from ..stpipe import Step
from .. import datamodels
from . import dark_sub
__all__ = ["DarkCurrentStep"]
[docs]class DarkCurrentStep(Step):
"""
DarkCurrentStep: Performs dark current correction by subtracting
dark current reference data from the input science data model.
"""
spec = """
dark_output = output_file(default = None) # Dark model or averaged dark subtracted
"""
reference_file_types = ['dark']
[docs] def process(self, input):
# Open the input data model
with datamodels.RampModel(input) as input_model:
# Get the name of the dark reference file to use
self.dark_name = self.get_reference_file(input_model, 'dark')
self.log.info('Using DARK reference file %s', self.dark_name)
# Check for a valid reference file
if self.dark_name == 'N/A':
self.log.warning('No DARK reference file found')
self.log.warning('Dark current step will be skipped')
result = input_model.copy()
result.meta.cal_step.dark = 'SKIPPED'
return result
# Create name for the intermediate dark, if desired.
dark_output = self.dark_output
if dark_output is not None:
dark_output = self.make_output_path(
None, basepath=dark_output, ignore_use_model=True
)
# Open the dark ref file data model - based on Instrument
instrument = input_model.meta.instrument.name
if(instrument == 'MIRI'):
dark_model = datamodels.DarkMIRIModel(self.dark_name)
else:
dark_model = datamodels.DarkModel(self.dark_name)
# Do the dark correction
result = dark_sub.do_correction(
input_model, dark_model, dark_output
)
dark_model.close()
return result