Probability surface plot matplotlib

Question

I have 2d values of x and y which span from x - [ 1 , 5 ] and y - [0.1 - 0.5]

How can I plot the 3d surface where the axis are x , y and P(y) in matplotlib ?

I found out the code for doing so in matlab on net but I am unable to understand it and consequently convert it into matplotlib... ( the range of values is completely different for below written code as to what I require )

  mu = [1 -1]; Sigma = [.9 .4; .4 .3];
  [X1,X2] = meshgrid(linspace(-1,3,25)', linspace(-3,1,25)');
  X = [X1(:) X2(:)];
  p = mvnpdf(X, mu, Sigma);
  surf(X1,X2,reshape(p,25,25));

Can someone help me out in doing the exact same thing for matplotlib ( plot_surface perhaps ? )

Answer 1

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.mlab as mlab
import numpy as np

def P(X, Y):
    return mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)      

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

x = np.linspace(-2, 2, 60)
y = np.linspace(-2, 2, 60)
X, Y = np.meshgrid(x, y)
Z = P(X, Y)
surf = ax.plot_surface(X, Y, Z, rstride = 1, cstride = 1, cmap = jet, linewidth = 0)
ax.set_zlim3d(0, Z.max())

plt.show()

yields