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The following is distilled from the [[Projects]] page for the benefit of potential [http://code.google.com/soc/Google Summer] [http://sophia.estec.esa.int/socis2012/?q=node/13 of Code] students. Although students are welcome to attempt any of the projects in that page or any of their own choosing, here we offer some suggestions on what good student projects might be.
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.


= General Guidelines =
You can also take a look at last years [[Summer of Code]] projects for inspiration.


Octave is mostly written in (sadly, mostly undocumented) C++ and its own scripting language (m-scripts), which includes (or should include) most of the Matlab language as a subset. We generally prefer a different Octave house style to the usual Matlab style for m-scripts, but it's primarily a superficial stylistic difference. Additionally, there are bits and pieces of Fortran, Perl, C, awk, and Unix shell scripts here and there. In addition to being familiar with C++ and/or Octave or Matlab's scripting languages, you should probably be familiar or learn about Octave's infrastructure:
= Steps Toward a Successful Application =


* [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.
==  Help Us Get To Know You ==
* [http://mercurial.selenic.com/ Mercurial] (abbreviated hg) is the [http://en.wikipedia.org/wiki/Distributed_Version_Control_System distributed version control system] (DVCS) we use for managing our source code. You should have some basic understanding of how a DVCS works, but hg is pretty easy to pick up, especially if you already know a VCS like git or svn.
* If you aren't communicating with us before the application is due, your application will not be accepted.
* 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.
*:* '''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.
* We primarily use [https://mailman.cae.wisc.edu/listinfo/octave-maintainers mailing lists] for communication. You should follow basic mailing list etiquette. For us, this mostly means "do not [http://en.wikipedia.org/wiki/Top_posting#Top-posting top post]".
*:* '''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!
* We also have [http://www.gnu.org/software/octave/chat.html an IRC channel]. The atmosphere is more relaxed, and we may talk about things that are not at all related to Octave.
* '''Do not wait for us to tell you what to do'''
* [http://octave.sf.net Octave-Forge] is a project closely related to Octave where packages reside. They are somewhat analogous to Matlab's toolboxes.
*: 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.
* 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.
*:* 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.


= Suggested projects =
== 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).
*: 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!


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.
== Things You'll be Expected to Know or Quickly Learn On Your Own ==


== Numerical ==
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.


These projects involve implementing certain mathematical functions in Octave.
* '''The Build System'''
*: [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 {{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.


'''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.
== Criteria by which applications are judged ==


'''Difficulty''': Mid-to-hard depending how much mathematics you know and how well you can read numerical analysis journal articles.
These might vary somewhat depending on the mentors and coordinators for a particular Summer of Code, but typically the main factors considered would be:


'''Potential mentor''': Carlo de Falco, Nir Krakauer, Fotios Kasolis, Luis Gustavo Lira
* '''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.


=== Incomplete sparse factorizations ichol, ilu ===
* '''Applicant shows understanding of topic'''
*: 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.


Implement incomplete Cholesky and LU factorization for sparse matrices. These functions are [http://www.mathworks.it/it/help/matlab/matrix-decomposition.html available in Matlab] as cholinc/ichol and luinc/ilu. Incomplete factorizations are useful as preconditioners
* '''Applicant shows understanding of and interest in Octave development'''
for iterative solvers such as [http://hg.savannah.gnu.org/hgweb/octave/file/119ce9f5e1a3/scripts/sparse/gmres.m gmres] and
*: The best evidence for this is previous contributions and interactions.
[http://hg.savannah.gnu.org/hgweb/octave/file/119ce9f5e1a3/scripts/sparse/gmres.m gmres] or [http://hg.savannah.gnu.org/hgweb/octave/file/119ce9f5e1a3/scripts/sparse/pcg.m pcg].
The classic book [http://netlib.org/linalg/html_templates/node81.html Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods] has a [http://netlib.org/linalg/html_templates/node100.html#SECTION00933000000000000000 chapter] describing the
ILU algorithm in detail, though the algorithm described there should be adapted to Octave's internal Sparse Matrix file format which is [http://netlib.org/linalg/html_templates/node92.html#SECTION00931200000000000000 CCS] rather than [http://netlib.org/linalg/html_templates/node91.html#SECTION00931100000000000000 CRS]. The implementation of ILU in Octave has been recently discussed in the maintainers list and initial implementations were posted in this [http://octave.1599824.n4.nabble.com/Ilu-function-tp4648677.html thread]. In another [http://octave.1599824.n4.nabble.com/Re-Octave-maintainers-Digest-Vol-80-Issue-15-tp4646303.html thread] it was suggested to implement the ILU by interfacing Octave to [http://www-users.cs.umn.edu/~saad/software/ITSOL/ ITSOL]. Compared to other
projects in this section this one might require more knowledge of C++.


