pipeline.hifa.tasks.applycal.qa

QA plugins for the ALMA applycal task.

This module demonstrates how to target QAScore messages at particular sections of the web log.

Functions

combine_scores(all_scores, hierarchy_base, …)	Combine and summarise a list of QA scores.
compress_data_selections(to_merge, …)	Combine adjacent data selections to give a new data structure that expresses the same data selection but in a more compressed form.
discard_dimension(to_merge, attrs)	Aggregate QA scores held in one or more DataSelection dimensions, discarding data selection indices for those dimensions.
get_qa_scores(ms, export_outliers, …)	Calculate amp/phase vs freq outliers for an EB and convert to QA scores.
in_casa_format(data_selections)	Restate data selections in concise CASA format.
map_data_selection_to_scores(scores)	Expand QAScores to a dict-based data structure that maps data selections to the QA scores applicable to that selection.
outliers_to_qa_scores(ms, outliers, …)	Convert a list of consolidated Outliers into a list of equivalent QAScores.
summarise_scores(all_scores, ms)	Process a list of QAscores, replacing the detailed and highly specific input scores with compressed representations intended for display in the web log accordion, and even more generalised summaries intended for display as warning banners.
take_min_as_representative(to_merge)	Filter out all but the worst score per data selection.
to_data_selection(tds)	Convert a pipeline QA TargetDataSelection object to a DataSelection tuple.

Classes

ALMAApplycalListQAHandler()	QA plugin to process lists of ALMA applycal results.
ALMAApplycalQAHandler()	QA plugin to handle an applycal result for a single ALMA EB.
DataSelection(vis, intent, scan, spw, ant, pol)
PIPE356Switches(calculate_metrics, …)
QAMessage(ms, outlier, reason)	QAMessage constructs a user-friendly QA message for an Outlier.