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+%global _empty_manifest_terminate_build 0
+Name:		python-fuzzy-c-means
+Version:	1.7.0
+Release:	1
+Summary:	A simple python implementation of Fuzzy C-means algorithm.
+License:	MIT
+URL:		https://github.com/omadson/fuzzy-c-means
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/9e/a1/fe18a9cb3a65fe0fbe2e96ec6acf0753a09fe4d24868f42530f7db5df22d/fuzzy_c_means-1.7.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-joblib
+Requires:	python3-numpy
+Requires:	python3-pydantic
+Requires:	python3-tabulate
+Requires:	python3-tqdm
+Requires:	python3-typer
+
+%description
+# fuzzy-c-means
+
+![GitHub](https://img.shields.io/github/license/omadson/fuzzy-c-means.svg)
+[![PyPI](https://img.shields.io/pypi/v/fuzzy-c-means.svg)](http://pypi.org/project/fuzzy-c-means/)
+[![Documentation Status](https://readthedocs.org/projects/fuzzy-c-means/badge/?version=latest)](https://fuzzy-c-means.readthedocs.io/en/latest/?badge=latest)
+[![GitHub last commit](https://img.shields.io/github/last-commit/omadson/fuzzy-c-means.svg)](https://github.com/omadson/fuzzy-c-means/commit/master)
+[![Downloads](https://pepy.tech/badge/fuzzy-c-means)](https://pepy.tech/project/fuzzy-c-means)
+[![DOI](https://zenodo.org/badge/186457481.svg)](https://zenodo.org/badge/latestdoi/186457481)
+
+
+**[Documentation](https://fuzzy-c-means.readthedocs.io/)** | **[Changelog](https://fuzzy-c-means.readthedocs.io/en/latest/CHANGELOG/)** | **[Citation](https://fuzzy-c-means.readthedocs.io/en/latest/citation/)**
+
+
+
+`fuzzy-c-means` is a Python module implementing the [Fuzzy C-means][1] clustering algorithm.
+
+## installation
+the `fuzzy-c-means` package is available in [PyPI](https://pypi.org/project/fuzzy-c-means/). to install, simply type the following command:
+```
+pip install fuzzy-c-means
+```
+## citation
+if you use `fuzzy-c-means` package in your paper, please cite it in your publication.
+```
+@software{dias2019fuzzy,
+  author       = {Madson Luiz Dantas Dias},
+  title        = {fuzzy-c-means: An implementation of Fuzzy $C$-means clustering algorithm.},
+  month        = may,
+  year         = 2019,
+  publisher    = {Zenodo},
+  doi          = {10.5281/zenodo.3066222},
+  url          = {https://git.io/fuzzy-c-means}
+}
+```
+
+<!-- ### citations
+ - [Gene-Based Clustering Algorithms: Comparison Between Denclue, Fuzzy-C, and BIRCH](https://doi.org/10.1177/1177932220909851)
+ - [Analisis Data Log IDS Snort dengan Algoritma Clustering Fuzzy C-Means](https://doi.org/10.24843/MITE.2020.v19i01.P14)
+ - [Comparative Analysis between the k-means and Fuzzy c-means Algorithms to Detect UDP Flood DDoS Attack on a SDN/NFV Environment](https://doi.org/10.5220/0010176201050112)
+ - [Mixture-of-Experts Variational Autoencoder for Clustering and Generating from Similarity-Based Representations on Single Cell Data](https://arxiv.org/abs/1910.07763)
+ - [Fuzzy Clustering: an Application to Distributional Reinforcement Learning](https://doi.org/10.34726/hss.2021.86783)
+ - [Fuzzy Clustering with Similarity Queries](https://arxiv.org/pdf/2106.02212.pdf)
+ - [Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variants](https://arxiv.org/abs/2110.09622)
+ - [Unsupervised clustering-based spectral analysis of bio-dyed textile samples](http://urn.fi/urn:nbn:fi:uef-20211291) -->
+
+
+## contributing and support
+
+this project is open for contributions. here are some of the ways for you to contribute:
+ - bug reports/fix
+ - features requests
+ - use-case demonstrations
+
+please open an [issue](https://github.com/omadson/fuzzy-c-means/issues) with enough information for us to reproduce your problem. A [minimal, reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) would be very helpful.
+
+to make a contribution, just fork this repository, push the changes in your fork, open up an issue, and make a pull request!
