scipy's splrep/splev for python interpolation returns nan
Question: I have a [data set](http://users-phys.au.dk/daniel89/test.txt) with the first
column is the `x` data (wavelenght) and the second column is the `y` data
(relative intensity).

I wish to interpolate it on to another `x_new`-data but my problem is that
`splrep` returns `nan`-values:

    
    
    >>import numpy as np
    >>from scipy.interpolate import splrep, splev
    >>d = np.loadtxt("test.txt")
    >>x,y = d[:,0],d[:,1]
    >>
    >>f = splrep( x,y,k=5 )
    >>print f
    >>(array([ 4501.19,  4501.19,  4501.19, ...,  7091.74,  7091.74,  7091.74]), array([ nan,  nan,  nan, ...,   0.,   0.,   0.]), 5)
    

It also happens when I don't specify `k`. Any suggestions how to overcome this
problem?


Answer: Your `x` values probably contain duplicates, use `s=...` keyword argument to
splrep to set a smoothing factor, because if this is not set the splines are
supposed to go through every point _exactly_ which is impossible with
duplicates.

It might be that they are not duplicates but just very close too.

