DcrAssembleCoaddTask¶
- class lsst.pipe.tasks.dcrAssembleCoadd.DcrAssembleCoaddTask(*args, **kwargs)¶
Bases:
CompareWarpAssembleCoaddTask
Assemble DCR coadded images from a set of warps.
Notes
As with AssembleCoaddTask, we want to assemble a coadded image from a set of Warps (also called coadded temporary exposures), including the effects of Differential Chromatic Refraction (DCR). For full details of the mathematics and algorithm, please see DMTN-037: DCR-matched template generation (https://dmtn-037.lsst.io).
This Task produces a DCR-corrected deepCoadd, as well as a dcrCoadd for each subfilter used in the iterative calculation. It begins by dividing the bandpass-defining filter into N equal bandwidth “subfilters”, and divides the flux in each pixel from an initial coadd equally into each as a “dcrModel”. Because the airmass and parallactic angle of each individual exposure is known, we can calculate the shift relative to the center of the band in each subfilter due to DCR. For each exposure we apply this shift as a linear transformation to the dcrModels and stack the results to produce a DCR-matched exposure. The matched exposures are subtracted from the input exposures to produce a set of residual images, and these residuals are reverse shifted for each exposures’ subfilters and stacked. The shifted and stacked residuals are added to the dcrModels to produce a new estimate of the flux in each pixel within each subfilter. The dcrModels are solved for iteratively, which continues until the solution from a new iteration improves by less than a set percentage, or a maximum number of iterations is reached. Two forms of regularization are employed to reduce unphysical results. First, the new solution is averaged with the solution from the previous iteration, which mitigates oscillating solutions where the model overshoots with alternating very high and low values. Second, a common degeneracy when the data have a limited range of airmass or parallactic angle values is for one subfilter to be fit with very low or negative values, while another subfilter is fit with very high values. This typically appears in the form of holes next to sources in one subfilter, and corresponding extended wings in another. Because each subfilter has a narrow bandwidth we assume that physical sources that are above the noise level will not vary in flux by more than a factor of
frequencyClampFactor
between subfilters, and pixels that have flux deviations larger than that factor will have the excess flux distributed evenly among all subfilters. IfsplitSubfilters
is set, then each subfilter will be further sub- divided during the forward modeling step (only). This approximates using a higher number of subfilters that may be necessary for high airmass observations, but does not increase the number of free parameters in the fit. This is needed when there are high airmass observations which would otherwise have significant DCR even within a subfilter. Because calculating the shifted images takes most of the time, splitting the subfilters is turned off by way of thesplitThreshold
option for low-airmass observations that do not suffer from DCR within a subfilter.- Attributes:
- bufferSize
int
The number of pixels to grow each subregion by to allow for DCR.
- bufferSize
Attributes Summary
Methods Summary
applyAltEdgeMask
(mask, altMaskList)Propagate alt EDGE mask to SENSOR_EDGE AND INEXACT_PSF planes.
applyAltMaskPlanes
(mask, altMaskSpans)Apply in place alt mask formatted as SpanSets to a mask.
applyModelWeights
(modelImages, refImage, ...)Smoothly replace model pixel values with those from a reference at locations away from detected sources.
assembleMetadata
(coaddExposure, ...)Set the metadata for the coadd.
assembleOnlineMeanCoadd
(coaddExposure, ...)Assemble the coadd using the "online" method.
assembleSubregion
(coaddExposure, bbox, ...)Assemble the coadd for a sub-region.
calculateConvergence
(dcrModels, ...)Calculate a quality of fit metric for the matched templates.
calculateGain
(convergenceList, gainList)Calculate the gain to use for the current iteration.
calculateModelWeights
(dcrModels, dcrBBox)Build an array that smoothly tapers to 0 away from detected sources.
calculateNImage
(dcrModels, bbox, ...)Calculate the number of exposures contributing to each subfilter.
calculateSingleConvergence
(dcrModels, ...)Calculate a quality of fit metric for a single matched template.
dcrAssembleSubregion
(dcrModels, ...)Assemble the DCR coadd for a sub-region.
dcrResiduals
(residual, visitInfo, wcs, ...)Prepare a residual image for stacking in each subfilter by applying the reverse DCR shifts.
