def test_fuv_timetag_1(self):
"""
FUV COS regression test #1
"""
asn_file = 'lckg01070_asn.fits'
# Prepare input files.
self.get_input_file(asn_file)
# Run CALCOS
calcos.calcos(asn_file)
# Compare results.
# The first outroot is the output from whole ASN,
# the rest are individual members.
outroots = [
'lckg01070', 'lckg01czq', 'lckg01d4q', 'lckg01d9q', 'lckg01dcq'
]
outputs = []
for sfx in ('x1dsum', 'x1dsum1', 'x1dsum2', 'x1dsum3', 'x1dsum4'):
fname = '{}_{}.fits'.format(outroots[0], sfx)
outputs.append((fname, fname))
for outroot in outroots[1:]:
for sfx in ('corrtag_a', 'corrtag_b', 'counts_a', 'counts_b',
'flt_a', 'flt_b', 'lampflash', 'x1d'):
fname = '{}_{}.fits'.format(outroot, sfx)
outputs.append((fname, fname))
self.compare_outputs(outputs, rtol=3e-7)
def test_fuv_timetag_1(self):
"""
FUV COS regression test #1
"""
asn_file = 'lckg01070_asn.fits'
# Prepare input files.
self.get_input_file(asn_file)
# Run CALCOS
calcos.calcos(asn_file)
# Compare results.
# The first outroot is the output from whole ASN,
# the rest are individual members.
outroots = ['lckg01070', 'lckg01czq', 'lckg01d4q', 'lckg01d9q',
'lckg01dcq']
outputs = []
for sfx in ('x1dsum', 'x1dsum1', 'x1dsum2', 'x1dsum3', 'x1dsum4'):
fname = '{}_{}.fits'.format(outroots[0], sfx)
outputs.append((fname, fname))
for outroot in outroots[1:]:
for sfx in ('corrtag_a', 'corrtag_b', 'counts_a', 'counts_b',
'flt_a', 'flt_b', 'lampflash', 'x1d'):
fname = '{}_{}.fits'.format(outroot, sfx)
outputs.append((fname, fname))
self.compare_outputs(outputs, rtol=3e-7)
def test_fuva_dark(self):
"""
FUV COS regression test #2
"""
files_to_download = [
'la7803fiq_rawtag_a.fits', 'la7803fiq_rawtag_b.fits',
'la7803fiq_spt.fits'
]
# Prepare input files.
self.get_input_files(files_to_download)
input_file = 'la7803fiq_rawtag_a.fits'
# Run CALCOS
calcos.calcos(input_file)
# Compare results.
# The first outroot is the output from whole ASN,
# the rest are individual members.
outroots = ['la7803fiq']
outputs = []
for outroot in outroots:
for sfx in ('corrtag_a', 'corrtag_b', 'counts_a', 'counts_b',
'flt_a', 'flt_b'):
fname = '{}_{}.fits'.format(outroot, sfx)
outputs.append((fname, fname))
self.compare_outputs(outputs, rtol=3e-7)
def calcos_iraf(input,
verbosity=1,
savetmp=no,
outdir="",
find_target=no,
cutoff=-1.,
shift_file="",
csum=no,
raw_csum=no,
compress=no,
comp_param="gzip,-0.01",
binx=1,
biny=1,
stimfile="",
livefile="",
burstfile="",
version=None):
# Interpret input parameters
find_target = _toBoolean(find_target)
csum = _toBoolean(csum)
raw_csum = _toBoolean(raw_csum)
savetmp = _toBoolean(savetmp)
compress = _toBoolean(compress)
if outdir.strip() == "":
outdir = None
if outdir is not None:
outdir = iraf.osfn(outdir)
if cutoff <= 0.:
cutoff = None
if shift_file.strip() == "": shift_file = None
if stimfile.strip() == "": stimfile = None
if livefile.strip() == "": livefile = None
if burstfile.strip() == "": burstfile = None
calcos.calcos(input,
outdir=outdir,
verbosity=verbosity,
find_target={
"flag": find_target,
"cutoff": cutoff
},
create_csum_image=csum,
raw_csum_coords=raw_csum,
binx=binx,
biny=biny,
compress_csum=compress,
compression_parameters=comp_param,
shift_file=shift_file,
save_temp_files=savetmp,
stimfile=stimfile,
livetimefile=livefile,
burstfile=burstfile)
def reduce(self, output_directory):
"""
Runs the CalCOS pipeline.
Parameters
----------
output_directory : str
Path for the reduced data products.
