def monolithic_solve():
"""Monolithic (interleaved) solver"""
P2_el = ufl.VectorElement("Lagrange", mesh.ufl_cell(), 2)
P1_el = ufl.FiniteElement("Lagrange", mesh.ufl_cell(), 1)
TH = P2_el * P1_el
W = dolfinx.FunctionSpace(mesh, TH)
(u, p) = ufl.TrialFunctions(W)
(v, q) = ufl.TestFunctions(W)
a00 = ufl.inner(ufl.grad(u), ufl.grad(v)) * dx
a01 = ufl.inner(p, ufl.div(v)) * dx
a10 = ufl.inner(ufl.div(u), q) * dx
a = a00 + a01 + a10
p00 = ufl.inner(ufl.grad(u), ufl.grad(v)) * dx
p11 = ufl.inner(p, q) * dx
p_form = p00 + p11
f = dolfinx.Function(W.sub(0).collapse())
p_zero = dolfinx.Function(W.sub(1).collapse())
L0 = inner(f, v) * dx
L1 = inner(p_zero, q) * dx
L = L0 + L1
bdofsW0_P2_0 = dolfinx.fem.locate_dofs_topological(
(W.sub(0), P2), facetdim, bndry_facets0)
bdofsW0_P2_1 = dolfinx.fem.locate_dofs_topological(
(W.sub(0), P2), facetdim, bndry_facets1)
bc0 = dolfinx.DirichletBC(u0, bdofsW0_P2_0, W.sub(0))
bc1 = dolfinx.DirichletBC(u0, bdofsW0_P2_1, W.sub(0))
A = dolfinx.fem.assemble_matrix(a, [bc0, bc1])
A.assemble()
P = dolfinx.fem.assemble_matrix(p_form, [bc0, bc1])
P.assemble()
b = dolfinx.fem.assemble_vector(L)
dolfinx.fem.apply_lifting(b, [a], [[bc0, bc1]])
b.ghostUpdate(addv=PETSc.InsertMode.ADD,
mode=PETSc.ScatterMode.REVERSE)
dolfinx.fem.set_bc(b, [bc0, bc1])
ksp = PETSc.KSP()
ksp.create(mesh.mpi_comm())
ksp.setOperators(A, P)
ksp.setType("minres")
pc = ksp.getPC()
pc.setType('lu')
def monitor(ksp, its, rnorm):
# print("Num it, rnorm:", its, rnorm)
pass
ksp.setTolerances(rtol=1.0e-8, max_it=50)
ksp.setMonitor(monitor)
ksp.setFromOptions()
x = A.createVecRight()
ksp.solve(b, x)
assert ksp.getConvergedReason() > 0
return b.norm(), x.norm(), A.norm(), P.norm()
def test_overlapping_bcs():
"""Test that, when boundaries condition overlap, the last provided
boundary condition is applied.
"""
n = 23
mesh = dolfinx.generation.UnitSquareMesh(MPI.COMM_WORLD, n, n)
V = dolfinx.fem.FunctionSpace(mesh, ("Lagrange", 1))
u, v = ufl.TrialFunction(V), ufl.TestFunction(V)
a = inner(u, v) * dx
L = inner(1, v) * dx
dofs_left = dolfinx.fem.locate_dofs_geometrical(
V, lambda x: x[0] < 1.0 / (2.0 * n))
dofs_top = dolfinx.fem.locate_dofs_geometrical(
V, lambda x: x[1] > 1.0 - 1.0 / (2.0 * n))
dof_corner = np.array(list(set(dofs_left).intersection(set(dofs_top))),
dtype=np.int64)
# Check only one dof pair is found globally
assert len(set(np.concatenate(MPI.COMM_WORLD.allgather(dof_corner)))) == 1
u0, u1 = dolfinx.Function(V), dolfinx.Function(V)
with u0.vector.localForm() as u0_loc:
u0_loc.set(0)
with u1.vector.localForm() as u1_loc:
u1_loc.set(123.456)
bcs = [
dolfinx.DirichletBC(u0, dofs_left),
dolfinx.DirichletBC(u1, dofs_top)
]
A, b = dolfinx.fem.create_matrix(a), dolfinx.fem.create_vector(L)
dolfinx.fem.assemble_matrix(A, a, bcs=bcs)
A.assemble()
# Check the diagonal (only on the rank that owns the row)
d = A.getDiagonal()
if len(dof_corner) > 0 and dof_corner[0] < V.dofmap.index_map.size_local:
d.array_r[dof_corner[0]] == 1.0
with b.localForm() as b_loc:
b_loc.set(0)
dolfinx.fem.assemble_vector(b, L)
dolfinx.fem.apply_lifting(b, [a], [bcs])
b.ghostUpdate(addv=PETSc.InsertMode.ADD, mode=PETSc.ScatterMode.REVERSE)
dolfinx.fem.set_bc(b, bcs)
b.ghostUpdate(addv=PETSc.InsertMode.INSERT, mode=PETSc.ScatterMode.FORWARD)
if len(dof_corner) > 0:
with b.localForm() as b_loc:
print(b_loc[dof_corner[0]])
assert b_loc[dof_corner[0]] == 123.456
def test_assemble_manifold():
"""Test assembly of poisson problem on a mesh with topological dimension 1
but embedded in 2D (gdim=2).
