matplotlib - Python scatter plot for large data -

I have a data set with surface measurement more accurate, I have an array that contains several million 3D digits, Which make a surface when plotted. So far, I have plotted it with the Metalllib Scatter function:

  Import as NP import Import from mpl_toolkits.mplot3d as a plt. Axis 3d fig = plt.figure (figsize = (10,10)) Ax = fig.add_subplot (111, projection = '3d') ax.scatter (x, y, z, s = 0.5, c = z , Cmap = 'hot', marker = '+')  

However, it is very slow, is there any more efficient way to do this? The problem is that I can not just sample large data sets, that is, just say three out of four points, since then the surface becomes transparent quickly.

I think I'm asking too much, but is there any way to get an interactive 3D plot of such a data set?