import os
from jwst.datamodels import ModelContainer
from ..stpipe import Step
from . import wfs_combine
__all__ = ["WfsCombineStep"]
[docs]
class WfsCombineStep(Step):
"""
This step combines pairs of dithered PSF images
"""
class_alias = "calwebb_wfs-image3"
spec = """
do_refine = boolean(default=False)
flip_dithers = boolean(default=True) # change the sign and switch order of images when x offset is negative
psf_size = integer(default=100)
blur_size = integer(default=10)
n_size = integer(default=2)
suffix = string(default="wfscmb")
"""
[docs]
def process(self, input_table):
self.suffix = 'wfscmb'
self.output_use_model = True
self.name_format = False
# Load the input ASN table
asn_table = self.load_as_level3_asn(input_table)
self.log.info('Using input table: %s', input_table)
self.log.info('The number of pairs of input files: %g', len(asn_table['products']))
output_container = ModelContainer()
# Process each pair of input images listed in the association table
for which_set in asn_table['products']:
# Get the list of science members in this pair
science_members = [
member
for member in which_set['members']
if member['exptype'].lower() == 'science'
]
infile_1 = science_members[0]['expname']
infile_2 = science_members[1]['expname']
outfile = which_set['name']
# Create the step instance
wfs = wfs_combine.DataSet(
infile_1, infile_2, outfile, self.do_refine, self.flip_dithers, self.psf_size,
self.blur_size, self.n_size
)
# Do the processing
output_model = wfs.do_all()
# The DataSet class does not close its resources. Do that here.
wfs.input_1.close()
wfs.input_2.close()
# Update necessary meta info in the output
output_model.meta.cal_step.wfs_combine = 'COMPLETE'
output_model.meta.asn.pool_name = asn_table['asn_pool']
output_model.meta.asn.table_name = os.path.basename(input_table)
output_model.meta.filename = which_set['name']
output_container.append(output_model)
# Return the output so it can be tested.
return output_container