Empty (clear) the metadata for this Task and all sub-Tasks.
fillCoadd
(dcrModels, skyInfo, warpRefList, ...)Create a list of coadd exposures from a list of masked images.
filterArtifacts
(spanSetList, ...[, ...])Filter artifact candidates.
filterWarps
(inputs, goodVisits)Return list of only inputRefs with visitId in goodVisits ordered by goodVisit.
findArtifacts
(templateCoadd, tempExpRefList, ...)Find artifacts.
Convenience method to provide the bitmask from the mask plane names
Get metadata for all tasks.
Get the task name as a hierarchical name including parent task names.
getName
()Get the name of the task.
Get a dictionary of all tasks as a shallow copy.
getTempExpDatasetName
([warpType])Return warp name for given warpType and task config
loadSubExposures
(bbox, statsCtrl, ...)Pre-load sub-regions of a list of exposures.
makeField
(doc)Make a
lsst.pex.config.ConfigurableField
for this task.makeSubtask
(name, **keyArgs)Create a subtask as a new instance as the
name
attribute of this task.makeSupplementaryDataGen3
(butlerQC, ...)Deprecated since version v25.0.
measureCoaddPsf
(coaddExposure)Detect sources on the coadd exposure and measure the final PSF.
newModelFromResidual
(dcrModels, ...)Calculate a new DcrModel from a set of image residuals.
prefilterArtifacts
(spanSetList, exp)Remove artifact candidates covered by bad mask plane.
prepareDcrInputs
(templateCoadd, warpRefList, ...)Prepare the DCR coadd by iterating through the visitInfo of the input warps.
prepareInputs
(refList)Prepare the input warps for coaddition by measuring the weight for each warp and the scaling for the photometric zero point.
prepareStats
([mask])Prepare the statistics for coadding images.
processResults
(coaddExposure[, ...])Interpolate over missing data and mask bright stars.
removeMaskPlanes
(maskedImage)Unset the mask of an image for mask planes specified in the config.
run
(skyInfo, warpRefList, imageScalerList, ...)Assemble the coadd.
runQuantum
(butlerQC, inputRefs, outputRefs)Do butler IO and transform to provide in memory objects for tasks
run
method.selectCoaddPsf
(templateCoadd, warpRefList)Compute the PSF of the coadd from the exposures with the best seeing.
setBrightObjectMasks
(exposure, brightObjectMasks)Set the bright object masks.
setInexactPsf
(mask)Set INEXACT_PSF mask plane.
setRejectedMaskMapping
(statsCtrl)Map certain mask planes of the warps to new planes for the coadd.
shrinkValidPolygons
(coaddInputs)Shrink coaddInputs' ccds' ValidPolygons in place.
stackCoadd
(dcrCoadds)Add a list of sub-band coadds together.
timer
(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
Attributes Documentation
Methods Documentation
- applyAltEdgeMask(mask, altMaskList)¶
Propagate alt EDGE mask to SENSOR_EDGE AND INEXACT_PSF planes.
- applyAltMaskPlanes(mask, altMaskSpans)¶
Apply in place alt mask formatted as SpanSets to a mask.
- Parameters:
- mask
lsst.afw.image.Mask
Original mask.
- altMaskSpans
dict
SpanSet lists to apply. Each element contains the new mask plane name (e.g. “CLIPPED and/or “NO_DATA”) as the key, and list of SpanSets to apply to the mask.
- mask
- Returns:
- mask
lsst.afw.image.Mask
Updated mask.
- mask
- applyModelWeights(modelImages, refImage, modelWeights)¶
Smoothly replace model pixel values with those from a reference at locations away from detected sources.
- Parameters:
- modelImages
list
oflsst.afw.image.Image
The new DCR model images from the current iteration. The values will be modified in place.
- refImage
lsst.afw.image.MaskedImage
A reference image used to supply the default pixel values.
