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pz_analysis

This repository contains a Python package allowing for streamlined evaluation of RAIL photometric redshift estimation outputs. Evaluations focus on comparing the performance of different algorithms using simulated galaxy catalog.

Project Structure

  • src/: Source code for the functions related to photometric redshift output evaluation.

Template codecov PyPI

TODO List

To ensure that your project and repository is stable from the very start there are a few todo items that you should take care of. Unfortunately the RAIL project template can not do these for you, otherwise it would :)

Immediate actions

Before including in Rail-hub

  • Make sure your main branch is protected
  • Update this README
  • Create an example notebook
  • Run pylint on your code
  • Remove this TODO list once all items are completed

RAIL: Redshift Assessment Infrastructure Layers

This package is part of the larger ecosystem of Photometric Redshifts in RAIL.

Citing RAIL

This code, while public on GitHub, has not yet been released by DESC and is still under active development. Our release of v1.0 will be accompanied by a journal paper describing the development and validation of RAIL.

If you make use of the ideas or software in RAIL, please cite the repository https://github.com/LSSTDESC/RAIL. You are welcome to re-use the code, which is open source and available under terms consistent with the MIT license.

External contributors and DESC members wishing to use RAIL for non-DESC projects should consult with the Photometric Redshifts (PZ) Working Group conveners, ideally before the work has started, but definitely before any publication or posting of the work to the arXiv.

Citing this package

If you use this package, you should also cite the appropriate papers for each code used. A list of such codes is included in the Citing RAIL section of the main RAIL Read The Docs page.

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