def __init__(self):
Load('TMVABranchAdder')
self.ba = root.TMVABranchAdder()
self.ba.defaultValue = -1.2
self.ba.presel = 'fjECFN_2_4_20>0'
for v in tagcfg.variables:
self.ba.AddVariable(v[0], v[2].replace('fj1', 'fj'))
for v in tagcfg.formulae:
self.ba.AddFormula(v[0], v[2].replace('fj1', 'fj'))
for s in tagcfg.spectators:
self.ba.AddSpectator(s[0])
self.ba.BookMVA('top_ecf_bdt',
_data_dir + '/trainings/top_ecfbdt_v8_BDT.weights.xml')
#!/usr/bin/env python
from PandaCore.Utils.load import Load
from PandaCore.Utils.logging import logger
import ROOT as root
import cppyy
import sys
# this module lets you build a LambdaSelection instance on the fly
# look we're doing C++ in python, we even have this:
this = sys.modules[__name__]
Load('PandaAnalyzer')
cppyy.cppdef('#include "PandaAnalysis/Flat/interface/GeneralTree.h"')
def build(stage, name, expr, anded=False):
left = 'std::function<bool(const GeneralTree* gt)>'
middle = '_fsel = [](const GeneralTree* gt) { return '
right = '; };'
cppyy.cppdef(left + name + middle + expr + right)
f = getattr(cppyy.gbl, name+'_fsel')
sel = root.LambdaSel(stage, name, f, anded)
setattr(this, name+'Sel', sel)
return sel
# e.g.:
# build(root.Selection.sReco, 'Trigger', '(gt->isData==0) || (gt->trigger!=0)', anded=True)
# build(root.Selection.sGen, 'GenBosonPt', 'gt->trueGenBosonPt > 100')
# build(root.Selection.sReco, 'FatJet', 'gt->fj1Pt>250')
# build(root.Selection.sReco, 'FatJet450', 'gt->fj1Pt>450')
basedir = getenv('PANDA_FLATDIR') + '/'
parser = argparse.ArgumentParser(description='plot stuff')
parser.add_argument('--proc', metavar='proc', type=str)
parser.add_argument('--outdir', metavar='outdir', type=str)
args = parser.parse_args()
figsdir = args.outdir
argv = []
import ROOT as root
from PandaCore.Utils.load import Load
from PandaCore.Tools.Misc import *
from PandaCore.Tools.root_interface import Selector
from math import sqrt
Load('CanvasDrawer')
root.gROOT.SetBatch()
root.gStyle.SetNumberContours(999)
root.gStyle.SetPalette(root.kCool)
SMOOTH = True
plot = root.CanvasDrawer()
plot.SetTDRStyle()
root.gStyle.SetPadRightMargin(0.2)
c = root.TCanvas()
plot.SetCanvas(c)
s = Selector()
s_nlo = Selector()
#!/usr/bin/env python
'''@package docstring
Loads some numerical functions defined in a C++ file
'''
from os import getenv
from ROOT import gROOT
from PandaCore.Utils.load import Load
Load('Functions')
#gROOT.LoadMacro(getenv('CMSSW_BASE')+'/src/PandaCore/Tools/interface/Functions.h')
#!/usr/bin/env python
import ROOT as root
import numpy as np
from array import array
from PandaCore.Tools.Misc import *
from PandaCore.Utils.load import Load
from PandaCore.Tools.root_interface import read_files, draw_hist
from os import getenv, system, path
from pprint import pprint
from multiprocessing.pool import ThreadPool
Load('HistogramDrawer')
tree_name = 'events'
class Process():
def __init__(self, name, pt, custom_color=root.nProcesses):
self.name = name
self.process_type = pt
if (custom_color == root.nProcesses):
self.color = pt
else:
self.color = custom_color
# public config - defaults
self.dashed = False
self.dotted = False
self.use_common_weight = True
self.use_common_cut = True
self.additional_cut = '1==1'
parser = argparse.ArgumentParser(description='plot stuff')
parser.add_argument('--outdir',metavar='outdir',type=str)
parser.add_argument('--finor', action='store_true')
parser.add_argument('--iso', action='store_true')
args = parser.parse_args()
figsdir = args.outdir
argv=[]
import ROOT as root
from PandaCore.Utils.load import Load
from PandaCore.Tools.Misc import *
