def stage2(cat=None,
variances=None,
T=None,
bands=None,
ps=None,
targetwcs=None,
**kwargs):
print('kwargs:', kwargs.keys())
#print 'variances:', variances
from desi_common import prepare_fits_catalog
TT = T.copy()
hdr = None
fs = None
T2, hdr = prepare_fits_catalog(cat, 1. / np.array(variances), TT, hdr,
bands, fs)
T2.about()
T2.writeto('cfht.fits')
ccmap = dict(g='g', r='r', i='m')
bandlist = [b for b in bands]
scat, S = get_sdss_sources(bandlist, targetwcs)
S.about()
I, J, d = match_radec(T2.ra, T2.dec, S.ra, S.dec, 1. / 3600.)
M = fits_table()
M.ra = S.ra[J]
M.dec = S.dec[J]
M.cfhtI = I
for band in bands:
mag = T2.get('decam_%s_mag' % band)[I]
sflux = np.array([s.getBrightness().getBand(band) for s in scat])[J]
smag = NanoMaggies.nanomaggiesToMag(sflux)
M.set('mag_%s' % band, mag)
M.set('smag_%s' % band, smag)
cc = ccmap[band]
plt.clf()
plt.subplot(2, 1, 1)
plt.plot(smag, mag, '.', color=cc, alpha=0.5)
lo, hi = 16, 24
plt.plot([lo, hi], [lo, hi], 'k-')
plt.xlabel('SDSS mag')
plt.ylabel('CFHT mag')
plt.axis([lo, hi, lo, hi])
plt.subplot(2, 1, 2)
plt.plot(smag, mag - smag, '.', color=cc, alpha=0.5)
lo, hi = 16, 24
plt.plot([lo, hi], [0, 0], 'k-')
plt.xlabel('SDSS mag')
plt.ylabel('CFHT - SDSS mag')
plt.axis([lo, hi, -1, 1])
plt.suptitle('%s band' % band)
ps.savefig()
M.writeto('cfht-matched.fits')
plt.clf()
lp, lt = [], []
for band in bands:
sn = T2.get('decam_%s_nanomaggies' % band) * np.sqrt(
T2.get('decam_%s_nanomaggies_invvar' % band))
#mag = T2.get('decam_%s_mag_corr' % band)
mag = T2.get('decam_%s_mag' % band)
print('band', band)
print('Mags:', mag)
print('SN:', sn)
cc = ccmap[band]
p = plt.semilogy(mag, sn, '.', color=cc, alpha=0.5)
lp.append(p[0])
lt.append('%s band' % band)
plt.xlabel('mag')
plt.ylabel('Flux Signal-to-Noise')
tt = [1, 2, 3, 4, 5, 10, 20, 30, 40, 50]
plt.yticks(tt, ['%i' % t for t in tt])
plt.axhline(5., color='k')
#plt.axis([21, 26, 1, 20])
plt.legend(lp, lt, loc='upper right')
plt.title('CFHT depth')
ps.savefig()
# ['tims', 'cons', 'pixscale', 'H', 'coimgs', 'detmaps', 'W', 'brick', 'detivs', 'targetrd']
return dict(T2=T2,
M=M,
tims=None,
detmaps=None,
detivs=None,
cons=None,
coimgs=None)
TT = T.copy()
for k in ['itx', 'ity', 'index']:
TT.delete_column(k)
for col in TT.get_columns():
if not col in ['tx', 'ty', 'blob']:
TT.rename(col, 'sdss_%s' % col)
TT.brickid = np.zeros(len(TT), np.int32) + brickid
TT.objid = np.arange(len(TT)).astype(np.int32)
invvars = None
hdr = None
fs = None
cat.thawAllRecursive()
T2, hdr = prepare_fits_catalog(cat, invvars, TT, hdr, bands, fs)
# Unpack shape columns
T2.shapeExp_r = T2.shapeExp[:, 0]
T2.shapeExp_e1 = T2.shapeExp[:, 1]
T2.shapeExp_e2 = T2.shapeExp[:, 2]
T2.shapeDev_r = T2.shapeExp[:, 0]
T2.shapeDev_e1 = T2.shapeExp[:, 1]
T2.shapeDev_e2 = T2.shapeExp[:, 2]
T2.shapeExp_r_ivar = T2.shapeExp_ivar[:, 0]
T2.shapeExp_e1_ivar = T2.shapeExp_ivar[:, 1]
T2.shapeExp_e2_ivar = T2.shapeExp_ivar[:, 2]
T2.shapeDev_r_ivar = T2.shapeExp_ivar[:, 0]
T2.shapeDev_e1_ivar = T2.shapeExp_ivar[:, 1]
T2.shapeDev_e2_ivar = T2.shapeExp_ivar[:, 2]
T2.writeto(opt.output)
def main():
"""Main program.
