AssembleCoaddTask¶
- class lsst.pipe.tasks.assembleCoadd.AssembleCoaddTask(*args, **kwargs)¶
Bases:
CoaddBaseTask
,PipelineTask
Assemble a coadded image from a set of warps (coadded temporary exposures).
We want to assemble a coadded image from a set of Warps (also called coadded temporary exposures or
coaddTempExps
). Each input Warp covers a patch on the sky and corresponds to a single run/visit/exposure of the covered patch. We provide the task with a list of Warps (selectDataList
) from which it selects Warps that cover the specified patch (pointed at bydataRef
). Each Warp that goes into a coadd will typically have an independent photometric zero-point. Therefore, we must scale each Warp to set it to a common photometric zeropoint. WarpType may be one of ‘direct’ or ‘psfMatched’, and the boolean configsconfig.makeDirect
andconfig.makePsfMatched
set which of the warp types will be coadded. The coadd is computed as a mean with optional outlier rejection. Criteria for outlier rejection are set inAssembleCoaddConfig
. Finally, Warps can have bad ‘NaN’ pixels which received no input from the source calExps. We interpolate over these bad (NaN) pixels.AssembleCoaddTask
uses several sub-tasks. These areScaleZeroPointTask
create and use an
imageScaler
object to scale the photometric zeropoint for each WarpInterpImageTask
interpolate across bad pixels (NaN) in the final coadd
You can retarget these subtasks if you wish.
Notes
The
lsst.pipe.base.cmdLineTask.CmdLineTask
interface supports a flag-d
to importdebug.py
from yourPYTHONPATH
; seebaseDebug
for more aboutdebug.py
files.AssembleCoaddTask
has no debug variables of its own. Some of the subtasks may support debug variables. See the documentation for the subtasks for further information.Examples
AssembleCoaddTask
assembles a set of warped images into a coadded image. TheAssembleCoaddTask
can be invoked by runningassembleCoadd.py
with the flag ‘–legacyCoadd’. Usage of assembleCoadd.py expects two inputs: a data reference to the tract patch and filter to be coadded, and a list of Warps to attempt to coadd. These are specified using--id
and--selectId
, respectively:--id = [KEY=VALUE1[^VALUE2[^VALUE3...] [KEY=VALUE1[^VALUE2[^VALUE3...] ...]] --selectId [KEY=VALUE1[^VALUE2[^VALUE3...] [KEY=VALUE1[^VALUE2[^VALUE3...] ...]]
Only the Warps that cover the specified tract and patch will be coadded. A list of the available optional arguments can be obtained by calling
assembleCoadd.py
with the--help
command line argument:assembleCoadd.py --help
To demonstrate usage of the
AssembleCoaddTask
in the larger context of multi-band processing, we will generate the HSC-I & -R band coadds from HSC engineering test data provided in theci_hsc
package. To begin, assuming that the lsst stack has been already set up, we must set up the obs_subaru andci_hsc
packages. This defines the environment variable$CI_HSC_DIR
and points at the location of the package. The raw HSC data live in the$CI_HSC_DIR/raw directory
. To begin assembling the coadds, we must firstprocessCcd
process the individual ccds in $CI_HSC_RAW to produce calibrated exposures
makeSkyMap
create a skymap that covers the area of the sky present in the raw exposures
makeCoaddTempExp
warp the individual calibrated exposures to the tangent plane of the coadd
We can perform all of these steps by running
$CI_HSC_DIR scons warp-903986 warp-904014 warp-903990 warp-904010 warp-903988
This will produce warped exposures for each visit. To coadd the warped data, we call assembleCoadd.py as follows:
assembleCoadd.py --legacyCoadd $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-I --selectId visit=903986 ccd=16 --selectId visit=903986 ccd=22 --selectId visit=903986 ccd=23 --selectId visit=903986 ccd=100 --selectId visit=904014 ccd=1 --selectId visit=904014 ccd=6 --selectId visit=904014 ccd=12 --selectId visit=903990 ccd=18 --selectId visit=903990 ccd=25 --selectId visit=904010 ccd=4 --selectId visit=904010 ccd=10 --selectId visit=904010 ccd=100 --selectId visit=903988 ccd=16 --selectId visit=903988 ccd=17 --selectId visit=903988 ccd=23 --selectId visit=903988 ccd=24
that will process the HSC-I band data. The results are written in
$CI_HSC_DIR/DATA/deepCoadd-results/HSC-I
.You may also choose to run:
scons warp-903334 warp-903336 warp-903338 warp-903342 warp-903344 warp-903346 assembleCoadd.py --legacyCoadd $CI_HSC_DIR/DATA --id patch=5,4 tract=0 filter=HSC-R --selectId visit=903334 ccd=16 --selectId visit=903334 ccd=22 --selectId visit=903334 ccd=23 --selectId visit=903334 ccd=100 --selectId visit=903336 ccd=17 --selectId visit=903336 ccd=24 --selectId visit=903338 ccd=18 --selectId visit=903338 ccd=25 --selectId visit=903342 ccd=4 --selectId visit=903342 ccd=10 --selectId visit=903342 ccd=100 --selectId visit=903344 ccd=0 --selectId visit=903344 ccd=5 --selectId visit=903344 ccd=11 --selectId visit=903346 ccd=1 --selectId visit=903346 ccd=6 --selectId visit=903346 ccd=12
to generate the coadd for the HSC-R band if you are interested in following multiBand Coadd processing as discussed in
pipeTasks_multiBand
(but note that normally, one would use theSafeClipAssembleCoaddTask
rather thanAssembleCoaddTask
to make the coadd.Attributes Summary
Methods Summary
applyAltMaskPlanes
(mask, altMaskSpans)Apply in place alt mask formatted as SpanSets to a mask.
