# Adapted from the gallery example, but replacing the axes method with the function from toolkits.

from matplotlib import cbook
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import numpy as np


def get_demo_image():
    z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
    # z is a numpy array of 15x15
    return z, (-3, 4, -4, 3)

fig, ax = plt.subplots(figsize=[5, 4])

# make data
Z, extent = get_demo_image()
Z2 = np.zeros((150, 150))
ny, nx = Z.shape
Z2[30:30+ny, 30:30+nx] = Z

ax.imshow(Z2, extent=extent, origin="lower")

# inset axes....
axins = inset_axes(ax, width="50%", height="50%")
axins.imshow(Z2, extent=extent, origin="lower")

# sub region of the original image
x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9
axins.set_xlim(x1, x2)
axins.set_ylim(y1, y2)
axins.set_xticklabels([])
axins.set_yticklabels([])

print("main axes position:", ax.get_position())
print("inset axes position:", axins.get_position())

ax.indicate_inset_zoom(axins, edgecolor="black")

plt.show()