human
I am working on the file "NumPy_reflectivity.ipynb".
The first task is:
Let's visualize these components for fun...
Can you write Python program for it?
assistant
#Here is the Python program you requested.

def add_subplot_axes(ax, rect, axisbg='w'):
    """
    Facilitates the addition of a small subplot within another plot.

    From: http://stackoverflow.com/questions/17458580/
    embedding-small-plots-inside-subplots-in-matplotlib

    License: CC-BY-SA

    Args:
        ax (axis): A matplotlib axis.
        rect (list): A rect specifying [left pos, bot pos, width, height]
    Returns:
        axis: The sub-axis in the specified position.
    """
    def axis_to_fig(axis):
        fig = axis.figure

        def transform(coord):
            a = axis.transAxes.transform(coord)
            return fig.transFigure.inverted().transform(a)

        return transform

    fig = plt.gcf()
    left, bottom, width, height = rect
    trans = axis_to_fig(ax)
    x1, y1 = trans((left, bottom))
    x2, y2 = trans((left + width, bottom + height))
    subax = fig.add_axes([x1, y1, x2 - x1, y2 - y1])
    x_labelsize = subax.get_xticklabels()[0].get_size()
    y_labelsize = subax.get_yticklabels()[0].get_size()
    x_labelsize *= rect[2] ** 0.5
    y_labelsize *= rect[3] ** 0.5
    subax.xaxis.set_tick_params(labelsize=x_labelsize)
    subax.yaxis.set_tick_params(labelsize=y_labelsize)
    return subax

from matplotlib import gridspec, spines

fig = plt.figure(figsize=(12, 6))

gs = gridspec.GridSpec(5, 8) 

# Set up axes.
axw = plt.subplot(gs[0, :5])   # Wavelet.
axg = plt.subplot(gs[1:4, :5]) # G
axm = plt.subplot(gs[:, 5])    # m
axe = plt.subplot(gs[:, 6])    # =
axd = plt.subplot(gs[1:4, 7])    # d

cax = add_subplot_axes(axg, [-0.08, 0.05, 0.03, 0.5])

params = {'ha': 'center', 
          'va': 'bottom',
          'size': 40,
          'weight': 'bold',
         }

axw.plot(G[5], 'o', c='r', mew=0)
axw.plot(G[5], 'r', alpha=0.4)
axw.locator_params(axis='y', nbins=3)
axw.text(1, 0.6, "wavelet", color='k')

im = axg.imshow(G, cmap='viridis', aspect='1', interpolation='none')
axg.text(45, G.shape[0]//2, "G", color='w', **params)
axg.axhline(5, color='r')
plt.colorbar(im, cax=cax)

y = np.arange(m.size)
axm.plot(m, y, 'o',...