Inflate benchmark data to ensure laziness.

Author: trexfeathers

benchmarks/asv.conf.json

@@ -4,7 +4,6 @@
     "project_url": "https://github.com/SciTools/iris",
     "repo": "..",
     "environment_type": "conda-delegated",
-    "conda_channels": ["conda-forge", "defaults"],
     "show_commit_url": "http://github.com/scitools/iris/commit/",
     "branches": ["upstream/main"],
 

benchmarks/asv_delegated_conda.py

@@ -66,6 +66,8 @@ def __init__(
             ignored.append("`requirements`")
         if tagged_env_vars:
             ignored.append("`tagged_env_vars`")
+        if conf.conda_channels:
+            ignored.append("conda_channels")
         if conf.conda_environment_file:
             ignored.append("`conda_environment_file`")
         message = (
@@ -75,6 +77,8 @@ def __init__(
         log.warning(message)
         requirements = {}
         tagged_env_vars = {}
+        # All that is required to create ASV's bare-bones environment.
+        conf.conda_channels = ["defaults"]
         conf.conda_environment_file = None
 
         super().__init__(conf, python, requirements, tagged_env_vars)

benchmarks/benchmarks/experimental/ugrid/regions_combine.py

@@ -30,7 +30,7 @@
 class MixinCombineRegions:
     # Characterise time taken + memory-allocated, for various stages of combine
     # operations on cubesphere-like test data.
-    params = [4, 500]
+    params = [50, 500]
     param_names = ["cubesphere-N"]
 
     def _parametrised_cache_filename(self, n_cubesphere, content_name):

benchmarks/benchmarks/load/__init__.py

@@ -27,7 +27,7 @@ class LoadAndRealise:
     # For data generation
     timeout = 600.0
     params = [
-        [(2, 2, 2), (1280, 960, 5), (2, 2, 1000)],
+        [(50, 50, 2), (1280, 960, 5), (2, 2, 1000)],
         [False, True],
         ["FF", "PP", "NetCDF"],
     ]

benchmarks/benchmarks/load/ugrid.py

@@ -77,7 +77,7 @@ class DataRealisation:
     warmup_time = 0.0
     timeout = 300.0
 
-    params = [1, int(2e5)]
+    params = [int(1e4), int(2e5)]
     param_names = ["number of faces"]
 
     def setup_common(self, **kwargs):

benchmarks/benchmarks/save.py

@@ -21,7 +21,7 @@
 
 
 class NetcdfSave:
-    params = [[1, 600], [False, True]]
+    params = [[50, 600], [False, True]]
     param_names = ["cubesphere-N", "is_unstructured"]
 
     def setup(self, n_cubesphere, is_unstructured):