output_quantities

lsst.verify.output_quantities(package_name, quantities, suffix=None, include_metrics=False, metrics_package='verify_metrics')

Output measurements, as astropy.units.Quantity objects, from a pipeline task execution to a lsst.verify-formatted JSON file.

Parameters:

package_name : str

Name of the package producing measurements. This name is used two ways:

1. Make fully-qualified metric names from keys in the quantities dictionary. For example, if a quantities dict has a key-value pair {'PA1': 5 * u.mmag} and package_name='validate_drp', the fully-qualified metric name is 'validate_drp.PA1'.
2. As a filename prefix for the output JSON file.

quantities : dict of astropy.units.Quantity values

Dictionary of measurements as plain astropy.units.Quantity instances. Each key is the name of a metric. If metric names are not fully-specified (in package.metric format), the package name can be provided with the package_name argument.

suffix : str, optional

Additional suffix to add to the output JSON filename:

{package_name}_{suffix}.verify.json

The suffix may be used to distinguish measurement output files from different tasks in the same package.

include_metrics : bool, optional

Metric and specification definitions are included in the JSON output if set to True. The metric and specification definitions are loaded from a metric package indicated by the metrics_package argument. Normally tasks do not need to include metric definitions if a post-processing step is used. Default: False.

metrics_package : str, optional

Name of the metrics package to obtain metrics from if include_metrics is True. Default is 'verify_metrics'.

Returns:

filename : str

Filename where the JSON file was written.

See also

lsst.verify.Job.write

Notes

This function is designed for lightweight lsst.verify framework usage. Rather than maintaining Job and Measurement objects, a task can simply record metric measurements as astropy.units.Quantity objects. With output_quantities, the task can output these measurements in a standardized lsst.verify JSON format. Post-processing tools can load this data for local analysis, or submit it to the https://squash.lsst.codes dashboard service.

Tasks that need to include Blobs, Measurement.extras or query Metric objects should create a Job instance and use Job.write instead.