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

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The following is distilled from the [[Projects]] page for the benefit of potential [http://code.google.com/soc/Google Summer] [http://sophia.estec.esa.int/socis2012/?q=node/13 of Code] (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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{{Note|GNU Octave is a [https://summerofcode.withgoogle.com/programs/2022/organizations/gnu-octave mentoring organization for GSoC 2022].}}
  
= Steps Toward a Successful Application =
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Since 2011 the GNU Octave project has successfully mentored:
 +
* [[Summer of Code | '''37 participants''' 🙂]]
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* [[Summer of Code | '''39 projects''' 📝]]
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in [[Summer of Code]] (SoC) programs by [https://summerofcode.withgoogle.com/ Google] and [https://esa.int/ ESA].
  
If you like any of the projects described below these are the steps you need to follow to apply:
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Those SoC programs aim to advertise open-source software development and to attract potential new Octave developers.
  
* '''Help Us Get To Know You'''<br>
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= Steps toward a successful application =
: If you aren't communicating with us before the application is due, your application will not be accepted.
 
:: '''Join the 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 IRC channel'''. Ask questions, submit patches, 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!
 
* '''Find Something That Interests You'''
 
: 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).  But don't just tell us how interested you are, show us.  You can do that by fixing a few bugs or interacting with us on IRC well before the deadline.  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 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.<br/>
 
:: You really only need to copy and answer the '''''public''''' part there, there is no need to showcase everything else to everybody reading your user page!
 
: Fill out our '''''private''''' application template.
 
:: This is best done by copying the '''[[Template:Student_application_template_private|template]]''' from its page and '''adding the required information to your application at Google (melange)''' 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 ==
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# 😉💬 '''We want to get to know you (before the deadline).  Communicate with us.'''
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#* Join [https://octave.discourse.group/ '''Octave Discourse'''] or [[IRC]]. Using a nickname is fine.
 +
#* 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 🚮
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# 👩‍🔬 '''Get your hands dirty.'''
 +
#* We are curious about your programming skills 🚀
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#** Your application will be much stronger if you [https://savannah.gnu.org/bugs/?group=octave fix Octave bugs] or [https://savannah.gnu.org/patch/?group=octave submit patches] before or during the application period.
 +
#** You can take a look at the [[short projects]] for some simple bugs to start with.
 +
#* '''Use Octave!'''
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#** If you come across something that does not work the way you like ➡️ try to fix that 🔧
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#** Or if you find a missing function ➡️ try to implement it.
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# 📝💡 '''Tell us what you are going to do.'''
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#* Do not write just to say what project you're interested in.  Be specific about what you are going to do, include links 🔗, show us you know what you are talking about 💡, and ask many [http://www.catb.org/esr/faqs/smart-questions.html smart questions] 🤓
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#* Remember, '''we are volunteer developers and not your boss''' 🙂
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# 📔 '''Prepare your proposal with us.'''
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#* Try to show us as early as possible a draft of your proposal 📑
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#* If we see your proposal for the first time after the application deadline, it might easily contain some paragraphs not fully clear to us.  Ongoing interaction will give us more confidence that you are capable of working on your project 🙂👍
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#* Then submit the proposal following the applicable rules, e.g. for [https://google.github.io/gsocguides/student/writing-a-proposal GSoC]. 📨
  
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.
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= How do we judge your application? =
  
* '''The Build System'''
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Depending on the mentors and SoC program there are varieties, but typically the main factors considered would be:
: [http://en.wikipedia.org/wiki/GNU_build_system The GNU build system] is used to build Octave.
 
: While you generally don't need to understand too much unless you actually want to change how Octave is built, you should be able to understand enough to get a general idea of how to build Octave.
 
: If you've ever done a <tt>configure && make && make install</tt> series of commands, you have already used the GNU build system.
 
: '''You must demonstrate that you are able to build the development version of Octave from sources before the application deadline.'''
 
* '''The Version Control System'''
 
: We use [http://mercurial.selenic.com/ 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 the same style for changes, commit messages, and so on.  You should also read the same [http://www.gnu.org/software/octave/doc/interpreter/Contributing-Guidelines.html#Contributing-Guidelines contributing] [http://hg.savannah.gnu.org/hgweb/octave/file/tip/etc/HACKING guidelines] we have for everyone.
 
* '''The Maintainers Mailing List'''
 
: We primarily use [https://mailman.cae.wisc.edu/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 [http://en.wikipedia.org/wiki/Top_posting#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'''
 
: [http://octave.sf.net Octave-Forge] is a project closely related to Octave where packages reside. They are somewhat analogous to Matlab's toolboxes.
 
* '''Related Skills'''
 
: In addition, you probably should know '''some''' mathematics, engineering, or experimental science or something of the sort.
 
: If you've used Matlab before, you probably have already been exposed to the kinds of problems that Octave is used for.
 
  
<noinclude>[[Category:Summer of Code]]</noinclude>
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* '''You have demonstrated interest in Octave and an ability to make substantial modifications to Octave'''
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*: The most important thing is that you've contributed some interesting code samples to judge your skills. It's OK during the application period to ask for help on how to format these code samples, which normally are Mercurial patches.
  
