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The following is distilled from the [[Projects]] page for the benefit of potential [https://summerofcode.withgoogle.com Google] and [https://socis.esa.int/ ESA] Summer of Code (SoC) 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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Since 2011 the GNU Octave project has mentored 38 students in [[Summer of Code]] (SoC) programs by [https://summerofcode.withgoogle.com/ Google] and [https://socis.esa.int/ ESA]. Those programs aim to advertise open-source software development and to attract potential new Octave developers.
  
You can also take a look at last years [[Summer of Code]] projects for inspiration.
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= Steps toward a successful application =
  
= Steps Toward a Successful Application =
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# 😉💬 '''We want to get to know you.  Communicate with us.'''
 +
#* Join [https://octave.discourse.group/ '''Octave Discourse'''] or our [https://webchat.freenode.net/?channels=#octave '''IRC channel'''].
 +
#* We are interested in you as motivated developer 💻  There is no need to present an overwhelming CV with prestigious universities 🏰 and programming contest awards 🏆 in it.  We are very fine if you just communicate using a nickname with us.
 +
#* If your first question is "Hi I'm new to Octave. What should I do?" '''you are out''' 🤦
 +
# 📝💡 '''Tell us what you are going to do.'''
 +
#* When you contact us for the first time, do not write just to say in what project you're interested in.  Be specific about what you are going to do, post many 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 voluntary developers and not your boss''' 🙂
 +
# 👩‍🔬 '''Get your hands dirty.'''
 +
#* We are curious about your programming skills ⌨️
 +
#** Try to [https://savannah.gnu.org/bugs/?group=octave fix Octave bugs] or [https://savannah.gnu.org/patch/?group=octave submit patches] '''before''' the end of the application deadline.
 +
#** Take a look at the [[Short projects]] for 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 you come across a missing function ➡️ try to implement it.
 +
# 📔 '''Prepare your proposal with us.'''
 +
#* GSoC, for example, [https://google.github.io/gsocguides/student/writing-a-proposal requires to submit a proposal].
 +
#* If we see your proposal for the first time after the application deadline, you can easily imagine that it might contain ambiguities or some paragraphs are not fully clear to us.  We easily get doubts if you are capable of working on your project 😓
 +
#* Try to show us as early as possible a draft of your proposal 👍
  
==  Help Us Get To Know You ==
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= How do we judge your application? =
* If you aren't communicating with us before the application is due, your application will not be accepted.
 
*:* '''Join the [https://lists.gnu.org/mailman/listinfo/octave-maintainers maintainers mailing list]''' or read the archives and see what topics we discuss and how the developers interact with each other.
 
*:* '''Hang out in our [https://webchat.freenode.net/?channels=#octave IRC channel]'''. Ask questions, answer questions from users, show us that you are motivated, and well-prepared. There will be more applicants than we can effectively mentor, so do ask for feedback on your public application to increase the strength of your proposal!
 
* '''Do not wait for us to tell you what to do'''
 
*: You should be doing something that interests you, and should not need us to tell you what to do.  Similarly, you shouldn't ask us what to do either.
 
*:* When you email the list and mentors, do not write it to say in what project you're interested. Be specific about your questions and clear on the email subject. For example, do not write an email with the subject "GSoC student interested in the ND images projects".  Such email is likely be ignored.  Instead, show you are already working on the topic, and email "Problem implementing morphological operators with bitpacked ND images".
 
*:* It is good to ask advice on how to solve something you can't but you must show some work done.  Remember, we are mentors and not your boss.  Read [http://www.catb.org/esr/faqs/smart-questions.html How to ask questions the smart way]: <blockquote>''Prepare your question. Think it through. Hasty-sounding questions get hasty answers, or none at all. The more you do to demonstrate that having put thought and effort into solving your problem before seeking help, the more likely you are to actually get help.''</blockquote>
 
*:* It can be difficult at the beginning to think on something to do.  This is nature of free and open source software development.  You will need to break the mental barrier that prevents you from thinking on what can be done.  Once you do that, you will have no lack of ideas for what to do next.
 
*:* Use Octave.  Eventually you will come across something that does not work the way you like.  Fix that.  Or you will come across a missing function.  Implement it.  It may be a hard problem (they usually are). While solving that problem, you may find other missing capabilities or smaller bug fixes.  Implement and contribute those to Octave.
 
*:* Take a look at the [[Short projects]] for something that may be simple to start with.
 
  
==  Find Something That Interests You ==
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Depending on the mentors and SoC program there are varieties, but typically the main factors considered would be:
*: It's '''critical''' that you '''find a project that excites you'''.  You'll be spending most of the summer working on it (we expect you to treat the SoC as a full-time job).
 
*: Don't just tell us how interested you are, show us that you're willing and able to '''contribute''' to Octave. You can do that by [https://savannah.gnu.org/bugs/?group=octave fixing a few bugs] or [https://savannah.gnu.org/patch/?group=octave submitting patches] well before the deadline, in addition to regularly interacting with Octave maintainers and users on the mailing list and IRC. Our experience shows us that successful SoC students demonstrate their interest early and often.
 
== Prepare Your Proposal With Us ==
 
*: By working with us to prepare your proposal, you'll be getting to know us and showing us how you approach problems. The best place for this is your Wiki user page and the [https://webchat.freenode.net/?channels=#octave IRC channel].
 
