taupair.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
 
""" Skim list building functions for tau-pair analyses """
 
__authors__ = [
    "Kenji Inami"
]
 
import basf2 as b2
import modularAnalysis as ma
from skim.standardlists.lightmesons import (loadStdAllF_0, loadStdAllKstar0,
                                            loadStdAllPhi, loadStdAllRho0)
from skimExpertFunctions import BaseSkim, fancy_skim_header
from stdCharged import stdE, stdK, stdMu, stdPi, stdPr
from stdPhotons import stdPhotons
from variables import variables as vm
 
__liaison__ = "Kenji Inami <kenji.inami@desy.de>"
 
 
@fancy_skim_header
class TauLFV(BaseSkim):
    """
    **Channel**: :math:`\\tau \\to l \\gamma, lll, l \\pi^0, l V^0, lhh, llp, phh`
 
    **Output particle lists**: ``e+:taulfv, mu+:taulfv, pi+:taulfv, K+:taulfv, p+:taulfv``,
    ``gamma:taulfv, pi0:taulfv, K_S0:taulfv, eta:taulfv, eta':taulfv``,
    ``omega:taulfv``
 
    **Criteria for 1 prong final states**: Number of good tracks < 5, :math:`1.0 < M < 2.0` GeV, :math:`-1.5 < \\Delta E < 0.5` GeV
 
    **Criteria for >1 prong final states** : Number of good tracks < 7,
    :math:`1.4 < M < 2.0` GeV, :math:`-1.0 < \\Delta E < 0.5` GeV
    """
    __authors__ = ["Kenji Inami"]
    __description__ = "Skim for Tau LFV decays."
    __contact__ = __liaison__
    __category__ = "physics, tau"
 
    produce_on_tau_samples = False  # retention is too high on taupair
 
    def load_standard_lists(self, path):
        stdE("all", path=path)
        stdK("all", path=path)
        stdMu("all", path=path)
        stdPi("all", path=path)
        stdPr("all", path=path)
        stdPhotons("all", path=path)
        loadStdAllRho0(path=path)
        loadStdAllKstar0(path=path)
        loadStdAllPhi(path=path)
        loadStdAllF_0(path=path)
 
    def build_lists(self, path):
        # particle selection
        trackCuts = "-3.0 < dz < 3.0 and dr < 1.0"
        ma.cutAndCopyList("e+:taulfv", "e+:all", trackCuts, path=path)
        ma.cutAndCopyList("mu+:taulfv", "mu+:all", trackCuts, path=path)
        ma.cutAndCopyList("pi+:taulfv", "pi+:all", trackCuts, path=path)
        ma.cutAndCopyList("K+:taulfv", "K+:all", trackCuts, path=path)
        ma.cutAndCopyList("p+:taulfv", "p+:all", trackCuts, path=path)
 
        ma.reconstructDecay("K_S0:taulfv -> pi+:all pi-:all", "0.3 < M < 0.7", path=path)
 
        gammaCuts = "E > 0.20 and clusterNHits > 1.5 and -0.8660 < cosTheta < 0.9563"
        ma.cutAndCopyList("gamma:taulfv", "gamma:all", gammaCuts, path=path)
 
        gammaLooseCuts = "E > 0.1 and -0.8660 < cosTheta < 0.9563 and clusterNHits > 1.5"
        ma.cutAndCopyLists("gamma:taulfvloose", "gamma:all", gammaLooseCuts, path=path)
        # pi0
        ma.reconstructDecay("pi0:taulfv -> gamma:taulfvloose gamma:taulfvloose", "0.115 < M < 0.152", path=path)
        # eta
        ma.reconstructDecay("eta:taulfv1 -> gamma:taulfvloose gamma:taulfvloose", "0.4 < M < 0.6", path=path)
        ma.reconstructDecay("eta:taulfv2 -> pi0:taulfv pi-:all pi+:all", "0.4 < M < 0.6", path=path)
        ma.copyLists("eta:taulfv", ["eta:taulfv1", "eta:taulfv2"], path=path)
        # eta"
        ma.reconstructDecay("eta':taulfv1 -> pi+:all pi-:all gamma:taulfvloose", "0.8 < M < 1.1", path=path)
        ma.reconstructDecay("eta':taulfv2 -> pi+:all pi-:all eta:taulfv", "0.8 < M < 1.1", path=path)
        ma.copyLists("eta':taulfv", ["eta':taulfv1", "eta':taulfv2"], path=path)
        # omega
        ma.reconstructDecay("omega:taulfv -> pi0:taulfv pi-:all pi+:all", "0.73 < M < 0.83", path=path)
 
