def load_joeys_style():
from ROOT import gStyle, gROOT
font_id = 12
gStyle.SetOptStat(0)
gStyle.SetTitleFont(font_id, "X") # LaTeX typeface
gStyle.SetTitleFont(font_id, "Y")
gStyle.SetTitleFont(font_id, "Z")
gStyle.SetTitleFont(font_id, "T")
gStyle.SetLabelFont(font_id, "X") # LaTeX typeface
gStyle.SetLabelFont(font_id, "Y")
gStyle.SetLabelFont(font_id, "Z")
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
gStyle.SetPadTopMargin(0.13)
gStyle.SetPadBottomMargin(0.25)
gStyle.SetPadLeftMargin(0.17)
gStyle.SetPadRightMargin(0.25)
gStyle.SetCanvasDefW(1500)
gStyle.SetCanvasDefH(900)
gStyle.SetTitleSize(0.06,"X")
gStyle.SetTitleSize(0.06,"Y")
gStyle.SetTitleSize(0.06,"Z")
gStyle.SetTitleSize(0.06,"T") # for title
gStyle.SetLabelSize(0.04,"X")
gStyle.SetLabelSize(0.04,"Y")
gStyle.SetLabelSize(0.04,"Z")
gStyle.SetTitleOffset(1.5,"X")
gStyle.SetTitleOffset(1.1,"Y")
gStyle.SetTitleOffset(1.3,"Z")
gROOT.ForceStyle()
def SetStyle():
gROOT.SetStyle('Plain')
gROOT.ForceStyle()
gStyle.SetTextFont(42)
gStyle.SetOptTitle(0)
gStyle.SetOptFit(1112)
gStyle.SetOptStat(1110)
gStyle.SetPadRightMargin(0.08)
gStyle.SetPadTopMargin(0.11)
gStyle.SetPadBottomMargin(0.12)
gStyle.SetTitleFont(42, 'x')
gStyle.SetTitleFont(42, 'y')
gStyle.SetTitleFont(42, 'z')
gStyle.SetTitleOffset(1.05, 'x')
gStyle.SetTitleOffset(1.00, 'y')
gStyle.SetTitleSize(0.05, 'x')
gStyle.SetTitleSize(0.05, 'y')
gStyle.SetTitleSize(0.05, 'z')
gStyle.SetLabelFont(42, 'x')
gStyle.SetLabelFont(42, 'y')
gStyle.SetLabelFont(42, 'z')
gStyle.SetLabelSize(0.05, 'x')
gStyle.SetLabelSize(0.05, 'y')
gStyle.SetLabelSize(0.05, 'z')
TGaxis.SetMaxDigits(3)
gStyle.SetStatY(0.9)
def Init():
from ROOT import gStyle
from ROOT import gROOT
gROOT.ProcessLine("gErrorIgnoreLevel = 2000;")
gStyle.SetCanvasColor(0);
gStyle.SetCanvasBorderMode(0);
gStyle.SetCanvasBorderSize(3);
gStyle.SetPadLeftMargin(0.125);
gStyle.SetPadBottomMargin(0.12);
gStyle.SetPadColor(0);
gStyle.SetPadBorderMode(0);
gStyle.SetFrameBorderMode(0);
gStyle.SetFrameBorderSize(0);
gStyle.SetFrameFillColor(0);
gStyle.SetOptStat(0);
gStyle.SetLabelOffset(0.005,"X");
gStyle.SetLabelSize(0.03,"X");
gStyle.SetLabelFont(42,"X");
gStyle.SetTitleOffset(.85,"X");
gStyle.SetTitleSize(0.04,"X");
gStyle.SetTitleFont(42,"X");
gStyle.SetLabelOffset(0.005,"Y");
gStyle.SetLabelSize(0.03,"Y");
gStyle.SetLabelFont(42,"Y");
gStyle.SetTitleOffset(.98,"Y");
gStyle.SetTitleSize(0.04,"Y");
gStyle.SetTitleFont(42,"Y");
gStyle.SetStatColor(0);
gStyle.SetStatBorderSize(0);
gStyle.SetTextFont(2);
gStyle.SetTextSize(.05);
gStyle.SetLegendBorderSize(1);
gStyle.SetHistLineWidth(2);
gStyle.SetTitleFillColor(0);
gStyle.SetTitleFontSize(0.06);
gStyle.SetTitleBorderSize(0);
gStyle.SetTitleAlign(13);
gStyle.SetTextAlign(22);
#RJ
gStyle.SetPadTickX(1);
gStyle.SetPadTickY(1);
gStyle.SetPadTopMargin(0.05);
gStyle.SetPadBottomMargin(0.13);
gStyle.SetPadLeftMargin(0.16);
gStyle.SetPadRightMargin(0.03);
def looks():
gROOT.ProcessLine('TGaxis::SetMaxDigits(3)')
gStyle.SetFrameBorderMode(0)
gStyle.SetFrameFillColor(0)
gStyle.SetCanvasBorderMode(0)
gStyle.SetCanvasColor(0)
gStyle.SetPadBorderMode(0)
gStyle.SetPadColor(0)
gStyle.SetStatColor(0)
gStyle.SetTitleFont(42, '')
gStyle.SetLabelFont(42, 'x')
gStyle.SetTitleFont(42, 'x')
gStyle.SetLabelFont(42, 'y')
gStyle.SetTitleFont(42, 'y')
gStyle.SetLabelFont(42, 'z')
gStyle.SetTitleFont(42, 'z')
gStyle.SetLabelSize(0.048, 'x')
gStyle.SetTitleSize(0.048, 'x')
gStyle.SetLabelSize(0.048, 'y')
gStyle.SetTitleSize(0.048, 'y')
gStyle.SetLabelSize(0.048, 'z')
gStyle.SetTitleSize(0.048, 'z')
gStyle.SetTitleSize(0.048, '')
gStyle.SetTitleAlign(23)
gStyle.SetTitleX(0.5)
gStyle.SetTitleBorderSize(0)
gStyle.SetTitleFillColor(0)
gStyle.SetTitleStyle(0)
gStyle.SetOptStat('emr')
gStyle.SetOptStat(0)
gStyle.SetStatBorderSize(0)
gStyle.SetStatFont(42)
gStyle.SetStatFontSize(0.048)
gStyle.SetStatY(0.9)
gStyle.SetStatX(0.86)
gStyle.SetHistLineColor(ROOT.kBlue + 2)
gStyle.SetLegendBorderSize(0)
gStyle.SetLegendFillColor(0)
gStyle.SetFuncWidth(2)
gStyle.SetFuncColor(2)
gStyle.SetPadTopMargin(0.08)
gStyle.SetPadBottomMargin(0.12)
gStyle.SetPadLeftMargin(0.12)
gStyle.SetPadRightMargin(0.06)
gStyle.SetCanvasDefX(400)
gStyle.SetCanvasDefY(20)
gStyle.SetCanvasDefH(420)
gStyle.SetCanvasDefW(610)
gStyle.SetFrameBorderMode(0)
gStyle.SetFrameLineWidth(2)
gStyle.SetHistLineWidth(2)
gStyle.SetTitleOffset(1.16, 'y')
gStyle.SetTitleOffset(1.20, 'x')
def set_pub_style():
from ROOT import gStyle
# No Canvas Border
gStyle.SetCanvasBorderMode(0)
gStyle.SetCanvasBorderSize(0)
# White BG
gStyle.SetCanvasColor(10)
# Format for axes
gStyle.SetLabelFont(42, 'xyz')
gStyle.SetLabelSize(0.05, 'xyz')
gStyle.SetLabelOffset(0.01, 'xyz')
# gStyle->SetNdivisions(510, 'xyz')
gStyle.SetTitleFont(42, 'xyz')
gStyle.SetTitleColor(1, 'xyz')
gStyle.SetTitleSize(0.06, 'xyz')
gStyle.SetTitleOffset(1.25, 'xyz')
# No pad borders
gStyle.SetPadBorderMode(0)
gStyle.SetPadBorderSize(0)
# White BG
gStyle.SetPadColor(10)
# Margins for labels etc.
gStyle.SetPadLeftMargin(0.155)
gStyle.SetPadBottomMargin(0.155)
gStyle.SetPadRightMargin(0.15)
gStyle.SetPadTopMargin(0.1)
# No error bars in x direction
gStyle.SetErrorX(0)
# Format legend
gStyle.SetLegendBorderSize(0)
def setStyle():
gROOT.Reset()
icol = 0
# WHITE
font = 42
# Helvetica
tsize = 0.05
gStyle.SetFrameBorderMode(icol)
gStyle.SetFrameFillColor(icol)
gStyle.SetCanvasBorderMode(icol)
gStyle.SetCanvasColor(icol)
gStyle.SetPadBorderMode(icol)
gStyle.SetPadColor(icol)
gStyle.SetStatColor(icol)
gStyle.SetPaperSize(20, 26)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.08)
gStyle.SetPadBottomMargin(0.15)
gStyle.SetPadLeftMargin(0.12)
gStyle.SetTitleXOffset(1.05)
gStyle.SetTitleYOffset(0.95)
gStyle.SetTextFont(font)
gStyle.SetTextSize(tsize)
gStyle.SetLabelFont(font, "x")
gStyle.SetTitleFont(font, "x")
gStyle.SetLabelFont(font, "y")
gStyle.SetTitleFont(font, "y")
gStyle.SetLabelFont(font, "z")
gStyle.SetTitleFont(font, "z")
gStyle.SetLabelSize(tsize * 0.85, "x")
gStyle.SetTitleSize(tsize * 1.10, "x")
gStyle.SetLabelSize(tsize * 0.85, "y")
gStyle.SetTitleSize(tsize * 1.10, "y")
gStyle.SetLabelSize(tsize * 0.85, "z")
gStyle.SetTitleSize(tsize * 1.10, "z")
gStyle.SetMarkerStyle(20)
gStyle.SetMarkerSize(1.)
gStyle.SetHistLineWidth(2)
gStyle.SetLineStyleString(2, "[12 12]")
# postscript dashes
gStyle.SetEndErrorSize(0.)
# gStyle.SetOptTitle(0);
gStyle.SetOptStat(0)
gStyle.SetOptFit(0)
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
gStyle.SetPaintTextFormat("4.1f")
def Styling():
# Center title
gStyle.SetTitleAlign(22)
gStyle.SetTitleX(.5)
gStyle.SetTitleY(.95)
gStyle.SetTitleBorderSize(0)
# Remove stats box
gStyle.SetOptStat(0)
# Set background color to white
gStyle.SetFillColor(10)
gStyle.SetFrameFillColor(10)
gStyle.SetCanvasColor(10)
gStyle.SetPadColor(10)
gStyle.SetTitleFillColor(0)
gStyle.SetStatColor(10)
# No colored frames around plots
gStyle.SetFrameBorderMode(0)
gStyle.SetCanvasBorderMode(0)
gStyle.SetPadBorderMode(0)
# Set the default line color for a fit function to be red
gStyle.SetFuncColor(2)
# Marker settings
gStyle.SetMarkerStyle(20)
# No border on legends
gStyle.SetLegendBorderSize(0)
# Disabled for violating NOvA style guidelines
# Scientific notation on axes
TGaxis.SetMaxDigits(3)
# Axis titles
gStyle.SetTitleSize(.055, "xyz")
gStyle.SetTitleOffset(2.2, "xyz")
gStyle.SetTitleOffset(2.2, "y")
gStyle.SetTitleSize(.05, "")
gStyle.SetTitleOffset(2.2, "")
# Axis labels (numbering)
gStyle.SetLabelSize(.05, "xyz")
gStyle.SetLabelOffset(.005, "xyz")
# Thicker lines
gStyle.SetHistLineWidth(2)
gStyle.SetFrameLineWidth(2)
gStyle.SetFuncWidth(2)
# Set the number of tick marks
gStyle.SetNdivisions(506, "xyz")
# Set tick marks on all sides
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
# Fonts
kNovaFont = 42
gStyle.SetStatFont(kNovaFont)
gStyle.SetLabelFont(kNovaFont, "xyz")
gStyle.SetTitleFont(kNovaFont, "xyz")
gStyle.SetTitleFont(kNovaFont, "")
# Apply same settings to titles
gStyle.SetTextFont(kNovaFont)
gStyle.SetLegendFont(kNovaFont)
def setPlotStyle(): gStyle.SetPadGridX(1) gStyle.SetPadGridY(1) gStyle.SetOptStat(1110) gStyle.SetLineWidth(2) gStyle.SetHistLineWidth(3) gStyle.SetPadTickX(1) gStyle.SetPadTickY(1) gStyle.SetTextFont(62) gStyle.SetLabelFont(62) gStyle.SetTitleFont(62) gStyle.SetLegendBorderSize(1) gStyle.SetLegendFont(62)
def loadstyle2():
gROOT.SetStyle("Plain")
gStyle.SetOptStat(0)
gStyle.SetOptStat(0000)
gStyle.SetPalette(0)
gStyle.SetCanvasColor(0)
gStyle.SetFrameFillColor(0)
gStyle.SetTitleOffset(1.15, "y")
gStyle.SetTitleFont(42, "xy")
gStyle.SetLabelFont(42, "xy")
gStyle.SetTitleSize(0.042, "xy")
gStyle.SetLabelSize(0.035, "xy")
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
def load_root_style():
"""
Set more advanced ROOT style for histograms
"""
gROOT.SetStyle("Plain")
gStyle.SetOptStat(0)
gStyle.SetPalette(0)
gStyle.SetCanvasColor(0)
gStyle.SetFrameFillColor(0)
gStyle.SetTitleOffset(1.15, "y")
gStyle.SetTitleFont(42, "xy")
gStyle.SetLabelFont(42, "xy")
gStyle.SetTitleSize(0.042, "xy")
gStyle.SetLabelSize(0.035, "xy")
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
def SetPaperStyle():
## histograms lines
gStyle.SetHistFillColor(0)
gStyle.SetHistFillStyle(0)
gStyle.SetHistLineColor(1)
gStyle.SetHistLineStyle(0)
gStyle.SetHistLineWidth(1)
## suppress plot titles and fit box
gStyle.SetOptTitle(0)
gStyle.SetOptFit(0)
## axis settings
gStyle.SetLabelFont(142, "xyz")
gStyle.SetLabelSize(0.04, "xyz")
gStyle.SetTitleFont(142, "xyz")
gStyle.SetTitleOffset(1.2, "xyz")
gStyle.SetTitleSize(0.05, "xyz")
## stat box
gStyle.SetOptStat(0) # suppress the stats box
def draw_model_perf():
gROOT.SetBatch()
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
gStyle.SetTextFont(42)
gStyle.SetTitleFont(42)
gStyle.SetLabelFont(42)
gStyle.SetPalette(kDarkBodyRadiator)
trees_dir = "/mnt/temp/mkabus/val-20201209/trees"
suffix = "filter4_poo0_drop0.00_depth4_batch0_scaler0_useSCMean1_useSCFluc1_pred_doR1" \
"_dophi0_doz0/"
pdf_dir_90 = "%s/phi90_r17_z17_%s" % (trees_dir, suffix)
pdf_dir_180 = "%s/phi180_r33_z33_%s" % (trees_dir, suffix)
filename = "model_perf_90-180"
file_formats = ["png"] # "pdf" - lasts long
nevs_90 = [10000, 18000] # 5000
nevs_180 = [10000, 18000]
nevs = nevs_90 + nevs_180
pdf_files_90 = [
"%s/pdfmaps_nEv%d.root" % (pdf_dir_90, nev) for nev in nevs_90
]
pdf_files_180 = [
"%s/pdfmaps_nEv%d.root" % (pdf_dir_180, nev) for nev in nevs_180
]
pdf_file_names = pdf_files_90 + pdf_files_180
grans = [90, 90, 180, 180]
colors = [kBlue, kOrange, kGreen, kRed]
markers_list = [(kFullSquare, kOpenSquare), (kFullCircle, kOpenCircle),
(kFullTriangleUp, kOpenTriangleUp),
(kFullDiamond, kOpenDiamond)]
var_name = "flucDistRDiff"
y_vars = ["rmsd", "means"]
y_vars_names = ["RMSE", "#mu"]
# y_labels = ["#it{RMSE} (cm)", "Mean (cm)"]
x_vars = ["rBinCenter", "fsector"]
x_vars_short = ["r"] #, "fsector"]
x_labels = ["#it{r} (cm)", "fsector"] # TODO: what units?
# "r_rmsd": 33, 195.0, 245.5, 20, # 83.5, 254.5, 200,
# "r_rmsd": "33, 83.5, 110, 200, 0.000, 0.06",
hist_strs = {
"r_rmsd": "33, 83.5, 245.5, 200, 0.000, 0.06",
"fsector_rmsd": "90, -1.0, 19, 200, 0.00, 0.1",
"r_means": "33, 83.5, 245.5, 200, -0.06, 0.06",
"fsector_means": "90, -1.0, 19, 200, -0.07, 0.01",
"r_rmsd_means": "33, 83.5, 245.5, 200, -0.06, 0.06"
}
date = datetime.date.today().strftime("%Y%m%d")
# flucDistR_entries>50
# deltaSCBinCenter>0.0121 && deltaSCBinCenter<0.0122
# deltaSCBinCenter>0.020 && deltaSCBinCenter<0.023
# rBinCenter > 200.0 && deltaSCBinCenter>0.04 && deltaSCBinCenter<0.057
# deltaSCBinCenter > 0.06 && deltaSCBinCenter < 0.07
delta_sc_str = "#int_{#it{r}, #it{#varphi}, #it{z}} " +\
"#frac{#it{#rho}_{SC} - #it{<#rho>}_{SC}}{#it{<#rho>}_{SC}}"
cuts = {
"deltaSC": {
"r_lim": (0.05, 0.07),
"fsector_lim": (0.00, 0.05),
"desc": lambda x: "%.2f < %s < %.2f" % (x[0], delta_sc_str, x[1])
},
"z": {
"r_lim": (0.0, 5.0),
"fsector_lim": (0.0, 5.0),
"desc": lambda x: "%.2f < #it{z} < %.2f cm" % x
},
"r": {
"r_lim": (0.0, 110.0),
"fsector_lim": (86.0, 86.1),
"desc": lambda x: "%.2f cm < #it{r} < %.2f cm" % x
},
"fsector": {
"r_lim": (9.00, 9.05),
"fsector_lim": (0.0, 20.0),
"desc": lambda x: "sector %d" % int(round(x[0]))
},
"phi": {
"r_lim": (3.1, 2.9),
"fsector_lim": (3.1, 2.9),
"desc": lambda x: "%.2f < #it{#varphi} < %.2f" % x
}
}
cut_fsector = "zBinCenter > %.2f && zBinCenter < %.2f" % cuts["z"]["fsector_lim"] +\
" && rBinCenter > %.2f && rBinCenter < %.2f" % cuts["r"]["fsector_lim"] +\
" && deltaSCBinCenter > %.2f && deltaSCBinCenter < %.2f" %\
cuts["deltaSC"]["fsector_lim"] +\
" && %s_rmsd > 0.0" % var_name
cut_r = "zBinCenter > %.2f && zBinCenter < %.2f" % cuts["z"]["r_lim"] +\
" && abs(phiBinCenter - %.1f) < %.1f" % cuts["phi"]["r_lim"] +\
" && deltaSCBinCenter > %.2f && deltaSCBinCenter < %.2f" %\
cuts["deltaSC"]["r_lim"] +\
" && %s_rmsd > 0.0" % var_name
cuts_list = [cut_r, cut_fsector]
# for y_var, y_label in zip(y_vars, y_labels):
y_label = "#it{RMSE} and #it{#mu} (cm)"
canvas, leg = setup_canvas("perf_%s" % y_label)
pdf_files = [
TFile.Open(pdf_file_name, "read") for pdf_file_name in pdf_file_names
]
trees = [pdf_file.Get("pdfmaps") for pdf_file in pdf_files]
variables = zip(x_vars, x_vars_short, x_labels, cuts_list)
for x_var, x_var_short, x_label, cut in variables:
hist_str = hist_strs["%s_%s_%s" % (x_var_short, y_vars[0], y_vars[1])]
hists = []
styles = enumerate(zip(nevs, colors, markers_list, trees, grans))
for ind, (nev, color, markers, tree, gran) in styles:
tree.SetMarkerColor(color)
tree.SetMarkerSize(2)
gran_str = "180#times 33 #times 33" if gran == 180 else "90#times 17 #times 17"
for y_ind, (y_var, y_var_name,
marker) in enumerate(zip(y_vars, y_vars_names,
markers)):
tree.SetMarkerStyle(marker)
hist_def = "th_%d_%d(%s)" % (ind, y_ind, hist_str)
tree.Draw("%s_%s:%s>>%s" % (var_name, y_var, x_var, hist_def),
cut, "prof")
hists.append(tree.GetHistogram())
leg.AddEntry(hists[-1], "%s" % y_var_name, "P")
leg.AddEntry("", "%d, %s" % (nev, gran_str), "")
for hist in hists:
setup_hist(x_label, y_label, hist)
hist.SetMaximum(0.06)
hist.SetMinimum(-0.06)
hist.Draw("same")
leg.Draw()
#tex = add_alice_text()
#tex.Draw()
txt = add_cut_desc(cuts, x_var_short)
txt.Draw()
for ff in file_formats:
canvas.SaveAs(
"%s_%s_%s_%s_%s.%s" %
(date, filename, x_var_short, y_vars[0], y_vars[1], ff))
for pdf_file in pdf_files:
pdf_file.Close()
c.Print("plots/"+c.GetName()+"_cdf.png")
c.Clear()
if __name__ == '__main__' :
gStyle.SetOptStat(0)
gStyle.SetTitleFont(42, "p")
gStyle.SetTitleColor(1)
gStyle.SetTitleTextColor(1)
gStyle.SetTitleFillColor(10)
gStyle.SetTitleFontSize(0.05)
gStyle.SetTitleOffset(1.2, "XYZ")
gStyle.SetTitleFont(42, "XYZ")
gStyle.SetLabelFont(42, "XYZ")
effFile = ROOT.TFile("egTriggerEff.root", "r")
rateFile = ROOT.TFile("egTriggerRates.root", "r")
eff = effFile.Get("analyzer/crystal_tree")
rate = rateFile.Get("analyzer/crystal_tree")
c = ROOT.TCanvas("canvas", "canvas", 1200, 600)
c.SetName("hovere")
c.SetTitle("H/E Value")
