def create_drizzle_products(total_obj_list, custom_limits=None):
"""
Run astrodrizzle to produce products specified in the total_obj_list.
Parameters
----------
total_obj_list: list
List of TotalProduct objects, one object per instrument/detector combination is
a visit. The TotalProduct objects are comprised of FilterProduct and ExposureProduct
objects.
custom_limits : list, optional
4-element list containing the mosaic bounding rectangle X min and max and Y min and max values for
custom mosaics
RETURNS
-------
product_list: list
A list of output products
"""
# Get rules files
rules_files = {}
log.info("Processing with astrodrizzle version {}".format(
drizzlepac.astrodrizzle.__version__))
# Generate list of all input exposure filenames that are to be processed
edp_names = []
for t in total_obj_list:
edp_names += [e.full_filename for e in t.edp_list]
# Define dataset-specific rules filenames for each input exposure
for imgname in edp_names:
rules_files[imgname] = proc_utils.get_rules_file(imgname,
rules_type='MVM')
log.debug(f'Generated LAYER RULES_FILE name of: \n\t{rules_files}\n')
# Keep track of all the products created for the output manifest
product_list = []
# For each detector (as the total detection product are instrument- and detector-specific),
# create the drizzle-combined filtered image, the drizzled exposure (aka single) images,
# and finally the drizzle-combined total detection image.
for filt_obj in total_obj_list:
if not filt_obj.valid_product:
# If this object has 'valid_product' set to False,
# skip processing this object
continue
filt_obj.rules_file = proc_utils.get_rules_file(
filt_obj.edp_list[0].full_filename,
rules_type='MVM',
rules_root=filt_obj.drizzle_filename)
log.debug(
f'Generated LAYER RULES_FILE name of: \n\t{filt_obj.rules_file}\n')
# add filter rules files to dict of all rules files for deletion later
rules_files[filt_obj.drizzle_filename] = filt_obj.rules_file
log.info("~" * 118)
# Get the common WCS for all images which are part of a total detection product,
# where the total detection product is detector-dependent.
meta_wcs = filt_obj.generate_metawcs(custom_limits=custom_limits)
log.info("CREATE DRIZZLE-COMBINED FILTER IMAGE: {}\n".format(
filt_obj.drizzle_filename))
filt_obj.wcs_drizzle_product(meta_wcs)
product_list.append(filt_obj.drizzle_filename)
product_list.append(filt_obj.trl_filename)
# Add individual single input images with updated WCS headers to manifest
for exposure_obj in filt_obj.edp_list:
product_list.append(exposure_obj.full_filename)
# Ensure that all drizzled products have headers that are to specification
try:
log.info("Updating these drizzle products for CAOM compatibility:")
fits_files = fnmatch.filter(product_list, "*dr?.fits")
for filename in fits_files:
log.info(" {}".format(filename))
proc_utils.refine_product_headers(filename, total_obj_list)
except Exception:
log.critical("Trouble updating drizzle products for CAOM.")
exc_type, exc_value, exc_tb = sys.exc_info()
traceback.print_exception(exc_type, exc_value, exc_tb, file=sys.stdout)
logging.exception("message")
# Remove rules files copied to the current working directory
for rules_filename in list(rules_files.values()):
log.info("Removed rules file {}".format(rules_filename))
os.remove(rules_filename)
# Add primary header information to all objects
for filt_obj in total_obj_list:
if filt_obj.valid_product:
filt_obj = poller_utils.add_primary_fits_header_as_attr(filt_obj)
# Return product list for creation of pipeline manifest file
return product_list
def create_drizzle_products(total_obj_list):
"""
Run astrodrizzle to produce products specified in the total_obj_list.
Parameters
----------
total_obj_list: list
List of TotalProduct objects, one object per instrument/detector combination is
a visit. The TotalProduct objects are comprised of FilterProduct and ExposureProduct
objects.
RETURNS
-------
product_list: list
A list of output products
"""
log.info("Processing with astrodrizzle version {}".format(drizzlepac.astrodrizzle.__version__))
# Get rules files
rules_files = {}
# Generate list of all input exposure filenames that are to be processed
edp_names = []
for t in total_obj_list:
edp_names += [e.full_filename for e in t.edp_list]
# Define dataset-specific rules filenames for each input exposure
for imgname in edp_names:
rules_files[imgname] = proc_utils.get_rules_file(imgname)
print('Generated RULES_FILE names of: \n{}\n'.format(rules_files))
# Keep track of all the products created for the output manifest
product_list = []
# For each detector (as the total detection product are instrument- and detector-specific),
# create the drizzle-combined filtered image, the drizzled exposure (aka single) images,
# and finally the drizzle-combined total detection image.
for total_obj in total_obj_list:
log.info("~" * 118)
# Get the common WCS for all images which are part of a total detection product,
# where the total detection product is detector-dependent.
meta_wcs = total_obj.generate_metawcs()
# Create drizzle-combined filter image as well as the single exposure drizzled image
for filt_obj in total_obj.fdp_list:
log.info("~" * 118)
filt_obj.rules_file = rules_files[filt_obj.edp_list[0].full_filename]
log.info("CREATE DRIZZLE-COMBINED FILTER IMAGE: {}\n".format(filt_obj.drizzle_filename))
filt_obj.wcs_drizzle_product(meta_wcs)
product_list.append(filt_obj.drizzle_filename)
product_list.append(filt_obj.trl_filename)
# Create individual single drizzled images
for exposure_obj in filt_obj.edp_list:
log.info("~" * 118)
exposure_obj.rules_file = rules_files[exposure_obj.full_filename]
log.info("CREATE SINGLE DRIZZLED IMAGE: {}".format(exposure_obj.drizzle_filename))
exposure_obj.wcs_drizzle_product(meta_wcs)
product_list.append(exposure_obj.drizzle_filename)
product_list.append(exposure_obj.full_filename)
# product_list.append(exposure_obj.headerlet_filename)
product_list.append(exposure_obj.trl_filename)
# Create drizzle-combined total detection image after the drizzle-combined filter image and
# drizzled exposure images in order to take advantage of the cosmic ray flagging.
log.info("CREATE DRIZZLE-COMBINED TOTAL IMAGE: {}\n".format(total_obj.drizzle_filename))
total_obj.rules_file = total_obj.fdp_list[0].rules_file
total_obj.wcs_drizzle_product(meta_wcs)
product_list.append(total_obj.drizzle_filename)
product_list.append(total_obj.trl_filename)
# Ensure that all drizzled products have headers that are to specification
try:
log.info("Updating these drizzle products for CAOM compatibility:")
fits_files = fnmatch.filter(product_list, "*dr?.fits")
for filename in fits_files:
log.info(" {}".format(filename))
proc_utils.refine_product_headers(filename, total_obj_list)
except Exception:
log.critical("Trouble updating drizzle products for CAOM.")
exc_type, exc_value, exc_tb = sys.exc_info()
traceback.print_exception(exc_type, exc_value, exc_tb, file=sys.stdout)
logging.exception("message")
# Remove rules files copied to the current working directory
for rules_filename in list(rules_files.values()):
log.info("Removed rules file {}".format(rules_filename))
os.remove(rules_filename)
# Add primary header information to all objects
for total_obj in total_obj_list:
total_obj = poller_utils.add_primary_fits_header_as_attr(total_obj)
for filt_obj in total_obj.fdp_list:
filt_obj = poller_utils.add_primary_fits_header_as_attr(filt_obj)
for exposure_obj in filt_obj.edp_list:
exposure_obj = poller_utils.add_primary_fits_header_as_attr(exposure_obj)
# Return product list for creation of pipeline manifest file
return product_list