def __draw_stack(self, regions, th1d_dict, output_name):
canvas = TCanvas("canvas", 'A basic canvas', 1000, 600)
stack = THStack("stack", "stack")
leg = Plotting.Create_Legend(0.60, 0.60, 0.95, 0.95)
for region in regions:
hist = th1d_dict[region]
hist.SetLineColor(1)
hist.SetLineWidth(1)
hist.SetMarkerColor(self.__get_colour(region))
hist.SetMarkerStyle(0)
hist.SetFillColor(self.__get_colour(region))
leg.AddEntry(hist, self.__get_label(region), "f")
stack.Add(hist)
del hist
stack.Draw("HIST")
stack.GetYaxis().SetTitle("Events")
stack.GetXaxis().SetTitle("True #it{E_{T}^{miss}} [GeV]")
leg.Draw()
canvas.Print(output_name)
def main():
extension = "pdf"
luminosity = 44307.4
ymin = 0
ymax = 0.024
data_set_names = [
(["SZee_all_susy_2l_0jets.root",
"SZmumu_all_susy_2l_0jets.root"], "Z#rightarrowll", 860 + 0, 23),
(["ZZ_1in3_susy_2l_0jets.root"], "ZZ#rightarrowll#nu#nu", 416 + 3, 43),
(["WZ_1in3_susy_2l_0jets.root"], "WZ#rightarrowl#null", 416 - 8, 33),
(["WW_1in3_susy_2l_0jets.root"], "WW#rightarrowl#nul#nu", 416 + 0, 20),
([
"ttbar_1in3_susy_2l_0jets.root", "top_1in3_susy_2l_0jets.root",
"antitop_1in3_susy_2l_0jets.root"
], "Top", 800 + 4, 21),
]
DATA_dir = os.path.join(os.environ["HOME_DIRECTORY"], "Data", "SR_SUSY")
## Creating the plots
gROOT.SetStyle("ATLAS")
gROOT.ForceStyle()
gStyle.SetErrorX(0.5)
canvas = TCanvas("canvas", 'A basic canvas', 800, 600)
# canvas.SetLogy()
## Adding in the legend
leg = Plotting.Create_Legend(0.60, 0.60, 0.95, 0.95, ncols=1)
## Creating the stack
stack = THStack("stack", "stack")
stack.SetMinimum(ymin)
stack.SetMaximum(ymax)
## Cycling through the different datasets
for datasets, label, colour, style in data_set_names:
## Creating the total histogram which will be filled
myhist = TH1D(label, label, 50, 0, 150)
myhist.SetStats(True)
myhist.StatOverflows(True)
for dataset in datasets:
## The root file is opened
rootfile_name = os.path.join(DATA_dir, dataset)
print(rootfile_name)
root_file = TFile.Open(rootfile_name, 'read')
tree = root_file.Get("mt2_Truth")
## Creating the current histogram which will be filled
thishist = TH1D(label, label, 50, 0, 150)
thishist.SetStats(True)
thishist.StatOverflows(True)
## Drawing the tree and saving the hist to the matrix
execution = "mt2>>{}".format(label)
tree.Draw(execution, "", "goff")
thishist.SetDirectory(0)
myhist.Add(thishist)
## We are dont with the file
root_file.Close()
del root_file
## Changing the properties of the histogram
myhist.Scale(1 / myhist.Integral("width"))
myhist.SetLineColor(colour)
myhist.SetMarkerColor(colour)
myhist.SetMarkerStyle(style)
myhist.SetMarkerSize(1.5)
## Adding the legend entry
leg.AddEntry(myhist, label, "p")
## Adding the object to the stack
stack.Add(myhist)
del myhist
## Drawing the stack on the currrent canvas
stack.Draw("NOSTACK HIST P")
leg.Draw()
## Setting axis labels
stack.GetXaxis().SetTitle("m_{T2} (True #it{E}_{T}^{miss}) [GeV]")
stack.GetYaxis().SetTitle("Normalised Distributions")
## Moving axis tick marks
stack.GetYaxis().SetMaxDigits(3)
