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🌱 Vivarium

Vivarium is framework for multi-agents simulations in Jax. It enables creating simple agents with two motors and two sensors, inspired by Braitenberg Vehicles , in a 2D rigid-body physics world. The physics engine is written in Jax-MD. With Vivarium, you can run predefined or custom simulations, and interact with them in real time using a Web Interface or Jupyter notebooks. See our tutorials to get started with the project.

Vivarium demo

See a preliminary demo of the project on this video.

📥 Installation

1- Clone the repository:

git clone [email protected]:clement-moulin-frier/vivarium.git
cd vivarium/

2- (Optional) Create and activate a virtual environment:

python -m venv myvenv
source myvenv/bin/activate

3- Install the dependencies:

pip install -r requirements.txt
pip install -e .

🚀 Usage

Run the simulation in a server 🖥️

To run the simulation in a server, use the following command:

python3 scripts/run_server.py

We use Hydra to manage simulations data. By default, the simulation will use the parameters specified in the default.yaml scene file located in the conf/scene directory.

Using custom scene files 🌄

You can customize the initial simulation parameters by creating your own scene files in YAML format and placing them in the conf/scene directory. Scene files can specify parameters such as the number of objects, their size, or the colors, positions, and behaviors of agents for example.

To use a custom scene file in your simulation, pass the scene option followed by the name of the scene file (without the .yaml extension) to the run_server.py script. For example, to run the prey_predator_large scene, use the following command:

python3 scripts/run_server.py scene=prey_predator_large

Any parameters not specified in the custom scene file will be inherited from the default.yaml scene.

Interact with it from a web interface 🌐

When the server is started, you can launch a web interface from another terminal to observe the simulation and interact with it:

panel serve scripts/run_interface.py --autoreload

Once this command will have completed, it will output a URL looking like http://localhost:5006/run_interface. Just click on it, and it will open the web interface in your browser. From there you can start the simulation and play with it.

Interact with it from a jupyter notebook 📓

You can also choose to control the simulator programmatically in Jupyter Notebook. We first recommend you to do the first tutorials listed below. Then you can select a notebook in the notebooks/sessions/ directory and start playing with it ! If you choose to do so, you don't need to start the server and the interface manually. Instead, you can start and stop them with a custom command you can find in the notebooks.

📚 Tutorials

To help you get started and explore the project, we provide a set of Jupyter notebook tutorials located in the notebooks/ directory. These tutorials cover various aspects of the project, from using the graphical interface to interacting with simulations and understanding the backend.

  • Web Interface Tutorial: Begin with the web interface tutorial to gain a basic understanding of the project and learn how to use the graphical interface.
  • Quickstart Tutorial: To learn how to interact with a simulation from a Jupyter notebook, follow the quickstart tutorial. This tutorial will guide you through creating, running, and manipulating simulations within a notebook environment.
  • Create a custom Scene: If you want to create your own simulations with custom parameters, check out the create a custom scene tutorial. This tutorial will show you how to create and use custom scene files to define the initial parameters of your simulations.
  • Simulator tutorial: For a deeper understanding of the simulator backend and its capabilities, check out the simulator tutorial. This tutorial provides insights into the underlying mechanics of the simulator and demonstrates how to leverage its features for advanced use cases

🛠 Development

gRPC Configuration 🔄

The projecte uses gRPC to communicate between server and clients. If you made any changes in the .proto file, you will need to recompile the gRPC files. Here is the command line instruction to do so:

python -m grpc_tools.protoc -I./vivarium/simulator/grpc_server/protos --python_out=./vivarium/simulator/grpc_server/ --pyi_out=./vivarium/simulator/grpc_server/ --grpc_python_out=./vivarium/simulator/grpc_server/ ./vivarium/simulator/grpc_server/protos/simulator.proto

Running Automated Tests 🧪

If you want to add tests for your local changes, you can write them in the tests/ directory. Make sure that the name or your files and test functions start with "test". You can then run the following command in the root of the directory to launch them :

pytest

Acknowledgments

The main contributors of this repository are Corentin Léger and Clément Moullin-Frier from the Flowers team at Inria, with participation of Martial Marzloff. CMF initiated the code base architecture in 2023 and CL was the main developper in 2024. CL was funded by the French National Research Agency, project ECOCURL, Grant ANR-20-CE23-0006.