FgcmBuildStarsTableTask¶
FgcmBuildStarsTableTask finds all the single-visit sources in a repository (or a subset based on command-line parameters) from sourceTable_visit parquet tables and extracts all the potential photometric calibration stars for input into fgcm.
This task additionally uses fgcm to match star observations into unique stars, and performs as much cleaning of the input catalog as possible.
A tutorial on the steps of running fgcmcal are found in the cookbook.
This fgcmcal task runs on sourceTable_visit catalogs from visits constrained by the --id parameter on the command line.
At the current time, fgcmcal does not support Gen3.
This is the second task in a typical fgcmcal processing chain.
The first is FgcmMakeLutTask, the third is FgcmFitCycleTask, and the fourth is FgcmOutputProductsTask.
FgcmBuildStarsTableTask is available as a command-line task, fgcmBuildStarsTable.py.
Processing summary¶
FgcmBuildStarsTableTask runs this sequence of operations:
- Finds unique visits and collates visit metadata, including exposure time, pointing, typical psf size, background level.
- Reads in all sources, selecting good stars according to the chosen source selector.
- Matches sources internally across bands to get a unique multi-band list of possible calibration stars.
- Matches possible calibration stars to a reference catalog.
- All results are stored in the output repo
fgcm-processdirectory.
fgcmBuildStarsTable.py command-line interface¶
fgcmBuildStarsTable.py REPOPATH [@file [@file2 ...]] [--output OUTPUTREPO | --rerun RERUN] [--id] [other options]
Key arguments:
REPOPATH- The input Butler repository’s URI or file path.
Key options:
--id:- The data IDs to process.
See also
See Command-line task argument reference for details and additional options.
Python API summary¶
from lsst.fgcmcal.fgcmBuildStarsTable import FgcmBuildStarsTableTask
-
class
FgcmBuildStarsTableTask Build stars for the FGCM global calibration, using sourceTable_visit catalogs
...
-
attribute
config Access configuration fields and retargetable subtasks.
-
method
runDataRef Cross-match and make star list for FGCM Input
...
See also
See the FgcmBuildStarsTableTask API reference for complete details.
Butler datasets¶
When run as the fgcmBuildStarsTable.py command-line task, or directly through the runDataRef method, FgcmBuildStarsTableTask obtains datasets from the input Butler data repository and persists outputs to the output Butler data repository.
Note that configurations for FgcmBuildStarsTableTask, and its subtasks, affect what datasets are persisted and what their content is.
Input datasets¶
sourceTable_visit- Full-depth source catalog, per-visit, in parquet format
calexp(s)- Calibrated exposures produced by
ProcessCcdTask(for exposure metadata) fgcmLookupTable- FGCM look-up table produced by FgcmMakeLutTask
Output datasets¶
fgcmVisitCatalog- Catalog (
lsst.afw.table) of visit metadata fgcmStarObservations- Catalog of star observations
fgcmStarIds- Catalog of unique star ids, positions, and number of observations
fgcmStarIndices- Catalog of indices linking unique star ids to star observations
fgcmReferenceStars- Catalog of reference stars matched to unique star ids.
Retargetable subtasks¶
fgcmLoadReferenceCatalog¶
- Default
lsst.fgcmcal.fgcmLoadReferenceCatalog.FgcmLoadReferenceCatalogTask- Field type
ConfigurableField
sourceSelector¶
- Default
'science'- Field type
- Single-selection
RegistryField - Choices
'science'lsst.meas.algorithms.sourceSelector.ScienceSourceSelectorTask'references'lsst.meas.algorithms.sourceSelector.ReferenceSourceSelectorTask'objectSize'lsst.meas.algorithms.objectSizeStarSelector.ObjectSizeStarSelectorTask'flagged'lsst.meas.algorithms.flaggedSourceSelector.FlaggedSourceSelectorTask'astrometry'lsst.meas.algorithms.astrometrySourceSelector.AstrometrySourceSelectorTask'matcher'lsst.meas.algorithms.matcherSourceSelector.MatcherSourceSelectorTask'diaCatalog'lsst.ip.diffim.diaCatalogSourceSelector.DiaCatalogSourceSelectorTask