TotalUnassociatedDiaObjectsMetricTask

class lsst.ap.association.metrics.TotalUnassociatedDiaObjectsMetricTask(**kwargs)

Bases: lsst.verify.tasks.ApdbMetricTask

Task that computes the number of DIAObjects with only one associated DIASource.

Attributes Summary

canMultiprocess

Methods Summary

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.
getResourceConfig()	Return resource configuration for this 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.
makeMeasurement(dbHandle, outputDataId)	Compute the number of unassociated DIAObjects.
makeSubtask(name, **keyArgs)	Create a subtask as a new instance as the name attribute of this task.
run(dbInfo[, outputDataId])	Compute a measurement from a database.
runQuantum(butlerQC, inputRefs, outputRefs)	Do Butler I/O to provide in-memory objects for run.
timer(name, logLevel)	Context manager to log performance data for an arbitrary block of code.

Attributes Documentation

canMultiprocess = True

Methods Documentation

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

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() → 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.

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")

makeMeasurement(dbHandle, outputDataId)

Compute the number of unassociated DIAObjects.

Parameters:

dbHandle : lsst.dax.apdb.Apdb

A database instance.

outputDataId : any data ID type

The subset of the database to which this measurement applies. Must be empty, as the number of unassociated sources is ill-defined for subsets of the dataset.

Returns:

measurement : lsst.verify.Measurement

The total number of unassociated objects.

Raises:

MetricComputationError

Raised on any failure to query the database.

ValueError

Raised if outputDataId is not empty

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(dbInfo, outputDataId={})

Compute a measurement from a database.

Parameters:

dbInfo : list

The datasets (of the type indicated by the config) from which to load the database. If more than one dataset is provided (as may be the case if DB writes are fine-grained), all are assumed identical.

outputDataId: any data ID type, optional

The output data ID for the metric value. Defaults to the empty ID, representing a value that covers the entire dataset.

Returns:

result : lsst.pipe.base.Struct

Result struct with component:

measurement

the value of the metric (lsst.verify.Measurement or None)

Raises:

MetricComputationError

Raised if an algorithmic or system error prevents calculation of the metric.

Notes

This implementation calls dbLoader to acquire a database handle (taking None if no input), then passes it and the value of outputDataId to makeMeasurement. The result of makeMeasurement is returned to the caller.

runQuantum(butlerQC, inputRefs, outputRefs)

Do Butler I/O to provide in-memory objects for run.

This specialization of runQuantum passes the output data ID to run.

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