dev(narugo): add more unittest

soundutils/similarity/base.py

@@ -53,11 +53,11 @@ def _align_sounds(
 
         if sr1 != c_sr:
             num_samples = int(sound1.time * c_sr)
-            data1 = resample(data1, num_samples)
+            data1 = resample(data1, num_samples, axis=-1)
             sr1 = c_sr
         if sr2 != c_sr:
             num_samples = int(sound2.time * c_sr)
-            data2 = resample(data2, num_samples)
+            data2 = resample(data2, num_samples, axis=-1)
             sr2 = c_sr
 
     if time_align in {'none', 'noncheck'}:

test/similarity/test_colleration.py

@@ -0,0 +1,75 @@
+import pytest
+
+from soundutils.similarity import SoundLengthNotMatch, SoundChannelsNotMatch, SoundResampleRateNotMatch, \
+    sound_pearson_similarity
+from test.testings import get_testfile
+
+
+@pytest.mark.unittest
+class TestSimilarityCorrelation:
+    @pytest.mark.parametrize(['file1', 'file2', 'v'], [
+        ('texas_short.wav', 'texas_short.wav', 1.0),
+        ('texas_short.wav', 'texas_long.wav', SoundLengthNotMatch),
+        ('texas_long.wav', 'texas_long.wav', 1.0),
+        ('texas_long.wav', 'texas_long.flac', 1.0),
+        ('texas_long.wav', 'texas_long.mp3', 0.9982756956202339),
+        ('stereo_sine_wave.wav', 'stereo_sine_wave_44100.wav', SoundResampleRateNotMatch),
+        ('texas_short.wav', 'stereo_sine_wave_44100.wav', SoundChannelsNotMatch),
+    ])
+    def test_sound_pearson_similarity(self, file1, file2, v):
+        file1 = get_testfile('assets', file1)
+        file2 = get_testfile('assets', file2)
+        if isinstance(v, type) and issubclass(v, BaseException):
+            with pytest.raises(v):
+                _ = sound_pearson_similarity(file1, file2)
+        else:
+            assert sound_pearson_similarity(file1, file2) == pytest.approx(v)
+
+    @pytest.mark.parametrize(['file1', 'file2', 'v'], [
+        ('texas_short.wav', 'texas_short.wav', 1.0),
+        ('texas_short.wav', 'texas_long.wav', -0.023363902648302855),
+        ('texas_long.wav', 'texas_short.wav', -0.023363902648302855),
+        ('texas_long.wav', 'texas_long.wav', 1.0),
+        ('texas_long.wav', 'texas_long.flac', 1.0),
+        ('texas_long.wav', 'texas_long.mp3', 0.9982756956202339),
+        ('stereo_sine_wave.wav', 'stereo_sine_wave_44100.wav', SoundResampleRateNotMatch),
+        ('texas_short.wav', 'stereo_sine_wave_44100.wav', SoundChannelsNotMatch),
+    ])
+    def test_sound_pearson_similarity_pad(self, file1, file2, v):
+        file1 = get_testfile('assets', file1)
+        file2 = get_testfile('assets', file2)
+        if isinstance(v, type) and issubclass(v, BaseException):
+            with pytest.raises(v):
+                _ = sound_pearson_similarity(file1, file2, time_align='pad')
+        else:
+            assert sound_pearson_similarity(file1, file2, time_align='pad') == pytest.approx(v)
+
+    @pytest.mark.parametrize(['file1', 'file2', 'time_align', 'v'], [
+        ('texas_short.wav', 'texas_short.wav', 'none', 1.0),
+        ('texas_short.wav', 'texas_short.wav', 'pad', 1.0),
+        ('texas_short.wav', 'texas_short.wav', 'prefix', 1.0),
+        ('texas_short.wav', 'texas_short.wav', 'resample_max', 1.0),
+        ('texas_short.wav', 'texas_short.wav', 'resample_min', 1.0),
+        ('texas_short.wav', 'texas_short.wav', 'bullshit', ValueError),
+
+        ('texas_short.wav', 'texas_long.wav', 'none', SoundLengthNotMatch),
+        ('texas_short.wav', 'texas_long.wav', 'pad', -0.023363902648302855),
+        ('texas_long.wav', 'texas_short.wav', 'pad', -0.023363902648302855),
+        ('texas_short.wav', 'texas_long.wav', 'prefix', -0.05039022356294788),
+        ('texas_short.wav', 'texas_long.wav', 'resample_max', -6.501929201342696e-05),
+        ('texas_long.wav', 'texas_short.wav', 'resample_max', -6.501929201342696e-05),
+        ('texas_short.wav', 'texas_long.wav', 'resample_min', -6.781880893649058e-05),
+        ('texas_long.wav', 'texas_short.wav', 'resample_min', -6.781880893649058e-05),
+
+        ('texas_long.wav', 'texas_long.wav', 'none', 1.0),
+        ('texas_long.wav', 'texas_long.flac', 'none', 1.0),
+        ('texas_long.wav', 'texas_long.mp3', 'none', 0.9982756956202339),
+    ])
+    def test_sound_pearson_similarity_time_align(self, file1, file2, time_align, v):
+        file1 = get_testfile('assets', file1)
+        file2 = get_testfile('assets', file2)
+        if isinstance(v, type) and issubclass(v, BaseException):
+            with pytest.raises(v):
+                _ = sound_pearson_similarity(file1, file2, time_align=time_align)
+        else:
+            assert sound_pearson_similarity(file1, file2, time_align=time_align) == pytest.approx(v)