==  Complete Your Application ==
 
*: 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.
 
*:* 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)''' or at '''ESA'''.<br>
 
*:* Only the organization admin and the possible mentors will see this data.  You can still edit it after submitting until the deadline!
 
  
== Things You'll be Expected to Know or Quickly Learn On Your Own ==
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* '''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.
  
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, successful applicants 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 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.
  
* '''The Build System'''
+
* '''Well thought out, adequately detailed, realistic project plan'''
*: [http://en.wikipedia.org/wiki/GNU_build_system The GNU build system] is used to build Octave.
+
*: "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.
*: 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 {{Codeline|./configure && make && make install}} series of commands, you have already used the GNU build system.
 
*: '''You must demonstrate that you are able to build the development version of Octave from sources before the application deadline.''' Linux is arguably the easiest system to work on. Instructions:
 
*:* [[Building]]
 
*:* [https://octave.org/doc/interpreter/Installation.html Octave Manual on Installing Octave]
 
* '''The Version Control System'''
 
*: We use [https://www.mercurial-scm.org/ Mercurial] (abbreviated hg).
 
*: Mercurial 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.
 
* '''The Procedure for Contributing Changesets'''
 
*: You will be expected to follow the same procedures as other contributors and core developers.
 
*: You will be helping current and future Octave developers by using our standard style for changes, commit messages, and so on.  You should also read the same [[Contribution guidelines | contribution]] [https://hg.savannah.gnu.org/hgweb/octave/file/tip/etc/HACKING.md guidelines] we have for everyone.
 
*: [[Hg_instructions_for_mentors#Mercurial_Tips_for_SoC_students | This page]] describes the procedures students are expected to use to publicly display their progress in a public mercurial repo during their work.
 
* '''The Maintainers Mailing List'''
 
*: We primarily use [https://lists.gnu.org/mailman/listinfo/octave-maintainers mailing lists] for communication among developers.
 
*: The mailing list is used most often for discussions about non-trivial changes to Octave, or for setting the direction of development.
 
*: You should follow basic mailing list etiquette. For us, this mostly means "do not [https://en.wikipedia.org/wiki/Posting_style#Top-posting top post]".
 
* '''The IRC Channel'''
 
*: We also have [http://webchat.freenode.net?channels=octave the #octave IRC channel in Freenode].
 
*: You should be familiar with the IRC channel.  It's very helpful for new contributors (you) to get immediate feedback on ideas and code.
 
*: Unless your primary mentor has a strong preference for some other method of communication, the IRC channel will likely be your primary means of communicating with your mentor and Octave developers.
 
* '''The Octave Forge Project'''
 
*: [https://octave.sourceforge.io/ Octave Forge] is a collection of contributed packages that enhance the capabilities of core Octave. They are somewhat analogous to Matlab's toolboxes.
 
* '''Related Skills'''
 
*: In addition, you probably should know '''some''' mathematics, engineering, experimental science, or something of the sort.
 
*: If so, you probably have already been exposed to the kinds of problems that Octave is used for.
 
 
 
== Criteria by which applications are judged ==
 
 
 
These might vary somewhat depending on the mentors and coordinators for a particular Summer of Code, but typically the main factors considered would be:
 
 
 
* '''Applicant has demonstrated an ability to make substantial modifications to Octave'''
 
*: The most important thing is that you've contributed some interesting code samples to judge you by. It's OK during the application period to ask for help on how to format these code samples, which normally are Mercurial patches.
 
  
* '''Applicant shows understanding of topic'''
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= What you should know about Octave =
*: Your application 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.
 
  
* '''Applicant shows understanding of and interest in Octave development'''
+
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 😇
*: The best evidence for this is previous contributions and interactions.
 
  
* '''Well thought out, adequately detailed, realistic project plan'''
+
You should know:
*: "I'm good at this, so trust me" isn't enough. You should describe which algorithms you'll use and how you'll integrate with existing Octave code. You should also prepare a full timeline and goals for the midterm and final evaluations.
+
# How to build Octave from it's 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 =
 
= Suggested projects =
  
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. You can also look at our [[Summer of Code|completed past projects]] for more inspiration.
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The following suggested projects are distilled from the [[Projects]] page for the benefit of potential SoC students. You can also look at our [[Summer of Code|completed past projects]] for more inspiration.
 
 
{{Note|These are suggested projects but you are welcome to propose your own projects provided you find an Octave mentor}}
 
 
 
== Summary table ==
 
 
 
{| class="wikitable sortable" style="text-align: center; width:99%"
 
|-
 
!Title
 
!Mentor
 
!co-Mentors
 
!Class
 
!New?
 
