Fix evaluate tests

tests/test_unit/test_evaluate_tracker.py

@@ -7,33 +7,40 @@
 
 
 @pytest.fixture
-def evaluation():
-    test_csv_file = Path(__file__).parents[1] / "data" / "gt_test.csv"
+def tracker_evaluate_interface():
+    annotations_file_csv = Path(__file__).parents[1] / "data" / "gt_test.csv"
     return TrackerEvaluate(
-        test_csv_file,
-        predicted_boxes_id=[],
+        annotations_file_csv,
+        predicted_boxes_dict={},
         iou_threshold=0.1,
         tracking_output_dir="/path/output",
     )
 
 
-def test_get_ground_truth_data(evaluation):
-    ground_truth_dict = evaluation.get_ground_truth_data()
+def test_get_ground_truth_data_structure(tracker_evaluate_interface):
+    """Test the loaded ground truth data has the expected structure."""
+    # Get ground truth data dict
+    ground_truth_dict = tracker_evaluate_interface.get_ground_truth_data()
 
+    # check type
     assert isinstance(ground_truth_dict, dict)
+    # check it is a nested dictionary
     assert all(
         isinstance(frame_data, dict)
         for frame_data in ground_truth_dict.values()
     )
 
+    # check data types for values in nested dictionary
     for frame_number, data in ground_truth_dict.items():
         assert isinstance(frame_number, int)
         assert isinstance(data["bbox"], np.ndarray)
         assert isinstance(data["id"], np.ndarray)
         assert data["bbox"].shape[1] == 4
 
 
-def test_ground_truth_data_from_csv(evaluation):
+def test_ground_truth_data_values(tracker_evaluate_interface):
+    """Test ground truth data holds expected values."""
+    # Define expected ground truth data
     expected_data = {
         11: {
             "bbox": np.array(
@@ -53,25 +60,33 @@ def test_ground_truth_data_from_csv(evaluation):
         },
     }
 
-    ground_truth_dict = evaluation.get_ground_truth_data()
+    # Get ground truth data dict
+    ground_truth_dict = tracker_evaluate_interface.get_ground_truth_data()
 
-    for frame_number, expected_frame_data in expected_data.items():
-        assert frame_number in ground_truth_dict
+    # Check if ground truth data matches expected values
+    for expected_frame_number, expected_frame_data in expected_data.items():
+        # check expected key is present
+        assert expected_frame_number in ground_truth_dict
 
-        assert len(ground_truth_dict[frame_number]["bbox"]) == len(
+        # check n of bounding boxes per frame matches the expected value
+        assert len(ground_truth_dict[expected_frame_number]["bbox"]) == len(
             expected_frame_data["bbox"]
         )
+
+        # check bbox arrays match the expected values
         for bbox, expected_bbox in zip(
-            ground_truth_dict[frame_number]["bbox"],
+            ground_truth_dict[expected_frame_number]["bbox"],
             expected_frame_data["bbox"],
         ):
             assert np.allclose(
                 bbox, expected_bbox
-            ), f"Frame {frame_number}, bbox mismatch"
+            ), f"Frame {expected_frame_number}, bbox mismatch"
 
+        # check id arrays match the expected values
         assert np.array_equal(
-            ground_truth_dict[frame_number]["id"], expected_frame_data["id"]
-        ), f"Frame {frame_number}, id mismatch"
+            ground_truth_dict[expected_frame_number]["id"],
+            expected_frame_data["id"],
+        ), f"Frame {expected_frame_number}, id mismatch"
 
 
 @pytest.mark.parametrize(
@@ -223,11 +238,19 @@ def test_ground_truth_data_from_csv(evaluation):
     ],
 )
 def test_count_identity_switches(
-    evaluation, prev_frame_id_map, current_frame_id_map, expected_output
+    tracker_evaluate_interface,
+    prev_frame_id_map,
+    current_frame_id_map,
+    expected_output,
 ):
-    evaluation.last_known_predicted_ids = {1: 11, 2: 12, 3: 13, 4: 14}
+    tracker_evaluate_interface.last_known_predicted_ids = {
+        1: 11,
+        2: 12,
+        3: 13,
+        4: 14,
+    }
     assert (
-        evaluation.count_identity_switches(
+        tracker_evaluate_interface.count_identity_switches(
             prev_frame_id_map, current_frame_id_map
         )
         == expected_output
@@ -243,11 +266,11 @@ def test_count_identity_switches(
         ([0, 0, 10, 10], [5, 15, 15, 25], 0.0),
     ],
 )
-def test_calculate_iou(box1, box2, expected_iou, evaluation):
+def test_calculate_iou(box1, box2, expected_iou, tracker_evaluate_interface):
     box1 = np.array(box1)
     box2 = np.array(box2)
 
-    iou = evaluation.calculate_iou(box1, box2)
+    iou = tracker_evaluate_interface.calculate_iou(box1, box2)
 
     # Check if IoU matches expected value
     assert iou == pytest.approx(expected_iou, abs=1e-2)
@@ -484,7 +507,7 @@ def test_evaluate_mota(
     pred_data,
     prev_frame_id_map,
     expected_output,
-    evaluation,
+    tracker_evaluate_interface,
 ):
     (
         mota,
@@ -494,7 +517,7 @@ def test_evaluate_mota(
         num_switches,
         total_gt,
         _,
-    ) = evaluation.evaluate_mota(
+    ) = tracker_evaluate_interface.evaluate_mota(
         gt_data,
         pred_data,
         0.1,  # iou_threshold