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I’ve never used RAIL, what does it do?

RAIL is a software library that can produce and test photometric redshifts (photo-zs) from many different codes at scale. With RAIL, users can:

  • create realistic sample galaxy photometric data for testing against photo-z codes

  • estimate photo-z distributions for single galaxies or entire populations, given either real or simulated data

  • evaluate the accuracy of the photo-zs against their ground truth

How do I install RAIL quickly?

There are two methods of installing RAIL quickly for use on your computer.

The first method is via the easy install script, which can be found in the releases page of the RAIL setup repository. Download and run the Python script, which will do an interactive question-based installation.

wget https://github.com/LSSTDESC/rail_setup/releases/latest/download/install_rail.py
python install_rail.py

Follow the prompts for installation. This script installs RAIL in a conda environment [env] (the name you enter when prompted), which is activated via

conda activate [env]

The second method is via running within a Docker container with RAIL installed. The RAIL image can be found on the LSSTDESC packages page. Pull the image, then build and run your container.

For more detailed instructions, visit the Installation page.

I’ve installed, now what?

Take a look at some of the examples to play with in the Interactive Mode Notebooks, including how to estimate the photometric redshift of a galaxy with known photometry across multiple photo-z codes.

I want to learn more, where should I go next?

To learn more about RAIL and its stages, visit the RAIL Stages section, starting with the What Are RAIL Stages? page.

To learn how to contribute, visit the Contributor Concepts page.

I’ve used RAIL, how do I credit it?

To learn how to cite RAIL, visit the Citations page.