def directories(args) :
## prepare structure of parent directories
dirs = []
for dir in args :
if is_number(get_mass(dir)) or get_mass(dir) == "common" :
dir = dir[:dir.rstrip('/').rfind('/')]
if not dir in dirs :
dirs.append(dir)
## prepare mapping of masses per parent directory
masses = {}
for dir in dirs :
buffer = []
for path in args :
if dir+'/' in path :
if is_number(get_mass(path)) :
mass = get_mass(path)
if not contained(mass, buffer) :
buffer.append(mass)
masses[dir] = list(buffer)
return (dirs, masses)
def directories(args) :
## prepare structure of parent directories
dirs = []
for dir in args :
if is_number(get_mass(dir)) or get_mass(dir) == "common" :
dir = dir[:dir.rstrip('/').rfind('/')]
if not dir in dirs :
dirs.append(dir)
## prepare mapping of masses per parent directory
masses = {}
for dir in dirs :
buffer = []
for path in args :
if dir+'/' in path :
if is_number(get_mass(path)) :
mass = get_mass(path)
if not contained(mass, buffer) :
buffer.append(mass)
masses[dir] = list(buffer)
return (dirs, masses)
if file == "tmp.txt":
# Ignore generated combined file - can't be parsed..
continue
an = matcher.match(file).group("ANALYSIS")
matcher = re.compile(exprV)
if an != "vhtt":
matcher = re.compile(expr)
cat = matcher.match(file).group("CATEGORY")
chn = matcher.match(file).group("CHANNEL")
per = matcher.match(file).group("PERIOD")
# print "an:",an,"chn:",chn,"cat:",cat,"per:",per
if an == "vhtt" and (cat == "0" or cat == "2"):
chn = "wh"
if an == "vhtt" and cat == "1":
chn = "zh"
if not contained(cat, categories):
categories.append(cat)
if not contained(chn, channels):
channels.append(chn)
if not contained(per, periods):
periods.append(per)
print "Picking up channels, categories and periods from datacards in input directory:", options.input
print "------------------------------------------------------------------------------"
print "Expecting datacards of type htt_chn_cat_per.txt, with the following valid "
print "variables: "
print " - chn : em, et, mt, mm, tt"
print " - cat : 0, 1, 2, 3, 5, 6, 7, 8, 9"
print " - per : 7TeV, 8TeV, 14TeV"
print "------------------------------------------------------------------------------"
print "Picked up categories are:", categories
def merge_efficiencies(channel, categories, periods) :
"""
Merge the contents of the *.tmp files used to temporarily safe the information for the calculation
of the signal efficiencies.The argument categories should contain a compact dictionary of event
sub-categories to be contracted into main event-categories, the argument contains the list of all
run periods to be considered. First the information per run period is added. Then the infomration
of the event sub-categories is contracted into the main event categories. The results are safed in
a *.tmp file labeld by the channel but no run period label. The information integrated over the
run periods but not yet contracted into the main event categories is safed in a file which carries
the extra label *_split.tmp. Only the signal channels ggH, qqH and VH are taken into account. VH
it the sum of WH, ZH and ttH.
