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%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 <Python_Bot@openeuler.org> - 1.0.1-1
- Package Spec generated
|
