Difference between revisions of "Summer of Code - Getting Started"

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The following is distilled from the [[Projects]] page for the benefit of potential [http://code.google.com/soc/Google Summer] [http://sophia.estec.esa.int/socis2012/?q=node/13 of Code] students. Although students are welcome to attempt any of the projects in that page or any of their own choosing, here we offer some suggestions on what good student projects might be.
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{{Note|GNU Octave is a [https://summerofcode.withgoogle.com/programs/2022/organizations/gnu-octave mentoring organization for GSoC 2022].}}
  
= Your steps to apply =
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Since 2011 the GNU Octave project has successfully mentored:
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* [[Summer of Code | '''37 participants''' 🙂]]
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* [[Summer of Code | '''39 projects''' 📝]]
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in [[Summer of Code]] (SoC) programs by [https://summerofcode.withgoogle.com/ Google] and [https://esa.int/ ESA].
  
If you like any of the projects described below these are the steps you need to follow to apply:
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Those SoC programs aim to advertise open-source software development and to attract potential new Octave developers.
  
# Find out that you would like to work together with us this summer!
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= Steps toward a successful application =
# Tell us about that and work on your project proposal. Do this together with us! Best place is your wiki user page, see below.
 
# Fill out our '''''public''''' application template. This is best done by '''[[Special:CreateAccount|creating an account at this wiki]]''' and copying the '''[[Template:Student_application_template_public|template]]''' from its page. <br/> You really only need to copy and answer the '''''public''''' part there, there is no need to showcase everything else to everybody reading your user page!
 
# Fill out our '''''private''''' application template. This is best done by copying the '''[[Template:Student_application_template_private|template]]''' from its page and ''' adding the required information to your application at Google (melange) '''.<br/> Only the organization admin and the possible mentors will see this data.<br/>You can still edit it after submitting until the deadline!
 
# Hang out in our IRC channel, ask questions, submit patches, show us that you are motivated and well-prepared. There sadly will be more applicants than we can mentor with high quality, so do ask for feedback on your public application to increase your odds!
 
# Start implementing your very own proposal! Code the summer away ;-)
 
<noinclude>[[Category:Summer of Code 2013]]</noinclude>
 
  
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# 😉💬 '''We want to get to know you (before the deadline).  Communicate with us.'''
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#* Join [https://octave.discourse.group/ '''Octave Discourse'''] or [[IRC]]. Using a nickname is fine.
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#* Show us that you're motivated to work on Octave 💻.  There is no need to present an overwhelming CV 🏆; evidence of involvement with Octave is more important.
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#* '''<span style="color:darkblue;">If you never talked to us, we will likely reject your proposal</span>''', even it looks good 🚮
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# 👩‍🔬 '''Get your hands dirty.'''
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#* We are curious about your programming skills 🚀
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#** Your application will be much stronger if you [https://savannah.gnu.org/bugs/?group=octave fix Octave bugs] or [https://savannah.gnu.org/patch/?group=octave submit patches] before or during the application period.
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#** You can take a look at the [[short projects]] for some simple bugs to start with.
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#* '''Use Octave!'''
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#** If you come across something that does not work the way you like ➡️ try to fix that 🔧
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#** Or if you find a missing function ➡️ try to implement it.
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# 📝💡 '''Tell us what you are going to do.'''
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#* Do not write just to say what project you're interested in.  Be specific about what you are going to do, include links 🔗, show us you know what you are talking about 💡, and ask many [http://www.catb.org/esr/faqs/smart-questions.html smart questions] 🤓
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#* Remember, '''we are volunteer developers and not your boss''' 🙂
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# 📔 '''Prepare your proposal with us.'''
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#* Try to show us as early as possible a draft of your proposal 📑
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#* If we see your proposal for the first time after the application deadline, it might easily contain some paragraphs not fully clear to us.  Ongoing interaction will give us more confidence that you are capable of working on your project 🙂👍
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#* Then submit the proposal following the applicable rules, e.g. for [https://google.github.io/gsocguides/student/writing-a-proposal GSoC]. 📨
  
= General Guidelines =
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= How do we judge your application? =
  
Octave is mostly written in (sadly, mostly undocumented) C++ and its own scripting language (m-scripts), which includes (or should include) most of the Matlab language as a subset. We generally prefer a different Octave house style to the usual Matlab style for m-scripts, but it's primarily a superficial stylistic difference. Additionally, there are bits and pieces of Fortran, Perl, C, awk, and Unix shell scripts here and there. In addition to being familiar with C++ and/or Octave or Matlab's scripting languages, you should probably be familiar or learn about Octave's infrastructure:
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Depending on the mentors and SoC program there are varieties, but typically the main factors considered would be:
  
* [http://en.wikipedia.org/wiki/GNU_build_system The GNU build system] is used to build Octave. While you generally don't need to understand too much unless you actually want to change how Octave is built, you should be able to understand enough to get a general idea of how to build Octave. If you've ever done a <tt>configure && make && make install</tt> series of commands, you have already used the GNU build system.
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* '''You have demonstrated interest in Octave and an ability to make substantial modifications to Octave'''
* [http://mercurial.selenic.com/ Mercurial] (abbreviated hg) is the [http://en.wikipedia.org/wiki/Distributed_Version_Control_System distributed version control system] (DVCS) we use for managing our source code. You should have some basic understanding of how a DVCS works, but hg is pretty easy to pick up, especially if you already know a VCS like git or svn.
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*: The most important thing is that you've contributed some interesting code samples to judge your skills. It's OK during the application period to ask for help on how to format these code samples, which normally are Mercurial patches.
* You should also read the same [http://www.gnu.org/software/octave/doc/interpreter/Contributing-Guidelines.html#Contributing-Guidelines contributing] [http://hg.savannah.gnu.org/hgweb/octave/file/tip/etc/HACKING guidelines] we have for everyone.
 
* We primarily use [https://mailman.cae.wisc.edu/listinfo/octave-maintainers mailing lists] for communication. You should follow basic mailing list etiquette. For us, this mostly means "do not [http://en.wikipedia.org/wiki/Top_posting#Top-posting top post]".
 
* We also have [http://webchat.freenode.net?channels=octave the #octave IRC channel in Freenode]. The atmosphere is more relaxed, and we may talk about things that are not at all related to Octave.
 
* [http://octave.sf.net Octave-Forge] is a project closely related to Octave where packages reside. They are somewhat analogous to Matlab's toolboxes.
 
* In addition, you probably should know '''some''' mathematics, engineering, or experimental science or something of the sort. If you've used Matlab before, you probably have already been exposed to the kinds of problems that Octave is used for.
 
  
= Suggested projects =
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* '''You showed understanding of your topic'''
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*: Your proposal should make it clear that you're reasonably well versed in the subject area and won't need all summer just to read up on it.
  
