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%global _empty_manifest_terminate_build 0
Name: python-GraphHierarchy
Version: 1.8
Release: 1
Summary: A module calculating quantities related to a network metric known as trophic coherence but now generalised to all networks, see Moutsinas, G., Shuaib, C., Guo, W., & Jarvis, S. (2019). Graph hierarchy and spread of infections. arXiv preprint arXiv:1908.04358 for more details.
License: MIT
URL: https://github.com/shuaib7860/GraphHierarchy
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/f6/cd/fff2e978e803c1ef153146bcf19d19ef4d62ec1e6d52d349d7dc1a1a65ea/GraphHierarchy-1.8.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-scipy
Requires: python3-networkx
%description
**GraphHierarchy** is a python package that calculates the hierarchical level of nodes in a network, the associated hierarchical differences for the edges and the hierarchical coherence of the network.
Hierarchical analysis is the mathematical generalisation of the trophic analysis of networks. Trophic levels and hence trophic coherence can be defined only on networks with well defined sources, known as basal nodes.
Trophic coherence, a measure of a network’s hierarchical organisation, has been shown to be linked to a network’s structural and dynamical properties. Thus trophic analysis of networks had been restricted to the ecological domain, until now.
Graph Hierarchy is a python package that implements this mathematical generalisation that allows for analysis of all network structures via the trophic approach.
See Moutsinas, G., Shuaib, C., Guo, W., & Jarvis, S. (2019). Graph hierarchy and spread of infections. arXiv preprint arXiv:1908.04358 for more details.
.. _GitHub: https://github.com/shuaib7860/GraphHierarchy
%package -n python3-GraphHierarchy
Summary: A module calculating quantities related to a network metric known as trophic coherence but now generalised to all networks, see Moutsinas, G., Shuaib, C., Guo, W., & Jarvis, S. (2019). Graph hierarchy and spread of infections. arXiv preprint arXiv:1908.04358 for more details.
Provides: python-GraphHierarchy
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-GraphHierarchy
**GraphHierarchy** is a python package that calculates the hierarchical level of nodes in a network, the associated hierarchical differences for the edges and the hierarchical coherence of the network.
Hierarchical analysis is the mathematical generalisation of the trophic analysis of networks. Trophic levels and hence trophic coherence can be defined only on networks with well defined sources, known as basal nodes.
Trophic coherence, a measure of a network’s hierarchical organisation, has been shown to be linked to a network’s structural and dynamical properties. Thus trophic analysis of networks had been restricted to the ecological domain, until now.
Graph Hierarchy is a python package that implements this mathematical generalisation that allows for analysis of all network structures via the trophic approach.
See Moutsinas, G., Shuaib, C., Guo, W., & Jarvis, S. (2019). Graph hierarchy and spread of infections. arXiv preprint arXiv:1908.04358 for more details.
.. _GitHub: https://github.com/shuaib7860/GraphHierarchy
%package help
Summary: Development documents and examples for GraphHierarchy
Provides: python3-GraphHierarchy-doc
%description help
**GraphHierarchy** is a python package that calculates the hierarchical level of nodes in a network, the associated hierarchical differences for the edges and the hierarchical coherence of the network.
Hierarchical analysis is the mathematical generalisation of the trophic analysis of networks. Trophic levels and hence trophic coherence can be defined only on networks with well defined sources, known as basal nodes.
Trophic coherence, a measure of a network’s hierarchical organisation, has been shown to be linked to a network’s structural and dynamical properties. Thus trophic analysis of networks had been restricted to the ecological domain, until now.
Graph Hierarchy is a python package that implements this mathematical generalisation that allows for analysis of all network structures via the trophic approach.
See Moutsinas, G., Shuaib, C., Guo, W., & Jarvis, S. (2019). Graph hierarchy and spread of infections. arXiv preprint arXiv:1908.04358 for more details.
.. _GitHub: https://github.com/shuaib7860/GraphHierarchy
%prep
%autosetup -n GraphHierarchy-1.8
%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-GraphHierarchy -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 1.8-1
- Package Spec generated
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