--- a/+scheme/Hypsyst2d.m	Fri Oct 12 08:50:25 2018 +0200
+++ b/+scheme/Hypsyst2d.m	Thu Jan 17 10:44:12 2019 +0100
@@ -6,10 +6,10 @@
         x,y % Grid
         X,Y % Values of x and y for each grid point
         order % Order accuracy for the approximation
-        
+
         D % non-stabalized scheme operator
         A, B, E %Coefficient matrices
-        
+
         H % Discrete norm
         % Norms in the x and y directions
         Hxi,Hyi % Kroneckerd norms. 1'*Hx*v corresponds to integration in the x dir.
@@ -17,65 +17,65 @@
         e_w, e_e, e_s, e_n
         params %parameters for the coeficient matrice
     end
-    
+
     methods
         %Solving Hyperbolic systems on the form u_t=-Au_x-Bu_y-Eu
         function obj = Hypsyst2d(m, lim, order, A, B, E, params)
             default_arg('E', [])
             xlim = lim{1};
             ylim = lim{2};
-            
+
             if length(m) == 1
                 m = [m m];
             end
-            
+
             obj.A=A;
             obj.B=B;
             obj.E=E;
-            
+
             m_x = m(1);
             m_y = m(2);
             obj.params = params;
-            
+
             ops_x = sbp.D2Standard(m_x,xlim,order);
             ops_y = sbp.D2Standard(m_y,ylim,order);
-            
+
             obj.x = ops_x.x;
             obj.y = ops_y.x;
-            
+
             obj.X = kr(obj.x,ones(m_y,1));
             obj.Y = kr(ones(m_x,1),obj.y);
-            
+
             Aevaluated = obj.evaluateCoefficientMatrix(A, obj.X, obj.Y);
             Bevaluated = obj.evaluateCoefficientMatrix(B, obj.X, obj.Y);
             Eevaluated = obj.evaluateCoefficientMatrix(E, obj.X, obj.Y);
-            
+
             obj.n = length(A(obj.params,0,0));
-            
+
             I_n = eye(obj.n);I_x = speye(m_x);
             obj.I_x = I_x;
             I_y = speye(m_y);
             obj.I_y = I_y;
-            
-            
+
+
             D1_x = kr(I_n, ops_x.D1, I_y);
             obj.Hxi = kr(I_n, ops_x.HI, I_y);
             D1_y = kr(I_n, I_x, ops_y.D1);
             obj.Hyi = kr(I_n, I_x, ops_y.HI);
-            
+
             obj.e_w = kr(I_n, ops_x.e_l, I_y);
             obj.e_e = kr(I_n, ops_x.e_r, I_y);
             obj.e_s = kr(I_n, I_x, ops_y.e_l);
             obj.e_n = kr(I_n, I_x, ops_y.e_r);
-            
+
             obj.m = m;
             obj.h = [ops_x.h ops_y.h];
             obj.order = order;
-            
+
             obj.D = -Aevaluated*D1_x-Bevaluated*D1_y-Eevaluated;
-            
+
         end
-        
+
         % Closure functions return the opertors applied to the own doamin to close the boundary
         % Penalty functions return the opertors to force the solution. In the case of an interface it returns the operator applied to the other doamin.
         %       boundary            is a string specifying the boundary e.g. 'l','r' or 'e','w','n','s'.
