function z = rel_entr( x, y )

%REL_ENTR   Scalar relative entropy.
%   REL_ENTR(X,Y) returns an array of the same size as X+Y with the 
%   relative entropy function applied to each element:
%                      { X.*LOG(X./Y) if X >  0 & Y >  0,
%      REL_ENTR(X,Y) = { 0            if X == 0 & Y >= 0,
%                      { +Inf         otherwise.
%   X and Y must either be the same size, or one must be a scalar. If X and
%   Y are vectors, then SUM(REL_ENTR(X,Y)) returns their relative entropy.
%   If they are PDFs (that is, if X>=0, Y>=0, SUM(X)==1, SUM(Y)==1) then
%   this is equal to their Kullback-Liebler divergence SUM(KL_DIV(X,Y)).
%   -SUM(REL_ENTR(X,1)) returns the entropy of X.
%
%   Disciplined convex programming information:
%       REL_ENTR(X,Y) is convex in both X and Y, nonmonotonic in X, and
%       nonincreasing in Y. Thus when used in CVX expressions, X must be
%       real and affine and Y must be concave. The use of REL_ENTR(X,Y) in
%       an objective or constraint will effectively constrain both X and Y 
%       to be nonnegative, hence there is no need to add additional
%       constraints X >= 0 or Y >= 0 to enforce this.

error(nargchk(2,2,nargin));
if ~isreal( x ) || ~isreal( y ),
    error( 'Arguments must be real.' );
end
t1 = x < 0  | y <= 0;
t2 = x == 0 & y >= 0;
x  = max( x, realmin );
y  = max( y, realmin );
z  = x .* log( x ./ y );
z( t1 ) = +Inf;
z( t2 ) = 0;

% Copyright 2010 Michael C. Grant and Stephen P. Boyd.
% See the file COPYING.txt for full copyright information.
% The command 'cvx_where' will show where this file is located.
