Fix regression tests for TubStatistics field_aggregations requirement

- Add FIELD_AGGREGATIONS to test configs that use TubDataset with config
- Add LAP_SORTING_CRITERIA to test configs that expect gyro_z_agg rankings
- Add FULL_SORTING_STRATEGY constant to tests that need gyro_z_agg in rankings
- Update tests to pass explicit sorting_strategy when testing gyro_z_agg

These tests previously relied on silent defaults that have been removed.

https://claude.ai/code/session_01BkSETqkmCyc5PavsvyAidf

Author: claude

donkeycar/tests/test_course_segmentation_integration.py

@@ -59,7 +59,19 @@ def _create_test_config(self):
         cfg = Config()
         cfg.USE_LAP_0 = False
         cfg.TRAIN_TEST_SPLIT = 0.8
-        cfg.GYRO_Z_INDEX = 1
+        cfg.FIELD_AGGREGATIONS = [
+            {
+                'field': 'car/gyro',
+                'output_key': 'gyro_z_agg',
+                'index': 1,
+                'aggregation': 'avg'
+            }
+        ]
+        cfg.LAP_SORTING_CRITERIA = [
+            {'key': 'time'},
+            {'key': 'distance'},
+            {'key': 'gyro_z_agg'},
+        ]
         return cfg
 
     def _create_test_tub(self):

donkeycar/tests/test_lap_pct_regression.py

@@ -18,6 +18,7 @@
 from donkeycar.parts.tub_v2 import Tub
 from donkeycar.parts.tub_statistics import TubStatistics, FieldAggregationSpec
 from donkeycar.pipeline.types import TubDataset, PctMode
+from donkeycar.pipeline.transformations import SortingStrategy
 
 
 # Standard field aggregation for gyro_z at index 1 (simulator convention)
@@ -31,6 +32,13 @@
     )
 ]
 
+# Sorting strategy that includes time, distance, and gyro_z_agg
+FULL_SORTING_STRATEGY = SortingStrategy([
+    {'key': 'time'},
+    {'key': 'distance'},
+    {'key': 'gyro_z_agg'},
+])
+
 
 class TestLapPerformanceRegression(unittest.TestCase):
     """Regression tests for lap-based training"""
@@ -58,7 +66,14 @@ def _create_test_config(self):
         cfg = Config()
         cfg.USE_LAP_0 = False
         cfg.TRAIN_TEST_SPLIT = 0.8
-        cfg.GYRO_Z_INDEX = 1
+        cfg.FIELD_AGGREGATIONS = [
+            {
+                'field': 'car/gyro',
+                'output_key': 'gyro_z_agg',
+                'index': 1,
+                'aggregation': 'avg'
+            }
+        ]
         return cfg
 
     def test_lap_mode_unchanged(self):
@@ -127,7 +142,8 @@ def test_lap_performance_calculation_unchanged(self):
 
         tub = Tub(self.tub_path, read_only=True)
         self.open_tubs.append(tub)
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
 
         # Calculate lap performance (original method)
         session_lap_rank = stats.calculate_lap_performance()

donkeycar/tests/test_pipeline.py

@@ -31,6 +31,13 @@
     )
 ]
 
+# Sorting strategy that includes time, distance, and gyro_z_agg
+FULL_SORTING_STRATEGY = SortingStrategy([
+    {'key': 'time'},
+    {'key': 'distance'},
+    {'key': 'gyro_z_agg'},
+])
+
 
 def random_records(size: int = 100) -> List[TubRecord]:
     return [random_record() for _ in range(size)]
@@ -241,7 +248,8 @@ def test_current_lap_pct_extension(self):
         tub = self._create_tub_with_data(records)
 
         # Generate lap times
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
         stats.generate_laptimes_from_records()
 
         # Close and reopen as read-only
@@ -251,7 +259,8 @@ def test_current_lap_pct_extension(self):
         tub = Tub(self.test_path, inputs, types, read_only=True)
 
         # Calculate lap performance
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
         session_lap_rank = stats.calculate_lap_performance(use_lap_0=True)
 
         # Test that records can be extended
@@ -275,17 +284,18 @@ def test_current_lap_pct_extension(self):
 
     def test_current_sorting_criteria(self):
         """
-        Test current hardcoded sorting by 'time', 'distance', 'gyro_z_agg'.
+        Test sorting by 'time', 'distance', 'gyro_z_agg' with explicit config.
 
         Validates that:
-        - Laps are sorted by these three criteria
+        - Laps are sorted by these three criteria when configured
         - Sorting is done using itemgetter
         - Rankings are assigned correctly
         """
         records = self._create_oval_track_data(num_laps=5, varying_performance=True)
         tub = self._create_tub_with_data(records)
 
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
         stats.generate_laptimes_from_records()
 
         # Close and reopen
@@ -294,7 +304,8 @@ def test_current_sorting_criteria(self):
         tub.close()
         tub = Tub(self.test_path, inputs, types, read_only=True)
 
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
         performance = stats.calculate_lap_performance(use_lap_0=True)
 
         session_id = list(performance.keys())[0]
@@ -366,10 +377,22 @@ def test_tub_dataset_with_lap_pct(self):
 
         # Create TubDataset with lap_pct enabled
         config = Config()
-        config.GYRO_Z_INDEX = 1
         config.USE_LAP_0 = True
         config.COMPRESS_SESSIONS_FOR_LAP_STATS = False
         config.NUM_BINS_FOR_LAP_STATS = None
+        config.FIELD_AGGREGATIONS = [
+            {
+                'field': 'car/gyro',
+                'output_key': 'gyro_z_agg',
+                'index': 1,
+                'aggregation': 'avg'
+            }
+        ]
+        config.LAP_SORTING_CRITERIA = [
+            {'key': 'time'},
+            {'key': 'distance'},
+            {'key': 'gyro_z_agg'},
+        ]
 
         dataset = TubDataset(config, [self.test_path], add_lap_pct=True)
         records_loaded = dataset.get_records()
@@ -449,12 +472,15 @@ class TestSortingStrategy(unittest.TestCase):
     """Test suite for the new SortingStrategy classes."""
 