# endcap: "22./x+0."
drawCDFs(c, rate, eff, "cluster_hovere", "", "14/x+.05", 5)
c.SetName("isolation")
c.SetTitle("Isolation Value")
def plot_hfptspectrum_ratios_comb(case_num, case_den, arraytype):
gROOT.SetStyle("Plain")
gStyle.SetOptStat(0)
gStyle.SetOptStat(0000)
gStyle.SetPalette(0)
gStyle.SetCanvasColor(0)
gStyle.SetFrameFillColor(0)
gStyle.SetOptTitle(0)
gStyle.SetTitleOffset(1.15, "y")
gStyle.SetTitleFont(42, "xy")
gStyle.SetLabelFont(42, "xy")
gStyle.SetTitleSize(0.042, "xy")
gStyle.SetLabelSize(0.035, "xy")
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
with open("data/database_ml_parameters_%s.yml" % case_num,
'r') as param_config_num:
data_param_num = yaml.load(param_config_num, Loader=yaml.FullLoader)
with open("data/database_ml_parameters_%s.yml" % case_den,
'r') as param_config_den:
data_param_den = yaml.load(param_config_den, Loader=yaml.FullLoader)
folder_plots_num = data_param_num[case_num]["analysis"][
"dir_general_plots"]
folder_plots_den = data_param_den[case_den]["analysis"][
"dir_general_plots"]
if not os.path.exists(folder_plots_num):
print("creating folder ", folder_plots_num)
os.makedirs(folder_plots_num)
if not os.path.exists(folder_plots_den):
print("creating folder ", folder_plots_den)
os.makedirs(folder_plots_den)
folder_num_allperiods = \
data_param_num[case_num]["analysis"][arraytype[0]]["data"]["resultsallp"]
folder_den_allperiods = \
data_param_den[case_den]["analysis"][arraytype[0]]["data"]["resultsallp"]
folder_num_triggered = \
data_param_num[case_num]["analysis"][arraytype[1]]["data"]["resultsallp"]
folder_den_triggered = \
data_param_den[case_den]["analysis"][arraytype[1]]["data"]["resultsallp"]
binsmin_num = data_param_num[case_num]["analysis"][
arraytype[0]]["sel_binmin2"]
binsmax_num = data_param_num[case_num]["analysis"][
arraytype[0]]["sel_binmax2"]
name_num = data_param_num[case_num]["analysis"][
arraytype[0]]["latexnamemeson"]
name_den = data_param_den[case_den]["analysis"][
arraytype[0]]["latexnamemeson"]
latexbin2var = data_param_num[case_num]["analysis"][
arraytype[0]]["latexbin2var"]
plotbinMB = data_param_num[case_num]["analysis"][arraytype[0]]["plotbin"]
plotbinHM = data_param_num[case_num]["analysis"][arraytype[1]]["plotbin"]
br_num = data_param_num[case_num]["ml"]["opt"]["BR"]
br_den = data_param_den[case_den]["ml"]["opt"]["BR"]
sigmav0_num = data_param_num[case_num]["analysis"]["sigmav0"]
sigmav0_den = data_param_den[case_den]["analysis"]["sigmav0"]
file_num_allperiods = TFile.Open("%s/finalcross%s%smulttot.root" % \
(folder_num_allperiods, case_num, arraytype[0]))
file_den_allperiods = TFile.Open("%s/finalcross%s%smulttot.root" % \
(folder_den_allperiods, case_den, arraytype[0]))
file_num_triggered = TFile.Open("%s/finalcross%s%smulttot.root" % \
(folder_num_triggered, case_num, arraytype[1]))
file_den_triggered = TFile.Open("%s/finalcross%s%smulttot.root" % \
(folder_den_triggered, case_den, arraytype[1]))
if not file_num_allperiods or not file_num_triggered:
print("---Warning: Issue with %s merged files. Meson ratio plot skipped (%s, %s)---" % \
(case_num, arraytype[0], arraytype[1]))
return
if not file_den_allperiods or not file_den_triggered:
print("---Warning: Issue with %s merged files. Meson ratio plot skipped (%s, %s)---" % \
(case_den, arraytype[0], arraytype[1]))
return
rootfilename = "%s/ComparisonRatios_%s%s_%scombined%s.root" % \
(folder_plots_num, case_num, case_den, arraytype[0], arraytype[1])
fileoutput = TFile.Open(rootfilename, "recreate")
ccross = TCanvas('cRatioCross', 'The Fit Canvas')
ccross.SetCanvasSize(1500, 1500)
ccross.SetWindowSize(500, 500)
maxplot = 1.0
if case_num == "Dspp":
maxplot = 0.5
ccross.cd(1).DrawFrame(0.9, 0, 30, maxplot, ";#it{p}_{T} (GeV/#it{c});%s / %s" % \
(name_num, name_den))
ccross.cd(1).SetLogx()
legyield = TLegend(.4, .68, .8, .88)
legyield.SetBorderSize(0)
legyield.SetFillColor(0)
legyield.SetFillStyle(0)
legyield.SetTextFont(42)
legyield.SetTextSize(0.025)
colors = [kBlack, kRed, kGreen + 2, kBlue]
for imult, iplot in enumerate(plotbinMB):
if not iplot:
continue
hratio = file_num_allperiods.Get("histoSigmaCorr%d" % (imult))
hratio.Scale(1. / (br_num * sigmav0_num * 1e12))
hcross_den = file_den_allperiods.Get("histoSigmaCorr%d" % (imult))
hcross_den.Scale(1. / (br_den * sigmav0_den * 1e12))
hratio.Divide(hcross_den)
hratio.SetLineColor(colors[imult % len(colors)])
hratio.SetMarkerColor(colors[imult % len(colors)])
hratio.SetMarkerStyle(21)
hratio.SetTitle(";#it{p}_{T} (GeV/#it{c});%s / %s" %
(name_num, name_den))
hratio.Draw("same")
legyieldstring = "%.1f #leq %s < %.1f (MB)" % \
(binsmin_num[imult], latexbin2var, binsmax_num[imult])
legyield.AddEntry(hratio, legyieldstring, "LEP")
fileoutput.cd()
hratio.Write("hratio_fromMB_%.1f_%s_%.1f" % \
(binsmin_num[imult], latexbin2var, binsmax_num[imult]))
for imult, iplot in enumerate(plotbinHM):
if not iplot:
continue
hratioHM = file_num_triggered.Get("histoSigmaCorr%d" % (imult))
hratioHM.Scale(1. / (br_num * sigmav0_num * 1e12))
hcrossHM_den = file_den_triggered.Get("histoSigmaCorr%d" % (imult))
hcrossHM_den.Scale(1. / (br_den * sigmav0_den * 1e12))
hratioHM.Divide(hcrossHM_den)
hratioHM.SetLineColor(colors[imult % len(colors)])
hratioHM.SetMarkerColor(colors[imult % len(colors)])
hratioHM.SetTitle(";#it{p}_{T} (GeV/#it{c});%s / %s" %
(name_num, name_den))
hratioHM.Draw("same")
legyieldstring = "%.1f #leq %s < %.1f (HM)" % \
(binsmin_num[imult], latexbin2var, binsmax_num[imult])
legyield.AddEntry(hratioHM, legyieldstring, "LEP")
fileoutput.cd()
hratioHM.Write("hratio_fromHM_%.1f_%s_%.1f" % \
(binsmin_num[imult], latexbin2var, binsmax_num[imult]))
legyield.Draw()
ccross.SaveAs("%s/PtSpec_ComparisonRatios_%s%s_%scombined%s_logx.eps" % \
(folder_plots_num, case_num, case_den, arraytype[0], arraytype[1]))
ccross.SaveAs("%s/PtSpec_ComparisonRatios_%s%s_%scombined%s_logx.eps" % \
(folder_plots_den, case_num, case_den, arraytype[0], arraytype[1]))
ccross.cd(1).SetLogx(0)
ccross.SaveAs("%s/PtSpec_ComparisonRatios_%s%s_%scombined%s.eps" % \
(folder_plots_num, case_num, case_den, arraytype[0], arraytype[1]))
ccross.SaveAs("%s/PtSpec_ComparisonRatios_%s%s_%scombined%s.eps" % \
(folder_plots_den, case_num, case_den, arraytype[0], arraytype[1]))
fileoutput.cd()
ccross.Write()
fileoutput.Close()
rootfilenameden = "%s/ComparisonRatios_%s%s_%scombined%s.root" % \
(folder_plots_den, case_num, case_den, arraytype[0], arraytype[1])
copyfile(rootfilename, rootfilenameden)
print("---Output stored in:", rootfilename, "and", rootfilenameden, "---")
def setStyle():
TColor.InitializeColors()
stops = array('d', [
0.0000, 0.1250, 0.2500, 0.3750, 0.5000, 0.6250, 0.7500, 0.8750, 1.0000
])
red = array('d', [
0.9764, 0.9956, 0.8186, 0.5301, 0.1802, 0.0232, 0.0780, 0.0592, 0.2082
])
green = array('d', [
0.9832, 0.7862, 0.7328, 0.7492, 0.7178, 0.6419, 0.5041, 0.3599, 0.1664
])
blue = array('d', [
0.0539, 0.1968, 0.3499, 0.4662, 0.6425, 0.7914, 0.8385, 0.8684, 0.5293
])
TColor.CreateGradientColorTable(9, stops, red, green, blue, 255, 1.0)
gStyle.SetHatchesLineWidth(1)
gStyle.SetNumberContours(255)
gStyle.SetNdivisions(505, "xyz")
gStyle.SetTitleBorderSize(0)
gStyle.SetTitleColor(1)
gStyle.SetTitleStyle(3013)
gStyle.SetTitleFillColor(0)
gStyle.SetTitleX(0.05)
gStyle.SetTitleW(0.4)
gStyle.SetTitleY(0.965)
gStyle.SetTitleH(0.065)
gStyle.SetCanvasBorderMode(0)
gStyle.SetCanvasBorderSize(3)
gStyle.SetCanvasColor(0)
gStyle.SetPadColor(0)
gStyle.SetPadBorderMode(0)
gStyle.SetFuncWidth(3)
gStyle.SetPadGridY(False)
gStyle.SetPadGridX(False)
gStyle.SetFrameLineWidth(1)
gStyle.SetMarkerSize(5)
gStyle.SetPadTickX(True)
gStyle.SetPadTickY(True)
#gStyle.SetPalette(1)
gStyle.SetHistLineWidth(3)
gStyle.SetHistLineColor(1)
gStyle.SetOptStat(0)
gStyle.SetOptFit(0)
gStyle.SetStatW(0.25)
gStyle.SetStatH(0.25)
gStyle.SetStatX(0.9)
gStyle.SetStatY(0.9)
gStyle.SetStatColor(0)
gStyle.SetStatFormat("6.4g")
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadBottomMargin(0.16)
gStyle.SetPadLeftMargin(0.12)
font = 42
gStyle.SetTextSize(.055)
gStyle.SetTextFont(font)
gStyle.SetLabelFont(font, "x")
gStyle.SetTitleFont(font, "x")
gStyle.SetLabelFont(font, "y")
gStyle.SetTitleFont(font, "y")
gStyle.SetLabelFont(font, "z")
gStyle.SetTitleFont(font, "z")
gStyle.SetTitleSize(.055, "x")
gStyle.SetTitleSize(.055, "y")
gStyle.SetTitleSize(.05, "z")
gStyle.SetLabelSize(.05, "x")
gStyle.SetLabelSize(.05, "y")
gStyle.SetLabelSize(.05, "z")
gStyle.SetLabelOffset(0.014, "x")
gStyle.SetLabelOffset(0.006, "y")
gStyle.SetLabelOffset(0.008, "z")
gStyle.SetTitleOffset(1, "y")
gStyle.SetTitleXOffset(1.2)
# use bold lines and markers
gStyle.SetMarkerStyle(20)
gStyle.SetMarkerColor(1)
gStyle.SetMarkerSize(1.2)
gStyle.SetLineStyleString(2, "[12 12]")
# postscript dashes
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
def initStyle():
gROOT.SetStyle("Plain")
# For the canvas:
gStyle.SetCanvasBorderMode(0)
gStyle.SetCanvasColor(kWhite)
gStyle.SetCanvasDefH(700) #Height of canvas
gStyle.SetCanvasDefW(700) #Width of canvas
gStyle.SetCanvasDefX(0) #Position on screen
gStyle.SetCanvasDefY(0)
# For the line:
gStyle.SetLineWidth(2)
# For the Pad:
gStyle.SetPadBorderMode(0)
# gStyle.SetPadBorderSize(Width_t size = 1)
gStyle.SetPadColor(kWhite)
gStyle.SetPadGridX(True)
gStyle.SetPadGridY(True)
gStyle.SetGridColor(0)
gStyle.SetGridStyle(3)
gStyle.SetGridWidth(1)
# For the frame:
gStyle.SetFrameBorderMode(0)
gStyle.SetFrameBorderSize(1)
gStyle.SetFrameFillColor(0)
gStyle.SetFrameFillStyle(0)
gStyle.SetFrameLineColor(1)
gStyle.SetFrameLineStyle(1)
gStyle.SetFrameLineWidth(1)
# For the histo:
# gStyle.SetHistFillColor(1)
# gStyle.SetHistFillStyle(0)
gStyle.SetHistLineColor(1)
gStyle.SetHistLineStyle(0)
gStyle.SetHistLineWidth(2)
# gStyle.SetLegoInnerR(Float_t rad = 0.5)
# gStyle.SetNumberContours(Int_t number = 20)
gStyle.SetEndErrorSize(2)
#gStyle.SetErrorMarker(20)
gStyle.SetErrorX(0.)
gStyle.SetMarkerStyle(8)
gStyle.SetMarkerSize(1)
#For the fit/function:
gStyle.SetOptFit(0)
gStyle.SetFitFormat("5.4g")
gStyle.SetFuncColor(2)
gStyle.SetFuncStyle(1)
gStyle.SetFuncWidth(1)
#For the date:
gStyle.SetOptDate(0)
# gStyle.SetDateX(Float_t x = 0.01)
# gStyle.SetDateY(Float_t y = 0.01)
# For the statistics box:
gStyle.SetOptFile(0)
gStyle.SetOptStat(0) # To display the mean and RMS: SetOptStat("mr")
gStyle.SetStatColor(kWhite)
gStyle.SetStatFont(42)
gStyle.SetStatFontSize(0.025)
gStyle.SetStatTextColor(1)
gStyle.SetStatFormat("6.4g")
gStyle.SetStatBorderSize(1)
gStyle.SetStatH(0.1)
gStyle.SetStatW(0.15)
# gStyle.SetStatStyle(Style_t style = 1001)
# gStyle.SetStatX(Float_t x = 0)
# gStyle.SetStatY(Float_t y = 0)
# Margins:
gStyle.SetPadTopMargin(0.11)
gStyle.SetPadBottomMargin(0.13)
gStyle.SetPadLeftMargin(0.17)
gStyle.SetPadRightMargin(0.07)
# For the Global title:
gStyle.SetOptTitle(0)
gStyle.SetTitleFont(42)
gStyle.SetTitleColor(1)
gStyle.SetTitleTextColor(1)
gStyle.SetTitleFillColor(10)
gStyle.SetTitleFontSize(0.04)
# gStyle.SetTitleH(0) # Set the height of the title box
# gStyle.SetTitleW(0) # Set the width of the title box
#gStyle.SetTitleX(0.35) # Set the position of the title box
#gStyle.SetTitleY(0.986) # Set the position of the title box
# gStyle.SetTitleStyle(Style_t style = 1001)
#gStyle.SetTitleBorderSize(0)
# For the axis titles:
gStyle.SetTitleColor(1, "XYZ")
gStyle.SetTitleFont(42, "XYZ")
gStyle.SetTitleSize(0.05, "XYZ")
# gStyle.SetTitleXSize(Float_t size = 0.02) # Another way to set the size?
# gStyle.SetTitleYSize(Float_t size = 0.02)
gStyle.SetTitleXOffset(1.)
gStyle.SetTitleYOffset(1.3)
#gStyle.SetTitleOffset(1.1, "Y") # Another way to set the Offset
# For the axis labels:
gStyle.SetLabelColor(1, "XYZ")
gStyle.SetLabelFont(42, "XYZ")
gStyle.SetLabelOffset(0.007, "XYZ")
gStyle.SetLabelSize(0.035, "XYZ")
# For the axis:
gStyle.SetAxisColor(1, "XYZ")
gStyle.SetStripDecimals(True)
gStyle.SetTickLength(0.03, "XYZ")
gStyle.SetNdivisions(510, "XYZ")
gStyle.SetPadTickX(
1) # To get tick marks on the opposite side of the frame
gStyle.SetPadTickY(1)
# Change for log plots:
gStyle.SetOptLogx(0)
gStyle.SetOptLogy(0)
gStyle.SetOptLogz(0)
gStyle.SetPalette(1) #(1,0)
# another top group addition
gStyle.SetHatchesSpacing(1.0)
# Postscript options:
gStyle.SetPaperSize(20., 20.)
