Python Extension

This NetLogo extension allows NetLogo models to run Python code. This allows models to make use of powerful Python libraries, such as numpy, TensorFlow, scipy, and others. It works by starting up a Python session that the model can then run code in and get results from. See the documentation here: https://github.com/qiemem/PythonExtension/blob/master/README.md

Installation instructions

1. Download the attached zip
2. Unzip it into the extensions directory of your NetLogo installation.

Thus, your NetLogo extensions directory should contain a folder called py with the following contents:

Demo models can be found in the demos folder. They should work with either Python 2 or Python 3.

The demo models depend on a number of libraries, all installable with pip or conda:

Flocking Clusters

• numpy
• sklearn

Both Wolf Sheep Predation models

• numpy
• matplotlib

Traffic Basic - Reinforcement

• numpy
• tensorflow
• keras

To install all dependencies, run pip install numpy matplotlib sklearn tensorflow keras in your terminal (assuming you have pip).

Changelist

Improvements:

• Halting the NetLogo model no longer automatically kills the Python session.
• Halt handling is much more robust in general.
• Improve documentation

Python Extension

Installation instructions

1. Download the attached zip
2. Unzip it into the extensions directory of your NetLogo installation.

Demo models can be found in the demos folder. They should work with either Python 2 or Python 3.

The demo models depend on a number of libraries, all installable with pip or conda:

Flocking Clusters

• numpy
• sklearn

Both Wolf Sheep Predation models

• numpy
• matplotlib

Traffic Basic - Reinforcement

• numpy
• tensorflow
• keras

To install all dependencies, run pip install numpy matplotlib sklearn tensorflow keras in your terminal (assuming you have pip).

Changelist

Bug fixes:

• Gracefully handles interruption of the Python process
• Somewhat gracefully handles user halting NetLogo by shutting down the Python process
• Does a better job of cleaning up the Python process

Python Extension alpha

Installation instructions

1. Download the attached zip
2. Unzip it into the extensions directory of your NetLogo installation.

Warning: This extension is untested on windows. There's a chance it will work if you just do py:setup "python.exe" or something, but I haven't tried

Demo models can be found in the demos folder. By default, they use Python 3. If you only have Python 2, simply change the line that reads py:setup "python3" to py:set "python".

The demo models depend on a number of libraries, all installable with pip:

Flocking Clusters

• numpy
• sklearn

Both Wolf Sheep Predation models

• numpy
• matplotlib

Traffic Basic - Reinforcement

• numpy
• tensorflow
• keras

To install all dependencies, run pip install numpy matplotlib sklearn tensorflow keras in your terminal (assuming you have pip).

Changelist

Features:

• New primitives for referencing correct Python installation in system independent way: py:python, py:python2, and py:python3
• New configuration file and menu for configuring default Python installations to use
• Much faster data transfer between Python and NetLogo

Bug fixes:

• Fail gracefully on NaN and Infinity

Python Extension alpha

Installation instructions

1. Download the attached zip
2. Unzip it into the extensions directory of your NetLogo installation.

Warning: This extension is untested on windows. There's a chance it will work if you just do py:setup "python.exe" or something, but I haven't tried

Demo models can be found in the demos folder. By default, they use Python 3. If you only have Python 2, simply change the line that reads py:setup "python3" to py:set "python".

The demo models depend on a number of libraries, all installable with pip:

Flocking Clusters

• numpy
• sklearn

Both Wolf Sheep Predation models

• numpy
• matplotlib

Traffic Basic - Reinforcement

• numpy
• tensorflow
• keras

To install all dependencies, run pip install numpy matplotlib sklearn tensorflow keras in your terminal (assuming you have pip).