%global _empty_manifest_terminate_build 0
Name:		python-dsatools
Version:	0.1.95
Release:	1
Summary:	The library with a most popular tools for Digital Signal Analysis (DSA)
License:	MIT
URL:		https://github.com/MVRonkin/dsatools
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/14/bc/c9eb25de43bb15c492045d651b310c50a3a7b275576c3cf104bc67bb9637/dsatools-0.1.95.tar.gz
BuildArch:	noarch

Requires:	python3-numpy
Requires:	python3-scipy
Requires:	python3-matplotlib

%description

Digital Signal Analysis (DSA) library for python.
The library includes such methods of signal analysis and
signal parameter estimation as arma-based techniques; 
subspace-based techniques; matrix-pencil-based methods; 
singular-spectrum analysis (SSA); dynamic-mode decomposition (DMD); 
empirical mode decomposition; variational mode decomposition; 
empirical wavelet transform; Hilbert vibration decomposition 
and many others.




%package -n python3-dsatools
Summary:	The library with a most popular tools for Digital Signal Analysis (DSA)
Provides:	python-dsatools
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-dsatools

Digital Signal Analysis (DSA) library for python.
The library includes such methods of signal analysis and
signal parameter estimation as arma-based techniques; 
subspace-based techniques; matrix-pencil-based methods; 
singular-spectrum analysis (SSA); dynamic-mode decomposition (DMD); 
empirical mode decomposition; variational mode decomposition; 
empirical wavelet transform; Hilbert vibration decomposition 
and many others.




%package help
Summary:	Development documents and examples for dsatools
Provides:	python3-dsatools-doc
%description help

Digital Signal Analysis (DSA) library for python.
The library includes such methods of signal analysis and
signal parameter estimation as arma-based techniques; 
subspace-based techniques; matrix-pencil-based methods; 
singular-spectrum analysis (SSA); dynamic-mode decomposition (DMD); 
empirical mode decomposition; variational mode decomposition; 
empirical wavelet transform; Hilbert vibration decomposition 
and many others.




%prep
%autosetup -n dsatools-0.1.95

%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-dsatools -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.95-1
- Package Spec generated