= Suggested projects =
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* '''You showed understanding of your topic'''
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*: Your proposal should make it clear that you're reasonably well versed in the subject area and won't need all summer just to read up on it.
  
The following projects are broadly grouped by category and probable skills required to tackle each. Remember to check [[Projects]] for more ideas if none of these suit you, and your own ideas are always welcome.
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* '''Well thought out, adequately detailed, realistic project plan'''
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*: "I'm good at this, so trust me" isn't enough.  In your proposal, you should describe which algorithms you'll use and how you'll integrate with existing Octave code. You should also prepare a project timeline and goals for the midterm and final evaluations.
  
== Numerical ==
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= What you should know about Octave =
  
These projects involve implementing certain mathematical functions in Octave.
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GNU Octave is mostly written in C++ and its own scripting language that is mostly compatible with Matlab. There are bits and pieces of Fortran, Perl, C, awk, and Unix shell scripts here and there. In addition to being familiar with C++ and Octave's scripting language, you as successful applicant will be familiar with or able to quickly learn about Octave's infrastructure. You can't spend the whole summer learning how to build Octave or prepare a changeset and still successfully complete your project 😇
  
'''Required skills''': You should understand quite a bit of mathematics. Words like "eigenvalue", "analytic", and "Taylor series" shouldn't scare you at all. There is probably little C++ experience required, and probably many of these problems can be solved with m-scripts.
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You should know:
 +
# 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]
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# How to submit patches (changesets).
 +
#* Read in this wiki: [[Contribution guidelines]], [[Mercurial]]
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#* Tools to know: [https://en.wikipedia.org/wiki/Mercurial Mercurial (hg)], [https://en.wikipedia.org/wiki/Git git]
  
'''Difficulty''': Mid-to-hard depending how much mathematics you know and how well you can read numerical analysis journal articles.
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= Suggested projects =
 
 
'''Potential mentor''': Carlo de Falco, Fotios Kasolis, Luis Gustavo Lira
 
 
 
=== Incomplete sparse factorizations ichol, ilu ===
 
 
 
Octave still lacks of an incomplete Cholesky and LU factorization for sparse matrices. These functions are [http://www.mathworks.com/help/matlab/matrix-decomposition.html available in Matlab] as ichol and ilu. Incomplete factorizations are useful as preconditioners for iterative solvers such as [http://hg.savannah.gnu.org/hgweb/octave/file/812162c34a93/scripts/sparse/gmres.m gmres] or [http://hg.savannah.gnu.org/hgweb/octave/file/812162c34a93/scripts/sparse/pcg.m pcg].
 
 
 
Good introductions to the math behind these factorizations are:
 
* [http://netlib.org/linalg/html_templates/node81.html Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods] especially [http://netlib.org/linalg/html_templates/node100.html#SECTION00933000000000000000 this chapter]
 
* [http://www-users.cs.umn.edu/~saad/IterMethBook_2ndEd.pdf Iterative Methods for Sparse Linear Systems (2nd Edition)] chapter 10 (also available as textbook)
 
 
 
One should additionally familiarize with Octave's internal sparse matrix format which is [http://netlib.org/linalg/html_templates/node92.html#SECTION00931200000000000000 CCS] rather than [http://netlib.org/linalg/html_templates/node91.html#SECTION00931100000000000000 CRS], used in the listed textbooks. In the past GSoC a solution using [http://www-users.cs.umn.edu/~saad/software/ITSOL/ ITSOL] has been created. This work needs several improvements before it can be integrated into the Octave core. Read more about the past GSoC project in [http://siko1056-gsoc.blogspot.de/ this blog]. A [http://siko1056-gsoc.blogspot.de/p/getting-my-work.html demo implementation] is also available from there.
 
 
 
Compared to other projects in this section this one might require more knowledge of C++ and mathematical software programming. But this project doesn't need to be started from scratch and can be continued from the previous approach, if desired. For more information feel free to contact <k.ohlhus@gmail.com>.
 
 
 
=== General purpose Finite Element library ===
 
 
 
Octave-Forge already has a set of packages for discretizing Partial Differential operators by Finite Elements and/or Finite Volumes,
 
namely the [[bim package]] which relies on the [http://octave.sf.net/msh msh package] (which is in turn based on [http://geuz.org/gmsh/ gmsh]) for creating and managing 2D triangular and 3D tetrahedral meshes and on the [http://octave.sf.net/fpl fpl package] for visualizing 2D results within Octave or exporting 2D or 3D results in a format compatible with [http://www.paraview.org Paraview] or [https://wci.llnl.gov/codes/visit/ VisIT]. These packages, though, offer only a limited choice of spatial discretization methods which are based on low degree polynomials and therefore have a low order of accuracy even for problems with extremely smooth solutions.
 
