ForcedPhotCcdTask¶

class lsst.meas.base.ForcedPhotCcdTask(butler=None, refSchema=None, initInputs=None, **kwds)¶

Bases: lsst.pipe.base.PipelineTask

A pipeline task for performing forced measurement on CCD images.

Parameters:

butler : None: Deprecated and unused. Should always be None.
refSchema : lsst.afw.table.Schema, optional: The schema of the reference catalog, passed to the constructor of the references subtask. Optional, but must be specified if initInputs is not; if both are specified, initInputs takes precedence.
initInputs : dict: Dictionary that can contain a key inputSchema containing the schema. If present will override the value of refSchema.
**kwds: Keyword arguments are passed to the supertask constructor.

Attributes Summary

`canMultiprocess`
`dataPrefix`

Methods Summary

`attachFootprints`(sources, refCat, exposure, …)	Attach footprints to blank sources prior to measurements.
`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`generateMeasCat`(exposureDataId, exposure, …)	Generate a measurement catalog.
`getAllSchemaCatalogs`()	Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
`getFullMetadata`()	Get metadata for all tasks.
`getFullName`()	Get the task name as a hierarchical name including parent task names.
`getName`()	Get the name of the task.
`getResourceConfig`()	Return resource configuration for this task.
`getSchemaCatalogs`()	The schema catalogs that will be used by this task.
`getTaskDict`()	Get a dictionary of all tasks as a shallow copy.
`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.
`mergeAndFilterReferences`(exposure, refCats, …)	Filter reference catalog so that all sources are within the boundaries of the exposure.
`prepareCalibratedExposure`(exposure[, …])	Prepare a calibrated exposure and apply external calibrations and sky corrections if so configured.
`run`(measCat, exposure, refCat, refWcs[, …])	Perform forced measurement on a single exposure.
`runQuantum`(butlerQC, inputRefs, outputRefs)	Method to do butler IO and or transforms to provide in memory objects for tasks run method
`timer`(name, logLevel)	Context manager to log performance data for an arbitrary block of code.

Attributes Documentation

canMultiprocess = True¶

dataPrefix = ''¶

Methods Documentation

attachFootprints(sources, refCat, exposure, refWcs)¶

Attach footprints to blank sources prior to measurements.

Notes

Footprints for forced photometry must be in the pixel coordinate system of the image being measured, while the actual detections may start out in a different coordinate system.

Subclasses of this class may implement this method to define how those Footprints should be generated.

This default implementation transforms depends on the footprintSource configuration parameter.

emptyMetadata() → None¶: Empty (clear) the metadata for this Task and all sub-Tasks.

generateMeasCat(exposureDataId, exposure, refCat, refWcs, idPackerName)¶

Generate a measurement catalog.

Parameters:

exposureDataId : DataId: Butler dataId for this exposure.
exposure : lsst.afw.image.exposure.Exposure: Exposure to generate the catalog for.
refCat : lsst.afw.table.SourceCatalog: Catalog of shapes and positions at which to force photometry.
refWcs : lsst.afw.image.SkyWcs: Reference world coordinate system. This parameter is not currently used.
idPackerName : str: Type of ID packer to construct from the registry.

Returns:

measCat : lsst.afw.table.SourceCatalog: Catalog of forced sources to measure.
expId : int: Unique binary id associated with the input exposure

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.

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.

getFullMetadata() → lsst.pipe.base._task_metadata.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.

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”.

getName() → str¶

Get the name of the task.

Returns:	taskName : `str` Name of the task.

See also

getFullName

getResourceConfig() → Optional[ResourceConfig]¶

Return resource configuration for this task.

Returns:	Object of type `ResourceConfig` or `None` if resource configuration is not defined for this task.

getSchemaCatalogs()¶

The schema catalogs that will be used by this task.

Returns:	schemaCatalogs : `dict` Dictionary mapping dataset type to schema catalog.

Notes

There is only one schema for each type of forced measurement. The dataset type for this measurement is defined in the mapper.

getTaskDict() → Dict[str, weakref]¶

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.

classmethod makeField(doc: str) → lsst.pex.config.configurableField.ConfigurableField¶

Make a lsst.pex.config.ConfigurableField for this task.

Parameters:	doc : `str` Help text for the field.
Returns:	configurableField : `lsst.pex.config.ConfigurableField` A `ConfigurableField` for this task.

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) → 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”.

Notes

The subtask must be defined by Task.config.name, an instance of ConfigurableField or RegistryField.

mergeAndFilterReferences(exposure, refCats, refWcs)¶

Filter reference catalog so that all sources are within the boundaries of the exposure.

Parameters:	exposure : `lsst.afw.image.exposure.Exposure` Exposure to generate the catalog for. refCats : sequence of `lsst.daf.butler.DeferredDatasetHandle` Handles for catalogs of shapes and positions at which to force photometry. refWcs : `lsst.afw.image.SkyWcs` Reference world coordinate system.
Returns:	refSources : `lsst.afw.table.SourceCatalog` Filtered catalog of forced sources to measure.

Notes

The majority of this code is based on the methods of lsst.meas.algorithms.loadReferenceObjects.ReferenceObjectLoader

prepareCalibratedExposure(exposure, skyCorr=None, externalSkyWcsCatalog=None, externalPhotoCalibCatalog=None, finalizedPsfApCorrCatalog=None)¶

Prepare a calibrated exposure and apply external calibrations and sky corrections if so configured.

Parameters:

exposure : lsst.afw.image.exposure.Exposure: Input exposure to adjust calibrations.
skyCorr : lsst.afw.math.backgroundList, optional: Sky correction frame to apply if doApplySkyCorr=True.
externalSkyWcsCatalog : lsst.afw.table.ExposureCatalog, optional: Exposure catalog with external skyWcs to be applied if config.doApplyExternalSkyWcs=True. Catalog uses the detector id for the catalog id, sorted on id for fast lookup.
externalPhotoCalibCatalog : lsst.afw.table.ExposureCatalog, optional: Exposure catalog with external photoCalib to be applied if config.doApplyExternalPhotoCalib=True. Catalog uses the detector id for the catalog id, sorted on id for fast lookup.
finalizedPsfApCorrCatalog : lsst.afw.table.ExposureCatalog, optional: Exposure catalog with finalized psf models and aperture correction maps to be applied if config.doApplyFinalizedPsf=True. Catalog uses the detector id for the catalog id, sorted on id for fast lookup.

Returns:

exposure : lsst.afw.image.exposure.Exposure: Exposure with adjusted calibrations.

run(measCat, exposure, refCat, refWcs, exposureId=None)¶

Perform forced measurement on a single exposure.

Parameters:

measCat : lsst.afw.table.SourceCatalog: The measurement catalog, based on the sources listed in the reference catalog.
exposure : lsst.afw.image.Exposure: The measurement image upon which to perform forced detection.
refCat : lsst.afw.table.SourceCatalog: The reference catalog of sources to measure.
refWcs : lsst.afw.image.SkyWcs: The WCS for the references.
exposureId : int: Optional unique exposureId used for random seed in measurement task.

Returns:

result : lsst.pipe.base.Struct

Structure with fields:

measCat: Catalog of forced measurement results (lsst.afw.table.SourceCatalog).

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 the lsst.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 the lsst.daf.butler.DatasetRef objects associated with the defined output connections.

timer(name: str, logLevel: int = 10) → Iterator[None]¶

Context manager to log performance data for an arbitrary block of code.

Parameters:	name : `str` Name of code being timed; data will be logged using item name: `Start` and `End`. logLevel A `logging` level constant.

Navigation

ForcedPhotCcdTask¶