[Scipy-tickets] [SciPy] #1642: BivariateSpline errors with kx=ky=1

SciPy Trac scipy-tickets@scipy....
Sat Apr 14 13:00:36 CDT 2012

#1642: BivariateSpline errors with kx=ky=1
 Reporter:  rgommers                 |       Owner:  somebody   
     Type:  defect                   |      Status:  new        
 Priority:  normal                   |   Milestone:  Unscheduled
Component:  scipy.interpolate        |     Version:  devel      
 Keywords:  surfit, bivariatespline  |  
 This warning was showing up by default for a long time. The cause seems to
 be that the optional nxest/nyest parameters to surfit, which are
 determined in fitpack.pyf, are too small if kx=ky=1.
     >>> x = [1,1,1,2,2,2,4,4,4]
     >>> y = [1,2,3,1,2,3,1,2,3]
     >>> z = array([0,7,8,3,4,7,1,3,4])
     >>> lut = SmoothBivariateSpline(x, y, z, kx=1, ky=1, s=0)
 /Users/rgommers/Code/scipy/scipy/interpolate/fitpack2.py:613: UserWarning:
 The required storage space exceeds the available storage space: nxest
 or nyest too small, or s too small.
 The weighted least-squares spline corresponds to the current set of
 This needs some investigation. I'll filter out the warning for now.

 A likely related problem:
 In [3]: %paste
         x = [1,1,1,2,2,2,3,3,3]
         y = [1,2,3,1,2,3,1,2,3]
         z = [0,7,8,3,4,7,1,3,4]
         s = 0.1
         tx = [1+s,3-s]
         ty = [1+s,3-s]
         lut = LSQBivariateSpline(x,y,z,tx,ty,kx=1,ky=1)
 ## -- End pasted text --
 /Users/rgommers/Code/scipy/scipy/interpolate/fitpack2.py:684: UserWarning:
 The coefficients of the spline returned have been computed as the
 minimal norm least-squares solution of a (numerically) rank deficient
 system (deficiency=7). If deficiency is large, the results may be
 inaccurate. Deficiency may strongly depend on the value of eps.

Ticket URL: <http://projects.scipy.org/scipy/ticket/1642>
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