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@@ -0,0 +1 @@ +/BMI500caonia-2.0.0.tar.gz diff --git a/python-bmi500caonia.spec b/python-bmi500caonia.spec new file mode 100644 index 0000000..a0ca682 --- /dev/null +++ b/python-bmi500caonia.spec @@ -0,0 +1,164 @@ +%global _empty_manifest_terminate_build 0 +Name: python-BMI500caonia +Version: 2.0.0 +Release: 1 +Summary: BMI500 HW4 +License: MIT License +URL: https://github.com/shaoyanpan/BMI500-HW4 +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/35/d7/c2b35fc365a85f6b4cd09937dfe9c41e8f52e45574121747edf0077dc6a5/BMI500caonia-2.0.0.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-matplotlib +Requires: python3-pandas +Requires: python3-scipy +Requires: python3-check-manifest + +%description +# The Kmeans unsupervised clustering package + +# Contents +This package is an example Kmeans' package for BMI500's project in Emory University. The package will automatically download the iris data collected from UCI. The dataset contains three classes of flowers, and the clustering algorithm is to seperate each group of the flowers. It does not necessary tell you what kind of flower is, but will tell you which flowers are in a same group. + +# FAQ + +## How to install? + +In your command line, type "pip install BMI500caonia" + +## How to use + +python + +from BMI500caonia import BMI500clustering + +BMI500clustering.Kmeans_run(n, iteration, random_state) + +(n is the number of clusters, iteration is the number of iteration, random_state is the number of random initializations) + +## Running time and hardware requirement + +The running time is 14 seconds in Titan'x 12 GB gpu and Intel Iris 16 GB cpu. + +## Future work + +The function should be modified to be more flexible in the future, so the user can customize parameters. + + + +%package -n python3-BMI500caonia +Summary: BMI500 HW4 +Provides: python-BMI500caonia +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-BMI500caonia +# The Kmeans unsupervised clustering package + +# Contents +This package is an example Kmeans' package for BMI500's project in Emory University. The package will automatically download the iris data collected from UCI. The dataset contains three classes of flowers, and the clustering algorithm is to seperate each group of the flowers. It does not necessary tell you what kind of flower is, but will tell you which flowers are in a same group. + +# FAQ + +## How to install? + +In your command line, type "pip install BMI500caonia" + +## How to use + +python + +from BMI500caonia import BMI500clustering + +BMI500clustering.Kmeans_run(n, iteration, random_state) + +(n is the number of clusters, iteration is the number of iteration, random_state is the number of random initializations) + +## Running time and hardware requirement + +The running time is 14 seconds in Titan'x 12 GB gpu and Intel Iris 16 GB cpu. + +## Future work + +The function should be modified to be more flexible in the future, so the user can customize parameters. + + + +%package help +Summary: Development documents and examples for BMI500caonia +Provides: python3-BMI500caonia-doc +%description help +# The Kmeans unsupervised clustering package + +# Contents +This package is an example Kmeans' package for BMI500's project in Emory University. The package will automatically download the iris data collected from UCI. The dataset contains three classes of flowers, and the clustering algorithm is to seperate each group of the flowers. It does not necessary tell you what kind of flower is, but will tell you which flowers are in a same group. + +# FAQ + +## How to install? + +In your command line, type "pip install BMI500caonia" + +## How to use + +python + +from BMI500caonia import BMI500clustering + +BMI500clustering.Kmeans_run(n, iteration, random_state) + +(n is the number of clusters, iteration is the number of iteration, random_state is the number of random initializations) + +## Running time and hardware requirement + +The running time is 14 seconds in Titan'x 12 GB gpu and Intel Iris 16 GB cpu. + +## Future work + +The function should be modified to be more flexible in the future, so the user can customize parameters. + + + +%prep +%autosetup -n BMI500caonia-2.0.0 + +%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-BMI500caonia -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 2.0.0-1 +- Package Spec generated @@ -0,0 +1 @@ +13d28b2c350a24558f97e59e054ade11 BMI500caonia-2.0.0.tar.gz |