The [http://geopdes.sf.net GeoPDEs] project, on the other hand, offers a complete suite of functions for discretizing a wide range of
 
differential operators related to important physical problems and uses basis functions of arbitrary polynomial degree that allow the construction of methods of high accuracy. These latter, though, are based on the IsoGeometric Analysis Method which, although very powerful and often better performing, is less widely known and adopted than the Finite Elements Method. The implementation of a general purpose library of Finite Elements seems therefore a valuable addition to Octave-Forge. Two possible interesting choices for implementing this package exist, the first consists of implementing the most common Finite Element spaces in the [http://geopdes.sf.net GeoPDEs] framework, which is possible as IsoGeometric Analysis can be viewed as a superset of the Finite Element Method, the other is to construct Octave language bindings for the free software library [http://fenicsproject.org/documentation/ FEniCS] based on the existing C++ or Python interfaces. This second approach has been developed during the GSOC 2013 and the Octave-Forge package [http://octave.sf.net/fem-fenics fem-fenics] is now available. However, fem-fenics could be extended in many different ways:
 
* implement the bindings for the UFL language inside Octave
 
* add new functions already available with Fenics but not yet in Octave
 
* create new functions specifically suited for Octave
 
* improve the efficiency of the code
 
The main goal for the fem-fenics package is ultimately to be merged with the FEnics project itself, so that it can remain in-sync with the main library development.
 
 
 
=== Improve logm, sqrtm, funm ===
 
 
 
The goal here is to implement some missing Matlab functions related to matrix functions like the [http://en.wikipedia.org/wiki/Matrix_exponential matrix exponential]. There is [http://octave.1599824.n4.nabble.com/matrix-functions-td3137935.html a general discussion] of the problem.
 
 
 
=== Generalised eigenvalue problem ===
 
 
 
[http://www.mathworks.com/help/techdoc/ref/eig.html Certain calling forms] of the <tt>eig</tt> function are missing. The problem is to understand what those missing forms are and implement them.
 
 
 
=== Various sparse matrix improvements ===
 
 
 
The implementation of sparse matrices in Octave needs several improvements. Any of [[Projects#Sparse Matrices|these]] would be good. The paper by [http://arxiv.org/abs/cs.MS/0604006 Bateman & Adler] is good reading for understanding the sparse matrix implementation.
 
 
 
=== Implement solver for initial-boundary value problems for parabolic-elliptic PDEs in 1D ===
 
 
 
The project will deliver a solver for initial-boundary value problems for parabolic-elliptic PDEs in 1D similar to Matlab's function <tt>pdepe</tt>. A good starting point is the [http://en.wikipedia.org/wiki/Method_of_lines method of lines] for which you can find more details [http://en.wikibooks.org/wiki/Partial_Differential_Equations/Method_of_Lines here] and [http://www.scholarpedia.org/article/Method_of_lines here], whereas an example implementation can be found [http://www.scholarpedia.org/article/Method_of_Lines/Example_Implementation here]. In addition, [http://www.pdecomp.net/ this page] provides some useful material.
 
 
 
=== Implement solver for 1D nonlinear boundary value problems ===
 
 
 
The project will complete the implementation of the bvp4c solver that is already available in an initial version in the odepkg package
 
by adding a proper error estimator and will implement a matlab-compatible version of the bvp5c solver.
 
Details on the methods to be implemented can be found in [http://dx.doi.org/10.1145/502800.502801 this paper] on bvp4c and [http://www.jnaiam.net/new/uploads/files/014dde86eef73328e7ab674d1a32aa9c.pdf this paper] on bvp5c. Further details are available in [http://books.google.it/books/about/Nonlinear_two_point_boundary_value_probl.html?id=s_pQAAAAMAAJ&redir_esc=y this book].
 
 
 
=== Geometric integrators for Hamiltonian Systems ===
 
 
 
[http://openlibrary.org/books/OL9056139M/Geometric_Numerical_Integration Geometric (AKA Symplectic) integrators] are useful for
 
multi-dimensional classical mechanics problems and for molecular dynamics simulations.
 
The odepkg package has a number of solvers for ODE, DAE and DDE problems but none of them is currently
 
specifically suited for second order problems in general and Hamiltonian systems in particular.
 
Therefore a new package for geometric integrators would be a useful contribution.
 
This could be created as new package or added as a set of new functions for odepkg.
 
The function interface should be consistent throughout the package and should be modeled to follow
 
that of other functions in odepkg (or that of DASPK and LSODE) but will need specific  extensions to accommodate for specific options that only make sense for this specific class of solvers.
 
An initial list of methods to be implemented includes (but is not limited to)
 
* Symplectic Euler methods, see [http://en.wikipedia.org/wiki/Semi-implicit_Euler_method here] and [http://openlibrary.org/books/OL9056139M/Geometric_Numerical_Integration here]
 
* Störmer-Verlet method, see [http://en.wikipedia.org/wiki/Verlet_integration here] and [http://openlibrary.org/books/OL9056139M/Geometric_Numerical_Integration here]
 
* Velocity Verlet method, see [http://en.wikipedia.org/wiki/Verlet_integration here] and [http://openlibrary.org/books/OL9056139M/Geometric_Numerical_Integration here]
 
* Symplectic partitioned Runge-Kutta methods, see [http://reference.wolfram.com/mathematica/tutorial/NDSolveSPRK.html here] or [http://dx.doi.org/10.1137/0733019 here]
 
* Spectral Variational Integrator methods, see [http://www3.nd.edu/~izaguirr/papers/acta_numerica.pdf here] or [http://www.math.ucsd.edu/~mleok/pdf/HaLe2012_SVI.pdf here]
 
 
 
For this latter there is an existing code which is already working but needs to be improved, posted on the patch tracker.
 
