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'],