#gStyle.SetPaperSize(TStyle.kA4)
#gStyle.SetPaperSize(27., 29.7)
#TGaxis.SetMaxDigits(3)
# gStyle.SetLineScalePS(Float_t scale = 3)
# gStyle.SetLineStyleString(Int_t i, const char* text)
# gStyle.SetHeaderPS(const char* header)
# gStyle.SetTitlePS(const char* pstitle)
#gStyle.SetColorModelPS(1)
# gStyle.SetBarOffset(Float_t baroff = 0.5)
# gStyle.SetBarWidth(Float_t barwidth = 0.5)
# gStyle.SetPaintTextFormat(const char* format = "g")
# gStyle.SetPalette(Int_t ncolors = 0, Int_t* colors = 0)
# gStyle.SetTimeOffset(Double_t toffset)
# gStyle.SetHistMinimumZero(kTRUE)
#gStyle.cd()
print "TDR Style initialized"
def applyRootStyle():
from ROOT import gROOT, gStyle, kWhite, kBlack, TColor
# Start from a plain default
gROOT.SetStyle("Plain")
lhcbMarkerType = 8
lhcbMarkerSize = 0.8
lhcbFont = 62
lhcbStatFontSize = 0.02
lhcbStatBoxWidth = 0.12
lhcbStatBoxHeight = 0.12
lhcbWidth = 1
lhcbTextSize = 0.05
lhcbLabelSize = 0.035
lhcbAxisLabelSize = 0.035
lhcbForeColour = kBlack
gStyle.SetFrameBorderMode(0)
gStyle.SetPadBorderMode(0)
# canvas options
gStyle.SetCanvasBorderSize(0)
gStyle.SetCanvasBorderMode(0)
# fonts
gStyle.SetTextFont(lhcbFont)
gStyle.SetTextSize(lhcbTextSize)
gStyle.SetLabelFont(lhcbFont, "x")
gStyle.SetLabelFont(lhcbFont, "y")
gStyle.SetLabelFont(lhcbFont, "z")
gStyle.SetLabelSize(lhcbLabelSize, "x")
gStyle.SetLabelSize(lhcbLabelSize, "y")
gStyle.SetLabelSize(lhcbLabelSize, "z")
gStyle.SetTitleFont(lhcbFont)
gStyle.SetTitleSize(lhcbAxisLabelSize, "x")
gStyle.SetTitleSize(lhcbAxisLabelSize, "y")
gStyle.SetTitleSize(lhcbAxisLabelSize, "z")
gStyle.SetTitleColor(kWhite)
gStyle.SetTitleFillColor(kWhite)
gStyle.SetTitleColor(kBlack)
gStyle.SetTitleBorderSize(0)
gStyle.SetTitleTextColor(kBlack)
# set title position
gStyle.SetTitleX(0.15)
gStyle.SetTitleY(0.97)
# turn off Title box
gStyle.SetTitleBorderSize(0)
gStyle.SetTitleTextColor(lhcbForeColour)
gStyle.SetTitleColor(lhcbForeColour)
# use bold lines and markers
gStyle.SetLineWidth(lhcbWidth)
gStyle.SetFrameLineWidth(lhcbWidth)
gStyle.SetHistLineWidth(lhcbWidth)
gStyle.SetFuncWidth(lhcbWidth)
gStyle.SetGridWidth(lhcbWidth)
gStyle.SetLineStyleString(2, "[12 12]")
gStyle.SetMarkerStyle(lhcbMarkerType)
gStyle.SetMarkerSize(lhcbMarkerSize)
# Grid
# gStyle.SetGridStyle(3)
# label offsets
gStyle.SetLabelOffset(0.015)
# by default, do not display histogram decorations:
gStyle.SetOptStat(1111)
# show probability, parameters and errors
gStyle.SetOptFit(1011)
# look of the statistics box:
gStyle.SetStatBorderSize(1)
gStyle.SetStatFont(lhcbFont)
gStyle.SetStatFontSize(lhcbStatFontSize)
gStyle.SetStatX(0.9)
gStyle.SetStatY(0.9)
gStyle.SetStatW(lhcbStatBoxWidth)
gStyle.SetStatH(lhcbStatBoxHeight)
# put tick marks on top and RHS of plots
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
# histogram divisions
gStyle.SetNdivisions(505, "x")
gStyle.SetNdivisions(510, "y")
# Style for 2D zcol plots
NRGBs = 5
NCont = 255
from array import array
stops = array('d', [0.00, 0.34, 0.61, 0.84, 1.00])
red = array('d', [0.00, 0.00, 0.87, 1.00, 0.51])
green = array('d', [0.00, 0.81, 1.00, 0.20, 0.00])
blue = array('d', [0.51, 1.00, 0.12, 0.00, 0.00])
TColor().CreateGradientColorTable(NRGBs, stops, red, green, blue, NCont)
gStyle.SetNumberContours(NCont)
# Force the style
gROOT.ForceStyle()
def main():
# usage description
usage = "Example: ./scripts/plotLimits.py -M Asymptotic -l logs -f qq --massrange 1200 7000 100"
# input parameters
parser = ArgumentParser(description='Script that plots limits for specified mass points',epilog=usage)
parser.add_argument('analysis', type=str, help='Analysis name')
parser.add_argument('model', type=str, help='Model name')
parser.add_argument("-M", "--method", dest="method", required=True,
choices=['ProfileLikelihood', 'HybridNew', 'Asymptotic', 'MarkovChainMC', 'theta', 'HybridNewGrid'],
help="Method to calculate upper limits",
metavar="METHOD")
parser.add_argument('--fit_function', type=str, default="f4", help="Name of fit function used for background estimate")
parser.add_argument('--timesAE', action='store_true', help="Set y-axis to sigma*BR*A*e, instead of sigma*BR")
parser.add_argument('--fitTrigger', action='store_true', help="Use trigger fit")
parser.add_argument('--correctTrigger', action='store_true', help="Use trigger correction")
parser.add_argument('--useMCTrigger', action='store_true', help="Use MC trigger emulation")
#results_group = parser.add_mutually_exclusive_group(required=True)
#results_group.add_argument("-l", "--logs_path", dest="logs_path",
# help="Path to log files",
# metavar="LOGS_PATH")
#results_group.add_argument("-r", "--results_file", dest="results_file",
# help="Path to a file containing results",
# metavar="RESULTS_FILE")
#parser.add_argument("-f", "--final_state", dest="final_state", required=True,
# help="Final state (e.g. qq, qg, gg)",
# metavar="FINAL_STATE")
#parser.add_argument("-f2", "--finalstate2", dest="final_state2", required=True, help="hG,lG,hR, or lR", metavar="FINAL_STATE2")
parser.add_argument("--noSyst", action="store_true", help="Make plots for limits without systematics")
parser.add_argument("--freezeNuisances", type=str, help="Make plots for limits with frozen nuisance parameters")
parser.add_argument("--postfix", dest="postfix", default='', help="Postfix for the output plot name (default: %(default)s)")
parser.add_argument("--fileFormat", dest="fileFormat", default='pdf', help="Format of the output plot (default: %(default)s)")
parser.add_argument("--saveObjects", type=str, help="Save plot objects")
parser.add_argument("--extraText", dest="extraText", default='', help="Extra text on the plot (default: %(default)s)")
parser.add_argument("--lumi_sqrtS", dest="lumi_sqrtS", default='19.7 fb^{-1} (8 TeV)', help="Integrated luminosity and center-of-mass energy (default: %(default)s)")
parser.add_argument("--printResults", dest="printResults", default=False, action="store_true", help="Print results to the screen")
mass_group = parser.add_mutually_exclusive_group(required=True)
mass_group.add_argument("--mass",
type=int,
nargs = '*',
default = 1000,
help="Mass can be specified as a single value or a whitespace separated list (default: %(default)i)"
)
mass_group.add_argument("--massrange",
type=int,
nargs = 3,
help="Define a range of masses to be produced. Format: min max step",
metavar = ('MIN', 'MAX', 'STEP')
)
mass_group.add_argument("--masslist",
help = "List containing mass information"
)
args = parser.parse_args()
if args.method == 'HybridNew':
searchmethod = 'Hybrid New'
# mass points for which resonance shapes will be produced
input_masses = []
if args.massrange != None:
MIN, MAX, STEP = args.massrange
input_masses = range(MIN, MAX+STEP, STEP)
elif args.masslist != None:
# A mass list was provided
print "Will create mass list according to", args.masslist
masslist = __import__(args.masslist.replace(".py",""))
input_masses = masslist.masses
else:
input_masses = args.mass
# sort masses
input_masses.sort()
from ROOT import kTRUE, kFALSE, gROOT, gStyle, gPad, TGraph, TCanvas, TLegend, TF1, TFile
from ROOT import kGreen, kYellow, kWhite
# Make acc*eff TGraph
ae_x = array('d',[325, 350, 400, 500, 600, 750, 900, 1200])
if args.timesAE:
ae_y = np.ones(len(ae_x))
else:
ae_y = array('d', [])
for mass in ae_x:
ae_y.append(analysis_config.simulation.get_signal_AE(args.analysis, args.model, int(mass)))
acceptance_times_efficiency = TGraph(len(ae_x), ae_x, ae_y)
#xs = array('d',[250,300,400,500,600,750,900,1200])
#trigger_correctionl = TF1("trigbbl_efficiency", "(1. / (1. + TMath::Exp(-1. * (x - [0]) / [1])))**[2]", 175, 400)
#trigger_correctionl.SetParameter(0, 1.82469e+02)
#trigger_correctionl.SetParameter(1, 2.87768e+01)
#trigger_correctionl.SetParameter(2, 9.11659e-01)
#trigger_correctionh = TF1("trigbbh_efficiency", "(1. / (1. + TMath::Exp(-1. * (x - [0]) / [1])))**[2]", 300, 600)
#trigger_correctionh.SetParameter(0, 3.61785e+02)
#trigger_correctionh.SetParameter(1, 3.16523e+01)
#trigger_correctionh.SetParameter(2, 4.84357e-01)
#if args.timesAE:
# ys = np.ones(len(xs))
#else:
# if args.analysis == "trigbbh_CSVTM" and args.model == "Hbb":
# #ys = array('d',[188./19751.,1304./19993.,2697./49494.,881./19999.,534./19598.])
# ys = array('d',[24./19737.,188./19751.,1171./19984.,1419./19992.,1304./19993.,2697./49494.,881./19999.,534./19598.])
# #graphMod = trigger_correctionh
# elif args.analysis == "trigbbl_CSVTM" and args.model == "Hbb":
# #ys = array('d',[30./2797.,1583./19995.,1295./19996.,999./19996.,528./19999.])
# ys = array('d',[574./19737.,763./39502.,651./19984.,583./19992.,984./39986.,1905./98988.,656./39998.,369./39196.])
# #graphMod = trigger_correctionh
# elif args.analysis == "trigbbh_CSVTM" and args.model == "RSG":
# #ys = array('d',[109./19751.,488./19993.,954./49494.,328./19999.,182./19598.])
# ys = array('d',[40./19977.,30./2797.,1522./19991.,1640./19396.,1583./19995.,1295./19996.,999./19996.,528./19999.])
# #graphMod = trigger_correctionl
# elif args.analysis == "trigbbl_CSVTM" and args.model == "RSG":
# #ys = array('d',[23./2797.,599./19995.,448./19996.,338./19996.,190./19999.])
# ys = array('d',[696./19977.,137./5594.,797./19991.,652./19396.,1206./39990.,891./39992.,675./39992.,379./39998.])
# #graphMod = trigger_correctionl
##ys = array('d',[1,1,1,1,1,1,1,1,])
#acceptance_times_efficiency = TGraph(len(xs),xs,ys)
# arrays holding results
masses = array('d')
xs_obs_limits = array('d')
xs_exp_limits = array('d')
masses_exp = array('d')
xs_exp_limits_1sigma = array('d')
xs_exp_limits_1sigma_up = array('d')
xs_exp_limits_2sigma = array('d')
xs_exp_limits_2sigma_up = array('d')
for mass in input_masses:
print ">> Reading results for %s %s resonance with m = %i GeV..."%(args.analysis, args.model, int(mass))
masses.append(mass)
masses_exp.append(mass)
# For masses above 1100, you scaled down the signal by 10 by hand, to help the limit setting.
#if args.analysis == "trigbbh_CSVTM" and mass >= 1100:
input_xs = 1./100.
#else:
# input_xs = 1.
if args.method == "HybridNewGrid":
found_limit = {"obs":False, "exp0":False, "exp1":False, "exp2":False, "exp-1":False, "exp-2":False}
for what in found_limit.keys():
log_file_path = limit_config.get_combine_log_path_grid(args.analysis, args.model, mass, args.fit_function, what, systematics=(not args.noSyst), frozen_nps=args.freezeNuisances, fitTrigger=args.fitTrigger, correctTrigger=args.correctTrigger, useMCTrigger=args.useMCTrigger)
print "Reading log file from " + log_file_path
log_file = open(log_file_path, 'r')
for line in log_file:
if re.search("^Limit: r <", line) and re.search("95%", line):
found_limit[what] = True
this_limit = float(line.split()[3])/acceptance_times_efficiency.Eval(mass)
print "Found limit for " + what + " = " + str(this_limit)
if what == "obs":
xs_obs_limits.append(this_limit * input_xs)
elif what == "exp0":
xs_exp_limits.append(this_limit * input_xs)
elif what == "exp1":
xs_exp_limits_1sigma_up.append(this_limit * input_xs)
elif what == "exp2":
xs_exp_limits_2sigma_up.append(this_limit * input_xs)
elif what == "exp-1":
xs_exp_limits_1sigma.append(this_limit * input_xs)
elif what == "exp-2":
xs_exp_limits_2sigma.append(this_limit * input_xs)
if not found_limit["obs"]:
xs_obs_limits.append(0)
if not found_limit["exp0"]:
xs_exp_limits.append(0)
if not found_limit["exp1"]:
xs_exp_limits_1sigma.append(0)
if not found_limit["exp2"]:
xs_exp_limits_1sigma_up.append(0)
if not found_limit["exp-1"]:
xs_exp_limits_2sigma.append(0)
if not found_limit["exp-2"]:
xs_exp_limits_2sigma_up.append(0)
if len(masses) != len(xs_obs_limits):
print "** ERROR: ** Could not find observed limit for m =", int(mass), "GeV. Aborting."
sys.exit(1)
else:
print "Reading log file from " + limit_config.get_combine_log_path(args.analysis, args.model, mass, args.fit_function, args.method, systematics=(not args.noSyst), frozen_nps=args.freezeNuisances, fitTrigger=args.fitTrigger, correctTrigger=args.correctTrigger, useMCTrigger=args.useMCTrigger)
if not os.path.exists((limit_config.get_combine_log_path(args.analysis, args.model, mass, args.fit_function, args.method, systematics=(not args.noSyst), frozen_nps=args.freezeNuisances, fitTrigger=args.fitTrigger, correctTrigger=args.correctTrigger, useMCTrigger=args.useMCTrigger))):
print "[plot_limits] WARNING : Log file not found! Setting limits to zero and skipping this point."
print "[plot_limits] WARNING : \t{}".format(limit_config.get_combine_log_path(args.analysis, args.model, mass, args.fit_function, args.method, systematics=(not args.noSyst), frozen_nps=args.freezeNuisances, fitTrigger=args.fitTrigger, correctTrigger=args.correctTrigger, useMCTrigger=args.useMCTrigger))
xs_obs_limits.append(0)
xs_exp_limits.append(0)
xs_exp_limits_1sigma.append(0)
xs_exp_limits_1sigma_up.append(0)
xs_exp_limits_2sigma.append(0)
xs_exp_limits_2sigma_up.append(0)
continue
log_file = open(limit_config.get_combine_log_path(args.analysis, args.model, mass, args.fit_function, args.method, systematics=(not args.noSyst), frozen_nps=args.freezeNuisances, fitTrigger=args.fitTrigger, correctTrigger=args.correctTrigger, useMCTrigger=args.useMCTrigger))
foundMethod = False
middle = 0
# read the log file
found_limit = {"obs":False, "exp":False, "exp+1":False, "exp+2":False, "exp-1":False, "exp-2":False}
for line in log_file:
if args.method == 'Asymptotic':
if re.search("^Observed Limit: r", line):
xs_obs_limits.append(float(line.split()[-1])/acceptance_times_efficiency.Eval(mass) * input_xs)
found_limit["obs"] = True
if mass == 325 and args.model == "ZPrime":
print "[debug] ZPrime 325 GeV limit = {}".format(xs_obs_limits[-1])
print "[debug] \tA*e={}, input_xs={}".format(acceptance_times_efficiency.Eval(mass), input_xs)
if re.search("^Expected 50.0%: r", line):
middle = float(line.split()[-1])
found_limit["exp"] = True
xs_exp_limits.append(middle/acceptance_times_efficiency.Eval(mass) * input_xs)
if re.search("^Expected 16.0%: r", line):
xs_exp_limits_1sigma.append((float(line.split()[-1]))/acceptance_times_efficiency.Eval(mass) * input_xs)
found_limit["exp-1"] = True
if re.search("^Expected 84.0%: r", line):
xs_exp_limits_1sigma_up.append(float(line.split()[-1])/acceptance_times_efficiency.Eval(mass) * input_xs)
found_limit["exp+1"] = True
if re.search("^Expected 2.5%: r", line):
xs_exp_limits_2sigma.append(float(line.split()[-1])/acceptance_times_efficiency.Eval(mass) * input_xs)
found_limit["exp-2"] = True
if re.search("^Expected 97.5%: r", line):
xs_exp_limits_2sigma_up.append(float(line.split()[-1])/acceptance_times_efficiency.Eval(mass) * input_xs)
found_limit["exp+2"] = True
elif args.method == 'theta':
if re.search('^# x; y; yerror', line):
foundMethod = True
if line.split()[0] == '0' and foundMethod:
xs_obs_limits.append(float(line.split()[1])/acceptance_times_efficiency.Eval(mass) * input_xs)
else:
searchmethod = "Hybrid New"
if re.search(' -- ' + searchmethod, line):
foundMethod = True
if re.search("^Limit: r", line) and foundMethod:
xs_obs_limits.append(float(line.split()[3])/acceptance_times_efficiency.Eval(mass) * input_xs)
found_limit["obs"] = True
print "[debug] Found limit " + str(xs_obs_limits[-1])
if not found_limit["obs"]:
xs_obs_limits.append(0)
if not found_limit["exp"]:
xs_exp_limits.append(0)
if not found_limit["exp+1"]:
xs_exp_limits_1sigma.append(0)
if not found_limit["exp+2"]:
xs_exp_limits_1sigma_up.append(0)
if not found_limit["exp-1"]:
xs_exp_limits_2sigma.append(0)
if not found_limit["exp-2"]:
xs_exp_limits_2sigma_up.append(0)
if len(masses) != len(xs_obs_limits):
print "** ERROR: ** Could not find observed limit for m =", int(mass), "GeV. Aborting."
sys.exit(1)
if args.method == 'Asymptotic' or args.method == 'HybridNewGrid':
if len(masses) != len(xs_exp_limits):
print "** ERROR: ** Could not find expected limit for m =", int(mass), "GeV. Aborting."
print "masses = ",
print masses
print "xs_exp_limits = ",
print xs_exp_limits
sys.exit(1)
if len(masses) != len(xs_exp_limits_1sigma):
print "** ERROR: ** Could not find expected 1 sigma down limit for m =", int(mass), "GeV. Aborting."
print "masses = ",
print masses
print "xs_exp_limits_1sigma = ",
print xs_exp_limits_1sigma
sys.exit(1)
if len(masses) != len(xs_exp_limits_1sigma_up):
print "** ERROR: ** Could not find expected 1 sigma up limit for m =", int(mass), "GeV. Aborting."
print "masses = ",
print masses
print "xs_exp_limits_1sigma_up = ",
print xs_exp_limits_1sigma_up
sys.exit(1)
if len(masses) != len(xs_exp_limits_2sigma):
print "** ERROR: ** Could not find expected 2 sigma down limit for m =", int(mass), "GeV. Aborting."
sys.exit(1)
if len(masses) != len(xs_exp_limits_2sigma_up):
print "** ERROR: ** Could not find expected 2 sigma up limit for m =", int(mass), "GeV. Aborting."
