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

canMultiprocess

Methods Summary

associateDiaSources(diaSourceTable, ...)

Associate DiaSources with DiaObjects.

createNewDiaObjects(unAssocDiaSources)

Loop through the set of DiaSources and create new DiaObjects for unassociated DiaSources.

emptyMetadata()

Empty (clear) the metadata for this Task and all sub-Tasks.

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.

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.

mergeAssociatedCatalogs(preloadedDiaSources, ...)

Merge the associated diaSource and diaObjects to their previous history.

mergeCatalogs(originalCatalog, newCatalog, ...)

Combine two catalogs, ensuring that the columns of the new catalog have the same dtype as the original.

purgeDiaObjects(bbox, wcs, diaObjCat[, ...])

Drop diaObjects that are outside the exposure bounding box.

run(diaSourceTable, legacySolarSystemTable, ...)

Process DiaSources and DiaObjects.

runForcedMeasurement(diaObjects, ...)

Forced Source Measurement

runQuantum(butlerQC, inputRefs, outputRefs)

Do butler IO and transform to provide in memory objects for tasks run method.

testDataFrameIndex(df)

Test the sorted DataFrame index for duplicates.

timer(name[, logLevel])

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

updateObjectTable(diaObjects, diaSources)

Update the diaObject table with the new diaSource records.

writeToApdb(updatedDiaObjects, ...)

Write to the Alert Production Database (Apdb).

Attributes Documentation

canMultiprocess: ClassVar[bool] = True

Methods Documentation

associateDiaSources(diaSourceTable, solarSystemObjectTable, diffIm, diaObjects)

Associate DiaSources with DiaObjects.

Associate new DiaSources with existing DiaObjects. Create new DiaObjects fron unassociated DiaSources. Index DiaSource catalogue after associations. Append new DiaObjects and DiaSources to their previous history. Test for DiaSource and DiaObject duplications. Compute DiaObject Summary statistics from their full DiaSource history. Test for duplication in the updated DiaObjects.

Parameters:
diaSourceTablepandas.DataFrame

Newly detected DiaSources.

solarSystemObjectTablepandas.DataFrame

Preloaded Solar System objects expected to be visible in the image.

diffImlsst.afw.image.ExposureF

Difference image exposure in which the sources in diaSourceCat were detected.

diaObjectspandas.DataFrame

Table of DiaObjects from preloaded DiaObjects.

Returns:
associatedDiaSourcespandas.DataFrame

Associated DiaSources with DiaObjects.

newDiaObjectspandas.DataFrame

Table of new DiaObjects after association.

associatedSsSourcespandas.DataFrame

Table of new ssSources after association.

createNewDiaObjects(unAssocDiaSources)

Loop through the set of DiaSources and create new DiaObjects for unassociated DiaSources.

Parameters:
unAssocDiaSourcespandas.DataFrame

Set of DiaSources to create new DiaObjects from.

Returns:
resultslsst.pipe.base.Struct

Results struct containing:

  • diaSourcespandas.DataFrame

    DiaSource catalog with updated DiaObject ids.

  • newDiaObjectspandas.DataFrame

    Newly created DiaObjects from the unassociated DiaSources.

  • nNewDiaObjectsint

    Number of newly created diaObjects.

emptyMetadata() None

Empty (clear) the metadata for this Task and all sub-Tasks.

getFullMetadata() TaskMetadata

Get metadata for all tasks.

Returns:
metadataTaskMetadata

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:
fullNamestr

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:
taskNamestr

Name of the task.

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:
taskDictdict

Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.

classmethod makeField(doc: str) ConfigurableField

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

Parameters:
docstr

Help text for the field.

Returns:
configurableFieldlsst.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: Any) None

Create a subtask as a new instance as the name attribute of this task.

Parameters:
namestr

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.

mergeAssociatedCatalogs(preloadedDiaSources, associatedDiaSources, diaObjects, newDiaObjects, diffIm)

Merge the associated diaSource and diaObjects to their previous history.

Parameters:
preloadedDiaSourcespandas.DataFrame

Previously detected DiaSources, loaded from the APDB.

associatedDiaSourcespandas.DataFrame

Associated DiaSources with DiaObjects.

diaObjectspandas.DataFrame

Table of DiaObjects from preloaded DiaObjects.

newDiaObjectspandas.DataFrame

Table of new DiaObjects after association.

Returns:
mergedDiaSourceHistorypandas.DataFrame

The combined catalog, with all of the rows from preloadedDiaSources catalog ordered before the rows of associatedDiaSources catalog.

mergedDiaObjectspandas.DataFrame

Table of new DiaObjects merged with their history.

updatedDiaObjectIdsnumpy.Array

Object Id’s from associated diaSources.

Raises:
RuntimeError

Raised if duplicate DiaObjects or duplicate DiaSources are found.

mergeCatalogs(originalCatalog, newCatalog, catalogName)

Combine two catalogs, ensuring that the columns of the new catalog have the same dtype as the original.

Parameters:
originalCatalogpandas.DataFrame

The original catalog to be added to.

newCatalogpandas.DataFrame

The new catalog to append to originalCatalog

catalogNamestr, optional

The name of the catalog to use for logging messages.