"""
## list of subsets (used for contraction of sub-categories)
subsets = []
## lines used to add periods
lines = dict([(per, []) for per in periods])
## combine run periods
for per in periods:
file = open('eff_'+channel+'_'+per+'.tmp')
for line in file :
values = line.split()
if len(values) == 1 :
if not contained(values[0], subsets) :
subsets.append(values[0])
lines[per].append(values)
file.close()
file = open('eff_'+channel+'_split.tmp', 'w')
for i in range(len(lines[periods[0]])) :
line = lines[periods[0]][i]
if len(line) == 1 :
file.write(line[0]+'\n')
else :
line_summed = []
for per in periods :
for j in range(len(lines[per][i])) :
if len(line_summed) == j :
line_summed.append(float(lines[per][i][j]) if j>0 else str(lines[per][i][j]))
elif j>0 :
line_summed[j]+=float(lines[per][i][j])
file.write("%s \t %f \t %f \n" % (line_summed[0], line_summed[1], line_summed[2]))
file.close()
## lines used to add sub-categories
lines = dict([(sub, []) for sub in subsets])
## combine sub-categories
file = open('eff_'+channel+'_split.tmp')
file_empty = True
for line in file :
file_empty = False
values = line.split()
if len(values) == 1 :
subset = values[0]
else :
for value in values :
lines[subset].append(value)
file.close()
if not file_empty :
file = open('eff_'+channel+'.tmp', 'w')
for cat, subsets in categories.iteritems() :
file.write(channel+'_'+cat+'\n')
if len(subsets) == 0 :
if options.analysis == "mssm" :
file.write("%s \t %s \t %s \n" % (lines[channel+'_'+cat][0], lines[channel+'_'+cat][1], lines[channel+'_'+cat][2]))
file.write("%s \t %s \t %s \n" % (lines[channel+'_'+cat][3], lines[channel+'_'+cat][4], lines[channel+'_'+cat][5]))
else :
file.write("%s \t %s \t %s \n" % (lines[channel+'_'+cat][0], lines[channel+'_'+cat][1], lines[channel+'_'+cat][2]))
file.write("%s \t %s \t %s \n" % (lines[channel+'_'+cat][3], lines[channel+'_'+cat][4], lines[channel+'_'+cat][5]))
file.write("%s \t %s \t %s \n" % (lines[channel+'_'+cat][6], lines[channel+'_'+cat][7], lines[channel+'_'+cat][8]))
else :
lines_summed = {}
if options.analysis == "mssm" :
lines_summed = {
'ggH' : 0.,
'bbH' : 0.,
}
else:
lines_summed = {
'ggH' : 0.,
'qqH' : 0.,
'VH' : 0.,
}
for sub in subsets :
if options.analysis == "mssm" :
lines_summed['ggH']+=float(lines[channel+'_'+cat+'_'+sub][1])
lines_summed['bbH']+=float(lines[channel+'_'+cat+'_'+sub][4])
else :
if len(lines[channel+'_'+cat+'_'+sub])>0 :
lines_summed['ggH']+=float(lines[channel+'_'+cat+'_'+sub][1])
lines_summed['qqH']+=float(lines[channel+'_'+cat+'_'+sub][4])
lines_summed['VH' ]+=float(lines[channel+'_'+cat+'_'+sub][7])
if options.analysis == "mssm" :
file.write("%s \t %f \t %s \n" % (lines[channel+'_'+cat+'_'+sub][0], lines_summed['ggH'], lines[channel+'_'+cat+'_'+sub][2]))
file.write("%s \t %f \t %s \n" % (lines[channel+'_'+cat+'_'+sub][3], lines_summed['bbH'], lines[channel+'_'+cat+'_'+sub][5]))
else :
if len(lines[channel+'_'+cat+'_'+sub])>0 :
file.write("%s \t %f \t %s \n" % (lines[channel+'_'+cat+'_'+sub][0], lines_summed['ggH'], lines[channel+'_'+cat+'_'+sub][2]))
file.write("%s \t %f \t %s \n" % (lines[channel+'_'+cat+'_'+sub][3], lines_summed['qqH'], lines[channel+'_'+cat+'_'+sub][5]))
file.write("%s \t %f \t %s \n" % (lines[channel+'_'+cat+'_'+sub][6], lines_summed['VH' ], lines[channel+'_'+cat+'_'+sub][8]))
file.close()
output.write("\\end{center} \n")
output.write("\\end{table*} \n")
return
## channels to be considered
channels = options.channels.split()
for idx in range(len(channels)) : channels[idx] = channels[idx].rstrip(',')## channels
## categories to be considered
categories = options.categories.split()
for idx in range(len(categories)) : categories[idx] = categories[idx].rstrip(',')
## periods to be considered
periods = options.period.split()
for idx in range(len(periods)) : periods[idx] = periods[idx].rstrip(',')
## extended dictionary of subsets to be contracted (used for merging of table yields)
if len(periods) == 1 and contained('7TeV', periods) :
subsets_extended = {
"0jet" : ["low_7TeV", "high_7TeV"],
"boost" : ["low_7TeV", "high_7TeV"],
"vbf" : ["7TeV"],
#"btag" : ["7TeV"],
#"nobtag": ["7TeV"],
}
if len(periods) == 1 and contained('8TeV', periods) :
subsets_extended = {
"0jet" : ["low_8TeV", "high_8TeV"],
"boost" : ["low_8TeV", "high_8TeV"],
#"boost" : ["8TeV"], ##for tt
"vbf" : ["8TeV"],
#"btag" : ["8TeV"],
#"nobtag": ["8TeV"],
def merge_efficiencies(channel, categories, periods):
"""
Merge the contents of the *.tmp files used to temporarily safe the information for the calculation
of the signal efficiencies.The argument categories should contain a compact dictionary of event
sub-categories to be contracted into main event-categories, the argument contains the list of all
run periods to be considered. First the information per run period is added. Then the infomration
of the event sub-categories is contracted into the main event categories. The results are safed in
a *.tmp file labeld by the channel but no run period label. The information integrated over the
run periods but not yet contracted into the main event categories is safed in a file which carries
the extra label *_split.tmp. Only the signal channels ggH, qqH and VH are taken into account. VH
it the sum of WH, ZH and ttH.
