# ITE / code / H_I_D / utilities / div_sample_generation.m

 ``` 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``` ```function [X,Y] = div_sample_generation(Z,ds) %Splits samples in Z (Z(:,t) is the t^th observation) into X and Y so that %X(:,t)-s are samples from the joint distribution and Y(:,t)-s are samples %from the product of the ds(m)-dimensional marginals [assumption: sum(ds)=size(Z,1)]. % %Copyright (C) 2012 Zoltan Szabo ("http://nipg.inf.elte.hu/szzoli", "szzoli (at) cs (dot) elte (dot) hu") % %This file is part of the ITE (Information Theoretical Estimators) Matlab/Octave toolbox. % %ITE is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by %the Free Software Foundation, either version 3 of the License, or (at your option) any later version. % %This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of %MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. % %You should have received a copy of the GNU General Public License along with ITE. If not, see . %verification [sum(ds)=size(Z,1)]: if sum(ds)~=size(Z,1) error('sum(ds) should be equal to size(Z,1).'); end %initialization: [D,num_of_samples] = size(Z); cum_ds = cumsum([1;ds(1:end-1)]);%1,d_1+1,d_1+d_2+1,... = starting indices of the subspaces. num_of_samples = floor(num_of_samples/2); %X: X = Z(:,1:num_of_samples); %Y: Y = zeros(D,num_of_samples);%preallocation for m = 1 : length(ds) idx = [cum_ds(m):cum_ds(m)+ds(m)-1]; Y(idx,:) = Z(idx,num_of_samples+randperm(num_of_samples)); end ```