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%global _empty_manifest_terminate_build 0
Name: python-sureal
Version: 0.9.0
Release: 1
Summary: Subjective Recovery Analysis
License: Apache 2.0
URL: https://github.com/Netflix/sureal
Source0: https://mirrors.aliyun.com/pypi/web/packages/6d/70/e146e338561db102536250f1e5b633a6246840d065884406cb5da88f6dbc/sureal-0.9.0.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-scipy
Requires: python3-matplotlib
Requires: python3-pandas
Requires: python3-setupmeta
%description
SUREAL is a toolbox developed by Netflix that includes a number of models for the recovery of mean opinion scores (MOS) from noisy measurements obtained in psychovisual subjective experiments.
Read `this <resource/doc/dcc17v3.pdf>`_ paper and `this latest <resource/doc/hvei2020.pdf>`_ paper for some background.
SUREAL also includes models to recover MOS from paired comparison (PC) subjective data, such as `Thurstone (Case V) <https://en.wikipedia.org/wiki/Thurstonian_model>`_ and `Bradley-Terry <https://en.wikipedia.org/wiki/Bradley%E2%80%93Terry_model>`_.
%package -n python3-sureal
Summary: Subjective Recovery Analysis
Provides: python-sureal
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-sureal
SUREAL is a toolbox developed by Netflix that includes a number of models for the recovery of mean opinion scores (MOS) from noisy measurements obtained in psychovisual subjective experiments.
Read `this <resource/doc/dcc17v3.pdf>`_ paper and `this latest <resource/doc/hvei2020.pdf>`_ paper for some background.
SUREAL also includes models to recover MOS from paired comparison (PC) subjective data, such as `Thurstone (Case V) <https://en.wikipedia.org/wiki/Thurstonian_model>`_ and `Bradley-Terry <https://en.wikipedia.org/wiki/Bradley%E2%80%93Terry_model>`_.
%package help
Summary: Development documents and examples for sureal
Provides: python3-sureal-doc
%description help
SUREAL is a toolbox developed by Netflix that includes a number of models for the recovery of mean opinion scores (MOS) from noisy measurements obtained in psychovisual subjective experiments.
Read `this <resource/doc/dcc17v3.pdf>`_ paper and `this latest <resource/doc/hvei2020.pdf>`_ paper for some background.
SUREAL also includes models to recover MOS from paired comparison (PC) subjective data, such as `Thurstone (Case V) <https://en.wikipedia.org/wiki/Thurstonian_model>`_ and `Bradley-Terry <https://en.wikipedia.org/wiki/Bradley%E2%80%93Terry_model>`_.
%prep
%autosetup -n sureal-0.9.0
%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-sureal -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.9.0-1
- Package Spec generated
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