The following projects are broadly grouped by category and probable skills required to tackle each. Remember to check [[Projects]] for more ideas if none of these suit you, and your own ideas are always welcome.
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* '''Well thought out, adequately detailed, realistic project plan'''
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*: "I'm good at this, so trust me" isn't enough.  In your proposal, you should describe which algorithms you'll use and how you'll integrate with existing Octave code. You should also prepare a project timeline and goals for the midterm and final evaluations.
  
== Numerical ==
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= What you should know about Octave =
  
These projects involve implementing certain mathematical functions in Octave.
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GNU Octave is mostly written in C++ and its own scripting language that is mostly compatible with Matlab. There are bits and pieces of Fortran, Perl, C, awk, and Unix shell scripts here and there. In addition to being familiar with C++ and Octave's scripting language, you as successful applicant will be familiar with or able to quickly learn about Octave's infrastructure. You can't spend the whole summer learning how to build Octave or prepare a changeset and still successfully complete your project 😇
  
'''Required skills''': You should understand quite a bit of mathematics. Words like "eigenvalue", "analytic", and "Taylor series" shouldn't scare you at all. There is probably little C++ experience required, and probably many of these problems can be solved with m-scripts.
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You should know:
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# How to build Octave from its source code using [http://en.wikipedia.org/wiki/GNU_build_system the GNU build system].
 +
#* Read in this wiki: [[Developer FAQ]], [[Building]]
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#* Tools to know: [https://en.wikipedia.org/wiki/GNU_Compiler_Collection gcc], [https://en.wikipedia.org/wiki/Make_(software) make]
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# How to submit patches (changesets).
 +
#* Read in this wiki: [[Contribution guidelines]], [[Mercurial]]
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#* Tools to know: [https://en.wikipedia.org/wiki/Mercurial Mercurial (hg)], [https://en.wikipedia.org/wiki/Git git]
  
'''Difficulty''': Mid-to-hard depending how much mathematics you know and how well you can read numerical analysis journal articles.
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= Suggested projects =
 
 
'''Potential mentor''': Carlo de Falco, Nir Krakauer, Fotios Kasolis, Luis Gustavo Lira
 
 
 
=== Incomplete sparse factorizations ichol, ilu ===
 
 
 
Implement incomplete Cholesky and LU factorization for sparse matrices. These functions are [http://www.mathworks.it/it/help/matlab/matrix-decomposition.html available in Matlab] as cholinc/ichol and luinc/ilu. Incomplete factorizations are useful as preconditioners
 
for iterative solvers such as [http://hg.savannah.gnu.org/hgweb/octave/file/119ce9f5e1a3/scripts/sparse/gmres.m gmres] and
 
[http://hg.savannah.gnu.org/hgweb/octave/file/119ce9f5e1a3/scripts/sparse/gmres.m gmres] or [http://hg.savannah.gnu.org/hgweb/octave/file/119ce9f5e1a3/scripts/sparse/pcg.m pcg].
 
The classic book [http://netlib.org/linalg/html_templates/node81.html Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods] has a [http://netlib.org/linalg/html_templates/node100.html#SECTION00933000000000000000 chapter] describing the
 
ILU algorithm in detail, though the algorithm described there should be adapted to Octave's internal Sparse Matrix file format which is [http://netlib.org/linalg/html_templates/node92.html#SECTION00931200000000000000 CCS] rather than [http://netlib.org/linalg/html_templates/node91.html#SECTION00931100000000000000 CRS]. The implementation of ILU in Octave has been recently discussed in the maintainers list and initial implementations were posted in this [http://octave.1599824.n4.nabble.com/Ilu-function-tp4648677.html thread]. In another [http://octave.1599824.n4.nabble.com/Re-Octave-maintainers-Digest-Vol-80-Issue-15-tp4646303.html thread] it was suggested to implement the ILU by interfacing Octave to [http://www-users.cs.umn.edu/~saad/software/ITSOL/ ITSOL]. Compared to other
 
projects in this section this one might require more knowledge of C++.
 
 
 
=== General purpose Finite Element library ===
 
 
 
Octave-Forge already has a set of packages for discretizing Partial Differential operators by Finite Elements and/or Finite Volumes,
 
namely the [[bim package]] which relies on the [http://octave.sf.net/msh msh package] (which is in turn based on [http://geuz.org/gmsh/ gmsh]) for creating and managing 2D triangular and 3D tetrahedral meshes and on the [http://octave.sf.net/fpl fpl package] for visualizing 2D results within Octave or exporting 2D or 3D results in a format compatible with [http://www.paraview.org Paraview] or [https://wci.llnl.gov/codes/visit/ VisIT]. These packages, though, offer only a limited choice of spatial discretization methods which are based on low degree polynomials and therefore have a low order of accuracy even for problems with extremely smooth solutions.
 
The [http://geopdes.sf.net GeoPDEs] project, on the other hand, offers a complete suite of functions for discretizing a wide range of
 
differential operators related to important physical problems and uses basis functions of arbitrary polynomial degree that allow the construction of methods of high accuracy. These latter, though, are based on the IsoGeometric Analysis Method which, although very powerful and often better performing, is less widely known and adopted than the Finite Elements Method. The implementation of a general purpose library of Finite Elements seems therefore a valuable addition to Octave-Forge. Two possible interesting choices for implementing this package exist, the first consists of implementing the most common Finite Element spaces in the [http://geopdes.sf.net GeoPDEs] framework, which is possible as IsoGeometric Analysis can be viewed as a superset of the Finite Element Method, the other is to construct Octave language bindings for the free software library [http://fenicsproject.org/documentation/ FEniCS] based on the existing C++ or Python interfaces.
 
 
 
=== Improve logm, sqrtm, funm ===
 
 
 
The goal here is to implement some missing Matlab functions related to matrix functions like the [http://en.wikipedia.org/wiki/Matrix_exponential matrix exponential]. There is [http://octave.1599824.n4.nabble.com/matrix-functions-td3137935.html a general discussion] of the problem.
 
 
 
=== Generalised eigenvalue problem ===
 
 
 
[http://www.mathworks.com/help/techdoc/ref/eig.html Certain calling forms] of the <tt>eig</tt> function are missing. The problem is to understand what those missing forms are and implement them.
 
 
 
=== Various sparse matrix improvements ===
 
 
 
The implementation of sparse matrices in Octave needs several improvements. Any of [[Projects#Sparse Matrices|these]] would be good. The paper by [http://arxiv.org/abs/cs.MS/0604006 Bateman & Adler] is good reading for understanding the sparse matrix implementation.
 
