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@@ -0,0 +1 @@ +/ipfn-1.4.4.tar.gz diff --git a/python-ipfn.spec b/python-ipfn.spec new file mode 100644 index 0000000..ce7d8eb --- /dev/null +++ b/python-ipfn.spec @@ -0,0 +1,101 @@ +%global _empty_manifest_terminate_build 0 +Name: python-ipfn +Version: 1.4.4 +Release: 1 +Summary: Iterative Proportional Fitting with N dimensions, for python +License: MIT +URL: https://github.com/Dirguis/ipfn.git +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/b8/82/acf73d6e8b3877e3b0ace42aad730bd8ac3b7320a70963092cdc6cc85ec9/ipfn-1.4.4.tar.gz +BuildArch: noarch + +Requires: python3-pandas +Requires: python3-numpy + +%description +Iterative proportional fitting is an algorithm used is many different fields such as economics or social sciences, to alter results in such a way that aggregates along one or several dimensions match known marginals (or aggregates along these same dimensions). +The algorithm exists in 2 versions: +* numpy version, which the fastest by far +* pandas version, which is much slower but easier to use than the numpy version +The algorithm recognizes the input variable type and and uses the appropriate version to solve the problem. To install the package: +* pip install ipfn +* pip install git+http://github.com/dirguis/ipfn@master +For more information and examples, please visit: +* `wikipedia page on ipf <https://en.wikipedia.org/wiki/Iterative_proportional_fitting>`_ +* `slides explaining the methodology and links to specific examples <http://www.demog.berkeley.edu/~eddieh/IPFDescription/AKDOLWDIPFTWOD.pdf>`_ + +%package -n python3-ipfn +Summary: Iterative Proportional Fitting with N dimensions, for python +Provides: python-ipfn +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-ipfn +Iterative proportional fitting is an algorithm used is many different fields such as economics or social sciences, to alter results in such a way that aggregates along one or several dimensions match known marginals (or aggregates along these same dimensions). +The algorithm exists in 2 versions: +* numpy version, which the fastest by far +* pandas version, which is much slower but easier to use than the numpy version +The algorithm recognizes the input variable type and and uses the appropriate version to solve the problem. To install the package: +* pip install ipfn +* pip install git+http://github.com/dirguis/ipfn@master +For more information and examples, please visit: +* `wikipedia page on ipf <https://en.wikipedia.org/wiki/Iterative_proportional_fitting>`_ +* `slides explaining the methodology and links to specific examples <http://www.demog.berkeley.edu/~eddieh/IPFDescription/AKDOLWDIPFTWOD.pdf>`_ + +%package help +Summary: Development documents and examples for ipfn +Provides: python3-ipfn-doc +%description help +Iterative proportional fitting is an algorithm used is many different fields such as economics or social sciences, to alter results in such a way that aggregates along one or several dimensions match known marginals (or aggregates along these same dimensions). +The algorithm exists in 2 versions: +* numpy version, which the fastest by far +* pandas version, which is much slower but easier to use than the numpy version +The algorithm recognizes the input variable type and and uses the appropriate version to solve the problem. To install the package: +* pip install ipfn +* pip install git+http://github.com/dirguis/ipfn@master +For more information and examples, please visit: +* `wikipedia page on ipf <https://en.wikipedia.org/wiki/Iterative_proportional_fitting>`_ +* `slides explaining the methodology and links to specific examples <http://www.demog.berkeley.edu/~eddieh/IPFDescription/AKDOLWDIPFTWOD.pdf>`_ + +%prep +%autosetup -n ipfn-1.4.4 + +%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-ipfn -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.4.4-1 +- Package Spec generated @@ -0,0 +1 @@ +b8653140a1c33e5aa7d5f8fd551d91c5 ipfn-1.4.4.tar.gz |