stack.GetXaxis().SetLabelOffset(0.017)
## Drawing all text
left = 0.2
size = 1.0
shift = 0.06
pos = 0.88
Plotting.Draw_ATLASLabel(left, pos, "Simulation", scale=1.0)
pos -= shift
Plotting.Draw_Text(left, pos, "work in progress", scale=size)
pos -= shift
Plotting.Draw_Lumi(left, pos, 0, scale=size)
pos -= shift
## Updating the canvas
canvas.Update()
out_file = "true_strans.{}".format(extension)
canvas.Print(out_file)
del canvas
return 0
signi_fpr, signi_tpr, _ = metrics.roc_curve(label, signi )
network_fpr, network_tpr, _ = metrics.roc_curve(label, network )
## Correcting the fpr into a backround rejection rate
tight_bck_rej = 1 - tight_fpr
signi_bck_rej = 1 - signi_fpr
network_bck_rej = 1 - network_fpr
## Converting the lines to tgraphs
tight_gr = TGraph( len(tight_tpr), tight_tpr, tight_bck_rej )
signi_gr = TGraph( len(signi_tpr), signi_tpr, signi_bck_rej )
network_gr = TGraph( len(network_tpr), network_tpr, network_bck_rej )
## Drawing the plots using ROOT
canvas = TCanvas( "canvas", 'A basic canvas', 600, 600 )
leg = Plotting.Create_Legend( 0.2, 0.2, 0.7, 0.40, border_size=0, margin=0.1 )
tight_gr.Draw( 'AL' )
signi_gr.Draw( 'L' )
network_gr.Draw( 'L' )
leg.AddEntry( tight_gr, "Tight #it{E}_{T}^{miss}", "l")
leg.AddEntry( signi_gr, "Object-based #it{E}_{T}^{miss} Significance", "l")
leg.AddEntry( network_gr, "Network #it{E}_{T}^{miss}", "l")
## Changing the colours
tight_gr.SetLineColor(4)
signi_gr.SetLineColor(801)
network_gr.SetLineColor(2)
tight_gr.SetLineWidth(2)
signi_gr.SetLineWidth(2)
def main(extension, network_name, data_set_name, process, luminosity, WP_list,
H1D_hist_list, H1D_tail_list, profile_list, tgraph_list,
H2D_hist_list):
gROOT.SetStyle("ATLAS")
gROOT.ForceStyle()
gStyle.SetErrorX(0.5)
OUTPUT_dir = os.path.join(os.environ["HOME_DIRECTORY"], "Output")
hist_dir = os.path.join(OUTPUT_dir, network_name, data_set_name)
rootfile_name = os.path.join(hist_dir, "histograms.root")
########## Loading and Plotting the TH1Ds ##########
for (var, min, max) in H1D_hist_list:
## Creating the canvas object
canvas = TCanvas("canvas_{}".format(var.name), 'A basic canvas', 800,
600)
## Adding a legend
leg = Plotting.Create_Legend(0.72, 0.60, 0.95, 0.95, show_stats=True)
## Superimposing all of the graphs into a stack
stack = Plotting.Draw_1D_Comp(rootfile_name, var, min, max, WP_list,
leg)
## If the stack fails then we skip
if stack == -1:
continue
## Drawing all text
draw_all_text(data_set_name, luminosity, process)
## Updating the canvas
canvas.Update()
## Saving the file
out_file = "{}/{}_{}.{}".format(hist_dir, data_set_name, var.plotname,
extension)
canvas.Print(out_file)
del canvas
########## Loading and Plotting the Tails ##########
for (var, min, max) in H1D_tail_list:
## Creating the canvas object
canvas = TCanvas("canvas_tail_{}".format(var.name), 'A basic canvas',
800, 600)
## Adding in the legend
leg = Plotting.Create_Legend(0.75, 0.65, 0.95, 0.95)
## Superimposing all of the graphs into a stack
filled_stack = Plotting.Draw_1D_Comp(rootfile_name,
