Translate tests: no threshold analysis by default

ndsl/stencils/testing/README.md

@@ -83,4 +83,4 @@ Upon failure, the test will drop a `netCDF` file in a `./.translate-errors` dire
 
 ## Environment variables
 
-- `PACE_TEST_N_THRESHOLD_SAMPLES`: Upon failure the system will try to perturb the output in an attempt to check for numerical instability. This means re-running the test for N samples. Default is `10`, `0` or less turns this feature off.
+- `NDSL_TEST_N_THRESHOLD_SAMPLES`: Upon failure the system will try to perturb the output in an attempt to check for numerical instability. This means re-running the test for N samples. Default is `0`, which turns this feature off.

ndsl/stencils/testing/test_translate.py

@@ -25,6 +25,7 @@
 OUTDIR = "./.translate-outputs"
 GPU_MAX_ERR = 1e-10
 GPU_NEAR_ZERO = 1e-15
+N_THRESHOLD_SAMPLES = int(os.getenv("NDSL_TEST_N_THRESHOLD_SAMPLES", 0))
 
 
 def platform():
@@ -89,7 +90,7 @@ def process_override(threshold_overrides, testobj, test_name, backend):
                 testobj.skip_test = bool(match["skip_test"])
         elif len(matches) > 1:
             raise Exception(
-                "misconfigured threshold overrides file, more than 1 specification for "
+                "Misconfigured threshold overrides file, more than 1 specification for "
                 + test_name
                 + " with backend="
                 + backend
@@ -98,9 +99,6 @@ def process_override(threshold_overrides, testobj, test_name, backend):
             )
 
 
-N_THRESHOLD_SAMPLES = int(os.getenv("PACE_TEST_N_THRESHOLD_SAMPLES", 10))
-
-
 def get_thresholds(testobj, input_data):
     _get_thresholds(testobj.compute, input_data)
 
@@ -158,7 +156,7 @@ def test_sequential_savepoint(
 ):
     if case.testobj is None:
         pytest.xfail(
-            f"no translate object available for savepoint {case.savepoint_name}"
+            f"No translate object available for savepoint {case.savepoint_name}."
         )
     stencil_config = StencilConfig(
         compilation_config=CompilationConfig(backend=backend),
@@ -178,7 +176,7 @@ def test_sequential_savepoint(
     if case.testobj.skip_test:
         return
     if not case.exists:
-        pytest.skip(f"Data at rank {case.grid.rank} does not exists")
+        pytest.skip(f"Data at rank {case.grid.rank} does not exist.")
     input_data = dataset_to_dict(case.ds_in)
     input_names = (
         case.testobj.serialnames(case.testobj.in_vars["data_vars"])
@@ -188,7 +186,7 @@ def test_sequential_savepoint(
         input_data = {name: input_data[name] for name in input_names}
     except KeyError as e:
         raise KeyError(
-            f"Variable {e} was described in the translate test but cannot be found in the NetCDF"
+            f"Variable {e} was described in the translate test but cannot be found in the NetCDF."
         )
     original_input_data = copy.deepcopy(input_data)
     # give the user a chance to load data from other savepoints to allow
@@ -208,7 +206,7 @@ def test_sequential_savepoint(
         try:
             ref_data = all_ref_data[varname]
         except KeyError:
-            raise KeyError(f"Output {varname} couldn't be found in output data")
+            raise KeyError(f"Output {varname} couldn't be found in output data.")
         if hasattr(case.testobj, "subset_output"):
             ref_data = case.testobj.subset_output(varname, ref_data)
         with subtests.test(varname=varname):

ndsl/stencils/testing/translate.py

@@ -85,14 +85,14 @@ def setup(self, inputs) -> None:
 
     def compute_func(self, **inputs) -> Optional[dict[str, Any]]:
         """Compute function to transform the dictionary of `inputs`.
-        Must return a dictionnary of updated variables"""
+        Must return a dictionary of updated variables"""
         raise NotImplementedError("Implement a child class compute method")
 
     def compute(self, inputs) -> dict[str, Any]:
-        """Transform inputs from NetCDF to gt4py.storagers, run compute_func then slice
+        """Transform inputs from NetCDF to gt4py.storages, run compute_func then slice
         the outputs based on specifications.
 
-        Return: Dictonnary of storages reshaped for comparison
+        Return: Dictionary of storages reshaped for comparison
         """
         self.setup(inputs)
         return self.slice_output(self.compute_from_storage(inputs))
@@ -201,7 +201,7 @@ def collect_start_indices(self, datashape, varinfo):
     def make_storage_data_input_vars(
         self, inputs, storage_vars=None, dict_4d=True
     ) -> None:
-        """From a set of raw inputs (straight from NetCDF), use the `in_vars` dictionnary to update inputs to
+        """From a set of raw inputs (straight from NetCDF), use the `in_vars` dictionary to update inputs to
         their configured shape.
 
         Return: None