wave3d: cleanup

fast/wave3d.py

@@ -88,45 +88,41 @@ def plot_3dfunc(u):
 # First, position source centrally in all dimensions, then set depth
 src.coordinates.data[0, :] = np.array(model.domain_size) * .5
 
-# We can plot the time signature to see the wavelet
-# src.show()
-
 # Define the wavefield with the size of the model and the time dimension
 u = TimeFunction(name="u", grid=model.grid, time_order=to, space_order=so)
 # Another one to clone data
 u2 = TimeFunction(name="u", grid=model.grid, time_order=to, space_order=so)
+ub = TimeFunction(name="ub", grid=model.grid, time_order=to, space_order=so)
+
 
 # We can now write the PDE
 # pde = model.m * u.dt2 - u.laplace + model.damp * u.dt
 # import pdb;pdb.set_trace()
 pde = u.dt2 - u.laplace
 
-# The PDE representation is as on paper
-# pde
-
 stencil = Eq(u.forward, solve(pde, u.forward))
-stencil
 
 # Finally we define the source injection and receiver read function to generate
 # the corresponding code
 # print(time_range)
 
-print("Init norm:", np.linalg.norm(u.data[:]))
+# print("Init norm:", np.linalg.norm(u.data[:]))
 src_term = src.inject(field=u.forward, expr=src * dt**2 / model.m)
 op0 = Operator([stencil] + src_term, subs=model.spacing_map, name='SourceDevitoOperator')
 # Run with source and plot
 op0.apply(time=time_range.num-1, dt=model.critical_dt)
 
+
 if len(shape) == 3:
     if args.plot:
         plot_3dfunc(u)
 
-devito_norm = norm(u)
-print("Init linalg norm 0 (inlined) :", norm(u))
-print("Init linalg norm 0 :", np.linalg.norm(u.data[0]))
-print("Init linalg norm 1 :", np.linalg.norm(u.data[1]))
-print("Init linalg norm 2 :", np.linalg.norm(u.data[2]))
-print("Norm of initial data:", np.linalg.norm(u.data[:]))
+# devito_norm = norm(u)
+# print("Init linalg norm 0 (inlined) :", norm(u))
+# print("Init linalg norm 0 :", np.linalg.norm(u.data[0]))
+# print("Init linalg norm 1 :", np.linalg.norm(u.data[1]))
+# print("Init linalg norm 2 :", np.linalg.norm(u.data[2]))
+# print("Norm of initial data:", np.linalg.norm(u.data[:]))
 
 configuration['mpi'] = 0
 u2.data[:] = u.data[:]
@@ -136,36 +132,33 @@ def plot_3dfunc(u):
 op1 = Operator([stencil], name='DevitoOperator')
 op1.apply(time=time_range.num-1, dt=model.critical_dt)
 
+configuration['mpi'] = 0
+ub.data[:] = u.data[:]
+configuration['mpi'] = 'basic'
+
 if len(shape) == 3:
     if args.plot:
         plot_3dfunc(u)
 
-#devito_output = u.data[:]
-print("After Operator 1: Devito norm:", np.linalg.norm(u.data[:]))
-print("Devito linalg norm 0:", np.linalg.norm(u.data[0]))
-print("Devito linalg norm 1:", np.linalg.norm(u.data[1]))
-print("Devito linalg norm 2:", np.linalg.norm(u.data[2]))
+# print("After Operator 1: Devito norm:", np.linalg.norm(u.data[:]))
+#print("Devito norm 0:", np.linalg.norm(u.data[0]))
+#print("Devito norm 1:", np.linalg.norm(u.data[1]))
+#print("Devito norm 2:", np.linalg.norm(u.data[2]))
 
 # Reset initial data
 configuration['mpi'] = 0
 u.data[:] = u2.data[:]
 configuration['mpi'] = 'basic'
-#v[:, ..., :] = 1
 
-print("Reinitialise data for XDSL:", np.linalg.norm(u.data[:]))
-print("Init XDSL linalg norm 0:", np.linalg.norm(u.data[0]))
-print("Init XDSL linalg norm 1:", np.linalg.norm(u.data[1]))
-print("Init XDSL linalg norm 2:", np.linalg.norm(u.data[2]))
+# print("Reinitialise data for XDSL:", np.linalg.norm(u.data[:]))
+# print("Init XDSL linalg norm 0:", np.linalg.norm(u.data[0]))
+# print("Init XDSL linalg norm 1:", np.linalg.norm(u.data[1]))
+# print("Init XDSL linalg norm 2:", np.linalg.norm(u.data[2]))
 
 # Run more with no sources now (Not supported in xdsl)
-xdslop = Operator([stencil], name='Operator')
+xdslop = XDSLOperator([stencil], name='XDSLOperator')
 xdslop.apply(time=time_range.num-1, dt=model.critical_dt)
 
-xdsl_output = u.copy()
-
-print("XDSL norm:", norm(u))
-print(f"xdsl output norm: {norm(xdsl_output)}")
-print("XDSL output linalg norm 0:", np.linalg.norm(u.data[0]))
-print("XDSL output linalg norm 1:", np.linalg.norm(u.data[1]))
-print("XDSL output linalg norm 2:", np.linalg.norm(u.data[2]))
-print("devito-norm:", devito_norm)
+print("XDSL output norm 0:", np.linalg.norm(u.data[0]), "vs:", np.linalg.norm(ub.data[0]))
+print("XDSL output norm 1:", np.linalg.norm(u.data[1]), "vs:", np.linalg.norm(ub.data[1]))
+print("XDSL output norm 2:", np.linalg.norm(u.data[2]), "vs:", np.linalg.norm(ub.data[2]))