- modelWeights
numpy.ndarray
orfloat
A 2D array of weight values that tapers smoothly to zero away from detected sources. Set to a placeholder value of 1.0 if
self.config.useModelWeights
is False.
- modelImages
- assembleMetadata(coaddExposure, tempExpRefList, weightList)¶
Set the metadata for the coadd.
This basic implementation sets the filter from the first input.
- assembleOnlineMeanCoadd(coaddExposure, tempExpRefList, imageScalerList, weightList, altMaskList, statsCtrl, nImage=None)¶
Assemble the coadd using the “online” method.
This method takes a running sum of images and weights to save memory. It only works for MEAN statistics.
- Parameters:
- coaddExposure
lsst.afw.image.Exposure
The target exposure for the coadd.
- tempExpRefList
list
List of data reference to tempExp.
- imageScalerList
list
List of image scalers.
- weightList
list
List of weights.
- altMaskList
list
List of alternate masks to use rather than those stored with tempExp, or None. Each element is dict with keys = mask plane name to which to add the spans.
- statsCtrl
lsst.afw.math.StatisticsControl
Statistics control object for coadd.
- nImage
lsst.afw.image.ImageU
, optional Keeps track of exposure count for each pixel.
- coaddExposure
- assembleSubregion(coaddExposure, bbox, tempExpRefList, imageScalerList, weightList, altMaskList, statsFlags, statsCtrl, nImage=None)¶
Assemble the coadd for a sub-region.
For each coaddTempExp, check for (and swap in) an alternative mask if one is passed. Remove mask planes listed in
config.removeMaskPlanes
. Finally, stack the actual exposures usinglsst.afw.math.statisticsStack
with the statistic specified by statsFlags. Typically, the statsFlag will be one of lsst.afw.math.MEAN for a mean-stack orlsst.afw.math.MEANCLIP
for outlier rejection using an N-sigma clipped mean where N and iterations are specified by statsCtrl. Assign the stacked subregion back to the coadd.- Parameters:
- coaddExposure
lsst.afw.image.Exposure
The target exposure for the coadd.
- bbox
lsst.geom.Box
Sub-region to coadd.
- tempExpRefList
list
List of data reference to tempExp.
- imageScalerList
list
List of image scalers.
- weightList
list
List of weights.
- altMaskList
list
List of alternate masks to use rather than those stored with tempExp, or None. Each element is dict with keys = mask plane name to which to add the spans.
- statsFlags
lsst.afw.math.Property
Property object for statistic for coadd.
- statsCtrl
lsst.afw.math.StatisticsControl
Statistics control object for coadd.
- nImage
lsst.afw.image.ImageU
, optional Keeps track of exposure count for each pixel.
- coaddExposure
- calculateConvergence(dcrModels, subExposures, bbox, warpRefList, weightList, statsCtrl)¶
Calculate a quality of fit metric for the matched templates.
- Parameters:
- dcrModels
lsst.pipe.tasks.DcrModel
Best fit model of the true sky after correcting chromatic effects.
- subExposures
dict
oflsst.afw.image.ExposureF
The pre-loaded exposures for the current subregion.
- bbox
lsst.geom.box.Box2I
Sub-region to coadd.
- warpRefList
list
oflsst.daf.butler.DeferredDatasetHandle
The data references to the input warped exposures.
- weightList
list
offloat
The weight to give each input exposure in the coadd.
- statsCtrl
lsst.afw.math.StatisticsControl
Statistics control object for coadd.
- dcrModels
- Returns:
- convergenceMetric
float
Quality of fit metric for all input exposures, within the sub-region.
- convergenceMetric
- calculateGain(convergenceList, gainList)¶
Calculate the gain to use for the current iteration.
After calculating a new DcrModel, each value is averaged with the value in the corresponding pixel from the previous iteration. This reduces oscillating solutions that iterative techniques are plagued by, and speeds convergence. By far the biggest changes to the model happen in the first couple iterations, so we can also use a more aggressive gain later when the model is changing slowly.
- Parameters:
- Returns:
- gain
float
Relative weight to give the new solution when updating the model. A value of 1.0 gives equal weight to both solutions.
