electron

Electron related event weights.

Classes:

ElectronSFConfig(correction, campaign[, ...])
electron_weights(*args, **kwargs)
electron_trigger_weights(*args, **kwargs)
electron_sceta(*args, **kwargs)

class ElectronSFConfig(correction, campaign, working_point='', hlt_path='', min_pt=0.0, max_pt=0.0)

Bases: object

Attributes:

correction
campaign
working_point
hlt_path
min_pt
max_pt

Methods:

new(obj)

correction: str

campaign: str

working_point: str | dict[str, Callable] = ''

hlt_path: str = ''

min_pt: float = 0.0

max_pt: float = 0.0

classmethod new(obj)

Return type:

ElectronSFConfig

class electron_weights(*args, **kwargs)

Bases: Producer

Attributes:

cache_instances
mc_only
supported_versions
use_supercluster_eta
uses
weight_name

Methods:

call_func(events[, electron_mask])	Creates electron weights using the correctionlib.
get_electron_config()
get_electron_file(external_files)
init_func(**kwargs)	Default init function.
requires_func(task, reqs, **kwargs)	Default requires function.
setup_func(task, reqs, inputs, ...)	Default setup function.
skip_func(**kwargs)	Default skip function.
update_cls_dict(cls_name, cls_dict, get_attr)

cache_instances = True

call_func(events, electron_mask=Ellipsis, **kwargs)

Creates electron weights using the correctionlib. Requires an external file in the config under electron_sf:

cfg.x.external_files = DotDict.wrap({
    "electron_sf": "/afs/cern.ch/work/m/mrieger/public/mirrors/jsonpog-integration-9ea86c4c/POG/EGM/2017_UL/electron.json.gz",  # noqa
})

get_electron_file can be adapted in a subclass in case it is stored differently in the external files.

The name of the correction set, the year string for the weight evaluation, and the name of the working point should be given as an auxiliary entry in the config:

cfg.x.electron_sf = ElectronSFConfig(
    correction="UL-Electron-ID-SF",
    campaign="2017",
    working_point="wp80iso",  # for trigger weights use hlt_path instead
)

The working_point can also be a dictionary mapping working point names to functions that return a boolean mask for the electrons. This is useful to compute scale factors for multiple working points at once, e.g. for the electron reconstruction scale factors:

cfg.x.electron_sf = ElectronSFConfig(
    correction="Electron-ID-SF",
    campaign="2022Re-recoE+PromptFG",
    working_point={
        "RecoBelow20": lambda variable_map: variable_map["pt"] < 20.0,
        "Reco20to75": lambda variable_map: (variable_map["pt"] >= 20.0) & (variable_map["pt"] < 75.0),
        "RecoAbove75": lambda variable_map: variable_map["pt"] >= 75.0,
    },
)

get_electron_config can be adapted in a subclass in case it is stored differently in the config.

Optionally, an electron_mask can be supplied to compute the scale factor weight based only on a subset of electrons.

Return type:

ak.Array

get_electron_config()

get_electron_file(external_files)

init_func(**kwargs)

Default init function.

Return type:

None

mc_only: bool = True

requires_func(task, reqs, **kwargs)

Default requires function.

Return type:

None

setup_func(task, reqs, inputs, reader_targets, **kwargs)

Default setup function.

Return type:

None

skip_func(**kwargs) → bool

Default skip function.

Return type:

bool

supported_versions = {1, 2, 3, 4, 5}

static update_cls_dict(cls_name, cls_dict, get_attr)

use_supercluster_eta = True

uses = {'Electron.{pt,eta,phi,deltaEtaSC}'}

weight_name = 'electron_weight'

class electron_trigger_weights(*args, **kwargs)

Bases: electron_weights

Attributes:

cache_instances
use_supercluster_eta
weight_name

Methods:

get_electron_config()
get_electron_file(external_files)
skip_func(**kwargs)	Default skip function.

cache_instances = True

get_electron_config()

get_electron_file(external_files)

skip_func(**kwargs) → bool

Default skip function.

Return type:

bool

use_supercluster_eta = False

weight_name = 'electron_trigger_weight'

class electron_sceta(*args, **kwargs)

Bases: Producer

Attributes:

cache_instances
produces
uses

Methods:

call_func(events, **kwargs)	Returns the electron super cluster eta.
skip_func(**kwargs)	Default skip function.
update_cls_dict(cls_name, cls_dict, get_attr)

cache_instances = True

call_func(events, **kwargs)

Returns the electron super cluster eta.

Return type:

Array

produces = {'Electron.superclusterEta'}

skip_func(**kwargs) → bool

Default skip function.

Return type:

bool

static update_cls_dict(cls_name, cls_dict, get_attr)

uses = {'Electron.{pt,phi,eta,deltaEtaSC}'}