"""
points = numpy.array([[0.0, 0.0], [0.2, 0.0], [0.4, 0.0], [0.6, 0.0],
[0.8, 0.0], [1.0, 0.0]],
dtype=numpy.float64)
cells = numpy.array([[0, 1], [1, 2], [2, 3], [3, 4], [4, 5]],
dtype=numpy.int32)
cell = ufl.Cell("interval", geometric_dimension=points.shape[1])
domain = ufl.Mesh(ufl.VectorElement("Lagrange", cell, 1))
mesh = create_mesh(MPI.COMM_WORLD, cells, points, domain)
assert mesh.geometry.dim == 2
assert mesh.topology.dim == 1
U = dolfinx.FunctionSpace(mesh, ("P", 1))
u, v = ufl.TrialFunction(U), ufl.TestFunction(U)
w = dolfinx.Function(U)
a = ufl.inner(ufl.grad(u), ufl.grad(v)) * ufl.dx(mesh)
L = ufl.inner(1.0, v) * ufl.dx(mesh)
bcdofs = dolfinx.fem.locate_dofs_geometrical(
U, lambda x: numpy.isclose(x[0], 0.0))
bcs = [dolfinx.DirichletBC(w, bcdofs)]
A = dolfinx.fem.assemble_matrix(a, bcs)
A.assemble()
b = dolfinx.fem.assemble_vector(L)
dolfinx.fem.apply_lifting(b, [a], [bcs])
dolfinx.fem.set_bc(b, bcs)
assert numpy.isclose(b.norm(), 0.41231)
assert numpy.isclose(A.norm(), 25.0199)
def test_assemble_manifold():
"""Test assembly of poisson problem on a mesh with topological dimension 1
but embedded in 2D (gdim=2).
"""
points = numpy.array([[0.0, 0.0], [0.2, 0.0], [0.4, 0.0], [0.6, 0.0],
[0.8, 0.0], [1.0, 0.0]],
dtype=numpy.float64)
cells = numpy.array([[0, 1], [1, 2], [2, 3], [3, 4], [4, 5]],
dtype=numpy.int32)
mesh = dolfinx.Mesh(dolfinx.MPI.comm_world,
dolfinx.cpp.mesh.CellType.interval, points, cells, [],
dolfinx.cpp.mesh.GhostMode.none)
mesh.geometry.coord_mapping = dolfinx.fem.create_coordinate_map(mesh)
assert mesh.geometry.dim == 2
assert mesh.topology.dim == 1
U = dolfinx.FunctionSpace(mesh, ("P", 1))
u, v = ufl.TrialFunction(U), ufl.TestFunction(U)
w = dolfinx.Function(U)
a = ufl.inner(ufl.grad(u), ufl.grad(v)) * ufl.dx(mesh)
L = ufl.inner(1.0, v) * ufl.dx(mesh)
bcdofs = dolfinx.fem.locate_dofs_geometrical(
U, lambda x: numpy.isclose(x[0], 0.0))
bcs = [dolfinx.DirichletBC(w, bcdofs)]
A = dolfinx.fem.assemble_matrix(a, bcs)
A.assemble()
b = dolfinx.fem.assemble_vector(L)
dolfinx.fem.apply_lifting(b, [a], [bcs])
dolfinx.fem.set_bc(b, bcs)
assert numpy.isclose(b.norm(), 0.41231)
assert numpy.isclose(A.norm(), 25.0199)
def test_assembly_solve_taylor_hood(mesh):
"""Assemble Stokes problem with Taylor-Hood elements and solve."""
