librosa/display.py
def waveplot(y, sr=22050, max_points=5e4, x_axis='time', offset=0.0,
             max_sr=1000, ax=None, **kwargs):
    '''Plot the amplitude envelope of a waveform.

    If `y` is monophonic, a filled curve is drawn between `[-abs(y), abs(y)]`.

    If `y` is stereo, the curve is drawn between `[-abs(y[1]), abs(y[0])]`,
    so that the left and right channels are drawn above and below the axis,
    respectively.

    Long signals (`duration >= max_points`) are down-sampled to at
    most `max_sr` before plotting.

    Parameters
    ----------
    y : np.ndarray [shape=(n,) or (2,n)]
        audio time series (mono or stereo)

    sr : number > 0 [scalar]
        sampling rate of `y`

    max_points : postive number or None
        Maximum number of time-points to plot: if `max_points` exceeds
        the duration of `y`, then `y` is downsampled.

        If `None`, no downsampling is performed.

    x_axis : str {'time', 'off', 'none'} or None
        If 'time', the x-axis is given time tick-marks.

    ax : matplotlib.axes.Axes or None
        Axes to plot on instead of the default `plt.gca()`.

    offset : float
        Horizontal offset (in seconds) to start the waveform plot

    max_sr : number > 0 [scalar]
        Maximum sampling rate for the visualization

    kwargs
        Additional keyword arguments to `matplotlib.pyplot.fill_between`

    Returns
    -------
    pc : matplotlib.collections.PolyCollection
        The PolyCollection created by `fill_between`.

    See also
    --------
    librosa.core.resample
    matplotlib.pyplot.fill_between


    Examples
    --------
    Plot a monophonic waveform

    >>> import matplotlib.pyplot as plt
    >>> y, sr = librosa.load(librosa.util.example_audio_file(), duration=10)
    >>> plt.figure()
    >>> plt.subplot(3, 1, 1)
    >>> librosa.display.waveplot(y, sr=sr)
    >>> plt.title('Monophonic')

    Or a stereo waveform

    >>> y, sr = librosa.load(librosa.util.example_audio_file(),
    ...                      mono=False, duration=10)
    >>> plt.subplot(3, 1, 2)
    >>> librosa.display.waveplot(y, sr=sr)
    >>> plt.title('Stereo')

    Or harmonic and percussive components with transparency

    >>> y, sr = librosa.load(librosa.util.example_audio_file(), duration=10)
    >>> y_harm, y_perc = librosa.effects.hpss(y)
    >>> plt.subplot(3, 1, 3)
    >>> librosa.display.waveplot(y_harm, sr=sr, alpha=0.25)
    >>> librosa.display.waveplot(y_perc, sr=sr, color='r', alpha=0.5)
    >>> plt.title('Harmonic + Percussive')
    >>> plt.tight_layout()
    '''

    util.valid_audio(y, mono=False)

    if not (isinstance(max_sr, int) and max_sr > 0):
        raise ParameterError('max_sr must be a non-negative integer')

    target_sr = sr
    hop_length = 1

    if max_points is not None:
        if max_points <= 0:
            raise ParameterError('max_points must be strictly positive')

        if max_points < y.shape[-1]:
            target_sr = min(max_sr, (sr * y.shape[-1]) // max_points)

        hop_length = sr // target_sr

        if y.ndim == 1:
            y = __envelope(y, hop_length)
        else:
            y = np.vstack([__envelope(_, hop_length) for _ in y])

    if y.ndim > 1:
        y_top = y[0]
        y_bottom = -y[1]
    else:
        y_top = y
        y_bottom = -y

    axes = __check_axes(ax)

    kwargs.setdefault('color', next(axes._get_lines.prop_cycler)['color'])

    locs = offset + core.frames_to_time(np.arange(len(y_top)),
                                        sr=sr,
                                        hop_length=hop_length)

    out = axes.fill_between(locs, y_bottom, y_top, **kwargs)

    axes.set_xlim([locs.min(), locs.max()])
    if x_axis == 'time':
        axes.xaxis.set_major_formatter(TimeFormatter(lag=False))
        axes.xaxis.set_label_text('Time')
    elif x_axis is None or x_axis in ['off', 'none']:
        axes.set_xticks([])
    else:
        raise ParameterError('Unknown x_axis value: {}'.format(x_axis))

    return out
def waveplot(y, sr=22050, max_points=5e4, x_axis='time', offset=0.0,
             max_sr=1000, ax=None, **kwargs):
    '''Plot the amplitude envelope of a waveform.

