def __init__(self, name, info):
self.plotTable = PrettyTable(
["Plot Group", "Weighted Events", "Error"])
self.output = open("%s.txt" % name, "w")
self.info = info
self.hists = [None, None, None, None]
self.callTime = ""
self.command = ""
def __init__(self, name, info, path='.'):
self.plotTable = PrettyTable(
["Plot Group", "Weighted Events", "Error"])
self.output = open("%s/%s_info.log" % (path, name), "w")
self.info = info
self.hists = [GenericHist()] * 4
self.callTime = ""
self.command = ""
self.name = name
def writeMCLogInfo(hist_info, selection, branch_name, luminosity, cut_string,
latex):
mc_info = PrettyTable(
["Plot Group", "Weighted Events", "Error", "Stat Error", "Raw Events"])
weighted_events = 0
total_background = 0
background_err = 0
total_err2 = 0
signal = 0
signal_err = 0
for plot_set, entry in hist_info.iteritems():
wevents = round(entry["weighted_events"],
3 if entry["weighted_events"] < 1 else 2)
mc_info.add_row([
plot_set, wevents,
round(entry["error"], 2),
round(entry["stat error"], 2),
int(round(entry["raw_events"]))
])
weighted_events += entry["weighted_events"]
total_err2 += entry["error"]**2
if "wz" not in plot_set:
total_background += entry["weighted_events"]
background_err += entry["error"] * entry["error"]
else:
signal += entry["weighted_events"]
signal_err += entry["error"]
total_err = math.sqrt(total_err2)
likelihood = 0 if weighted_events <= 0 else \
signal/math.sqrt(weighted_events)
likelihood_err = 0 if signal <= 0 or weighted_events <= 0 else \
likelihood*math.sqrt((signal_err/signal)**2 + \
(0.5*total_err/weighted_events)**2)
sigbkgd = 0 if weighted_events <= 0 else signal / weighted_events
sigbkgd_err = 0 if signal <= 0 or weighted_events <= 0 else \
sigbkgd*math.sqrt((signal_err/signal)**2 + (total_err/weighted_events)**2)
if weighted_events == 0:
raise RuntimeError("Empty histogram produced for variable " +
branch_name)
with open("temp.txt", "a") as mc_file:
mc_file.write("\n" + (mc_info.get_string() if not latex else mc_info.
get_latex_string()) + "\n")
mc_file.write(
"\nTotal sum of Monte Carlo: %0.2f +/- %0.2f" %
(round(weighted_events, 2),
round(
math.sqrt(
sum([x["error"] * x["error"]
for x in hist_info.values()])), 2)))
mc_file.write(
"\nTotal sum of background Monte Carlo: %0.2f +/- %0.2f" %
(round(total_background, 2), round(math.sqrt(background_err), 2)))
mc_file.write("\nRatio S/(S+B): %0.2f +/- %0.2f" %
(round(sigbkgd, 2), round(sigbkgd_err, 2)))
mc_file.write("\nRatio S/sqrt(S+B): %0.2f +/- %0.2f" %
(round(likelihood, 2), round(likelihood_err, 2)))
def makeLogFile(channels, hist_info, args):
with open("temp.txt", "w") as log_file:
meta_info = '-'*80 + '\n' + \
'Script called at %s\n' % datetime.datetime.now() + \
'The command was: %s\n' % ' '.join(sys.argv) + \
'-'*80 + '\n'
log_file.write(meta_info)
log_file.write("Selection: %s" % args.selection)
log_file.write("\nLuminosity: %0.2f fb^{-1}\n" % (args.luminosity))
log_file.write('-' * 80 + '\n')
columns = ["Process"] + ["\\" + c for c in channels] + ["Total Yield"]
