Re: [Numpy-discussion] (no subject)

Scipy doesn't have a function for the Laplace transform, it has only a
Laplace distribution in scipy.stats and a Laplace filter in scipy.ndimage. An inverse Laplace transform would be very welcome I'd think - it has real world applications, and there's no good implementation in any open source library as far as I can tell. It's probably doable, but not the easiest topic for a GSoC I think. From what I can find, the paper "Numerical Transform Inversion Using Gaussian Quadrature" from den Iseger contains what's considered the current state of the art algorithm. Browsing that gives a reasonable idea of the difficulty of implementing `ilaplace`.
A brief scanning through the paper "Numerical Transform Inversion Using Gaussian Quadrature" from den Iseger does indicate the complexity of the algorithm. But GSoC project or not, can't we work on it, step by step? As I would love to see a contender for Matlab's ilaplace on open source front!!
You can have a look at https://github.com/scipy/scipy/pull/2908/files for ideas. Most of the things that need improving or we really think we should have in Scipy are listed there. Possible topics are not restricted to that list though - it's more important that you pick something you're interested in and have the required background and coding skills for.
Thanks a lot for the roadmap. Of the options provided, I found the 'Cython'ization of Cluster great. Would it be possible to do it as the Summer project if I spend the month learning Cython? Regards Janani
Cheers, Ralf

On Thu, Jan 23, 2014 at 11:58 PM, jennifer stone <jenny.stone125@gmail.com>wrote:
Scipy doesn't have a function for the Laplace transform, it has only a
Laplace distribution in scipy.stats and a Laplace filter in scipy.ndimage. An inverse Laplace transform would be very welcome I'd think - it has real world applications, and there's no good implementation in any open source library as far as I can tell. It's probably doable, but not the easiest topic for a GSoC I think. From what I can find, the paper "Numerical Transform Inversion Using Gaussian Quadrature" from den Iseger contains what's considered the current state of the art algorithm. Browsing that gives a reasonable idea of the difficulty of implementing `ilaplace`.
A brief scanning through the paper "Numerical Transform Inversion Using Gaussian Quadrature" from den Iseger does indicate the complexity of the algorithm. But GSoC project or not, can't we work on it, step by step? As I would love to see a contender for Matlab's ilaplace on open source front!!
Yes, it would be quite nice to have. So if you're interested, by all means give it a go. An issue for a GSoC will be how to maximize the chance of success - typically merging smaller PRs frequently helps a lot in that respect, but we can't merge an ilaplace implementation step by step.
You can have a look at https://github.com/scipy/scipy/pull/2908/files for
ideas. Most of the things that need improving or we really think we should have in Scipy are listed there. Possible topics are not restricted to that list though - it's more important that you pick something you're interested in and have the required background and coding skills for.
Thanks a lot for the roadmap. Of the options provided, I found the 'Cython'ization of Cluster great. Would it be possible to do it as the Summer project if I spend the month learning Cython?
There are a couple of things to consider. Your proposal should be neither too easy nor too ambitious for one summer. Cythonizing cluster is probably not enough for a full summer of work, especially if you can re-use some Cython code that David WF or other people already have. So some new functionality can be added to your proposal. The other important point is that you need to find a mentor. Cluster is one of the smaller modules that doesn't see a lot of development and most of the core devs may not know so well. A good proposal may help find an interested mentor. I suggest you start early with a draft proposal, and iterate a few times based on feedback on this list. You may want to have a look at your email client settings by the way, your replies seem to start new threads. Cheers, Ralf
Regards Janani
Cheers, Ralf
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
participants (2)
-
jennifer stone
-
Ralf Gommers