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calc_fct.py
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calc_fct.py
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#!/usr/bin/python
import sys
import getopt
import numpy as np
from scipy import stats
statsFile="Client.txt"
num_of_shortflows=0
num_of_longflows=0
list_of_shortflows = []
list_of_longflows = []
list_of_shortecnM = []
list_of_longecnM = []
list_of_shortecnC = []
list_of_longecnC = []
outputfile = 'result'
def ReadArgs(argv):
global statsFile
statsfile = ''
try:
opts, args = getopt.getopt(argv,"hi:","ifile=")
except getopt.GetoptError:
print 'usage: python my_plotter.py -i <inputfile>'
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print 'usage: python my_plotter.py -i <inputfile>'
sys.exit()
elif opt in ("-i", "--ifile"):
statsfile = arg
statsFile = statsfile
print 'Stats file is ', statsFile
def ReadFile():
global num_of_shortflows
global num_of_longflows
fct,fsize = np.loadtxt(statsFile, delimiter=':' , usecols = (2,3), dtype = str , unpack=True)
for i in range (0,len(fct)):
c,d = fsize[i].split('\t')
a,b = fct[i].split('\t')
c = float(c)
if(c == 16 or c == 8 or c == 32):
list_of_shortflows.append(a)
num_of_shortflows+=1
elif(c > 1023 or c == 64):
list_of_longflows.append(a)
num_of_longflows+=1
for i in range (0,num_of_shortflows):
list_of_shortflows[i] = float(list_of_shortflows[i])
for i in range (0,num_of_longflows):
list_of_longflows[i] = float(list_of_longflows[i])
def plotMean(value):
i50print = 0
i99print = 0
dummy_ecn_list = []
f = open(outputfile, 'a+')
if(value =='short'):
f.write( "\nplotting Short\n")
list_of_lists = list_of_shortflows
if(value == 'long'):
f.write( "\nplotting Long\n")
list_of_lists = list_of_longflows
a = np.mean(list_of_lists)
b = stats.hmean(list_of_lists)
f.write(str(a))
f.write('\n')
f.write("Long flows throughput with arithmetic mean:")
f.write(str(0.008388608/(a/1000)))
f.write('\n')
f.write("Long flows throughput with harmonic mean:")
f.write(str(0.008388608/(b/1000)))
f.write('\n')
f.close()
def plotCDF(value):
i50print = 0
i99print = 0
dummy_ecn_list = []
f = open(outputfile, 'a+')
if(value =='short'):
f.write( "\nplotting Short\n")
list_of_lists = list_of_shortflows
if(value == 'long'):
f.write( "\nplotting Long\n")
list_of_lists = list_of_longflows
list_of_lists = sorted(list_of_lists)
a = np.percentile(list_of_lists, 50)
b = np.percentile(list_of_lists, 80)
c = np.percentile(list_of_lists, 90)
z = np.percentile(list_of_lists, 91)
y = np.percentile(list_of_lists, 92)
x = np.percentile(list_of_lists, 93)
w = np.percentile(list_of_lists, 94)
d = np.percentile(list_of_lists, 95)
l = np.percentile(list_of_lists, 96)
h = np.percentile(list_of_lists, 97)
i = np.percentile(list_of_lists, 98)
e = np.percentile(list_of_lists, 99)
g = np.percentile(list_of_lists, 99.9)
k = np.mean(list_of_lists)
j = stats.hmean(list_of_lists)
f.write(str(a))
f.write('\n')
f.write(str(b))
f.write('\n')
f.write(str(c))
f.write('\n')
f.write(str(z))
f.write('\n')
f.write(str(y))
f.write('\n')
f.write(str(x))
f.write('\n')
f.write(str(w))
f.write('\n')
f.write(str(d))
f.write('\n')
f.write(str(l))
f.write('\n')
f.write(str(h))
f.write('\n')
f.write(str(i))
f.write('\n')
f.write(str(e))
f.write('\n')
f.write(str(g))
f.write('\n')
f.write('\n')
f.write("Short flows throughput with arithmetic mean:")
f.write(str(0.000131072/(k/1000)))
f.write('\n')
f.write("Short flows throughput with harmonic mean:")
f.write(str(0.000131072/(j/1000)))
f.write('\n')
f.close()
if __name__=="__main__":
ReadArgs(sys.argv[1:])
ReadFile()
outputfile = outputfile + statsFile
f = open(outputfile, 'w')
f.close
if(num_of_shortflows>1):
plotCDF("short")
if(num_of_longflows>1):
plotMean("long")