- gain
- Raises:
- ValueError
If
len(convergenceList) != len(gainList)+1
.
- calculateModelWeights(dcrModels, dcrBBox)¶
Build an array that smoothly tapers to 0 away from detected sources.
- Parameters:
- dcrModels
lsst.pipe.tasks.DcrModel
Best fit model of the true sky after correcting chromatic effects.
- dcrBBox
lsst.geom.box.Box2I
Sub-region of the coadd which includes a buffer to allow for DCR.
- dcrModels
- Returns:
- weights
numpy.ndarray
orfloat
A 2D array of weight values that tapers smoothly to zero away from detected sources. Set to a placeholder value of 1.0 if
self.config.useModelWeights
is False.
- weights
- Raises:
- ValueError
If
useModelWeights
is set andmodelWeightsWidth
is negative.
- calculateNImage(dcrModels, bbox, warpRefList, spanSetMaskList, statsCtrl)¶
Calculate the number of exposures contributing to each subfilter.
- Parameters:
- dcrModels
lsst.pipe.tasks.DcrModel
Best fit model of the true sky after correcting chromatic effects.
- bbox
lsst.geom.box.Box2I
Bounding box of the patch to coadd.
- warpRefList
list
oflsst.daf.butler.DeferredDatasetHandle
The data references to the input warped exposures.
- spanSetMaskList
list
ofdict
containing spanSet lists, orNone
Each element of the
dict
contains the new mask plane name (e.g. “CLIPPED and/or “NO_DATA”) as the key, and the list of SpanSets to apply to the mask.- statsCtrl
lsst.afw.math.StatisticsControl
Statistics control object for coadd
- dcrModels
- Returns:
- calculateSingleConvergence(dcrModels, exposure, significanceImage, statsCtrl)¶
Calculate a quality of fit metric for a single matched template.
- Parameters:
- dcrModels
lsst.pipe.tasks.DcrModel
Best fit model of the true sky after correcting chromatic effects.
- exposure
lsst.afw.image.ExposureF
The input warped exposure to evaluate.
- significanceImage
numpy.ndarray
Array of weights for each pixel corresponding to its significance for the convergence calculation.
- statsCtrl
lsst.afw.math.StatisticsControl
Statistics control object for coadd.
- dcrModels
- Returns:
- convergenceMetric
float
Quality of fit metric for one exposure, within the sub-region.
- convergenceMetric
- dcrAssembleSubregion(dcrModels, subExposures, bbox, dcrBBox, warpRefList, statsCtrl, convergenceMetric, gain, modelWeights, refImage, dcrWeights)¶
Assemble the DCR coadd for a sub-region.
Build a DCR-matched template for each input exposure, then shift the residuals according to the DCR in each subfilter. Stack the shifted residuals and apply them as a correction to the solution from the previous iteration. Restrict the new model solutions from varying by more than a factor of
modelClampFactor
from the last solution, and additionally restrict the individual subfilter models from varying by more than a factor offrequencyClampFactor
from their average. Finally, mitigate potentially oscillating solutions by averaging the new solution with the solution from the previous iteration, weighted by their convergence metric.- Parameters:
- dcrModels
lsst.pipe.tasks.DcrModel
Best fit model of the true sky after correcting chromatic effects.
- subExposures
dict
oflsst.afw.image.ExposureF
The pre-loaded exposures for the current subregion.
- bbox
lsst.geom.box.Box2I
Bounding box of the subregion to coadd.
- dcrBBox
lsst.geom.box.Box2I
Sub-region of the coadd which includes a buffer to allow for DCR.
- warpRefList
list
oflsst.daf.butler.DeferredDatasetHandle
The data references to the input warped exposures.
- statsCtrl
lsst.afw.math.StatisticsControl
Statistics control object for coadd.
- convergenceMetric
float
Quality of fit metric for the matched templates of the input images.
- gain
float
, optional Relative weight to give the new solution when updating the model.