P2 = fem.VectorFunctionSpace(mesh, ("Lagrange", 2))
P1 = fem.FunctionSpace(mesh, ("Lagrange", 1))
def boundary0(x):
"""Define boundary x = 0"""
return x[0] < 10 * numpy.finfo(float).eps
def boundary1(x):
"""Define boundary x = 1"""
return x[0] > (1.0 - 10 * numpy.finfo(float).eps)
# Locate facets on boundaries
facetdim = mesh.topology.dim - 1
bndry_facets0 = dolfinx.mesh.locate_entities_boundary(
mesh, facetdim, boundary0)
bndry_facets1 = dolfinx.mesh.locate_entities_boundary(
mesh, facetdim, boundary1)
bdofs0 = dolfinx.fem.locate_dofs_topological(P2, facetdim, bndry_facets0)
bdofs1 = dolfinx.fem.locate_dofs_topological(P2, facetdim, bndry_facets1)
u0 = dolfinx.Function(P2)
u0.vector.set(1.0)
u0.vector.ghostUpdate(addv=PETSc.InsertMode.INSERT,
mode=PETSc.ScatterMode.FORWARD)
bc0 = dolfinx.DirichletBC(u0, bdofs0)
bc1 = dolfinx.DirichletBC(u0, bdofs1)
u, p = ufl.TrialFunction(P2), ufl.TrialFunction(P1)
v, q = ufl.TestFunction(P2), ufl.TestFunction(P1)
a00 = inner(ufl.grad(u), ufl.grad(v)) * dx
a01 = ufl.inner(p, ufl.div(v)) * dx
a10 = ufl.inner(ufl.div(u), q) * dx
a11 = None
p00 = a00
p01, p10 = None, None
p11 = inner(p, q) * dx
# FIXME
# We need zero function for the 'zero' part of L
p_zero = dolfinx.Function(P1)
f = dolfinx.Function(P2)
L0 = ufl.inner(f, v) * dx
L1 = ufl.inner(p_zero, q) * dx
def nested_solve():
"""Nested solver"""
A = dolfinx.fem.assemble_matrix_nest([[a00, a01], [a10, a11]],
[bc0, bc1],
[["baij", "aij"], ["aij", ""]])
A.assemble()
P = dolfinx.fem.assemble_matrix_nest([[p00, p01], [p10, p11]],
[bc0, bc1],
[["aij", "aij"], ["aij", ""]])
P.assemble()
b = dolfinx.fem.assemble_vector_nest([L0, L1])
dolfinx.fem.apply_lifting_nest(b, [[a00, a01], [a10, a11]], [bc0, bc1])
for b_sub in b.getNestSubVecs():
b_sub.ghostUpdate(addv=PETSc.InsertMode.ADD,
mode=PETSc.ScatterMode.REVERSE)
bcs = dolfinx.cpp.fem.bcs_rows(
dolfinx.fem.assemble._create_cpp_form([L0, L1]), [bc0, bc1])
dolfinx.fem.set_bc_nest(b, bcs)
b.assemble()
ksp = PETSc.KSP()
ksp.create(mesh.mpi_comm())
ksp.setOperators(A, P)
nested_IS = P.getNestISs()
ksp.setType("minres")
pc = ksp.getPC()
pc.setType("fieldsplit")
pc.setFieldSplitIS(["u", nested_IS[0][0]], ["p", nested_IS[1][1]])
ksp_u, ksp_p = pc.getFieldSplitSubKSP()
ksp_u.setType("preonly")
ksp_u.getPC().setType('lu')
ksp_p.setType("preonly")
def monitor(ksp, its, rnorm):
# print("Num it, rnorm:", its, rnorm)
pass
ksp.setTolerances(rtol=1.0e-8, max_it=50)
ksp.setMonitor(monitor)
ksp.setFromOptions()
x = b.copy()
ksp.solve(b, x)
assert ksp.getConvergedReason() > 0
return b.norm(), x.norm(), nest_matrix_norm(A), nest_matrix_norm(P)
def blocked_solve():
"""Blocked (monolithic) solver"""
A = dolfinx.fem.assemble_matrix_block([[a00, a01], [a10, a11]],
[bc0, bc1])
A.assemble()
P = dolfinx.fem.assemble_matrix_block([[p00, p01], [p10, p11]],
[bc0, bc1])
P.assemble()
b = dolfinx.fem.assemble_vector_block([L0, L1],
[[a00, a01], [a10, a11]],
[bc0, bc1])
ksp = PETSc.KSP()
ksp.create(mesh.mpi_comm())
ksp.setOperators(A, P)
ksp.setType("minres")
pc = ksp.getPC()
pc.setType('lu')
ksp.setTolerances(rtol=1.0e-8, max_it=50)
ksp.setFromOptions()
x = A.createVecRight()
ksp.solve(b, x)
assert ksp.getConvergedReason() > 0
