elif args.lumi < 500.:
g_max = 2.
else:
g_max = 1.5
else:
if args.lumi < 200.:
g_max = 5.
elif args.lumi < 500.:
g_max = 4.
else:
g_max = 3.
g_values = np.linspace(0.1, g_max, num=20)
grid = statscan.Grid(mass_values, g_values)
calc = statscan.StatCalc(None, args.bkg, args.lumi * 1e3)
for i, mass, g in grid:
width = XSecTwoHDM.width_tt(args.cp, mass, g=g)
parton_xsec = XSecTwoHDM(mA=mass,
wA=width,
gA=g,
mH=mass,
wH=width,
gH=g)
if args.cp == 'A':
parton_xsec.gH = 0.
else:
parton_xsec.gA = 0.
from math import isclose
import hmssm
from spectrum import RecoMtt
import statscan
if __name__ == '__main__':
mA = 500.
tanbeta = 5.
significance_ref = 0.9155510617044962
cls_ref = 0.3621699755911078
parton_xsec = hmssm.XSecHMSSM(mA, tanbeta, 'params/hMSSM.root')
reco_mtt = RecoMtt(parton_xsec, resolution=0.1)
calc = statscan.StatCalc(reco_mtt, 'ttbar_res10.root', 150e3)
with statscan.suppress_stdout():
significance = calc.significance()
cls = calc.cls()
print('Significance\n Current: {}\n Reference: {}'.format(
significance, significance_ref))
print('CLs\n Current: {}\n Reference: {}'.format(cls, cls_ref))
if isclose(significance, significance_ref) and isclose(cls, cls_ref):
print('\033[1;32mTest passed\033[0m')
else:
print('\033[1;31mTest failed\033[0m')