AssociationTask¶

class lsst.ap.association.AssociationTask(**kwargs)¶

Bases: lsst.pipe.base.Task

Associate DIAOSources into existing DIAObjects.

This task performs the association of detected DIASources in a visit with the previous DIAObjects detected over time. It also creates new DIAObjects out of DIASources that cannot be associated with previously detected DIAObjects.

Methods Summary

`associate_sources`(dia_objects, dia_sources)	Associate the input DIASources with the catalog of DIAObjects.
`check_dia_souce_radec`(dia_sources)	Check that all DiaSources have non-NaN values for RA/DEC.
`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`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.
`getSchemaCatalogs`()	Get the schemas generated 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.
`match`(dia_objects, dia_sources, score_struct)	Match DIAsources to DIAObjects given a score and create new DIAObject Ids for new unassociated DIASources.
`retrieve_dia_objects`(exposure, apdb)	Convert the exposure object into HTM pixels and retrieve DIAObjects contained within the exposure.
`run`(dia_sources, exposure, apdb)	Load DIAObjects from the database, associate the sources, and persist the results into the L1 database.
`score`(dia_objects, dia_sources, max_dist)	Compute a quality score for each dia_source/dia_object pair between this catalog of DIAObjects and the input DIASource catalog.
`timer`(name[, logLevel])	Context manager to log performance data for an arbitrary block of code.
`update_dia_objects`(dia_objects, …)	Update select dia_objects currently stored within the database or create new ones.

Methods Documentation

associate_sources(dia_objects, dia_sources)¶

Associate the input DIASources with the catalog of DIAObjects.

DiaObject DataFrame must be indexed on diaObjectId.

Parameters:

dia_objects : pandas.DataFrame: Catalog of DIAObjects to attempt to associate the input DIASources into.
dia_sources : pandas.DataFrame: DIASources to associate into the DIAObjectCollection.

Returns:

result : lsst.pipeBase.Struct

Results struct with components:

updated_and_new_dia_object_ids : ids of new and updated dia_objects as the result of association. (list of int).
new_dia_objects : Newly created DiaObjects from unassociated diaSources. (pandas.DataFrame)
n_updated_dia_objects : Number of previously known dia_objects with newly associated DIASources. (int).
n_new_dia_objects : Number of newly created DIAObjects from unassociated DIASources (int).
n_unupdated_dia_objects : Number of previous DIAObjects that were not associated to a new DIASource (int).

check_dia_souce_radec(dia_sources)¶

Check that all DiaSources have non-NaN values for RA/DEC.

If one or more DiaSources are found to have NaN values, throw a warning to the log with the ids of the offending sources. Drop them from the table.

Parameters:	dia_sources : `pandas.DataFrame` Input DiaSources to check for NaN values.
Returns:	trimmed_sources : `pandas.DataFrame` DataFrame of DiaSources trimmed of all entries with NaN values for RA/DEC.

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

getAllSchemaCatalogs()¶

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()¶

Get metadata for all tasks.

Returns:	metadata : `lsst.daf.base.PropertySet` The `PropertySet` 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()¶

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()¶

Get the name of the task.

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

See also

Task.getAllSchemaCatalogs

Notes

Warning

Subclasses that use schemas must override this method. The default implemenation 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.

getTaskDict()¶

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)¶

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("a brief description of what this task does")

makeSubtask(name, **keyArgs)¶

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 pex_config ConfigurableField or RegistryField.

match(dia_objects, dia_sources, score_struct)¶

Match DIAsources to DIAObjects given a score and create new DIAObject Ids for new unassociated DIASources.

Parameters:

dia_objects : pandas.DataFrame

A SourceCatalog of DIAObjects to associate to DIASources.

dia_sources : pandas.DataFrame

A contiguous catalog of dia_sources for which the set of scores has been computed on with DIAObjectCollection.score.

score_struct : lsst.pipe.base.Struct

Results struct with components:

scores: array of floats of match quality

updated DIAObjects (array-like of float).
obj_ids: array of floats of match quality

updated DIAObjects (array-like of int).
obj_idxs: indexes of the matched DIAObjects in the catalog.

(array-like of int)

Default values for these arrays are INF, -1 and -1 respectively for unassociated sources.

Returns:

result : lsst.pipeBase.Struct

Results struct with components:

updated_and_new_dia_object_ids : ids of new and updated dia_objects as the result of association. (list of int).
new_dia_objects : Newly created DiaObjects from unassociated diaSources. (pandas.DataFrame)
n_updated_dia_objects : Number of previously know dia_objects with newly associated DIASources. (int).
n_new_dia_objects : Number of newly created DIAObjects from unassociated DIASources (int).
n_unupdated_dia_objects : Number of previous DIAObjects that were not associated to a new DIASource (int).

retrieve_dia_objects(exposure, apdb)¶

Convert the exposure object into HTM pixels and retrieve DIAObjects contained within the exposure.

DiaObject DataFrame will be indexed on diaObjectId.

Parameters:	exposure : `lsst.afw.image.Exposure` An exposure specifying a bounding region with a WCS to load DIAOjbects within. apdb : `lsst.dax.apdb.Apdb` Apdb connection object to retrieve DIAObjects from.
Returns:	diaObjects : `pandas.DataFrame` DiaObjects within the exposure boundary.

run(dia_sources, exposure, apdb)¶

Load DIAObjects from the database, associate the sources, and persist the results into the L1 database.

Parameters:	dia_sources : `pandas.DataFrame` DIASources to be associated with existing DIAObjects. exposure : `lsst.afw.image` Input exposure representing the region of the sky the dia_sources were detected on. Should contain both the solved WCS and a bounding box of the ccd. apdb : `lsst.dax.apdb.Apdb` Apdb connection object to retrieve DIASources/Objects from and write to.
Returns:	result : `lsst.pipe.base.Struct` Results struct with components. `dia_objects` : Complete set of dia_objects covering the input exposure. Catalog contains newly created, updated, and untouched diaObjects. (`pandas.DataFrame`)

score(dia_objects, dia_sources, max_dist)¶

Compute a quality score for each dia_source/dia_object pair between this catalog of DIAObjects and the input DIASource catalog.

max_dist sets maximum separation in arcseconds to consider a dia_source a possible match to a dia_object. If the pair is beyond this distance no score is computed.

Parameters:

dia_objects : pandas.DataFrame: A contiguous catalog of DIAObjects to score against dia_sources.
dia_sources : pandas.DataFrame: A contiguous catalog of dia_sources to “score” based on distance and (in the future) other metrics.
max_dist : lsst.geom.Angle: Maximum allowed distance to compute a score for a given DIAObject DIASource pair.

Returns:

result : lsst.pipe.base.Struct

Results struct with components:

scores: array of floats of match quality updated DIAObjects

(array-like of float).
obj_idxs: indexes of the matched DIAObjects in the catalog.

(array-like of int)
obj_ids: array of floats of match quality updated DIAObjects

(array-like of int).

Default values for these arrays are INF, -1, and -1 respectively for unassociated sources.

timer(name, logLevel=10000)¶

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 `lsst.log` level constant.

Navigation

AssociationTask¶