You need miniconda installed :

https://docs.conda.io/en/latest/miniconda.html#linux-installers

and then get the librairies as stated in lardenv.yml :

conda env create -f lardenv.yml

⚠️ It'll take about 2-3 GB of space!

then : conda activate lardenv

The rtree library is now also needed, but cannot be downloaded from conda. Instructions to get it within lardenv:

• all above steps
• cd /your_miniconda_repository/envs/lardenv/bin
• pip install rtree

Check and modify config.py :

• store_path : your directory where the output file will be stored
• plot_path : your directory where control plots will be stored
• Update np02/runs.yaml if needed

To launch lardon, type python reader.py with the following options:

• -run <run nb> which run number
• -sub <subfile name> which subfile (e.g. 1_a)
• -n <nb of events> how many events to process, default is -1=all file
• -out <output file option> optional extra name for the output
• -type <type of data> for the special runs, default is cosmic
• -reco <your_reco_parameters.yaml> if you want to change some reconstruction parameters, default uses default_reco.yaml

e.g. : To run the first 10 events of run 1415, subfile 5_b, type :

python reader.py -run 1415 -sub 5_b -n 10 -out example

the output h5file will be store_path/1415_5_b_example.h5

add -mc the_mc_root_file.root

the simulation will be added to a run of data (preferably a noise only run!)

⚠️ Note that the MC file should be in a specific format - only from Qscan at the moment

• electrons drift along z axis - the cathode is at z=-300cm
• all distance are in cm

The file default_reco.yaml contains all parameters needed for the reconstruction. If you want to change/add parameters, you can create your own .yaml file, following the name: value format. You don't have to copy all variables, the default one will be taken.

By default, no control plots are produced, but you can call the plotting functions in reader.py anywhere in the reconstruction loop.

All plot functions have the two options :

• option="extra_output_name_if_you_want" [default is none]
• to_be_shown=True/False if you want to see the plot live [default is False]

plot.plot_ed_data()

take a look at plotting/event_display.py to see all possible plots (just one crp/one view, zoom, ...)

plot.plot_wvf_single_current([(crp,view,ch),(crp,view,ch),..]) [one wvf/plot]

plot.plot_wvf_multi_current([(crp,view,ch),(crp,view,ch),..]) [all wvf superimposed]

plot.plot_wvf_evo([wvf1, wvf2,...], title="your plot title", legends=['leg1', 'leg2',...])

where wvf1 would be a copy of the waveform at some point in the reconstruction with :

wvf1 = dc.data(crp, view, ch, :].copy()

plot.plot_2dcrp_clusters() <- shown in CRP/View format

plot.plot_2dview_clusters() <- shown in x/y format

[same for plot_2dxxx_hits()]

plot.plot_2dview_2dtracks()

plot.plot_2dview_hits_and_3dtracks() <- two views separated (all hits and 2d tracks also shown)

plot.plot_3d() <- in 3d