MonitoringSource#

class ctapipe.io.MonitoringSource(*args: t.Any, **kwargs: t.Any)[source]#

Bases: TelescopeComponent

Parent class for MonitoringSource.

MonitoringSource read input files and fill ArrayEventContainer instances with corresponding monitoring data based on the event trigger time.

A new MonitoringSource should be created for each type of monitoring file read into ctapipe, e.g. HDF5 files are read by the HDF5MonitoringSource.

MonitoringSource provides a common high-level interface for accessing monitoring information from different data sources. Creating an MonitoringSource for a new file format or other monitoring source ensures that data can be accessed in a common way, regardless of the file format or data origin.

MonitoringSource itself is an abstract class, but will create an appropriate subclass. An MonitoringSource can also be created through the configuration system, by passing config or parent as appropriate. E.g. if using MonitoringSource inside of a Tool, you would do:

>>> self.monitoring_source = MonitoringSource(parent=self)

Attributes Summary

`monitoring_types`	The monitoring types provided by this monitoring source
`plugin_entry_point`

Methods Summary

`close`()	Close this event source.
`fill_monitoring_container`(event)	Fill the monitoring container for a given event.
`get_table`(monitoring_type[, tel_id])	Get the raw monitoring table for a given monitoring type.
`get_values`(monitoring_type, time[, tel_id])	Get monitoring values for specific timestamp(s).
`has_any_monitoring_types`(monitoring_types)	Check if any of `monitoring_types` is in self.monitoring_types

Attributes Documentation

monitoring_types#

The monitoring types provided by this monitoring source

Returns:

tuple[ctapipe.io.MonitoringType]

plugin_entry_point = 'ctapipe_monitoring'#

Methods Documentation

close()[source]#

Close this event source.

No-op by default. Should be overridden by sources needing a cleanup-step

abstractmethod fill_monitoring_container(event: ArrayEventContainer)[source]#

Fill the monitoring container for a given event.

Populates event.monitoring with telescope-level and array-level monitoring data for the event’s trigger time.

Parameters:

eventArrayEventContainer: The event to fill. Uses event.trigger.time for data selection.

abstractmethod get_table(monitoring_type: MonitoringType, tel_id: int = None, **kwargs) → Table[source]#

Get the raw monitoring table for a given monitoring type.

Parameters:

monitoring_typeMonitoringType: The type of monitoring data to retrieve.
tel_idint, optional: Telescope ID for telescope-level monitoring (camera, telescope pointing). None for array-level monitoring (weather, FRAM, LiDAR).
**kwargs: Implementation-specific parameters (e.g., subtype for PIXEL_STATISTICS).

Returns:

astropy.table.Table: The monitoring table.

Raises:

KeyError: If monitoring_type is not available.
TypeError: If tel_id scope doesn’t match monitoring_type requirements.

abstractmethod get_values(monitoring_type: MonitoringType, time: Time, tel_id: int = None, **kwargs)[source]#

Get monitoring values for specific timestamp(s).

Performs interpolation or nearest-neighbor lookup as appropriate.

Parameters:

monitoring_typeMonitoringType: The type of monitoring data to retrieve.
timeastropy.time.Time: Target timestamp(s). Can be scalar or array.
tel_idint, optional: Telescope ID for telescope-level monitoring. None for array-level.
**kwargs: Implementation-specific parameters (e.g., timestamp_tolerance, query_method).

Returns:

dict[str, astropy.units.Quantity | numpy.ndarray] or astropy.coordinates.SkyCoord: Monitoring values at requested time(s). Return type depends on monitoring_type.

Raises:

KeyError: If monitoring_type unavailable
ValueError: If time out of bounds.
TypeError: If tel_id scope doesn’t match monitoring_type requirements.

has_any_monitoring_types(monitoring_types) → bool[source]#

Check if any of monitoring_types is in self.monitoring_types

Parameters:

monitoring_types: Iterable: Iterable of monitoring types