The following instructions are for Linux and Mac OS X. It should be possible to install and run PyNN on Windows, but this has not been tested.
Installing PyNN requires:
Optional dependencies are:
The easiest way to get PyNN is to use pip:
$ pip install PyNN
If you would prefer to install manually, download the latest source distribution, then run the setup script, e.g.:
$ tar xzf PyNN-0.12.1.tar.gz $ pip install ./PyNN-0.12.1
This will install it to your Python
site-packages directory, and may
require root privileges. We strongly recommend, however, that you use a
virtualenv or a Conda environment. We assume you have already installed the
simulator(s) you wish to use it with. If this is not the case, see below for
For recent versions of NEURON,
$ pip install neuron
may be all you need. If you have more complex needs, try the following.
Download the sources for NEURON 8.0 or later, in
.tar.gz format, from http://www.neuron.yale.edu/neuron/download/getstd.
Also download Interviews from the same location.
Compile Interviews and NEURON according to the instructions given at http://www.neuron.yale.edu/neuron/static/download/compilestd_unix.html,
except that when you run configure, add the options
--with-nrnpython and, optionally,
$ ./configure --prefix=`pwd` --with-nrnpython --with-paranrn $ make $ make install
Make sure that you add the Interviews and NEURON
bin directories to your path.
Test that the Python support has been enabled by running:
$ nrniv -python NEURON -- VERSION 8.2.2 release/8.2 (93d41fafd) 2022-12-15 Duke, Yale, and the BlueBrain Project -- Copyright 1984-2022 See http://neuron.yale.edu/neuron/credits >>> import hoc >>> import nrn
Now you can compile and install NEURON as a Python package:
$ cd src/nrnpython $ python setup.py install
Now test everything worked:
$ python >>> import neuron
If you run into problems, check out the NEURON Forum.
Now test that NEURON works with PyNN:
>>> import pyNN.neuron as sim
(The first time you do this, PyNN will compile some PyNN-specific membrane mechanisms).
Installing NEST and PyNEST¶
NEST 3.4-3.6 can be downloaded from http://www.nest-simulator.org/download/. Earlier versions of NEST may not work with this version of PyNN. The full installation instructions are available at https://nest-simulator.readthedocs.io/en/v3.4/installation/index.html/.
Now try it out:
$ cd ~ $ python >>> import nest -- N E S T -- Copyright (C) 2004 The NEST Initiative Version: 3.4 ... >>> nest.node_models ('weight_recorder', 'gauss_rate_ipn', 'lin_rate_ipn', 'sigmoid_rate_ipn', 'sigmoid_rate_gg_1998_ipn', 'tanh_rate_ipn', ...)
'aeif_cond_alpha' is in the list of models. If it is not, you may need to install a newer version of the GNU Scientific Library and then recompile NEST.
Now test NEST together with PyNN using something like the following:
>>> import pyNN.nest as sim >>> sim.setup() >>> sim.end()
If you get a warning “Unable to install NEST extensions. Certain models may not be available” then ensure the program nest-config is on your system PATH. If you still get this message even after adding the directory containing nest-config to the PATH, then you will still be able to use pyNN.nest, just a small number of models will not be available.
Instructions for downloading and installing Brian 2 are available from https://briansimulator.org/install/. Note that this version of PyNN works with Brian 2. If you need to use Brian 1, try PyNN 0.9.6.
At present, Arbor only works with the experimental multi-compartment neuron models; support for point neuron models is planned for the next release.