Metadata-Version: 2.2
Name: pz-rail-som
Version: 1.1.2
Author-email: "LSST Dark Energy Science Collaboration (DESC)" <later@later.com>
License: MIT License
        
        Copyright (c) 2023 LSST Dark Energy Science Collaboration (DESC)
        
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Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: deprecated
Requires-Dist: pandas
Requires-Dist: pz-rail-base>=1.0.3
Requires-Dist: scikit-learn
Requires-Dist: minisom
Requires-Dist: somoclu
Provides-Extra: dev
Requires-Dist: qp-prob[full]; extra == "dev"
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: pre-commit; extra == "dev"
Requires-Dist: pylint; extra == "dev"

# RAIL som

[![Template](https://img.shields.io/badge/Template-LINCC%20Frameworks%20Python%20Project%20Template-brightgreen)](https://lincc-ppt.readthedocs.io/en/latest/)
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[![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/LSSTDESC/rail_som/smoke-test.yml)](https://github.com/LSSTDESC/rail_som/actions/workflows/smoke-test.yml)

**somoclu** - RAIL estimator, summarizer, and classifier using the somoclu implementation of Self-Organizing Maps

# RAIL: Redshift Assessment Infrastructure Layers

RAIL is a flexible software library providing tools to produce at-scale
photometric redshift data products, including uncertainties and summary
statistics, and stress-test them under realistically complex systematics.
A detailed description of RAIL's modular structure is available in the 
[Overview](https://lsstdescrail.readthedocs.io/en/latest/source/overview.html) 
on ReadTheDocs.

RAIL serves as the infrastructure supporting many extragalactic applications 
of the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory,
including Rubin-wide commissioning activities. RAIL was initiated by the
Photometric Redshifts (PZ) Working Group (WG) of the LSST Dark Energy Science 
Collaboration (DESC) as a result of the lessons learned from the 
[Data Challenge 1 (DC1) experiment](https://academic.oup.com/mnras/article/499/2/1587/5905416) 
to enable the PZ WG Deliverables in 
[the LSST-DESC Science Roadmap (see Sec. 5.18)](https://lsstdesc.org/assets/pdf/docs/DESC_SRM_latest.pdf), 
aiming to guide the selection and implementation of redshift estimators in DESC
analysis pipelines. RAIL is developed and maintained by a diverse team
comprising DESC Pipeline Scientists (PSs), international in-kind contributors,
LSST Interdisciplinary Collaboration for Computing (LINCC) Frameworks software
engineers, and other volunteers, but all are welcome to join the team
regardless of LSST data rights. 

## Installation

Installation instructions are available under 
[Installation](https://lsstdescrail.readthedocs.io/en/latest/source/installation.html)
on ReadTheDocs.

## Contributing

The greatest strength of RAIL is its extensibility; those interested in
contributing to RAIL should start by consulting the 
[Contributing guidelines](https://lsstdescrail.readthedocs.io/en/latest/source/contributing.html)
on ReadTheDocs.

## Citing RAIL

RAIL is open source and may be used according to the terms of its 
[LICENSE](https://github.com/LSSTDESC/RAIL/blob/main/LICENSE) 
[(BSD 3-Clause)](https://opensource.org/licenses/BSD-3-Clause).
If you make use of the ideas or software here in any publication, you must cite
this repository <https://github.com/LSSTDESC/RAIL> as "LSST-DESC PZ WG (in prep)" 
with the [Zenodo DOI](https://doi.org/10.5281/zenodo.7017551).
Please consider also inviting the developers as co-authors on publications
resulting from your use of RAIL by 
[making an issue](https://github.com/LSSTDESC/RAIL/issues/new/choose).
Additionally, several of the codes accessible through the RAIL ecosystem must 
be cited if used in a publication. A convenient list of what to cite may be found under 
[Citing RAIL](https://lsstdescrail.readthedocs.io/en/latest/source/citing.html) on ReadTheDocs.
