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summary.py
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summary.py
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import json
import math
import numpy as np
################################################################################
# Methods ...
#for value in ['signal_num','cb_mean','cb_sigma','cb_alphaL','cb_alphaR','cb_nL','cb_nR',]:
def val_err(dct,string):
return (
dct[string][0], # central value
dct[string][0]-dct[string][1] # central value - low value = error
)
def print_signal_header():
print(
"Trigger"+
" Counts"+
" Mass"+
" Width"+
" cb_alphaL"+
" cb_nL"+
" cb_alphaR"+
" cb_nR"
)
def print_signal_row(dct,trigger,lumi,isMC='mc',region='Jpsi',blind=False):
sub_dct = dct[isMC][region][trigger]
print(f'{trigger:16s}, ',end='')
val,err = val_err(sub_dct,"signal_num")
count = (val,err)
#if isMC=='mc': count = expectation(val,lumi,err,region)
if blind==False: print(f'{val:7.1f}+/-{err:5.1f} , ',end='')
else: print(' blinded , ',end='')
val,err = val_err(sub_dct,"cb_mean")
print(f'{val:5.3f}+/-{err:5.3f} , ',end='')
val,err = val_err(sub_dct,"cb_sigma")
print(f'{val:5.3f}+/-{err:5.3f} , ',end='')
val,err = val_err(sub_dct,"cb_alphaL")
print(f'{val:4.2f}+/-{err:4.2f} , ',end='')
val,err = val_err(sub_dct,"cb_nL")
print(f'{val:6.2f}+/-{err:5.2f} , ',end='')
val,err = val_err(sub_dct,"cb_alphaR")
print(f'{val:4.2f}+/-{err:4.2f} , ',end='')
val,err = val_err(sub_dct,"cb_nR")
print(f'{val:6.2f}+/-{err:5.2f} , ',end='')
print()
return count
def print_signal_table(dct,triggers,isMC="mc",region="Jpsi",blind=False):
print("Table of signal parameter values for","isMC=",isMC,"region=",region)
print_signal_header()
counts = []
for trigger,lumi in triggers:
count,err = print_signal_row(dct,trigger,lumi,isMC=isMC,region=region,blind=blind)
counts.append((count,err))
print()
return counts
def print_bkgd_header():
print(
"Trigger"+
" comb_num"+
" exp_slope"
" part_num"+
" expo_slope"+
#" expo_offset"+
" erfc_mean"+
" erfc_sigma"
)
def print_bkgd_row(dct,trigger,isMC='data',region='Jpsi',partial=True):
sub_dct = dct[isMC][region][trigger]
print(f'{trigger:16s}, ',end='')
val,err = val_err(sub_dct,"comb_num")
print(f'{val:7.1f}+/-{err:5.1f} , ',end='')
val,err = val_err(sub_dct,"exp_slope")
print(f'{val:5.2f}+/-{err:4.2f} , ',end='')
if partial==True:
val,err = val_err(sub_dct,"part_num")
print(f'{val:7.1f}+/-{err:6.1f} , ',end='')
val,err = val_err(sub_dct,"expo_slope")
#print(f'{val:6.1f}+/-{err:5.1f} , ',end='')
#val,err = val_err(sub_dct,"expo_offset")
print(f'{val:5.2f}+/-{err:4.2f} , ',end='')
val,err = val_err(sub_dct,"erfc_mean")
print(f'{val:5.2f}+/-{err:4.2f} , ',end='')
val,err = val_err(sub_dct,"erfc_sigma")
print(f'{val:5.3f}+/-{err:4.3f} , ',end='')
print()
def print_bkgd_table(dct,triggers,region="Jpsi",partial=True):
isMC='data'
print("Table of background parameter values for","isMC=",isMC,"region=",region)
print_bkgd_header()
for trigger,lumi in triggers:
print_bkgd_row(dct,trigger,isMC=isMC,region=region,partial=partial)
print()
def print_comparison_header():
print(
"Trigger"+
" Lint [fb]"+
" AxE [1e-4]"
" Exp. counts"+
" Obs. counts"+
