columnflow.weight

columnflow.weight#

Tools for producing new columns to be used as event or object weights.

Classes:

WeightProducer(*args[, requires_func, ...])

Base class for all weight producers, i.e., functions that produce and return a single column that is meant to be used as a per-event or per-object weight.

Functions:

weight_producer([func, bases, mc_only, ...])

Decorator for creating a new WeightProducer subclass with additional, optional bases and attaching the decorated function to it as call_func().
class WeightProducer(*args, requires_func=law.util.no_value, setup_func=law.util.no_value, sandbox=law.util.no_value, call_force=law.util.no_value, max_chunk_size=law.util.no_value, pick_cached_result=law.util.no_value, inst_dict=None, **kwargs)[source]#

Bases: TaskArrayFunction

Base class for all weight producers, i.e., functions that produce and return a single column that is meant to be used as a per-event or per-object weight.

Attributes:

exposed

Methods:

weight_producer([func, bases, mc_only, ...])

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

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

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

When nominal_only is True or shifts_only is set, the producer is skipped and not considered by other calibrators, selectors and producers in case they are evaluated on a order.Shift (using the global_shift_inst attribute) whose name does not match.

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 WeightProducer class.

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

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

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

Return type:

DerivableMeta | Callable

Returns:

New WeightProducer subclass.

weight_producer(func=None, bases=(), mc_only=False, data_only=False, **kwargs)#

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

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

When nominal_only is True or shifts_only is set, the producer is skipped and not considered by other calibrators, selectors and producers in case they are evaluated on a order.Shift (using the global_shift_inst attribute) whose name does not match.

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 WeightProducer class.

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

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

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

Return type:

DerivableMeta | Callable

Returns:

New WeightProducer subclass.