# Set matrix operator
solver.setOperators(A)
# Compute solution
solver.setMonitor(lambda ksp, its, rnorm: print(
"Iteration: {}, rel. residual: {}".format(its, rnorm)))
solver.solve(b, u.vector)
solver.view()
# Save solution to XDMF format
file = XDMFFile(MPI.comm_world, "elasticity.xdmf")
file.write(u)
unorm = u.vector.norm()
if MPI.rank(mesh.mpi_comm()) == 0:
print("Solution vector norm:", unorm)
# Save colored mesh partitions in VTK format if running in parallel
# if MPI.size(mesh.mpi_comm()) > 1:
# File("partitions.pvd") << MeshFunction("size_t", mesh, mesh.topology.dim, \
# MPI.rank(mesh.mpi_comm()))
# Project and write stress field to post-processing file
# W = TensorFunctionSpace(mesh, "Discontinuous Lagrange", 0)
# stress = project(sigma(u), V=W)
# File("stress.pvd") << stress
# Plot solution
# import matplotlib.pyplot as plt
# import dolfinx.plotting
# Use Chebyshev smoothing for multigrid
opts["mg_levels_ksp_type"] = "chebyshev"
opts["mg_levels_pc_type"] = "jacobi"
# Improve estimate of eigenvalues for Chebyshev smoothing
opts["mg_levels_esteig_ksp_type"] = "cg"
opts["mg_levels_ksp_chebyshev_esteig_steps"] = 20
# Create CG Krylov solver and turn convergence monitoring on
solver = PETSc.KSP().create(MPI.COMM_WORLD)
solver.setFromOptions()
# Set matrix operator
solver.setOperators(A)
# Compute solution
solver.setMonitor(lambda ksp, its, rnorm: print(
"Iteration: {}, rel. residual: {}".format(its, rnorm)))
solver.solve(b, u.vector)
solver.view()
# Save solution to XDMF format
with XDMFFile(MPI.COMM_WORLD, "elasticity.xdmf", "w") as file:
file.write_mesh(mesh)
file.write_function(u)
unorm = u.vector.norm()
if mesh.mpi_comm().rank == 0:
print("Solution vector norm:", unorm)