%global _empty_manifest_terminate_build 0 Name: python-dynesty Version: 2.1.0 Release: 1 Summary: A dynamic nested sampling package for computing Bayesian posteriors and evidences. License: MIT URL: https://github.com/joshspeagle/dynesty Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a8/6f/c4d4a7840fa60054e3156ee4985c6566ae0069afdeca1f12ec24cb0f5ed2/dynesty-2.1.0.tar.gz BuildArch: noarch %description ![dynesty in action](https://github.com/joshspeagle/dynesty/blob/master/docs/images/title.gif) A Dynamic Nested Sampling package for computing Bayesian posteriors and evidences. Pure Python. MIT license. ### Documentation Documentation can be found [here](https://dynesty.readthedocs.io). ### Installation The most stable release of `dynesty` can be installed through [pip](https://pip.pypa.io/en/stable) via ``` pip install dynesty ``` The current (less stable) development version can be installed by running ``` python setup.py install ``` from inside the repository. ### Demos Several Jupyter notebooks that demonstrate most of the available features of the code can be found [here](https://github.com/joshspeagle/dynesty/tree/master/demos). ### Attribution If you find the package useful in your research, please cite at least *both* of these references: * The original paper [Speagle (2020)](https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.3132S/abstract) * The python implementation [Koposov et al. (2023)](https://doi.org/10.5281/zenodo.3348367) (the citation info is at the bottom of the page on the right) and ideally also papers describing the underlying methods (see the [documentation](https://dynesty.readthedocs.io/en/latest/references.html) for more details) ### Reporting issues If you want to report issues, or have questions, please do that on [github](https://github.com/joshspeagle/dynesty/issues). ### Contributing Patches and contributions are very welcome! Please see [CONTRIBUTING.md](https://github.com/joshspeagle/dynesty/blob/master/CONTRIBUTING.md) for more details. %package -n python3-dynesty Summary: A dynamic nested sampling package for computing Bayesian posteriors and evidences. Provides: python-dynesty BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-dynesty ![dynesty in action](https://github.com/joshspeagle/dynesty/blob/master/docs/images/title.gif) A Dynamic Nested Sampling package for computing Bayesian posteriors and evidences. Pure Python. MIT license. ### Documentation Documentation can be found [here](https://dynesty.readthedocs.io). ### Installation The most stable release of `dynesty` can be installed through [pip](https://pip.pypa.io/en/stable) via ``` pip install dynesty ``` The current (less stable) development version can be installed by running ``` python setup.py install ``` from inside the repository. ### Demos Several Jupyter notebooks that demonstrate most of the available features of the code can be found [here](https://github.com/joshspeagle/dynesty/tree/master/demos). ### Attribution If you find the package useful in your research, please cite at least *both* of these references: * The original paper [Speagle (2020)](https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.3132S/abstract) * The python implementation [Koposov et al. (2023)](https://doi.org/10.5281/zenodo.3348367) (the citation info is at the bottom of the page on the right) and ideally also papers describing the underlying methods (see the [documentation](https://dynesty.readthedocs.io/en/latest/references.html) for more details) ### Reporting issues If you want to report issues, or have questions, please do that on [github](https://github.com/joshspeagle/dynesty/issues). ### Contributing Patches and contributions are very welcome! Please see [CONTRIBUTING.md](https://github.com/joshspeagle/dynesty/blob/master/CONTRIBUTING.md) for more details. %package help Summary: Development documents and examples for dynesty Provides: python3-dynesty-doc %description help ![dynesty in action](https://github.com/joshspeagle/dynesty/blob/master/docs/images/title.gif) A Dynamic Nested Sampling package for computing Bayesian posteriors and evidences. Pure Python. MIT license. ### Documentation Documentation can be found [here](https://dynesty.readthedocs.io). ### Installation The most stable release of `dynesty` can be installed through [pip](https://pip.pypa.io/en/stable) via ``` pip install dynesty ``` The current (less stable) development version can be installed by running ``` python setup.py install ``` from inside the repository. ### Demos Several Jupyter notebooks that demonstrate most of the available features of the code can be found [here](https://github.com/joshspeagle/dynesty/tree/master/demos). ### Attribution If you find the package useful in your research, please cite at least *both* of these references: * The original paper [Speagle (2020)](https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.3132S/abstract) * The python implementation [Koposov et al. (2023)](https://doi.org/10.5281/zenodo.3348367) (the citation info is at the bottom of the page on the right) and ideally also papers describing the underlying methods (see the [documentation](https://dynesty.readthedocs.io/en/latest/references.html) for more details) ### Reporting issues If you want to report issues, or have questions, please do that on [github](https://github.com/joshspeagle/dynesty/issues). ### Contributing Patches and contributions are very welcome! Please see [CONTRIBUTING.md](https://github.com/joshspeagle/dynesty/blob/master/CONTRIBUTING.md) for more details. %prep %autosetup -n dynesty-2.1.0 %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-dynesty -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Wed Apr 12 2023 Python_Bot - 2.1.0-1 - Package Spec generated