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
164
165
|
function bnet_miss = gener_MCAR_net(bnet_orig, base_proba)
% function bnet_miss = gener_MCAR_net(bnet_orig, base_proba)
%
% bnet_orig : a bnet
% base_proba : a probability for value to be missing
%
% bnet_miss : a bnet that could be used in gener_data_from_bnet_miss function
% to generate incomplete MCAR dataset
%
% Francois.Olivier.C.H@gmail.com
%%%%%%%%%%%% INIT
%bnet_miss = gener_MCAR_net(bnet_orig, base_proba, upd, bnet_biss)
%if nargin<4, upd = 0; else upd = 1; end
%if nargin<3, manual = 0; end
if nargin<2, error('Not enougth arguments'); end
% création du réseau
dag = bnet_orig.dag;
N = size(dag,2);
ns = bnet_orig.node_sizes;
%if nargin<4,
ns_miss = zeros(1,3*N);
ns_miss(1:N) = ns;
ns_miss(N+1:2*N) = 2*ones(1,N); % 1= node i-N present, 2= node i-N missing
ns_miss(2*N+1:3*N) = ns+1; % 1:ns, absent
dag_miss = zeros(3*N,3*N);
dag_miss(1:N,1:N) = dag;
dag_miss(N+1:2*N,N+1:2*N)=mk_rnd_dag(N,N-ceil(rand*N/2)); %dag_miss(N+1:2*N,N+1:2*N)=mk_rnd_dag(N,2);
for i=1:N, dag_miss(i,2*N+i)=1; dag_miss(N+i,2*N+i)=1; end
bnet_miss = mk_bnet(dag_miss, ns_miss);
CPT = CPT_from_bnet(bnet_orig, 0);
for i=1:N
bnet_miss.CPD{i} = tabular_CPD (bnet_miss, i, CPT{i});
end
% CPD of nodes M
for i=1:N,
if find(bnet_miss.order==i)<find(bnet_miss.order==N+i),
CPT_M=[];
for j=1:ns_miss(i), for l=1:ns_miss(N+i), for k=1:ns_miss(2*N+i),
CPT_M=[CPT_M (((j==k)&(l==1))|((k==ns_miss(2*N+i))&(l==2)))];
end, end, end
else
CPT_M=[];
for k=1:ns_miss(2*N+i), for l=1:ns_miss(N+i), for j=1:ns_miss(i),
CPT_M=[CPT_M (((j==k)&(l==1))|((k==ns_miss(2*N+i))&(l==2)))];
end, end, end
end
bnet_miss.CPD{2*N+i} = tabular_CPD (bnet_miss, 2*N+i, CPT_M);
end
% else
% ns_miss = bnet_miss.node_sizes;
% dag_miss = bnet_miss.dag;
% end
%%%%%%%%%%%% Base probability of missing value
p = base_proba;
for i=1:N
fam = find(dag_miss(:,N+i)==1)';
semisize = prod(ns_miss(fam)); % as node N+i is binary to say i is present or missing
CPT = zeros(1,2*semisize);
CPT(1:semisize) = 1-p;
CPT(semisize+1:2*semisize) = p;
bnet_miss.CPD{N+i} = tabular_CPD (bnet_miss, N+i, CPT);
end
% if manual, % manual generation
%
% if upd==1;
%
% fprintf('Base probability of a data to be missing is %1.4f',base_proba);
%
% b=-1;
% while ~(b==0 | b==1), b = input('Would you like to change a probability of a node to be missing (1 for yes, 0 for no) ? '); end
%
% %%%%%%%%%%%% Update CPT with MCAR process
% while b
% fprintf('Nodes are from 1 to %d. ',N);
% i=0;
% while i<1 | i>N | round(i)~=i, i = input('Which node ? '); end
% fam = find(dag(:,i)==1)';
% fam_miss = find(dag_miss(:,N+i)==1)';
% cas = -ones(1, length(fam_miss)+1);
% familly = [fam_miss, N+i];
% p=-1;
% while p<0 | p>1, p = input(' - A priori probability for this node to be missing ? ');end
% semisize = prod(ns_miss(fam_miss));
% CPT = zeros(1,2*semisize);
% CPT(1:semisize) = 1-p;
% CPT(semisize+1:2*semisize) = p;
% bnet_miss.CPD{N+i} = tabular_CPD (bnet_miss, N+i, CPT);
% b=-1;
% while ~(b==0 | b==1), b = input('Would you like to change a probability of a node to be missing (1 for yes, 0 for no) ? ');end
% end
% end
%
%
% else % automatic generation
%%%%%%%%%%%% creating BETAs
% %% To use multiple of 5 percent in probs
% if N<=25,
% BETA = gener_problist(base_proba, N);
% else
% nboucles = floor(N/25);
% BETA = [];
% for i=1:nboucles
% BETA1 = gener_problist(base_proba, 25);
% BETA = [BETA, BETA1];
% end
% nreste = rem(N,25);
% BETA1 = gener_problist(base_proba, nreste);
% BETA = [BETA, BETA1];
% end
BETA = gener_discrete_dist(N, base_proba);
order=[];
missdagtmp = bnet_miss.dag(N+1:2*N,N+1:2*N);
unprocessed = 1:N;
while ~isempty(unprocessed)
npar=[];
for i=1:N, npar(end+1)=length(parents(missdagtmp,i));end,
[npar, ord] = sort(npar);
while ~ismember(ord(1),unprocessed)
ord=ord(2:end);
end
order = [order, ord(1)];
missdagtmp(ord(1),:)=0;
unprocessed = mysetdiff(unprocessed,ord(1));
end
%%%%%%%%%%%% Update CPT with MCAR process
for i=1:length(BETA)
fam_miss = find(dag_miss(:,N+order(i))==1)';
p=BETA(i);
semisize = prod(ns_miss(fam_miss));
if isempty(fam_miss),
CPT = zeros(1,2*semisize);
CPT(1:semisize) = 1-p;
CPT(semisize+1:2*semisize) = p;
bnet_miss.CPD{N+order(i)} = tabular_CPD (bnet_miss, N+order(i), CPT);
else
%node = N+order(i)
%for k=1:semisize
% XI(k) = eval_xi(bnet_miss, N+order(i), k);
% %XI(k+semisize)=1-XI(k);
%end
%MUi1 = zeros(1,semisize);
%MUi1 = gener_mu(p, semisize, XI);
MUi1k = gener_discrete_dist(semisize, p);
CPT = zeros(1,2*semisize);
CPT(1:semisize) = 1-MUi1k;
CPT(semisize+1:2*semisize) = MUi1k;
bnet_miss.CPD{N+order(i)} = tabular_CPD (bnet_miss, N+order(i), CPT);
end
% end
end
|
