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
Integrando TI ao seu negócio
