AbstractMetadataMetricTask¶

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

Bases: lsst.verify.tasks.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.
`getResourceConfig`()	Return resource configuration for 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.
`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 = 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:	metadata : `lsst.pipe.base.TaskMetadata` A metadata object. metadataKeys : `dict` [`str`, `str`] Keys are arbitrary labels, values are metadata keys (or their substrings) in the format of `lsst.pipe.base.Task.getFullMetadata()`.
Returns:	metadataValues : `dict` [`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() → 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”.

classmethod getInputMetadataKeys(config)¶

Return the metadata keys read by this task.

Parameters:

config : cls.ConfigClass: Configuration for this task.

Returns:

keys : dict [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:	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.

getTaskDict() → Dict[str, weakref.ReferenceType[lsst.pipe.base.task.Task]]¶

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")

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(**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:	struct : `lsst.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:	name : `str` Name of code being timed; data will be logged using item name: `Start` and `End`. logLevel A `logging` level constant.

Navigation

AbstractMetadataMetricTask¶