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tickets/DM-47164: Update to new ISR task #278

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tickets/DM-47164: Update to new ISR task #278

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3215888
Updated ISR tasks in pipeline files.
jfcrenshaw Oct 27, 2024
197df0a
Updated change log
jfcrenshaw Oct 27, 2024
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8 changes: 8 additions & 0 deletions doc/versionHistory.rst
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Expand Up @@ -6,6 +6,14 @@
Version History
##################

.. _lsst.ts.wep-12.4.0:

-------------
12.4.0
-------------

* Updated to use new ISR task (lsst.ip.isr.IsrTask --> lsst.ip.isr.IsrTaskLSST)

.. _lsst.ts.wep-12.3.0:

-------------
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28 changes: 10 additions & 18 deletions pipelines/directDetect/cwfsDirectDetectPipeline.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,27 +8,19 @@ instrument: lsst.obs.lsst.LsstCam
# 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.
class: lsst.ip.isr.IsrTaskLSST
config:
connections.outputExposure: "postISRCCD"
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
doAmpOffset: true
ampOffset.doApplyAmpOffset: false
# Turn off slow steps in ISR
doBrighterFatter: false
doCrosstalk: false
# Turn off flats, biases, darks because we don't have these in test repo
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:
Expand All @@ -40,4 +32,4 @@ tasks:
config:
estimateZernikes.maxNollIndex: 28
estimateZernikes.saveHistory: False
estimateZernikes.maskKwargs: {'doMaskBlends': False}
estimateZernikes.maskKwargs: { "doMaskBlends": False }
28 changes: 10 additions & 18 deletions pipelines/directDetect/scienceDirectDetectPipeline.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,27 +8,19 @@ instrument: lsst.obs.lsst.LsstCam
# 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.
class: lsst.ip.isr.IsrTaskLSST
config:
connections.outputExposure: "postISRCCD"
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
doAmpOffset: true
ampOffset.doApplyAmpOffset: false
# Turn off slow steps in ISR
doBrighterFatter: false
doCrosstalk: false
# Turn off flats, biases, darks because we don't have these in test repo
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:
Expand All @@ -40,4 +32,4 @@ tasks:
config:
estimateZernikes.maxNollIndex: 28
estimateZernikes.saveHistory: False
estimateZernikes.maskKwargs: {'doMaskBlends': False}
estimateZernikes.maskKwargs: { "doMaskBlends": False }
4 changes: 2 additions & 2 deletions pipelines/production/comCamRapidAnalysisPipeline.yaml
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Expand Up @@ -19,9 +19,9 @@ tasks:
config:
estimateZernikes.maxNollIndex: 28
estimateZernikes.saveHistory: False
estimateZernikes.maskKwargs: {'doMaskBlends': False}
estimateZernikes.maskKwargs: { "doMaskBlends": False }
isr:
class: lsst.ip.isr.IsrTask
class: lsst.ip.isr.IsrTaskLSST
config:
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
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4 changes: 2 additions & 2 deletions pipelines/production/comCamSimRapidAnalysisPipeline.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -19,9 +19,9 @@ tasks:
config:
estimateZernikes.maxNollIndex: 28
estimateZernikes.saveHistory: False
estimateZernikes.maskKwargs: {'doMaskBlends': False}
estimateZernikes.maskKwargs: { "doMaskBlends": False }
isr:
class: lsst.ip.isr.IsrTask
class: lsst.ip.isr.IsrTaskLSST
config:
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
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26 changes: 9 additions & 17 deletions tests/testData/pipelineConfigs/testBasePipeline.yaml
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Expand Up @@ -8,26 +8,18 @@ instrument: lsst.obs.lsst.LsstCam
# 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.
class: lsst.ip.isr.IsrTaskLSST
config:
connections.outputExposure: 'postISRCCD'
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
doAmpOffset: true
ampOffset.doApplyAmpOffset: false
# Turn off slow steps in ISR
doBrighterFatter: false
doCrosstalk: false
# Turn off flats, biases, darks because we don't have these in test repo
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'
generateDonutCatalogWcsTask:
class: lsst.ts.wep.task.generateDonutCatalogWcsTask.GenerateDonutCatalogWcsTask
26 changes: 9 additions & 17 deletions tests/testData/pipelineConfigs/testCalcZernikesCwfsSetupPipeline.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,27 +8,19 @@ instrument: lsst.obs.lsst.LsstCam
# 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.
class: lsst.ip.isr.IsrTaskLSST
config:
