IRAC-EGS catalogue: the catalogue comes from dmu0_IRAC-EGS
.
In the catalogue, we keep:
We don't know when the maps have been observed. We will use the year of the reference paper.
from herschelhelp_internal import git_version
print("This notebook was run with herschelhelp_internal version: \n{}".format(git_version()))
%matplotlib inline
#%config InlineBackend.figure_format = 'svg'
import matplotlib.pyplot as plt
plt.rc('figure', figsize=(10, 6))
from collections import OrderedDict
import os
from astropy import units as u
from astropy.coordinates import SkyCoord
from astropy.table import Column, Table
import numpy as np
from herschelhelp_internal.flagging import gaia_flag_column
from herschelhelp_internal.masterlist import nb_astcor_diag_plot, remove_duplicates
from herschelhelp_internal.utils import astrometric_correction, flux_to_mag
OUT_DIR = os.environ.get('TMP_DIR', "./data_tmp")
try:
os.makedirs(OUT_DIR)
except FileExistsError:
pass
RA_COL = "irac-egs_ra"
DEC_COL = "irac-egs_dec"
imported_columns = OrderedDict({
'no.': "irac-egs_id",
'ALPHA_GR_DEC_ORDER': "irac-egs_ra",
'DELTA_GR_DEC_ORDER': "irac-egs_dec",
'irac36_final': "f_irac-egs_i1",
'err_irac36_final': "ferr_irac-egs_i1",
'irac45_final': "f_irac-egs_i2",
'err_irac45_final': "ferr_irac-egs_i2",
'irac58_final': "f_irac-egs_i3",
'err_irac58_final': "ferr_irac-egs_i3",
'irac80_final': "f_irac-egs_i4",
'err_irac80_final': "ferr_irac-egs_i4",
})
catalogue = Table.read("../../dmu0/dmu0_IRAC-EGS/data/IRAC_EGS.fits")[list(imported_columns)]
for column in imported_columns:
catalogue[column].name = imported_columns[column]
epoch = 2011 # TODO: Check
# Clean table metadata
catalogue.meta = None
# Adding flux and band-flag columns
for col in catalogue.colnames:
if col.startswith('f_'):
errcol = "ferr{}".format(col[1:])
# Some object have a magnitude to 0, we suppose this means missing value
catalogue[col][np.isclose(catalogue[col], -99.) ] = np.nan
catalogue[errcol][np.isclose(catalogue[errcol], -99.) ] = np.nan
#fluxes already in uJy
mag, error = flux_to_mag(np.array(catalogue[col])*1.e-6, np.array(catalogue[errcol])*1.e-6)
catalogue.add_column(Column(mag , name="m{}".format(col[1:])))
catalogue.add_column(Column(error , name="m{}".format(errcol[1:])))
# Add empty aperture columns
catalogue.add_column(Column(np.full(len(catalogue), np.nan), name="m_ap{}".format(col[1:])))
catalogue.add_column(Column(np.full(len(catalogue), np.nan), name="merr_ap{}".format(col[1:])))
catalogue.add_column(Column(np.full(len(catalogue), np.nan), name="f_ap{}".format(col[1:])))
catalogue.add_column(Column(np.full(len(catalogue), np.nan), name="ferr_ap{}".format(col[1:])))
# Band-flag column
if "ap" not in col:
catalogue.add_column(Column(np.zeros(len(catalogue), dtype=bool), name="flag{}".format(col[1:])))
# TODO: Set to True the flag columns for fluxes that should not be used for SED fitting.
catalogue[:10].show_in_notebook()
We remove duplicated objects from the input catalogues.
SORT_COLS = ['ferr_irac-egs_i1', 'ferr_irac-egs_i2', 'ferr_irac-egs_i3', 'ferr_irac-egs_i4']
FLAG_NAME = 'wfc_flag_cleaned'
nb_orig_sources = len(catalogue)
catalogue = remove_duplicates(catalogue, RA_COL, DEC_COL, sort_col=SORT_COLS,flag_name=FLAG_NAME)
nb_sources = len(catalogue)
print("The initial catalogue had {} sources.".format(nb_orig_sources))
print("The cleaned catalogue has {} sources ({} removed).".format(nb_sources, nb_orig_sources - nb_sources))
print("The cleaned catalogue has {} sources flagged as having been cleaned".format(np.sum(catalogue[FLAG_NAME])))
We match the astrometry to the Gaia one. We limit the Gaia catalogue to sources with a g band flux between the 30th and the 70th percentile. Some quick tests show that this give the lower dispersion in the results.
gaia = Table.read("../../dmu0/dmu0_GAIA/data/GAIA_EGS.fits")
gaia_coords = SkyCoord(gaia['ra'], gaia['dec'])
nb_astcor_diag_plot(catalogue[RA_COL], catalogue[DEC_COL],
gaia_coords.ra, gaia_coords.dec)
delta_ra, delta_dec = astrometric_correction(
SkyCoord(catalogue[RA_COL], catalogue[DEC_COL]),
gaia_coords
)
print("RA correction: {}".format(delta_ra))
print("Dec correction: {}".format(delta_dec))
catalogue[RA_COL] = catalogue[RA_COL] + delta_ra.to(u.deg)
catalogue[DEC_COL] = catalogue[DEC_COL] + delta_dec.to(u.deg)
nb_astcor_diag_plot(catalogue[RA_COL], catalogue[DEC_COL],
gaia_coords.ra, gaia_coords.dec)
catalogue.add_column(
gaia_flag_column(SkyCoord(catalogue[RA_COL], catalogue[DEC_COL]), epoch, gaia)
)
GAIA_FLAG_NAME = "irac-egs_flag_gaia"
catalogue['flag_gaia'].name = GAIA_FLAG_NAME
print("{} sources flagged.".format(np.sum(catalogue[GAIA_FLAG_NAME] > 0)))
catalogue.write("{}/IRAC-EGS.fits".format(OUT_DIR), overwrite=True)