如何使用 2D x 和 y 对 RGBA 数组进行 pcolormesh？

Question

I have a RGBA array ( img ) with 2D x and y like this:

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(100)

x = np.arange(10, 20)
y = np.arange(0, 10)
x, y = np.meshgrid(x, y)

img = np.random.randint(low=0, high=255, size=(10, 10, 4))

According to this question , we can pass any array to plot and set the color using img :

fig, axs = plt.subplots()
axs.pcolormesh(x, y, img[:, :,0], color=img.reshape((img.shape[0]*img.shape[1]), 4)/255)

However, it just changed the edgecolors.

I want to show it like axs.imshow(img)

Answer 1

Maybe matplotlib has changed a bit how it works? (Or maybe the old question only works with Basemap ?) Now the colormapping is only assigned when the plot is drawn, so overwriting colors assigned via color= .

What seems to work is a dummy draw and only then assign new colors:

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(100)

x = np.arange(10, 21)
y = np.arange(0, 11)
x, y = np.meshgrid(x, y)

img = np.random.randint(low=0, high=255, size=(10, 10, 4))

fig, ax = plt.subplots()
mesh = ax.pcolormesh(x, y, img[:, :,0])
fig.canvas.draw() # dummy redraw
mesh.set_color(img.reshape(-1, 4)/255)
plt.show()

PS: Also note that img.reshape(-1, 4) is a shortcut (and more maintainable) version of img.reshape(img.shape[0]*img.shape[1], 4) .

Also note that the x and y refer to the borders between the cells, and there need to be one value more than the number of cells in each dimension. Therefore, I incremented np.arange(10, 20) to np.arange(10, 21) , but if you want 10..19 as centers, you need to subtract 0.5 for the position of the border (as eg np.arange(10, 21) - 0.5 )