#! /usr/bin/env python
from stdatamodels.jwst import datamodels
from ..stpipe import Step
from ..lib.exposure_types import IMAGING_TYPES
import logging
from .assign_wcs import load_wcs
from .util import MSAFileError, update_fits_wcsinfo
from .util import wfss_imaging_wcs, wcs_bbox_from_shape
from .nircam import imaging as nircam_imaging
from .niriss import imaging as niriss_imaging
log = logging.getLogger(__name__)
log.setLevel(logging.DEBUG)
__all__ = ["AssignWcsStep"]
WFSS_TYPES = set(['nrc_wfss', 'nis_wfss'])
[docs]
class AssignWcsStep(Step):
"""
AssignWcsStep: Create a gWCS object and store it in ``Model.meta``.
Reference file types:
camera Camera model (NIRSPEC)
collimator Collimator Model (NIRSPEC)
disperser Disperser model (NIRSPEC)
distortion Spatial distortion model (FGS, MIRI, NIRCAM, NIRISS)
filteroffset Filter offsets (MIRI Imager)
fore Transform through the FORE optics (NIRSPEC)
fpa Transform in the FPA plane (NIRSPEC)
ifufore Transforms from the MSA plane to the plane of the IFU slicer (NIRSPEC)
ifupost Transforms from the slicer plane to the MSA plane (NIRSPEC)
ifuslicer Metrology of the IFU slicer (NIRSPEC)
msa Metrology of the MSA plane (NIRSPEC)
ote Transform through the Optical Telescope Element (NIRSPEC)
specwcs Wavelength calibration models (MIRI, NIRCAM, NIRISS)
regions Stores location of the regions on the detector (MIRI)
wavelengthrange Typical wavelength ranges (MIRI, NIRCAM, NIRISS, NIRSPEC)
Parameters
----------
input : `~jwst.datamodels.ImageModel`, `~jwst.datamodels.IFUImageModel`, `~jwst.datamodels.CubeModel`
Input exposure.
"""
class_alias = "assign_wcs"
spec = """
sip_approx = boolean(default=True) # enables SIP approximation for imaging modes.
sip_max_pix_error = float(default=0.1) # max err for SIP fit, forward.
sip_degree = integer(max=6, default=None) # degree for forward SIP fit, None to use best fit.
sip_max_inv_pix_error = float(default=0.1) # max err for SIP fit, inverse.
sip_inv_degree = integer(max=6, default=None) # degree for inverse SIP fit, None to use best fit.
sip_npoints = integer(default=12) # number of points for SIP
slit_y_low = float(default=-.55) # The lower edge of a slit.
slit_y_high = float(default=.55) # The upper edge of a slit.
"""
reference_file_types = ['distortion', 'filteroffset', 'specwcs', 'regions',
'wavelengthrange', 'camera', 'collimator', 'disperser',
'fore', 'fpa', 'msa', 'ote', 'ifupost',
'ifufore', 'ifuslicer']
[docs]
def process(self, input, *args, **kwargs):
reference_file_names = {}
with datamodels.open(input) as input_model:
# If input type is not supported, log warning, set to 'skipped', exit
if not (isinstance(input_model, datamodels.ImageModel) or
isinstance(input_model, datamodels.CubeModel) or
isinstance(input_model, datamodels.IFUImageModel)):
log.warning("Input dataset type is not supported.")
log.warning("assign_wcs expects ImageModel, IFUImageModel or CubeModel as input.")
log.warning("Skipping assign_wcs step.")
result = input_model.copy()
result.meta.cal_step.assign_wcs = 'SKIPPED'
return result
for reftype in self.reference_file_types:
reffile = self.get_reference_file(input_model, reftype)
reference_file_names[reftype] = reffile if reffile else ""
log.debug(f'reference files used in assign_wcs: {reference_file_names}')
# Get the MSA metadata file if needed and add to reffiles
if input_model.meta.exposure.type == "NRS_MSASPEC":
msa_metadata_file = input_model.meta.instrument.msa_metadata_file
if msa_metadata_file is not None and msa_metadata_file.strip() not in ["", "N/A"]:
msa_metadata_file = self.make_input_path(msa_metadata_file)
reference_file_names['msametafile'] = msa_metadata_file
else:
message = "MSA metadata file (MSAMETFL) is required for NRS_MSASPEC exposures."
log.error(message)
raise MSAFileError(message)
slit_y_range = [self.slit_y_low, self.slit_y_high]
result = load_wcs(input_model, reference_file_names, slit_y_range)
if not (result.meta.exposure.type.lower() in (IMAGING_TYPES.union(WFSS_TYPES)) and self.sip_approx):
return result
result_exptype = result.meta.exposure.type.lower()
# fit sip approx., degree is chosen by best fit
if result_exptype in IMAGING_TYPES:
try:
update_fits_wcsinfo(
result,
max_pix_error=self.sip_max_pix_error,
degree=self.sip_degree,
max_inv_pix_error=self.sip_max_inv_pix_error,
inv_degree=self.sip_inv_degree,
npoints=self.sip_npoints,
crpix=None
)
except (ValueError, RuntimeError) as e:
log.warning("Failed to update 'meta.wcsinfo' with FITS SIP "
f'approximation. Reported error is:\n"{e.args[0]}"')
else: # WFSS modes
try:
# A bounding_box is needed for the imaging WCS
bbox = wcs_bbox_from_shape(result.data.shape)
if result_exptype == 'nis_wfss':
imaging_func = niriss_imaging
else:
imaging_func = nircam_imaging
wfss_imaging_wcs(result, imaging_func, bbox=bbox,
max_pix_error=self.sip_max_pix_error,
degree=self.sip_degree,
npoints=self.sip_npoints,
)
except (ValueError, RuntimeError) as e:
log.warning("Failed to update 'meta.wcsinfo' with FITS SIP "
f'approximation. Reported error is:\n"{e.args[0]}"')
return result