The code is tested with Python 3.6.4 (or greater) with the following non standard packages installed:

numpy pandas csv

If working at CERN on lxplus, you can do for example:

cmsrel CMSSW_10_6_28
cd  CMSSW_10_6_28/src
cmsenv

Then follow instructions below.

Clone the repository in a new folder:

git clone [email protected]:CMSROMA/ArraySizeAna.git
cd ArraySizeAna

Raw data files are available in the "data" folder. For the moment, the file name is just the array number. Es.

796.txt	799.txt	800.txt	803.txt	805.txt	809.txt

Note: It should be changed in future with unique run number and date.

Run analysis on all raw data available:

python3 runAll.py --inputdir data/

Several .csv files are created in the current directory. Es.:

796.csv	799.csv	800.csv	803.csv	805.csv	809.csv

Merge all files into a single csv file:

cat *.csv > all.csv

The final file will look like this:

796,56.243,0.011,0.052,0.057,0.014,0.017,0.022,56.298,56.239,0.004,56.268,0.016,0.044,0.125,0.014,0.043,0.045,51.508,51.431,0.014,51.47,0.04,0.08,0.019,3.368,3.333,0.002,3.333,0.019
799,56.286,0.002,0.059,0.041,0.014,0.009,0.017,56.344,56.286,0.003,56.315,0.015,0.052,0.032,0.014,0.012,0.018,51.478,51.442,0.006,51.46,0.014,0.08,0.016,3.394,3.358,0.002,3.358,0.016
800,56.252,0.017,0.125,0.103,0.034,0.03,0.045,56.352,56.232,0.009,56.292,0.033,0.079,0.081,0.027,0.031,0.041,51.48,51.395,0.012,51.438,0.029,0.12,0.024,3.352,3.292,0.002,3.292,0.024
803,56.23,0.036,0.124,0.076,0.037,0.019,0.042,56.351,56.249,0.008,56.3,0.031,0.09,0.074,0.028,0.023,0.036,51.39,51.305,0.011,51.347,0.026,0.104,0.023,3.389,3.311,0.002,3.311,0.023
805,56.296,0.006,0.022,0.049,0.007,0.015,0.017,56.348,56.304,0.003,56.326,0.016,0.158,0.104,0.053,0.031,0.061,51.856,51.71,0.019,51.783,0.048,0.168,0.043,3.491,3.4,0.004,3.4,0.043
809,56.279,0.008,0.068,0.1,0.021,0.029,0.036,56.346,56.264,0.007,56.305,0.027,0.213,0.122,0.083,0.034,0.09,51.852,51.672,0.027,51.762,0.068,0.165,0.037,3.402,3.281,0.003,3.281,0.037

where the column names are defined/described inside the "Dimensions.py" code and they are:

l_results_names = ["array",
                       "L_bar_mu","L_bar_std",
                       "L_maxVar_LS","L_maxVar_LN","L_std_LS","L_std_LN","L_std_tot","L_max","L_mean","L_mean_std","L_mean_mitu","L_std_mitu",
                       "W_maxVar_LO","W_maxVar_LE","W_std_LO","W_std_LE","W_std_tot","W_max","W_mean","W_mean_std","W_mean_mitu","W_std_mitu",
                       "T_maxVar_FS","T_std_FS","T_max","T_mean","T_mean_std","T_mean_mitu","T_std_mitu"]