Furthermore, methods to implement solutions of problems with rigid constraints should be implemented, e.g.
 
* SHAKE, see [http://en.wikipedia.org/wiki/Constraint_algorithm here] or [http://dx.doi.org/10.1016/0021-9991(77)90098-5 here]
 
* RATTLE, see [http://dx.doi.org/10.1016/0021-9991(83)90014-1 here] or [http://dx.doi.org/10.1002/jcc.540161003 here]
 
 
 
'''Potential mentor:''' Mattia Penati, Edie Miglio, Carlo de Falco
 
 
 
=== Matlab-compatible ODE solvers in core-Octave ===
 
 
 
* Adapt "odeset" and "odeget" from the odepkg package so that the list of supported options is more Matlab-compatible, in the sense that all option names that are supported by Matlab should be available. On the other hand, Matlab returns an error if an option which is not in the list of known options is passed to "odeset", but we would rather make this a warning in order to allow for special extensions, for example for symplectic integrators.
 
* Adapt the interface of "ode45" in odepkg to be completely Matlab compatible, fix its code and documentation style and move it to Octave-core.
 
* Build Matlab compatible versions of "ode15s" and "ode15i". jwe has prototype implementations [https://savannah.gnu.org/patch/index.php?8102|here] of these built as wrappers to "dassl" and "daspk". An initial approach could be to just improve these wrappers, but eventually it would be better to have wrappers for "IDA" from the sundials library.
 
* Implement Matlab compatible versions of "deval".
 
 
 
'''Potential mentor:''' Sebastian Schöps, Carlo de Falco
 
 
 
== GUI ==
 
 
 
Octave currently includes an experimental native GUI, written in Qt. There are various ways in which it could be improved.
 
 
 
'''Required skills''': C++ and Qt. Whatever tools you want to use to write Qt code are fine, but Qt Creator is a popular choice nowadays.
 
 
 
'''Difficulty''': Mostly medium, depending if you've had Qt or GUI development experience before.
 
 
 
'''Potential mentor''': Jordi Gutiérrez Hermoso, Michael Goffioul, Torsten
 
 
 
=== Finish the Octave GUI ===
 
<strike>
 
The GUI is currently on its own branch in hg. It is not stable enough and its design is still in flux. It is in a very alpha stage and needs to be turned into a real usable product. At the moment, it consists of the basic building blocks (terminal window, editor, variable browser, history, file browser) that are put together into a main interface. The GUI uses the Qt library. Among the things to improve are:
 
* improve integration with octave: variable browser/editor, debugger, profiler...
 
* define and implement an option/preferences dialog
 
* improve additional components like the documentation browser
 
</strike>
 
Fix existing bugs related to the GUI, which can be browsed [https://savannah.gnu.org/bugs/index.php?go_report=Apply&group=octave&func=browse&set=custom&msort=0&report_id=100&advsrch=0&status_id=1&resolution_id=0&assigned_to=0&category_id=107&bug_group_id=0&history_search=0&history_field=0&history_event=modified&history_date_dayfd=5&history_date_monthfd=2&history_date_yearfd=2014&chunksz=50&spamscore=5&boxoptionwanted=1#options here]
 
 
 
=== Implement a Qt widget for manipulating plots ===
 
 
 
Octave has had for some time a native OpenGL plotter. The plotter requires some user interaction for manipulating the plots, and it's been using fltk for quite some time. We want to replace this with Qt, so it fits better with the overall GUI look-and-feel and is easier to extend in the future.
 
 
 
[https://github.com/goffioul/QtHandles QtHandles] is a current work in progress integrating the octave OpenGL renderer plus good support for GUI elements (uicontrol, uimenu, uitoolbar...). This project may initially consists of integrating the existing QtHandles code base into Octave. Then if time permits, further improvements can be made to QtHandles.
 
 
 
=== Create a better (G)UI for the profiler ===
 
 
 
During GSoC 2011, Daniel Kraft successfully implemented a profiler for Octave. It needs a better interface and a way to generate reports. This may be done with Qt, but not necessarily, and HTML reports might also be good.
 
 
 
=== Create a graphical design tool for tuning closed loop control system (control pkg) ===
 
 
 
When tuning a SISO feedback system it is very helpful to be able to grab a pole or a zero and move them by dragging them with the mouse. As they are moving the software must update all the plotted lines. There should be the ability to display various graphs rlocuse, bode, step, impulse etc. and have them all change dynamically as the mouse is moving. The parameters of the compensator must be displayed and updated.
 
Potential mentor: Doug Stewart
 
 
 
== Graphics ==
 
 
 
Octave has a new native OpenGL plotter (currently via [http://en.wikipedia.org/wiki/Fltk fltk], but we want to move away from that). There are several possible projects involved with it.
 
 
 
'''Required skills''': C++ and OpenGL. General understanding of computer graphics.
 
 
 
'''Difficulty''': Medium, depending on your previous understanding of the topic.
 
