TIMBER  beta
Tree Interface for Making Binned Events with RDataFrame
Functions
AutoJME tool (AutoJME.py)

Automatic calculation of JES, JER, JMS, and JMR factors and uncertainties per-jet per-event and calibration of \(p_{T}\) and mass with associated variations performed as well. More...

Functions

def AutoJME (a, jetCollection, year, dataEra='')
 Automatic calculation of JES, JER, JMS, and JMR factors and uncertainties per-jet per-event and calibration of \(p_{T}\) and mass with associated variations performed as well. More...
 

Detailed Description

Automatic calculation of JES, JER, JMS, and JMR factors and uncertainties per-jet per-event and calibration of \(p_{T}\) and mass with associated variations performed as well.

Function Documentation

◆ AutoJME()

def TIMBER.Tools.AutoJME.AutoJME (   a,
  jetCollection,
  year,
  dataEra = '' 
)

Automatic calculation of JES, JER, JMS, and JMR factors and uncertainties per-jet per-event and calibration of \(p_{T}\) and mass with associated variations performed as well.

Apply standard JME modules to analyzer() object a for a given jet collection, year, and data era (if a.isData). Output collection name will be called "Calibrated<jetCollection>" and will have the modified mass and pt and if MC, will have four possible variations of each variable for JES, JER, JMS, and JMR.

For MC FatJets (AK8s), apply JES and JER to the \(p_{T}\) and JES, JER, JMS, and JMR to the mass. For MC Jets (AK4s), apply JES and JER to the \(p_{T}\).

For data, only recalibrate the jets for the new JECs.

Parameters
a(analyzer): TIMBER analyzer object which will be manipulated and returned.
jetCollection(str): FatJet or Jet.
year(int): 2016, 2017, 2018, 2017UL, or 2018UL.
dataEra(str, optional): If providing data, include the "era" (A or B or C, etc). Defaults to ''.
Exceptions
ValueErrorProvided jet collection is not "FatJet" or "Jet"
Returns
analyzer Manipulated version of the input analyzer object.