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# Copyright (C) 2020-2021 Jørgen S. Dokken
#
# This file is part of DOLFINX_MPC
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
from mpi4py import MPI
from petsc4py import PETSc
import dolfinx.fem as fem
import numpy as np
import numpy.testing as nt
import pytest
import scipy.sparse.linalg
import ufl
from dolfinx import default_scalar_type
from dolfinx.common import Timer, TimingType, list_timings
from dolfinx.mesh import create_unit_square, locate_entities_boundary, meshtags
import dolfinx_mpc
import dolfinx_mpc.utils
from dolfinx_mpc.utils import get_assemblers # noqa: F401
@pytest.mark.parametrize("get_assemblers", ["C++"], indirect=True)
def test_surface_integrals(get_assemblers): # noqa: F811
assemble_matrix, assemble_vector = get_assemblers
N = 4
mesh = create_unit_square(MPI.COMM_WORLD, N, N)
V = fem.functionspace(mesh, ("Lagrange", 1, (mesh.geometry.dim,)))
# Fixed Dirichlet BC on the left wall
def left_wall(x):
return np.isclose(x[0], 0, atol=100 * np.finfo(x.dtype).resolution)
fdim = mesh.topology.dim - 1
left_facets = locate_entities_boundary(mesh, fdim, left_wall)
bc_dofs = fem.locate_dofs_topological(V, 1, left_facets)
u_bc = fem.Function(V)
u_bc.x.array[:] = 0
bc = fem.dirichletbc(u_bc, bc_dofs)
bcs = [bc]
# Traction on top of domain
def top(x):
return np.isclose(x[1], 1, atol=100 * np.finfo(x.dtype).resolution)
top_facets = locate_entities_boundary(mesh, 1, top)
arg_sort = np.argsort(top_facets)
mt = meshtags(mesh, fdim, top_facets[arg_sort], np.full(len(top_facets), 3, dtype=np.int32))
ds = ufl.Measure("ds", domain=mesh, subdomain_data=mt, subdomain_id=3)
g = fem.Constant(mesh, default_scalar_type((0, -9.81e2)))
# Elasticity parameters
E = 1.0e2
nu = 0.0
mu = fem.Constant(mesh, default_scalar_type(E / (2.0 * (1.0 + nu))))
lmbda = fem.Constant(mesh, default_scalar_type(E * nu / ((1.0 + nu) * (1.0 - 2.0 * nu))))
# Stress computation
def sigma(v):
return 2.0 * mu * ufl.sym(ufl.grad(v)) + lmbda * ufl.tr(ufl.sym(ufl.grad(v))) * ufl.Identity(len(v))
# Define variational problem
u = ufl.TrialFunction(V)
v = ufl.TestFunction(V)
a = ufl.inner(sigma(u), ufl.grad(v)) * ufl.dx
rhs = ufl.inner(fem.Constant(mesh, default_scalar_type((0, 0))), v) * ufl.dx + ufl.inner(g, v) * ds
bilinear_form = fem.form(a)
linear_form = fem.form(rhs)
# Setup LU solver
solver = PETSc.KSP().create(mesh.comm)
solver.setType(PETSc.KSP.Type.PREONLY)
solver.getPC().setType(PETSc.PC.Type.LU)
# Setup multipointconstraint
def l2b(li):
return np.array(li, dtype=mesh.geometry.x.dtype).tobytes()
s_m_c = {}
for i in range(1, N):
s_m_c[l2b([1, i / N])] = {l2b([1, 1]): 0.8}
mpc = dolfinx_mpc.MultiPointConstraint(V)
mpc.create_general_constraint(s_m_c, 1, 1)
mpc.finalize()
with Timer("~TEST: Assemble matrix old"):
A = assemble_matrix(bilinear_form, mpc, bcs=bcs)
with Timer("~TEST: Assemble vector"):
b = assemble_vector(linear_form, mpc)
dolfinx_mpc.apply_lifting(b, [bilinear_form], [bcs], mpc)
b.ghostUpdate(addv=PETSc.InsertMode.ADD_VALUES, mode=PETSc.ScatterMode.REVERSE)
fem.petsc.set_bc(b, bcs)
solver.setOperators(A)
uh = fem.Function(mpc.function_space)
uh.x.array[:] = 0
solver.solve(b, uh.x.petsc_vec)
uh.x.scatter_forward()
mpc.backsubstitution(uh)
# Solve the MPC problem using a global transformation matrix
# and numpy solvers to get reference values
# Generate reference matrices and unconstrained solution
A_org = fem.petsc.assemble_matrix(bilinear_form, bcs)
A_org.assemble()
L_org = fem.petsc.assemble_vector(linear_form)
fem.petsc.apply_lifting(L_org, [bilinear_form], [bcs])