 
 
'''Potential mentor''': Michael Goffioul
 
 
 
=== Lighting ===
 
 
 
Implement transparency and lighting in OpenGL backend(s). A basic implementation is available in [http://octave.svn.sourceforge.net/viewvc/octave/trunk/octave-forge/extra/jhandles/ JHandles]. This needs to be ported/re-implement/re-engineered/optimized in the C++ OpenGL renderer of Octave.
 
 
 
=== Object selection in OpenGL renderer ===
 
 
 
This project is about the implementation of a selection method of graphics elements within the OpenGL renderer [http://glprogramming.com/red/chapter13.html]
 
 
 
=== Non-OpenGL renderer ===
 
 
 
Besides the original gnuplot backend, Octave also contains an OpenGL-based renderer for advanced and more powerful 3D plots. However, OpenGL is not perfectly suited for 2D-only plots where other methods could result in better graphics. The purpose of this project is to implement an alternate graphics renderer for 2D only plots (although 3D is definitely not the focus, extending the new graphics renderer to support basic 3D features should also be taken into account). There is no particular toolkit/library that must be used, but natural candidates are:
 
* [http://qt.nokia.com Qt]: the GUI is currently written in Qt and work is also in progress to provide a Qt/OpenGL based backend [https://github.com/goffioul/QtHandles]
 
* [http://en.wikipedia.org/wiki/Cairo_%28software%29 Cairo]: this library is widely used and known to provides high-quality graphics with support for PS/PDF/SVG output.
 
 
 
=== TeX/LaTeX markup ===
 
 
 
Text objects in plots (like titles, labels, texts...) in the OpenGL renderer only support plain text mode without any formatting possibility. Support for TeX and/or LaTeX formatting needs to be added.
 
 
 
* The TeX formatting support actually only consists of a very limited subset of the TeX language. This can be implemented directly in C++ into Octave by extending the existing text engine, avoiding to add a dependency on a full TeX system.  Essentially, support for Greek letters, super/sub-scripts, and several mathematical symbols needs to be supported.  For example,
 
 
 
:<pre>\alpha \approx \beta_0 + \gamma^\chi</pre>
 
 
 
:Would be rendered as,
 
 
 
:&alpha; &asymp; &beta;<sub>0</sub> + &gamma;<sup>&chi;</sup>
 
 
 
:This is analogous to how special characters may be included in a wiki using html.
 
 
 
:<pre>&amp;alpha; &amp;asymp; &amp;beta;<sub>0</sub> + &amp;gamma;<sup>&amp;chi;</sup></pre>
 
 
 
:The text object's {{Codeline|extent}} for the rendered result needs to be calculated and the text placed the location specified by the text object's {{Codeline|position}} property.  An itemized list of a text objects properties can be found [http://www.gnu.org/software/octave/doc/interpreter/Text-Properties.html here].
 
 
 
* On the other hand, the LaTeX formatting support is expected to provide full LaTeX capabilities. This will require to use an external LaTeX system to produce text graphics in some format (to be specified) that is then integrated into Octave plots.
 
 
 
:The matplotlib project [http://matplotlib.sourceforge.net/users/usetex.html has already done this in Python] and might be used as an example of how to do this in Octave.  Mediawiki has also also done [http://en.wikipedia.org/wiki/Wikipedia:Texvc something similar]. There is also [http://forge.scilab.org/index.php/p/jlatexmath/ JLaTeXMath], a Java API to display LaTeX code in mathematical mode.
 
 
 
== Interpreter ==
 
 
 
The interpreter is written in C++, undocumented. There are many possible projects associated with it.
 
 
 
'''Required skills''': ''Very good'' C and C++ knowledge, possibly also understanding of [http://en.wikipedia.org/wiki/Gnu_bison GNU bison] and [http://en.wikipedia.org/wiki/Flex_lexical_analyser flex]. Understanding how compilers and interpreters are made plus being able to understand how to use a profiler and a debugger will probably be essential skills.
 
 
 
'''Difficulty''': Mid hard to very hard. Some of the biggest problems will probably be the interpreter.
 
 
 
'''Potential mentors''': John W. Eaton, Jordi Gutiérrez Hermoso, Max Brister.
 
 
 
=== Improve JIT compiling ===
 
 
 
Octave's interpreter is ''very'' slow on some loops. Last year, thanks to Max Brister's work, an initial implement of a just-in-time compiler (JITC) in [http://llvm.org LLVM] for GSoC 2012. This project consists in understanding Max's current implementation and extending it so that functions and exponents  (e.g. 2^z) compile with the JITC. This requires knowledge of compilers, C++, LLVM, and the Octave or Matlab languages. A capable student who demonstrates the ability to acquire this knowledge quickly may also be considered. Max himself will mentor this project. [http://planet.octave.org/octconf2012/jit.pdf Here] is Max's OctConf 2012 presentation about his current implementation. See also [[JIT]].
 
 
 
=== Improve memory management ===
 
 
 
From profiling the interpreter, it appears that a lot of time is spending allocating and deallocating memory. A better memory management algorithm might provide some improvement.
 
