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Resource:PyNN

Name: Resource:PyNN
Description:

PyNN (pronounced 'pine') is 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.
Other Name(s): PyNN
Parent Organization: Institut National de la Recherche Agronomique
Resource Type(s): Software development tool
Keywords: python, software
Resource: Resource
URL: http://pynn.gforge.inria.fr/
Id: nif-0000-23351
Link to OWL / RDF: Download this content as OWL/RDF

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Resource:Open Source Brain

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Facts about Resource:PyNNRDF feed
CurationStatuscurated  +
DefiningCitationhttp://pynn.gforge.inria.fr/  +
Definition

PyNN (pronounced 'pine') is a Pyth
PyNN (pronounced 'pine') is 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 ofInstitut National de la Recherche Agronomique  +
KeywordsPython  +, and Software  +
LabelResource:PyNN  +
ModifiedDate22 June 2013  +
Page has default formThis property is a special property in this wiki.Resource  +
SuperCategoryResource  +
SynonymPyNN  +