# hist.Draw("e")
# gPad.Modified()
# hist_sim.Draw("esames")
#else:
# hist_sim.Draw("e")
# gPad.Modified()
# hist.Draw("esames")
#
#
#
#
#can.SaveAs("clusterPlots_Pos" + cfg.position + ".pdf")
can.SaveAs(name + ".pdf]")
lhcbStyle.setLHCbStyle()
gStyle.SetOptStat(1)
#measurements = [
# ["1431786652", "a_at_0deg", "pos_a_0_deg"]
# ,["1432091294", "a_at_10deg", "pos_a_10_deg"]
# ,["1432264510", "a_at_20deg", "pos_a_20_deg"]
# ,["1432350729", "a_at_30deg", "pos_a_30_deg"]
# ,["1432169457", "c_at_0deg", "pos_c_0_deg"]
# ,["1432089102", "c_at_10deg", "pos_c_10_deg"]
# ,["1432187205", "c_at_20deg", "pos_c_20_deg"]
# ,["1432358809", "c_at_30deg", "pos_c_30_deg"]
# ]
#for measurement in measurements:
#
# hist.Draw("e")
# gPad.Modified()
# hist_sim.Draw("esames")
# else:
# hist_sim.Draw("e")
# gPad.Modified()
# hist.Draw("esames")
#
#
#
#
# can.SaveAs("clusterPlots_Pos" + cfg.position + ".pdf")
can.SaveAs(name + ".pdf]")
lhcbStyle.setLHCbStyle()
gStyle.SetOptStat(1)
path = "/home/ttekampe/SciFi/results/DataSimCompare/"
data_path = "/home/ttekampe/SciFi/results/clusters/"
# t = "6thTry"
# t = "6thTry_LSw_125"
# t = "6thTry_LSw_125_measured_att"
t = "standard_boole"
# data_name = "testbeam_data_pos_{position}_at_{angle}_deg_corrected_clusterAnalyis.root"
data_name = "testbeam_data_pos_{position}_at_{angle}_deg_corrected_clusterAnalyisexpected_cl_pos.root"
# sim_name = "testbeam_simulation_position_{position}_at_{angle}deg_toolFixed_clusterAnalyis.root"
spdbinwidth = (upperlim2 - lowerlim2)/bincount
i = int(bpt[0]/bptbinwidth) +1
j = int(spd[0]/spdbinwidth) + 1
r = ROOT.TRandom3(0)
o[0] = r.Gaus(Weight.GetBinContent(i, j), Weight.GetBinError(i, j))
brBranch.Fill()
nt.SetBranchStatus("*", 1)
nt.Write()
m.Close()
print time.asctime(time.localtime()), "Branch Filled!"
c=ROOT.TCanvas()
c.Divide(2,1)
lhcb.setLHCbStyle()
#Extracts the two reweighting variables and their ranges from a CSV file, and then runs the Reweight function above based this information
def plotsep(name, source, data, MC, bincount):
import csv
print time.asctime(time.localtime()), "Extracting information from " + str(source)
with open(source, 'rb') as csvfile:
i = 0
reader = csv.reader(csvfile, delimiter=',', quotechar='|')
v = []
ul = []
ll = []
for row in reader:
x = row
v.append(x[0])