ParticleClassifier

class ctapipe.reco.sklearn.ParticleClassifier(**kwargs: Any)

Bases: SKLearnClassificationReconstructor

Predict dl2 particle classification.

Attributes Summary

positive_class	Particle id (in simtel system) of the positive class.
property	Property predicted, overridden in subclass.
target	Name of the target table column for training.

Methods Summary

__call__(event)	Event-wise prediction for the EventSource-Loop.
predict_table(key, table)	Predict on a table of events.

Attributes Documentation

positive_class

Particle id (in simtel system) of the positive class. Default is 0 for gammas.

property = 4

Property predicted, overridden in subclass.

target: str = 'true_shower_primary_id'

Name of the target table column for training.

Methods Documentation

__call__(event: ArrayEventContainer) → None

Event-wise prediction for the EventSource-Loop.

Fills the event.dl2.<your-feature>[name] container.

Parameters:

event: ArrayEventContainer

predict_table(key, table: Table) → dict[ReconstructionProperty, Table]

Predict on a table of events.

Parameters:

keyHashable

Key of the model. Currently always a TelescopeDescription as we train models per telescope type.

tableTable

Table of features

Returns:

tableTable

Table(s) with predictions, matches the corresponding container definition(s)