Jason Moore | 2 Mar 20:44 2015
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Bad news

It doesn't seem like we were selected for the GSoC this year:

https://www.google-melange.com/gsoc/org/list/public/google/gsoc2015

Jason
moorepants.info
+01 530-601-9791

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Aaron Meurer | 2 Mar 20:42 2015
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GSoC Update

So I have some bad news. Google did not accept our application to be a
mentoring organization this year.

We are still in the process of finding out from Google why they did
not accept our application. The most we know now is that they received
"many more applications than they were able to accommodate".

For those of you who were planning to apply, don't fret. We will still
participate under the umbrella of PSF, and possibly others. However,
it is likely that we won't get as many slots as we have in the past,
so you should put extra hard work into your application to make it the
best. I wrote a blog post a few years ago with advice for prospective
students that is still relevant today
https://asmeurersympy.wordpress.com/2011/04/27/advice-for-future-prospective-gsoc-students/.

Aaron Meurer

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Jason Moore | 2 Mar 17:37 2015
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Preprint on Maple's core data structure design

Though this may be interesting to folks here:

https://peerj.com/preprints/504/

Jason
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Luv Agarwal | 2 Mar 01:03 2015
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CAD Implementation - GSoC 2015


Hi,

I am Luv Agarwal, a sophomore pursuing b-tech in computer science. From the past 20 days I have been hopping around CAD (cylindrical algebraic decomposition) and Quantifier Elimination basics, algorithms, improvements and other related stuff to successfully and efficiently implement it. Other than these I read about other uses of CAD like Inequalities solving, collision detection which I suppose can be implemented in the course of Quantifier elimination implementation.

It will be really good if SymPy can perform CAD as it can then be used for quantifier elimination, theorem proving in algebraic geometry, evaluating multiple integrals and in assumptions engine. (Source: https://mattpap.github.io/masters-thesis/html/src/conclusions.html#cylindrical-algebraic-decomposition)

I Plan to implement partial cylindrical algebraic decomposition and quantifier elimination (By - George E. Collins and Hoon Hong). I will check if this partial CAD can be used in other CAD applications. If not then I will make sure that I think of an implementation which can perform both partial as well as full CAD.

My current status of quantifier elimination:

I have read the following:
  1. Collin's original paper Quantifier Elimination for Real Closed Fields by Cylindrical Algebraic Decomposition which contains the core algorithms.
  2. Few papers which talk about the usage of CAD.
  3. Hong's implementation of quantifier elimination from partial cylindrical algebraic decomposition that introduces partial cad which is an enhancement of the complete CAD to perform quantifier elimination.
  4. A small but powerful improvement By Hong in a CAD projection operator.

After all this heavy reading I have a good understanding about the working of these algorithms and what will be needed to implement it. (I have implemented a small  component (projection phase) of CAD for testing purposes). Though I haven't thought about it's  implementation details in SymPy, but I have thought in general. I will soon post those details together with my GSoC proposal.

Also, can someone please update me why FOL (GsoC-2014 by Soumya Dipti Biswas) is not yet merged as quantifier elimination demands it.

Algorithm Functionality:

Input: A quantified formula F.
Output: A quantifier free formula F' (in free variables of F) equivalent to F.

Example:
    >>> F = ForAll(x, x*y=0)
    >>> Reduce(F)
    >>> y = 0

It would be a great help if I can get some community feedbacks.

Thanks.

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mohit shah | 1 Mar 18:46 2015
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GSoC 2015-Electromagnetism

Hi,
  I have gone through the documentation of SymPy and noticed that there is no electromagnetism module available. I would like to work on it this summer as a GSoC project. I have given some thought to it and roughly have a structure in mind. I was thinking of implementing electrostatics, electric fields, potentials, magnetostatics and magnetic fields. I have also written some code to start with the project. 

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Sudhanshu Mishra | 1 Mar 17:03 2015
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Add "Introduction to Contributing" on sympy.org

Hi all,

I think we should put this (https://github.com/sympy/sympy/wiki/introduction-to-contributing) in "Quick links" on sympy.org. It'll be good for newcomers who want to know what to do next.

Regards
Sudhanshu Mishra

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Mihir Wadwekar | 27 Feb 22:45 2015
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GSOC 2015: Extending ODE module.

Hi,

I am Mihir Wadwekar, a 3rd year undergrad pursuing computer science at IIIT Hyderabad. I have been tinkering with Sympy for some time now and have committed 4 patches in it.  I do understand how the codebase works and would like to work upon the ODE module as part of my GSOC 2015 project.

I am planning to extend the solving of 1st-order differential equations using lie groups to also include 2nd order differential equations. 

