Merge branch 'main' into jp3858-white_light

.pre-commit-config.yaml

@@ -65,7 +65,6 @@ repos:
             jwst/spectral_leak/.* |
             jwst/srctype/.* |
             jwst/straylight/.* |
-            jwst/superbias/.* |
             jwst/tests/.* |
             jwst/tso_photometry/.* |
             jwst/wfs_combine/.* |

.ruff.toml

@@ -47,7 +47,6 @@ exclude = [
     "jwst/spectral_leak/**.py",
     "jwst/srctype/**.py",
     "jwst/straylight/**.py",
-    "jwst/superbias/**.py",
     "jwst/tso_photometry/**.py",
     "jwst/wfs_combine/**.py",
 ]
@@ -146,6 +145,5 @@ ignore-fully-untyped = true  # Turn off annotation checking for fully untyped co
 "jwst/spectral_leak/**.py" = ["D", "N", "A", "ARG", "B", "C4", "ICN", "INP", "ISC", "LOG", "NPY", "PGH", "PTH", "S", "SLF", "SLOT", "T20", "TRY", "UP", "YTT", "E501"]
 "jwst/srctype/**.py" = ["D", "N", "A", "ARG", "B", "C4", "ICN", "INP", "ISC", "LOG", "NPY", "PGH", "PTH", "S", "SLF", "SLOT", "T20", "TRY", "UP", "YTT", "E501"]
 "jwst/straylight/**.py" = ["D", "N", "A", "ARG", "B", "C4", "ICN", "INP", "ISC", "LOG", "NPY", "PGH", "PTH", "S", "SLF", "SLOT", "T20", "TRY", "UP", "YTT", "E501"]
-"jwst/superbias/**.py" = ["D", "N", "A", "ARG", "B", "C4", "ICN", "INP", "ISC", "LOG", "NPY", "PGH", "PTH", "S", "SLF", "SLOT", "T20", "TRY", "UP", "YTT", "E501"]
 "jwst/tso_photometry/**.py" = ["D", "N", "A", "ARG", "B", "C4", "ICN", "INP", "ISC", "LOG", "NPY", "PGH", "PTH", "S", "SLF", "SLOT", "T20", "TRY", "UP", "YTT", "E501"]
 "jwst/wfs_combine/**.py" = ["D", "N", "A", "ARG", "B", "C4", "ICN", "INP", "ISC", "LOG", "NPY", "PGH", "PTH", "S", "SLF", "SLOT", "T20", "TRY", "UP", "YTT", "E501"]

changes/9073.extract_1d.rst

@@ -0,0 +1 @@
+For MIRI MRS data added residual fringe corrected columns to extracted spectrum table

changes/9193.assign_wcs.rst

@@ -0,0 +1 @@
+Fix MIRI LRS s_region in assign_wcs

changes/9193.resample.rst

@@ -0,0 +1 @@
+Fix MIRI LRS s_region and WCS in resample_spec

docs/jwst/extract_1d/description.rst

@@ -77,7 +77,11 @@ be an output table extension with the name EXTRACT1D.  This extension will
 have columns WAVELENGTH, FLUX, FLUX_ERROR, FLUX_VAR_POISSON, FLUX_VAR_RNOISE,
 FLUX_VAR_FLAT, SURF_BRIGHT, SB_ERROR, SB_VAR_POISSON, SB_VAR_RNOISE,
 SB_VAR_FLAT, DQ, BACKGROUND, BKGD_ERROR, BKGD_VAR_POISSON, BKGD_VAR_RNOISE,
-BKGD_VAR_FLAT and NPIXELS. Some metadata for the slit will be written to the header for
+BKGD_VAR_FLAT and NPIXELS. In the case of MIRI MRS data there are three additional
+columns in the output table:  RF_FLUX, RF_SURF_BRIGHT, and RF_BACKGROUND.
+For more details on the MIRI MRS extracted data see :ref:`MIRI-MRS-1D-residual-fringe`.
+
+Some metadata for the slit will be written to the header for
 the table extension, mostly copied from the input SCI extension headers.
 