return b.norm(), x.norm(), A.norm(), P.norm()
def monolithic_solve():
"""Monolithic (interleaved) solver"""
P2_el = ufl.VectorElement("Lagrange", mesh.ufl_cell(), 2)
P1_el = ufl.FiniteElement("Lagrange", mesh.ufl_cell(), 1)
TH = P2_el * P1_el
W = dolfinx.FunctionSpace(mesh, TH)
(u, p) = ufl.TrialFunctions(W)
(v, q) = ufl.TestFunctions(W)
a00 = ufl.inner(ufl.grad(u), ufl.grad(v)) * dx
a01 = ufl.inner(p, ufl.div(v)) * dx
a10 = ufl.inner(ufl.div(u), q) * dx
a = a00 + a01 + a10
p00 = ufl.inner(ufl.grad(u), ufl.grad(v)) * dx
p11 = ufl.inner(p, q) * dx
p_form = p00 + p11
f = dolfinx.Function(W.sub(0).collapse())
p_zero = dolfinx.Function(W.sub(1).collapse())
L0 = inner(f, v) * dx
L1 = inner(p_zero, q) * dx
L = L0 + L1
bdofsW0_P2_0 = dolfinx.fem.locate_dofs_topological(
(W.sub(0), P2), facetdim, bndry_facets0)
bdofsW0_P2_1 = dolfinx.fem.locate_dofs_topological(
(W.sub(0), P2), facetdim, bndry_facets1)
bc0 = dolfinx.DirichletBC(u0, bdofsW0_P2_0, W.sub(0))
bc1 = dolfinx.DirichletBC(u0, bdofsW0_P2_1, W.sub(0))
A = dolfinx.fem.assemble_matrix(a, [bc0, bc1])
A.assemble()
P = dolfinx.fem.assemble_matrix(p_form, [bc0, bc1])
P.assemble()
b = dolfinx.fem.assemble_vector(L)
dolfinx.fem.apply_lifting(b, [a], [[bc0, bc1]])
b.ghostUpdate(addv=PETSc.InsertMode.ADD,
mode=PETSc.ScatterMode.REVERSE)
dolfinx.fem.set_bc(b, [bc0, bc1])
ksp = PETSc.KSP()
ksp.create(mesh.mpi_comm())
ksp.setOperators(A, P)
ksp.setType("minres")
pc = ksp.getPC()
pc.setType('lu')
def monitor(ksp, its, rnorm):
# print("Num it, rnorm:", its, rnorm)
pass
ksp.setTolerances(rtol=1.0e-8, max_it=50)
ksp.setMonitor(monitor)
ksp.setFromOptions()
x = A.createVecRight()
ksp.solve(b, x)
assert ksp.getConvergedReason() > 0
return b.norm(), x.norm(), A.norm(), P.norm()
bnorm0, xnorm0, Anorm0, Pnorm0 = nested_solve()
bnorm1, xnorm1, Anorm1, Pnorm1 = blocked_solve()
bnorm2, xnorm2, Anorm2, Pnorm2 = monolithic_solve()
assert bnorm1 == pytest.approx(bnorm0, 1.0e-12)
assert xnorm1 == pytest.approx(xnorm0, 1.0e-8)
assert Anorm1 == pytest.approx(Anorm0, 1.0e-12)
assert Pnorm1 == pytest.approx(Pnorm0, 1.0e-12)
assert bnorm2 == pytest.approx(bnorm0, 1.0e-12)
assert xnorm2 == pytest.approx(xnorm0, 1.0e-8)
assert Anorm2 == pytest.approx(Anorm0, 1.0e-12)
assert Pnorm2 == pytest.approx(Pnorm0, 1.0e-12)
def test_assembly_solve_taylor_hood(mesh):
"""Assemble Stokes problem with Taylor-Hood elements and solve."""
gdim = mesh.geometry.dim
P2 = dolfinx.function.VectorFunctionSpace(mesh, ("Lagrange", 2))
P1 = dolfinx.function.FunctionSpace(mesh, ("Lagrange", 1))
def boundary0(x):
"""Define boundary x = 0"""
return x[0] < 10 * numpy.finfo(float).eps
def boundary1(x):
"""Define boundary x = 1"""
return x[0] > (1.0 - 10 * numpy.finfo(float).eps)
def initial_guess_u(x):
u_init = numpy.row_stack((numpy.sin(x[0]) * numpy.sin(x[1]),
numpy.cos(x[0]) * numpy.cos(x[1])))
if gdim == 3:
u_init = numpy.row_stack((u_init, numpy.cos(x[2])))
return u_init
def initial_guess_p(x):
return -x[0]**2 - x[1]**3
u_bc_0 = dolfinx.Function(P2)
u_bc_0.interpolate(
lambda x: numpy.row_stack(tuple(x[j] + float(j) for j in range(gdim))))
u_bc_1 = dolfinx.Function(P2)
u_bc_1.interpolate(
lambda x: numpy.row_stack(tuple(numpy.sin(x[j]) for j in range(gdim))))
