|
wolffd@0
|
1 function [me, st, md, no] = nanstats(D)
|
|
wolffd@0
|
2
|
|
wolffd@0
|
3 %NANSTATS Statistical operations that ignore NaNs and Infs.
|
|
wolffd@0
|
4 %
|
|
wolffd@0
|
5 % [mean, std, median, nans] = nanstats(D)
|
|
wolffd@0
|
6 %
|
|
wolffd@0
|
7 % Input and output arguments:
|
|
wolffd@0
|
8 % D (struct) data or map struct
|
|
wolffd@0
|
9 % (matrix) size dlen x dim
|
|
wolffd@0
|
10 %
|
|
wolffd@0
|
11 % me (double) columnwise mean
|
|
wolffd@0
|
12 % st (double) columnwise standard deviation
|
|
wolffd@0
|
13 % md (double) columnwise median
|
|
wolffd@0
|
14 % no (vector) columnwise number of samples (finite, not-NaN)
|
|
wolffd@0
|
15
|
|
wolffd@0
|
16 % Contributed to SOM Toolbox vs2, February 2nd, 2000 by Juha Vesanto
|
|
wolffd@0
|
17 % http://www.cis.hut.fi/projects/somtoolbox/
|
|
wolffd@0
|
18
|
|
wolffd@0
|
19 % Version 2.0beta juuso 300798 200900
|
|
wolffd@0
|
20
|
|
wolffd@0
|
21 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
wolffd@0
|
22 %% check arguments
|
|
wolffd@0
|
23
|
|
wolffd@0
|
24 (nargchk(1, 1, nargin)); % check no. of input args is correct
|
|
wolffd@0
|
25
|
|
wolffd@0
|
26 if isstruct(D),
|
|
wolffd@0
|
27 if strcmp(D.type,'som_map'), D = D.codebook;
|
|
wolffd@0
|
28 else D = D.data;
|
|
wolffd@0
|
29 end
|
|
wolffd@0
|
30 end
|
|
wolffd@0
|
31 [dlen dim] = size(D);
|
|
wolffd@0
|
32 me = zeros(dim,1)+NaN;
|
|
wolffd@0
|
33 md = me;
|
|
wolffd@0
|
34 st = me;
|
|
wolffd@0
|
35 no = me;
|
|
wolffd@0
|
36
|
|
wolffd@0
|
37 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
wolffd@0
|
38 %% computation
|
|
wolffd@0
|
39
|
|
wolffd@0
|
40 for i = 1:dim,
|
|
wolffd@0
|
41 ind = find(isfinite(D(:, i))); % indices of non-NaN/Inf elements
|
|
wolffd@0
|
42 n = length(ind); % no of non-NaN/Inf elements
|
|
wolffd@0
|
43
|
|
wolffd@0
|
44 me(i) = sum(D(ind, i)); % compute average
|
|
wolffd@0
|
45 if n == 0, me(i) = NaN; else me(i) = me(i) / n; end
|
|
wolffd@0
|
46
|
|
wolffd@0
|
47 if nargout>1,
|
|
wolffd@0
|
48 md(i) = median(D(ind, i)); % compute median
|
|
wolffd@0
|
49
|
|
wolffd@0
|
50 if nargout>2,
|
|
wolffd@0
|
51 st(i) = sum((me(i) - D(ind, i)).^2); % compute standard deviation
|
|
wolffd@0
|
52 if n == 0, st(i) = NaN;
|
|
wolffd@0
|
53 elseif n == 1, st(i) = 0;
|
|
wolffd@0
|
54 else st(i) = sqrt(st(i) / (n - 1));
|
|
wolffd@0
|
55 end
|
|
wolffd@0
|
56
|
|
wolffd@0
|
57 if nargout>3,
|
|
wolffd@0
|
58 no(i) = n; % number of samples (finite, not-NaN)
|
|
wolffd@0
|
59 end
|
|
wolffd@0
|
60 end
|
|
wolffd@0
|
61 end
|
|
wolffd@0
|
62 end
|
|
wolffd@0
|
63
|
|
wolffd@0
|
64 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
|
wolffd@0
|
65
|
