notebook.community

Edit and run 





In [2]:



    


%pylab inline --no-import-all
import ROOT



    


















    






Populating the interactive namespace from numpy and matplotlib

















In [3]:



    


import rootnotes
c1 = rootnotes.default_canvas()



    











In [4]:



    


%ls csv



    


















    






ConvertToRoot.C                        parameterized_inc05_indexed.root?dl=0
fixed.csv                              parameterized_inc10.csv
parameterized.root                     parameterized_inc10.root
parameterized_inc05.csv.gz             parameterized_inc10_indexed.root
parameterized_inc05.root

















In [5]:



    


f= ROOT.TFile('csv/parameterized.root')
tree = f.Get('parameterized')



    











In [6]:



    


tree.Print()



    











In [40]:



    


tree.Draw('mwwbb:nn','jesParam==1 && label==1')
c1



    


















    
Out[40]:
























In [13]:



    


tree.Draw('jesParam*10','','')
c1



    


















    
Out[13]:
























In [41]:



    


jesParamValues = np.linspace(5,15,11)/10
jesParamValues



    


















    
Out[41]:








array([ 0.5,  0.6,  0.7,  0.8,  0.9,  1. ,  1.1,  1.2,  1.3,  1.4,  1.5])

















In [42]:



    


jesTrueValues = [0.75, 0.9, 0.95, 0.975, 1, 1.025, 1.05, 1.1, 1.25]
jesParamValues = jesTrueValues
tree.SetLineColor(0)
tree.Draw('jesTrue*10','label==0 ')
tree.SetLineColor(2)
for i in jesTrueValues:
    print 'label==0 && jesTrue==%s' %(i)
    print i, tree.Draw('jesTrue*10','label==0 && fabs(jesTrue-%s)<0.001' %(i),'same')
c1



    


















    






label==0 && jesTrue==0.75
0.75 1231848
label==0 && jesTrue==0.9
0.9 1231848
label==0 && jesTrue==0.95
0.95 1231848
label==0 && jesTrue==0.975
0.975 1231848
label==0 && jesTrue==1
1 1231848
label==0 && jesTrue==1.025
1.025 1231848
label==0 && jesTrue==1.05
1.05 1231848
label==0 && jesTrue==1.1
1.1









    






---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
<ipython-input-42-689e24038960> in <module>()
      6 for i in jesTrueValues:
      7     print 'label==0 && jesTrue==%s' %(i)
----> 8     print i, tree.Draw('jesTrue*10','label==0 && fabs(jesTrue-%s)<0.001' %(i),'same')
      9 c1

KeyboardInterrupt: 
















In [43]:



    


histograms = []
for jesTrue in jesTrueValues:
    for jesParam in jesParamValues:
        for label in [0,1]:
            title = 'h_%.3f_%.3f_%d' %(jesTrue, jesParam,label)
            print title
            h = ROOT.TH1F(title, 'test',100,0,1)
            histograms.append(h)
            cut = 'fabs(jesTrue-%f)<0.001 && fabs(jesParam-%f)<0.001 && label == %d' \
            %(jesTrue, jesParam,label)
            print cut
            tree.Draw('nn >> '+title, cut)



    


















    






