empty#

Empty selectors that still produce the minimal set of columns potentially required in downstream tasks.

Classes:

empty(*args, **kwargs)

class empty(*args, **kwargs)[source]#

Bases: Selector

Methods:

call_func(events, stats, **kwargs)

Empty selector that only writes a minimal set of columns that are potentially required in downstream tasks, such as cutflow and plotting related tasks.

init_func()

Initializes the selector by finding the id of the inclusive category if no hard-coded category ids are given on class-level.

Attributes:

category_ids

data_only

exposed

inclusive_category_name

mc_only

nominal_only

produces

shifts_only

uses

call_func(events, stats, **kwargs)#

Empty selector that only writes a minimal set of columns that are potentially required in downstream tasks, such as cutflow and plotting related tasks.

Parameters:
  • events (Array) – The input events.

  • stats (defaultdict) – The statistics dictionary.

  • **kwargs

    Additional keyword arguments that are passed to all other TaskArrayFunction’s.

Return type:

tuple[Array, SelectionResult]

Returns:

A tuple containing the original events and a SelectionResult object with a trivial event mask.

category_ids = None#
data_only = False#
exposed = True#
inclusive_category_name = 'incl'#
init_func()#

Initializes the selector by finding the id of the inclusive category if no hard-coded category ids are given on class-level.

Raises:

ValueError – If the inclusive category cannot be found.

Return type:

None

mc_only = False#
nominal_only = False#
produces = {<class 'columnflow.production.processes.process_ids'>, <class 'columnflow.production.cms.mc_weight.mc_weight'>, 'category_ids'}#
shifts_only = None#
uses = {<class 'columnflow.production.processes.process_ids'>, <class 'columnflow.production.cms.mc_weight.mc_weight'>, <class 'columnflow.selection.stats.increment_stats'>}#