 
 
=== Implement solver for initial-boundary value problems for parabolic-elliptic PDEs in 1D ===
 
 
 
The project will deliver a solver for initial-boundary value problems for parabolic-elliptic PDEs in 1D similar to Matlab's function <tt>pdepe</tt>. A good starting point is the [http://en.wikipedia.org/wiki/Method_of_lines method of lines] for which you can find more details [http://en.wikibooks.org/wiki/Partial_Differential_Equations/Method_of_Lines here] and [http://www.scholarpedia.org/article/Method_of_lines here], whereas an example implementation can be found [http://www.scholarpedia.org/article/Method_of_Lines/Example_Implementation here]. In addition, [http://www.pdecomp.net/ this page] provides some useful material.
 
 
 
=== Implement solver for 1D nonlinear boundary value problems ===
 
 
 
The project will complete the implementation of the bvp4c solver that is already available in an initial version in the odepkg package
 
by adding a proper error estimator and will implement a matlab-compatible version of the bvp5c solver.
 
Details on the methods to be implemented can be found in [http://dx.doi.org/10.1145/502800.502801 this paper] on bvp4c and [http://www.jnaiam.net/new/uploads/files/014dde86eef73328e7ab674d1a32aa9c.pdf this paper] on bvp5c. Further details are available in [http://books.google.it/books/about/Nonlinear_two_point_boundary_value_probl.html?id=s_pQAAAAMAAJ&redir_esc=y this book].
 
 
 
== GUI ==
 
 
 
Octave is currently working on a new native GUI. It is written in Qt, but it is still not ready for production. There are various ways in which it could be improved.
 
 
 
'''Required skills''': C++ and Qt. Whatever tools you want to use to write Qt code are fine, but Qt Creator is a popular choice nowadays.
 
 
 
'''Difficulty''': Mostly medium, depending if you've had Qt or GUI development experience before.
 
 
 
'''Potential mentor''': Jordi Gutiérrez Hermoso, Michael Goffioul, Torsten
 
 
 
=== Finish the Octave GUI ===
 
 
 
The GUI is currently on its own branch in hg. It is not stable enough and its design is still in flux. It is in a very alpha stage and needs to be turned into a real usable product. At the moment, it consists of the basic building blocks (terminal window, editor, variable browser, history, file browser) that are put together into a main interface. The GUI uses the Qt library. Among the things to improve are:
 
* improve integration with octave: variable browser/editor, debugger, profiler...
 
* define and implement an option/preferences dialog
 
* improve additional components like the documentation browser
 
 
 
=== Implement a Qt widget for manipulating plots ===
 
 
 
Octave has had for some time a native OpenGL plotter. The plotter requires some user interaction for manipulating the plots, and it's been using fltk for quite some time. We want to replace this with Qt, so it fits better with the overall GUI look-and-feel and is easier to extend in the future.
 
 
 
[https://github.com/goffioul/QtHandles QtHandles] is a current work in progress integrating the octave OpenGL renderer plus good support for GUI elements (uicontrol, uimenu, uitoolbar...). This project may initially consists of integrating the existing QtHandles code base into Octave. Then if time permits, further improvements can be made to QtHandles.
 
 
 
=== Create a better (G)UI for the profiler ===
 
 
 
During GSoC 2011, Daniel Kraft successfully implemented a profiler for Octave. It needs a better interface and a way to generate reports. This may be done with Qt, but not necessarily, and HTML reports might also be good.
 
 
 
=== Create a graphical design tool for tuning closed loop control system (control pkg) ===
 
 
 
When tuning a SISO feedback system it is very helpful to be able to grab a pole or a zero and move them by dragging them with the mouse. As they are moving the software must update all the plotted lines. There should be the ability to display various graphs rlocuse, bode, step, impulse etc. and have them all change dynamically as the mouse is moving. The parameters of the compensator must be displayed and updated.
 
Potential mentor: Doug Stewart
 
 
 
== Graphics ==
 
 
 
Octave has a new native OpenGL plotter (currently via [http://en.wikipedia.org/wiki/Fltk fltk], but we want to move away from that). There are several possible projects involved with it.
 
 
 
'''Required skills''': C++ and OpenGL. General understanding of computer graphics.
 
 
 
'''Difficulty''': Medium, depending on your previous understanding of the topic.
 
 
 
'''Potential mentor''': Michael Goffioul
 
 
 
=== Lighting ===
 
 
 
Implement transparency and lighting in OpenGL backend(s). A basic implementation is available in [http://octave.svn.sourceforge.net/viewvc/octave/trunk/octave-forge/extra/jhandles/ JHandles]. This needs to be ported/re-implement/re-engineered/optimized in the C++ OpenGL renderer of Octave.
 
 
 
=== Object selection in OpenGL renderer ===
 
 
 
This project is about the implementation of a selection method of graphics elements within the OpenGL renderer [http://glprogramming.com/red/chapter13.html]
 
 
 
=== Non-OpenGL renderer ===
 
 
 
Besides the original gnuplot backend, Octave also contains an OpenGL-based renderer for advanced and more powerful 3D plots. However, OpenGL is not perfectly suited for 2D-only plots where other methods could result in better graphics. The purpose of this project is to implement an alternate graphics renderer for 2D only plots (although 3D is definitely not the focus, extending the new graphics renderer to support basic 3D features should also be taken into account). There is no particular toolkit/library that must be used, but natural candidates are:
 
* [http://qt.nokia.com Qt]: the GUI is currently written in Qt and work is also in progress to provide a Qt/OpenGL based backend [https://github.com/goffioul/QtHandles]
 
* [http://en.wikipedia.org/wiki/Cairo_%28software%29 Cairo]: this library is widely used and known to provides high-quality graphics with support for PS/PDF/SVG output.
 
 
 
=== TeX/LaTeX markup ===
 
 
 
Text objects in plots (like titles, labels, texts...) in the OpenGL renderer only support plain text mode without any formatting possibility. Support for TeX and/or LaTeX formatting needs to be added.
 
 
 
The TeX formatting support actually only consists of a very limited subset of the TeX language. This can be implemented directly in C++ into Octave by extending the existing text engine, avoiding to add a dependency on a full TeX system.
 
 
 
On the other hand, the LaTeX formatting support is expected to provide full LaTeX capabilities. This will require to use an external LaTeX system to produce text graphics in some format (to be specified) that is then integrated into Octave plots.
 
 
 
The matplotlib project [http://matplotlib.sourceforge.net/users/usetex.html has already done this in Python] and might be used as an example of how to do this in Octave.  Mediawiki has also also done [http://en.wikipedia.org/wiki/Wikipedia:Texvc something similar].
 
 
 
== Interpreter ==
 
 
 
The interpreter is written in C++, undocumented. There are many possible projects associated with it.
 
 
 
'''Required skills''': ''Very good'' C and C++ knowledge, possibly also understanding of [http://en.wikipedia.org/wiki/Gnu_bison GNU bison] and [http://en.wikipedia.org/wiki/Flex_lexical_analyser flex]. Understanding how compilers and interpreters are made plus being able to understand how to use a profiler and a debugger will probably be essential skills.
 
