def clean(struct, createvar=False, badpixelstruct=None, mult=True, dblist=None, ampccd=2,
xdict=[], subover=True,trim=True, subbias=False, bstruct=None,
median=False, function='polynomial',order=3,rej_lo=3,rej_hi=3,niter=10,
plotover=False, log=None, verbose=True):
infile=struct
#prepare the files
struct=prepare(struct, createvar=createvar, badpixelstruct=badpixelstruct)
#reset the names in the structures
for i in range(1,len(struct)):
struct[i].name=struct[i].header['EXTNAME']
#gain correct the files
usedb=False
if dblist: usedb=True
struct=gain(struct, mult=mult,usedb=usedb, dblist=dblist, ampccd=ampccd, log=log, verbose=verbose)
#xtalk correct the files
usedb=False
if xdict:
obsdate=saltkey.get('DATE-OBS', struct[0])
try:
obsdate=int('%s%s%s' % (obsdate[0:4],obsdate[5:7], obsdate[8:]))
xkey=np.array(xdict.keys())
date=xkey[abs(xkey-obsdate).argmin()]
xcoeff=xdict[date]
except Exception,e :
msg='WARNING--Can not find xtalk coefficient for %s because %s' % (e, infile)
if log: log.warning(msg)
xcoeff=xdict[xdict.keys()[-1]]
def clean(struct, createvar=False, badpixelstruct=None, mult=True, \
subover=True, trim=True, subbias=False, bstruct=None, imstack=False,
median=False, \
function='polynomial', order=5, rej_lo=3, rej_hi=3, niter=5, \
log=None, verbose=True):
"""Clean HRS data and files. This includes the following steps currently:
* overscan correction
* bias subtraction
* gain correction
* mosaic correction
"""
infile = struct
tfile = struct[0]._file
#prepare the HRS files
struct = hrsprepare(struct)
struct[0]._file = tfile
ampccd = len(struct) - 1
#prepare the files
struct = prepare(struct,
createvar=createvar,
badpixelstruct=badpixelstruct,
namps=ampccd)
#gain correct the files
usedb = False
struct = gain(struct,
mult=mult,
usedb=usedb,
dblist=None,
ampccd=ampccd,
log=log,
verbose=verbose)
#overscan and bias correction
struct = bias(struct,
subover=subover,
trim=trim,
subbias=subbias,
bstruct=bstruct,
median=median,
function=function,
order=order,
rej_lo=rej_lo,
rej_hi=rej_hi,
niter=niter,
plotover=False,
log=log,
verbose=verbose)
#stack the data if requested
if imstack and ampccd > 1:
struct = stack(struct)
#struct=salt2iraf(struct)
return struct
def clean(struct,
createvar=False,
badpixelstruct=None,
mult=True,
dblist=None,
ampccd=2,
xdict=[],
subover=True,
trim=True,
subbias=False,
bstruct=None,
median=False,
function='polynomial',
order=3,
rej_lo=3,
rej_hi=3,
niter=10,
plotover=False,
log=None,
verbose=True):
infile = struct
#prepare the files
struct = prepare(struct,
createvar=createvar,
badpixelstruct=badpixelstruct)
#reset the names in the structures
for i in range(1, len(struct)):
struct[i].name = struct[i].header['EXTNAME']
#gain correct the files
usedb = False
if dblist: usedb = True
struct = gain(struct,
mult=mult,
usedb=usedb,
dblist=dblist,
ampccd=ampccd,
log=log,
verbose=verbose)
#xtalk correct the files
usedb = False
if xdict:
obsdate = saltkey.get('DATE-OBS', struct[0])
try:
obsdate = int('%s%s%s' % (obsdate[0:4], obsdate[5:7], obsdate[8:]))
xkey = np.array(xdict.keys())
date = xkey[abs(xkey - obsdate).argmin()]
xcoeff = xdict[date]
except Exception, e:
msg = 'WARNING--Can not find xtalk coefficient for %s because %s' % (
e, infile)
if log: log.warning(msg)
xcoeff = xdict[xdict.keys()[-1]]
def clean(struct, createvar=False, badpixelstruct=None, mult=True, dblist=None, ampccd=2,
xdict=[], subover=True,trim=True, subbias=False, bstruct=None,
median=False, function='polynomial',order=3,rej_lo=3,rej_hi=3,niter=10,
crtype=None,thresh=5,mbox=3, bbox=11, \
bthresh=3, flux_ratio=0.2, gain=1, rdnoise=5, bfactor=2, fthresh=5,\
