parser.add_argument("-w", "--write", action="store_true")
parser.add_argument("-cg", "--contourgraph", action="store_true")
parser.add_argument("-fg", "--flatgraph", action="store_true")
cfg = parser.parse_args()
name = "JPsi"
source = 'sources/jsi2.csv'
data = "DATA_Bplus_Kplusmumu_qsqcut"
MC = "MC_Bplus_KplusJpsimumu_qsqcut"
KemuMC = "MC_Bplus_Kplusmue_newresampled"
print time.asctime(time.localtime()), "Starting Code"
if cfg.reweight:
#Creates a 2D weighting histogram from the JPsiK data, and adds a weight branch to the JpsiK MC
tdrw.plotsep(name, source, data, MC, int(cfg.bincount))
if cfg.write:
#Loads the 2D Histogram and uses it to add a weight branch to the MC Data
wkemu.extract(source, KemuMC, int(cfg.bincount))
if cfg.contourgraph:
#Creates a PDF comparing the S Weighted Data and the Reweighted Monte Carlo Data
plt.plotsep(name, source, data, MC, int(cfg.bincount))
if cfg.flatgraph:
#Creates histograms showing the seperation betweeen Sweighted Data and Reweighted Monte Carlo for single variables
rwbe.plotsep(name, source, data, MC, int(cfg.bincount), weighting=True)
print time.asctime(time.localtime()), "Code Finished"
import rwbe
import argparse
import pylab as pl
name = "JPsi"
source = 'sources/jsi2.csv'
data = "with_bdt_kmumu_1112_isolncut"
MC = "with_bdt_jpsik_12_mc_isoln_newpid_corr_allvars_etacut"
b=[]
chindofperbin=[]
for i in range(1, 15):
n = i*600
b.append(n)
z = rwbe.plotsep(name, source, data, MC, n)
chindofperbin.append(z)
print i
pl.plot(b, chindofperbin)
pl.show()
raw_input("prompt")