connections.outputExposure: "postISRCCD"
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
doAmpOffset: true
ampOffset.doApplyAmpOffset: false
# Turn off slow steps in ISR
doBrighterFatter: false
doCrosstalk: false
# Turn off flats, biases, darks because we don't have these in test repo
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'
generateDonutCatalogWcsTask:
class: lsst.ts.wep.task.generateDonutCatalogWcsTask.GenerateDonutCatalogWcsTask
config:
Expand Down
26 changes: 9 additions & 17 deletions tests/testData/pipelineConfigs/testCalcZernikesLatissPipeline.yaml
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Expand Up @@ -4,27 +4,19 @@ description: wep basic processing test pipeline
instrument: lsst.obs.lsst.Latiss
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.
class: lsst.ip.isr.IsrTaskLSST
config:
connections.outputExposure: "postISRCCD"
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
doAmpOffset: true
ampOffset.doApplyAmpOffset: false
# Turn off slow steps in ISR
doBrighterFatter: false
doCrosstalk: false
# Turn off flats, biases, darks because we don't have these in test repo
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_PER_ROW'
generateDonutDirectDetectTask:
class: lsst.ts.wep.task.generateDonutDirectDetectTask.GenerateDonutDirectDetectTask
config:
Expand Down
26 changes: 9 additions & 17 deletions tests/testData/pipelineConfigs/testCalcZernikesScienceSensorSetupPipeline.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,27 +8,19 @@ instrument: lsst.obs.lsst.LsstCam
# 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.
class: lsst.ip.isr.IsrTaskLSST
config:
connections.outputExposure: "postISRCCD"
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
doAmpOffset: true
ampOffset.doApplyAmpOffset: false
# Turn off slow steps in ISR
doBrighterFatter: false
doCrosstalk: false
# Turn off flats, biases, darks because we don't have these in test repo
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'
generateDonutCatalogWcsTask:
class: lsst.ts.wep.task.generateDonutCatalogWcsTask.GenerateDonutCatalogWcsTask
config:
Expand Down
26 changes: 9 additions & 17 deletions tests/testData/pipelineConfigs/testCutoutsCwfsPipeline.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,27 +8,19 @@ instrument: lsst.obs.lsst.LsstCam
# 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.
class: lsst.ip.isr.IsrTaskLSST
config:
connections.outputExposure: "postISRCCD"
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
doAmpOffset: true
ampOffset.doApplyAmpOffset: false
# Turn off slow steps in ISR
doBrighterFatter: false
doCrosstalk: false
# Turn off flats, biases, darks because we don't have these in test repo
doBias: False
doVariance: True
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'
generateDonutCatalogWcsTask:
class: lsst.ts.wep.task.generateDonutCatalogWcsTask.GenerateDonutCatalogWcsTask
config:
Expand Down
26 changes: 9 additions & 17 deletions tests/testData/pipelineConfigs/testCutoutsFamPipeline.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,27 +8,19 @@ instrument: lsst.obs.lsst.LsstCam
# 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.
class: lsst.ip.isr.IsrTaskLSST
config:
connections.outputExposure: "postISRCCD"
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
doAmpOffset: true
ampOffset.doApplyAmpOffset: false
# Turn off slow steps in ISR
doBrighterFatter: false
doCrosstalk: false
# Turn off flats, biases, darks because we don't have these in test repo
doBias: False
doVariance: True
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'
generateDonutCatalogWcsTask:
class: lsst.ts.wep.task.generateDonutCatalogWcsTask.GenerateDonutCatalogWcsTask
config:
Expand Down
26 changes: 9 additions & 17 deletions tests/testData/pipelineConfigs/testCutoutsLatissPipeline.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,27 +8,19 @@ instrument: lsst.obs.lsst.Latiss
# 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.
class: lsst.ip.isr.IsrTaskLSST
config:
connections.outputExposure: "postISRCCD"
# Although we don't have to apply the amp offset corrections, we do want
# to compute them for analyzeAmpOffsetMetadata to report on as metrics.
doAmpOffset: true
ampOffset.doApplyAmpOffset: false
# Turn off slow steps in ISR
doBrighterFatter: false
doCrosstalk: false
# Turn off flats, biases, darks because we don't have these in test repo
doBias: False
doVariance: True
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_PER_ROW'
generateDonutDirectDetectTask:
class: lsst.ts.wep.task.generateDonutDirectDetectTask.GenerateDonutDirectDetectTask
cutOutDonutsScienceSensorTask:
Expand Down
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