%global _empty_manifest_terminate_build 0 Name: python-SimpleGP Version: 1.0.1 Release: 1 Summary: please add a summary manually as the author left a blank one License: MIT License URL: https://github.com/marcovirgolin/SimpleGP Source0: https://mirrors.aliyun.com/pypi/web/packages/b3/d3/cc905b49813af85c7c0b61326175cee86fac76f71b451f6d2ad61713f6f0/SimpleGP-1.0.1.tar.gz BuildArch: noarch Requires: python3-numpy Requires: python3-scikit-learn %description # Simple Genetic Programming ### For Symbolic Regression This Python 3 code is a simple implementation of genetic programming for symbolic regression, and has been developed for educational purposes. ## Dependencies `numpy` & `sklearn`. The file `test.py` shows an example of usage. ## Installation You can install it with pip using `python3 -m pip install --user simplegp`, or locally by downloading the code and running `python3 setup.py install --user`. ## Reference If you use this code, please support our research by citing one (or more) of our works for which this code was made or adopted: > M. Virgolin, A. De Lorenzo, E. Medvet, F. Randone. "Learning a Formula of Interpretability to Learn Interpretable Formulas". [Parallel Problem Solving from Nature -- PPSN XVI, pp. 79--93](https://link.springer.com/chapter/10.1007/978-3-030-58115-2_6), Springer (2020). ([arXiv preprint arXiv:2004.11170](https://arxiv.org/abs/2004.11170)) > M. Virgolin. "Genetic Programming is Naturally Suited to Evolve Bagging Ensembles". [arXiv preprint arXiv:2009.06037v5](https://arxiv.org/abs/2009.06037v5) (2021) ## Multi-objective For a multi-objective version, see [pyNSGP](https://github.com/marcovirgolin/pyNSGP). %package -n python3-SimpleGP Summary: please add a summary manually as the author left a blank one Provides: python-SimpleGP BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-SimpleGP # Simple Genetic Programming ### For Symbolic Regression This Python 3 code is a simple implementation of genetic programming for symbolic regression, and has been developed for educational purposes. ## Dependencies `numpy` & `sklearn`. The file `test.py` shows an example of usage. ## Installation You can install it with pip using `python3 -m pip install --user simplegp`, or locally by downloading the code and running `python3 setup.py install --user`. ## Reference If you use this code, please support our research by citing one (or more) of our works for which this code was made or adopted: > M. Virgolin, A. De Lorenzo, E. Medvet, F. Randone. "Learning a Formula of Interpretability to Learn Interpretable Formulas". [Parallel Problem Solving from Nature -- PPSN XVI, pp. 79--93](https://link.springer.com/chapter/10.1007/978-3-030-58115-2_6), Springer (2020). ([arXiv preprint arXiv:2004.11170](https://arxiv.org/abs/2004.11170)) > M. Virgolin. "Genetic Programming is Naturally Suited to Evolve Bagging Ensembles". [arXiv preprint arXiv:2009.06037v5](https://arxiv.org/abs/2009.06037v5) (2021) ## Multi-objective For a multi-objective version, see [pyNSGP](https://github.com/marcovirgolin/pyNSGP). %package help Summary: Development documents and examples for SimpleGP Provides: python3-SimpleGP-doc %description help # Simple Genetic Programming ### For Symbolic Regression This Python 3 code is a simple implementation of genetic programming for symbolic regression, and has been developed for educational purposes. ## Dependencies `numpy` & `sklearn`. The file `test.py` shows an example of usage. ## Installation You can install it with pip using `python3 -m pip install --user simplegp`, or locally by downloading the code and running `python3 setup.py install --user`. ## Reference If you use this code, please support our research by citing one (or more) of our works for which this code was made or adopted: > M. Virgolin, A. De Lorenzo, E. Medvet, F. Randone. "Learning a Formula of Interpretability to Learn Interpretable Formulas". [Parallel Problem Solving from Nature -- PPSN XVI, pp. 79--93](https://link.springer.com/chapter/10.1007/978-3-030-58115-2_6), Springer (2020). ([arXiv preprint arXiv:2004.11170](https://arxiv.org/abs/2004.11170)) > M. Virgolin. "Genetic Programming is Naturally Suited to Evolve Bagging Ensembles". [arXiv preprint arXiv:2009.06037v5](https://arxiv.org/abs/2009.06037v5) (2021) ## Multi-objective For a multi-objective version, see [pyNSGP](https://github.com/marcovirgolin/pyNSGP). %prep %autosetup -n SimpleGP-1.0.1 %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-SimpleGP -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Jun 20 2023 Python_Bot - 1.0.1-1 - Package Spec generated