To become a coherent swarm, worker bees locate their queen by tracking her pheromones, but how can distant individuals exploit these chemical signals which decay rapidly in space and time? In our study (Nguyen et al. 2020), we show that bees use the scenting behavior to collectively create a communication network to propagate pheromone signals. This repository provides Python code for the agent-based model (AMB) that simulates the collective communication that allows bees to localize the queen and form a swarm around her. Full simulations shown in the paper were run on compute clusters; default values for simulation time and arena size provided here results in a smaller and shorter example that could be run locally at a reasonable time.
- Python 3.6.10
- NumPy 1.18.5
- H5py 2.10.0
- Matplotlib 3.1.3
The complete list of required packages provided in requirements.txt, which you can install in your environment with the command pip install -r requirements.txt. Setting up a Python virtual environment, such as conda, is highly recommended.
Default parameters are already set up. To further set up or change parameters for the simulation, navigate to the file config_src.py under config/. Free parameters of the model discussed in the paper:
num_workers: Number of worker bees in arena (default:50)worker_threshold: Concentration threshold that activates a bee from random walk to either scenting or directed walk state (default:0.01)worker_bias_scalar: Magnitude of the directional diffusion of pheromone released by a bee (default:40)
python run_simulation.py runs a simulation with the provided parameters from config/config_src.py.
In the folder experiments, a subfolder will be created for this particular simulation with the name format N{num_workers}_T{worker_threshold}_wb{worker_bias_scalar}_seed{random seed}. A cfg file is created in this folder to record the model parameters for this simulation. The file bee_hist.h5 contains time-series data for the position, state, scenting direction, distance from the queen of all bees. The file envir_hist.h5 contains the time-series data for the environmental maps of pheromone diffusion and decay created by the collective scenting of the bees.
Example: python make_movie.py -p N50_T0.01000_wb30.0_seed42 -r 5 -s 1 processes the h5 data files to visualize the simulation in a video.
Command line parameters:
-por--path: Path to the experiment folder in the folder experiments (default:N50_T0.01000_wb30.0_seed42)-ror--fps: Frame per second for output movie (default:5)-sor--stepsize: Step size for plotting data for output movie (default:1)
Inside the experiment folder (e.g. experiments/N50_T0.01000_wb30.0_seed42), a folder named movie_frames will be created to store png's of the visualization plots. When the entire dataset is visualized, a movie in the format N{num_workers}_T{worker_threshold}_wb{worker_bias_scalar}_seed{random seed}.mp4 is created in the experiment folder.
Example movie:
Reference: Nguyen DMT, Iuzzolino ML, Mankel A, Bozek K, Stephens GJ, Peleg O (2020). Flow-Mediated Collective Olfactory Communication in Honeybee Swarms. bioRxiv 2020.05.23.112540; doi: https://doi.org/10.1101/2020.05.23.112540.