    If `y` is monophonic, a filled curve is drawn between `[-abs(y), abs(y)]`.

    If `y` is stereo, the curve is drawn between `[-abs(y[1]), abs(y[0])]`,
    so that the left and right channels are drawn above and below the axis,
    respectively.

    Long signals (`duration >= max_points`) are down-sampled to at
    most `max_sr` before plotting.

    Parameters
    ----------
    y : np.ndarray [shape=(n,) or (2,n)]
        audio time series (mono or stereo)

    sr : number > 0 [scalar]
        sampling rate of `y`

    max_points : postive number or None
        Maximum number of time-points to plot: if `max_points` exceeds
        the duration of `y`, then `y` is downsampled.

        If `None`, no downsampling is performed.

    x_axis : str {'time', 'off', 'none'} or None
        If 'time', the x-axis is given time tick-marks.

    ax : matplotlib.axes.Axes or None
        Axes to plot on instead of the default `plt.gca()`.

    offset : float
        Horizontal offset (in seconds) to start the waveform plot

    max_sr : number > 0 [scalar]
        Maximum sampling rate for the visualization

    kwargs
        Additional keyword arguments to `matplotlib.pyplot.fill_between`

    Returns
    -------
    pc : matplotlib.collections.PolyCollection
        The PolyCollection created by `fill_between`.

    See also
    --------
    librosa.core.resample
    matplotlib.pyplot.fill_between


    Examples
    --------
    Plot a monophonic waveform

    >>> import matplotlib.pyplot as plt
    >>> y, sr = librosa.load(librosa.util.example_audio_file(), duration=10)
    >>> plt.figure()
    >>> plt.subplot(3, 1, 1)
    >>> librosa.display.waveplot(y, sr=sr)
    >>> plt.title('Monophonic')

    Or a stereo waveform

    >>> y, sr = librosa.load(librosa.util.example_audio_file(),
    ...                      mono=False, duration=10)
    >>> plt.subplot(3, 1, 2)
    >>> librosa.display.waveplot(y, sr=sr)
    >>> plt.title('Stereo')

    Or harmonic and percussive components with transparency

    >>> y, sr = librosa.load(librosa.util.example_audio_file(), duration=10)
    >>> y_harm, y_perc = librosa.effects.hpss(y)
    >>> plt.subplot(3, 1, 3)
    >>> librosa.display.waveplot(y_harm, sr=sr, alpha=0.25)
    >>> librosa.display.waveplot(y_perc, sr=sr, color='r', alpha=0.5)
    >>> plt.title('Harmonic + Percussive')
    >>> plt.tight_layout()
    '''

    util.valid_audio(y, mono=False)

    if not (isinstance(max_sr, int) and max_sr > 0):
        raise ParameterError('max_sr must be a non-negative integer')

    target_sr = sr
    hop_length = 1

    if max_points is not None:
        if max_points <= 0:
            raise ParameterError('max_points must be strictly positive')

        if max_points < y.shape[-1]:
            target_sr = min(max_sr, (sr * y.shape[-1]) // max_points)

        hop_length = sr // target_sr

        if y.ndim == 1:
            y = __envelope(y, hop_length)
        else:
            y = np.vstack([__envelope(_, hop_length) for _ in y])

    if y.ndim > 1:
        y_top = y[0]
        y_bottom = -y[1]
    else:
        y_top = y
        y_bottom = -y

    axes = __check_axes(ax)

    kwargs.setdefault('color', next(axes._get_lines.prop_cycler)['color'])

    locs = offset + core.frames_to_time(np.arange(len(y_top)),
                                        sr=sr,
                                        hop_length=hop_length)

    out = axes.fill_between(locs, y_bottom, y_top, **kwargs)

    axes.set_xlim([locs.min(), locs.max()])
    if x_axis == 'time':
        axes.xaxis.set_major_formatter(TimeFormatter(lag=False))
        axes.xaxis.set_label_text('Time')
    elif x_axis is None or x_axis in ['off', 'none']:
        axes.set_xticks([])
    else:
        raise ParameterError('Unknown x_axis value: {}'.format(x_axis))

