Installation with conda#
Install#
Installation via a conda environment circumvents compatibility issues when installing certain libraries. This guide assumes you have a working installation of conda.
First, update conda:
conda update -n base -c defaults conda
Next, create a conda environment (we name this autogalaxy to signify it is for the PyAutoGalaxy install):
The command below creates this environment with some of the bigger package requirements, the rest will be installed via pip:
conda create -n autogalaxy astropy scikit-image scikit-learn scipy
Activate the conda environment (you will have to do this every time you want to run PyAutoGalaxy):
conda activate autogalaxy
We upgrade pip to ensure certain libraries install:
pip install --upgrade pip
The latest version of PyAutoGalaxy is installed via pip as follows (specifying the version as shown below ensures the installation has clean dependencies):
pip install autogalaxy
You may get warnings which state something like:
ERROR: autoarray 2024.1.27.4 has requirement numpy<=1.22.1, but you'll have numpy 1.22.2 which is incompatible.
ERROR: numba 0.53.1 has requirement llvmlite<0.37,>=0.36.0rc1, but you'll have llvmlite 0.38.0 which is incompatible.
If you see these messages, they do not mean that the installation has failed and the instructions below will identify clearly if the installation is a success.
If there are no errors (but only the warnings above) PyAutoGalaxy is installed!
If there is an error check out the troubleshooting section.
Numba#
Numba (https://numba.pydata.org) is an optional library which makes PyAutoGalaxy run a lot faster, which we strongly recommend users have installed.
You can install numba via the following command:
pip install numba
Some users have experienced difficulties installing numba, which is why it is an optional library. If your installation is not successful, you can use PyAutoGalaxy without it installed for now, to familiarize yourself with the software and determine if it is the right software for you.
If you decide that PyAutoGalaxy is the right software, then I recommend you commit the time to getting a successful numba install working, with more information provided at this readthedocs page
Workspace#
Next, clone the autogalaxy workspace (the line --depth 1 clones only the most recent branch on
the autogalaxy_workspace, reducing the download size):
cd /path/on/your/computer/you/want/to/put/the/autogalaxy_workspace
git clone https://github.com/Jammy2211/autogalaxy_workspace --depth 1
cd autogalaxy_workspace
Run the welcome.py script to get started!
python3 welcome.py
It should be clear that PyAutoGalaxy runs without issue.
If there is an error check out the troubleshooting section.
Optional#
For interferometer analysis there are two optional dependencies that must be installed via the commands:
pip install pynufft
pip install pylops==1.11.1
PyAutoGalaxy will run without these libraries and it is recommended that you only install them if you intend to do interferometer analysis.
If you run interferometer code a message explaining that you need to install these libraries will be printed, therefore it is safe not to install them initially.