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Updating MC validation #418

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9051437
Update gen processor
bryates Jun 20, 2024
829468e
Updated gen processor
bryates Jun 20, 2024
1cf2c60
Fix lint error (duplicate line)
bryates Jun 20, 2024
c86ed65
Add l0pt and j0pt
bryates Jun 20, 2024
12f0232
Gen photon processor
bryates Jun 28, 2024
d53dd21
Fix lint
bryates Jun 28, 2024
c0d92be
Adding run gen script
bryates Jul 1, 2024
8653a46
Point to gen photon processor
bryates Jul 1, 2024
63d8b16
Correct name
bryates Jul 1, 2024
f785767
Fix to processor
bryates Jul 1, 2024
e170c78
Matching some channels from photon analysis, adding appl
bryates Jul 3, 2024
45bc60a
Correct categorization, add random numbers for testing SF NPs
bryates Jul 3, 2024
35ff202
1j -> 2j
bryates Jul 3, 2024
7ef3f20
Remove sow requirements
bryates Jul 3, 2024
66dbf09
Use CMS naming convention for photon SFs
bryates Jul 3, 2024
8b3ecfa
More CMS naming for photon SFs
bryates Jul 3, 2024
41f1254
Move things around again
bryates Jul 4, 2024
7cab3c3
Fix lint issue
bryates Jul 8, 2024
917d3df
Match processor naming for now
bryates Jul 9, 2024
95fd95b
Update run script
bryates Jul 11, 2024
bc9d0b7
CR invert ZllGamma mask
bryates Nov 18, 2024
5c07496
Merge branch 'master' into mc_validation
bryates Nov 18, 2024
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56 changes: 31 additions & 25 deletions analysis/mc_validation/mc_validation_gen_processor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,36 +2,40 @@
import numpy as np
import awkward as ak
np.seterr(divide='ignore', invalid='ignore', over='ignore')
from coffea import hist, processor
from coffea import processor
import hist

from topcoffea.modules.GetValuesFromJsons import get_lumi
from topcoffea.modules.objects import *
#from topcoffea.modules.corrections import get_ht_sf
from topcoffea.modules.selection import *
from topcoffea.modules.HistEFT import HistEFT
import topeft.modules.object_selection as te_os
from topcoffea.modules.histEFT import HistEFT
import topcoffea.modules.eft_helper as efth
from topcoffea.modules.get_param_from_jsons import GetParam
from topcoffea.modules.paths import topcoffea_path
get_tc_param = GetParam(topcoffea_path("params/params.json"))


class AnalysisProcessor(processor.ProcessorABC):

def __init__(self, samples, wc_names_lst=[], hist_lst=None, ecut_threshold=None, do_errors=False, do_systematics=False, split_by_lepton_flavor=False, skip_signal_regions=False, skip_control_regions=False, muonSyst='nominal', dtype=np.float32):
def __init__(self, samples, wc_names_lst=[], hist_lst=None, ecut_threshold=None, do_errors=False, do_systematics=False, split_by_lepton_flavor=False, skip_signal_regions=False, skip_control_regions=False, dtype=np.float32):