 For slit-like modes, the extraction region is
@@ -423,10 +427,15 @@ can be applied to the flux-calibrated detector data in the :ref:`residual_fringe
 is part of the :ref:`calwebb_spec2 <calwebb_spec2>` pipeline, but currently it is skipped by default. For more
 information see :ref:`residual_fringe <residual_fringe_step>`.
 
-The pipeline also can apply a 1-D residual fringe correction. This correction is only relevant for MIRI MRS data and 
-can be turned on by setting the optional parameter `ifu_rfcorr = True`  in the ``extract_1d`` step.
+The pipeline also can apply a 1-D residual fringe correction. This correction is only relevant for MIRI MRS
+single band data. The parameter controlling applying the residual fringe correction is by default set to true, 
+`ifu_rfcorr = True`,  in the ``extract_1d`` step.
 Empirically, the 1-D correction step has been found to work better than the 2-D correction step if it is
-applied to per-band spectra.
+applied to per-band spectra. If the MIRI MRS data is from multiple bands/channels the residual fringe correction
+is turned off. Three additional columns are present in MIRI MRS extracted spectra: RF_FLUX, RF_SURF_BRIGHT, and 
+RF_BACKGROUND. These three columns are the flux, surface brightness and background arrays with the residiual
+fringe correction applied. If the data is not from a single band or the residual fringe correction fails
+NaN values are reported for the arrays. 
 
 When using the `ifu_rfcorr` option in the ``extract_1d`` step  to apply a 1-D residual fringe
 correction, it is applied during the extraction of spectra from the IFU cube. The 1D residual fringe code can also

jwst/assign_wcs/assign_wcs.py

@@ -2,7 +2,8 @@
 import importlib
 from gwcs.wcs import WCS
 from .util import (update_s_region_spectral, update_s_region_imaging,
-                   update_s_region_nrs_ifu, update_s_region_mrs)
+                   update_s_region_nrs_ifu, update_s_region_mrs,
+                   update_s_region_lrs)
 from ..lib.exposure_types import IMAGING_TYPES, SPEC_TYPES, NRS_LAMP_MODE_SPEC_TYPES
 from ..lib.dispaxis import get_dispersion_direction
 from ..lib.wcs_utils import get_wavelengths
@@ -72,8 +73,13 @@ def load_wcs(input_model, reference_files={}, nrs_slit_y_range=None):
 
         if output_model.meta.exposure.type.lower() not in exclude_types:
             imaging_types = IMAGING_TYPES.copy()
-            imaging_types.update(['mir_lrs-fixedslit', 'mir_lrs-slitless'])
-            if output_model.meta.exposure.type.lower() in imaging_types:
+            imaging_types.update(['mir_lrs-slitless'])
+            imaging_lrs_types = ['mir_lrs-fixedslit']
+            if output_model.meta.exposure.type.lower() in imaging_lrs_types:
+                # uses slits corners in V2, V3 that are read in from the
+                # lrs specwcs reference file
+                update_s_region_lrs(output_model, reference_files)
+            elif output_model.meta.exposure.type.lower() in imaging_types:
                 try:
                     update_s_region_imaging(output_model)
                 except Exception as exc:

jwst/assign_wcs/miri.py

@@ -5,15 +5,13 @@
 from astropy.modeling import models
 from astropy import coordinates as coord
 from astropy import units as u
-from astropy.io import fits
-
 from scipy.interpolate import UnivariateSpline
 import gwcs.coordinate_frames as cf
 from gwcs import selector
 
 from stdatamodels.jwst.datamodels import (DistortionModel, FilteroffsetModel,
                                           DistortionMRSModel, WavelengthrangeModel,
-                                          RegionsModel, SpecwcsModel)
+                                          RegionsModel, SpecwcsModel, MiriLRSSpecwcsModel)
 from stdatamodels.jwst.transforms.models import (MIRI_AB2Slice, IdealToV2V3)
 
 from . import pointing
@@ -239,7 +237,6 @@ def lrs_xytoabl(input_model, reference_files):
     the "specwcs" and "distortion" reference files.
 
