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
|
#!/var/www/html/compbio/BNW_1.3/bnw-env/bin/python3
import os
import sys
import math
#sys.path.append('/home/jziebart/.local/bin')
#sys.path.append('/home/jziebart/.local/lib')
import plotly
import plotly.graph_objs as go
import csv
import string
def mean_stdev(y):
mean = sum(y)
mean = sum(y)/len(y)
stdev = 0
for yi in y:
stdev = stdev + (yi - mean)**2
stdev = stdev/(len(y)-1)
stdev = math.sqrt(stdev)
return mean,stdev;
def standardize(y):
mean,stdev = mean_stdev(y)
ystd = []
for yi in y:
yi = (yi - mean)/stdev
ystd.append(yi)
return ystd
netID = sys.argv[-1]
outfile = netID+"violin_plotly_evidence.html"
filename=netID+"continuous_input.txt"
f=open(filename,"r")
#Read the first line to get the variable names
line=f.readline()
#line = map(string.strip,line.strip().split("\t"))
varNames = line.strip().split("\t")
#varNames = line
line=f.readline()
#line = map(string.strip,line.strip().split("\t"))
line = line.strip().split("\t")
for i in range(len(line)):
line[i] = int(line[i])
cd_types = line
cNames = []
for i in range(len(varNames)):
if cd_types[i] == 1:
cNames.append(varNames[i])
#Get the variables with evidence
evfile=netID+"varname.txt"
evf=open(evfile,"r")
line=evf.readline()
#ev_vars = map(string.strip,line.strip().split("\t"))
ev_vars = line.strip().split("\t")
keepVars = []
for i in cNames:
if i not in ev_vars:
keepVars.append(i)
#Read in original data
data = []
line = f.readline()
while line:
#line = map(string.strip,line.strip().split("\t"))
line = line.strip().split("\t")
temp = []
for i in range(len(varNames)):
if cd_types[i] == 1:
temp.append(float(line[i]))
data.append(temp)
line = f.readline()
#Read in data for violin plots
filename2=netID+"violin_evidence.txt"
f2=open(filename2,"r")
line = f2.readline()
pdf_varName = []
pdf_data = []
while line:
line = line.strip()
if line == "Data for new node":
line = f2.readline()
pdf_varName.append(line.strip())
line = f2.readline()
pdf_data.append([line.strip()])
else:
pdf_data[-1].append(float(line.strip()))
line = f2.readline()
layout = go.Layout(
title="Distributions considering evidence",
titlefont=dict(
family='Arial, sans-serif',
size=24,
color='black'
),
title_xref="paper",
title_x=0.5,
title_xanchor="center",
title_yanchor="middle",
yaxis=dict(title="Distributions of standardized data"),
legend=dict(orientation='h'),
margin=dict(t=40,l=70,b=40)
)
fig = go.Figure(layout=layout)
icount = 0
for i in range(len(keepVars)):
for j in range(len(cNames)):
if keepVars[i] == cNames[j]:
idata = j
break
for j in range(len(pdf_varName)):
if keepVars[i] == pdf_varName[j]:
ipdf = j
break
y = []
for j in range(len(data)):
y.append(data[j][idata])
y_stand = standardize(y)
#Add traces to violin plot
if icount == 0:
fig.add_trace(go.Violin(y=y_stand,x0=cNames[idata],side='negative',legendgroup='Data',name='Fit to original data',fillcolor='blue',line=dict(color='blue'),hoverinfo='none',points='all',scalegroup=cNames[idata]))
fig.add_trace(go.Violin(y=pdf_data[ipdf],x0=cNames[idata],side='positive',legendgroup='Network parameters considering evidence',name='Network parameters considering evidence',fillcolor='orange',line=dict(color='orange'),hoverinfo='none',points=False,scalegroup=cNames[idata]))
icount = 1
else:
fig.add_trace(go.Violin(y=y_stand,x0=cNames[idata],side='negative',legendgroup='Data',name='Data',fillcolor='blue',line=dict(color='blue'),showlegend=False,hoverinfo='none',points='all',scalegroup=cNames[idata]))
fig.add_trace(go.Violin(y=pdf_data[ipdf],x0=cNames[idata],side='positive',legendgroup='Network parameters considering evidence',name='Network parameters considering evidence',fillcolor='orange',line=dict(color='orange'),showlegend=False,hoverinfo='none',points=False,scalegroup=cNames[idata]))
plotly.offline.plot(fig,filename=outfile)
|
