AbstractMetadataMetricTask

class lsst.verify.tasks.AbstractMetadataMetricTask(**kwargs)

Bases: MetricTask

A base class for tasks that compute metrics from metadata values.

This class contains code that is agnostic to whether the input is one metadata object or many.

Parameters:

*args

**kwargs

Constructor parameters are the same as for lsst.pipe.base.PipelineTask.

Notes

This class should be customized by overriding getInputMetadataKeys and run.

Attributes Summary

canMultiprocess

Methods Summary

emptyMetadata()	Empty (clear) the metadata for this Task and all sub-Tasks.
extractMetadata(metadata, metadataKeys)	Read multiple keys from a metadata object.
getFullMetadata()	Get metadata for all tasks.
getFullName()	Get the task name as a hierarchical name including parent task names.
getInputMetadataKeys(config)	Return the metadata keys read by this task.
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.
run(**kwargs)	Run the MetricTask on in-memory data.
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: ClassVar[bool] = True

Methods Documentation

emptyMetadata() → None

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

static extractMetadata(metadata, metadataKeys)

Read multiple keys from a metadata object.

Parameters:

metadatalsst.pipe.base.TaskMetadata

A metadata object.

metadataKeysdict [str, str]

Keys are arbitrary labels, values are metadata keys (or their substrings) in the format of lsst.pipe.base.Task.getFullMetadata().

Returns:

metadataValuesdict [str, any]

Keys are the same as for metadataKeys, values are the value of each metadata key, or None if no matching key was found.

Raises:

lsst.verify.tasks.MetricComputationError

Raised if any metadata key string has more than one match in metadata.

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”.

abstract classmethod getInputMetadataKeys(config)

Return the metadata keys read by this task.

Parameters:

configcls.ConfigClass

Configuration for this task.

Returns:

keysdict [str, str]

The keys are the (arbitrary) names of values to use in task code, the values are the metadata keys to be looked up (see the metadataKeys parameter to extractMetadata). Metadata keys are assumed to include task prefixes in the format of lsst.pipe.base.Task.getFullMetadata(). This method may return a substring of the desired (full) key, but the string must match a unique metadata key.

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.

abstract run(**kwargs)

Run the MetricTask on in-memory data.

Parameters:

**kwargs

Keyword arguments matching the inputs given in the class config; see lsst.pipe.base.PipelineTask.run for more details.

Returns:

structlsst.pipe.base.Struct

A Struct containing at least the following component:

• measurement: the value of the metric (lsst.verify.Measurement or None). This method is not responsible for adding mandatory metadata (e.g., the data ID); this is handled by the caller. None may be used to indicate that a metric is undefined or irrelevant instead of raising NoWorkFound.

Raises:

lsst.verify.tasks.MetricComputationError

Raised if an algorithmic or system error prevents calculation of the metric. Examples include corrupted input data or unavoidable exceptions raised by analysis code. The MetricComputationError should be chained to a more specific exception describing the root cause.

Not having enough data for a metric to be applicable is not an error, and should raise NoWorkFound (see below) instead of this exception.

lsst.pipe.base.NoWorkFound

Raised if the metric is ill-defined or otherwise inapplicable to the data. Typically this means that the pipeline step or option being measured was not run.

runQuantum(butlerQC, inputRefs, outputRefs)

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

This specialization of runQuantum performs error-handling specific to MetricTasks.

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