columnflow.calibration

columnflow.calibration#

Object and event calibration tools.

Classes:

Calibrator(*args, **kwargs)

Base class for all calibrators.

Functions:

calibrator([func, bases, mc_only, data_only])

Decorator for creating a new Calibrator subclass with additional, optional bases and attaching the decorated function to it as call_func.
class Calibrator(*args, **kwargs)[source]#

Bases: TaskArrayFunction

Base class for all calibrators.

Attributes:

exposed

cache_instances

Methods:

calibrator([func, bases, mc_only, data_only])

Decorator for creating a new Calibrator subclass with additional, optional bases and attaching the decorated function to it as call_func.
exposed = True#
classmethod calibrator(func=None, bases=(), mc_only=False, data_only=False, **kwargs)[source]#

Decorator for creating a new Calibrator subclass with additional, optional bases and attaching the decorated function to it as call_func.

When mc_only (data_only) is True, the calibrator is skipped and not considered by other calibrators, selectors and producers in case they are evalauted on a order.Dataset (using the dataset_inst attribute) whose is_mc (is_data) attribute is False.

All additional kwargs are added as class members of the new subclasses.

Parameters:

  • func (Callable | None, default: None) – Function to be wrapped and integrated into new Calibrator class.

  • bases (tuple, default: ()) – Additional bases for the new Calibrator.

  • mc_only (bool, default: False) – Boolean flag indicating that this Calibrator should only run on Monte Carlo simulation and skipped for real data.

  • data_only (bool, default: False) – Boolean flag indicating that this Calibrator should only run on real data and skipped for Monte Carlo simulation.

Return type:

DerivableMeta | Callable

Returns:

New Calibrator subclass.

cache_instances = True#
calibrator(func=None, bases=(), mc_only=False, data_only=False, **kwargs)#

Decorator for creating a new Calibrator subclass with additional, optional bases and attaching the decorated function to it as call_func.

When mc_only (data_only) is True, the calibrator is skipped and not considered by other calibrators, selectors and producers in case they are evalauted on a order.Dataset (using the dataset_inst attribute) whose is_mc (is_data) attribute is False.

All additional kwargs are added as class members of the new subclasses.

Parameters:

  • func (Callable | None, default: None) – Function to be wrapped and integrated into new Calibrator class.

  • bases (tuple, default: ()) – Additional bases for the new Calibrator.

  • mc_only (bool, default: False) – Boolean flag indicating that this Calibrator should only run on Monte Carlo simulation and skipped for real data.

  • data_only (bool, default: False) – Boolean flag indicating that this Calibrator should only run on real data and skipped for Monte Carlo simulation.

Return type:

DerivableMeta | Callable

Returns:

New Calibrator subclass.

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