[SciPy-User] creating a 3D surface plot from collected data

[Joe Kington]

Are your data already gridded? Or are they irregularly spaced?  Seeing as
how you mentioned "real" data, I'm assuming they're irregularly spaced.

The iy, ix example assumes that you have a regular grid that has been
exported as an x,y,z file instead of a grid of z coordinates.

If they're not already a regular grid, you'll need to interpolate them onto
a regular grid before using any of the 3D surface plotting routines.

(I'll skip my "interpolation is an artform" rant, here...  For a quick look
splines are fine.)

Look into using the various functions in sp.interpolate.  The example I
threw together below uses a thin-plate spline, but there are lots of other
options.

import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
import scipy.interpolate
from mpl_toolkits.mplot3d import Axes3D

x = np.random.random(10)
y = np.random.random(10)
z = np.random.random(10)

spline = sp.interpolate.Rbf(x,y,z,function='thin-plate')

xi = np.linspace(x.min(), x.max(), 50)
yi = np.linspace(y.min(), y.max(), 50)
xi, yi = np.meshgrid(xi, yi)

zi = spline(xi,yi)

fig = plt.figure()
ax = Axes3D(fig)
ax.plot_surface(xi,yi,zi)
plt.show()

Hope that helps,
-Joe

On Mon, Feb 15, 2010 at 8:17 AM, URI
<zallen at urologicresearchinstitute.org>wrote:

> I am trying to figure out how to create a 3D surface plot from some x,y,z
> data
> that I have.  I don't have any particular preference as to how to do it,
> but
> from poking around on the web it seems like mplot3d should be able to do
> it,
> based on what I see in the tutorial (look at the wireframe or surface plot
> sections):
>
> http://matplotlib.sourceforge.net/mpl_toolkits/mplot3d/tutorial.html
>
> The problem I have is that none of the example source code is based on
> working
> with numbers from actual data.  The only thing I could find that addresses
> this
> issue is at the very bottom of this page under the heading "Another
> Example":
> http://www.scipy.org/Cookbook/Matplotlib/mplot3D
>
> I've tried to duplicate this method but I get errors, and I don't really
> understand it anyway.  The place I get lost is here:
>
> Z = numpy.zeros((len(Y), len(X)), 'Float32')
> for d in data:
>   x, y, z = d
>   ix = int(x * 10)
>   iy = int(y * 10)
>   Z[iy, ix] = z
>
>
> I don't understand how ix and iy are supposed to give me valid indeces for
> the Z
> array (and Python doesn't seem to understand it either, it gives me an
> error at
> that last line).
>
> Can someone either explain this method to me, or point me in a different
> direction?
>
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>
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