[Numpy-discussion] nd_image.affine_transform edge effects
Stefan van der Walt
stefan@sun.ac...
Thu Mar 22 20:47:44 CDT 2007
On Thu, Mar 22, 2007 at 04:33:53PM -0700, Travis Oliphant wrote:
> >I would rather opt for changing the spline fitting algorithm than for
> >padding with zeros.
> >
> >
> From what I understand, the splines used in ndimage have the implicit
> mirror-symmetric boundary condition which also allows them to be
> computed rapidly. There may be ways to adapt other boundary conditions
> and maintain rapid evaluation, but it is not trivial as far as I know.
> Standard spline-fitting allows multiple boundary conditions because
> matrix inversion is used. I think the spline-fitting done in ndimage
> relies on equal-spacing and mirror-symmetry to allow simple IIR filters
> to be used to compute the spline coefficients very rapidly.
Thanks, Travis. I wasn't aware of these restrictions.
Would it be possible to call fitpack to do the spline fitting? I
noticed that it doesn't exhibit the same mirror-property:
In [24]: z = scipy.interpolate.splrep([0,1,2,3,4],[0,4,3,2,1])
In [25]: scipy.interpolate.splev([0,1,2,3,4,5],z)
Out[25]:
array([ -1.32724622e-16, 4.00000000e+00, 3.00000000e+00,
2.00000000e+00, 1.00000000e+00, -1.25000000e+00])
Regards
Stéfan
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