On Wed, Aug 29, 2012 at 10:46 PM, <josef.pktd@gmail.com> wrote:

On Wed, Aug 29, 2012 at 3:29 PM, eat <e.antero.tammi@gmail.com> wrote:
> Hi,
>
> Apparently I'm somehow misusing the functionality of interp1d(.) or does
> following behavior imply a bug in scipy. A minimum snippet (with plots) to
> demonstrate the problem:
> In []: from scipy.interpolate import interp1d
> In []: n= 1000
> In []: x, y= randn(n), linspace(0, 1, n)
> In []: x.sort()
> In []: plot(x, y, lw= 2)
> Out[]: [<matplotlib.lines.Line2D object at 0x12E190D0>]
>
> In []: f= interp1d(x, y, 'cubic')
> In []: xi= linspace(x.min(), x.max(), n)
> In []: plot(xi, f(xi))
> Out[]: [<matplotlib.lines.Line2D object at 0x12E20830>]

I guess, some x's are too close to each other to fit a cubic
interpolation without a lot of overshooting.

Makes sense, although what are too close seems to be quite conservative:

In []: d= x[1:]- x[:-1]

In []: d.sort()

In []: d[:3]

Out[]: array([ 2.09893021e-06, 2.36059137e-06, 7.52680662e-06])

Regards,

-eat

Reversing x and y looks fine.

Using the splines directly and add a small s>0 might also work.

Josef

>
> Regards,
> -eat
>
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