如何使用matplotlib在背景图像上绘制多个子图？

Question

我想在一个国家的地图（图像）上绘制一些散点图。这个想法是描绘绘制图的区域的数据可视化。

所以，这是我绘制map of USA图像的方式，我向左上方和中间绘制的圆圈是我想要显示散点图的地方：

import numpy as np
import matplotlib.pyplot as plt

fig=plt.figure(figsize=(10,15))

im = plt.imread("usa-states-map.jpg")
implot = plt.imshow(im, extent=[0, 200, 0, 150])

# A circle in the upper left region
theta=np.linspace(0,2*np.pi,50)
faux_radius = 15
z=np.cos(theta)*faux_radius + 45
t=np.sin(theta)*faux_radius + 130
plt.plot(z,t)

# A circle in the middle region
theta=np.linspace(0,3*np.pi,50)
faux_radius = 15
z=np.cos(theta)*faux_radius + 100
t=np.sin(theta)*faux_radius + 80
plt.plot(z,t)

这样绘制图像：

我继续绘制散点图，如下：

import numpy as np
import matplotlib.pyplot as plt

fig=plt.figure(figsize=(10,15))

im = plt.imread("usa-states-map.jpg")
implot = plt.imshow(im, extent=[0, 200, 0, 150])

# A circle in the upper left region
theta=np.linspace(0,2*np.pi,50)
faux_radius = 15
z=np.cos(theta)*faux_radius + 45
t=np.sin(theta)*faux_radius + 130
plt.plot(z,t)

# A circle in the middle region
theta=np.linspace(0,3*np.pi,50)
faux_radius = 15
z=np.cos(theta)*faux_radius + 100
t=np.sin(theta)*faux_radius + 80
plt.plot(z,t)

# Scatter plot 1
ax1 = plt.subplot(2,2,1)
ax1.scatter(x_1_a, y_1_a, marker="s")
ax1.scatter(x_1_b, y_1_b, marker="o")

# Scatter plot 2
ax1 = plt.subplot(2,2,2)
ax1.scatter(x_2_a, y_2_a, marker="s")
ax1.scatter(x_2_a, y_2_b, marker="o")

但它产生的输出不会显示背景图像，只会绘制散点图：

[]

我甚至尝试使用zorder，它应该告诉matplotlib哪个图应该在顶部，哪个在底部，但无效 - 它产生与上面相同的输出：

implot = plt.imshow(im, extent=[0, 200, 0, 150], zorder=1)
...
...
...
# Scatter plot 1
ax1 = plt.subplot(2,2,1)
ax1.scatter(x_1_a, y_1_a, marker="s", zorder=2)
ax1.scatter(x_1_b, y_1_b, marker="o", zorder=2)

# Scatter plot 2
ax1 = plt.subplot(2,2,2)
ax1.scatter(x_2_a, y_2_a, marker="s", zorder=3)
ax1.scatter(x_2_a, y_2_b, marker="o", zorder=3)

如何修复此问题以获得所需结果？我甚至不需要在地图上出现2个圆圈 - 这些只是为了说明我想绘制2个散点图的位置。感谢。

Answer 1

我能够使用评论中的plt.axes建议来解决问题：

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

fig = plt.figure(figsize=(10, 15),facecolor='white')
ax = fig.add_axes([0, 0, 1, 1])
ax.axis('off')
im = plt.imread("usa-states-map.jpg")
implot = plt.imshow(im)
plt.xticks([])
plt.yticks([])

# this is an inset axes over the main axes for the top left region
a = plt.axes([.2, .6, .2, .1], facecolor='w')
plt.scatter(x_1_a, y_1_a, marker="s")
plt.scatter(x_1_b, y_1_b, marker="o")
plt.legend(['%.2f%%' %(100*len(x_1_a)/(len(x_1_a)+len(y_1_a))), '%.2f%%' %(100*len(y_1_a)/(len(x_1_a)+len(y_1_a)))], loc='upper right');

# this is an inset axes over the main axes for the middle region
a = plt.axes([.45, .45, .2, .1], facecolor='w')
plt.scatter(x_2_a, y_2_a, marker="s")
plt.scatter(x_2_b, y_2_b, marker="o")
plt.legend(['%.2f%%' %(100*len(x_2_b)/(len(x_2_b)+len(y_2_b))), '%.2f%%' %(100*len(y_2_b)/(len(x_2_b)+len(y_2_b)))], loc='upper right');

plt.show()