1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
|
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()
|
