LPipe - LRIS automated reduction pipeline

LPipe is a fully-automated, end-to-end high-level IDL pipeline for processing of single-object longslit and imaging data taken with the Low Resolution Imaging Spectrograph (LRIS) on Keck I.

The pipeline is designed to produce complete reductions (flux-calibrated 1D spectra and stacked imaging frames) given raw LRIS data and without any user input (in standard cases).

Download complete tarball
Installation guide
Detailed usage instructions


The pipeline was developed largely for the goal of securing immediate classifications of optical transients discovered by the Palomar Transient Factory while at the telescope (to inform real-time decisions about further follow-up) as well as to uniformly process deep imaging of large numbers of separate fields from a multi-year host-galaxy survey. However, it should be useful for all LRIS users interested in observations of individual sources (multi-slit modes are not yet supported). Frequent users who need to reduce large volumes of survey data quickly, as well as new users looking to reduce data without investing large amounts of time in learning details of the output file formats, may find it useful.

The codebase is all written in IDL, with the exception of an astrometric routine written in python (used for imaging alignment). SWarp and SExtractor are also required for the imaging pipeline.

LPipe generally takes a few hours to process a single night of observations on a standard modern workstation. (Depending on what binning modes were used and the nature of the observations it can be much faster or slower.)

The code is being constantly developed and improved to improve the quality of the output and robustness of the data processing, so check back on occasion for updates and bug fixes.



Required software:

GSFC IDLastro library (needed for all stages)
autoastrometry.py (needed for astrometric calibration)
SExtractor (needed for astrometric/photometric calibration)
SWarp (needed to coadd images)


Please don't hesitate to e-mail any questions or comments to Daniel Perley (dperley@astro.caltech.edu)