yield_table = PrettyTable(columns)
yield_info = OrderedDict()
formatted_names = {
"wz-powheg": "WZ (POWHEG)",
"wz-mgmlm": "WZ (MG MLM)",
"QCD-WZjj": "QCD-WZjj",
"EW-WZjj": "EW-WZjj",
"wzjj-ewk": "WZjj EWK",
"wzjj-ewk_filled": "WZjj EWK",
"wzjj-vbfnlo": "WZjj EWK (VBFNLO)",
"nonprompt": "Nonprompt",
"top-ewk": "t+V/VVV",
"zg": "Z$\gamma$",
"vv-powheg": "VV (POWHEG)",
"vv": "VV",
"wz": "WZ (MG5\_aMC)",
"wz-powheg": "WZ (POWHEG)",
"predyield": "Pred. Background",
"data_2016": "Data",
"data": "Data",
"data_2016H": "Data (2016H)",
}
sigfigs = 3
for name, entry in hist_info.iteritems():
if "aqgc" in name:
continue
for i, chan in enumerate(channels):
# Channels should be ordered the same way as passed to the histogram
# This bin 0 is the underflow, bin 1 is total, and bin 2
# is the first bin with channel content (mmm/emm/eem/eee by default)
if name == "data":
yield_info[chan] = "%i" % entry[chan][0]
else:
yield_info[chan] = getFormattedYieldAndError(
entry[chan][0], entry[chan][1], sigfigs)
if name == "data":
yield_info["Total Yield"] = "%i" % entry["total"][0]
else:
yield_info["Total Yield"] = getFormattedYieldAndError(
entry["total"][0], entry["total"][1], sigfigs)
yield_table.add_row([formatted_names[name]] + yield_info.values())
with open("temp.txt", "a") as log_file:
log_file.write(yield_table.get_latex_string())
def makeLogFile(channels, hist_stack, data_hist, signal_stack):
with open("temp.txt", "w") as log_file:
meta_info = '-'*80 + '\n' + \
'Script called at %s\n' % datetime.datetime.now() + \
'The command was: %s\n' % ' '.join(sys.argv) + \
'-'*80 + '\n'
log_file.write(meta_info)
log_file.write("Selection: %s" % args.selection)
log_file.write("\nLuminosity: %0.2f fb^{-1}\n" % (args.luminosity))
log_file.write('-' * 80 + '\n')
columns = ["Process"] + ["\\" + c for c in channels] + ["Total Yield"]
yield_table = PrettyTable(columns)
yield_info = OrderedDict()
hists = hist_stack.GetHists()
hists.sort(key=lambda x: x.Integral(), reverse=True)
formatted_names = {
"wz-powheg": "WZ (POWHEG)",
"wz-mgmlm": "WZ (MG MLM)",
"wz3lnu-mgmlm-0j": "WZ+0j (MG MLM)",
"wz3lnu-mgmlm-1j": "WZ+1j (MG MLM)",
"wz3lnu-mgmlm-2j": "WZ+2j (MG MLM)",
"wz3lnu-mgmlm-3j": "WZ+3j (MG MLM)",
"chargedHiggsWZ-m300": "m_{H^{\pm}} = 300",
"chargedHiggsWZ-m400": "m_{H^{\pm}} = 400",
"chargedHiggsWZ-m500": "m_{H^{\pm}} = 500",
"chargedHiggsWZ-m600": "m_{H^{\pm}} = 600",
"chargedHiggsWZ-m700": "m_{H^{\pm}} = 700",
"chargedHiggsWZ-m800": "m_{H^{\pm}} = 800",
"chargedHiggsWZ-m900": "m_{H^{\pm}} = 900",
"chargedHiggsWZ-m1000": "m_{H^{\pm}} = 1000",
"chargedHiggsWZ-m1500": "m_{H^{\pm}} = 1500",
"chargedHiggsWZ-m2000": "m_{H^{\pm}} = 2000",
"wzjj-ewk": "WZjj EWK",
"wzjj-vbfnlo": "WZjj EWK (VBFNLO)",
"nonprompt": "Nonprompt",
"top-ewk": "t+V/VVV",
"zg": "Z$\gamma$",
"vv-powheg": "VV (POWHEG)",
"vv": "VV (MG5\_aMC)",
"wz": "WZ (MG5\_aMC)",
"wz-powheg": "WZ (POWHEG)",
"predyield": "Pred. Background" if signal_stack else "Predicted Yield",
"data_2016": "Data",
"data_2016H": "Data (2016H)",
