def findGalaxies(ra_center, dec_center, radius, rMagMax, baMin, baMax):
# CONSTANTS
rad2deg = 180./math.pi
csize = 100000
obj = "ASSEMBLEDGALAXY"
expmjd = 0.
gal_count = 0
wavelen_step = 0.25
Sixflts = ['float','float','float','float','float','float']
# BANDPASSES
# Instantiate bandpasses and read into lsstbp.
bpdir = os.getenv("LSST_THROUGHPUTS_BASELINE")
filterlist = ('u', 'g', 'r', 'i', 'z', 'y')
lsstbp = {}
for f in filterlist:
lsstbp[f] = Bandpass(wavelen_min=300,wavelen_max=1200, wavelen_step=0.1)
lsstbp[f].readThroughput(os.path.join(bpdir, 'total_' + f + '.dat'), wavelen_step=wavelen_step)
# SEDS
# Read in all of the galaxy seds in the root directory:
galdir = "/astro/net/lsst1/shared/data/galaxySED/"
gals = {}
gallist = os.listdir(galdir)
for i in range(len(gallist)):
if gallist[i].endswith('.gz'):
gallist[i] = gallist[i][:-3]
for gal in gallist:
gals[gal] = Sed()
gals[gal].readSED_flambda(os.path.join(galdir, gal))
# Check on resampling - want all galaxy seds to have the same wavelength range.
# (although our LSST ranges are 300 - 1200 nm, the SED's are ~27 to 2290 nm).
if ((gals[gallist[0]].wavelen.min() < 30) & (gals[gallist[0]].wavelen.max() > 2000)):
# If true, then gals[gallist[0]] is okay to use as a template -- this ought to be true.
wavelen_match = gals[gallist[0]].wavelen
else:
print "Had to use simple wavelength array for matching"
wavelen_match = numpy.arange(30, 2200, 0.1, dtype='float')
for gal in gallist:
if gals[gal].needResample(wavelen_match = wavelen_match):
gals[gal].resampleSED(wavelen_match = wavelen_match)
# Create the galactic a, b values from CCM 89 for the source galaxy and ours.
# adjust for redshift, add Milky Way dust (recalculate a and b),
# normalize fluxes and calculate magnitudes:
# First: calculate source galaxy a/b on wavelength range required for
# source galaxy (internal)from CCM 89.
a_int, b_int = gals[gallist[0]].setupCCMab()
# Second: calculate milky way a/b on wavelength range required for calculating
# magnitudes - i.e. 300 to 1200 nm.
# Set up a Sed object that is the same for all galaxies, all chunks.
# Start with a flat SED with F_AB = 3631 Jy
tmpgal = Sed()
tmpgal.setFlatSED(wavelen_min=300, wavelen_max=1200, wavelen_step=wavelen_step)
a_mw, b_mw = tmpgal.setupCCMab() # so this is a/b on 300-1200 range.
# Set up phi, the wavelength-normalized system response for each filter, for each bandpass.
# sb is the system response function (throughputs). Also set up a bandpass list, for
# manyMagCalc method and initiate mags w/dust.
bplist = []
for f in filterlist:
lsstbp[f].sbTophi()
bplist.append(lsstbp[f])
phiarray, dlambda = tmpgal.setupPhiArray(bplist)
objId = numpy.empty(0)
ra = numpy.empty(0)
dec = numpy.empty(0)
diskFluxNorm = numpy.empty(0)
bulgeFluxNorm = numpy.empty(0)
diskSedFilename = numpy.empty(0)
bulgeSedFilename = numpy.empty(0)
a_disk = numpy.empty(0)
b_disk = numpy.empty(0)
a_bulge = numpy.empty(0)
b_bulge = numpy.empty(0)
pa_d = numpy.empty(0)
rdshft = numpy.empty(0)
Rmags = numpy.empty(0)
#QUERY
#myqdb = queryDB.queryDB(chunksize=csize,objtype=obj, filetypes=('REFERENCECATALOG',))
myqdb = queryDB.queryDB(chunksize=csize,objtype=obj, filetypes=('TEST',))
# Specify a circular field of view:
ic = myqdb.getInstanceCatalogByCirc(ra_center, dec_center, radius, expmjd=expmjd)
# Begin iteratively acquiring data
gal_count = 0
while ic is not None:
gal_loop = len(ic.dataArray['raJ2000'])
gal_count += gal_loop
objId = numpy.concatenate((objId, ic.dataArray['objId']), axis=0)
ra = numpy.concatenate((ra, ic.dataArray['raJ2000']*rad2deg), axis=0)
dec = numpy.concatenate((dec, ic.dataArray['decJ2000']*rad2deg), axis=0)
diskFluxNorm = numpy.concatenate((diskFluxNorm, ic.dataArray['diskFluxNorm']), axis=0)
bulgeFluxNorm = numpy.concatenate((bulgeFluxNorm, ic.dataArray['bulgeFluxNorm']), axis=0)
diskSedFilename = numpy.concatenate((diskSedFilename, ic.dataArray['diskSedFilename']), axis=0)
bulgeSedFilename = numpy.concatenate((bulgeSedFilename, ic.dataArray['bulgeSedFilename']), axis=0)
a_disk = numpy.concatenate((a_disk, ic.dataArray['semiMajorDisk']), axis=0)
b_disk = numpy.concatenate((b_disk, ic.dataArray['semiMinorDisk']), axis=0)
a_bulge = numpy.concatenate((a_bulge, ic.dataArray['semiMajorBulge']), axis=0)
b_bulge = numpy.concatenate((b_bulge, ic.dataArray['semiMinorBulge']), axis=0)
pa_d = numpy.concatenate((pa_d, ic.dataArray['positionAngleDisk']), axis=0)
rdshft = numpy.concatenate((rdshft, ic.dataArray['redshift']), axis=0)
# Get next chunk, if it exists.
ic = myqdb.getNextChunk()
myqdb.closeSession()
# Calculate galactic coordinates:
gLon = []
gLat = []
for i in range(gal_count):
gcoord = afwCoord.IcrsCoord(ra[i], dec[i]).toGalactic()
gLon.append(gcoord.getL(afwCoord.DEGREES)*math.pi/180.)