"""
import argparse
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('-b',
'--brick',
type=int,
metavar='BRICK',
help='Brick ID to run: default %(default)s',
default=377306)
parser.add_argument('-s',
'--sed-matched',
action='store_true',
help='Run SED-matched filter?')
parser.add_argument('-B',
'--bands',
default='grz',
help='Bands to retrieve')
parser.add_argument('-o',
'--output',
metavar='FILE',
help='Output filename for catalog',
default='initial-cat.fits')
parser.add_argument('-t', '--threads', type=int, help='Run multi-threaded')
parser.add_argument('-W',
'--width',
type=int,
dest='W',
default=3600,
metavar='PIXELS',
help='Target image width (default %(default)s)')
parser.add_argument('-H',
'--height',
type=int,
dest='H',
default=3600,
metavar='PIXELS',
help='Target image height (default %(default)s)')
if not (('BOSS_PHOTOOBJ' in os.environ) and
('PHOTO_RESOLVE' in os.environ)):
print(
'''$BOSS_PHOTOOBJ and $PHOTO_RESOLVE not set -- on NERSC, you can do:
export BOSS_PHOTOOBJ=/project/projectdirs/cosmo/data/sdss/pre13/eboss/photoObj.v5b
export PHOTO_RESOLVE=/project/projectdirs/cosmo/data/sdss/pre13/eboss/resolve/2013-07-29
To read SDSS files from the local filesystem rather than downloading them.
''')
opt = parser.parse_args()
brickid = opt.brick
bands = opt.bands
if opt.threads and opt.threads > 1:
from astrometry.util.multiproc import multiproc
mp = multiproc(opt.threads)
else:
mp = multiproc()
ps = None
plots = False
decals = Decals()
brick = decals.get_brick(brickid)
print('Chosen brick:')
brick.about()
targetwcs = wcs_for_brick(brick, W=opt.W, H=opt.H)
W, H = targetwcs.get_width(), targetwcs.get_height()
# Read SDSS sources
cat, T = get_sdss_sources(bands, targetwcs)
if opt.sed_matched:
# Read images
tims = decals.tims_touching_wcs(targetwcs,
mp,
mock_psf=True,
bands=bands)
print('Rendering detection maps...')
detmaps, detivs = detection_maps(tims, targetwcs, bands, mp)
SEDs = sed_matched_filters(bands)
Tnew, newcat, nil = run_sed_matched_filters(SEDs, bands, detmaps,
detivs, (T.itx, T.ity),
targetwcs)
T = merge_tables([T, Tnew], columns='fillzero')
cat.extend(newcat)
from desi_common import prepare_fits_catalog
TT = T.copy()
for k in ['itx', 'ity', 'index']:
TT.delete_column(k)
for col in TT.get_columns():
if not col in ['tx', 'ty', 'blob']:
TT.rename(col, 'sdss_%s' % col)
TT.brickid = np.zeros(len(TT), np.int32) + brickid
TT.objid = np.arange(len(TT)).astype(np.int32)
invvars = None
hdr = None
fs = None
cat.thawAllRecursive()
T2, hdr = prepare_fits_catalog(cat, invvars, TT, hdr, bands, fs)
# Unpack shape columns
T2.shapeExp_r = T2.shapeExp[:, 0]
T2.shapeExp_e1 = T2.shapeExp[:, 1]
T2.shapeExp_e2 = T2.shapeExp[:, 2]
T2.shapeDev_r = T2.shapeExp[:, 0]
T2.shapeDev_e1 = T2.shapeExp[:, 1]
T2.shapeDev_e2 = T2.shapeExp[:, 2]
T2.shapeExp_r_ivar = T2.shapeExp_ivar[:, 0]
T2.shapeExp_e1_ivar = T2.shapeExp_ivar[:, 1]
T2.shapeExp_e2_ivar = T2.shapeExp_ivar[:, 2]
T2.shapeDev_r_ivar = T2.shapeExp_ivar[:, 0]
T2.shapeDev_e1_ivar = T2.shapeExp_ivar[:, 1]
T2.shapeDev_e2_ivar = T2.shapeExp_ivar[:, 2]
T2.writeto(opt.output)
