automatic import of python-cuda-guass-normalopeneuler20.03

3 files changed, 158 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
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+/cuda_guass_normal-1.13.tar.gz
diff --git a/python-cuda-guass-normal.spec b/python-cuda-guass-normal.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-cuda-guass-normal
+Version:	1.13
+Release:	1
+Summary:	A package used in DNN trainning in ATLAS analysis
+License:	MIT
+URL:		https://pypi.org/project/cuda-guass-normal/
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/bc/a0/9cd5883f14f949a0a8d2103d8ae811af0b41de3e54501de22f7c720cf32b/cuda_guass_normal-1.13.tar.gz
+BuildArch:	noarch
+
+
+%description
+Python package use cuda to normalize input variables using cuda package in ATLAS analysis
+
+Function use to do Guassian Normalization:
+Mean:
+$$\mu_{i}=\frac{\sum x_{i}\times w_{i}}{\sum w_{i}}$$
+Variance:
+$$\sigma_{i}=\frac{\sum (x_{i}-\mu_{i})^{2}\times w_{i}}{\frac{N-1}{N}\times\sum w_{i}}$$
+Normalized input feature:
+$$\bar{x_{i}}=\frac{x_{i}-\mu_{i}}{\sigma_{i}}$$
+
+Main function: guass_normal((1),(2),(3))
+
+Input:
+
+(1):Numpy array contain all input features you want to normalize.
+(2):Numpy array used to calculate each feature's mean and variance.
+(3):1-d Numpy array contains each events weight in (2)
+
+(1) and (2) must have the same number of columns.
+
+cuda_cut((1),(2),(3)): Used to calculate event yield after applying DNN cut.
+
+Input:
+(1): 1-d numpy array include the variable  you want to cut.
+(2): 1-d numpy array include event weight.
+(3): cut threshold 
+
+
+
+
+%package -n python3-cuda-guass-normal
+Summary:	A package used in DNN trainning in ATLAS analysis
+Provides:	python-cuda-guass-normal
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-cuda-guass-normal
+Python package use cuda to normalize input variables using cuda package in ATLAS analysis
+
+Function use to do Guassian Normalization:
+Mean:
+$$\mu_{i}=\frac{\sum x_{i}\times w_{i}}{\sum w_{i}}$$
+Variance:
+$$\sigma_{i}=\frac{\sum (x_{i}-\mu_{i})^{2}\times w_{i}}{\frac{N-1}{N}\times\sum w_{i}}$$
+Normalized input feature:
+$$\bar{x_{i}}=\frac{x_{i}-\mu_{i}}{\sigma_{i}}$$
+
+Main function: guass_normal((1),(2),(3))
+
+Input:
+
+(1):Numpy array contain all input features you want to normalize.
+(2):Numpy array used to calculate each feature's mean and variance.
+(3):1-d Numpy array contains each events weight in (2)
+
+(1) and (2) must have the same number of columns.
+
+cuda_cut((1),(2),(3)): Used to calculate event yield after applying DNN cut.
+
+Input:
+(1): 1-d numpy array include the variable  you want to cut.
+(2): 1-d numpy array include event weight.
+(3): cut threshold 
+
+
+
+
+%package help
+Summary:	Development documents and examples for cuda-guass-normal
+Provides:	python3-cuda-guass-normal-doc
+%description help
+Python package use cuda to normalize input variables using cuda package in ATLAS analysis
+
+Function use to do Guassian Normalization:
+Mean:
+$$\mu_{i}=\frac{\sum x_{i}\times w_{i}}{\sum w_{i}}$$
+Variance:
+$$\sigma_{i}=\frac{\sum (x_{i}-\mu_{i})^{2}\times w_{i}}{\frac{N-1}{N}\times\sum w_{i}}$$
+Normalized input feature:
+$$\bar{x_{i}}=\frac{x_{i}-\mu_{i}}{\sigma_{i}}$$
+
+Main function: guass_normal((1),(2),(3))
+
+Input:
+
+(1):Numpy array contain all input features you want to normalize.
+(2):Numpy array used to calculate each feature's mean and variance.
+(3):1-d Numpy array contains each events weight in (2)
+
+(1) and (2) must have the same number of columns.
+
+cuda_cut((1),(2),(3)): Used to calculate event yield after applying DNN cut.
+
+Input:
+(1): 1-d numpy array include the variable  you want to cut.
+(2): 1-d numpy array include event weight.
+(3): cut threshold 
+
+
+
+
+%prep
+%autosetup -n cuda_guass_normal-1.13
+
+%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-cuda-guass-normal -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.13-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..ad00491
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+6df7586816e23477d7351b4c211cbccf  cuda_guass_normal-1.13.tar.gz