def versions(
self,
path: str,
*,
ext: str = None,
) -> typing.List[str]:
r"""Versions of a file.
Args:
path: path to file on backend
ext: file extension, if ``None`` uses characters after last dot
Returns:
list of versions in ascending order
"""
folder, file = self.split(path)
name = audeer.basename_wo_ext(file, ext=ext)
vs = self._versions(folder, name)
return audeer.sort_versions(vs)
def test_custom(config, level):
# create feature extractor
fex = opensmile.Smile(config, level)
# extract from file
y_file = fex.process_file(pytest.WAV_FILE)
# extract from array
x, sr = audiofile.read(pytest.WAV_FILE)
y_array = fex.process_signal(x, sr, file=pytest.WAV_FILE)
# assertions
assert fex.config_name == audeer.basename_wo_ext(config)
assert fex.config_path == audeer.safe_path(config)
assert fex.num_features == len(fex.feature_names)
assert fex.feature_names == y_file.columns.to_list()
pd.testing.assert_frame_equal(y_file, y_array)
def test_basename_wo_ext(path, ext, basename):
b = audeer.basename_wo_ext(path, ext=ext)
assert b == basename
assert type(b) is str
'A German database of emotional utterances '
'spoken by actors '
'recorded as a part of the DFG funded research project '
'SE462/3-1 in 1997 and 1999. '
'Recordings took place in the anechoic chamber '
'of the Technical University Berlin, '
'department of Technical Acoustics. '
'It contains about 500 utterances '
'from ten different actors '
'expressing basic six emotions and neutral.'
)
files = sorted(
[os.path.join('wav', f) for f in os.listdir(os.path.join(src_dir, 'wav'))]
)
names = [audeer.basename_wo_ext(f) for f in files]
emotion_mapping = {
'W': 'anger',
'L': 'boredom',
'E': 'disgust',
'A': 'fear',
'F': 'happiness',
'T': 'sadness',
'N': 'neutral',
}
emotions = list(parse_names(names, from_i=5, to_i=6, mapping=emotion_mapping))
y = pd.read_csv(
os.path.join(src_dir, 'erkennung.txt'),
usecols=['Satz', 'erkannt'],