Installation Guide | readthedocs | Introduction on Binder | HowToGalaxy
Welcome to the PyAutoGalaxy Workspace. You can get started right away by going to the autogalaxy workspace Binder. Alternatively, you can get set up by following the installation guide on our readthedocs.
We recommend new users begin by looking at the following notebooks:
notebooks/overview: Examples giving an overview of PyAutoGalaxy's core features.notebooks/howtogalaxy: Detailed step-by-step Jupyter notebook lectures on how to use PyAutoGalaxy.
If you haven't already, install PyAutoGalaxy via pip or conda.
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_workspaceRun the welcome.py script to get started!
python3 welcome.pyThe workspace includes the following main directories:
notebooks: PyAutoGalaxy examples written as Jupyter notebooks.scripts: PyAutoGalaxy examples written as Python scripts.config: Configuration files which customize PyAutoGalaxy's behaviour.dataset: Where data is stored, including example datasets distributed.output: Where the PyAutoGalaxy analysis and visualization are output.
The examples in the notebooks and scripts folders are structured as follows:
overview: Examples giving an overview of PyAutoGalaxy's core features.howtogalaxy: Detailed step-by-step Jupyter notebook lectures on how to use PyAutoGalaxy.imaging: Examples for analysing and simulating CCD imaging data (e.g. Hubble, Euclid).interferometer: Examples for analysing and simulating interferometer datasets (e.g. ALMA, JVLA).multi: Modeling multiple datasets simultaneously (E.g. multi-wavelength imaging, imaging and interferometry).plot: An API reference guide for PyAutoGalaxy's plotting tools.misc: Miscellaneous scripts for specific galaxy analysis.
Inside these packages are packages titled advanced which only users familiar PyAutoGalaxy should check out.
In the imaging, interferometer, and multi folders you'll find the following packages:
modeling: Examples of how to fit a galaxy model to data via a non-linear search.simulators: Scripts for simulating realistic imaging and interferometer data of strong galaxies.data_preparation: Tools to preprocessdatabefore an analysis (e.g. convert units, create masks).results: Examples using the results of a model-fit.advanced: Advanced modeling scripts which use PyAutoGalaxy's advanced features.
The files README.rst distributed throughout the workspace describe what is in each folder.
We recommend new users begin with the example notebooks / scripts in the overview folder and the HowToGalaxy tutorials.
This version of the workspace is built and tested for using PyAutoGalaxy v2024.1.27.4.
Included is the HowToGalaxy lecture series, which provides an introduction to strong gravitational galaxy modeling. It can be found in the workspace & consists of 5 chapters:
Introduction: An introduction to galaxy morphology & PyAutoGalaxy.Galaxy Modeling: How to model strong galaxies, including a primer on Bayesian analysis and model-fitting via a non-linear search .Search Chaining: Chaining non-linear searches together to build model-fitting pipelines & tailor them to your own science case.Pixelizations: How to perform pixelized reconstructions of a galaxy.
To make changes in the tutorial notebooks, please make changes in the corresponding python files(.py) present in the scripts folder of each chapter. Please note that marker # %% alternates between code cells and markdown cells.
Support for installation issues, help with galaxy modeling and using PyAutoGalaxy is available by raising an issue on the autogalaxy_workspace GitHub page. or joining the PyAutoGalaxy Slack channel, where we also provide the latest updates on PyAutoGalaxy.
Slack is invitation-only, so if you'd like to join send an email requesting an invite.