FgcmCalibrateTractTableTask

FgcmCalibrateTractTableTask will run the full fgcmcal processing cycle on a single tract with multi-band coverage. Note that the results will not be as robust as a full global calibration because of the limited ability to track instrumental changes from observations in a single tract. Running FgcmCalibrateTractTableTask requires a look-up table generated by FgcmMakeLutTask.

FgcmCalibrateTractTableTask uses FgcmBuildStarsTableTask to extract stars from sourceTable_visit parquet tables. If only individual calexp source catalog files are available, use FgcmCalibrateTractTask instead.

FgcmCalibrateTractTableTask is available as a command-line task, fgcmCalibrateTractTable.py.

Processing summary

FgcmCalibrateTractTableTask runs the full fgcmcal processing, from building star lists to fitting to the output of final products. Specifically, it will:

1. Build the star lists: FgcmBuildStarsTableTask

2. Run the fitter until convergence: FgcmFitCycleTask

3. Output the final data products: FgcmOutputProductsTask

fgcmCalibrateTractTable.py command-line interface

fgcmCalibrateTractTable.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. The tract must be specified.

See also

See Command-line task argument reference for details and additional options.

Python API summary

from lsst.fgcmcal.fgcmCalibrateTractTable import FgcmCalibrateTractTableTask

classFgcmCalibrateTractTableTask(butler=None, **kwargs)

Calibrate a single tract using fgcmcal, using sourceTable_visit (parquet) input catalogs...

attributeconfig

Access configuration fields and retargetable subtasks.

methodrun(dataRefDict, tract, buildStarsRefObjLoader=None, returnCatalogs=True, butler=None)

Run the calibrations for a single tract with fgcm...

methodrunDataRef(butler, dataRefs)

Run full FGCM calibration on a single tract, including building star list, fitting multiple cycles, and making outputs...

See also

See the FgcmCalibrateTractTableTask API reference for complete details.

Butler datasets

When run as the fgcmCalibrateTractTable.py command-line task, or directly through the runDataRef method, FgcmCalibrateTractTableTask obtains datasets from the input Butler data repository and persists outputs to the output Butler data repository. Note that configurations for FgcmCalibrateTractTableTask, and its subtasks, affect what datasets are persisted and what their content is.

Input datasets

camera

Camera geometry and detector object

fgcmLookupTable

FGCM look-up table produced by FgcmMakeLutTask

Output datasets

fgcm_stars

Reference catalog of standard stars. See FgcmOutputProductsTask

fgcm_photoCalib_tract

One fgcm_photoCalib_tract photometric calibration file is output for each visit / ccd / tract.

transmission_atmosphere_fgcm_tract

One atmospheric transmission curve is output for each visit.

Retargetable subtasks

fgcmBuildStars

Default

lsst.fgcmcal.fgcmBuildStars.FgcmBuildStarsTask

Field type

ConfigurableField

Task to load and match stars for fgcm

fgcmOutputProducts

Default

lsst.fgcmcal.fgcmOutputProducts.FgcmOutputProductsTask

Field type

ConfigurableField

Task to output fgcm products

Configuration fields

connections

Data type

lsst.pipe.base.config.Connections

Field type

ConfigField

Configurations describing the connections of the PipelineTask to datatypes

convergenceTolerance

Default

0.005

Field type

float Field

Tolerance on repeatability convergence (per band)

doDebuggingPlots

Default

False

Field type

bool Field

Make plots for debugging purposes?

fgcmFitCycle

Data type

lsst.fgcmcal.fgcmFitCycle.FgcmFitCycleConfig

Field type

ConfigField

Config to run a single fgcm fit cycle

maxFitCycles

Default

5

Field type

int Field

Maximum number of fit cycles

saveMetadata

Default

True

Field type

bool Field

Flag to enable/disable metadata saving for a task, enabled by default.

Examples

fgcmCalibrateTractTable.py /datasets/hsc/repo --rerun <rerun name> --id visit=26024^26028^26032^26036^26044^26046^26048^26050^26058^26060^26062^26070^26072^26074^26080^26084^26094^23864^23868^23872^23876^23884^23886^23888^23890^23898^23900^23902^23910^23912^23914^23920^23924^28976^1258^1262^1270^1274^1278^1280^1282^1286^1288^1290^1294^1300^1302^1306^1308^1310^1314^1316^1324^1326^1330^24494^24504^24522^24536^24538^23212^23216^23224^23226^23228^23232^23234^23242^23250^23256^23258^27090^27094^27106^27108^27116^27118^27120^27126^27128^27130^27134^27136^27146^27148^27156^380^384^388^404^408^424^426^436^440^442^446^452^456^458^462^464^468^470^472^474^478^27032^27034^27042^27066^27068 ccd=0..8^10..103 tract=9615