!Difficulty
 
!Last active
 
|-
 
! <br />!! !! !! !! !! !!
 
|-
 
| [[Summer of Code - Getting Started#ode15s_:_Matlab_Compatible_DAE_solver | ode15{i,s} : Matlab Compatible DAE solvers]] || Carlo de Falco || Francesco Faccio, Marco Caliari, Jacopo Corno, Sebastian Schöps || Numerical || No  || Medium || GSoC 2016
 
|-
 
| [[Summer of Code - Getting Started#Improve_logm.2C_sqrtm.2C_funm | Improve logm, sqrtm, funm]] || ? || Marco Caliari, Mudit Sharma || Numerical || [https://github.com/RickOne16/matrix No]  || Hard || Independent devs 2016
 
|-
 
| [[Summer of Code - Getting Started#Improve_iterative_methods_for_sparse_linear_systems | Improve iterative methods for sparse linear systems]] || Marco Caliari || Carlo de Falco || Numerical || No  || Hard || SOCIS 2016
 
|-
 
| [[Summer of Code - Getting Started#EPA_hydrology_software_suite | EPA hydrology software suite]] || [[User:KaKiLa| KaKiLa]] || ? || Octave Forge || Yes || Medium || Never
 
|-
 
| [[Summer of Code - Getting Started#FullSWOF overland flow simulator | FullSWOF overland flow simulator]] || [[User:KaKiLa| KaKiLa]] || ? || Octave Forge || Yes || Medium || Never
 
|-
 
| [[Summer of Code - Getting Started#TISEAN_package | TISEAN: Nonlinear Time Series Analysis]] || [[User:KaKiLa|KaKiLa]] || ? || Octave Forge || [[TISEAN_package | No]] || Medium || GSoC 2015
 
|-
 
| [[Summer of Code - Getting Started#Octave_Package_management | Octave Package management]] || Sebastian Schöps || [[User:KaKiLa|KaKiLa]], Carnë Draug, Carlo de Falco || Infrastructure || Yes  || Medium || Never
 
|-
 
| [[Summer of Code - Getting Started#Symbolic_package | Symbolic package]] || Colin B. Macdonald || Mike Miller, Abhinav Tripathi || Octave Forge || [https://github.com/cbm755/octsympy Octsympy]  || Medium || GSoC 2016
 
|-
 
| [[Summer of Code - Getting Started#OCS | OCS package]] || Sebastian Schöps || Sebastian Schöps || Octave Forge, Numerical || Yes || Easy || Never
 
|-
 
| [[Summer of Code - Getting Started#Using_Python_within_Octave | Pytave project]] || Mike Miller || Colin B. Macdonald, Abhinav Tripathi || Infrastructure || No  || Medium || some in GSoC 2016
 
|-
 
| [[Summer of Code - Getting Started#JSON_encoding.2Fdecoding | JSON encoding/decoding]] || [[User:Siko1056|Kai T. Ohlhus]] || ? || Infrastructure || Yes  || Medium || Never
 
|-
 
| [[Summer of Code - Getting Started#Jupyter_Notebook_Integration | Jupyter Notebook Integration]] || Mike Miller || Colin B. Macdonald, [[User:Siko1056|Kai T. Ohlhus]] || Infrastructure ||  Yes || Medium || Never
 
|-
 
| [[Summer of Code - Getting Started#Chebfun_in_Octave | Chebfun in Octave]] || Colin B. Macdonald || [[User:KaKiLa|KaKiLa]] || Infrastructure, Numerical || Yes  || Hard || Never
 
|-
 
| [[Summer of Code - Getting Started#PolarAxes and Plotting Improvements | PolarAxes and Plotting Improvements ]] || ? || Rik || Graphics || Yes  || Medium || Never
 
|}
 
 
 
== Numerical ==
 
 
 
These projects involve implementing certain mathematical functions, primarily in core Octave.
 
  
=== ode15{i,s} : Matlab Compatible DAE solvers ===
+
{{Note|Do you use Octave at your university or 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.}}
  
An initial implementation of a Matlab compatible ode15{i,s} solver,
+
== ode15{i,s} : Matlab Compatible DAE solvers ==
based on [http://computation.llnl.gov/projects/sundials SUNDIALS],
 
was done by Francesco Faccio during
 
GSOC 2016.
 
The blog describing the work is [http://gsoc2016ode15s.blogspot.it/ here].
 
The resulting code has been pushed into the main Octave repository in the development branch and
 
consists mainly of the following three files
 
[http://hg.savannah.gnu.org/hgweb/octave/file/4890b1c4a6bd/libinterp/dldfcn/__ode15__.cc __ode15__.cc],
 
[http://hg.savannah.gnu.org/hgweb/octave/file/4890b1c4a6bd/scripts/ode/ode15i.m ode15i.m] and
 
[http://hg.savannah.gnu.org/hgweb/octave/file/4890b1c4a6bd/scripts/ode/ode15s.m ode15s.m].
 
The list of outstanding tracker tickets concerning this implementation can be found
 
[https://savannah.gnu.org/search/?Search=Search&words=ode15&type_of_search=bugs&only_group_id=1925&exact=1&max_rows=25#options here]
 
  
Possible useful improvements that could be done in a new project include:
+
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}}].
  
* Implement a better function for selecting consistent initial conditions compatible with Matlab's decic.m. The algorithm to use is described [http://faculty.smu.edu/shampine/cic.pdf here]
+
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.
  
* make ode15{i,s} with datatypes other than double
 
 
* improve interpolation at intermediate time steps.
 
 
* general code profiling and optimization
 
 
Other tasks, not strictly connected to ode15{i,s} but closely related that could be added
 
to a possible project plan would be improving documentation and tests in odepkg and removing
 
overlaps with the documentation in core Octave.
 
 
 
* '''Required skills'''
 
* '''Required skills'''
: C++; C; familiarity with numerical methods for DAEs; Basic knowledge of makefiles and/or autotools.
+
: Knowledge of Octave, C/C++; familiarity with numerical methods for DAEs
* '''Difficulty'''
 
: Medium.
 
