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The Manifesto

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.

You should join us! Sign up by filling out this form.

Currently, we are:

  • John T. Prince, Department of Chemistry & Biochemistry, Brigham Young University
  • John O. Woods, Marcotte Lab, The University of Texas at Austin

Why Ruby?

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:

  1. Everything returns a value. Ruby's better object model means better of chaining of computation.
  2. Iterators are way better than for loops.
  3. Readability. Ruby is incredibly readable, which makes it uber-maintainable.
  4. Metaprogramming. Sometimes the simplest solution is to write a code generator. Sometimes, eigenclasses are the cleanest.
  5. Integration into Rails. The influence of Rails on Ruby is undeniable. Web-based visualization for scientific projects is the future.
  6. 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
  • flotomatic: Rails gem for the Flot Javascript library, for web data visualization.
  • NArray: Numerical Ruby NArray and Ruby/PGPLOT.
  • Ruby GSL: Ruby interface for the GNU Scientific Library


Numeric Array and Matrix Library

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.

Visualization and Plotting Library

Goals: High-quality, interactive, dynamic visualizations of the sort seen in Processing.

  • Based in OpenGL for interactivity and native 3D on many platforms.
    • FFI-OpenGL or Rice with GLT
    • WebGL support for HTML5 Canvas
    • Multi-touch
  • Make matplotlib drool, but be inspired by it.