- modelWeights
numpy.ndarray
orfloat
A 2D array of weight values that tapers smoothly to zero away from detected sources. Set to a placeholder value of 1.0 if
self.config.useModelWeights
is False.- refImage
lsst.afw.image.Image
A reference image used to supply the default pixel values.
- dcrWeights
list
oflsst.afw.image.Image
Per-pixel weights for each subfilter. Equal to 1/(number of unmasked images contributing to each pixel).
- dcrModels
- dcrResiduals(residual, visitInfo, wcs, effectiveWavelength, bandwidth)¶
Prepare a residual image for stacking in each subfilter by applying the reverse DCR shifts.
- Parameters:
- residual
numpy.ndarray
The residual masked image for one exposure, after subtracting the matched template.
- visitInfo
lsst.afw.image.VisitInfo
Metadata for the exposure.
- wcs
lsst.afw.geom.SkyWcs
Coordinate system definition (wcs) for the exposure.
- residual
- Yields:
- residualImage
numpy.ndarray
The residual image for the next subfilter, shifted for DCR.
- residualImage
- fillCoadd(dcrModels, skyInfo, warpRefList, weightList, calibration=None, coaddInputs=None, mask=None, variance=None)¶
Create a list of coadd exposures from a list of masked images.
- Parameters:
- dcrModels
lsst.pipe.tasks.DcrModel
Best fit model of the true sky after correcting chromatic effects.
- skyInfo
lsst.pipe.base.Struct
Patch geometry information, from getSkyInfo.
- warpRefList
list
oflsst.daf.butler.DeferredDatasetHandle
The data references to the input warped exposures.
- weightList
list
offloat
The weight to give each input exposure in the coadd.
- calibration
lsst.afw.Image.PhotoCalib
, optional Scale factor to set the photometric calibration of an exposure.
- coaddInputs
lsst.afw.Image.CoaddInputs
, optional A record of the observations that are included in the coadd.
- mask
lsst.afw.image.Mask
, optional Optional mask to override the values in the final coadd.
- variance
lsst.afw.image.Image
, optional Optional variance plane to override the values in the final coadd.
- dcrModels
- Returns:
- dcrCoadds
list
oflsst.afw.image.ExposureF
A list of coadd exposures, each exposure containing the model for one subfilter.
- dcrCoadds
- filterArtifacts(spanSetList, epochCountImage, nImage, footprintsToExclude=None)¶
Filter artifact candidates.
- Parameters:
- spanSetList
list
oflsst.afw.geom.SpanSet
List of SpanSets representing artifact candidates.
- epochCountImage
lsst.afw.image.Image
Image of accumulated number of warpDiff detections.
- nImage
lsst.afw.image.ImageU
Image of the accumulated number of total epochs contributing.
- spanSetList
- Returns:
- maskSpanSetList
list
List of SpanSets with artifacts.
- maskSpanSetList
- filterWarps(inputs, goodVisits)¶
Return list of only inputRefs with visitId in goodVisits ordered by goodVisit.
- Parameters:
- inputs
list
ofDeferredDatasetRef
List of
lsst.pipe.base.connections.DeferredDatasetRef
with dataId containing visit.- goodVisit
dict
Dictionary with good visitIds as the keys. Value ignored.
- inputs
- Returns:
- filteredInputs
list
ofDeferredDatasetRef
Filtered and sorted list of inputRefs with visitId in goodVisits ordered by goodVisit.
- filteredInputs
- findArtifacts(templateCoadd, tempExpRefList, imageScalerList)¶
Find artifacts.
Loop through warps twice. The first loop builds a map with the count of how many epochs each pixel deviates from the templateCoadd by more than
config.chiThreshold
sigma. The second loop takes each difference image and filters the artifacts detected in each using count map to filter out variable sources and sources that are difficult to subtract cleanly.- Parameters:
- Returns:
- getBadPixelMask()¶
Convenience method to provide the bitmask from the mask plane names
- getFullMetadata() TaskMetadata ¶
Get metadata for all tasks.
- Returns:
- metadata
TaskMetadata
The keys are the full task name. Values are metadata for the top-level task and all subtasks, sub-subtasks, etc.
