diff options
| author | CoprDistGit <infra@openeuler.org> | 2023-05-10 06:25:04 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-05-10 06:25:04 +0000 |
| commit | 82fcb6ac1b5504a1155effd803cfb9faf365b957 (patch) | |
| tree | 9b11683b3c70b72177a27aafcba3d671352eda60 | |
| parent | 107ea11585cab5839076087639ed512581d9ef88 (diff) | |
automatic import of python-lea
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-lea.spec | 123 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 125 insertions, 0 deletions
@@ -0,0 +1 @@ +/lea-3.4.4.tar.gz diff --git a/python-lea.spec b/python-lea.spec new file mode 100644 index 0000000..c50a577 --- /dev/null +++ b/python-lea.spec @@ -0,0 +1,123 @@ +%global _empty_manifest_terminate_build 0 +Name: python-lea +Version: 3.4.4 +Release: 1 +Summary: Discrete probability distributions in Python +License: LGPL +URL: http://bitbucket.org/piedenis/lea +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/88/1d/bcd296e04f93d15eed58959a3209256252c8d0265c02ab343afa6e71cb15/lea-3.4.4.tar.gz +BuildArch: noarch + + +%description +Lea is a Python module aiming at working with discrete probability distributions in an intuitive way. + +It allows you modeling a broad range of random phenomena: gambling, weather, finance, etc. More generally, Lea may be used for any finite set of discrete values having known probability: numbers, booleans, date/times, symbols,... Each probability distribution is modeled as a plain object, which can be named, displayed, queried or processed to produce new probability distributions. + +Lea also provides advanced functions and Probabilistic Programming (PP) features; these include conditional probabilities, joint probability distributions, Bayesian networks, Markov chains and symbolic computation. + +All probability calculations in Lea are performed by a new exact algorithm, the Statues algorithm, which is based on variable binding and recursive generators. For problems intractable through exact methods, Lea provides on-demand approximate algorithms, namely MC rejection sampling and likelihood weighting. + +Beside the above-cited functions, Lea provides some machine learning functions, including Maximum-Likelihood and Expectation-Maximization algorithms. + +Lea can be used for AI, education (probability theory & PP), generation of random samples, etc. + +To install Lea 3.4.4, type the following command: +:: + + pip install lea==3.4.4 + +Please go on Lea project page (beside) for a comprehensive documentation. + +%package -n python3-lea +Summary: Discrete probability distributions in Python +Provides: python-lea +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-lea +Lea is a Python module aiming at working with discrete probability distributions in an intuitive way. + +It allows you modeling a broad range of random phenomena: gambling, weather, finance, etc. More generally, Lea may be used for any finite set of discrete values having known probability: numbers, booleans, date/times, symbols,... Each probability distribution is modeled as a plain object, which can be named, displayed, queried or processed to produce new probability distributions. + +Lea also provides advanced functions and Probabilistic Programming (PP) features; these include conditional probabilities, joint probability distributions, Bayesian networks, Markov chains and symbolic computation. + +All probability calculations in Lea are performed by a new exact algorithm, the Statues algorithm, which is based on variable binding and recursive generators. For problems intractable through exact methods, Lea provides on-demand approximate algorithms, namely MC rejection sampling and likelihood weighting. + +Beside the above-cited functions, Lea provides some machine learning functions, including Maximum-Likelihood and Expectation-Maximization algorithms. + +Lea can be used for AI, education (probability theory & PP), generation of random samples, etc. + +To install Lea 3.4.4, type the following command: +:: + + pip install lea==3.4.4 + +Please go on Lea project page (beside) for a comprehensive documentation. + +%package help +Summary: Development documents and examples for lea +Provides: python3-lea-doc +%description help +Lea is a Python module aiming at working with discrete probability distributions in an intuitive way. + +It allows you modeling a broad range of random phenomena: gambling, weather, finance, etc. More generally, Lea may be used for any finite set of discrete values having known probability: numbers, booleans, date/times, symbols,... Each probability distribution is modeled as a plain object, which can be named, displayed, queried or processed to produce new probability distributions. + +Lea also provides advanced functions and Probabilistic Programming (PP) features; these include conditional probabilities, joint probability distributions, Bayesian networks, Markov chains and symbolic computation. + +All probability calculations in Lea are performed by a new exact algorithm, the Statues algorithm, which is based on variable binding and recursive generators. For problems intractable through exact methods, Lea provides on-demand approximate algorithms, namely MC rejection sampling and likelihood weighting. + +Beside the above-cited functions, Lea provides some machine learning functions, including Maximum-Likelihood and Expectation-Maximization algorithms. + +Lea can be used for AI, education (probability theory & PP), generation of random samples, etc. + +To install Lea 3.4.4, type the following command: +:: + + pip install lea==3.4.4 + +Please go on Lea project page (beside) for a comprehensive documentation. + +%prep +%autosetup -n lea-3.4.4 + +%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-lea -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 3.4.4-1 +- Package Spec generated @@ -0,0 +1 @@ +01807bd8405ea7f579c8d84c5c5e609e lea-3.4.4.tar.gz |
