gwsim 0.2.0

A Python package for simulating gravitational wave detector data for mock data challenges.

gwsim

A Python package for generating Mock Data Challenge (MDC) datasets for the gravitational-wave (GW) community. It simulates strain data for detectors like Einstein Telescope, providing a unified interface for reproducible GW data generation.

Features

• Modular Design: Uses mixins for flexible simulator composition
• Detector Support: Built-in support for various GW detectors with custom configuration options
• Waveform Generation: Integrates with PyCBC and LALSuite for accurate signal simulation
• Noise Models: Supports colored and correlated noise generation (In-Progress)
• Population Models: Handles injection populations for signals and glitches
• Data Formats: Outputs in standard GW formats (GWF frames)
• CLI Interface: Command-line tools for easy simulation workflows

Installation

We recommend using uv to manage virtual environments for installing gwsim.

If you don't have uv installed, you can install it with pip. See the project pages for more details:

• Install via pip: pip install --upgrade pip && pip install uv
• Project pages: uv on PyPI | uv on GitHub
• Full documentation and usage guide: uv docs

From PyPI

# Create a virtual environment (recommended with uv)
uv venv gwsim-env
source gwsim-env/bin/activate  # On Windows: gwsim-env\Scripts\activate
uv pip install gwsim

From Source

git clone https://gitlab.et-gw.eu/et-projects/software/gwsim.git
ce gwsim
# Create a virtual environment (recommended with uv)
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install .

Quick Start

Command Line

# Generate simulated data
gwsim simulate config.yaml

Configuration

gwsim uses YAML configuration files for reproducible simulations. See examples/config.yaml for a complete example.

Key configuration sections:

• globals: Shared parameters (sampling rate, duration, etc.)
• simulators: List of noise, signal, and glitch generators

Documentation

Full documentation to be available at readthedocs.io.

Contributing

Contributions are welcome!

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

Testing

Run the test suite:

pytest

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For questions or issues, please open an issue on GitLab or contact the maintainers.