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@@ -0,0 +1 @@ +/inference-tools-0.11.0.tar.gz diff --git a/python-inference-tools.spec b/python-inference-tools.spec new file mode 100644 index 0000000..e6ec58c --- /dev/null +++ b/python-inference-tools.spec @@ -0,0 +1,206 @@ +%global _empty_manifest_terminate_build 0 +Name: python-inference-tools +Version: 0.11.0 +Release: 1 +Summary: A collection of python tools for Bayesian data analysis +License: MIT +URL: https://github.com/C-bowman/inference-tools +Source0: https://mirrors.aliyun.com/pypi/web/packages/f4/34/4666a4890a09786c4be51e2c6ce631942cd0db760666e14425214bea6fee/inference-tools-0.11.0.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-matplotlib +Requires: python3-importlib-metadata +Requires: python3-sphinx +Requires: python3-sphinx-rtd-theme +Requires: python3-pytest +Requires: python3-pytest-cov +Requires: python3-pyqt5 +Requires: python3-hypothesis +Requires: python3-freezegun + +%description +# inference-tools + +[](https://inference-tools.readthedocs.io/en/stable/?badge=stable) +[](https://github.com/C-bowman/inference-tools/blob/master/LICENSE) +[](https://pypi.org/project/inference-tools/) + +[](https://zenodo.org/badge/latestdoi/149741362) + +This package provides a set of Python-based tools for Bayesian data analysis +which are simple to use, allowing them to applied quickly and easily. + +Inference-tools is not a framework for Bayesian modelling (e.g. like [PyMC](https://docs.pymc.io/)), +but instead provides tools to sample from user-defined models using MCMC, and to analyse and visualise +the sampling results. + +## Features + + - Implementations of MCMC algorithms like Gibbs sampling and Hamiltonian Monte-Carlo for + sampling from user-defined posterior distributions. + + - Density estimation and plotting tools for analysing and visualising inference results. + + - Gaussian-process regression and optimisation. + + +| | | | +|:-------------------------:|:-------------------------:|:-------------------------:| +| [Gibbs Sampling](https://github.com/C-bowman/inference-tools/blob/master/demos/gibbs_sampling_demo.ipynb) <img width="1604" alt="1" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_gibbs_sampling.png"> | [Hamiltonian Monte-Carlo](https://github.com/C-bowman/inference-tools/blob/master/demos/hamiltonian_mcmc_demo.ipynb) <img width="1604" alt="2" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_hmc.png"> | [Density estimation](https://github.com/C-bowman/inference-tools/blob/master/demos/density_estimation_demo.ipynb) <img width="1604" alt="3" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_density_estimation.png"> | +| Matrix plotting <img width="1604" alt="4" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/getting_started_images/matrix_plot_example.png"> | Highest-density intervals <img width="1604" alt="5" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_hdi.png"> | [GP regression](https://github.com/C-bowman/inference-tools/blob/master/demos/gp_regression_demo.ipynb) <img width="1604" alt="6" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_gpr.png"> | + +## Installation + +inference-tools is available from [PyPI](https://pypi.org/project/inference-tools/), +so can be easily installed using [pip](https://pip.pypa.io/en/stable/) as follows: +```bash +pip install inference-tools +``` + +## Documentation + +Full documentation is available at [inference-tools.readthedocs.io](https://inference-tools.readthedocs.io/en/stable/). + + +%package -n python3-inference-tools +Summary: A collection of python tools for Bayesian data analysis +Provides: python-inference-tools +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-inference-tools +# inference-tools + +[](https://inference-tools.readthedocs.io/en/stable/?badge=stable) +[](https://github.com/C-bowman/inference-tools/blob/master/LICENSE) +[](https://pypi.org/project/inference-tools/) + +[](https://zenodo.org/badge/latestdoi/149741362) + +This package provides a set of Python-based tools for Bayesian data analysis +which are simple to use, allowing them to applied quickly and easily. + +Inference-tools is not a framework for Bayesian modelling (e.g. like [PyMC](https://docs.pymc.io/)), +but instead provides tools to sample from user-defined models using MCMC, and to analyse and visualise +the sampling results. + +## Features + + - Implementations of MCMC algorithms like Gibbs sampling and Hamiltonian Monte-Carlo for + sampling from user-defined posterior distributions. + + - Density estimation and plotting tools for analysing and visualising inference results. + + - Gaussian-process