def read_meert_catalog(phot_type=None):
"""Loader for the Meert et al. 2015 catalog of improved photometric measurements
for galaxies in the SDSS DR7 main galaxy catalog
input: phot_type - integer corresponding to the photometry model fit type from the catalog
1=best fit, 2=deVaucouleurs, 3=Sersic, 4=DeVExp, 5=SerExp
returns combined structured array with all the data
"""
import pyfits
from setup import data_home_dir
if (phot_type < 1) or (phot_type > 5):
raise Exception(
'unsupported type of Meert et al. photometry: %d, choose number between 1 and 5'
)
datadir = data_home_dir()
datameertnonpar = datadir + '\\Meert2015_v2\UPenn_PhotDec_nonParam_rband.fits'
datameertnonparg = datadir + '\\Meert2015_v2\UPenn_PhotDec_nonParam_gband.fits'
datameert = datadir + '\\Meert2015_v2\UPenn_PhotDec_Models_rband.fits'
datasdss = datadir + '\\Meert2015_v2\UPenn_PhotDec_CAST.fits'
datasdssmodels = datadir + '\\Meert2015_v2\UPenn_PhotDec_CASTmodels.fits'
datameertg = datadir + '\\Meert2015_v2\UPenn_PhotDec_Models_gband.fits'
datamorph = datadir + '\\Meert2015_v2\UPenn_PhotDec_H2011.fits' # morphology probabilities from Huertas-Company et al. 2011
# mdata tables: 1=best fit, 2=deVaucouleurs, 3=Sersic, 4=DeVExp, 5=SerExp
mdata = pyfits.open(datameert)[phot_type].data
mdatag = pyfits.open(datameertg)[phot_type].data
mnpdata = pyfits.open(datameertnonpar)[1].data
mnpdatag = pyfits.open(datameertnonparg)[1].data
sdata = pyfits.open(datasdss)[1].data
phot_r = pyfits.open(datasdssmodels)[1].data
morph = pyfits.open(datamorph)[1].data
# eliminate galaxies with bad photometry
fflag = mdata['finalflag']
print(np.size(fflag), "galaxies in Meert et al. sample initially")
def isset(flag, bit):
"""Return True if the specified bit is set in the given bit mask"""
return (flag & (1 << bit)) != 0
# use minimal quality cuts and flags recommended by Alan Meert
igood = [(phot_r['petroMag'] > 0.) & (phot_r['petroMag'] < 100.) &
(mnpdata['kcorr'] > 0) & (mdata['m_tot'] > 0) &
(mdata['m_tot'] < 100) & (isset(fflag, 1) | isset(fflag, 4)
| isset(fflag, 10) | isset(fflag, 14))]
sdata = sdata[igood]
phot_r = phot_r[igood]
mdata = mdata[igood]
mnpdata = mnpdata[igood]
mdatag = mdatag[igood]
mnpdatag = mnpdatag[igood]
morph = morph[igood]
return sdata, mdata, mnpdata, phot_r, mdatag, mnpdatag, morph
def read_meert_catalog(phot_type=None):
"""Loader for the Meert et al. 2015 catalog of improved photometric measurements
for galaxies in the SDSS DR7 main galaxy catalog
input: phot_type - integer corresponding to the photometry model fit type from the catalog
1=best fit, 2=deVaucouleurs, 3=Sersic, 4=DeVExp, 5=SerExp
returns combined structured array with all the data
"""
import pyfits
from setup import data_home_dir
if (phot_type < 1) or (phot_type > 5):
raise Exception('unsupported type of Meert et al. photometry: %d, choose number between 1 and 5')
datadir = data_home_dir()
datameertnonpar = datadir+'/Meert2015_v2/UPenn_PhotDec_nonParam_rband.fits'
datameertnonparg = datadir+'/Meert2015_v2/UPenn_PhotDec_nonParam_gband.fits'
datameertnonpari = datadir+'/Meert2015_v2/UPenn_PhotDec_nonParam_iband.fits'
datameert = datadir+'/Meert2015_v2/UPenn_PhotDec_Models_rband.fits'
datasdss = datadir+'/Meert2015_v2/UPenn_PhotDec_CAST.fits'
datasdssmodels = datadir+'/Meert2015_v2/UPenn_PhotDec_CASTmodels.fits'
datameertg = datadir+'/Meert2015_v2/UPenn_PhotDec_Models_gband.fits'
datameerti = datadir+'/Meert2015_v2/UPenn_PhotDec_Models_iband.fits'
datamorph = datadir+'/Meert2015_v2/UPenn_PhotDec_H2011.fits' # morphology probabilities from Huertas-Company et al. 2011
# mdata tables: 1=best fit, 2=deVaucouleurs, 3=Sersic, 4=DeVExp, 5=SerExp
mdata = pyfits.open(datameert)[phot_type].data
mdatag = pyfits.open(datameertg)[phot_type].data
mdatai = pyfits.open(datameerti)[phot_type].data
mnpdata = pyfits.open(datameertnonpar)[1].data
mnpdatag = pyfits.open(datameertnonparg)[1].data
mnpdatai = pyfits.open(datameertnonpari)[1].data
sdata = pyfits.open(datasdss)[1].data
phot_r = pyfits.open(datasdssmodels)[1].data
morph = pyfits.open(datamorph)[1].data
# eliminate galaxies with bad photometry
fflag = mdata['finalflag']
print np.size(fflag), "galaxies in Meert et al. sample initially"
def isset(flag, bit):
"""Return True if the specified bit is set in the given bit mask"""
return (flag & (1 << bit)) != 0
# use minimal quality cuts and flags recommended by Alan Meert
igood = [(phot_r['petroMag'] > 0.) & (phot_r['petroMag'] < 100.) & (mnpdata['kcorr'] > 0) &
(mdata['m_tot'] > 0) & (mdata['m_tot'] < 100) &
(isset(fflag, 1) | isset(fflag, 4) | isset(fflag, 10) | isset(fflag, 14))]
sdata = sdata[igood]; phot_r = phot_r[igood]; mdata = mdata[igood]; mdatai = mdatai[igood]
mnpdata = mnpdata[igood]; mdatag = mdatag[igood]; mnpdatag = mnpdatag[igood]; morph = morph[igood]; mnpdatai = mnpdatai[igood];
return sdata, mdata, mnpdata, phot_r, mdatag, mnpdatag, morph, mdatai, mnpdatai
ax.contour(H, linewidths=np.linspace(1,2,len(lvls))[::-1],
colors='whitesmoke', alpha=0.4, levels = lvls, norm = LogNorm(),
extent = [xbins[0], xbins[-1], ybins[0], ybins[-1]], interpolation='bicubic')
if outfile != None:
plt.savefig(outfile)
plt.show()
if __name__ == '__main__':
from read_sdss_fits import read_sdss_fits
from setup import data_home_dir
# read fits file with the SDSS DR8 main spectroscopic sample
data = read_sdss_fits(data_home_dir()+'SDSSspecgalsDR8.fit')
z_max = 0.04
# redshift cut
sdata = data[data['z'] < z_max]
mr = sdata['modelMag_r']
gr = sdata['modelMag_g'] - sdata['modelMag_r']
r50 = sdata['petroR50_r']
sb = mr - 2.5*np.log10(0.5) + 2.5*np.log10(np.pi*(r50)**2)
from colossus.cosmology import cosmology
# set cosmology to the best values from 9-year WMAP data
cosmo = cosmology.setCosmology('WMAP9')