Dont use subarray features for the ml unit tests

- Files with the impact reconstructor applied have a differing amount of tables in the dl1 and the dl2 group. See #1961 for details. This breaks the unit tests as it tries to apply the model to telescopes without dl1 information available Co-authored-by: Noah Biederbeck <[email protected]>
cta-observatory · Oct 27, 2022 · 3ca9bc5 · 3ca9bc5
1 parent 692f81a
commit 3ca9bc5
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Showing 2 changed files with 3 additions and 7 deletions.
diff --git a/ctapipe/ml/tools/tests/test_apply.py b/ctapipe/ml/tools/tests/test_apply.py
@@ -3,15 +3,13 @@
 import shutil
 
 
-def test_apply_energy_regressor(
-    energy_regressor_path, dl2_shower_geometry_file, tmp_path
-):
+def test_apply_energy_regressor(energy_regressor_path, dl1_parameters_file, tmp_path):
     from ctapipe.ml.tools.apply_energy_regressor import ApplyEnergyRegressor
 
-    input_path = tmp_path / dl2_shower_geometry_file.name
+    input_path = tmp_path / dl1_parameters_file.name
 
     # create copy to not mutate common test file
-    shutil.copy2(dl2_shower_geometry_file, input_path)
+    shutil.copy2(dl1_parameters_file, input_path)
 
     ret = run_tool(
         ApplyEnergyRegressor(),

diff --git a/ctapipe/resources/ml-config.yaml b/ctapipe/resources/ml-config.yaml
@@ -21,7 +21,6 @@ TrainEnergyRegressor:
       - concentration_cog
       - concentration_core
       - morphology_num_pixels
-      - HillasReconstructor_average_intensity
       - mirror_area
 
 
@@ -48,5 +47,4 @@ TrainParticleIdClassifier:
       - concentration_cog
       - concentration_core
       - morphology_num_pixels
-      - HillasReconstructor_average_intensity
       - mirror_area