def showWaveletCoeff(coefficients, filename='tmp', format='pdf',
    threshold_value=0, color='black', color_threshold='black', figsize=(7, 
    8), title=''):
    """
    Show and save the wavelet and scale coefficients in a plot.

    Parameters
    ----------
    coeff: list of numpy.array's
        With in '0' position the scale coefficients. Equal to the
        ``pywt.wavedec()`` return.
    filename: string
        Optional, is 'tmp' by default. This is the first part of the
        name of the figure.
    format: string
        Optional, is 'pdf' by default. This is the last part of the name of the
        figure. Can be 'png', 'ps', 'eps' and 'svg' too.

    threshold_value: int, float or list.
        Optional, is 0 by default, this means that bothing new happens.
        Otherwise, a line in threshold value will be plotted in all wavelet
        coefficients plots. This value can be a list too, but they was to be
        the same size of wavelet coefficients (without the scale coefficient).

    Returns
    -------
    void:
        Nothing is returned, the plots is show and save.

    See also
    --------
    pywt.wavedec: Function that decomposes the signal in wavelet and
        scale coefficients
    pywt.waverec: Function that recomposes the signal from wavelet and
        scale coefficients

    filtration.filtration: Function that use this function to filter via
        wavelet coefficients

    filtration.filtrationCusum: Function that use Cumulative Sum Control Chart
        and some variation for filter wavelet coefficients.
    """
    import numpy as np
    import matplotlib.pyplot as plt
    if isinstance(threshold_value, (int, float, np.float64, np.int32, np.int64)
        ):
        threshold_list = [threshold_value] * len(coefficients)
    else:
        threshold_list = [0] + list(threshold_value)
    N = len(coefficients) - 1
    fig, ax = plt.subplots(len(coefficients), 1, figsize=figsize)
    ax[0].set_title(title)
    ax[0].plot(coefficients[0], color=color, label='$c_0$ ($c_%d$)' % N)
    ax[0].legend(loc=1)
    ax[0].grid()
    for i in range(1, len(coefficients)):
        ax[i].plot(coefficients[i], color=color, label='$d_%d$ ($d_%d$)' %
            (i - 1, N - i + 1))
        if threshold_list[i] != 0:
            x_min, x_max = ax[i].get_xlim()
            ax[i].hlines(threshold_list[i], x_min, x_max, colors=
                color_threshold, linestyles='dashed')
            ax[i].hlines(-threshold_list[i], x_min, x_max, colors=
                color_threshold, linestyles='dashed', label='$\\lambda$')
        ax[i].legend(loc=1)
        ax[i].grid()
    plt.tight_layout()
    plt.savefig('%s' % filename + '.' + format)
    plt.show()
    return
