-
Notifications
You must be signed in to change notification settings - Fork 10
/
util.py
158 lines (134 loc) · 3.68 KB
/
util.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
#!/usr/bin/env python
__author__ = 'jsommers@colgate.edu'
import random
from ipaddr import IPv4Network, IPv4Address
import math
def zipit(xtup):
assert(len(xtup) == 2)
a = list(xtup[0])
b = list(xtup[1])
if len(a) < len(b):
a = a * len(b)
a.insert(0,0)
b.insert(0,b[0])
mg = modulation_generator(zip(a,b))
return mg
def frange(a, b, c):
xlist = []
if a < b:
assert (c > 0)
while a <= b:
xlist.append(a)
a += c
if a > b and xlist[-1] != b:
xlist.append(b)
else:
assert (c < 0)
while a >= b:
xlist.append(a)
a += c
if a < b and xlist[-1] != b:
xlist.append(b)
return xlist
def modulation_generator(xlist):
for x in xlist:
yield x
def randomunifint(lo, hi):
r = random.randint
while True:
yield r(lo, hi)
def randomuniffloat(lo, hi):
r = random.random
while True:
yield r()*(hi-lo)+lo
def randomchoice(*choices):
r = random.choice
while True:
yield r(choices)
def randomchoicefile(infilename):
xlist = []
with open(infilename) as inf:
for line in inf:
for value in line.strip().split():
try:
xlist.append(float(value))
except:
pass
index = 0
while True:
yield xlist[index]
index = (index + 1) % len(xlist)
def pareto(offset,alpha):
pow = math.pow
r = random.random
while True:
yield (offset * ((1.0/pow(r(), 1.0/alpha)) - 1.0));
def exponential(lam):
r = random.expovariate
while True:
yield r(lam)
def normal(mean, sdev):
r = random.normalvariate
while True:
yield r(mean, sdev)
def lognormal(mean, sdev):
r = random.lognormvariate
while True:
yield r(mean, sdev)
def gamma(alpha, beta):
r = random.gammavariate
while True:
yield r(alpha, beta)
def weibull(alpha, beta):
r = random.weibullvariate
while True:
yield r(alpha, beta)
def mkdict(s):
xdict = {}
if isinstance(s, str):
s = s.split()
for kvstr in s:
k,v = kvstr.split('=')
xdict[k] = v
return xdict
def removeuniform(p):
r = random.random
while True:
yield (r() < p)
def empiricaldistribution(fname):
assert(os.path.exists(fname))
while True:
with open(fname, 'r') as infile:
for line in infile:
for x in line.split():
yield float(x)
# function alias
empirical = empiricaldistribution
def subnet_generator(prefix, numhosts):
'''Given a prefix and number of hosts to carve out for
subnets within this prefix, create a generator object
that returns a new subnet (as an ipaddr.IPv4Network) with
each subsequent call to next()'''
ceil = math.ceil
log = math.log
ipfx = IPv4Network(prefix)
prefixhosts = ipfx.numhosts
numhosts += 2
numhosts = int(ceil(log(numhosts, 2)) ** 2)
prefixlen = '/' + str(32 - int(log(numhosts,2)))
baseint = int(ipfx)
numsubnets = prefixhosts / numhosts
for i in xrange(numsubnets):
addr = IPv4Address(baseint + (numhosts * i))
prefix = IPv4Network(str(addr) + prefixlen)
yield prefix
def default_ip_to_macaddr(ipaddr):
'''Convert an IPv4 address to a 48-bit MAC address-like creature. Just
hardcode the two high-order bytes, and fill in remainder with IP address'''
ip = int(IPv4Address(ipaddr))
mac = []
for i in xrange(4):
mac.append(((ip >> (8*i)) & 0xff))
mac.extend([0x02,0x00])
mac = [ "{:02x}".format(b) for b in reversed(mac) ]
return ':'.join(mac)