seiscode-models

A robust Python package for seismic modeling, simulation configurations, and waveform processing utilities. Designed with a clean API, strict type hinting, and seamless cloud-native CI/CD workflows.

Features

• Seismic Modeling Core: Extensible Python framework for forward modeling and synthetic data generation.
• High Performance: Optimized numerical routines and data structures.
• Modern Python Standards: Fully type-hinted, tested across multiple Python versions (3.8–3.11), and linted with Ruff.
• Automated CI/CD: Continuous integration, automated semantic versioning, and publishing pipeline via GitHub Actions.

Installation

You can install the latest stable version of seiscode-models directly from PyPI:

pip install seiscode-models

Or install it for local development from source:

git clone [https://github.com/PageotD/seiscode-models.git](https://github.com/PageotD/seiscode-models.git)
cd seiscode-models
pip install -e ".[dev]"

Quick Start

Here is a quick example showing how to initialize a basic modeling configuration and run a simulation routine:

from seiscode_models.config import ModelConfig
from seiscode_models.engine import SeismicEngine

# 1. Define the simulation configuration
config = ModelConfig(
    velocity_model="homogeneous",
    p_wave_velocity=3500.0,  # m/s
    s_wave_velocity=2000.0,  # m/s
    density=2200.0,          # kg/m^3
    frequency=15.0           # Hz
)

# 2. Initialize the engine and execute simulation
engine = SeismicEngine(config=config)
result = engine.run_forward_modeling()

print(f"Simulation completed successfully. Peak amplitude: {result.max_amplitude:.4f}")

For more advanced use cases, check out the examples directory or the CHANGELOG.md.

Running Tests

To run the test suite locally with pytest:

pytest tests/ -v --cov=seiscode_models

Citation

If you use seiscode-models in your research or academic work, please cite it using the following Zenodo DOI:

Pageot, D. (2026). seiscode-models: A Python package for seismic modeling (Version x.y.z). Zenodo. https://doi.org/10.5281/zenodo.23349342

License

This project is open-source under the MIT License.