 
 
=== Implement classdef classes ===
 
 
 
Matlab has two kinds of classes: old style @classes and new style classdef. Octave has only fully implemented the old style. There is partial support for new classes in [http://hg.savannah.gnu.org/hgweb/octave/shortlog/classdef our classdef branch]. There is irregular work here, and classdef is [http://www.mathworks.com/help/matlab/matlab_oop/method-attributes.html a very] [http://www.mathworks.com/help/matlab/events-sending-and-responding-to-messages.html complicated] [http://www.mathworks.com/help/matlab/enumeration-classes.html thing] to fully implement. A successful project would be to implement enough of classdef for most basic usages. Familiarity with Matlab's current classdef support would be a huge plus. Michael Goffioul and jwe can mentor this.
 
 
 
== Infrastructure ==
 
 
 
There are several projects closely related to Octave but not exactly core Octave that could be worked on. They are mostly infrastructure around Octave, stuff that would help a lot.
 
 
 
'''Required skills''': Various. See below.
 
 
 
'''Difficulty''': Various. See below.
 
 
 
'''Potential mentor''': Jordi Gutiérrez Hermoso, Carlo de Falco
 
 
 
=== Finish the Agora website ===
 
 
 
In 2009, the Mathworks decided to restrict the terms of use Matlab Central, a place dedicated to Matlab collaboration. The Mathworks forbade copyleft licenses and using the "free" code found in Matlab central on anything other than Mathworks products (e.g. forbidding from using it on Octave, even if the authors of the code wanted to allow this). Thus Octave users have no place to centrally, quickly, and conveniently share Octave code. See the [[FAQ#Why_can.27t_I_use_code_from_File_Exchange_in_Octave.3F_It.27s_released_under_a_BSD_license.21|FAQ]] for more details.
 
 
 
In response to this, a website started to form, [http://agora.octave.org/ Agora Octave].
 
 
 
This should be relatively easy webdev in Python using [http://en.wikipedia.org/wiki/Django_%28web_framework%29 Django].
 
 
 
Things to be considered when working on this:
 
 
 
* [http://octave-forge.blogspot.ie/2012/08/octconf2012-agora-and-pkg.html discussion of Agora during OctConf2012]
 
* [http://scipy-central.org/ Scipy Central] - a website with the same objective as Agora for Scipy. Their [https://github.com/kgdunn/SciPyCentral/ code] is released under a BSD license. Might be useful to reuse some parts.
 
 
 
Most of the basic functionality of Agora is already in, but there are many ways in which it could be improved, such as implementing comment threads, giving it an email interface, or a ReSTful API which could be used from Octave for package management. See also [[Agora]].
 
 
 
=== Improve binary packaging ===
 
 
 
We would like to be able to easily generate binary packages for Windows and Mac OS X. Right now, it's difficult and tedious to do so. Any way to help us do this in a faster way would be appreciated. Required knowledge is understanding how building binaries in Windows and Mac OS X works. Our current approach to fixing this is to cross-compile from a GNU system using [http://mxe.cc/ MXE] or [http://lilypond.org/gub/ GUB].
 
 
 
'''Skills Required''': Knowledge of GNU build systems, Makefiles, configure files, chasing library dependencies, how to use a compiler. If you choose to work on GUB, Python will be required. No m-scripting or C++ necessary, beyond understanding [http://david.rothlis.net/c/compilation_model/ the C++ compilation model].
 
 
 
'''Difficulty''': Medium to easy. You need to understand how build systems work and how to fix packages when they don't build.
 
 
 
'''Possible mentors''': John W. Eaton or Jordi Gutiérrez Hermoso
 
 
 
=== Installation of packages ===
 
We would like to enhance the management of Octave-forge packages from within Octave environment. Currently there is a working (but rather monolithic) function that is used to do the job. The work would be to improve the way Octave interacts with the package server. Since the functionality is already sketched by the current function, the most important skill is software design.
 
 
 
'''Minimum requirements''': Ability to read and write Octave code. Minimal FTP/HTTP knowledge.
 
  
'''Difficulty''': Easy
+
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.
  
== Octave-Forge packages ==
+
{{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.}}
  
=== Improve MPI package ===
+
== openlibm ==
Octave Forge's [http://octave.sourceforge.net/mpi/index.html MPI package]
 
is a wrapper for basic MPI functions for parallel computing. It is implemented
 
by wrapping MPI function calls in simple DLD functions that map Octave's Datataypes to
 
MPI Derived Datatypes.
 
The proposed project deals with improving and extending the Octave MPI package, for example:
 
* Octave MPI applications can currently be only run in batch mode, add the ability to launch parallel jobs and collect their output in an interactive Octave session.
 
* Implement functions for non-blocking communication (MPI_Isend, MPI_Irecv)
 
* Implement one-to-many (Broadcast, Scatter), many-to-one (Reduce, Gather), and many-to-many (All Reduce, Allgather) communication routines
 
  
'''Required skills''': C++. Message Passing Interface (MPI).
+
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.
  
'''Difficulty''': medium.
+
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.
  