=== General purpose Finite Element library ===
* '''Well thought out, adequately detailed, realistic project plan'''
*: "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.


Octave-Forge already has a set of packages for discretizing Partial Differential operators by Finite Elements and/or Finite Volumes,
= Suggested projects =
namely the [[bim package]] which relies on the [http://octave.sf.net/msh msh package] (which is in turn based on [http://geuz.org/gmsh/ gmsh]) for creating and managing 2D triangular and 3D tetrahedral meshes and on the [http://octave.sf.net/fpl fpl package] for visualizing 2D results within Octave or exporting 2D or 3D results in a format compatible with [http://www.paraview.org Paraview] or [https://wci.llnl.gov/codes/visit/ VisIT]. These packages, though, offer only a limited choice of spatial discretization methods which are based on low degree polynomials and therefore have a low order of accuracy even for problems with extremely smooth solutions.
The [http://geopdes.sf.net GeoPDEs] project, on the other hand, offers a complete suite of functions for discretizing a wide range of
differential operators related to important physical problems and uses basis functions of arbitrary polynomial degree that allow the construction of methods of high accuracy. These latter, though, are based on the IsoGeometric Analysis Method which, although very powerful and often better performing, is less widely known and adopted than the Finite Elements Method. The implementation of a general purpose library of Finite Elements seems therefore a valuable addition to Octave-Forge. Two possible interesting choices for implementing this package exist, the first consists of implementing the most common Finite Element spaces in the [http://geopdes.sf.net GeoPDEs] framework, which is possible as IsoGeometric Analysis can be viewed as a superset of the Finite Element Method, the other is to construct Octave language bindings for the free software library [http://fenicsproject.org/documentation/ FEniCS] based on the existing C++ or Python interfaces.


=== Improve logm, sqrtm, funm ===
The 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.


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.
{{Note|These are suggested projects but you are welcome to propose your own projects provided you find an Octave mentor}}


=== Generalised eigenvalue problem ===
== Summary table ==


[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.
{| class="wikitable sortable" style="text-align: center; width:99%"
|-
!Title
!Mentor
!co-Mentors
!Class
!New?
!Difficulty
!Last active
|-
! <br />!! !! !! !! !! !!
|-
| [[Summer of Code - Getting Started#ode15.7Bi.2Cs.7D_:_Matlab_Compatible_DAE_solvers | 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 | Pythonic package]] || 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
|}


=== Various sparse matrix improvements ===
== Numerical ==


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.
These projects involve implementing certain mathematical functions, primarily in core Octave.


=== Implement solver for initial-boundary value problems for parabolic-elliptic PDEs in 1D ===
=== ode15{i,s} : Matlab Compatible DAE solvers ===


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.
An initial implementation of a Matlab compatible ode15{i,s} solver,
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]


== GUI ==
Possible useful improvements that could be done in a new project include:


Octave is currently working on a new native GUI. It is written in Qt, but it is still not ready for production. There are various ways in which it could be improved.
* 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]


'''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.
* make ode15{i,s} with datatypes other than double


'''Difficulty''': Mostly medium, depending if you've had Qt or GUI development experience before.
* improve interpolation at intermediate time steps.


