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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
|