- metadata
Notes
The returned metadata includes timing information (if
@timer.timeMethod
is used) and any metadata set by the task. The name of each item consists of the full task name with.
replaced by:
, followed by.
and the name of the item, e.g.:topLevelTaskName:subtaskName:subsubtaskName.itemName
using
:
in the full task name disambiguates the rare situation that a task has a subtask and a metadata item with the same name.
- getFullName() str ¶
Get the task name as a hierarchical name including parent task names.
- Returns:
- fullName
str
The full name consists of the name of the parent task and each subtask separated by periods. For example:
The full name of top-level task “top” is simply “top”.
The full name of subtask “sub” of top-level task “top” is “top.sub”.
The full name of subtask “sub2” of subtask “sub” of top-level task “top” is “top.sub.sub2”.
- fullName
- getTaskDict() dict[str, weakref.ReferenceType[lsst.pipe.base.task.Task]] ¶
Get a dictionary of all tasks as a shallow copy.
- Returns:
- taskDict
dict
Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.
- taskDict
- getTempExpDatasetName(warpType='direct')¶
Return warp name for given warpType and task config
- loadSubExposures(bbox, statsCtrl, warpRefList, imageScalerList, spanSetMaskList)¶
Pre-load sub-regions of a list of exposures.
- Parameters:
- bbox
lsst.geom.box.Box2I
Sub-region to coadd.
- statsCtrl
lsst.afw.math.StatisticsControl
Statistics control object for coadd.
- warpRefList
list
oflsst.daf.butler.DeferredDatasetHandle
The data references to the input warped exposures.
- imageScalerList
list
oflsst.pipe.task.ImageScaler
The image scalars correct for the zero point of the exposures.
- spanSetMaskList
list
ofdict
containing spanSet lists, orNone
Each element is dict with keys = mask plane name to add the spans to.
- bbox
- Returns:
- classmethod makeField(doc: str) ConfigurableField ¶
Make a
lsst.pex.config.ConfigurableField
for this task.- Parameters:
- doc
str
Help text for the field.
- doc
- Returns:
- configurableField
lsst.pex.config.ConfigurableField
A
ConfigurableField
for this task.
- configurableField
Examples
Provides a convenient way to specify this task is a subtask of another task.
Here is an example of use:
class OtherTaskConfig(lsst.pex.config.Config): aSubtask = ATaskClass.makeField("brief description of task")
- makeSubtask(name: str, **keyArgs: Any) None ¶
Create a subtask as a new instance as the
name
attribute of this task.- Parameters:
- name
str
Brief name of the subtask.
- **keyArgs
Extra keyword arguments used to construct the task. The following arguments are automatically provided and cannot be overridden:
config
.parentTask
.
- name
Notes
The subtask must be defined by
Task.config.name
, an instance ofConfigurableField
orRegistryField
.
- makeSupplementaryDataGen3(butlerQC, inputRefs, outputRefs)¶
Deprecated since version v25.0: makeSupplementaryDataGen3 is deprecated in favor of _makeSupplementaryData
- measureCoaddPsf(coaddExposure)¶
Detect sources on the coadd exposure and measure the final PSF.
- Parameters:
- coaddExposure
lsst.afw.image.Exposure
The final coadded exposure.
- coaddExposure
- newModelFromResidual(dcrModels, residualGeneratorList, dcrBBox, statsCtrl, gain, modelWeights, refImage, dcrWeights)¶
Calculate a new DcrModel from a set of image residuals.
- Parameters:
- dcrModels
lsst.pipe.tasks.DcrModel
Current model of the true sky after correcting chromatic effects.
- residualGeneratorList
generator
ofnumpy.ndarray
The residual image for the next subfilter, shifted for DCR.
- dcrBBox
lsst.geom.box.Box2I
Sub-region of the coadd which includes a buffer to allow for DCR.
- statsCtrl
lsst.afw.math.StatisticsControl
Statistics control object for coadd.
- gain
float
Relative weight to give the new solution when updating the model.
