[Refactor]: Refactor integration tests and add use_cfg flag to run_diags()

.github/workflows/build_workflow.yml

@@ -99,10 +99,18 @@ jobs:
           mamba info
 
       - if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
-        name: Run Tests
+        name: Run Unit Tests
+        run: pytest tests/e3sm_diags
+
+      - if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
+        name: Download Integration Test Data
+        run: python -m tests.integration.download_data
+
+      - if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
+        name: Run Integration Tests
         env:
           CHECK_IMAGES: False
-        run: bash tests/test.sh
+        run: pytest tests/integration
 
   publish-docs:
     if: ${{ github.event_name == 'push' }}

Makefile

@@ -55,6 +55,14 @@ clean-test: ## remove test and coverage artifacts
 	rm -fr .pytest_cache
 	rm -rf .mypy_cache
 
+clean-test-int-res: ## remove integration test results and image check failures
+	rm -rf tests/integration/all_sets_results_test
+	rm -rf tests/integration/image_check_failures
+
+clean-test-int-data:  # remove integration test data and images (expected) -- useful when they are updated
+	rm -rf tests/integration/integration_test_data
+	rm -rf tests/integration/integration_test_images
+
 # Quality Assurance
 # ----------------------
 pre-commit:  # run pre-commit quality assurance checks

docs/source/dev_guide/testing.rst

@@ -56,7 +56,7 @@ The unit and integration tests are run automatically as part of this.
 Complete run test
 -----------------
 
-``tests/complete_run.py`` checks the images generated by all diagnostics to
+``tests/integration/complete_run.py`` checks the images generated by all diagnostics to
 see if any differ from expected.
 This test is not run as part of the unit test suite, because it relies on a large
 quantity of data found on LCRC (Anvil/Chrysalis).
@@ -78,7 +78,7 @@ Now that you have your changes on LCRC, enter your development environment. Then
     .. code::
 
         pip install . # Install your changes
-        python -m unittest tests/complete_run.py
+        pytest tests/integration/complete_run.py
 
 If this test passes, you're done. If it fails however, that means
 your code has changed what the output looks like.
@@ -108,11 +108,11 @@ then you need to update the expected images.
         find . -type f -name '*.png' > ../image_list_all_sets.txt
         cd ..
 
-Run ``python -m unittest tests/complete_run.py`` again. Now, the test should pass.
+Run ``pytest tests/integration/complete_run.py`` again. Now, the test should pass.
 
 After merging your pull request, edit ``README.md``.
 The version should be the version of E3SM Diags you ran
-``python -m unittest tests/complete_run.py`` with,
-the date should be the date you ran ``python -m unittest tests/complete_run.py`` on,
+``pytest tests/integration/complete_run.py`` with,
+the date should be the date you ran ``pytest tests/integration/complete_run.py`` on,
 and the hash should be for the top commit shown by ``git log`` or on
 https://github.com/E3SM-Project/e3sm_diags/commits/main.

e3sm_diags/e3sm_diags_driver.py

@@ -347,15 +347,16 @@ def _collapse_results(parameters: List[List[CoreParameter]]) -> List[CoreParamet
     return output_parameters
 
 
-def main(parameters=[]):
+def main(parameters=[]) -> List[CoreParameter]:
     # Get the diagnostic run parameters
     # ---------------------------------
     parser = CoreParser()
 
     # If no parameters are passed, use the parser args as defaults. Otherwise,
     # create the dictionary of expected parameters.
-    if not parameters:
+    if len(parameters) == 0:
         parameters = get_parameters(parser)
+
     expected_parameters = create_parameter_dict(parameters)
 
     if not os.path.exists(parameters[0].results_dir):
@@ -408,6 +409,8 @@ def main(parameters=[]):
         )
         raise Exception(message)
 
+    return parameters_results
+
 
 if __name__ == "__main__":
     main()

e3sm_diags/parameter/core_parameter.py

@@ -7,6 +7,32 @@
 
 logger = custom_logger(__name__)
 
+# FIXME: There is probably a better way of defining default sets because most of
+# this is repeated in SETS_TO_PARAMETERS and SETS_TO_PARSERS.
+# Also integration tests will break if "mp_partition" is included because
+# we did not take it into account yet.
+DEFAULT_SETS = [
+    "zonal_mean_xy",
+    "zonal_mean_2d",
+    "zonal_mean_2d_stratosphere",
+    "meridional_mean_2d",
+    "lat_lon",
+    "polar",
+    "area_mean_time_series",
+    "cosp_histogram",
+    "enso_diags",
+    "qbo",
+    "streamflow",
+    "diurnal_cycle",
+    "arm_diags",
+    "tc_analysis",
+    "annual_cycle_zonal_mean",
+    "lat_lon_land",
+    "lat_lon_river",
+    "aerosol_aeronet",
+    "aerosol_budget",
+]
+
 
 class CoreParameter:
     def __init__(self):
@@ -58,28 +84,8 @@ def __init__(self):
         # 'model_vs_obs' (by default), 'model_vs_model', or 'obs_vs_obs'.
         self.run_type: str = "model_vs_obs"
 
-        # A list of the sets to be run. Default is all sets
-        self.sets: List[str] = [
-            "zonal_mean_xy",
-            "zonal_mean_2d",
-            "zonal_mean_2d_stratosphere",
-            "meridional_mean_2d",
-            "lat_lon",
-            "polar",
-            "area_mean_time_series",
-            "cosp_histogram",
-            "enso_diags",
-            "qbo",
-            "streamflow",
-            "diurnal_cycle",
-            "arm_diags",
-            "tc_analysis",
-            "annual_cycle_zonal_mean",
-            "lat_lon_land",
-            "lat_lon_river",
-            "aerosol_aeronet",
-            "aerosol_budget",
-        ]
+        # A list of the sets to be run, by default all sets.
+        self.sets: List[str] = DEFAULT_SETS
 
         # The current set that is being ran when looping over sets in
         # `e3sm_diags_driver.run_diag()`.

e3sm_diags/plot/cartopy/arm_diags_plot.py

@@ -174,6 +174,7 @@ def plot_convection_onset_statistics(
         var_time_absolute = cwv.getTime().asComponentTime()
         time_interval = int(var_time_absolute[1].hour - var_time_absolute[0].hour)
 
+        # FIXME: UnboundLocalError: local variable 'cwv_max' referenced before assignment
         number_of_bins = int(np.ceil((cwv_max - cwv_min) / bin_width))
         bin_center = np.arange(
             (cwv_min + (bin_width / 2)),