plot.py

#!/usr/bin/python

# This script parses the log file generated by the connected protocol FileLog logger
# How to use :
#   python plot.py [file] [sampling] [first] [end]
#      [file] the file log
#      [sampling] frequency of logging in seconds
#      [first] offset of the first point to be displayed in graph
#      [end] offset of the last point to be displayed in graph

import sys
import numpy as np
import matplotlib.pyplot as plt

file = sys.argv[1]
sampling = float(sys.argv[2])
first = int(sys.argv[3])
if (len(sys.argv) > 4):
  end = int(sys.argv[4])
else:
  end = -1
  
# parse log file
with open(file) as f:
  data = f.read()
  
data = data.split('\n')

x_range = range(first, len(data[0:end]))

x = [index * sampling for index in x_range]
  
sending_period = [row.split(' ')[0] for row in data[first:end]]
cc_window_flow_size = [row.split(' ')[1] for row in data[first:end]]
remote_arrival_speed = [row.split(' ')[2] for row in data[first:end]]
remote_link_capacity = [row.split(' ')[3] for row in data[first:end]]
rtt = [row.split(' ')[4] for row in data[first:end]]
rtt_var = [row.split(' ')[5] for row in data[first:end]]
ack_period = [row.split(' ')[6] for row in data[first:end]]
nack_count = [row.split(' ')[7] for row in data[first:end]]
ack_count = [row.split(' ')[8] for row in data[first:end]]
ack_sent_count = [row.split(' ')[9] for row in data[first:end]]
ack2_count = [row.split(' ')[10] for row in data[first:end]]
ack2_sent_count = [row.split(' ')[11] for row in data[first:end]]
multiplexer_sent_count = [row.split(' ')[12] for row in data[first:end]]
flow_sent_count = [row.split(' ')[13] for row in data[first:end]]
received_count = [row.split(' ')[14] for row in data[first:end]]
local_arrival_speed = [row.split(' ')[15] for row in data[first:end]]
local_link_capacity = [row.split(' ')[16] for row in data[first:end]]
remote_window_flow_size = [row.split(' ')[17] for row in data[first:end]]

mean_sending_period = np.mean(list(map(float, sending_period)))

print("Means :")
print(" * rtt : %d us" % (np.mean(list(map(float, rtt)))))
if (mean_sending_period > 0):
  print(" * sending period : %d us" % mean_sending_period)
  print(" * bandwidth : %d packets/sec ( %dMbits / sec)" % (1000000 / mean_sending_period , 1 / mean_sending_period * 1500 * 8))

print(" * congestion window flow size : %d packets" % (np.mean(list(map(float, cc_window_flow_size)))))
print(" * local arrival speed : %d packets/sec" % (np.mean(list(map(float, local_arrival_speed)))))
print(" * local link capacity : %d packets/sec" % (np.mean(list(map(float, local_link_capacity)))))
print(" * ack_sent_count : %d" % (np.mean(list(map(float, ack_sent_count)))))
print(" * ack2_sent_count : %d" % (np.mean(list(map(float, ack2_sent_count)))))
print("\n")
print(" * remote window flow size : %d packets" % (np.mean(list(map(float, remote_window_flow_size)))))
print(" * remote arrival speed : %d packets/sec" % (np.mean(list(map(float, remote_arrival_speed)))))
print(" * remote link capacity : %d packets/sec" % (np.mean(list(map(float, remote_link_capacity)))))
print(" * ack count : %d" % (np.mean(list(map(float, ack_count)))))
print(" * ack2 count : %d" % (np.mean(list(map(float, ack2_count)))))

y_client = [
  sending_period,
  cc_window_flow_size,
  remote_arrival_speed,
  remote_link_capacity,
  rtt,
  nack_count,
  ack_count,
  multiplexer_sent_count,
  remote_window_flow_size
]

label_client = [
  "sending period (us)",
  "cc window flow size (pkt)",
  "remote arrival speed (pkt/s)",
  "remote link capacity (pkt/s)",
  "rtt (us)",
  "nack count",
  "ack count",
  "multiplexer sent",
  "remote window flow"
]

y_server = [
  local_arrival_speed,
  local_link_capacity,
  rtt,
  rtt_var,
  ack_period,
  ack_sent_count,
  ack2_count,
  received_count
]

label_server = [
  "local arrival speed (pkt/s)",
  "local link capacity (pkt/s)",
  "rtt (us)",
  "rtt_var (us)",
  "ack period (us)",
  "ack sent",
  "ack2 count",
  "received_count"
]

# display sending statistics as graph
fig_client = plt.figure(1)
i = 1
for y_arr_client, label_arr_client in zip(y_client, label_client):
  ax = fig_client.add_subplot(len(label_client)*100 + 10 + i)
  ax.plot(x, y_arr_client, label=label_arr_client)
  ax.set_ylim(bottom=0)
  i = i + 1
  fig_client.suptitle("stat client side")
  ax.legend()

# display receiving statistics as graph
fig_server = plt.figure(2)
i = 1
for y_arr_server, label_arr_server in zip(y_server, label_server):
  ax = fig_server.add_subplot(len(label_server)*100 + 10 + i)
  ax.plot(x, y_arr_server, label=label_arr_server)
  ax.set_ylim(bottom=0)
  i = i + 1
  fig_server.suptitle("stat server side")
  ax.legend()
  
plt.show()