% function [lik, likv]=mfa_cl(X,Lh,Ph,Mu,Pi);% % Calculates log likelihoods of a data set under a mixture of factor% analysis model.%% X - data matrix% Lh - factor loadings % Ph - diagonal uniquenesses matrix% Mu - mean vectors% Pi - priors%% lik - log likelihood of X % likv - vector of log likelihoods% % If 0 or 1 output arguments requested, lik is returned. If 2 output% arguments requested, [lik likv] is returned.function [lik, likv]=mfa_cl(X,Lh,Ph,Mu,Pi);N=length(X(:,1));D=length(X(1,:));K=length(Lh(1,:));M=length(Pi);if (abs(sum(Pi)-1) > 1e-6)   disp('ERROR: Pi should sum to 1');  return;elseif ((size(Lh) ~= [D*M K]) | (size(Ph) ~= [D 1]) | (size(Mu) ~= [M D]) ...  | (size(Pi) ~= [M 1] & size(Pi) ~= [1 M]))     disp('ERROR in input matrix sizes');  return;end;  tiny=exp(-744);const=(2*pi)^(-D/2);I=eye(K);Phi=1./Ph;Phid=diag(Phi);for k=1:M    Lht=Lh((k-1)*D+1:k*D,:);  LP=Phid*Lht;  MM=Phid-LP*inv(I+Lht'*LP)*LP';  dM=sqrt(det(MM));      	  Xk=(X-ones(N,1)*Mu(k,:));   XM=Xk*MM;   H(:,k)=const*Pi(k)*dM*exp(-0.5*sum((XM.*Xk)'))'; 	end;Hsum=rsum(H); 				likv=log(Hsum+(Hsum==0)*tiny);lik=sum(likv);