sys.exit(1)
if args.method == 'Asymptotic' or args.method == 'HybridNewGrid':
# complete the expected limit arrays
for i in range(0,len(masses)):
masses_exp.append( masses[len(masses)-i-1] )
xs_exp_limits_1sigma.append( xs_exp_limits_1sigma_up[len(masses)-i-1] )
xs_exp_limits_2sigma.append( xs_exp_limits_2sigma_up[len(masses)-i-1] )
if args.printResults:
print "masses =", masses.tolist()
print "xs_obs_limits =", xs_obs_limits.tolist()
print "xs_exp_limits =", xs_exp_limits.tolist()
print ""
print "masses_exp =", masses_exp.tolist()
print "xs_exp_limits_1sigma =", xs_exp_limits_1sigma.tolist()
print "xs_exp_limits_2sigma =", xs_exp_limits_2sigma.tolist()
gROOT.SetBatch(kTRUE);
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
gStyle.SetTitleFont(42, "XYZ")
gStyle.SetTitleSize(0.05, "XYZ")
gStyle.SetLabelFont(42, "XYZ")
gStyle.SetLabelSize(0.05, "XYZ")
gStyle.SetCanvasBorderMode(0)
gStyle.SetFrameBorderMode(0)
gStyle.SetCanvasColor(kWhite)
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
gStyle.SetPadLeftMargin(0.15)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.15)
gROOT.ForceStyle()
# theory curves: gg
massesS8 = array('d', [1000.0,1100.0,1200.0,1300.0,1400.0,1500.0,1600.0,1700.0,1800.0,1900.0,2000.0,2100.0,2200.0,2300.0,2400.0,2500.0,2600.0,2700.0,2800.0,2900.0,3000.0,3100.0,3200.0,3300.0,3400.0,3500.0,3600.0,3700.0,3800.0,3900.0,4000.0,4100.0,4200.0,4300.0,4400.0,4500.0,4600.0,4700.0,4800.0,4900.0,5000.0,5100.0,5200.0,5300.0,5400.0,5500.0,5600.0,5700.0,5800.0,5900.0,6000.0])
xsS8 = array('d', [5.46E+02,3.12E+02,1.85E+02,1.12E+02,7.19E+01,4.59E+01,3.02E+01,2.01E+01,1.37E+01,9.46E+00,6.55E+00,4.64E+00,3.27E+00,2.36E+00,1.70E+00,1.24E+00,9.11E-01,6.69E-01,4.97E-01,3.71E-01,2.78E-01,2.07E-01,1.55E-01,1.19E-01,9.26E-02,7.08E-02,5.43E-02,4.15E-02,3.22E-02,2.50E-02,1.92E-02,1.51E-02,1.19E-02,9.25E-03,7.35E-03,5.86E-03,4.53E-03,3.66E-03,2.91E-03,2.33E-03,1.86E-03,1.45E-03,1.12E-03,8.75E-04,6.90E-04,5.55E-04,4.47E-04,3.63E-04,2.92E-04,2.37E-04,1.97E-04])
graph_xsS8 = TGraph(len(massesS8),massesS8,xsS8)
graph_xsS8.SetLineWidth(3)
graph_xsS8.SetLineStyle(8)
graph_xsS8.SetLineColor(6)
# theory curves: qg
massesString = array('d', [1000.0,1100.0,1200.0,1300.0,1400.0,1500.0,1600.0,1700.0,1800.0,1900.0,2000.0,2100.0,2200.0,2300.0,2400.0,2500.0,2600.0,2700.0,2800.0,2900.0,3000.0,3100.0,3200.0,3300.0,3400.0,3500.0,3600.0,3700.0,3800.0,3900.0,4000.0,4100.0,4200.0,4300.0,4400.0,4500.0,4600.0,4700.0,4800.0,4900.0,5000.0,5100.0,5200.0,5300.0,5400.0,5500.0,5600.0,5700.0,5800.0,5900.0,6000.0,6100.0,6200.0,6300.0,6400.0,6500.0,6600.0,6700.0,6800.0,6900.0,7000.0,7100.0,7200.0,7300.0,7400.0,7500.0,7600.0,7700.0,7800.0,7900.0,8000.0,8100.0,8200.0,8300.0,8400.0,8500.0,8600.0,8700.0,8800.0,8900.0,9000.0,9100.,9200.,9300.,9400.,9500.,9600.,9700.,9800.,9900.,10000.])
xsString = array('d', [8316.184311558545,5312.93137758767,3435.0309937336524,2304.4139502741305,1569.8115447896687,1090.9516635659693,770.901859690924,551.9206062572061,399.69535383507633,293.77957451762086,218.15126842827823,162.87634729465125,123.17685479653694,93.63530805932386,71.53697229809124,55.37491301647483,42.75271508357369,33.36378355470234,26.06619302090876,20.311817606835643,16.1180931789545,12.768644973921226,10.142660425967444,8.057990848043234,6.400465846290908,5.115134438331436,4.132099789492928,3.3193854239538734,2.6581204529344302,2.157554604919995,1.7505176068913348,1.4049155245498584,1.140055677916783,0.9253251132104159,0.7522038169131606,0.6119747371392215,0.49612321727328523,0.40492020959456737,0.33091999402250655,0.27017917021492555,0.2201693919322846,0.17830700070267996,0.14564253802358157,0.11940534430331146,0.09694948234356839,0.0793065371847468,0.06446186373361917,0.05282660618352478,
0.0428516302310620888,0.0348997638039910363,0.0283334766442618227,0.0231416918363592127,0.0187417921340763783,0.0153501307395115115,0.0124396534127133717,0.0100542205744949455,0.0081744954858627415,0.0066338099362915941,0.0053365711503318145,0.00430912459914657443,0.00346381039244064343,0.00278602671711227174,0.00225154342228859257,0.0018082930150063248,0.00143929440338502119,0.0011581373956044489,0.00091869589873893118,0.00073410823691329855,0.00058669382997948734,0.0004661568745858897,0.000368716655469570365,0.000293168485206959169,0.000230224535021638668,0.000182317101888465142,0.000143263359883433282,0.000112630538527214965,0.000088189175598406759,0.000068708474367442343,0.000053931726669273556,0.0000416417855733682702,0.0000326529676755488658,0.0000254365480426201587,0.0000198410151166864761,0.0000154034425617473576,0.0000119095554601641413,9.2537574320108232e-6,7.2155417437856749e-6,5.6130924422251982e-6,4.36634755605624901e-6,3.39717456406994868e-6,2.6766018046173896e-6])
massesQstar = array('d', [1000.0,1100.0,1200.0,1300.0,1400.0,1500.0,1600.0,1700.0,1800.0,1900.0,2000.0,2100.0,2200.0,2300.0,2400.0,2500.0,2600.0,2700.0,2800.0,2900.0,3000.0,3100.0,3200.0,3300.0,3400.0,3500.0,3600.0,3700.0,3800.0,3900.0,4000.0,4100.0,4200.0,4300.0,4400.0,4500.0,4600.0,4700.0,4800.0,4900.0,5000.0,5100.0,5200.0,5300.0,5400.0,5500.0,5600.0,5700.0,5800.0,5900.0,6000.0,6100.0,6200.0,6300.0,6400.0,6500.0,6600.0,6700.0,6800.0,6900.0,7000.0,7100.0,7200.0,7300.0,7400.0,7500.0,7600.0,7700.0,7800.0,7900.0,8000.0,8100.0,8200.0,8300.0,8400.0,8500.0,8600.0,8700.0,8800.0,8900.0,9000.0])
xsQstar = array('d', [0.4101E+03,0.2620E+03,0.1721E+03,0.1157E+03,0.7934E+02,0.5540E+02,0.3928E+02,0.2823E+02,0.2054E+02,0.1510E+02,0.1121E+02,0.8390E+01,0.6328E+01,0.4807E+01,0.3674E+01,0.2824E+01,0.2182E+01,0.1694E+01,0.1320E+01,0.1033E+01,0.8116E+00,0.6395E+00,0.5054E+00,0.4006E+00,0.3182E+00,0.2534E+00,0.2022E+00,0.1616E+00,0.1294E+00,0.1038E+00,0.8333E-01,0.6700E-01,0.5392E-01,0.4344E-01,0.3503E-01,0.2827E-01,0.2283E-01,0.1844E-01,0.1490E-01,0.1205E-01,0.9743E-02,0.7880E-02,0.6373E-02,0.5155E-02,0.4169E-02,0.3371E-02,0.2725E-02,0.2202E-02,0.1779E-02,0.1437E-02,0.1159E-02,0.9353E-03,0.7541E-03,0.6076E-03,0.4891E-03,0.3935E-03,0.3164E-03,0.2541E-03,0.2039E-03,0.1635E-03,0.1310E-03,0.1049E-03,0.8385E-04,0.6699E-04,0.5347E-04,0.4264E-04,0.3397E-04,0.2704E-04,0.2151E-04,0.1709E-04,0.1357E-04,0.1077E-04,0.8544E-05,0.6773E-05,0.5367E-05,0.4251E-05,0.3367E-05,0.2666E-05,0.2112E-05,0.1673E-05,0.1326E-05])
graph_xsString = TGraph(len(massesString),massesString,xsString)
graph_xsString.SetLineWidth(3)
graph_xsString.SetLineStyle(8)
graph_xsString.SetLineColor(9)
graph_xsQstar = TGraph(len(massesQstar),massesQstar,xsQstar)
graph_xsQstar.SetLineWidth(3)
graph_xsQstar.SetLineStyle(2)
graph_xsQstar.SetLineColor(1)
# theory curves: qq
massesTh = array('d', [1000.0,1100.0,1200.0,1300.0,1400.0,1500.0,1600.0,1700.0,1800.0,1900.0,2000.0,2100.0,2200.0,2300.0,2400.0,2500.0,2600.0,2700.0,2800.0,2900.0,3000.0,3100.0,3200.0,3300.0,3400.0,3500.0,3600.0,3700.0,3800.0,3900.0,4000.0,4100.0,4200.0,4300.0,4400.0,4500.0,4600.0,4700.0,4800.0,4900.0,5000.0,5100.0,5200.0,5300.0,5400.0,5500.0,5600.0,5700.0,5800.0,5900.0,6000.0,6100.0,6200.0,6300.0,6400.0,6500.0,6600.0,6700.0,6800.0,6900.0,7000.0,7100.0,7200.0,7300.0,7400.0,7500.0,7600.0,7700.0,7800.0,7900.0,8000.0,8100.0,8200.0,8300.0,8400.0,8500.0,8600.0,8700.0,8800.0,8900.0,9000.0])
xsAxi = array('d', [0.1849E+03,0.1236E+03,0.8473E+02,0.5937E+02,0.4235E+02,0.3069E+02,0.2257E+02,0.1680E+02,0.1263E+02,0.9577E+01,0.7317E+01,0.5641E+01,0.4374E+01,0.3411E+01,0.2672E+01,0.2103E+01,0.1658E+01,0.1312E+01,0.1041E+01,0.8284E+00,0.6610E+00,0.5294E+00,0.4250E+00,0.3417E+00,0.2752E+00,0.2220E+00,0.1792E+00,0.1449E+00,0.1172E+00,0.9487E-01,0.7686E-01,0.6219E-01,0.5033E-01,0.4074E-01,0.3298E-01,0.2671E-01,0.2165E-01,0.1755E-01,0.1422E-01,0.1152E-01,0.9322E-02,0.7539E-02,0.6092E-02,0.4917E-02,0.3965E-02,0.3193E-02,0.2568E-02,0.2062E-02,0.1653E-02,0.1323E-02,0.1057E-02,0.8442E-03,0.6728E-03,0.5349E-03,0.4242E-03,0.3357E-03,0.2644E-03,0.2077E-03,0.1627E-03,0.1271E-03,0.9891E-04,0.7686E-04,0.5951E-04,0.4592E-04,0.3530E-04,0.2704E-04,0.2059E-04,0.1562E-04,0.1180E-04,0.8882E-05,0.6657E-05,0.4968E-05,0.3693E-05,0.2734E-05,0.2016E-05,0.1481E-05,0.1084E-05,0.7903E-06,0.5744E-06,0.4160E-06,0.3007E-06])
xsDiquark = array('d', [0.5824E+02,0.4250E+02,0.3172E+02,0.2411E+02,0.1862E+02,0.1457E+02,0.1153E+02,0.9211E+01,0.7419E+01,0.6019E+01,0.4912E+01,0.4031E+01,0.3323E+01,0.2750E+01,0.2284E+01,0.1903E+01,0.1590E+01,0.1331E+01,0.1117E+01,0.9386E+00,0.7900E+00,0.6658E+00,0.5618E+00,0.4745E+00,0.4010E+00,0.3391E+00,0.2869E+00,0.2428E+00,0.2055E+00,0.1740E+00,0.1473E+00,0.1246E+00,0.1055E+00,0.8922E-01,0.7544E-01,0.6376E-01,0.5385E-01,0.4546E-01,0.3834E-01,0.3231E-01,0.2720E-01,0.2288E-01,0.1922E-01,0.1613E-01,0.1352E-01,0.1132E-01,0.9463E-02,0.7900E-02,0.6584E-02,0.5479E-02,0.4551E-02,0.3774E-02,0.3124E-02,0.2581E-02,0.2128E-02,0.1750E-02,0.1437E-02,0.1177E-02,0.9612E-03,0.7833E-03,0.6366E-03,0.5160E-03,0.4170E-03,0.3360E-03,0.2700E-03,0.2162E-03,0.1725E-03,0.1372E-03,0.1087E-03,0.8577E-04,0.6742E-04,0.5278E-04,0.4114E-04,0.3192E-04,0.2465E-04,0.1894E-04,0.1448E-04,0.1101E-04,0.8322E-05,0.6253E-05,0.4670E-05])
xsWprime = array('d', [0.8811E+01,0.6024E+01,0.4216E+01,0.3010E+01,0.2185E+01,0.1610E+01,0.1200E+01,0.9043E+00,0.6875E+00,0.5271E+00,0.4067E+00,0.3158E+00,0.2464E+00,0.1932E+00,0.1521E+00,0.1201E+00,0.9512E-01,0.7554E-01,0.6012E-01,0.4792E-01,0.3827E-01,0.3059E-01,0.2448E-01,0.1960E-01,0.1571E-01,0.1259E-01,0.1009E-01,0.8090E-02,0.6483E-02,0.5193E-02,0.4158E-02,0.3327E-02,0.2660E-02,0.2125E-02,0.1695E-02,0.1351E-02,0.1075E-02,0.8546E-03,0.6781E-03,0.5372E-03,0.4248E-03,0.3353E-03,0.2642E-03,0.2077E-03,0.1629E-03,0.1275E-03,0.9957E-04,0.7757E-04,0.6027E-04,0.4670E-04,0.3610E-04,0.2783E-04,0.2140E-04,0.1641E-04,0.1254E-04,0.9561E-05,0.7269E-05,0.5510E-05,0.4167E-05,0.3143E-05,0.2364E-05,0.1774E-05,0.1329E-05,0.9931E-06,0.7411E-06,0.5523E-06,0.4108E-06,0.3055E-06,0.2271E-06,0.1687E-06,0.1254E-06,0.9327E-07,0.6945E-07,0.5177E-07,0.3863E-07,0.2888E-07,0.2162E-07,0.1622E-07,0.1218E-07,0.9156E-08,0.6893E-08])
xsZprime = array('d', [0.5027E+01,0.3398E+01,0.2353E+01,0.1663E+01,0.1196E+01,0.8729E+00,0.6450E+00,0.4822E+00,0.3638E+00,0.2769E+00,0.2123E+00,0.1639E+00,0.1272E+00,0.9933E-01,0.7789E-01,0.6134E-01,0.4848E-01,0.3845E-01,0.3059E-01,0.2440E-01,0.1952E-01,0.1564E-01,0.1256E-01,0.1010E-01,0.8142E-02,0.6570E-02,0.5307E-02,0.4292E-02,0.3473E-02,0.2813E-02,0.2280E-02,0.1848E-02,0.1499E-02,0.1216E-02,0.9864E-03,0.8002E-03,0.6490E-03,0.5262E-03,0.4264E-03,0.3453E-03,0.2795E-03,0.2260E-03,0.1826E-03,0.1474E-03,0.1188E-03,0.9566E-04,0.7690E-04,0.6173E-04,0.4947E-04,0.3957E-04,0.3159E-04,0.2516E-04,0.2001E-04,0.1587E-04,0.1255E-04,0.9906E-05,0.7795E-05,0.6116E-05,0.4785E-05,0.3731E-05,0.2900E-05,0.2247E-05,0.1734E-05,0.1334E-05,0.1022E-05,0.7804E-06,0.5932E-06,0.4492E-06,0.3388E-06,0.2544E-06,0.1903E-06,0.1417E-06,0.1051E-06,0.7764E-07,0.5711E-07,0.4186E-07,0.3055E-07,0.2223E-07,0.1612E-07,0.1164E-07,0.8394E-08])
graph_xsAxi = TGraph(len(massesTh),massesTh,xsAxi)
graph_xsAxi.SetLineWidth(3)
graph_xsAxi.SetLineStyle(3)
graph_xsAxi.SetLineColor(63)
graph_xsDiquark = TGraph(len(massesTh),massesTh,xsDiquark)
graph_xsDiquark.SetLineWidth(3)
graph_xsDiquark.SetLineStyle(9)
graph_xsDiquark.SetLineColor(8)
graph_xsWprime = TGraph(len(massesTh),massesTh,xsWprime)
graph_xsWprime.SetLineWidth(3)
graph_xsWprime.SetLineStyle(7)
graph_xsWprime.SetLineColor(46)
graph_xsZprime = TGraph(len(massesTh),massesTh,xsZprime)
graph_xsZprime.SetLineWidth(3)
graph_xsZprime.SetLineStyle(5)
graph_xsZprime.SetLineColor(38)
# limits
if args.method == "Asymptotic" or args.method == "HybridNewGrid":
graph_exp_2sigma = ( TGraph(len(masses_exp),masses_exp,xs_exp_limits_2sigma) if len(xs_exp_limits_2sigma) > 0 else TGraph(0) )
graph_exp_2sigma.SetFillColor(kYellow)
graph_exp_1sigma = ( TGraph(len(masses_exp),masses_exp,xs_exp_limits_1sigma) if len(xs_exp_limits_2sigma) > 0 else TGraph(0) )
graph_exp_1sigma.SetFillColor(kGreen+1)
graph_exp = ( TGraph(len(masses),masses,xs_exp_limits) if len(xs_exp_limits_2sigma) > 0 else TGraph(0) )
#graph_exp.SetMarkerStyle(24)
graph_exp.SetLineWidth(3)
graph_exp.SetLineStyle(2)
graph_exp.SetLineColor(4)
graph_obs = TGraph(len(masses),masses,xs_obs_limits)
graph_obs.SetMarkerStyle(20)
graph_obs.SetLineWidth(3)
#graph_obs.SetLineStyle(1)
graph_obs.SetLineColor(1)
c = TCanvas("c", "",800,800)
c.cd()
legend = TLegend(.58,.72,.90,.90)
legend.SetBorderSize(0)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
legend.SetTextSize(0.03)
legend.SetHeader('95% CL upper limits')
if len(xs_exp_limits_2sigma) > 0 and (args.method == "Asymptotic" or args.method == "HybridNewGrid"):
frame = graph_exp_2sigma.GetHistogram().Clone()
else:
frame = graph_obs.GetHistogram().Clone()
frame.Reset()
frame.GetXaxis().SetTitle("Resonance mass [GeV]")
frame.GetXaxis().SetTitleOffset(1.05)
if args.timesAE:
#if args.model == "ZPrime":
# frame.GetYaxis().SetTitle("#sigma #times BR(c#bar{c},b#bar{b}) #times #it{A} #times #epsilon [pb]")
#else:
frame.GetYaxis().SetTitle("#sigma #times BR(b#bar{b}) #times #it{A} #times #epsilon [pb]")
else:
#if args.model == "ZPrime":
# frame.GetYaxis().SetTitle("#sigma #times BR(c#bar{c},b#bar{b}) [pb]")
#else:
frame.GetYaxis().SetTitle("#sigma #times BR(b#bar{b}) [pb]")
frame.GetYaxis().SetTitleOffset(1.2)
if args.timesAE:
frame.GetYaxis().SetRangeUser(1e-03,1e+01)
else:
frame.GetYaxis().SetRangeUser(1e-01,5e+02)
frame.Draw("axis")
if len(xs_exp_limits_2sigma) > 0 and (args.method == "Asymptotic" or args.method == "HybridNewGrid"):
graph_exp_2sigma.GetXaxis().SetTitle("Resonance mass [GeV]")
graph_exp_2sigma.GetXaxis().SetTitleOffset(1.1)
graph_exp_2sigma.GetYaxis().SetTitle("#sigma #times #it{B} [pb]")
graph_exp_2sigma.GetYaxis().SetTitleOffset(1.1)
#graph_exp_2sigma.GetYaxis().SetRangeUser(1e-03,1e+02)
#graph_exp_2sigma.GetXaxis().SetNdivisions(1005)
graph_exp_2sigma.Draw("F")
graph_exp_1sigma.Draw("F")
graph_exp.Draw("L")
graph_obs.Draw("LP")
legend.AddEntry(graph_obs,"Observed","lp")
legend.AddEntry(graph_exp,"Expected","lp")
legend.AddEntry(graph_exp_1sigma,"#pm 1#sigma","F")
legend.AddEntry(graph_exp_2sigma,"#pm 2#sigma","F")
else:
graph_obs.GetXaxis().SetTitle("Resonance mass [GeV]")
graph_obs.GetYaxis().SetTitle("#sigma #times #it{B} [pb]")
graph_obs.GetYaxis().SetTitleOffset(1.1)
graph_obs.GetYaxis().SetRangeUser(1e-02,1e+03)
#graph_obs.GetXaxis().SetNdivisions(1005)
graph_obs.Draw("LP")
legend.AddEntry(graph_obs,"Observed","lp")
#if args.final_state == 'gg' :
# graph_xsS8.Draw("L")
#elif args.final_state == 'qg' :
# graph_xsQstar.Draw("L")
# graph_xsString.Draw("L")
#elif args.final_state == 'qq' :
# graph_xsAxi.Draw("L")
# graph_xsDiquark.Draw("L")
# graph_xsWprime.Draw("L")
# graph_xsZprime.Draw("L")
legend.Draw()
#legendTh = TLegend(.60,.72,.90,.88)
#legendTh.SetBorderSize(0)
#legendTh.SetFillColor(0)
#legendTh.SetFillStyle(0)
#legendTh.SetTextFont(42)
#legendTh.SetTextSize(0.03)
#legendTh.AddEntry(graph_xsAxi,"Axigluon/coloron","l")
#legendTh.AddEntry(graph_xsDiquark,"Scalar diquark","l")
#legendTh.AddEntry(graph_xsWprime,"W' SSM","l")
#legendTh.AddEntry(graph_xsZprime,"Z' SSM","l")
#legendTh.Draw()
# draw the lumi text on the canvas
CMS_lumi.extraText = args.extraText
CMS_lumi.lumi_sqrtS = args.lumi_sqrtS # used with iPeriod = 0 (free form)
iPos = 11
iPeriod = 0
CMS_lumi.CMS_lumi(c, iPeriod, iPos)
gPad.RedrawAxis()
c.SetLogy()
postfix = ( ('_' + args.postfix) if args.postfix != '' else '' )
if args.noSyst:
postfix += "_noSyst"
if args.freezeNuisances:
postfix += "_" + args.freezeNuisances.replace(",", "_")
if args.fitTrigger:
postfix += "_fitTrigger"
elif args.correctTrigger:
postfix += "_correctTrigger"
if args.useMCTrigger:
postfix += "_useMCTrigger"
fileName = limit_config.paths["limit_plots"] + '/xs_limit_%s_%s_%s_%s.%s'%(args.method,args.analysis, args.model + postfix, args.fit_function, args.fileFormat.lower())
if args.timesAE:
fileName = fileName.replace("xs_limit", "xsAE_limit")
c.SaveAs(fileName)
print "Plot saved to '%s'"%(fileName)
graph_obs.Print("all")
if args.saveObjects:
output_file = args.saveObjects
if args.timesAE:
output_file = output_file.replace(".root", "_timesAE.root")
f = TFile(output_file, "RECREATE")
if args.method == "Asymptotic" or args.method == "HybridNewGrid":
graph_exp_2sigma.SetName("graph_exp_2sigma")
graph_exp_2sigma.Write()
graph_exp_1sigma.SetName("graph_exp_1sigma")
graph_exp_1sigma.Write()
graph_exp.SetName("graph_exp")
graph_exp.Write()
graph_obs.SetName("graph_obs")
graph_obs.Write()
f.Close()
def setTDRStyle(force):
gStyle.SetCanvasBorderMode(0)
gStyle.SetCanvasColor(kWhite)
gStyle.SetCanvasDefH(600)
gStyle.SetCanvasDefW(600)
gStyle.SetCanvasDefX(0)
gStyle.SetCanvasDefY(0)
gStyle.SetPadBorderMode(0)
gStyle.SetPadColor(kWhite)
gStyle.SetPadGridX(False)
gStyle.SetPadGridY(False)
gStyle.SetGridColor(0)
gStyle.SetGridStyle(3)
gStyle.SetGridWidth(1)
gStyle.SetFrameBorderMode(0)
gStyle.SetFrameBorderSize(1)
gStyle.SetFrameFillColor(0)
gStyle.SetFrameFillStyle(0)
gStyle.SetFrameLineColor(1)
gStyle.SetFrameLineStyle(1)
gStyle.SetFrameLineWidth(1)
if force:
gStyle.SetHistLineColor(1)
gStyle.SetHistLineStyle(0)
gStyle.SetHistLineWidth(1)
gStyle.SetEndErrorSize(2)
gStyle.SetErrorX(0.)
