%global _empty_manifest_terminate_build 0
Name:		python-FDApy
Version:	0.8.7
Release:	1
Summary:	please add a summary manually as the author left a blank one
License:	MIT
URL:		https://github.com/StevenGolovkine/FDApy
Source0:	https://mirrors.aliyun.com/pypi/web/packages/fa/58/ce9f4cebb3bff6cc026cd2a9239f96fa8248a215e6a6b50ec75b6ec5929b/FDApy-0.8.7.tar.gz
BuildArch:	noarch

Requires:	python3-csaps
Requires:	python3-ggplot
Requires:	python3-numpy
Requires:	python3-pandas
Requires:	python3-patsy
Requires:	python3-pygam
Requires:	python3-scikit-learn
Requires:	python3-scipy

%description
Statistics that deals with discrete observations of continuous d-dimensional
functions.

This package provide modules for the analysis of such data. It includes
methods for different dimensional data as well as irregularly sampled
functional data. An implementation of (multivariate) functional principal
component analysis is also given. Moreover, a simulation toolbox is provided.
It might be used to simulate different clusters of functional data.

Check out the `documentation <https://fdapy.readthedocs.io/en/stable/>`_ for
more complete information on the available features within the package.


%package -n python3-FDApy
Summary:	please add a summary manually as the author left a blank one
Provides:	python-FDApy
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-FDApy
Statistics that deals with discrete observations of continuous d-dimensional
functions.

This package provide modules for the analysis of such data. It includes
methods for different dimensional data as well as irregularly sampled
functional data. An implementation of (multivariate) functional principal
component analysis is also given. Moreover, a simulation toolbox is provided.
It might be used to simulate different clusters of functional data.

Check out the `documentation <https://fdapy.readthedocs.io/en/stable/>`_ for
more complete information on the available features within the package.


%package help
Summary:	Development documents and examples for FDApy
Provides:	python3-FDApy-doc
%description help
Statistics that deals with discrete observations of continuous d-dimensional
functions.

This package provide modules for the analysis of such data. It includes
methods for different dimensional data as well as irregularly sampled
functional data. An implementation of (multivariate) functional principal
component analysis is also given. Moreover, a simulation toolbox is provided.
It might be used to simulate different clusters of functional data.

Check out the `documentation <https://fdapy.readthedocs.io/en/stable/>`_ for
more complete information on the available features within the package.


%prep
%autosetup -n FDApy-0.8.7

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

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

%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.8.7-1
- Package Spec generated