From A.Agocs: Fixed integer overflow in mu calculation. The multiplication nB*orbits in AliTriggerRunScalers::CalculateMu was truncated to 32 bits because the result type of the multiplication is the widest of its operand, which is UInt_t of the orbits variable, a 32 bit unsigned integer. I found that this is not always enough to contain the result of the multiplication. Run 146805 from period LHC11a overflows the multiplication: nB = 47
orbits = 275952095
nb*orbits = 12969748465 = 3 * 2^32 + 84846577
Reduce the number of histograms in case of SS plotting option is on, if it is requested
Add some new MC related histograms in several classes
Electron analysis produces now electron or calorimeter hadron AOD to be used in isolation and correlation
---> Added another output slot with a TTree with cascade candidates,
as a necessary first step towards a re-execution of 7TeV analysis for
cross-checking the MC "bad chunk" bug as well as a potential execution
with a simulaneous V0+cascade extraction code for 2.76TeV pp. This is a
renewed version of the code used for the Multi-strange at 7TeV paper.
---> Still needed: isolation and rejection of "bad chunks" in MC (will
leave that for the next commit, now this is under testing phase).
Min pt cut on cascade daughter tracks added (parameter); control histos for the cut above added; big output objects (AliCFContainers) removed from the TList output and moved to separate output slots.
Fixed bug with half-and-half v0s identified as whole ones in MC, made better histograms of (most) cut variables, renamed histograms, added histograms for direct comparison between MC and data
Now, we use the reconstructor
to properly pedestal subtract and gain calibrate the
signals. This allows us - since the signals are now on
the same footing - to fit a function the summed spectra.
The fit function used is a Landau convolved with a Gaussian.
The quality is set based on chi^2/nu of the fits, as well
as the relative errors of the fit parameters. Both pieces
of information is shown on the plots by adding TLatex
objects to the TH1::fListOfFunctions. The color of the
function line reflects the quality (green: good, orange:
problem, red: bad).
Also, the average number of read-out errors per sub-detector
FMD1, 2, and 3 are computed and the quality set based on this
number. The means are shown on the plot together with the
used thresholds. Again, the color of the text reflects the
quality.
In all cases, the quality of the individual plots are set on
the objects themselves in the member TObject::fUniqueID. This
can then be retrieved by a Amore agent script to set the quality
of the individual objects in the Amore environment. This script
is simple and looks like
// -*- mode: C++ -*-
#include <map>
void
FMDshifterQuality(TObjArray* objs, map<string,int>* map)
{
for (Int_t i = 0; i < objs->GetEntriesFast(); i++) {
TObject* o = objs->At(i);
if (!o) continue;
// Printf("Setting quality of %s to %d", o->GetName(), o->GetUniqueID());
std::string s(o->GetName());
(*map)[s] = o->GetUniqueID();
}
}
This should be added to the AMORE database at P2, and the fmd.configfile
should look like
# QA species definition. Options: [default] [calib] [low] [high] [cosmic]
qa_species default calib low high cosmic
# Low cut for fitting energy loss specrta
ELossLowCut 0.3
# Number of RMS to fit beyound maximum
ELossNRMS 2.
# Cut on chi^2/nu of fit for bad value
ELossBadChi2Nu 100.
# Cut on chi^2/nu of fit for f**ked up value
ELossFkupChi2Nu 200.
# Least number of entries before fitting
ELossMinEntries 10000.
# Cut on average number of R/O errors per detector
ROErrorsBad 0.31
# Cut on average number of R/O errors per detector
ROErrorsFkup 0.51
The AliFMDQAChecker now also properly uses the QA thresholds from
the P2 environment by querying the (specific) CDB storage. To set
this up, a QAThresholds.configfile should be added for the FMD detector
with the content:
#
# Thresholds for the FMD
#
# Cut on chi^2/nu of fit for bad value
ELossBadChi2Nu D 100.
# Cut on chi^2/nu of fit for f**ked up value
ELossFkupChi2Nu D 200
# Cut on parameter relative error
ELossGoodParError D 0.1
# Cut on average number of R/O errors per detector
ROErrorsBad D 0.31
# Cut on average number of R/O errors per detector
ROErrorsFkup D 0.51
#
# EOF
#
The revision should eventually be ported to the release, but
I'd like to do some more checks when I'm back from vacation.
- support compilation with GCC 4.1 and 4.2
- add TARGET_ARCHITECTURE=none where no flags will be added
- change TARGET_ARCHITECTURE default to none for AliRoot
From Theodor Rascanu: These changes are necessary since we need to have the code in aliroot for the approval of our heavy flavour electron v2 analysis note: https://aliceinfo.cern.ch/Notes/node/92
Using a conservative 3% estimate for the K0s signal extraction systematics. Using explicit names for the files with the final spectra. Drawing the BGBW fitting curves on top of lin-scale spectra.
git://git.uio.no / u / mrichter / AliRoot.git / log