L_org.ghostUpdate(addv=PETSc.InsertMode.ADD_VALUES, mode=PETSc.ScatterMode.REVERSE)
fem.petsc.set_bc(L_org, bcs)
root = 0
comm = mesh.comm
with Timer("~TEST: Compare"):
# Gather LHS, RHS and solution on one process
is_complex = np.issubdtype(default_scalar_type, np.complexfloating) # type: ignore
scipy_dtype = np.complex128 if is_complex else np.float64
A_csr = dolfinx_mpc.utils.gather_PETScMatrix(A_org, root=root)
K = dolfinx_mpc.utils.gather_transformation_matrix(mpc, root=root)
L_np = dolfinx_mpc.utils.gather_PETScVector(L_org, root=root)
u_mpc = dolfinx_mpc.utils.gather_PETScVector(uh.x.petsc_vec, root=root)
if MPI.COMM_WORLD.rank == root:
KTAK = K.T.astype(scipy_dtype) * A_csr.astype(scipy_dtype) * K.astype(scipy_dtype)
reduced_L = K.T.astype(scipy_dtype) @ L_np.astype(scipy_dtype)
# Solve linear system
d = scipy.sparse.linalg.spsolve(KTAK, reduced_L)
# Back substitution to full solution vector
uh_numpy = K.astype(scipy_dtype) @ d
nt.assert_allclose(
uh_numpy.astype(u_mpc.dtype),
u_mpc,
rtol=500 * np.finfo(default_scalar_type).resolution,
)
L_org.destroy()
b.destroy()
A_org.destroy()
solver.destroy()
list_timings(comm, [TimingType.wall])
@pytest.mark.parametrize("get_assemblers", ["C++"], indirect=True)
def test_surface_integral_dependency(get_assemblers): # noqa: F811
assemble_matrix, assemble_vector = get_assemblers
N = 10
mesh = create_unit_square(MPI.COMM_WORLD, N, N)
V = fem.functionspace(mesh, ("Lagrange", 1, (mesh.geometry.dim,)))
def top(x):
return np.isclose(x[1], 1)
fdim = mesh.topology.dim - 1
top_facets = locate_entities_boundary(mesh, fdim, top)
indices = np.array([], dtype=np.intc)
values = np.array([], dtype=np.intc)
markers = {3: top_facets}
for key in markers.keys():
indices = np.append(indices, markers[key])
values = np.append(values, np.full(len(markers[key]), key, dtype=np.intc))
sort = np.argsort(indices)
mt = meshtags(
mesh,
mesh.topology.dim - 1,
np.array(indices[sort], dtype=np.intc),
np.array(values[sort], dtype=np.intc),
)
ds = ufl.Measure("ds", domain=mesh, subdomain_data=mt)
g = fem.Constant(mesh, default_scalar_type((2, 1)))
h = fem.Constant(mesh, default_scalar_type((3, 2)))
# Define variational problem
u = ufl.TrialFunction(V)
v = ufl.TestFunction(V)
a = ufl.inner(u, v) * ds(3) + ufl.inner(ufl.grad(u), ufl.grad(v)) * ds
rhs = ufl.inner(g, v) * ds + ufl.inner(h, v) * ds(3)
bilinear_form = fem.form(a)
linear_form = fem.form(rhs)
# Create multipoint constraint and assemble system
def l2b(li):
return np.array(li, dtype=mesh.geometry.x.dtype).tobytes()
s_m_c = {}
for i in range(1, N):
s_m_c[l2b([1, i / N])] = {l2b([1, 1]): 0.3}
mpc = dolfinx_mpc.MultiPointConstraint(V)
mpc.create_general_constraint(s_m_c, 1, 1)
mpc.finalize()
with Timer("~TEST: Assemble matrix"):
A = assemble_matrix(bilinear_form, mpc)
with Timer("~TEST: Assemble vector"):
b = assemble_vector(linear_form, mpc)
b.ghostUpdate(addv=PETSc.InsertMode.ADD_VALUES, mode=PETSc.ScatterMode.REVERSE)
# Solve the MPC problem using a global transformation matrix
# and numpy solvers to get reference values
# Generate reference matrices and unconstrained solution
A_org = fem.petsc.assemble_matrix(bilinear_form)
A_org.assemble()
L_org = fem.petsc.assemble_vector(linear_form)
L_org.ghostUpdate(addv=PETSc.InsertMode.ADD_VALUES, mode=PETSc.ScatterMode.REVERSE)
root = 0
comm = mesh.comm
with Timer("~TEST: Compare"):
dolfinx_mpc.utils.compare_mpc_lhs(A_org, A, mpc, root=root)
dolfinx_mpc.utils.compare_mpc_rhs(L_org, b, mpc, root=root)
L_org.destroy()
b.destroy()
A_org.destroy()
A.destroy()
list_timings(comm, [TimingType.wall])
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