NormalizeFea.m

function fea = NormalizeFea(fea,row)
% if row == 1, normalize each row of fea to have unit norm;
% if row == 0, normalize each column of fea to have unit norm;
%
%   version 3.0 --Jan/2012 
%   version 2.0 --Jan/2012 
%   version 1.0 --Oct/2003 
%
%   Written by Deng Cai (dengcai AT gmail.com)
%

if ~exist('row','var')
    row = 1;
end

if row
    nSmp = size(fea,1); % number of rows
    feaNorm = max(1e-14,full(sum(fea.^2,2))); % sum(aa,2) returns a vector that each element is the sum of the row
                                              % sum(aa,2) sum of the row
                                              % and returns a column vector
                                              % feaNorm: is a vector, where
                                              % each element is the sum of
                                              % squares of each row. 
    fea = spdiags(feaNorm.^-.5,0,nSmp,nSmp)*fea;  %Sparse matrix formed from diagonals
else
    nSmp = size(fea,2);
    feaNorm = max(1e-14,full(sum(fea.^2,1))');
    fea = fea*spdiags(feaNorm.^-.5,0,nSmp,nSmp);
end
            
return;

% 
% if row
%     [nSmp, mFea] = size(fea); % nSmp number of samples 
%                               % mFea number of feature
%     if issparse(fea)
%         fea2 = fea';
%         feaNorm = mynorm(fea2,1);
%         for i = 1:nSmp
%             fea2(:,i) = fea2(:,i) ./ max(1e-10,feaNorm(i));
%         end
%         fea = fea2';
%     else
%         feaNorm = sum(fea.^2,2).^.5;
%         fea = fea./feaNorm(:,ones(1,mFea));
%     end
% else
%     [mFea, nSmp] = size(fea);
%     if issparse(fea)
%         feaNorm = mynorm(fea,1);
%         for i = 1:nSmp
%             fea(:,i) = fea(:,i) ./ max(1e-10,feaNorm(i));
%         end
%     else
%         feaNorm = sum(fea.^2,1).^.5;
%         fea = fea./feaNorm(ones(1,mFea),:);
%     end
% end
%