facetdim = mesh.topology.dim - 1
mf = dolfinx.MeshFunction("size_t", mesh, facetdim, 0)
mf.mark(boundary0, 1)
mf.mark(boundary1, 2)
bndry_facets0 = numpy.where(mf.values == 1)[0]
bndry_facets1 = numpy.where(mf.values == 2)[0]
bdofs0 = dolfinx.fem.locate_dofs_topological(P2, facetdim, bndry_facets0)
bdofs1 = dolfinx.fem.locate_dofs_topological(P2, facetdim, bndry_facets1)
bcs = [
dolfinx.DirichletBC(u_bc_0, bdofs0),
dolfinx.DirichletBC(u_bc_1, bdofs1)
]
u, p = dolfinx.Function(P2), dolfinx.Function(P1)
du, dp = ufl.TrialFunction(P2), ufl.TrialFunction(P1)
v, q = ufl.TestFunction(P2), ufl.TestFunction(P1)
F = [
inner(ufl.grad(u), ufl.grad(v)) * dx + inner(p, ufl.div(v)) * dx,
inner(ufl.div(u), q) * dx
]
J = [[derivative(F[0], u, du),
derivative(F[0], p, dp)],
[derivative(F[1], u, du),
derivative(F[1], p, dp)]]
P = [[J[0][0], None], [None, inner(dp, q) * dx]]
# -- Blocked and monolithic
Jmat0 = dolfinx.fem.create_matrix_block(J)
Pmat0 = dolfinx.fem.create_matrix_block(P)
Fvec0 = dolfinx.fem.create_vector_block(F)
snes = PETSc.SNES().create(dolfinx.MPI.comm_world)
snes.setTolerances(rtol=1.0e-15, max_it=10)
snes.getKSP().setType("minres")
snes.getKSP().getPC().setType("lu")
snes.getKSP().getPC().setFactorSolverType("mumps")
problem = NonlinearPDE_SNESProblem(F, J, [u, p], bcs, P=P)
snes.setFunction(problem.F_block, Fvec0)
snes.setJacobian(problem.J_block, J=Jmat0, P=Pmat0)
u.interpolate(initial_guess_u)
p.interpolate(initial_guess_p)
x0 = dolfinx.fem.create_vector_block(F)
with u.vector.localForm() as _u, p.vector.localForm() as _p:
dolfinx.cpp.la.scatter_local_vectors(x0, [_u.array_r, _p.array_r], [
u.function_space.dofmap.index_map,
p.function_space.dofmap.index_map
])
x0.ghostUpdate(addv=PETSc.InsertMode.INSERT,
mode=PETSc.ScatterMode.FORWARD)
snes.solve(None, x0)
assert snes.getConvergedReason() > 0
# -- Blocked and nested
Jmat1 = dolfinx.fem.create_matrix_nest(J)
Pmat1 = dolfinx.fem.create_matrix_nest(P)
Fvec1 = dolfinx.fem.create_vector_nest(F)
snes = PETSc.SNES().create(dolfinx.MPI.comm_world)
snes.setTolerances(rtol=1.0e-15, max_it=10)
nested_IS = Jmat1.getNestISs()
snes.getKSP().setType("minres")
snes.getKSP().setTolerances(rtol=1e-12)
snes.getKSP().getPC().setType("fieldsplit")
snes.getKSP().getPC().setFieldSplitIS(["u", nested_IS[0][0]],
["p", nested_IS[1][1]])
ksp_u, ksp_p = snes.getKSP().getPC().getFieldSplitSubKSP()
ksp_u.setType("preonly")
ksp_u.getPC().setType('lu')
ksp_u.getPC().setFactorSolverType('mumps')
ksp_p.setType("preonly")
ksp_p.getPC().setType('lu')
ksp_p.getPC().setFactorSolverType('mumps')
problem = NonlinearPDE_SNESProblem(F, J, [u, p], bcs, P=P)
snes.setFunction(problem.F_nest, Fvec1)
snes.setJacobian(problem.J_nest, J=Jmat1, P=Pmat1)
u.interpolate(initial_guess_u)
p.interpolate(initial_guess_p)
x1 = dolfinx.fem.create_vector_nest(F)
for x1_soln_pair in zip(x1.getNestSubVecs(), (u, p)):
x1_sub, soln_sub = x1_soln_pair
soln_sub.vector.ghostUpdate(addv=PETSc.InsertMode.INSERT,
mode=PETSc.ScatterMode.FORWARD)
soln_sub.vector.copy(result=x1_sub)
x1_sub.ghostUpdate(addv=PETSc.InsertMode.INSERT,
mode=PETSc.ScatterMode.FORWARD)
x1.set(0.0)
snes.solve(None, x1)
assert snes.getConvergedReason() > 0
assert nest_matrix_norm(Jmat1) == pytest.approx(Jmat0.norm(), 1.0e-12)
