def merge_hists(hists_d, merge_groups):
out_d = dict()
for merge_name, items in merge_groups.items():
hist = hists_d[items[0]].Clone()
for item in items[1:]:
hist.Add(hists_d[item])
out_d[merge_name] = hist
out_d[merge_name].SetTitle("%s" % merge_name)
return out_d
def merge_hists(hists_d, merge_groups):
out_d = dict()
for merge_name, items in merge_groups.items():
hist = hists_d[items[0]].Clone()
for item in items[1:]:
hist.Add(hists_d[item])
out_d[merge_name] = hist
out_d[merge_name].SetTitle("%s" % merge_name)
return out_d
def get_sample_dict(path, sample_d):
out_d = dict()
for (name, samples) in sample_d.items():
files = []
for samp in samples:
fn = path + "/" + samp + ".root"
try:
fi = ROOT.TFile(fn)
except Exception as e:
logging.getLogger().warning("Could not open sample %s: %s" % (fn, str(e)))
fi = None
if fi:
files.append(fi)
out_d[name] = files
return out_d
def get_sample_dict(path, sample_d):
out_d = dict()
for (name, samples) in sample_d.items():
files = []
for samp in samples:
fn = path + "/" + samp + ".root"
try:
fi = ROOT.TFile(fn)
except Exception as e:
logging.getLogger().warning("Could not open sample %s: %s" %
(fn, str(e)))
fi = None
if fi:
files.append(fi)
out_d[name] = files
return out_d
import ROOT
from odict import OrderedDict as dict
import string
import logging
#Here the latter items will become topmost in stacks
merge_cmds = dict()
merge_cmds["data"] = ["SingleMu"]
merge_cmds["diboson"] = ["WW", "WZ", "ZZ"]
merge_cmds["W(#rightarrow l #nu) + jets"] = [
"W1Jets_exclusive", "W2Jets_exclusive", "W3Jets_exclusive",
"W4Jets_exclusive"
]
merge_cmds["DY-jets"] = ["DYJets"]
merge_cmds["t#bar{t} (#rightarrow lq, ll)"] = [
"TTJets_FullLept", "TTJets_SemiLept"
]
#merge_cmds["t#bar{t}"] = ["TTJets_MassiveBinDECAY"]
merge_cmds["tW-channel"] = ["T_tW", "Tbar_tW"]
merge_cmds["s-channel"] = ["T_s", "Tbar_s"]
merge_cmds["t-channel"] = ["T_t", "Tbar_t"]
def lumi_textbox(lumi, pos="top-left"):
"""
This method creates and draws the "CMS Preliminary" luminosity box,
displaying the lumi in 1/fb and the COM energy.
**Mandatory arguments:
lumi - the integrated luminosity in 1/pb
infile_SL = set_file_name("histograms_presel_2b_SL", mctrig, topw, noWeight, dosys=args.doSys)
standalone = True
f_SL = ROOT.TFile(indir + infile_SL)
pars_SL = f_SL.Get("pars") # read lumi normalization of mc histograms
hist_lumi_SL = pars_SL.GetBinContent(pars_SL.GetXaxis().FindBin("Lumi") )
#lf = 19.6/hist_lumi_SL # scale lumi to new value if needed, default 1
lf=1
Lumi = hist_lumi_SL*lf
from odict import OrderedDict as dict
processes_SM = dict()
processes_SM["ttH125"] = f_SL.Get("ttH125/cut_flow_smu_ttH125")
processes_SM["ttjj"] = f_SL.Get("ttjj/cut_flow_smu_ttjj")
processes_SM["ttb"] = f_SL.Get("ttb/cut_flow_smu_ttb")
processes_SM["ttbb"] = f_SL.Get("ttbb/cut_flow_smu_ttbb")
processes_SM["TTV"] = f_SL.Get("TTV/cut_flow_smu_TTV")
processes_SM["SingleT"] = f_SL.Get("SingleT/cut_flow_smu_SingleT")
processes_SM["EWK"] = f_SL.Get("EWK/cut_flow_smu_EWK")
processes_SM["DiBoson"] = f_SL.Get("DiBoson/cut_flow_smu_DiBoson")
sumBkg_SM = processes_SM["ttjj"].Clone("sumBkg") # Get a cut-flow histogram for sum Bkg
for proc, cf_hist in processes_SM.iteritems():
if not proc == "ttH125" and not proc=="ttjj":
sumBkg_SM.Add(cf_hist)
data_SM = f_SL.Get("singleMu_data/cut_flow_smu_singleMu_data") # get cut-flow of data
import re
from odict import OrderedDict as dict
tracking_cfg_parameters = dict()
from sub_fun import read_template, write_outfile, create_cmssw_cfg_from_template, create_batch_submission_script, create_varstrings
from infilelists import infilelist_Zee
# Chi2 scan
tracking_cfg_parameters["maxCand"] = [5, 5, 5, 5, 5, 5 ]
