Metadata-Version: 1.1
Name: FisherExact
Version: 1.4
Summary: Fishe's Exact test for mxn contingency table
Home-page: https://github.com/maclandrol/FisherExact
Author: Emmanuel Noutahi
Author-email: fmr.noutahi@umontreal.ca
License: GPL
Download-URL: https://github.com/maclandrol/FisherExact/archive/1.4.tar.gz
Description: [![PyPI version](https://badge.fury.io/py/FisherExact.svg)](https://badge.fury.io/py/FisherExact)
        
        # FisherExact
        
        Fisher exact test for mxn contingency table
        
        ## Installation 
        
        FisherExact should be python2/3 compatible. You can install it with pip : `pip install FisherExact`
        
        If you get an error about builtins module, install "future" with `pip install future`
        
        This package use fortran sources, so you need to have a fortran compiler (`gfortran`) installed. See here ==> https://gcc.gnu.org/wiki/GFortranBinaries.
        
        The source code was tested on Linux and Mac (thanks to [@fomightez](https://github.com/fomightez))
        
        ## Binary Usage
        
        A binary is provided to use FisherExact from the terminal
        
        	usage: fexact [-h] [--simulate [SIMULATE]] [--hybrid] [--midP]
        	              [--retry ATTEMPT] [--workspace WORKSPACE] [--version]
        	              table
        
        	Fisher's Exact test for mxn contingency table
        
        	positional arguments:
        	  table                 Contingency table in a file, without header
        
        	optional arguments:
        	  -h, --help            show this help message and exit
        	  --simulate [SIMULATE]
        	                        Simulate p-values with n replicates
        	  --hybrid              Use hybrid mode
        	  --midP                Use midP correction
        	  --retry ATTEMPT       Number of attempt to made if execution fail
        	  --workspace WORKSPACE
        	                        Workspace size to use, Increase this if the program
        	                        crash
        	  --version             show program's version number and exit
        
        
        ## Contingency table format if fexact is used as binary
        
        The accepted format is space/tab or comma (or both) separated values with an optionnal first line starting with a "#" that specified the number of rows and column:
        
        For example, the following format are accepted
        
        ```
        # 2 3
        8        2       12
        1        5       2
        ```
        
        ```
        8 2 12
        1 5 2
        ```
        
        ```
        #2, 3
        8	2	12
        1	5	2
        ```
        
        ```
        8,2,12
        1,5,2
        ```
        
        
        ## Use as a module
        
        	fisher_exact(table, alternative='two-sided', hybrid=False, midP=False, simulate_pval=False, replicate=2000, workspace=300, attempt=2, seed=None)
                Performs a Fisher exact test on a mxn contingency table.
                
                Parameters
                ----------
                table : array_like of ints
                    A 2x2 contingency table.  Elements should be non-negative integers.
                alternative : {'two-sided', 'less', 'greater'}, optional
                    Which alternative hypothesis to the null hypothesis the test uses.
                    Default is 'two-sided'.  Only used in the 2 x 2 case (with the scipy function).
                    In every other case, the two-sided pval is returned.
                mult : int 
                    Specify the size of the workspace used in the network algorithm.  
                    Only used for non-simulated p-values larger than 2 x 2 table. 
                    You might want to increase this if the p-value failed
                hybrid : bool
                    Only used for larger than 2 x 2 tables, in which cases it indicates
                    whether the exact probabilities (default) or a hybrid approximation 
                    thereof should be computed.
                midP : bool
                    Use this to enable mid-P correction. Could lead to slow computation.
                    This is not applicable for simulation p-values. `alternative` cannot 
                    be used if you enable midpoint correction.
                simulate_pval : bool 
                    Indicate whether to compute p-values by Monte Carlo simulation,
                     in larger than 2 x 2 tables.
                replicate : int
                    An integer specifying the number of replicates used in the Monte Carlo test.
                workspace : int
                    An integer specifying the workspace size. Default value is 300. 
                attempt : int
                    Number of attempts to try, if the workspace size is not enough. 
                    On each attempt, the workspace size is doubled. 
                seed : int
                    Random number to use as seed. If a seed isn't provided. 4 bytes will be read 
                    from os.urandom. If this fail, getrandbits of the random module 
                    (with 32 random bits) will be used. In the particular case where both failed,
                    the current time will be used
                
                Returns
                -------
                p_value : float
                    The probability of a more extreme table, where 'extreme' is in a 
                    probabilistic sense.
        
        
Keywords: statistic fisher independence test
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Natural Language :: English
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