gbox=3, maxiter=5, \
plotover=False, log=None, verbose=True):
infile=struct
#prepare the files
struct=prepare(struct, createvar=False, badpixelstruct=None)
#bias correct the file
struct=bias(struct,subover=subover, trim=trim, subbias=subbias,
bstruct=bstruct, median=median, function=function,
order=order, rej_lo=rej_lo, rej_hi=rej_hi, niter=niter,
plotover=plotover, log=log, verbose=verbose)
#reset the names in the structures
for i in range(1,len(struct)):
struct[i].name=struct[i].header['EXTNAME']
#add the variance and bad pixel frame
nextend=len(struct)-1
nsciext=nextend
if createvar:
#create the inv. variance frames
for i in range(1, nsciext+1):
hdu=CreateVariance(struct[i], i, nextend+i)
try:
pass
except Exception, e:
msg='Cannot create variance frame in extension %i of %s because %s' % (nextend+i, infile, e)
raise SaltError(msg)
struct[i].header['VAREXT'] = (nextend+i, 'Extension for Variance Frame')
struct.append(hdu)
nextend+=nsciext
#create the badpixelframes
for i in range(1, nsciext+1):
try:
hdu=createbadpixel(struct, badpixelstruct, i, nextend+i)
except Exception, e:
msg='Could not create bad pixel extension in ext %i of %s because %s' % (nextend+i, infile, e)
raise SaltError(msg)
struct[i].header['BPMEXT'] = (nextend+i, 'Extension for Bad Pixel Mask')
struct.append(hdu)
def clean(struct, createvar=False, badpixelstruct=None, mult=True, \
subover=True, trim=True, subbias=False, bstruct=None, imstack=False,
median=False, \
function='polynomial', order=5, rej_lo=3, rej_hi=3, niter=5, \
log=None, verbose=True):
"""Clean HRS data and files. This includes the following steps currently:
* overscan correction
* bias subtraction
* gain correction
* mosaic correction
"""
infile=struct
tfile=struct[0]._file
#prepare the HRS files
struct=hrsprepare(struct)
struct[0]._file=tfile
ampccd=len(struct)-1
#prepare the files
struct=prepare(struct, createvar=createvar, badpixelstruct=badpixelstruct, namps=ampccd)
#gain correct the files
usedb=False
struct=gain(struct, mult=mult,usedb=usedb, dblist=None, ampccd=ampccd, log=log, verbose=verbose)
#overscan and bias correction
struct=bias(struct,subover=subover, trim=trim, subbias=subbias,
bstruct=bstruct, median=median, function=function,
order=order, rej_lo=rej_lo, rej_hi=rej_hi, niter=niter,
plotover=False, log=log, verbose=verbose)
#stack the data if requested
if imstack and ampccd>1:
struct=stack(struct)
#struct=salt2iraf(struct)
return struct
def quickclean(filename, interp='linear', cleanup=True, clobber=False, logfile='saltclean.log', verbose=True):
"""Start the process to reduce the data and produce a single mosaicked image"""
print filename
#create the input file name
status=0
infile=os.path.basename(filename)
rawpath=os.path.dirname(filename)
outpath='./'
outfile=outpath+'mbxp'+infile
print infile, rawpath, outpath
#check to see if it exists and return if clobber is no
if os.path.isfile(outfile) and not clobber: return
#set up the files needed
if infile[0]=='P':
gaindb = iraf.osfn('pysalt$data/rss/RSSamps.dat')
xtalkfile = iraf.osfn('pysalt$data/rss/RSSxtalk.dat')
geomfile = iraf.osfn('pysalt$data/rss/RSSgeom.dat')
elif infile[0]=='S':
gaindb = iraf.osfn('pysalt$data/scam/SALTICAMamps.dat')
xtalkfile = iraf.osfn('pysalt$data/scam/SALTICAMxtalk.dat')
geomfile = iraf.osfn('pysalt$data/scam/SALTICAMgeom.dat')
#verify the file
struct=saltio.openfits(rawpath+'/'+infile)
struct.verify('exception')
#check to see if detmode is there
if not saltkey.found('DETMODE', struct[0]):
return
#reduce the file
struct=prepare(struct, createvar=False, badpixelstruct=None)
