Different method for bandwidth aggregation

aggregate-mod.py

+#!/usr/bin/env python3
+# vim: expandtab shiftwidth=4 softtabstop=4
+
+
+#iperf -V -Z cubic -t 30 -c fdb2:f689:4248:2bc8::3 -p 12345
+
+import argparse
+import copy
+import math
+import os
+import re
+import signal
+import subprocess
+import tempfile
+#import threading
+import time
+
+def signal_handler(signum, frame):
+    clean_up()
+    raise SystemExit
+
+def testy(a,b):
+    print(a)
+    print(b)
+    print(sender)
+    return 0
+
+def clean_up():
+# Clean up
+    if args.legacy:
+        tcpprobe.terminate()
+    if args.tcpdump == "1":
+        tcpdump.terminate()
+    if args.cpunetlog != "":
+        cpunetlog.terminate()
+    for i in sender:
+#        if i['utility'].returncode == None:
+            try:
+                i['utility'].kill()
+            except ProcessLookupError:
+                pass
+#        i['utility_file'].close()
+    time.sleep(1)
+
+#def parse_dir(directory):
+
+def qsort1(list):
+    """Quicksort using list comprehensions"""
+    if list == []: 
+        return []
+    else:
+        pivot = list[0]
+        lesser = qsort1([x for x in list[1:] if x < pivot])
+        greater = qsort1([x for x in list[1:] if x >= pivot])
+        return lesser + [pivot] + greater 
+
+def quantil(list,p):
+    length = len(list)
+    len_p = (length * p)-1
+    if math.ceil(len_p) == len_p:
+        return ((list[int(len_p)] + list[int(len_p + 1)]) / 2)
+    else:
+        return list[math.ceil(len_p)]
+    
+
+signal.signal(signal.SIGINT, signal_handler)
+signal.signal(signal.SIGTERM, signal_handler)
+
+parser = argparse.ArgumentParser(description='Configure test environment.')
+
+parser.add_argument('folders', nargs="*", default="./", help="Folder to search for files")
+parser.add_argument('-m', '--mask', default="")
+
+args = parser.parse_args()
+
+mypid = os.getpid()
+
+#print(args.folders)
+
+#for key, folder in enumerate(args.folders):
+#    args.folders[key] = os.path.abspath(folder)
+
+args.folders = [os.path.abspath(folder) for folder in args.folders]
+
+print(args.folders)
+rtt_values_file = tempfile.TemporaryFile(mode='r+')
+bw_values_file = tempfile.TemporaryFile(mode='r+')
+netperf_throughput_file = tempfile.TemporaryFile(mode='r+')
+netperf_retrans_file = tempfile.TemporaryFile(mode='r+')
+rtt_file_lines = 0
+bw_file_lines = 0
+
+for folder in args.folders:
+    for path, dirs, files in os.walk(folder):
+        for file in files:
+            if file[:9+len(args.mask)] == "tcpprobe_"+args.mask:
+                tcpprobe_file = open(path + "/" + file)
+                for line in tcpprobe_file:
+                    line = line.split(" ")
+                    #print(line[9])
+                    rtt_values_file.write(line[9]+'\n')
+                    rtt_file_lines += 1
+                tcpprobe_file.close()
+            elif file[:3+len(args.mask)] == "bw_"+args.mask:
+                bw_file = open(path + "/" + file)
+                sum_b = 0
+                last_bw = (0, 0)
+                for line in bw_file:
+                    line = line.split(" ")
+                    this_bw = (float(line[0]), float(line[3]))
+                    if this_bw[0] < math.ceil(last_bw[0]):
+                        sum_b+= (this_bw[0] - last_bw[0])*this_bw[1]
+                    elif math.floor(this_bw[0]) - math.ceil(last_bw[0]) >= 1:
+                        for i in range(math.floor(this_bw[0]) - math.ceil(last_bw[0])):
+                            bw_values_file.write("0"+"\n")
+                            #print(math.floor(last_bw[0])+i,0)
+                            sum_b = (this_bw[0] - math.floor(this_bw[0]))*this_bw[1]
+                    else:
+                        sum_b += (math.ceil(last_bw[0]) - last_bw[0]) * float(line[3])
+                        bw_values_file.write(str(sum_b)+"\n")
+                        #print(math.floor(last_bw[0]), sum_b)
+                        sum_b = (this_bw[0] - math.floor(this_bw[0]))*this_bw[1]
+                    
+                    last_bw = this_bw
+
+                    #bw_values_file.write(line[3])
