Python wave.Error方法代碼示例

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def _read_audio(self, audio_data):

        try:
            fin = wave.open(io.BytesIO(audio_data))
        except (wave.Error, EOFError):
            raise OSError("Error reading the audio file. Only WAV files are supported.")

        if fin.getnchannels() != 1:
            raise OSError("Only mono audio files are supported.")

        fin_len = fin.getnframes() / fin.getframerate()  # num frames / frame rate = length in seconds

        if fin_len > 10:
            raise OSError("This model is designed to work with short (about 5 second) audio files only.")

        return fin 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def _read_fmt_chunk(self, chunk):

        # added support for wave extensible

        wFormatTag, self._nchannels, self._framerate, dwAvgBytesPerSec, wBlockAlign = struct.unpack_from(b'<HHLLH', chunk.read(14))
        if wFormatTag in  (wave.WAVE_FORMAT_PCM, WAVE_EXTENSIBLE_PCM):
            sampwidth = struct.unpack_from(b'<H', chunk.read(2))[0]
            self._sampwidth = (sampwidth + 7) // 8
        else:
            raise wave.Error('unknown format: %r' % (wFormatTag,))

        if not self._sampwidth in (2, 3):
            raise wave.Error('unsupported sample width: %r' % (self._sampwidth,))

        self._framesize = self._nchannels * self._sampwidth
        self._comptype = 'NONE'
        self._blockalign = wBlockAlign
        self._compname = 'not compressed' 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def _is_good_wave(self, filename):
        """
        check if wav is in correct format for MARF.
        """
        par = None
        try:
            w_file = wave.open(filename)
            par = w_file.getparams()
            w_file.close()
        except wave.Error as exc:
            print (exc)
            return False

        if par[:3] == (1, 2, 8000) and par[-1:] == ('not compressed',):
            return True
        else:
            return False 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def test_unpickling_object_that_is_not_imported_raises_error(self):

        def get_the_pickle():
            import wave
            obj = wave.Error
            return pickle_dump(obj)

        serialized = get_the_pickle()
        # Making sure that the module is unloaded.
        del sys.modules['wave']
        module_dot_name = 'wave.Error'

        expected_msg = MODULE_NOT_FOUND_MSG.format(module_dot_name)
        with pytest.raises(ModuleNotFoundError) as excinfo:
            pickle_load(serialized, safe_to_import=module_dot_name)
        assert expected_msg == str(excinfo.value) 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def test_aifc(h, f):
    import aifc
    if not h.startswith(b'FORM'):
        return None
    if h[8:12] == b'AIFC':
        fmt = 'aifc'
    elif h[8:12] == b'AIFF':
        fmt = 'aiff'
    else:
        return None
    f.seek(0)
    try:
        a = aifc.open(f, 'r')
    except (EOFError, aifc.Error):
        return None
    return (fmt, a.getframerate(), a.getnchannels(),
            a.getnframes(), 8 * a.getsampwidth()) 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def _scan_wave(cls, wav_file):
        """Scan the `wav_file` using soxi

        Support only for integer formats but efficient implementation.

        """
        try:
            with wave.open(wav_file, 'r') as fwav:
                return cls._metawav(
                    fwav.getnchannels(),
                    fwav.getframerate(),
                    fwav.getnframes(),
                    fwav.getnframes() / fwav.getframerate())
        except wave.Error:
            raise ValueError(
                '{}: cannot read file, is it a wav?'.format(wav_file))

    # we use a memoize cache because Audio.load is often called to
    # load only segments of a file. So the cache avoid to reload again
    # and again the same file to extract only a chunk of it. A little
    # maxsize is enough because access to audio chunks are usually
    # ordered. 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def __init__(self, filename, file=None):
        if file is None:
            file = open(filename, 'rb')

        self._file = file

        try:
            self._wave = wave.open(file)
        except wave.Error as e:
            raise WAVEDecodeException(e)

        nchannels, sampwidth, framerate, nframes, comptype, compname = self._wave.getparams()

        self.audio_format = AudioFormat(channels=nchannels, sample_size=sampwidth * 8, sample_rate=framerate)

        self._bytes_per_frame = nchannels * sampwidth
        self._duration = nframes / framerate
        self._duration_per_frame = self._duration / nframes
        self._num_frames = nframes

        self._wave.rewind() 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def readin(file):
    """
    Reads in the given wave file and returns a new PyAudio stream object from it.

