%global _empty_manifest_terminate_build 0 Name: python-nxviz Version: 0.7.4 Release: 1 Summary: Graph Visualization Package License: MIT license URL: https://github.com/ericmjl/nxviz Source0: https://mirrors.aliyun.com/pypi/web/packages/94/d7/7635769f432b35d7cb05a16847ee6f0e64416476a552c91e56afe579666f/nxviz-0.7.4.tar.gz BuildArch: noarch Requires: python3-matplotlib Requires: python3-more-itertools Requires: python3-networkx Requires: python3-numpy Requires: python3-palettable Requires: python3-pandas Requires: python3-seaborn %description # nxviz: Composable and rational network visualizations in matplotlib `nxviz` is a package for building _rational_ network visualizations using matplotlib as a backend. Inspired heavily by the principles espoused in the grammar of graphics, nxviz provides ways to _compose_ a graph visualization together by adhering to the following recipe: 1. Prioritize node placement, mapping data to position and visual properties, 2. Draw in edges, mapping data to visual properties, 3. Add in annotations and highlights on the graph. `nxviz` is simultaneously a data visualization research project, art project, and declarative data visualization tool. We hope you enjoy using it to build beautiful graph visualizations. ## Installation ### Official Releases `nxviz` is available on PyPI: ```bash pip install nxviz ``` It's also available on conda-forge: ```bash conda install -c conda-forge nxviz ``` ### Pre-releases Pre-releases are done by installing directly from git: ```bash pip install git+https://github.com/ericmjl/nxviz.git ``` ## Quickstart To make a Circos plot: ```python # We assume you have a graph G that is a NetworkX graph object. # In this example, all nodes possess the "group" and "value" node attributes # where "group" is categorical and "value" is continuous, # and all edges have the "edge_value" node attribute as well. import nxviz as nv ax = nv.circos( G, group_by="group", sort_by="value", node_color_by="group", edge_alpha_by="edge_value" ) nv.annotate.circos_group(G, group_by="group") ``` ![](images/circos.png) For more examples, including other plots that can be made, please see the examples gallery on the docs. %package -n python3-nxviz Summary: Graph Visualization Package Provides: python-nxviz BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-nxviz # nxviz: Composable and rational network visualizations in matplotlib `nxviz` is a package for building _rational_ network visualizations using matplotlib as a backend. Inspired heavily by the principles espoused in the grammar of graphics, nxviz provides ways to _compose_ a graph visualization together by adhering to the following recipe: 1. Prioritize node placement, mapping data to position and visual properties, 2. Draw in edges, mapping data to visual properties, 3. Add in annotations and highlights on the graph. `nxviz` is simultaneously a data visualization research project, art project, and declarative data visualization tool. We hope you enjoy using it to build beautiful graph visualizations. ## Installation ### Official Releases `nxviz` is available on PyPI: ```bash pip install nxviz ``` It's also available on conda-forge: ```bash conda install -c conda-forge nxviz ``` ### Pre-releases Pre-releases are done by installing directly from git: ```bash pip install git+https://github.com/ericmjl/nxviz.git ``` ## Quickstart To make a Circos plot: ```python # We assume you have a graph G that is a NetworkX graph object. # In this example, all nodes possess the "group" and "value" node attributes # where "group" is categorical and "value" is continuous, # and all edges have the "edge_value" node attribute as well. import nxviz as nv ax = nv.circos( G, group_by="group", sort_by="value", node_color_by="group", edge_alpha_by="edge_value" ) nv.annotate.circos_group(G, group_by="group") ``` ![](images/circos.png) For more examples, including other plots that can be made, please see the examples gallery on the docs. %package help Summary: Development documents and examples for nxviz Provides: python3-nxviz-doc %description help # nxviz: Composable and rational network visualizations in matplotlib `nxviz` is a package for building _rational_ network visualizations using matplotlib as a backend. Inspired heavily by the principles espoused in the grammar of graphics, nxviz provides ways to _compose_ a graph visualization together by adhering to the following recipe: 1. Prioritize node placement, mapping data to position and visual properties, 2. Draw in edges, mapping data to visual properties, 3. Add in annotations and highlights on the graph. `nxviz` is simultaneously a data visualization research project, art project, and declarative data visualization tool. We hope you enjoy using it to build beautiful graph visualizations. ## Installation ### Official Releases `nxviz` is available on PyPI: ```bash pip install nxviz ``` It's also available on conda-forge: ```bash conda install -c conda-forge nxviz ``` ### Pre-releases Pre-releases are done by installing directly from git: ```bash pip install git+https://github.com/ericmjl/nxviz.git ``` ## Quickstart To make a Circos plot: ```python # We assume you have a graph G that is a NetworkX graph object. # In this example, all nodes possess the "group" and "value" node attributes # where "group" is categorical and "value" is continuous, # and all edges have the "edge_value" node attribute as well. import nxviz as nv ax = nv.circos( G, group_by="group", sort_by="value", node_color_by="group", edge_alpha_by="edge_value" ) nv.annotate.circos_group(G, group_by="group") ``` ![](images/circos.png) For more examples, including other plots that can be made, please see the examples gallery on the docs. %prep %autosetup -n nxviz-0.7.4 %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-nxviz -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Thu Jun 08 2023 Python_Bot - 0.7.4-1 - Package Spec generated