var,
min,
max,
WP_list,
leg,
isTail=True)
## If the stack fails then we skip
if filled_stack == -1:
continue
## Drawing all text
draw_all_text(data_set_name, luminosity, process)
## Adding the legend
leg.Draw()
canvas.Update()
canvas.SetLogy()
out_file = "{}/{}_{}_tail.{}".format(hist_dir, data_set_name,
var.plotname, extension)
canvas.Print(out_file)
del canvas
########## Profiles and TGraphs ##########
for (var_x, var_y, min, max) in profile_list + tgraph_list:
## Are we looking at a TGraph or a TProfile
isTgraph = True if (var_x, var_y, min, max) in tgraph_list else False
## Creating the canvas object
canvas = TCanvas("canvas_{}_{}".format(var_x.name, var_y.name),
'A basic canvas', 800, 600)
## Adding in the legend
leg = Plotting.Create_Legend(0.75, 0.65, 0.95, 0.95)
## Superimposing all of the graphs into a stack
filled_stack = Plotting.Draw_2D_Comp(rootfile_name,
var_x,
var_y,
min,
max,
WP_list,
leg,
isTgraph=isTgraph)
## If the stack fails then we skip
if filled_stack == -1:
continue
## Drawing all text
draw_all_text(data_set_name, luminosity, process)
## Updating the canvas
canvas.Update()
out_file = "{}/{}_{}_{}.{}".format(hist_dir, data_set_name,
var_x.plotname, var_y.plotname,
extension)
canvas.Print(out_file)
del canvas
########## 2D histograms (each as their own) ##########
for (vx, vy) in H2D_hist_list:
for wp in WP_list:
if wp.name not in ["Tight", "Network"]:
continue
canvas = TCanvas(
"{}_{}_{}_2D".format(vx.plotname, vy.plotname, wp.name),
'A basic canvas', 800, 800)
# gStyle.SetPalette(53)
# TColor.InvertPalette()
graph_name = "2D_{}_vs_{}_{}".format(vx.name, vy.name, wp.name)
hist = Plotting.GetGraphFromFile(rootfile_name, graph_name)
ylabel = wp.name + " " + vy.x_label + " " + vy.units
if wp.name == "Network":
if network_name == "flat_ann":
ylabel = "(A) " + ylabel
if network_name == "smpl_ann":
ylabel = "(B) " + ylabel
if network_name == "deep_ann":
ylabel = "(Z) " + ylabel
hist.GetXaxis().SetTitle(vx.x_label + " " + vx.units)
hist.GetYaxis().SetTitle(ylabel)
# canvas.SetLogz()
hist.Draw("col")
if vx.name == "Truth" or "Tghtx":
xline = TLine(0, 0, 200, 200)
xline.SetLineColor(1)
xline.SetLineWidth(2)
xline.Draw()
# dline = TLine(0,0,80,-80)
# dline.SetLineColor(1)
# dline.SetLineWidth(2)
# dline.Draw()
else:
hist.GetXaxis().SetTitle("E_{x}^{miss} - E_{x}^{miss, true} " +
vx.units)
hist.GetYaxis().SetTitle("E_{y}^{miss} - E_{y}^{miss, true} " +
vy.units)
xline = TLine(-50, 0, 50, 0)
xline.SetLineColor(1)
xline.SetLineWidth(2)
xline.Draw()
yline = TLine(0, -50, 0, 50)
yline.SetLineColor(1)
yline.SetLineWidth(2)
yline.Draw()
hist.GetYaxis().SetMaxDigits(3)
hist.GetXaxis().SetLabelOffset(0.017)
# Adding in some text and the ATLAS Labels
leg = Plotting.Create_Legend(0.19, 0.78, 0.58, 0.94)
leg.Draw()
Plotting.Draw_ATLASLabel(0.2, 0.89, text="Simulation")
Plotting.Draw_Text(0.2, 0.84, text="work in progress", scale=1)
Plotting.Draw_Text(0.2, 0.79, text=process, scale=1)
canvas.Update()