        # event selection
        vm.addAlias("netChargeLFV", "formula(countInList(pi+:taulfv, charge == 1) - countInList(pi+:taulfv, charge == -1))")
        tauLFVCuts1 = "nParticlesInList(pi+:taulfv) < 5 and 1.0 < M < 2.0 and -1.5 < deltaE < 0.5"
        tauLFVCuts3 = "nParticlesInList(pi+:taulfv) < 7 and 1.4 < M < 2.0 and -1.0 < deltaE < 0.5"
 
        tau_lgamma_Channels = ["e+:taulfv gamma:taulfv",
                               "mu+:taulfv gamma:taulfv"
                               ]
 
        tau_lll_Channels = ["e+:taulfv e+:taulfv e-:taulfv",
                            "mu+:taulfv mu+:taulfv mu-:taulfv",
                            "mu+:taulfv e+:taulfv e-:taulfv",
                            "e+:taulfv mu+:taulfv mu-:taulfv",
                            "e+:taulfv e+:taulfv mu-:taulfv",
                            "mu+:taulfv mu+:taulfv e-:taulfv"
                            ]
 
        tau_lP01_Channels = ["e+:taulfv pi0:taulfv",
                             "mu+:taulfv pi0:taulfv",
                             "e+:taulfv eta:taulfv1",
                             "mu+:taulfv eta:taulfv1"
                             ]
        tau_lP03_Channels = ["e+:taulfv eta:taulfv2",
                             "mu+:taulfv eta:taulfv2",
                             "e+:taulfv eta':taulfv",
                             "mu+:taulfv eta':taulfv",
                             "e+:taulfv K_S0:taulfv",
                             "mu+:taulfv K_S0:taulfv"
                             ]
 
        tau_lS0_Channels = ["e+:taulfv f_0:all",
                            "mu+:taulfv f_0:all"
                            ]
 
        tau_lV0_Channels = ["e+:taulfv rho0:all",
                            "mu+:taulfv rho0:all",
                            "e+:taulfv K*0:all",
                            "mu+:taulfv K*0:all",
                            "e+:taulfv anti-K*0:all",
                            "mu+:taulfv anti-K*0:all",
                            "e+:taulfv phi:all",
                            "mu+:taulfv phi:all",
                            "e+:taulfv omega:taulfv",
                            "mu+:taulfv omega:taulfv"
                            ]
 
        tau_lhh_Channels = ["e+:taulfv pi-:taulfv pi+:taulfv",
                            "mu+:taulfv pi-:taulfv pi+:taulfv",
                            "e-:taulfv pi+:taulfv pi+:taulfv",
                            "mu-:taulfv pi+:taulfv pi+:taulfv",
                            "e+:taulfv K-:taulfv K+:taulfv",
                            "mu+:taulfv K-:taulfv K+:taulfv",
                            "e-:taulfv K+:taulfv K+:taulfv",
                            "mu-:taulfv K+:taulfv K+:taulfv",
                            "e+:taulfv K-:taulfv pi+:taulfv",
                            "mu+:taulfv K-:taulfv pi+:taulfv",
                            "e-:taulfv K+:taulfv pi+:taulfv",
                            "mu-:taulfv K+:taulfv pi+:taulfv",
                            "e+:taulfv K_S0:taulfv K_S0:taulfv",
                            "mu+:taulfv K_S0:taulfv K_S0:taulfv"
                            ]
 
        tau_bnv_Channels = ["mu+:taulfv mu+:taulfv anti-p-:taulfv",
                            "mu-:taulfv mu+:taulfv p+:taulfv",
                            "anti-p-:taulfv pi+:taulfv pi+:taulfv",
                            "p+:taulfv pi-:taulfv pi+:taulfv",
                            "anti-p-:taulfv pi+:taulfv K+:taulfv",
                            "p+:taulfv pi-:taulfv K+:taulfv"
                            ]
 
        tau_lgamma_list = []
        for chID, channel in enumerate(tau_lgamma_Channels):
            ma.reconstructDecay("tau+:LFV_lgamma" + str(chID) + " -> " + channel, tauLFVCuts1, chID, path=path)
            tau_lgamma_list.append("tau+:LFV_lgamma" + str(chID))
 
