Fix parallelization issues

src/toast/ops/interpolate_healpix.py

@@ -174,17 +174,21 @@ def _exec(self, data, detectors=None, **kwargs):
         # timestreams.
 
         world_comm = data.comm.comm_world
-        world_rank = world_comm.rank
+        if world_comm is None:
+            world_rank = 0
+        else:
+            world_rank = world_comm.rank
 
         for file_name, map_name in zip(self.file_names, self.map_names):
             if map_name not in self.maps:
                 if world_rank == 0:
                     m = np.atleast_2d(read_healpix(file_name, None, dtype=np.float32))
-                    mshape = m.shape
+                    map_shape = m.shape
                 else:
                     m = None
-                    mshape = None
-                map_shape = world_comm.bcast(mshape)
+                    map_shape = None
+                if world_comm is not None:
+                    map_shape = world_comm.bcast(map_shape)
                 self.maps[map_name] = MPIShared(map_shape, np.float32, world_comm)
                 self.maps[map_name].set(m)
 

src/toast/tests/ops_interpolate_healpix.py

@@ -47,14 +47,14 @@ def test_interpolate(self):
         )
         weights.apply(data)
 
+        hpix_file = os.path.join(self.outdir, "fake.fits")
         if data.comm.comm_world is None or data.comm.comm_world.rank == 0:
             # Create a smooth sky
             lmax = 3 * pixels.nside
             cls = np.ones([4, lmax + 1])
             np.random.seed(98776)
             fake_sky = hp.synfast(cls, pixels.nside, fwhm=np.radians(30))
             # Write this to a file
-            hpix_file = os.path.join(self.outdir, "fake.fits")
             hp.write_map(hpix_file, fake_sky)
 
         # Scan the map from the file