%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 - 1.8-1 - Package Spec generated