"""
try:
import calcos
except:
raise ImportError('CalCOS not installed')
print('\nWill run CalCOS on the following raw data products:\n')
self.info.pprint(max_lines=50)
run = raw_input('\nContinue? (y)/n ')
if run != 'n':
for asn in self.asn:
calcos.calcos(asn, verbosity=2, outdir=output_directory)
def test_gsag_calibration(gsagtab):
"""Move gsagtab into TEST_DIR and calibrate with CalCOS.
Any datasets that fail calibration will be emailed to the user.
"""
print '#-------------------------#'
print 'Calibrating with %s'%(gsagtab)
print '#-------------------------#'
os.environ['lref'] = '/grp/hst/cdbs/lref/'
os.environ['testdir'] = TEST_DIR
if not os.path.exists(TEST_DIR):
os.mkdir(TEST_DIR)
shutil.copy( gsagtab ,os.path.join(TEST_DIR,'new_gsag.fits') )
test_datasets = glob.glob( os.path.join(TEST_DIR, '*rawtag_a.fits') )
#Remove products
for ext in ('*_counts*.fits','*_flt*.fits','*_x1d*.fits','*lampflash*.fits','*corrtag*.fits'):
os.system('rm '+TEST_DIR+'/'+ext)
for item in test_datasets:
pyfits.setval( item,'RANDSEED',value=8675309,ext=0 )
pyfits.setval( item,'GSAGTAB',value='testdir$new_gsag.fits',ext=0 )
failed_runs = []
for item in test_datasets:
try:
status = calcos.calcos( item,outdir=TEST_DIR )
print "CalCOS exit status is",status
except:
failed_runs.append( item )
if status != 0:
failed_runs.append( item )
if len(failed_runs):
send_email(subject='GSAGTAB Calibration Error',message='Failed calibration\n\n'+'\n'+'\n'.join(failed_runs) )
for omit in omitlist:
phdr.update(omit, 'OMIT')
for per in performlist:
phdr.update(per, 'PERFORM')
for key in reffiles:
phdr.update(key, reffiles[key])
for key in statflag:
phdr.update(key, statflag[key])
fd.close()
print 'Keywords of file %s have been modified...' % file
#calibration
filelist = [file[:-14] for file in filelist if 'rawtag_a.fits' in file]
for file in filelist:
C.calcos(file)
#collapsing
#for file in filelist:
#which file should be process?
# data = PF.open(file[] + '_corr_a/b.fits')[1].data
#find centre, collapse dispersion direction and find max
#define area, + / - width
#collapse in cross-dispersion direction
#save a new file
for omit in omitlist:
phdr.update(omit, 'OMIT')
for per in performlist:
phdr.update(per, 'PERFORM')
for key in reffiles:
phdr.update(key, reffiles[key])
for key in statflag:
phdr.update(key, statflag[key])
fd.close()
print 'Keywords of file %s have been modified...' % file
#calibration
filelist = [file[:-14] for file in filelist if 'rawtag_a.fits' in file]
for file in filelist:
C.calcos(file)
#collapsing
#for file in filelist:
#which file should be process?
# data = PF.open(file[] + '_corr_a/b.fits')[1].data
#find centre, collapse dispersion direction and find max
#define area, + / - width
#collapse in cross-dispersion direction
#save a new file
print 'Script ends...'
os.chdir(out_dir)
if not os.path.exists('out/'):
os.mkdir('out/')
for item in glob.glob('*asn.fits'):
shutil.copy( item, 'out/' )
cal_list = glob.glob('*corrtag_a*')
for corrtag in cal_list:
try:
calcos.calcos(corrtag, 'out/')
except:
print 'Exception occured'
pass
os.chdir( 'out/' )
for item in glob.glob( '*x1d.fits' ):
fits = pyfits.open( item )
for i in range(len( fits[1].data ) ):
if not fits[1].data[i]['FLUX'].any():
fits[1].data[i]['DQ_WGT'] = 0
fits.writeto( item, clobber=True )
for item in glob.glob( '*asn.fits' ):
remake_asn( item )
else:
shutil.copy(file_name, os.path.join(out_dir, file_name))
os.chdir(out_dir)
if not os.path.exists('out/'):
os.mkdir('out/')
for item in glob.glob('*asn.fits'):
shutil.copy(item, 'out/')
cal_list = glob.glob('*corrtag_a*')
for corrtag in cal_list:
try:
calcos.calcos(corrtag, 'out/')
except:
print 'Exception occured'
pass
os.chdir('out/')
for item in glob.glob('*x1d.fits'):
fits = pyfits.open(item)
for i in range(len(fits[1].data)):
if not fits[1].data[i]['FLUX'].any():
fits[1].data[i]['DQ_WGT'] = 0
fits.writeto(item, clobber=True)
for item in glob.glob('*asn.fits'):
remake_asn(item)
def calibrate_files(outputfolder, item): calcos.calcos(item ,outdir=outputfolder)