 
 
'''Difficulty''': Mid hard to very hard. Some of the biggest problems will probably be the interpreter.
 
 
 
'''Potential mentors''': John W. Eaton, Jordi Gutiérrez Hermoso, Max Brister.
 
 
 
=== Improve JIT compiling ===
 
 
 
Octave's interpreter is ''very'' slow on some loops. Last year, thanks to Max Brister's work, an initial implement of a just-in-time compiler (JITC) in [http://llvm.org LLVM] for GSoC 2012. This project consists in understanding Max's current implementation and extending it so that functions and exponents  (e.g. 2^z) compile with the JITC. This requires knowledge of compilers, C++, LLVM, and the Octave or Matlab languages. A capable student who demonstrates the ability to acquire this knowledge quickly may also be considered. Max himself will mentor this project. [http://planet.octave.org/octconf2012/jit.pdf Here] is Max's OctConf 2012 presentation about his current implementation.
 
 
 
=== Improve memory management ===
 
 
 
From profiling the interpreter, it appears that a lot of time is spending allocating and deallocating memory. A better memory management algorithm might provide some improvement.
 
 
 
=== Implement classdef classes ===
 
 
 
Matlab has two kinds of classes: old style @classes and new style classdef. Octave has only fully implemented the old style. There is partial support for new classes in [http://hg.savannah.gnu.org/hgweb/octave/shortlog/classdef our classdef branch]. There is irregular work here, and classdef is [http://www.mathworks.com/help/matlab/matlab_oop/method-attributes.html a very] [http://www.mathworks.com/help/matlab/events-sending-and-responding-to-messages.html complicated] [http://www.mathworks.com/help/matlab/enumeration-classes.html thing] to fully implement. A successful project would be to implement enough of classdef for most basic usages. Familiarity with Matlab's current classdef support would be a huge plus. Michael Goffioul and jwe can mentor this.
 
 
 
== Infrastructure ==
 
 
 
There are several projects closely related to Octave but not exactly core Octave that could be worked on. They are mostly infrastructure around Octave, stuff that would help a lot.
 
 
 
'''Required skills''': Various. See below.
 
 
 
'''Difficulty''': Various. See below.
 
 
 
'''Potential mentor''': Jordi Gutiérrez Hermoso, Carlo de Falco
 
 
 
=== Finish the Agora website ===
 
 
 
In 2009, the Mathworks decided to restrict the terms of use Matlab Central, a place dedicated to Matlab collaboration. The Mathworks forbade copyleft licenses and using the "free" code found in Matlab central on anything other than Mathworks products (e.g. forbidding from using it on Octave, even if the authors of the code wanted to allow this). Thus Octave users have no place to centrally, quickly, and conveniently share Octave code. See the [[FAQ#Why_can.27t_I_use_code_from_File_Exchange_in_Octave.3F_It.27s_released_under_a_BSD_license.21|FAQ]] for more details.
 
 
 
In response to this, a website started to form, [http://agora.octave.org/ Agora Octave].
 
 
 
This should be relatively easy webdev in Python using [http://en.wikipedia.org/wiki/Django_%28web_framework%29 Django].
 
 
 
Things to be considered when working on this:
 
  
* [http://octave-forge.blogspot.ie/2012/08/octconf2012-agora-and-pkg.html discussion of Agora during OctConf2012]
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The following suggested projects are distilled from the [[Projects]] page for the benefit of potential SoC participants. You can also look at our [[Summer of Code|completed past projects]] for more inspiration.
* [http://scipy-central.org/ Scipy Central] - a website with the same objective as Agora for Scipy. Their [https://github.com/kgdunn/SciPyCentral/ code] is released under a BSD license. Might be useful to reuse some parts.
 
  
Most of the basic functionality of Agora is already in, but there are many ways in which it could be improved, such as implementing comment threads, giving it an email interface, or a ReSTful API which could be used from Octave for package management.
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{{Note|Do you use Octave at your working place or university? Do you have some numerical project in mind?  You are always welcome to '''propose your own projects'''.  If you are passionate about your project, it will be easy to find an Octave developer to mentor and guide you.}}
  
=== Update the Emacs octave mode ===
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== openlibm ==
  
[http://en.wikipedia.org/wiki/Emacs Emacs] has an octave-mode that requires a lot of updating and maintenance. This should also be an easy project if you already use Emacs and [http://en.wikipedia.org/wiki/Elisp elisp].
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Over the years Octave faced many issues (see [[openlibm | the openlibm page in this wiki]] for examples) about different [https://en.wikipedia.org/wiki/C_mathematical_functions#libm C mathematical functions library] (in short: "libm") implementations on various systems.  To overcome similar issues, developers of the [https://en.wikipedia.org/wiki/Julia_(programming_language) Julia Programming Language] started the [https://openlibm.org/ openlibm] project "to have a good libm [ ...] that work[s] consistently across compilers and operating systems, and in 32-bit and 64-bit environments".  openlibm is supported by major Linux distributions (e.g. [https://packages.ubuntu.com/focal/libopenlibm-dev Debian/Ubuntu], [https://src.fedoraproject.org/rpms/openlibm RHEL/Fedora],[https://software.opensuse.org/package/openlibm SLES/openSUSE], ...) and the [https://hg.octave.org/mxe-octave/rev/480f60641fc2 MS Windows MXE package] was added as well.
  
=== Improve binary packaging ===
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This project consists of learning about the usage of [https://en.wikipedia.org/wiki/GNU_Autotools GNU Autotools] in Octave and ways to detect openlibm.  As the next step the Octave code base has to be reviewed under the guidance of a mentor and relevant code changes should be performed.  Finally, relevant code changes in the [[Tests | Octave test suite]] are performed and tested on various Linux, MS Windows, and macOS machines with the help of the Octave community.
  
We would like to be able to easily generate binary packages for Windows and Mac OS X. Right now, it's difficult and tedious to do so. Any way to help us do this in a faster way would be appreciated. Required knowledge is understanding how building binaries in Windows and Mac OS X works. Our current approach to fixing this is to cross-compile from a GNU system using [http://mxe.cc/ MXE] or [http://lilypond.org/gub/ GUB].
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* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
 +
: ~175 hours (easy)
 +
* '''Required skills'''
 +
: Octave, C/C++, Autotools
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/cdf Carlo de Falco], [https://octave.discourse.group/u/siko1056 Kai]
  
'''Skills Required''': Knowledge of GNU build systems, Makefiles, configure files, chasing library dependencies, how to use a compiler. If you choose to work on GUB, Python will be required. No m-scripting or C++ necessary, beyond understanding [http://david.rothlis.net/c/compilation_model/ the C++ compilation model].
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== ode15{i,s} : Matlab Compatible DAE solvers ==
  
'''Difficulty''': Medium to easy. You need to understand how build systems work and how to fix packages when they don't build.
+
An initial implementation of Matlab compatible Differential Algebraic Equations (DAE) solvers, {{manual|ode15i}} and {{manual|ode15s}}, based on [https://computing.llnl.gov/projects/sundials SUNDIALS],
 +
was done by [https://gsoc2016ode15s.blogspot.com/ Francesco Faccio during GSoC 2016].  The code is maintained in the main Octave repository and consists mainly of the following three files: [https://hg.savannah.gnu.org/hgweb/octave/file/tip/libinterp/dldfcn/__ode15__.cc {{path|libinterp/dldfcn/__ode15__.cc}}], [https://hg.savannah.gnu.org/hgweb/octave/file/tip/scripts/ode/ode15i.m {{path|scripts/ode/ode15i.m}}] and [https://hg.savannah.gnu.org/hgweb/octave/file/tip/scripts/ode/ode15s.m {{path|scripts/ode/ode15s.m}}].
  
