# Calculate the distance to the nearest satellite that is too heavy
idx, sep2d, satdist3d = lenscoords_bin.match_to_catalog_3d(
satcoords_bin, nthneighbor=2)
satdistlist[massmask_lens] = satdist3d
# Add the result to the catalogue
(satdistcat[d])[nanmask] = satdistlist
print('logmbins:', logmlims)
print('dlogm:', dlogm)
# Write the results to a fits table
filename = '/data/users/brouwer/LensCatalogues/%s_isolated_galaxies_perc_h%i' % (
cat, h * 100.)
if '-' in cat:
name = cat.split('-')[-1]
outputnames = np.append(
['ID', 'logmstar_%s' % name],
['dist%s%s_%s' % (n, rationame, name) for n in rationames])
else:
outputnames = np.append(['ID', 'logmstar'],
['dist%s%s' % (n, rationame) for n in rationames])
formats = np.append(['D'] * 2, ['D'] * len(massratios))
output = np.append([lensID, logmstarcat], satdistcat, axis=0)
print(outputnames, formats, output)
utils.write_catalog('%s.fits' % filename, outputnames, formats, output)
# Import lens catalog
fields, path_lenscat, lenscatname, lensID, lensRA, lensDEC, lensZ, lensDc, rmag, rmag_abs, logmstar =\
utils.import_lenscat(cat, h, cosmo)
# Mean difference with the GAMA masses (log(M_ANN)-log(M_G))
if ('kids' in cat) or ('matched' in cat):
#diff_GL = -0.10978165582547783
diff_GL = -0.056
else:
diff_GL = 0.
bias = 0.2
logmstar_GL = logmstar - diff_GL
logmstar_min = logmstar_GL - bias
logmstar_max = logmstar_GL + bias
logmbar, logmbar_GL, logmbar_min, logmbar_max = \
[calc_logmbar(b) for b in [logmstar, logmstar_GL, logmstar_min, logmstar_max]]
output = [lensID, logmstar, logmbar, logmstar_GL, logmbar_GL, \
logmstar_min, logmbar_min, logmstar_max, logmbar_max]
outputnames = ['ID', 'logmstar', 'logmbar', 'logmstar_GL', 'logmbar_GL', \
'logmstar_min', 'logmbar_min', 'logmstar_max', 'logmbar_max']
filename = '/data/users/brouwer/LensCatalogues/baryonic_mass_catalog_%s.fits' % cat
formats = ['D'] * len(outputnames)
utils.write_catalog(filename, outputnames, formats, output)