        tau_lll_list = []
        for chID, channel in enumerate(tau_lll_Channels):
            ma.reconstructDecay("tau+:LFV_lll" + str(chID) + " -> " + channel, tauLFVCuts3, chID, path=path)
            tau_lll_list.append("tau+:LFV_lll" + str(chID))
 
        tau_lP0_list = []
        for chID, channel in enumerate(tau_lP01_Channels):
            ma.reconstructDecay("tau+:LFV_lP01" + str(chID) + " -> " + channel, tauLFVCuts1, chID, path=path)
            tau_lP0_list.append("tau+:LFV_lP01" + str(chID))
        for chID, channel in enumerate(tau_lP03_Channels):
            ma.reconstructDecay("tau+:LFV_lP03" + str(chID) + " -> " + channel, tauLFVCuts3, chID, path=path)
            tau_lP0_list.append("tau+:LFV_lP03" + str(chID))
 
        tau_lS0_list = []
        for chID, channel in enumerate(tau_lS0_Channels):
            ma.reconstructDecay("tau+:LFV_lS0" + str(chID) + " -> " + channel, tauLFVCuts3, chID, path=path)
            tau_lS0_list.append("tau+:LFV_lS0" + str(chID))
 
        tau_lV0_list = []
        for chID, channel in enumerate(tau_lV0_Channels):
            ma.reconstructDecay("tau+:LFV_lV0" + str(chID) + " -> " + channel, tauLFVCuts3, chID, path=path)
            tau_lV0_list.append("tau+:LFV_lV0" + str(chID))
 
        tau_lhh_list = []
        for chID, channel in enumerate(tau_lhh_Channels):
            ma.reconstructDecay("tau+:LFV_lhh" + str(chID) + " -> " + channel, tauLFVCuts3, chID, path=path)
            tau_lhh_list.append("tau+:LFV_lhh" + str(chID))
 
        tau_bnv_list = []
        for chID, channel in enumerate(tau_bnv_Channels):
            ma.reconstructDecay("tau+:LFV_bnv" + str(chID) + " -> " + channel, tauLFVCuts3, chID, path=path)
            tau_bnv_list.append("tau+:LFV_bnv" + str(chID))
 
        tau_lfv_lists = tau_lgamma_list + tau_lll_list + tau_lP0_list + tau_lS0_list + tau_lV0_list + tau_lhh_list + tau_bnv_list
        self.SkimLists = tau_lfv_lists
 
    def validation_histograms(self, path):
        ma.copyLists('tau+:LFV', self.SkimLists, path=path)
 
        # the variables that are printed out are: M, deltaE
        ma.variablesToHistogram(
            filename='TauLFV_Validation.root',
            decayString='tau+:LFV',
            variables=[('M', 100, 1.00, 2.00), ('deltaE', 120, -1.6, 0.6)],
            variables_2d=[('M', 50, 1.00, 2.00, 'deltaE', 60, -1.6, 0.6)],
            path=path
        )
 
 
@fancy_skim_header
class TauGeneric(BaseSkim):
    """
    **Channel**: :math:`e^+ e^- \\to \\tau^+ \\tau^-`
 
    **Criteria**:
 
    Ntrk = 2
 
    1. Number of good tracks = 2, net charge < 2
    2. ``visibleEnergyOfEventCMS < 10 GeV and E_ECLtrk < 6 GeV`` and ``missingMomentumOfEvent_theta < 2.6180``
    3. ``visibleEnergyOfEventCMS > 3 GeV or max P_t > 1 GeV``
    4. max. opening angle < 178 deg.
 