 
* '''Potential mentors'''
 
* '''Potential mentors'''
 
: Francesco Faccio, Carlo de Falco, Marco Caliari, Jacopo Corno, Sebastian Schöps
 
: Francesco Faccio, Carlo de Falco, Marco Caliari, Jacopo Corno, Sebastian Schöps
  
=== Improve logm, sqrtm, funm ===
+
== 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.
  
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. A good starting point for available algorithms and open-source implementations is Higham and Deadman's [http://eprints.ma.man.ac.uk/2102/01/covered/MIMS_ep2014_8.pdf "A Catalogue of Software for Matrix Functions"].
+
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?
  
 
* '''Required skills'''
 
* '''Required skills'''
: Read and Write both C++ and Octave code, find and read research papers, research experience in numerical analysis, familiarity with analysis of algorithms.
+
: Knowledge of Octave, C/C++, Python
* '''Difficulty'''
 
: Difficult.
 
 
* '''Potential mentors'''
 
* '''Potential mentors'''
: Marco Caliari, Mudit Sharma
+
: Mike Miller, Colin B. Macdonald, Abhinav Tripathi
  
=== Improve iterative methods for sparse linear systems ===
+
== Improve TIFF image support ==
  
GNU Octave currently has the following Krylov subspace methods for sparse linear systems: pcg (spd matrices) and pcr (Hermitian matrices), bicg,
+
[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:
bicgstab, cgs, gmres, and qmr (general matrices). The description of some of them (pcr, qmr) and their error messages are not aligned. Moreover, they have similar blocks of code (input check for instance) which can be written once and for all in common functions. The first step in this project could be a revision and a synchronization of the codes, starting from the project [https://socis16octave-improveiterativemethods.blogspot.com/ SOCIS2016] which is already merged into Octave (cset {{cset|6266e321ef22}}).
 
  
In Matlab, some additional methods are available: minres and symmlq (symmetric matrices), bicgstabl (general matrices), lsqr (least
+
* GM has build option {{codeline|quantum}} which defines the bitdepth to use when reading an image:
squares). The second step in this project could be the implementation of some of these missing functions.
+
** 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.
  
The [https://www-users.cs.umn.edu/~saad/IterMethBook_2ndEd.pdf reference book by Yousef Saad] is available online.
+
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.
  
 
* '''Required skills'''
 
* '''Required skills'''
: numerical linear algebra, m-file programming.
+
: Knowledge of Octave, C/C++
* '''Difficulty'''
+
* '''Potential mentors'''
: Maybe hard the mathematical part, medium the programming part.
+
: Carnë Draug
* '''Mentor'''
 
: Marco Caliari, Carlo de Falco
 
  
=== Chebfun in Octave ===
+
== PolarAxes and Plotting Improvements ==
  
[https://www.chebfun.org/ Chebfun] is a mathematics and software project for "numerical computing with functions".  Basically it approximates functions to machine precision accuracy (10<sup>-15</sup>) using piecewise Chebyshev polynomial interpolants. Operations on those functions (arithmetic, derivatives, root-finding, etc) are then overloaded and return new interpolating polynomials, which are themselves proxies for the actual solution.
+
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}}.
  
Chebfun makes extensive use of classdef classes, and is one of the largest Free Software projects to do so.  Unfortunately it currently only works in Matlab.  This project seeks to (1) improve Octave's classdef support and (2) tweak Chebfun to work under Octave, for example, removing undocumented classdef features.  The final goal is to have at least basic Chebfun features working on Octave.  An additional goal would be making <code>pkg install chebfun.zip</code> work in Octave.
+
* '''Required skills'''
 +
: Knowledge of Octave, C/C++; optional experience with OpenGL programming
 +
* '''Potential mentors'''
 +
: Rik
  
The impact of this project is improving Octave and allowing Chebfun to be used without proprietary software.
+
== Table datatype ==
  
How to get started:
+
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.
 
 
* Learn about [https://www.chebfun.org/ Chebfun]
 
* Browse [https://savannah.gnu.org/bugs/?group=octave Octave's bug list] for "classdef"-related bugs.
 
 
 
* Clone this Chebfun [https://github.com/cbm755/chebfun/tree/octave_dev octave_dev branch].
 
** On that, <code>f = chebfun(@(x) sin(x), [-2 6])</code> should work with Octave 4.3.0+ and maybe even with 4.2.1.  Check that <code>f(pi)</code> and <code>g = f + 1</code> work.
 
** A good first task would be to study [https://github.com/cbm755/chebfun/commit/e20b0ad2dc89cfe8e50ba461b864eff7d5bbef17 this commit], a workaround for <code>f.funs{1}</code> using <code>temp = f.funs; temp{1}</code>.  <code>2*f</code> is failing, can you fix it, perhaps with this workaround?  Or can you make <code>f.funs{1}</code> work by changing something in <code>@chebfun/subsref.m</code>?
 
  
 +
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.
  
 
* '''Required skills'''
 
* '''Required skills'''
: Octave m-file programming, classdef programming, probably C++, some familiarity with Approximation Theory (a branch of mathematics).
+
: Knowledge of Octave, C/C++
* '''Difficulty'''
 
: Medium (fixing Octave classdef bugs likely harder and requires a deep dive into how Octave supports OOP).
 
