In [1]:
from herschelhelp_internal import git_version
print("This notebook was run with herschelhelp_internal version: \n{}".format(git_version()))
In [2]:
%matplotlib inline
#%config InlineBackend.figure_format = 'svg'
import matplotlib.pyplot as plt
plt.rc('figure', figsize=(10, 6))
plt.style.use('ggplot')
import locale
locale.setlocale(locale.LC_ALL, 'en_GB')
import os
import time
import itertools
from astropy.coordinates import SkyCoord
from astropy.table import Table
from astropy import units as u
from astropy import visualization as vis
import numpy as np
from matplotlib_venn import venn3, venn2
from herschelhelp_internal.masterlist import (nb_compare_mags, nb_ccplots, nb_histograms, find_last_ml_suffix,
quick_checks)
In [3]:
OUT_DIR = os.environ.get('OUT_DIR', "./data")
SUFFIX = find_last_ml_suffix()
#SUFFIX = "20171016"
master_catalogue_filename = "master_catalogue_spire-nep_{}.fits".format(SUFFIX)
master_catalogue = Table.read("{}/{}".format(OUT_DIR, master_catalogue_filename))
print("Diagnostics done using: {}".format(master_catalogue_filename))
0 - Quick checks¶
In [4]:
quick_checks(master_catalogue)
I - Summary of wavelength domains¶
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flag_obs = master_catalogue['flag_optnir_obs']
flag_det = master_catalogue['flag_optnir_det']
II - Comparing magnitudes in similar filters¶
The master list if composed of several catalogues containing magnitudes in similar filters on different instruments. We are comparing the magnitudes in these corresponding filters.
In [6]:
u_bands = []
g_bands = [ "GPC1 g"]
r_bands = [ "GPC1 r"]
i_bands = [ "GPC1 i"]
z_bands = [ "GPC1 z"]
y_bands = [ "GPC1 y"]
II.a - Comparing depths¶
We compare the histograms of the total aperture magnitudes of similar bands.
In [7]:
for bands in [u_bands, g_bands, r_bands, i_bands, z_bands, y_bands]:
colnames = ["m_{}".format(band.replace(" ", "_").lower()) for band in bands]
nb_histograms(master_catalogue, colnames, bands)
II.b - Comparing magnitudes¶
We compare one to one each magnitude in similar bands.
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for band_of_a_kind in [u_bands, g_bands, r_bands, i_bands, z_bands, y_bands]:
for band1, band2 in itertools.combinations(band_of_a_kind, 2):
basecol1, basecol2 = band1.replace(" ", "_").lower(), band2.replace(" ", "_").lower()
col1, col2 = "m_ap_{}".format(basecol1), "m_ap_{}".format(basecol2)
nb_compare_mags(master_catalogue[col1], master_catalogue[col2],
labels=("{} (aperture)".format(band1), "{} (aperture)".format(band2)))
col1, col2 = "m_{}".format(basecol1), "m_{}".format(basecol2)
nb_compare_mags(master_catalogue[col1], master_catalogue[col2],
labels=("{} (total)".format(band1), "{} (total)".format(band2)))
III - Comparing magnitudes to reference bands¶
Cross-match the master list to SDSS to compare magnitudes.
In [9]:
master_catalogue_coords = SkyCoord(master_catalogue['ra'], master_catalogue['dec'])
III.a - Comparing u, g, r, i, and z bands to SDSS¶
The catalogue is cross-matched to SDSS-DR13 withing 0.2 arcsecond.
We compare the u, g, r, i, and z magnitudes to those from SDSS using fiberMag for the aperture magnitude and petroMag for the total magnitude.
In [10]:
sdss = Table.read("../../dmu0/dmu0_SDSS-DR13/data/SDSS-DR13_SPIRE-NEP.fits")
sdss_coords = SkyCoord(sdss['ra'] * u.deg, sdss['dec'] * u.deg)
idx, d2d, _ = sdss_coords.match_to_catalog_sky(master_catalogue_coords)
mask = (d2d < 0.2 * u.arcsec)
sdss = sdss[mask]
ml_sdss_idx = idx[mask]
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for band_of_a_kind in [u_bands, g_bands, r_bands, i_bands, z_bands]:
for band in band_of_a_kind:
sdss_mag_ap = sdss["fiberMag_{}".format(band[-1])]
master_cat_mag_ap = master_catalogue["m_ap_{}".format(band.replace(" ", "_").lower())][ml_sdss_idx]
nb_compare_mags(sdss_mag_ap, master_cat_mag_ap,
labels=("SDSS {} (fiberMag)".format(band[-1]), "{} (aperture)".format(band)))
sdss_mag_tot = sdss["petroMag_{}".format(band[-1])]
master_cat_mag_tot = master_catalogue["m_ap_{}".format(band.replace(" ", "_").lower())][ml_sdss_idx]
nb_compare_mags(sdss_mag_ap, master_cat_mag_ap,
labels=("SDSS {} (petroMag)".format(band[-1]), "{} (total)".format(band)))
IV - Comparing aperture magnitudes to total ones.¶
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nb_ccplots(
master_catalogue['m_gpc1_r'],
master_catalogue['m_ap_gpc1_r'] - master_catalogue['m_gpc1_r'],
"r total magnitude (GPC1)", "r aperture mag - total mag (GPC1)",
np.full(len(master_catalogue), 1.),
invert_x=True
)
V - Color-color and magnitude-color plots¶
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nb_ccplots(
master_catalogue['m_gpc1_g'] - master_catalogue['m_gpc1_z'],
master_catalogue['m_gpc1_r'] - master_catalogue['m_gpc1_y'],
"i - z (GPC1)", "z - J (GPC1)",
np.full(len(master_catalogue), 1.)
) #No stellarity in panstarrs so use all sources
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