Statistics Aggregator

Reference/API

ctapipe.monitoring.aggregator Module

Algorithms to compute aggregated time-series statistics from columns of an astropy table.

These classes take as input an events table containing any event-wise quantities (e.g., images, scalars, vectors), divide it into time chunks, which may optionally overlap, and compute various aggregated statistics for each chunk. The statistics include the count, mean, median, and standard deviation. The result is a monitoring table with columns describing the start and stop time of the chunk and the aggregated statistic values.

The aggregation is always performed along axis=0 (the event dimension), making these classes suitable for any N-dimensional event-wise data.

Classes

BaseChunking(*args, **kwargs)	Abstract base class for chunking strategies.
SizeChunking(*args, **kwargs)	Divides tables into chunks based on number of rows.
TimeChunking(*args, **kwargs)	Divides tables into chunks based on time intervals.
BaseAggregator(*args, **kwargs)	Base class for aggregators that compute statistics over chunks of data.
StatisticsAggregator(*args, **kwargs)	Base component to handle the computation of aggregated statistic values from a table containing any event-wise quantities (e.g., images, scalars, vectors, or other arrays).
PlainAggregator(*args, **kwargs)	Compute aggregated statistic values from a chunk of event-wise data using numpy functions.
SigmaClippingAggregator(*args, **kwargs)	Compute aggregated statistic values from a chunk of event-wise data using astropy's sigma clipping functions.

Class Inheritance Diagram