Differentiable Ray Tracing (RT) Python framework for Telecommunications-oriented applications.
Important
For 3D scenarios at city-scales, checkout DiffeRT.
While installing DiffeRT2d and its dependencies on your global Python is fine, we recommend using a virtual environment (e.g., venv) for a local installation.
DiffeRT2d uses JAX for automatic differentation, which in turn may use (or not) CUDA for GPU acceleration.
If needed, please refer to JAX's installation guidelines for more details.
The recommended way to install the latest release is to use pip:
pip install differt2dAn alternative way to install DiffeRT2d is to clone the git repository, and install from there: read the contributing guide to know how.
For a quick introduction to DiffeRT2d, check you our Quickstart tutorial!
You may find a multitude of usage examples across the documentation or the examples folder, or directly in the examples gallery.
Contributions are more than welcome! Please read through our contributing section.
If you think you found a bug, an error in the documentation, or wish there was some feature that is currently missing, we would love to hear from you!
The best way to reach us is via the GitHub issues. If your problem is not covered by an already existing (closed or open) issue, then we suggest you create a new issue.
The more precise you are in the description of your problem, the faster we will be able to help you!
Sometimes, you may have a question about , not necessarily an issue.
There are two ways you can reach us for questions:
- via the GitHub issues;
- or via GitHub discussions.
Finally, if you do not have any GitHub account, or just wish to contact the author of DiffeRT2d, you can do so at: jeertmans@icloud.com.