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ITE / code / IPA / data_generation / datasets / sample_subspaces_multiD_geom_Lshape.m

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function [e] = sample_subspaces_multiD_geom_Lshape(d,num_of_samples)
%Sampling from a random variable uniformly distributed on a d-dimensional L-shape.
%
%INPUT:
%	num_of_samples: number of samples to be generated.
%OUTPUT:
%   e: e(:,t) is the t^th sample. size(e,2) = num_of_samples.
%EXAMPLE:
%   e = sample_subspaces_multiD_geom_Lshape(4,1000);
%
%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 <http://www.gnu.org/licenses/>.

%0,e1+e2,...,e1+e2+...+ed:
    E = [zeros(d,1),triu(ones(d))];
	
%random starting vertex:
    start_index = discrete_nonuniform_sampling(ones(d,1)/d, 1,num_of_samples);%column index
	
%end vertex:
    end_index = start_index + 1;
	
e = E(:,start_index) + repmat(rand(1,num_of_samples),d,1).* (E(:,end_index) - E(:,start_index));