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 git@github.com: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"]