Summer of Code - Getting Started: Difference between revisions

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{{Note|GNU Octave is a [https://summerofcode.withgoogle.com/programs/2022/organizations/gnu-octave mentoring organization for GSoC 2022].}}
{{Note|GNU Octave is a [https://summerofcode.withgoogle.com/programs/2024/organizations/gnu-octave mentoring organization for GSoC 2024].}}


Since 2011 the GNU Octave project has successfully mentored:
Since 2011 the GNU Octave project has successfully mentored:
* [[Summer of Code | '''37 participants''' 🙂]]
* [[Summer of Code | '''42 participants''' 🙂]]
* [[Summer of Code | '''39 projects''' 📝]]
* [[Summer of Code | '''44 projects''' 📝]]
in [[Summer of Code]] (SoC) programs by [https://summerofcode.withgoogle.com/ Google] and [https://esa.int/ ESA].
in [[Summer of Code]] (SoC) programs by [https://summerofcode.withgoogle.com/ Google] and [https://esa.int/ ESA].


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# 😉💬 '''We want to get to know you (before the deadline).  Communicate with us.'''
# 😉💬 '''We want to get to know you (before the deadline).  Communicate with us.'''
#* Join [https://octave.discourse.group/ '''Octave Discourse'''] or [[IRC]]. Using a nickname is fine.
#* Join [https://octave.discourse.group/ '''Octave Discourse'''] or [[IRC]] for general discussion and to ask questions (Please do not use the bug tracker for general GSOC inquiries unrelated to specific bugs found with Octave.) 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.
#* 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.
#* '''<span style="color:darkblue;">If you never talked to us, we will likely reject your proposal</span>''', even it looks good 🚮
#* '''<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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#* Try to show us as early as possible a draft of your proposal 📑
#* 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 🙂👍
#* 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 🙂👍
#* Here’s a sample proposal outline that you can use as a reference when drafting your own application. [https://docs.google.com/document/d/1kGtT9_f0FrXdCKwyKEWwOV6R-AU90bkd/edit?usp=sharing&ouid=115736651221450989198&rtpof=true&sd=true Sample Proposal]
#* Then submit the proposal following the applicable rules, e.g. for [https://google.github.io/gsocguides/student/writing-a-proposal GSoC]. 📨
#* Then submit the proposal following the applicable rules, e.g. for [https://google.github.io/gsocguides/student/writing-a-proposal GSoC]. 📨


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= Suggested projects =
= Suggested projects =


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.
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]], or the current [https://hg.savannah.gnu.org/hgweb/octave/file/tip/etc/ROADMAP.md | Octave Development Roadmap] for more inspiration.


{{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.}}
{{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. Please note that for such a proposal to be successful it will almost certainly involve initiating pre-proposal discussion over at the [https://octave.discourse.group Octave Discourse forum].}}


== openlibm ==
== Adding more Classification classes and implementing missing methods in statistics package ==


Over the years Octave faced many issues (e.g. bug {{bug|55538}}) 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.
Although a ClassificationKNN class was added in the latest statistics release (1.6.1), it still lacks several methods (only `predict` is available at the moment). This GSoC project aims at implementing more methods, such as crossval, cvloss, lime, loss, margin, partialDependence, plotPartialDependence, etc., as well as adding more classdefs related to classification classes, such as ClassificationGAM, ClassificationDiscriminant, ClassificationSVM, ClassificationNeuralNetwork, ClassificationNaiveBayes, etc. The statistics package, although heavily developed during the past years, still lacks a lot of classdef functionality. The scope is to implement classification classdef objects and their relevant methods in a MATLAB-compatible way.  
 
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.


* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
: ~175 hours (easy)
: ~350 hours (hard)
* '''Required skills'''
* '''Required skills'''
: Octave, C/C++, Autotools
: Octave, classdef, good knowledge of statistical methods
* '''Potential mentors'''
* '''Potential mentors'''
: [https://octave.discourse.group/u/cdf Carlo de Falco], [https://octave.discourse.group/u/siko1056 Kai]
: [https://octave.discourse.group/u/pr0m1th3as Andreas Bertsatos]
 
== ode15{i,s} : Matlab Compatible DAE solvers ==


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],
== Custom re-implementation of the texi2html (v.1.82) command line tool ==
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}}].