+
+<!-- ## contributors
+ - [Madson Dias](https://github.com/omadson)
+ - [Dirk Nachbar](https://github.com/dirknbr)
+ - [Alberth Florêncio](https://github.com/zealberth) -->
+
+[1]: https://doi.org/10.1016/0098-3004(84)90020-7
+[2]: http://scikit-learn.org/
+
+
+
+%package -n python3-fuzzy-c-means
+Summary:	A simple python implementation of Fuzzy C-means algorithm.
+Provides:	python-fuzzy-c-means
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-fuzzy-c-means
+# fuzzy-c-means
+
+![GitHub](https://img.shields.io/github/license/omadson/fuzzy-c-means.svg)
+[![PyPI](https://img.shields.io/pypi/v/fuzzy-c-means.svg)](http://pypi.org/project/fuzzy-c-means/)
+[![Documentation Status](https://readthedocs.org/projects/fuzzy-c-means/badge/?version=latest)](https://fuzzy-c-means.readthedocs.io/en/latest/?badge=latest)
+[![GitHub last commit](https://img.shields.io/github/last-commit/omadson/fuzzy-c-means.svg)](https://github.com/omadson/fuzzy-c-means/commit/master)
+[![Downloads](https://pepy.tech/badge/fuzzy-c-means)](https://pepy.tech/project/fuzzy-c-means)
+[![DOI](https://zenodo.org/badge/186457481.svg)](https://zenodo.org/badge/latestdoi/186457481)
+
+
+**[Documentation](https://fuzzy-c-means.readthedocs.io/)** | **[Changelog](https://fuzzy-c-means.readthedocs.io/en/latest/CHANGELOG/)** | **[Citation](https://fuzzy-c-means.readthedocs.io/en/latest/citation/)**
+
+
+
+`fuzzy-c-means` is a Python module implementing the [Fuzzy C-means][1] clustering algorithm.
+
+## installation
+the `fuzzy-c-means` package is available in [PyPI](https://pypi.org/project/fuzzy-c-means/). to install, simply type the following command:
+```
+pip install fuzzy-c-means
+```
+## citation
+if you use `fuzzy-c-means` package in your paper, please cite it in your publication.
+```
+@software{dias2019fuzzy,
+  author       = {Madson Luiz Dantas Dias},
+  title        = {fuzzy-c-means: An implementation of Fuzzy $C$-means clustering algorithm.},
+  month        = may,
+  year         = 2019,
+  publisher    = {Zenodo},
+  doi          = {10.5281/zenodo.3066222},
+  url          = {https://git.io/fuzzy-c-means}
+}
+```
+
+<!-- ### citations
+ - [Gene-Based Clustering Algorithms: Comparison Between Denclue, Fuzzy-C, and BIRCH](https://doi.org/10.1177/1177932220909851)
+ - [Analisis Data Log IDS Snort dengan Algoritma Clustering Fuzzy C-Means](https://doi.org/10.24843/MITE.2020.v19i01.P14)
+ - [Comparative Analysis between the k-means and Fuzzy c-means Algorithms to Detect UDP Flood DDoS Attack on a SDN/NFV Environment](https://doi.org/10.5220/0010176201050112)
+ - [Mixture-of-Experts Variational Autoencoder for Clustering and Generating from Similarity-Based Representations on Single Cell Data](https://arxiv.org/abs/1910.07763)
+ - [Fuzzy Clustering: an Application to Distributional Reinforcement Learning](https://doi.org/10.34726/hss.2021.86783)
+ - [Fuzzy Clustering with Similarity Queries](https://arxiv.org/pdf/2106.02212.pdf)
+ - [Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variants](https://arxiv.org/abs/2110.09622)
+ - [Unsupervised clustering-based spectral analysis of bio-dyed textile samples](http://urn.fi/urn:nbn:fi:uef-20211291) -->
+
+
+## contributing and support
+
+this project is open for contributions. here are some of the ways for you to contribute:
+ - bug reports/fix
+ - features requests
+ - use-case demonstrations
+
+please open an [issue](https://github.com/omadson/fuzzy-c-means/issues) with enough information for us to reproduce your problem. A [minimal, reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) would be very helpful.
+
+to make a contribution, just fork this repository, push the changes in your fork, open up an issue, and make a pull request!
