return lumi
if __name__ == "__main__":
style1=GetStyleHtt()
style1.cd()
x_att1, y_att1 = np.loadtxt('att.txt', unpack=True)
x_att=array("d",x_att1)
y_att=array("d",y_att1)
gatt = ROOT.TGraph(len(x_att), x_att,y_att)
x_amm, y_amm = np.loadtxt('amm.txt', unpack=True)
for i in range(0,len(x_amm)):
BRmm=gamma_mu(1,float(x_amm[i]),1)
BRtt=gamma_tau(1,float(x_amm[i]),1)
#y_amm[i]=y_amm[i]*BRtt/BRmm
y_amm[i]=100*y_amm[i]
gamm = ROOT.TGraph(len(x_amm), x_amm.flatten('C'),y_amm.flatten('C'))
canvas = MakeCanvas("asdf","asdf",800,800)
canvas.cd()
canvas.SetLogy()
gamm.Draw("AC")
gamm.SetLineColor(ROOT.EColor.kAzure-1)
gamm.SetLineStyle(7)
gamm.GetXaxis().SetRangeUser(25,80);
gamm.GetXaxis().SetLimits(25,80);
gamm.SetMinimum(5.0);
gamm.SetMaximum(200);
gamm.GetXaxis().SetTitle("m_{a} (GeV)");
mintanbeta=0.1
maxtanbeta=5
n=100
step=(maxtanbeta-mintanbeta)/n
BRmm=1
BRtt=1
BRbb=1
a_ymmbb=[]
a_x=[]
a_ymmtt=[]
for i in range(0,100):
tanbeta=mintanbeta+step*i
width=get_total_width(args.model,float(args.ma),tanbeta)
BRmm=gamma_mu(tanbeta,float(args.ma),args.model)/width
BRtt=gamma_tau(tanbeta,args.ma,args.model)/width
BRbb=gamma_quarks(tanbeta,args.ma,args.model,6)/width
a_ymmbb.append(limit_mmbb1*0.00017/(2*BRbb*BRmm))
a_ymmtt.append(limit_mmtt1/(BRtt*BRtt))
#print limit_mmbb1,limit_mmtt1
#print BRbb,BRmm,BRtt
#print limit_mmbb1*0.00017/(2*BRbb*BRmm),limit_mmtt1/(BRtt*BRtt)
a_x.append(tanbeta)
x = array("d", a_x)
ymmbb = array("d", a_ymmbb)
ymmtt = array("d", a_ymmtt)
gmmtt = ROOT.TGraph(len(x),x,ymmtt)
gmmbb = ROOT.TGraph(len(x),x,ymmbb)
parser = argparse.ArgumentParser()
parser.add_argument('--model', type=int, default='1', help="Which type of 2HDM?")
parser.add_argument('--tanbeta', type=float, default='1', help="Which tan beta?")
