#! /usr/bin/env python
from stdatamodels.jwst import datamodels
from ..stpipe import Step
from . import klip
__all__ = ["KlipStep"]
[docs]
class KlipStep(Step):
"""
KlipStep: Performs KLIP processing on a science target coronagraphic
exposure. The input science exposure is assumed to be a fully calibrated
level-2b image. The processing is performed using a set of reference PSF
images observed in the same coronagraphic mode.
"""
class_alias = "klip"
spec = """
truncate = integer(default=50,min=0) # The number of KL transform rows to keep
"""
[docs]
def process(self, target, psfrefs):
with datamodels.open(target) as target_model:
# Retrieve the parameter values
truncate = self.truncate
self.log.info('KL transform truncation = %d', truncate)
# Get the PSF reference images
refs_model = datamodels.open(psfrefs)
# Call the KLIP routine
psf_sub, psf_fit = klip.klip(target_model, refs_model, truncate)
# Update the step completion status
psf_sub.meta.cal_step.klip = 'COMPLETE'
# return psf_sub, psf_fit
return psf_sub