 
* '''Potential mentors'''
 
* '''Potential mentors'''
: Colin B. Macdonald, [[User:KaKiLa|KaKiLa]], Mike Miller (?), Carnë Draug (?), someone from Chebfun team (?).
+
: [[User:siko1056|Kai]]
  
== Adding functionality to Forge packages ==
+
== Jupyter Notebook Integration ==
  
 +
<q>The [https://jupyter.org Jupyter Notebook] is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.</q>
  
=== EPA hydrology software suite ===
+
To interactively work with Octave code within Jupyter Notebooks, there already exists an [https://github.com/Calysto/octave_kernel Octave kernel for Jupyter].
Create native interfaces to the EPA software suites.
 
  
Starting points
+
'''This project''' aims to support the '''opposite direction''': running (and filling) Jupyter Notebook within GNU Octave. This would enable Jupyter Notebook users to evaluate '''long running Octave Notebooks''' on a computing server without permanent browser connection, which is [https://github.com/jupyter/notebook/issues/1647 still a pending issue].  To achieve this, different strategies are possible:
* [https://forja.cica.es/projects/epanet-octave/ epanet-octave].
 
* [https://github.com/OpenWaterAnalytics/ Open Water Analytics]
 
  
* '''SWMM'''
+
# Synchronize an internal Octave data structure (e.g. classdef object) with the Jupyter Notebook. Probably the safest approach, but does not enable any interactivity from the Octave GUI.
** [https://www.epa.gov/water-research/storm-water-management-model-swmm Official page]
+
# Import/export a Jupyter Notebook as Octave script (translate non-code sections to comments and vice versa). Files can be edited from the Octave GUI, but probably conversion losses might occur (e.g. embedded graphics).
** Check work done in [https://github.com/water-systems/MatSWMM MatSWMM] [http://digital.csic.es/bitstream/10261/132982/1/MatSWMM.pdf article]
+
# A synthesis of both approaches?
  
* '''EPANET'''
+
In general a [https://nbformat.readthedocs.io/en/latest/ Jupyter Notebook] is a plain JSON document, which will be supported in Octave 7 (current development version) or through the [https://gnu-octave.github.io/pkg-index/package/pkg-json JSON package] for older Octave versions.
** [https://www.epa.gov/water-research/epanet Official page]
 
  
 
* '''Required skills'''
 
* '''Required skills'''
: m-file scripting, C, C++, API knowledge, file I/O, classdef (optional).
+
: Knowledge of Octave, C/C++
 +
* '''Potential mentors'''
 +
: [[User:siko1056|Kai]]
  
* '''Difficulty'''
+
== Adding functionality to packages ==
: easy/medium
 
  
* '''Mentor'''
+
=== OCS package ===
: [[User:KaKiLa|KaKiLa]]
 
  
===  FullSWOF overland flow simulator ===
+
The [[Ocs package | OCS package]] is a circuit simulator. The objective of this project is to increase compatibility with [https://en.wikipedia.org/wiki/SPICE SPICE] and improve compatibility with other Octave packages, e.g. the [[Control package]]. Please study the [https://octave.sourceforge.io/ocs/overview.html available functions] of this package.  
Create scripting tools for (optional: native interfaces).
 
 
 
Starting points
 
* [https://www.idpoisson.fr/fullswof/ The FullSWOF Project].
 
* [https://arxiv.org/abs/1204.3210 FullSWOF: A software for overland flow simulation]
 
* [https://bitbucket.org/binello7/fswof2d Initial work on Bitbucket]
 
  
 
* '''Required skills'''
 
* '''Required skills'''
: m-file scripting, C, C++, API knowledge, file I/O, classdef (optional).
+
: Knowledge of Octave, C/C++; FORTRAN API knowledge
 
+
* '''Potential mentors'''
* '''Difficulty'''
+
: Sebastian Schöps, Carlo de Falco
: easy/medium
 
 
 
* '''Mentor'''
 
: [[User:KaKiLa|KaKiLa]]
 
 
 
=== TISEAN package ===
 
 
 
[http://www.mpipks-dresden.mpg.de/~tisean/Tisean_3.0.1/index.html TISEAN] is a suite of code for nonlinear time series analysis. It has been [[TISEAN package | partially re-implemented]] as libre software. The objective is to integrate TISEAN as an Octave Forge package, as was done for the Control package.
 
[[TISEAN_package | A lot has been completed]] 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. Do check [[TISEAN_package:Procedure#Table_of_functions|the progress of the project]] to see if you are interested.
 
 
* [http://octave.sourceforge.net/tisean/overview.html Package help at source forge.]
 
* [https://sourceforge.net/p/octave/tisean/ci/default/tree/ Package repository at source forge.]
 
 
 
* '''Required skills'''
 
: m-file scripting, C, C++, and FORTRAN API knowledge.
 
* '''Difficulty'''
 
: easy/medium
 
* '''Mentor'''
 
: [[User:KaKiLa|KaKiLa]]
 
  
 
=== Symbolic package ===
 
=== Symbolic package ===
  
Octave's [https://github.com/cbm755/octsympy Symbolic package] handles symbolic computing and other CAS 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.  Recently, a GSoC2016 project successfully re-implemented this communication using the new [https://bitbucket.org/mtmiller/pytave Pytave tool].
+
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]].
  
This project proposes to go further: instead of using Pytave 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 Pytave 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 "f.diff(x)" instead of "diff(f, x)".
+
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>.
  