tracking_cfg_parameters["maxChi2"] = [10, 30, 50, 100, 300, 2000]
tracking_cfg_parameters["nSigma"] = [3, 3, 3, 3, 3, 3 ]
# Max cand scan
tracking_cfg_parameters["maxCand"] += [3, 4, 6, 7]
tracking_cfg_parameters["maxChi2"] += [2000, 2000, 2000, 2000]
tracking_cfg_parameters["nSigma"] += [3, 3, 3, 3]
# nSigma scan
tracking_cfg_parameters["maxCand"] += [5, 5, 5]
tracking_cfg_parameters["maxChi2"] += [2000, 2000, 2000]
tracking_cfg_parameters["nSigma"] += [2, 4, 5]
print "Creating " + str(len(tracking_cfg_parameters["maxCand"]) )+ " jobs"
varstrings = create_varstrings(tracking_cfg_parameters, iter = len(tracking_cfg_parameters["maxCand"]), skip_default = False)
filelists = {
# "Flat_Pt": "",
# "Pt10": "",
# "Pt100": "",
def legend(hists, pos="top-right", **kwargs):
"""
***Mandatory arguments:
hists - list of TH1* type objects
The title of the histogram(TH1.GetTitle()) is used as the name in the legend.
The legend will be in the order of the histograms.
***Optional arguments:
names - names of the processes displayed at the legend instead of the histogram titles. Order
1. data
2. MC samples in the reverse order to appear in the legend
pos - a string specifying the desired position on the canvas
width, height - the size of the legend in relative coordinates
styles - an optional list of characters form the set of {p,f} specifying
whether to draw a filled legend marker (MC) or a point (data)
If the length of style characters does not equal the length of
the histogram list, the last character is duplicated to have styles
for all histograms.
For example:
hists=[hist_data, hist_mc1, hist_mc2, hist_mc3]
styles=["p","f"] becomes styles["p", "f", "f", "f"]
and the data histogram will be drawn as "p", the mc histogram as "f"
returns - instance of TLegend. You must keep a reference to the instance
to avoid losing the legend, e.g. you must do
...
h = TH1F(...)
leg = legend([h], ...) <<< note the leg=..
...
Instead of
...
legend([h], ...)
"""
#Names of the processes as displayed on a legend
names = kwargs.get("names")
#The relative size of the text in the legend
text_size = kwargs.get("text_size", 0.03)
#If you have long names you should make the width larger
width = kwargs.get("width", 0.21)
#The height is determined automatically with some sensible settings from
#the number of legend items
height = kwargs.get("height", 0.03 * len(hists))
#The style characters for drawing the legend
styles = kwargs.get("styles", ["p", "f"])
#Fill the style character array to correct length
if len(styles) < len(hists):
styles += [styles[-1]] * (len(hists) - len(styles))
#Check that each histo has a style character
if len(styles) != len(hists):
raise ValueError(
"styles must have the same number of objects as hists")
#We'll be popping form back, so need to reverse
styles.reverse()
#Some 'reasonable' hard-coded positions
#[bottom_left_x, bottom_left_y, top_right_x, top_right_y]
#FIXME: fine-tune and make your own
if pos == "top-right":
leg_coords = [-1, -1, 0.93, 0.91]
if pos == "top-left":
leg_coords = [-1, -1, 0.45, 0.91]
#Calculate the bottom-left coordinate from top right using the width and height
if leg_coords[0] == -1:
leg_coords[0] = leg_coords[2] - width
if leg_coords[1] == -1:
leg_coords[1] = leg_coords[3] - height
#Expand the array using the wildcard
leg = ROOT.TLegend(*leg_coords)
if "names" in kwargs:
rnames = names[::-1]
data = rnames.pop()
rnames.insert(0, data)
from odict import OrderedDict as dict
name_hist_pairs = dict(zip(rnames, hists))
for name in name_hist_pairs:
leg_style = styles.pop()
leg.AddEntry(name_hist_pairs[name], name, leg_style)
else:
for hist in hists:
