blob: 76b1ea0593239ae0efc1d8e4b066a9c8a16e4853 (
plain)
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
|
#Daniel Mack
#Random Skeleton Generators
import networkx as nx
import random as rand
#Modified Erdos-Renyi Graph Generator
def erdosGen(SANet, tasks, conds, inDegree, outDegree):
inD = {}
outD = {}
pairs = {}
haltGen = 0;
haltOut = 0;
haltIn = 0;
#continue until the graph has met the in/out degreee limits
while haltGen == 0:
ctask = ""
ccond = ""
found = 0
while found == 0:
#Choose Task
ctask = tasks[rand.randrange(len(tasks))]
#Choose Cond
ccond = conds[rand.randrange(len(conds))]
key = ctask + "," + ccond
#if already been used as either an effect or precondition
if key in pairs:
found = 0
else:
#valid pair for random pairing
found = 1
pairs[key] = 1
#choose direction
EfforPre = rand.randrange(2)
#If 0 then it's a precondition link
if EfforPre == 0 and haltIn == 0:
SANet.add_edge(ccond, ctask)
if ctask in inD:
inD[ctask] += 1
else:
inD[ctask] = 1
elif haltOut == 0:
#otherwise it's an effect
SANet.add_edge(ctask, ccond)
if ctask in outD:
outD[ctask] += 1
else:
outD[ctask] = 1
#Check for Stopping Conditions
totalIn = 0.0
totalOut = 0.0
for each in tasks:
if each in inD:
totalIn += inD[each]
if each in outD:
totalOut += outD[each]
avgIn = totalIn/len(tasks)
avgOut = totalOut/len(tasks)
if avgIn >= inDegree:
haltIn = 1
if avgOut >= outDegree:
haltOut = 1
if haltIn == 1 and haltOut == 1:
print avgIn
print avgOut
haltGen = 1
return SANet
|