- modelWeights
numpy.ndarray
orfloat
A 2D array of weight values that tapers smoothly to zero away from detected sources. Set to a placeholder value of 1.0 if
self.config.useModelWeights
is False.- refImage
lsst.afw.image.Image
A reference image used to supply the default pixel values.
- dcrWeights
list
oflsst.afw.image.Image
Per-pixel weights for each subfilter. Equal to 1/(number of unmasked images contributing to each pixel).
- dcrModels
- Returns:
- dcrModel
lsst.pipe.tasks.DcrModel
New model of the true sky after correcting chromatic effects.
- dcrModel
- prefilterArtifacts(spanSetList, exp)¶
Remove artifact candidates covered by bad mask plane.
Any future editing of the candidate list that does not depend on temporal information should go in this method.
- Parameters:
- spanSetList
list
oflsst.afw.geom.SpanSet
List of SpanSets representing artifact candidates.
- exp
lsst.afw.image.Exposure
Exposure containing mask planes used to prefilter.
- spanSetList
- Returns:
- returnSpanSetList
list
oflsst.afw.geom.SpanSet
List of SpanSets with artifacts.
- returnSpanSetList
- prepareDcrInputs(templateCoadd, warpRefList, weightList)¶
Prepare the DCR coadd by iterating through the visitInfo of the input warps.
Sets the property
bufferSize
.- Parameters:
- templateCoadd
lsst.afw.image.ExposureF
The initial coadd exposure before accounting for DCR.
- warpRefList
list
oflsst.daf.butler.DeferredDatasetHandle
The data references to the input warped exposures.
- weightList
list
offloat
The weight to give each input exposure in the coadd. Will be modified in place if
doAirmassWeight
is set.
- templateCoadd
- Returns:
- dcrModels
lsst.pipe.tasks.DcrModel
Best fit model of the true sky after correcting chromatic effects.
- dcrModels
- Raises:
- NotImplementedError
If
lambdaMin
is missing from the Mapper class of the obs package being used.
- prepareInputs(refList)¶
Prepare the input warps for coaddition by measuring the weight for each warp and the scaling for the photometric zero point.
Each Warp has its own photometric zeropoint and background variance. Before coadding these Warps together, compute a scale factor to normalize the photometric zeropoint and compute the weight for each Warp.
- prepareStats(mask=None)¶
Prepare the statistics for coadding images.
- Parameters:
- mask
int
, optional Bit mask value to exclude from coaddition.
- mask
- Returns:
- stats
Struct
Statistics as a struct with attributes:
statsCtrl
Statistics control object for coadd (
StatisticsControl
).statsFlags
Statistic for coadd (
Property
).
- stats
- processResults(coaddExposure, brightObjectMasks=None, dataId=None)¶
Interpolate over missing data and mask bright stars.
- removeMaskPlanes(maskedImage)¶
Unset the mask of an image for mask planes specified in the config.
- Parameters:
- maskedImage
lsst.afw.image.MaskedImage
The masked image to be modified.
- maskedImage
- Raises:
- InvalidParameterError
Raised if no mask plane with that name was found.
- run(skyInfo, warpRefList, imageScalerList, weightList, supplementaryData=None)¶
Assemble the coadd.
Requires additional inputs Struct
supplementaryData
to contain atemplateCoadd
that serves as the model of the static sky.Find artifacts and apply them to the warps’ masks creating a list of alternative masks with a new “CLIPPED” plane and updated “NO_DATA” plane Then pass these alternative masks to the base class’s assemble method.
Divide the
templateCoadd
evenly between each subfilter of aDcrModel
as the starting best estimate of the true wavelength- dependent sky. Forward model theDcrModel
using the known chromatic effects in each subfilter and calculate a convergence metric based on how well the modeled template matches the input warps. If the convergence has not yet reached the desired threshold, then shift and stack the residual images to build a newDcrModel
. Apply conditioning to prevent oscillating solutions between iterations or between subfilters.Once the
DcrModel
reaches convergence or the maximum number of iterations has been reached, fill the metadata for each subfilter image and make them propercoaddExposure
s.- Parameters:
- skyInfo
lsst.pipe.base.Struct
Patch geometry information, from getSkyInfo
- warpRefList
list
oflsst.daf.butler.DeferredDatasetHandle
The data references to the input warped exposures.
