Switch eager example over to weak DG

examples/wave/wave-eager.py

@@ -69,12 +69,7 @@ def wave_flux(discr, c, w_tpair):
             0.5*normal_times(v_jump),
             )
 
-    flux_strong = join_fields(
-            np.dot(v.int, normal),
-            normal_times(u.int),
-            ) - flux_weak
-
-    return discr.interp(w_tpair.dd, "all_faces", c*flux_strong)
+    return discr.interp(w_tpair.dd, "all_faces", c*flux_weak)
 
 
 def wave_operator(discr, c, w):
@@ -87,12 +82,12 @@ def wave_operator(discr, c, w):
     dir_bc = join_fields(-dir_u, dir_v)
 
     return (
-            - join_fields(
-                -c*discr.div(v),
-                -c*discr.grad(u)
-                )
-            +  # noqa: W504
             discr.inverse_mass(
+                join_fields(
+                    c*discr.weak_div(v),
+                    c*discr.weak_grad(u)
+                    )
+                -  # noqa: W504
                 discr.face_mass(
                     wave_flux(discr, c=c, w_tpair=interior_trace_pair(discr, w))
                     + wave_flux(discr, c=c, w_tpair=TracePair(

grudge/eager.py

@@ -66,6 +66,17 @@ class EagerDGDiscretization(DGDiscretizationWithBoundaries):
         return sum(
                 self.grad(vec_i)[i] for i, vec_i in enumerate(vecs))
 
+    @memoize_method
+    def _bound_weak_grad(self):
+        return bind(self, sym.stiffness_t(self.dim) * sym.Variable("u"))
+
+    def weak_grad(self, vec):
+        return self._bound_weak_grad()(vec.queue, u=vec)
+
+    def weak_div(self, vecs):
+        return sum(
+                self.weak_grad(vec_i)[i] for i, vec_i in enumerate(vecs))
+
     @memoize_method
     def normal(self, dd):
         with cl.CommandQueue(self.cl_context) as queue: