Weight.py
2.23 KB
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from numpy import shape, arange, log10, histogram
from matplotlib.pyplot import figure, show, hist
from Read import ReadGeneration, ReadWeight, ReadEnergy
def drawWeightHisto(fileId):
'''
Plot particles'weights histogram, generation by generation
Input: directory name
Output: particles'weights histogram
'''
fig = figure()
ax = fig.add_subplot(111)
nbBins =100
weight = ReadWeight(fileId)
generation = ReadGeneration(fileId)
print "file", fileId, "->", shape(generation)[0], "events"
for gen in list(set(generation)):
hist(log10(weight[generation==gen]),nbBins,log=1,range=[0,7],alpha=.5,
label="gen="+str(int(gen)))
ax.legend(loc='best')
ax.set_xlabel("Weight [log]")
ax.set_ylabel("Number of events")
show()
#######################################################################################
def weightVsEnergy(fileId,gen=-1):
'''
Compute particles'weight versus energy
Input: directory name
Input (optional): generation (default = all)
'''
energy = ReadEnergy(fileId)
weight = ReadWeight(fileId)
nbBins = 100
if gen != -1:
generation = ReadGeneration(fileId)
energy=energy[generation==gen]
weight=weight[generation==gen]
nbBins =40
weight,ener=histogram(log10(energy),nbBins,weights=log10(weight))
nb,ener=histogram(log10(energy),nbBins)
ener=10**ener
enercenter=(ener[1:nbBins+1]+ener[0:nbBins])/2
weight /= nb
return enercenter, weight
def drawWeightVsEnergy(fileId):
'''
Plot particles'weight versus energy, generation by generation
Input: directory name
Output: graph of particles'weight versus energy
'''
fig = figure()
ax = fig.add_subplot(111)
generation = ReadGeneration(fileId)
print "file", fileId, "->", shape(generation)[0], "events"
for gen in list(set(generation)):
energy,weight = weightVsEnergy(fileId,gen)
ax.plot(energy,weight,".",label="gen="+str(int(gen)))
energy,weight = weightVsEnergy(fileId)
ax.plot(energy,weight,"k",label="gen=all")
ax.set_xscale('log')
ax.grid(b=True,which='major')
ax.legend(loc="best")
ax.set_title(fileId)
ax.set_xlabel("energy [GeV]")
ax.set_ylabel("mean weight [log]")
show()