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
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
