threshold = bins[np.cumsum(hist) * (bins[1] - bins[0]) > 0.8][0]
mnorm2d = np.ma.masked_less(norm2d, threshold)
com = ndimage.measurements.center_of_mass(mnorm2d)
plt.imshow(norm2d, origin='lower')
plt.scatter(*com[::-1])
plt.show()
ndimage's center_of_mass to calculate the position of a Gaussian peak