gd.py

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator
import numpy as np


fig = plt.figure()
ax = fig.gca(projection='3d')

# Make data.
X = np.arange(1000, 4000, 3)
xlen = len(X)
Y = np.arange(1000, 4000, 3)
ylen = len(Y)
X, Y = np.meshgrid(X, Y)
Z = ((((X/((Y/3.5)+X))*300)*0.3)+(((((X*3.25)+10000)-(Y*3.25))/100)*0.7))-50
Z[Z < 0] = 0
Z2 = 90*np.exp((91/360000)*(X - Y)) + (140/9)*(np.log(X) - np.log(Y))
Z2[Z2 < 0] = 0

# Create an empty array of strings with the same shape as the meshgrid, and
# populate it with two colors in a checkerboard pattern.
colortuple = ('y', 'b')
colortuple2 = ('r', 'r')

colors = np.empty(X.shape, dtype=str)
colors2 = np.empty(X.shape, dtype=str)
for y in range(ylen):
    for x in range(xlen):
        colors[x, y] = colortuple[(x + y) % len(colortuple)]
        colors2[x, y] = colortuple2[(x + y) % len(colortuple2)]

# Plot the surface with face colors taken from the array we made.
surf = ax.plot_surface(X, Y, Z, facecolors=colors, linewidth=0)
surf = ax.plot_surface(X, Y, Z2, facecolors=colors2, linewidth=0)

# Customize the z axis.
ax.set_zlim(0, 150)
ax.w_zaxis.set_major_locator(LinearLocator(6))

plt.show()