Move error for empty image_parameters trait into FeatureAggregator

src/ctapipe/image/statistics.py

@@ -10,7 +10,7 @@
     StatisticsContainer,
 )
 from ..core import Component, FeatureGenerator, QualityQuery
-from ..core.traits import List, Tuple, Unicode
+from ..core.traits import List, TraitError, Tuple, Unicode
 from ..vectorization import (
     collect_features,
     get_subarray_index,
@@ -156,6 +156,9 @@ def aggregate_table(self, mono_parameters: Table) -> Table:
         Construct table containing aggregated image parameters
         from table of telescope events.
         """
+        if len(self.image_parameters) == 0:
+            raise TraitError("No DL1 image parameters to aggregate are specified.")
+
         mono_parameters = self.feature_generator(mono_parameters)
         passes_cuts = self.quality_query.get_table_mask(mono_parameters)
 

src/ctapipe/tools/aggregate_features.py

@@ -4,7 +4,7 @@
 import tables
 from tqdm.auto import tqdm
 
-from ..core import Tool, ToolConfigurationError
+from ..core import Tool
 from ..core.traits import Bool, Integer, Path, flag
 from ..image import FeatureAggregator
 from ..io import HDF5Merger, TableLoader, write_table
@@ -118,10 +118,6 @@ def setup(self):
             )
         )
         self.aggregator = FeatureAggregator(parent=self)
-        if len(self.aggregator.image_parameters) == 0:
-            raise ToolConfigurationError(
-                "No image parameters to aggregate are specified."
-            )
 
     def start(self):
         """Aggregate DL1 image parameters for input tables."""

src/ctapipe/tools/process.py

@@ -7,7 +7,7 @@
 from tqdm.auto import tqdm
 
 from ..calib import CameraCalibrator, GainSelector
-from ..core import QualityQuery, Tool, ToolConfigurationError
+from ..core import QualityQuery, Tool
 from ..core.traits import Bool, classes_with_traits, flag
 from ..image import FeatureAggregator, ImageCleaner, ImageModifier, ImageProcessor
 from ..image.extractor import ImageExtractor
@@ -172,7 +172,6 @@ class ProcessorTool(Tool):
     )
 
     def setup(self):
-
         # setup components:
         self.event_source = self.enter_context(EventSource(parent=self))
 
@@ -305,7 +304,6 @@ def start(self):
             unit="ev",
             disable=not self.progress_bar,
         ):
-
             self.log.debug("Processessing event_id=%s", event.index.event_id)
 
             if not self.event_type_filter(event):
@@ -330,10 +328,6 @@ def start(self):
                 self.process_shower(event)
 
             if self.write.write_dl1_aggregates:
-                if len(self.aggregate.image_parameters) == 0:
-                    raise ToolConfigurationError(
-                        "No DL1 image parameters to aggregate are specified."
-                    )
                 self.aggregate(event)
 
             self.write(event)

src/ctapipe/tools/tests/test_aggregate_features.py

@@ -3,6 +3,7 @@
 import pytest
 
 from ctapipe.core import ToolConfigurationError, run_tool
+from ctapipe.core.traits import TraitError
 from ctapipe.io import TableLoader
 
 
@@ -14,8 +15,7 @@ def test_aggregate_features(dl2_shower_geometry_file_lapalma, tmp_path):
     config_path = tmp_path / "config.json"
 
     with pytest.raises(
-        ToolConfigurationError,
-        match="No image parameters to aggregate are specified.",
+        TraitError, match="No DL1 image parameters to aggregate are specified."
     ):
         run_tool(
             AggregateFeatures(),
@@ -72,10 +72,11 @@ def test_aggregate_features(dl2_shower_geometry_file_lapalma, tmp_path):
             dl2=False,
             simulated=False,
         )
-        assert "hillas_length_max" in events.colnames
-        assert "hillas_length_min" in events.colnames
-        assert "hillas_length_mean" in events.colnames
-        assert "hillas_length_std" in events.colnames
-        assert "timing_slope_mean" in events.colnames
-        assert "HillasReconstructor_tel_impact_distance_mean" in events.colnames
-        assert "hillas_abs_skewness_mean" in events.colnames
+        for col in [
+            "hillas_length",
+            "timing_slope",
+            "HillasReconstructor_tel_impact_distance",
+            "hillas_abs_skewness",
+        ]:
+            for suffix in ["max", "min", "mean", "std"]:
+                assert f"{col}_{suffix}" in events.colnames