     """
-
     # subarray to full array transform
     subarray2full = subarray_transform(input_model)
 
@@ -253,19 +250,13 @@ def lrs_xytoabl(input_model, reference_files):
     else:
         subarray_dist = distortion
 
-    ref = fits.open(reference_files['specwcs'])
-
-    with ref:
-        lrsdata = np.array([d for d in ref[1].data])
-        # Get the zero point from the reference data.
-        # The zero_point is X, Y  (which should be COLUMN, ROW)
-        # These are 1-indexed in CDP-7 (i.e., SIAF convention) so must be converted to 0-indexed
-        if input_model.meta.exposure.type.lower() == 'mir_lrs-fixedslit':
-            zero_point = ref[0].header['imx'] - 1, ref[0].header['imy'] - 1
-        elif input_model.meta.exposure.type.lower() == 'mir_lrs-slitless':
-            zero_point = ref[0].header['imxsltl'] - 1, ref[0].header['imysltl'] - 1
-            # Transform to slitless subarray from full array
-            zero_point = subarray2full.inverse(zero_point[0], zero_point[1])
+    refmodel = MiriLRSSpecwcsModel(reference_files['specwcs'])
+    if input_model.meta.exposure.type.lower() == 'mir_lrs-fixedslit':
+        zero_point = refmodel.meta.x_ref - 1, refmodel.meta.y_ref - 1
+    elif input_model.meta.exposure.type.lower() == 'mir_lrs-slitless':
+        zero_point = refmodel.meta.x_ref_slitless - 1, refmodel.meta.y_ref_slitless - 1
+        # Transform to slitless subarray from full array
+        zero_point = subarray2full.inverse(zero_point[0], zero_point[1])
 
     # Figure out the typical along-slice pixel scale at the center of the slit
     v2_cen, v3_cen = subarray_dist(zero_point[0], zero_point[1])
@@ -276,14 +267,14 @@ def lrs_xytoabl(input_model, reference_files):
     # centroid trace along the detector in pixels relative to nominal location.
     # x0,y0(ul) x1,y1 (ur) x2,y2(lr) x3,y3(ll) define corners of the box within which the distortion
     # and wavelength calibration was derived
-    xcen = lrsdata[:, 0]
-    ycen = lrsdata[:, 1]
-    wavetab = lrsdata[:, 2]
-    x0 = lrsdata[:, 3]
-    y0 = lrsdata[:, 4]
-    x1 = lrsdata[:, 5]
-    y2 = lrsdata[:, 8]
-
+    xcen = refmodel.wavetable.x_center
+    ycen = refmodel.wavetable.y_center
+    wavetab = refmodel.wavetable.wavelength
+    x0 = refmodel.wavetable.x0
+    y0 = refmodel.wavetable.y0
+    x1 = refmodel.wavetable.x1
+    y2 = refmodel.wavetable.y2
+    refmodel.close()
     # If in fixed slit mode, define the bounding box using the corner locations provided in
     # the CDP reference file.
     if input_model.meta.exposure.type.lower() == 'mir_lrs-fixedslit':
@@ -313,7 +304,6 @@ def lrs_xytoabl(input_model, reference_files):
     # This function will give slit dX as a function of Y subarray pixel value
     dxmodel = models.Tabular1D(lookup_table=xshiftref, points=ycen_subarray, name='xshiftref',
                                  bounds_error=False, fill_value=np.nan)
-
     if input_model.meta.exposure.type.lower() == 'mir_lrs-fixedslit':
         bb_sub = (bb_sub[0], (dxmodel.points[0].min(), dxmodel.points[0].max()))
     # Fit for the wavelength as a function of Y
@@ -325,7 +315,6 @@ def lrs_xytoabl(input_model, reference_files):
     # This model will now give the wavelength corresponding to a given Y subarray pixel value
     wavemodel = models.Tabular1D(lookup_table=wavereference, points=ycen_subarray, name='waveref',
                                  bounds_error=False, fill_value=np.nan)
-
     # Wavelength barycentric correction
     try:
         velosys = input_model.meta.wcsinfo.velosys
@@ -383,6 +372,7 @@ def lrs_xytoabl(input_model, reference_files):
 
     return dettoabl
 
+
 def lrs_abltov2v3l(input_model, reference_files):
     """
     The second part of LRS-FIXEDSLIT and LRS-SLITLESS WCS pipeline.
@@ -405,19 +395,16 @@ def lrs_abltov2v3l(input_model, reference_files):
     else:
         subarray_dist = distortion
 
