remove dependence on ModelContainer, operate on one model at a time

src/stcal/alignment/resample_utils.py

@@ -42,89 +42,87 @@ def calc_pixmap(in_wcs, out_wcs, shape=None):
     return np.dstack(transform_function(grid[0], grid[1]))
 
 
-# is this allowed in stcal, since it operates on a datamodel?
-# seems ok. jump step for example does use models
-def make_output_wcs(input_models, ref_wcs=None,
-                    pscale_ratio=None, pscale=None, rotation=None, shape=None,
-                    crpix=None, crval=None):
-    """Generate output WCS here based on footprints of all input WCS objects.
-
-    Parameters
-    ----------
-    input_models : list of `DataModel objects`
-        Each datamodel must have a ~gwcs.WCS object.
-
-    pscale_ratio : float, optional
-        Ratio of input to output pixel scale. Ignored when ``pscale``
-        is provided.
-
-    pscale : float, None, optional
-        Absolute pixel scale in degrees. When provided, overrides
-        ``pscale_ratio``.
-
-    rotation : float, None, optional
-        Position angle of output image Y-axis relative to North.
-        A value of 0.0 would orient the final output image to be North up.
-        The default of `None` specifies that the images will not be rotated,
-        but will instead be resampled in the default orientation for the camera
-        with the x and y axes of the resampled image corresponding
-        approximately to the detector axes.
-
-    shape : tuple of int, None, optional
-        Shape of the image (data array) using ``numpy.ndarray`` convention
-        (``ny`` first and ``nx`` second). This value will be assigned to
-        ``pixel_shape`` and ``array_shape`` properties of the returned
-        WCS object.
-
-    crpix : tuple of float, None, optional
-        Position of the reference pixel in the image array. If ``crpix`` is not
-        specified, it will be set to the center of the bounding box of the
-        returned WCS object.
-
-    crval : tuple of float, None, optional
-        Right ascension and declination of the reference pixel. Automatically
-        computed if not provided.
-
-    Returns
-    -------
-    output_wcs : object
-        WCS object, with defined domain, covering entire set of input frames
-    """
-    if ref_wcs is None:
-        wcslist = [i.meta.wcs for i in input_models]
-        for w, i in zip(wcslist, input_models):
-            if w.bounding_box is None:
-                w.bounding_box = util.wcs_bbox_from_shape(i.data.shape)
-        naxes = wcslist[0].output_frame.naxes
-
-        if naxes != 2:
-            msg = f"Output WCS needs 2 spatial axes \
-                    but the supplied WCS has {naxes} axes."
-            raise RuntimeError(msg)
-
-        output_wcs = util.wcs_from_footprints(
-            input_models,
-            pscale_ratio=pscale_ratio,
-            pscale=pscale,
-            rotation=rotation,
-            shape=shape,
-            crpix=crpix,
-            crval=crval
-        )
-
-    else:
-        naxes = ref_wcs.output_frame.naxes
-        if naxes != 2:
-            msg = f"Output WCS needs 2 spatial axes \
-                    but the supplied WCS has {naxes} axes."
-            raise RuntimeError(msg)
-        output_wcs = deepcopy(ref_wcs)
-        if shape is not None:
-            output_wcs.array_shape = shape
-
-    # Check that the output data shape has no zero length dimensions
-    if not np.prod(output_wcs.array_shape):
-        msg = f"Invalid output frame shape: {tuple(output_wcs.array_shape)}"
-        raise ValueError(msg)
-
-    return output_wcs
+# def make_output_wcs(input_models, ref_wcs=None,
+#                     pscale_ratio=None, pscale=None, rotation=None, shape=None,
+#                     crpix=None, crval=None):
+#     """Generate output WCS here based on footprints of all input WCS objects.
+
+#     Parameters
+#     ----------
+#     input_models : list of `DataModel objects`
+#         Each datamodel must have a ~gwcs.WCS object.
+
+#     pscale_ratio : float, optional
+#         Ratio of input to output pixel scale. Ignored when ``pscale``
+#         is provided.
+
+#     pscale : float, None, optional
+#         Absolute pixel scale in degrees. When provided, overrides
+#         ``pscale_ratio``.
+
+#     rotation : float, None, optional
+#         Position angle of output image Y-axis relative to North.
+#         A value of 0.0 would orient the final output image to be North up.
+#         The default of `None` specifies that the images will not be rotated,
+#         but will instead be resampled in the default orientation for the camera
+#         with the x and y axes of the resampled image corresponding
+#         approximately to the detector axes.
+
+#     shape : tuple of int, None, optional
+#         Shape of the image (data array) using ``numpy.ndarray`` convention
+#         (``ny`` first and ``nx`` second). This value will be assigned to
+#         ``pixel_shape`` and ``array_shape`` properties of the returned
+#         WCS object.
+
+#     crpix : tuple of float, None, optional
+#         Position of the reference pixel in the image array. If ``crpix`` is not
+#         specified, it will be set to the center of the bounding box of the
+#         returned WCS object.
+
+#     crval : tuple of float, None, optional
+#         Right ascension and declination of the reference pixel. Automatically
+#         computed if not provided.
+
+#     Returns
+#     -------
+#     output_wcs : object
+#         WCS object, with defined domain, covering entire set of input frames
+#     """
+#     if ref_wcs is None:
+#         wcslist = [i.meta.wcs for i in input_models]
+#         for w, i in zip(wcslist, input_models):
+#             if w.bounding_box is None:
+#                 w.bounding_box = util.wcs_bbox_from_shape(i.data.shape)
+#         naxes = wcslist[0].output_frame.naxes
+
+#         if naxes != 2:
+#             msg = f"Output WCS needs 2 spatial axes \
+#                     but the supplied WCS has {naxes} axes."
+#             raise RuntimeError(msg)
+
+#         output_wcs = util.wcs_from_footprints(
+#             input_models,
+#             pscale_ratio=pscale_ratio,
+#             pscale=pscale,
+#             rotation=rotation,
+#             shape=shape,
+#             crpix=crpix,
+#             crval=crval
+#         )
+
+#     else:
+#         naxes = ref_wcs.output_frame.naxes
+#         if naxes != 2:
+#             msg = f"Output WCS needs 2 spatial axes \
+#                     but the supplied WCS has {naxes} axes."
+#             raise RuntimeError(msg)
+#         output_wcs = deepcopy(ref_wcs)
+#         if shape is not None:
+#             output_wcs.array_shape = shape
+
+#     # Check that the output data shape has no zero length dimensions
+#     if not np.prod(output_wcs.array_shape):
+#         msg = f"Invalid output frame shape: {tuple(output_wcs.array_shape)}"
+#         raise ValueError(msg)
+
+#     return output_wcs