applyOverrides
(config)A hook to allow a task to change the values of its config after the camera-specific overrides are loaded but before any command-line overrides are applied.
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.
Empty (clear) the metadata for this Task and all sub-Tasks.
filterWarps
(inputs, goodVisits)Return list of only inputRefs with visitId in goodVisits ordered by goodVisit
Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
!
getCoaddDatasetName
([warpType])Return coadd name for given warpType and task config
Get metadata for all tasks.
Get the task name as a hierarchical name including parent task names.
getName
()Get the name of the task.
Return resource configuration for this task.
Get the schemas generated by this task.
getSkyInfo
(patchRef)!
Get a dictionary of all tasks as a shallow copy.
getTempExpDatasetName
([warpType])Return warp name for given warpType and task config
getTempExpRefList
(patchRef, calExpRefList)Generate list data references corresponding to warped exposures that lie within the patch to be coadded.
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.makeSupplementaryData
(dataRef[, ...])Make additional inputs to run() specific to subclasses (Gen2)
makeSupplementaryDataGen3
(butlerQC, ...)Make additional inputs to run() specific to subclasses (Gen3)
parseAndRun
([args, config, log, doReturnResults])Parse an argument list and run the command.
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.
readBrightObjectMasks
(dataRef)Retrieve the bright object masks.
removeMaskPlanes
(maskedImage)Unset the mask of an image for mask planes specified in the config.
run
(skyInfo, tempExpRefList, ...[, ...])Assemble a coadd from input warps
runDataRef
(dataRef[, selectDataList, ...])Assemble a coadd from a set of Warps.
runQuantum
(butlerQC, inputRefs, outputRefs)Method to do butler IO and or transforms to provide in memory objects for tasks run method
selectExposures
(patchRef[, skyInfo, ...])!
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.
timer
(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
writeConfig
(butler[, clobber, doBackup])Write the configuration used for processing the data, or check that an existing one is equal to the new one if present.
writeMetadata
(dataRef)Write the metadata produced from processing the data.
writePackageVersions
(butler[, clobber, ...])Compare and write package versions.
writeSchemas
(butler[, clobber, doBackup])Write the schemas returned by
lsst.pipe.base.Task.getAllSchemaCatalogs
.Attributes Documentation
Methods Documentation
- 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
- classmethod applyOverrides(config)¶
A hook to allow a task to change the values of its config after the camera-specific overrides are loaded but before any command-line overrides are applied.
- Parameters:
- configinstance of task’s
ConfigClass
Task configuration.
- configinstance of task’s
Notes
This is necessary in some cases because the camera-specific overrides may retarget subtasks, wiping out changes made in ConfigClass.setDefaults. See LSST Trac ticket #2282 for more discussion.
Warning
This is called by CmdLineTask.parseAndRun; other ways of constructing a config will not apply these overrides.
- 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
- filterWarps(inputs, goodVisits)¶
Return list of only inputRefs with visitId in goodVisits ordered by goodVisit
- Parameters:
- inputslist
List of
lsst.pipe.base.connections.DeferredDatasetRef
with dataId containing visit- goodVisit
dict
Dictionary with good visitIds as the keys. Value ignored.
- getAllSchemaCatalogs() Dict[str, Any] ¶
Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
- Returns:
- schemacatalogs
dict
Keys are butler dataset type, values are a empty catalog (an instance of the appropriate
lsst.afw.table
Catalog type) for all tasks in the hierarchy, from the top-level task down through all subtasks.
