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
|
function [ labels, cases, bnet, node_sizes, data,labelsold] = readInput( dfile, sfile, nnodes, std_flag )
%readInput is to be used when reading in a network with a known structure
%
%Input:
% dfile = name of the file containing the data (required)
% sfile = name of the file containing the structure (required)
% nnodes = number of nodes in the network (required)
% std_flag = flag for whether or not to standardize the data.
% (optional-- Default is FALSE)
%
% See readInputData.m and readInputStructure.m for description of the
% format of the dfile and sfile, respectively.
%
%Output:
% labels = cell array with the names of the nodes.
% cases = cell array with the data.
% bnet = BNT bayesian network with the input structure.
%
% readInput is called by runBN_initial.m
if nargin < 4
std_flag = false(1);
end
% read in the file with the data
[labelsold,node_sizes,cases, data] = readInputData(dfile,nnodes);
% read in the file with the structure
[dag] = readInputStructure(sfile,labelsold);
% check the ordering of the nodes and reorder if necessary
[labels,cases,dag,node_sizes,ord_flag] = checkStructure(labelsold,cases,dag,node_sizes);
dcount = 0;
for i = 1:nnodes
if node_sizes(i) ~= 1
dcount = dcount + 1;
end
end
discrete = zeros(1,dcount);
dcount = 0;
for i = 1:nnodes
if node_sizes(i) ~= 1
dcount = dcount + 1;
discrete(dcount) = i;
end
end
bnet = mk_bnet(dag,node_sizes,'discrete',discrete,'names',labels);
%bnet.dag
checkDiscreteNodes(bnet,cases);
% standardize continuous data to have a mean = 0 and std = 1
if (std_flag)
[cases] = standardizeData(labels,node_sizes,cases);
end
end
% end of readInput.m
|