 
* '''Required skills'''
 
* '''Required skills'''
: OO-programming with m-files, Python, and possibly C/C++ for improving Pytave (if needed).
+
: Knowledge of Octave, C/C++, Python; object-oriented programming (OOP) in Octave
* '''Difficulty'''
+
* '''Potential mentors'''
: easy/medium
 
* '''Mentors and/or other team members'''
 
 
: Colin B. Macdonald, Mike Miller, Abhinav Tripathi
 
: Colin B. Macdonald, Mike Miller, Abhinav Tripathi
  
=== OCS ===
+
=== TISEAN package ===
  
[[Ocs package | OCS]] is a circuit simulator for Octave. The objective of this project is to update the code to use modern features of Octave (e.g. classdef), fix open bugs, increase compatibility with SPICE and improve compatibility with other Octave packages (odepkg, control etc).
+
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.  Which are of importance for many scientific disciplines involving statistical computations and signal processing.
 
   
 
   
* [http://octave.sourceforge.net/ocs/overview.html Package help at source forge.]
 
 
 
* '''Required skills'''
 
* '''Required skills'''
: m-file scripting, C, C++, and FORTRAN API knowledge.
+
: Knowledge of Octave, C/C++; FORTRAN API knowledge
* '''Difficulty'''
+
* '''Potential mentors'''
: easy/medium
+
: [[User:KaKiLa|KaKiLa]]
* '''Mentor'''
 
: Sebastian Schöps, Carlo de Falco
 
 
 
== Infrastructure ==
 
 
 
=== JSON encoding/decoding ===
 
 
 
[https://en.wikipedia.org/wiki/JSON JavaScript Object Notation], in short JSON, is a very common human readable and structured data format.  Unfortunately, GNU Octave still lacks of builtin support of that data format.  Having JSON support, Octave can improve for example it's web service functions, which often exchange JSON data these days.  Another interesting applicatoin is described in another Octave GSoC project, see [[Summer of Code - Getting Started#Jupyter_Integration | Jupyter integration]].
 
 
 
In bug {{bug|53100}} a vivid discussion about proper JSON support took place.  As JSON is a highly demanded feature for Octave, there are already several attempts to fill the gap:
 
 
 
* [https://github.com/fangq/jsonlab jsonlab] (M-file implementation, probably slow for large JSON files)
 
* [https://www.artefact.tk/software/matlab/jsonio/ JSONio] (C MEX wrapper around [https://github.com/zserge/jsmn jsmn])
 
* [https://github.com/Andy1978/octave-rapidjson octave-rapidjson] (C++ Octave wrapper around [https://rapidjson.org/ rapidjson])
 
* [https://github.com/apjanke/octave-jsonstuff octave-jsonstuff] (C++ Octave wrapper around [https://github.com/open-source-parsers/jsoncpp jsoncpp])
 
 
 
For different reasons, none of them can be directly merged into Octave core yet.  Thus there is still lots of work to do.  The goal of this project is to evaluate (and to cherry pick from) the implementations above, to create Matlab compatible [https://www.mathworks.com/help/matlab/ref/jsonencode.html jsonencode] and [https://www.mathworks.com/help/matlab/ref/jsondecode.html jsondecode] functions.  This involves proper documentation of the work and unit tests to ensure the correctness of the implementation.
 
 
 
* '''Minimum requirements'''
 
: Good Octave and C/C++ programming knowledge.  Ability to make use of C/C++ libraries.
 
* '''Difficulty'''
 
: Medium.
 
* '''Mentor'''
 
: [[User:Siko1056|Kai T. Ohlhus]]
 
 
 
 
 
=== Jupyter Notebook Integration ===
 
 
 
[http://jupyter.org Jupyter Notebook] is a web-based worksheet interface for computing.  There is a [https://github.com/Calysto/octave_kernel Octave kernel for Jupyter].  This project seeks in first place to improve that kernel to make Octave a first-class experience within the Jupyter Notebook.
 
 
 
In general the [https://nbformat.readthedocs.io/en/latest/ Jupyter Notebook Format] is a plain JSON document.  In combination with another Octave GSoC project (see [[Summer of Code - Getting Started#JSON_encoding.2Fdecoding | JSON encoding/decoding]]), a second valuable outcome was that Octave can run (and fill) those Jupyter Notebooks on it's own.  This would enable Jupyter Notebook users to evaluate long running Octave Notebooks on a computing server without permanent browser connection, which is [https://github.com/jupyter/notebook/issues/1647 still a pending issue].
 
 
 
* '''Minimum requirements'''
 
: Good Octave and Python programming knowledge.
 
* '''Difficulty'''
 
: Medium.
 
* '''Mentors'''
 
: Colin B. Macdonald, Mike Miller, [[User:Siko1056|Kai T. Ohlhus]]
 
 
 
=== Using Python within Octave ===
 
 
 
[https://bitbucket.org/mtmiller/pytave Pytave] allows one to call Python functions and interact with Python objects from within Octave .m file code and from the Octave command line interface.  Ideally, Pytave will not be a separate project, but rather a core feature of Octave.  This project aims to improve Pytave with the goal of merging the code into the core Octave code base. 
 
 
 
Based on a previous summer project related to Pytave, this work will consist of fast-paced collaborative software development based on tackling the [https://bitbucket.org/mtmiller/pytave/issues?status=new&status=open pytave 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 decision 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?
 
