from stdatamodels.jwst import datamodels
from ..stpipe import Step
from . import rscd_sub
__all__ = ["RscdStep"]
[docs]
class RscdStep(Step):
"""
RscdStep: Performs an RSCD correction to MIRI data.
Baseline version flags the first N groups as 'DO_NOT_USE' in
the 2nd and later integrations in a copy of the input
science data model.
Enhanced version is not ready nor enabled.
"""
class_alias = "rscd"
# allow switching between baseline and enhanced algorithms
spec = """
type = option('baseline','enhanced',default = 'baseline') # Type of correction
"""
# TBD - only do this for the 2nd+ integrations
# do nothing for single integration exposures
reference_file_types = ['rscd']
[docs]
def process(self, input):
# Open the input data model
with datamodels.RampModel(input) as input_model:
# check the data is MIRI data
detector = input_model.meta.instrument.detector
if detector.startswith('MIR'):
# Get the name of the rscd reference file to use
self.rscd_name = self.get_reference_file(input_model, 'rscd')
self.log.info('Using RSCD reference file %s', self.rscd_name)
# Check for a valid reference file
if self.rscd_name == 'N/A':
self.log.warning('No RSCD reference file found')
self.log.warning('RSCD step will be skipped')
input_model.meta.cal_step.rscd = 'SKIPPED'
return input_model
# Load the rscd ref file data model
rscd_model = datamodels.RSCDModel(self.rscd_name)
# Do the rscd correction
result = rscd_sub.do_correction(input_model, rscd_model, self.type)
# Close the reference file
rscd_model.close()
else:
self.log.warning('RSCD correction is only for MIRI data')
self.log.warning('RSCD step will be skipped')
result = input_model.copy()
result.meta.cal_step.rscd = 'SKIPPED'
return result