'''Potential mentor''': Jordi Gutiérrez Hermoso, Michael Goffioul, Torsten
* general code profiling and optimization


=== Finish the Octave GUI ===
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'''
: C++; C; familiarity with numerical methods for DAEs; Basic knowledge of makefiles and/or autotools.
* '''Difficulty'''
: Medium.
* '''Potential mentors'''
: Francesco Faccio, Carlo de Falco, Marco Caliari, Jacopo Corno, Sebastian Schöps


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 logm, sqrtm, funm ===
* improve integration with octave: variable browser/editor, debugger, profiler...
* define and implement an option/preferences dialog
* improve additional components like the documentation browser
 
=== Implement a Qt widget for manipulating plots ===


Octave has had for some time a native OpenGL plotter. The plotter requires some user interaction for manipulating the plots, and it's been using fltk for quite some time. We want to replace this with Qt, so it fits better with the overall GUI look-and-feel and is easier to extend in the future.
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"].


[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.
* '''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.
* '''Difficulty'''
: Difficult.
* '''Potential mentors'''
: Marco Caliari, Mudit Sharma


=== Create a better (G)UI for the profiler ===
=== Improve iterative methods for sparse linear systems ===


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.
GNU Octave currently has the following Krylov subspace methods for sparse linear systems: pcg (spd matrices) and pcr (Hermitian matrices), bicg,
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}}).


=== Create a graphical design tool for tuning closed loop control system (control pkg) ===
In Matlab, some additional methods are available: minres and symmlq (symmetric matrices), bicgstabl (general matrices), lsqr (least
squares). The second step in this project could be the implementation of some of these missing functions.


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.
The [https://www-users.cs.umn.edu/~saad/IterMethBook_2ndEd.pdf reference book by Yousef Saad] is available online.
Potential mentor: Doug Stewart


== Graphics ==
* '''Required skills'''
: numerical linear algebra, m-file programming.
* '''Difficulty'''
: Maybe hard the mathematical part, medium the programming part.
* '''Mentor'''
: Marco Caliari, Carlo de Falco


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.
=== Chebfun in Octave ===


'''Required skills''': C++ and OpenGL. General understanding of computer graphics.
[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.


'''Difficulty''': Medium, depending on your previous understanding of the topic.
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.


'''Potential mentor''': Michael Goffioul
The impact of this project is improving Octave and allowing Chebfun to be used without proprietary software.


=== Lighting ===
How to get started:


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.
* Learn about [https://www.chebfun.org/ Chebfun]
* Browse [https://savannah.gnu.org/bugs/?group=octave Octave's bug list] for "classdef"-related bugs.


=== Object selection in OpenGL renderer ===
* 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>?


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 ===
* '''Required skills'''
: Octave m-file programming, classdef programming, probably C++, some familiarity with Approximation Theory (a branch of mathematics).
* '''Difficulty'''
: Medium (fixing Octave classdef bugs likely harder and requires a deep dive into how Octave supports OOP).
* '''Potential mentors'''
: Colin B. Macdonald, [[User:KaKiLa|KaKiLa]], Mike Miller (?), Carnë Draug (?), someone from Chebfun team (?).


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:
== Adding functionality to Forge packages ==
* [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.
=== EPA hydrology software suite ===
Create native interfaces to the EPA software suites.


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.
Starting points
* [https://forja.cica.es/projects/epanet-octave/ epanet-octave].
* [https://github.com/OpenWaterAnalytics/ Open Water Analytics]


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.
* '''SWMM'''
** [https://www.epa.gov/water-research/storm-water-management-model-swmm Official page]
** Check work done in [https://github.com/water-systems/MatSWMM MatSWMM] [http://digital.csic.es/bitstream/10261/132982/1/MatSWMM.pdf article]


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].
* '''EPANET'''
** [https://www.epa.gov/water-research/epanet Official page]


== Interpreter ==
* '''Required skills'''
: m-file scripting, C, C++, API knowledge, file I/O, classdef (optional).


The interpreter is written in C++, undocumented. There are many possible projects associated with it.
* '''Difficulty'''
: easy/medium


'''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.
* '''Mentor'''
: [[User:KaKiLa|KaKiLa]]


'''Difficulty''': Mid hard to very hard. Some of the biggest problems will probably be the interpreter.
===  FullSWOF overland flow simulator ===
Create scripting tools for (optional: native interfaces).