 
 
* '''Mentors'''
 
: Mike Miller, Colin B. Macdonald, Abhinav Tripathi, others?
 
 
 
 
 
=== Octave Package management ===
 
 
 
[[Packages]] are extensions for Octave, that are mainly maintained by the [[Octave Forge]] community.
 
To get those extension to work with Octave, there is a single function, {{manual|pkg}}, which does pretty much everything.
 
This function has a few limitations which are hard to implement with the current codebase, and will most likely require a full rewrite.
 
A major step forward for a rewritten package manager is the [https://github.com/apjanke/octave-packajoozle/ "packajoozle" project] by Andrew Janke.
 
 
 
The planned improvements (see also {{bug|39479}}) are:
 
 
 
* install and update from repositories (hg and git)
 
* automatic handling of dependencies
 
* easily load, update or check specific package versions
 
* management of tests and demos in C++ sources of packages
 
* more flexibility on dependencies, e.g., dependent on specific Octave build options or being dependent in one of multiple packages
 
* support for multiple version packages
 
* support for multiple Octave installs
 
* support for system-wide and user installed packages
 
* testing packages (<code>pkg test <package-name></code>)
 
* improved metadata acquisition (<code>pkg list -forge</code>) from https://octave.sourceforge.io/
 
 
 
The main objective of this project is to make {{manual|pkg}} more user friendly and to make it a tool to foster third party participation in Octave.
 
However, the current {{manual|pkg}} also performs some maintenance functions which it probably should not.
 
Instead a package for developers should be created with such tools.
 
To do this enhancement effectively, a refactoring of the current {{codeline|pkg}} code will be needed (see [https://github.com/apjanke/octave-packajoozle/ "packajoozle" project]).
 
 
 
Many of these problems have been solved in other languages.
 
Familiarity with how other languages handle this problem will be useful to come up with elegant solutions.
 
In some cases, there are standards to follow.
 
For example, there are specifications published by freedesktop.org about where files should go ([http://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html base directory spec]) and Windows seems to have its own standards.
 
See bugs {{bug|36477}} and {{bug|40444}} for more details.
 
 
 
In addition, package names may start to collide very easily.
 
One horrible way to workaround this by is choosing increasingly complex package names that give no hint on the package purpose.
 
A much better is option is providing an Authority category like Perl 6 does.
 
Nested packages is also an easy way to provide packages for specialized subjects (think {{codeline|image::morphology}}).
 
A new {{manual|pkg}} would think all this things now, or allow their implementation at a later time.
 
Read the [[OEP:pkg|unfinished plan]] for more details.
 
 
 
* '''Minimum requirements'''
 
: Ability to read and write Octave code, experience with Octave packages, and understanding of the basics of autotools. The most important skill is software design.
 
* '''Difficulty'''
 
: Medium.
 
* '''Mentor'''
 
: [[User:KaKiLa|KaKiLa]], Carnë Draug, Carlo de Falco, Sebastian Schöps
 
 
 
== Image Analysis ==
 
 
 
=== Improvements to N-dimensional image processing ===
 
 
 
The image package has partial functionality for N-dimensional images. These images exist for example in medical imaging where slices from scans are assembled to form anatomical 3D images. If taken over time and at different laser wavelengths or light filters, they can also result in 5D images. Albeit less common, images with even more dimensions also exist. However, their existence is irrelevant since most of the image processing operations are mathematical operations which are independent of the number of dimensions.
 
 
 
As part of GSoC 2013, the core functions for image IO, {{codeline|imwrite}} and {{codeline|imread}}, were extended to better support this type of images. Likewise, many functions in the image package, mostly morphology operators, were expanded to deal with this type of image. Since then, many other functions have been improved, sometimes completely rewritten, to abstract from the number of dimensions. In a certain way, supporting ND images is also related to choosing good algorithms since such large images tend to be quite large.
 
 
 
This project will continue on the previous work, and be mentored by the previous GSoC student and current image package maintainer. Planning the project requires selection of functions lacking ND support and identifying their dependencies. For example, supporting {{codeline|imclose}} and {{codeline|imopen}} was better implemented by supporting {{codeline|imerode}} and {{codeline|imdilate}} which then propagated ND support to all of its dependencies. These dependencies need to be discovered first since often they are not being used yet, and may even be missing function. This project can also be about implementing functions that have [[Image package#Missing functions | not yet been implemented]]. Also note that while some functions in the image package will accept ND images as input, they are actually not correctly implemented and will give incorrect results.
 
 
 
* '''Required skills'''
 
: m-file scripting, and a fair amount of C++ since a lot of image analysis cannot be vectorized. Familiarity with common CS algorithms and willingness to read literature describing new algorithms will be useful.
 
* '''Difficulty'''
 
: Difficult.
 
* '''Potential mentor'''
 
: Carnë Draug
 
 
 
=== Improve Octave's image IO ===
 
 
 
There are a lot of image formats. To handle this, Octave uses [http://www.graphicsmagick.org/ GraphicsMagic] (GM), a library capable of handling [http://www.graphicsmagick.org/formats.html a lot of them] in a single C++ interface. However, GraphicsMagick still has its limitations. The most important are:
 
 
 
* 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, but building it too low 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 away 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 would implement better image IO for scientific file formats while leaving GM handle the others. Since TIFF is the de facto standard for scientific images, this should be done first. Among the targets for the project are:
 
 
 
* implement the Tiff class which is a wrap around libtiff, using classdef. To avoid creating too many private __oct functions, this project could also create a C++ interface to declare new Octave classdef functions.
 
