Support test data in benchmark workflows

.github/workflows/benchmark.yml

@@ -10,6 +10,10 @@ jobs:
   benchmark:
     runs-on: ubuntu-latest
 
+    env:
+      IRIS_TEST_DATA_DIR: benchmarks/iris-test-data
+      OVERRIDE_TEST_DATA_REPOSITORY: ${IRIS_TEST_DATA_DIR}/test_data
+
     steps:
       # Checks-out your repository under $GITHUB_WORKSPACE, so your job can access it
       - uses: actions/checkout@v2
@@ -38,6 +42,27 @@ jobs:
           key: ${{ runner.os }}-${{ github.sha }}
           restore-keys: ${{ runner.os }}
 
+      - name: Get test data version
+        run: |
+          echo "IRIS_TEST_DATA_VERSION=$(wget --quiet -O - https://raw.githubusercontent.com/SciTools/iris-test-data/master/version.txt)" >> $GITHUB_ENV
+
+      # - name: Cache test data directory
+      #   id: cache-test-data
+      #   uses: actions/cache@v2
+      #   with:
+      #     path: |
+      #       ${{ env.IRIS_TEST_DATA_DIR }}
+      #     key: 
+      #       test-data-${{ env.IRIS_TEST_DATA_VERSION }}
+
+      - name: Fetch the test data
+        # if: steps.cache-test-data.outputs.cache-hit != 'true'
+        run: |
+          wget --quiet https://github.com/SciTools/iris-test-data/archive/v${IRIS_TEST_DATA_VERSION}.zip -O iris-test-data.zip
+          unzip -q iris-test-data.zip
+          mkdir --parents ${IRIS_TEST_DATA_DIR}
+          mv iris-test-data-${IRIS_TEST_DATA_VERSION} ${IRIS_TEST_DATA_DIR}
+
       - name: Run CI benchmarks
         run: |
           mkdir --parents benchmarks/.asv

benchmarks/benchmarks/regridding.py

@@ -0,0 +1,42 @@
+"""
+This file currently exists as a simple demonstration of Airspeed Velocity
+performance testing. it is expected to be expanded/replaced in future.
+
+"""
+
+# import iris tests first so that some things can be initialised before
+# importing anything else.
+from iris import tests
+
+import iris
+from iris.analysis import AreaWeighted
+
+
+@tests.skip_data
+class RegriddingTests:
+    def setup(self):
+        # Prepare a cube and a regridding scheme.
+        cube_file_path = tests.get_data_path(
+            ["NetCDF", "global", "xyt", "SMALL_hires_wind_u_for_ipcc4.nc"]
+        )
+        # cube_file_path = tests.get_data_path(
+        #     ["NetCDF", "GloSea", "glosea_bm.nc"]
+        # )
+        self.cube = iris.load_cube(cube_file_path)
+
+        template_file_path = tests.get_data_path(
+            ["NetCDF", "global", "xyt", "SMALL_hires_wind_u_for_ipcc4.nc"]
+        )
+        # template_file_path = tests.get_data_path(
+        #     ["NetCDF", "GloSea", "template_regrid.nc"]
+        # )
+        self.template_cube = iris.load_cube(template_file_path)
+
+        # Chunked data makes the regridder run repeatedly
+        self.cube.data = self.cube.lazy_data().rechunk((1, -1, -1))
+
+    def time_regrid_area_w(self):
+        # Regrid the cube onto the template.
+        out = self.cube.regrid(self.template_cube, AreaWeighted())
+        # Realise the data
+        out.data