from stdatamodels.jwst import datamodels
from jwst.ami import ami_normalize
from jwst.stpipe import Step
__all__ = ["AmiNormalizeStep"]
[docs]
class AmiNormalizeStep(Step):
"""Normalize target LG results using reference LG results."""
class_alias = "ami_normalize"
spec = """
suffix = string(default='aminorm-oi')
""" # noqa: E501
[docs]
def process(self, target, reference):
"""
Normalize the LG results for science target, using the LG results for reference target.
Parameters
----------
target : str or `~stdatamodels.jwst.datamodels.AmiOIModel`
Target input file name or datamodel.
reference : str or `~stdatamodels.jwst.datamodels.AmiOIModel`
Reference input file name or datamodel.
Returns
-------
result : `~stdatamodels.jwst.datamodels.AmiOIModel`
AMI data model that's been normalized
"""
# Open the target and reference input models
target_model = self.prepare_output(target, open_as_type=datamodels.AmiOIModel)
reference_model = self.prepare_output(reference, open_as_type=datamodels.AmiOIModel)
# Call the normalization routine
result = ami_normalize.normalize_lg(target_model, reference_model)
result.meta.cal_step.ami_normalize = "COMPLETE"
# Close the input models
if target_model is not target:
target_model.close()
if reference_model is not reference:
reference_model.close()
# We're done
return result