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Resource:PyNN

Name: Resource:PyNN
Description: A Python package for simulator-independent specification of neuronal network models. In other words, you can write the code for a model once, using the PyNN API, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST and PCSIM).

The API has two parts, a low-level, procedural API (functions create(), connect(), set(), record(), record_v()), and a high-level, object-oriented API (classes Population and Projection, which have methods like set(), record(), setWeights(), etc.).

The low-level API is good for small networks, and perhaps gives more flexibility. The high-level API is good for hiding the details and the book-keeping, and is intended to have a one-to-one mapping with FacetsML.

The other thing that is required to write a model once and run it on multiple simulators is standard cell models. PyNN translates standard cell-model names and parameter names into simulator-specific names, e.g. standard model IF_curr_alpha is iaf_neuron in NEST and StandardIF in NEURON, while SpikeSourcePoisson is a poisson_generator in NEST and a NetStim in NEURON. Only a small number off cell models have been implemented so far.
Abbreviation: PyNN
Parent Organization: Resource:NeuralEnsemble
Resource Type(s): Software development tool
Resource: Resource
URL: http://neuralensemble.org/PyNN/
Alt. URL(s): http://pynn.gforge.inria.fr/
*Id: nif-0000-23351
PMID: PMID 19194529
Availability: CeCILL license
Keywords: Python, software
Link to OWL / RDF: Download this content as OWL/RDF

Categories related to Resource:PyNN

Resource:Open Source Brain

Curation status: Curated

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Facts about Resource:PyNNRDF feed
AbbrevPyNN  +
AltURLhttp://pynn.gforge.inria.fr/  +
AvailabilityCeCILL license  +
CurationStatuscurated  +
DefiningCitationhttp://neuralensemble.org/PyNN/  +
DefinitionA Python package for simulator-independent A Python package for simulator-independent specification of neuronal network models. In other words, you can write the code for a model once, using the PyNN API, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST and PCSIM).

The API has two parts, a low-level, procedural API (functions create(), connect(), set(), record(), record_v()), and a high-level, object-oriented API (classes Population and Projection, which have methods like set(), record(), setWeights(), etc.).

The low-level API is good for small networks, and perhaps gives more flexibility. The high-level API is good for hiding the details and the book-keeping, and is intended to have a one-to-one mapping with FacetsML.

The other thing that is required to write a model once and run it on multiple simulators is standard cell models. PyNN translates standard cell-model names and parameter names into simulator-specific names, e.g. standard model IF_curr_alpha is iaf_neuron in NEST and StandardIF in NEURON, while SpikeSourcePoisson is a poisson_generator in NEST and a NetStim in NEURON. Only a small number off cell models have been implemented so far.
models have been implemented so far.
Has default formThis property is a special property in this wiki.Resource  +
Has roleSoftware development tool  +
Idnif-0000-23351  +
Is part ofResource:NeuralEnsemble  +
KeywordsPython  +, and Software  +
LabelResource:PyNN  +
ModifiedDate21 July 2014  +
PMID19194529  +
Page has default formThis property is a special property in this wiki.Resource  +
SuperCategoryResource  +