source: prextra/gendatw.m @ 160

%GENDATW Sample dataset by given weigths
%
%   B = GENDATW(A,V,N)
%
% INPUT
%   A    Dataset
%   V    Vector with weigths for each object in A
%   N    Number of objects to be generated (default size A);
%
% OUTPUT
%   B    Dataset
%
% DESCRIPTION
% The dataset A is sampled using the weigths in V as a prior distribution.

function b = gendatw(a,v,n)

isdataset(a);
if nargin < 3, n  = size(a,1); end

v = v./sum(v);
if any(v<0)
    error('Weights should be positive');
end

mins = 0;
nn = 0;
while(mins < 2)
        N = genclass(n,v);
        L = [];
        while any(N > 0)
            L = [L find(N > 0)];
            N = N-1;
        end
        b = a(L,:);
        mins = min(classsizes(b));
        nn = nn + 1;
        if nn > 100
                error('Problems with weighted subsampling. Please enlarge training set.')
        end
end

return