how to fit 2D contour plot to 2D gaussian

[reham.mostafa.14268]

I have a 2D contour plot and I want to fit it with 2D Gaussian. This is the script I used to plot the 2D contour.

import numpy as np
from pylab import *
from scipy.stats import kde
x = np.genfromtxt("deltaDEC.dat",delimiter="\n")
y = np.genfromtxt("cosDEC.dat",delimiter="\n")
n = len(x)
H, xedges, yedges = np.histogram2d(x, y, range=[[-40,40], [-40,40]], bins=(50, 50))
extent = [yedges[0], yedges[-1], xedges[0], xedges[-1]]
levels = (400, 200, 100, 50, 20)
cset = contour(H, levels, origin='lower',colors=['black', 'pink','green','blue','red'],linewidths=(1.9, 1.6, 1.5, 1.4),extent=extent)
clabel(cset, inline=1, fontsize=10, fmt='%1.0i')
ylim(-10, 10)
xlim(-40, 40)
xlabel('delta_RA/cos(DEC)')
ylabel('delta_DEC')
for c in cset.collections:
  c.set_linestyle('solid')
colorbar()
show()

How to fit Gaussian to 2D histogram in the same plot?