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This repository has been archived by the owner on Jan 31, 2022. It is now read-only.
I do think this is the wrong way to interpret this bug. We should change the scurve object to be a TGraphAsymmErrors made by dividing 2 histograms so C-P confidence intervals are used. Then all fits will be done with an efficiency of 0 to 1 and have the proper error bars. This would also mean several scurves could be statistically summed together and the analysis would be robust. It would also allow the number of pulses per Vcal bin to be unequal and the fit could still work.
I think this is a good suggestion, but I think this is enough of a change where it should be it's own separate issue. For now the proposed solution will serve as a "short term" fix.
Brief summary of issue
In
anaUltraScurve.py
the value forevents/2
is still harded at line 151. Here it is set as500
but should be an input parameter from the input TTree.This should be changed since if a user takes an scurve with non-default settings (nevt=1000) this part of the code may not work as intended.
Low priority since this will work on scans taken with default parameters.
Types of issue
Expected Behavior
Value for
events/2
at line 151 should not be hard coded but instead be an input parameter.Current Behavior
Value is hard coded at
events/2 = 500
at line 151.Possible Solution (for bugs)
Change Line 151 to take an input instead of a hard coded value.
Your Environment
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