[SciPy-user] Fitting sphere to 3d data points

[James Vincent]

Hello,

	Is it possible to fit a sphere to 3D data points using  
scipy.optimize.leastsq? I'd like to minimize the residual for the  
distance from the actual x,y,z point and the fitted sphere surface. I  
can see how to minimize for z, but that's not really what I'm looking  
for. Is there a better way to do this? Thanks for any help.

params = a,b,c and r
a,b,c are the fitted center point of the sphere, r is the radius

err = distance-to-center - radius
err = sqrt( x-a)**2 + (y-b)**2 + (z-c)**2) - r



----
James J. Vincent, Ph.D.
National Cancer Institute
National Institutes of Health
Laboratory of Molecular Biology
Building 37, Room 5120
37 Convent Drive, MSC 4264
Bethesda, MD 20892 USA

301-451-8755
jjv5 at nih.gov


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