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do_WidthTable.py
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do_WidthTable.py
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import operator
class result(object):
def __init__(self, method, mass, var, cat, width, mean, res, regression=False):
self.method = method
self.mass = mass
self.var = var
self.cat = cat
self.width = width
self.mean = mean
self.res = res
self.regression = regression
def __str__(self):
return "method= " + str(self.method) + "\tmass= " + str(self.mass) + "\tvar= " + str(self.var) + "\tcat= " + str(self.cat) + "\twidth= " + str(self.width) + "\tmean= " + str(self.mean) + "\tres= " + str(self.res) + "\tregression= ", str(self.regression)
def __getitem__(self, i):
if i == 0: return self.method
if i == 1: return self.mass
if i == 2: return self.var
if i == 3: return self.cat
if i == 4: return self.width
if i == 5: return self.mean
if i == 6: return self.res
if i == 7: return self.regression
def getAllResults(filename):
allresults = []
with open(filename) as file:
for line in file:
l = line.split()
imethod = l.index('method=') + 1
imass = l.index('mass=') + 1
ivar = l.index('var=') + 1
icat = l.index('cat=') + 1
iwidth = l.index('width=') + 1
imean = l.index('mean=') + 1
ires = l.index('res=') + 1
res = result(l[imethod], int(l[imass]), l[ivar], l[icat], float(l[iwidth]), float(l[imean]), float(l[ires]))
allresults.append(res)
return allresults
def getFromPerformanceSummary(mass_, var_):
filename = "performanceSummary_m" + str(mass_) + "_" + var_ + ".txt"
allresults = []
with open(filename) as file:
for line in file:
l = line.split()
# Skip the first header line
if "Category" in l[0]:
continue
# Fill no regression first
cat_ = l[0]
method_ = l[1]
mean_ = float(l[2])
width_ = float(l[3])
res_ = float(l[4])
res = result( method_, mass_, var_, cat_, width_, mean_, res_, False)
allresults.append(res)
# With regression
mean_ = float(l[5])
width_ = float(l[6])
res_ = float(l[7])
res = result( method_, mass_, var_, cat_, width_, mean_, res_, True)
allresults.append(res)
return allresults
def filterResults(allResults, isRegression=False):
allResults = [res for res in allResults if res.cat != "allcat" and res.regression == isRegression ]
# allResults = [res for res in allResults if res.var != "mgg" and res.method != "CrystalBall" ]
# allResults.sort(cmp=lambda a,b: cmp(a.mass, b.mass))
return allResults
def getResultsForMass(allResults, mass):
return [res for res in allResults if res.mass == mass]
def sortNicely(allResults):
# var, cat, method
allResults.sort(key=operator.itemgetter(2,3,0))
return allResults
allResults = []
for mass in map(int, "270 300 350 400".split()):
for spectrum in ["mjj", "mggjj"]:
for res in getFromPerformanceSummary(mass, spectrum) :
allResults.append( res )
print "without regression"
filteredResults = filterResults(allResults, False)
for mass in map(int, "270 300 350 400".split()):
line = str(mass)
for res in sortNicely(getResultsForMass(filteredResults, mass)):
line += " & "
line += str(round(res.res, 2))
# print res
line += "\\\\"
print line
print "with regression"
filteredResults = filterResults(allResults, True)
for mass in map(int, "270 300 350 400".split()):
line = str(mass)
for res in sortNicely(getResultsForMass(filteredResults, mass)):
line += " & "
line += str(round(res.res, 2))
# print res
line += "\\\\"
print line
#filename = "resolution_SigmaEff_all.txt"
#allResults = getAllResults(filename)
#filteredResults = filterResults(allResults)
##for mass in map(int, "260 270 300 350 400 450 500 550 600 650 700 800 900 1000 1100".split()):
#for mass in map(int, "270 300 350 400".split()):
# line = str(mass)
# for res in sortNicely(getResultsForMass(filteredResults, mass)):
# line += " & "
# line += str(round(res.width, 2))
## print res
# line += "\\\\"
# print line
#