'''Possible mentors''': John W. Eaton or Jordi Gutiérrez Hermoso
+
The {{manual|decic}} function for selecting consistent initial conditions for ode15i can be made more Matlab compatible by using [http://dx.doi.org/10.1515/JNMA.2002.291 another algorithm].  Another useful extension is to make ode15{i,s} work with datatypes other than double and to improve interpolation at intermediate time steps.
  
=== Installation of packages ===
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
We would like to enhance the management of Octave-forge packages from within Octave environment. Currently there is a working (but rather monolithic) function that is used to do the job. The work would be to improve the way Octave interacts with the package server. Since the functionality is already sketched by the current function, the most important skill is software design.
+
: ~350 hours (medium)
 +
* '''Required skills'''
 +
: Octave, C/C++; familiarity with numerical methods for DAEs
 +
* '''Potential mentors'''
 +
: Francesco Faccio, [https://octave.discourse.group/u/cdf Carlo de Falco], [https://octave.discourse.group/u/marco_caliari Marco Caliari], Jacopo Corno, [https://octave.discourse.group/u/schoeps Sebastian Schöps]
  
'''Minimum requirements''': Ability to read and write Octave code. Minimal FTP/HTTP knowledge.
+
== Symbolic package ==
  
'''Difficulty''': Easy
+
The [[Symbolic package]] provides symbolic computing and other [https://en.wikipedia.org/wiki/Computer_algebra_system computer algebra system] tools.  The main component of Symbolic is a pure m-file class "@sym" which uses the Python package [https://www.sympy.org SymPy] to do (most of) the actual computations.  The package aims to expose much of the functionality of SymPy while also providing a high level of compatibility with the Matlab Symbolic Math Toolbox.  The Symbolic package requires communication between Octave and Python.  In 2016 another GSoC project successfully re-implemented this communication using the new [[Pythonic|Pythonic package]].
  
== Octave-Forge packages ==
+
This project proposes to take this work further while also improving the long-term viability of the Symbolic package.  Some goals include:
 +
* the possibility of using Pythonic directly rather than as one possible communication layer.  For example, we might make "@sym" a subclass of "@pyobject".  We also could stop using the "pycall_sympy__" interface and use Pythonic directly from methods.  Note: there are open questions about how to do this during a transition time when we still support other IPC mechanisms.
 +
* exposing more functionality of SymPy with ''less glue'' in between.  For example, we could allow OO-style method calls such as <code>f.diff(x)</code> as well as <code>diff(f, x)</code>.
 +
* Improvements to the Pythonic package and its long-term maintenance.
 +
* fixing up Symbolic to work with the latest releases of SymPy and Octave.  The project has lagged for a few years and needs some efforts to port to recent and upcoming changes in SymPy code.
 +
* making Symbolic easier to maintain.  The project currently has a low ''bus factor'': improving the CI, making regular releases easier, improving other aspects of maintenance and making the project more welcoming to newcomers.
  
=== Rewrite symbolic package ===
+
Working on this project involves and interesting and challenging mix of m-file code, Python code, and in the case of Pythonic, perhaps some lower-level C code.
Octave's current [http://octave.svn.sourceforge.net/viewvc/octave/trunk/octave-forge/main/symbolic/ symbolic] package for symbolic computation is outdated, fragile and limited in its capabilities. The new symbolic package should offer better Matlab compatibility, for example handling of symbolic matrices. Like the current symbolic package, the new package could use the proven [http://www.ginac.de/ GiNaC] library for symbolic computations.
 
  
The work would be to integrate GiNaC by using Octave's objects and classes. This can be done in C++ in a way similar to Michele Martone's new [http://librsb.sourceforge.net/ sparsersb] package.
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
 +
: ~350 hours (medium)
 +
* '''Required skills'''
 +
: Octave, C/C++, Python; object-oriented programming (OOP) in Octave
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/cbm Colin B. Macdonald], [https://octave.discourse.group/u/mtmiller Mike Miller], Abhinav Tripathi
  
'''Required skills''': C++. Ability to understand Octave and GiNaC API documentation.
+
== Improve TIFF image support ==
  
'''Difficulty''': medium.
+
[https://en.wikipedia.org/wiki/TIFF Tag Image File Format (TIFF)] is the de facto standard for scientific images.  Octave uses the [http://www.graphicsmagick.org/ GraphicsMagic] (GM) C++ library to handle [http://www.graphicsmagick.org/formats.html TIFF and many others image formats]. However, GM still has several limitations:
  
'''Potential mentor''': Lukas Reichlin
+
* GM has build option {{codeline|quantum}} which defines the bitdepth to use when reading an image:
 +
** Building GM with '''high quantum''' means that images of smaller bitdepth will take a lot more memory when reading.
 +
** Building GM with '''low quantum''' will make it impossible to read images of higher bitdepth. It also means that the image needs to always be rescaled to the correct range.
 +
* GM supports unsigned integers only, thus incorrectly reading files such as TIFF with floating-point data.
 +
* GM hides details of the image such as whether the image file is indexed.  This makes it hard to access the real data stored on file.
  
=== Improvements to n-dimensional image processing ===
+
This project aims to implement better TIFF image support using [https://en.wikipedia.org/wiki/Libtiff libtiff], while leaving GM handle all other image formats.  After writing a [https://octave.org/doc/v6.1.0/classdef-Classes.html classdef] interface to libtiff, improve the Octave functions {{manual|imread}}, {{manual|imwrite}}, and {{manual|imfinfo}} to make use of it.
  
