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import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
def get_demo_image():
import numpy as np
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)
F = plt.figure(1, (5.5, 3.5))
grid = ImageGrid(F, 111, # similar to subplot(111)
nrows_ncols = (1, 3),
axes_pad = 0.1,
add_all=True,
label_mode = "L",
)
Z, extent = get_demo_image() # demo image
im1=Z
im2=Z[:,:10]
im3=Z[:,10:]
vmin, vmax = Z.min(), Z.max()
for i, im in enumerate([im1, im2, im3]):
ax = grid[i]
ax.imshow(im, origin="lower", vmin=vmin, vmax=vmax, interpolation="nearest")
plt.draw()
plt.show()
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