leg_style = styles.pop()
leg.AddEntry(hist, hist.GetTitle(), leg_style)
leg.Draw()
leg.SetFillColor(ROOT.kWhite)
leg.SetLineColor(ROOT.kWhite)
leg.SetTextSize(text_size)
#Need to return the legend to keep a reference
return leg
f_DL = ROOT.TFile(indir + infile_DL)
pars_SL = f_SL.Get("pars") # read lumi normalization of mc histograms
pars_DL = f_DL.Get("pars")
hist_lumi_SL = pars_SL.GetBinContent(pars_SL.GetXaxis().FindBin("Lumi") )
hist_lumi_DL = pars_DL.GetBinContent(pars_DL.GetXaxis().FindBin("Lumi") )
if hist_lumi_SL != hist_lumi_DL:
print "WARNING: lumi_SL != lumi_DL, using lumi_SL"
lf = 1 #19.5/hist_lumi # scale lumi to new value if needed, default 1
Lumi = hist_lumi_SL*lf
from odict import OrderedDict as dict
processes_SL = dict()
processes_SL["ttH125"] = f_SL.Get("ttH125/cut_flow_ttH125")
processes_SL["ttjj"] = f_SL.Get("ttjj/cut_flow_ttjj")
processes_SL["ttb"] = f_SL.Get("ttb/cut_flow_ttb")
processes_SL["ttbb"] = f_SL.Get("ttbb/cut_flow_ttbb")
processes_SL["TTV"] = f_SL.Get("TTV/cut_flow_TTV")
processes_SL["SingleT"] = f_SL.Get("SingleT/cut_flow_SingleT")
processes_SL["EWK"] = f_SL.Get("EWK/cut_flow_EWK")
processes_SL["DiBoson"] = f_SL.Get("DiBoson/cut_flow_DiBoson")
processes_DL = dict()
processes_DL["ttH125"] = f_DL.Get("ttH125/cut_flow_ttH125")
processes_DL["ttjj"] = f_DL.Get("ttjj/cut_flow_ttjj")
processes_DL["ttb"] = f_DL.Get("ttb/cut_flow_ttb")
processes_DL["ttbb"] = f_DL.Get("ttbb/cut_flow_ttbb")
processes_DL["TTV"] = f_DL.Get("TTV/cut_flow_TTV")
data = data_mu.Clone("data")
data.Add(data_el)
if not (hist_to_plot[:3] == "num"):
data.Rebin(nrebin)
if mode=="DL":
data_mu = h.Get("diMu_data/" + hist_to_plot + "_diMu_data")
data_el = h.Get("diEl_data/" + hist_to_plot + "_diEl_data")
data = data_mu.Clone("data")
data.Add(data_el)
if not(hist_to_plot[:3] == "num"):
data.Rebin(nrebin)
from odict import OrderedDict as dict
mc = dict()
mc["EWK"] = h.Get("EWK/" + hist_to_plot + "_EWK") #
mc["SingleTop"] = h.Get("SingleT/" + hist_to_plot + "_SingleT")
mc["DiBoson"] = h.Get("DiBoson/" + hist_to_plot + "_DiBoson")
mc["TTV"] = h.Get("TTV/" + hist_to_plot + "_TTV")
if inclusive_ttjets:
mc["TTJets"] = h.Get("TTJets/" + hist_to_plot + "_TTJets")
else:
mc["ttjj"] = h.Get("ttjj/" + hist_to_plot + "_ttjj")
mc["ttb"] = h.Get("ttb/" + hist_to_plot + "_ttb")
mc["ttbb"] = h.Get("ttbb/" + hist_to_plot + "_ttbb")
mc["TTH125"] = h.Get("ttH125/" + hist_to_plot + "_ttH125")
for key in mc:
def legend(hists, pos="top-right", **kwargs):
"""
***Mandatory arguments:
hists - list of TH1* type objects
The title of the histogram(TH1.GetTitle()) is used as the name in the legend.
The legend will be in the order of the histograms.
***Optional arguments:
names - names of the processes displayed at the legend instead of the histogram titles. Order
1. data
2. MC samples in the reverse order to appear in the legend
pos - a string specifying the desired position on the canvas
width, height - the size of the legend in relative coordinates
styles - an optional list of characters form the set of {p,f} specifying
whether to draw a filled legend marker (MC) or a point (data)
If the length of style characters does not equal the length of
the histogram list, the last character is duplicated to have styles
for all histograms.
For example:
hists=[hist_data, hist_mc1, hist_mc2, hist_mc3]
styles=["p","f"] becomes styles["p", "f", "f", "f"]
and the data histogram will be drawn as "p", the mc histogram as "f"
returns - instance of TLegend. You must keep a reference to the instance
to avoid losing the legend, e.g. you must do
...
h = TH1F(...)
leg = legend([h], ...) <<< note the leg=..
...
Instead of
...
legend([h], ...)
