Sprints
For new-comers to Git, a half-hour tutorial will be held at the beginning of the sprints.
To add a proposed sprint click here
Astropy |
| Jul 20th - 09:00 AM Erik Bray |
We'll be meeting to hack on the Astropy project (http://www.astropy.org/), a unified collection of core tools for Astronomy. There's plenty to for developers at all levels--from documentation, to testing, to bug fixes and new features. If you're new to the code base there will be a few of us to help get you up and running... |
SymPy graph <-> Theano graph |
| Jul 20th - 09:00 AM Frederic Bastien |
Converting SymPy graph into Theano graph would allow to use Theano compilation to get faster code. Converting Theano graph into SymPy graph would allow reusing SymPy pretty printing. There is some difficulty as each graph do not convey the same information, but we can discuss the possible solution to those problem and implement some of them... |
NumPy |
| Jul 20th - 09:00 AM Travis Oliphant |
We will be working on all aspects of NumPy and there is plenty to do even for new-comers. You don't need to be an expert in C or C++ to help out. 1) Migrating Issues to Github 2) Chasing down bugs 3) Working on the NumPy web-page 4) Helping with NumPy 1.7.0 beta release. |
Scikit-learn |
| Jul 20th - 09:00 AM Jake Vanderplas |
Update: Jake will be unable to attend due to family circumstances. David Warde-Farley will be around to help coordinate the sprint. Scikit-learn is a package for machine learning and statistical data exploration in python. It has an active development community, a fast release cycle, and is a great way to contribute to the scientific python universe... |
mystic+pathos+dill: let's serialize all of python, and do large-scale high-performance parallel optimization |
| Mike McKearns |
We have built a robust framework (mystic) that lowers the barrier to solving complex problems in predictive science. Mystic is built to rigorously solve high-dimensional non-convex optimization problems with highly nonlinear complex constraints. Mystic is capable of solving global optimization problems with thousands of parameters and thousands of constraints, and makes it almost trivial to leverage high-performance parallel computing... |
Bokeh / BokehJS - web plotting in Python |
| Peter Wang, Bryan Van de Ven |
Improve GIS support, polar plots, additional interactive tools, and write more examples and docs for high-level interface. Possibly start hacking on Matplotlib compatibility layer, if there is enough interest. |
Numba |
| Siu Kwan Lam, Travis Oliphant |
Help people learn to use Numba, write more examples, as well as learn how to contribute to the project. Simpler projects to tackle: Adding more support for type inference on NumPy functions; Adding more typed containers such as typedset, typeddict, or typedchannel; Adding support for LLVM intrinsics beyond just instructions; and adding a source annotation mode for Numba... |
PySide and Scientific GUIs |
| Stephan Diebel, Corran Webster |
Help build more stable and complete support for scientific graphical user interfaces. There will be a particular focus on improvements to the PySide wrappers around the Qt library, as well as improvements to the Enaml framework. |
yt: parallel volume rendering, integration with the IPython notebook, and handling unit conversions |
| Nathan Goldbaum |
yt is a community-developed analysis package for astrophysical n-body and hydrodynamics simulations. In preparation for the upcoming yt 3.0 release, we would like to work on a new system for handling unit conversions, add improved support for parallel volume rendering of arbitrary datasets, including observational and non-astrophysical data, and create browser-based data exploration widgets that will be readily pluggable into the IPython notebook... |