def totEvtEff(self,org,dir=None):
low1p,low1,low2p,denom,lowNX,denomX=None,None,None,None,None,None
for step in org.steps:
for plotName in sorted(step.keys()):
if 'LowNE1' == plotName : low1=step[plotName]
if 'NE' == plotName : denom=step[plotName]
if 'NX' == plotName: denomX=step[plotName]
efflow1 = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(low1,denom)])
#fs = [0.01,0.02,0.03,0.06,0.1,0.2,0.3,0.6,1.,2.,3.,6.,10.,20.,30.,60.,100.]
fs = [0.4,0.6,1.,1.4]
fs = [round(a,5) for a in fs]
N=len(fs)
sysmap={'1500494':0.10,'1000148':0.10,'350148':0.10,'12048':0.10}
f=0.89
for i,sample in enumerate(org.samples):
digits=re.findall(r'\d+',sample['name'])
SQ,CHI=digits[0],digits[1]
name='SQ_'+str(SQ)+"_CHI_"+str(CHI) + ('_priv' if 'priv' in sample['name'] else '')
sys=0.1
ctau = self.ctau[self.sig_names.index(name)]
for j in range(N):
x,y=r.Double(0),r.Double(0)
efflow1[i].GetPoint(j,x,y)
e1 = f*float(y)
e1Err = f*efflow1[i].GetErrorY(j)
if e1 > 0. : e1Err = e1*math.sqrt(sys*sys+pow(e1Err/e1,2))
factor=fs[j]
#if factor in [0.1,1,10]:
objects=[ SQ,CHI,factor*ctau,rnd(100*e1,3),rnd(100*e1Err,3)]
print " & ".join(str(a) for a in objects ) + ' \\\\'
output=[(e1,e1Err),(e1,e1Err),[e1,e1Err]]
name = name.replace('_priv','')
pickle.dump(output,open(supy.whereami()+'/../results/'+dir+'/efficiencies/'+name+'_'+str(factor)+'.pkl','w'))
def totEvtEff(self,org,dir=None):
high1,low1,denom=None,None,None
for step in org.steps:
for plotName in sorted(step.keys()):
if 'HighNE1' == plotName : high1=step[plotName]
if 'LowNE1' == plotName : low1=step[plotName]
if 'NE' == plotName : denom=step[plotName]
efflow1 = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(low1,denom)])
effhigh1 = tuple([r.TGraphAsymmErrors(n,d,"cl=0.683 n") for n,d in zip(high1,denom)])
fs = [0.4,0.6,1.,1.4]# old factors for the record if not approved
#fs = [0.1,0.2,0.3,0.6,1.,2.,3.,6.,10.]
allfs = [0.1*a for a in fs] + fs + [10*a for a in fs]
allfs = [round(a,5) for a in allfs]
N=len(allfs)
forbidden=[7,8,9,16,17,18]
sysmap={'1000350':0.075,'1000150':0.075,'400150':0.096,'40050':0.091,'20050':0.10}
f=0.89
for i,sample in enumerate(org.samples):
digits=re.findall(r'\d+',sample['name'])
H,X=digits[1],digits[4]
sys=sysmap[H+X]
name='H_'+str(H)+'_X_'+str(X)
ctau = self.ctau[self.sig_names.index(name)]
for j in range(N):
#if j in forbidden: continue
x,y=r.Double(0),r.Double(0)
efflow1[i].GetPoint(j,x,y)
e1 = f*float(y)
e1Err = f*efflow1[i].GetErrorY(j)
if j>N/3:
effhigh1[i].GetPoint(j,x,y)
e1p = f*float(y)
e1pErr = f*effhigh1[i].GetErrorY(j)
if e1 > 0. : e1Err = e1*math.sqrt(sys*sys+pow(e1Err/e1,2))
factor=allfs[j]
#if factor in [0.1,1,10]:
objects=[ H,X,factor*ctau,rnd(100*e1,3)]
print " & ".join(str(a) for a in objects ) + ' \\\\'
output=[(e1,e1Err),(e1,e1Err),[e1,e1Err]]
pickle.dump(output,open(supy.whereami()+'/../results/'+dir+'/efficiencies/'+name+'_'+str(factor)+'.pkl','w'))
x,w=[],[]
H,X=0,0
for file1,file2 in zip(files1,files2):
data1,data2=pickle.load(open(dir1+'/'+file1)),pickle.load(open(dir2+'/'+file2))
strings=file1[:-4].split('_')
if ((H!=strings[1] or X!=strings[3]) and H!=0):
avg,err=weightedAvg(x,w)
print round(avg,5),round(err,5)
x,w=[],[]
H,X,factor = strings[1],strings[3],eval(strings[4])
if factor != 0.1 and factor!=1 and factor!=10 : continue
e1,e2 = data1[dict[option][1]],data2[dict[option][1]]
if e1[0]==e2[0]==0 : continue
diff = 100* 2*(e1[0]-e2[0])/(e1[0]+e2[0])
n1=pow(e1[0]/e1[1],2)
n2=pow(e2[0]/e2[1],2)
if n1-n2==0: continue
diffe = diff*1./math.sqrt(abs(n1-n2))
#diffe=1
#diffe = 100* 4/pow(e1[0]+e2[0],2)*math.sqrt(pow(e2[0]*e1[1],2)+pow(e1[0]*e2[1],2))
x.append(diff)
w.append(diffe)
e1=tuple([str(rnd(a,2)) for a in e1])
e2=tuple([str(rnd(a,2)) for a in e2])
print file1,e1,e2,rnd(diff,2),rnd(diffe,2)
avg,err = weightedAvg(x,w)
print round(avg,5),round(err,5)
eval(file[:-4].split('_')[3]),
eval(file[:-4].split('_')[4]))
)
files2=sorted(os.listdir(dir2),key=lambda file: (eval(file[:-4].split('_')[1]),
eval(file[:-4].split('_')[3]),
eval(file[:-4].split('_')[4]))
)
files3=sorted(os.listdir(dir3),key=lambda file: (eval(file[:-4].split('_')[1]),
eval(file[:-4].split('_')[3]),
eval(file[:-4].split('_')[4]))
)
x,w=[],[]
for file1,file2,file3 in zip(files1,files2,files3):
dict1,dict2,dict3=pickle.load(open(dir1+'/'+file1)),pickle.load(open(dir2+'/'+file2)),pickle.load(open(dir3+'/'+file3))
factor = eval(file1[:-4].split('_')[4])
if factor != 0.1 and factor!=1 and factor!=10 : continue
e1,e2,e3 = dict1['eff'],dict2['eff'],dict3['eff']
if e1[0]==e2[0]==0 : continue
#x = 0.5*(max(e1[0]+e1[1],e2[0]+e2[1],e3[0]+e3[1])+min(e1[0]-e1[1],e2[0]-e2[1],e3[0]-e3[1]))
#xe = 0.5*(max(e1[0]+e1[1],e2[0]+e2[1],e3[0]+e3[1])-min(e1[0]-e1[1],e2[0]-e2[1],e3[0]-e3[1]))
x = 50*(max(e1[0],e2[0],e3[0])+min(e1[0],e2[0],e3[0]))
xe = 50*(max(e1[0],e2[0],e3[0])-min(e1[0],e2[0],e3[0]))
diffe=1
e1=tuple([str(rnd(a,2)) for a in e1])
e2=tuple([str(rnd(a,2)) for a in e2])
print file1,e1,e2,rnd(x,2),rnd(xe,2),rnd(100*xe/x,2)