'''Potential mentors''': John W. Eaton, Jordi Gutiérrez Hermoso, Max Brister.
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]


=== Improve JIT compiling ===
* '''Required skills'''
: m-file scripting, C, C++, API knowledge, file I/O, classdef (optional).


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.
* '''Difficulty'''
: easy/medium


=== Improve memory management ===
* '''Mentor'''
: [[User:KaKiLa|KaKiLa]]


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.
=== TISEAN package ===


=== Implement classdef classes ===
[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]].


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.
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.]  


== Infrastructure ==
* '''Required skills'''
: m-file scripting, C, C++, and FORTRAN API knowledge.
* '''Difficulty'''
: easy/medium
* '''Mentor'''
: [[User:KaKiLa|KaKiLa]]


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.
=== Symbolic package ===


'''Required skills''': Various. See below.
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 [[Pythonic|Pythonic package]].


'''Difficulty''': Various. See below.
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)".


'''Potential mentor''': Jordi Gutiérrez Hermoso, Carlo de Falco
* '''Required skills'''
: OO-programming with m-files, Python, and possibly C/C++ for improving Pythonic (if needed).
* '''Difficulty'''
: easy/medium
* '''Mentors and/or other team members'''
: Colin B. Macdonald, Mike Miller, Abhinav Tripathi


=== Finish the Agora website ===
=== OCS ===


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.
[[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), [https://savannah.gnu.org/search/?Search=Search&words=%28ocs%29&type_of_search=bugs&only_group_id=1925&exact=1&max_rows=25#options fix open bugs], increase compatibility with SPICE and improve compatibility with other Octave packages (odepkg, control etc).
* [http://octave.sourceforge.net/ocs/overview.html Package help at source forge.]  


In response to this, a website started to form, [http://agora.octave.org/ Agora Octave].
* '''Required skills'''
: m-file scripting, C, C++, and FORTRAN API knowledge.
* '''Difficulty'''
: easy/medium
* '''Mentor'''
: Sebastian Schöps, Carlo de Falco


This should be relatively easy webdev in Python using [http://en.wikipedia.org/wiki/Django_%28web_framework%29 Django].
== Infrastructure ==


Things to be considered when working on this:
=== JSON encoding/decoding ===


* [http://octave-forge.blogspot.ie/2012/08/octconf2012-agora-and-pkg.html discussion of Agora during OctConf2012]
[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]].
* [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.
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:


=== Update the Emacs octave mode ===
* [https://github.com/fangq/jsonlab jsonlab] (M-file implementation, probably slow for large JSON files)
* [https://github.com/gllmflndn/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://rapidjson.org/ RapidJSON])


[http://en.wikipedia.org/wiki/Emacs Emacs] has an octave-mode that requires a lot of updating and maintenance. This should also be an easy project if you already use Emacs and [http://en.wikipedia.org/wiki/Elisp elisp].
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.


=== Improve binary packaging ===
* '''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]]


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. Medium difficulty.
=== Jupyter Notebook Integration ===


=== Installation of packages ===
[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.
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.
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].


'''Difficulty''': Easy
* '''Minimum requirements'''
: Good Octave and Python programming knowledge.
* '''Difficulty'''
: Medium.
* '''Mentors'''
: Colin B. Macdonald, Mike Miller, [[User:Siko1056|Kai T. Ohlhus]]


== Octave-Forge packages ==
=== Using Python within Octave ===


=== Rewrite symbolic package ===
[[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.
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.
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''': C++. Ability to understand Octave and GiNaC API documentation.
* '''Mentors'''
: Mike Miller, Colin B. Macdonald, Abhinav Tripathi, others?


'''Difficulty''': medium.


