[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
knots.
warnings.warn(message)
}}}
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.
warnings.warn(message)
}}}
--
Ticket URL: <http://projects.scipy.org/scipy/ticket/1642>
SciPy <http://www.scipy.org>
SciPy is open-source software for mathematics, science, and engineering.
More information about the Scipy-tickets
mailing list