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Release 0.10.1
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changelog

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==============
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Release 0.10.1
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==============
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see doc/releases/0.10.1.txt
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==============
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Release 0.10.0
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==============

doc/conf.py

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# The short X.Y version.
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version = '0.10'
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# The full version, including alpha/beta/rc tags.
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release = '0.10.1.dev'
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release = '0.10.1'
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# The language for content autogenerated by Sphinx. Refer to documentation
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# for a list of supported languages.
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# -- inter-Sphinx mapping options ----------------------------------------------
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intersphinx_mapping = {'python': ('http://docs.python.org/3.8', None)}
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intersphinx_mapping = {'python': ('http://docs.python.org/3.9', None)}

doc/connections.txt

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* the name of the post-synaptic mechanism (e.g. ‘excitatory’, ‘NMDA’)
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(if not specified, PyNN picks a default depending on the weight
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parameter of the synapse type);
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parameter of the synapse type);
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* a label (autogenerated if not specified);
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* a :class:`Space` object, which determines how distances should be
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calculated for distance-dependent wiring schemes or parameter values.

doc/download.txt

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Source distributions
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--------------------
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The `latest stable version of PyNN`_ (0.10.0) may be downloaded from the
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The `latest stable version of PyNN`_ (0.10.1) may be downloaded from the
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`Python Package Index`_. This is recommended for
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anyone using PyNN for the first time.
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Older versions:
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* `0.10.0 <https://pypi.python.org/pypi/PyNN/0.10.0>`_
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* `0.9.6 <https://pypi.python.org/pypi/PyNN/0.9.6>`_
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* `0.8.0 <https://pypi.python.org/pypi/PyNN/0.8.0>`_
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* `0.7.5 <https://pypi.python.org/pypi/PyNN/0.7.5>`_

doc/installation.txt

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Installing PyNN requires:
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* Python (version 2.7, 3.6+)
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* Python (version 3.7+)
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* a recent version of the NumPy_ package
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* the lazyarray_ package
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* the Neo_ package (>= 0.8.0)
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* the Neo_ package (>= 0.11.0)
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* at least one of the supported simulators: e.g. NEURON, NEST, or Brian 2.
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Optional dependencies are:
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If you would prefer to install manually, :doc:`download the latest
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source distribution <download>`, then run the setup script, e.g.::
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$ tar xzf PyNN-0.10.0.tar.gz
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$ cd PyNN-0.10.0
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$ tar xzf PyNN-0.10.1.tar.gz
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$ cd PyNN-0.10.1
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$ python setup.py install
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This will install it to your Python :file:`site-packages` directory, and may

doc/introduction.txt

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It is straightforward to port an existing model from a Python-supporting simulator to PyNN, since this can be done incrementally, replacing one piece of simulator-specific code at a time with the PyNN equivalent, and testing that the model behaviour is unchanged at each step.
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:doc:`Download<download>` the current stable release of the library (0.10.0) or get the development version from the `Git repository`_ .
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:doc:`Download<download>` the current stable release of the library (0.10.1) or get the development version from the `Git repository`_ .
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Licence
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-------

pyNN/__init__.py

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:license: CeCILL, see LICENSE for details.
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"""
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__version__ = '0.10.1.dev'
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__version__ = '0.10.1'
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__all__ = ["common", "random", "nest", "neuron", "brian2",
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"recording", "errors", "space", "descriptions",
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"standardmodels", "parameters", "core", "serialization"]

pyNN/common/projections.py

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return 'Projection("%s")' % self.label
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def __getitem__(self, i):
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"""Return the *i*th connection within the Projection."""
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"""Return the /i/th connection within the Projection."""
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raise NotImplementedError
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def __iter__(self):

setup.py

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setup(
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name="PyNN",
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version="0.10.1.dev",
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version="0.10.1",
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packages=['pyNN', 'pyNN.nest', 'pyNN.neuron',
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'pyNN.brian2', 'pyNN.common', 'pyNN.mock', 'pyNN.neuroml',
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'pyNN.recording', 'pyNN.standardmodels', 'pyNN.descriptions',

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