def process_frame(fn1, fn2, out_dir):
flat_fn = None
obj_fn = None
fn1_header = fits.PrimaryHDU.readfrom(fn1, ignore_missing_end=True).header
fn2_header = fits.PrimaryHDU.readfrom(fn2, ignore_missing_end=True).header
if fn1_header['flat'] == 1 and fn1_header['calmpos'] == 1:
flat_fn = fn1
obj_fn = fn2
obj_header = fn2_header
flat_header = fn1_header
if fn2_header['flat'] == 1 and fn2_header['calmpos'] == 1:
if flat_fn is not None:
raise DrpException('two flats, no object frame')
else:
flat_fn = fn2
obj_fn = fn1
obj_header = fn1_header
flat_header = fn2_header
if flat_fn is None:
raise DrpException('no flat')
if obj_header['ECHLPOS'] > 100:
print('ERROR: cannot reduce low-resolution image (ECHLPOS > 100')
exit(1)
if obj_header['NAXIS1'] != constants.N_COLS:
raise DrpException('NAXIS1 != {}'.format(constants.N_COLS))
if obj_header['NAXIS2'] != constants.N_ROWS:
raise DrpException('NAXIS2 != {}'.format(constants.N_COLS))
if obj_header['FILNAME'].lower().find('nirspec') < 0:
raise DrpException('unsupported filter: {}'.format(obj_header['FILNAME']))
if create_raw_data_sets.flat_criteria_met(obj_header, flat_header, ignore_dispers=True) is False:
raise DrpException('flat is not compatible with object frame')
rawDataSet = RawDataSet.RawDataSet(obj_fn, obj_header)
rawDataSet.flatFileNames.append(flat_fn)
if not os.path.exists(out_dir):
try:
os.mkdir(out_dir)
except:
msg = 'output directory {} does not exist and cannot be created'.format(out_dir)
raise IOError(msg)
logger = logging.getLogger('main')
# generate reduced data set by reducing raw data set
reducedDataSet = reduce_frame.reduce(rawDataSet, out_dir)
# write reduction summary to log file
write_summary(reducedDataSet)
# produce data products from reduced data set
if config.params['no_products'] is True:
logger.info('data product generation inhibited by command line switch')
else:
products.gen(reducedDataSet, out_dir)
# if diagnostics mode is enabled, then produce diagnostic data products
if config.params['dgn'] is True:
logger.info('diagnostic mode enabled, generating diagnostic data products')
dgn.gen(reducedDataSet, out_dir)
return
def process_dir(in_dir, base_out_dir):
"""
NSDRP. Assembles raw data sets from FITS files in the input directory,
then generates reduced data sets from raw data sets. Level 1 data products
are generated from the reduced data sets and saved in the output directory.
"""
# use main logger for outer logging, reduce_frame makes the per frame logger
logger = logging.getLogger('main')
ssFptr = start_summary_ss(in_dir, base_out_dir)
# get list of raw data sets arranged in chronological order
rawDataSets = create_raw_data_sets.create(in_dir)
if rawDataSets is None:
return
# keep track of how many data sets have been successfully reduced
n_reduced = len(rawDataSets)
# instantiate a flat cacher so each flat or set of flats is only reduced once
flatCacher = FlatCacher.FlatCacher(logger, base_out_dir + '/flats')
reducedDataSets = []
nirspecConfig = None
# process each raw data set
for rawDataSet in rawDataSets:
# determine the output directory to use for this frame
out_dir = get_out_dir(rawDataSet.objFileName, base_out_dir);
if nirspecConfig is None:
nirspecConfig = NirspecConfig.NirspecConfig(rawDataSet.objHeader)
else:
if nirspecConfig.isTheSame(rawDataSet.objHeader) == False:
if len(reducedDataSets) > 0:
if len(reducedDataSets) > 1:
mcal(reducedDataSets)
gen_data_products(reducedDataSets, nirspecConfig, base_out_dir, ssFptr)
del reducedDataSets[:]
logger.info('starting new multi-frame set for nirpsec config: {}'.format(
nirspecConfig.toString()))
nirspecConfig = NirspecConfig.NirspecConfig(rawDataSet.objHeader)
try:
reducedDataSets.append(reduce_frame.reduce(rawDataSet, out_dir, flatCacher))
except DrpException as e:
n_reduced -= 1
logger.error('failed to reduce {}: {}'.format(
rawDataSet.objFileName, e.message))
except IOError as e:
logger.critical('DRP failed due to I/O error: {}'.format(str(e)))
sys.exit(1)
if len(reducedDataSets) > 1:
logger.info('doing multi-frame calibration on {} frames, nirspec config: {}'.format(
len(reducedDataSets), nirspecConfig.toString()))
mcal(reducedDataSets)
gen_data_products(reducedDataSets, nirspecConfig, base_out_dir, ssFptr)
if len(rawDataSets) > 0:
logger.info('n object frames reduced = {}/{}'.format(
n_reduced, len(rawDataSets)))
ssFptr.close()
logger.info('end nsdrp')
return