'''Potential mentor''': Lukas Reichlin
=== Octave Package management ===


=== Improvements to n-dimensional image processing ===
[[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 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 can result in 4d images. All of the base functions should be modified so that they can handle n-dimensional images, and corresponding Matlab functions such as <code>bwconncomp</code> or n-dimensional version of <code>bwdist</code> should be implemented.
The planned improvements (see also {{bug|39479}}) are:


'''Required skills''': Mostly m-file scripting, perhaps some C++. Familiarity with common CS algorithms would be useful.
* 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/


'''Difficulty''': medium.
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]).


'''Potential mentor''': Jordi Gutiérrez Hermoso
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.


=== Interface to Electronic Circuit Simulator ===
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.


[http://sourceforge.net/projects/qucs/ Qucs] is a C++ based circuit simulation package. This project aims to create an interface to the Qucs algorithms to allow the transient, i.e. time series, simulation of circuits in Octave within a larger ODE system simulation, and possibly make other analysis types available directly from Octave. The C++ interface would be based on handle class syntax currently in development in the <code>classdef</code> branch of the repository. This method has already been successfully tested on other projects, and examples of this type of interface are available (e.g. [https://sourced.ecdf.ed.ac.uk/projects/see/xfemm here] and [https://www.mathworks.com/matlabcentral/fileexchange/38964-example-matlab-class-wrapper-for-a-c++-class here]).
* '''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


'''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.
== Image Analysis ==


'''Difficulty''': medium.
=== Improvements to N-dimensional image processing ===


'''Potential mentor''': Richard Crozier
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.


'''Main Goals'''
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.
* Create an Octave circuit class which can load and parse a Qucs circuit netlist
* Create class methods with functionality similar to the <code>trsolver</code> C++ class methods in Qucs, i.e with the ability to call the DC solution code, and transient solution code at each time step.  
* Create a method of accessing the current circuit solution values in Octave at each time step.
'''Bonus Goals'''
* Create new circuit elements which allow Octave to apply voltages and currents during a circuit simulation.


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.


=== Fix audio processing ===
* '''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


Audio processing is currently almost completely broken in Octave. It currently only works with Linux's Open Sound System, which most Linux installation don't use anymore. We therefore need a modern, cross-platform way to play and record audio. This could be part of the Octave-Forge audio package, but the core audio functions themselves are also lacking. We need this to work across OSes, so an external audio library should be used. [http://www.portaudio.com/ Portaudio] or [http://www.music.mcgill.ca/~gary/rtaudio/ rtaudio] seem like a mature possibility. The core <code>play</code> and <code>record</code> functions should be fixed to use an external audio library, and in addition, the <code>audiorecorder</code> and <code>audioplayer</code> classes should be implemented.
=== Improve Octave's image IO ===


'''Required skills''': C++ and probably at least a superficial understanding of signal or audio processing.
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:


'''Difficulty''': Medium, depending on the abilities of the student.
* 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.


'''Possible mentors''': Pantxo Diribarne
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:


=== Color management functions in image package ===
* 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


The goal is to implement these functions:
* '''Required skills'''
: Knowledge of C++ and C since most libraries are written in those languages.
* '''Difficulty'''
: Medium.
* '''Potential mentor'''
: Carnë Draug


    iccread
== Graphics ==
    iccwrite
    makecform
    applycform
 
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:
 
<syntaxhighlight lang="octave">
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].


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).
=== PolarAxes and Plotting Improvements ===


'''Required skills''': C++ programming, some knowledge of ICC profiles desirable.
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}}.


'''Difficulty''': Easy.
* '''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


'''Possible Mentor''': Patrick Noffke <patrick.noffke@gmail.com>
<noinclude>
[[Category:Summer of Code]]
[[Category:Project Ideas]]
</noinclude>

Revision as of 02:54, 30 March 2020

The following is distilled from the Projects page for the benefit of potential Google and 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.

You can also take a look at last years Summer of Code projects for inspiration.

Steps Toward a Successful Application

Help Us Get To Know You

  • 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, 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 How to ask questions the smart way:

      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.

    • 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

  • 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 fixing a few bugs or 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 IRC channel.

Complete Your Application

  • Fill out our public application template.
    • This is best done by creating an account at this wiki, and copying the 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 from its page and adding the required information to your application at Google (melange) or at ESA.
    • 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

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.