}
signal_names = []
if signal_stack:
hists += signal_stack.GetHists()
signal_names = [h.GetName() for h in signal_stack.GetHists()]
signal_names.append("predyield")
hist_allbackground = ROOT.TH1D("predyield", "all background",
1 + len(channels), 0, 1 + len(channels))
hists.append(hist_allbackground)
if data_hist:
hists.Add(data_hist)
sigfigs = 0 if not data_hist else 1
for hist in hists:
if hist.GetName() not in signal_names and "data" not in hist.GetName():
hist_allbackground.Add(hist)
for i, chan in enumerate(channels):
# Channels should be ordered the same way as passed to the histogram
# Thus bin 0 is the underflow, bin 1 is total, and bin 2
# is the first bin with channel content (mmm/emm/eem/eee by default)
yield_info[chan] = getFormattedYieldAndError(hist, i + 2, sigfigs)
yield_info["Total Yield"] = getFormattedYieldAndError(hist, 1, sigfigs)
yield_table.add_row(
[formatted_names[hist.GetName().replace("_standalone", "")]] +
yield_info.values())
with open("temp.txt", "a") as log_file:
log_file.write(yield_table.get_latex_string())
class LogFile:
def __init__(self, name, info):
self.plotTable = PrettyTable(
["Plot Group", "Weighted Events", "Error"])
self.output = open("%s.txt" % name, "w")
self.info = info
self.hists = [None, None, None, None]
self.callTime = ""
self.command = ""
def getBackground(self):
return self.hists[BKG]
def getSignal(self):
return self.hists[SIGNAL]
def getTotalMC(self):
return self.hists[TOTAL]
def getData(self):
return self.hists[DATA]
def addMC(self, groupHists, drawOrder):
for groupName in [i for i in drawOrder[::-1] if i in groupHists]:
hist = groupHists[groupName]
wEvents, error = self.getIntErr(hist)
self.plotTable.add_row(sl((groupName, wEvents, error)))
self.addHist(hist, BKG)
self.addHist(self.getBackground(), TOTAL)
def addHist(self, hist, dest):
if not self.hists[dest]:
self.hists[dest] = hist.Clone()
else:
self.hists[dest].Add(hist)
def addSignal(self, signal, groupName):
self.addHist(signal, SIGNAL)
wEvents, error = self.getIntErr(signal)
self.plotTable.add_row(sl((groupName, wEvents, error)))
self.addHist(signal, TOTAL)
def addMetaInfo(self, callTime, command):
self.callTime = callTime
self.command = command
def getIntErr(self, hist):
error = array.array('d', [0])
wEvents = hist.IntegralAndError(0, hist.GetNbinsX(), error)
return (wEvents, error[0])
def writeOut(self, isLatex=False):
self.output.write('-' * 80 + '\n')
self.output.write("Script called at %s \n" % self.callTime)
self.output.write("The command was: %s \n" % self.command)
self.output.write('-' * 80 + '\n')
self.output.write("Selection: %s/%s\n" %
(self.info.getAnalysis(), self.info.getSelection()))
self.output.write("Luminosity: %0.2f fb^{-1}\n" %
(self.info.getLumi() / 1000))
#output.write("\nPlotting branch: %s\n" % branch_name)
if isLatex:
self.output.write('\n' + self.plotTable.get_latex_string() +
'\n' * 2)
else:
self.output.write('\n' + self.plotTable.get_string() + '\n' * 2)
self.output.write("Total sum of Monte Carlo: %0.2f +/- %0.2f \n" %