+
+<!-- ## contributors
+ - [Madson Dias](https://github.com/omadson)
+ - [Dirk Nachbar](https://github.com/dirknbr)
+ - [Alberth Florêncio](https://github.com/zealberth) -->
+
+[1]: https://doi.org/10.1016/0098-3004(84)90020-7
+[2]: http://scikit-learn.org/
+
+
+
+%package help
+Summary:	Development documents and examples for fuzzy-c-means
+Provides:	python3-fuzzy-c-means-doc
+%description help
+# fuzzy-c-means
+
+![GitHub](https://img.shields.io/github/license/omadson/fuzzy-c-means.svg)
+[![PyPI](https://img.shields.io/pypi/v/fuzzy-c-means.svg)](http://pypi.org/project/fuzzy-c-means/)
+[![Documentation Status](https://readthedocs.org/projects/fuzzy-c-means/badge/?version=latest)](https://fuzzy-c-means.readthedocs.io/en/latest/?badge=latest)
+[![GitHub last commit](https://img.shields.io/github/last-commit/omadson/fuzzy-c-means.svg)](https://github.com/omadson/fuzzy-c-means/commit/master)
+[![Downloads](https://pepy.tech/badge/fuzzy-c-means)](https://pepy.tech/project/fuzzy-c-means)
+[![DOI](https://zenodo.org/badge/186457481.svg)](https://zenodo.org/badge/latestdoi/186457481)
+
+
+**[Documentation](https://fuzzy-c-means.readthedocs.io/)** | **[Changelog](https://fuzzy-c-means.readthedocs.io/en/latest/CHANGELOG/)** | **[Citation](https://fuzzy-c-means.readthedocs.io/en/latest/citation/)**
+
+
+
+`fuzzy-c-means` is a Python module implementing the [Fuzzy C-means][1] clustering algorithm.
+
+## installation
+the `fuzzy-c-means` package is available in [PyPI](https://pypi.org/project/fuzzy-c-means/). to install, simply type the following command:
+```
+pip install fuzzy-c-means
+```
+## citation
+if you use `fuzzy-c-means` package in your paper, please cite it in your publication.
+```
+@software{dias2019fuzzy,
+  author       = {Madson Luiz Dantas Dias},
+  title        = {fuzzy-c-means: An implementation of Fuzzy $C$-means clustering algorithm.},
+  month        = may,
+  year         = 2019,
+  publisher    = {Zenodo},
+  doi          = {10.5281/zenodo.3066222},
+  url          = {https://git.io/fuzzy-c-means}
+}
+```
+
+<!-- ### citations
+ - [Gene-Based Clustering Algorithms: Comparison Between Denclue, Fuzzy-C, and BIRCH](https://doi.org/10.1177/1177932220909851)
+ - [Analisis Data Log IDS Snort dengan Algoritma Clustering Fuzzy C-Means](https://doi.org/10.24843/MITE.2020.v19i01.P14)
+ - [Comparative Analysis between the k-means and Fuzzy c-means Algorithms to Detect UDP Flood DDoS Attack on a SDN/NFV Environment](https://doi.org/10.5220/0010176201050112)
+ - [Mixture-of-Experts Variational Autoencoder for Clustering and Generating from Similarity-Based Representations on Single Cell Data](https://arxiv.org/abs/1910.07763)
+ - [Fuzzy Clustering: an Application to Distributional Reinforcement Learning](https://doi.org/10.34726/hss.2021.86783)
+ - [Fuzzy Clustering with Similarity Queries](https://arxiv.org/pdf/2106.02212.pdf)
+ - [Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variants](https://arxiv.org/abs/2110.09622)
+ - [Unsupervised clustering-based spectral analysis of bio-dyed textile samples](http://urn.fi/urn:nbn:fi:uef-20211291) -->
+
+
+## contributing and support
+
+this project is open for contributions. here are some of the ways for you to contribute:
+ - bug reports/fix
+ - features requests
+ - use-case demonstrations
+
+please open an [issue](https://github.com/omadson/fuzzy-c-means/issues) with enough information for us to reproduce your problem. A [minimal, reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) would be very helpful.
+
+to make a contribution, just fork this repository, push the changes in your fork, open up an issue, and make a pull request!
+
+<!-- ## contributors
+ - [Madson Dias](https://github.com/omadson)
+ - [Dirk Nachbar](https://github.com/dirknbr)
+ - [Alberth Florêncio](https://github.com/zealberth) -->
+
+[1]: https://doi.org/10.1016/0098-3004(84)90020-7
+[2]: http://scikit-learn.org/
+
+
+
+%prep
+%autosetup -n fuzzy-c-means-1.7.0
+
+%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-fuzzy-c-means -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.7.0-1
+- Package Spec generated