Use a variable to set alpha opacity in a colormap

I would like to plot the 2 output variables, say map1 and map2, as a function of 2 input variables, say x and y using colormaps. So as to do so, I want to represent map1 using a color scale while map2 would rely on a transparency scale. Yet, the alpha option cannot take an np.array as an argument and the following code is doomed to failure.

fig=plt.figure(num=None, figsize=(21,12), dpi=80, facecolor='w', edgecolor='k')
ax1=plt.subplot(211)
im = ax1.pcolor(map1, cmap='Spectral_r', alpha=map2)
fig.colorbar(im)

Would anybody see a way to do this? I don't want to use another overlapped color scale and really want map2 to be represented with a transparency function so as the visibility of a background grid for instance would tell the reader the amplitude of map2.

You could do this with pcolormesh, and set the alpha for the faces of the QuadMesh afterwards. For example:

import numpy as np
import matplotlib.pyplot as plt

fig,ax = plt.subplots(1)
ax.set_aspect('equal')

# The data array
m1 = np.random.rand(5,5)
# The alpha array. Normalize your map2 to the range 0,1
m2 = np.linspace(0,1,25).reshape(5,5) 

p = ax.pcolormesh(m1)
plt.savefig('myfig.png') # or fig.canvas.draw()

for i,j in zip(p.get_facecolors(),m2.flatten()):
    i[3] = j # Set the alpha value of the RGBA tuple using m2

plt.savefig('myfig.png')

Note: you seem to have to save the figure (or plt.show() or fig.canvas.draw()) after the pcolormesh command, to generate the p.get_facecolors array; that's why I save the figure twice. There is probably a more elegant solution to that, but I can't think of it off the top of my head. Here's the output; notice the alpha increase from the bottom left towards the top right: