bkgtest = copy.deepcopy(backgroundlist)
sumbkg = 0
sumdata = 0
for each in bkgtest + datatest:
each.cut_parameter(cut_btagin_is, 1)
# each.cut_parameter(cut_btagout_less, 0)
if "data" not in each.alias:
sumbkg += sum(each.weight)
else:
sumdata += len(each.weight)
print("Making plots...")
direct = ""
name = "mbbcut-1tag" + correctionname
bins = [200, 220, 240, 260, 290, 320, 350, 380, 410, 450, 550, 650, 750, 850, 1000, 1200, 1400, 1800]
stackplot(bkgtest + datatest,b'ptfj1',bins,1000.,
xlabel=r"$p_{T}^{FJ}[GeV]$", filename=direct + "ptfj1" + name, print_height=True,
title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.5, log_y=True, title3="2 lep. 1 btag merged", chi2=True)
bins = [260, 300, 400, 500, 600, 700, 800, 1000, 1200, 1400, 1800, 2200]
stackplot(bkgtest + datatest,b'mVH',bins,1000.,
xlabel=r"$m_{VH}[GeV]$", filename=direct + "mvh" + name, print_height=True,
title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.5, log_y=True, title3="2 lep. 1 btag merged", chi2=True)
datatest = copy.deepcopy(datalist)
bkgtest = copy.deepcopy(backgroundlist)
sumbkg = 0
sumdata = 0
for each in bkgtest + datatest:
each.cut_parameter(cut_btagin_is, 1)
each.cut_parameter(cut_btagout_less, 0)
if "data" not in each.alias:
1850, 2000
]
bincheck(binning, bins)
all_sample1 = []
for each in all_sample:
#print(type(each))
if isinstance(each, str):
continue
all_sample1.append(each)
stackplot(all_sample1,
variable_name,
bins,
1.,
xlabel=r"$m_{VH}[GeV]$",
title3="2 lep.," + btag + " b-tag " + region,
filename="output/cpp_make_plot_test/" + filename[0:-5],
print_height=False,
title2=t2,
auto_colour=False,
limit_y=0.6,
upper_y=2.6,
sys=True,
log_y=True)
'''
sample_list = {"Wl", "Wcl", "Wbl", "Wbb", "Wbc", "Wcc", "WZ", "WW", "Zcc", "Zcl", "Zbl", "Zbc", "Zl", "Zbb", "ZZ", "stopWt", "stops", "stopt", "ttbar", "ggZllH125", "qqZllH125", "stopWt_dilep"}
colors = ['g', 'g', 'g', 'g', 'g', 'g', 'tab:orange','tab:orange', 'royalblue','royalblue','royalblue','royalblue','royalblue','royalblue','royalblue','yellow','yellow','yellow','yellow', 'yellow','yellow','yellow']
with open("mVHsr.txt","r") as f:
for each_line in f:
sample = json.loads(each_line)
nominals = []
for each, color in zip(sample_list,colors):
if each not in sample:
mysample = rescale(mysample)
mysample = slopecorrection(mysample)
title3 = "mBBcr " + str(2) + " btags"
bins = [
0, 50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700,
750, 800, 850, 900, 950, 1000, 1050, 1100, 1150, 1200, 1250, 1300
]
print(bins)
chi2, nod = stackplot(mysample,
b'pTV',
bins,
1000.,
xlabel=r"$p_{TV}[GeV]$",
title3=title3,
filename="test1",
print_height=True,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True,
printzpjets=True,
chi2=True)
bins = range(0, 2000, 30)
chi2, nod = stackplot(mysample,
b'mVH',
bins,
1000.,
xlabel=r"$p_{TV}[GeV]$",
title3=title3,
filename="testmvh1",
]
if dorebin:
bins = range(0, 1400, 20)
bins = autobin_withdatazlljet(all_sample_after_beforecorrection,
bins,
alias="Zlljet",
variable=b"pTV")
print(bins)
chi2, nod = stackplot(all_sample_after,
b'pTV',
bins,
1000.,
xlabel=r"$p_{TV}[GeV]$",
title3=title3,
filename=direct + "pTV" + name,
print_height=True,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True,
printzpjets=True,
chi2=True)
print("pTV", chi2, nod)
bins = [
50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700,
750, 800, 850, 900, 1000, 1150, 1350, 1550, 1800
]
chi2, nod = stackplot(all_sample_after,
b'mVH',
bins,
bins = np.linspace(41,200,num=50)
stackplot(all_sample,b'mLL',bins,1000.,
xlabel=r"$M_{Z}[GeV]$", title3="2 lep., > 2 b-tag", filename="31amZ", print_height=True,
title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.6)
'''
#bins = np.linspace(100,1200,50)
#bins = range(0,40000,20000)
#bins = range(0,100,1)
bins = range(0,10000,40)
all_sample_after = [each for each in all_sample]
# stackplot(all_sample_after,b'ptL1',bins,1000.,
# xlabel=r"$pt_{l1}[GeV]$", title3="loose selection, 2 btags", filename="ptL1", print_height=True,
# title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.0, log_y=True)
#bins = [50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 1000, 1150, 1350, 1550, 1800]
stackplot(all_sample_after,b'pTV',bins,1000.,
xlabel=r"$p_{TV}[GeV]$", title3="mBB 1 btags", filename="output/t_make_plot/" + "pTV-mbbcr", print_height=True,
title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.0, log_y=True)
