Update tests/metrics/test_compute_average_precision.py

Co-authored-by: Eric Kerfoot <[email protected]> Signed-off-by: YunLiu <[email protected]>
Project-MONAI · Feb 19, 2025 · ccca17d · ccca17d
1 parent 35aca33
commit ccca17d
Showing 1 changed file with 16 additions and 32 deletions.
diff --git a/tests/metrics/test_compute_average_precision.py b/tests/metrics/test_compute_average_precision.py
@@ -116,25 +116,24 @@
     float("nan"),
 ]
 
+ALL_TESTS = [
+    TEST_CASE_1,
+    TEST_CASE_2,
+    TEST_CASE_3,
+    TEST_CASE_4,
+    TEST_CASE_5,
+    TEST_CASE_6,
+    TEST_CASE_7,
+    TEST_CASE_8,
+    TEST_CASE_9,
+    TEST_CASE_10,
+    TEST_CASE_11,
+    TEST_CASE_12,
+]
 
 class TestComputeAveragePrecision(unittest.TestCase):
 
-    @parameterized.expand(
-        [
-            TEST_CASE_1,
-            TEST_CASE_2,
-            TEST_CASE_3,
-            TEST_CASE_4,
-            TEST_CASE_5,
-            TEST_CASE_6,
-            TEST_CASE_7,
-            TEST_CASE_8,
-            TEST_CASE_9,
-            TEST_CASE_10,
-            TEST_CASE_11,
-            TEST_CASE_12,
-        ]
-    )
+    @parameterized.expand(ALL_TESTS)
     def test_value(self, y_pred, y, softmax, to_onehot, average, expected_value):
         y_pred_trans = Compose([ToTensor(), Activations(softmax=softmax)])
         y_trans = Compose([ToTensor(), AsDiscrete(to_onehot=to_onehot)])
@@ -143,22 +142,7 @@ def test_value(self, y_pred, y, softmax, to_onehot, average, expected_value):
         result = compute_average_precision(y_pred=y_pred, y=y, average=average)
         np.testing.assert_allclose(expected_value, result, rtol=1e-5)
 
-    @parameterized.expand(
-        [
-            TEST_CASE_1,
-            TEST_CASE_2,
-            TEST_CASE_3,
-            TEST_CASE_4,
-            TEST_CASE_5,
-            TEST_CASE_6,
-            TEST_CASE_7,
-            TEST_CASE_8,
-            TEST_CASE_9,
-            TEST_CASE_10,
-            TEST_CASE_11,
-            TEST_CASE_12,
-        ]
-    )
+    @parameterized.expand(ALL_TESTS)
     def test_class_value(self, y_pred, y, softmax, to_onehot, average, expected_value):
         y_pred_trans = Compose([ToTensor(), Activations(softmax=softmax)])
         y_trans = Compose([ToTensor(), AsDiscrete(to_onehot=to_onehot)])