Difference: AtlasDataAnalysis (134 vs. 135)

Revision 1352011-12-20 - AlistairGemmell

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templates/fit/out_120.log

This is the paydirt - the output to screen from the fitting stage. Look at the end of this file, and you shall see the exclusions generated by all the pseudoexperiments performed on the ANN output, in a little table, also giving +/- 1/2 sigma results.

Added:

>
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From here you can also get a record of the yields of the various processes considered by the Neural Net (the number of events expected for each process after applying all our preselection cuts, cutmasks, etc in our specified luminosity):

Print out Yield ================
  Channel   & tt       & ttH     & ttbb    & Wlnu     & Wbb     & Wc      & Wcc     & st_Wt   & st_schan & st_tchan & eFake    & Data\\

SemiLeptonic& 2154.475 &   2.598 &  49.313 & 4140.901 & 160.634 & 498.841 & 322.464 &  83.942 &   3.265  &  18.288  & 4069.197 & 10616.000
       sum  & 2154.475 &   2.598 &  49.313 & 4140.901 & 160.634 & 498.841 & 322.464 &  83.942 &   3.265  &  18.288  & 4069.197 & 10616.000
======================================================
NSig 2.59829 NBkg 11501.3 NData 10616
======================================================
End Print out

Just above this is information of the weighted histograms of the various processes (weighted such that the integral equals the yield).

Channel: SemiLeptonic(0) Process: eFake(10)
ib= 1 0.88551 1.50073 wgt=      0.88551 wgtE=     1.50073 wgtEsum2= 2.2522

The first number is the bin number being considered. wgt is the weighted integral of that bin, and all preceding bins (i.e. the total integral up to that point)

Immediately following this is the record of generating the first pseudoexperiment. It lists the weighted contents of each of the bins of a neural net histogram, assuming background only, with poisson fluctuations. It then gives the integral of this pseudoexperiment:

Pseudodata Integral: 11506

For obvious reasons this should be similar to the projected background yield.

Later on, at the start of the fitting we also have the following:

= After fit ==========================================
Parameters fit: 7
Name        Value        Error
=========== ============ =========
LumiTrigLepID : 0.0140496 0.903865
JES : 0.00324431 0.980996
Met : 0.00131664 0.99884
btag : 0.0197434 0.649849
NLOAccep : -0.0627014 0.727165
pdf : -0.0106981 0.99073
xsec : 0.00620052 0.923289

These values come from a Minuit fit, so should be taken with a pinch of salt. The 'Value' compares the results of the pseudoexperiment for all the various errors, and compares it to what you told it. E.g. if you said you had 1fb-1 for luminosity, but the pseudodata suggested a luminosity of 1.01, then Value would be 0.01 - you are 'out' by 1%. 'Error' says how much of your proposed error you have 'used' - if you say you have a 10% error on your luminosity, but the fit suggests at 1% error, then 'Error' would be 0.10 - you are using 10% of your 'allowed' error.

drivetestFlatFitAtlastth.rootUnscaledTemplates.root.

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