import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
from mpl_toolkits.mplot3d import axes3d

x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
y = [1, 2, 3, 4, 5, 6, 7, 8]

X, Y = np.meshgrid(x, y)

matrix = np.array([[np.nan, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
                    [np.nan, 1.0, 2.0, 3.0, 4.0, 4.0, 4.0, 3.0, 2.0, 1.0, 1.0],
                    [np.nan, np.nan, 4.0, 5.0, 6.0, 8.0, 6.0, 5.0, 4.0, 3.0, np.nan],
                    [np.nan, np.nan, 7.0, 8.0, 11.0, 12.0, 11.0, 8.0, 7.0, np.nan, np.nan],
                    [np.nan, np.nan, 8.0, 9.0, 10.0, 16.0, 10.0, 9.0, 10.0, 7.0, np.nan],
                    [np.nan, np.nan, np.nan, 12.0, 16.0, 20.0, 16.0, 12.0, 11.0, np.nan, np.nan],
                    [np.nan, np.nan, np.nan, np.nan, 22.0, 24.0, 22.0, 20.0, 18.0, np.nan, np.nan],
                    [np.nan, np.nan, np.nan, np.nan, np.nan, 28.0, 26.0, 25.0, np.nan, np.nan, np.nan]])
maskMat = np.ma.masked_invalid(matrix)
print(maskMat)

fig = plt.figure()
ax = fig.gca(projection = '3d')
normC = mpl.colors.Normalize(vmax = maskMat.max(), vmin = maskMat.min())
colors = mpl.cm.plasma(normC(maskMat))
surf = ax.plot_surface(X, Y, maskMat, norm = normC)
plt.show()