diff options
Diffstat (limited to 'sourcecodes/bnt-master/KPMtools/mk_stochastic.m')
| -rw-r--r-- | sourcecodes/bnt-master/KPMtools/mk_stochastic.m | 27 |
1 files changed, 27 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/KPMtools/mk_stochastic.m b/sourcecodes/bnt-master/KPMtools/mk_stochastic.m new file mode 100644 index 00000000..68aac6ab --- /dev/null +++ b/sourcecodes/bnt-master/KPMtools/mk_stochastic.m @@ -0,0 +1,27 @@ +function [T,Z] = mk_stochastic(T) +% MK_STOCHASTIC Ensure the argument is a stochastic matrix, i.e., the sum over the last dimension is 1. +% [T,Z] = mk_stochastic(T) +% +% If T is a vector, it will sum to 1. +% If T is a matrix, each row will sum to 1. +% If T is a 3D array, then sum_k T(i,j,k) = 1 for all i,j. + +% Set zeros to 1 before dividing +% This is valid since S(j) = 0 iff T(i,j) = 0 for all j + +if (ndims(T)==2) && (size(T,1)==1 || size(T,2)==1) % isvector + [T,Z] = normalise(T); +elseif ndims(T)==2 % matrix + Z = sum(T,2); + S = Z + (Z==0); + norm = repmat(S, 1, size(T,2)); + T = T ./ norm; +else % multi-dimensional array + ns = size(T); + T = reshape(T, prod(ns(1:end-1)), ns(end)); + Z = sum(T,2); + S = Z + (Z==0); + norm = repmat(S, 1, ns(end)); + T = T ./ norm; + T = reshape(T, ns); +end |