 h_0.750_0.750_0
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 0
h_0.750_0.750_1
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 1
h_0.750_0.900_0
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 0
h_0.750_0.900_1
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 1
h_0.750_0.950_0
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 0
h_0.750_0.950_1
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 1
h_0.750_0.975_0
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 0
h_0.750_0.975_1
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 1
h_0.750_1.000_0
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 0
h_0.750_1.000_1
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 1
h_0.750_1.025_0
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 0
h_0.750_1.025_1
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 1
h_0.750_1.050_0
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 0
h_0.750_1.050_1
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 1
h_0.750_1.100_0
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 0
h_0.750_1.100_1
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 1
h_0.750_1.250_0
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 0
h_0.750_1.250_1
fabs(jesTrue-0.750000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 1
h_0.900_0.750_0
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 0
h_0.900_0.750_1
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 1
h_0.900_0.900_0
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 0
h_0.900_0.900_1
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 1
h_0.900_0.950_0
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 0
h_0.900_0.950_1
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 1
h_0.900_0.975_0
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 0
h_0.900_0.975_1
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 1
h_0.900_1.000_0
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 0
h_0.900_1.000_1
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 1
h_0.900_1.025_0
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 0
h_0.900_1.025_1
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 1
h_0.900_1.050_0
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 0
h_0.900_1.050_1
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 1
h_0.900_1.100_0
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 0
h_0.900_1.100_1
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 1
h_0.900_1.250_0
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 0
h_0.900_1.250_1
fabs(jesTrue-0.900000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 1
h_0.950_0.750_0
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 0
h_0.950_0.750_1
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 1
h_0.950_0.900_0
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 0
h_0.950_0.900_1
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 1
h_0.950_0.950_0
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 0
h_0.950_0.950_1
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 1
h_0.950_0.975_0
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 0
h_0.950_0.975_1
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 1
h_0.950_1.000_0
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 0
h_0.950_1.000_1
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 1
h_0.950_1.025_0
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 0
h_0.950_1.025_1
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 1
h_0.950_1.050_0
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 0
h_0.950_1.050_1
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 1
h_0.950_1.100_0
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 0
h_0.950_1.100_1
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 1
h_0.950_1.250_0
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 0
h_0.950_1.250_1
fabs(jesTrue-0.950000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 1
h_0.975_0.750_0
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 0
h_0.975_0.750_1
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 1
h_0.975_0.900_0
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 0
h_0.975_0.900_1
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 1
h_0.975_0.950_0
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 0
h_0.975_0.950_1
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 1
h_0.975_0.975_0
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 0
h_0.975_0.975_1
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 1
h_0.975_1.000_0
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 0
h_0.975_1.000_1
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 1
h_0.975_1.025_0
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 0
h_0.975_1.025_1
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 1
h_0.975_1.050_0
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 0
h_0.975_1.050_1
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 1
h_0.975_1.100_0
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 0
h_0.975_1.100_1
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 1
h_0.975_1.250_0
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 0
h_0.975_1.250_1
fabs(jesTrue-0.975000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 1
h_1.000_0.750_0
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 0
h_1.000_0.750_1
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 1
h_1.000_0.900_0
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 0
h_1.000_0.900_1
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 1
h_1.000_0.950_0
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 0
h_1.000_0.950_1
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 1
h_1.000_0.975_0
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 0
h_1.000_0.975_1
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 1
h_1.000_1.000_0
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 0
h_1.000_1.000_1
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 1
h_1.000_1.025_0
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 0
h_1.000_1.025_1
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 1
h_1.000_1.050_0
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 0
h_1.000_1.050_1
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 1
h_1.000_1.100_0
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 0
h_1.000_1.100_1
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 1
h_1.000_1.250_0
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 0
h_1.000_1.250_1
fabs(jesTrue-1.000000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 1
h_1.025_0.750_0
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 0
h_1.025_0.750_1
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 1
h_1.025_0.900_0
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 0
h_1.025_0.900_1
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 1
h_1.025_0.950_0
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 0
h_1.025_0.950_1
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 1
h_1.025_0.975_0
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 0
h_1.025_0.975_1
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 1
h_1.025_1.000_0
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 0
h_1.025_1.000_1
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 1
h_1.025_1.025_0
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 0
h_1.025_1.025_1
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 1
h_1.025_1.050_0
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 0
h_1.025_1.050_1
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 1
h_1.025_1.100_0
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 0
h_1.025_1.100_1
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 1
h_1.025_1.250_0
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 0
h_1.025_1.250_1
fabs(jesTrue-1.025000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 1
h_1.050_0.750_0
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 0
h_1.050_0.750_1
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 1
h_1.050_0.900_0
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 0
h_1.050_0.900_1
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 1
h_1.050_0.950_0
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 0
h_1.050_0.950_1
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 1
h_1.050_0.975_0
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 0
h_1.050_0.975_1
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 1
h_1.050_1.000_0
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 0
h_1.050_1.000_1
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 1
h_1.050_1.025_0
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 0
h_1.050_1.025_1
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 1
h_1.050_1.050_0
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 0
h_1.050_1.050_1
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 1
h_1.050_1.100_0
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 0
h_1.050_1.100_1
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 1
h_1.050_1.250_0
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 0
h_1.050_1.250_1
fabs(jesTrue-1.050000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 1
h_1.100_0.750_0
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 0
h_1.100_0.750_1
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 1
h_1.100_0.900_0
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 0
h_1.100_0.900_1
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 1
h_1.100_0.950_0
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 0
h_1.100_0.950_1
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 1
h_1.100_0.975_0
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 0
h_1.100_0.975_1
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 1
h_1.100_1.000_0
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 0
h_1.100_1.000_1
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 1
h_1.100_1.025_0
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 0
h_1.100_1.025_1
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 1
h_1.100_1.050_0
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 0
h_1.100_1.050_1
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 1
h_1.100_1.100_0
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 0
h_1.100_1.100_1
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 1
h_1.100_1.250_0
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 0
h_1.100_1.250_1
fabs(jesTrue-1.100000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 1
h_1.250_0.750_0
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 0
h_1.250_0.750_1
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-0.750000)<0.001 && label == 1
h_1.250_0.900_0
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 0
h_1.250_0.900_1
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-0.900000)<0.001 && label == 1
h_1.250_0.950_0
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 0
h_1.250_0.950_1
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-0.950000)<0.001 && label == 1
h_1.250_0.975_0
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 0
h_1.250_0.975_1
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-0.975000)<0.001 && label == 1
h_1.250_1.000_0
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 0
h_1.250_1.000_1
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.000000)<0.001 && label == 1
h_1.250_1.025_0
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 0
h_1.250_1.025_1
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.025000)<0.001 && label == 1
h_1.250_1.050_0
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 0
h_1.250_1.050_1
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.050000)<0.001 && label == 1
h_1.250_1.100_0
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 0
h_1.250_1.100_1
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.100000)<0.001 && label == 1
h_1.250_1.250_0
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 0
h_1.250_1.250_1
fabs(jesTrue-1.250000)<0.001 && fabs(jesParam-1.250000)<0.001 && label == 1

















