def test_slide_and_accumulate():
ed = EventDetector(class_labels=['event1', 'event2'],
disable_progress_bar=True,
params={
'hop_length_seconds': 0.02,
})
probabilities = numpy.array(
[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0])
# Test sum
res = ed._slide_and_accumulate(input_probabilities=probabilities,
window_length=2,
accumulation_type='sliding_sum').tolist()
nose.tools.assert_list_equal(res, [3, 5, 7, 9, 11, 13, 15, 17, 9, 10])
# Test mean
res = ed._slide_and_accumulate(input_probabilities=probabilities,
window_length=2,
accumulation_type='sliding_mean').tolist()
nose.tools.assert_list_equal(
res, [1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.0, 10.0])
# Test median
res = ed._slide_and_accumulate(
input_probabilities=probabilities,
window_length=3,
accumulation_type='sliding_median').tolist()
nose.tools.assert_list_equal(
res, [2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 8.0, 9.0, 10.0])
nose.tools.assert_raises(AssertionError, ed._slide_and_accumulate,
probabilities, 2, "test")
def test_contiguous_regions():
ed = EventDetector(class_labels=['event1', 'event2'],
disable_progress_bar=True,
params={
'hop_length_seconds': 0.02,
})
activity_array = numpy.array(
[0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1])
res = ed._contiguous_regions(activity_array=activity_array).tolist()
nose.tools.assert_list_equal(res, [[4, 8], [12, 14], [16, 20]])
def test_activity_processing():
ed = EventDetector(class_labels=['event1', 'event2'],
disable_progress_bar=True,
params={
'hop_length_seconds': 0.02,
})
activity = numpy.array([1.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0])
res = ed._activity_processing(activity_vector=activity,
window_size=3,
processing_type="median_filtering").tolist()
nose.tools.assert_list_equal(
res, [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0])
nose.tools.assert_raises(AssertionError, ed._activity_processing, activity,
3, "test")
def test_get_target_matrix_dict():
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(
filename=os.path.join('material', 'test.mfcc.cpickle'))
data = {
'file1.wav': feature_container,
'file2.wav': feature_container,
}
annotations = {
'file1.wav':
MetaDataContainer([{
'file': 'file1.wav',
'scene_label': 'scene1',
'event_onset': 0.0,
'event_offset': 1.0,
'event_label': 'event1',
}, {
'file': 'file1.wav',
'scene_label': 'scene1',
'event_onset': 1.0,
'event_offset': 2.0,
'event_label': 'event2',
}]),
'file2.wav':
MetaDataContainer([{
'file': 'file2.wav',
'scene_label': 'scene1',
'event_onset': 0.0,
'event_offset': 1.0,
'event_label': 'event2',
}, {
'file': 'file2.wav',
'scene_label': 'scene1',
'event_onset': 1.0,
'event_offset': 2.0,
'event_label': 'event1',
}]),
}
ed = EventDetector(class_labels=['event1', 'event2'],
disable_progress_bar=True,
params={
'hop_length_seconds': 0.02,
})
target_matrix = ed._get_target_matrix_dict(data=data,
annotations=annotations)
# Test shape
nose.tools.eq_(target_matrix['file1.wav'].shape, (501, 2))
nose.tools.eq_(target_matrix['file2.wav'].shape, (501, 2))
# Test content
nose.tools.eq_(numpy.sum(target_matrix['file1.wav'][:, 0] == 1), 50)
nose.tools.eq_(numpy.sum(target_matrix['file1.wav'][:, 1] == 1), 50)
nose.tools.eq_(numpy.sum(target_matrix['file2.wav'][:, 0] == 1), 50)
nose.tools.eq_(numpy.sum(target_matrix['file2.wav'][:, 1] == 1), 50)
def test_generate_validation():
annotations = {
'file1.wav':
MetaDataContainer([{
'file': 'file1.wav',
'scene_label': 'scene1',
'event_onset': 0.0,
'event_offset': 1.0,
'event_label': 'event1',
'location_identifier': 'a',
}, {
'file': 'file1.wav',
'scene_label': 'scene1',
'event_onset': 1.0,
'event_offset': 2.0,
'event_label': 'event2',
'location_identifier': 'a',
}, {
'file': 'file1.wav',
'scene_label': 'scene1',
'event_onset': 2.0,
'event_offset': 3.0,
'event_label': 'event2',
'location_identifier': 'a',
}, {
'file': 'file1.wav',
'scene_label': 'scene1',
'event_onset': 4.0,
'event_offset': 5.0,
'event_label': 'event1',
'location_identifier': 'a',
}, {
'file': 'file1.wav',
'scene_label': 'scene1',
'event_onset': 1.0,
'event_offset': 2.0,
'event_label': 'event1',
'location_identifier': 'a',
}]),
'file2.wav':
MetaDataContainer([{
'file': 'file2.wav',
'scene_label': 'scene1',
'event_onset': 0.0,
'event_offset': 1.0,
'event_label': 'event2',
'location_identifier': 'b',
}, {
'file': 'file2.wav',
'scene_label': 'scene1',
'event_onset': 1.0,
'event_offset': 2.0,
'event_label': 'event1',
'location_identifier': 'b',
}, {
'file': 'file2.wav',
'scene_label': 'scene1',
'event_onset': 2.0,
'event_offset': 3.0,
'event_label': 'event2',
'location_identifier': 'b',
}, {
'file': 'file2.wav',
'scene_label': 'scene1',
'event_onset': 3.0,
'event_offset': 4.0,
'event_label': 'event2',
'location_identifier': 'b',
}])
}
ed = EventDetector(class_labels=['event1', 'event2'],
disable_progress_bar=True,
params={
'hop_length_seconds': 0.02,
})
# Test generated_scene_location_event_balanced
validation_set = ed._generate_validation(
annotations=annotations,
validation_type='generated_scene_location_event_balanced',
valid_percentage=0.50,
seed=0)
nose.tools.eq_(len(validation_set), 1)
# Test generated_event_file_balanced
annotations = {
'file1.wav':
MetaDataContainer([
{
'file': 'file1.wav',
'scene_label': 'scene1',
'event_onset': 0.0,
'event_offset': 1.0,
'event_label': 'event1',
'location_identifier': 'a',
},
]),
'file2.wav':
MetaDataContainer([
{
'file': 'file2.wav',
'scene_label': 'scene1',
'event_onset': 0.0,
'event_offset': 1.0,
'event_label': 'event2',
'location_identifier': 'b',
},
])
}
validation_set = ed._generate_validation(
annotations=annotations,
validation_type='generated_event_file_balanced',
valid_percentage=0.50,
seed=0)
nose.tools.assert_list_equal(validation_set, ['file1.wav', 'file2.wav'])
nose.tools.assert_raises(AssertionError, ed._generate_validation,
annotations, 'test', 0.5)