Metadata-Version: 1.1
Name: pebaystats
Version: 0.3
Summary: descriptive statistics using Pebay results
Home-page: http://github.com/brillozon-code/pebaystats
Author: Mike Martinez
Author-email: brillozon@gmail.com
License: Apache License 2.0
Download-URL: https://github.com/brillozon-code/pebaystats/archive/0.1.tar.gz
Description: pebaystats
        ----------
        
        This package is based on the formulas described in the document
        `Formulas for Robust, One-Pass Parallel Computation of Covariances and Arbitrary-Order Statistical Moments, Phillipe Pébay, Sandia National Laboratories <http://infoserve.sandia.gov/sand_doc/2008/086212.pdf>`_
        
        To create an accumulator, do the following::
        
            >>>> import pebaystats as pbs
            >>>> stats1 = pbs.dstats(2,1)
        
            >>>> stats3 = pbs.dstats(4,3)
        
        Add data values to the accumulator::
        
            >>>> stats1.add(24.5)
            >>>> stats1.add(42)
        
            >>>> stats3.add([24.5,23.4,65])
            >>>> stats3.add([24.5,23.4,65])
            >>>> stats3.add([25.4,65,23.4])
        
        Remove data values from the accumulator::
        
            >>>> stats1.remove(24.5)
        
        Extract the descriptive statistics from the accumulator::
        
            >>>> stats1.statistics(True)
            Data elements accumulated in stats1: 1
        
            array([[ 42.],
                   [  0.]])
        
            >>>> stats3.statistics(True)
            Data elements accumulated in stats3: 3
        
            array([[ 24.8       ,  37.26666667,  51.13333333],
                   [  0.42426407,  19.61042806,  19.61042806],
                   [  0.19540667,  61.40667933, -61.40667933],
                   [ -1.5       ,  -1.5       ,  -1.5       ]])
        
        
        
        
        
        History
        -------
        
        0.1 (2016-11-13)
        -------------------------------
        * First release on PyPI
        
        0.2 (2016-11-13)
        -------------------------------
        * Corrected some setup configuration issues
        
        0.3 (2016-11-14)
        -------------------------------
        * Added support and tests for serialization
        
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Scientific/Engineering :: Mathematics
