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Nengo: Large-scale brain modelling in Python

An illustration of the three principles of the NEF

Installation

We will be making a release on PyPI soon, meaning you will be able to pip install nengo. For now, you can do the following:

pip install -e git://github.com/ctn-waterloo/nengo.git#egg=nengo

Nengo supports Python 2.6, 2.7, and 3.3+ in a single codebase.

Usage

TODO

Documentation & Examples

Documentation and examples can be found at ReadTheDocs.

Testing

One way to verify that your installation is working correctly is to run the unit tests. We use py.test, so you can run the Nengo unit tests with:

py.test --pyargs nengo

The test suite can take some time to run, so we recommend install the pytest-xdist plugin and running py.test --pyargs nengo -n 4 or however many free CPU cores you have available.

Running individual tests

Tests in a specific test file can be run by calling py.test on that file. For example:

py.test nengo/tests/test_node.py

will run all the tests in test_node.py.

Individual tests can be run using the -k EXPRESSION argument. Only tests that match the given substring expression are run. For example:

py.test nengo/tests/test_node.py -k test_circular

will run any tests with test_circular in the name, in the file test_node.py.

Plotting the results of tests

Many Nengo test routines have the built-in ability to plot test results for easier debugging. To enable this feature, set the environment variable NENGO_TEST_PLOT=1, for example:

NENGO_TEST_PLOT=1 py.test --pyargs nengo

Plots are placed in nengo.simulator.plots in whatever directory py.test is invoked from.

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A Python library for creating and simulating large-scale brain models

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