Welcome to ImagingLSS’s documentation!

ImagingLSS implements a data model of the DECALS imaging survey data. The intended use of ImagingLSS is to generate large scale structure catalogues and masks from the DECALS imaging survey data.

Conceptually, ImagingLSS is a consumer of the products of Legacy Pipe, the data pipe line of the DECam Legacy Survey.

Currently, DR2 is supported. Previous Data Releases are also supported (since Early Data Release, or EDR), though in the future we may drop the support in order to simplify the code base.

Users Guide

• Installation
  • Dependency
  • Data Dependency
  • Location of Data Release
  • DR2 at NERSC
  • Example Dataset
• Usage: Data Pipeline
  • Building the Cache
  • Generating Object Catalogue
  • Generating Complete Random Sky Mask
  • Apply Star veto mask
  • Query Completeness
  • Assemble Final Product
• Data Model
• Helper routines
  • WCS
• Working with Jupyter Notebook

API Reference

• API Reference
  • imaginglss package

Known Issues

• Due to internal caching of the catalogue, the running time is faster after first time.
• If the data release has updated (rare but it happened), and the cache files are out of date. Run forget_cache.py to clear the cache.

Indices and tables

• Index
• Module Index
• Search Page