regression and optimisation. + + +| | | | +|:-------------------------:|:-------------------------:|:-------------------------:| +| [Gibbs Sampling](https://github.com/C-bowman/inference-tools/blob/master/demos/gibbs_sampling_demo.ipynb) <img width="1604" alt="1" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_gibbs_sampling.png"> | [Hamiltonian Monte-Carlo](https://github.com/C-bowman/inference-tools/blob/master/demos/hamiltonian_mcmc_demo.ipynb) <img width="1604" alt="2" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_hmc.png"> | [Density estimation](https://github.com/C-bowman/inference-tools/blob/master/demos/density_estimation_demo.ipynb) <img width="1604" alt="3" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_density_estimation.png"> | +| Matrix plotting <img width="1604" alt="4" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/getting_started_images/matrix_plot_example.png"> | Highest-density intervals <img width="1604" alt="5" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_hdi.png"> | [GP regression](https://github.com/C-bowman/inference-tools/blob/master/demos/gp_regression_demo.ipynb) <img width="1604" alt="6" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_gpr.png"> | + +## Installation + +inference-tools is available from [PyPI](https://pypi.org/project/inference-tools/), +so can be easily installed using [pip](https://pip.pypa.io/en/stable/) as follows: +```bash +pip install inference-tools +``` + +## Documentation + +Full documentation is available at [inference-tools.readthedocs.io](https://inference-tools.readthedocs.io/en/stable/). + + +%package help +Summary: Development documents and examples for inference-tools +Provides: python3-inference-tools-doc +%description help +# inference-tools + +[](https://inference-tools.readthedocs.io/en/stable/?badge=stable) +[](https://github.com/C-bowman/inference-tools/blob/master/LICENSE) +[](https://pypi.org/project/inference-tools/) + +[](https://zenodo.org/badge/latestdoi/149741362) + +This package provides a set of Python-based tools for Bayesian data analysis +which are simple to use, allowing them to applied quickly and easily. + +Inference-tools is not a framework for Bayesian modelling (e.g. like [PyMC](https://docs.pymc.io/)), +but instead provides tools to sample from user-defined models using MCMC, and to analyse and visualise +the sampling results. + +## Features + + - Implementations of MCMC algorithms like Gibbs sampling and Hamiltonian Monte-Carlo for + sampling from user-defined posterior distributions. + + - Density estimation and plotting tools for analysing and visualising inference results. + + - Gaussian-process regression and optimisation. + + +| | | | +|:-------------------------:|:-------------------------:|:-------------------------:| +| [Gibbs Sampling](https://github.com/C-bowman/inference-tools/blob/master/demos/gibbs_sampling_demo.ipynb) <img width="1604" alt="1" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_gibbs_sampling.png"> | [Hamiltonian Monte-Carlo](https://github.com/C-bowman/inference-tools/blob/master/demos/hamiltonian_mcmc_demo.ipynb) <img width="1604" alt="2" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_hmc.png"> | [Density estimation](https://github.com/C-bowman/inference-tools/blob/master/demos/density_estimation_demo.ipynb) <img width="1604" alt="3" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_density_estimation.png"> | +| Matrix plotting <img width="1604" alt="4" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/getting_started_images/matrix_plot_example.png"> | Highest-density intervals <img width="1604" alt="5" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_hdi.png"> | [GP regression](https://github.com/C-bowman/inference-tools/blob/master/demos/gp_regression_demo.ipynb) <img width="1604" alt="6" src="https://raw.githubusercontent.com/C-bowman/inference-tools/master/docs/source/images/gallery_images/gallery_gpr.png"> | + +## Installation + +inference-tools is available from [PyPI](https://pypi.org/project/inference-tools/), +so can be easily installed using [pip](https://pip.pypa.io/en/stable/) as follows: +```bash +pip install inference-tools +``` + +## Documentation + +Full documentation is available at [inference-tools.readthedocs.io](https://inference-tools.readthedocs.io/en/stable/). + + +%prep +%autosetup -n inference-tools-0.11.0 + +%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-inference-tools -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.11.0-1 +- Package Spec generated @@ -0,0 +1 @@ +86010fc4d1f8a5e4d2bcca6e4ae8db9a inference-tools-0.11.0.tar.gz |