Refactor filtering test (#287)

neuroinformatics-unit · Aug 29, 2024 · f47d6e7 · f47d6e7
1 parent 9612951
commit f47d6e7
Showing 1 changed file with 16 additions and 22 deletions.
diff --git a/tests/test_unit/test_filtering.py b/tests/test_unit/test_filtering.py
@@ -157,25 +157,19 @@ def test_filter_on_position(
     assert not position_filtered.equals(valid_input_dataset.position)
 
 
-# Expected number of nans in the position array per individual,
-# for each dataset
-expected_n_nans_in_position_per_indiv = {
-    "valid_poses_dataset": {0: 0, 1: 0},
-    # filtering should not introduce nans if input has no nans
-    "valid_bboxes_dataset": {0: 0, 1: 0},
-    # filtering should not introduce nans if input has no nans
-    "valid_poses_dataset_with_nan": {0: 7, 1: 0},
-    # individual with index 0 has 7 frames with nans in position after
-    # filtering individual with index 1 has no nans after filtering
-    "valid_bboxes_dataset_with_nan": {0: 7, 1: 0},
-    # individual with index 0 has 7 frames with nans in position after
-    # filtering individual with index 0 has no nans after filtering
-}
-
-
+# Expected number of nans in the position array per
+# individual, after applying a filter with window size 3
 @pytest.mark.parametrize(
-    ("valid_dataset, expected_n_nans_in_position_per_indiv"),
-    [(k, v) for k, v in expected_n_nans_in_position_per_indiv.items()],
+    ("valid_dataset, expected_nans_in_filtered_position_per_indiv"),
+    [
+        (
+            "valid_poses_dataset",
+            {0: 0, 1: 0},
+        ),  # filtering should not introduce nans if input has no nans
+        ("valid_bboxes_dataset", {0: 0, 1: 0}),
+        ("valid_poses_dataset_with_nan", {0: 7, 1: 0}),
+        ("valid_bboxes_dataset_with_nan", {0: 7, 1: 0}),
+    ],
 )
 @pytest.mark.parametrize(
     ("filter_func, filter_kwargs"),
@@ -188,7 +182,7 @@ def test_filter_with_nans_on_position(
     filter_func,
     filter_kwargs,
     valid_dataset,
-    expected_n_nans_in_position_per_indiv,
+    expected_nans_in_filtered_position_per_indiv,
     helpers,
     request,
 ):
@@ -199,7 +193,7 @@ def test_filter_with_nans_on_position(
     def _assert_n_nans_in_position_per_individual(
         valid_input_dataset,
         position_filtered,
-        expected_n_nans_in_position_per_indiv,
+        expected_nans_in_filt_position_per_indiv,
     ):
         # compute n nans in position after filtering per individual
         n_nans_after_filtering_per_indiv = {
@@ -210,7 +204,7 @@ def _assert_n_nans_in_position_per_individual(
         # check number of nans per indiv is as expected
         for i in range(valid_input_dataset.dims["individuals"]):
             assert n_nans_after_filtering_per_indiv[i] == (
-                expected_n_nans_in_position_per_indiv[i]
+                expected_nans_in_filt_position_per_indiv[i]
                 * valid_input_dataset.dims["space"]
                 * valid_input_dataset.dims.get("keypoints", 1)
             )
@@ -225,7 +219,7 @@ def _assert_n_nans_in_position_per_individual(
     _assert_n_nans_in_position_per_individual(
         valid_input_dataset,
         position_filtered,
-        expected_n_nans_in_position_per_indiv,
+        expected_nans_in_filtered_position_per_indiv,
     )
 
     # if input had nans,