- schemacatalogs
Notes
This method may be called on any task in the hierarchy; it will return the same answer, regardless.
The default implementation should always suffice. If your subtask uses schemas the override
Task.getSchemaCatalogs
, not this method.
- getBadPixelMask()¶
! @brief Convenience method to provide the bitmask from the mask plane names
- getCoaddDatasetName(warpType='direct')¶
Return coadd name for given warpType and task config
- Parameters:
- warpTypestring
Either ‘direct’ or ‘psfMatched’
- Returns:
- CoaddDatasetName
string
- CoaddDatasetName
- 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
- getResourceConfig() ResourceConfig | None ¶
Return resource configuration for this task.
- Returns:
- Object of type
ResourceConfig
orNone
if resource - configuration is not defined for this task.
- Object of type
- getSchemaCatalogs() Dict[str, Any] ¶
Get the schemas generated by this task.
- Returns:
- schemaCatalogs
dict
Keys are butler dataset type, values are an empty catalog (an instance of the appropriate
lsst.afw.table
Catalog type) for this task.
- schemaCatalogs
See also
Task.getAllSchemaCatalogs
Notes
Warning
Subclasses that use schemas must override this method. The default implementation returns an empty dict.
This method may be called at any time after the Task is constructed, which means that all task schemas should be computed at construction time, not when data is actually processed. This reflects the philosophy that the schema should not depend on the data.
Returning catalogs rather than just schemas allows us to save e.g. slots for SourceCatalog as well.
- getSkyInfo(patchRef)¶
! @brief Use @ref coaddBase::getSkyInfo “getSkyInfo” to return the skyMap, tract and patch information, wcs and the outer bbox of the patch.
@param[in] patchRef data reference for sky map. Must include keys “tract” and “patch”
@return pipe_base Struct containing: - skyMap: sky map - tractInfo: information for chosen tract of sky map - patchInfo: information about chosen patch of tract - wcs: WCS of tract - bbox: outer bbox of patch, as an geom Box2I
- getTaskDict() Dict[str, ReferenceType[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
- Parameters:
- warpTypestring
Either ‘direct’ or ‘psfMatched’
- Returns:
- WarpDatasetName
string
- WarpDatasetName
- getTempExpRefList(patchRef, calExpRefList)¶
Generate list data references corresponding to warped exposures that lie within the patch to be coadded.
- 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
.
- makeSupplementaryData(dataRef, selectDataList=None, warpRefList=None)¶
Make additional inputs to run() specific to subclasses (Gen2)
Duplicates interface of
runDataRef
method Available to be implemented by subclasses only if they need the coadd dataRef for performing preliminary processing before assembling the coadd.
- makeSupplementaryDataGen3(butlerQC, inputRefs, outputRefs)¶
Make additional inputs to run() specific to subclasses (Gen3)
Duplicates interface of
runQuantum
method. Available to be implemented by subclasses only if they need the coadd dataRef for performing preliminary processing before assembling the coadd.- Parameters:
- butlerQC
lsst.pipe.base.ButlerQuantumContext
Gen3 Butler object for fetching additional data products before running the Task specialized for quantum being processed
- inputRefs
lsst.pipe.base.InputQuantizedConnection
Attributes are the names of the connections describing input dataset types. Values are DatasetRefs that task consumes for corresponding dataset type. DataIds are guaranteed to match data objects in
inputData
.- outputRefs
lsst.pipe.base.OutputQuantizedConnection
Attributes are the names of the connections describing output dataset types. Values are DatasetRefs that task is to produce for corresponding dataset type.
- butlerQC
- classmethod parseAndRun(args=None, config=None, log=None, doReturnResults=False)¶
Parse an argument list and run the command.
- Parameters:
- args
list
, optional - config
lsst.pex.config.Config
-type, optional Config for task. If
None
useTask.ConfigClass
.- log
logging.Logger
-type, optional Log. If
None
use the default log.- doReturnResults
bool
, optional If
True
, return the results of this task. Default isFalse
. This is only intended for unit tests and similar use. It can easily exhaust memory (if the task returns enough data and you call it enough times) and it will fail when using multiprocessing if the returned data cannot be pickled.
