pasbc3d

examples/particles_above_salt/particles_above_salt_bc_3d.py

@@ -75,8 +75,7 @@ def compute(args):
     if (dim==2):
         (Sc, tau, Vp, Rs, Xo, Xn, N) = (0.70,  25, 0.04, 2.0, (-600,0), (600,750), (1537, 512))
     elif (dim==3):
-        (Sc, tau, Vp, Rs, Xo, Xn, N) = (7.00, 25, 0.04, 2.0, (-110,0,0), (65,100,100), (3073, 1024, 1024))
-        N = (513,128,128)
+        (Sc, tau, Vp, Rs, Xo, Xn, N) = (15.00, 25, 0.04, 2.0, (-110,0,0), (65,100,100), (3073, 1024, 1024))
     else:
         raise NotImplementedError
 
@@ -184,6 +183,7 @@ def compute(args):
     
     #> Diffusion of vorticity, S and C
     diffuse_S = Diffusion(implementation=impl,
+             enforce_implementation=False,
              name='diffuse_S',
              pretty_name='diffS',
              nu = nu_S,
@@ -191,6 +191,7 @@ def compute(args):
              variables = {S: npts},
              dt=dt, **extra_op_kwds)
     diffuse_C = Diffusion(implementation=impl,
+             enforce_implementation=False,
              name='diffuse_C',
              pretty_name='diffC',
              nu = nu_C,
@@ -219,10 +220,12 @@ def compute(args):
     
     ### Build standard operators
     #> Poisson operator to recover the velocity from the vorticity
-    poisson = PoissonCurl(name='poisson', velocity=velo, vorticity=vorti, 
-                            variables={velo:npts, vorti: npts},
-                            diffusion=nu_W, dt=dt,
-                            implementation=impl, **extra_op_kwds)
+    poisson = PoissonCurl(name='poisson',
+                          enforce_implementation=False,
+                          velocity=velo, vorticity=vorti, 
+                          variables={velo:npts, vorti: npts},
+                          diffusion=nu_W, dt=dt,
+                          implementation=impl, **extra_op_kwds)
     
     #> Operator to compute the infinite norm of the velocity
     min_max_U = MinMaxFieldStatistics(name='min_max_U', field=velo,
@@ -274,7 +277,7 @@ def compute(args):
         )
 
     problem = Problem(method=method)
-    problem.insert(poisson, dump_fields,
+    problem.insert(poisson, 
                    diffuse_S, diffuse_C,
                    splitting, 
                    min_max_U, min_max_W, adapt_dt)