DiaObjectCalculationTask

class lsst.meas.base.DiaObjectCalculationTask(plugMetadata=None, **kwargs)

Bases: lsst.meas.base.CatalogCalculationTask

Run plugins which operate on a catalog of DIA sources.

This task facilitates running plugins which will operate on a source catalog. These plugins may do things such as classifying an object based on source record entries inserted during a measurement task.

This task differs from CatalogCaculationTask in the following ways:

-No multi mode is available for plugins. All plugins are assumed to run

in single mode.

-Input and output catalog types are assumed to be pandas.DataFrames with

columns following those used in the Apdb.

-No schema argument is passed to the plugins. Each plugin specifies

output columns and required inputs.

Parameters:

plugMetaData : lsst.daf.base.PropertyList or None

Will be modified in-place to contain metadata about the plugins being run. If None, an empty PropertyList will be created.

**kwargs

Additional arguments passed to the superclass constructor.

Notes

Plugins may either take an entire catalog to work on at a time, or work on individual records.

Methods Summary

callCompute(diaObjectCat, diaSourceCat, …)	Run each of the plugins on the catalog.
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.
initializePlugins()	Initialize the plugins according to the configuration.
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(diaObjectCat, diaSourceCat, …)	The entry point for the DIA catalog calculation task.
timer(name, logLevel)	Context manager to log performance data for an arbitrary block of code.

Methods Documentation

callCompute(diaObjectCat, diaSourceCat, updatedDiaObjectIds, filterNames)

Run each of the plugins on the catalog.

For catalog column names see the lsst.cat schema definitions for the DiaObject and DiaSource tables (http://github.com/lsst/cat).

Parameters:

diaObjectCat : pandas.DataFrame

DiaObjects to update values of and append new objects to. DataFrame should be indexed on “diaObjectId”

diaSourceCat : pandas.DataFrame

DiaSources associated with the DiaObjects in diaObjectCat. DataFrame must be indexed on [“diaObjectId”, “filterName”, “diaSourceId”]`

updatedDiaObjectIds : numpy.ndarray

Integer ids of the DiaObjects to update and create.

filterNames : list of str

List of string names of filters to be being processed.

Returns:

returnStruct : lsst.pipe.base.Struct

Struct containing:

diaObjectCat

Full set of DiaObjects including both un-updated and updated/new DiaObjects (pandas.DataFrame).

updatedDiaObjects

Catalog of DiaObjects that were updated or created by this task (pandas.DataFrame).

Raises:

KeyError

Raises if pandas.DataFrame indexing is not properly set.

emptyMetadata() → None

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

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

getSchemaCatalogs() → Dict[str, Any]

Get the schemas generated by this task.

Returns:

schemaCatalogs : dict

Keys are butler dataset type, values are an empty catalog (an instance of the appropriate lsst.afw.table Catalog type) for this task.

See also

Task.getAllSchemaCatalogs

Notes

Warning

Subclasses that use schemas must override this method. The default implementation 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() → 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.

initializePlugins()

Initialize the plugins according to the configuration.

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(diaObjectCat, diaSourceCat, updatedDiaObjectIds, filterNames)

The entry point for the DIA catalog calculation task.

Run method both updates the values in the diaObjectCat and appends newly created DiaObjects to the catalog. For catalog column names see the lsst.cat schema definitions for the DiaObject and DiaSource tables (http://github.com/lsst/cat).

Parameters:

diaObjectCat : pandas.DataFrame

DiaObjects to update values of and append new objects to. DataFrame should be indexed on “diaObjectId”

diaSourceCat : pandas.DataFrame

DiaSources associated with the DiaObjects in diaObjectCat. DataFrame should be indexed on ["diaObjectId", "filterName", "diaSourceId"]

updatedDiaObjectIds : numpy.ndarray

Integer ids of the DiaObjects to update and create.

filterNames : list of str

List of string names of filters to be being processed.

Returns:

returnStruct : lsst.pipe.base.Struct

Struct containing:

diaObjectCat

Full set of DiaObjects including both un-updated and updated/new DiaObjects (pandas.DataFrame).

updatedDiaObjects

Catalog of DiaObjects that were updated or created by this task (pandas.DataFrame).

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.

See also

timer.logInfo

Examples

Creating a timer context:

with self.timer("someCodeToTime"):
    pass  # code to time