-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathmain.py
More file actions
81 lines (70 loc) · 3.1 KB
/
main.py
File metadata and controls
81 lines (70 loc) · 3.1 KB
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
import measures_on_simple_data as msd
import transform_network as transform
import network_utils as utils
from networkx import number_connected_components, connected_component_subgraphs
from math import sqrt
try:
import matplotlib.pyplot as plt
except:
raise
# print stats, draw and save figures
def drawAndSaveReal():
utils.analyseGraph(msd.readFeederData(13), "feeder13", 13)
utils.analyseGraph(msd.readFeederData(34), "feeder34", 34)
utils.analyseGraph(msd.readFeederData(37), "feeder37", 37)
utils.analyseGraph(msd.readFeederData(123), "feeder123", 123)
### subcomponents of feeder 123
utils.analyseGraph(msd.readFeederData(124), "feeder124", 124)
utils.analyseGraph(msd.readFeederData(125), "feeder125", 125)
utils.analyseGraph(msd.readFeederData(126), "feeder126", 126)
utils.analyseGraph(msd.readFeederData(127), "feeder127", 127)
utils.analyseGraph(msd.readFeederData(128), "feeder128", 128)
# print stats, draw and save figures
def drawAndSaveSynthetic():
utils.analyseGraph(transform.synthetic(13), "synthetic13", 130)
utils.analyseGraph(transform.synthetic(34), "synthetic34", 340)
utils.analyseGraph(transform.synthetic(37), "synthetic37", 350)
utils.analyseGraph(transform.synthetic(123), "synthetic123", 1230)
### subcomponents of feeder 123
utils.analyseGraph(transform.synthetic(124, True), "synthetic_sub124", 12400)
utils.analyseGraph(transform.synthetic(125, True), "synthetic_sub125", 12500)
utils.analyseGraph(transform.synthetic(126, True), "synthetic_sub126", 12600)
utils.analyseGraph(transform.synthetic(127, True), "synthetic_sub127", 12700)
utils.analyseGraph(transform.synthetic(128, True), "synthetic_sub128", 12800)
def inferParameters(n):
utils.analyseGraph(transform.syntheticInferred(n, True), "synthetic_" + str(n), n * 1000)
# print stats of all real feeders and synthetic networks
def printStats():
utils.printStatsV(transform.synthetic(13))
utils.printStatsV(transform.synthetic(34))
utils.printStatsV(transform.synthetic(37))
utils.printStatsV(transform.synthetic(123))
### subcomponents of feeder 123
utils.printStatsV(msd.readFeederData(124))
utils.printStatsV(msd.readFeederData(125))
utils.printStatsV(msd.readFeederData(126))
utils.printStatsV(msd.readFeederData(127))
utils.printStatsV(msd.readFeederData(128))
utils.printStatsV(transform.synthetic(124, True))
utils.printStatsV(transform.synthetic(125, True))
utils.printStatsV(transform.synthetic(126, True))
utils.printStatsV(transform.synthetic(127, True))
utils.printStatsV(transform.synthetic(128, True))
def teststat(k):
nb_cc = []
for i in range(0,30):
nb_cc.append(number_connected_components(transform.synthetic(k, True)))
#nb_cc.append(i)
print(nb_cc)
mean = sum(nb_cc)/len(nb_cc)
print(mean)
dev = [(x - mean)*(x-mean) for x in nb_cc]
std_dev = sqrt(sum(dev)/len(nb_cc))
print(std_dev)
return
# teststat(124)
#[13, 34, 37, 123, 36, 36, 19, 16, 16]
#inferParameters(35)
#drawAndSaveReal()
drawAndSaveSynthetic()
#plt.show()