Currently for first-order differential equation, infinitesimals are generated which fit the linearized symmetry condition. Canonical co-ordinates are derived from these infinitesimals by solving relatively simpler PDE's. These coordinates on substitution make the equation a problem of quadrature. After solving it, the original variables are substituted back to get the solution.

Finding a pair of infinitesimals is the most difficult part of it. There is no easy way to generate them yet and as a result various intelligent guesses are made and tried out till one fits the symmetry condition and makes the ODE invariant. Similar procedure can be used for 2nd order differential equations. However their symmetry condition and the type of guesses for the infinitesimals is different. Also the infinitesimals here have an additional variable( dy/dx ).

The 2nd order part can be built upon the previous structure. There is a function 'infinitesimals' which generates infinitesimals by calling all heuristics functions. This function can be changed to recognize the order of the ODE and call the heuristic functions of that ODE. Some heuristics are common for both ODE's, but still would require some changes due to the presence of an additional variable in 2nd order equations. Other new guesses would be written from scratch. A brief summary of the guesses for 2nd order is provided here.

After generating infinitesimals for 2nd order there are multiple ways to approach the remaining part. Solving through canonical coordinates as done in 1st order eqautions is one of the way. Since it is already implemented for 1st order, I plan to go forward with this approach. However canonical variables may sometimes cause computation failures due to inverse transformations and hence I also want to implement the method of first integrals.

A lot of depth can be added here. More intelligent guesses for 1st and 2nd order equations can also be implemented. Lie groups is a vast field and could itself be a proper module. Your views on the complexity would really help as there is a lot of material to read.

It would be a great boost for ODE solving module if 2nd order differential equations can also be solved through lie groups. Using lie groups is a more generic method and does not require any special classification of ODE. This can form a base for higher-degree ODE's. 

I do have a vision for implementing this is depth but would like to know your initial thoughts on this before I go ahead.

Thanks.

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Jason Moore | 28 Feb 16:50 2015
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Would someone like to introduce SymPy at the PyCon Sage Days?

Viviane Pons (viviane.pons-BFYkhu8ZSXU@public.gmane.org) is hosting a Sage Days during the PyCon sprints (http://wiki.sagemath.org/days67) and would like someone from SymPy to give a short talk to introduce SymPy.

Will anyone be at PyCon and like to give this presentation?

Jason
moorepants.info
+01 530-601-9791

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Darshan Chaudhary | 28 Feb 01:49 2015
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GSoC 2015 Application : Improved PDE solver.

Greetings everyone !

I am Darshan Chaudhary and am pursuing my B.E.(Hons.) from BITS Pilani, Hyd Campus India. I have been active in the SymPy community since the last 2 months. For my GSoC project, I chose to work on the Partial Differential Equations module in SymPy which was started by Manoj Kumar in 2013 but hasn't seen much development since. Currently, it can only handle the most basic 1st order linear PDEs. I propose to extend the functionality of the solver by implementing the Method of Characteristics which will enable it to also solve semi-linear and quasilinear 1st order PDEs.

Also, I plan on adding the ability to classify 2nd order PDEs into Parabolic, Hyperbolic or Elliptic. This classification will serve as the bedrock on which the future endeavor of solving the equations will rest.

I have prepared the first draft of the application : https://github.com/sympy/sympy/wiki/GSoC-2015-Application-:-Darshan-Chaudhary-Improved-PDE-Solver

Kindly review and provide comments/suggestions

Thanks !

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Prakash kumar | 27 Feb 05:51 2015
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Understanding the codebase(GSOC 2015- Solvers)

Hello,

I am a 3rd year Computer Science and Engineering student at G. B. Pant Govt. Engineering College, Delhi,India. I am an aspirant of GSOC 2015. I want to work on the topic of solvers. 
I studied the code of solveset and understood it. Before going further I want to fix this(https://github.com/sympy/sympy/issues/8711) issue for better understanding of head and tail of codebase.
Can you please tell me how should I proceed for fixing the issue?

Thank You
Prakash Kumar
https://github.com/prakash09

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Balkrishna Srivastava | 26 Feb 23:09 2015

GSOC 2015 Aspirant

Hi,

I am a 3rd year undergraduate at BITS PIlani, Pilani Campus, India pursuing my M.Sc. (Hons.) in Physics and B.E.(Hons.) in Computer Science.

I will be through with my M.Sc. this semester, have started with my B.E. last semester, and have been coding in python since last year.

I went through the GSOC 2015 project ideas of SymPy, and I would wish to contribute to the projects under the physics section.

Please guide me how to go ahead with the project ideas.

Thanking You

Regards
Balkrishna Srivastava

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