'''Potential mentor''': Carlo de Falco, Michael Creel, Sukanta Basu
+
* '''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]
  
=== Rewrite symbolic package ===
+
== ode15{i,s} : Matlab Compatible DAE solvers ==
Octave's current [http://octave.svn.sourceforge.net/viewvc/octave/trunk/octave-forge/main/symbolic/ symbolic] package for symbolic computation is outdated, fragile and limited in its capabilities. The new symbolic package should offer better Matlab compatibility, for example handling of symbolic matrices. Like the current symbolic package, the new package could use the proven [http://www.ginac.de/ GiNaC] library for symbolic computations.
 
  
The work would be to integrate GiNaC by using Octave's objects and classes. This can be done in C++ in a way similar to Michele Martone's new [http://librsb.sourceforge.net/ sparsersb] package.
+
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}}].
  
This idea has not been selected by any SoC student yet, if you want to see it happen before next SoC
+
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.
you can offer a bounty [http://www.freedomsponsors.org/core/issue/289/gnu-octave-rewrite-the-symbolic-package here].
 
  
'''Required skills''': C++. Ability to understand Octave and GiNaC API documentation.
+
* '''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]
  
'''Difficulty''': medium.
+
== Symbolic package ==
  
'''Potential mentor''': Lukas Reichlin
+
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]].
  
=== Improvements to N-dimensional image processing ===
+
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.
  
The image package has partial functionality for N-dimensional images. These images do exist in practice for example in medical imaging where slices from scans are assembled to form anatomical 3D images, or even exposures taken over time on different wavelengths can result in 5D images. As part of GSoC 2013, the core functions {{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 images. Still, many are left to, specially image transformation and analysis of ROIs.
+
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.
  
Note that while many of the functions in the image package will not complain about ND images, they are actually not correctly implemented and will give incorrect results.
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
 +
: ~350 hours (medium)
 +
* '''Required skills'''
 +
: Octave, C/C++, Python; object-oriented programming (OOP) in Octave
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/cbm Colin B. Macdonald], [https://octave.discourse.group/u/mtmiller Mike Miller], Abhinav Tripathi
  
'''Required skills''': Mostly m-file scripting, some C++. Familiarity with common CS algorithms will be useful.
+
== Improve TIFF image support ==
  
'''Difficulty''': difficult.
+
[https://en.wikipedia.org/wiki/TIFF Tag Image File Format (TIFF)] is the de facto standard for scientific images.  Octave uses the [http://www.graphicsmagick.org/ GraphicsMagic] (GM) C++ library to handle [http://www.graphicsmagick.org/formats.html TIFF and many others image formats]. However, GM still has several limitations:
  
'''Potential mentor''': Jordi Gutiérrez Hermoso
+
* 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.
  
=== Interface to Electronic Circuit Simulator ===
+
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.
  
[http://sourceforge.net/projects/qucs/ Qucs] is a C++ based circuit simulation package. This project aims to improve the interface to the Qucs algorithms to allow the transient, i.e. time series, simulation of circuits in Octave within a larger ODE system simulation driven by Octave. Other possible goals would be to make other analysis types available directly from Octave. There is an existing C++ interface which is based on handle class syntax available in the development version of Octave. The Qucs interface is intended to have two modes, synchronous and asynchronous. The asynchronous mode uses qucs to solve a circuit between two given time steps (internally taking as many smaller time steps as required), returning only the final result. This method is well developed. The alternative synchronous mode is intended to give full control of the time steps to Octave, and it is this mode which requires more work. A simple synchronous interface exists which can be built upon.
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
 +
: ~175 hours (medium)
 +
* '''Required skills'''
 +
: Octave, C/C++
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/carandraug Carnë Draug]
  
'''Required skills''': C++ and m-file scripting. Familiarity with new classdef syntax would be useful. May require some modification/adaptation of the Qucs sources. Familiarity with the Octave ODE solvers useful but not essential. Ability to compile Octave from the development sources.
+
== PolarAxes and Plotting Improvements ==
  
'''Difficulty''': medium.
+
Octave currently provides supports for polar axes by using a Cartesian 2-D axes and adding a significant number of properties and callback listeners to get things to work.  What is needed is the implementation of a dedicated "polaraxes" object in C++.  This will require creating a new fundamental graphics object type, and programming in C++/OpenGL to render the object.  When "polaraxes" exists as an object type, then m-files will be written to access them, including polaraxes.m, polarplot.m, rticks.m, rticklabels.m, thetaticks, thetaticklabels.m, rlim.m, thetalim.m.  This relates to bug {{bug|49804}}.
  
'''Potential mentor''': Richard Crozier
+
* '''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]
  
'''Main Goals'''
+
== Table datatype ==
* Improve the functionality of the transient solver interface by implementing a robust synchronous simulation mode that integrates well with Octave ode solvers, particularly those from the odepkg package from OctaveForge.
 
* Create interface to other analysis types (AC, DC, S-Parameter and Harmonic Balance)
 
* Packaging the interface for Octave
 
  
=== Color management functions in image package ===
+
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.
  