assert Fvec1.norm() == pytest.approx(Fvec0.norm(), 1.0e-12)
assert x1.norm() == pytest.approx(x0.norm(), 1.0e-12)
# -- Monolithic
P2_el = ufl.VectorElement("Lagrange", mesh.ufl_cell(), 2)
P1_el = ufl.FiniteElement("Lagrange", mesh.ufl_cell(), 1)
TH = P2_el * P1_el
W = dolfinx.FunctionSpace(mesh, TH)
U = dolfinx.Function(W)
dU = ufl.TrialFunction(W)
u, p = ufl.split(U)
du, dp = ufl.split(dU)
v, q = ufl.TestFunctions(W)
F = inner(ufl.grad(u), ufl.grad(v)) * dx + inner(p, ufl.div(v)) * dx \
+ inner(ufl.div(u), q) * dx
J = derivative(F, U, dU)
P = inner(ufl.grad(du), ufl.grad(v)) * dx + inner(dp, q) * dx
bdofsW0_P2_0 = dolfinx.fem.locate_dofs_topological((W.sub(0), P2),
facetdim, bndry_facets0)
bdofsW0_P2_1 = dolfinx.fem.locate_dofs_topological((W.sub(0), P2),
facetdim, bndry_facets1)
bcs = [
dolfinx.DirichletBC(u_bc_0, bdofsW0_P2_0, W.sub(0)),
dolfinx.DirichletBC(u_bc_1, bdofsW0_P2_1, W.sub(0))
]
Jmat2 = dolfinx.fem.create_matrix(J)
Pmat2 = dolfinx.fem.create_matrix(P)
Fvec2 = dolfinx.fem.create_vector(F)
snes = PETSc.SNES().create(dolfinx.MPI.comm_world)
snes.setTolerances(rtol=1.0e-15, max_it=10)
snes.getKSP().setType("minres")
snes.getKSP().getPC().setType("lu")
snes.getKSP().getPC().setFactorSolverType("mumps")
problem = NonlinearPDE_SNESProblem(F, J, U, bcs, P=P)
snes.setFunction(problem.F_mono, Fvec2)
snes.setJacobian(problem.J_mono, J=Jmat2, P=Pmat2)
U.interpolate(lambda x: numpy.row_stack(
(initial_guess_u(x), initial_guess_p(x))))
x2 = dolfinx.fem.create_vector(F)
x2.array = U.vector.array_r
snes.solve(None, x2)
assert snes.getConvergedReason() > 0
assert Jmat2.norm() == pytest.approx(Jmat0.norm(), 1.0e-12)
assert Fvec2.norm() == pytest.approx(Fvec0.norm(), 1.0e-12)
assert x2.norm() == pytest.approx(x0.norm(), 1.0e-12)
def test_assembly_solve_taylor_hood(mesh):
"""Assemble Stokes problem with Taylor-Hood elements and solve."""
P2 = function.VectorFunctionSpace(mesh, ("Lagrange", 2))
P1 = function.FunctionSpace(mesh, ("Lagrange", 1))
def boundary0(x):
"""Define boundary x = 0"""
return x[0] < 10 * numpy.finfo(float).eps
def boundary1(x):
"""Define boundary x = 1"""
return x[0] > (1.0 - 10 * numpy.finfo(float).eps)
facetdim = mesh.topology.dim - 1
mf = dolfinx.MeshFunction("size_t", mesh, facetdim, 0)
mf.mark(boundary0, 1)
mf.mark(boundary1, 2)
bndry_facets0 = numpy.where(mf.values == 1)[0]
bndry_facets1 = numpy.where(mf.values == 2)[0]
bdofs0 = dolfinx.fem.locate_dofs_topological(P2, facetdim, bndry_facets0)
bdofs1 = dolfinx.fem.locate_dofs_topological(P2, facetdim, bndry_facets1)
u0 = dolfinx.Function(P2)
u0.vector.set(1.0)
u0.vector.ghostUpdate(addv=PETSc.InsertMode.INSERT,
mode=PETSc.ScatterMode.FORWARD)
bc0 = dolfinx.DirichletBC(u0, bdofs0)
bc1 = dolfinx.DirichletBC(u0, bdofs1)
u, p = ufl.TrialFunction(P2), ufl.TrialFunction(P1)
v, q = ufl.TestFunction(P2), ufl.TestFunction(P1)
a00 = inner(ufl.grad(u), ufl.grad(v)) * dx
a01 = ufl.inner(p, ufl.div(v)) * dx
a10 = ufl.inner(ufl.div(u), q) * dx
a11 = None
p00 = a00
p01, p10 = None, None
p11 = inner(p, q) * dx
# FIXME
# We need zero function for the 'zero' part of L
p_zero = dolfinx.Function(P1)
f = dolfinx.Function(P2)
L0 = ufl.inner(f, v) * dx
