Function to offset the "center" of a colormap. Useful for
    data with a negative min and positive max and you want the
    middle of the colormap's dynamic range to be at zero

    Parameters
    ----------
    cmap:
        The matplotlib colormap to be altered
    start:
        Offset from lowest point in the colormap's range.  Defaults to 0.0 (no
        lower ofset). Should be between 0.0 and `midpoint`.
    midpoint:
        The new center of the colormap. Defaults to 0.5 (no shift). Should be
        between 0.0 and 1.0. In general, this should be  1 - vmax/(vmax +
        abs(vmin)) For example if your data range from -15.0 to +5.0 and you
        want the center of the colormap at 0.0, `midpoint` should be set to  1
        - 5/(5 + 15)) or 0.75
    stop:
        Offset from highets point in the colormap's range.  Defaults to 1.0 (no
        upper ofset). Should be between `midpoint` and 1.0.

def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'):
    '''
    Function to offset the "center" of a colormap. Useful for
    data with a negative min and positive max and you want the
    middle of the colormap's dynamic range to be at zero

    Parameters
    ----------
    cmap:
        The matplotlib colormap to be altered
    start:
        Offset from lowest point in the colormap's range.  Defaults to 0.0 (no
        lower ofset). Should be between 0.0 and `midpoint`.
    midpoint:
        The new center of the colormap. Defaults to 0.5 (no shift). Should be
        between 0.0 and 1.0. In general, this should be  1 - vmax/(vmax +
        abs(vmin)) For example if your data range from -15.0 to +5.0 and you
        want the center of the colormap at 0.0, `midpoint` should be set to  1
        - 5/(5 + 15)) or 0.75
    stop:
        Offset from highets point in the colormap's range.  Defaults to 1.0 (no
        upper ofset). Should be between `midpoint` and 1.0.
    '''
    cdict = {
        'red': [],
        'green': [],
        'blue': [],
        'alpha': []
    }

    # regular index to compute the colors
    reg_index = np.linspace(start, stop, 257)

    # shifted index to match the data
    shift_index = np.hstack([
        np.linspace(0.0, midpoint, 128, endpoint=False),
        np.linspace(midpoint, 1.0, 129, endpoint=True)
    ])

    for ri, si in zip(reg_index, shift_index):
        r, g, b, a = cmap(ri)

        cdict['red'].append((si, r, r))
        cdict['green'].append((si, g, g))
        cdict['blue'].append((si, b, b))
        cdict['alpha'].append((si, a, a))

    newcmap = mpl.colors.LinearSegmentedColormap(name, cdict)
    plt.register_cmap(cmap=newcmap)

    return newcmap