MetricsControllerTask¶

class lsst.verify.gen2tasks.MetricsControllerTask(config=None, **kwargs)¶

Bases: lsst.pipe.base.Task

A Task for executing a collection of lsst.verify.tasks.MetricTask objects.

This class handles Butler input of datasets needed by metrics, as well as persistence of the resulting measurements.

Notes

MetricsControllerTask is a stand-in for functionality provided by the Gen 3 Tasks framework. It will become redundant once we fully adopt that framework.

Because MetricsControllerTask cannot support the full functionality of the Gen 3 framework, it places several restrictions on its metrics:

each MetricTask must measure a unique metric

no MetricTask may depend on the output of another MetricTask

the granularity of the metrics is determined by the inputs to runDataRefs; configuration information specifying a different granularity is allowed but is ignored

Attributes Summary

measurers The tasks to be executed by this object (iterable of lsst.verify.tasks.MetricTask).

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.
`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.
`runDataRefs`(datarefs[, customMetadata, …])	Call all registered metric tasks on each dataref.
`timer`(name[, logLevel])	Context manager to log performance data for an arbitrary block of code.

Attributes Documentation

measurers = []¶: The tasks to be executed by this object (iterable of lsst.verify.tasks.MetricTask).

Methods Documentation

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 : `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()¶

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 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()¶

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("brief description of task")

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 ConfigurableField or RegistryField.

runDataRefs(datarefs, customMetadata=None, skipExisting=False)¶

Call all registered metric tasks on each dataref.

This method loads all datasets required to compute a particular metric, and persists the metrics as one or more lsst.verify.Job objects. Only metrics that successfully produce a Measurement will be included in a job.

Parameters:

datarefs : list of lsst.daf.persistence.ButlerDataRef: The data to measure. Datarefs may be complete or partial; each generates a measurement at the same granularity (e.g., a dataref with only "visit" specified generates visit-level measurements).
customMetadata : dict, optional: Any metadata that are needed for a specific pipeline, but that are not needed by the lsst.verify framework or by general-purpose measurement analysis code (these cases are handled by the metadataAdder subtask). If omitted, only generic metadata are added. Both keys and values must be valid inputs to Metadata.
skipExisting : bool, optional: If this flag is set, MetricsControllerTask will skip computing metrics for any data ID that already has an output job file on disk. While this option is useful for restarting failed runs, it does not check whether the file is valid.

Returns:

struct : lsst.pipe.base.Struct

A Struct containing the following component:

jobs : a list of collections of measurements (list of lsst.verify.Job). Each job in the list contains the measurement(s) for the corresponding dataref, and each job has at most one measurement for each element in self.measurers. A particular measurement is omitted if it could not be created. If skipExisting is set, any jobs that already exist on disk are also omitted.

Notes

Some objects may be persisted, or incorrectly persisted, in the event of an exception.

timer(name, logLevel=10)¶

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

MetricsControllerTask¶