The {{manual|decic}} function for selecting consistent initial conditions for ode15i can be made more Matlab compatible by using [https://faculty.smu.edu/shampine/cic.pdf 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.
Implement a compiled .oct function to relax the dependency of the pkg-octave-doc package on texi2html (v.1.82) command line tool, which is no longer maintained or further developed but also not readily available to all linux distributions. The idea is to have a `texi2html` function within the pkg-octave-doc package that will replace the functionality of the texi2html (v.1.82) command line tool. This will also help improve the speed of pkg-octave-doc processing large packages, which contain specific tags (such as @math) which are currently handled within Octave code.


* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
: ~350 hours (medium)
: ~350 hours (hard)
* '''Required skills'''
* '''Required skills'''
: Octave, C/C++; familiarity with numerical methods for DAEs
: Perl, C++, Octave, Texinfo, HTML
* '''Potential mentors'''
* '''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]
: [https://octave.discourse.group/u/pr0m1th3as Andreas Bertsatos]


== Using Python within Octave ==


[[Pythonic]] allows one to call Python functions and interact with Python objects from within Octave .m file code and from the Octave command line interface.  Pythonic may eventually not be a separate package, but rather a core feature of Octave.  This project aims to improve Pythonic with the goal of making the package more stable, maintainable, and full-featured.
== Port Chebfun to Octave and improve classdef support ==
 
Based on a previous summer project related to Pythonic, this work will consist of fast-paced collaborative software development based on tackling the [https://gitlab.com/mtmiller/octave-pythonic/issues Pythonic issue list].  You would also be expected to participate in software design decisions and discussion, as well as improve documentation, doctests, and unit tests.  As an example of the sorts of decisions being made, note that Octave indexes from 1 whereas Python typically indexes from 0; in which cases is it appropriate to make this transparent to the user?


[https://www.chebfun.org| Chebfun] uses interpolation to approximate functions to very high accuracy, giving numerical computing that feels like symbolic computing.
The software is implemented as collection of "classdef" classes and is Free and Open Source Software.
However, Chebfun does not yet work with Octave, largely due to differences and issues with Octave's classdef implementation.
This project has two aims: (1) make changes to the Chebfun code to make it work on Octave and (2) improve Octave's classdef functionality.
Some initial steps toward to first goal can be found on [https://github.com/cbm755/chebfun/tree/octave_dev| this octave_dev branch].
The second goal will likely involve a collaborative effort because classdef is a priority on [https://hg.savannah.gnu.org/hgweb/octave/file/tip/etc/ROADMAP.md | Octave's Development Roadmap] and because other proposed projects also involve classdef.
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
: ~350 hours (medium)
: ~350 hours (hard)
* '''Required skills'''
* '''Required skills'''
: Octave, C/C++, Python
: Octave, object-oriented programming, polynomial interpolation and approximation theory, C++.
* '''Potential mentors'''
* '''Potential mentors'''
: [https://octave.discourse.group/u/mtmiller Mike Miller], [https://octave.discourse.group/u/cbm Colin B. Macdonald], Abhinav Tripathi
: [https://octave.discourse.group/u/cbm Colin B. Macdonald]


== Improve TIFF image support ==


[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:
<!--
== ode15{i,s} : Matlab Compatible DAE solvers ==


* GM has build option {{codeline|quantum}} which defines the bitdepth to use when reading an image:
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],
** Building GM with '''high quantum''' means that images of smaller bitdepth will take a lot more memory when reading.
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}}].
** 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 [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 {{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.


* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
: ~350 hours (medium)
: ~350 hours (medium)
* '''Required skills'''
* '''Required skills'''
: Octave, C/C++
: Octave, C/C++; familiarity with numerical methods for DAEs
* '''Potential mentors'''
* '''Potential mentors'''
: [https://octave.discourse.group/u/carandraug Carnë Draug]
: 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]
-->


<!--
== PolarAxes and Plotting Improvements ==
== PolarAxes and Plotting Improvements ==


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}}.
Octave currently provides support 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}}.


* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
Line 129: Line 128:
* '''Potential mentors'''
* '''Potential mentors'''
: [https://octave.discourse.group/u/rik Rik]
: [https://octave.discourse.group/u/rik Rik]
-->


<!--
== Table datatype ==
== Table datatype ==


Line 141: Line 142:
: Octave, C/C++
: Octave, C/C++
* '''Potential mentors'''
* '''Potential mentors'''
: [https://octave.discourse.group/u/siko1056 Kai]
: ???
-->
 
<!--
== TISEAN package ==
 
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.
 
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
: ~350 hours (medium)
* '''Required skills'''
: Octave, C/C++; FORTRAN API knowledge
* '''Potential mentors'''
: [https://octave.discourse.group/u/kakila KaKiLa]
-->


== YAML encoding/decoding ==
<!--
== Better tab completion ==


[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]].
Links: [https://savannah.gnu.org/bugs/index.php?62492 https://savannah.gnu.org/bugs/index.php?62492] and [https://savannah.gnu.org/bugs/?53384 https://savannah.gnu.org/bugs/?53384]


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.
Description: currently pressing Tab at the Octave command prompt attempts autocompletion of all identifiers in scope (variables, functions, classdefs etc) as well as files and directories in the path. It is not context sensitive.


The first step is research about existing Octave/Matlab and C/C++ implementations, for example:
Project: Improve tab completion. For example,


* https://code.google.com/archive/p/yamlmatlab/ (uses Java)
* Typing
* http://vision.is.tohoku.ac.jp/~kyamagu/ja/software/yaml/ (uses Java)
: load x
and then pressing tab should ideally give all loadable files and directories starting with x, not unrelated results like variables or functions.  


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.
* Typing
:cd
and tab should only give directories.


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.
* Any file and directory names that are included in the results should include those with spaces and special characters including those that would be interpreted as operators by Octave.
 
* Typing commands like
: axis
or
: format
and pressing tab should give only those options relevant to that command. E.g. format can be followed by short / long / loose / compact etc but not by a file or variable. Similarly axis can be followed by ij / xy / tight / equal / actual limits etc but not by files or directories. And so on for other commands. This should be made possible for both preexisting commands and for yet-to-be-written commands without any rewriting of existing function code or documentation.
 
To get more examples, see how bash completion works. You can type git or hg and then tab and it will give the list of available commands. If you type "sort --r" and then tab, it gives the list of options to sort starting with "--r", etc.


* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
: ~350 hours (easy)
: ~350 hours (medium)
* '''Required skills'''
* '''Required skills'''
: Octave, C/C++
: ???
* '''Potential mentors'''
* '''Potential mentors'''
: [https://octave.discourse.group/u/siko1056 Kai]
: ???
-->


== Symbolic package ==
<!--
== Graphics rendering back to front sorting ==


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 the full 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]].
Several incompatibilities have been identified in how Octave plots transparent objects in 3D, causing certain transparent objects to hide opaque objects behind them even though they're not supposed to. The vast majority of them were isolated to one problem: if the objects to be drawn are rendered such that the one farthest away from the viewer is rendered first and nearer objects are rendered on top of that, then transparency would be automatically achieved, but this needs very careful coding to stay performant and to avoid rendering objects that will be overwritten fully by others. See [https://savannah.gnu.org/bugs/?57980] for a summary.
 
This project proposes to go further: instead of using Pythonic only for the communication layer, we'll use it throughout the Symbolic project.  For example, we might make "@sym" a subclass of "@pyobject".  We also could stop using the "python_cmd" interface and use Pythonic directly from methods. The main goal was already mentioned: to expose the ''full functionality'' of SymPy. For example, we would allow OO-style method calls such as <code>f.diff(x)</code> instead of <code>diff(f, x)</code>.


* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
: ~350 hours (medium)
: ~350 hours (medium)
* '''Required skills'''
* '''Required skills'''
: Octave, C/C++, Python; object-oriented programming (OOP) in Octave
: ???
* '''Potential mentors'''
* '''Potential mentors'''
: [https://octave.discourse.group/u/cbm Colin B. Macdonald], [https://octave.discourse.group/u/mtmiller Mike Miller], Abhinav Tripathi
: ???
-->
 
<!--
== Symbolic package ==


== TISEAN package ==
The [[Symbolic package]] provides symbolic computing and other [https://en.wikipedia.org/wiki/Computer_algebra_system computer algebra system] tools via the [https://sympy.org SymPy Python library].  GSoC projects in 2016 and 2022 improved the package.


