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__authors__ = "Martin Sandve Alnæs"
__date__ = "2008-03-12 -- 2009-01-28"
# Modified by Anders Logg, 2008
# Modified by Garth N. Wells, 2009
import pytest
from utils import LagrangeElement
from ufl import (
Argument,
Coefficient,
FacetNormal,
FunctionSpace,
Mesh,
SpatialCoordinate,
TestFunction,
TrialFunction,
adjoint,
div,
dot,
ds,
dx,
grad,
inner,
sin,
triangle,
)
from ufl.algorithms import (
compute_form_data,
expand_derivatives,
expand_indices,
extract_arguments,
extract_coefficients,
extract_elements,
extract_unique_elements,
)
from ufl.corealg.traversal import (
post_traversal,
pre_traversal,
unique_post_traversal,
unique_pre_traversal,
)
# TODO: add more tests, covering all utility algorithms
@pytest.fixture(scope="module")
def element():
return LagrangeElement(triangle, 1)
@pytest.fixture(scope="module")
def domain():
return Mesh(LagrangeElement(triangle, 1, (2,)))
@pytest.fixture(scope="module")
def space(element, domain):
return FunctionSpace(domain, element)
@pytest.fixture(scope="module")
def arguments(space):
v = TestFunction(space)
u = TrialFunction(space)
return (v, u)
@pytest.fixture(scope="module")
def coefficients(space):
c = Coefficient(space)
f = Coefficient(space)
return (c, f)
@pytest.fixture
def forms(arguments, coefficients, domain):
v, u = arguments
c, f = coefficients
n = FacetNormal(domain)
a = u * v * dx
L = f * v * dx
b = u * v * dx(0) + inner(c * grad(u), grad(v)) * dx(1) + dot(n, grad(u)) * v * ds + f * v * dx
return (a, L, b)
def test_extract_arguments_vs_fixture(arguments, forms):
assert arguments == tuple(extract_arguments(forms[0]))
assert tuple(arguments[:1]) == tuple(extract_arguments(forms[1]))
def test_extract_coefficients_vs_fixture(coefficients, forms):
assert coefficients == tuple(extract_coefficients(forms[2]))
def test_extract_elements_and_extract_unique_elements(forms, element, domain):
b = forms[2]
integrals = b.integrals_by_type("cell")
integrals[0].integrand()
element1 = element
element2 = element
space1 = FunctionSpace(domain, element1)
space2 = FunctionSpace(domain, element2)
v = TestFunction(space1)
u = TrialFunction(space2)
a = u * v * dx
assert extract_elements(a) == (element1, element2)
assert extract_unique_elements(a) == (element1,)
def test_pre_and_post_traversal(space):
v = TestFunction(space)
f = Coefficient(space)
g = Coefficient(space)
p1 = f * v
p2 = g * v
s = p1 + p2
# NB! These traversal algorithms are intended to guarantee only
# parent before child and vice versa, not this particular
# ordering:
assert list(pre_traversal(s)) == [s, p2, g, v, p1, f, v]
assert list(post_traversal(s)) == [g, v, p2, f, v, p1, s]
assert list(unique_pre_traversal(s)) == [s, p2, g, v, p1, f]
assert list(unique_post_traversal(s)) == [v, f, p1, g, p2, s]
def test_expand_indices(domain):
element = LagrangeElement(triangle, 2)
space = FunctionSpace(domain, element)
v = TestFunction(space)
u = TrialFunction(space)
def evaluate(form):
return form.cell_integral()[0].integrand()(
(), {v: 3, u: 5}
) # TODO: How to define values of derivatives?
a = div(grad(v)) * u * dx
# a1 = evaluate(a)
a = expand_derivatives(a)
# a2 = evaluate(a)
a = expand_indices(a)
# a3 = evaluate(a)
# TODO: Compare a1, a2, a3
# TODO: Test something more
def test_adjoint(domain):
cell = triangle
V1 = LagrangeElement(cell, 1)
V2 = LagrangeElement(cell, 2)
s1 = FunctionSpace(domain, V1)
s2 = FunctionSpace(domain, V2)
u = TrialFunction(s1)
v = TestFunction(s2)
assert u.number() > v.number()
u2 = Argument(s1, 2)
v2 = Argument(s2, 3)
assert u2.number() < v2.number()
a = u * v * dx
a_arg_degrees = [arg.ufl_element().embedded_superdegree for arg in extract_arguments(a)]
assert a_arg_degrees == [2, 1]
b = adjoint(a)
b_arg_degrees = [arg.ufl_element().embedded_superdegree for arg in extract_arguments(b)]
assert b_arg_degrees == [1, 2]
c = adjoint(a, (u2, v2))
c_arg_degrees = [arg.ufl_element().embedded_superdegree for arg in extract_arguments(c)]
assert c_arg_degrees == [1, 2]
d = adjoint(b)
d_arg_degrees = [arg.ufl_element().embedded_superdegree for arg in extract_arguments(d)]
assert d_arg_degrees == [2, 1]
def test_remove_component_tensors(domain):
x = SpatialCoordinate(domain)
u = sin(x[0])
f = div(grad(div(grad(u))))
form = f * dx
fd = compute_form_data(form, do_remove_component_tensors=True)
assert "ComponentTensor" not in repr(fd.preprocessed_form)
|
