fixes per @melanieclarke comments

CHANGES.rst

@@ -38,7 +38,7 @@ cube_build
 datamodels
 ----------
 
-- Added `ModelLibrary` class to allow passing ``"on-disk"`` models between steps in the
+- Added `ModelLibrary` class to allow passing on-disk models between steps in the
   image3 pipeline. [#8683]
 
 emicorr
@@ -68,17 +68,17 @@ outlier_detection
 - Fixed failures due to a missing ``wcs.array_shape`` attribute when the
   ``outlier_detection`` step was run standalone using e.g. ``strun`` [#8645]
 
-set_telescope_pointing
-----------------------
-
-- replace usage of ``copy_arrays=True`` with ``memmap=False`` [#8660]
-
 - Refactored separate modes into submodules instead of inheriting from a base class.
   Moved non-JWST-specific code to stcal. [#8613]
 
 - For imaging modes, step now uses `ModelLibrary` to handle accessing models consistently
   whether they are in memory or on disk. [#8683]
 
+set_telescope_pointing
+----------------------
+
+- replace usage of ``copy_arrays=True`` with ``memmap=False`` [#8660]
+
 pipeline
 --------
 

docs/jwst/tweakreg/README.rst

@@ -87,7 +87,6 @@ other ways of supplying custom source catalogs to the step:
 
 1. Adding ``tweakreg_catalog`` attribute to the ``members`` of the input ASN
    table - see `~jwst.datamodels.ModelLibrary` for more details.
-   # FIXME: does this still work as described?
    Catalog file names are relative to ASN file path.
 
 2. Providing a simple two-column text file, specified via step's parameter

jwst/datamodels/library.py

@@ -129,11 +129,6 @@ def _assign_member_to_model(self, model, member):
         if not hasattr(model.meta, "asn"):
             model.meta["asn"] = {}
 
-        # if (model.meta.asn.table_name is None) and ("table_name" in self.asn.keys()): # do not clobber existing values
-        #     setattr(model.meta.asn, "table_name", self.asn["table_name"])
-
-        # if (model.meta.asn.pool_name is None) and ("asn_pool" in self.asn.keys()): # do not clobber existing values
-        #     setattr(model.meta.asn, "pool_name", self.asn["asn_pool"])
         if "table_name" in self.asn.keys():
             setattr(model.meta.asn, "table_name", self.asn["table_name"])
 

jwst/lib/exposure_types.py

@@ -89,6 +89,8 @@ def is_nrs_autoflat(datamodel):
 
 def is_moving_target(datamodel):
     """ Determine if a moving target exposure."""
-    if (hasattr(datamodel.meta.target, 'type') and datamodel.meta.target.type is not None and datamodel.meta.target.type.lower() == 'moving'):
+    if (hasattr(datamodel.meta.target, 'type') \
+            and datamodel.meta.target.type is not None \
+            and datamodel.meta.target.type.lower() == 'moving'):
         return True
     return False

jwst/outlier_detection/outlier_detection_step.py

@@ -160,7 +160,7 @@ def process(self, input_data):
         else:
             self.log.error("Outlier detection failed for unknown/unsupported ",
                            f"mode: {mode}")
-            return self._set_status(input_data, True)
+            return self._set_status(input_data, False)
 
         return self._set_status(result_models, True)
 

jwst/resample/resample.py

@@ -953,6 +953,17 @@ def compute_image_pixel_area(wcs):
 
 
 def copy_asn_info_from_library(library, output_model):
+    """
+    Transfer association information from the input library to the output model.
+
+    Parameters
+    ----------
+    library : ModelLibrary
+        The input library of data models.
+
+    output_model : DataModel
+        The output data model to which the association information will be copied.
+    """
     if not hasattr(library, "asn"):
         # No ASN table, occurs when input comes from ModelContainer in spectroscopic modes
         # in this case do nothing; the asn info will be passed along later

jwst/resample/resample_spec.py

@@ -16,7 +16,6 @@
 from stdatamodels.jwst import datamodels
 
 from jwst.assign_wcs.util import compute_scale, wrap_ra
-from jwst.datamodels import ModelContainer
 from jwst.resample import resample_utils
 from jwst.resample.resample import ResampleData
 
@@ -191,7 +190,6 @@ def __init__(self, input_models, output=None, single=False, blendheaders=False,
             self.blank_output.meta.photometry.pixelarea_arcsecsq = (
                 output_pix_area * np.rad2deg(3600)**2)
 
-        self.output_models = ModelContainer()
 
     def build_nirspec_output_wcs(self, input_models, refmodel=None):
         """

jwst/resample/resample_spec_step.py

@@ -135,17 +135,14 @@ def _process_multislit(self, input_models):
             resamp = resample_spec.ResampleSpecData(container, **self.drizpars)
 
             library = ModelLibrary(container, on_disk=False)
-            library = resamp.do_drizzle(library)
-            with library:
-                for i, model in enumerate(library):
-                    container[i] = model
-                    library.shelve(model, modify=False)
-            del library
-
-            for model in container:
-                self.update_slit_metadata(model)
-                update_s_region_spectral(model)
-                result.slits.append(model)
+            drizzled_library = resamp.do_drizzle(library)
+            with drizzled_library:
+                for i, model in enumerate(drizzled_library):
+                    self.update_slit_metadata(model)
+                    update_s_region_spectral(model)
+                    result.slits.append(model)
+                    drizzled_library.shelve(model, i, modify=False)
+            del library, drizzled_library
 
             # Keep the first computed pixel scale ratio for storage
             if self.pixel_scale is not None and pscale_ratio is None:
@@ -211,14 +208,12 @@ def _process_slit(self, input_models):
         resamp = resample_spec.ResampleSpecData(input_models, **self.drizpars)
 
         library = ModelLibrary(input_models, on_disk=False)
-        library = resamp.do_drizzle(library)
-        with library:
-            for i, model in enumerate(library):
-                input_models[i] = model
-                library.shelve(model, modify=False)
-        del library
-
-        result = input_models[0]
+        drizzled_library = resamp.do_drizzle(library)
+        with drizzled_library:
+            result = drizzled_library.borrow(0)
+            drizzled_library.shelve(result, 0, modify=False)
+        del library, drizzled_library
+
         result.meta.bunit_data = input_models[0].meta.bunit_data
         if self.pixel_scale is None:
             result.meta.resample.pixel_scale_ratio = self.pixel_scale_ratio

jwst/resample/resample_step.py

@@ -109,9 +109,6 @@ def process(self, input):
                 else:
                     model.meta.resample.pixel_scale_ratio = resamp.pscale_ratio
                 model.meta.resample.pixfrac = kwargs['pixfrac']
-                # update filename to reflect new product
-                # necessary to get source_catalog output names to match i2d filename
-                # model.meta.filename = self.output_file
                 result.shelve(model)
 
             if len(result) == 1: