%global _empty_manifest_terminate_build 0 Name: python-scikit-optimize Version: 0.9.0 Release: 1 Summary: Sequential model-based optimization toolbox. License: BSD 3-clause URL: https://scikit-optimize.github.io/ Source0: https://mirrors.nju.edu.cn/pypi/web/packages/e4/8a/33c96e29446e70c6151f2287b81ec6f28302011fd1b5bb6a220c7dab5903/scikit-optimize-0.9.0.tar.gz BuildArch: noarch Requires: python3-joblib Requires: python3-pyaml Requires: python3-numpy Requires: python3-scipy Requires: python3-scikit-learn Requires: python3-matplotlib %description Scikit-Optimize, or ``skopt``, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. ``skopt`` aims to be accessible and easy to use in many contexts. The library is built on top of NumPy, SciPy and Scikit-Learn. We do not perform gradient-based optimization. For gradient-based optimization algorithms look at ``scipy.optimize`` `here `_. Approximated objective function after 50 iterations of ``gp_minimize``. Plot made using ``skopt.plots.plot_objective``. %package -n python3-scikit-optimize Summary: Sequential model-based optimization toolbox. Provides: python-scikit-optimize BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-scikit-optimize Scikit-Optimize, or ``skopt``, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. ``skopt`` aims to be accessible and easy to use in many contexts. The library is built on top of NumPy, SciPy and Scikit-Learn. We do not perform gradient-based optimization. For gradient-based optimization algorithms look at ``scipy.optimize`` `here `_. Approximated objective function after 50 iterations of ``gp_minimize``. Plot made using ``skopt.plots.plot_objective``. %package help Summary: Development documents and examples for scikit-optimize Provides: python3-scikit-optimize-doc %description help Scikit-Optimize, or ``skopt``, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. ``skopt`` aims to be accessible and easy to use in many contexts. The library is built on top of NumPy, SciPy and Scikit-Learn. We do not perform gradient-based optimization. For gradient-based optimization algorithms look at ``scipy.optimize`` `here `_. Approximated objective function after 50 iterations of ``gp_minimize``. Plot made using ``skopt.plots.plot_objective``. %prep %autosetup -n scikit-optimize-0.9.0 %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-scikit-optimize -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Mon Apr 10 2023 Python_Bot - 0.9.0-1 - Package Spec generated