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"""Unit tests for parts of the PETSc interface not tested via the
GenericFoo interface
"""
# Copyright (C) 2015-2017 Garth N. Wells
#
# This file is part of DOLFIN.
#
# DOLFIN is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# DOLFIN is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with DOLFIN. If not, see <http://www.gnu.org/licenses/>.
from dolfin import (UnitSquareMesh, TrialFunction, TestFunction,
MPI, FunctionSpace, assemble, Constant, dx,
parameters, has_petsc)
if has_petsc() :
from dolfin import (PETScVector, PETScMatrix, PETScNestMatrix,
PETScLUSolver, PETScKrylovSolver)
from dolfin_utils.test import (skip_if_not_PETSc,
skip_if_not_petsc4py,
pushpop_parameters)
@skip_if_not_PETSc
def test_vector():
"Test PETScVector interface"
prefix = "my_vector_"
x = PETScVector(MPI.comm_world)
x.set_options_prefix(prefix)
assert x.get_options_prefix() == prefix
x.init(300)
assert x.get_options_prefix() == prefix
@skip_if_not_PETSc
def test_krylov_solver_norm_type():
"""Check setting of norm type used in testing for convergence by
PETScKrylovSolver
"""
norm_type = (PETScKrylovSolver.norm_type.default_norm,
PETScKrylovSolver.norm_type.natural,
PETScKrylovSolver.norm_type.preconditioned,
PETScKrylovSolver.norm_type.none,
PETScKrylovSolver.norm_type.unpreconditioned)
for norm in norm_type:
# Solve a system of equations
mesh = UnitSquareMesh(4, 4)
V = FunctionSpace(mesh, "Lagrange", 1)
u, v = TrialFunction(V), TestFunction(V)
a = u*v*dx
L = Constant(1.0)*v*dx
A, b = assemble(a), assemble(L)
solver = PETScKrylovSolver("cg")
solver.parameters["maximum_iterations"] = 2
solver.parameters["error_on_nonconvergence"] = False
solver.set_norm_type(norm)
solver.set_operator(A)
solver.solve(b.copy(), b)
solver.get_norm_type()
if norm is not PETScKrylovSolver.norm_type.default_norm:
assert solver.get_norm_type() == norm
@skip_if_not_PETSc
def test_krylov_solver_options_prefix(pushpop_parameters):
"Test set/get PETScKrylov solver prefix option"
# Set backend
parameters["linear_algebra_backend"] = "PETSc"
# Prefix
prefix = "test_foo_"
# Create solver and set prefix
solver = PETScKrylovSolver()
solver.set_options_prefix(prefix)
# Check prefix (pre solve)
assert solver.get_options_prefix() == prefix
# Solve a system of equations
mesh = UnitSquareMesh(4, 4)
V = FunctionSpace(mesh, "Lagrange", 1)
u, v = TrialFunction(V), TestFunction(V)
a, L = u*v*dx, Constant(1.0)*v*dx
A, b = assemble(a), assemble(L)
solver.set_operator(A)
solver.solve(b.copy(), b)
# Check prefix (post solve)
assert solver.get_options_prefix() == prefix
@skip_if_not_PETSc
def test_options_prefix(pushpop_parameters):
"Test set/get prefix option for PETSc objects"
def run_test(A, init_function):
# Prefix
prefix = "test_foo_"
# Set prefix
A.set_options_prefix(prefix)
# Get prefix (should be empty since vector has been initialised)
# assert not A.get_options_prefix()
# Initialise vector
init_function(A)
# Check prefix
assert A.get_options_prefix() == prefix
# Try changing prefix post-intialisation (should throw error)
# with pytest.raises(RuntimeError):
# A.set_options_prefix("test")
# Test vector
def init_vector(x):
x.init(100)
x = PETScVector(MPI.comm_world)
run_test(x, init_vector)
# Test matrix
def init_matrix(A):
mesh = UnitSquareMesh(12, 12)
V = FunctionSpace(mesh, "Lagrange", 1)
u, v = TrialFunction(V), TestFunction(V)
assemble(u*v*dx, tensor=A)
A = PETScMatrix()
run_test(A, init_matrix)
# FIXME: Need to straighten out the calls to PETSc
# FooSetFromOptions calls in the solver wrapers
# Test solvers
# def init_solver(A, solver):
# A = PETScMatrix()
# init_matrix(A)
# solver.set_operator(A)
# Test Krylov solver
# solver = PETScKrylovSolver()
# run_test(solver, init_solver)
# Test KY solver
# solver = PETScLUSolver()
# run_test(solver, init_solver)
@skip_if_not_PETSc
def test_nest_matrix(pushpop_parameters):
# Create Matrices and insert into nest
A00 = PETScMatrix()
A01 = PETScMatrix()
A10 = PETScMatrix()
mesh = UnitSquareMesh(12, 12)
V = FunctionSpace(mesh, "Lagrange", 2)
Q = FunctionSpace(mesh, "Lagrange", 1)
u, v = TrialFunction(V), TestFunction(V)
p, q = TrialFunction(Q), TestFunction(Q)
assemble(u*v*dx, tensor=A00)
assemble(p*v*dx, tensor=A01)
assemble(u*q*dx, tensor=A10)
AA = PETScNestMatrix([A00, A01, A10, None])
# Create compatible RHS Vectors and insert into nest
u = PETScVector()
p = PETScVector()
x = PETScVector()
A00.init_vector(u, 1)
A01.init_vector(p, 1)
AA.init_vectors(x, [u, p])
@skip_if_not_petsc4py
def test_lu_cholesky():
"""Test that PETScLUSolver selects LU or Cholesky solver based on
symmetry of matrix operator.
"""
from petsc4py import PETSc
mesh = UnitSquareMesh(MPI.comm_world, 12, 12)
V = FunctionSpace(mesh, "Lagrange", 1)
u, v = TrialFunction(V), TestFunction(V)
A = PETScMatrix(mesh.mpi_comm())
assemble(Constant(1.0)*u*v*dx, tensor=A)
# Check that solver type is LU
solver = PETScLUSolver(mesh.mpi_comm(), A, "petsc")
pc_type = solver.ksp().getPC().getType()
assert pc_type == "lu"
# Set symmetry flag
A.mat().setOption(PETSc.Mat.Option.SYMMETRIC, True)
# Check symmetry flags
symm = A.mat().isSymmetricKnown()
assert symm[0] == True
assert symm[1] == True
# Check that solver type is Cholesky since matrix has now been
# marked as symmetric
solver = PETScLUSolver(mesh.mpi_comm(), A, "petsc")
pc_type = solver.ksp().getPC().getType()
assert pc_type == "cholesky"
# Re-assemble, which resets symmetry flag
assemble(Constant(1.0)*u*v*dx, tensor=A)
solver = PETScLUSolver(mesh.mpi_comm(), A, "petsc")
pc_type = solver.ksp().getPC().getType()
assert pc_type == "lu"
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