  • The 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 ./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:
  • The Version Control System
    We use Mercurial (abbreviated hg).
    Mercurial is the 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 we have for everyone.
    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 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 top post".
  • The IRC Channel
    We also have 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
    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
    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
    The best evidence for this is previous contributions and interactions.
  • Well thought out, adequately detailed, realistic project plan
    "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.

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 completed past projects for more inspiration.

Info icon.svg
These are suggested projects but you are welcome to propose your own projects provided you find an Octave mentor

Summary table

Title Mentor co-Mentors Class New? Difficulty Last active

ode15{i,s} : Matlab Compatible DAE solvers Carlo de Falco Francesco Faccio, Marco Caliari, Jacopo Corno, Sebastian Schöps Numerical No Medium GSoC 2016
Improve logm, sqrtm, funm ? Marco Caliari, Mudit Sharma Numerical No Hard Independent devs 2016
Improve iterative methods for sparse linear systems Marco Caliari Carlo de Falco Numerical No Hard SOCIS 2016
EPA hydrology software suite KaKiLa ? Octave Forge Yes Medium Never
FullSWOF overland flow simulator KaKiLa ? Octave Forge Yes Medium Never
TISEAN: Nonlinear Time Series Analysis KaKiLa ? Octave Forge No Medium GSoC 2015
Octave Package management Sebastian Schöps KaKiLa, Carnë Draug, Carlo de Falco Infrastructure Yes Medium Never
Symbolic package Colin B. Macdonald Mike Miller, Abhinav Tripathi Octave Forge Octsympy Medium GSoC 2016
OCS package Sebastian Schöps Sebastian Schöps Octave Forge, Numerical Yes Easy Never
Pythonic package Mike Miller Colin B. Macdonald, Abhinav Tripathi Infrastructure No Medium some in GSoC 2016
JSON encoding/decoding Kai T. Ohlhus ? Infrastructure Yes Medium Never
Jupyter Notebook Integration Mike Miller Colin B. Macdonald, Kai T. Ohlhus Infrastructure Yes Medium Never
Chebfun in Octave Colin B. Macdonald KaKiLa Infrastructure, Numerical Yes Hard Never
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

An initial implementation of a Matlab compatible ode15{i,s} solver, based on SUNDIALS, was done by Francesco Faccio during GSOC 2016. The blog describing the work is here. The resulting code has been pushed into the main Octave repository in the development branch and consists mainly of the following three files __ode15__.cc, ode15i.m and ode15s.m. The list of outstanding tracker tickets concerning this implementation can be found here

Possible useful improvements that could be done in a new project include:

  • Implement a better function for selecting consistent initial conditions compatible with Matlab's decic.m. The algorithm to use is described here
  • 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
C++; C; familiarity with numerical methods for DAEs; Basic knowledge of makefiles and/or autotools.
  • Difficulty
Medium.
  • Potential mentors
Francesco Faccio, Carlo de Falco, Marco Caliari, Jacopo Corno, Sebastian Schöps

Improve logm, sqrtm, funm

The goal here is to implement some missing Matlab functions related to matrix functions like the matrix exponential. There is a general discussion of the problem. A good starting point for available algorithms and open-source implementations is Higham and Deadman's "A Catalogue of Software for Matrix Functions".

  • 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.
  • Difficulty
Difficult.
  • Potential mentors
Marco Caliari, Mudit Sharma

Improve iterative methods for sparse linear systems

GNU Octave currently has the following Krylov subspace methods for sparse linear systems: pcg (spd matrices) and pcr (Hermitian matrices), bicg, 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 SOCIS2016 which is already merged into Octave (cset 6266e321ef22).

In Matlab, some additional methods are available: minres and symmlq (symmetric matrices), bicgstabl (general matrices), lsqr (least squares). The second step in this project could be the implementation of some of these missing functions.

The reference book by Yousef Saad is available online.

