PyNEST: a convenient interface to the NEST simulator
The neural simulation tool NEST (http://www.nest-initiative.org) is a simulator for heterogeneous networks of point neurons or neurons with a small number of compartments. It aims at simulations of large neural systems with more than 10^4 neurons and 10^7 to 10^9 synapses. NEST is implemented in C++...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2009-01-01
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| Series: | Frontiers in Neuroinformatics |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/neuro.11.012.2008/full |
| _version_ | 1818582190833795072 |
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| author | Jochen M Eppler Jochen M Eppler Moritz Helias Eilif Muller Markus Diesmann Markus Diesmann Markus Diesmann Marc-Oliver Gewaltig Marc-Oliver Gewaltig |
| author_facet | Jochen M Eppler Jochen M Eppler Moritz Helias Eilif Muller Markus Diesmann Markus Diesmann Markus Diesmann Marc-Oliver Gewaltig Marc-Oliver Gewaltig |
| author_sort | Jochen M Eppler |
| collection | DOAJ |
| description | The neural simulation tool NEST (http://www.nest-initiative.org) is a simulator for heterogeneous networks of point neurons or neurons with a small number of compartments. It aims at simulations of large neural systems with more than 10^4 neurons and 10^7 to 10^9 synapses. NEST is implemented in C++ and can be used on a large range of architectures from single-core laptops over multi-core desktop computers to super-computers with thousands of processor cores. Python (http://www.python.org) is a modern programming language that has recently received considerable attention in Computational Neuroscience. Python is easy to learn and has many extension modules for scientific computing (e.g. http://www.scipy.org). In this contribution we describe PyNEST, the new user interface to NEST. PyNEST combines NEST’s efficient simulation kernel with the simplicity and flexibility of Python. Compared to NEST’s native simulation language SLI, PyNEST makes it easier to set up simulations, generate stimuli, and analyze simulation results. We describe how PyNEST connects NEST and Python and how it is implemented. With a number of examples, we illustrate how it is used. |
| first_indexed | 2024-12-16T07:45:27Z |
| format | Article |
| id | doaj.art-9b541606509445319b94b4e7df0e6c00 |
| institution | Directory Open Access Journal |
| issn | 1662-5196 |
| language | English |
| last_indexed | 2024-12-16T07:45:27Z |
| publishDate | 2009-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj.art-9b541606509445319b94b4e7df0e6c002022-12-21T22:38:59ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962009-01-01210.3389/neuro.11.012.2008363PyNEST: a convenient interface to the NEST simulatorJochen M Eppler0Jochen M Eppler1Moritz Helias2Eilif Muller3Markus Diesmann4Markus Diesmann5Markus Diesmann6Marc-Oliver Gewaltig7Marc-Oliver Gewaltig8Albert-Ludwigs UniversityHonda Research Institute Europe GmbHAlbert-Ludwigs UniversitySwiss Federal Institute of Technology, EPFLAlbert-Ludwigs UniversityRIKENRiken Brain Science InstituteAlbert-Ludwigs UniversityHonda Research Institute Europe GmbHThe neural simulation tool NEST (http://www.nest-initiative.org) is a simulator for heterogeneous networks of point neurons or neurons with a small number of compartments. It aims at simulations of large neural systems with more than 10^4 neurons and 10^7 to 10^9 synapses. NEST is implemented in C++ and can be used on a large range of architectures from single-core laptops over multi-core desktop computers to super-computers with thousands of processor cores. Python (http://www.python.org) is a modern programming language that has recently received considerable attention in Computational Neuroscience. Python is easy to learn and has many extension modules for scientific computing (e.g. http://www.scipy.org). In this contribution we describe PyNEST, the new user interface to NEST. PyNEST combines NEST’s efficient simulation kernel with the simplicity and flexibility of Python. Compared to NEST’s native simulation language SLI, PyNEST makes it easier to set up simulations, generate stimuli, and analyze simulation results. We describe how PyNEST connects NEST and Python and how it is implemented. With a number of examples, we illustrate how it is used.http://journal.frontiersin.org/Journal/10.3389/neuro.11.012.2008/fullmodellingnetworkslarge-scale simulationprogrammingpythonscientific computing |
| spellingShingle | Jochen M Eppler Jochen M Eppler Moritz Helias Eilif Muller Markus Diesmann Markus Diesmann Markus Diesmann Marc-Oliver Gewaltig Marc-Oliver Gewaltig PyNEST: a convenient interface to the NEST simulator Frontiers in Neuroinformatics modelling networks large-scale simulation programming python scientific computing |
| title | PyNEST: a convenient interface to the NEST simulator |
| title_full | PyNEST: a convenient interface to the NEST simulator |
| title_fullStr | PyNEST: a convenient interface to the NEST simulator |
| title_full_unstemmed | PyNEST: a convenient interface to the NEST simulator |
| title_short | PyNEST: a convenient interface to the NEST simulator |
| title_sort | pynest a convenient interface to the nest simulator |
| topic | modelling networks large-scale simulation programming python scientific computing |
| url | http://journal.frontiersin.org/Journal/10.3389/neuro.11.012.2008/full |
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