gStyle.SetMarkerStyle(20)
gStyle.SetOptFit(1)
gStyle.SetFitFormat("5.4g")
gStyle.SetFuncColor(2)
gStyle.SetFuncStyle(1)
gStyle.SetFuncWidth(1)
gStyle.SetOptDate(0)
gStyle.SetOptFile(0)
gStyle.SetOptStat(0)
gStyle.SetStatColor(kWhite)
gStyle.SetStatFont(42)
gStyle.SetStatFontSize(0.04)
gStyle.SetStatTextColor(1)
gStyle.SetStatFormat("6.4g")
gStyle.SetStatBorderSize(1)
gStyle.SetStatH(0.1)
gStyle.SetStatW(0.2)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.13)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadRightMargin(0.04)
gStyle.SetOptTitle(0)
gStyle.SetTitleFont(42)
gStyle.SetTitleColor(1)
gStyle.SetTitleTextColor(1)
gStyle.SetTitleFillColor(10)
gStyle.SetTitleFontSize(0.05)
gStyle.SetTitleColor(1, "XYZ")
gStyle.SetTitleFont(42, "XYZ")
gStyle.SetTitleSize(0.06, "XYZ")
gStyle.SetTitleXOffset(0.9)
gStyle.SetTitleYOffset(1.25)
gStyle.SetLabelColor(1, "XYZ")
gStyle.SetLabelFont(42, "XYZ")
gStyle.SetLabelOffset(0.007, "XYZ")
gStyle.SetLabelSize(0.05, "XYZ")
gStyle.SetAxisColor(1, "XYZ")
gStyle.SetStripDecimals(True)
gStyle.SetTickLength(0.03, "XYZ")
gStyle.SetNdivisions(510, "XYZ")
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
gStyle.SetOptLogx(0)
gStyle.SetOptLogy(0)
gStyle.SetOptLogz(0)
gStyle.SetPaperSize(20.,20.)
gROOT.ForceStyle()
def initialize2(self):
# For the canvas:
gStyle.SetCanvasBorderMode(0)
gStyle.SetCanvasColor(kWhite)
gStyle.SetCanvasDefH(600) #Height of canvas
gStyle.SetCanvasDefW(600) #Width of canvas
gStyle.SetCanvasDefX(0) #POsition on screen
gStyle.SetCanvasDefY(0)
# For the Pad:
gStyle.SetPadBorderMode(0)
# gStyle.SetPadBorderSize(Width_t size = 1)
gStyle.SetPadColor(kWhite)
gStyle.SetPadGridX(False)
gStyle.SetPadGridY(False)
gStyle.SetGridColor(0)
gStyle.SetGridStyle(3)
gStyle.SetGridWidth(1)
# For the frame:
gStyle.SetFrameBorderMode(0)
gStyle.SetFrameBorderSize(1)
gStyle.SetFrameFillStyle(1000)
gStyle.SetFrameFillColor(0)
gStyle.SetFrameFillStyle(0)
gStyle.SetFrameLineColor(1)
gStyle.SetFrameLineStyle(1)
gStyle.SetFrameLineWidth(1)
# For the histo:
# gStyle.SetHistFillColor(1)
# gStyle.SetHistFillStyle(0)
gStyle.SetHistLineColor(1)
gStyle.SetHistLineStyle(0)
gStyle.SetHistLineWidth(1)
# gStyle.SetLegoInnerR(Float_t rad = 0.5)
# gStyle.SetNumberContours(Int_t number = 20)
gStyle.SetEndErrorSize(2)
# gStyle.SetErrorMarker(20)
gStyle.SetErrorX(0.)
gStyle.SetMarkerStyle(20)
#For the fit/function:
gStyle.SetOptFit(1)
gStyle.SetFitFormat("5.4g")
gStyle.SetFuncColor(2)
gStyle.SetFuncStyle(1)
gStyle.SetFuncWidth(1)
#For the date:
gStyle.SetOptDate(0)
# gStyle.SetDateX(Float_t x = 0.01)
# gStyle.SetDateY(Float_t y = 0.01)
# For the statistics box:
gStyle.SetOptFile(0)
gStyle.SetOptStat(
0) # To display the mean and RMS: SetOptStat("mr")
gStyle.SetStatColor(kWhite)
gStyle.SetStatFont(42)
gStyle.SetStatFontSize(0.025)
gStyle.SetStatTextColor(1)
gStyle.SetStatFormat("6.4g")
gStyle.SetStatBorderSize(1)
gStyle.SetStatH(0.1)
gStyle.SetStatW(0.15)
# gStyle.SetStatStyle(Style_t style = 1001)
# gStyle.SetStatX(Float_t x = 0)
# gStyle.SetStatY(Float_t y = 0)
# Margins:
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.13)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadRightMargin(0.02)
# For the Global title:
gStyle.SetOptTitle(0)
gStyle.SetTitleFont(42)
gStyle.SetTitleColor(1)
gStyle.SetTitleTextColor(1)
gStyle.SetTitleFillColor(10)
gStyle.SetTitleFontSize(0.05)
# gStyle.SetTitleH(0) # Set the height of the title box
# gStyle.SetTitleW(0) # Set the width of the title box
# gStyle.SetTitleX(0) # Set the position of the title box
# gStyle.SetTitleY(0.985) # Set the position of the title box
# gStyle.SetTitleStyle(Style_t style = 1001)
# gStyle.SetTitleBorderSize(2)
# For the axis titles:
gStyle.SetTitleColor(1, "XYZ")
gStyle.SetTitleFont(42, "XYZ")
gStyle.SetTitleSize(0.06, "XYZ")
# gStyle.SetTitleXSize(Float_t size = 0.02) # Another way to set the size?
# gStyle.SetTitleYSize(Float_t size = 0.02)
gStyle.SetTitleXOffset(0.9)
gStyle.SetTitleYOffset(1.25)
# gStyle.SetTitleOffset(1.1, "Y") # Another way to set the Offset
# For the axis labels:
gStyle.SetLabelColor(1, "XYZ")
gStyle.SetLabelFont(42, "XYZ")
gStyle.SetLabelOffset(0.007, "XYZ")
gStyle.SetLabelSize(0.05, "XYZ")
# For the axis:
gStyle.SetAxisColor(1, "XYZ")
gStyle.SetStripDecimals(True)
gStyle.SetTickLength(0.03, "XYZ")
gStyle.SetNdivisions(510, "XYZ")
gStyle.SetPadTickX(
1) # To get tick marks on the opposite side of the frame
gStyle.SetPadTickY(1)
# Change for log plots:
gStyle.SetOptLogx(0)
gStyle.SetOptLogy(0)
gStyle.SetOptLogz(0)
# Postscript options:
gStyle.SetPaperSize(20., 20.)
def rootStyle(batchMode=True):
from ROOT import gROOT, gStyle, kWhite, kBlack
# No info messages
gROOT.ProcessLine("gErrorIgnoreLevel = kWarning;")
# Batch mode (no TCanvas)
gROOT.SetBatch(batchMode)
# Start from a plain default
gROOT.SetStyle("Plain")
lhcbMarkerType = 8
lhcbMarkerSize = 0.8
lhcbFont = 62
lhcbStatFontSize = 0.02
lhcbStatBoxWidth = 0.12
lhcbStatBoxHeight = 0.12
lhcbWidth = 1
lhcbTextSize = 0.05
lhcbLabelSize = 0.035
lhcbAxisLabelSize = 0.035
lhcbForeColour = kBlack
gStyle.SetFrameBorderMode(0)
gStyle.SetPadBorderMode(0)
# canvas options
gStyle.SetCanvasBorderSize(0)
gStyle.SetCanvasBorderMode(0)
# fonts
gStyle.SetTextFont(lhcbFont)
gStyle.SetTextSize(lhcbTextSize)
gStyle.SetLabelFont(lhcbFont, "x")
gStyle.SetLabelFont(lhcbFont, "y")
gStyle.SetLabelFont(lhcbFont, "z")
gStyle.SetLabelSize(lhcbLabelSize, "x")
gStyle.SetLabelSize(lhcbLabelSize, "y")
gStyle.SetLabelSize(lhcbLabelSize, "z")
gStyle.SetTitleFont(lhcbFont)
gStyle.SetTitleSize(lhcbAxisLabelSize, "x")
gStyle.SetTitleSize(lhcbAxisLabelSize, "y")
gStyle.SetTitleSize(lhcbAxisLabelSize, "z")
gStyle.SetTitleColor(kWhite)
gStyle.SetTitleFillColor(kWhite)
gStyle.SetTitleColor(kBlack)
gStyle.SetTitleBorderSize(0)
gStyle.SetTitleTextColor(kBlack)
# set title position
gStyle.SetTitleX(0.15)
gStyle.SetTitleY(0.97)
# turn off Title box
gStyle.SetTitleBorderSize(0)
gStyle.SetTitleTextColor(lhcbForeColour)
gStyle.SetTitleColor(lhcbForeColour)
# use bold lines and markers
gStyle.SetLineWidth(lhcbWidth)
gStyle.SetFrameLineWidth(lhcbWidth)
gStyle.SetHistLineWidth(lhcbWidth)
gStyle.SetFuncWidth(lhcbWidth)
gStyle.SetGridWidth(lhcbWidth)
gStyle.SetLineStyleString(2, "[12 12]")
gStyle.SetMarkerStyle(lhcbMarkerType)
gStyle.SetMarkerSize(lhcbMarkerSize)
# label offsets
gStyle.SetLabelOffset(0.015)
# by default, do not display histogram decorations:
gStyle.SetOptStat(1111)
# show probability, parameters and errors
gStyle.SetOptFit(1011)
# look of the statistics box:
gStyle.SetStatBorderSize(1)
gStyle.SetStatFont(lhcbFont)
gStyle.SetStatFontSize(lhcbStatFontSize)
gStyle.SetStatX(0.9)
gStyle.SetStatY(0.9)
gStyle.SetStatW(lhcbStatBoxWidth)
gStyle.SetStatH(lhcbStatBoxHeight)
# put tick marks on top and RHS of plots
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
# histogram divisions
gStyle.SetNdivisions(505, "x")
gStyle.SetNdivisions(510, "y")
# Force the style
gROOT.ForceStyle()
def setStyle():
gStyle.SetPadBorderMode(0)
gStyle.SetFrameBorderMode(0)
gStyle.SetPadBottomMargin(0.12)
gStyle.SetPadLeftMargin(0.12)
gStyle.SetCanvasColor(ROOT.kWhite)
gStyle.SetCanvasDefH(600)
#Height of canvas
gStyle.SetCanvasDefW(600)
#Width of canvas
gStyle.SetCanvasDefX(0)
#POsition on screen
gStyle.SetCanvasDefY(0)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.15)
#0.13);
gStyle.SetPadLeftMargin(0.11)
#0.16);
gStyle.SetPadRightMargin(0.05)
#0.02);
# For the Pad:
gStyle.SetPadBorderMode(0)
gStyle.SetPadColor(ROOT.kWhite)
gStyle.SetPadGridX(ROOT.kFALSE)
gStyle.SetPadGridY(ROOT.kFALSE)
gStyle.SetGridColor(0)
gStyle.SetGridStyle(3)
gStyle.SetGridWidth(1)
# For the frame:
gStyle.SetFrameBorderMode(0)
gStyle.SetFrameBorderSize(1)
gStyle.SetFrameFillColor(0)
gStyle.SetFrameFillStyle(0)
gStyle.SetFrameLineColor(1)
gStyle.SetFrameLineStyle(1)
gStyle.SetFrameLineWidth(1)
gStyle.SetAxisColor(1, "XYZ")
gStyle.SetStripDecimals(ROOT.kTRUE)
gStyle.SetTickLength(0.03, "XYZ")
gStyle.SetNdivisions(505, "XYZ")
gStyle.SetPadTickX(1)
# To get tick marks on the opposite side of the frame
gStyle.SetPadTickY(1)
gStyle.SetGridColor(0)
gStyle.SetGridStyle(3)
gStyle.SetGridWidth(1)
gStyle.SetTitleColor(1, "XYZ")
gStyle.SetTitleFont(42, "XYZ")
gStyle.SetTitleSize(0.05, "XYZ")
gStyle.SetTitleXOffset(1.15)
#0.9);
gStyle.SetTitleYOffset(1.3)
# => 1.15 if exponents
gStyle.SetLabelColor(1, "XYZ")
gStyle.SetLabelFont(42, "XYZ")
gStyle.SetLabelOffset(0.007, "XYZ")
gStyle.SetLabelSize(0.045, "XYZ")
gStyle.SetPadBorderMode(0)
gStyle.SetFrameBorderMode(0)
gStyle.SetTitleTextColor(1)
gStyle.SetTitleFillColor(10)
gStyle.SetTitleFontSize(0.05)
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
gStyle.SetOptFit(1)
NRGBs = 5
NCont = 255
stops = [0.00, 0.34, 0.61, 0.84, 1.00]
red = [0.00, 0.00, 0.87, 1.00, 0.51]
green = [0.00, 0.81, 1.00, 0.20, 0.00]
blue = [0.51, 1.00, 0.12, 0.00, 0.00]
stopsArray = array('d', stops)
redArray = array('d', red)
greenArray = array('d', green)
blueArray = array('d', blue)
TColor.CreateGradientColorTable(NRGBs, stopsArray, redArray, greenArray,
blueArray, NCont)
gStyle.SetNumberContours(NCont)
def set_root_env():
#//TStyle* genieStyle = new TStyle("genieStyle", "GENIE Style")
#//set the background color to white
gStyle.SetFillColor(10)
gStyle.SetFrameFillColor(10)
gStyle.SetCanvasColor(10)
gStyle.SetPadColor(10)
gStyle.SetTitleFillColor(0)
gStyle.SetStatColor(10)
#dont put a colored frame around the plots
gStyle.SetFrameBorderMode(0)
gStyle.SetCanvasBorderMode(0)
gStyle.SetPadBorderMode(0)
gStyle.SetLegendBorderSize(3)
#use the primary color palette
#gStyle.SetPalette(1,0)
#set the default line color for a histogram to be black
gStyle.SetHistLineColor(ROOT.kBlack)
#set the default line color for a fit function to be red
gStyle.SetFuncColor(ROOT.kRed)
#make the axis labels black
gStyle.SetLabelColor(ROOT.kBlack, "xyz")
#set the default title color to be black
gStyle.SetTitleColor(ROOT.kBlack)
#set the margins
gStyle.SetPadBottomMargin(0.18)
gStyle.SetPadTopMargin(0.08)
gStyle.SetPadRightMargin(0.08)
gStyle.SetPadLeftMargin(0.17)
#set axis label and title text sizes
gStyle.SetLabelFont(42, "xyz")
gStyle.SetLabelSize(0.04, "xyz")
gStyle.SetLabelOffset(0.015, "xyz")
gStyle.SetTitleFont(42, "xyz")
gStyle.SetTitleSize(0.04, "xyz")
gStyle.SetTitleOffset(1.4, "y")
gStyle.SetTitleOffset(1.3, "x")
gStyle.SetStatFont(42)
gStyle.SetStatFontSize(0.07)
gStyle.SetTitleBorderSize(1)
gStyle.SetStatBorderSize(0)
gStyle.SetTextFont(42)
gStyle.SetTitleW(0.5)
gStyle.SetTitleH(0.1)
#set line widths
gStyle.SetFrameLineWidth(2)
gStyle.SetFuncWidth(2)
gStyle.SetHistLineWidth(2)
#set the number of divisions to show
gStyle.SetNdivisions(506, "xy")
#gStyle.SetPadTickX(-50202)
#turn off xy grids
gStyle.SetPadGridX(0)
gStyle.SetPadGridY(0)
#set the tick mark style
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
#turn off stats
gStyle.SetOptStat(0)
gStyle.SetOptFit(0)
#marker/line settings
#gStyle.SetMarkerStyle(20)
gStyle.SetMarkerSize(.95) #0.7
gStyle.SetLineWidth(2)
gStyle.SetErrorX(0)
gStyle.SetHistLineStyle(0) #It was 3 for a dotted line
#done
gStyle.cd()
gROOT.ForceStyle()
# pylint: disable=missing-function-docstring, missing-class-docstring
# pylint: disable=fixme
import datetime
import numpy as np
from root_numpy import fill_hist # pylint: disable=import-error
from ROOT import TH1F, TH2F, TFile, TCanvas, TLegend, TPaveText, gPad # pylint: disable=import-error, no-name-in-module
from ROOT import gStyle, kWhite, kBlue, kGreen, kRed, kCyan, kOrange, kMagenta # pylint: disable=import-error, no-name-in-module
from ROOT import gROOT # pylint: disable=import-error, no-name-in-module
gROOT.SetStyle("Plain")
gROOT.SetBatch()
gStyle.SetOptStat(0)
gStyle.SetTextFont(42)
gStyle.SetLabelFont(42, "xyz")
gStyle.SetTitleFont(42, "xyz")
def create_apply_histos(config, suffix, infix=""):
h_dist = TH2F("%s_%s%s" % (config.h_dist_name, infix, suffix),
"", 500, -5, 5, 500, -5, 5)
h_deltas = TH1F("%s_%s%s" % (config.h_deltas_name, infix, suffix), "", 1000, -1., 1.)
