Summer of Code - Getting Started: Difference between revisions

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== Image Analysis ==
== Image Analysis ==
=== Improvements to N-dimensional image processing ===
The image package has partial functionality for N-dimensional images. These images exist for example in medical imaging where slices from scans are assembled to form anatomical 3D images. If taken over time and at different laser wavelengths or light filters, they can also result in 5D images. Albeit less common, images with even more dimensions also exist. However, their existence is irrelevant since most of the image processing operations are mathematical operations which are independent of the number of dimensions.
As part of GSoC 2013, the core functions for image IO, {{codeline|imwrite}} and {{codeline|imread}}, were extended to better support this type of images. Likewise, many functions in the image package, mostly morphology operators, were expanded to deal with this type of image. Since then, many other functions have been improved, sometimes completely rewritten, to abstract from the number of dimensions. In a certain way, supporting ND images is also related to choosing good algorithms since such images tend to be quite large.
This project will build 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 functions. This project can also be about implementing functions that have [[Image package#Missing functions | not yet been implemented]]. Also note that while some functions in the image package will accept ND images as input, they are actually not correctly implemented and will give incorrect results.
* '''Required skills'''
: m-file scripting, and a fair amount of C++ since a lot of image analysis cannot be vectorized. Familiarity with common computer science algorithms and willingness to read literature describing new algorithms will be useful.
* '''Difficulty'''
: Difficult.
* '''Potential mentor'''
: Carnë Draug

=== Improve Octave's image IO ===
=== Improve Octave's image IO ===

Revision as of 03:19, 21 January 2021

The following is largely 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 just 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 to 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 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 might 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


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, 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} work 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
  • Potential mentors
Francesco Faccio, Carlo de Falco, Marco Caliari, Jacopo Corno, Sebastian Schöps

Adding functionality to 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
  • Mentor

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
  • Mentor

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
  • Mentor

Symbolic package

Octave's Symbolic package provides symbolic computing and other computer algebra system tools. The main component of Symbolic is a pure m-file class "@sym" which uses the Python package SymPy to do (most of) the actual computations. The package aims to expose the full functionality of SymPy while also providing a high level of compatibility with the Matlab Symbolic Math Toolbox. The Symbolic package requires communication between Octave and Python. 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
  • Mentors and/or other team members
Colin B. Macdonald, Mike Miller, Abhinav Tripathi


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
  • Mentor
Sebastian Schöps, Carlo de Falco


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?

Image Analysis

Improve Octave's image IO

There are a lot of image formats. 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 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 wrapper 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 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
  • Potential mentor
Carnë Draug


PolarAxes and Plotting Improvements

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