pyTomoAO is an open-source Python library for tomographic reconstruction in tomography-based Adaptive Optics (AO) systems. It provides tools to reconstruct atmospheric turbulence phase maps and project them onto deformable mirrors for different AO architectures, including:
- LTAO (Laser Tomography Adaptive Optics)
- MOAO (Multi-Object Adaptive Optics)
- Support for LTAO, and MOAO tomographic reconstructions.
- Efficient numerical solvers for tomographic phase reconstruction.
- Tools for fitting reconstructed phase maps onto deformable mirrors.
- Extensible and modular design to allow easy adaptation to different AO systems.
- Optimized for performance with NumPy, SciPy, and Numba.
pip install git+https://github.com/jacotay7/pyTomoAO.gitor clone the repository:
git clone https://github.com/jacotay7/pyTomoAO.git
cd pyTomoAO
pip install -e .import pyTomoAO
# Example usage coming soon- Implement fundamental reconstruction algorithms.
- Add GPU acceleration for real-time processing.
- Improve deformable mirror fitting routines.
- Develop detailed documentation and examples.
- Implement MCAO reconstructor
git clone https://github.com/jacotay7/pyTomoAO.git
cd pyTomoAO
pip install .To build the documentation, you need to install the package with the documentation dependencies and then run the build command:
pip install .[docs]
cd docs
make htmlTo run tests using pytest, ensure you have pytest installed. You can install it via pip:
pip install pytestOnce installed, you can run the tests by executing the following command in the root directory of the repository:
pytestThis will automatically discover and run all the test files in the repository.
Contributions are welcome! Feel free to open issues or submit pull requests.
TODO
For questions and discussions, open an issue on GitHub or contact one of:
- Jacob Taylor (Software): jtaylor@keck.hawaii.edu
- Uriel Conod (Algorithm): urielconod@phas.ubc.ca