args = parser.parse_args()
style1=GetStyleHtt()
style1.cd()
#### h->aa->mmtt ####
x_mmtt1, y_mmtt1 = np.loadtxt('mmtt.txt', unpack=True)
x_mmtt=array("d",x_mmtt1)
y_mmtt=array("d",y_mmtt1)
for i in range(0,len(x_mmtt)):
width=get_total_width(args.model,float(x_mmtt[i]),args.tanbeta)
BRtt=gamma_tau(args.tanbeta,float(x_mmtt[i]),args.model)/width
y_mmtt[i]=y_mmtt[i]/(BRtt*BRtt)
gmmtt = ROOT.TGraph(len(x_mmtt), x_mmtt,y_mmtt)
#### h->aa->mmbb ####
x_mmbb, y_mmbb = np.loadtxt('mmbb.txt', unpack=True)
for i in range(0,len(x_mmbb)):
width=get_total_width(args.model,float(x_mmbb[i]),args.tanbeta)
BRmm=gamma_mu(args.tanbeta,float(x_mmbb[i]),args.model)/width
BRbb=gamma_quarks(args.tanbeta,float(x_mmbb[i]),args.model,6)/width
y_mmbb[i]=y_mmbb[i]*0.00017
y_mmbb[i]=y_mmbb[i]/(2*BRmm*BRbb)
gmmbb = ROOT.TGraph(len(x_mmbb), x_mmbb.flatten('C'),y_mmbb.flatten('C'))
#### h->aa->tttt (HIG-14-019) ####
x_tttt1, y_tttt1 = np.loadtxt('tttt1.txt', unpack=True)
BRmm=1
BRtt=1
BRbb=1
a_y1=[]
a_y2=[]
a_y3=[]
a_y4=[]
a_x=[]
for i in range(0,100):
tanbeta=mintanbeta+step*i
width1=get_total_width(1,float(args.ma),tanbeta)
width2=get_total_width(2,float(args.ma),tanbeta)
width3=get_total_width(3,float(args.ma),tanbeta)
width4=get_total_width(4,float(args.ma),tanbeta)
BRmm1=gamma_mu(tanbeta,float(args.ma),1)/width1
BRtt1=gamma_tau(tanbeta,args.ma,1)/width1
BRbb1=gamma_quarks(tanbeta,args.ma,1,6)/width1
BRmm2=gamma_mu(tanbeta,float(args.ma),2)/width2
BRtt2=gamma_tau(tanbeta,args.ma,2)/width2
BRbb2=gamma_quarks(tanbeta,args.ma,2,6)/width2
BRmm3=gamma_mu(tanbeta,float(args.ma),3)/width3
BRtt3=gamma_tau(tanbeta,args.ma,3)/width3
BRbb3=gamma_quarks(tanbeta,args.ma,3,6)/width3
BRmm4=gamma_mu(tanbeta,float(args.ma),4)/width4
BRtt4=gamma_tau(tanbeta,args.ma,4)/width4
BRbb4=gamma_quarks(tanbeta,args.ma,4,6)/width4
if args.channel=="mmtt":
a_y1.append(2*BRtt1*BRmm1)
a_y2.append(2*BRtt2*BRmm2)
a_y3.append(2*BRtt3*BRmm3)
a_y4.append(2*BRtt4*BRmm4)
maxbeta=5
if (args.model==4):
minbeta=0.28
maxbeta=0.9
x_mmtt1, y_mmtt1 = np.loadtxt('mmtt.txt', unpack=True)
x_mmtt=array("d",x_mmtt1)
y_mmtt=array("d",y_mmtt1)
hist=ROOT.TH2F("hist","hist",len(x_mmtt)-1,x_mmtt[0],x_mmtt[len(x_mmtt)-1],binbeta,minbeta,maxbeta)
for b in range(0,binbeta+1):
tanbeta=0.001+minbeta+1.0*b*(maxbeta-minbeta)/(binbeta)
for i in range(0,len(x_mmtt)):
#for b in range(0,binbeta):
#tanbeta=minbeta+1.0*b*(maxbeta-minbeta)/binbeta
width=get_total_width(args.model,float(x_mmtt[i]),tanbeta)
BRtt=gamma_tau(tanbeta,float(x_mmtt[i]),args.model)/width
y=y_mmtt[i]/(BRtt*BRtt)
print x_mmtt[i],tanbeta,y
hist.Fill(x_mmtt[i],1.0*tanbeta,y)
#hist.SetContour(500)
canvas = MakeCanvas("asdf","asdf",800,800)
canvas.SetRightMargin(0.2)
canvas.SetLeftMargin(0.15)
canvas.cd()
canvas.SetLogz()
hist.GetXaxis().SetTitle("m_{a} (GeV)")
hist.GetYaxis().SetTitle("tan#beta")
hist.GetZaxis().SetTitle("#frac{#sigma(h)}{#sigma_{SM}} #times B(h#rightarrowaa)")
if (args.model==3):
hist.GetZaxis().SetRangeUser(0.04,1.6)
