Metadata-Version: 1.1
Name: fitter
Version: 1.0.0
Summary: A tool to fit data to many distributions and best one(s)
Home-page: ['http://packages.python.org/easydev/']
Author: Thomas Cokelaer
Author-email: cokelaer@gmail.com
License: GPL
Download-URL: ['http://pypi.python.org/pypi/easydev']
Description: 
        
        #############################
        FITTER documentation
        #############################
        
        .. image:: https://badge.fury.io/py/fitter.svg
            :target: https://pypi.python.org/pypi/fitter
        
        .. image:: https://pypip.in/d/fitter/badge.png
            :target: https://crate.io/packages/fitter/
        
        .. image:: https://secure.travis-ci.org/cokelaer/fitter.png
            :target: http://travis-ci.org/cokelaer/fitter
        
        .. image:: https://coveralls.io/repos/cokelaer/fitter/badge.png?branch=master 
            :target: https://coveralls.io/r/cokelaer/fitter?branch=master 
        
        .. image:: https://landscape.io/github/cokelaer/fitter/master/landscape.png
            :target: https://landscape.io/github/cokelaer/fitter/master
        
        .. image:: https://badge.waffle.io/cokelaer/fitter.png?label=ready&title=Ready 
            :target: https://waffle.io/cokelaer/fitter
        
        
        Compatible with Python 2.7 and >=3.3
        
        .. note:: Bug report, issues, contributions ? Please visit 
            `gitbub <http://github.com/cokelaer/fitter>`_
        
        What is it ?
        ################
        
        **fitter** package provides a simple class to identify the distribution from which a data samples is generated from. It uses 80 distributions from Scipy and allows you to plot the results to check what is the most probable distribution and the best parameters.
        
        
        Installation
        ###################
        
        ::
        
            pip install fitter
        
        
        Usage
        ##################
        
        
        First, let us create a data samples with N = 1e5 points from a gamma distribution::
        
            from scipy import stats
            data = stats.gamma.rvs(2, loc=1.5, scale=2, size=100000)
        
        
        Now, without any knowledge about the distribution or its parameter, what is the distribution that fits the data best ? Scipy has 80 distributions and the :class:`fitter.Fitter` class will scan all of them, call the fit function for you, ignoring those that fail or run forever and finally give you a summary of the best distributions in the sense of sum of the square errors. The best is to give an example::
        
        
            from fitter import Fitter
            f = Fitter(data)
            f.fit()
            # may take some time since by default, all distributions are tried
            # but you call manually provide a smaller set of distributions 
            f.summary()
        
        
        .. image:: http://pythonhosted.org/fitter/_images/index-1.png
            :target: http://pythonhosted.org/fitter/_images/index-1.png
        
        
        See the `online <http://pythonhosted.org/fitter/>`_ documentation for details.
        
        
        
        
        
        
Keywords: fit,distribution,fitting,scipy
Platform: Linux
Platform: Unix
Platform: MacOsX
Platform: Windows
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires: sphinx
Requires: numpy
Requires: matplotlib
Requires: scipy
Requires: pandas
