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This is a project building an agent-based modeling system in Python.

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Indra

This is a project building an agent-based modeling system in Python. The ultimate goal is to build a GUI front-end that will allow non-coders to build models, while at the same time permitting coders to use Python for more flexibility in model creation.

We are currently building indra2, a new version of the system. Our API Serever is moving along, we have a react frontend in progress, and many models have been ported to version 2.

Developing and Contributing

To configure your system for development, first install Python 3 and git and then run make create_dev_env. This will install some dependencies using PIP. Follow the outputted instructions for setting your environment variables.

To build the Docker container with the development environment, run make dev_container.

To run the Docker container with the development environment, run ./dev_cont.sh.

To run tests on Python code, run make pytests. To run tests on JavaScript code, run make jstests. To run tests on both Python and JavaScript code, run make tests. These can be run inside or outside the Docker container. Optionally, you can first cd into APIServer, indra, models, or webapp before running make tests to run only the tests for that directory.

To test the APIServer with the front end locally:

  • Back end:
    • cd into APIServer and run ./api.sh to start the server.
  • Front end:
    • Run make setup_react to install all modules listed as dependencies.
    • Within each file in webapp/src/components/, find and replace https://indrasnet.pythonanywhere.com/ with your server's address (which should be http://127.0.0.1:8000 if you ran api.sh above).
    • cd into webapp and run npm run start.
    • To open test coverage of Front End in your browser, cd into webapp and run npm run coverage.

If ImportError: bad magic number in 'config': b'\x03\xf3\r\n' occurs, please try to run find . -name \*.pyc -delete .

Work in Progress

Trying to get all the models working from the API server.

Flocking: Using Windows Subsystem for Linux(WSL), on Ubuntu 18.04, entering the iPython terminal through the "Examine Model Data" option in the Flocking menu and entering user.env to check environment values returns an error with printer.pretty(obj). This occurs with all other models. Need other people to try and replicate this error. Entering user, or any of the other properties like .menu or .user_msgs do not return any errors.

Selecting the Matplotlib options (Population Graph, Scatter Plot, etc) in the model menus return nothing. No graphs can be seen. Current theory is that matplotlib is not configured correctly on WSL. To get around this, you can use a Windows X-Server like Xming, and add export DISPLAY=localhost:0.0 to your login script. This will allow the matplotlib graphs to show in an external window.

Still need to figure out how to have small groups/flocks gather together into a single flock. (Idea: treat each mini-flock as an agent and draw borders, to which we apply bird_action() to each triangular point of the mini-flock, making sure mini flocks form a proper flock? )

With regard to the Kanban board:

  1. I have not been able to replicate this problem at all with single birds. However small groups/flocks will stop moving the moment all the birds have joined a group/flock. This seems like intended behavior, but the next step is to have these small flocks gather together to make a single flock.
  2. Also have not been able to replicate this. It seems like the distance checking has been already fixed.
  3. All the tests have been updated. However, test_bird_action(), the most important one, currently is using an inelegant solution to test bird_action() because of an odd problem with agent properties. I've left comments on test_bird_action() as a sort of TO DO or reminder.
  4. Documentation still needs to be written.
  5. Need to see if the model works on APIServer.
  6. Haven't figured out how to orient markers yet.

Frontend: Dark mode currently does not change the colors of components, such as the header or buttons. Mobile design has not been implememnted. We had planned on having the carousel image be below the menu items. The general layout could be structured a little better. Especially on the action menu page. There is a lot of white space that is not being utilized and the alignment of things like the header, the title, and menu items are inconsistent. There are some unused component files that should be removed. A lot of testing needs to be implemented.

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This is a project building an agent-based modeling system in Python.

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