def shift_images(imd, img, imi):
"""
This isn't so useful yet because color terms
are probably needed
"""
import sdsspy
import scipy.ndimage
if False:
return img, imi
run=imd['run']
camcol=imd['camcol']
path=sdsspy.filename('photoField', run=run, camcol=camcol)
if not os.path.exists(path):
print 'astrometry not found, no shifts applied'
return img, imi
ast=sdsspy.astrom.Astrom(run=run,camcol=camcol)
idrowg,idrowr,idrowi=imd['drow'][1:1+3]
idcolg,idcolr,idcoli=imd['dcol'][1:1+3]
# use corner of atlas image as reference
rowr,colr= imd['row0'][2], imd['col0'][2]
ra_r,dec_r = ast.pix2eq(imd['field'],'r',rowr, colr)
rowg,colg= ast.eq2pix(imd['field'], 'g', ra_r, dec_r)
rowi,coli= ast.eq2pix(imd['field'], 'i', ra_r, dec_r)
gshift=array([rowg-rowr, colg-colr], dtype='f4')
ishift=array([rowi-rowr, coli-colr], dtype='f4')
gshift[0] -= idrowg
gshift[1] -= idcolg
ishift[0] -= idrowi
ishift[1] -= idcoli
gout = scipy.ndimage.interpolation.shift(img, gshift,
output='f4',
order=1,
mode='constant',
cval=0.0)
iout = scipy.ndimage.interpolation.shift(imi, ishift,
output='f4',
order=1,
mode='constant',
cval=0.0)
return gout,iout
def collate(self):
"""
Keep objects if have nrunmin matches in both model and psf flux, in
*any* one of g,r,i
"""
runs = stripe82_run_list()
#runs=runs[where1(runs == 259)]
pcoldir = self.coldir('primary82')
ecoldir = self.coldir('epochs82')
if os.path.exists(pcoldir):
raise ValueError("primary coldir exists: '%s'\n Start Fresh" % pcoldir)
if os.path.exists(ecoldir):
raise ValueError("epochs coldir exists: '%s'\n Start Fresh" % ecoldir)
pcols = columns.Columns(pcoldir)
pcols.create()
ecols = columns.Columns(ecoldir)
ecols.create()
# count in the epochs columns
epochs_index = 0
for run in runs:
for camcol in [1,2,3,4,5,6]:
fname=sdsspy.filename('photoCombineCamcol', run, camcol)
if os.path.exists(fname):
data=sdsspy.read('photoCombineCamcol', run, camcol,
verbose=True,lower=True)
# first select by number of runs matched, then do flag
# selection and such
print(" selecting r-band nrunmin >",self.nrunmin)
model_nuse = data['cmodel_nuse'][:,2]
psf_nuse = data['psf_nuse'][:,2]
w=where1( (psf_nuse >= self.nrunmin) & (model_nuse >= self.nrunmin) )
print(" kept:",w.size)
if w.size > 0:
data = data[w]
print(" getting sweep matches for flags")
data = self.match_sweeps(data)
print(" found",data.size,"sweep matches")
if data.size > 0:
print(" selecting flags and rflux >",self.rlim)
w = where1( get_select_logic(data, self.rlim) )
print(" kept:",w.size)
if w.size > 0:
data = data[w]
print(" making primary output")
poutput = self.make_primary_output(data)
print(" gathering epochs")
epochs, epochs_indices, epochs_count = \
self.gather_epochs(data, epochs_index)
poutput['epochs_index'] = epochs_indices
poutput['epochs_count'] = epochs_count
nexpected = self.calc_expected_nepoch(data)
if epochs.size != nexpected:
#if nexpected-epochs.size == 1:
#print("FOUND ERROR nexpected greater than epochs by 1. primary bug?")
#else:
# raise ValueError("Expected",nexpected,"epochs, but found",epochs.size)
print("ERROR: Expected",nexpected,"epochs, but found",epochs.size)
print(" found:",epochs.size)
print(" making epochs output")
eoutput = self.make_epochs_output(epochs)
pcols.write_columns(poutput)
ecols.write_columns(eoutput)
# keep track of index in epochs database
epochs_index += epochs.size