The image package has partial functionality for n-dimensional images. These images do exist in practice for example in medical imaging where slices from scans are assembled to form anatomical 3d images, or even exposures taken over time on different wavelengths can result in 5d images. All of the base functions should be modified so that they can handle n-dimensional images, and corresponding Matlab functions such as <code>bwconncomp</code> or n-dimensional version of <code>bwdist</code> should be implemented. In addition,
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
the core functions {{codeline|imwrite}} and {{codeline|imread}} need to be adjusted to deal with this type images (usually multipage TIFF).
+
: ~175 hours (medium)
 +
* '''Required skills'''
 +
: Octave, C/C++
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/carandraug Carnë Draug]
  
'''Required skills''': Mostly m-file scripting, perhaps some C++. Familiarity with common CS algorithms would be useful.
+
== PolarAxes and Plotting Improvements ==
  
'''Difficulty''': medium.
+
Octave currently provides supports for polar axes by using a Cartesian 2-D axes and adding a significant number of properties and callback listeners to get things to work.  What is needed is the implementation of a dedicated "polaraxes" object in C++.  This will require creating a new fundamental graphics object type, and programming in C++/OpenGL to render the object.  When "polaraxes" exists as an object type, then m-files will be written to access them, including polaraxes.m, polarplot.m, rticks.m, rticklabels.m, thetaticks, thetaticklabels.m, rlim.m, thetalim.m.  This relates to bug {{bug|49804}}.
  
'''Potential mentor''': Jordi Gutiérrez Hermoso
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
 +
: ~350 hours (medium)
 +
* '''Required skills'''
 +
: Octave, C/C++; optional experience with OpenGL programming
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/rik Rik]
  
=== Interface to Electronic Circuit Simulator ===
+
== Table datatype ==
  
[http://sourceforge.net/projects/qucs/ Qucs] is a C++ based circuit simulation package. This project aims to create an interface to the Qucs algorithms to allow the transient, i.e. time series, simulation of circuits in Octave within a larger ODE system simulation, and possibly make other analysis types available directly from Octave. The C++ interface would be based on handle class syntax currently in development in the <code>classdef</code> branch of the repository. This method has already been successfully tested on other projects, and examples of this type of interface are available (e.g. [https://sourced.ecdf.ed.ac.uk/projects/see/xfemm here] and [https://www.mathworks.com/matlabcentral/fileexchange/38964-example-matlab-class-wrapper-for-a-c++-class here]).
+
In 2013, Matlab introduced a [https://www.mathworks.com/help/matlab/tables.html new table datatype] to conveniently organize and access data in tabular form. This datatype has not been introduced to Octave yet (see bug {{bug|44571}}).  However, there are two initial implementation approaches https://github.com/apjanke/octave-tablicious and https://github.com/gnu-octave/table.
  
'''Required skills''': C++ and m-file scripting. Familiarity with new classdef syntax would be useful. May require some modification/adaptation of the Qucs sources. Familiarity with the Octave ODE solvers useful but not essential.
+
Based upon the existing approaches, the goal of this project is to define an initial subset of [https://www.mathworks.com/help/matlab/tables.htmlMatlab's table functions], which involve sorting, splitting, merging, and file I/O and implement it within the given time frame.
  
'''Difficulty''': medium.
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
 +
: ~350 hours (hard)
 +
* '''Required skills'''
 +
: Octave, C/C++
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/siko1056 Kai] [https://octave.discourse.group/u/Abdallah_Elshamy Abdallah]
  
'''Potential mentor''': Richard Crozier
+
== YAML encoding/decoding ==
  
'''Main Goals'''
+
[https://en.wikipedia.org/wiki/YAML YAML], is a very common human readable and structured data format. Unfortunately, GNU Octave (and Matlab) still lacks of builtin support of that omnipresent data format. Having YAML support, Octave can easily read and write config files, which often use YAML or JSON. The latter JSON format has been [[Summer of Code#GSoC_2020 | successfully implemented for Octave during GSoC 2020]].
* Create an Octave circuit class which can load and parse a Qucs circuit netlist
 
* Create class methods with functionality similar to the <code>trsolver</code> C++ class methods in Qucs, i.e with the ability to call the DC solution code, and transient solution code at each time step.  
 
* Create a method of accessing the current circuit solution values in Octave at each time step.
 
'''Bonus Goals'''
 
* Create new circuit elements which allow Octave to apply voltages and currents during a circuit simulation.
 
  
 +
The goal of this project is to repeat the GSoC 2020 success story with [https://github.com/biojppm/rapidyaml Rapid YAML] or another fast C/C++ library.
  
=== Fix audio processing ===
+
The first step is research about existing Octave/Matlab and C/C++ implementations, for example:
  
Audio processing is currently almost completely broken in Octave. It currently only works with Linux's Open Sound System, which most Linux installations don't use anymore. We therefore need a modern, cross-platform way to play and record audio. This could be part of the Octave-Forge audio package, but the core audio functions themselves are also lacking. We need this to work across OSes, so an external audio library should be used. [http://www.portaudio.com/ Portaudio] or [http://www.music.mcgill.ca/~gary/rtaudio/ rtaudio] seem like a mature possibility. The core <code>play</code> and <code>record</code> functions should be fixed to use an external audio library, and in addition, the <code>audiorecorder</code> and <code>audioplayer</code> classes should be implemented.
+
* https://code.google.com/archive/p/yamlmatlab/ (uses Java)
 +
* http://vision.is.tohoku.ac.jp/~kyamagu/ja/software/yaml/ (uses Java)
  
'''Required skills''': C++ and probably at least a superficial understanding of signal or audio processing.
+
Then evaluate (and to cherry pick from) existing implementations above, compare strength and weaknesses.  After this, an Octave package containing en- and decoding functions (for example <code>yamlencode</code> and <code>yamldecode</code>) shall be created.  This involves proper documentation of the work and unit tests to ensure the correctness of the implementation.
  
'''Difficulty''': Medium, depending on the abilities of the student.
+
Finally, the package is considered to be merged into core Octave, probably after the GSoC project.  However, it can be used immediately from Octave as package and is backwards-compatible with older Octave versions.
  
'''Possible mentors''': Pantxo Diribarne, Mike Miller
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
 +
: ~175 hours (easy)
 +
* '''Required skills'''
 +
: Octave, C/C++
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/siko1056 Kai], [https://octave.discourse.group/u/Abdallah_Elshamy Abdallah]
  
=== Color management functions in image package ===
+
== TISEAN package ==
  
The goal is to implement these functions:
+
The [[TISEAN package]] provides an Octave interface to [https://www.pks.mpg.de/~tisean/Tisean_3.0.1/index.html TISEAN] is a suite of code for nonlinear time series analysis.  In 2015, another GSoC project started with the work to create interfaces to many TISEAN functions, but [[TISEAN_package:Procedure | there is still work left to do]].  There are missing functions to do computations on spike trains, to simulate autoregresive models, to create specialized plots, etc.  These are of importance for many scientific disciplines involving statistical computations and signal processing.
  
    iccread
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
    iccwrite
+
: ~350 hours (medium)
    makecform
+
* '''Required skills'''
    applycform
+
: Octave, C/C++; FORTRAN API knowledge
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/kakila KaKiLa]
  