    return out
def waveplot ( y , sr = 22050 , max_points = 5e4 , x_axis = 'time' , offset = 0.0 , max_sr = 1000 , ax = None , * * kwargs ) : util . valid_audio ( y , mono = False ) if not ( isinstance ( max_sr , int ) and max_sr > 0 ) : raise ParameterError ( 'max_sr must be a non-negative integer' ) target_sr = sr hop_length = 1 if max_points is not None : if max_points <= 0 : raise ParameterError ( 'max_points must be strictly positive' ) if max_points < y . shape [ - 1 ] : target_sr = min ( max_sr , ( sr * y . shape [ - 1 ] ) // max_points ) hop_length = sr // target_sr if y . ndim == 1 : y = __envelope ( y , hop_length ) else : y = np . vstack ( [ __envelope ( _ , hop_length ) for _ in y ] ) if y . ndim > 1 : y_top = y [ 0 ] y_bottom = - y [ 1 ] else : y_top = y y_bottom = - y axes = __check_axes ( ax ) kwargs . setdefault ( 'color' , next ( axes . _get_lines . prop_cycler ) [ 'color' ] ) locs = offset + core . frames_to_time ( np . arange ( len ( y_top ) ) , sr = sr , hop_length = hop_length ) out = axes . fill_between ( locs , y_bottom , y_top , * * kwargs ) axes . set_xlim ( [ locs . min ( ) , locs . max ( ) ] ) if x_axis == 'time' : axes . xaxis . set_major_formatter ( TimeFormatter ( lag = False ) ) axes . xaxis . set_label_text ( 'Time' ) elif x_axis is None or x_axis in [ 'off' , 'none' ] : axes . set_xticks ( [ ] ) else : raise ParameterError ( 'Unknown x_axis value: {}' . format ( x_axis ) ) return out
Plot the amplitude envelope of a waveform.

    If `y` is monophonic, a filled curve is drawn between `[-abs(y), abs(y)]`.

    If `y` is stereo, the curve is drawn between `[-abs(y[1]), abs(y[0])]`,
    so that the left and right channels are drawn above and below the axis,
    respectively.

    Long signals (`duration >= max_points`) are down-sampled to at
    most `max_sr` before plotting.

    Parameters
    ----------
    y : np.ndarray [shape=(n,) or (2,n)]
        audio time series (mono or stereo)

    sr : number > 0 [scalar]
        sampling rate of `y`

    max_points : postive number or None
        Maximum number of time-points to plot: if `max_points` exceeds
        the duration of `y`, then `y` is downsampled.

        If `None`, no downsampling is performed.

    x_axis : str {'time', 'off', 'none'} or None
        If 'time', the x-axis is given time tick-marks.

    ax : matplotlib.axes.Axes or None
        Axes to plot on instead of the default `plt.gca()`.

    offset : float
        Horizontal offset (in seconds) to start the waveform plot

    max_sr : number > 0 [scalar]
        Maximum sampling rate for the visualization

    kwargs
        Additional keyword arguments to `matplotlib.pyplot.fill_between`

    Returns
    -------
    pc : matplotlib.collections.PolyCollection
        The PolyCollection created by `fill_between`.

    See also
    --------
    librosa.core.resample
    matplotlib.pyplot.fill_between


    Examples
    --------
    Plot a monophonic waveform

    >>> import matplotlib.pyplot as plt
    >>> y, sr = librosa.load(librosa.util.example_audio_file(), duration=10)
    >>> plt.figure()
    >>> plt.subplot(3, 1, 1)
    >>> librosa.display.waveplot(y, sr=sr)
    >>> plt.title('Monophonic')

    Or a stereo waveform

    >>> y, sr = librosa.load(librosa.util.example_audio_file(),
    ...                      mono=False, duration=10)
    >>> plt.subplot(3, 1, 2)
    >>> librosa.display.waveplot(y, sr=sr)
    >>> plt.title('Stereo')

    Or harmonic and percussive components with transparency

    >>> y, sr = librosa.load(librosa.util.example_audio_file(), duration=10)
    >>> y_harm, y_perc = librosa.effects.hpss(y)
    >>> plt.subplot(3, 1, 3)
    >>> librosa.display.waveplot(y_harm, sr=sr, alpha=0.25)
    >>> librosa.display.waveplot(y_perc, sr=sr, color='r', alpha=0.5)
    >>> plt.title('Harmonic + Percussive')
    >>> plt.tight_layout()
Plot the amplitude envelope of a waveform .