h_deltas_vs_dist = TH2F("%s_%s%s" % \
(config.h_deltas_vs_dist_name, infix, suffix),
"", 500, -5.0, 5.0, 100, -0.5, 0.5)
return h_dist, h_deltas, h_deltas_vs_dist
def fill_std_dev_apply_hist(h_deltas_vs_dist, hist_name, suffix, infix=""):
h1tmp = h_deltas_vs_dist.ProjectionX("h1tmp")
h_std_dev = h1tmp.Clone("%s_%s%s" % (hist_name, infix, suffix))
h_std_dev.Reset()
def setStyle():
gStyle.SetCanvasColor(0)
gStyle.SetCanvasBorderSize(10)
gStyle.SetCanvasBorderMode(0)
gStyle.SetCanvasDefH(700)
gStyle.SetCanvasDefW(700)
gStyle.SetPadColor(0)
gStyle.SetPadBorderSize(10)
gStyle.SetPadBorderMode(0)
gStyle.SetPadBottomMargin(0.13)
gStyle.SetPadTopMargin(0.08)
gStyle.SetPadLeftMargin(0.15)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadGridX(0)
gStyle.SetPadGridY(0)
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
gStyle.SetFrameFillStyle(0)
gStyle.SetFrameFillColor(0)
gStyle.SetFrameLineColor(1)
gStyle.SetFrameLineStyle(0)
gStyle.SetFrameLineWidth(1)
gStyle.SetFrameBorderSize(10)
gStyle.SetFrameBorderMode(0)
gStyle.SetNdivisions(505)
gStyle.SetLineWidth(2)
gStyle.SetHistLineWidth(2)
gStyle.SetFrameLineWidth(2)
gStyle.SetLegendFillColor(root.kWhite)
gStyle.SetLegendFont(42)
gStyle.SetMarkerSize(1.2)
gStyle.SetMarkerStyle(20)
gStyle.SetLabelSize(0.040, "X")
gStyle.SetLabelSize(0.040, "Y")
gStyle.SetLabelOffset(0.010, "X")
gStyle.SetLabelOffset(0.010, "Y")
gStyle.SetLabelFont(42, "X")
gStyle.SetLabelFont(42, "Y")
gStyle.SetTitleBorderSize(0)
gStyle.SetTitleFont(42)
gStyle.SetTitleFont(42, "X")
gStyle.SetTitleFont(42, "Y")
gStyle.SetTitleSize(0.045, "X")
gStyle.SetTitleSize(0.045, "Y")
gStyle.SetTitleOffset(1.4, "X")
gStyle.SetTitleOffset(1.4, "Y")
gStyle.SetTextSize(0.055)
gStyle.SetTextFont(42)
gStyle.SetOptStat(0)
def CLICdpStyle():
gROOT.SetStyle("Plain")
gStyle.SetCanvasColor(root.kWhite)
gStyle.SetFrameFillColor(root.kWhite)
gStyle.SetStatColor(root.kWhite)
gStyle.SetPadColor(root.kWhite)
gStyle.SetFillColor(10)
gStyle.SetTitleFillColor(root.kWhite)
gStyle.SetPaperSize(20, 26)
gStyle.SetDrawBorder(0)
gStyle.SetCanvasBorderMode(0)
gStyle.SetPadBorderMode(0)
gStyle.SetFrameBorderMode(0)
gStyle.SetLegendBorderSize(0)
gStyle.SetTextSize(0.05)
gStyle.SetTitleSize(0.06, "xyz")
gStyle.SetLabelSize(0.06, "xyz")
gStyle.SetLabelOffset(0.015, "xyz")
gStyle.SetTitleOffset(1.2, "yz")
gStyle.SetTitleOffset(1.17, "x")
font = 42
gStyle.SetTitleFont(font)
gStyle.SetTitleFontSize(0.06)
gStyle.SetStatFont(font)
gStyle.SetStatFontSize(0.07)
gStyle.SetTextFont(font)
gStyle.SetLabelFont(font, "xyz")
gStyle.SetTitleFont(font, "xyz")
gStyle.SetTitleBorderSize(0)
gStyle.SetStatBorderSize(1)
gStyle.SetMarkerStyle(1)
gStyle.SetLineWidth(2)
gStyle.SetMarkerSize(1.2)
gStyle.SetPalette(1)
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
gStyle.SetOptFit(0)
gStyle.SetEndErrorSize(5)
gStyle.SetHistLineWidth(2)
gStyle.SetFrameLineWidth(2)
gStyle.SetFuncWidth(2)
gStyle.SetHistLineColor(root.kBlack)
gStyle.SetFuncColor(root.kBlack)
gStyle.SetLabelColor(root.kBlack, "xyz")
gStyle.SetPadBottomMargin(0.18)
gStyle.SetPadTopMargin(0.11)
gStyle.SetPadRightMargin(0.08)
gStyle.SetPadLeftMargin(0.17)
gStyle.SetNdivisions(506, "xy")
gStyle.SetPadGridX(0)
gStyle.SetPadGridY(0)
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
gStyle.SetCanvasDefW(800)
gStyle.SetCanvasDefH(700)
gROOT.ForceStyle()
def main(options, args):
from ROOT import gSystem, gROOT, gStyle
gROOT.SetBatch()
gSystem.Load("libRooFitCore")
if options.doWebPage:
from lip.Tools.rootutils import loadToolsLib, apply_modifs
loadToolsLib()
from ROOT import TFile, RooFit, RooArgSet, RooDataHist, RooKeysPdf, RooHistPdf, TCanvas, TLegend, TLatex, TArrow, TPaveText, RooAddPdf, RooArgList
from ROOT import kWhite, kBlue, kOpenSquare
if options.doWebPage:
from ROOT import HtmlHelper, HtmlTag, HtmlTable, HtmlPlot
rootglobestyle.setTDRStyle()
gStyle.SetMarkerSize(1.5)
gStyle.SetTitleYOffset(1.5)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.13)
gStyle.SetLabelFont(42, "XYZ")
gStyle.SetLabelOffset(0.007, "XYZ")
gStyle.SetLabelSize(0.05, "XYZ")
gStyle.SetTitleSize(0.06, "XYZ")
gStyle.SetTitleXOffset(0.9)
gStyle.SetTitleYOffset(1.24)
gStyle.SetTitleFont(42, "XYZ")
##
## Read files
##
options.outdir = "%s_m%1.0f" % (options.outdir, options.mH)
if options.fp:
options.outdir += "_fp"
ncat = options.ncat
cats = options.cats
if cats is "":
categories = ["_cat%d" % i for i in range(0, ncat)]
else:
categories = ["_cat%s" % i for i in cats.split(",")]
if options.mva:
clables = {
"_cat0": ("MVA > 0.89", ""),
"_cat1": ("0.74 #leq MVA", "MVA < 0.89"),
"_cat2": ("0.545 #leq MVA", "MVA < 0.74"),
"_cat3": ("0.05 #leq MVA", "MVA < 0.545"),
"_cat4": ("Di-jet", "Tagged"),
"_cat5": ("Di-jet", "Tagged"),
"_combcat": ("All Classes", "Combined")
}
else:
clables = {
"_cat0": ("max(|#eta|<1.5", "min(R_{9})>0.94"),
"_cat1": ("max(|#eta|<1.5", "min(R_{9})<0.94"),
"_cat2": ("max(|#eta|>1.5", "min(R_{9})>0.94"),
"_cat3": ("max(|#eta|>1.5", "min(R_{9})<0.94"),
"_cat4": ("Di-jet", "Tagged"),
"_cat5": ("Di-jet", "Tagged"),
"_combcat": ("All Classes", "Combined")
}
helper = Helper()
fin = TFile.Open(options.infile)
helper.files.append(fin)
ws = fin.Get("cms_hgg_workspace")
mass = ws.var("CMS_hgg_mass")
mass.SetTitle("m_{#gamma#gamma}")
mass.setUnit("GeV")
mass.setRange(100., 150.)
mass.setBins(100, "plot")
mass.setBins(5000)
print ws
aset = RooArgSet(mass)
helper.objs.append(mass)
helper.objs.append(aset)
fitopt = (RooFit.Minimizer("Minuit2", ""), RooFit.Minos(False),
RooFit.SumW2Error(False), RooFit.NumCPU(8))
if not options.binned and not options.refit:
finpdf = TFile.Open(options.infilepdf)
helper.files.append(finpdf)
wspdf = finpdf.Get("wsig")
else:
wspdf = ws
for c in categories:
processes = ["ggh", "vbf", "wzh"]
if options.fp:
processes = ["vbf", "wzh"]
### elif clables[c][0] == "Di-jet":
### processes = [ "vbf", "ggh" ]
dsname = "sig_mass_m%1.0f%s" % (options.mH, c)
print dsname
print ws
ds = ws.data("sig_%s_mass_m%1.0f%s" %
(processes[0], options.mH, c)).Clone(dsname)
for proc in processes[1:]:
ds.append(ws.data("sig_%s_mass_m%1.0f%s" % (proc, options.mH, c)))
helper.dsets.append(ds)
if options.binned:
binned_ds = RooDataHist("binned_%s" % dsname, "binned_%s" % dsname,
aset, ds)
pdf = RooKeysPdf("pdf_%s_%s" % (dsname, f), "pdf_%s" % dsname,
mass, ds)
plot_pdf = RooHistPdf("pdf_%s" % dsname, "pdf_%s" % dsname, aset,
plot_ds)
helper.add(binned_ds, binned_ds.GetName())
else:
if options.refit:
if options.refitall and clables[c][0] != "Di-jet":
rpdfs = []
for proc in processes:
for ngaus in range(1, 4):
pp = build_pdf(ws, "%s_%s" % (c, proc), ngaus,
ngaus == 3)
pp.fitTo(
ws.data("sig_%s_mass_m%1.0f%s" %
(proc, options.mH, c)),
RooFit.Strategy(0), *fitopt)
rpdfs.append(pp)
pdf = RooAddPdf("hggpdfrel%s" % c, "hggpdfrel%s" % c,
RooArgList(*tuple(rpdfs)))
else:
if options.refitall and clables[c][0] == "Di-jet":
for ngaus in range(1, 5):
pdf = build_pdf(ws, c, ngaus, ngaus == 5)
pdf.fitTo(ds, RooFit.Strategy(0), *fitopt)
else:
for ngaus in range(1, 4):
pdf = build_pdf(ws, c, ngaus, ngaus == 3)
pdf.fitTo(ds, RooFit.Strategy(0), *fitopt)
else:
pdfs = (wspdf.pdf("hggpdfrel%s_%s" % (c, p))
for p in processes)
pdf = RooAddPdf("hggpdfrel%s" % c, "hggpdfrel%s" % c,
RooArgList(*pdfs))
helper.add(pdf, pdf.GetName())
plot_pdf = pdf.Clone("pdf_%s" % dsname)
plot_ds = RooDataHist("plot_%s" % dsname, "plot_%s" % dsname, aset,
"plot")
plot_ds.add(ds)
cdf = pdf.createCdf(aset)
hmin, hmax, hm = get_FWHM(mass, pdf, cdf, options.mH - 10.,
options.mH + 10.)
wmin, wmax = get_eff_sigma(mass, pdf, cdf, options.mH - 10.,
options.mH + 10.)
### hmin, hmax, hm = get_FWHM( points )
helper.add(plot_ds, plot_ds.GetName())
helper.add(plot_pdf, plot_pdf.GetName())
helper.add((wmin, wmax), "eff_sigma%s" % c)
helper.add((hmin, hmax, hm), "FWHM%s" % c)
helper.add(ds.sumEntries(),
"sumEntries%s" % c) # signal model integral
# data integral for PAS tables
data = ws.data("data_mass%s" % c)
helper.add(
data.sumEntries("CMS_hgg_mass>=%1.4f && CMS_hgg_mass<=%1.4f" %
(options.mH - 10., options.mH + 10.)),
"data_sumEntries%s" % c)
del cdf
del pdf
dsname = "sig_mass_m%1.0f_combcat" % options.mH
print dsname
combined_ds = helper.dsets[0].Clone(dsname)
for d in helper.dsets[1:]:
combined_ds.append(d)
if options.binned:
binned_ds = RooDataHist("binned_%s" % dsname, "binned_%s" % dsname,
aset, combined_ds)
pdf = RooKeysPdf("pdf_%s" % (dsname), "pdf_%s" % dsname, mass,
combined_ds)
plot_pdf = RooHistPdf("pdf_%s" % dsname, "pdf_%s" % dsname, aset,
plot_ds)
helper.add(binned_ds, binned_ds.GetName())
else:
#### pdf = build_pdf(ws,"_combcat")
#### pdf.fitTo(combined_ds, RooFit.Strategy(0), *fitopt )
#### plot_pdf = pdf.Clone( "pdf_%s" % dsname )
pdf = RooAddPdf(
"pdf_%s" % dsname, "pdf_%s" % dsname,
RooArgList(*(helper.histos["hggpdfrel%s" % c]
for c in categories)))
plot_pdf = pdf
cdf = pdf.createCdf(aset)
plot_ds = RooDataHist("plot_%s" % dsname, "plot_%s" % dsname, aset, "plot")
plot_ds.add(combined_ds)
wmin, wmax = get_eff_sigma(mass, pdf, cdf, options.mH - 10.,
options.mH + 10.)
hmin, hmax, hm = get_FWHM(mass, pdf, cdf, options.mH - 10.,
options.mH + 10.)
helper.add(plot_ds, plot_ds.GetName())
helper.add(plot_pdf, plot_pdf.GetName())
helper.add((wmin, wmax), "eff_sigma_combcat")
helper.add((hmin, hmax, hm), "FWHM_combcat")
helper.add(plot_ds.sumEntries(), "sumEntries_combcat")
mass.setRange("higgsrange", options.mH - 25., options.mH + 15.)
del cdf
del pdf
del helper.dsets
### label = TLatex(0.1812081,0.8618881,"#scale[0.8]{#splitline{CMS preliminary}{Simulation}}")
label = TLatex(0.7, 0.86,
"#scale[0.65]{#splitline{CMS preliminary}{Simulation}}")
label.SetNDC(1)
##
## Make web page with plots
##
if options.doWebPage:
hth = HtmlHelper(options.outdir)
hth.navbar().cell(HtmlTag("a")).firstChild().txt("..").set(
"href", "../?C=M;O=D")
hth.navbar().cell(HtmlTag("a")).firstChild().txt("home").set(
"href", "./")
tab = hth.body().add(HtmlTable())
ip = 0
for c in ["_combcat"] + categories:
### for c in categories:
if options.doWebPage and ip % 4 == 0:
row = tab.row()
ip = ip + 1
dsname = "sig_mass_m%1.0f%s" % (options.mH, c)
canv = TCanvas(dsname, dsname, 600, 600)
helper.objs.append(canv)
### leg = TLegend(0.4345638,0.6835664,0.9362416,0.9178322)
leg = TLegend(0.2, 0.96, 0.5, 0.55)
#apply_modifs( leg, [("SetLineColor",kWhite),("SetFillColor",kWhite),("SetFillStyle",0),("SetLineStyle",0)] )
hplotcompint = mass.frame(RooFit.Bins(250), RooFit.Range("higgsrange"))
helper.objs.append(hplotcompint)
helper.objs.append(leg)
plot_ds = helper.histos["plot_%s" % dsname]
plot_pdf = helper.histos["pdf_%s" % dsname]
wmin, wmax = helper.histos["eff_sigma%s" % c]
hmin, hmax, hm = helper.histos["FWHM%s" % c]
print hmin, hmax, hm
style = (RooFit.LineColor(kBlue), RooFit.LineWidth(2),
RooFit.FillStyle(0))
style_seff = (
RooFit.LineWidth(2),
RooFit.FillStyle(1001),
RooFit.VLines(),
RooFit.LineColor(15),
)
style_ds = (RooFit.MarkerStyle(kOpenSquare), )
plot_ds.plotOn(hplotcompint, RooFit.Invisible())
plot_pdf.plotOn(hplotcompint, RooFit.NormRange("higgsrange"),
RooFit.Range(wmin, wmax), RooFit.FillColor(19),
RooFit.DrawOption("F"), *style_seff)
seffleg = hplotcompint.getObject(int(hplotcompint.numItems() - 1))
plot_pdf.plotOn(hplotcompint, RooFit.NormRange("higgsrange"),
RooFit.Range(wmin, wmax), RooFit.LineColor(15),
*style_seff)
plot_pdf.plotOn(hplotcompint, RooFit.NormRange("higgsrange"),
RooFit.Range("higgsrange"), *style)
pdfleg = hplotcompint.getObject(int(hplotcompint.numItems() - 1))
plot_ds.plotOn(hplotcompint, *style_ds)
pointsleg = hplotcompint.getObject(int(hplotcompint.numItems() - 1))
iob = int(hplotcompint.numItems() - 1)
leg.AddEntry(pointsleg, "Simulation", "pe")
leg.AddEntry(pdfleg, "Parametric model", "l")
leg.AddEntry(seffleg,
"#sigma_{eff} = %1.2f GeV " % (0.5 * (wmax - wmin)), "fl")
clabel = TLatex(0.74, 0.65,
"#scale[0.65]{#splitline{%s}{%s}}" % clables[c])
clabel.SetNDC(1)
helper.objs.append(clabel)
hm = hplotcompint.GetMaximum() * 0.5 * 0.9
### hm = pdfleg.GetMaximum()*0.5
fwhmarrow = TArrow(hmin, hm, hmax, hm)
fwhmarrow.SetArrowSize(0.03)
helper.objs.append(fwhmarrow)
fwhmlabel = TPaveText(0.20, 0.58, 0.56, 0.48, "brNDC")
fwhmlabel.SetFillStyle(0)
fwhmlabel.SetLineColor(kWhite)
reducedFWHM = (hmax - hmin) / 2.3548200
fwhmlabel.AddText("FWHM/2.35 = %1.2f GeV" % reducedFWHM)
helper.objs.append(fwhmlabel)
hplotcompint.SetTitle("")
hplotcompint.GetXaxis().SetNoExponent(True)
hplotcompint.GetXaxis().SetTitle("m_{#gamma#gamma} (GeV)")
hplotcompint.GetXaxis().SetNdivisions(509)
## hplotcompint.GetYaxis().SetTitle("A.U.");
## hplotcompint.GetYaxis().SetRangeUser(0.,hplotcompint.GetMaximum()*1.4);
hplotcompint.Draw()
leg.Draw("same")
label.Draw("same")
clabel.Draw("same")
fwhmarrow.Draw("<>")
fwhmlabel.Draw("same")
plot_ds.sumEntries()
if options.doWebPage:
hpl = HtmlPlot(canv, False, "", True, True, True)
hpl.caption("<i>%s</i>" % canv.GetTitle())
row.cell(hpl)
else:
if os.path.isdir(options.outdir) is False:
os.mkdir(options.outdir)
for ext in "C", "png", "pdf":
canv.SaveAs(
os.path.join(options.outdir,
"%s.%s" % (canv.GetName(), ext)))
if "comb" in c:
ip = 0
if options.doWebPage:
print "Creating pages..."
hth.dump()
for f in helper.files:
f.Close()
gROOT.Reset()
from pprint import pprint
pprint(helper)
print 'Summary statistics per event class'
print 'Cat\tSignal\t\tData/GeV (in %3.1f+/-10)\tsigEff\tFWHM/2.35' % options.mH
sigTotal = 0.
dataTotal = 0.
for c in categories:
sigVal = helper.histos["sumEntries%s" % c]
datVal = helper.histos["data_sumEntries%s" % c]
sigTotal += sigVal
dataTotal += datVal
for c in categories:
sigVal = helper.histos["sumEntries%s" % c]
datVal = helper.histos["data_sumEntries%s" % c]
effSig = 0.5 * (helper.histos["eff_sigma%s" % c][1] -
helper.histos["eff_sigma%s" % c][0])
fwhm = (helper.histos["FWHM%s" % c][1] -
helper.histos["FWHM%s" % c][0]) / 2.3548200
print c, '\t%3.1f (%3.1f%%)\t%3.1f (%3.1f%%)\t\t\t%2.2f\t%2.2f' % (
sigVal, 100. * sigVal / sigTotal, datVal /
(10. + 10.), 100. * datVal / dataTotal, effSig, fwhm)
print "Done."
