Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/KPMtools/mk_stochastic.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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-1:000000000000 | 0:e9a9cd732c1e |
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1 function [T,Z] = mk_stochastic(T) | |
2 % MK_STOCHASTIC Ensure the argument is a stochastic matrix, i.e., the sum over the last dimension is 1. | |
3 % [T,Z] = mk_stochastic(T) | |
4 % | |
5 % If T is a vector, it will sum to 1. | |
6 % If T is a matrix, each row will sum to 1. | |
7 % If T is a 3D array, then sum_k T(i,j,k) = 1 for all i,j. | |
8 | |
9 % Set zeros to 1 before dividing | |
10 % This is valid since S(j) = 0 iff T(i,j) = 0 for all j | |
11 | |
12 if (ndims(T)==2) & (size(T,1)==1 | size(T,2)==1) % isvector | |
13 [T,Z] = normalise(T); | |
14 elseif ndims(T)==2 % matrix | |
15 Z = sum(T,2); | |
16 S = Z + (Z==0); | |
17 norm = repmat(S, 1, size(T,2)); | |
18 T = T ./ norm; | |
19 else % multi-dimensional array | |
20 ns = size(T); | |
21 T = reshape(T, prod(ns(1:end-1)), ns(end)); | |
22 Z = sum(T,2); | |
23 S = Z + (Z==0); | |
24 norm = repmat(S, 1, ns(end)); | |
25 T = T ./ norm; | |
26 T = reshape(T, ns); | |
27 end |