out_file = "{}/{}_{}.{}".format(hist_dir, data_set_name,
graph_name, extension)
canvas.Print(out_file)
return 0
def main():
extension = "pdf"
####### File names and locations ########
network_name = "deep_ann"
data_set_name = "ttbar_1in3_tt_strict" #_NOJETS _SOMEJETS
######################################
process = "#it{t#bar{t}}"
luminosity = 44307.4
## Initialising plotting variables
Var_Lin = Plotting.Variable(
"Lin",
"Linear_Response",
"#Delta_{T}^{lin}",
"",
)
Var_Truth = Plotting.Variable("Truth", "TrueET", "True #it{E}_{T}^{miss}",
"[GeV]")
ymin = -0.2
ymax = 0.5
plot_list = [
("main_ann", "Tight", "", 4, 21),
("main_ann", "Network", "", 2, 20),
("flat_ann", "Network", "(A) ", 3, 22),
("smpl_ann", "Network", "(B) ", 6, 23),
]
## Creating the plots
gROOT.SetStyle("ATLAS")
gROOT.ForceStyle()
gStyle.SetErrorX(0.5)
canvas = TCanvas("canvas_{}_{}".format(Var_Truth.name, Var_Lin.name),
'A basic canvas', 800, 600)
## Adding in the legend
leg = Plotting.Create_Legend(0.65, 0.70, 0.95, 0.95)
## Creating the stack
stack = THStack("stack", Var_Truth.name + Var_Lin.name)
stack.SetMinimum(ymin)
stack.SetMaximum(ymax)
## Cycling through the different network directories
for network_name, wp_name, prefix, colour, marker in plot_list:
OUTPUT_dir = os.path.join(os.environ["HOME_DIRECTORY"], "Output")
hist_dir = os.path.join(OUTPUT_dir, network_name, data_set_name)
rootfile_name = os.path.join(hist_dir, "histograms.root")
## Creating the working point variable
wp = Plotting.WorkingPoint(wp_name)
## Generating the graph name
graph_name = "{}_vs_{}_{}".format(Var_Truth.name, Var_Lin.name,
wp.name)
## Loading the graph using its name and file location
graph = Plotting.GetGraphFromFile(rootfile_name, graph_name)
if graph == -1:
continue
## Setting the colors specific to the working point
graph.SetLineColor(colour)
graph.SetMarkerColor(colour)
graph.SetMarkerStyle(marker)
## Adding the legend entry
leg.AddEntry(graph, prefix + wp.name, "p")
## Adding the object to the stack
stack.Add(graph)
del graph
## Drawing the stack on the currrent canvas
stack.Draw("nostack")
leg.Draw()
## Setting axis labels
stack.GetXaxis().SetTitle(Var_Truth.x_label + " " + Var_Truth.units)
stack.GetYaxis().SetTitle(Var_Lin.x_label + " " + Var_Lin.units)
## Moving axis tick marks
stack.GetYaxis().SetMaxDigits(3)
stack.GetXaxis().SetLabelOffset(0.017)
## Drawing all text
left = 0.29
size = 1.0
shift = 0.06
pos = 0.88
Plotting.Draw_ATLASLabel(left, pos, "Simulation", scale=1.0)
pos -= shift
Plotting.Draw_Text(left, pos, "work in progress", scale=size)
pos -= shift
Plotting.Draw_Lumi(left, pos, 0, scale=size)
pos -= shift
Plotting.Draw_Text(left, pos, process, scale=size)
pos -= shift
## Updating the canvas
canvas.Update()
out_file = "response_comparison_zoom.{}".format(extension)
canvas.Print(out_file)
del canvas
return 0
def STACK(extension,
OUTPUT_dir,
network_name,
luminosity,
output_flag,
output_mod,
generator,
extra_text,
fudge,
text,
MC_list,
Real_Data,
var,
wp=None):
is_wp = False if wp is None else True
