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testDonutFromRefitWcsPipeline.yaml
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testDonutFromRefitWcsPipeline.yaml
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# This yaml file is used to define the tasks and configuration of
# a Gen 3 pipeline used for testing in ts_wep.
description: wep basic processing test pipeline
# Here we specify the corresponding instrument for the data we
# will be using.
instrument: lsst.obs.lsst.LsstCam
# Then we can specify each task in our pipeline by a name
# and then specify the class name corresponding to that task
tasks:
isr:
class: lsst.ip.isr.isrTask.IsrTask
# Below we specify the configuration settings we want to use
# when running the task in this pipeline. Since our data doesn't
# include bias or flats we only want to use doApplyGains and
# doOverscan in our isr task.
config:
connections.outputExposure: "preFitPostISRCCD"
doBias: False
doVariance: False
doLinearize: False
doCrosstalk: False
doDefect: False
doNanMasking: False
doInterpolate: False
doBrighterFatter: False
doDark: False
doFlat: False
doApplyGains: True
doFringe: False
doOverscan: True
python: OverscanCorrectionTask.ConfigClass.fitType = 'MEDIAN'
generateDonutDirectDetectTask:
class: lsst.ts.wep.task.generateDonutDirectDetectTask.GenerateDonutDirectDetectTask
config:
connections.donutCatalog: "directDetectDonutTable"
connections.exposure: "preFitPostISRCCD"
generateDonutFromRefitWcsTask:
class: lsst.ts.wep.task.generateDonutFromRefitWcsTask.GenerateDonutFromRefitWcsTask
config:
connections.astromRefCat: "cal_ref_cat"
connections.photoRefCat: "cal_ref_cat"
astromRefFilter: "g"
astromTask.referenceSelector.doMagLimit: False
donutSelector.unblendedSeparation: 1
cutOutDonutsScienceSensorTask:
class: lsst.ts.wep.task.cutOutDonutsScienceSensorTask.CutOutDonutsScienceSensorTask
config:
# Test with default instrument configuration parameters
donutStampSize: 160
initialCutoutPadding: 40
calcZernikesTask:
class: lsst.ts.wep.task.calcZernikesTask.CalcZernikesTask