These functions are useful for color management, in particular for converting data (especially images) between color spaces.  ICC profiles are essentially used to store look-up tables or matrix transforms (or both) that define the conversions.  For example, to convert an CMYK image to sRGB, you would load a "print" ICC profile that defines the conversion from CMYK to L*a*b* (the CIE color space that is supposed to match the human visual system), then load another profile that defines the conversion from L*a*b* to sRGB (there is a standard profile for this conversion (IEC 61966-2-1), which is why Matlab has a built-in conversion from sRGB to L*a*b*).  To do the above conversions in Matlab, you would use the following code:
+
= Project sizes =
  
<syntaxhighlight lang="octave">
+
Since GSoC 2022 there exist two project sizes<ref>https://groups.google.com/g/google-summer-of-code-announce/c/_ekorpcglB8</ref><ref>https://google.github.io/gsocguides/mentor/defining-a-project-ideas-list</ref>:
cmykImage = double(imread('cmyk-image-filename.tif'));
+
* '''~175 hours''' (~12 weeks, Jun 13 - Sept 12)
iccProfile = iccread('icc-profile-filename.icc');
+
* '''~350 hours''' (~22 weeks, Jun 13 - Nov 21)
labImage = applycform(cmykImage, makecform('clut', iccProfile, 'AToB3'));
 
rgbImage = applycform(labImage, makecform('lab2srgb'));
 
</syntaxhighlight>
 
  
The <code>'AToB3'</code> selects one of the color transforms (look-up tables) contained in the profile.  This one is "Absolute Colorimetric."  More details on ICC profiles may be obtained from [http://www.color.org/icc_specs2.xalter the ICC spec].
+
= Footnotes =
  
Knowledge of ICC profiles (at least knowledge of their application) would be a prerequisite.  Since [http://www.littlecms.com/ littlecms] implements all the necessary functions for reading, writing, and applying profiles, it would be primarily a matter of integrating this library into Octave (assuming that is the preferred implementation -- one could certainly read the ICC files directly, but why reinvent that particular wheel).
+
<references />
  
'''Required skills''': C++ programming, some knowledge of ICC profiles desirable.
+
= See also =
  
'''Difficulty''': Easy.
+
* https://summerofcode.withgoogle.com/
 +
* [https://google.github.io/gsocguides/student/ GSoC Student Guide]
 +
* [https://google.github.io/gsocguides/mentor/ GSoC Mentor Guide]
 +
* [https://developers.google.com/open-source/gsoc/timeline GSoC Timeline]
  
'''Possible Mentor''': Patrick Noffke <patrick.noffke@gmail.com>
+
[[Category:Summer of Code]]
 +
[[Category:Project Ideas]]

Latest revision as of 11:09, 15 April 2022

Info icon.svg

Since 2011 the GNU Octave project has successfully mentored:

in Summer of Code (SoC) programs by Google and ESA.

Those SoC programs aim to advertise open-source software development and to attract potential new Octave developers.

Steps toward a successful application[edit]

  1. 😉💬 We want to get to know you (before the deadline). Communicate with us.
    • Join Octave Discourse or IRC. Using a nickname is fine.
    • Show us that you're motivated to work on Octave 💻. There is no need to present an overwhelming CV 🏆; evidence of involvement with Octave is more important.
    • If you never talked to us, we will likely reject your proposal, even it looks good 🚮
  2. 👩‍🔬 Get your hands dirty.
    • We are curious about your programming skills 🚀
    • Use Octave!
      • If you come across something that does not work the way you like ➡️ try to fix that 🔧
      • Or if you find a missing function ➡️ try to implement it.
  3. 📝💡 Tell us what you are going to do.
    • Do not write just to say what project you're interested in. Be specific about what you are going to do, include links 🔗, show us you know what you are talking about 💡, and ask many smart questions 🤓
    • Remember, we are volunteer developers and not your boss 🙂
  4. 📔 Prepare your proposal with us.
    • Try to show us as early as possible a draft of your proposal 📑
    • If we see your proposal for the first time after the application deadline, it might easily contain some paragraphs not fully clear to us. Ongoing interaction will give us more confidence that you are capable of working on your project 🙂👍
    • Then submit the proposal following the applicable rules, e.g. for GSoC. 📨

How do we judge your application?[edit]

Depending on the mentors and SoC program there are varieties, but typically the main factors considered would be:

  • You have demonstrated interest in Octave and an ability to make substantial modifications to Octave
    The most important thing is that you've contributed some interesting code samples to judge your skills. It's OK during the application period to ask for help on how to format these code samples, which normally are Mercurial patches.
  • You showed understanding of your topic
    Your proposal should make it clear that you're reasonably well versed in the subject area and won't need all summer just to read up on it.
  • Well thought out, adequately detailed, realistic project plan
    "I'm good at this, so trust me" isn't enough. In your proposal, you should describe which algorithms you'll use and how you'll integrate with existing Octave code. You should also prepare a project timeline and goals for the midterm and final evaluations.

What you should know about Octave[edit]

GNU Octave is mostly written in C++ and its own scripting language that is mostly compatible with Matlab. There are bits and pieces of Fortran, Perl, C, awk, and Unix shell scripts here and there. In addition to being familiar with C++ and Octave's scripting language, you as successful applicant will be familiar with or able to quickly learn about Octave's infrastructure. You can't spend the whole summer learning how to build Octave or prepare a changeset and still successfully complete your project 😇

You should know:

  1. How to build Octave from its source code using the GNU build system.
  2. How to submit patches (changesets).

Suggested projects[edit]

The following suggested projects are distilled from the Projects page for the benefit of potential SoC participants. You can also look at our completed past projects for more inspiration.

Info icon.svg
Do you use Octave at your working place or university? Do you have some numerical project in mind? You are always welcome to propose your own projects. If you are passionate about your project, it will be easy to find an Octave developer to mentor and guide you.

openlibm[edit]

Over the years Octave faced many issues (see the openlibm page in this wiki for examples) about different C mathematical functions library (in short: "libm") implementations on various systems. To overcome similar issues, developers of the Julia Programming Language started the openlibm project "to have a good libm [ ...] that work[s] consistently across compilers and operating systems, and in 32-bit and 64-bit environments". openlibm is supported by major Linux distributions (e.g. Debian/Ubuntu, RHEL/Fedora,SLES/openSUSE, ...) and the MS Windows MXE package was added as well.

This project consists of learning about the usage of GNU Autotools in Octave and ways to detect openlibm. As the next step the Octave code base has to be reviewed under the guidance of a mentor and relevant code changes should be performed. Finally, relevant code changes in the Octave test suite are performed and tested on various Linux, MS Windows, and macOS machines with the help of the Octave community.