self._samples = samples
self._wc_names_lst = wc_names_lst
self._dtype = dtype

# Create the histograms
self._accumulator = processor.dict_accumulator({
"mll_fromzg_e" : HistEFT("Events", wc_names_lst, hist.Cat("sample", "sample"), hist.Bin("mll_fromzg_e", "invmass ee from z/gamma", 40, 0, 200)),
"mll_fromzg_m" : HistEFT("Events", wc_names_lst, hist.Cat("sample", "sample"), hist.Bin("mll_fromzg_m", "invmass mm from z/gamma", 40, 0, 200)),
"mll_fromzg_t" : HistEFT("Events", wc_names_lst, hist.Cat("sample", "sample"), hist.Bin("mll_fromzg_t", "invmass tautau from z/gamma", 40, 0, 200)),
"mll" : HistEFT("Events", wc_names_lst, hist.Cat("sample", "sample"), hist.Bin("mll", "Invmass l0l1", 60, 0, 600)),
"ht" : HistEFT("Events", wc_names_lst, hist.Cat("sample", "sample"), hist.Bin("ht", "Scalar sum of genjet pt", 100, 0, 1000)),
"ht_clean" : HistEFT("Events", wc_names_lst, hist.Cat("sample", "sample"), hist.Bin("ht_clean", "Scalar sum of clean genjet pt", 100, 0, 1000)),
"tops_pt" : HistEFT("Events", wc_names_lst, hist.Cat("sample", "sample"), hist.Bin("tops_pt", "Pt of the sum of the tops", 50, 0, 500)),
"tX_pt" : HistEFT("Events", wc_names_lst, hist.Cat("sample", "sample"), hist.Bin("tX_pt", "Pt of the t(t)X system", 40, 0, 400)),
"njets" : HistEFT("Events", wc_names_lst, hist.Cat("sample", "sample"), hist.Bin("njets", "njets", 10, 0, 10)),
})
proc_axis = hist.axis.StrCategory([], name="process", growth=True)
self._accumulator = {
"mll_fromzg_e" : HistEFT(proc_axis, hist.axis.Regular(40, 0, 200, name="mll_fromzg_e", label=r"invmass ee from z/gamma"), wc_names=wc_names_lst, rebin=False),
"mll_fromzg_m" : HistEFT(proc_axis, hist.axis.Regular(40, 0, 200, name="mll_fromzg_m", label=r"invmass mm from z/gamma"), wc_names=wc_names_lst, rebin=False),
"mll_fromzg_t" : HistEFT(proc_axis, hist.axis.Regular(40, 0, 200, name="mll_fromzg_t", label=r"invmass tautau from z/gamma"), wc_names=wc_names_lst, rebin=False),
"mll" : HistEFT(proc_axis, hist.axis.Regular(60, 0, 600, name="mll", label=r"Invmass l0l1"), wc_names=wc_names_lst, rebin=False),
"ht" : HistEFT(proc_axis, hist.axis.Regular(100, 0, 1000, name="ht", label=r"Scalar sum of genjet pt"), wc_names=wc_names_lst, rebin=False),
"ht_clean" : HistEFT(proc_axis, hist.axis.Regular(100, 0, 1000, name="ht_clean", label=r"Scalar sum of clean genjet pt"), wc_names=wc_names_lst, rebin=False),
"tops_pt" : HistEFT(proc_axis, hist.axis.Regular(50, 0, 500, name="tops_pt", label=r"Pt of the sum of the tops"), wc_names=wc_names_lst, rebin=False),
"l0_pt" : HistEFT(proc_axis, hist.axis.Regular(50, 0, 500, name="l0_pt", label=r"Pt of leading lepton"), wc_names=wc_names_lst, rebin=False),
"j0_pt" : HistEFT(proc_axis, hist.axis.Regular(50, 0, 500, name="j0_pt", label=r"Pt of leading jet"), wc_names=wc_names_lst, rebin=False),
"tX_pt" : HistEFT(proc_axis, hist.axis.Regular(40, 0, 400, name="tX_pt", label=r"Pt of the t(t)X system"), wc_names=wc_names_lst, rebin=False),
"njets" : HistEFT(proc_axis, hist.axis.Regular(10, 0, 10, name="njets", label=r"njets"), wc_names=wc_names_lst, rebin=False),
}

# Set the list of hists to fill
if hist_lst is None:
Expand Down Expand Up @@ -100,7 +104,7 @@ def process(self, events):

# Jet object selection
genjet = genjet[genjet.pt > 30]
is_clean_jet = isClean(genjet, gen_e, drmin=0.4) & isClean(genjet, gen_m, drmin=0.4) & isClean(genjet, gen_t, drmin=0.4)
is_clean_jet = te_os.isClean(genjet, gen_e, drmin=0.4) & te_os.isClean(genjet, gen_m, drmin=0.4) & te_os.isClean(genjet, gen_t, drmin=0.4)
genjet_clean = genjet[is_clean_jet]
njets = ak.num(genjet_clean)

Expand Down Expand Up @@ -132,6 +136,8 @@ def process(self, events):
"ht_clean" : ht_clean,
"tX_pt" : tX_pt,
"tops_pt" : tops_pt,
"l0_pt" : ak.firsts(gen_l.pt),
"j0_pt" : ak.firsts(genjet.pt),
"njets" : njets,
}

Expand All @@ -150,7 +156,7 @@ def process(self, events):
# If this is not an eft sample, get the genWeight
if eft_coeffs is None: genw = events["genWeight"]
else: genw = np.ones_like(events["event"])
lumi = get_lumi(year)*1000.0
lumi = 1000.0*get_tc_param(f"lumi_{year}")
event_weight = lumi*xsec*genw/sow

# Example of reweighting based on Ht
Expand All @@ -161,7 +167,7 @@ def process(self, events):

### Loop over the hists we want to fill ###

hout = self.accumulator.identity()
hout = self.accumulator

for dense_axis_name, dense_axis_vals in dense_axis_dict.items():

Expand All @@ -171,16 +177,16 @@ def process(self, events):
event_weight_cut = event_weight[isnotnone_mask]
eft_coeffs_cut = eft_coeffs
if eft_coeffs is not None: eft_coeffs_cut = eft_coeffs[isnotnone_mask]
eft_w2_coeffs_cut = eft_w2_coeffs
if eft_w2_coeffs is not None: eft_w2_coeffs_cut = eft_w2_coeffs[isnotnone_mask]
#eft_w2_coeffs_cut = eft_w2_coeffs
#if eft_w2_coeffs is not None: eft_w2_coeffs_cut = eft_w2_coeffs[isnotnone_mask]

# Fill the histos
axes_fill_info_dict = {
dense_axis_name : dense_axis_vals_cut,
"sample" : histAxisName,
"process" : histAxisName,
"weight" : event_weight_cut,
"eft_coeff" : eft_coeffs_cut,
"eft_err_coeff" : eft_w2_coeffs_cut,
#"eft_err_coeff" : eft_w2_coeffs_cut,
}

hout[dense_axis_name].fill(**axes_fill_info_dict)
Expand Down
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