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Info
titleDocumentation

usage : python CALcalib.py -P-D-M Mode
where -P : plot results
-D : Print this doc and stop
-M : PLot Monitoring run : FLE FHE only, This option bypass Mode option
where Mode is : - LAC

  • FLE
  • FHE
  • ALL
    where Tag is the ouput basename

A script only to plot threshold distribution (/a/sulky36/g.glast.u33/sanchez/PlotRun.py)

Info
titleDocumentation

usage : python PlotRun.py -D-M Mode Tag
where -D : Print this doc and stop
-M : PLot Monitoring run : FLE FHE only, This option bypass Mode option
where Mode is : - LAC

  • FLE
  • FHE
  • ALL
    where Tag is the ouput basename

First look at genTrigMonitorHists and fitTrigMonitorHists

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Zach made some changes in the code to be less sensitive to the trigger noise. The main change is a better definition of 'firstNonZeroBin' variable. Here is part of his mail.

Basically I have replaced David's 'firstNonZeroBin' variable w/ a 'firstBin>15%max' which should serve the same purpose - it should avoid sensitivity to any noise triggers in the LAC circuit.

Also I have a gemDeltaEventTime < 500 microseconds cut in genLACHists.exe which should also reduce noise hits.

Also I restricted the threshold fit parameter, making it a little more stable.

I use the new code with the same configuration files and the same run.


LAC value distribution for run 077018222. The new code greatly improve the fit. Only few LAC value are obviously not found.

LEX8 signal histograms for 2 channel badly fitted


LEX8 signal histogram for crystal T3L5C8 , the same as abovewhich was badly fitted with previous version.

Impact on LAC runs, TVAC run 077016907.

There is no major impact. Fitted LAC values remain almost the same.

Using sasha's code

I have use sasha's code with run 077018222. I put his code in cmt and was able to compile it.

I used fill_LAC_hists.C to make histogram and plot_lac_all_channels.cxx to make the following plot.
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Tip
titleNext step

Use : fit_lac_thresh.cxx and compare result with the new version of the GR analyze chain.

Conclusions

We are ready to monitor LAC, FLE, FHE threshold.

training with run backgnd-GR-v15r0-2

h.3 GR code
We train with a simulated run.
PED : digitization-licos-v3r9p3_077014293_digi_DIGI.FLIGHT_GAIN.calPed.txt
MuSlope : digitization-licos-v3r9p3_077014313_digi_DIGI.FLIGHT_GAIN.muSlope.txt

We fit LAC threshold for the NEG face.

Image Added
LAC distribution for NEG face obtained with Zach code

Tip
titlechange in the code

We change firstBin > 15%max by firstBin > 20%max. Without this, the code rise an exception.

h.3 python script to monitor
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FLE/FHE distribution obtained with the monitoring code

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CalMaxEne>>hflenofhe","CalMaxEne>0 && (GemConditionsWord==4 || GemConditionsWord==5 || GemConditionsWord==6 || GemConditionsWord==7)

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CalMaxEne>>hnoflefhe","CalMaxEne>0 && (GemConditionsWord==8 ||GemConditionsWord==9 || GemConditionsWord==10 || GemConditionsWord==11)

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CalMaxEne>>hflefhe","CalMaxEne>0 && (GemConditionsWord==12 || GemConditionsWord==13 || GemConditionsWord==14 || GemConditionsWord==15)

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CalMaxEne>>hnoflenofhe","CalMaxEne>0 && (GemConditionsWord==1 || GemConditionsWord==2 || GemConditionsWord==3 )

Finding LAC value with nomSciOps runs

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