diff options
Diffstat (limited to 'python-fuzzy-c-means.spec')
| -rw-r--r-- | python-fuzzy-c-means.spec | 273 |
1 files changed, 273 insertions, 0 deletions
diff --git a/python-fuzzy-c-means.spec b/python-fuzzy-c-means.spec new file mode 100644 index 0000000..8a1063a --- /dev/null +++ b/python-fuzzy-c-means.spec @@ -0,0 +1,273 @@ +%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 + + +[](http://pypi.org/project/fuzzy-c-means/) +[](https://fuzzy-c-means.readthedocs.io/en/latest/?badge=latest) +[](https://github.com/omadson/fuzzy-c-means/commit/master) +[](https://pepy.tech/project/fuzzy-c-means) +[](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 + + +[](http://pypi.org/project/fuzzy-c-means/) +[](https://fuzzy-c-means.readthedocs.io/en/latest/?badge=latest) +[](https://github.com/omadson/fuzzy-c-means/commit/master) +[](https://pepy.tech/project/fuzzy-c-means) +[](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 + + +[](http://pypi.org/project/fuzzy-c-means/) +[](https://fuzzy-c-means.readthedocs.io/en/latest/?badge=latest) +[](https://github.com/omadson/fuzzy-c-means/commit/master) +[](https://pepy.tech/project/fuzzy-c-means) +[](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 |