from PandaCore.Tools.root_interface import Selector
from math import sqrt
Load('GraphAsymmErrDrawer')
root.gROOT.SetBatch()
lumi=36000
import PandaAnalysis.VBF.PandaSelection as sel
cut = 'fabs(jotEta[{0}])>2.75 && fabs(jotEta[{0}])<3 && filter==1'
cut = tAND(cut, '!(fabs(jotEta[{0}]+2.81)<0.4 && fabs(jotPhi[{0}]-2.07)<0.4)')
if args.finor:
cut = tAND(cut, 'nJotEC==1')
sigcut = 'finor[1]!=0' if args.finor else 'jotL1EGBX[{0}]==-1'
if args.iso:
sigcut = tAND(sigcut, 'jotL1EGIso[{0}]>0')
plot = root.GraphAsymmErrDrawer()
plot.SetLineWidth(3)
#!/usr/bin/env python
from sys import argv
from os import getenv, system
me = argv[0]
cat = argv[1]
radius = argv[2]
argv = []
from PandaCore.Utils.load import Load
import PandaAnalysis.Tagging.TnPSel as sel
from PandaCore.Tools.Misc import tAND
import ROOT as root
Load('Cutter')
flatdir = getenv('PANDA_FLATDIR') + '/'
outdir = flatdir + 'tnp_' + radius + '/'
system('mkdir -p ' + outdir)
fins = {
'Data': ['SingleMuon'],
'1': ['WJets'],
'2': ['Diboson', 'SingleTop', 'TTbar'],
'3': ['SingleTop', 'TTbar']
}
cuts = {
'Data': '1==1',
'1': '1==1',
'2': '(fjIsMatched==0||fjGenSize>%s)' % radius,
'3': '(fjIsMatched==1&&fjGenSize<%s)' % radius
#!/usr/bin/env python
from sys import argv
import argparse
parser = argparse.ArgumentParser(description='plot stuff')
parser.add_argument('--outdir',metavar='outdir',type=str)
parser.add_argument('--sample',metavar='sample',type=str)
args = parser.parse_args()
argv = []
import ROOT as root
from PandaCore.Utils.load import Load
Load('PandaCoreTools')
Load('PandaCoreDrawers')
es = root.EventSyncher()
es.relative = False
f1 = '/home/snarayan/home000/store/panda/v_8026_0_5_slim/%s.root'%args.sample
f2 = '/home/snarayan/home000/store/panda/v_8026_0_5_ak8/%s.root'%args.sample
es.preselection = 'fj1Pt>400'
formulae = [
('fj1Pt',400,1200,'p_{T}',True),
('fj1MaxCSV',0,1,'Max CA15 subjet CSV',False),
]
for f in formulae:
es.AddFormula(*f)
import argparse
parser = argparse.ArgumentParser(description='interpolate')
parser.add_argument('--mass', type=str)
parser.add_argument('--mass_reco', type=str, default=None)
args = parser.parse_args()
sname = argv[0].split('/')[-1]
argv = []
from PandaCore.Tools.Misc import *
from PandaCore.Utils.load import Load
from PandaCore.Tools.root_interface import read_tree, draw_hist
import ROOT as root
from math import sqrt
Load('BranchAdder')
ba = root.BranchAdder()
ba.verbose = False
ba.formula = 'genBosonPt'
bins = array('f', [250, 280, 310, 350, 400, 450, 600, 1000])
N = len(bins) - 1
h_base = root.TH1F('hbase', '', N, bins)
systs = [
'btagUp', 'btagDown', 'mistagUp', 'mistagDown', 'sjbtagUp', 'sjbtagDown',
'sjmistagUp', 'sjmistagDown'
]
basedir = getenv('PANDA_FITTING')
from re import sub
from sys import argv, exit
from os import environ, system, path
from array import array
sname = argv[0].split('/')[-1]
m_V = int(argv[1])
m_DM = int(argv[2])
argv = []
import ROOT as root
from PandaCore.Tools.Misc import *
from PandaCore.Utils.load import Load
from PandaCore.Tools.root_interface import read_tree, draw_hist, rename_dtypes
Load('Normalizer')
'''
This script does the following things:
- Read an input list of T2 files and xrdcp them locally
- hadd these files
- Remove the input files and only keep the merged one
- Normalize the merged file
- For each w in [1]+weights, draw the mediator pT distribution with weight (w*normalizedWeight)
- Delete the merged file and stageout the file with histograms
'''
#CONFIG = 'couplings' # or finer or normal
CONFIG = 'normal'
list_dir = '/home/bmaier/cms/MonoTop/interpolation/'
xsec_path = 'non-resonant'