def __init__(self, v, v_out):
if isinstance(v, expression.Expression) or not isinstance(
v, (ufl.core.expr.Expr, function.Function)):
raise ValueError(
"Can only recover UFL expression or Functions not '%s'" %
type(v))
# Check shape values
if v.ufl_shape != v_out.ufl_shape:
raise RuntimeError(
'Shape mismatch between source %s and target function spaces %s in project'
% (v.ufl_shape, v_out.ufl_shape))
self._same_fspace = (isinstance(v, function.Function)
and v.function_space() == v_out.function_space())
self.v = v
self.v_out = v_out
self.V = v_out.function_space()
# Check the number of local dofs
if self.v_out.function_space().finat_element.space_dimension(
) != self.v.function_space().finat_element.space_dimension():
raise RuntimeError(
"Number of local dofs for each field must be equal.")
self.average_kernel = kernels.Average(self.V)
def test_average(geometry, mesh):
cell = mesh.ufl_cell().cellname()
DG1_elt = FiniteElement("DG", cell, 1, variant="equispaced")
vec_DG1 = VectorFunctionSpace(mesh, DG1_elt)
vec_DG0 = VectorFunctionSpace(mesh, "DG", 0)
vec_CG1 = VectorFunctionSpace(mesh, "CG", 1)
# We will fill DG1_field with values, and average them to CG_field
# First need to put the values into DG0 and then interpolate
DG0_field = Function(vec_DG0)
DG1_field = Function(vec_DG1)
CG_field = Function(vec_CG1)
weights = Function(vec_CG1)
DG0_field, weights, true_values, CG_index = setup_values(
geometry, DG0_field, weights)
DG1_field.interpolate(DG0_field)
kernel = kernels.Average(vec_CG1)
kernel.apply(CG_field, weights, DG1_field)
tolerance = 1e-12
if geometry == "1D":
assert abs(CG_field.dat.data[CG_index] - true_values) < tolerance
elif geometry == "2D":
assert abs(CG_field.dat.data[CG_index][0] - true_values[0]) < tolerance
assert abs(CG_field.dat.data[CG_index][1] - true_values[1]) < tolerance
def test_average(geometry, mesh):
cell = mesh.ufl_cell().cellname()
DG1_elt = FiniteElement("DG", cell, 1, variant="equispaced")
vec_DG1 = VectorFunctionSpace(mesh, DG1_elt)
vec_CG1 = VectorFunctionSpace(mesh, "CG", 1)
# We will fill DG_field with values, and average them to CG_field
DG_field = Function(vec_DG1)
CG_field = Function(vec_CG1)
weights = Function(vec_CG1)
DG_field, weights, true_values = setup_values(geometry, DG_field, weights)
kernel = kernels.Average(vec_CG1)
kernel.apply(CG_field, weights, DG_field)
tolerance = 1e-12
if geometry == "1D":
assert abs(CG_field.dat.data[1] - true_values) < tolerance
elif geometry == "2D":
assert abs(CG_field.dat.data[2][0] - true_values[0]) < tolerance
assert abs(CG_field.dat.data[2][1] - true_values[1]) < tolerance