From bdd51b494ce3aae6aaab18c0c5b02cc51b094584 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Fri, 5 May 2023 06:55:43 +0000 Subject: automatic import of python-pysot --- .gitignore | 1 + python-pysot.spec | 114 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 116 insertions(+) create mode 100644 python-pysot.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..332c9e3 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/pySOT-0.3.3.tar.gz diff --git a/python-pysot.spec b/python-pysot.spec new file mode 100644 index 0000000..5c8330c --- /dev/null +++ b/python-pysot.spec @@ -0,0 +1,114 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pySOT +Version: 0.3.3 +Release: 1 +Summary: Surrogate Optimization Toolbox +License: LICENSE.rst +URL: https://github.com/dme65/pySOT +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c8/38/9f980e8d985151b59b0d2f38b24ab42407623657e98bbda686d1a9be8ed0/pySOT-0.3.3.tar.gz +BuildArch: noarch + +Requires: python3-scipy +Requires: python3-pyDOE2 +Requires: python3-POAP +Requires: python3-pytest +Requires: python3-dill +Requires: python3-scikit-learn + +%description +The Python Surrogate Optimization Toolbox (pySOT) is an asynchronous parallel +optimization toolbox for computationally expensive global optimization problems. +pySOT is built on top of the Plumbing for Optimization with Asynchronous Parallelism (POAP), +which is an event-driven framework for building and combining asynchronous optimization +strategies. POAP has support for both threads and MPI. +pySOT implements many popular surrogate optimization algorithms such as the +Stochastic RBF (SRBF) and DYCORS methods by Regis and Shoemaker, and the SOP +method by Krityakierne et. al. We also support Expected Improvement (EI) and +Lower Confidence Bounds (LCB), which are popular in Bayesian optimization. All +optimization algorithms can be used in serial, synchronous parallel, and +asynchronous parallel and we support both continuous and integer variables. +The toolbox is hosted on GitHub: https://github.com/dme65/pySOT +Documentation: http://pysot.readthedocs.io/ + +%package -n python3-pySOT +Summary: Surrogate Optimization Toolbox +Provides: python-pySOT +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pySOT +The Python Surrogate Optimization Toolbox (pySOT) is an asynchronous parallel +optimization toolbox for computationally expensive global optimization problems. +pySOT is built on top of the Plumbing for Optimization with Asynchronous Parallelism (POAP), +which is an event-driven framework for building and combining asynchronous optimization +strategies. POAP has support for both threads and MPI. +pySOT implements many popular surrogate optimization algorithms such as the +Stochastic RBF (SRBF) and DYCORS methods by Regis and Shoemaker, and the SOP +method by Krityakierne et. al. We also support Expected Improvement (EI) and +Lower Confidence Bounds (LCB), which are popular in Bayesian optimization. All +optimization algorithms can be used in serial, synchronous parallel, and +asynchronous parallel and we support both continuous and integer variables. +The toolbox is hosted on GitHub: https://github.com/dme65/pySOT +Documentation: http://pysot.readthedocs.io/ + +%package help +Summary: Development documents and examples for pySOT +Provides: python3-pySOT-doc +%description help +The Python Surrogate Optimization Toolbox (pySOT) is an asynchronous parallel +optimization toolbox for computationally expensive global optimization problems. +pySOT is built on top of the Plumbing for Optimization with Asynchronous Parallelism (POAP), +which is an event-driven framework for building and combining asynchronous optimization +strategies. POAP has support for both threads and MPI. +pySOT implements many popular surrogate optimization algorithms such as the +Stochastic RBF (SRBF) and DYCORS methods by Regis and Shoemaker, and the SOP +method by Krityakierne et. al. We also support Expected Improvement (EI) and +Lower Confidence Bounds (LCB), which are popular in Bayesian optimization. All +optimization algorithms can be used in serial, synchronous parallel, and +asynchronous parallel and we support both continuous and integer variables. +The toolbox is hosted on GitHub: https://github.com/dme65/pySOT +Documentation: http://pysot.readthedocs.io/ + +%prep +%autosetup -n pySOT-0.3.3 + +%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-pySOT -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot - 0.3.3-1 +- Package Spec generated diff --git a/sources b/sources new file mode 100644 index 0000000..7c68894 --- /dev/null +++ b/sources @@ -0,0 +1 @@ +2cf4262efc95db0c90d9f0af41363ad0 pySOT-0.3.3.tar.gz -- cgit v1.2.3