https://github.com/NeuralEnsemble/PyNN

A Python package for simulator-independent specification of neuronal network models.
https://github.com/NeuralEnsemble/PyNN

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A Python package for simulator-independent specification of neuronal network models.

• Host: GitHub
• URL: https://github.com/NeuralEnsemble/PyNN
• Owner: NeuralEnsemble
• License: other
• Created: 2013-05-17T07:50:05.000Z (over 11 years ago)
• Default Branch: master
• Last Pushed: 2024-07-25T09:06:48.000Z (4 months ago)
• Last Synced: 2024-11-07T18:56:48.389Z (2 days ago)
• Language: Python
• Size: 21.6 MB
• Stars: 277
• Watchers: 26
• Forks: 126
• Open Issues: 130
• Metadata Files:
  • Readme: README.rst
  • Changelog: changelog
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Authors: AUTHORS
  • Codemeta: codemeta.json

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README

        
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

:copyright: Copyright 2006-2024 by the PyNN team, see AUTHORS.

:license: CeCILL, see LICENSE for details.

.. image:: https://github.com/NeuralEnsemble/PyNN/actions/workflows/full-test.yml/badge.svg

   :target: https://github.com/NeuralEnsemble/PyNN/actions/workflows/full-test.yml

   :alt: Unit Test Status

.. image:: https://coveralls.io/repos/NeuralEnsemble/PyNN/badge.svg?branch=master&service=github

   :target: https://coveralls.io/github/NeuralEnsemble/PyNN?branch=master

   :alt: Test coverage

Funding

-------

Development of PyNN has been partially funded by the European Union Sixth Framework Program (FP6) under

grant agreement FETPI-015879 (FACETS), by the European Union Seventh Framework Program (FP7/2007­-2013)

under grant agreements no. 269921 (BrainScaleS) and no. 604102 (HBP),

and by the European Union’s Horizon 2020 Framework Programme for

Research and Innovation under the Specific Grant Agreements No. 720270 (Human Brain Project SGA1)

, No. 785907 (Human Brain Project SGA2) and No. 945539 (Human Brain Project SGA3).