  • Required skills
numerical linear algebra, m-file programming.
  • Difficulty
Maybe hard the mathematical part, medium the programming part.
  • Mentor
Marco Caliari, Carlo de Falco

Chebfun in Octave

Chebfun is a mathematics and software project for "numerical computing with functions". Basically it approximates functions to machine precision accuracy (10-15) 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.

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 pkg install chebfun.zip work in Octave.

The impact of this project is improving Octave and allowing Chebfun to be used without proprietary software.

How to get started:

  • Clone this Chebfun octave_dev branch.
    • On that, f = chebfun(@(x) sin(x), [-2 6]) should work with Octave 4.3.0+ and maybe even with 4.2.1. Check that f(pi) and g = f + 1 work.
    • A good first task would be to study this commit, a workaround for f.funs{1} using temp = f.funs; temp{1}. 2*f is failing, can you fix it, perhaps with this workaround? Or can you make f.funs{1} work by changing something in @chebfun/subsref.m?


  • Required skills
Octave m-file programming, classdef programming, probably C++, some familiarity with Approximation Theory (a branch of mathematics).
  • Difficulty
Medium (fixing Octave classdef bugs likely harder and requires a deep dive into how Octave supports OOP).
  • Potential mentors
Colin B. Macdonald, KaKiLa, Mike Miller (?), Carnë Draug (?), someone from Chebfun team (?).

Adding functionality to Forge packages

EPA hydrology software suite

Create native interfaces to the EPA software suites.

Starting points

  • Required skills
m-file scripting, C, C++, API knowledge, file I/O, classdef (optional).
  • Difficulty
easy/medium
  • Mentor
KaKiLa

FullSWOF overland flow simulator

Create scripting tools for (optional: native interfaces).

Starting points

  • Required skills
m-file scripting, C, C++, API knowledge, file I/O, classdef (optional).
  • Difficulty
easy/medium
  • Mentor
KaKiLa

TISEAN package

TISEAN is a suite of code for nonlinear time series analysis. It has been partially re-implemented as libre software. The objective is to integrate TISEAN as an Octave Forge package, as was done for the Control package. A lot has been completed 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. Do check the progress of the project to see if you are interested.

  • Required skills
m-file scripting, C, C++, and FORTRAN API knowledge.
  • Difficulty
easy/medium
  • Mentor
KaKiLa

Symbolic package

Octave's 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 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 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
OO-programming with m-files, Python, and possibly C/C++ for improving Pythonic (if needed).
  • Difficulty
easy/medium
  • Mentors and/or other team members
Colin B. Macdonald, Mike Miller, Abhinav Tripathi

OCS

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).

  • Required skills
m-file scripting, C, C++, and FORTRAN API knowledge.
  • Difficulty
easy/medium
  • Mentor
Sebastian Schöps, Carlo de Falco

Infrastructure

JSON encoding/decoding

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 Jupyter integration.

In 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:

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 jsonencode and 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
Kai T. Ohlhus

Jupyter Notebook Integration

Jupyter Notebook is a web-based worksheet interface for computing. There is a 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 Jupyter Notebook Format is a plain JSON document. In combination with another Octave GSoC project (see 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 still a pending issue.

  • Minimum requirements
Good Octave and Python programming knowledge.
  • Difficulty
Medium.
  • Mentors
Colin B. Macdonald, Mike Miller, Kai T. Ohlhus

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.

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?

  • 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, 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 "packajoozle" project by Andrew Janke.

The planned improvements (see also #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 (pkg test <package-name>)
  • improved metadata acquisition (pkg list -forge) from https://octave.sourceforge.io/

The main objective of this project is to make pkg more user friendly and to make it a tool to foster third party participation in Octave. However, the current 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 pkg code will be needed (see "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 (base directory spec) and Windows seems to have its own standards. See bugs #36477 and #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 image::morphology). A new pkg would think all this things now, or allow their implementation at a later time. Read the 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
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, imwrite and 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 imclose and imopen was better implemented by supporting imerode and 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 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 GraphicsMagic (GM), a library capable of handling a lot of them in a single C++ interface. However, GraphicsMagick still has its limitations. The most important are:

  • 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, 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 #35565, #49804, #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