Matplotlib create surface plot (x,y,z,color) given csv data - getting wrong colors

Question

How can I read in four columns of data to create a surface plot which is colored by the fourth variable? In my case, the data was generated using four nested for loops, so the rightmost columns change most frequently while the leftmost columns change least frequently.

Here is what I've tried so far. It is creating a solid colored graph but the coloring is wrong.

import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
import pylab
from scipy.interpolate import griddata

dat = open('ex.csv', 'w')
dat.write('x,y,z,c\n')
for x in range(20):
    for y in range(20):
             dat.write(','.join([str(s) for s in [x,y,x+y,x+y,'\n']]))
dat.close()

fig = matplotlib.pyplot.gcf()
subdat = np.genfromtxt('ex.csv', delimiter=',',skiprows=1)
X = subdat[:,0]
Y = subdat[:,1]
Z = subdat[:,2]
C = subdat[:,3]

xi = np.linspace(X.min(),X.max(),100)
yi = np.linspace(Y.min(),Y.max(),100)

zi = griddata((X, Y), Z, (xi[None,:], yi[:,None]), method='cubic')
ci = griddata((X, Y), C, (xi[None,:], yi[:,None]), method='cubic')

ax1 = fig.add_subplot(111, projection='3d')

xig, yig = np.meshgrid(xi, yi)
surf = ax1.plot_surface(xig, yig, zi,facecolors=cm.rainbow(ci))

m = cm.ScalarMappable(cmap=cm.rainbow)
m.set_array(ci)
col = plt.colorbar(m)
plt.show()

(coloring is wrong, should be the same as elevation value with continuous gradient)

Answer 1

The problem here is that the facecolors aren't normalizing as might be expected. Try this, which does the normalizing explicitely:

norm = matplotlib.colors.Normalize()
surf = ax1.plot_surface(xig, yig, zi, facecolors=cm.rainbow(norm(ci)))