+                    #bw_file_lines += 1
+                bw_file.close()
+            elif file[:8+len(args.mask)] == "netperf_"+args.mask:
+                netperf_file = open(path + "/" + file)
+                count = 0
+                for line in netperf_file:
+                    count+=1
+                    if count == 6:
+                        netperf_throughput_file.write(line[11:])
+                    elif count == 42:
+                        netperf_retrans_file.write(line[24:])
+                netperf_file.close()
+                
+
+bw_values_file.seek(0)
+rtt_values_file.seek(0)
+netperf_throughput_file.seek(0)
+netperf_retrans_file.seek(0)
+
+def statify_list(sorted_list, n):
+    avg = sum( sorted_list ) / n
+    std_deviation = math.sqrt((1/(n - 1)) * sum( [ (value-avg)**2 for value in sorted_list ] ))
+    q_25 = quantil(sorted_list, 0.25)
+    q_75 = quantil(sorted_list, 0.75)
+    iqr = q_75 - q_25
+    bot = sorted_list[0]
+    top = sorted_list[len(sorted_list) - 1]
+    whisker_bot = bot
+    for value in sorted_list:
+        if value >= (q_25 - iqr*1.5):
+            whisker_bot = value
+            break
+    whisker_top = top
+    for value in reversed(sorted_list):
+        if value <= (q_75 + iqr*1.5):
+            whisker_top = value
+            break
+    
+    percent_under_whisker = 0
+    count = 0
+    for value in sorted_list:
+        if value < whisker_bot:
+            count += 1
+        else:
+            percent_under_whisker = (count / n) * 100
+            break
+
+    count = 0
+    for value in reversed(sorted_list):
+        if value > whisker_top:
+            count += 1
+        else:
+            percent_over_whisker = (count / n) * 100
+            break
+            
+    print("Average:\t"+str(avg))
+    print("Std. deviation:\t"+str(std_deviation))
+    print("0.25 Quantil:\t"+str(q_25))
+    print("0.75 Quantil:\t"+str(q_75))
+    print("IQR:\t\t"+str(iqr))
+    print("bot. whisker:\t"+str(whisker_bot))
+    print("top whisker:\t"+str(whisker_top))
+    print("% < whisker:\t"+str(percent_under_whisker))
+    print("% > whisker:\t"+str(percent_over_whisker))
+
+    #return list with extreme outliers removed
+    for value in sorted_list:
+        if value < (q_25 - iqr*3.0):
+            del sorted_list[0]
+        else:
+            break
+    for value in reversed(sorted_list):
+        if value > (q_75 + iqr*3.0):
+            del sorted_list[len(sorted_list)-1]
+        else:
+            break
+    print("min. without outliers: "+str(sorted_list[0]))
+    print("max. without outliers: "+str(sorted_list[len(sorted_list)-1]))
+    print("Std. deviation without outliers: "+str(math.sqrt((1/(n - 1)) * sum( [ (value-avg)**2 for value in sorted_list ] ))))
+
+    return sorted_list
+
+sorted_bw = sorted([ float(line) for line in bw_values_file ])
+sorted_rtt = sorted([ float(line) for line in rtt_values_file ])
+sorted_netperf_throughput = sorted([ float(line) for line in netperf_throughput_file ])
+sorted_netperf_retrans = sorted([ float(line) for line in netperf_retrans_file ])
+print("Bandwidth: ")
+print("=============================")
+sorted_bw = statify_list(sorted_bw, len(sorted_bw))
+print("")
+print("Round Trip Time: ")
+print("=============================")
+sorted_rtt = statify_list(sorted_rtt, len(sorted_rtt))
+print("")
+print("Netperf Throughput: ")
+print("=============================")
+if len(sorted_netperf_throughput) == 1:
+    sorted_netperf_throughput += sorted_netperf_throughput
+sorted_netperf_throughput = statify_list(sorted_netperf_throughput, len(sorted_netperf_throughput))
+print("")
+print("Netperf Retransmissions: ")
+print("=============================")
+if len(sorted_netperf_retrans) == 1:
+    sorted_netperf_retrans += sorted_netperf_retrans
+sorted_netperf_retrans = statify_list(sorted_netperf_retrans, len(sorted_netperf_retrans))
+
+#from pylab import *
+
+#boxplot(sorted_bw)
+#show()
+#boxplot(sorted_rtt)
+#show()
+
+#rtt_q_25 = quantil(sorted_rtt, 0.25)
+#rtt_q_75 = quantil(sorted_rtt, 0.75)
+#rtt_iqr = rtt_q_75 - rtt_q_25
+
+#print(bw_values_file.read())
+#print(bw_file_lines)
+