def test_build_matrix_places(ctx_factory,
source_discr_stage, target_discr_stage, visualize=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
# prevent cache explosion
from sympy.core.cache import clear_cache
clear_cache()
qbx_forced_limit = -1
place_ids = (
sym.DOFDescriptor(
geometry=sym.DEFAULT_SOURCE,
discr_stage=source_discr_stage),
sym.DOFDescriptor(
geometry=sym.DEFAULT_TARGET,
discr_stage=target_discr_stage),
)
# build test operators
qbx = _build_qbx_discr(queue, nelements=8, target_order=2, ndim=2,
curve_f=partial(ellipse, 1.0))
op, u_sym, _ = _build_op(lpot_id=1, ndim=2,
source=place_ids[0],
target=place_ids[1],
qbx_forced_limit=qbx_forced_limit)
from pytential.symbolic.execution import GeometryCollection
places = GeometryCollection(qbx, auto_where=place_ids)
source_discr = places.get_discretization(place_ids[0])
target_discr = places.get_discretization(place_ids[1])
index_set = _build_block_index(source_discr, factor=0.6)
from pytential.symbolic.execution import _prepare_expr
op = _prepare_expr(places, op)
# build full QBX matrix
from pytential.symbolic.matrix import MatrixBuilder
mbuilder = MatrixBuilder(queue,
dep_expr=u_sym,
other_dep_exprs=[],
dep_source=places.get_geometry(place_ids[0]),
dep_discr=places.get_discretization(place_ids[0]),
places=places,
context={})
qbx_mat = mbuilder(op)
# build full p2p matrix
from pytential.symbolic.matrix import P2PMatrixBuilder
mbuilder = P2PMatrixBuilder(queue,
dep_expr=u_sym,
other_dep_exprs=[],
dep_source=places.get_geometry(place_ids[0]),
dep_discr=places.get_discretization(place_ids[0]),
places=places,
context={})
p2p_mat = mbuilder(op)
assert p2p_mat.shape == (target_discr.nnodes, source_discr.nnodes)
# build block qbx and p2p matrices
from pytential.symbolic.matrix import NearFieldBlockBuilder
mbuilder = NearFieldBlockBuilder(queue,
dep_expr=u_sym,
other_dep_exprs=[],
dep_source=places.get_geometry(place_ids[0]),
dep_discr=places.get_discretization(place_ids[0]),
places=places,
index_set=index_set,
context={})
mat = mbuilder(op)
if place_ids[0].discr_stage is not None:
assert _max_block_error(qbx_mat, mat, index_set.get(queue)) < 1.0e-14
from pytential.symbolic.matrix import FarFieldBlockBuilder
mbuilder = FarFieldBlockBuilder(queue,
dep_expr=u_sym,
other_dep_exprs=[],
dep_source=places.get_geometry(place_ids[0]),
dep_discr=places.get_discretization(place_ids[0]),
places=places,
index_set=index_set,
context={},
exclude_self=True)
mat = mbuilder(op)
assert _max_block_error(p2p_mat, mat, index_set.get(queue)) < 1.0e-14
def test_build_matrix_fixed_stage(ctx_factory,
source_discr_stage,
target_discr_stage,
visualize=False):
"""Checks that the block builders match for difference stages."""
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
actx = PyOpenCLArrayContext(queue)
# prevent cache explosion
from sympy.core.cache import clear_cache
clear_cache()
case = extra.CurveTestCase(
name="starfish",
curve_fn=NArmedStarfish(5, 0.25),
target_order=4,
resolutions=[32],
index_sparsity_factor=0.6,
op_type="scalar",
tree_kind=None,
)
logger.info("\n%s", case)
# {{{ geometry
dd = sym.DOFDescriptor(case.name)
qbx = case.get_layer_potential(actx, case.resolutions[-1],
case.target_order)
places = GeometryCollection(
{case.name: qbx},
auto_where=(dd.copy(discr_stage=source_discr_stage),
dd.copy(discr_stage=target_discr_stage)))
dd = places.auto_source
density_discr = places.get_discretization(dd.geometry, dd.discr_stage)
# }}}
# {{{ symbolic
if source_discr_stage is target_discr_stage:
qbx_forced_limit = -1
else:
qbx_forced_limit = None
sym_u, sym_op = case.get_operator(places.ambient_dim, qbx_forced_limit)
from pytential.symbolic.execution import _prepare_expr
sym_prep_op = _prepare_expr(places, sym_op)
# }}}
# {{{ check
source_discr = places.get_discretization(case.name, source_discr_stage)
target_discr = places.get_discretization(case.name, target_discr_stage)
logger.info("nelements: %d", density_discr.mesh.nelements)
