def test_symbolic_evaluation(actx_factory):
"""
Evaluate a symbolic expression by plugging in numbers and
:class:`~meshmode.dof_array.DOFArray`s and compare the result to the equivalent
quantity computed explicitly.
"""
actx = actx_factory()
mesh = generate_regular_rect_mesh(
a=(-np.pi/2,)*2,
b=(np.pi/2,)*2,
nelements_per_axis=(4,)*2)
from grudge.eager import EagerDGDiscretization
discr = EagerDGDiscretization(actx, mesh, order=2)
nodes = thaw(actx, discr.nodes())
sym_coords = pmbl.make_sym_vector("x", 2)
sym_f = (
pmbl.var("exp")(-pmbl.var("t"))
* pmbl.var("cos")(sym_coords[0])
* pmbl.var("sin")(sym_coords[1]))
t = 0.5
f = sym.EvaluationMapper({"t": t, "x": nodes})(sym_f)
expected_f = np.exp(-t) * actx.np.cos(nodes[0]) * actx.np.sin(nodes[1])
assert actx.to_numpy(discr.norm(f - expected_f)/discr.norm(expected_f)) < 1e-12
def sym_eval(expr, x_vec):
# FIXME: When pymbolic supports array containers
mapper = sym.EvaluationMapper({"x": x_vec})
from arraycontext import rec_map_array_container
result = rec_map_array_container(mapper, expr)
# If expressions don't depend on coords (e.g., order 0), evaluated result
# will be scalar-valued, so promote to DOFArray(s) before returning
return result * (0 * x_vec[0] + 1)
def sym_eval(expr, t):
return sym.EvaluationMapper({"c": p.c, "x": nodes, "t": t})(expr)
def sym_eval(expr):
return sym.EvaluationMapper({"x": nodes, "t": t})(expr)
def sym_eval_mirgecom(expr):
return sym.EvaluationMapper({
"x": nodes_mirgecom,
"t": t
})(expr)
def _sym_eval(expr, **kwargs):
return sym.EvaluationMapper(kwargs)(expr)
