This is a wrapper to integrate the clustering redshift code yet_another_wizz (YAW) into RAIL:
- code: https://github.com/jlvdb/yet_another_wizz.git
- docs: https://yet-another-wizz.readthedocs.io/
- PyPI: https://pypi.org/project/yet_another_wizz/
- Docker: https://hub.docker.com/r/jlvdb/yet_another_wizz/
Original publication: https://arxiv.org/abs/2007.01846
The wrapper closely resembles the structure and functionality of YAW by implementing four different RAIL stages:
- YawCacheCreate, which implements the spatial patches of YAW data catalogues,
- YawAutoCorrelate/YawCrossCorrelate, which implement the expensive pair counting of the correlation measurements, and
- YawSummarize, which transforms the pair counts to a redshift estimate with an optional mitigation for galaxy sample bias.
The repository includes an extensive example notebook
examples/full_example.ipynb
with further documentation and an example ceci pipeline
src/rail/pipelines/estimation/yaw_pipeline.yml
for procesing large and/or more complex data sets.
This package is part of the larger ecosystem of Photometric Redshifts in 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.
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.