print('Wrote', opt.output)
return 0
TT = T.copy()
for k in ["itx", "ity", "index"]:
TT.delete_column(k)
for col in TT.get_columns():
if not col in ["tx", "ty", "blob"]:
TT.rename(col, "sdss_%s" % col)
TT.brickid = np.zeros(len(TT), np.int32) + brickid
TT.objid = np.arange(len(TT)).astype(np.int32)
invvars = None
hdr = None
fs = None
cat.thawAllRecursive()
T2, hdr = prepare_fits_catalog(cat, invvars, TT, hdr, bands, fs)
# Unpack shape columns
T2.shapeExp_r = T2.shapeExp[:, 0]
T2.shapeExp_e1 = T2.shapeExp[:, 1]
T2.shapeExp_e2 = T2.shapeExp[:, 2]
T2.shapeDev_r = T2.shapeExp[:, 0]
T2.shapeDev_e1 = T2.shapeExp[:, 1]
T2.shapeDev_e2 = T2.shapeExp[:, 2]
T2.shapeExp_r_ivar = T2.shapeExp_ivar[:, 0]
T2.shapeExp_e1_ivar = T2.shapeExp_ivar[:, 1]
T2.shapeExp_e2_ivar = T2.shapeExp_ivar[:, 2]
T2.shapeDev_r_ivar = T2.shapeExp_ivar[:, 0]
T2.shapeDev_e1_ivar = T2.shapeExp_ivar[:, 1]
T2.shapeDev_e2_ivar = T2.shapeExp_ivar[:, 2]
T2.writeto(opt.output)
def stage2(cat=None, variances=None, T=None, bands=None, ps=None,
targetwcs=None, **kwargs):
print 'kwargs:', kwargs.keys()
#print 'variances:', variances
from desi_common import prepare_fits_catalog
TT = T.copy()
hdr = None
fs = None
T2,hdr = prepare_fits_catalog(cat, 1./np.array(variances), TT, hdr, bands, fs)
T2.about()
T2.writeto('cfht.fits')
ccmap = dict(g='g', r='r', i='m')
bandlist = [b for b in bands]
scat,S = get_sdss_sources(bandlist, targetwcs)
S.about()
I,J,d = match_radec(T2.ra, T2.dec, S.ra, S.dec, 1./3600.)
M = fits_table()
M.ra = S.ra[J]
M.dec = S.dec[J]
M.cfhtI = I
for band in bands:
mag = T2.get('decam_%s_mag' % band)[I]
sflux = np.array([s.getBrightness().getBand(band) for s in scat])[J]
smag = NanoMaggies.nanomaggiesToMag(sflux)
M.set('mag_%s' % band, mag)
M.set('smag_%s' % band, smag)
cc = ccmap[band]
plt.clf()
plt.subplot(2,1,1)
plt.plot(smag, mag, '.', color=cc, alpha=0.5)
lo,hi = 16,24
plt.plot([lo,hi],[lo,hi], 'k-')
plt.xlabel('SDSS mag')
plt.ylabel('CFHT mag')
plt.axis([lo,hi,lo,hi])
plt.subplot(2,1,2)
plt.plot(smag, mag - smag, '.', color=cc, alpha=0.5)
lo,hi = 16,24
plt.plot([lo,hi],[0, 0], 'k-')
plt.xlabel('SDSS mag')
plt.ylabel('CFHT - SDSS mag')
plt.axis([lo,hi,-1,1])
plt.suptitle('%s band' % band)
ps.savefig()
M.writeto('cfht-matched.fits')
plt.clf()
lp,lt = [],[]
for band in bands:
sn = T2.get('decam_%s_nanomaggies' % band) * np.sqrt(T2.get('decam_%s_nanomaggies_invvar' % band))
#mag = T2.get('decam_%s_mag_corr' % band)
mag = T2.get('decam_%s_mag' % band)
print 'band', band
print 'Mags:', mag
print 'SN:', sn
cc = ccmap[band]
p = plt.semilogy(mag, sn, '.', color=cc, alpha=0.5)
lp.append(p[0])
lt.append('%s band' % band)
plt.xlabel('mag')
plt.ylabel('Flux Signal-to-Noise')
tt = [1,2,3,4,5,10,20,30,40,50]
plt.yticks(tt, ['%i' % t for t in tt])
plt.axhline(5., color='k')
#plt.axis([21, 26, 1, 20])
plt.legend(lp, lt, loc='upper right')
plt.title('CFHT depth')
ps.savefig()
# ['tims', 'cons', 'pixscale', 'H', 'coimgs', 'detmaps', 'W', 'brick', 'detivs', 'targetrd']
return dict(T2=T2, M=M, tims=None, detmaps=None, detivs=None,
cons=None, coimgs=None)
def main():
"""Main program.
