def test_file(tmpdir):
segment = audinterface.Segment(
process_func=lambda s, sr: INDEX,
sampling_rate=None,
resample=False,
verbose=False,
)
# create test file
root = str(tmpdir.mkdir('wav'))
file = 'file.wav'
path = os.path.join(root, file)
af.write(path, SIGNAL, SAMPLING_RATE)
# test absolute path
result = segment.process_file(path)
assert all(result.levels[0] == path)
assert all(result.levels[1] == INDEX.levels[0])
assert all(result.levels[2] == INDEX.levels[1])
result = segment.process_file(path, start=pd.to_timedelta('1s'))
assert all(result.levels[0] == path)
assert all(result.levels[1] == INDEX.levels[0] + pd.to_timedelta('1s'))
assert all(result.levels[2] == INDEX.levels[1] + pd.to_timedelta('1s'))
# test relative path
result = segment.process_file(file, root=root)
assert all(result.levels[0] == file)
assert all(result.levels[1] == INDEX.levels[0])
assert all(result.levels[2] == INDEX.levels[1])
result = segment.process_file(file, root=root, start=pd.to_timedelta('1s'))
assert all(result.levels[0] == file)
assert all(result.levels[1] == INDEX.levels[0] + pd.to_timedelta('1s'))
assert all(result.levels[2] == INDEX.levels[1] + pd.to_timedelta('1s'))
def test_invert(signal, sampling_rate, segment_func, result):
model = audinterface.Segment(
process_func=segment_func,
invert=True,
)
index = model(signal, sampling_rate)
pd.testing.assert_index_equal(index, result)
def test_signal_kwargs():
def segment_func(s, sr, arg1, arg2):
assert arg1 == 'foo'
assert arg2 == 'bar'
audinterface.Segment(
process_func=segment_func,
arg1='foo',
arg2='bar',
)
def test_folder(tmpdir, num_workers, multiprocessing):
model = audinterface.Segment(
process_func=lambda s, sr: INDEX,
sampling_rate=None,
resample=False,
num_workers=num_workers,
multiprocessing=multiprocessing,
verbose=False,
)
path = str(tmpdir.mkdir('wav'))
files = [os.path.join(path, f'file{n}.wav') for n in range(3)]
for file in files:
af.write(file, SIGNAL, SAMPLING_RATE)
result = model.process_folder(path)
assert all(result.levels[0] == files)
assert all(result.levels[1] == INDEX.levels[0])
assert all(result.levels[2] == INDEX.levels[1])
def test_signal(signal, sampling_rate, segment_func, start, end, result):
model = audinterface.Segment(process_func=segment_func, )
index = model.process_signal(signal, sampling_rate, start=start, end=end)
pd.testing.assert_index_equal(index, result)
def test_index(tmpdir, num_workers, multiprocessing):
def process_func(x, sr):
dur = pd.to_timedelta(x.shape[-1] / sr, unit='s')
return audinterface.utils.signal_index(
'0.1s',
dur - pd.to_timedelta('0.1s'),
)
segment = audinterface.Segment(
process_func=process_func,
sampling_rate=None,
resample=False,
num_workers=num_workers,
multiprocessing=multiprocessing,
verbose=False,
)
# create signal and file
sampling_rate = 8000
signal = np.random.uniform(-1.0, 1.0, (1, 3 * sampling_rate))
root = str(tmpdir.mkdir('wav'))
file = 'file.wav'
path = os.path.join(root, file)
af.write(path, signal, sampling_rate)
# empty index
index = audformat.segmented_index()
result = segment.process_index(index)
assert result.empty
result = segment.process_signal_from_index(signal, sampling_rate, index)
assert result.empty
# segmented index without file level
index = audinterface.utils.signal_index(
pd.timedelta_range('0s', '2s', 3),
pd.timedelta_range('1s', '3s', 3),
)
expected = audinterface.utils.signal_index(
index.get_level_values('start') + pd.to_timedelta('0.1s'),
index.get_level_values('end') - pd.to_timedelta('0.1s'),
)
result = segment.process_signal_from_index(signal, sampling_rate, index)
pd.testing.assert_index_equal(result, expected)
# segmented index with absolute paths
index = audformat.segmented_index(
[path] * 3,
pd.timedelta_range('0s', '2s', 3),
pd.timedelta_range('1s', '3s', 3),
)
expected = audformat.segmented_index(
[path] * 3,
index.get_level_values('start') + pd.to_timedelta('0.1s'),
index.get_level_values('end') - pd.to_timedelta('0.1s'),
)
result = segment.process_index(index)
pd.testing.assert_index_equal(result, expected)
result = segment.process_signal_from_index(signal, sampling_rate, index)
pd.testing.assert_index_equal(result, expected)
# filewise index with absolute paths
index = pd.Index([path], name='file')
expected = audformat.segmented_index(path, '0.1s', '2.9s')
result = segment.process_index(index)
pd.testing.assert_index_equal(result, expected)
result = segment.process_signal_from_index(signal, sampling_rate, index)
pd.testing.assert_index_equal(result, expected)
# segmented index with relative paths
index = audformat.segmented_index(
[file] * 3,
pd.timedelta_range('0s', '2s', 3),
pd.timedelta_range('1s', '3s', 3),
)
expected = audformat.segmented_index(
[file] * 3,
index.get_level_values('start') + pd.to_timedelta('0.1s'),
index.get_level_values('end') - pd.to_timedelta('0.1s'),
)
result = segment.process_index(index, root=root)
pd.testing.assert_index_equal(result, expected)
result = segment.process_signal_from_index(signal, sampling_rate, index)
pd.testing.assert_index_equal(result, expected)
# filewise index with relative paths
index = pd.Index([file], name='file')
expected = audformat.segmented_index(file, '0.1s', '2.9s')
result = segment.process_index(index, root=root)
pd.testing.assert_index_equal(result, expected)
result = segment.process_signal_from_index(signal, sampling_rate, index)
pd.testing.assert_index_equal(result, expected)
import pandas as pd
import pytest
import audformat
import audinterface
import audiofile as af
SAMPLING_RATE = 8000
NUM_CHANNELS = 2
NUM_FEATURES = 3
NUM_FRAMES = 5
SIGNAL_1D = np.ones((1, SAMPLING_RATE))
SIGNAL_2D = np.ones((NUM_CHANNELS, SAMPLING_RATE))
SEGMENT = audinterface.Segment(
process_func=lambda x, sr: audinterface.utils.signal_index(
pd.to_timedelta(0),
pd.to_timedelta(x.shape[1] / sr, unit='s') / 2,
))
def feature_extractor(signal, _):
return np.ones((NUM_CHANNELS, NUM_FEATURES))
def features_extractor_sliding_window(signal, _, hop_size):
num_time_steps = int(np.ceil(signal.shape[1] / hop_size))
return np.ones((NUM_CHANNELS, NUM_FEATURES, num_time_steps))
def test_feature():
# You have to specify sampling rate with unit == 'samples' and win_dur