- args
- Returns:
- struct
lsst.pipe.base.Struct
Fields are:
argumentParser
the argument parser (
lsst.pipe.base.ArgumentParser
).parsedCmd
the parsed command returned by the argument parser’s
parse_args
method (argparse.Namespace
).taskRunner
the task runner used to run the task (an instance of
Task.RunnerClass
).resultList
results returned by the task runner’s
run
method, one entry per invocation (list
). This will typically be a list ofStruct
, each containing at least anexitStatus
integer (0 or 1); seeTask.RunnerClass
(TaskRunner
by default) for more details.
- struct
Notes
Calling this method with no arguments specified is the standard way to run a command-line task from the command-line. For an example see
pipe_tasks
bin/makeSkyMap.py
or almost any other file in that directory.If one or more of the dataIds fails then this routine will exit (with a status giving the number of failed dataIds) rather than returning this struct; this behaviour can be overridden by specifying the
--noExit
command-line option.
- 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.
- Parameters:
- refList
list
List of data references to tempExp
- refList
- Returns:
- result
lsst.pipe.base.Struct
Result struct with components:
- result
- prepareStats(mask=None)¶
Prepare the statistics for coadding images.
- Parameters:
- mask
int
, optional Bit mask value to exclude from coaddition.
- mask
- Returns:
- stats
lsst.pipe.base.Struct
Statistics structure with the following fields:
statsCtrl
: Statistics control object for coadd
statsFlags
: Statistic for coadd (lsst.afw.math.Property
)
- stats
- processResults(coaddExposure, brightObjectMasks=None, dataId=None)¶
Interpolate over missing data and mask bright stars.
- Parameters:
- coaddExposure
lsst.afw.image.Exposure
The coadded exposure to process.
- dataRef
lsst.daf.persistence.ButlerDataRef
Butler data reference for supplementary data.
- coaddExposure
- readBrightObjectMasks(dataRef)¶
Retrieve the bright object masks.
Returns None on failure.
- Parameters:
- dataRef
lsst.daf.persistence.butlerSubset.ButlerDataRef
A Butler dataRef.
- dataRef
- Returns:
- result
lsst.daf.persistence.butlerSubset.ButlerDataRef
Bright object mask from the Butler object, or None if it cannot be retrieved.
- result
- 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
- run(skyInfo, tempExpRefList, imageScalerList, weightList, altMaskList=None, mask=None, supplementaryData=None)¶
Assemble a coadd from input warps
Assemble the coadd using the provided list of coaddTempExps. Since the full coadd covers a patch (a large area), the assembly is performed over small areas on the image at a time in order to conserve memory usage. Iterate over subregions within the outer bbox of the patch using
assembleSubregion
to stack the corresponding subregions from the coaddTempExps with the statistic specified. Set the edge bits the coadd mask based on the weight map.- Parameters:
- skyInfo
lsst.pipe.base.Struct
Struct with geometric information about the patch.
- tempExpRefList
list
List of data references to Warps (previously called CoaddTempExps).
- imageScalerList
list
List of image scalers.
- weightList
list
List of weights
- altMaskList
list
, optional List of alternate masks to use rather than those stored with tempExp.
- mask
int
, optional Bit mask value to exclude from coaddition.
- supplementaryDatalsst.pipe.base.Struct, optional
Struct with additional data products needed to assemble coadd. Only used by subclasses that implement
makeSupplementaryData
and overriderun
.
- skyInfo
- Returns:
- result
lsst.pipe.base.Struct
Result struct with components:
coaddExposure
: coadded exposure (lsst.afw.image.Exposure
).nImage
: exposure count image (lsst.afw.image.Image
), if requested.inputMap
: bit-wise map of inputs, if requested.warpRefList
: input list of refs to the warps (lsst.daf.butler.DeferredDatasetHandle
orlsst.daf.persistence.ButlerDataRef
) (unmodified)
imageScalerList
: input list of image scalers (unmodified)weightList
: input list of weights (unmodified)
- result
- runDataRef(dataRef, selectDataList=None, warpRefList=None)¶
Assemble a coadd from a set of Warps.
Pipebase.CmdlineTask entry point to Coadd a set of Warps. Compute weights to be applied to each Warp and find scalings to match the photometric zeropoint to a reference Warp. Assemble the Warps using
run
. Interpolate over NaNs and optionally write the coadd to disk. Return the coadded exposure.- Parameters:
- dataRef
lsst.daf.persistence.butlerSubset.ButlerDataRef
Data reference defining the patch for coaddition and the reference Warp (if
config.autoReference=False
). Used to access the following data products: -self.config.coaddName + "Coadd_skyMap"
-self.config.coaddName + "Coadd_ + <warpType> + "Warp"
(optionally) -self.config.coaddName + "Coadd"
- selectDataList
list
List of data references to Calexps. Data to be coadded will be selected from this list based on overlap with the patch defined by dataRef, grouped by visit, and converted to a list of data references to warps.
