Editing Summer of Code - Getting Started

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

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

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

= Steps toward a successful application =

# 😉💬 '''We want to get to know you (before the deadline).  Communicate with us.'''
#* Join [https://octave.discourse.group/ '''Octave Discourse'''] or our [https://webchat.freenode.net/?channels=#octave '''IRC channel''']. 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.
#* '''<span style="color:darkblue;">If you never talked to us, we will likely reject your proposal</span>''', even it looks good 🚮
# 👩‍🔬 '''Get your hands dirty.'''
#* We are curious about your programming skills 🚀
#** 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.
#** You can take a look at the [[short projects]] for some simple bugs to start with.
#* '''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.
# 📝💡 '''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 [http://www.catb.org/esr/faqs/smart-questions.html smart questions] 🤓
#* Remember, '''we are volunteer developers and not your boss''' 🙂
# 📔 '''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 [https://google.github.io/gsocguides/student/writing-a-proposal GSoC]. 📨

= How do we judge your application? =

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 =

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:
# 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]]
#* Tools to know: [https://en.wikipedia.org/wiki/GNU_Compiler_Collection gcc], [https://en.wikipedia.org/wiki/Make_(software) make]
# How to submit patches (changesets).
#* Read in this wiki: [[Contribution guidelines]], [[Mercurial]]
#* Tools to know: [https://en.wikipedia.org/wiki/Mercurial Mercurial (hg)], [https://en.wikipedia.org/wiki/Git git]

= 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.

{{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.}}

== openlibm ==

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.

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'''
: ~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]

== 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], 
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 [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'''
: ~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]

== Symbolic package ==

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]].

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.

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''' [[#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

== 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:

* 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.

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.

* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
: ~175 hours (medium)
* '''Required skills'''
: Octave, C/C++
* '''Potential mentors'''
: [https://octave.discourse.group/u/carandraug Carnë Draug]

== 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}}.

* '''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]

== Table datatype ==

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.

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.

* '''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]

== YAML encoding/decoding ==

[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]].

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.

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

* https://code.google.com/archive/p/yamlmatlab/ (uses Java)
* http://vision.is.tohoku.ac.jp/~kyamagu/ja/software/yaml/ (uses Java)

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.

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''' [[#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]

== 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]

= 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>:
* '''~175 hours''' (~12 weeks, Jun 13 - Sept 12)
* '''~350 hours''' (~22 weeks, Jun 13 - Nov 21)

= Footnotes =

<references />

= See also =

* 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]

[[Category:Summer of Code]]
[[Category:Project Ideas]]