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** HITMAPS plotting macro **
# Events #
The idea is to develop some scripts that will make it easy to
analyze the 2D hitmaps, where the number of hits for every strip
is splitted in non-overlapping windows of 10000 events.
The test file is
data15_hi.00287382.calibration_SCTNoise.sctcal.HITMAP.c0._0002.SCTHitMaps.root
which is under /afs/cern.ch/user/a/agasconb/public
In the 24h calibration loop webpage there's a complete list of
the noisy strips for this run (287382), for every 'waffer'. That list
contains the information published in the BadStripSummary xml file:
those strips with occupancy >= 1.5%
The new 2D histograms allow to check the time dependence of the
'noisiness' of the strips. There could be strips that:
* Are noisy because during part of the run had enough hits
to be above the 1.5% threshold, even if during other parts
of the run they had no hits or;
* strips that are noisy during a few periods, but in the total
run don't sum up enough hits to be considered noisy, 'transient
noisy' strips.
One example of the latter is SCTB/0_2_8_-3_02D (barrel, layer 2, phi 8,
eta -3, side 0; 0 being the first barrel layer). In this module,
the noisy strips are [697-698 717 749]. Strips 670,700,703 and 744
are noisy during part the of the run, but in the whole run they
are not 'noisy enough' and as such are not computed as noisy strips
(see TransientExample.png).
# Lumiblocks #
In addition to splitting the strip occupancy in windows of a certain
number of events, the same has been done recording the occupancy
of each strip in each lumiblock. The other root output file (SCTLB)
now contains 2D histograms, one for every waffer, where
the number of hits per strip and lumiblock is stored.
The number of events per lumiblock is not constant. To compute
the occupancy from the raw number of hits, we have to retrieve
the number of events per lumiblock from the GENERAL/events
TH1I histogram
### AnalysisMacro.py ###
This macro loops over the 2D histograms, looking for those with
at least one window with one noisy strips. It saves the 'occupancy
maps' (scaling the 2D histogram and setting the minimum to 0.015,
to avoid the rest of strips) to an output file.