-    ref = fits.open(reference_files['specwcs'])
-
-    with ref:
-        # Get the zero point from the reference data.
-        # The zero_point is X, Y  (which should be COLUMN, ROW)
-        # These are 1-indexed in CDP-7 (i.e., SIAF convention) so must be converted to 0-indexed
-        if input_model.meta.exposure.type.lower() == 'mir_lrs-fixedslit':
-            zero_point = ref[0].header['imx'] - 1, ref[0].header['imy'] - 1
-        elif input_model.meta.exposure.type.lower() == 'mir_lrs-slitless':
-            zero_point = ref[0].header['imxsltl'] - 1, ref[0].header['imysltl'] - 1
-            # Transform to slitless subarray from full array
-            zero_point = subarray2full.inverse(zero_point[0], zero_point[1])
-
+    refmodel = MiriLRSSpecwcsModel(reference_files['specwcs'])
+    if input_model.meta.exposure.type.lower() == 'mir_lrs-fixedslit':
+        zero_point = refmodel.meta.x_ref - 1, refmodel.meta.y_ref - 1
+    elif input_model.meta.exposure.type.lower() == 'mir_lrs-slitless':
+        zero_point = refmodel.meta.x_ref_slitless - 1, \
+            refmodel.meta.y_ref_slitless - 1
+        # Transform to slitless subarray from full array
+        zero_point = subarray2full.inverse(zero_point[0], zero_point[1])
+
+    refmodel.close()
     # Figure out the typical along-slice pixel scale at the center of the slit
     v2_cen, v3_cen = subarray_dist(zero_point[0], zero_point[1])
     v2_off, v3_off = subarray_dist(zero_point[0] + 1, zero_point[1])
@@ -447,6 +434,7 @@ def lrs_abltov2v3l(input_model, reference_files):
 
     return abl_to_v2v3l
 
+
 def ifu(input_model, reference_files):
     """
     The MIRI MRS WCS pipeline.

jwst/assign_wcs/util.py

@@ -19,10 +19,10 @@
 from stpipe.exceptions import StpipeExitException
 from stcal.alignment.util import compute_s_region_keyword, compute_s_region_imaging
 
-from stdatamodels.jwst.datamodels import WavelengthrangeModel
+from stdatamodels.jwst.datamodels import WavelengthrangeModel, MiriLRSSpecwcsModel
 from stdatamodels.jwst.transforms.models import GrismObject
 
-from ..lib.catalog_utils import SkyObject
+from jwst.lib.catalog_utils import SkyObject
 
 
 log = logging.getLogger(__name__)
@@ -807,6 +807,51 @@ def update_s_region_imaging(model):
         model.meta.wcsinfo.s_region = s_region
 
 
+def update_s_region_lrs(model, reference_files):
+    """
+    Update ``S_REGION`` using V2,V3 of the slit corners from reference file.
+
+    s_region for model is updated in place.
+
+    Parameters
+    ----------
+    model : DataModel
+        Input model
+    reference_files : list
+        List of reference files for assign_wcs.
+    """
+    refmodel = MiriLRSSpecwcsModel(reference_files['specwcs'])
+
+    v2vert1 = refmodel.meta.v2_vert1
+    v2vert2 = refmodel.meta.v2_vert2
+    v2vert3 = refmodel.meta.v2_vert3
+    v2vert4 = refmodel.meta.v2_vert4
+
+    v3vert1 = refmodel.meta.v3_vert1
+    v3vert2 = refmodel.meta.v3_vert2
+    v3vert3 = refmodel.meta.v3_vert3
+    v3vert4 = refmodel.meta.v3_vert4
+
+    refmodel.close()
+    v2 = [v2vert1, v2vert2, v2vert3, v2vert4]
+    v3 = [v3vert1, v3vert2, v3vert3, v3vert4]
+
+    if (any(elem is None for elem in v2) or
+        any(elem is None for elem in v3)):
+        log.info("The V2,V3 coordinates of the MIRI LRS-Fixed slit contains NaN values.")
+        log.info("The s_region will not be updated")
+
+    lam = 7.0 # wavelength does not matter for s region so just assign a value in range of LRS
+    s = model.meta.wcs.transform('v2v3', 'world', v2, v3, lam)
+    a = s[0]
+    b = s[1]
+    footprint = np.array([[a[0], b[0]],
+                          [a[1], b[1]],
+                          [a[2], b[2]],
+                          [a[3], b[3]]])
+
+    update_s_region_keyword(model, footprint)
+
 def compute_footprint_spectral(model):
     """
     Determine spatial footprint for spectral observations using the instrument model.
@@ -844,9 +889,11 @@ def compute_footprint_spectral(model):
     return footprint, (lam_min, lam_max)
 
