automatic import of python-pyodesysopeneuler20.03

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+%global _empty_manifest_terminate_build 0
+Name:		python-pyodesys
+Version:	0.14.2
+Release:	1
+Summary:	Straightforward numerical integration of ODE systems from Python.
+License:	BSD
+URL:		https://github.com/bjodah/pyodesys
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/dc/4e/227dbb03fa5c305ff18c8ce29cd12cbdca01ea786e218a33f8b59adda818/pyodesys-0.14.2.tar.gz
+BuildArch:	noarch
+
+
+%description
+``pyodesys`` provides a straightforward way
+of numerically integrating systems of ordinary differential equations (initial value problems).
+It unifies the interface of several libraries for performing the numerical integration as well as
+several libraries for symbolic representation. It also provides a convenience class for 
+representing and integrating ODE systems defined by symbolic expressions, e.g. `SymPy <http://www.sympy.org>`_
+expressions. This allows the user to write concise code and rely on ``pyodesys`` to handle the subtle differences
+between libraries.
+The numerical integration is performed using either:
+- `scipy.integrate.ode <http://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.ode.html>`_
+- pygslodeiv2_
+- pyodeint_
+- pycvodes_
+Note that implicit steppers require a user supplied callback for calculating the Jacobian.
+``pyodesys.SymbolicSys`` derives the Jacobian automatically.
+The symbolic representation is usually in the form of SymPy expressions, but the user may
+choose another symbolic back-end (see `sym <https://github.com/bjodah/sym>`_).
+When performance is of utmost importance, e.g. in model fitting where results are needed
+for a large set of initial conditions and parameters, the user may transparently
+rely on compiled native code (classes in ``pyodesys.native.native_sys`` can generate optimal C++ code).
+The major benefit is that there is no need to manually rewrite the corresponding expressions in another
+programming language.
+
+%package -n python3-pyodesys
+Summary:	Straightforward numerical integration of ODE systems from Python.
+Provides:	python-pyodesys
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-pyodesys
+``pyodesys`` provides a straightforward way
+of numerically integrating systems of ordinary differential equations (initial value problems).
+It unifies the interface of several libraries for performing the numerical integration as well as
+several libraries for symbolic representation. It also provides a convenience class for 
+representing and integrating ODE systems defined by symbolic expressions, e.g. `SymPy <http://www.sympy.org>`_
+expressions. This allows the user to write concise code and rely on ``pyodesys`` to handle the subtle differences
+between libraries.
+The numerical integration is performed using either:
+- `scipy.integrate.ode <http://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.ode.html>`_
+- pygslodeiv2_
+- pyodeint_
+- pycvodes_
+Note that implicit steppers require a user supplied callback for calculating the Jacobian.
+``pyodesys.SymbolicSys`` derives the Jacobian automatically.
+The symbolic representation is usually in the form of SymPy expressions, but the user may
+choose another symbolic back-end (see `sym <https://github.com/bjodah/sym>`_).
+When performance is of utmost importance, e.g. in model fitting where results are needed
+for a large set of initial conditions and parameters, the user may transparently
+rely on compiled native code (classes in ``pyodesys.native.native_sys`` can generate optimal C++ code).
+The major benefit is that there is no need to manually rewrite the corresponding expressions in another
+programming language.
+
+%package help
+Summary:	Development documents and examples for pyodesys
+Provides:	python3-pyodesys-doc
+%description help
+``pyodesys`` provides a straightforward way
+of numerically integrating systems of ordinary differential equations (initial value problems).
+It unifies the interface of several libraries for performing the numerical integration as well as
+several libraries for symbolic representation. It also provides a convenience class for 
+representing and integrating ODE systems defined by symbolic expressions, e.g. `SymPy <http://www.sympy.org>`_
+expressions. This allows the user to write concise code and rely on ``pyodesys`` to handle the subtle differences
+between libraries.
+The numerical integration is performed using either:
+- `scipy.integrate.ode <http://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.ode.html>`_
+- pygslodeiv2_
+- pyodeint_
+- pycvodes_
+Note that implicit steppers require a user supplied callback for calculating the Jacobian.
+``pyodesys.SymbolicSys`` derives the Jacobian automatically.
+The symbolic representation is usually in the form of SymPy expressions, but the user may
+choose another symbolic back-end (see `sym <https://github.com/bjodah/sym>`_).
+When performance is of utmost importance, e.g. in model fitting where results are needed
+for a large set of initial conditions and parameters, the user may transparently
+rely on compiled native code (classes in ``pyodesys.native.native_sys`` can generate optimal C++ code).
+The major benefit is that there is no need to manually rewrite the corresponding expressions in another
+programming language.
+
+%prep
+%autosetup -n pyodesys-0.14.2
+
+%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-pyodesys -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.14.2-1
+- Package Spec generated