def processdata(instrume, obsdate, propcode, median, function, order, rej_lo, rej_hi, niter, interp, logfile, verbose):
"""Clean and process the data"""
#set up instrument specific naming
if instrume=='rss':
instrume_name='RSS'
prefix='P'
elif instrume=='scam':
instrume_name='SALTICAM'
prefix='S'
rawpath = instrume+'/raw'
prodpath = instrume+'/product'
img_list=[]
for img in glob.glob('%s/raw/%s*fits' % (instrume, prefix)):
struct=pyfits.open(img)
if struct[0].header['PROPID'].upper().strip() != 'JUNK':
img_list.append(img)
img_str=','.join(img_list)
obslog = '%s/%s%sOBSLOG.fits' % (prodpath, prefix, obsdate)
gaindb = iraf.osfn('pysalt$data/%s/%samps.dat' % (instrume, instrume_name))
#gaindb = ''
xtalkfile = iraf.osfn('pysalt$data/%s/%sxtalk.dat' % (instrume, instrume_name))
geomfile = iraf.osfn('pysalt$data/%s/%sgeom.dat' % (instrume, instrume_name))
if len(img_list)>0:
saltclean(images=img_str,outpath=prodpath,obslogfile=obslog,gaindb=gaindb,
xtalkfile=xtalkfile,geomfile=geomfile,subover=True,trim=True,
median=median,function=function,order=order,rej_lo=rej_lo,
rej_hi=rej_hi,niter=niter,masbias=True,subbias=False,interp=interp,
clobber=True,logfile=logfile,verbose=verbose)
rawsize = 0.
rawnum = 0
prodsize = 0.
prodnum = 0
if len(img_list)>0:
files = glob.glob('%s/raw/%s*.fits' % (instrume, prefix))
rawnum = len(files)
for file in files:
rawsize += os.stat(file).st_size
files = glob.glob('%s/product/*%s*.fits' % (instrume, prefix))
prodnum = len(files)
for file in files:
prodsize += os.stat(file).st_size
# collate RSS data for individual PIs
outpath = '.'
if len(img_list):
saltobsid(propcode=propcode,obslog=obslog,rawpath=rawpath,prodpath=prodpath, outpath=outpath,clobber=True,logfile=logfile,verbose=verbose)
return rawsize, rawnum, prodsize, prodnum
def hrsprocess(instrume, obsdate,propcode, median, function, order, rej_lo, rej_hi, niter, interp, logfile, verbose):
"""Clean and process HRS data"""
from saltobslog import saltobslog
prefix = 'H'
rawpath = instrume+'/raw'
prodpath = instrume+'/product'
img_list=[]
for img in glob.glob('%s/raw/%s*fits' % (instrume, 'H')):
struct=pyfits.open(img)
if struct[0].header['PROPID'].upper().strip() != 'JUNK':
img_list.append(img)
for img in glob.glob('%s/raw/%s*fits' % (instrume, 'R')):
struct=pyfits.open(img)
if struct[0].header['PROPID'].upper().strip() != 'JUNK':
img_list.append(img)
print 'HRS IMAGE LIST ', len(img_list)
if len(img_list)>0:
img_str=','.join(img_list)
obslog = '%s/%s%sOBSLOG.fits' % (prodpath, prefix, obsdate)
hrsclean(images=img_str,outpath=prodpath,obslogfile=obslog,
subover=True,trim=True, median=median,function=function,order=order,rej_lo=rej_lo,
rej_hi=rej_hi,niter=niter,masbias=True,subbias=False,interp=interp,
clobber=True,logfile=logfile,verbose=verbose)
rawsize = 0.
rawnum = 0
prodsize = 0.
prodnum = 0
if len(img_list)>0:
files = glob.glob('%s/raw/%s*.fits' % (instrume, prefix))
rawnum = len(files)
for infile in files:
rawsize += os.stat(infile).st_size
files = glob.glob('%s/product/*%s*.fits' % (instrume, prefix))
prodnum = len(files)
for infile in files:
prodsize += os.stat(infile).st_size
# collate HRS data for individual PIs
outpath = '.'
if len(img_list)>0:
saltobsid(propcode=propcode,obslog=obslog,rawpath=rawpath,prodpath=prodpath, outpath=outpath, prefix='mbgph', fprefix='bgph',clobber=True,logfile=logfile,verbose=verbose)
return rawsize, rawnum, prodsize, prodnum