test/similarity/test_spectral.py

@@ -73,3 +73,27 @@ def test_sound_spectral_centroid_distance_time_align(self, file1, file2, time_al
                 _ = sound_spectral_centroid_distance(file1, file2, time_align=time_align)
         else:
             assert sound_spectral_centroid_distance(file1, file2, time_align=time_align) == pytest.approx(v)
+
+    @pytest.mark.parametrize(['file1', 'file2', 'sr_align', 'v'], [
+        ('stereo_sine_wave.wav', 'stereo_sine_wave.wav', 'none', 0.0),
+        ('stereo_sine_wave.wav', 'stereo_sine_wave.wav', 'min', 0.0),
+        ('stereo_sine_wave.wav', 'stereo_sine_wave.wav', 'max', 0.0),
+        ('stereo_sine_wave.wav', 'stereo_sine_wave.wav', 'bullshit', ValueError),
+
+        ('stereo_sine_wave.wav', 'stereo_sine_wave_44100.wav', 'none', SoundResampleRateNotMatch),
+        ('stereo_sine_wave.wav', 'stereo_sine_wave_44100.wav', 'min', 0.0014548659720306609),
+        ('stereo_sine_wave.wav', 'stereo_sine_wave_44100.wav', 'max', 0.0013925866190809756),
+
+        ('stereo_sine_wave.wav', 'stereo_sine_wave_3x_40_900.wav', 'none', SoundResampleRateNotMatch),
+        ('stereo_sine_wave.wav', 'stereo_sine_wave_3x_40_900.wav', 'min', 20.705757783547845),
+        ('stereo_sine_wave.wav', 'stereo_sine_wave_3x_40_900.wav', 'max', 20.89222150977781),
+    ])
+    def test_sound_spectral_centroid_distance_sr_align(self, file1, file2, sr_align, v):
+        file1 = get_testfile('assets', file1)
+        file2 = get_testfile('assets', file2)
+        if isinstance(v, type) and issubclass(v, BaseException):
+            with pytest.raises(v):
+                _ = sound_spectral_centroid_distance(file1, file2, time_align='pad', resample_rate_align=sr_align)
+        else:
+            assert sound_spectral_centroid_distance(file1, file2, time_align='pad', resample_rate_align=sr_align) \
+                   == pytest.approx(v)