lsst.ap.pipe

The lsst.ap.pipe module links together a set of common image processing tasks so that a user may run one command on a dataset of raw, ingested images rather than several. The Alert Production (AP) pipeline includes the following key data processing Tasks for LSST Prompt Data Products: IsrTask, CharacterizeImageTask, CalibrateTask, ImageDifferenceTask, and DiaPipelineTask.

At present, the alert production pipeline is implemented using two separate frameworks that store and retrieve data from “Butler” repositories in incompatible ways:

• ApPipeTask is an lsst.pipe.base.CmdLineTask that reads and writes data using the lsst.daf.persistence package. This is the established “Gen 2” framework.

• ApPipe is an lsst.pipe.base.Pipeline that reads and writes data using the lsst.daf.butler package. This “Gen 3” framework is expected to be the only implementation in the future.

Overview

• Overview of the AP pipeline

Using lsst.ap.pipe in Gen 2

• Getting started with the AP pipeline (Gen 2)
• Running the AP pipeline (Gen 2)
• Setting up the Alert Production Database for ap_pipe

Using lsst.ap.pipe in Gen 3

• Getting started with the AP pipeline (Gen 3)
• Running the AP pipeline (Gen 3)
• Setting up the Alert Production Database for ap_pipe
• Running the AP pipeline in the Batch Production System (bps)

Contributing

lsst.ap.pipe is developed at https://github.com/lsst/ap_pipe. You can find Jira issues for this module under the ap_pipe component.

Script reference

• make_apdb.py

Task reference

Command-line tasks

ApPipeTask

Command-line task representing the entire AP pipeline.

Python API reference

lsst.ap.pipe Package

Classes

ApPipeConfig(*args, **kw)	Settings and defaults for ApPipeTask.
ApPipeTask(butler, *args, **kwargs)	Command-line task representing the entire AP pipeline.