    :param file: The path to the file to read in
    :return (waveform, stream): (The actual audio data as a waveform, the PyAudio object for said data)
    """

    # Open the waveform from the command argument
    try:
        waveform = wave.open(file, 'r')
    except wave.Error:
        print('The program can only process wave audio files (.wav)')
        sys.exit()
    except FileNotFoundError:
        print('The chosen file does not exist')
        sys.exit()

    # Load PyAudio and create a useable waveform object
    stream = pa.open(
        format=pa.get_format_from_width(waveform.getsampwidth()),
        channels=waveform.getnchannels(),
        rate=waveform.getframerate(),
        output=True
    )

    # Return the waveform as well as the generated PyAudio stream object
    return waveform, stream 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def __init__(self, fp, sample_rate, sample_width):
        self._fp = fp
        try:
            self._wavep = wave.open(self._fp, 'r')
        except wave.Error as e:
            logging.warning('error opening WAV file: %s, '
                            'falling back to RAW format', e)
            self._fp.seek(0)
            self._wavep = None
        self._sample_rate = sample_rate
        self._sample_width = sample_width
        self._sleep_until = 0 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def wav_read(file_name, mono=False):
    """Reads a wav file and returns it data. If `mono` is \
    set to true, the returned audio data are monophonic.

    :param file_name: The file name of the wav file.
    :type file_name: str
    :param mono: Get mono version.
    :type mono: bool
    :return: The data and the sample rate.
    :rtype: (numpy.core.multiarray.ndarray, int)
    """
    try:
        samples, sample_rate = _load_wav_with_wave(file_name)
        with wave.open(file_name) as wav:
            sample_width = wav.getsampwidth()

        if sample_width == 1:
            # 8 bit case
            samples = (samples.astype(float) / _normFact['int8']) - 1.0
        elif sample_width == 2:
            # 16 bit case
            samples = samples.astype(float) / _normFact['int16']
        elif sample_width == 3:
            # 24 bit case
            samples = samples.astype(float) / _normFact['int24']
    except wave.Error:
        # 32 bit case
        samples, sample_rate = _load_wav_with_scipy(file_name)

    if samples.shape[1] == 1:
        samples = samples.squeeze(-1)

    # mono conversion
    if mono and samples.ndim == 2:
        samples = (samples[:, 0] + samples[:, 1]) * 0.5

    return samples, sample_rate 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def test_wav(h, f):
    import wave
    # 'RIFF' <len> 'WAVE' 'fmt ' <len>
    if not h.startswith(b'RIFF') or h[8:12] != b'WAVE' or h[12:16] != b'fmt ':
        return None
    f.seek(0)
    try:
        w = wave.openfp(f, 'r')
    except (EOFError, wave.Error):
        return None
    return ('wav', w.getframerate(), w.getnchannels(),
                   w.getnframes(), 8*w.getsampwidth()) 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def read_wave_file(filename, use_numpy=False):
    try:
        w = wave.open(filename)
        a = numpy.fromstring(w.readframes(9999999999), dtype=NUMPY_DTYPE)
        if use_numpy:
            return numpy.reshape(a, (w.getnchannels(), -1), 'F')
        else:
            return [
                a[i::w.getnchannels()]
                for i in xrange(w.getnchannels())
            ]
    except wave.Error:
        print "Could not open %s" % filename
        raise 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def test_wav(h, f):
    import wave
    # 'RIFF' <len> 'WAVE' 'fmt ' <len>
    if not h.startswith(b'RIFF') or h[8:12] != b'WAVE' or h[12:16] != b'fmt ':
        return None
    f.seek(0)
    try:
        w = wave.open(f, 'r')
    except (EOFError, wave.Error):
        return None
    return ('wav', w.getframerate(), w.getnchannels(),
                   w.getnframes(), 8*w.getsampwidth()) 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def generate_dir(directory):
    for filename in os.listdir(directory):
        fullpath = os.path.join(os.path.abspath(directory), filename)
        try:
            with wave.open(fullpath) as f:
                n_channels = f.getnchannels()
                width = f.getsampwidth()
                rate = f.getframerate()
                snippet = AudioSnippet(f.readframes(16000))
            for i, e in enumerate(snippet.generate_contrastive()):
                gen_name = os.path.join(directory, "gen-{}-{}".format(i, filename))
                e.save(gen_name)
            print("Generated from {}".format(filename))
        except (wave.Error, IsADirectoryError, PermissionError) as e:
            pass 

# 需要導入模塊: import wave [as 別名]
# 或者: from wave import Error [as 別名]
def clean_dir(directory=".", cutoff_ms=1000):
    """Trims all audio in directory to the loudest window of length cutoff_ms. 1 second is consistent
    with the speech command dataset.

    Args:
        directory: The directory containing all the .wav files. Should have nothing but .wav
        cutoff_ms: The length of time to trim audio to in milliseconds
    """
    for filename in os.listdir(directory):
        fullpath = os.path.join(directory, filename)
        try:
            with wave.open(fullpath) as f:
                n_channels = f.getnchannels()
                width = f.getsampwidth()
                rate = f.getframerate()
                n_samples = int((cutoff_ms / 1000) * rate)
                snippet = AudioSnippet(f.readframes(10 * n_samples))
            snippet.trim_window(n_samples * width)
            with wave.open(fullpath, "w") as f:
                f.setnchannels(n_channels)
                f.setsampwidth(width)
                f.setframerate(rate)
                f.writeframes(snippet.byte_data)
            print("Trimmed {} to {} ms".format(filename, cutoff_ms))
        except (wave.Error, IsADirectoryError, PermissionError) as e:
            pass