Hello, scipy.interpolate.fitpack2.InterpolatedUnivariateSpline seems to be a 1d interpolation method. I used the Cookbook/Rebinning-Example to Interpolate. I don't know if it works with InterpolatedUnivariateSpline. I also tried out scipy.interpolate.interpolate.interp2d. But I get an error. Probably somebody knows what I'm doing wrong. Here's the script: import scipy.interpolate #just some data a = numpy.zeros((4,4), dtype=''Float32') oldx= numpy.arange(4) oldy = numpy.arange(4) newx = numpy.zeros((4), dtype=''Float32') newy =numpy.zeros((4), dtype=''Float32') for s in range(8): newx[s] = s * 0.5 newy[s] = s * 0.5 #interpolation intinst = scipy.interpolate.interpolate.interp2d(oldx, oldy, a, kind = 'cubic') interpolated = intinst(newx, newy) And here's the error: /usr/lib/python2.3/site-packages/scipy/interpolate/interpolate.py in __call__(self, x, y, dx, dy) 62 x = atleast_1d(x) 63 y = atleast_1d(y) ---> 64 z,ier=fitpack._fitpack._bispev(*(self.tck+[x,y,dx,dy])) 65 if ier==10: raise ValueError,"Invalid input data" 66 if ier: raise TypeError,"An error occurred" AttributeError: interp2d instance has no attribute 'tck' Thanks for your help. Greetings Maik Maik Trömel wrote:
Date: Tue, 5 Sep 2006 11:29:49 -0400
From: "A. M. Archibald" <peridot.faceted@gmail.com> Subject: Re: [SciPy-user] Interpolate 1D To: "SciPy Users List" <scipy-user@scipy.org> Message-ID: <ce557a360609050829n797be48bv81709ad18bed7e0f@mail.gmail.com> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
On 05/09/06, Maik Tr?mel <maik.troemel@maitro.net> wrote:
Hello list,
when I try to use scipy.interpolate.interpolate.interp1d( olddims[-1], a, kind='cubic' ) I get an ERROR:
File "/usr/lib/python2.3/site-packages/scipy/interpolate/interpolate.py", line 118, in __init__ raise NotImplementedError, "Only linear supported for now. Use "\ NotImplementedError: Only linear supported for now. Use fitpack routines for other types.
But under
http://www.scipy.org/doc/api_docs/scipy.interpolate.interpolate.interp1d.htm...
kind = 'cubic' is listed. Whats wrong with the command? Or is cubic not implemented yet?
Thanks for your help!
It seems not to be implemented, but you can use scipy.interpolate.fitpack2.InterpolatedUnivariateSpline to do the same thing for splines (of various orders). I think it also provides all the handy extras like derivatives and root-finding. It doesn't seem to be able to raise exceptions or insert NaNs for out-of-bound values, it just extrapolates. But otherwise it seems to be the right tool for the job.
A. M. Archibald
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