Overview

PyAutoCTI requires Python 3.8 - 3.11 and support Linux and MacOS operating systems (Windows support is targeted in the future).

To use PyAutoCTI the c++ library arCTIc (https://github.com/jkeger/arctic) must also be installed. Installation instructions for arCTIc can be found both on its GitHub page and in the PyAutoCTI readthedocs.

PyAutoCTI can be installed via the Python distribution Anaconda or using Pypi to pip install PyAutoCTI into your Python distribution.

We recommend Anaconda as it manages the installation of many major libraries (e.g. numpy, scipy, matplotlib, etc.) making installation more straight forward.

The installation guide for both approaches can be found at:

• Anaconda installation guide

• PyPI installation guide

Users who wish to build PyAutoCTI from source (e.g. via a git clone) should follow our building from source installation guide.

Known Issues

There is a known issue installing PyAutoCTI via both conda and pip associated with the libraries llvmlite and numba. If your installation raises an error mentioning either library, follow the instructions in our troubleshooting section.

Dependencies

PyAutoCTI has the following dependencies:

PyAutoConf https://github.com/rhayes777/PyAutoConf

PyAutoFit https://github.com/rhayes777/PyAutoFit

PyAutoArray https://github.com/Jammy2211/PyAutoArray

dynesty https://github.com/joshspeagle/dynesty

emcee https://github.com/dfm/emcee

PySwarms https://github.com/ljvmiranda921/pyswarms

colossus: https://bdiemer.bitbucket.io/colossus/

astropy https://www.astropy.org/

corner.py https://github.com/dfm/corner.py

matplotlib https://matplotlib.org/

numba https://github.com/numba/numba

numpy https://numpy.org/

scipy https://www.scipy.org/

scikit-image: https://github.com/scikit-image/scikit-image

scikit-learn: https://github.com/scikit-learn/scikit-learn