[Numpy-discussion] [ANN] Multidimensional Array - MDArray (0.5.0)

Rodrigo Botafogo rodrigo at rodrigobotafogo.com
Fri May 17 09:20:47 EDT 2013


Although this is not directly connected to NumPy, I believe that it could
be of interest to the NymPy community.  If, by any reason it is inproper to
post this type of announcement on this list, please let me know.

I´m happy to announce a new version of MDArray...


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
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