Changes for page PyNN: resources

Last modified by adavison on 2022/10/04 14:25

From version 10.2
edited by adavison
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To version 16.1
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1 -This collab is currently being used to plan tutorials for PyNN. Once we have completed at least one of the "Installing PyNN" tutorials and the "Building and simulating a simple model" tutorial, we will make it public.
1 +PyNN (//pronounced 'pine'//) is a simulator-independent language for building neuronal network models.
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3 +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>>url:http://www.neuron.yale.edu/neuron/]], [[NEST>>url:http://www.nest-initiative.org/?page=Software]], and [[Brian>>url:http://briansimulator.org/]]), and on the [[SpiNNaker>>url:http://apt.cs.manchester.ac.uk/projects/SpiNNaker/]] and [[BrainScaleS>>url:https://www.humanbrainproject.eu/en/silicon-brains/]] neuromorphic hardware systems.
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4 -== Planned tutorials ==
5 +== [[Tutorials>>Tutorials]]   [[Documentation>>https://neuralensemble.org/docs/PyNN/]] [[Homepage>>http://neuralensemble.org/PyNN/]] ==
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6 -The first three tutorials should be followed in sequence. Following this, the remaining, more advanced, tutorials can be followed in any order.
7 +== [[Source code>>https://github.com/NeuralEnsemble/PyNN]] [[Issue tracker>>https://github.com/NeuralEnsemble/PyNN/issues]]   [[Community>>https://neuralensemble.org/community]] ==
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8 -* [[Introduction to PyNN>>doc:.Tutorials.Introduction to PyNN.WebHome]]
9 -* [[Installing PyNN>>doc:.Tutorials.Installing PyNN.WebHome]]
10 -** on Linux
11 -** on Mac OS
12 -** on Windows
13 -** in the EBRAINS Jupyter Lab
14 -* [[Building and simulating a simple model>>doc:.Tutorials.Building and simulating a simple model.WebHome]]
15 -* [[Recording and data handling>>doc:.Tutorials.Recording and data handling.WebHome]]
16 -* Structuring larger models
17 -* Models with spatial structure
18 -* Synaptic plasticity
19 -* Randomness and reproducibility
20 -* Running parallel simulations
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