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jennifer stone
Hello,
This is Jennifer Stupensky. I would like to contribute to NumPy this GSoC. What are the potential projects that can be taken up within the scope of GSoC? Thanks a lot in anticipation
Regards
Jennifer

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Charles R Harris
Hi Jennifer,


On Sat, Jan 18, 2014 at 11:48 AM, jennifer stone <[hidden email]> wrote:
Hello,
This is Jennifer Stupensky. I would like to contribute to NumPy this GSoC. What are the potential projects that can be taken up within the scope of GSoC? Thanks a lot in anticipation
Regards

What are your interests and experience? If you use numpy, are there things you would like to fix, or enhancements you would like to see?

Chuck

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jennifer stone
In reply to this post by jennifer stone

>What are your interests and experience? If you use numpy, are there things
>you would like to fix, or enhancements you would like to see?

Chuck
 
 I am an undergraduate student with CS as major and have interest in Math and Physics. This has led me to use NumPy and SciPy to work on innumerable cases involving special polynomial functions and polynomials like Legendre polynomials, Bessel Functions and so on. So, The packages are closer known to me from this point of view. I have a few proposals in mind. But I don't have any idea if they are acceptable within the scope of GSoC
1. Many special functions and polynomials are neither included in NumPy nor on SciPy.. These include Ellipsoidal Harmonic Functions (lames function), Cylindrical Harmonic function. Scipy at present supports only spherical Harmonic function.
Further, why cant we extend SciPy  to incorporate Inverse Laplace Transforms? At present Matlab has this amazing function ilaplace and SymPy does have Inverse_Laplace_transform but it would be better to incorporate all in one package. I mean SciPy does have function to evaluate laplace transform

After having written this, I feel that this post should have been sent to SciPy
but as a majority of contributors are the same I proceed.
Please suggest any other possible projects, as I would like to continue with SciPy or NumPy, preferably NumPy as I have been fiddling with its source code for a month now and so am pretty comfortable with it.
 
As for my experience, I have known C for past 4 years and have been a python lover for past 1 year. I am pretty new to open source communities, started before a manth and a half.

regards
Jennifer

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Stéfan van der Walt
On Tue, 21 Jan 2014 21:56:17 +0530, jennifer stone wrote:

>  I am an undergraduate student with CS as major and have interest in Math
> and Physics. This has led me to use NumPy and SciPy to work on innumerable
> cases involving special polynomial functions and polynomials like Legendre
> polynomials, Bessel Functions and so on. So, The packages are closer known
> to me from this point of view. I have a* few proposals* in mind. But I
> don't have any idea if they are acceptable within the scope of GSoC
> 1. Many special functions and polynomials are neither included in NumPy nor
> on SciPy.. These include Ellipsoidal Harmonic Functions (lames function),
> Cylindrical Harmonic function. Scipy at present supports only spherical
> Harmonic function.

SciPy's spherical harmonics are very inefficient if one is only interested in
computing one specific order.  I'd be so happy if someone would work on that!

Stéfan

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Charles R Harris
In reply to this post by jennifer stone



On Tue, Jan 21, 2014 at 9:26 AM, jennifer stone <[hidden email]> wrote:

>What are your interests and experience? If you use numpy, are there things
>you would like to fix, or enhancements you would like to see?

Chuck
 
 I am an undergraduate student with CS as major and have interest in Math and Physics. This has led me to use NumPy and SciPy to work on innumerable cases involving special polynomial functions and polynomials like Legendre polynomials, Bessel Functions and so on. So, The packages are closer known to me from this point of view. I have a few proposals in mind. But I don't have any idea if they are acceptable within the scope of GSoC
1. Many special functions and polynomials are neither included in NumPy nor on SciPy.. These include Ellipsoidal Harmonic Functions (lames function), Cylindrical Harmonic function. Scipy at present supports only spherical Harmonic function.
Further, why cant we extend SciPy  to incorporate Inverse Laplace Transforms? At present Matlab has this amazing function ilaplace and SymPy does have Inverse_Laplace_transform but it would be better to incorporate all in one package. I mean SciPy does have function to evaluate laplace transform

After having written this, I feel that this post should have been sent to SciPy
but as a majority of contributors are the same I proceed.
Please suggest any other possible projects, as I would like to continue with SciPy or NumPy, preferably NumPy as I have been fiddling with its source code for a month now and so am pretty comfortable with it.
 
As for my experience, I have known C for past 4 years and have been a python lover for past 1 year. I am pretty new to open source communities, started before a manth and a half.


It does sound like scipy might be a better match, I don't think anyone would complain if you cross posted. Both scipy and numpy require GSOC candidates to have a pull request accepted as part of the application process. I'd suggest implementing a function not currently in scipy that you think would be useful. That would also help in finding a mentor for the summer. I'd also suggest getting familiar with cython.