gLat.append(gcoord.getB(afwCoord.DEGREES)*math.pi/180.)
ebv_mw = (EBV.calculateEbv(gLon, gLat, ebvMapNorth, ebvMapSouth, interp = True))
del gLon
del gLat
print 'gLon, gLat calculated'
# Now calculate magnitudes for each galaxy. If you have a bulge, initiate its Sed
# instance, multiply fnu by the bulge flux normalization and apply the bulge dust
# model (currently zero). Next initiate a Sed instance for the disk (if you have
# one), multiply fnu by the disk flux normalization and apply the disk dust model.
# If you have bulge and disk Sed's, add them together; if not you'll just use
# whichever one you have. Correct for redshift, resample the Sed since now it's
# shifted in wavelength, add the Milky Way dust and calculate magnitudes using the
# manyMag method. Uncorrected Magnitudes (no dust, reddening, redshifting added)
# are calculated as well.
uncmags = numpy.zeros(gal_count, dtype={'names':['u','g','r','i','z','y'], 'formats':Sixflts})
raEdge = numpy.zeros(len(ra))
decEdge = numpy.zeros(len(ra))
option = numpy.zeros(len(ra)) + 5
raEdge = ra - a_disk/3600.*math.sin((pa_d)*math.pi/180.)
decEdge = dec + a_disk/3600.*math.cos((pa_d)*math.pi/180.)
# Uncorrected Magnitudes (no dust, reddening, redshifting added)
for i in range(gal_count):
galdisk = diskSedFilename[i]
galbulge = bulgeSedFilename[i]
#raEdge = ra[i] - a_disk[i]/3600.*math.sin((pa_d[i])*math.pi/180.)
#decEdge = dec[i] + a_disk[i]/3600.*math.cos((pa_d[i])*math.pi/180.)
if (galbulge is not None) and (galdisk is not None):
ba_disk = b_disk[i]/a_disk[i]
ba_bulge = b_bulge[i]/a_bulge[i]
baRatio = (diskFluxNorm[i]*ba_disk + bulgeFluxNorm[i]
*ba_bulge)/(diskFluxNorm[i] + bulgeFluxNorm[i])
if baMin <= baRatio <= baMax:
option[i] = 2
else: continue
tmpbulge = uncMagCalc(rdshft[i], gals[galbulge].wavelen, gals[galbulge].flambda,
multiFlux=bulgeFluxNorm[i])
tmpdisk = uncMagCalc(rdshft[i], gals[galdisk].wavelen, gals[galdisk].flambda,
multiFlux=diskFluxNorm[i])
newgal = uncMagCalc(rdshft[i], tmpdisk.wavelen, (tmpdisk.flambda+tmpbulge.flambda), finish=1)
tmpmags = newgal.manyMagCalc(phiarray, dlambda)
elif galbulge is not None:
baRatio = b_disk[i]/a_disk[i]
if baMin <= baRatio <= baMax:
option[i] = 0
else: continue
tmpbulge = uncMagCalc(rdshft[i], gals[galbulge].wavelen, gals[galbulge].flambda,
multiFlux=bulgeFluxNorm[i], finish=1)
tmpmags = tmpbulge.manyMagCalc(phiarray, dlambda)
elif galdisk is not None:
baRatio = b_disk[i]/a_disk[i]
if baMin <= baRatio <= baMax:
option[i] = 1
else: continue
tmpdisk = uncMagCalc(rdshft[i], gals[galdisk].wavelen, gals[galdisk].flambda,
multiFlux=diskFluxNorm[i], finish=1)
tmpmags = tmpdisk.manyMagCalc(phiarray, dlambda)
j = 0
for f in filterlist:
uncmags[f][i] = tmpmags[j]
j += 1
del diskSedFilename, bulgeSedFilename, tmpmags
del Av_d, Rv_d, Av_b, Rv_b, rdshft, uncmags, raEdge, decEdge
idx = numpy.where((tmpmags[2] <= rMagMax) & (option != 5))
rmags = tmpmags[2][idx]
objId = ojbId[idx]
option.append(option)
ra = ra[idx]
dec = dec[idx]
baRatio = baRatio[idx]
a_disk = a_disk[idx]
b_disk = b_disk[idx]
a_bulge = a_bulge[idx]
b_bulge = b_bulge[idx]
diskFluxNorm = diskFluxNorm[idx]
bulgeFluxNorm = bulgeFluxNorm[idx]
pa_d = pa_d[idx]
raEdge = raEdge[idx]
decEdge = decEdge[idx]
#print '%11.7f %11.7f %11.7f %11.7f' % (ra[i], dec[i], tmpmags[2], baRatio)
print '# iterations: ', iteration + 1
print 'Total # of galaxies: %d' % (gal_count)
print 'Number of qualifying Galaxies within a radius of %s deg. is %s' % (radius, len(rmags))
#print 'len(ra), len(rmags), len(baRatio), len(option): ', len(ra), len(rmags), len(baRatio), len(option)
return ra, dec, rmags, baRatio, option, objId, a_disk, b_disk, a_bulge, b_bulge, diskFluxNorm, bulgeFluxNorm, pa_d, raEdge, decEdge
