function output=NCer(input);
%output=NCer(input); input matrix

input(logical(eye(size(input))))=nanmax(input(:));
sparsity=sum(input(:))/length(input(:));
output=nansum(input,2)*nansum(input,1);
output(logical(eye(size(output))))=nanmax(output(:));

path(path,'/home/jesse')

    [B,i,j] = unique(output(:));
freq = histc(j,1:length(i));
B=B(end:-1:1);
freq=freq(end:-1:1);
spar=cumsum(freq)/sum(freq);
thresh=B(max(find((spar-sparsity)<=0)));
output=real(output>=thresh);
output=sparse(output);

%output=sparse(output & output');