### style parameters
gROOT.SetStyle("Plain")
gROOT.SetBatch(True)
gStyle.SetLegendFillColor(0)
gStyle.SetLegendBorderSize(0)
gStyle.SetStatBorderSize(0)
gStyle.SetTitleBorderSize(0)
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
gStyle.SetTitleX(0.14) ## to be changed to 0.15
gStyle.SetTitleY(0.96)
gStyle.SetTitleW(0.8)
gStyle.SetTextFont(42)
gStyle.SetLegendFont(42)
gStyle.SetLabelFont(42, 'xy')
gStyle.SetTitleFont(42, 'xy')
tauScale = '0.03'
shiftedMet = 'sqrt(pow(mex+'+tauScale+'*l1Px+'+tauScale+'*l2Px,2)+pow(mey+'+tauScale+'*l1Py+'+tauScale+'*l2Py,2))'
baseline = ' l1Pt>45 && l2Pt>45 && abs(l1Eta)<2.1 && abs(l2Eta)<2.1 && diTauCharge!=0 '
#### should be redundant once skimmed
baseline += ' && l1LooseEle>0.5 && l2LooseEle>0.5 '
baseline += ' && l1LooseMu >0.5 && l2LooseMu >0.5 '
baseline += ' && l2againstElectronNewLooseMVA3>0.5 '
######################################
# baseline += ' && nbJets == 0'
baseline += ' && muon1Pt==-1 && electron1Pt==-1 '
def main():
# usage description
usage = "Example: ./scripts/plotSignificance.py -l logs -f qq --massrange 1200 6000 100"
# input parameters
parser = ArgumentParser(
description='Script that plots significance for specified mass points',
epilog=usage)
parser.add_argument('analysis', type=str, help='Analysis name')
parser.add_argument('model', type=str, help='Model name')
parser.add_argument("-M",
"--method",
dest="method",
choices=['ProfileLikelihood', 'HybridNew', 'theta'],
default='ProfileLikelihood',
help="Method to calculate upper limits",
metavar="METHOD")
parser.add_argument(
'--fit_function',
type=str,
default="dijet4",
help="Name of fit function used for background estimate")
parser.add_argument(
"--sigRange",
dest="sigRange",
type=float,
default=2.5,
help="Significance range to plot (default: %(default)f)")
parser.add_argument(
"--postfix",
dest="postfix",
default='',
help="Postfix for the output plot name (default: %(default)s)")
parser.add_argument(
"--fileFormat",
dest="fileFormat",
default='pdf',
help="Format of the output plot (default: %(default)s)")
parser.add_argument("--extraText",
dest="extraText",
default='Preliminary',
help="Extra text on the plot (default: %(default)s)")
parser.add_argument(
"--lumi_sqrtS",
dest="lumi_sqrtS",
default='19.7 fb^{-1} (13 TeV)',
help=
"Integrated luminosity and center-of-mass energy (default: %(default)s)"
)
parser.add_argument("--printResults",
dest="printResults",
default=False,
action="store_true",
help="Print results to the screen")
parser.add_argument('--fitTrigger',
action='store_true',
help="Use trigger fit")
parser.add_argument('--correctTrigger',
action='store_true',
help="Use trigger correction")
parser.add_argument('--useMCTrigger',
action='store_true',
help="Use MC trigger emulation")
parser.add_argument("--noSyst",
action="store_true",
help="Make plots for limits without systematics")
parser.add_argument(
"--freezeNuisances",
type=str,
help="Make plots for limits with frozen nuisance parameters")
mass_group = parser.add_mutually_exclusive_group(required=True)
mass_group.add_argument(
"--mass",
type=int,
nargs='*',
default=1000,
help=
"Mass can be specified as a single value or a whitespace separated list (default: %(default)i)"
)
mass_group.add_argument(
"--massrange",
type=int,
nargs=3,
help="Define a range of masses to be produced. Format: min max step",
metavar=('MIN', 'MAX', 'STEP'))
mass_group.add_argument("--masslist",
help="List containing mass information")
args = parser.parse_args()
# mass points for which resonance shapes will be produced
input_masses = []
if args.massrange != None:
MIN, MAX, STEP = args.massrange
input_masses = range(MIN, MAX + STEP, STEP)
elif args.masslist != None:
# A mass list was provided
print "Will create mass list according to", args.masslist
masslist = __import__(args.masslist.replace(".py", ""))
input_masses = masslist.masses
else:
input_masses = args.mass
# sort masses
input_masses.sort()
# arrays holding results
masses = array('d')
significances = array('d')
p0_values = array('d')
for mass in input_masses:
masses.append(mass)
#print ">> Reading results for resonance with m = %i GeV..."%(int(mass))
log_file = open(
limit_config.get_combine_log_path(
args.analysis,
args.model,
mass,
args.fit_function,
args.method,
what="significance",
systematics=(not args.noSyst),
frozen_nps=args.freezeNuisances,
fitTrigger=args.fitTrigger,
correctTrigger=args.correctTrigger,
useMCTrigger=args.useMCTrigger), 'r')
if args.method == 'theta':
logName = logName.replace('significance_', '')
# read the log file
for line in log_file:
if args.method == 'theta':
if re.search("^{'signal': {'Z':", line):
significances.append(
float(line.split()[-1].lstrip('[').rstrip('}').rstrip(
']')))
else:
if re.search("^Significance:", line):
significances.append(float(line.split()[1]))
elif re.search("^Null p-value:", line):
p0_values.append(float(line.split()[2]))
if len(masses) != len(significances):
print "** ERROR: ** Could not find significance for m =", int(
mass), "GeV. Aborting."
sys.exit(1)
if len(masses) != len(p0_values):
print "** ERROR: ** Could not find p0 value for m =", int(
mass), "GeV. Aborting."
sys.exit(1)
# Allow only positive fluctuations
if significances[-1] < 0:
significances[-1] = 0.
if args.printResults:
print "masses =", masses.tolist()
print "significances =", significances.tolist()
print "p0_values =", p0_values.tolist()
# import ROOT stuff
from ROOT import kTRUE, kFALSE, gROOT, gStyle, gPad, TGraph, TCanvas, TLegend
from ROOT import kGreen, kYellow, kWhite, kRed, kBlue
gROOT.SetBatch(kTRUE)
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
gStyle.SetTitleFont(42, "XYZ")
gStyle.SetTitleSize(0.06, "XYZ")
gStyle.SetLabelFont(42, "XYZ")
gStyle.SetLabelSize(0.05, "XYZ")
gStyle.SetCanvasBorderMode(0)
gStyle.SetFrameBorderMode(0)
gStyle.SetCanvasColor(kWhite)
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
gStyle.SetPadLeftMargin(0.15)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.15)
gROOT.ForceStyle()
graph_sig = TGraph(len(masses), masses, significances)
graph_sig.GetXaxis().SetTitle("Resonance mass [GeV]")
graph_sig.GetYaxis().SetTitle("p_0")
graph_sig.GetYaxis().SetTitleOffset(1.2)
graph_sig.GetYaxis().SetRangeUser(0., args.sigRange)
graph_sig.SetLineWidth(2)
graph_sig.SetLineColor(kRed)
graph_sig.SetMarkerStyle(21)
graph_sig.SetMarkerSize(1)
graph_sig.SetMarkerColor(kBlue)
c = TCanvas("c", "", 800, 800)
c.cd()
graph_sig.Draw("ALP")
# draw the lumi text on the canvas
CMS_lumi.extraText = args.extraText
CMS_lumi.lumi_sqrtS = args.lumi_sqrtS # used with iPeriod = 0 (free form)
iPos = 11
iPeriod = 0
CMS_lumi.CMS_lumi(c, iPeriod, iPos)
gPad.RedrawAxis()
c.SetGridx()
c.SetGridy()
fileName = limit_config.paths[
"limit_plots"] + '/significance_%s_%s_%s_%s.%s' % (
args.method, args.analysis, args.model + args.postfix,
args.fit_function, args.fileFormat.lower())
c.SaveAs(fileName)
#print "Significance plot saved to '%s'"%(fileName)
graph_p0 = TGraph(len(masses), masses, p0_values)
graph_p0.GetXaxis().SetTitle("Resonance mass [GeV]")
graph_p0.GetYaxis().SetTitle("p_{0} (local)")
graph_p0.GetYaxis().SetTitleOffset(1.2)
graph_p0.GetYaxis().SetRangeUser(1.e-3, 1.)
graph_p0.SetLineWidth(2)
graph_p0.SetLineColor(kRed)
graph_p0.SetMarkerStyle(21)
graph_p0.SetMarkerSize(1)
graph_p0.SetMarkerColor(kBlue)
c_p0 = TCanvas("c_p0", "", 800, 800)
c_p0.SetLogy()
c_p0.cd()
graph_p0.Draw("ALP")
# draw the lumi text on the canvas
# draw the lumi text on the canvas
CMS_lumi.extraText = args.extraText
CMS_lumi.lumi_sqrtS = args.lumi_sqrtS # used with iPeriod = 0 (free form)
iPos = 11
iPeriod = 0
CMS_lumi.CMS_lumi(c, iPeriod, iPos)
#Root.CMSLabel(0.2, 0.2, "Internal", 1, 0.65)
gPad.RedrawAxis()
c_p0.SetGridx()
c_p0.SetGridy()
fileName = limit_config.paths["limit_plots"] + '/p0_%s_%s_%s_%s.%s' % (
args.method, args.analysis, args.model + args.postfix,
args.fit_function, args.fileFormat.lower())
c_p0.SaveAs(fileName)
print "p0 plot saved to '%s'" % (fileName)
def main():
# usage description
usage = "Example: ./scripts/plotLimits.py -M Asymptotic -l logs -f qq --massrange 1200 7000 100"
# input parameters
parser = ArgumentParser(
description='Script that plots limits for specified mass points',
epilog=usage)
parser.add_argument("-M",
"--method",
dest="method",
required=True,
choices=[
'ProfileLikelihood', 'HybridNew', 'Asymptotic',
'MarkovChainMC', 'theta'
],
help="Method to calculate upper limits",
metavar="METHOD")
results_group = parser.add_mutually_exclusive_group(required=True)
results_group.add_argument("-l",
"--logs_path",
dest="logs_path",
help="Path to log files",
metavar="LOGS_PATH")
results_group.add_argument("-r",
"--results_file",
dest="results_file",
help="Path to a file containing results",
metavar="RESULTS_FILE")
parser.add_argument("-f",
"--final_state",
dest="final_state",
required=True,
help="Final state (e.g. qq, qg, gg)",
metavar="FINAL_STATE")
parser.add_argument(
"--postfix",
dest="postfix",
default='',
help="Postfix for the output plot name (default: %(default)s)")
parser.add_argument(
"--fileFormat",
dest="fileFormat",
default='pdf',
help="Format of the output plot (default: %(default)s)")
parser.add_argument("--extraText",
dest="extraText",
default='Simulation Preliminary',
help="Extra text on the plot (default: %(default)s)")
parser.add_argument(
"--lumi_sqrtS",
dest="lumi_sqrtS",
default='1 fb^{-1} (13 TeV)',
help=
"Integrated luminosity and center-of-mass energy (default: %(default)s)"
)
parser.add_argument("--printResults",
dest="printResults",
default=False,
action="store_true",
help="Print results to the screen")
mass_group = parser.add_mutually_exclusive_group(required=True)
mass_group.add_argument(
"--mass",
type=int,
nargs='*',
default=1000,
help=
"Mass can be specified as a single value or a whitespace separated list (default: %(default)i)"
)
mass_group.add_argument(
"--massrange",
type=int,
nargs=3,
help="Define a range of masses to be produced. Format: min max step",
metavar=('MIN', 'MAX', 'STEP'))
mass_group.add_argument("--masslist",
help="List containing mass information")
args = parser.parse_args()
# mass points for which resonance shapes will be produced
input_masses = []
if args.massrange != None:
MIN, MAX, STEP = args.massrange
input_masses = range(MIN, MAX + STEP, STEP)
elif args.masslist != None:
# A mass list was provided
print "Will create mass list according to", args.masslist
masslist = __import__(args.masslist.replace(".py", ""))
input_masses = masslist.masses
else:
input_masses = args.mass
# sort masses
input_masses.sort()
# arrays holding results
masses = array('d')
xs_obs_limits = array('d')
xs_exp_limits = array('d')
masses_exp = array('d')
xs_exp_limits_1sigma = array('d')
xs_exp_limits_1sigma_up = array('d')
xs_exp_limits_2sigma = array('d')
xs_exp_limits_2sigma_up = array('d')
if args.logs_path != None:
logs_path = os.path.join(os.getcwd(), args.logs_path)
for mass in input_masses:
print ">> Reading results for %s resonance with m = %i GeV..." % (
args.final_state, int(mass))
masses.append(mass)
if args.method == 'Asymptotic': masses_exp.append(mass)
logName = 'limits_%s_%s_m%i.log' % (args.method, args.final_state,
int(mass))
if args.method == 'theta': logName = logName.replace('limits_', '')
log_file = open(os.path.join(logs_path, logName), 'r')
foundMethod = False
# read the log file
for line in log_file:
if args.method == 'Asymptotic':
if re.search("^Observed Limit: r", line):
xs_obs_limits.append(float(line.split()[-1]))
if re.search("^Expected 50.0%: r", line):
xs_exp_limits.append(float(line.split()[-1]))
if re.search("^Expected 16.0%: r", line):
xs_exp_limits_1sigma.append(float(line.split()[-1]))
if re.search("^Expected 84.0%: r", line):
xs_exp_limits_1sigma_up.append(float(line.split()[-1]))
if re.search("^Expected 2.5%: r", line):
xs_exp_limits_2sigma.append(float(line.split()[-1]))
if re.search("^Expected 97.5%: r", line):
xs_exp_limits_2sigma_up.append(float(line.split()[-1]))
elif args.method == 'theta':
if re.search('^# x; y; yerror', line):
foundMethod = True
if line.split()[0] == '0' and foundMethod:
xs_obs_limits.append(float(line.split()[1]))
else:
if re.search(' -- ' + args.method, line):
foundMethod = True
if re.search("^Limit: r", line) and foundMethod:
xs_obs_limits.append(float(line.split()[3]))
if len(masses) != len(xs_obs_limits):
print "** ERROR: ** Could not find observed limit for m =", int(
mass), "GeV. Aborting."
sys.exit(1)
if args.method == 'Asymptotic':
if len(masses) != len(xs_exp_limits):
print "** ERROR: ** Could not find expected limit for m =", int(
mass), "GeV. Aborting."
sys.exit(1)
if len(masses) != len(xs_exp_limits_1sigma):
print "** ERROR: ** Could not find expected 1 sigma down limit for m =", int(
mass), "GeV. Aborting."
sys.exit(1)
if len(masses) != len(xs_exp_limits_1sigma_up):
print "** ERROR: ** Could not find expected 1 sigma up limit for m =", int(
mass), "GeV. Aborting."
sys.exit(1)
if len(masses) != len(xs_exp_limits_2sigma):
print "** ERROR: ** Could not find expected 2 sigma down limit for m =", int(
mass), "GeV. Aborting."
sys.exit(1)
if len(masses) != len(xs_exp_limits_2sigma_up):
print "** ERROR: ** Could not find expected 2 sigma up limit for m =", int(
mass), "GeV. Aborting."
sys.exit(1)
if args.method == 'Asymptotic':
# complete the expected limit arrays
for i in range(0, len(masses)):
masses_exp.append(masses[len(masses) - i - 1])
xs_exp_limits_1sigma.append(
xs_exp_limits_1sigma_up[len(masses) - i - 1])
xs_exp_limits_2sigma.append(
xs_exp_limits_2sigma_up[len(masses) - i - 1])
else:
print ">> Importing results..."
sys.path.insert(0, os.path.dirname(args.results_file))
results = __import__(
os.path.basename(args.results_file).replace(".py", ""))
all_masses = np.array(results.masses)
all_masses_exp = np.array(results.masses_exp)
indices = []
indices_exp = []
# search for indices of input_masses
for mass in input_masses:
where = np.where(all_masses == mass)[0]
if len(where) == 0:
print "** WARNING: ** Cannot find results for m =", int(
mass
), "GeV in the provided results file. Skipping this mass point."
indices.extend(where)
if len(all_masses_exp) > 0:
where = np.where(all_masses_exp == mass)[0]
if len(where) == 0:
print "** WARNING: ** Cannot find results for m =", int(
mass
), "GeV in the provided results file. Skipping this mass point."
indices_exp.extend(where)
# sort indices
indices.sort()
indices_exp.sort()
for i in indices:
masses.append(results.masses[i])
xs_obs_limits.append(results.xs_obs_limits[i])
if len(all_masses_exp) > 0:
xs_exp_limits.append(results.xs_exp_limits[i])
for i in indices_exp:
masses_exp.append(results.masses_exp[i])
xs_exp_limits_1sigma.append(results.xs_exp_limits_1sigma[i])
xs_exp_limits_2sigma.append(results.xs_exp_limits_2sigma[i])
if args.printResults:
print "masses =", masses.tolist()
print "xs_obs_limits =", xs_obs_limits.tolist()
print "xs_exp_limits =", xs_exp_limits.tolist()
print ""
print "masses_exp =", masses_exp.tolist()
print "xs_exp_limits_1sigma =", xs_exp_limits_1sigma.tolist()
print "xs_exp_limits_2sigma =", xs_exp_limits_2sigma.tolist()
# import ROOT stuff
from ROOT import kTRUE, kFALSE, gROOT, gStyle, gPad, TGraph, TCanvas, TLegend
from ROOT import kGreen, kYellow, kWhite
gROOT.SetBatch(kTRUE)
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
gStyle.SetTitleFont(42, "XYZ")
gStyle.SetTitleSize(0.06, "XYZ")
gStyle.SetLabelFont(42, "XYZ")
gStyle.SetLabelSize(0.05, "XYZ")
gStyle.SetCanvasBorderMode(0)
gStyle.SetFrameBorderMode(0)
gStyle.SetCanvasColor(kWhite)
gStyle.SetPadTickX(1)
gStyle.SetPadTickY(1)
gStyle.SetPadLeftMargin(0.15)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.15)
gROOT.ForceStyle()
# theory curves: gg
massesS8 = array('d', [
1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1600.0, 1700.0, 1800.0,
1900.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0, 2700.0,
2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0, 3600.0,
3700.0, 3800.0, 3900.0, 4000.0, 4100.0, 4200.0, 4300.0, 4400.0, 4500.0,
4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0, 5400.0,
5500.0, 5600.0, 5700.0, 5800.0, 5900.0, 6000.0
])
xsS8 = array('d', [
5.46E+02, 3.12E+02, 1.85E+02, 1.12E+02, 7.19E+01, 4.59E+01, 3.02E+01,
2.01E+01, 1.37E+01, 9.46E+00, 6.55E+00, 4.64E+00, 3.27E+00, 2.36E+00,
1.70E+00, 1.24E+00, 9.11E-01, 6.69E-01, 4.97E-01, 3.71E-01, 2.78E-01,
2.07E-01, 1.55E-01, 1.19E-01, 9.26E-02, 7.08E-02, 5.43E-02, 4.15E-02,
3.22E-02, 2.50E-02, 1.92E-02, 1.51E-02, 1.19E-02, 9.25E-03, 7.35E-03,
5.86E-03, 4.53E-03, 3.66E-03, 2.91E-03, 2.33E-03, 1.86E-03, 1.45E-03,
1.12E-03, 8.75E-04, 6.90E-04, 5.55E-04, 4.47E-04, 3.63E-04, 2.92E-04,
2.37E-04, 1.97E-04
])
graph_xsS8 = TGraph(len(massesS8), massesS8, xsS8)
graph_xsS8.SetLineWidth(3)
graph_xsS8.SetLineStyle(8)
graph_xsS8.SetLineColor(6)
# theory curves: qg
massesString = array('d', [
1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1600.0, 1700.0, 1800.0,
1900.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0, 2700.0,
2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0, 3600.0,
3700.0, 3800.0, 3900.0, 4000.0, 4100.0, 4200.0, 4300.0, 4400.0, 4500.0,
4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0, 5400.0,
5500.0, 5600.0, 5700.0, 5800.0, 5900.0, 6000.0, 6100.0, 6200.0, 6300.0,
6400.0, 6500.0, 6600.0, 6700.0, 6800.0, 6900.0, 7000.0, 7100.0, 7200.0,
7300.0, 7400.0, 7500.0, 7600.0, 7700.0, 7800.0, 7900.0, 8000.0, 8100.0,
8200.0, 8300.0, 8400.0, 8500.0, 8600.0, 8700.0, 8800.0, 8900.0, 9000.0,
9100., 9200., 9300., 9400., 9500., 9600., 9700., 9800., 9900., 10000.
