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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def fill_between(a, b, logy=None, axes=None, **kwargs):
 """ Fill the region between two histograms or graphs. Parameters a : Hist A rootpy Hist b : Hist A rootpy Hist logy : bool, optional (default=None) If True then clip the region between 1E-300 and 1E300. If None (the default) then automatically determine if the axes are log-scale and if this clipping should be performed. axes : matplotlib Axes instance, optional (default=None) The axes to plot on. If None then use the global current axes. kwargs : additional keyword arguments, optional Additional keyword arguments are passed directly to matplotlib's fill_between function. Returns ------- Returns the value from matplotlib's fill_between function. """

    if axes is None:
        axes = plt.gca()
    if logy is None:
        logy = axes.get_yscale() == 'log'
    if not isinstance(a, _Hist) or not isinstance(b, _Hist):
        raise TypeError(
            "fill_between only operates on 1D histograms")
    a.check_compatibility(b, check_edges=True)
    x = []
    top = []
    bottom = []
    for abin, bbin in zip(a.bins(overflow=False), b.bins(overflow=False)):
        up = max(abin.value, bbin.value)
        dn = min(abin.value, bbin.value)
        x.extend([abin.x.low, abin.x.high])
        top.extend([up, up])
        bottom.extend([dn, dn])
    x = np.array(x)
    top = np.array(top)
    bottom = np.array(bottom)
    if logy:
        np.clip(top, 1E-300, 1E300, out=top)
        np.clip(bottom, 1E-300, 1E300, out=bottom)
    return axes.fill_between(x, top, bottom, **kwargs)