Suppress warnings about NaNs in input data from TweakRegStep

CHANGES.rst

@@ -136,14 +136,23 @@ residual_fringe
 - Fix a bug with 1d residual fringe zeroing out negative fluxes instead of
   ignoring them. [#8261]
 
+source_catalog
+--------------
+
+- Suppress warnings from ``photutils.background.Background2D`` regarding
+  NaNs in the input data. [#8308]
+
 tweakreg
 --------
 
 - Update ``sregion`` after WCS corrections are applied. [#8158]
 
-- Added option to choose IRAFStarFinder and segmentation.SourceFinder
+- Add option to choose IRAFStarFinder and segmentation.SourceFinder
   instead of DAOStarFinder and exposed star finder parameters. [#8203]
 
+- Suppress warnings from ``photutils.background.Background2D`` regarding
+  NaNs in the input data. [#8308]
+
 
 1.13.4 (2024-01-25)
 ===================

jwst/source_catalog/detection.py

@@ -70,23 +70,26 @@ def _background2d(self):
         bkg_estimator = MedianBackground()
         filter_size = (3, 3)
 
-        try:
-            bkg = Background2D(self.data, self.box_size,
-                               filter_size=filter_size,
-                               coverage_mask=self.coverage_mask,
-                               sigma_clip=sigma_clip,
-                               bkg_estimator=bkg_estimator)
-        except ValueError:
-            # use the entire unmasked array
-            bkg = Background2D(self.data, self.data.shape,
-                               filter_size=filter_size,
-                               coverage_mask=self.coverage_mask,
-                               sigma_clip=sigma_clip,
-                               bkg_estimator=bkg_estimator,
-                               exclude_percentile=100.)
-            log.info('Background could not be estimated in meshes. '
-                     'Using the entire unmasked array for background '
-                     f'estimation: bkg_boxsize={self.data.shape}.')
+        # All data have NaNs.  Suppress warnings about them.
+        with warnings.catch_warnings():
+            warnings.filterwarnings(action="ignore", category=AstropyUserWarning)
+            try:
+                bkg = Background2D(self.data, self.box_size,
+                                   filter_size=filter_size,
+                                   coverage_mask=self.coverage_mask,
+                                   sigma_clip=sigma_clip,
+                                   bkg_estimator=bkg_estimator)
+            except ValueError:
+                # use the entire unmasked array
+                bkg = Background2D(self.data, self.data.shape,
+                                   filter_size=filter_size,
+                                   coverage_mask=self.coverage_mask,
+                                   sigma_clip=sigma_clip,
+                                   bkg_estimator=bkg_estimator,
+                                   exclude_percentile=100.)
+                log.info('Background could not be estimated in meshes. '
+                         'Using the entire unmasked array for background '
+                         f'estimation: bkg_boxsize={self.data.shape}.')
 
         return bkg
 
@@ -150,8 +153,9 @@ def convolve_data(data, kernel_fwhm, mask=None):
     """
     kernel = make_kernel(kernel_fwhm)
 
+    # All data have NaNs.  Supress warnings about them.
     with warnings.catch_warnings():
-        warnings.simplefilter('ignore', AstropyUserWarning)
+        warnings.filterwarnings(action="ignore", category=AstropyUserWarning)
         return convolve(data, kernel, mask=mask, normalize_kernel=True)
 
 

jwst/tweakreg/tweakreg_catalog.py

@@ -200,7 +200,7 @@ def make_tweakreg_catalog(model, snr_threshold, bkg_boxsize=400, starfinder='dao
     else:
         raise ValueError(f"Unknown starfinder type: {starfinder}")
 
-    # Mask the non-imaging area (e.g. MIRI)
+    # Mask the non-imaging area, e.g. reference pixels and MIRI non-science area
     coverage_mask = ((dqflags.pixel['NON_SCIENCE'] +
                       dqflags.pixel['DO_NOT_USE']) &
                      model.dq).astype(bool)