function K=svmWriteKernel(K_file,type,D,Dnull,gamma)
% Deprecated!

% since A is: E_{p(y|x)}\{||x||_2^2\}, we concatenate it to the kernel to
% provide the nulldoc row,col that SVM_light expects.
%nulldocK = exp(-gamma * A);

% SVM_light fixup
% Line 4058 of svm_learn.c performs the following to estimate SVM c:
%    avgxlen+=sqrt( K(i,i)-2*K(i,nulldoc)+K(nulldoc,nulldoc));
% Thus, avgxlen goes to NaN unless the following is true:
%    (K(i,i)+K(nulldoc,nulldoc))/2 >= K(i,nulldoc)
% Hence, K(nulldoc,nulldoc)=2 will never let it go NaN, assuming:
%    K(i,nulldoc) \in [0,1]

% nulldocK is a col vector

if nargin<3
	error('must supply kernel type and matrix');
end

if strcmp(type,'rbf')
	if nargin~=5
		error('rbf kernel: must supply square euclidean distances, square '...
			'euclidean distance from zero, and gamma');
	end
	K = exp(-gamma * [[0 Dnull'];[Dnull D]]);
elseif strcmp(type,'linear')
	Dnull = sparse(1,size(Dnull,1));
	K = [[0 Dnull'];[Dnull D]];
else
	error('unrecognized kernel type');
end

floatfmt = '%.16g';
jvdmatrixWrite(K_file,K,floatfmt);