DiaPipelineTask¶
- class lsst.ap.association.DiaPipelineTask(initInputs=None, **kwargs)¶
Bases:
PipelineTask
Task for loading, associating and storing Difference Image Analysis (DIA) Objects and Sources.
Attributes Summary
Methods Summary
createNewDiaObjects
(unAssocDiaSources)Loop through the set of DiaSources and create new DiaObjects for unassociated DiaSources.
Empty (clear) the metadata for this Task and all sub-Tasks.
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.
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.purgeDiaObjects
(bbox, wcs, diaObjCat[, buffer])Drop diaObjects that are outside the exposure bounding box.
run
(diaSourceTable, solarSystemObjectTable, ...)Process DiaSources and DiaObjects.
runQuantum
(butlerQC, inputRefs, outputRefs)Do butler IO and transform to provide in memory objects for tasks
run
method.Test the sorted DataFrame index for duplicates.
timer
(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
Attributes Documentation
Methods Documentation
- createNewDiaObjects(unAssocDiaSources)¶
Loop through the set of DiaSources and create new DiaObjects for unassociated DiaSources.
- Parameters:
- unAssocDiaSources
pandas.DataFrame
Set of DiaSources to create new DiaObjects from.
- unAssocDiaSources
- Returns:
- results
lsst.pipe.base.Struct
Results struct containing:
diaSources
: DiaSource catalog with updated DiaObject ids. (pandas.DataFrame
)newDiaObjects
: Newly created DiaObjects from the unassociated DiaSources. (pandas.DataFrame
)nNewDiaObjects
: Number of newly created diaObjects.(int
)
- results
- 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
- getName() str ¶
Get the name of the task.
- Returns:
- taskName
str
Name of the task.
- taskName
See also
getFullName
Get the full name of the task.
- 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
- 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
.
- purgeDiaObjects(bbox, wcs, diaObjCat, buffer=0)¶
Drop diaObjects that are outside the exposure bounding box.
- Parameters:
- bbox
lsst.geom.Box2I
Bounding box of the exposure.
- wcs
lsst.afw.geom.SkyWcs
Coordinate system definition (wcs) for the exposure.
- diaObjCat
pandas.DataFrame
DiaObjects loaded from the Apdb.
- buffer
int
, optional Width, in pixels, to pad the exposure bounding box.
- bbox
- Returns:
- diaObjCat
pandas.DataFrame
DiaObjects loaded from the Apdb, restricted to the exposure bounding box.
- diaObjCat
- run(diaSourceTable, solarSystemObjectTable, diffIm, exposure, template, band, idGenerator)¶
Process DiaSources and DiaObjects.
Load previous DiaObjects and their DiaSource history. Calibrate the values in the diaSourceCat. Associate new DiaSources with previous DiaObjects. Run forced photometry at the updated DiaObject locations. Store the results in the Alert Production Database (Apdb).
- Parameters:
- diaSourceTable
pandas.DataFrame
Newly detected DiaSources.
- diffIm
lsst.afw.image.ExposureF
Difference image exposure in which the sources in
diaSourceCat
were detected.- exposure
lsst.afw.image.ExposureF
Calibrated exposure differenced with a template to create
diffIm
.- template
lsst.afw.image.ExposureF
Template exposure used to create diffIm.
- band
str
The band in which the new DiaSources were detected.
- idGenerator
lsst.meas.base.IdGenerator
Object that generates source IDs and random number generator seeds.
- diaSourceTable
- Returns:
- results
lsst.pipe.base.Struct
Results struct with components.
apdbMaker
: Marker dataset to store in the Butler indicating that this ccdVisit has completed successfully. (lsst.dax.apdb.ApdbConfig
)associatedDiaSources
: Catalog of newly associated DiaSources. (pandas.DataFrame
)
- results
- 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
- testDataFrameIndex(df)¶
Test the sorted DataFrame index for duplicates.
Wrapped as a separate function to allow for mocking of the this task in unittesting. Default of a mock return for this test is True.
- Parameters:
- df
pandas.DataFrame
DataFrame to text.
- df
- Returns:
bool
True if DataFrame contains duplicate rows.