("Einc", inc_field_scat.e),
("Hinc", inc_field_scat.h),
("bdry_normals", bdry_normals),
("e_bc_residual", eh_bc_values[:3]),
("h_bc_residual", eh_bc_values[3]),
])
from pytential.qbx import QBXTargetAssociationFailedException
try:
fplot_repr = eval_repr_at(places,
target="plot_targets",
source="qbx_target_tol")
except QBXTargetAssociationFailedException as e:
fplot.write_vtk_file("failed-targets.vts", [
("failed_targets",
actx.to_numpy(actx.thaw(e.failed_target_flags))),
])
raise
fplot_repr = EHField(vector_from_device(actx.queue, fplot_repr))
fplot_inc = EHField(
vector_from_device(
actx.queue, eval_inc_field_at(places,
target="plot_targets")))
fplot.write_vtk_file("potential-%s.vts" % resolution, [
("E", fplot_repr.e),
("H", fplot_repr.h),
("Einc", fplot_inc.e),
("Hinc", fplot_inc.h),
])
def exec_compute_potential_insn_fmm(self, actx: PyOpenCLArrayContext, insn,
bound_expr, evaluate, fmm_driver):
"""
:arg fmm_driver: A function that accepts four arguments:
*wrangler*, *strength*, *geo_data*, *kernel*, *kernel_arguments*
:returns: a tuple ``(assignments, extra_outputs)``, where *assignments*
is a list of tuples containing pairs ``(name, value)`` representing
assignments to be performed in the evaluation context.
*extra_outputs* is data that *fmm_driver* may return
(such as timing data), passed through unmodified.
"""
target_name_and_side_to_number, target_discrs_and_qbx_sides = (
self.get_target_discrs_and_qbx_sides(insn, bound_expr))
geo_data = self.qbx_fmm_geometry_data(bound_expr.places,
insn.source.geometry,
target_discrs_and_qbx_sides)
# FIXME Exert more positive control over geo_data attribute lifetimes using
# geo_data.<method>.clear_cache(geo_data).
# FIXME Synthesize "bad centers" around corners and edges that have
# inadequate QBX coverage.
# FIXME don't compute *all* output kernels on all targets--respect that
# some target discretizations may only be asking for derivatives (e.g.)
from pytential import bind, sym
waa = bind(
bound_expr.places,
sym.weights_and_area_elements(self.ambient_dim,
dofdesc=insn.source))(actx)
densities = [evaluate(density) for density in insn.densities]
strengths = [waa * density for density in densities]
flat_strengths = tuple(flatten(strength) for strength in strengths)
base_kernel = single_valued(knl.get_base_kernel()
for knl in insn.source_kernels)
output_and_expansion_dtype = (self.get_fmm_output_and_expansion_dtype(
insn.source_kernels, flat_strengths[0]))
kernel_extra_kwargs, source_extra_kwargs = (
self.get_fmm_expansion_wrangler_extra_kwargs(
actx, insn.target_kernels + insn.source_kernels,
geo_data.tree().user_source_ids, insn.kernel_arguments,
evaluate))
wrangler = self.expansion_wrangler_code_container(
target_kernels=insn.target_kernels,
source_kernels=insn.source_kernels).get_wrangler(
actx.queue,
geo_data,
output_and_expansion_dtype,
self.qbx_order,
self.fmm_level_to_order,
source_extra_kwargs=source_extra_kwargs,
kernel_extra_kwargs=kernel_extra_kwargs,
_use_target_specific_qbx=self._use_target_specific_qbx)
from pytential.qbx.geometry import target_state
if (actx.thaw(geo_data.user_target_to_center()) == target_state.FAILED
).any().get():
raise RuntimeError("geometry has failed targets")
# {{{ geometry data inspection hook
if self.geometry_data_inspector is not None:
perform_fmm = self.geometry_data_inspector(insn, bound_expr,
geo_data)
if not perform_fmm:
return [(o.name, 0) for o in insn.outputs]
# }}}
# Execute global QBX.
all_potentials_on_every_target, extra_outputs = (fmm_driver(
wrangler, flat_strengths, geo_data, base_kernel,
kernel_extra_kwargs))
results = []
for o in insn.outputs:
target_side_number = target_name_and_side_to_number[
o.target_name, o.qbx_forced_limit]
target_discr, _ = target_discrs_and_qbx_sides[target_side_number]
target_slice = slice(*geo_data.target_info(
).target_discr_starts[target_side_number:target_side_number + 2])
result = \
all_potentials_on_every_target[o.target_kernel_index][target_slice]
from meshmode.discretization import Discretization
if isinstance(target_discr, Discretization):
from meshmode.dof_array import unflatten
result = unflatten(actx, target_discr, result)
results.append((o.name, result))
return results, extra_outputs
def test_off_surface_eval_vs_direct(ctx_factory, do_plot=False):
logging.basicConfig(level=logging.INFO)
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
# prevent cache 'splosion
from sympy.core.cache import clear_cache
clear_cache()
nelements = 300
target_order = 8
qbx_order = 3
mesh = make_curve_mesh(WobblyCircle.random(8, seed=30),
np.linspace(0, 1, nelements+1),
target_order)
from pytential.qbx import QBXLayerPotentialSource
from meshmode.discretization import Discretization
from meshmode.discretization.poly_element import \
InterpolatoryQuadratureSimplexGroupFactory
pre_density_discr = Discretization(
actx, mesh, InterpolatoryQuadratureSimplexGroupFactory(target_order))
direct_qbx = QBXLayerPotentialSource(
pre_density_discr, 4*target_order, qbx_order,
fmm_order=False,
target_association_tolerance=0.05,
)
fmm_qbx = QBXLayerPotentialSource(
pre_density_discr, 4*target_order, qbx_order,
fmm_order=qbx_order + 3,
_expansions_in_tree_have_extent=True,
target_association_tolerance=0.05,
)
fplot = FieldPlotter(np.zeros(2), extent=5, npoints=500)
from pytential.target import PointsTarget
ptarget = PointsTarget(fplot.points)
from sumpy.kernel import LaplaceKernel
places = GeometryCollection({
"direct_qbx": direct_qbx,
"fmm_qbx": fmm_qbx,
"target": ptarget})
direct_density_discr = places.get_discretization("direct_qbx")
fmm_density_discr = places.get_discretization("fmm_qbx")
from pytential.qbx import QBXTargetAssociationFailedException
op = sym.D(LaplaceKernel(2), sym.var("sigma"), qbx_forced_limit=None)
try:
direct_sigma = direct_density_discr.zeros(actx) + 1
direct_fld_in_vol = bind(places, op,
auto_where=("direct_qbx", "target"))(
actx, sigma=direct_sigma)
except QBXTargetAssociationFailedException as e:
fplot.show_scalar_in_matplotlib(
actx.to_numpy(actx.thaw(e.failed_target_flags)))
import matplotlib.pyplot as pt
pt.show()
raise
fmm_sigma = fmm_density_discr.zeros(actx) + 1
fmm_fld_in_vol = bind(places, op,
auto_where=("fmm_qbx", "target"))(
actx, sigma=fmm_sigma)
err = actx.np.fabs(fmm_fld_in_vol - direct_fld_in_vol)
linf_err = actx.to_numpy(err).max()
print("l_inf error:", linf_err)
if do_plot:
#fplot.show_scalar_in_mayavi(0.1*.get(queue))
fplot.write_vtk_file("potential.vts", [
("fmm_fld_in_vol", actx.to_numpy(fmm_fld_in_vol)),
("direct_fld_in_vol", actx.to_numpy(direct_fld_in_vol))
])
assert linf_err < 1e-3