     def test_default_sorting_strategy(self):
-        """Test default sorting strategy (time, distance, gyro_z_agg)."""
+        """Test default sorting strategy (time, distance only).
+
+        Note: gyro_z_agg was removed from defaults because it requires
+        explicit field_aggregations configuration.
+        """
         strategy = default_lap_sorting_strategy()
-        self.assertEqual(len(strategy.criteria), 3)
+        self.assertEqual(len(strategy.criteria), 2)
         self.assertEqual(strategy.criteria[0]['key'], 'time')
         self.assertEqual(strategy.criteria[1]['key'], 'distance')
-        self.assertEqual(strategy.criteria[2]['key'], 'gyro_z_agg')
 
     def test_sorting_with_transformation(self):
         """Test sorting with transformation using plain functions."""
@@ -671,10 +697,17 @@ def test_tub_dataset_with_custom_ranking_keys(self):
         tub_path = self._create_test_tub()
 
         config = Config()
-        config.GYRO_Z_INDEX = 1
         config.USE_LAP_0 = True
         config.COMPRESS_SESSIONS_FOR_LAP_STATS = False
         config.NUM_BINS_FOR_LAP_STATS = None
+        config.FIELD_AGGREGATIONS = [
+            {
+                'field': 'car/gyro',
+                'output_key': 'gyro_z_agg',
+                'index': 1,
+                'aggregation': 'avg'
+            }
+        ]
 
         # Use only time and distance for ranking
         custom_keys = ['time', 'distance']

donkeycar/tests/test_segment_performance.py

@@ -19,6 +19,7 @@
 from donkeycar.parts.tub_v2 import Tub
 from donkeycar.parts.tub_statistics import TubStatistics, FieldAggregationSpec
 from donkeycar.pipeline.types import TubRecord
+from donkeycar.pipeline.transformations import SortingStrategy
 
 
 # Standard field aggregation for gyro_z at index 1 (simulator convention)
@@ -32,6 +33,13 @@
     )
 ]
 
+# Sorting strategy that includes time, distance, and gyro_z_agg
+FULL_SORTING_STRATEGY = SortingStrategy([
+    {'key': 'time'},
+    {'key': 'distance'},
+    {'key': 'gyro_z_agg'},
+])
+
 
 class TestSegmentPerformanceCalculation(unittest.TestCase):
     """Test segment performance ranking across laps"""
@@ -160,7 +168,8 @@ def test_segment_performance_structure(self):
         """Test that calculate_segment_performance returns correct structure"""
         tub = Tub(self.tub_path, read_only=True)
         self.open_tubs.append(tub)
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
 
         session_rank = stats.calculate_segment_performance()
 
@@ -198,7 +207,8 @@ def test_segment_ranking_across_laps(self):
         """Test that same segment in different laps gets different rankings"""
         tub = Tub(self.tub_path, read_only=True)
         self.open_tubs.append(tub)
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
 
         session_rank = stats.calculate_segment_performance()
         session_id = list(session_rank.keys())[0]
@@ -223,7 +233,8 @@ def test_segment_0_fastest_in_lap_1(self):
         """Test that segment 0 is ranked fastest in lap 1"""
         tub = Tub(self.tub_path, read_only=True)
         self.open_tubs.append(tub)
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
 
         session_rank = stats.calculate_segment_performance()
         session_id = list(session_rank.keys())[0]
@@ -245,7 +256,8 @@ def test_segment_1_fastest_in_lap_1(self):
         """Test that segment 1 is ranked fastest in lap 1"""
         tub = Tub(self.tub_path, read_only=True)
         self.open_tubs.append(tub)
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
 
         session_rank = stats.calculate_segment_performance()
         session_id = list(session_rank.keys())[0]
@@ -266,7 +278,8 @@ def test_ranking_percentiles(self):
         """Test that rankings are proper percentiles (0.33, 0.67, 1.0)"""
         tub = Tub(self.tub_path, read_only=True)
         self.open_tubs.append(tub)
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
 
         session_rank = stats.calculate_segment_performance()
         session_id = list(session_rank.keys())[0]
@@ -292,7 +305,8 @@ def test_synthetic_best_lap_creation(self):
         """Test that we can create synthetic best lap from best segments"""
         tub = Tub(self.tub_path, read_only=True)
         self.open_tubs.append(tub)
-        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1)
+        stats = TubStatistics(tub, field_aggregations=GYRO_Z_INDEX_1,
+                              sorting_strategy=FULL_SORTING_STRATEGY)
 
         session_rank = stats.calculate_segment_performance()
         session_id = list(session_rank.keys())[0]

donkeycar/tests/test_segment_training_integration.py

@@ -60,8 +60,15 @@ def _create_test_config(self):
         cfg = Config()
         cfg.USE_LAP_0 = False
         cfg.TRAIN_TEST_SPLIT = 0.8
-        cfg.GYRO_Z_INDEX = 1
         cfg.SEGMENT_PCT_MODE = True
+        cfg.FIELD_AGGREGATIONS = [
+            {
+                'field': 'car/gyro',
+                'output_key': 'gyro_z_agg',
+                'index': 1,
+                'aggregation': 'avg'
+            }
+        ]
         return cfg
 
     def test_end_to_end_segment_training_workflow(self):