KO | EN

GitLite

Minimalist Open Source Repository Search Engine

gitlite — search

#dsh #dsh-plugin #developer-tools #ai-agent #claude-code #codex #typescript #ai-agents #deepseek-harness #mcp #cli #rust

FisherExact

★ 38 Open GitHub ↗

Fisher exact test for mxn contingency table in python

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

> [!WARNING]
>
> ## This repository is archived and no longer maintained
>
> **For new projects, use [`scipy.stats.fisher_exact`](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.fisher_exact.html) instead.**
>
> Since [SciPy 1.15.0](https://docs.scipy.org/doc/scipy-1.15.0/release/1.15.0-notes.html), SciPy supports Fisher’s exact test for two-dimensional **R × C contingency tables**.
>
> See the [original SciPy issue](https://github.com/scipy/scipy/issues/7099) and the [implementation PR](https://github.com/scipy/scipy/pull/21996).

[![PyPI version](https://badge.fury.io/py/FisherExact.svg)](https://pypi.org/project/FisherExact/)
[![DOI](https://img.shields.io/badge/DOI-10.5281%2Fzenodo.2587757-blue.svg)](https://doi.org/10.5281/zenodo.2587757)

# 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.

### If you need to cite.

```
@article{maclandrol,
title={Fisher\'s exact test for MxN contingency table}, 
DOI={10.5281/zenodo.2587757},
publisher={Zenodo}, 
author={Emmanuel Noutahi}, 
year={2018}
}
```

FisherExact

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README