Adding Unit Test for Tonal Extractor

test/src/unittests/extractor/test_tonalextractor.py

@@ -0,0 +1,115 @@
+#!/usr/bin/env python
+
+# Copyright (C) 2006-2021  Music Technology Group - Universitat Pompeu Fabra
+#
+# This file is part of Essentia
+#
+# Essentia is free software: you can redistribute it and/or modify it under
+# the terms of the GNU Affero General Public License as published by the Free
+# Software Foundation (FSF), either version 3 of the License, or (at your
+# option) any later version.
+#
+# This program is distributed in the hope that it will be useful, but WITHOUT
+# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+# FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more
+# details.
+#
+# You should have received a copy of the Affero GNU General Public License
+# version 3 along with this program. If not, see http://www.gnu.org/licenses/
+
+from essentia_test import *
+import numpy as np
+
+class TestTonalExtractor(TestCase):
+
+    def testEmpty(self):
+        # Test if the algorithm handles an empty input signal correctly
+        with self.assertRaises(RuntimeError):
+            chords_changes_rate, _, _, chords_number_rate, _, _, _, _, _, _, _, key_strength = TonalExtractor()(np.array([], dtype=np.float32))
+
+    def testSilence(self):
+        # In this test we jiuts check three of the output parameters of type real
+        silence_vec = np.zeros(44100, dtype=np.single)
+        chords_changes_rate, _, _, chords_number_rate, _, _, _, _, _, _, _, key_strength = TonalExtractor()(silence_vec)
+        self.assertEqual(chords_changes_rate, 0.0)
+        self.assertGreaterEqual(chords_number_rate, 0.0)
+        self.assertEqual(key_strength, 0.0)
+
+    def testInvalidParameters(self):
+        # Test if the algorithm handles invalid parameters correctly
+        extractor = TonalExtractor()
+
+        # Test case 1: Negative frameSize
+        with self.subTest(msg="Negative frameSize"):
+            with self.assertRaises(RuntimeError):
+                extractor.configure(frameSize=-1, hopSize=2048, tuningFrequency=440.0)
+
+        # Test case 2: Negative hopSize
+        with self.subTest(msg="Negative hopSize"):
+            with self.assertRaises(RuntimeError):
+                extractor.configure(frameSize=4096, hopSize=-1, tuningFrequency=440.0)
+
+        # Test case 3: Negative tuningFrequency
+        with self.subTest(msg="Negative tuningFrequency"):
+            with self.assertRaises(RuntimeError):
+                extractor.configure(frameSize=4096, hopSize=2048, tuningFrequency=-440.0)
+
+        # Test case 4: Zero frameSize and hopSize
+        with self.subTest(msg="Zero frameSize and hopSize"):
+            with self.assertRaises(RuntimeError):
+                extractor.configure(frameSize=0, hopSize=0, tuningFrequency=440.0)
+
+        # Test case 5: Zero frameSize
+        with self.subTest(msg="Zero frameSize"):
+            with self.assertRaises(RuntimeError):
+                extractor.configure(frameSize=0, hopSize=2048, tuningFrequency=440.0)
+
+        # Test case 6: Zero hopSize
+        with self.subTest(msg="Zero hopSize"):
+            with self.assertRaises(RuntimeError):
+                extractor.configure(frameSize=4096, hopSize=0, tuningFrequency=440.0)
+
+        # Test case 7: Non-negative parameters
+        with self.subTest(msg="Valid parameters"):
+            # This should not raise an exception
+            extractor.configure(frameSize=4096, hopSize=2048, tuningFrequency=440.0)
+
+    def testRandomInput(self):
+        n = 10
+        for _ in range(n):
+            rand_input = np.random.random(88200).astype(np.single) * 2 - 1
+            result = TonalExtractor()(rand_input)
+            expected_result = np.sum(rand_input * rand_input) ** 0.67
+            self.assertAlmostEqual(result[0], expected_result, 9.999e+02)
+
+    def testRegression(self):
+        frameSizes = [128, 256, 512, 1024, 2048, 4096]
+        hopSizes = [256, 512, 1024, 2048, 4096, 8192]
+
+        input_filename = join(testdata.audio_dir, "recorded", "dubstep.wav")  # Replace 'testdata' with actual path
+        real_audio_input = MonoLoader(filename=input_filename)()
+
+
+        # Iterate through pairs of frameSize and corresponding hopSize
+        for fs, hs in zip(frameSizes, hopSizes):
+            with self.subTest(frameSize=fs, hopSize=hs):
+                # Process the algorithm on real audio with the current frameSize and hopSize
+                te = TonalExtractor()
+                te.configure(frameSize=fs, hopSize=hs)
+                chords_changes_rate, _, _, chords_number_rate, _, _, _, _, _, _, _, key_strength= te(real_audio_input)
+
+                # Perform assertions on one or more outputs
+                # Example: Assert that chords_changes_rate is a non-negative scalar
+                self.assertIsInstance(chords_changes_rate, (int, float))
+                self.assertGreaterEqual(chords_changes_rate, 0)
+                self.assertIsInstance(chords_number_rate, (int, float))
+                self.assertGreaterEqual(chords_number_rate, 0)
+                self.assertIsInstance(key_strength, (int, float))
+                self.assertGreaterEqual(key_strength, 0)
+                # You can add more assertions on other outputs as needed
+
+
+suite = allTests(TestTonalExtractor)
+
+if __name__ == '__main__':
+    unittest.main()