TST: add test

audeering · Mar 28, 2023 · 4a338e5 · 4a338e5
1 parent c6a49ce
commit 4a338e5
Showing 1 changed file with 27 additions and 11 deletions.
diff --git a/tests/test_feature.py b/tests/test_feature.py
@@ -937,29 +937,45 @@ def test_process_signal(
 
 
 @pytest.mark.parametrize(
-    'index,expected_features',
+    'feature, signal, sampling_rate, index, expected',
     [
         (
+            audinterface.Feature(
+                feature_names=('o1', 'o2', 'o3'),
+                process_func=feature_extractor,
+                channels=range(NUM_CHANNELS),
+            ),
+            SIGNAL_2D,
+            SAMPLING_RATE,
             audinterface.utils.signal_index(
                 [pd.to_timedelta('0s'), pd.to_timedelta('1s')],
                 [pd.to_timedelta('2s'), pd.to_timedelta('3s')],
             ),
             np.ones((2, NUM_CHANNELS * NUM_FEATURES)),
         ),
+        (
+            audinterface.Feature(
+                feature_names=('string'),
+                process_func=lambda x, sr, idx: ['a', 'abc'][idx],
+            ),
+            SIGNAL_1D,
+            SAMPLING_RATE,
+            audinterface.utils.signal_index(
+                [pd.to_timedelta('0s'), pd.to_timedelta('1s')],
+                [pd.to_timedelta('2s'), pd.to_timedelta('3s')],
+            ),
+            np.array([['a'], ['abc']]),
+        ),
     ],
 )
-def test_process_signal_from_index(index, expected_features):
-    extractor = audinterface.Feature(
-        feature_names=('o1', 'o2', 'o3'),
-        process_func=feature_extractor,
-        channels=range(NUM_CHANNELS),
-    )
-    features = extractor.process_signal_from_index(
-        SIGNAL_2D,
-        SAMPLING_RATE,
+def test_process_signal_from_index(feature, signal, sampling_rate, index,
+                                   expected):
+    df = feature.process_signal_from_index(
+        signal,
+        sampling_rate,
         index,
     )
-    np.testing.assert_array_equal(features.values, expected_features)
+    np.testing.assert_array_equal(df.values, expected)
 
 
 @pytest.mark.parametrize(