To build Stone Soup use the command python -m pip install -e .[dev].
To run the beamformer / Kalman filter examples, use the commands:
python examples/run_2dcapon_kf.py --datafile=examples/1_target_theta0p8_phi0p2_omega50_noise0.csv
python examples/run_2dcapon_kf.py --datafile=examples/1_target_theta0p8_phi0p2_omega50_noise0p1.csv
Stone Soup is a software project to provide the target tracking and state estimation community with a framework for the development and testing of tracking and state estimation algorithms.
An article is available that details the background to the project, and contains links to sample data.
Stone Soup is currently in beta.
Please see the Stone Soup documentation for more information.
Please see the tutorials,
examples,
and demonstrations,
which you can also try out on Binder:
Stone Soup uses the following dependencies:
| Name | License |
|---|---|
| Python (v3.6+) | PSFL |
| numpy | BSD |
| SciPy | BSD |
| matplotlib | PSF/BSD-compatible |
| ruamel.yaml | MIT |
| pymap3d | MIT |
| utm | MIT |
| ordered-set | MIT |
| setuptools | MIT |
| rtree | MIT |
These dependencies are required for running Stone Soup tests.
| Name | License |
|---|---|
| pytest | MIT |
| Flake8 | MIT |
| Coverage.py | Apache 2.0 |
These dependencies are required for building Stone Soup documentation.
| Name | License |
|---|---|
| Sphinx | BSD |
| sphinx-gallery | BSD |
| pillow | PIL Software License |
| folium | MIT |
Stone Soup is released under MIT License. Please see License for details.