Getting started

Nengo runs on Windows, Mac OS X and Linux and requires Python. To install Nengo, we recommend using pip.

pip install nengo nengo-gui

To make sure that the installation worked, run

nengo

and you should see a message about the Nengo server starting, and a webpage will open with the NengoGUI environment.

If you do not have pip installed, or if you run into any errors when installing Nengo with pip, expand the sections below for more detailed instructions.

pip will do its best to install all of Nengo’s requirements when it installs Nengo. However, if anything goes wrong during this process, you can install Nengo’s requirements manually before doing pip install nengo again.

Detailed installation instructions

pip install nengo nengo-gui

conda install numpy pip
pip install nengo nengo-gui

brew install python
pip install numpy
pip install nengo nengo-gui

sudo apt install python-numpy python-pip
pip install nengo nengo-gui

sudo yum install python-numpy python-pip
pip install nengo nengo-gui

Running models

Once you have Nengo installed, there are two ways to run Nengo models. They can be run either with the NengoGUI, or they can be run with a Python interpreter.

With NengoGUI

The NengoGUI is a web-based interface for designing and running Nengo models. To start the GUI, open a terminal and run the nengo command.

To access the GUI, you use a web browser like Google Chrome or Firefox. You should see a depiction of the network on the left panel, and a code editor on the right panel.

The network illustration on the left panel is interactive. You can drag to move the network objects, scroll with the mouse to zoom in and out, and right-click on objects to display plots that will update in real time as the model simulates (see the GUI documentation for more details).

The code editor on the right panel shows the Python code defining the Nengo model. While you can write any Python code in this editor, we add a few additional constraints to ensure the GUI runs smoothly:

• Your top-level network must be called model.
• You cannot construct a Simulator object, as the GUI makes its own Simulator under the hood.
• You cannot show plots created with Matplotlib, as the GUI has its own set of visualizations.

To access a series of tutorials that introduce you to the GUI and to the basics of building models with Nengo, click on the folder icon at the top-left of the GUI, select “built-in examples”, and then “tutorial”.

If you see a warning that says something like Warning: Simulators cannot be manually run inside nengo_gui, then you are likely running a model that is designed to run with a Python interpreter (see below for details). If the model you are trying to run is a Nengo example, then it’s likely that a similar example exists within the built-in examples accessible through the folder icon at the top-left of the GUI.

With a Python interpreter

The Nengo core is written in Python. In order to install Nengo, you likely also installed a Python distribution, whether it be through a package manager provided by your operating system, through Anaconda, or by some other means. You can use Nengo through any Python interpreter, like any other Python package.

All Python distributions come with an interpreter that you can usually run through a terminal by typing in python and hitting enter. You should see a prompt that looks like this:

$ python
Python 3.5.3 (default, Jan 19 2017, 14:11:04)
[GCC 6.3.0 20170118] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>

You can then import nengo and start building models.

>>> import nengo
>>> model = nengo.Network("My model")

Since Nengo is a normal Python package, it interacts well with other Scientific Python packages, including plotting libraries like Matplotlib.

The Jupyter notebook provides another way to run Python scripts. We provide Nengo core examples as Jupyter notebooks because you can see plots in the same interface as the code. Jupyter notebooks are also text files, but have the extension .ipynb. These are run through the Jupyter notebook. To try this out, download single-neuron.ipynb (press Ctrl+s to save the notebook if it doesn’t download automatically). Then open a terminal, enter

$ jupyter notebook

and click on single-neuron.ipynb to run the example. After running all the cells, you should see these plots.

To access a series of tutorials that use Nengo with a Python interpreter, see the Nengo documentation.

Learning more

• Documentation
• Videos
• Publications

Reference

The following links are useful to refer to when building models.

• Nengo core documentation
• Nengo modelling API