L1 = ufl.inner(p_zero, q) * dx
# -- Blocked (nested)
A0 = dolfinx.fem.assemble_matrix_nest([[a00, a01], [a10, a11]], [bc0, bc1])
A0.assemble()
A0norm = nest_matrix_norm(A0)
P0 = dolfinx.fem.assemble_matrix_nest([[p00, p01], [p10, p11]], [bc0, bc1])
P0.assemble()
P0norm = nest_matrix_norm(P0)
b0 = dolfinx.fem.assemble_vector_nest([L0, L1])
dolfinx.fem.apply_lifting_nest(b0, [[a00, a01], [a10, a11]], [bc0, bc1])
for b_sub in b0.getNestSubVecs():
b_sub.ghostUpdate(addv=PETSc.InsertMode.ADD,
mode=PETSc.ScatterMode.REVERSE)
bcs0 = dolfinx.cpp.fem.bcs_rows(
dolfinx.fem.assemble._create_cpp_form([L0, L1]), [bc0, bc1])
dolfinx.fem.set_bc_nest(b0, bcs0)
b0.assemble()
b0norm = b0.norm()
ksp = PETSc.KSP()
ksp.create(mesh.mpi_comm())
ksp.setOperators(A0, P0)
nested_IS = P0.getNestISs()
ksp.setType("minres")
pc = ksp.getPC()
pc.setType("fieldsplit")
pc.setFieldSplitIS(["u", nested_IS[0][0]], ["p", nested_IS[1][1]])
ksp_u, ksp_p = pc.getFieldSplitSubKSP()
ksp_u.setType("preonly")
ksp_u.getPC().setType('lu')
ksp_u.getPC().setFactorSolverType('mumps')
ksp_p.setType("preonly")
def monitor(ksp, its, rnorm):
# print("Num it, rnorm:", its, rnorm)
pass
ksp.setTolerances(rtol=1.0e-8, max_it=50)
ksp.setMonitor(monitor)
ksp.setFromOptions()
x0 = b0.copy()
ksp.solve(b0, x0)
assert ksp.getConvergedReason() > 0
# -- Blocked (monolithic)
A1 = dolfinx.fem.assemble_matrix_block([[a00, a01], [a10, a11]],
[bc0, bc1])
A1.assemble()
assert A1.norm() == pytest.approx(A0norm, 1.0e-12)
P1 = dolfinx.fem.assemble_matrix_block([[p00, p01], [p10, p11]],
[bc0, bc1])
P1.assemble()
assert P1.norm() == pytest.approx(P0norm, 1.0e-12)
b1 = dolfinx.fem.assemble_vector_block([L0, L1], [[a00, a01], [a10, a11]],
[bc0, bc1])
assert b1.norm() == pytest.approx(b0norm, 1.0e-12)
ksp = PETSc.KSP()
ksp.create(mesh.mpi_comm())
ksp.setOperators(A1, P1)
ksp.setType("minres")
pc = ksp.getPC()
pc.setType('lu')
pc.setFactorSolverType('mumps')
ksp.setTolerances(rtol=1.0e-8, max_it=50)
ksp.setFromOptions()
x1 = A1.createVecRight()
ksp.solve(b1, x1)
assert ksp.getConvergedReason() > 0
assert x1.norm() == pytest.approx(x0.norm(), 1e-8)
# -- Monolithic
P2_el = ufl.VectorElement("Lagrange", mesh.ufl_cell(), 2)
P1_el = ufl.FiniteElement("Lagrange", mesh.ufl_cell(), 1)
TH = P2_el * P1_el
W = dolfinx.FunctionSpace(mesh, TH)
(u, p) = ufl.TrialFunctions(W)
(v, q) = ufl.TestFunctions(W)
a00 = ufl.inner(ufl.grad(u), ufl.grad(v)) * dx
a01 = ufl.inner(p, ufl.div(v)) * dx
a10 = ufl.inner(ufl.div(u), q) * dx
a = a00 + a01 + a10
p00 = ufl.inner(ufl.grad(u), ufl.grad(v)) * dx
p11 = ufl.inner(p, q) * dx
p_form = p00 + p11
f = dolfinx.Function(W.sub(0).collapse())
p_zero = dolfinx.Function(W.sub(1).collapse())
L0 = inner(f, v) * dx
L1 = inner(p_zero, q) * dx
L = L0 + L1
bdofsW0_P2_0 = dolfinx.fem.locate_dofs_topological((W.sub(0), P2),
facetdim, bndry_facets0)
bdofsW0_P2_1 = dolfinx.fem.locate_dofs_topological((W.sub(0), P2),
facetdim, bndry_facets1)
bc0 = dolfinx.DirichletBC(u0, bdofsW0_P2_0, W.sub(0))
bc1 = dolfinx.DirichletBC(u0, bdofsW0_P2_1, W.sub(0))
A2 = dolfinx.fem.assemble_matrix(a, [bc0, bc1])
A2.assemble()
assert A2.norm() == pytest.approx(A0norm, 1.0e-12)
P2 = dolfinx.fem.assemble_matrix(p_form, [bc0, bc1])
P2.assemble()