"""
import argparse
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('-b', '--brick', type=int, metavar='BRICK',
help='Brick ID to run: default %(default)s', default=377306)
parser.add_argument('-s', '--sed-matched', action='store_true',
help='Run SED-matched filter?')
parser.add_argument('-B', '--bands', default='grz', help='Bands to retrieve')
parser.add_argument('-o', '--output', metavar='FILE', help='Output filename for catalog',
default='initial-cat.fits')
parser.add_argument('-t', '--threads', type=int, help='Run multi-threaded')
parser.add_argument('-W', '--width', type=int, dest='W', default=3600,
metavar='PIXELS', help='Target image width (default %(default)s)')
parser.add_argument('-H', '--height', type=int, dest='H', default=3600,
metavar='PIXELS', help='Target image height (default %(default)s)')
if not (('BOSS_PHOTOOBJ' in os.environ) and ('PHOTO_RESOLVE' in os.environ)):
print('''$BOSS_PHOTOOBJ and $PHOTO_RESOLVE not set -- on NERSC, you can do:
export BOSS_PHOTOOBJ=/project/projectdirs/cosmo/data/sdss/pre13/eboss/photoObj.v5b
export PHOTO_RESOLVE=/project/projectdirs/cosmo/data/sdss/pre13/eboss/resolve/2013-07-29
To read SDSS files from the local filesystem rather than downloading them.
''')
opt = parser.parse_args()
brickid = opt.brick
bands = opt.bands
if opt.threads and opt.threads > 1:
from astrometry.util.multiproc import multiproc
mp = multiproc(opt.threads)
else:
mp = multiproc()
ps = None
plots = False
decals = Decals()
brick = decals.get_brick(brickid)
print('Chosen brick:')
brick.about()
targetwcs = wcs_for_brick(brick, W=opt.W, H=opt.H)
W,H = targetwcs.get_width(), targetwcs.get_height()
# Read SDSS sources
cat,T = get_sdss_sources(bands, targetwcs)
if opt.sed_matched:
# Read images
tims = decals.tims_touching_wcs(targetwcs, mp, mock_psf=True, bands=bands)
print('Rendering detection maps...')
detmaps, detivs = detection_maps(tims, targetwcs, bands, mp)
SEDs = sed_matched_filters(bands)
Tnew,newcat,nil = run_sed_matched_filters(SEDs, bands, detmaps, detivs,
(T.itx,T.ity), targetwcs)
T = merge_tables([T,Tnew], columns='fillzero')
cat.extend(newcat)
from desi_common import prepare_fits_catalog
TT = T.copy()
for k in ['itx','ity','index']:
TT.delete_column(k)
for col in TT.get_columns():
if not col in ['tx', 'ty', 'blob']:
TT.rename(col, 'sdss_%s' % col)
TT.brickid = np.zeros(len(TT), np.int32) + brickid
TT.objid = np.arange(len(TT)).astype(np.int32)
invvars = None
hdr = None
fs = None
cat.thawAllRecursive()
T2,hdr = prepare_fits_catalog(cat, invvars, TT, hdr, bands, fs)
# Unpack shape columns
T2.shapeExp_r = T2.shapeExp[:,0]
T2.shapeExp_e1 = T2.shapeExp[:,1]
T2.shapeExp_e2 = T2.shapeExp[:,2]
T2.shapeDev_r = T2.shapeExp[:,0]
T2.shapeDev_e1 = T2.shapeExp[:,1]
T2.shapeDev_e2 = T2.shapeExp[:,2]
T2.shapeExp_r_ivar = T2.shapeExp_ivar[:,0]
T2.shapeExp_e1_ivar = T2.shapeExp_ivar[:,1]
T2.shapeExp_e2_ivar = T2.shapeExp_ivar[:,2]
T2.shapeDev_r_ivar = T2.shapeExp_ivar[:,0]
T2.shapeDev_e1_ivar = T2.shapeExp_ivar[:,1]
T2.shapeDev_e2_ivar = T2.shapeExp_ivar[:,2]
T2.writeto(opt.output)
print('Wrote', opt.output)
return 0