Resource:PyNN

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Resource:PyNN

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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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Facts about Resource:PyNNRDF feed

CurationStatus	curated +
DefiningCitation	http://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 role	Software development tool +
Id	nif-0000-23351 +
Is part of	Institut National de la Recherche Agronomique +
Keywords	Python +, and Software +
Label	Resource:PyNN +
ModifiedDate	18 May 2011 +
Page has default formThis property is a special property in this wiki.	Resource +
SuperCategory	Resource +
Synonym	PyNN +