--- a/+time/SBPInTimeScaled.m	Wed Apr 10 22:22:46 2019 +0200
+++ b/+time/SBPInTimeScaled.m	Wed Apr 10 22:40:55 2019 +0200
@@ -7,7 +7,7 @@
         A,B
         f
 
-        k % total time step.
+        dt % total time step.
 
         blockSize % number of points in each block
         N % Number of components
@@ -29,7 +29,7 @@
     end
 
     methods
-        function obj = SBPInTimeScaled(A, B, f, k, t0, v0, scaling, TYPE, order, blockSize)
+        function obj = SBPInTimeScaled(A, B, f, dt, t0, v0, scaling, TYPE, order, blockSize)
             default_arg('TYPE','gauss');
             default_arg('f',[]);
 
@@ -51,7 +51,7 @@
                 obj.f = @(t)sparse(length(v0),1);
             end
 
-            obj.k = k;
+            obj.dt = dt;
             obj.blockSize = blockSize;
             obj.N = length(v0);
 
@@ -61,13 +61,13 @@
             %==== Build the time discretization matrix =====%
             switch TYPE
                 case 'equidistant'
-                    ops = sbp.D2Standard(blockSize,{0,obj.k},order);
+                    ops = sbp.D2Standard(blockSize,{0,obj.dt},order);
                 case 'optimal'
-                    ops = sbp.D1Nonequidistant(blockSize,{0,obj.k},order);
+                    ops = sbp.D1Nonequidistant(blockSize,{0,obj.dt},order);
                 case 'minimal'
-                    ops = sbp.D1Nonequidistant(blockSize,{0,obj.k},order,'minimal');
+                    ops = sbp.D1Nonequidistant(blockSize,{0,obj.dt},order,'minimal');
                 case 'gauss'
-                    ops = sbp.D1Gauss(blockSize,{0,obj.k});
+                    ops = sbp.D1Gauss(blockSize,{0,obj.dt});
             end
 
             I = speye(size(A));
@@ -121,7 +121,7 @@
 
             obj.vtilde = obj.e_T'*w;
 
-            obj.t = obj.t + obj.k;
+            obj.t = obj.t + obj.dt;
             obj.n = obj.n + 1;
         end
     end