如何在Matplotlib中绘制单元格为方形的pcolor图？

Absolutely! The rectangular cells you're seeing happen because Matplotlib automatically scales the x and y axes based on your data's range, which stretches the cells unevenly. To fix this, you just need to enforce equal scaling for both axes so each unit on x matches each unit on y visually.

Here's how to modify your code:

import matplotlib.pyplot as plt
import numpy as np  # Adjust if you're using scipy's meshgrid instead

# Replace with your actual x, y, z data
x = np.linspace(0, 5, 6)
y = np.linspace(0, 5, 6)
z = np.random.rand(5, 5)  # Note: pcolor expects z to be one dimension smaller than X/Y

fig = plt.figure()
X, Y = np.meshgrid(x, y)
plt.pcolor(X, Y, z, edgecolors='k', linewidths=1, snap=True)
plt.colorbar()

# This is the key line to make cells square
plt.axis('equal')

# Alternatively, for more control (great if x/y ranges are very different):
# ax = plt.gca()
# ax.set_aspect('equal', adjustable='box')

plt.show()

What's going on here? #

• plt.axis('equal') forces Matplotlib to display each unit of x and y with the same physical length on the screen. No matter how your x and y ranges compare, this will make every cell in the pcolor grid a perfect square.
• If your x and y data have drastically different ranges (like x spanning 0-100 while y spans 0-10), using ax.set_aspect('equal', adjustable='box') will adjust the overall figure size to fit the square cells without leaving huge empty spaces.

Give this a try—it should fix the rectangular cell issue right away!

内容的提问来源于stack exchange，提问作者Constantinus Spanakis