-
Notifications
You must be signed in to change notification settings - Fork 0
/
Main_Plot_Analysis.py
163 lines (149 loc) · 6.71 KB
/
Main_Plot_Analysis.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
158
159
160
161
162
163
import getopt
import sys
import matplotlib.pyplot as plt
from collections import defaultdict
if __name__ == "__main__":
folder = "MainPlotData/"
#file_input = ["BMS2-10000-7-4.txt","BMS2-10000-7-4.txt","BMS2-10000-10-4.txt","BMS2-10000-10.txt"]
file_input = ["BMS1-1000-7-4.txt","BMS1-1000-7-4.txt","BMS1-1000-10-4.txt","BMS1-1000-10.txt"]
#file_input = ["BMS1-1000-7-4.txt", "BMS1-1000-7-4.txt", "BMS2-10000-2-1.txt", "BMS1-1000-10.txt"]
x_label = ["p", "m", "r", "p"]
y_label = ["KL-Divergence","KL-Divergence","KL-Divergence","Times (sec)"]
marker = ["o", "s", "X", "D", "*", "^", "H", "1"]
color = ["b", "g", "r", "c", "m", "y", "k"]
changing_variable = ["m", "p", "p", "with RCM"]
# controllo gli eventuali argomenti di command line
try:
opts, args = getopt.getopt(sys.argv[1:], "hf:i:x:y:v:",
["folder=", "file=", "x=", "y=", "v="])
except getopt.GetoptError:
print(
'Main_Plot_Analysis.py\n' +
' -f <path della cartella>\n' +
' -i <nomi dei file di cui fare plotting, intervallati da virgola>\n' +
' -x <etichette assi x, intervallate da virgola>\n' +
' -y <etichette assi y, intervallate da virgola>\n' +
' -v <etichette altre variabili, intervallate da virgola>')
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print(
'Main_Plot_Analysis.py\n' +
' -f <path della cartella>\n' +
' -i <nomi dei file di cui fare plotting, intervallati da virgola>\n' +
' -x <etichette assi x, intervallate da virgola>\n' +
' -y <etichette assi y, intervallate da virgola>\n' +
' -v <etichette altre variabili, intervallate da virgola>')
sys.exit()
elif opt in ("-f", "--folder"):
folder = arg
elif opt in ("-i", "--file"):
file_input = arg.split(",")
elif opt in ("-x", "--x"):
x_label = arg.split(",")
elif opt in ("-y", "--y"):
y_label = arg.split(",")
elif opt in ("-v", "--v"):
changing_variable = arg.split(",")
if len(file_input) != len(x_label) or len(file_input) != len(y_label) or len(file_input) != len(
changing_variable) or len(x_label) != len(y_label) or len(x_label) != len(changing_variable) or len(
y_label) != len(changing_variable):
print(
'Main_Plot_Analysis.py\n' +
' -f <path della cartella>\n' +
' -i <nomi dei file di cui fare plotting, intervallati da virgola>\n' +
' -x <etichette assi x, intervallate da virgola>\n' +
' -y <etichette assi y, intervallate da virgola>\n' +
' -v <etichette altre variabili, intervallate da virgola>')
sys.exit(2)
for i in range(len(file_input)):
folder_t = folder + str(i)+"/"
file_read = open(folder_t + file_input[i], "r")
triplets = file_read.read().split(";")
file_read.close()
ns_list = []
p_list = []
KL_list = []
for triplet in triplets:
if triplet == "":
continue
triplet = triplet.split(",")
ns_list.append(triplet[0])
p_list.append(triplet[1])
KL_list.append(float(triplet[2]))
def list_duplicates(seq):
dd = defaultdict(list)
for i, item in enumerate(seq):
dd[item].append(i)
return ((key, locs) for key, locs in dd.items()
if len(locs) > 1)
dict_ns = dict(sorted(list_duplicates(ns_list)))
dict_p = dict(sorted(list_duplicates(p_list)))
dict_fin = dict()
for val in dict_ns.keys():
for val1 in dict_p.keys():
for arr in dict_ns.get(val):
for arr1 in dict_p.get(val1):
if arr == arr1:
tt = dict_fin.get(str(val) + "," + str(val1))
if tt is not None:
tt[0] += KL_list[arr]
tt[1] += 1
else:
dict_fin[str(val) + "," + str(val1)] = [KL_list[arr], 1]
if len(dict_fin) == 0 :
for val in dict_ns.keys():
for p_in in range(len(p_list)):
dict_fin[str(val) + "," + str(p_list[p_in])] = [KL_list[p_in], 1]
ns_list = list(dict.fromkeys(ns_list))
p_list = list(dict.fromkeys(p_list))
dict_keys = dict_fin.keys()
for in_n in range(len(ns_list)):
n = ns_list[in_n]
x = list()
y = list()
att = list()
for p in p_list:
key = str(n) + "," + str(p)
if key in dict_keys:
arr_t = dict_fin[key]
att.append(arr_t[1])
y.append(arr_t[0] / arr_t[1])
x.append(int(p))
for i_1 in range(len(x)-1):
for i_2 in range(i_1+1, len(x)):
if x[i_1] > x[i_2]:
t = x[i_1]
x[i_1] = x[i_2]
x[i_2] = t
t = y[i_1]
y[i_1] = y[i_2]
y[i_2] = t
i_m1 = in_n % len(marker)
i_m2 = in_n % len(color)
plt.plot(x, y, marker=marker[i_m1], linestyle='-', color=color[i_m2],
label=changing_variable[i] + ' = ' + str(n) + " " + str(att))
plt.xlabel(x_label[i])
plt.ylabel(y_label[i])
plt.title(file_input[i].split(".")[0])
plt.legend(frameon=False, loc='upper center') # , ncol=2, bbox_to_anchor=(0.5, 0.05))
plt.show()
print("Analysis n: %s" % i)
data = file_input[i].split(".")[0].split("-")
print("Dataset: "+data[0])
if i == 0:
print("QID matrix dimension: "+data[1])
print("R value: " + data[2])
print("R attempts: " + data[3])
elif i == 1:
print("QID matrix dimension: " + data[1])
print("R value: " + data[2])
print("R attempts: " + data[3])
elif i == 2:
print("QID matrix dimension: " + data[1])
print("Number of sensitive attributes: " + data[2])
print("R attempts: " + data[3])
elif i == 3:
print("QID matrix dimension: "+data[1])
print("Number of sensitive attributes: " + data[2])
print("")