基本示例：

import matplotlib.pyplot as plt
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
import numpy as np
# Sample data
lons = np.linspace(-180, 180, 1000)
lats = np.linspace(-90, 90, 500)
data = np.random.rand(len(lats), len(lons))  # dummy data for the map
fig, ax = plt.subplots()
ax.imshow(data, extent=[-180, 180, -90, 90], origin='lower')
# Assuming you have your image loaded as a numpy array
img = plt.imread('gradient_image.png')
# Box coordinates, for instance:
box_bottom_left = (-150, -60)
box_top_right = (-100, -30)
box_width = box_top_right[0] - box_bottom_left[0]
box_height = box_top_right[1] - box_bottom_left[1]
# Adjust the image dimensions to fit the bounding box aspect ratio
adjusted_image = plt.imshow(img).set_data(img)
adjusted_image.set_extent([box_bottom_left[0], box_top_right[0], box_bottom_left[1], box_top_right[1]])
# Add the adjusted image to the map
imagebox = OffsetImage(adjusted_image, zoom=1)
ab = AnnotationBbox(imagebox, (box_bottom_left[0], box_bottom_left[1]), frameon=False, boxcoords="data", pad=0)
ax.add_artist(ab)
plt.show()