* improve imread, imwrite, and imfinfo for tiff files using the newly created Tiff class
 
* port the bioformats into Octave and prepare a package for it
 
* investigate other image IO libraries
 
* clean up and finish the dicom package to include into Octave core
 
* prepare a matlab compatible implementation of the FITS package for inclusion in Octave core
 
 
 
* '''Required skills'''
 
: Knowledge of C++ and C since most libraries are written in those languages.
 
* '''Difficulty'''
 
: Medium.
 
* '''Potential mentor'''
 
: Carnë Draug
 
 
 
== Graphics ==
 
 
 
=== 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 listerners to get things to work.  What is needed is a first class implementation of a "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" exist 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.  relates to {{bug|35565}}, {{bug|49804}}, {{bug|52643}}.
 
 
 
* '''Minimum requirements'''
 
: Ability to read and write C++ code.  Ability to read and write Octave code.  Experience with OpenGL programming is optional.
 
* '''Difficulty'''
 
: Medium.
 
* '''Mentor'''
 
: Rik
 
  
<noinclude>
 
 
[[Category:Summer of Code]]
 
[[Category:Summer of Code]]
 
[[Category:Project Ideas]]
 
[[Category:Project Ideas]]
</noinclude>
 

Latest revision as of 21:02, 14 February 2021

Since 2011 the GNU Octave project has mentored 38 students in Summer of Code (SoC) programs by Google and ESA. Those 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. Communicate with us.
    • Join Octave Discourse or our IRC channel.
    • We are interested in you as motivated developer 💻 There is no need to present an overwhelming CV with prestigious universities 🏰 and programming contest awards 🏆 in it. We are very fine if you just communicate using a nickname with us.
    • If your first question is "Hi I'm new to Octave. What should I do?" you are out 🤦
  2. 📝💡 Tell us what you are going to do.
    • When you contact us for the first time, do not write just to say in what project you're interested in. Be specific about what you are going to do, post many links 🔗, show us you know what you are talking about 💡, and ask many smart questions 🤓
    • Remember, we are voluntary developers and not your boss 🙂
  3. 👩‍🔬 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 you come across a missing function ➡️ try to implement it.
  4. 📔 Prepare your proposal with us.
    • GSoC, for example, requires to submit a proposal.
    • If we see your proposal for the first time after the application deadline, you can easily imagine that it might contain ambiguities or some paragraphs are not fully clear to us. We easily get doubts if you are capable of working on your project 😓
    • Try to show us as early as possible a draft of your proposal 👍

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 it's 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 students. You can also look at our completed past projects for more inspiration.

Info icon.svg
Do you use Octave at your university or 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.

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.

  • Required skills
Knowledge of Octave, C/C++; familiarity with numerical methods for DAEs
  • Potential mentors
Francesco Faccio, Carlo de Falco, Marco Caliari, Jacopo Corno, Sebastian Schöps

Using Python within Octave[edit]

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.

Based on a previous summer project related to Pythonic, this work will consist of fast-paced collaborative software development based on tackling the 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?

  • Required skills
Knowledge of Octave, C/C++, Python
  • Potential mentors
Mike Miller, Colin B. Macdonald, 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.

  • Required skills
Knowledge of 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.

  • Required skills
Knowledge of 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.

  • Required skills
Knowledge of Octave, C/C++
  • Potential mentors
Kai

Jupyter Notebook Integration[edit]

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.

To interactively work with Octave code within Jupyter Notebooks, there already exists an Octave kernel for Jupyter.

This project aims to support the opposite direction: running (and filling) Jupyter Notebook within GNU Octave. This would enable Jupyter Notebook users to evaluate long running Octave Notebooks on a computing server without permanent browser connection, which is still a pending issue. To achieve this, different strategies are possible:

  1. Synchronize an internal Octave data structure (e.g. classdef object) with the Jupyter Notebook. Probably the safest approach, but does not enable any interactivity from the Octave GUI.
  2. Import/export a Jupyter Notebook as Octave script (translate non-code sections to comments and vice versa). Files can be edited from the Octave GUI, but probably conversion losses might occur (e.g. embedded graphics).
  3. A synthesis of both approaches?

In general a Jupyter Notebook is a plain JSON document, which will be supported in Octave 7 (current development version) or through the JSON package for older Octave versions.

  • Required skills
Knowledge of Octave, C/C++
  • Potential mentors
Kai

Adding functionality to packages[edit]

OCS package[edit]

The OCS package is a circuit simulator. The objective of this project is to increase compatibility with SPICE and improve compatibility with other Octave packages, e.g. the Control package. Please study the available functions of this package.

  • Required skills
Knowledge of Octave, C/C++; FORTRAN API knowledge
  • Potential mentors
Sebastian Schöps, Carlo de Falco

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 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 package.

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 f.diff(x) instead of diff(f, x).

  • Required skills
Knowledge of Octave, C/C++, Python; object-oriented programming (OOP) in Octave
  • Potential mentors
Colin B. Macdonald, Mike Miller, Abhinav Tripathi

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. Which are of importance for many scientific disciplines involving statistical computations and signal processing.

  • Required skills
Knowledge of Octave, C/C++; FORTRAN API knowledge
  • Potential mentors
KaKiLa