# bins = range(0,1000,50)
# stackplot(all_sample_after,b'pTB1',bins,1000.,
# xlabel=r"$pt_{b1}[GeV]$", title3="loose selection, 2 btags", filename="pTB1", print_height=True,
# title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.0, log_y=True)
# bins = range(5,80,3)
# stackplot(all_sample_after,b'MET',bins,1000.,
# xlabel=r"$pt_{L2}[GeV]$", title3="muon same charge srcut, < 2 btag", filename="ptL2_3_test", print_height=True,
# title2=t2,auto_colour=False, limit_y = 0.5, upper_y=3.0, log_y=False)
# bins = np.linspace(0, 3.15, num=20)
# stackplot(all_sample_after,b'delphi1',bins,1.,
# xlabel=r"$delphi1$", title3="l same charge srcut, < 3 btag",title4 = "PTl2 < 20 GeV" ,filename="delphi1l", print_height=True,
# title2=t2,auto_colour=False, limit_y = 0.5, upper_y=3, log_y=False, blind = False)
# stackplot(all_sample_after,b'delphi2',bins,1.,
def flow(new, old, ntag):
t2 = r"$\mathit{\sqrt{s}=13\:TeV,139\:fb^{-1}}$"
title3 = "mBBcr " + str(ntag) + " btags"
bins = [
50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700,
750, 800, 850, 900, 1000, 1150, 1350, 1550, 1800
]
chi2, nod = stackplot(Zsplit(new),
b'mVHres',
bins,
1000.,
xlabel=r"$m_{VH}[GeV]$",
title3=title3,
filename="mVH-new" + str(ntag) + "tag",
print_height=False,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True)
chi2, nod = stackplot(Zsplit(old),
b'mVHres',
bins,
1000.,
xlabel=r"$m_{VH}[GeV]$",
title3=title3,
filename="mVH-old" + str(ntag) + "tag",
print_height=False,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True)
bins = np.array([2, 3, 4, 5, 6, 7, 8, 9]) - 0.001
chi2, nod = stackplot(Zsplit(new),
b"nJets",
bins,
1,
xlabel=r"number of jets",
title3=title3,
filename="njet-new" + str(ntag) + "tag",
print_height=False,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True)
chi2, nod = stackplot(Zsplit(old),
b"nJets",
bins,
1,
xlabel=r"number of jets",
title3=title3,
filename="njet-old" + str(ntag) + "tag",
print_height=False,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True)
bins = np.array([0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4.5]) - 0.001
chi2, nod = stackplot(Zsplit(new),
b"dEtaBB",
bins,
1,
xlabel=r"$\Delta\eta_{BB}$",
title3=title3,
filename="etabb-new" + str(ntag) + "tag",
print_height=False,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True)
chi2, nod = stackplot(Zsplit(old),
b"dEtaBB",
bins,
1,
xlabel=r"$\Delta\eta_{BB}$",
title3=title3,
filename="etabb-old" + str(ntag) + "tag",
print_height=False,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True)
bins = [150, 200, 250, 300, 350, 400, 500, 600, 800, 1800]
chi2, nod = stackplot(Zsplit(new),
b"ptH",
bins,
1000.,
xlabel=r"$pT_{BB}[GeV]$",
title3=title3,
filename="ptH-new" + str(ntag) + "tag",
print_height=False,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True)
chi2, nod = stackplot(Zsplit(old),
b"ptH",
bins,
1000.,
xlabel=r"$pT_{BB}[GeV]$",
title3=title3,
filename="ptH-old" + str(ntag) + "tag",
print_height=False,
title2=t2,
auto_colour=False,
limit_y=0.5,
upper_y=2.0,
log_y=True)
data = copy.deepcopy(old)
eventpop(data, "Zlljet")
for each in data:
if each.alias != "data":
each.weight *= -1
new = eventkepp(new, "Zlljet")
setcolour(new, "r")
old = eventkepp(old, "Zlljet")
setcolour(old, "b")
setcolour(data, "k")
bins = [
150, 200, 250, 300, 350, 400, 500, 600, 700, 800, 900, 1000, 1500, 1800
]
histplot_withsub([new, old, data],
b'mVHres',
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1000.,
removenorm=None,
filename="mVH" + str(ntag) + "tag",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
histplot_withsub([new, old, data],
b'mVHres',
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1000.,
removenorm="data",
filename="mVH" + str(ntag) + "tag_density",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
bins = [150, 200, 250, 300, 350, 400, 500, 600, 800, 1800]
histplot_withsub([new, old, data],
b"ptH",
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1000.,
xlabel=r"$pT_{BB}[GeV]$",
removenorm=None,
filename="ptbb" + str(ntag) + "tag",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
histplot_withsub([new, old, data],
b"ptH",
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1000.,
xlabel=r"$pT_{BB}[GeV]$",
removenorm="data",
filename="ptbb" + str(ntag) + "tag_density",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
bins = [150, 200, 250, 300, 350, 400, 500, 600, 800, 1800]
