzero(r.source_id > 0), np.count_nonzero( rx.source_id > 0), np.count_nonzero(r.source_id != rx.source_id) rx = rx[(rx.source_id > 0) & (r.source_id != rx.source_id)].reset_index(drop=True) rx.to_hdf('/data/jls/GaiaDR2/spectro/%s_input_pm.hdf5' % survey, 'data')
def run_rave_on(): rave = load_rave(output_folder + 'RAVEON_input.hdf5', use_dr1=DR1) return rave = check_photometry(rave) run_distance_pipeline(rave, output_folder + 'RAVE_Cannon_distances%s.hdf5' % name_str, 'raveid', 'RAVE Cannon', npool=npool, with_parallax=with_parallax)
def run_rave_dr5_fillin(): rave = load_rave(use_dr1=DR1, use_dr5=True) rave2 = Table.read(output_folder + 'RAVE_DR5_distances.hdf5') rave = check_photometry(rave[rave2['flag'] == 3].reset_index(drop=True)) run_distance_pipeline(rave, output_folder + 'RAVE_DR5_distances_fillin.hdf5', 'raveid', 'RAVE DR5', npool=npool, with_parallax=with_parallax)
def run_rave_dr5(): rave = load_rave(output_file=output_folder + 'RAVE_input.hdf5', use_dr1=DR1, use_dr5=True) return rave = check_photometry(rave) run_distance_pipeline(rave, output_folder + 'RAVE_DR5_distances%s.hdf5' % name_str, 'raveid', 'RAVE DR5', npool=npool, with_parallax=with_parallax, thin_mag=0.1)
def run_rave_dr5(): rave = load_rave(use_dr1=DR1, use_dr5=True) if TEST: rave = rave.sample(n=TESTNUMBER, random_state=random_seed).reset_index(drop=True) rave = check_photometry(rave) run_distance_pipeline(rave, output_folder + 'RAVE_DR5_distances%s.hdf5' % name_str, 'raveid', 'RAVE DR5', npool=npool, with_parallax=with_parallax)
def run_rave_on_extra(): rave = load_rave(output_folder + 'RAVEON_input_pm.hdf5', use_dr1=DR1) if TEST: rave = rave.sample(n=TESTNUMBER, random_state=random_seed).reset_index(drop=True) rave = check_photometry(rave) run_distance_pipeline(rave, output_folder + 'RAVE_Cannon_distances_pm%s.hdf5' % name_str, 'raveid', 'RAVE Cannon', npool=npool, with_parallax=with_parallax)