ForcedPhotCoaddTask¶

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

Bases: lsst.pipe.base.PipelineTask

A pipeline task for performing forced measurement on coadd 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

`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.
`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 = 'deepCoadd_'¶

Methods Documentation

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

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

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. refCatInBand : `lsst.afw.table.SourceCatalog` Catalog of shapes and position in the band forced photometry is currently being performed refWcs : `lsst.afw.image.SkyWcs` Reference world coordinate system. idPackerName : `str` Type of ID packer to construct from the registry. footprintData : `ScarletDataModel` or `lsst.afw.table.SourceCatalog` Either the scarlet data models or the deblended catalog containing footprints. If `footprintData` is `None` then the footprints contained in `refCatInBand` are used.
Returns:	measCat : `lsst.afw.table.SourceCatalog` Catalog of forced sources to measure. expId : `int` Unique binary id associated with the input exposure
Raises:	LookupError Raised if a footprint with a given source id was in the reference catalog but not in the reference catalog in band (meaning there was some sort of mismatch in the two input catalogs)

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.

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

ForcedPhotCoaddTask¶