logger.info("ndofs: %d", source_discr.ndofs)
logger.info("ndofs: %d", target_discr.ndofs)
icols = case.get_block_indices(actx, source_discr, matrix_indices=False)
irows = case.get_block_indices(actx, target_discr, matrix_indices=False)
index_set = MatrixBlockIndexRanges(actx.context, icols, irows)
kwargs = dict(
dep_expr=sym_u,
other_dep_exprs=[],
dep_source=places.get_geometry(case.name),
dep_discr=density_discr,
places=places,
context=case.knl_concrete_kwargs,
)
# qbx
from pytential.symbolic import matrix
mat = matrix.MatrixBuilder(actx, **kwargs)(sym_prep_op)
blk = matrix.NearFieldBlockBuilder(actx, index_set=index_set,
**kwargs)(sym_prep_op)
assert mat.shape == (target_discr.ndofs, source_discr.ndofs)
assert extra.max_block_error(mat, blk, index_set.get(queue)) < 1.0e-14
# p2p
mat = matrix.P2PMatrixBuilder(actx, exclude_self=True,
**kwargs)(sym_prep_op)
blk = matrix.FarFieldBlockBuilder(actx,
index_set=index_set,
exclude_self=True,
**kwargs)(sym_prep_op)
assert mat.shape == (target_discr.ndofs, source_discr.ndofs)
assert extra.max_block_error(mat, blk, index_set.get(queue)) < 1.0e-14
def test_qbx_block_builder(ctx_factory, factor, ndim, lpot_id,
visualize=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
# prevent cache explosion
from sympy.core.cache import clear_cache
clear_cache()
place_ids = (
sym.DOFDescriptor(
geometry=sym.DEFAULT_SOURCE,
discr_stage=sym.QBX_SOURCE_STAGE2),
sym.DOFDescriptor(
geometry=sym.DEFAULT_TARGET,
discr_stage=sym.QBX_SOURCE_STAGE2),
)
target_order = 2 if ndim == 3 else 7
qbx = _build_qbx_discr(queue, target_order=target_order, ndim=ndim)
op, u_sym, _ = _build_op(lpot_id, ndim=ndim,
source=place_ids[0],
target=place_ids[1],
qbx_forced_limit="avg")
from pytential.symbolic.execution import GeometryCollection, _prepare_expr
places = GeometryCollection(qbx, auto_where=place_ids)
expr = _prepare_expr(places, op)
density_discr = places.get_discretization(place_ids[0])
index_set = _build_block_index(density_discr, factor=factor)
from pytential.symbolic.matrix import NearFieldBlockBuilder
mbuilder = NearFieldBlockBuilder(queue,
dep_expr=u_sym,
other_dep_exprs=[],
dep_source=places.get_geometry(place_ids[0]),
dep_discr=places.get_discretization(place_ids[0]),
places=places,
index_set=index_set,
context={})
blk = mbuilder(expr)
from pytential.symbolic.matrix import MatrixBuilder
mbuilder = MatrixBuilder(queue,
dep_expr=u_sym,
other_dep_exprs=[],
dep_source=places.get_geometry(place_ids[0]),
dep_discr=places.get_discretization(place_ids[0]),
places=places,
context={})
mat = mbuilder(expr)
index_set = index_set.get(queue)
if visualize:
blk_full = np.zeros_like(mat)
mat_full = np.zeros_like(mat)
for i in range(index_set.nblocks):
itgt, isrc = index_set.block_indices(i)
blk_full[np.ix_(itgt, isrc)] = index_set.block_take(blk, i)
mat_full[np.ix_(itgt, isrc)] = index_set.take(mat, i)
import matplotlib.pyplot as mp
_, (ax1, ax2) = mp.subplots(1, 2,
figsize=(10, 8), constrained_layout=True)
ax1.imshow(mat_full)
ax1.set_title('MatrixBuilder')
ax2.imshow(blk_full)
ax2.set_title('NearFieldBlockBuilder')
mp.savefig("test_qbx_block_builder.png", dpi=300)
assert _max_block_error(mat, blk, index_set) < 1.0e-14
case.target_order)
places = GeometryCollection(qbx, auto_where=(dd, dd.to_stage1()))
density_discr = places.get_discretization(dd.geometry, dd.discr_stage)
logger.info("nelements: %d", density_discr.mesh.nelements)
logger.info("ndofs: %d", density_discr.ndofs)
# }}}
# {{{ symbolic
sym_u, sym_op = case.get_operator(ambient_dim)
from pytential.symbolic.execution import _prepare_expr
sym_prep_op = _prepare_expr(places, sym_op)
# }}}
# {{{ matrix
index_set = case.get_block_indices(actx, density_discr)
kwargs = dict(dep_expr=sym_u,
other_dep_exprs=[],
dep_source=places.get_geometry(dd.geometry),
dep_discr=density_discr,
places=places,
context=case.knl_concrete_kwargs)
if block_builder_type == "qbx":
from pytential.symbolic.matrix import MatrixBuilder