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+%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
+
+[![Documentation Status](https://readthedocs.org/projects/inference-tools/badge/?version=stable)](https://inference-tools.readthedocs.io/en/stable/?badge=stable)
+[![GitHub license](https://img.shields.io/github/license/C-bowman/inference-tools?color=blue)](https://github.com/C-bowman/inference-tools/blob/master/LICENSE)
+[![PyPI - Downloads](https://img.shields.io/pypi/dm/inference-tools?color=purple)](https://pypi.org/project/inference-tools/)
+![PyPI - Python Version](https://img.shields.io/pypi/pyversions/inference-tools)
+[![DOI](https://zenodo.org/badge/149741362.svg)](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
+
+[![Documentation Status](https://readthedocs.org/projects/inference-tools/badge/?version=stable)](https://inference-tools.readthedocs.io/en/stable/?badge=stable)
+[![GitHub license](https://img.shields.io/github/license/C-bowman/inference-tools?color=blue)](https://github.com/C-bowman/inference-tools/blob/master/LICENSE)
+[![PyPI - Downloads](https://img.shields.io/pypi/dm/inference-tools?color=purple)](https://pypi.org/project/inference-tools/)
+![PyPI - Python Version](https://img.shields.io/pypi/pyversions/inference-tools)
+[![DOI](https://zenodo.org/badge/149741362.svg)](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
+
+[![Documentation Status](https://readthedocs.org/projects/inference-tools/badge/?version=stable)](https://inference-tools.readthedocs.io/en/stable/?badge=stable)
+[![GitHub license](https://img.shields.io/github/license/C-bowman/inference-tools?color=blue)](https://github.com/C-bowman/inference-tools/blob/master/LICENSE)
+[![PyPI - Downloads](https://img.shields.io/pypi/dm/inference-tools?color=purple)](https://pypi.org/project/inference-tools/)
+![PyPI - Python Version](https://img.shields.io/pypi/pyversions/inference-tools)
+[![DOI](https://zenodo.org/badge/149741362.svg)](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