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%global _empty_manifest_terminate_build 0
Name: python-SWaN-accel
Version: 1.18
Release: 1
Summary: A pacakge to classify sleep-wear, wake-wear, and non-wear in accelerometer dataset.
License: MIT License
URL: https://bitbucket.org/mhealthresearchgroup/packageswanfortime.git
Source0: https://mirrors.aliyun.com/pypi/web/packages/41/30/3ad99aee8cc05f9499bb2565d04dbdca154b2dd9076f54117c5a4df7f344/SWaN_accel-1.18.tar.gz
BuildArch: noarch
Requires: python3-scikit-learn
%description
# SWaN_accel package
This is an algorithm to distinguish between sleep-wear, wake-wear, and non-wear in accelerometer dataset.
To install the package, use the following pip command:
### pip install swan_accel
To import the two relevant methods from the package, type:
### from SWaN_accel import swan_first_pass, swan_second_pass
To run swan first pass algorithm:
### swan_first_pass.main(df=dataframe object, file_path=path for output file,sampling_rate=sampling rate of data)
To run swan second pass algorithm
### swan_second_pass.main(day_folder=path of the date folder, debug="No")
%package -n python3-SWaN-accel
Summary: A pacakge to classify sleep-wear, wake-wear, and non-wear in accelerometer dataset.
Provides: python-SWaN-accel
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-SWaN-accel
# SWaN_accel package
This is an algorithm to distinguish between sleep-wear, wake-wear, and non-wear in accelerometer dataset.
To install the package, use the following pip command:
### pip install swan_accel
To import the two relevant methods from the package, type:
### from SWaN_accel import swan_first_pass, swan_second_pass
To run swan first pass algorithm:
### swan_first_pass.main(df=dataframe object, file_path=path for output file,sampling_rate=sampling rate of data)
To run swan second pass algorithm
### swan_second_pass.main(day_folder=path of the date folder, debug="No")
%package help
Summary: Development documents and examples for SWaN-accel
Provides: python3-SWaN-accel-doc
%description help
# SWaN_accel package
This is an algorithm to distinguish between sleep-wear, wake-wear, and non-wear in accelerometer dataset.
To install the package, use the following pip command:
### pip install swan_accel
To import the two relevant methods from the package, type:
### from SWaN_accel import swan_first_pass, swan_second_pass
To run swan first pass algorithm:
### swan_first_pass.main(df=dataframe object, file_path=path for output file,sampling_rate=sampling rate of data)
To run swan second pass algorithm
### swan_second_pass.main(day_folder=path of the date folder, debug="No")
%prep
%autosetup -n SWaN_accel-1.18
%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-SWaN-accel -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.18-1
- Package Spec generated
|