"""
## list of subsets (used for contraction of sub-categories)
subsets = []
## lines used to add periods
lines = dict([(per, []) for per in periods])
## combine run periods
for per in periods:
file = open('eff_' + channel + '_' + per + '.tmp')
for line in file:
values = line.split()
if len(values) == 1:
if not contained(values[0], subsets):
subsets.append(values[0])
lines[per].append(values)
file.close()
file = open('eff_' + channel + '_split.tmp', 'w')
for i in range(len(lines[periods[0]])):
line = lines[periods[0]][i]
if len(line) == 1:
file.write(line[0] + '\n')
else:
line_summed = []
for per in periods:
for j in range(len(lines[per][i])):
if len(line_summed) == j:
line_summed.append(
float(lines[per][i][j]
) if j > 0 else str(lines[per][i][j]))
elif j > 0:
line_summed[j] += float(lines[per][i][j])
file.write("%s \t %f \t %f \n" %
(line_summed[0], line_summed[1], line_summed[2]))
file.close()
## lines used to add sub-categories
lines = dict([(sub, []) for sub in subsets])
## combine sub-categories
file = open('eff_' + channel + '_split.tmp')
file_empty = True
for line in file:
file_empty = False
values = line.split()
if len(values) == 1:
subset = values[0]
else:
for value in values:
lines[subset].append(value)
file.close()
if not file_empty:
file = open('eff_' + channel + '.tmp', 'w')
for cat, subsets in categories.iteritems():
file.write(channel + '_' + cat + '\n')
if len(subsets) == 0:
if options.analysis == "mssm":
file.write("%s \t %s \t %s \n" %
(lines[channel + '_' + cat][0],
lines[channel + '_' + cat][1],
lines[channel + '_' + cat][2]))
file.write("%s \t %s \t %s \n" %
(lines[channel + '_' + cat][3],
lines[channel + '_' + cat][4],
lines[channel + '_' + cat][5]))
else:
file.write("%s \t %s \t %s \n" %
(lines[channel + '_' + cat][0],
lines[channel + '_' + cat][1],
lines[channel + '_' + cat][2]))
file.write("%s \t %s \t %s \n" %
(lines[channel + '_' + cat][3],
lines[channel + '_' + cat][4],
lines[channel + '_' + cat][5]))
file.write("%s \t %s \t %s \n" %
(lines[channel + '_' + cat][6],
lines[channel + '_' + cat][7],
lines[channel + '_' + cat][8]))
else:
lines_summed = {}
if options.analysis == "mssm":
lines_summed = {
'ggH': 0.,
'bbH': 0.,
}
else:
lines_summed = {
'ggH': 0.,
'qqH': 0.,
'VH': 0.,
}
for sub in subsets:
if options.analysis == "mssm":
lines_summed['ggH'] += float(lines[channel + '_' +
cat + '_' + sub][1])
lines_summed['bbH'] += float(lines[channel + '_' +
cat + '_' + sub][4])
else:
if len(lines[channel + '_' + cat + '_' + sub]) > 0:
lines_summed['ggH'] += float(
lines[channel + '_' + cat + '_' + sub][1])
lines_summed['qqH'] += float(
lines[channel + '_' + cat + '_' + sub][4])
lines_summed['VH'] += float(
lines[channel + '_' + cat + '_' + sub][7])
if options.analysis == "mssm":
file.write("%s \t %f \t %s \n" %
(lines[channel + '_' + cat + '_' + sub][0],
lines_summed['ggH'],
lines[channel + '_' + cat + '_' + sub][2]))
file.write("%s \t %f \t %s \n" %
(lines[channel + '_' + cat + '_' + sub][3],
lines_summed['bbH'],