    Ntrk = 3,4
 
    1. Number of good tracks = 3 or 4, net charge < 2
    2. ``visibleEnergyOfEventCMS < 10.5 GeV and E_ECLtrk < 6 GeV``
    3. ``visibleEnergyOfEventCMS > 3 GeV or max P_t > 1 GeV``
    4. max. opening angle < 178 deg.
    5. Event divided by thrust axis; No. good tracks in tag side = 1 or 3
    6. ``M_tag < 1.8 GeV`` and ``M_sig < 2.3 GeV``
 
    Ntrk = 5,6
 
    1. Number of good tracks = 5 or 6, net charge < 2
    2. Event divided by thrust axis; No. good tracks in tag side = 1 or 3
    3. ``M_tag < 1.8 GeV`` and ``M_sig < 2.3 GeV``
    """
    __authors__ = ["Kenji Inami"]
    __description__ = "Skim for Tau generic decays."
    __contact__ = __liaison__
    __category__ = "physics, tau"
 
    produce_on_tau_samples = False  # retention is too high on taupair
 
    def load_standard_lists(self, path):
        stdPi("all", path=path)
        stdPhotons("all", path=path)
 
    def additional_setup(self, path):
        """
        Set particle lists and variables for TauGeneric skim.
 
        **Output particle lists**: ``pi+:tauskim, gamma:tauskim, pi+:S1/S2, gamma:S1/S2``
 
        **Variables**:
 
        * ``nGoodTracks``: number of good tracks in an event
        * ``netCharge``: total net charge of good tracks
        * ``nTracksS1/nTracksS2:`` number of good tracks in each hemisphere ``S1/S2`` divided by thrust axis
        * ``invMS1/invMS2``: invariant mass of particles in each hemisphere
        * ``maxPt``: maximum Pt amoung good tracks
        * ``E_ECLtrk``: total ECL energy of good tracks
        """
 
        # Track and gamma cuts
        trackCuts = "-3.0 < dz < 3.0 and dr < 1.0"
        # trackCuts += " and -0.8660 < cosTheta < 0.9563"
        gammaCuts = "E > 0.15"
        gammaCuts += " and -0.8660 < cosTheta < 0.9563"
        ma.cutAndCopyList("pi+:tauskim", "pi+:all", trackCuts, path=path)
        ma.cutAndCopyList("gamma:tauskim", "gamma:all", gammaCuts, path=path)
 
        # Get EventShape variables
        ma.buildEventShape(["pi+:tauskim", "gamma:tauskim"],
                           allMoments=False, foxWolfram=False, cleoCones=False,
                           sphericity=False, jets=False, path=path)
        ma.buildEventKinematics(["pi+:tauskim", "gamma:tauskim"], path=path)
 
        # Split in signal and tag
        ma.cutAndCopyList("pi+:S1", "pi+:tauskim", "cosToThrustOfEvent > 0", path=path)
        ma.cutAndCopyList("pi+:S2", "pi+:tauskim", "cosToThrustOfEvent < 0", path=path)
        ma.cutAndCopyList("gamma:S1", "gamma:tauskim", "cosToThrustOfEvent > 0", path=path)
        ma.cutAndCopyList("gamma:S2", "gamma:tauskim", "cosToThrustOfEvent < 0", path=path)
 
        vm.addAlias("nGoodTracks", "nParticlesInList(pi+:tauskim)")
        vm.addAlias("netCharge", "formula(countInList(pi+:tauskim, charge == 1) - countInList(pi+:tauskim, charge == -1))")
        vm.addAlias("nTracksS1", "nParticlesInList(pi+:S1)")
        vm.addAlias("nTracksS2", "nParticlesInList(pi+:S2)")
        vm.addAlias("invMS1", "invMassInLists(pi+:S1, gamma:S1)")
        vm.addAlias("invMS2", "invMassInLists(pi+:S2, gamma:S2)")
        # vm.addAlias("Evis", "visibleEnergyOfEventCMS")
        vm.addAlias("maxPt", "maxPtInList(pi+:tauskim)")
        vm.addAlias("E_ECLtrk", "formula(totalECLEnergyOfParticlesInList(pi+:tauskim))")
        vm.addAlias("maxOp", "useCMSFrame(maxOpeningAngleInList(pi+:tauskim))")
 
    def build_lists(self, path):
        # reconstruct with each Ntrk case
        ma.reconstructDecay('tau+:g2 -> pi+:S1', 'nGoodTracks == 2 and -2 < netCharge <2', path=path)
        ma.reconstructDecay('tau+:g34 -> pi+:S1', '[nGoodTracks == 3 or nGoodTracks == 4] and -2 < netCharge <2', path=path)
        ma.reconstructDecay('tau+:g56 -> pi+:S1', '[nGoodTracks == 5 or nGoodTracks == 6] and -2 < netCharge <2', path=path)
 