 
+
 def update_s_region_spectral(model):
     """ Update the S_REGION keyword.
     """
+
     footprint, spectral_region = compute_footprint_spectral(model)
     update_s_region_keyword(model, footprint)
     model.meta.wcsinfo.spectral_region = spectral_region

jwst/extract_1d/extract_1d_step.py

@@ -97,7 +97,7 @@ class Extract1dStep(Step):
         and maximize the quality of the 1d spectrum. Used for IFU mode only.
     ifu_rfcorr : bool
         Switch to select whether or not to apply a 1d residual fringe correction
-        for MIRI MRS IFU spectra.  Default is False.
+        for MIRI MRS IFU spectra.  Default is True.
     ifu_set_srctype : str
         For MIRI MRS IFU data override srctype and set it to either POINT or EXTENDED.
     ifu_rscale : float
@@ -170,7 +170,7 @@ class Extract1dStep(Step):
     center_xy = float_list(min=2, max=2, default=None)  # IFU extraction x/y center
     ifu_autocen = boolean(default=False) # Auto source centering for IFU point source data.
     bkg_sigma_clip = float(default=3.0)  # background sigma clipping threshold for IFU
-    ifu_rfcorr = boolean(default=False) # Apply 1d residual fringe correction
+    ifu_rfcorr = boolean(default=True) # Apply 1d residual fringe correction (MIRI MRS only)
     ifu_set_srctype = option("POINT", "EXTENDED", None, default=None) # user-supplied source type
     ifu_rscale = float(default=None, min=0.5, max=3) # Radius in terms of PSF FWHM to scale extraction radii
     ifu_covar_scale = float(default=1.0) # Scaling factor to apply to errors to account for IFU cube covariance
@@ -342,6 +342,36 @@ def _extract_soss(self, model):
 
         return result
 
+    def _check_mrs_type(self, model):
+        """
+        Check if the MIRI MRS data is for a single band.
+
+        Parameters
+        ----------
+        model : DataModel
+            Input model.
+
+        Returns
+        -------
+        band_check : bool
+            Flag is data is for a single MIRI MRS band.
+        """
+        # check channel is only 1 value and band is only 1 value
+        validch = ["1", "2", "3", "4"]
+        validband = ["short", "medium", "long"]
+        band_check = False
+        ch_check = False
+        b_check = False
+        if model.meta.instrument.channel in validch:
+            ch_check = True
+        if str(model.meta.instrument.band).lower() in validband:
+            b_check = True
+
+        if ch_check and b_check:
+            band_check = True
+
+        return band_check
+
     def _extract_ifu(self, model, exp_type, extract_ref, apcorr_ref):
         """
         Extract IFU spectra from a single datamodel.
@@ -367,6 +397,21 @@ def _extract_ifu(self, model, exp_type, extract_ref, apcorr_ref):
             source_type = self.ifu_set_srctype
             self.log.info(f"Overriding source type and setting it to {self.ifu_set_srctype}")
 
+        if exp_type == "MIR_MRS":
+            band_cube = self._check_mrs_type(model)
+            if self.ifu_rfcorr and not band_cube:
+                message = (
+                    "Turning off residual fringe correction for MIRI MRS data "
+                    "because the input is not a single IFU band"
+                )
+                self.log.info(message)
+                self.ifu_rfcorr = False
+        else:
+            self.ifu_rfcorr = False
+            self.log.info(
+                "Turning off residual fringe correction because it only works on MIRI MRS data"
+            )
+
         result = ifu_extract1d(
             model,
             extract_ref,