histplot_withsub([new, old, data],
b"pTV",
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1000.,
xlabel=r"$pT_{V}[GeV]$",
removenorm=None,
filename="ptV" + str(ntag) + "tag",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
histplot_withsub([new, old, data],
b"pTV",
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1000.,
xlabel=r"$pT_{V}[GeV]$",
removenorm="data",
filename="ptV" + str(ntag) + "tag_density",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
bins = np.array([2, 3, 4, 5, 6, 7, 8, 9]) - 0.001
histplot_withsub([new, old, data],
b"nJets",
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1,
xlabel=r"number of jets",
removenorm=None,
filename="njet" + str(ntag) + "tag",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
histplot_withsub([new, old, data],
b"nJets",
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1,
xlabel=r"number of jets",
removenorm="data",
filename="njet" + str(ntag) + "tag_density",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
bins = np.array([0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4.5]) - 0.001
histplot_withsub([new, old, data],
b"dEtaBB",
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1,
xlabel=r"$\Delta\eta_{BB}$",
removenorm=None,
filename="eta" + str(ntag) + "tag",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
histplot_withsub([new, old, data],
b"dEtaBB",
bins,
labels=["Sherpa v2.2.10", "Sherpa v2.2.1", "data"],
scales=1,
xlabel=r"$\Delta\eta_{BB}$",
removenorm="data",
filename="eta" + str(ntag) + "tag_density",
central="data",
title3=title3,
title2=t2,
do_errorbar=True)
# title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.0, log_y=True, title3="2 lep.",)
# bins = [10, 50, 100, 150, 250, 350, 450, 550, 650, 750]
# stackplot(bkgtest + datatest,b'ptTrkJetsinFJ2',bins,1000.,
# xlabel=r"$pT_{Trkj2}[GeV]$", filename=direct + "ptTrkJetsinFJ2" + name, print_height=True,
# title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.5, log_y=True, title3="2 lep.",)
datatest = copy.deepcopy(datalist)
bkgtest = copy.deepcopy(backgroundlist)
sumbkg = 0
sumdata = 0
for each in bkgtest + datatest:
# each.cut_parameter(cut_btagout_less, 0)
if "data" not in each.alias:
sumbkg += sum(each.weight)
else:
sumdata += len(each.weight)
print(sumbkg)
print(sumdata)
print("Making plots...")
direct = ""
name = "mbbcut-3ptag"
bins = range(0,700,30)
stackplot(bkgtest + datatest,b'ptHcorr',bins,1000.,
xlabel=r"$pT_{BB}[GeV]$", filename=direct + "ptBB" + name, print_height=True,
title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.5, log_y=True, title3="2 lep. 3+ btag resolved",)
if "data" not in each.alias:
sumbkg += sum(each.weight)
else:
sumdata += len(each.weight)
print(sumbkg)
print(sumdata)
print("Making plots...")
direct = ""
name = "mbbcut-1tag"
bins = [200, 220, 240, 260, 290, 320, 350, 380, 410, 450, 550, 650, 750, 850, 1000, 1200, 1400, 1800]
stackplot(bkgtest + datatest,b'ptfj1',bins,1000.,
xlabel=r"$pT_{FJ}[GeV]$", filename=direct + "ptfj1" + name, print_height=True,
title2=t2,auto_colour=False, limit_y = 0.5, upper_y=2.5, log_y=True, title3="2 lep. 1 btag merged",)
datatest = copy.deepcopy(datalist)
bkgtest = copy.deepcopy(backgroundlist)
sumbkg = 0
sumdata = 0
for each in bkgtest + datatest:
each.cut_parameter(cut_btagin_is, 2)
# each.cut_parameter(cut_btagout_less, 0)
if "data" not in each.alias:
sumbkg += sum(each.weight)
else:
sumdata += len(each.weight)
print(sumbkg)
print(sumdata)
backgroundlist.append(content)
test = get_signalid("ggA")
out = splitesamples(signallist[0], test)
new_signallist = []
for each in out:
new_signallist.append(each[1])
for each in out:
print(each[0], sum(each[1].weight))
each[1].alias = "ggA" + str(each[0]) + " GeV"
saveevents_pandas([each[1]], str(each[0])+".csv")
saveevents_pandas(backgroundlist, "background.csv")
# if datalist:
# saveevents(datalist,"data")
# if signallist:
# saveevents(signallist,"signal")
# if backgroundlist:
# saveevents(backgroundlist,"backgrounds")
# make stack plot. delete if not needed.
print("Making plots...")
title3="mbbcr"
direct = ""
name = "SR-"
bins = [50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 1000, 1150, 1350, 1550, 1800]
stackplot(backgroundlist+datalist,b'mVHres',bins,1000.,
xlabel=r"$m_{VH}[GeV]$", title3=title3, filename=direct + "mVH" + name, print_height=True,
title2=t2, auto_colour=False, limit_y=0.5, upper_y=2.0, log_y=True)