%global _empty_manifest_terminate_build 0
Name:		python-FisherExact
Version:	1.4.2
Release:	1
Summary:	Fishe's Exact test for mxn contingency table
License:	GPL
URL:		https://github.com/maclandrol/FisherExact
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/6f/e9/a849764e3da0f166cd1e37c624fc74f918920c72feb72f351854cbfedd94/FisherExact-1.4.2.tar.gz
BuildArch:	noarch


%description
        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

%package -n python3-FisherExact
Summary:	Fishe's Exact test for mxn contingency table
Provides:	python-FisherExact
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-FisherExact
        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

%package help
Summary:	Development documents and examples for FisherExact
Provides:	python3-FisherExact-doc
%description help
        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

%prep
%autosetup -n FisherExact-1.4.2

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-FisherExact -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Sun Apr 23 2023 Python_Bot <Python_Bot@openeuler.org> - 1.4.2-1
- Package Spec generated