KF_timing.py

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import ROOT
import csv
import matplotlib.pyplot as plt
import numpy as np

# Data preparation
ptDict = {}

# Open the output file
with open('output.log', mode='r') as csv_file:
    csv_reader = csv.reader(csv_file, delimiter=',')
    # read lines and go for it
    for csv_row in csv_reader : 
        if len(csv_row) > 1 :                
            # get the job id
            jobID = csv_row[0]
            # etabin, pt value, exec time
            etabin = float(csv_row[1])
            ptvalue = float(csv_row[2])
            exectime = float(csv_row[3])

            # Make sure you have all the keys ready
            try :
                pdict =  ptDict[ptvalue]
            except :
                ptDict[ptvalue] = {}
                pdict =  ptDict[ptvalue]

            # Now fill the sub dictionary
            try :
                vpdict = pdict[etabin]
            except:
                pdict[etabin] = []
                vpdict = pdict[etabin]
      
            vpdict += [ exectime ]

# plot the ptDict
plt.figure(figsize=(7, 5))

ax = plt.subplot(111)
plt.loglog(ptDict.keys(),[i[0][0] for i in np.array(list(ptDict.values()))],'.-', label='0<$\eta$<0.5')
plt.loglog(ptDict.keys(),[i[1][0] for i in np.array(list(ptDict.values()))],'.-', label='0.5<$\eta$<1.0')
plt.loglog(ptDict.keys(),[i[2][0] for i in np.array(list(ptDict.values()))],'.-', label='1.0<$\eta$<1.5')
plt.loglog(ptDict.keys(),[i[3][0] for i in np.array(list(ptDict.values()))],'.-', label='1.5<$\eta$<2.0')
plt.loglog(ptDict.keys(),[i[4][0] for i in np.array(list(ptDict.values()))],'.-', label='2.0<$\eta$<2.5')
ax.set_xlabel('$p_T$ [GeV/c]')
ax.set_ylabel('time/track [sec]')
plt.yscale('log')
ax.set_xlim((0.09,105))
plt.legend(numpoints=1)

plt.suptitle("KF timing vs. $p_T$")

plt.show()