sl(self.getIntErr(self.getTotalMC())))
if self.getSignal():
self.output.write(
"Total sum of background Monte Carlo: %0.2f +/- %0.2f \n" %
sl(self.getIntErr(self.getBackground())))
self.output.write("Ratio S/(S+B): %0.2f +/- %0.2f \n" %
sl(self.getSigBkgRatio()))
self.output.write("Ratio S/sqrt(S+B): %0.2f +/- %0.2f \n" %
sl(self.getLikelihood()))
if self.getData():
self.output.write("Number of events in data %d \n" %
self.getData.Integral())
self.output.close()
def getSigBkgRatio(self):
sig, sigErr = self.getIntErr(self.getSignal())
tot, totErr = self.getIntErr(self.getTotalMC())
sigbkgd = sig / tot
sigbkgdErr = sigbkgd * math.sqrt((sigErr / sig)**2 + (totErr / tot)**2)
return (sigbkgd, sigbkgdErr)
def getLikelihood(self):
sig, sigErr = self.getIntErr(self.getSignal())
tot, totErr = self.getIntErr(self.getTotalMC())
likelihood = sig / math.sqrt(tot)
likelihoodErr = likelihood * math.sqrt((sigErr / sig)**2 +
(0.5 * totErr / tot)**2)
return (likelihood, likelihoodErr)
class LogFile:
def __init__(self, name, info, path='.'):
self.plotTable = PrettyTable(
["Plot Group", "Weighted Events", "Error"])
self.output = open("%s/%s_info.log" % (path, name), "w")
self.info = info
self.hists = [GenericHist()] * 4
self.callTime = ""
self.command = ""
self.name = name
def getBackground(self):
return self.hists[BKG]
def getSignal(self):
return self.hists[SIGNAL]
def getTotalMC(self):
return self.hists[TOTAL]
def getData(self):
return self.hists[DATA]
def addMC(self, drawOrder):
for name, hist in drawOrder:
wEvents, error = self.getIntErr(hist)
self.plotTable.add_row(sl((name, wEvents, error)))
self.hists[BKG] += hist
self.hists[TOTAL] += self.getBackground()
def addSignal(self, signal, groupName):
self.hists[SIGNAL] += signal
wEvents, error = self.getIntErr(signal)
self.plotTable.add_row(sl((groupName, wEvents, error)))
self.hists[TOTAL] += signal
def addMetaInfo(self, callTime, command):
self.callTime = callTime
self.command = command
def getIntErr(self, hist):
wEvents = sum(hist.hist)
error = math.sqrt(sum(hist.histErr2))
return (wEvents, error)
def writeOut(self, isLatex=False):
self.output.write('-' * 80 + '\n')
self.output.write("Script called at %s \n" % self.callTime)
self.output.write("The command was: %s \n" % self.command)
self.output.write("The name of this Histogram is: %s \n" % self.name)
self.output.write('-' * 80 + '\n')
self.output.write("Selection: %s/%s\n" %
(self.info.getAnalysis(), self.info.getSelection()))
self.output.write("Luminosity: %0.2f fb^{-1}\n" %
(self.info.getLumi() / 1000))
#output.write("\nPlotting branch: %s\n" % branch_name)
if isLatex:
self.output.write('\n' + self.plotTable.get_latex_string() +
'\n' * 2)
else:
self.output.write('\n' + self.plotTable.get_string() + '\n' * 2)
if not self.getTotalMC().empty():
self.output.write("Total sum of Monte Carlo: %0.2f +/- %0.2f \n" %
sl(self.getIntErr(self.getTotalMC())))
if not self.getSignal().empty():
self.output.write(
"Total sum of background Monte Carlo: %0.2f +/- %0.2f \n" %