## The name of the histogram to be used
hist_name = "{}_{}".format(var.name, wp.name) if is_wp else var.name
## Creating the canvas
canvas = TCanvas("canvas" + hist_name, 'A basic canvas', 800, 800)
## Creating the first pad to contain the basic histogram plots
histo_pad = TPad("histo_pad", "histo_pad", 0, 0.25, 1.0, 1.0)
histo_pad.SetBottomMargin(0)
histo_pad.Draw()
histo_pad.cd()
# if is_wp:
histo_pad.SetLogy()
## Adding in the legend
leg = Plotting.Create_Legend(0.70, 0.45, 0.95, 0.95, text_size=0.045)
## Creating a stack for the canvas
stack = THStack("stack", var.name)
hist_list = []
integral_list = []
for s, mc in enumerate(MC_list):
rootfile_name = os.path.join(OUTPUT_dir, network_name, mc.file,
"histograms.root")
hist = Plotting.GetGraphFromFile(rootfile_name, hist_name)
if hist == -1:
continue
hist.Scale(fudge * luminosity)
hist.SetMarkerColor(mc.colour)
hist.SetFillColor(mc.colour)
hist.SetLineColor(1)
hist.SetLineWidth(1)
hist.SetMarkerStyle(0)
leg.AddEntry(hist, mc.label, "f")
integral_list.append(hist.Integral(0, hist.GetNbinsX() + 1))
hist.Scale(1, "width")
hist_list.append(hist)
if s == 0:
MC_Total = hist.Clone()
else:
MC_Total.Add(hist.Clone())
del hist
## If the list is empty and no histograms were found then we skip the rest
if not integral_list and is_wp:
print("No MC histograms found for working point {}\n".format(wp.name))
return 0
## Now we use the integrals to sort the histograms in descending order
ord_idx = np.argsort(integral_list)
## Adding the histograms to the stack
for i in ord_idx:
# Draw the object on the stack
stack.Add(hist_list[i])
stack.Draw("HIST")
stack.GetYaxis().SetTitleOffset(1.2)
## Adding the MC Statistical, lumi and xsec uncertainty
for i in range(1, MC_Total.GetNbinsX() + 1):
if MC_Total.GetBinContent(i) > 0:
e = MC_Total.GetBinError(i)
h = MC_Total.GetBinContent(i)
MC_Total.SetBinError(i,
h * np.sqrt((e / h)**2 + 0.05**2 + 0.02**2))
MC_Total.SetMarkerSize(0.)
MC_Total.SetFillStyle(3001)
MC_Total.SetMarkerColor(1)
MC_Total.SetFillColor(2)
MC_Total.Draw("E2 SAME")
## Adding the data points
rootfile_name = os.path.join(OUTPUT_dir, network_name, Real_Data.file,
"histograms.root")
real_hist = Plotting.GetGraphFromFile(rootfile_name, hist_name)
real_hist.SetLineColor(1)
real_hist.SetMarkerColor(Real_Data.colour)
real_hist.SetMarkerStyle(20)
real_hist.SetMarkerSize(1.2)
real_int = real_hist.Integral(0, real_hist.GetNbinsX() + 1)
leg.AddEntry(real_hist, Real_Data.label, "p")
real_hist.Scale(1, "width")
real_hist.Draw("e1p SAME")
print("Real events = {:}".format(real_int))
print("MC events = {:}".format(sum(integral_list)))
print("Fudge Factor = {:10.10}".format(real_int / sum(integral_list)))
# print( "Z events = {:}".format( sum(integral_list[:3]) ) )
# print( "Non Z events = {:}".format( sum(integral_list[3:]) ) )
# print( "Z Factor = {:10.10}".format( ( real_int - sum(integral_list[3:]) ) / sum(integral_list[:3]) ) )
## Adding in some text and the ATLAS Labels
# if fudge != 1: text += " (#uparrow{:.2f}%)".format(fudge*100-100)
s = 1.0