])
xsString = array('d', [
8316.184311558545, 5312.93137758767, 3435.0309937336524,
2304.4139502741305, 1569.8115447896687, 1090.9516635659693,
770.901859690924, 551.9206062572061, 399.69535383507633,
293.77957451762086, 218.15126842827823, 162.87634729465125,
123.17685479653694, 93.63530805932386, 71.53697229809124,
55.37491301647483, 42.75271508357369, 33.36378355470234,
26.06619302090876, 20.311817606835643, 16.1180931789545,
12.768644973921226, 10.142660425967444, 8.057990848043234,
6.400465846290908, 5.115134438331436, 4.132099789492928,
3.3193854239538734, 2.6581204529344302, 2.157554604919995,
1.7505176068913348, 1.4049155245498584, 1.140055677916783,
0.9253251132104159, 0.7522038169131606, 0.6119747371392215,
0.49612321727328523, 0.40492020959456737, 0.33091999402250655,
0.27017917021492555, 0.2201693919322846, 0.17830700070267996,
0.14564253802358157, 0.11940534430331146, 0.09694948234356839,
0.0793065371847468, 0.06446186373361917, 0.05282660618352478,
0.0428516302310620888, 0.0348997638039910363, 0.0283334766442618227,
0.0231416918363592127, 0.0187417921340763783, 0.0153501307395115115,
0.0124396534127133717, 0.0100542205744949455, 0.0081744954858627415,
0.0066338099362915941, 0.0053365711503318145, 0.00430912459914657443,
0.00346381039244064343, 0.00278602671711227174, 0.00225154342228859257,
0.0018082930150063248, 0.00143929440338502119, 0.0011581373956044489,
0.00091869589873893118, 0.00073410823691329855, 0.00058669382997948734,
0.0004661568745858897, 0.000368716655469570365,
0.000293168485206959169, 0.000230224535021638668,
0.000182317101888465142, 0.000143263359883433282,
0.000112630538527214965, 0.000088189175598406759,
0.000068708474367442343, 0.000053931726669273556,
0.0000416417855733682702, 0.0000326529676755488658,
0.0000254365480426201587, 0.0000198410151166864761,
0.0000154034425617473576, 0.0000119095554601641413,
9.2537574320108232e-6, 7.2155417437856749e-6, 5.6130924422251982e-6,
4.36634755605624901e-6, 3.39717456406994868e-6, 2.6766018046173896e-6
])
massesQstar = array('d', [
1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1600.0, 1700.0, 1800.0,
1900.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0, 2700.0,
2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0, 3600.0,
3700.0, 3800.0, 3900.0, 4000.0, 4100.0, 4200.0, 4300.0, 4400.0, 4500.0,
4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0, 5400.0,
5500.0, 5600.0, 5700.0, 5800.0, 5900.0, 6000.0, 6100.0, 6200.0, 6300.0,
6400.0, 6500.0, 6600.0, 6700.0, 6800.0, 6900.0, 7000.0, 7100.0, 7200.0,
7300.0, 7400.0, 7500.0, 7600.0, 7700.0, 7800.0, 7900.0, 8000.0, 8100.0,
8200.0, 8300.0, 8400.0, 8500.0, 8600.0, 8700.0, 8800.0, 8900.0, 9000.0
])
xsQstar = array('d', [
0.4101E+03, 0.2620E+03, 0.1721E+03, 0.1157E+03, 0.7934E+02, 0.5540E+02,
0.3928E+02, 0.2823E+02, 0.2054E+02, 0.1510E+02, 0.1121E+02, 0.8390E+01,
0.6328E+01, 0.4807E+01, 0.3674E+01, 0.2824E+01, 0.2182E+01, 0.1694E+01,
0.1320E+01, 0.1033E+01, 0.8116E+00, 0.6395E+00, 0.5054E+00, 0.4006E+00,
0.3182E+00, 0.2534E+00, 0.2022E+00, 0.1616E+00, 0.1294E+00, 0.1038E+00,
0.8333E-01, 0.6700E-01, 0.5392E-01, 0.4344E-01, 0.3503E-01, 0.2827E-01,
0.2283E-01, 0.1844E-01, 0.1490E-01, 0.1205E-01, 0.9743E-02, 0.7880E-02,
0.6373E-02, 0.5155E-02, 0.4169E-02, 0.3371E-02, 0.2725E-02, 0.2202E-02,
0.1779E-02, 0.1437E-02, 0.1159E-02, 0.9353E-03, 0.7541E-03, 0.6076E-03,
0.4891E-03, 0.3935E-03, 0.3164E-03, 0.2541E-03, 0.2039E-03, 0.1635E-03,
0.1310E-03, 0.1049E-03, 0.8385E-04, 0.6699E-04, 0.5347E-04, 0.4264E-04,
0.3397E-04, 0.2704E-04, 0.2151E-04, 0.1709E-04, 0.1357E-04, 0.1077E-04,
0.8544E-05, 0.6773E-05, 0.5367E-05, 0.4251E-05, 0.3367E-05, 0.2666E-05,
0.2112E-05, 0.1673E-05, 0.1326E-05
])
graph_xsString = TGraph(len(massesString), massesString, xsString)
graph_xsString.SetLineWidth(3)
graph_xsString.SetLineStyle(8)
graph_xsString.SetLineColor(9)
graph_xsQstar = TGraph(len(massesQstar), massesQstar, xsQstar)
graph_xsQstar.SetLineWidth(3)
graph_xsQstar.SetLineStyle(2)
graph_xsQstar.SetLineColor(1)
# theory curves: qq
massesTh = array('d', [
1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1600.0, 1700.0, 1800.0,
1900.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0, 2700.0,
2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0, 3600.0,
3700.0, 3800.0, 3900.0, 4000.0, 4100.0, 4200.0, 4300.0, 4400.0, 4500.0,
4600.0, 4700.0, 4800.0, 4900.0, 5000.0, 5100.0, 5200.0, 5300.0, 5400.0,
5500.0, 5600.0, 5700.0, 5800.0, 5900.0, 6000.0, 6100.0, 6200.0, 6300.0,
6400.0, 6500.0, 6600.0, 6700.0, 6800.0, 6900.0, 7000.0, 7100.0, 7200.0,
7300.0, 7400.0, 7500.0, 7600.0, 7700.0, 7800.0, 7900.0, 8000.0, 8100.0,
8200.0, 8300.0, 8400.0, 8500.0, 8600.0, 8700.0, 8800.0, 8900.0, 9000.0
])
xsAxi = array('d', [
0.1849E+03, 0.1236E+03, 0.8473E+02, 0.5937E+02, 0.4235E+02, 0.3069E+02,
0.2257E+02, 0.1680E+02, 0.1263E+02, 0.9577E+01, 0.7317E+01, 0.5641E+01,
0.4374E+01, 0.3411E+01, 0.2672E+01, 0.2103E+01, 0.1658E+01, 0.1312E+01,
0.1041E+01, 0.8284E+00, 0.6610E+00, 0.5294E+00, 0.4250E+00, 0.3417E+00,
0.2752E+00, 0.2220E+00, 0.1792E+00, 0.1449E+00, 0.1172E+00, 0.9487E-01,
0.7686E-01, 0.6219E-01, 0.5033E-01, 0.4074E-01, 0.3298E-01, 0.2671E-01,
0.2165E-01, 0.1755E-01, 0.1422E-01, 0.1152E-01, 0.9322E-02, 0.7539E-02,
0.6092E-02, 0.4917E-02, 0.3965E-02, 0.3193E-02, 0.2568E-02, 0.2062E-02,
0.1653E-02, 0.1323E-02, 0.1057E-02, 0.8442E-03, 0.6728E-03, 0.5349E-03,
0.4242E-03, 0.3357E-03, 0.2644E-03, 0.2077E-03, 0.1627E-03, 0.1271E-03,
0.9891E-04, 0.7686E-04, 0.5951E-04, 0.4592E-04, 0.3530E-04, 0.2704E-04,
0.2059E-04, 0.1562E-04, 0.1180E-04, 0.8882E-05, 0.6657E-05, 0.4968E-05,
0.3693E-05, 0.2734E-05, 0.2016E-05, 0.1481E-05, 0.1084E-05, 0.7903E-06,
0.5744E-06, 0.4160E-06, 0.3007E-06
])
xsDiquark = array('d', [
0.5824E+02, 0.4250E+02, 0.3172E+02, 0.2411E+02, 0.1862E+02, 0.1457E+02,
0.1153E+02, 0.9211E+01, 0.7419E+01, 0.6019E+01, 0.4912E+01, 0.4031E+01,
0.3323E+01, 0.2750E+01, 0.2284E+01, 0.1903E+01, 0.1590E+01, 0.1331E+01,
0.1117E+01, 0.9386E+00, 0.7900E+00, 0.6658E+00, 0.5618E+00, 0.4745E+00,
0.4010E+00, 0.3391E+00, 0.2869E+00, 0.2428E+00, 0.2055E+00, 0.1740E+00,
0.1473E+00, 0.1246E+00, 0.1055E+00, 0.8922E-01, 0.7544E-01, 0.6376E-01,
0.5385E-01, 0.4546E-01, 0.3834E-01, 0.3231E-01, 0.2720E-01, 0.2288E-01,
0.1922E-01, 0.1613E-01, 0.1352E-01, 0.1132E-01, 0.9463E-02, 0.7900E-02,
0.6584E-02, 0.5479E-02, 0.4551E-02, 0.3774E-02, 0.3124E-02, 0.2581E-02,
0.2128E-02, 0.1750E-02, 0.1437E-02, 0.1177E-02, 0.9612E-03, 0.7833E-03,
0.6366E-03, 0.5160E-03, 0.4170E-03, 0.3360E-03, 0.2700E-03, 0.2162E-03,
0.1725E-03, 0.1372E-03, 0.1087E-03, 0.8577E-04, 0.6742E-04, 0.5278E-04,
0.4114E-04, 0.3192E-04, 0.2465E-04, 0.1894E-04, 0.1448E-04, 0.1101E-04,
0.8322E-05, 0.6253E-05, 0.4670E-05
])
xsWprime = array('d', [
0.8811E+01, 0.6024E+01, 0.4216E+01, 0.3010E+01, 0.2185E+01, 0.1610E+01,
0.1200E+01, 0.9043E+00, 0.6875E+00, 0.5271E+00, 0.4067E+00, 0.3158E+00,
0.2464E+00, 0.1932E+00, 0.1521E+00, 0.1201E+00, 0.9512E-01, 0.7554E-01,
0.6012E-01, 0.4792E-01, 0.3827E-01, 0.3059E-01, 0.2448E-01, 0.1960E-01,
0.1571E-01, 0.1259E-01, 0.1009E-01, 0.8090E-02, 0.6483E-02, 0.5193E-02,
0.4158E-02, 0.3327E-02, 0.2660E-02, 0.2125E-02, 0.1695E-02, 0.1351E-02,
0.1075E-02, 0.8546E-03, 0.6781E-03, 0.5372E-03, 0.4248E-03, 0.3353E-03,
0.2642E-03, 0.2077E-03, 0.1629E-03, 0.1275E-03, 0.9957E-04, 0.7757E-04,
0.6027E-04, 0.4670E-04, 0.3610E-04, 0.2783E-04, 0.2140E-04, 0.1641E-04,
0.1254E-04, 0.9561E-05, 0.7269E-05, 0.5510E-05, 0.4167E-05, 0.3143E-05,
0.2364E-05, 0.1774E-05, 0.1329E-05, 0.9931E-06, 0.7411E-06, 0.5523E-06,
0.4108E-06, 0.3055E-06, 0.2271E-06, 0.1687E-06, 0.1254E-06, 0.9327E-07,
0.6945E-07, 0.5177E-07, 0.3863E-07, 0.2888E-07, 0.2162E-07, 0.1622E-07,
0.1218E-07, 0.9156E-08, 0.6893E-08
])
xsZprime = array('d', [
0.5027E+01, 0.3398E+01, 0.2353E+01, 0.1663E+01, 0.1196E+01, 0.8729E+00,
0.6450E+00, 0.4822E+00, 0.3638E+00, 0.2769E+00, 0.2123E+00, 0.1639E+00,
0.1272E+00, 0.9933E-01, 0.7789E-01, 0.6134E-01, 0.4848E-01, 0.3845E-01,
0.3059E-01, 0.2440E-01, 0.1952E-01, 0.1564E-01, 0.1256E-01, 0.1010E-01,
0.8142E-02, 0.6570E-02, 0.5307E-02, 0.4292E-02, 0.3473E-02, 0.2813E-02,
0.2280E-02, 0.1848E-02, 0.1499E-02, 0.1216E-02, 0.9864E-03, 0.8002E-03,
0.6490E-03, 0.5262E-03, 0.4264E-03, 0.3453E-03, 0.2795E-03, 0.2260E-03,
0.1826E-03, 0.1474E-03, 0.1188E-03, 0.9566E-04, 0.7690E-04, 0.6173E-04,
0.4947E-04, 0.3957E-04, 0.3159E-04, 0.2516E-04, 0.2001E-04, 0.1587E-04,
0.1255E-04, 0.9906E-05, 0.7795E-05, 0.6116E-05, 0.4785E-05, 0.3731E-05,
0.2900E-05, 0.2247E-05, 0.1734E-05, 0.1334E-05, 0.1022E-05, 0.7804E-06,
0.5932E-06, 0.4492E-06, 0.3388E-06, 0.2544E-06, 0.1903E-06, 0.1417E-06,
0.1051E-06, 0.7764E-07, 0.5711E-07, 0.4186E-07, 0.3055E-07, 0.2223E-07,
0.1612E-07, 0.1164E-07, 0.8394E-08
])
graph_xsAxi = TGraph(len(massesTh), massesTh, xsAxi)
graph_xsAxi.SetLineWidth(3)
graph_xsAxi.SetLineStyle(3)
graph_xsAxi.SetLineColor(63)
graph_xsDiquark = TGraph(len(massesTh), massesTh, xsDiquark)
graph_xsDiquark.SetLineWidth(3)
graph_xsDiquark.SetLineStyle(9)
graph_xsDiquark.SetLineColor(8)
graph_xsWprime = TGraph(len(massesTh), massesTh, xsWprime)
graph_xsWprime.SetLineWidth(3)
graph_xsWprime.SetLineStyle(7)
graph_xsWprime.SetLineColor(46)
graph_xsZprime = TGraph(len(massesTh), massesTh, xsZprime)
graph_xsZprime.SetLineWidth(3)
graph_xsZprime.SetLineStyle(5)
graph_xsZprime.SetLineColor(38)
# limits
graph_exp_2sigma = (TGraph(len(masses_exp), masses_exp,
xs_exp_limits_2sigma)
if len(xs_exp_limits_2sigma) > 0 else TGraph(0))
graph_exp_2sigma.SetFillColor(kYellow)
graph_exp_1sigma = (TGraph(len(masses_exp), masses_exp,
xs_exp_limits_1sigma)
if len(xs_exp_limits_2sigma) > 0 else TGraph(0))
graph_exp_1sigma.SetFillColor(kGreen + 1)
graph_exp = (TGraph(len(masses), masses, xs_exp_limits)
if len(xs_exp_limits_2sigma) > 0 else TGraph(0))
#graph_exp.SetMarkerStyle(24)
graph_exp.SetLineWidth(3)
graph_exp.SetLineStyle(2)
graph_exp.SetLineColor(4)
graph_obs = TGraph(len(masses), masses, xs_obs_limits)
graph_obs.SetMarkerStyle(20)
graph_obs.SetLineWidth(3)
#graph_obs.SetLineStyle(1)
graph_obs.SetLineColor(1)
c = TCanvas("c", "", 800, 800)
c.cd()
legend = TLegend(.60, .55, .90, .70)
legend.SetBorderSize(0)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
legend.SetTextSize(0.03)
legend.SetHeader('95% CL upper limits')
if len(xs_exp_limits_2sigma) > 0:
graph_exp_2sigma.GetXaxis().SetTitle("%s resonance mass [GeV]" %
(args.final_state))
graph_exp_2sigma.GetYaxis().SetTitle(
"#sigma #times #it{B} #times #it{A} [pb]")
graph_exp_2sigma.GetYaxis().SetTitleOffset(1.1)
graph_exp_2sigma.GetYaxis().SetRangeUser(1e-02, 1e+03)
#graph_exp_2sigma.GetXaxis().SetNdivisions(1005)
graph_exp_2sigma.Draw("AF")
graph_exp_1sigma.Draw("F")
graph_exp.Draw("L")
graph_obs.Draw("LP")
legend.AddEntry(graph_obs, "Observed", "lp")
legend.AddEntry(graph_exp, "Expected", "lp")
legend.AddEntry(graph_exp_1sigma, "#pm 1#sigma", "F")
legend.AddEntry(graph_exp_2sigma, "#pm 2#sigma", "F")
else:
graph_obs.GetXaxis().SetTitle("%s resonance mass [GeV]" %
(args.final_state))
graph_obs.GetYaxis().SetTitle(
"#sigma #times #it{B} #times #it{A} [pb]")
graph_obs.GetYaxis().SetTitleOffset(1.1)
graph_obs.GetYaxis().SetRangeUser(1e-02, 1e+03)
#graph_obs.GetXaxis().SetNdivisions(1005)
graph_obs.Draw("ALP")
legend.AddEntry(graph_obs, "Observed", "lp")
if args.final_state == 'gg':
graph_xsS8.Draw("L")
elif args.final_state == 'qg':
graph_xsQstar.Draw("L")
graph_xsString.Draw("L")
elif args.final_state == 'qq':
graph_xsAxi.Draw("L")
graph_xsDiquark.Draw("L")
graph_xsWprime.Draw("L")
graph_xsZprime.Draw("L")
legend.Draw()
if args.final_state == 'gg':
legendTh = TLegend(.60, .80, .90, .84)
legendTh.SetBorderSize(0)
legendTh.SetFillColor(0)
legendTh.SetFillStyle(0)
legendTh.SetTextFont(42)
legendTh.SetTextSize(0.03)
legendTh.AddEntry(graph_xsS8, "S8", "l")
legendTh.Draw()
elif args.final_state == 'qg':
legendTh = TLegend(.60, .80, .90, .88)
legendTh.SetBorderSize(0)
legendTh.SetFillColor(0)
legendTh.SetFillStyle(0)
legendTh.SetTextFont(42)
legendTh.SetTextSize(0.03)
legendTh.AddEntry(graph_xsString, "String", "l")
legendTh.AddEntry(graph_xsQstar, "Excited quark", "l")
legendTh.Draw()
elif args.final_state == 'qq':
legendTh = TLegend(.60, .72, .90, .88)
legendTh.SetBorderSize(0)
legendTh.SetFillColor(0)
legendTh.SetFillStyle(0)
legendTh.SetTextFont(42)
legendTh.SetTextSize(0.03)
legendTh.AddEntry(graph_xsAxi, "Axigluon/coloron", "l")
legendTh.AddEntry(graph_xsDiquark, "Scalar diquark", "l")
legendTh.AddEntry(graph_xsWprime, "W' SSM", "l")
legendTh.AddEntry(graph_xsZprime, "Z' SSM", "l")
legendTh.Draw()
# draw the lumi text on the canvas
CMS_lumi.extraText = args.extraText
CMS_lumi.lumi_sqrtS = args.lumi_sqrtS # used with iPeriod = 0 (free form)
iPos = 11
iPeriod = 0
CMS_lumi.CMS_lumi(c, iPeriod, iPos)
gPad.RedrawAxis()
c.SetLogy()
fileName = 'xs_limit_%s_%s.%s' % (args.method, args.final_state + (
('_' + args.postfix) if args.postfix != '' else ''),
args.fileFormat.lower())
c.SaveAs(fileName)
print "Plot saved to '%s'" % (fileName)
