Test tab correction.

GMR.m

@@ -9,14 +9,14 @@ MuTmp = zeros(nbVarOut,model.nbStates);
 expData = zeros(nbVarOut,nbData);
 expSigma = zeros(nbVarOut,nbVarOut,nbData);
 for t=1:nbData
-  %Compute activation weight
-  %See Eq. (3.0.5) in doc/TechnicalReport.pdf
-  for i=1:model.nbStates
-    H(i,t) = model.Priors(i) * gaussPDF(DataIn(:,t), model.Mu(in,i), model.Sigma(in,in,i)); 
-  end
-  H(:,t) = H(:,t)/sum(H(:,t));
-  %Compute expected conditional means
-  %See Eq. (3.0.3) in doc/TechnicalReport.pdf
+	%Compute activation weight
+	%See Eq. (3.0.5) in doc/TechnicalReport.pdf
+	for i=1:model.nbStates
+		H(i,t) = model.Priors(i) * gaussPDF(DataIn(:,t), model.Mu(in,i), model.Sigma(in,in,i)); 
+	end
+	H(:,t) = H(:,t)/sum(H(:,t));
+	%Compute expected conditional means
+	%See Eq. (3.0.3) in doc/TechnicalReport.pdf
 	for i=1:model.nbStates
 		MuTmp(:,i) = model.Mu(out,i) + model.Sigma(out,in,i)/model.Sigma(in,in,i) * (DataIn(:,t)-model.Mu(in,i));
 		expData(:,t) = expData(:,t) + H(i,t) * MuTmp(:,i);
@@ -26,9 +26,9 @@ for t=1:nbData
 	for i=1:model.nbStates
 		SigmaTmp = model.Sigma(out,out,i) - model.Sigma(out,in,i)/model.Sigma(in,in,i) * model.Sigma(in,out,i);
 		expSigma(:,:,t) = expSigma(:,:,t) + H(i,t) * (SigmaTmp + MuTmp(:,i)*MuTmp(:,i)');  
-	 	for j=1:model.nbStates
-		 	expSigma(:,:,t) = expSigma(:,:,t) - H(i,t)*H(j,t) * (MuTmp(:,i)*MuTmp(:,j)');  
-	 	end
+		for j=1:model.nbStates
+			expSigma(:,:,t) = expSigma(:,:,t) - H(i,t)*H(j,t) * (MuTmp(:,i)*MuTmp(:,j)');  
+		end
 	end
 end