lines[channel + '_' + cat + '_' + sub][5]))
else:
if len(lines[channel + '_' + cat + '_' + sub]) > 0:
file.write("%s \t %f \t %s \n" %
(lines[channel + '_' + cat + '_' + sub][0],
lines_summed['ggH'],
lines[channel + '_' + cat + '_' + sub][2]))
file.write("%s \t %f \t %s \n" %
(lines[channel + '_' + cat + '_' + sub][3],
lines_summed['qqH'],
lines[channel + '_' + cat + '_' + sub][5]))
file.write("%s \t %f \t %s \n" %
(lines[channel + '_' + cat + '_' + sub][6],
lines_summed['VH'],
lines[channel + '_' + cat + '_' + sub][8]))
file.close()
## channels to be considered
channels = options.channels.split()
for idx in range(len(channels)):
channels[idx] = channels[idx].rstrip(',') ## channels
## categories to be considered
categories = options.categories.split()
for idx in range(len(categories)):
categories[idx] = categories[idx].rstrip(',')
## periods to be considered
periods = options.period.split()
for idx in range(len(periods)):
periods[idx] = periods[idx].rstrip(',')
## extended dictionary of subsets to be contracted (used for merging of table yields)
if len(periods) == 1 and contained('7TeV', periods):
subsets_extended = {
"0jet": ["low_7TeV", "high_7TeV"],
"boost": ["low_7TeV", "high_7TeV"],
"vbf": ["7TeV"],
#"btag" : ["7TeV"],
#"nobtag": ["7TeV"],
}
if len(periods) == 1 and contained('8TeV', periods):
subsets_extended = {
"0jet": ["low_8TeV", "high_8TeV"],
"boost": ["low_8TeV", "high_8TeV"],
#"boost" : ["8TeV"], ##for tt
"vbf": ["8TeV"],
#"btag" : ["8TeV"],
#"nobtag": ["8TeV"],
if file == 'tmp.txt':
# Ignore generated combined file - can't be parsed..
continue
an = matcher.match(file).group('ANALYSIS')
matcher = re.compile(exprV)
if an != 'vhtt' :
matcher = re.compile(expr)
cat = matcher.match(file).group('CATEGORY')
chn = matcher.match(file).group('CHANNEL')
per = matcher.match(file).group('PERIOD')
#print "an:",an,"chn:",chn,"cat:",cat,"per:",per
if an == 'vhtt' and (cat == '0' or cat == '2'):
chn = 'wh'
if an == 'vhtt' and cat == '1' :
chn = 'zh'
if not contained(cat, categories) :
categories.append(cat)
if not contained(chn, channels) :
channels.append(chn)
if not contained(per, periods) :
periods.append(per)
print "Picking up channels, categories and periods from datacards in input directory:", options.input
print "------------------------------------------------------------------------------"
print "Expecting datacards of type htt_chn_cat_per.txt, with the following valid "
print "variables: "
print " - chn : em, et, mt, mm, tt"
print " - cat : 0, 1, 2, 3, 5, 6, 7, 8, 9"
print " - per : 7TeV, 8TeV, 14TeV"
print "------------------------------------------------------------------------------"
print "Picked up categories are:", categories
else :
## directories and mases per directory
struct = directories(args)
lxb_submit(struct[0], struct[1], cmd, "{MODEL} {OPTS} {USER}".format(MODEL=model, OPTS=opts, USER=options.opt))
##
## INJECTED (asymptotic limits with signal injected, implementation for SM only)
##
if options.optInject :
