def __axis_log(data, n_ticks, horiz, sr=22050, kwargs=None,
               secondary_axis='linear', minor=None, **_kwargs):

    axes_phantom = plt.gca()

    if kwargs is None:
        kwargs = dict()

    aspect = kwargs.pop('aspect', None)
    fmt = _kwargs.pop('freq_fmt', 'Hz')

    n, ticker, labeler = __get_shape_artists(data, horiz)
    t_log, t_inv = __log_scale(n)

    if horiz:
        axis = 'x'

        if minor == 'log':
            ax2 = __log_scale(data.shape[0])[0]
        else:
            ax2 = np.arange(data.shape[0])
        ax1 = t_log
    else:
        axis = 'y'
        if minor == 'log':
            ax1 = __log_scale(data.shape[1])[0]
        else:
            ax1 = np.arange(data.shape[1])

        ax2 = t_log

    args = (ax1, ax2, data)

    # NOTE:  2013-11-14 16:15:33 by Brian McFee <brm2132@columbia.edu>
    #  We draw the image twice here. This is a hack to get around
    #  NonUniformImage not properly setting hooks for color.
    #  Drawing twice enables things like colorbar() to work properly.

    im_phantom = img.NonUniformImage(axes_phantom,
                                     extent=(args[0].min(), args[0].max(),
                                             args[1].min(), args[1].max()),
                                     **kwargs)
    im_phantom.set_data(*args)

    kwargs['aspect'] = aspect

    axes_phantom.images[0] = im_phantom

    positions = np.linspace(0, n-1, n_ticks, endpoint=True).astype(int)
    # One extra value here to catch nyquist
    values = np.linspace(0, 0.5 * sr, n, endpoint=True)

    _, label = frequency_ticks(positions, values[t_inv[positions]],
                               n_ticks=None, axis=axis, freq_fmt=fmt)
    labeler(label)
file-like filter output: bold green on white
dataset/ETHPy150Open bmcfee/librosa/librosa/display.py/__axis_log--crossover with--dataset/ETHPy150Open gabrielfalcao/couleur/test_file_filter.py/test_output_bold_green_on_bold_white