From 192c952c2da014680a790448f3bfe2a296000039 Mon Sep 17 00:00:00 2001
From: Rob Hallam <0504004h@student.gla.ac.uk>
Date: Thu, 29 Aug 2024 09:49:11 +0100
Subject: [PATCH] test: add TestLoudAudioFEFunctional

Functional tests for LoudAudioFeatureExtractor

Currently uses one manually-generated video with blank audio except between
15-20s where 1-2 sine tones are present
---
 test/test_feature_extractors_functional.py | 42 ++++++++++++++++++++++
 1 file changed, 42 insertions(+)

diff --git a/test/test_feature_extractors_functional.py b/test/test_feature_extractors_functional.py
index b608bf5..706b509 100644
--- a/test/test_feature_extractors_functional.py
+++ b/test/test_feature_extractors_functional.py
@@ -48,3 +48,45 @@ class TestVideoActivityFEFunctional(FEFunctionalTest):
         self.assertTrue(testfe.features)
         # check if the feature interval is within the expected range
         self.assertTrue(testfe.features[0].interval.start >= START_TIME)
+
+
+class TestLoudAudioFEFunctional(FEFunctionalTest):
+    """TestAudioLoudnessFEFunctional -- functional tests for audio loudness feature extractor
+    """
+
+    def test_audio_loudness_functional_one_feature(self):
+        """Test audio loudness feature extractor
+
+        use:
+         - sample_videos/sample-manual-audio.mp4 :: audio at 15-20s -- pass if audio detected anywhere in this range
+                                                                    -- peak at 16s - 18s, verify this is highest scoring
+        """
+        SAMPLE_VIDEO = f"{self.SAMPLE_DIR}/sample-manual-audio.mp4"
+
+        START_TIME = 15
+        END_TIME = 20
+        PEAK_START = 16
+        PEAK_END = 18
+        # create mock source with the video
+        source = mocks.MockSource(path=SAMPLE_VIDEO)
+
+        # create the feature extractor
+        testfe = extractors.LoudAudioFeatureExtractor(input_files=[source])
+        testfe.setup()
+        testfe.run()
+        testfe.teardown()
+
+        # check if the feature was extracted:
+        self.assertTrue(testfe.features)
+        # check if the feature interval is within the expected range
+        self.assertTrue(testfe.features[0].interval.start >= START_TIME)
+
+        # get sorted list of features based on feature.score
+        sorted_features = sorted(testfe.features, key=lambda x: x.score, reverse=True)
+        # check if the highest scoring feature is within the peak range
+        self.assertTrue(sorted_features[0].interval.start >= PEAK_START)
+
+
+
+if __name__ == "__main__":
+    unittest.main()