Summer of Code - Getting Started

GNU Octave has been selected as mentoring organization for GSoC 2021.

Since 2011 the GNU Octave project has mentored 38 students in Summer of Code (SoC) programs by Google and ESA. Those programs aim to advertise open-source software development and to attract potential new Octave developers.

Steps toward a successful application

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

How do we judge your application?

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

• You have demonstrated interest in Octave and an ability to make substantial modifications to Octave

  The most important thing is that you've contributed some interesting code samples to judge your skills. It's OK during the application period to ask for help on how to format these code samples, which normally are Mercurial patches.

• You showed understanding of your topic

  Your proposal should make it clear that you're reasonably well versed in the subject area and won't need all summer just to read up on it.

• Well thought out, adequately detailed, realistic project plan

  "I'm good at this, so trust me" isn't enough. In your proposal, you should describe which algorithms you'll use and how you'll integrate with existing Octave code. You should also prepare a project timeline and goals for the midterm and final evaluations.

What you should know about Octave

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

You should know:

1. How to build Octave from it's source code using the GNU build system.
   • Read in this wiki: Developer FAQ, Building
   • Tools to know: gcc, make
2. How to submit patches (changesets).
   • Read in this wiki: Contribution guidelines, Mercurial
   • Tools to know: Mercurial (hg), git

Suggested projects

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

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

ode15{i,s} : Matlab Compatible DAE solvers

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

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

• Required skills

Knowledge of Octave, C/C++; familiarity with numerical methods for DAEs

• Potential mentors

Francesco Faccio, Carlo de Falco, Marco Caliari, Jacopo Corno, Sebastian Schöps

Using Python within Octave

Pythonic allows one to call Python functions and interact with Python objects from within Octave .m file code and from the Octave command line interface. Pythonic may eventually not be a separate package, but rather a core feature of Octave. This project aims to improve Pythonic with the goal of making the package more stable, maintainable, and full-featured.

Based on a previous summer project related to Pythonic, this work will consist of fast-paced collaborative software development based on tackling the Pythonic issue list. You would also be expected to participate in software design decisions and discussion, as well as improve documentation, doctests, and unit tests. As an example of the sorts of decisions being made, note that Octave indexes from 1 whereas Python typically indexes from 0; in which cases is it appropriate to make this transparent to the user?

• Required skills

Knowledge of Octave, C/C++, Python

• Potential mentors

Mike Miller, Colin B. Macdonald, Abhinav Tripathi

Improve TIFF image support

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

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

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

• Required skills

Knowledge of Octave, C/C++

• Potential mentors

Carnë Draug

PolarAxes and Plotting Improvements

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

• Required skills

Knowledge of Octave, C/C++; optional experience with OpenGL programming

• Potential mentors

Rik

Table datatype

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

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

• Required skills

Knowledge of Octave, C/C++

• Potential mentors

Kai

Jupyter Notebook Integration

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

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

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

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

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

• Required skills

Knowledge of Octave, C/C++

• Potential mentors

Kai

Adding functionality to packages

OCS package

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

• Required skills

Knowledge of Octave, C/C++; FORTRAN API knowledge

• Potential mentors

Sebastian Schöps, Carlo de Falco

Symbolic package

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

This project proposes to go further: instead of using Pythonic only for the communication layer, we'll use it throughout the Symbolic project. For example, we might make "@sym" a subclass of "@pyobject". We also could stop using the "python_cmd" interface and use Pythonic directly from methods. The main goal was already mentioned: to expose the full functionality of SymPy. For example, we would allow OO-style method calls such as f.diff(x) instead of diff(f, x).

• Required skills

Knowledge of Octave, C/C++, Python; object-oriented programming (OOP) in Octave

• Potential mentors

Colin B. Macdonald, Mike Miller, Abhinav Tripathi

TISEAN package

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

• Required skills

Knowledge of Octave, C/C++; FORTRAN API knowledge

• Potential mentors

KaKiLa