#reset the names in the structures
for i in range(1,len(struct)):
struct[i].name=struct[i].header['EXTNAME']
#gain correct the files
usedb=True
dblist= saltio.readgaindb(gaindb)
log=open(logfile, 'a')
ampccd = struct[0].header['NAMPS'] / struct[0].header['NCCDS']
struct=gain(struct, mult=True,usedb=usedb, dblist=dblist, ampccd=ampccd, log=None, verbose=verbose)
struct=bias(struct, subover=True,trim=True,subbias=False,
median=False,function='polynomial',order=5,rej_lo=3,rej_hi=3,niter=10,
plotover=False,log=None, verbose=verbose)
if struct[0].header['CCDTYPE']=='OBJECT' and struct[0].header['EXPTIME']>90:
struct = multicrclean(struct, crtype='median', thresh=5, mbox=5, bbox=25, bthresh=5, flux_ratio=0.2, \
gain=1, rdnoise=5, bfactor=2, fthresh=5, gbox=0, maxiter=5, log=None, verbose=verbose)
pinfile=outpath+'bxp'+infile
saltio.writefits(struct, pinfile, clobber)
saltred.saltmosaic(images=pinfile,
outimages='',outpref=outpath+'m',geomfile=geomfile, fill=True,
interp=interp,cleanup=cleanup,clobber=clobber,logfile=logfile,
verbose=verbose)
profile=outpath+'mbxp'+infile
#remove intermediate steps
if cleanup:
if os.path.isfile(pinfile): os.remove(pinfile)
return
def quickclean(filename,
interp='linear',
cleanup=True,
clobber=False,
logfile='saltclean.log',
verbose=True):
"""Start the process to reduce the data and produce a single mosaicked image"""
print filename
#create the input file name
status = 0
infile = os.path.basename(filename)
rawpath = os.path.dirname(filename)
outpath = './'
outfile = outpath + 'mbxp' + infile
print infile, rawpath, outpath
#check to see if it exists and return if clobber is no
if os.path.isfile(outfile) and not clobber: return
#set up the files needed
if infile[0] == 'P':
gaindb = iraf.osfn('pysalt$data/rss/RSSamps.dat')
xtalkfile = iraf.osfn('pysalt$data/rss/RSSxtalk.dat')
geomfile = iraf.osfn('pysalt$data/rss/RSSgeom.dat')
elif infile[0] == 'S':
gaindb = iraf.osfn('pysalt$data/scam/SALTICAMamps.dat')
xtalkfile = iraf.osfn('pysalt$data/scam/SALTICAMxtalk.dat')
geomfile = iraf.osfn('pysalt$data/scam/SALTICAMgeom.dat')
#verify the file
struct = saltio.openfits(rawpath + '/' + infile)
struct.verify('exception')
#check to see if detmode is there
if not saltkey.found('DETMODE', struct[0]):
return
#reduce the file
struct = prepare(struct, createvar=False, badpixelstruct=None)
#reset the names in the structures
for i in range(1, len(struct)):
struct[i].name = struct[i].header['EXTNAME']
#gain correct the files
usedb = True
dblist = saltio.readgaindb(gaindb)
log = open(logfile, 'a')
ampccd = struct[0].header['NAMPS'] / struct[0].header['NCCDS']
struct = gain(struct,
mult=True,
usedb=usedb,
dblist=dblist,
ampccd=ampccd,
log=None,
verbose=verbose)
struct = bias(struct,
subover=True,
trim=True,
subbias=False,
median=False,
function='polynomial',
order=5,
rej_lo=3,
rej_hi=3,
niter=10,
plotover=False,
log=None,
verbose=verbose)
if struct[0].header[
'CCDTYPE'] == 'OBJECT' and struct[0].header['EXPTIME'] > 90:
struct = multicrclean(struct, crtype='median', thresh=5, mbox=5, bbox=25, bthresh=5, flux_ratio=0.2, \
gain=1, rdnoise=5, bfactor=2, fthresh=5, gbox=0, maxiter=5, log=None, verbose=verbose)
pinfile = outpath + 'bxp' + infile
saltio.writefits(struct, pinfile, clobber)
saltred.saltmosaic(images=pinfile,
outimages='',
outpref=outpath + 'm',
geomfile=geomfile,
fill=True,
interp=interp,
cleanup=cleanup,
clobber=clobber,
logfile=logfile,
verbose=verbose)
profile = outpath + 'mbxp' + infile
#remove intermediate steps
if cleanup:
if os.path.isfile(pinfile): os.remove(pinfile)
return
