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 anlsst.pipe.base.CmdLineTask
that reads and writes data using the lsst.daf.persistence package. This is the established “Gen 2” framework.ApPipe
is anlsst.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¶
Using lsst.ap.pipe in Gen 2¶
Using lsst.ap.pipe in Gen 3¶
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¶
Task reference¶
Command-line tasks¶
- ApPipeTask
- Command-line task representing the entire AP pipeline.
Python API reference¶
lsst.ap.pipe Package¶
Classes¶
ApPipeConfig |
Settings and defaults for ApPipeTask. |
ApPipeTask (butler, *args, **kwargs) |
Command-line task representing the entire AP pipeline. |