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.
There are no specific plans for Symbolic in GSoC 2023, but improvements elsewhere that would help Symbolic include:
* Developing the Octave-Pythonic package.
* Fix the storage of non-expressions by working with upstream SymPy: currently we rely on deprecated functionality in SymPy.
* Improvements and fixes to classdef-related issues in Octave itself.
* Developing the Octave Jupyter kernel.


* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
: ~350 hours (medium)
: ~350 hours (medium)
* '''Required skills'''
* '''Required skills'''
: Octave, C/C++; FORTRAN API knowledge
: ???
* '''Potential mentors'''
* '''Potential mentors'''
: [https://octave.discourse.group/u/kakila KaKiLa]
: ???
-->


= Project sizes =
= Project sizes =


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>:
As of 2024, possible project sizes are 90 (small), 175 (medium), or 350 hours (large) <ref>https://developers.google.com/open-source/gsoc/faq#how_much_time_does_gsoc_participation_take</ref>.
* '''~175 hours''' (~12 weeks, Jun 13 - Sept 12)
* '''~350 hours''' (~22 weeks, Jun 13 - Nov 21)


= Footnotes =
= Footnotes =

Latest revision as of 05:22, 22 September 2024

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 for general discussion and to ask questions (Please do not use the bug tracker for general GSOC inquiries unrelated to specific bugs found with Octave.) 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 🙂👍
    • Here’s a sample proposal outline that you can use as a reference when drafting your own application. Sample Proposal
    • 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, or the current | Octave Development Roadmap for more inspiration.

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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. Please note that for such a proposal to be successful it will almost certainly involve initiating pre-proposal discussion over at the Octave Discourse forum.

Adding more Classification classes and implementing missing methods in statistics package[edit]

Although a ClassificationKNN class was added in the latest statistics release (1.6.1), it still lacks several methods (only `predict` is available at the moment). This GSoC project aims at implementing more methods, such as crossval, cvloss, lime, loss, margin, partialDependence, plotPartialDependence, etc., as well as adding more classdefs related to classification classes, such as ClassificationGAM, ClassificationDiscriminant, ClassificationSVM, ClassificationNeuralNetwork, ClassificationNaiveBayes, etc. The statistics package, although heavily developed during the past years, still lacks a lot of classdef functionality. The scope is to implement classification classdef objects and their relevant methods in a MATLAB-compatible way.

  • Project size [?] and Difficulty
~350 hours (hard)
  • Required skills
Octave, classdef, good knowledge of statistical methods
  • Potential mentors
Andreas Bertsatos

Custom re-implementation of the texi2html (v.1.82) command line tool[edit]

Implement a compiled .oct function to relax the dependency of the pkg-octave-doc package on texi2html (v.1.82) command line tool, which is no longer maintained or further developed but also not readily available to all linux distributions. The idea is to have a `texi2html` function within the pkg-octave-doc package that will replace the functionality of the texi2html (v.1.82) command line tool. This will also help improve the speed of pkg-octave-doc processing large packages, which contain specific tags (such as @math) which are currently handled within Octave code.

  • Project size [?] and Difficulty
~350 hours (hard)
  • Required skills
Perl, C++, Octave, Texinfo, HTML
  • Potential mentors
Andreas Bertsatos


Port Chebfun to Octave and improve classdef support[edit]

Chebfun uses interpolation to approximate functions to very high accuracy, giving numerical computing that feels like symbolic computing. The software is implemented as collection of "classdef" classes and is Free and Open Source Software. However, Chebfun does not yet work with Octave, largely due to differences and issues with Octave's classdef implementation. This project has two aims: (1) make changes to the Chebfun code to make it work on Octave and (2) improve Octave's classdef functionality. Some initial steps toward to first goal can be found on this octave_dev branch. The second goal will likely involve a collaborative effort because classdef is a priority on | Octave's Development Roadmap and because other proposed projects also involve classdef.

  • Project size [?] and Difficulty
~350 hours (hard)
  • Required skills
Octave, object-oriented programming, polynomial interpolation and approximation theory, C++.
  • Potential mentors
Colin B. Macdonald





Project sizes[edit]

As of 2024, possible project sizes are 90 (small), 175 (medium), or 350 hours (large) [1].

Footnotes[edit]

See also[edit]