- warpRefList
list
List of data references to Warps to be coadded. Note:
warpRefList
is just the new name fortempExpRefList
.
- dataRef
- Returns:
- retStruct
lsst.pipe.base.Struct
Result struct with components:
coaddExposure
: coadded exposure (Exposure
).nImage
: exposure count image (Image
).
- retStruct
- runQuantum(butlerQC, inputRefs, outputRefs)¶
Method to do butler IO and or transforms to provide in memory objects for tasks run method
- Parameters:
- butlerQC
ButlerQuantumContext
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.
PipelineTask (Gen3) entry point to Coadd a set of Warps. Analogous to
runDataRef
, it prepares all the data products to be passed torun
, and processes the results before returning a struct of results to be written out. AssembleCoadd cannot fit all Warps in memory. Therefore, its inputs are accessed subregion by subregion by the Gen3DeferredDatasetHandle
that is analagous to the Gen2lsst.daf.persistence.ButlerDataRef
. Any updates to this method should correspond to an update inrunDataRef
while both entry points are used.
- selectExposures(patchRef, skyInfo=None, selectDataList=[])¶
! @brief Select exposures to coadd
Get the corners of the bbox supplied in skyInfo using @ref geom.Box2D and convert the pixel positions of the bbox corners to sky coordinates using @ref afw::geom::SkyWcs::pixelToSky “skyInfo.wcs.pixelToSky”. Use the @ref selectImages::WcsSelectImagesTask “WcsSelectImagesTask” to select exposures that lie inside the patch indicated by the dataRef.
- @param[in] patchRef data reference for sky map patch. Must include keys “tract”, “patch”,
plus the camera-specific filter key (e.g. “filter” or “band”)
@param[in] skyInfo geometry for the patch; output from getSkyInfo @param[in] selectDataList list of @ref selectImages::SelectStruct “SelectStruct”
to consider for selection
@return a list of science exposures to coadd, as butler data references
- setBrightObjectMasks(exposure, brightObjectMasks, dataId=None)¶
Set the bright object masks.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure under consideration.
- dataId
lsst.daf.persistence.dataId
Data identifier dict for patch.
- brightObjectMasks
lsst.afw.table
Table of bright objects to mask.
- 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
- timer(name: str, logLevel: int = 10) Iterator[None] ¶
Context manager to log performance data for an arbitrary block of code.
- Parameters:
See also
timer.logInfo
Examples
Creating a timer context:
with self.timer("someCodeToTime"): pass # code to time
- writeConfig(butler, clobber=False, doBackup=True)¶
Write the configuration used for processing the data, or check that an existing one is equal to the new one if present.
- Parameters:
- butler
lsst.daf.persistence.Butler
Data butler used to write the config. The config is written to dataset type
CmdLineTask._getConfigName
.- clobber
bool
, optional A boolean flag that controls what happens if a config already has been saved:
- doBackup
bool
, optional Set to
True
to backup the config files if clobbering.
- butler
- writeMetadata(dataRef)¶
Write the metadata produced from processing the data.
- Parameters:
- dataRef
Butler data reference used to write the metadata. The metadata is written to dataset type
CmdLineTask._getMetadataName
.
- writePackageVersions(butler, clobber=False, doBackup=True, dataset='packages')¶
Compare and write package versions.
- Parameters:
- butler
lsst.daf.persistence.Butler
Data butler used to read/write the package versions.
- clobber
bool
, optional A boolean flag that controls what happens if versions already have been saved:
- doBackup
bool
, optional If
True
and clobbering, old package version files are backed up.- dataset
str
, optional Name of dataset to read/write.
- butler
- Raises:
- TaskError
Raised if there is a version mismatch with current and persisted lists of package versions.
Notes
Note that this operation is subject to a race condition.
- writeSchemas(butler, clobber=False, doBackup=True)¶
Write the schemas returned by
lsst.pipe.base.Task.getAllSchemaCatalogs
.- Parameters:
- butler
lsst.daf.persistence.Butler
Data butler used to write the schema. Each schema is written to the dataset type specified as the key in the dict returned by
getAllSchemaCatalogs
.- clobber
bool
, optional A boolean flag that controls what happens if a schema already has been saved:
- doBackup
bool
, optional Set to
True
to backup the schema files if clobbering.
- butler
Notes
If
clobber
isFalse
and an existing schema does not match a current schema, then some schemas may have been saved successfully and others may not, and there is no easy way to tell which is which.