Biologger Sim Documentation

Real-time simulation environment for marine animal tracking and behavioral prediction

Biologger Sim provides a simulation framework for developing and validating biologger algorithms. It supports a “Dual-Mode” architecture:

  1. Lab Mode: High-precision, acausal processing for post-hoc analysis.

  2. Simulation Mode: Real-time, causal processing for on-tag algorithm development.

It integrates with NVIDIA Omniverse via ZeroMQ for high-fidelity visualization.

Python Version License

Features

✅ Dual-Mode Processing

  • Lab Mode: Replicates R-based post-hoc analysis with batch calibration and acausal filtering.

  • Simulation Mode: Simulates real-time tag constraints with causal filtering and online calibration.

✅ High-Fidelity Visualization

  • ZeroMQ integration with NVIDIA Omniverse.

  • Real-time streaming of sensor data and derived metrics.

✅ Configurable Pipelines

  • YAML-based configuration for species-specific parameters.

  • Support for custom sensor fusion and behavioral classification models.

Quick Start

# Install from source
git clone https://github.com/lhzn-io/biologger-sim.git
cd biologger-sim
micromamba env create -f environment.yml
micromamba activate biologger-sim
pip install -e .

# Run simulation
python -m biologger_sim --config config/Swordfish-RED001_20220812_19A0564-postfacto.yaml

Documentation

Contents

Indices and tables