[SciPy-dev] Next SciPy release

[David Huard]

Hi all,

I'm trying to fix a bug with the integrate method of the UnivariateSpline
class in the interpolate package (fitpack2.py), and I'd need some help. Here
is what I understood so far.

The fitpack library defines a bunch of function and subroutines with similar
inputs, for instance

*subroutine* splev(t,n,c,k,x,y,m,ier)
integer n,k,m,ier
*real*8* t(n),c(n),x(m),y(m)

*real*8* *function* splint(t,n,c,k,a,b,wrk)
*real*8* a,b
integer n,k
*real*8* t(n),c(n),wrk(n)

Notice that for both, c is a length n vector.

However, in the interface file fitpack.pyf, we have :
for splev :
real*8 dimension(n-k-1),depend(n,k),check(len(c)==n-k-1),intent(in) :: c

and for splint:
real*8 dimension(n),depend(n),check(len(c)==n) :: c

So for splev, c has length (n-k-1) instead of n. However, when splev gets
called from the UnivariateSpline class (with a c of length n-k-1 stored in
_eval_args), it looks like it works. On the other hand, the integral method
calling splint returns an error message like :

0-th dimension must be fixed to 14 but got 10

I filed a ticket (201) with an example that generates this error. From what
I understand, changing the interface for c in splint to copy splev would
solve the problem, but I don't undersand why splev works in the first place,
since the fortran subroutine asks a length n vector.


Thanks,

David


2006/5/19, Ed Schofield <schofield at ftw.at>:
>
> Hi all,
>
> Now that NumPy 0.9.8 is out, I'd like to make a new SciPy release
> (0.4.9) early next week.
>
> Now's the time for any last-minute fixes or documentation improvements
> (hint, hint!)
>
> -- Ed
>
> _______________________________________________
> Scipy-dev mailing list
> Scipy-dev at scipy.net
> http://www.scipy.net/mailman/listinfo/scipy-dev
>
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