- imageScalerList
list
oflsst.pipe.task.ImageScaler
The image scalars correct for the zero point of the exposures.
- weightList
list
offloat
The weight to give each input exposure in the coadd
- supplementaryData
lsst.pipe.base.Struct
Result struct returned by
_makeSupplementaryData
with attributes:templateCoadd
Coadded exposure (
lsst.afw.image.Exposure
).
- skyInfo
- Returns:
- result
lsst.pipe.base.Struct
Results as a struct with attributes:
- result
- runQuantum(butlerQC, inputRefs, outputRefs)¶
Do butler IO and transform to provide in memory objects for tasks
run
method.- Parameters:
- butlerQC
QuantumContext
A butler which is specialized to operate in the context of a
lsst.daf.butler.Quantum
.- inputRefs
InputQuantizedConnection
Datastructure whose attribute names are the names that identify connections defined in corresponding
PipelineTaskConnections
class. The values of these attributes are thelsst.daf.butler.DatasetRef
objects associated with the defined input/prerequisite connections.- outputRefs
OutputQuantizedConnection
Datastructure whose attribute names are the names that identify connections defined in corresponding
PipelineTaskConnections
class. The values of these attributes are thelsst.daf.butler.DatasetRef
objects associated with the defined output connections.
- butlerQC
Notes
Assemble a coadd from a set of Warps.
- selectCoaddPsf(templateCoadd, warpRefList)¶
Compute the PSF of the coadd from the exposures with the best seeing.
- Parameters:
- templateCoadd
lsst.afw.image.ExposureF
The initial coadd exposure before accounting for DCR.
- warpRefList
list
oflsst.daf.butler.DeferredDatasetHandle
The data references to the input warped exposures.
- templateCoadd
- Returns:
- psf
lsst.meas.algorithms.CoaddPsf
The average PSF of the input exposures with the best seeing.
- psf
- setBrightObjectMasks(exposure, brightObjectMasks, dataId=None)¶
Set the bright object masks.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure under consideration.
- brightObjectMasks
lsst.afw.table
Table of bright objects to mask.
- dataId
lsst.daf.butler.DataId
, optional Data identifier dict for patch.
- exposure
- setInexactPsf(mask)¶
Set INEXACT_PSF mask plane.
If any of the input images isn’t represented in the coadd (due to clipped pixels or chip gaps), the
CoaddPsf
will be inexact. Flag these pixels.- Parameters:
- mask
lsst.afw.image.Mask
Coadded exposure’s mask, modified in-place.
- mask
- static setRejectedMaskMapping(statsCtrl)¶
Map certain mask planes of the warps to new planes for the coadd.
If a pixel is rejected due to a mask value other than EDGE, NO_DATA, or CLIPPED, set it to REJECTED on the coadd. If a pixel is rejected due to EDGE, set the coadd pixel to SENSOR_EDGE. If a pixel is rejected due to CLIPPED, set the coadd pixel to CLIPPED.
- Parameters:
- statsCtrl
lsst.afw.math.StatisticsControl
Statistics control object for coadd.
- statsCtrl
- Returns:
- shrinkValidPolygons(coaddInputs)¶
Shrink coaddInputs’ ccds’ ValidPolygons in place.
Either modify each ccd’s validPolygon in place, or if CoaddInputs does not have a validPolygon, create one from its bbox.
- Parameters:
- coaddInputs
lsst.afw.image.coaddInputs
Original mask.
- coaddInputs
- stackCoadd(dcrCoadds)¶
Add a list of sub-band coadds together.
- Parameters:
- dcrCoadds
list
oflsst.afw.image.ExposureF
A list of coadd exposures, each exposure containing the model for one subfilter.
- dcrCoadds
- Returns:
- coaddExposure
lsst.afw.image.ExposureF
A single coadd exposure that is the sum of the sub-bands.
- coaddExposure