[jruby-user] [ANN] Multidimensional Array - MDArray (0.5.0)

[Rodrigo Botafogo]

MDArray

=======

MDArray is a multi dimensional array implemented for JRuby inspired by NumPy (www.numpy.org) 

and Narray (narray.rubyforge.org) by Masahiro Tanaka.  MDArray stands on the shoulders of 

Java-NetCDF and Parallel Colt.

 

NetCDF-Java Library is a Java interface to NetCDF files, as well as to many other types of 

scientific data formats.  It is developed and distributed by Unidata (http://www.unidata.ucar.edu). 

Parallel Colt (sites.google.com/site/piotrwendykier/software/parallelcolt) is a multithreaded 

version of Colt (http://acs.lbl.gov/software/colt/).  Colt provides a set of Open Source 

Libraries for High Performance Scientific and Technical Computing in Java. Scientific 

and technical computing is characterized by demanding problem sizes and a need for high 

performance at reasonably small memory footprint.

MDArray and SciRuby

===================

MDArray subscribes fully to the SciRuby Manifesto (http://sciruby.com/).  

"Ruby has for some time had 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. 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 is occurring now, we believe, with numeric and visualization libraries for Ruby."

Main properties

===============

  + Homogeneous multidimensional array, a table of elements (usually numbers), all of the 

      same type, indexed by a tuple of positive integers;

  + Easy calculation for large numerical multi dimensional arrays;

  + Basic types are: boolean, byte, short, int, long, float, double, string, structure;

  + Based on JRuby, which allows importing Java libraries;

  + Operator: +,-,*,/,%,**, >, >=, etc.

  + Functions: abs, ceil, floor, truncate, is_zero, square, cube, fourth;

  + Binary Operators: &, |, ^, ~ (binary_ones_complement), <<, >>;

  + Ruby Math functions: acos, acosh, asin, asinh, atan, atan2, atanh, cbrt, cos, erf, exp, 

      gamma, hypot, ldexp, log, log10, log2, sin, sinh, sqrt, tan, tanh, neg;

  + Boolean operations on boolean arrays: and, or, not;

  + Fast descriptive statistics from Parallel Colt (complete list found bellow);

  + Easy manipulation of arrays: reshape, reduce dimension, permute, section, slice, etc.

  + Reading of two dimensional arrays from CSV files (mainly for debugging and simple 

      testing purposes);

  + StatList: a list that can grow/shrink and that can compute Parallel Colt descriptive 

      statistics. 

Descriptive statistics methods

==============================

auto_correlation, correlation, covariance, durbin_watson, frequencies, geometric_mean, 

harmonic_mean, kurtosis, lag1, max, mean, mean_deviation, median, min, moment, moment3, 

moment4, pooled_mean, pooled_variance, product, quantile, quantile_inverse, 

rank_interpolated, rms, sample_covariance, sample_kurtosis, 

sample_kurtosis_standard_error, sample_skew, sample_skew_standard_error, 

sample_standard_deviation, sample_variance, sample_weighted_variance, skew, split,  

standard_deviation, standard_error, sum, sum_of_inversions, sum_of_logarithms, 

sum_of_powers, sum_of_power_deviations, sum_of_squares, sum_of_squared_deviations, 

trimmed_mean, variance, weighted_mean, weighted_rms, weighted_sums, winsorized_mean.

Installation and download

=========================

  + Install Jruby

  + jruby -S gem install mdarray

Contributors

============

  + Contributors are welcome.

Homepages

=========

  + http://rubygems.org/gems/mdarray

  + https://github.com/rbotafogo/mdarray/wiki

HISTORY

=======

  + 16/05/2013: Version 0.5.0: All loops transfered to Java with over 50% performance 

      improvement.  Descriptive statistics from Parallel Colt.

  + 19/04/2013: Version 0.4.3: Fixes a simple (but fatal bug).  No new features

  + 17/04/2013: Version 0.4.2: Adds simple statistics and boolean operators

  + 05/05/2013: Version 0.4.0: Initial release

--
Rodrigo Botafogo

Integrando TI ao seu negócio

[Stephen Boesch]

Thanks, this is great progress towards permitting choice of using  jruby  - as opposed to constrained to python.   i'm not in a position to be an early adopter but will follow this with keen interest.

2013/5/17 Rodrigo Botafogo <rod...@rodrigobotafogo.com>

[Rodrigo Botafogo]

Stephen,

Thanks for the support.

Do you use NumPy.  May I ask what your use case is?  

Cheers,

Rodrigo