" Ratio"
)
def ntoys(): return 50.e6
def expectation(val,lumi,err=None,region="Jpsi"):
bf = {
"Jpsi":0.001*0.06,
"Psi2S":6.2e-4*7.9e-3,
"LowQ2":4.5e-7,
}.get(region)
eff = val / ntoys()
eff_err = err / ntoys()
exp = lumi * 4.7e11 * 0.4 * bf * eff
exp_err = exp * (eff_err/eff)
return (exp,exp_err)
def print_comparison_table(dct,triggers,region="Jpsi",blind=False):
print("Comparison for observed (data) and expected (MC) in region",region)
print_comparison_header()
ratios = []
for trigger,lumi in triggers:
data = dct["data"][region][trigger]
mc = dct["mc"][region][trigger]
print(f"{trigger:16s}, ",end="")
print(f"{lumi:4.2f}, ",end="")
val,err = val_err(mc,"signal_num")
eff = val / ntoys()
eff_err = err / ntoys()
print(f"{eff/1.e-4:4.2f}+/-{eff_err/1.e-4:4.2f}, " , end="")
exp,exp_err = expectation(val,lumi,err,region)
print(f"{exp:7.1f}+/-{exp_err:5.1f}, ",end="")
obs,obs_err = val_err(data,"signal_num")
if blind==False: print(f'{obs:7.1f}+/-{obs_err:5.1f} ',end='')
else: print(' blinded ',end='')
ratio = obs/exp if exp > 0. else 0.
ratio_err = math.sqrt(exp)/exp * ratio if exp > 0. else 0.
if blind==False: print(f'{ratio:5.2f}+/-{ratio_err:5.2f} ',end='')
else: print(' blinded ',end='')
print()
ratios.append((ratio,ratio_err))
return ratios
def summary(filename,triggers=None,blind=True) :
print("Parsing json file ...")
# Open file and parse json
dct = {}
try:
with open(filename,'r') as f:
try:
dct = json.load(f)
except json.decoder.JSONDecodeError:
print("Problem parsing json contained in file:",filename)
except FileNotFoundError:
print("Problem opening file:",filename)
# Check if MC content is there
if "mc" not in dct:
print("Incorrect json format...")
return
# Tables ...
_partial=True
mc_jpsi = print_signal_table(dct,triggers,isMC="mc",region="Jpsi")
data_jpsi = print_signal_table(dct,triggers,isMC="data",region="Jpsi")
print_bkgd_table(dct,triggers,region="Jpsi",partial=_partial)
mc_psi2s = print_signal_table(dct,triggers,isMC="mc",region="Psi2S")
data_psi2s = print_signal_table(dct,triggers,isMC="data",region="Psi2S")
print_bkgd_table(dct,triggers,region="Psi2S",partial=_partial)
mc_lowq2 = print_signal_table(dct,triggers,isMC="mc",region="LowQ2")
data_lowq2 = print_signal_table(dct,triggers,isMC="data",region="LowQ2",blind=blind)
print_bkgd_table(dct,triggers,region="LowQ2",partial=_partial)
# Comparison
ratios_jpsi = print_comparison_table(dct,triggers,region="Jpsi")
ratios_psi2s = print_comparison_table(dct,triggers,region="Psi2S")
ratios_lowq2 = print_comparison_table(dct,triggers,region="LowQ2",blind=blind)
# Compare
print()
print("Obs and exp: Jpsi and Psi2S")
for (trg,lumi),d_jpsi,m_jpsi,d_psi2s,m_psi2s in zip(triggers,data_jpsi,mc_jpsi,data_psi2s,mc_psi2s):
m_jpsi = expectation(m_jpsi[0],lumi,m_jpsi[1],"Jpsi")
m_psi2s = expectation(m_psi2s[0],lumi,m_psi2s[1],"Psi2S")
print(
f'Trigger: {trg:16s}',
f' (J/psi) Exp: {m_jpsi[0]:7.1f}, Obs: {d_jpsi[0]:7.1f}',
f' (Psi2S) Exp: {m_psi2s[0]:6.1f}, Obs: {d_psi2s[0]:6.1f}',
)
# Double ratio
print()
print("Double ratio: [obs/exp]_Psi2S / [obs/exp]_Jpsi")
for trg,jpsi,psi2s in zip(triggers,ratios_jpsi,ratios_psi2s):
ratio = psi2s[0]/jpsi[0] if jpsi[0]>0. else 0.