        # Selection criteria
        # Ntrk=2
        ma.applyCuts('tau+:g2', 'visibleEnergyOfEventCMS < 10', path=path)
        ma.applyCuts('tau+:g2', 'E_ECLtrk < 6', path=path)
        ma.applyCuts('tau+:g2', 'missingMomentumOfEvent_theta < 2.6180', path=path)
        ma.applyCuts('tau+:g2', 'visibleEnergyOfEventCMS > 3 or maxPt > 1', path=path)
        ma.applyCuts('tau+:g2', 'maxOp < 3.106686', path=path)
        # Ntrk=3,4
        ma.applyCuts('tau+:g34', 'visibleEnergyOfEventCMS < 10.5', path=path)
        ma.applyCuts('tau+:g34', 'E_ECLtrk < 6', path=path)
        ma.applyCuts('tau+:g34', 'visibleEnergyOfEventCMS > 3 or maxPt > 1', path=path)
        ma.applyCuts('tau+:g34', 'maxOp < 3.106686', path=path)
        ma.applyCuts('tau+:g34',
                     '[[ nTracksS1 == 1 or nTracksS1 == 3 ] and invMS1 < 1.8 and invMS2 < 2.3 ] or '
                     '[[ nTracksS2 == 1 or nTracksS2 == 3 ] and invMS2 < 1.8 and invMS1 < 2.3 ]', path=path)
        # Ntrk=5,6
        ma.applyCuts('tau+:g56',
                     '[[ nTracksS1 == 1 or nTracksS1 == 3 ] and invMS1 < 1.8 and invMS2 < 2.3 ] or '
                     '[[ nTracksS2 == 1 or nTracksS2 == 3 ] and invMS2 < 1.8 and invMS1 < 2.3 ]', path=path)
 
        # For skimming, the important thing is if the final particleList is empty or not.
        eventParticle = ['tau+:g2', 'tau+:g34', 'tau+:g56']
 
        self.SkimLists = eventParticle
 
    def validation_histograms(self, path):
        self.additional_setup(path)
 
        vm.addAlias('Theta_miss', 'formula(missingMomentumOfEvent_theta*180/3.14159)')
 
        # contact = "kenji@hepl.phys.nagoya-u.ac.jp"
 
        #       validation_tools.metadata.create_validation_histograms, to add contact
        #       info without reopening and closing ROOT file and add 'shifter' flag
 
        ma.variablesToHistogram(
            filename='TauGeneric_Validation.root',
            decayString='',
            variables=[('nGoodTracks', 7, 1, 8),
                       ('visibleEnergyOfEventCMS', 40, 0, 12),
                       ('E_ECLtrk', 70, 0, 7),
                       ('maxPt', 60, 0, 6),
                       ('invMS1', 60, 0, 3),
                       ('invMS2', 60, 0, 3),
                       ('Theta_miss', 30, 0, 180)],
            variables_2d=[('invMS1', 30, 0, 3, 'invMS2', 30, 0, 3)],
            path=path
        )
        b2.process(path)
 
 
@fancy_skim_header
class TauThrust(BaseSkim):
    """
    **Channel**: :math:`e^+ e^- \\to \\tau^+ \\tau^-`
 
    **Criteria**:
 
    * ``1 < No. good tracks < 7``
    * ``net charge == 0``
    * Event divided by thrust axis; select 1x1, 1x3, 1x5, 3x3 topology
    * ``0.8 < thrust``
    * ``visibleEnergyOfEventCMS < 10.4 GeV``
    * For 1x1 topology, ``thrust < 0.99``
    """
    __authors__ = ["Ami Rostomyan", "Kenji Inami"]
    __description__ = "Skim for Tau decays using thrust."
    __contact__ = __liaison__
    __category__ = "physics, tau"
 
    produce_on_tau_samples = False  # retention is too high on taupair
 
    def load_standard_lists(self, path):
        stdPi("all", path=path)
        stdPhotons("all", path=path)
 
    def additional_setup(self, path):
        """
        Set particle lists and variables for TauThrust skim.
 