## the input for lxb-injected.py should be a path, that is passed on as an
## option and the masses in question. Prepare here the corresponding paths
## and directories.
paths = []
dirs = {}
for dir in args :
head = dir[:dir.rstrip('/').rfind('/')]
if not contained(head, paths) :
paths.append(head)
dirs[head] = []
for dir in args :
for path in paths :
if path in dir :
tail = dir[dir.rstrip('/').rfind('/')+1:]
if is_number(tail) :
dirs[path].append(tail)
if not options.calculate_injected :
## prepare options
opts = options.opt
opts+=" --observedOnly"
if not options.nuisances == "" :
opts+=" --no-prefit --external-pulls \"{PATH}\" --signal-plus-background {SPLUSB}".format(PATH=options.nuisances, SPLUSB=options.signal_plus_BG)
method = options.injected_method#"--asymptotic"
## channels to be considered
channels = options.channels.split()
for idx in range(len(channels)):
channels[idx] = channels[idx].rstrip(",") ## channels
## categories to be considered
categories = options.categories.split()
for idx in range(len(categories)):
categories[idx] = categories[idx].rstrip(",")
## periods to be considered
periods = options.period.split()
for idx in range(len(periods)):
periods[idx] = periods[idx].rstrip(",")
## extended dictionary of subsets to be contracted (used for merging of table yields)
if len(periods) == 1 and contained("7TeV", periods):
if options.analysis == "mssm":
subsets_extended = {"btag": ["7TeV"], "nobtag": ["7TeV"]}
else:
if len(channels) == 1 and contained("em", channels):
subsets_extended = {
"0jet": ["low_7TeV", "high_7TeV"],
"1jet": ["low_7TeV", "high_7TeV"],
"vbf": ["loose_7TeV"],
}
elif len(channels) == 1 and contained("et", channels):
subsets_extended = {
"0jet": ["medium_7TeV", "high_7TeV"],
"1jet": ["medium_7TeV", "high_mediumhiggs_7TeV"],
"vbf": ["loose_7TeV"],
}
for idx in range(len(channels)) : channels[idx] = channels[idx].rstrip(',')## channels
## categories
categories = options.categories.split()
for idx in range(len(categories)) : categories[idx] = categories[idx].rstrip(',')
## periods
periods = options.period.split()
for idx in range(len(periods)) : periods[idx] = periods[idx].rstrip(',')
os.system("rm -f *.tmp")
for chn in channels :
for per in periods :
for cat in categories :
filename = options.input+"/htt_"+chn+"_"+cat+"_"+per+"-"+options.mass+".txt"
extractor(filename, per)
if contained("0", categories) and contained("1", categories):
mergingCategories(chn,'0Jet',per)
if contained("1", categories) and contained("2", categories):
mergingCategories(chn,'Boosted',per)
if contained("6", categories) and contained("7", categories):
mergingCategories(chn,'Btag',per)
if contained("7TeV", periods) and contained("8TeV", periods) :
for cat in categories :
mergingPeriods(chn, cat)
makingTables(chn, "7+8TeV", True)
else :
for per in periods :
makingTables(chn, per, True)
os.system("rm *.tmp")
## channels to be considered
channels = options.channels.split()
for idx in range(len(channels)):
channels[idx] = channels[idx].rstrip(',') ## channels
## categories to be considered
categories = options.categories.split()
for idx in range(len(categories)):
categories[idx] = categories[idx].rstrip(',')
## periods to be considered
periods = options.period.split()
for idx in range(len(periods)):
periods[idx] = periods[idx].rstrip(',')
## extended dictionary of subsets to be contracted (used for merging of table yields)
if len(periods) == 1 and contained('7TeV', periods):
if options.analysis == "mssm":
subsets_extended = {
"btag": ["7TeV"],
"nobtag": ["7TeV"],
}
else:
if len(channels) == 1 and contained('em', channels):
subsets_extended = {
"0jet": ["low_7TeV", "high_7TeV"],
"1jet": ["low_7TeV", "high_7TeV"],
"vbf": ["loose_7TeV"],
}
elif len(channels) == 1 and contained('et', channels):
subsets_extended = {
"0jet": ["medium_7TeV", "high_7TeV"],