ratio_err = ( jpsi[1]/ jpsi[0])**2. if jpsi[0]>0. else 0.
ratio_err += (psi2s[1]/psi2s[0])**2. if psi2s[0]>0. else 0.
ratio_err = ratio * np.sqrt(ratio_err)
#print(trg,ratio,ratio_err)
print(f'Trigger: {trg[0]:16s}, Lumi: {trg[1]:4.2f}, Ratio: {ratio:4.2f} +/- {ratio_err:4.2f}')
# Ratio of AxE
print()
print("AxE [x1E-4]")
for trg,m_jpsi,m_psi2s,m_lowq2 in zip(triggers,mc_jpsi,mc_psi2s,mc_lowq2):
print(
f'Trigger: {trg[0]:16s}',
f' (AxE) J/psi: {m_jpsi[0]*1.e4/ntoys():4.2f}',
f'Psi2S: {m_psi2s[0]*1.e4/ntoys():4.2f}',
f'LowQ2: {m_lowq2[0]*1.e4/ntoys():5.3f}',
f' (Ratios) LowQ2/Jpsi: {m_lowq2[0]/m_jpsi[0] if m_jpsi[0]>0. else 0.:5.3f}',
f'Psi2S/Jpsi: {m_psi2s[0]/m_jpsi[0] if m_jpsi[0]>0. else 0.:5.3f}',
)
# Predict Psi2S
print()
print("Predict @ Psi(2S)")
for (trg,lumi),r_jpsi,m_psi2s,d_psi2s in zip(triggers,ratios_jpsi,mc_psi2s,data_psi2s):
m_psi2s = expectation(m_psi2s[0],lumi,m_psi2s[1],"Psi2S")
print(
f'Trigger: {trg:16s}',
f' Obs/Exp @ Jpsi: {r_jpsi[0]:4.2f}',
f' Exp @ Psi2S: {m_psi2s[0]:5.1f}',
f' Pred @ Psi2S: {m_psi2s[0]*r_jpsi[0]:5.1f}',
f' Obs @ Psi2S: {d_psi2s[0]:5.1f}',
)
# Predict LowQ2 (blinded)
print()
print("Predict @ low q2")
for (trg,lumi),r_jpsi,m_lowq2,d_lowq2 in zip(triggers,ratios_jpsi,mc_lowq2,data_lowq2):
m_lowq2 = expectation(m_lowq2[0],lumi,m_lowq2[1],"LowQ2")
print(
f'Trigger: {trg:16s}',
f' Obs/Exp @ Jpsi: {r_jpsi[0]:4.2f}',
f' Exp @ LowQ2: {m_lowq2[0]:5.1f}',
f' Pred @ LowQ2: {m_lowq2[0]*r_jpsi[0]:5.1f}',
' Obs @ LowQ2:',
f'{d_lowq2[0]:5.1f}' if blind==False else 'blinded',
)
################################################################################
# Main ...
if __name__ == "__main__":
# Production tag
tag = ["2022Sep05","2022Oct12","2022Nov14","2022Test"][-1]
filename = 'output/'+tag+'/params/parameters.json'
triggers = [
# ("trigger_none",7.36),
# ("trigger_OR",7.10),
("L1_11p0_HLT_6p5",7.09),
("L1_10p5_HLT_6p5",7.04),
("L1_10p5_HLT_5p0",6.28),
("L1_8p5_HLT_5p0",6.18),
("L1_8p0_HLT_5p0",5.60),
("L1_7p0_HLT_5p0",2.00),
("L1_6p5_HLT_4p5",1.78),
("L1_6p0_HLT_4p0",0.65),
("L1_5p5_HLT_6p0",0.15),
("L1_5p5_HLT_4p0",0.00),
]
summary(filename,triggers=triggers,blind=True)