@@ -92,18 +92,18 @@
                     error('No such boundary condition')
             end
         end
-        
-        function [closure, penalty] = interface(obj,boundary,neighbour_scheme,neighbour_boundary)
-            error('An interface function does not exist yet');
+
+        function [closure, penalty] = interface(obj, boundary, neighbour_scheme, neighbour_boundary, type)
+            error('Not implemented');
         end
-        
+
         function N = size(obj)
             N = obj.m;
         end
-        
+
         function [ret] = evaluateCoefficientMatrix(obj, mat, X, Y)
             params = obj.params;
-            
+
             if isa(mat,'function_handle')
                 [rows,cols] = size(mat(params,0,0));
                 matVec = mat(params,X',Y');
@@ -116,7 +116,7 @@
                 cols = cols/side;
             end
             ret = cell(rows,cols);
-            
+
             for ii = 1:rows
                 for jj=1:cols
                     ret{ii,jj} = diag(matVec(ii,(jj-1)*side+1:jj*side));
@@ -124,13 +124,13 @@
             end
             ret = cell2mat(ret);
         end
-        
+
         %Characteristic boundary conditions
         function [closure, penalty] = boundary_condition_char(obj,boundary)
             params = obj.params;
             x = obj.x;
             y = obj.y;
-            
+
             switch boundary
                 case {'w','W','west'}
                     e_ = obj.e_w;
@@ -164,7 +164,7 @@
             pos = signVec(1);
             zeroval = signVec(2);
             neg = signVec(3);
-            
+
             switch boundPos
                 case {'l'}
                     tau = sparse(obj.n*side,pos);
@@ -180,13 +180,13 @@
                     penalty = -Hi*e_*V*tau*Vi_minus;
             end
         end
-        
+
         % General boundary condition in the form Lu=g(x)
         function [closure,penalty] = boundary_condition_general(obj,boundary,L)
             params = obj.params;
             x = obj.x;
             y = obj.y;
-            
+
             switch boundary
                 case {'w','W','west'}
                     e_ = obj.e_w;
@@ -218,14 +218,14 @@
                     boundPos = 'r';
                     Hi = obj.Hyi;
                     [V,Vi,D,signVec] = obj.matrixDiag(mat,x,y(end));
-                    L = obj.evaluateCoefficientMatrix(L,x,y(end));      
+                    L = obj.evaluateCoefficientMatrix(L,x,y(end));
                     side = max(length(x));
             end
-            
+
             pos = signVec(1);
             zeroval = signVec(2);
             neg = signVec(3);
-            
+
             switch boundPos
                 case {'l'}
                     tau = sparse(obj.n*side,pos);
@@ -233,7 +233,7 @@
                     Vi_minus = Vi(pos+zeroval+1:obj.n*side,:);
                     V_plus = V(:,1:pos);
                     V_minus = V(:,(pos+zeroval)+1:obj.n*side);
-                    
+
                     tau(1:pos,:) = -abs(D(1:pos,1:pos));
                     R = -inv(L*V_plus)*(L*V_minus);
                     closure = Hi*e_*V*tau*(Vi_plus-R*Vi_minus)*e_';
@@ -243,7 +243,7 @@
                     tau((pos+zeroval)+1:obj.n*side,:) = -abs(D((pos+zeroval)+1:obj.n*side,(pos+zeroval)+1:obj.n*side));
                     Vi_plus = Vi(1:pos,:);
                     Vi_minus = Vi((pos+zeroval)+1:obj.n*side,:);
-                    
+
                     V_plus = V(:,1:pos);
                     V_minus = V(:,(pos+zeroval)+1:obj.n*side);
                     R = -inv(L*V_minus)*(L*V_plus);
@@ -251,13 +251,13 @@
                     penalty = -Hi*e_*V*tau*inv(L*V_minus)*L;
             end
         end
-        
+
         % Function that diagonalizes a symbolic matrix A as A=V*D*Vi
         % D         is a diagonal matrix with the eigenvalues on A on the diagonal sorted by their sign
         %                                    [d+       ]
         %                               D =  [   d0    ]
         %                                    [       d-]
-        % signVec   is a vector specifying the number of possitive, zero and negative eigenvalues of D   
+        % signVec   is a vector specifying the number of possitive, zero and negative eigenvalues of D
         function [V,Vi, D,signVec] = matrixDiag(obj,mat,x,y)
             params = obj.params;
             syms xs ys
@@ -265,12 +265,12 @@
             Vi = inv(V);
             xs = x;
             ys = y;
-            
+
             side = max(length(x),length(y));
             Dret = zeros(obj.n,side*obj.n);
             Vret = zeros(obj.n,side*obj.n);
             Viret = zeros(obj.n,side*obj.n);
-            
+
             for ii = 1:obj.n
                 for jj = 1:obj.n
                     Dret(jj,(ii-1)*side+1:side*ii) = eval(D(jj,ii));
@@ -278,7 +278,7 @@
                     Viret(jj,(ii-1)*side+1:side*ii) = eval(Vi(jj,ii));
                 end
             end
-            
+
             D = sparse(Dret);
             V = sparse(Vret);
             Vi = sparse(Viret);
@@ -286,16 +286,16 @@
             Vi = obj.evaluateCoefficientMatrix(Vi,x,y);
             D = obj.evaluateCoefficientMatrix(D,x,y);
             DD = diag(D);
-            
+
             poseig = (DD>0);
             zeroeig = (DD==0);
             negeig = (DD<0);
-            
+
             D = diag([DD(poseig); DD(zeroeig); DD(negeig)]);
             V = [V(:,poseig) V(:,zeroeig) V(:,negeig)];
             Vi = [Vi(poseig,:); Vi(zeroeig,:); Vi(negeig,:)];
             signVec = [sum(poseig),sum(zeroeig),sum(negeig)];
         end
-        
+
     end
 end
\ No newline at end of file