import numpy as np
import matplotlib.pyplot as plt

from mpl_toolkits.axes_grid1.axes_rgb import make_rgb_axes, RGBAxes


def get_demo_image():
    from matplotlib.cbook import get_sample_data
    f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
    z = np.load(f)
    # z is a numpy array of 15x15
    return z, (-3, 4, -4, 3)


def get_rgb():
    Z, extent = get_demo_image()

    Z[Z < 0] = 0.
    Z = Z/Z.max()

    R = Z[:13, :13]
    G = Z[2:, 2:]
    B = Z[:13, 2:]

    return R, G, B


def make_cube(r, g, b):
    ny, nx = r.shape
    R = np.zeros([ny, nx, 3], dtype="d")
    R[:, :, 0] = r
    G = np.zeros_like(R)
    G[:, :, 1] = g
    B = np.zeros_like(R)
    B[:, :, 2] = b

    RGB = R + G + B

    return R, G, B, RGB


def demo_rgb():
    fig, ax = plt.subplots()
    ax_r, ax_g, ax_b = make_rgb_axes(ax, pad=0.02)
    #fig.add_axes(ax_r)
    #fig.add_axes(ax_g)
    #fig.add_axes(ax_b)

    r, g, b = get_rgb()
    im_r, im_g, im_b, im_rgb = make_cube(r, g, b)
    kwargs = dict(origin="lower", interpolation="nearest")
    ax.imshow(im_rgb, **kwargs)
    ax_r.imshow(im_r, **kwargs)
    ax_g.imshow(im_g, **kwargs)
    ax_b.imshow(im_b, **kwargs)


def demo_rgb2():
    fig = plt.figure(2)
    ax = RGBAxes(fig, [0.1, 0.1, 0.8, 0.8], pad=0.0)
    #fig.add_axes(ax)
    #ax.add_RGB_to_figure()

    r, g, b = get_rgb()
    kwargs = dict(origin="lower", interpolation="nearest")
    ax.imshow_rgb(r, g, b, **kwargs)

    ax.RGB.set_xlim(0., 9.5)
    ax.RGB.set_ylim(0.9, 10.6)

    for ax1 in [ax.RGB, ax.R, ax.G, ax.B]:
        for sp1 in ax1.spines.values():
            sp1.set_color("w")
        for tick in ax1.xaxis.get_major_ticks() + ax1.yaxis.get_major_ticks():
            tick.tick1line.set_mec("w")
            tick.tick2line.set_mec("w")

    return ax


demo_rgb()
ax = demo_rgb2()

plt.show() 

• 2023/03/28 Ver=1.03 Python 3.11.2 で確認
• 2020/10/30 Ver=1.01 Python 3.7.8 で確認
• 2018/11/24 Ver=1.01 初版リリース

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