azulero 0.4.1

Bring colors to Euclid tiles!

Bring colors to Euclid tiles!

Azul(ero)* downloads and merges VIS and NIR observations over a MER tile. It detects and inpaints bad pixels (hot and cold pixels, saturated stars...), and combines the 4 channels (I, Y, J, H) into an sRGB image.

*I started this project when Euclid EROs came out...

License

Apache-2.0

Disclaimer

⚠️ This is a beta version! ⚠️

• The tool is far from perfect and can be frustrating.
• Error cases are not handled and messages may be cryptic or misleading.
• Please make sure to read the "How to help?" section below before using this version.

Installation and setup

Install the azulero package with:

pip install azulero

If you wish to access Euclid-internal data, setup the ~/.netrc file for eas-dps-rest-ops.esac.esa.int and euclidsoc.esac.esa.int with your Euclid credentials:

machine eas-dps-rest-ops.esac.esa.int
  login <login>
  password <password>
machine euclidsoc.esac.esa.int
  login <login>
  password <password>

Basic usage

The typical workflow is as follows:

• 📥 Download the MER-processed FITS file of your tiles with azul retrieve.
• ✂️ Optionally select the region to be processed with azul crop.
• 🌟 Blend the channels and inpaint artifacts with azul process.

Usage:

azul [--workspace <workspace>] retrieve [--dsr <dataset_release>] [--from <provider>] <tile_indices>
azul [--workspace <workspace>] crop <tile_index>
azul [--workspace <workspace>] process <tile_slicing>

with:

• <workspace> - The parent directory to save everything, in which one folder per tile will be created (defaults to the current directory).
• <dataset_release> - The dataset release of the tiles to be downloaded (defaults to a list of known releases).
• <provider> - The data archive name.
• <tile_indices> - The space-separated list of tiles to be downloaded.
• <tile_index> - A single tile index.
• <tile_slicing> - A single tile index, optionally followed by a slicing à-la NumPy.

Example: The Ring Field

Here is an example output and the commands which produced it below:

azul retrieve 102159776 --from sas
azul crop 102159776
azul process 102159776[5500:7500,5000:7000] -w 2000 --nirl 0.1 --jr 0.9 --ib 0.5 -a 0.5 -b -1

I have post-processed the output to my liking:

The two thick blue rings 💍 are artifacts of the VIS instrument known as ghosts. To my knowledge, the galaxy in the center has never been resolved this way. Rendering the image allowed me to discover this is a splendid polar ring 💍 galaxy! The previously unseen golden structure top left may be an Einstein ring 💍 or a collisional ring 💍 -- the question remains open.

As you can see, getting a nice image required a bit of parametrization. This is because we are using the public Q1 data. DR1 data, to be published in 2026, have a much better signal-to-noise ratio, and default parameters give very good results. I already rendered the DR1 version of this field; I cannot share it today, but I can already tell you it is mesmerizing 😏

Advanced usage

One day I'll find some time to write something useful here... 🤔

In the meantime, please read the algorithm description and check help messages:

azul -h
azul retrieve -h
azul crop -h
azul process -h

How to help?

• Report bugs, request features, tell me what you think of the tool and results...
• Mention myself (Dr Antoine Basset, CNES) and/or azulero when you publish images processed with this tool.
• Share with me your images, I'm curious!

Contributors

• Dr Mischa Schirmer (MPIA): Azul's color blending is freely inspired by that Mischa's script eummy.py.
• Téo Bouvard (Thales): drafed retrieve.
• Rollin Gimenez (CNES): Fixed packaging.
• Kane Nguyen-Kim (IAP): Provided URLs for retrieving public data.

Acknowledgements

• 🔥 Congratulations to the whole Euclid community; The mosaics are simply unbelievable!
• 😍 Thank you also for answering my dummy questions on the contents of the images I posted.