This is a wrapper for RAIL (see below) to integrate the clustering redshift code yet_another_wizz:
- 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/
The current wrapper implements most of the functionality of yet_another_wizz, which is an external dependency for this package. The wrapper currently implements five different stages and three custom data handles:
- A cache directory, which stores a data set and its corresponding random points. Both catalogs are split into spatial patches which are used for the covariance estimation. The cache directory is created and destroyed with two dedicated stages.
- A handle for yet_another_wizz pair count data (stored as HDF5 file), which are created as outputs of the cross- and autocorrelation stages.
- A handle for yet_another_wizz clustering redshift estimates (stored as python pickle file), which is created by the final estimator summary stage.
A jupyter notebook containing a full example with more detailed descriptions is included in
examples/full_example.ipynb
and an example RAIL pipeline can be generated an executed with code found in
src/rail/pipelines/estimation/algos
The summary stage produces a qp.Ensemble, but does so by simply setting all
negative correlation amplitudes in all generated (spatial) samples to zero.
This needs refinement in a future release. For now it is advised to use the
second output of the summary stage, which is the raw clutering redshift estimate
from yet_another_wizz (yaw.RedshiftData).
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.