[SciPy-User] faster interpolations (interp1d)
Tue Mar 1 01:31:13 CST 2011
On Mon, Feb 28, 2011 at 5:25 PM, James McCormac <email@example.com>wrote:
> Hi eat,
> you sent me a suggestion for faster 1d interpolations using matrices a few
> weeks back but I cannot find the email anywhere when I looked for it
> Here is a better explanation of what I am trying to do. For example I have
> a 1d array of 500 elements. I want to interpolate them quadratically so
> each array becomes 10 values, 50,000 in total.
> I have 500x500 pixels and I want to get 0.01 pixel resolution.
> code snipet:
> # collapse an image in the x direction
> # make an array for the 1d spectra
> x = np.linspace(0, (x_2-x_1), (x_2-x_1))
> # interpolation
> f2_xr = interp1d(x, ref_xproj, kind='quadratic')
> # new x array for interpolated data
> xnew = np.linspace(0, (x_2-x_1), (x_2-x_1)*100)
> # FFT of interpolated spectra
> F_ref_xproj = fftpack.fft(f2_xr(xnew))
> Can I do this type of interpolation faster using the method you described
I'll misinterpreted your original question and the method I suggested there
is not applicable.
To better understand your situation, few questions:
- what you described above; it does work for you in technical sense?
- if so, then the problem is with the execution performance?
- what are your current timings?
- how much you'll need to enhance them?
> SciPy-User mailing list
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the SciPy-User