def test_with_statement():
FeatureExtractor(store=True, overwrite=True).extract(
audio_file=os.path.join('material', 'test.wav'),
extractor_name='mfcc',
extractor_params={
'mfcc': {
'n_mfcc': 10
}
},
storage_paths={
'mfcc': os.path.join('material', 'test.mfcc.cpickle')
}
)
feature_container = FeatureContainer().load(filename=os.path.join('material', 'test.mfcc.cpickle'))
with FeatureNormalizer() as feature_normalizer:
feature_normalizer.accumulate(feature_container)
nose.tools.eq_(feature_normalizer['N'][0], 501)
numpy.testing.assert_array_equal(feature_normalizer['mean'][0][0],
numpy.mean(feature_container.feat[0], axis=0))
numpy.testing.assert_array_equal(feature_normalizer['S1'][0],
numpy.sum(feature_container.feat[0], axis=0))
numpy.testing.assert_array_equal(feature_normalizer['S2'][0],
numpy.sum(feature_container.feat[0] ** 2, axis=0))
test_accumulate_finalize()
def test_normalizer():
FeatureExtractor(store=True, overwrite=True).extract(
audio_file=os.path.join('material', 'test.wav'),
extractor_name='mfcc',
extractor_params={'mfcc': {
'n_mfcc': 10
}},
storage_paths={'mfcc': os.path.join('material', 'test.mfcc.cpickle')})
# Test 1
test_recipe = 'mfcc=0-5'
test_recipe_parsed = ParameterContainer()._parse_recipe(recipe=test_recipe)
feature_container = FeatureContainer().load(
filename=os.path.join('material', 'test.mfcc.cpickle'))
feature_normalizer = FeatureNormalizer().accumulate(
feature_container=feature_container).finalize()
feature_stacker = FeatureStacker(recipe=test_recipe_parsed)
feature_normalizer = feature_stacker.normalizer(
normalizer_list={'mfcc': feature_normalizer})
nose.tools.eq_(feature_normalizer['N'][0][0], 501)
nose.tools.eq_(feature_normalizer['mean'][0].shape[0], 1)
nose.tools.eq_(feature_normalizer['mean'][0].shape[1], 6)
nose.tools.eq_(feature_normalizer['std'][0].shape[0], 1)
nose.tools.eq_(feature_normalizer['std'][0].shape[1], 6)
# Test 2
test_recipe = 'mfcc=1,2,3,4'
test_recipe_parsed = ParameterContainer()._parse_recipe(recipe=test_recipe)
feature_container = FeatureContainer().load(
filename=os.path.join('material', 'test.mfcc.cpickle'))
feature_normalizer = FeatureNormalizer().accumulate(
feature_container=feature_container).finalize()
feature_stacker = FeatureStacker(recipe=test_recipe_parsed)
feature_normalizer = feature_stacker.normalizer(
normalizer_list={'mfcc': feature_normalizer})
nose.tools.eq_(feature_normalizer['N'][0][0], 501)
nose.tools.eq_(feature_normalizer['mean'][0].shape[0], 1)
nose.tools.eq_(feature_normalizer['mean'][0].shape[1], 4)
nose.tools.eq_(feature_normalizer['std'][0].shape[0], 1)
nose.tools.eq_(feature_normalizer['std'][0].shape[1], 4)
# Test 3
test_recipe = 'mfcc'
test_recipe_parsed = ParameterContainer()._parse_recipe(recipe=test_recipe)
feature_container = FeatureContainer().load(
filename=os.path.join('material', 'test.mfcc.cpickle'))
feature_normalizer = FeatureNormalizer().accumulate(
feature_container=feature_container).finalize()
feature_stacker = FeatureStacker(recipe=test_recipe_parsed)
feature_normalizer = feature_stacker.normalizer(
normalizer_list={'mfcc': feature_normalizer})
nose.tools.eq_(feature_normalizer['N'][0][0], 501)
nose.tools.eq_(feature_normalizer['mean'][0].shape[0], 1)
nose.tools.eq_(feature_normalizer['mean'][0].shape[1], 10)
nose.tools.eq_(feature_normalizer['std'][0].shape[0], 1)
nose.tools.eq_(feature_normalizer['std'][0].shape[1], 10)