"""
# Names of the processes as displayed on a legend
names = kwargs.get("names")
# The relative size of the text in the legend
text_size = kwargs.get("text_size", 0.03)
# If you have long names you should make the width larger
width = kwargs.get("width", 0.21)
# The height is determined automatically with some sensible settings from
# the number of legend items
height = kwargs.get("height", 0.03 * len(hists))
# The style characters for drawing the legend
styles = kwargs.get("styles", ["p", "f"])
# Fill the style character array to correct length
if len(styles) < len(hists):
styles += [styles[-1]] * (len(hists) - len(styles))
# Check that each histo has a style character
if len(styles) != len(hists):
raise ValueError("styles must have the same number of objects as hists")
# We'll be popping form back, so need to reverse
styles.reverse()
# Some 'reasonable' hard-coded positions
# [bottom_left_x, bottom_left_y, top_right_x, top_right_y]
# FIXME: fine-tune and make your own
if pos == "top-right":
leg_coords = [-1, -1, 0.93, 0.91]
if pos == "top-left":
leg_coords = [-1, -1, 0.45, 0.91]
# Calculate the bottom-left coordinate from top right using the width and height
if leg_coords[0] == -1:
leg_coords[0] = leg_coords[2] - width
if leg_coords[1] == -1:
leg_coords[1] = leg_coords[3] - height
# Expand the array using the wildcard
leg = ROOT.TLegend(*leg_coords)
if "names" in kwargs:
rnames = names[::-1]
data = rnames.pop()
rnames.insert(0, data)
from odict import OrderedDict as dict
name_hist_pairs = dict(zip(rnames, hists))
for name in name_hist_pairs:
leg_style = styles.pop()
leg.AddEntry(name_hist_pairs[name], name, leg_style)
else:
for hist in hists:
leg_style = styles.pop()
leg.AddEntry(hist, hist.GetTitle(), leg_style)
leg.Draw()
leg.SetFillColor(ROOT.kWhite)
leg.SetLineColor(ROOT.kWhite)
leg.SetTextSize(text_size)
# Need to return the legend to keep a reference
return leg
import ROOT
from odict import OrderedDict as dict
import string
import logging
#Here the latter items will become topmost in stacks
merge_cmds = dict()
merge_cmds["data"] = ["SingleMu"]
merge_cmds["diboson"] = ["WW", "WZ", "ZZ"]
merge_cmds["W(#rightarrow l #nu) + jets"] = ["W1Jets_exclusive", "W2Jets_exclusive", "W3Jets_exclusive", "W4Jets_exclusive"]
merge_cmds["DY-jets"] = ["DYJets"]
merge_cmds["t#bar{t} (#rightarrow lq, ll)"] = ["TTJets_FullLept", "TTJets_SemiLept"]
#merge_cmds["t#bar{t}"] = ["TTJets_MassiveBinDECAY"]
merge_cmds["tW-channel"] = ["T_tW", "Tbar_tW"]
merge_cmds["s-channel"] = ["T_s", "Tbar_s"]
merge_cmds["t-channel"] = ["T_t", "Tbar_t"]
def lumi_textbox(lumi, pos="top-left"):
"""
This method creates and draws the "CMS Preliminary" luminosity box,
displaying the lumi in 1/fb and the COM energy.
**Mandatory arguments:
lumi - the integrated luminosity in 1/pb
**Optional arguments:
pos - a string specifying the position of the lumi box.
**returns:
A TPaveText instance with the lumi information
"""
if mode == "SL":
cut_flow_base = "cut_flow_smu"
elif mode == "DL":
cut_flow_base = "cut_flow_di_mu"
elif args.lep == "ele":
if mode == "SL":
cut_flow_base = "cut_flow_sele"
elif mode == "DL":
cut_flow_base = "cut_flow_di_ele"
else:
cut_flow_base = "cut_flow"
print "reading cut flow from histograms: " + cut_flow_base
from odict import OrderedDict as dict
processes = dict()
processes["ttH125"] = f.Get("ttH125/" + cut_flow_base + "_ttH125")
processes["ttjj"] = f.Get("ttjj/" + cut_flow_base + "_ttjj")
processes["ttb"] = f.Get("ttb/" + cut_flow_base + "_ttb")
processes["ttbb"] = f.Get("ttbb/" + cut_flow_base + "_ttbb")
processes["TTV"] = f.Get("TTV/" + cut_flow_base + "_TTV")
processes["SingleT"] = f.Get("SingleT/" + cut_flow_base + "_SingleT")
processes["EWK"] = f.Get("EWK/" + cut_flow_base + "_EWK")
processes["DiBoson"] = f.Get("DiBoson/" + cut_flow_base + "_DiBoson")
#evt_weight = {}
#for process in processes:
# evt_weight[process] = (f.Get(process + "/weights_" + process) ).GetBinContent(1)
evt_weight = get_evt_weight(f,processes)
