%global _empty_manifest_terminate_build 0 Name: python-Pytrad Version: 0.1.1.5 Release: 1 Summary: Pytrad Python Package License: MIT License URL: https://github.com/cmu-phil/pytrad Source0: https://mirrors.aliyun.com/pypi/web/packages/6e/dd/924f75bed29d14de5368343e3448aa65bfe879f4f0fd46de772a1d002a8a/Pytrad-0.1.1.5.tar.gz BuildArch: noarch Requires: python3-numpy Requires: python3-scipy Requires: python3-scikit-learn Requires: python3-graphviz Requires: python3-statsmodels Requires: python3-pandas Requires: python3-matplotlib Requires: python3-networkx Requires: python3-pydot %description # Pytrad: Causal Discovery for Python Pytrad is an open-source causal discovery library for Python, which is a Python translation and extension of [Tetrad](https://github.com/cmu-phil/tetrad). The package is on its very first version and we are actively developing it. Please, as a beta user, if you are willing, would you please kindly share any feedbacks (issues, suggestions, etc.) about it with us? # Package Overview Our Pytrad implements methods for causal discovery: * Constrained-based causal discovery methods. * Score-based causal discovery methods. * Causal discovery methods based on constrained functional causal models. * Hidden causal representation learning. * Granger causality. * Multiple utilities for building your own method, such as independence tests, score functions, graph operations, and evaluations. # Install Pytrad needs the following packages to be installed beforehand: * python 3 * numpy * networkx * pandas * scipy * scikit-learn * statsmodels * pydot (For visualization) * matplotlib * graphviz To use Pytrad, we could install it using [pip](https://pypi.org/project/sqlparse/): ``` pip install pytrad ``` # Documentation Please kindly refer to [Pytrad Doc](https://pytrad-docs.readthedocs.io/en/latest/) for detailed tutorials and usages. %package -n python3-Pytrad Summary: Pytrad Python Package Provides: python-Pytrad BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-Pytrad # Pytrad: Causal Discovery for Python Pytrad is an open-source causal discovery library for Python, which is a Python translation and extension of [Tetrad](https://github.com/cmu-phil/tetrad). The package is on its very first version and we are actively developing it. Please, as a beta user, if you are willing, would you please kindly share any feedbacks (issues, suggestions, etc.) about it with us? # Package Overview Our Pytrad implements methods for causal discovery: * Constrained-based causal discovery methods. * Score-based causal discovery methods. * Causal discovery methods based on constrained functional causal models. * Hidden causal representation learning. * Granger causality. * Multiple utilities for building your own method, such as independence tests, score functions, graph operations, and evaluations. # Install Pytrad needs the following packages to be installed beforehand: * python 3 * numpy * networkx * pandas * scipy * scikit-learn * statsmodels * pydot (For visualization) * matplotlib * graphviz To use Pytrad, we could install it using [pip](https://pypi.org/project/sqlparse/): ``` pip install pytrad ``` # Documentation Please kindly refer to [Pytrad Doc](https://pytrad-docs.readthedocs.io/en/latest/) for detailed tutorials and usages. %package help Summary: Development documents and examples for Pytrad Provides: python3-Pytrad-doc %description help # Pytrad: Causal Discovery for Python Pytrad is an open-source causal discovery library for Python, which is a Python translation and extension of [Tetrad](https://github.com/cmu-phil/tetrad). The package is on its very first version and we are actively developing it. Please, as a beta user, if you are willing, would you please kindly share any feedbacks (issues, suggestions, etc.) about it with us? # Package Overview Our Pytrad implements methods for causal discovery: * Constrained-based causal discovery methods. * Score-based causal discovery methods. * Causal discovery methods based on constrained functional causal models. * Hidden causal representation learning. * Granger causality. * Multiple utilities for building your own method, such as independence tests, score functions, graph operations, and evaluations. # Install Pytrad needs the following packages to be installed beforehand: * python 3 * numpy * networkx * pandas * scipy * scikit-learn * statsmodels * pydot (For visualization) * matplotlib * graphviz To use Pytrad, we could install it using [pip](https://pypi.org/project/sqlparse/): ``` pip install pytrad ``` # Documentation Please kindly refer to [Pytrad Doc](https://pytrad-docs.readthedocs.io/en/latest/) for detailed tutorials and usages. %prep %autosetup -n Pytrad-0.1.1.5 %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-Pytrad -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Jun 20 2023 Python_Bot - 0.1.1.5-1 - Package Spec generated