assert P2.norm() == pytest.approx(P0norm, 1.0e-12)
b2 = dolfinx.fem.assemble_vector(L)
dolfinx.fem.apply_lifting(b2, [a], [[bc0, bc1]])
b2.ghostUpdate(addv=PETSc.InsertMode.ADD, mode=PETSc.ScatterMode.REVERSE)
dolfinx.fem.set_bc(b2, [bc0, bc1])
b2norm = b2.norm()
assert b2norm == pytest.approx(b0norm, 1.0e-12)
ksp = PETSc.KSP()
ksp.create(mesh.mpi_comm())
ksp.setOperators(A2, P2)
ksp.setType("minres")
pc = ksp.getPC()
pc.setType('lu')
pc.setFactorSolverType('mumps')
def monitor(ksp, its, rnorm):
# print("Num it, rnorm:", its, rnorm)
pass
ksp.setTolerances(rtol=1.0e-8, max_it=50)
ksp.setMonitor(monitor)
ksp.setFromOptions()
x2 = A2.createVecRight()
ksp.solve(b2, x2)
assert ksp.getConvergedReason() > 0
assert x0.norm() == pytest.approx(x2.norm(), 1e-8)
mesh_fine.topology.create_connectivity(fdim_fine, mesh_fine.topology.dim)
mesh_coarse.topology.create_connectivity(fdim_coarse, mesh_coarse.topology.dim)
boundary_facets_fine = np.where(
np.array(dolfinx.cpp.mesh.compute_boundary_facets(mesh_fine.topology)) ==
1)[0]
boundary_facets_coarse = np.where(
np.array(dolfinx.cpp.mesh.compute_boundary_facets(mesh_coarse.topology)) ==
1)[0]
boundary_dofs_fine = dolfinx.fem.locate_dofs_topological(
V_fine, fdim_fine, boundary_facets_fine)
boundary_dofs_coarse = dolfinx.fem.locate_dofs_topological(
V_coarse, fdim_coarse, boundary_facets_coarse)
bc_fine = dolfinx.DirichletBC(u_fine, boundary_dofs_fine)
u_D_fine = ufl.TrialFunction(V_fine)
v_D_fine = ufl.TestFunction(V_fine)
f_fine = dolfinx.Constant(mesh_fine, -6)
a_fine = ufl.dot(ufl.grad(u_D_fine), ufl.grad(v_D_fine)) * ufl.dx
#A_fine = dolfinx.fem.assemble_matrix(a_fine, bcs=[bc_fine])
# A_fine.assemble()
bc_coarse = dolfinx.DirichletBC(u_coarse, boundary_dofs_coarse)
u_D_coarse = ufl.TrialFunction(V_coarse)
v_D_coarse = ufl.TestFunction(V_coarse)
f_coarse = dolfinx.Constant(mesh_coarse, -6)
a_coarse = ufl.dot(ufl.grad(u_D_coarse), ufl.grad(v_D_coarse)) * ufl.dx
#A_coarse = dolfinx.fem.assemble_matrix(a_coarse, bcs=[bc_coarse])
# A_coarse.assemble()
"""ai1, aj1, av1 = A_fine.getValuesCSR()
dof_dict_i[cord_tup] = j
mesh_dof_list_dict[i] = dof_dict_i # Stores the dofs at a level in dict
del dof_dict_i
uD_i = dolfinx.Function(V_i)
uD_i.interpolate(lambda x: 1 + x[0]**2 + 2 * x[1]**2)
uD_i.vector.ghostUpdate(addv=PETSc.InsertMode.INSERT,
mode=PETSc.ScatterMode.FORWARD)
fdim_i = mesh_i.topology.dim - 1
mesh_i.topology.create_connectivity(fdim_i, mesh_i.topology.dim)
boundary_facets_i = np.where(
np.array(dolfinx.cpp.mesh.compute_boundary_facets(mesh_i.topology)) ==
1)[0]
boundary_dofs_i = dolfinx.fem.locate_dofs_topological(
V_i, fdim_i, boundary_facets_i)
bc_i = dolfinx.DirichletBC(uD_i, boundary_dofs_i)
u_i = ufl.TrialFunction(V_i)
v_i = ufl.TestFunction(V_i)
f_i = dolfinx.Constant(mesh_i, -6)
a_i = ufl.dot(ufl.grad(u_i), ufl.grad(v_i)) * ufl.dx
A_i = dolfinx.fem.assemble_matrix(a_i, bcs=[bc_i])
A_i.assemble()
assert isinstance(A_i, PETSc.Mat)
ai, aj, av = A_i.getValuesCSR()
A_sp_i = scp.sparse.csr_matrix((av, aj, ai))
del A_i, av, ai, aj
# Stores the Sparse version of the Stiffness Matrices
A_sp_dict[i] = (A_sp_i, i)
L_i = f_i * v_i * ufl.dx
b_i = dolfinx.fem.create_vector(L_i)
with b_i.localForm() as loc_b:
