spectral methods in Python
Hello guys! I'm new to this list. I'm very interested in spectral methods, and for that purpose I use Python, numpy and scipy a lot. Recently I have made an extension module for Python, consisting of some 85 functions, useful for implementation of spectral methods. It is based on D.Funaro's Fortran library *splib*. Therefore I call my project *pysplib*. Here's the link to my github repo: https://github.com/nikola-m/pysplib The naming scheme of functions is very simple and economic (concieved by D.Funaro). It uses three pairs of letters denoting 1) what item we want to return (nodes, derivative matrices, expansion coefficients,function values,etc.), 2) which orthogonal functions we operate on (Chebyshev,Legendre,Jacobi,Hermite), and 3) what set of points we use (Gauss,Gaus-Lobatto,Gauss-radau). So we have: zechgl - ZEros (nodes) of CHebyshev polynomials at Gauss-Lobatto points or colega - COefficients, LEgendre, GAuss etc. There's a very comprehensive documentation in pdf, covering theoretical aspect of these functions. I would like to get some feedback,so send an email if you have any comments or questions. If it proves useful for scipy as a community, you may adopt it, and maybe include in some module. Regards! -- Nikola Mirkov Research Assistant Institute of Nuclear Sciences "Vinca" Laboratory for Thermal Engineering and Energy Belgrade, Serbia
On Thu, Feb 14, 2013 at 3:05 PM, Nikola Mirkov <largeddysimulation@gmail.com
wrote:
Hello guys! I'm new to this list.
Hi, welcome.
I'm very interested in spectral methods, and for that purpose I use Python, numpy and scipy a lot.
Recently I have made an extension module for Python, consisting of some 85 functions, useful for implementation of spectral methods.
It is based on D.Funaro's Fortran library *splib*. Therefore I call my project *pysplib*.
Here's the link to my github repo: https://github.com/nikola-m/pysplib
The naming scheme of functions is very simple and economic (concieved by D.Funaro). It uses three pairs of letters denoting 1) what item we want to return (nodes, derivative matrices, expansion coefficients,function values,etc.), 2) which orthogonal functions we operate on (Chebyshev,Legendre,Jacobi,Hermite), and 3) what set of points we use (Gauss,Gaus-Lobatto,Gauss-radau). So we have:
zechgl - ZEros (nodes) of CHebyshev polynomials at Gauss-Lobatto points or colega - COefficients, LEgendre, GAuss etc.
There's a very comprehensive documentation in pdf, covering theoretical aspect of these functions.
Link: http://cdm.unimo.it/home/matematica/funaro.daniele/rout.htm
I would like to get some feedback,so send an email if you have any comments or questions. If it proves useful for scipy as a community, you may adopt it, and maybe include in some module.
First observation: licensing seems problematic. The original code doesn't contain a license as far as I can see. Did you ask Prof. Funaro if he's OK with you redistributing his code under the GPL? Even if you did, GPL code is not OK for inclusion in SciPy, it needs to be BSD-compatible. The functionality sounds interesting though. Cheers, Ralf
participants (2)
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Nikola Mirkov
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Ralf Gommers