Apply suggestions from code review

Co-authored-by: Trevor Hillebrand <[email protected]>

compass/landice/mesh.py

@@ -444,7 +444,7 @@ def get_dist_to_edge_and_gl(self, thk, topg, x, y,
         logger.info('WARNING: window_size was set to a value smaller'
                     ' than high_dist and/or high_dist_bed. Resetting'
                     f' window_size to {max(high_dist, high_dist_bed)}, '
-                    ' which is  max(high_dist, high_dist_bed)')
+                    ' which is max(high_dist, high_dist_bed)')
         window_size = max(high_dist, high_dist_bed)
 
     dx = x[1] - x[0]  # assumed constant and equal in x and y
@@ -971,8 +971,8 @@ def preprocess_ais_data(self, source_gridded_dataset,
 
         tic = time.perf_counter()
         logger.info(f"Beginning interpolation for {field}")
-        # NOTE: Do not need to evaluate the extrapolator at all gridcells.
-        #       Only needed for ice-free gricells, since it's NN extrapolation
+        # NOTE: Do not need to evaluate the extrapolator at all grid cells.
+        #       Only needed for ice-free grid cells, since it's NN extrapolation
         data.variables[field][0, :] = interp(xGrid, yGrid)
         toc = time.perf_counter()
         logger.info(f"Interpolation completed in {toc - tic} seconds")
@@ -1027,7 +1027,7 @@ def interp_gridded2mali(self, source_file, mali_scrip, nProcs, dest_file, proj,
         MALI input file to which data should be remapped
 
     proj: str
-        projection of the source dataset ...
+        projection of the source dataset
 
     variables: str or list of strings
 
@@ -1069,8 +1069,6 @@ def __guess_scrip_name(filename):
     check_call(args, logger=logger)
 
     # Generate remapping weights
-    # Testing shows 5 badger/grizzly nodes works well.
-    # 2 nodes is too few. I have not tested anything in between.
     logger.info('generating gridded dataset -> MPAS weights')
     args = ['srun', '-n', nProcs, 'ESMF_RegridWeightGen',
             '--source', source_scrip,

compass/landice/tests/antarctica/mesh.py

@@ -74,7 +74,7 @@ def run(self):
 
         section_name = 'mesh'
 
-        # do we want to add this to the config file?
+        # TODO: do we want to add this to the config file?
         source_gridded_dataset = 'antarctica_8km_2024_01_29.nc'
 
         bm_updated_gridded_dataset = add_bedmachine_thk_to_ais_gridded_data(
@@ -141,7 +141,7 @@ def run(self):
         interp_gridded2mali(self, bedmachine_dataset, dst_scrip_file, nProcs,
                             self.mesh_filename, src_proj, variables="all")
 
-        # only interpolate a subset of MEASURES varibles onto the MALI mesh
+        # only interpolate a subset of MEaSUREs variables onto the MALI mesh
         measures_vars = ['observedSurfaceVelocityX',
                          'observedSurfaceVelocityY',
                          'observedSurfaceVelocityUncertainty']

compass/landice/tests/greenland/mesh.py

@@ -103,7 +103,7 @@ def run(self):
         interp_gridded2mali(self, bedmachine_dataset, dst_scrip_file, nProcs,
                             self.mesh_filename, src_proj, variables="all")
 
-        # only interpolate a subset of MEASURES varibles onto the MALI mesh
+        # only interpolate a subset of MEaSUREs variables onto the MALI mesh
         measures_vars = ['observedSurfaceVelocityX',
                          'observedSurfaceVelocityY',
                          'observedSurfaceVelocityUncertainty']
@@ -149,7 +149,7 @@ def run(self):
         dHdtErr = np.abs(dHdt) * 0.05
         # Use threshold of |dHdt| > 1.0 to determine invalid data
         mask = np.abs(dHdt) > 1.0
-        # Assign 100% uncertainty where data is missing
+        # Assign very large uncertainty where data is missing
         dHdtErr = dHdtErr.where(~mask, 1.0)
         # Remove ridiculous values
         dHdt = dHdt.where(~mask, 0.0)

compass/landice/tests/greenland/mesh_gen/mesh_gen.cfg

@@ -57,7 +57,7 @@ data_path = /global/cfs/cdirs/fanssie/standard_datasets/GIS_datasets/
 # (default value is for Perlmutter)
 bedmachine_filename = BedMachineGreenland-v5_edits_floodFill_extrap.nc
 
-# filename of the MEASURES ice velocity dataset
+# filename of the MEaSUREs ice velocity dataset
 # (default value is for Perlmutter)
 measures_filename = greenland_vel_mosaic500_extrap.nc
 

docs/developers_guide/landice/framework.rst

@@ -57,9 +57,9 @@ clean up steps after interpolation for the AIS mesh case.
 to the gridded dataset in order to separate the ice sheet from peripheral ice.
 
 :py:func:`compass.landice.mesh.interp_gridded2mali()` interpolates gridded data
-(e.g. BedMachine thickness or MEASURES ice velocity) to a MALI mesh, accounting
+(e.g. BedMachine thickness or MEaSUREs ice velocity) to a MALI mesh, accounting
 for masking of the ice extent to avoid interpolation ramps. This functions works
-for either the Antarctic or Greenland Icesheets. 
+for both Antarctica and Greenland. 
 
 :py:func:`compass.landice.mesh.preprocess_ais_data()` performs adjustments to
 gridded AIS datasets needed for rest of compass workflow to utilize them.