[squaredmax,rowIndex]=MaxSqDistAndRowIndexbw2Mat(mat1,mat2)

% % find max. square distance and corresponding row index
% % b/w to two 2D arrays 'mat1' and 'mat2'. 
% % the algorithms is based on euclidean distance 
function [squaredmax,rowIndex]=MaxSqDistAndRowIndexbw2Mat(mat1,mat2)
% mat1=[x11,x12,...x1n;
%       x11,x12,...x1n; 
%       ...
%       xn1,xn2,...xnn; 

% mat2=[y11,y12,...y1n;
%       y11,y12,...y1n; 
%       ...
%       yn1,yn2,...ynn; 
% OR in brief mat1 and mat2 format is like following
%                               [P1;
%                                P2;
%                                P3;
%                                P4;
%                                ...
%                                PN];


if ~isequal(size(mat1),size(mat2))
    error('Two matrices must of of equal size');
end

% %Casting for accurate computation
mat1=double(mat1); 
mat2=double(mat2);

rowIndex=1;
squaredmax=sum( (mat1(1,:)-mat2(1,:)).^2,2 );

for k=1:size(mat1,1)
    % computing square distance b/w kth row
    SqDist=sum( (mat1(k,:)-mat2(k,:)).^2,2 )  ;
    % %  SqDist=TwoNormSqDist(mat1(k,:),mat2(k,:)); %No longer in use
    if(SqDist > squaredmax )
        squaredmax=SqDist;
        rowIndex=k;
    end
end


% % % --------------------------------
% % % Author: Dr. Murtaza Khan
% % % Email : [e-mail]
% % % --------------------------------