Prerequisits:

• have ROOT and python3 installed
• On mac: have the DetectorEvent header and lib installed (to read the EUDAQ data files)
  • it is also included in this rep for convenience, under DetectorEvent/ for different dates
• on the DAQ PC:
  • it is already compiled in work/eudaq/lib/libeudaq_det_event_dict.so

Setup:

• On mac: Setup ROOT
• On the DAQ PC it is already setup
• On mac: export LD_LIBRARY_PATH=$PWD/DetectorEvent/DATEDIR:$LD_LIBRARY_PATH (DATEDIR is the specific date where the lib is valid for)
• On the DAQ PC: export LD_LIBRARY_PATH=$HOME/work/eudaq/lib:$LD_LIBRARY_PATH
• put data files somewhere with enough space
  • there's a dir called test_data with example data already
  • the data from eudaq on the DAQ PC it is in: $HOME/work/eudaq/user/stave/misc/run_data/
• copy the run data file e.g. to the test_data dir (can be whatever you want)
• change config file as needed (see examples in the conf/ dir)
  • particularly change the path to the input file to wherever you copied it
  • it is assumed that the file name starts with tree_ and ends with RunX.root where X is the EUDAQ run number between 0 and 1000000

Quick start, assuming that the detector is aligned already (but read below...):

• Must run: python3 noise_analyzer.py -conf conf/config_file_name.txt
• Then run: python3 serial_analyzer.py -conf conf/config_file_name.txt
• OR run: python3 multiproc_analyzer.py -conf conf/config_file_name.txt
• Summarize: python3 postproc_analyzer.py -conf conf/config_file_name.txt
• Finally, check the event_displays dir

Directories and input business:

• Once you run any of the scripts listed above (and below), several dirs and files will be created in the same dir where the input file from the config is:
  • a dedicated run dir, e.g. run_0000046 if the EUDAQ run number is 46
  • a subdir for the event displays, e.g. run_0000046/event_displays if the EUDAQ run number is 46
  • an input file will copy placed in run_0000046/ if the EUDAQ run number is 46

Run noise scan:

• if you want to process only part of the events, set the "nmax2process" parameter as needed
• to process all events check that the "nmax2process" parameter is larger than what you have in data
• python3 noise_analyzer.py -conf conf/config_file_name.txt

Run analysis:

• run noise scan (see above)
• if you want to process only part of the events, set the "nmax2process" / "nmax2processMP" parameter as needed
• to process all events check that the "nmax2process" / "nmax2processMP" parameter is larger than what you have in data
• run analysis serially OR in parallel:
  • python3 serial_analyzer.py -conf conf/config_file_name.txt
  • python3 multiproc_analyzer.py -conf conf/config_file_name.txt
• look at the histograms in the new root file

Run alignment with cosmics:

• run noise scan (see above)
• step 1: python3 multiproc_analyzer.py -conf conf/config_file_name.txt with all misalignment parameters set to 0 in the config file
• step 2: aligning wrt e.g. ALPIDE_0 or all at once after adjusting the parameters in the config: maxchi2align, axes2align, naligniter.
  • [option A.1] python3 alignment_fitter.py -conf conf/config_file_name.txt -ref ALPIDE_0 or
  • [option A.2] python3 alignment_fitter.py -conf conf/config_file_name.txt
• step 3: choosing the fit strategy
  • [option B.1] if the axes2align parameter equals to xytheta then the fit will be FULLY-SIMULTANEOUS in 3D
  • [option B.2] if the axes2align parameter equals to xy, xtheta or ytheta then the fit will be SEMI-SIMULTANEOUS in 2D
  • [option B.3] if the axes2align parameter equals to x, y or theta then the fit will be SEQUENTIAL (i.e. non-simultaneous) in 1D
  • Notes:
    • if e.g. -det ALPIDE_0 was used in option A.1 then you need to keep all misalignment parameters of ALPIDE_0 fixed to 0 in the config file always
    • it is advised to use one reference detector and align only the N-1 planes with respect to that with either the sequential or the simultaneous fit
    • if the fit is SEMI-SIMULTANEOUS or SEQUENTIAL, you need to repeat steps 2-5 for all axes (e.g. axes2align=x->axes2align=y->axes2align=theta)
• step 4: put the non-zero resulting misalignment values in the config file for the relevant detectors
• step 5: run step 1 again, but with the new (non-zero wherever relevant) misalignment parameters in the config file (from step 3)
• step 6: check the residuals and the chi2 histograms

Plot some postprocessing histos and fit the residuals:

• step 1: run the alignment as discussed above
• step 2: python3 postproc_analyzer.py -conf conf/config_file_name.txt
• step 3: look at the pdf file created in the dir where the root file is (as listed in the config file)

Run the postprocessing plotting as above but for a few similar runs combined:

• provide the list of runs in the config file in field named runnums under the MULTIRUN area
• run step 2 as in the section above, but with the -mult 1 flag enabled:
  • python3 postproc_analyzer.py -conf conf/config_file_name.txt -mult 1
  • the inputfile from the config has to point to one of the runs in the runs list but it will be otherwise not used.
  • the histograms files belonging to the runs in the list will be hadded
    • the histogram file of each run must exist individually in its dedicated dir (see "Run analysis" section)
    • the plotting will be done with the result as an input