src/stcal/alignment/util.py

@@ -584,7 +584,6 @@ def update_fits_wcsinfo(datamodel, max_pix_error=0.01, degree=None,
 
     Parameters
     ----------
-
     datamodel : `ImageModel`
         The input data model for imaging or WFSS mode whose ``meta.wcsinfo``
         field should be updated from GWCS. By default, ``datamodel.meta.wcs``
@@ -687,7 +686,6 @@ def update_fits_wcsinfo(datamodel, max_pix_error=0.01, degree=None,
 
     Notes
     -----
-
     Use of this requires a judicious choice of required accuracies.
     Attempts to use higher degrees (~7 or higher) will typically fail due
     to floating point problems that arise with high powers.

src/stcal/tweakreg/astrometric_utils.py

@@ -5,9 +5,8 @@
 from astropy import units as u
 from astropy.coordinates import SkyCoord
 from astropy.table import Table
-from astropy.time import Time
 
-from stcal.alignment import compute_fiducial, resample_utils
+from stcal.alignment import compute_fiducial
 
 ASTROMETRIC_CAT_ENVVAR = "ASTROMETRIC_CATALOG_URL"
 DEF_CAT_URL = "http://gsss.stsci.edu/webservices"
@@ -31,20 +30,27 @@
 
 
 def create_astrometric_catalog(
-        input_models,
+        wcs,
+        epoch,
         catalog="GAIADR3",
         output="ref_cat.ecsv",
         gaia_only=False,
         table_format="ascii.ecsv",
-        existing_wcs=None,
-        num_sources=None,
-        epoch=None):
+        num_sources=None):
     """Create an astrometric catalog that covers the inputs' field-of-view.
 
     Parameters
     ----------
-    input_models : list of `~jwst.datamodel.JwstDataModel`
-        Each datamodel must have a ~gwcs.WCS object.
+    wcs : `~astropy.wcs.WCS`
+        WCS object specified by the user as generated by
+        `resample.resample_utils.make_output_wcs`. This will typically
+        have the same plate-scale and orientation as the first member in the
+        list of input images to make_output_wcs. Fortunately, for alignment,
+        this doesn't matter since no resampling of data will be performed.
+
+    epoch : float
+        Reference epoch used to update the coordinates for proper motion
+        (in decimal year).
 
     catalog : str, optional
         Name of catalog to extract astrometric positions for sources in the
@@ -58,19 +64,12 @@ def create_astrometric_catalog(
     gaia_only : bool, optional
         Specify whether or not to only use sources from GAIA in output catalog
 
-    existing_wcs : model
-        existing WCS object specified by the user as generated by
-        `resample.resample_utils.make_output_wcs`
-
     num_sources : int
         Maximum number of brightest/faintest sources to return in catalog.
         If `num_sources` is negative, return that number of the faintest
         sources.  By default, all sources are returned.
 
-    epoch : float, optional
-        Reference epoch used to update the coordinates for proper motion
-        (in decimal year). If `None` then the epoch is obtained from
-        the metadata.
+
 
     Notes
     -----
@@ -83,20 +82,9 @@ def create_astrometric_catalog(
         Astropy Table object of the catalog
     """
     # start by creating a composite field-of-view for all inputs
-    # This default output WCS will have the same plate-scale and orientation
-    # as the first member in the list.
-    # Fortunately, for alignment, this doesn't matter since no resampling of
-    # data will be performed.
-    outwcs = existing_wcs if existing_wcs is not None \
-        else resample_utils.make_output_wcs(input_models)
-    radius, fiducial = compute_radius(outwcs)
+    radius, fiducial = compute_radius(wcs)
 
     # perform query for this field-of-view
-    epoch = (
-        epoch
-        if epoch is not None
-        else Time(input_models[0].meta.observation.date).decimalyear
-    )
     ref_dict = get_catalog(
         fiducial[0],
         fiducial[1],