pos = 0.88
shift = 0.05
Plotting.Draw_ATLASLabel(0.20, pos, "work in progress", scale=1.0)
pos -= shift + 0.01
Plotting.Draw_Lumi(0.20, pos, luminosity, scale=s)
pos -= shift
Plotting.Draw_Text(0.20, pos, text, scale=s)
pos -= shift
Plotting.Draw_Text(0.20, pos, generator, scale=s)
Plotting.Draw_Text(0.55, 0.8, extra_text)
leg.Draw()
## Plotting axis and limits
stack.GetYaxis().SetTitle("Events per GeV")
if var.ymin is not None: stack.SetMinimum(var.ymin)
if var.ymax is not None: stack.SetMaximum(var.ymax)
if var.xmin is not None and var.xmax is not None:
stack.GetXaxis().SetLimits(var.xmin, var.xmax)
## Creating the ratio pad
canvas.cd()
ratio_pad = TPad("ratio_pad", "ratio_pad", 0, 0, 1.0, 0.25)
ratio_pad.SetTopMargin(0.0)
ratio_pad.SetBottomMargin(0.3)
ratio_pad.Draw()
ratio_pad.cd()
ratio_pad.SetGrid(0, 1)
## Plotting the the MC error histogram
MC_flat = MC_Total.Clone()
for i in range(1, MC_Total.GetNbinsX() + 1):
MC_flat.SetBinContent(i, 1)
if MC_Total.GetBinContent(i) > 0:
MC_flat.SetBinError(
i,
MC_Total.GetBinError(i) / MC_Total.GetBinContent(i))
MC_flat.SetMarkerSize(0.)
MC_flat.SetFillStyle(3001)
MC_flat.SetMarkerColor(1)
MC_flat.SetFillColor(2)
MC_flat.SetMaximum(1.6)
MC_flat.SetMinimum(0.4)
MC_flat.Draw("E2")
leg.AddEntry(MC_flat, "MC stat unc", "f")
## Plotting the ratio of MC to Data
ratio_hist = real_hist.Clone()
mcratio_hist = MC_Total.Clone()
mcratio_hist.SetError(arr.array('d', [0]))
ratio_hist.Divide(mcratio_hist)
ratio_hist.Draw("ep SAME")
## Plotting axis and limits
if var.xmin is not None and var.xmax is not None:
ratio_hist.GetXaxis().SetRange(var.xmin, var.xmax)
x_title = wp.name + " " + var.x_label + " " + var.units if is_wp else var.x_label + " " + var.units
MC_flat.GetXaxis().SetTitle(x_title)
MC_flat.GetXaxis().SetTitleSize(25)
MC_flat.GetXaxis().SetTitleFont(43)
MC_flat.GetXaxis().SetTitleOffset(4)
MC_flat.GetXaxis().SetLabelFont(43)
MC_flat.GetXaxis().SetLabelSize(20)
MC_flat.GetYaxis().SetTitle("Data/MC")
MC_flat.GetYaxis().SetNdivisions(206, False)
MC_flat.GetYaxis().ChangeLabel(-1, -1, -1, -1, -1, -1, " ")
MC_flat.GetYaxis().ChangeLabel(1, -1, -1, -1, -1, -1, " ")
MC_flat.GetYaxis().SetTitleSize(25)
MC_flat.GetYaxis().SetTitleFont(43)
MC_flat.GetYaxis().SetTitleOffset(1.55)
MC_flat.GetYaxis().SetLabelFont(43)
MC_flat.GetYaxis().SetLabelSize(20)
## Adding in a line on the x-axis
line = TLine(ratio_hist.GetBinLowEdge(1), 1,
ratio_hist.GetBinLowEdge(ratio_hist.GetNbinsX() + 1), 1)
line.SetLineWidth(1)
line.SetLineColor(1)
line.SetLineStyle(9)
line.Draw()
## Saving the canvas
canvas.Update()
out_folder = "{}/{}/Stack".format(OUTPUT_dir, network_name)
if not os.path.exists(out_folder):
os.system("mkdir -p {}".format(out_folder))
out_file = os.path.join(out_folder, "{}_{}".format(output_flag, var.name))
if is_wp: out_file += "_" + wp.name
out_file += "_{}".format(generator)
if "0 Jets" in extra_text: out_file += "_NOJETS"
out_file += "{}.{}".format(output_mod, extension)
canvas.Print(out_file)