MultiMetadataMetricTask

MultiMetadataMetricTask is a base class for generating Measurements from task metadata of a higher granularity than the metric. The class handles loading metadata and extracting the keys of interest, while subclasses are responsible for creating the Measurement from the extracted values.

See MetadataMetricTask for when the metadata and metric have the same granularity.

MultiMetadataMetricTask is currently a subclass of lsst.verify.tasks.MetricTask. It is expected that MultiMetadataMetricTask can be migrated to the Gen 3 framework without affecting its subclasses.

Processing summary

MultiMetadataMetricTask runs this sequence of operations:

1. Find the metadata key(s) needed to compute the metric by calling the customizable getInputMetadataKeys method.
2. Search all the metadata objects passed to run for the keys, and extract the corresponding values.
3. Process the values by calling the customizable makeMeasurement method, and return the Measurement.

Python API summary

from lsst.verify.tasks.metadataMetricTask import MultiMetadataMetricTask

classMultiMetadataMetricTask(**kwargs)

A base class for tasks that compute metrics from multiple metadata objects...

attributeconfig

Access configuration fields and retargetable subtasks.

methodrun(metadata)

Compute a measurement from science task metadata...

See also

See the MultiMetadataMetricTask API reference for complete details.

Butler datasets

Input datasets

metadata

The metadata of the top-level command-line task (e.g., ProcessCcdTask, ApPipeTask) being instrumented. Because the metadata produced by each top-level task is a different Butler dataset type, this dataset must be explicitly configured when running MultiMetadataMetricTask or a MetricsControllerTask that contains it.

Retargetable subtasks

No subtasks.

Configuration fields

connections

Data type

lsst.pipe.base.config.Connections

Field type

ConfigField

Configurations describing the connections of the PipelineTask to datatypes