sl(self.getIntErr(self.getBackground())))
self.output.write("Ratio S/(S+B): %0.2f +/- %0.2f \n" %
sl(self.getSigBkgRatio()))
self.output.write("Ratio S/sqrt(S+B): %0.2f +/- %0.2f \n" %
sl(self.getLikelihood()))
if not self.getData().empty():
self.output.write("Number of events in data %d \n" %
self.getIntErr(self.getData())[0])
self.output.close()
def getSigBkgRatio(self):
sig, sigErr = self.getIntErr(self.getSignal())
tot, totErr = self.getIntErr(self.getTotalMC())
sigbkgd = sig / tot
sigbkgdErr = sigbkgd * math.sqrt((sigErr / sig)**2 + (totErr / tot)**2)
return (sigbkgd, sigbkgdErr)
def getLikelihood(self):
sig, sigErr = self.getIntErr(self.getSignal())
tot, totErr = self.getIntErr(self.getTotalMC())
likelihood = sig / math.sqrt(tot)
likelihoodErr = likelihood * math.sqrt((sigErr / sig)**2 +
(0.5 * totErr / tot)**2)
return (likelihood, likelihoodErr)
def writeMCLogInfo(hist_info, selection, branch_name, luminosity, cut_string):
meta_info = (
"-" * 80
+ "\n"
+ "Script called at %s\n" % datetime.datetime.now()
+ "The command was: %s\n" % " ".join(sys.argv)
+ "-" * 80
+ "\n"
)
mc_info = PrettyTable(["Plot Group", "Weighted Events", "Error", "Stat Error", "Raw Events"])
weighted_events = 0
total_background = 0
background_err = 0
total_err2 = 0
sigbkgd = 0
sigbkgd_err = 0
signal = 0
signal_err = 0
likelihood = 0
likelihood_err = 0
for plot_set, entry in hist_info.iteritems():
mc_info.add_row(
[
plot_set,
round(entry["weighted_events"], 2),
round(entry["error"], 2),
round(entry["stat error"], 2),
entry["raw_events"],
]
)
weighted_events += entry["weighted_events"]
total_err2 += entry["error"] ** 2
if "wz" not in plot_set:
total_background += entry["weighted_events"]
background_err += entry["error"] * entry["error"]
else:
signal += entry["weighted_events"]
signal_err += entry["error"]
total_err = math.sqrt(total_err2)
likelihood = signal / math.sqrt(weighted_events)
likelihood_err = likelihood * math.sqrt((signal_err / signal) ** 2 + (0.5 * total_err / weighted_events) ** 2)
sigbkgd = signal / weighted_events
sigbkgd_err = sigbkgd * math.sqrt((signal_err / signal) ** 2 + (total_err / weighted_events) ** 2)
with open("temp.txt", "w") as mc_file:
mc_file.write(meta_info)
mc_file.write("Selection: %s" % selection)
mc_file.write("\nAdditional cut: %s" % ("None" if cut_string == "" else cut_string))
mc_file.write("\nLuminosity: %0.2f fb^{-1}" % (luminosity))
mc_file.write("\nPlotting branch: %s\n" % branch_name)
mc_file.write(mc_info.get_string())
mc_file.write(
"\nTotal sum of Monte Carlo: %0.2f +/- %0.2f"
% (
round(weighted_events, 2),
round(math.sqrt(sum([x["error"] * x["error"] for x in hist_info.values()])), 2),
)
)
mc_file.write(
"\nTotal sum of background Monte Carlo: %0.2f +/- %0.2f"
% (round(total_background, 2), round(math.sqrt(background_err), 2))
)
mc_file.write("\nRatio S/(S+B): %0.2f +/- %0.2f" % (round(sigbkgd, 2), round(sigbkgd_err, 2)))
mc_file.write("\nRatio S/sqrt(S+B): %0.2f +/- %0.2f" % (round(likelihood, 2), round(likelihood_err, 2)))