Returns:
mergedCatalogpandas.DataFrame

The combined catalog, with all of the rows from originalCatalog ordered before the rows of newCatalog

purgeDiaObjects(bbox, wcs, diaObjCat, diaObjectIds=None, buffer=0)

Drop diaObjects that are outside the exposure bounding box.

Parameters:
bboxlsst.geom.Box2I

Bounding box of the exposure.

wcslsst.afw.geom.SkyWcs

Coordinate system definition (wcs) for the exposure.

diaObjCatpandas.DataFrame

DiaObjects loaded from the Apdb.

bufferint, optional

Width, in pixels, to pad the exposure bounding box.

Returns:
diaObjCatpandas.DataFrame

DiaObjects loaded from the Apdb, restricted to the exposure bounding box.

run(diaSourceTable, legacySolarSystemTable, diffIm, exposure, template, preloadedDiaObjects, preloadedDiaSources, preloadedDiaForcedSources, band, idGenerator, solarSystemObjectTable=None)

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:
diaSourceTablepandas.DataFrame

Newly detected DiaSources.

legacySolarSystemTablepandas.DataFrame

Not used

diffImlsst.afw.image.ExposureF

Difference image exposure in which the sources in diaSourceCat were detected.

exposurelsst.afw.image.ExposureF

Calibrated exposure differenced with a template to create diffIm.

templatelsst.afw.image.ExposureF

Template exposure used to create diffIm.

preloadedDiaObjectspandas.DataFrame

Previously detected DiaObjects, loaded from the APDB.

preloadedDiaSourcespandas.DataFrame

Previously detected DiaSources, loaded from the APDB.

preloadedDiaForcedSourcespandas.DataFrame

Catalog of previously detected forced DiaSources, from the APDB

bandstr

The band in which the new DiaSources were detected.

idGeneratorlsst.meas.base.IdGenerator

Object that generates source IDs and random number generator seeds.

solarSystemObjectTablepandas.DataFrame

Preloaded Solar System objects expected to be visible in the image.

Returns:
resultslsst.pipe.base.Struct

Results struct with components.

  • apdbMarker : 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)

  • diaForcedSources : Catalog of new and previously detected forced DiaSources. (pandas.DataFrame)

  • diaObjects : Updated table of DiaObjects. (pandas.DataFrame)

  • associatedSsSources : Catalog of ssSource records. (pandas.DataFrame)

Raises:
RuntimeError

Raised if duplicate DiaObjects or duplicate DiaSources are found.

runForcedMeasurement(diaObjects, updatedDiaObjects, exposure, diffIm, idGenerator)

Forced Source Measurement

Forced photometry on the difference and calibrated exposures using the new and updated DiaObject locations.

Parameters:
diaObjectspandas.DataFrame

Catalog of DiaObjects.

updatedDiaObjectspandas.DataFrame

Catalog of updated DiaObjects.

exposurelsst.afw.image.ExposureF

Calibrated exposure differenced with a template to create diffIm.

diffImlsst.afw.image.ExposureF

Difference image exposure in which the sources in diaSourceCat were detected.

idGeneratorlsst.meas.base.IdGenerator

Object that generates source IDs and random number generator seeds.

Returns:
diaForcedSourcespandas.DataFrame

Catalog of calibrated forced photometered fluxes on both the difference and direct images at DiaObject locations.

runQuantum(butlerQC, inputRefs, outputRefs)

Do butler IO and transform to provide in memory objects for tasks run method.

Parameters:
butlerQCQuantumContext

A butler which is specialized to operate in the context of a lsst.daf.butler.Quantum.

inputRefsInputQuantizedConnection

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.

outputRefsOutputQuantizedConnection

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.

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:
dfpandas.DataFrame

DataFrame to text.

Returns:
bool

True if DataFrame contains duplicate rows.

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

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

Parameters:
namestr

Name of code being timed; data will be logged using item name: Start and End.

logLevelint

A logging level constant.

See also

lsst.utils.timer.logInfo

Implementation function.

Examples

Creating a timer context:

with self.timer("someCodeToTime"):
    pass  # code to time
updateObjectTable(diaObjects, diaSources)

Update the diaObject table with the new diaSource records.

Parameters:
diaObjectspandas.DataFrame

Table of new DiaObjects merged with their history.

diaSourcespandas.DataFrame

The combined preloaded and associated diaSource catalog.

Returns:
updatedDiaObjectspandas.DataFrame

Table of DiaObjects updated with the number of associated DiaSources

writeToApdb(updatedDiaObjects, associatedDiaSources, diaForcedSources)

Write to the Alert Production Database (Apdb).

Store DiaSources, updated DiaObjects, and DiaForcedSources in the Alert Production Database (Apdb).

Parameters:
updatedDiaObjectspandas.DataFrame

Catalog of updated DiaObjects.

associatedDiaSourcespandas.DataFrame

Associated DiaSources with DiaObjects.

diaForcedSourcespandas.DataFrame

Catalog of calibrated forced photometered fluxes on both the difference and direct images at DiaObject locations.