https://github.com/neuralensemble/pype9
Python pipelines to simulate and manipulate neuronal models, and networks thereof, described in NineML (http://nineml.net)
https://github.com/neuralensemble/pype9
Last synced: 11 months ago
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Python pipelines to simulate and manipulate neuronal models, and networks thereof, described in NineML (http://nineml.net)
- Host: GitHub
- URL: https://github.com/neuralensemble/pype9
- Owner: NeuralEnsemble
- License: mit
- Created: 2014-10-08T04:35:14.000Z (over 11 years ago)
- Default Branch: master
- Last Pushed: 2020-04-12T12:01:37.000Z (about 6 years ago)
- Last Synced: 2025-06-07T18:09:31.605Z (about 1 year ago)
- Language: Python
- Homepage:
- Size: 22.2 MB
- Stars: 3
- Watchers: 8
- Forks: 7
- Open Issues: 31
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
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README
Pype9
=====
.. image:: https://travis-ci.org/NeuralEnsemble/pype9.svg?branch=master
:target: https://travis-ci.org/NeuralEnsemble/pype9
.. image:: https://coveralls.io/repos/github/NeuralEnsemble/pype9/badge.svg?branch=master
:target: https://coveralls.io/github/NeuralEnsemble/pype9?branch=master
.. image:: https://img.shields.io/pypi/pyversions/pype9.svg
:target: https://pypi.python.org/pypi/pype9/
:alt: Supported Python versions
.. image:: https://img.shields.io/pypi/v/pype9.svg
:target: https://pypi.python.org/pypi/pype9/
:alt: Latest Version
.. image:: https://readthedocs.org/projects/pype9/badge/?version=latest
:target: http://pype9.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
PYthon PipelinEs for 9ML (Pype9) is a collection of Python pipelines
for simulating networks of neuron models described in NineML_ with various
simulator backends.
Links
-----
* Documentation: http://pype9.readthedocs.org
* Mailing list: `NeuralEnsemble Google Group`_
* Issue tracker: https://github.com/NeuralEnsemble/pype9/issues
Supported Simulators
--------------------
Pype9 works with either or both of the following simulator backends
* Neuron_ >= 7.5
* NEST_ >= 2.14.0
Detailed instructions on how to install these simulators on different platforms
can be found in the `Installation documentation`_.
Unsupported NineML
------------------
NineML_ aims to be a comprehensive description language for neural simulation. This
means that it allows the expression of some uncommon configurations that are
difficult to implement in Neuron_ and NEST_. Work is planned to make the NEURON
and NEST pipelines in Pype9 support NineML_ fully, however until then the
following restrictions apply to models that can be used with Pype9.
* synapses must be linear
* synapses can only have one variable that varies over a projection (e.g.
weight)
* no recurrent analog connections between populations (e.g. gap junctions)
* only one event send port per cell
* names given to NineML_ elements are not escaped and therefore can clash with
built-in keywords and some PyPe9 method names (e.g. 'lambda' is a reserved
keyword in Python). Please avoid using names that clash with C++ or Python
keywords (NB: This will be fixed in future versions).
Examples
--------
Given a cell model described in NineML_ saved in
``my_hodgkin_huxley.xml``, the simulator pipeline can run from the command line:
.. code-block:: bash
$ pype9 simulate my_hodgkin_huxley.xml#hh_props neuron 100.0 0.01 \
--play isyn isyn.neo.pkl --record v v.neo.pkl --init_value v -65.0 mV
or in a Python script
.. code-block:: python
from pype9.simulator.neuron import cell, Simulation
from nineml import units as un
HodgkinHuxley = cell.MetaClass('my_hodgkin_huxley.xml#hh_class')
with Simulation(dt=0.01 * un.ms, seed=1234) as sim:
hh = HodgkinHuxley('my_hodgkin_huxley.xml#hh_props', v=-65.0 * un.mV)
hh.record('v')
sim.run(100.0 * un.ms)
v = hh.recording('v')
Pype9 also supports network models described in NineML_ via integration with PyNN_
.. code-block:: bash
$ pype9 simulate brunel.xml nest 1000.0 0.01 \
--record Exc.spike_output Exc-nest.neo.pkl \
--record Inh.spike_output Inh-nest.neo.pkl \
--seed 12345
or
.. code-block:: python
from pype9.simulator.neuron import Network, Simulation
from nineml import units as un
with Simulation(dt=0.01 * un.ms, seed=1234) as sim:
brunel_ai = Network('brunel.xml#AI')
brunel_ai.component_array('Exc').record('spike_output')
brunel_ai.component_array('Inh').record('spike_output')
sim.run(1000.0 * un.ms)
exc_spikes = brunel_ai.component_array('Exc').recording('spike_output')
inh_spikes = brunel_ai.component_array('Inh').recording('spike_output')
See `Creating Simulations in Python`_ in the Pype9 docs for more examples and pipelines.
In addition to the ``simulate`` command there is also a ``plot`` command for
conveniently plotting the results of the simulation with Matplotlib_,
and a ``convert`` command to convert NineML_ files between different serialization
formats (XML, YAML, JSON and HDF5) and NineML_ versions (1.0 and 2.0dev). See the
documentation for details.
:copyright: Copyright 20012-2016 by the Pype9 team, see AUTHORS.
:license: MIT, see LICENSE for details.
.. _PyNN: http://neuralensemble.org/docs/PyNN/
.. _`NeuralEnsemble Google Group`: https://groups.google.com/forum/#!forum/neuralensemble
.. _Matplotlib: http://matplotlib.org
.. _`Creating Simulations in Python`: http://pype9.readthedocs.io/latest/scripting.html
.. _`Installation documentation`: http://pype9.readthedocs.io/en/latest/installation.html
.. _NineML: http://nineml.net
.. _NEST: https://nest-simulator.org
.. _Neuron: https://neuron.yale.edu.au