  • Project size [?] and Difficulty
~175 hours (easy)
  • Required skills
Octave, C/C++, Autotools
  • Potential mentors
Carlo de Falco, Kai

ode15{i,s} : Matlab Compatible DAE solvers[edit]

An initial implementation of Matlab compatible Differential Algebraic Equations (DAE) solvers, ode15i and ode15s, based on SUNDIALS, was done by Francesco Faccio during GSoC 2016. The code is maintained in the main Octave repository and consists mainly of the following three files: libinterp/dldfcn/__ode15__.cc, scripts/ode/ode15i.m and scripts/ode/ode15s.m.

The decic function for selecting consistent initial conditions for ode15i can be made more Matlab compatible by using another algorithm. Another useful extension is to make ode15{i,s} work with datatypes other than double and to improve interpolation at intermediate time steps.

  • Project size [?] and Difficulty
~350 hours (medium)
  • Required skills
Octave, C/C++; familiarity with numerical methods for DAEs
  • Potential mentors
Francesco Faccio, Carlo de Falco, Marco Caliari, Jacopo Corno, Sebastian Schöps

Symbolic package[edit]

The Symbolic package provides symbolic computing and other computer algebra system tools. The main component of Symbolic is a pure m-file class "@sym" which uses the Python package SymPy to do (most of) the actual computations. The package aims to expose much of the functionality of SymPy while also providing a high level of compatibility with the Matlab Symbolic Math Toolbox. The Symbolic package requires communication between Octave and Python. In 2016 another GSoC project successfully re-implemented this communication using the new Pythonic package.

This project proposes to take this work further while also improving the long-term viability of the Symbolic package. Some goals include:

  • the possibility of using Pythonic directly rather than as one possible communication layer. For example, we might make "@sym" a subclass of "@pyobject". We also could stop using the "pycall_sympy__" interface and use Pythonic directly from methods. Note: there are open questions about how to do this during a transition time when we still support other IPC mechanisms.
  • exposing more functionality of SymPy with less glue in between. For example, we could allow OO-style method calls such as f.diff(x) as well as diff(f, x).
  • Improvements to the Pythonic package and its long-term maintenance.
  • fixing up Symbolic to work with the latest releases of SymPy and Octave. The project has lagged for a few years and needs some efforts to port to recent and upcoming changes in SymPy code.
  • making Symbolic easier to maintain. The project currently has a low bus factor: improving the CI, making regular releases easier, improving other aspects of maintenance and making the project more welcoming to newcomers.

Working on this project involves and interesting and challenging mix of m-file code, Python code, and in the case of Pythonic, perhaps some lower-level C code.

  • Project size [?] and Difficulty
~350 hours (medium)
  • Required skills
Octave, C/C++, Python; object-oriented programming (OOP) in Octave
  • Potential mentors
Colin B. Macdonald, Mike Miller, Abhinav Tripathi

Improve TIFF image support[edit]

Tag Image File Format (TIFF) is the de facto standard for scientific images. Octave uses the GraphicsMagic (GM) C++ library to handle TIFF and many others image formats. However, GM still has several limitations:

  • GM has build option quantum which defines the bitdepth to use when reading an image:
    • Building GM with high quantum means that images of smaller bitdepth will take a lot more memory when reading.
    • Building GM with low quantum will make it impossible to read images of higher bitdepth. It also means that the image needs to always be rescaled to the correct range.
  • GM supports unsigned integers only, thus incorrectly reading files such as TIFF with floating-point data.
  • GM hides details of the image such as whether the image file is indexed. This makes it hard to access the real data stored on file.

This project aims to implement better TIFF image support using libtiff, while leaving GM handle all other image formats. After writing a classdef interface to libtiff, improve the Octave functions imread, imwrite, and imfinfo to make use of it.

  • Project size [?] and Difficulty
~175 hours (medium)
  • Required skills
Octave, C/C++
  • Potential mentors
Carnë Draug

PolarAxes and Plotting Improvements[edit]

Octave currently provides supports for polar axes by using a Cartesian 2-D axes and adding a significant number of properties and callback listeners to get things to work. What is needed is the implementation of a dedicated "polaraxes" object in C++. This will require creating a new fundamental graphics object type, and programming in C++/OpenGL to render the object. When "polaraxes" exists as an object type, then m-files will be written to access them, including polaraxes.m, polarplot.m, rticks.m, rticklabels.m, thetaticks, thetaticklabels.m, rlim.m, thetalim.m. This relates to bug #49804.

  • Project size [?] and Difficulty
~350 hours (medium)
  • Required skills
Octave, C/C++; optional experience with OpenGL programming
  • Potential mentors
Rik

Table datatype[edit]

In 2013, Matlab introduced a new table datatype to conveniently organize and access data in tabular form. This datatype has not been introduced to Octave yet (see bug #44571). However, there are two initial implementation approaches https://github.com/apjanke/octave-tablicious and https://github.com/gnu-octave/table.

Based upon the existing approaches, the goal of this project is to define an initial subset of table functions, which involve sorting, splitting, merging, and file I/O and implement it within the given time frame.

  • Project size [?] and Difficulty
~350 hours (hard)
  • Required skills
Octave, C/C++
  • Potential mentors
Kai Abdallah

YAML encoding/decoding[edit]

YAML, is a very common human readable and structured data format. Unfortunately, GNU Octave (and Matlab) still lacks of builtin support of that omnipresent data format. Having YAML support, Octave can easily read and write config files, which often use YAML or JSON. The latter JSON format has been successfully implemented for Octave during GSoC 2020.

The goal of this project is to repeat the GSoC 2020 success story with Rapid YAML or another fast C/C++ library.

The first step is research about existing Octave/Matlab and C/C++ implementations, for example:

Then evaluate (and to cherry pick from) existing implementations above, compare strength and weaknesses. After this, an Octave package containing en- and decoding functions (for example yamlencode and yamldecode) shall be created. This involves proper documentation of the work and unit tests to ensure the correctness of the implementation.

Finally, the package is considered to be merged into core Octave, probably after the GSoC project. However, it can be used immediately from Octave as package and is backwards-compatible with older Octave versions.

  • Project size [?] and Difficulty
~175 hours (easy)
  • Required skills
Octave, C/C++
  • Potential mentors
Kai, Abdallah

TISEAN package[edit]

The TISEAN package provides an Octave interface to TISEAN is a suite of code for nonlinear time series analysis. In 2015, another GSoC project started with the work to create interfaces to many TISEAN functions, but there is still work left to do. There are missing functions to do computations on spike trains, to simulate autoregresive models, to create specialized plots, etc. These are of importance for many scientific disciplines involving statistical computations and signal processing.

  • Project size [?] and Difficulty
~350 hours (medium)
  • Required skills
Octave, C/C++; FORTRAN API knowledge
  • Potential mentors
KaKiLa

Project sizes[edit]

Since GSoC 2022 there exist two project sizes[1][2]:

  • ~175 hours (~12 weeks, Jun 13 - Sept 12)
  • ~350 hours (~22 weeks, Jun 13 - Nov 21)

Footnotes[edit]

See also[edit]