Skip to main content

No project description provided

Project description

RAIL base

Template DOI codecov PyPI GitHub Workflow Status

Bases classes for RAIL stages.

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 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 to enable the PZ WG Deliverables in the LSST-DESC Science Roadmap (see Sec. 5.18), 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 on ReadTheDocs.

Contributing

The greatest strength of RAIL is its extensibility; those interested in contributing to RAIL should start by consulting the Contributing guidelines on ReadTheDocs.

Citing RAIL

RAIL is open source and may be used according to the terms of its LICENSE (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. Please consider also inviting the developers as co-authors on publications resulting from your use of RAIL by making an issue. 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 on ReadTheDocs.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pz_rail_base-1.0.6.tar.gz (6.5 MB view details)

Uploaded Source

Built Distribution

pz_rail_base-1.0.6-py3-none-any.whl (6.5 MB view details)

Uploaded Python 3

File details

Details for the file pz_rail_base-1.0.6.tar.gz.

File metadata

  • Download URL: pz_rail_base-1.0.6.tar.gz
  • Upload date:
  • Size: 6.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for pz_rail_base-1.0.6.tar.gz
Algorithm Hash digest
SHA256 8ec34084e994f7bc322a0bdbbcdfa35bf2ef44580f606d0e872c70de63f43cb9
MD5 3a1fb3a558d3d2b3c97974b196695c92
BLAKE2b-256 d1eee98390b19c2c6b9740628fa0741ed845a4f78031874badbd44a360b3ad65

See more details on using hashes here.

Provenance

File details

Details for the file pz_rail_base-1.0.6-py3-none-any.whl.

File metadata

File hashes

Hashes for pz_rail_base-1.0.6-py3-none-any.whl
Algorithm Hash digest
SHA256 b1eab83ebfc6bf20dfdc563c50ae35bdbbaca259af723dd051c988141d97f7ea
MD5 7392e9507541a3e3691dcf910d18b7d6
BLAKE2b-256 ffe7dfc935a30d2d302c9f70fe0682b86edcc643cbef2ee48bc885ad957bafb4

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page