Ruby has no equivalent to the beautifully constructed numpy, scipy, and matplotlib libraries for Python. We believe that the time for a Ruby science and visualization package has come and gone. Sometimes when a solution of sugar and water becomes super-saturated, from it precipitates a pure, delicious, and diabetes-inducing crystal of sweetness, induced by no more than the tap of a finger. So it is, we believe, with the need for numeric and visualization libraries in Ruby.
We are not the first with this idea, but we want to bring it to life.
Who We Are
We are Rubyists, lovers of chunky bacon, and scientists. Driven mad by the glee of our Python-loving colleagues, we came together humming Les Mis.
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Currently, we are:
- John T. Prince, Department of Chemistry & Biochemistry, Brigham Young University
- John O. Woods, Marcotte Lab, The University of Texas at Austin
First and least, Ruby is a language with a sense of humor.
But more importantly, numerical computation and visualization can be done much better in Ruby, for a number of reasons:
- Everything returns a value. Ruby's better object model means better of chaining of computation.
- Iterators are way better than for loops.
- Readability. Ruby is incredibly readable, which makes it uber-maintainable.
- Metaprogramming. Sometimes the simplest solution is to write a code generator. Sometimes, eigenclasses are the cleanest.
- Integration into Rails. The influence of Rails on Ruby is undeniable. Web-based visualization for scientific projects is the future.
- R is nice but clunky. The learning curve is enormous. It does some things very well, and others not very well at all.
Alternatives and Sources of Inspiration
- rsruby, rinruby, simpler: gems which connect Ruby to R
- NArray: Numerical Ruby NArray and Ruby/PGPLOT.
- Ruby GSL: Ruby interface for the GNU Scientific Library
Numeric Array and Matrix Library
For what it is worth, the broad success of python is due, in large part, to its numerical computing core, numpy. A few examples: h5py, pymol, mdanalysis,...
Goals: Stable, robust, fast, extremely well-documented core numerical library.
- FFI (C) or Rice (C++ with Boost)
- Allow for custom C functions with FFI or Rice.
- Good at casting
- Consider broadcasting
- Thoroughly documented, on par with Yaml Cookbook
- Convenience wrappers for GSL, perhaps in a separate module.
- Eventual inclusion in Ruby core.
NArray is a fantastic library that has served the community for many years. Can it be extended and better documented, or is it better to start from scratch (borrowing conceptually from NArray where we can) using an FFI or Rice interface?
Visualization and Plotting Library
Goals: High-quality, interactive, dynamic visualizations of the sort seen in Processing.
- Consider basing it in OpenGL for interactivity and native 3D on many platforms.
- FFI-OpenGL or Rice with GLT
- WebGL support for HTML5 Canvas
- Or SVG based? Cairo?
- Make matplotlib drool, but also be inspired by it.