diff options
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-pynn.spec | 155 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 157 insertions, 0 deletions
@@ -0,0 +1 @@ +/PyNN-0.11.0.tar.gz diff --git a/python-pynn.spec b/python-pynn.spec new file mode 100644 index 0000000..68ef59d --- /dev/null +++ b/python-pynn.spec @@ -0,0 +1,155 @@ +%global _empty_manifest_terminate_build 0 +Name: python-PyNN +Version: 0.11.0 +Release: 1 +Summary: A Python package for simulator-independent specification of neuronal network models +License: CeCILL http://www.cecill.info +URL: https://pypi.org/project/PyNN/ +Source0: https://mirrors.aliyun.com/pypi/web/packages/5e/55/4a904b95ecb1c50e716e0ba48e0918daf522c9c6bac5b75e0c08c1030217/PyNN-0.11.0.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-lazyarray +Requires: python3-neo +Requires: python3-quantities +Requires: python3-mpi4py +Requires: python3-brian2 +Requires: python3-sphinx +Requires: python3-matplotlib +Requires: python3-scipy +Requires: python3-neuron +Requires: python3-matplotlib +Requires: python3-scipy +Requires: python3-h5py +Requires: python3-pytest +Requires: python3-wheel +Requires: python3-mpi4py +Requires: python3-scipy +Requires: python3-matplotlib +Requires: python3-Cheetah3 +Requires: python3-h5py + +%description +PyNN (pronounced '*pine*') is a simulator-independent language for building +neuronal network models. +In other words, you can write the code for a model once, using the PyNN API and +the Python programming language, and then run it without modification on any +simulator that PyNN supports (currently NEURON, NEST and Brian 2) and +on a number of neuromorphic hardware systems. +The PyNN API aims to support modelling at a high-level of abstraction +(populations of neurons, layers, columns and the connections between them) while +still allowing access to the details of individual neurons and synapses when +required. PyNN provides a library of standard neuron, synapse and synaptic +plasticity models, which have been verified to work the same on the different +supported simulators. PyNN also provides a set of commonly-used connectivity +algorithms (e.g. all-to-all, random, distance-dependent, small-world) but makes +it easy to provide your own connectivity in a simulator-independent way. +Even if you don't wish to run simulations on multiple simulators, you may +benefit from writing your simulation code using PyNN's powerful, high-level +interface. In this case, you can use any neuron or synapse model supported by +your simulator, and are not restricted to the standard models. +- Home page: http://neuralensemble.org/PyNN/ +- Documentation: http://neuralensemble.org/docs/PyNN/ +- Mailing list: https://groups.google.com/forum/?fromgroups#!forum/neuralensemble +- Bug reports: https://github.com/NeuralEnsemble/PyNN/issues + +%package -n python3-PyNN +Summary: A Python package for simulator-independent specification of neuronal network models +Provides: python-PyNN +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-PyNN +PyNN (pronounced '*pine*') is a simulator-independent language for building +neuronal network models. +In other words, you can write the code for a model once, using the PyNN API and +the Python programming language, and then run it without modification on any +simulator that PyNN supports (currently NEURON, NEST and Brian 2) and +on a number of neuromorphic hardware systems. +The PyNN API aims to support modelling at a high-level of abstraction +(populations of neurons, layers, columns and the connections between them) while +still allowing access to the details of individual neurons and synapses when +required. PyNN provides a library of standard neuron, synapse and synaptic +plasticity models, which have been verified to work the same on the different +supported simulators. PyNN also provides a set of commonly-used connectivity +algorithms (e.g. all-to-all, random, distance-dependent, small-world) but makes +it easy to provide your own connectivity in a simulator-independent way. +Even if you don't wish to run simulations on multiple simulators, you may +benefit from writing your simulation code using PyNN's powerful, high-level +interface. In this case, you can use any neuron or synapse model supported by +your simulator, and are not restricted to the standard models. +- Home page: http://neuralensemble.org/PyNN/ +- Documentation: http://neuralensemble.org/docs/PyNN/ +- Mailing list: https://groups.google.com/forum/?fromgroups#!forum/neuralensemble +- Bug reports: https://github.com/NeuralEnsemble/PyNN/issues + +%package help +Summary: Development documents and examples for PyNN +Provides: python3-PyNN-doc +%description help +PyNN (pronounced '*pine*') is a simulator-independent language for building +neuronal network models. +In other words, you can write the code for a model once, using the PyNN API and +the Python programming language, and then run it without modification on any +simulator that PyNN supports (currently NEURON, NEST and Brian 2) and +on a number of neuromorphic hardware systems. +The PyNN API aims to support modelling at a high-level of abstraction +(populations of neurons, layers, columns and the connections between them) while +still allowing access to the details of individual neurons and synapses when +required. PyNN provides a library of standard neuron, synapse and synaptic +plasticity models, which have been verified to work the same on the different +supported simulators. PyNN also provides a set of commonly-used connectivity +algorithms (e.g. all-to-all, random, distance-dependent, small-world) but makes +it easy to provide your own connectivity in a simulator-independent way. +Even if you don't wish to run simulations on multiple simulators, you may +benefit from writing your simulation code using PyNN's powerful, high-level +interface. In this case, you can use any neuron or synapse model supported by +your simulator, and are not restricted to the standard models. +- Home page: http://neuralensemble.org/PyNN/ +- Documentation: http://neuralensemble.org/docs/PyNN/ +- Mailing list: https://groups.google.com/forum/?fromgroups#!forum/neuralensemble +- Bug reports: https://github.com/NeuralEnsemble/PyNN/issues + +%prep +%autosetup -n PyNN-0.11.0 + +%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-PyNN -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.11.0-1 +- Package Spec generated @@ -0,0 +1 @@ +c890ff667d28843caf95fa1115552e01 PyNN-0.11.0.tar.gz |