def analysis_tree_all_reweighed(graph, cuts, snodes, **kwargs):
cutnodes = []
for cut_name, cut in cuts:
lepton = cut_name.split("_")[0]
cutnode = tree.CutNode(cut, graph, cut_name, snodes, [],
filter_funcs=[
lambda x,lepton=lepton: tree.is_samp(x, lepton)
])
cutnodes.append(
cutnode
)
#an extra QCD cleaning cut on top of the previous cut, which is only done in antiiso
for syst in ["nominal", "up", "down"]:
cn = tree.CutNode(
Cuts.antiiso(lepton, syst) * Cuts.deltaR_QCD(),
graph, "antiiso_%s" % syst, [cutnode], [],
filter_funcs=[
lambda p: tree.is_samp(p, "antiiso")
]
)
cutnodes.append(
cn
)
from histo_descs import create_plots
create_plots(graph, cutnodes, **kwargs)
isos[lep] = dict()
isos[lep]['iso'] = CutNode(
Cut("1.0"), #At present no special cuts have to be applied on the ISO region
graph, lep + "__iso", par, [],
filter_funcs=[lambda x: "/iso/" in x[0].name]
)
isol.append(isos[lep]['iso'])
#Antiiso with variations in the isolation cut
for aiso_syst in ["nominal", "up", "down"]:
#dR with variations
for dr_syst in ["nominal", "up", "down"]:
cn = 'antiiso_' + aiso_syst + '_dR_' + dr_syst
isos[lep][cn] = CutNode(
#Apply any additional anti-iso cuts (like dR) along with antiiso variations.
Cuts.antiiso(lep, aiso_syst) * Cuts.deltaR_QCD(dr_syst),
graph, lep + "__" + cn, par, [],
filter_funcs=[
lambda x: is_samp(x, "antiiso") and is_samp(x, "data")
]
)
isol.append(isos[lep][cn])
# [iso, antiiso] --> jet --> [jets2-3]
jet = Node(graph, "jet", isol, [])
jets = dict()
for i in [2,3]:
jets[i] = CutNode(Cuts.n_jets(i), graph, "%dj"%i, [jet], [])
tag = Node(graph, "tag", jet.children(), [])
tags = dict()