In [44]:



    


for h in histograms:
    print h.GetEntries()



    


















    






136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0
136872.0
304744.0

















In [45]:



    


newf = ROOT.TFile("histograms_parameterized.root","RECREATE")
for h in histograms:
    h.GetEntries()
    h.Write()
newf.Close()



    











In [30]:



    


len(histograms)



    


















    
Out[30]:








198

















In [34]:



    


opt = ''
for i in range(99):
    histograms[2*i+1].Draw(opt)
    opt = 'same'
c1



    


















    
Out[34]:
























In [26]:



    


sigHist = ROOT.TH1F('sigHist','',30,0,3000)
bkgHist = sigHist.Clone('bkgHist')
tree.Draw("mwwbb >> sigHist","ijesParam==3 && ijesTrue==3 && label==1")
tree.Draw("mwwbb >> bkgHist","ijesParam==3 && ijesTrue==3 && label==0")
sigHist.Draw()
bkgHist.Draw('same')
c1



    


















    






TFile::Append:0: RuntimeWarning: Replacing existing TH1: sigHist (Potential memory leak).










    
Out[26]:
























In [27]:



    


sigHist.Divide(bkgHist)
sigHist.Draw('e')
c1



    


















    
Out[27]:
























In [ ]:

Content source: cranmer/parametrized-learning

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