The goal is to implement these functions:
+
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.
  
    iccread
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
    iccwrite
+
: ~350 hours (hard)
    makecform
+
* '''Required skills'''
    applycform
+
: Octave, C/C++
 +
* '''Potential mentors'''
 +
: [https://octave.discourse.group/u/siko1056 Kai] [https://octave.discourse.group/u/Abdallah_Elshamy Abdallah]
  
These functions are useful for color management, in particular for converting data (especially images) between color spaces.  ICC profiles are essentially used to store look-up tables or matrix transforms (or both) that define the conversions.  For example, to convert an CMYK image to sRGB, you would load a "print" ICC profile that defines the conversion from CMYK to L*a*b* (the CIE color space that is supposed to match the human visual system), then load another profile that defines the conversion from L*a*b* to sRGB (there is a standard profile for this conversion (IEC 61966-2-1), which is why Matlab has a built-in conversion from sRGB to L*a*b*).  To do the above conversions in Matlab, you would use the following code:
+
== YAML encoding/decoding ==
  
<syntaxhighlight lang="octave">
+
[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]].
cmykImage = double(imread('cmyk-image-filename.tif'));
 
iccProfile = iccread('icc-profile-filename.icc');
 
labImage = applycform(cmykImage, makecform('clut', iccProfile, 'AToB3'));
 
rgbImage = applycform(labImage, makecform('lab2srgb'));
 
</syntaxhighlight>
 
  
The <code>'AToB3'</code> selects one of the color transforms (look-up tables) contained in the profile.  This one is "Absolute Colorimetric."  More details on ICC profiles may be obtained from [http://www.color.org/icc_specs2.xalter the ICC spec].
+
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.
  
Knowledge of ICC profiles (at least knowledge of their application) would be a prerequisite.  Since [http://www.littlecms.com/ littlecms] implements all the necessary functions for reading, writing, and applying profiles, it would be primarily a matter of integrating this library into Octave (assuming that is the preferred implementation -- one could certainly read the ICC files directly, but why reinvent that particular wheel).
+
The first step is research about existing Octave/Matlab and C/C++ implementations, for example:
  
'''Required skills''': C++ programming, some knowledge of ICC profiles desirable.
+
* https://code.google.com/archive/p/yamlmatlab/ (uses Java)
 +
* http://vision.is.tohoku.ac.jp/~kyamagu/ja/software/yaml/ (uses Java)
  
'''Difficulty''': Easy.
+
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.
  
'''Possible Mentor''': Patrick Noffke <patrick.noffke@gmail.com>
+
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.
  
=== High Precision Arithmetic Computation ===
+
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty'''
The Linear Algebra Fortran libraries used by Octave make use of of single (32 bits) and double (64 bits) precision floating point numbers. Many operations are stopped when matrices condition number goes below 1e-16: such matrices are considered as ill-conditionned. There are cases where this is not enough, for instance simulations implying chemical concentrations covering the range 10^4 up to 10^34. There are a number of ways to increase the numerical resolution, like f.i. make use of 128 bits quadruple precision numbers available in GFortran. A simpler option is to build an interface over Gnu MPL arbitrary precision library, which is used internally by gcc and should be available on any platform where gcc runs. Such approach has been made available for MatLab under the name mptoolbox and is licensed under a BSD license. The author kindly provided a copy of the latest version and agreed to have it ported under Octave and re-distributed under GPL v3.0
+
: ~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]
  
The architecture consists of an Octave class interface implementing "mp" (multi-precision) objects. Arithmetic operations are forwarded to MPL using MEX files. This is totally transparent to the end user, except when displaying numbers. This implementation needs to be ported and tested under Octave.
+
== TISEAN package ==
 
'''Required skills''': Octave classes and object programming. C for understanding the MEX glue code.
 
  
'''Difficulty''': medium.
+
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.
  
'''Potential mentor''': Pascal Dupuis
+
* '''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]
  
=== Mapping package ===
+
= Project sizes =
The [[Mapping package]] has started but lacks many functions, see [[Mapping package#Missing functions]].  Source code for some of the calculations has been donated and could be ported, or at least used for testing.  Choose this project if you'd like to learn more about mapping and GPS!
 
 
'''Required skills''': m-file scripting
 
  
'''Difficulty''': medium
+
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)
  
'''Potential mentor''': TBD
+
= Footnotes =
  
= HG Procedures for students and mentors =
+
<references />
  
[[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.
+
= See also =
  
[[hg instructions for mentors | This page]] describes what mentors should do to review their work.
+
* 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:Summer of Code]]
 
[[Category:Project Ideas]]
 
[[Category:Project Ideas]]

Latest revision as of 14:09, 15 April 2022

Info icon.svg

Since 2011 the GNU Octave project has successfully mentored:

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

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

Steps toward a successful application[edit]

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

How do we judge your application?[edit]

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

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

What you should know about Octave[edit]

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

You should know:

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

Suggested projects[edit]

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

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

openlibm[edit]

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

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

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

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

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

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

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

Symbolic package[edit]

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

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

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

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

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

Improve TIFF image support[edit]

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

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

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

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

PolarAxes and Plotting Improvements[edit]

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

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

Table datatype[edit]

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

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

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

YAML encoding/decoding[edit]

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

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

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

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

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

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

TISEAN package[edit]

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

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

Project sizes[edit]

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

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

Footnotes[edit]

See also[edit]