        **Constructed particle lists**: ``pi+:thrust, gamma:thrust, pi+:thrustS1/thrustS2, pi0:thrust``
 
        **Variables**:
 
        * ``nGoodTracksThrust``: number of good tracks in an event
        * ``netChargeThrust``: total net charge of good tracks
        * ``nTracksS1Thrust/nTracksS2Thrust``: number of good tracks in each hemisphere S1/S2 divided by thrust axis
        """
        # Track and gamma cuts
        trackCuts = '-3.0 < dz < 3.0 and dr < 1.0'
        ma.cutAndCopyList('pi+:thrust', 'pi+:all', trackCuts, path=path)
        gammaForPi0Cuts = 'E > 0.1 and -0.8660 < cosTheta < 0.9563 and clusterNHits > 1.5'
        ma.cutAndCopyLists('gamma:thrustForPi0', 'gamma:all', gammaForPi0Cuts, path=path)
        ma.reconstructDecay('pi0:thrust -> gamma:thrustForPi0 gamma:thrustForPi0', '0.115 < M < 0.152', path=path)
        gammaCuts = 'E > 0.20 and clusterNHits > 1.5 and -0.8660 < cosTheta < 0.9563'
        gammaCuts += ' and isDaughterOfList(pi0:thrust) == 0'
        ma.cutAndCopyList('gamma:thrust', 'gamma:all', gammaCuts, path=path)
 
        # Get EventShape variables
        ma.buildEventShape(['pi+:thrust', 'pi0:thrust', 'gamma:thrust'],
                           allMoments=False, foxWolfram=False, cleoCones=False,
                           sphericity=False, jets=False, path=path)
        ma.buildEventKinematics(['pi+:thrust', 'pi0:thrust', 'gamma:thrust'], path=path)
 
        # Split in signal and tag
        ma.cutAndCopyList('pi+:thrustS1', 'pi+:thrust', 'cosToThrustOfEvent > 0', path=path)
        ma.cutAndCopyList('pi+:thrustS2', 'pi+:thrust', 'cosToThrustOfEvent < 0', path=path)
 
        vm.addAlias('nGoodTracksThrust', 'nParticlesInList(pi+:thrust)')
        vm.addAlias('netChargeThrust', 'formula(countInList(pi+:thrust, charge == 1) - countInList(pi+:thrust, charge == -1))')
        vm.addAlias('nTracksS1Thrust', 'nParticlesInList(pi+:thrustS1)')
        vm.addAlias('nTracksS2Thrust', 'nParticlesInList(pi+:thrustS2)')
 
    def build_lists(self, path):
        ma.reconstructDecay("tau+:thrust -> pi+:thrustS1", "", path=path)
        eventParticle = ["tau+:thrust"]
 
        # Selection criteria
        ma.applyCuts("tau+:thrust", "1 < nGoodTracksThrust < 7", path=path)  # cut1
        ma.applyCuts("tau+:thrust", "netChargeThrust == 0", path=path)  # cut2
 
        topologyCuts = "[nTracksS1Thrust == 1 and nTracksS2Thrust == 1]"  # 1x1
        topologyCuts += " or [nTracksS1Thrust == 1 and nTracksS2Thrust == 3]"\
            " or [nTracksS1Thrust == 3 and nTracksS2Thrust == 1]"  # 1x3, 3x1
        topologyCuts += " or [nTracksS1Thrust == 1 and nTracksS2Thrust == 5]"\
            " or [nTracksS1Thrust == 5 and nTracksS2Thrust == 1]"  # 1x5, 5x1
        topologyCuts += " or [nTracksS1Thrust == 3 and nTracksS2Thrust == 3]"  # 3x3
 
        ma.applyCuts("tau+:thrust", topologyCuts, path=path)  # cut3
        ma.applyCuts("tau+:thrust", "0.8 < thrust", path=path)  # cut4
        ma.applyCuts("tau+:thrust", "visibleEnergyOfEventCMS < 10.4", path=path)  # cut5
        # cut6 thrust upper cut for 1x1 topology
        ma.applyCuts("tau+:thrust", "thrust < 0.99 or nGoodTracksThrust!=2", path=path)
 
        self.SkimLists = eventParticle
 
    def validation_histograms(self, path):
        self.additional_setup(path)
 
        #       validation_tools.metadata.create_validation_histograms, to add contact
        #       info without reopening and closing ROOT file and add 'shifter' flag
 
        ma.variablesToHistogram(
            filename='TauThrust_Validation.root',
            decayString='',
            variables=[('nGoodTracksThrust', 7, 1, 8),
                       ('visibleEnergyOfEventCMS', 40, 0, 12),
                       ('thrust', 50, 0.75, 1)],
            path=path
        )