Chuck  

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Charles R Harris



On Tue, Jan 21, 2014 at 9:46 AM, Charles R Harris <[hidden email]> wrote:



On Tue, Jan 21, 2014 at 9:26 AM, jennifer stone <[hidden email]> wrote:

>What are your interests and experience? If you use numpy, are there things
>you would like to fix, or enhancements you would like to see?

Chuck
 
 I am an undergraduate student with CS as major and have interest in Math and Physics. This has led me to use NumPy and SciPy to work on innumerable cases involving special polynomial functions and polynomials like Legendre polynomials, Bessel Functions and so on. So, The packages are closer known to me from this point of view. I have a few proposals in mind. But I don't have any idea if they are acceptable within the scope of GSoC
1. Many special functions and polynomials are neither included in NumPy nor on SciPy.. These include Ellipsoidal Harmonic Functions (lames function), Cylindrical Harmonic function. Scipy at present supports only spherical Harmonic function.
Further, why cant we extend SciPy  to incorporate Inverse Laplace Transforms? At present Matlab has this amazing function ilaplace and SymPy does have Inverse_Laplace_transform but it would be better to incorporate all in one package. I mean SciPy does have function to evaluate laplace transform

After having written this, I feel that this post should have been sent to SciPy
but as a majority of contributors are the same I proceed.
Please suggest any other possible projects, as I would like to continue with SciPy or NumPy, preferably NumPy as I have been fiddling with its source code for a month now and so am pretty comfortable with it.
 
As for my experience, I have known C for past 4 years and have been a python lover for past 1 year. I am pretty new to open source communities, started before a manth and a half.


It does sound like scipy might be a better match, I don't think anyone would complain if you cross posted. Both scipy and numpy require GSOC candidates to have a pull request accepted as part of the application process. I'd suggest implementing a function not currently in scipy that you think would be useful. That would also help in finding a mentor for the summer. I'd also suggest getting familiar with cython.


I don't see you on github yet, are you there? If not, you should set up an account to work in. See the developer guide for some pointers.

Chuck


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ralfgommers
In reply to this post by Charles R Harris



On Tue, Jan 21, 2014 at 5:46 PM, Charles R Harris <[hidden email]> wrote:



On Tue, Jan 21, 2014 at 9:26 AM, jennifer stone <[hidden email]> wrote:

>What are your interests and experience? If you use numpy, are there things
>you would like to fix, or enhancements you would like to see?

Chuck
 
 I am an undergraduate student with CS as major and have interest in Math and Physics. This has led me to use NumPy and SciPy to work on innumerable cases involving special polynomial functions and polynomials like Legendre polynomials, Bessel Functions and so on. So, The packages are closer known to me from this point of view. I have a few proposals in mind. But I don't have any idea if they are acceptable within the scope of GSoC
1. Many special functions and polynomials are neither included in NumPy nor on SciPy.. These include Ellipsoidal Harmonic Functions (lames function), Cylindrical Harmonic function. Scipy at present supports only spherical Harmonic function.
 
Further, why cant we extend SciPy  to incorporate Inverse Laplace Transforms? At present Matlab has this amazing function ilaplace and SymPy does have Inverse_Laplace_transform but it would be better to incorporate all in one package. I mean SciPy does have function to evaluate laplace transform

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`.
 
After having written this, I feel that this post should have been sent to SciPy
but as a majority of contributors are the same I proceed.
Please suggest any other possible projects,

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.

Cheers,
Ralf


as I would like to continue with SciPy or NumPy, preferably NumPy as I have been fiddling with its source code for a month now and so am pretty comfortable with it.
 
As for my experience, I have known C for past 4 years and have been a python lover for past 1 year. I am pretty new to open source communities, started before a manth and a half.


It does sound like scipy might be a better match, I don't think anyone would complain if you cross posted. Both scipy and numpy require GSOC candidates to have a pull request accepted as part of the application process. I'd suggest implementing a function not currently in scipy that you think would be useful. That would also help in finding a mentor for the summer. I'd also suggest getting familiar with cython.

Chuck  

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jennifer stone
In reply to this post by jennifer stone


 
Both scipy and numpy require GSOC
candidates to have a pull request accepted as part of the application
process. I'd suggest implementing a function not currently in scipy that
you think would be useful. That would also help in finding a mentor for the
summer. I'd also suggest getting familiar with cython.

Chuck
 
Thanks a lot for the heads-up. I am yet to be familiarized with Cython and it indeed is playing a crucial role especially in the 'special' module 

I don't see you on github yet, are you there? If not, you should set up an
account to work in. See the developer guide
<http://docs.scipy.org/doc/numpy/dev/>for some pointers.

Chuck
I am present on github but the profile at present is just a mark of humble mistakes of a beginner to open-sourcing, The id is https://github.com/jennystone.
I hope to build upon my profile.

Jennifer

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jennifer stone
In reply to this post by jennifer stone




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



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ralfgommers



On Thu, Jan 23, 2014 at 11:58 PM, jennifer stone <[hidden email]> 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



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