def test_vortex_init(ctx_factory):
"""
Simple test to check that Vortex2D initializer
creates the expected solution field.
"""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
dim = 2
nel_1d = 4
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=[(0.0, ), (-5.0, )],
b=[(10.0, ), (5.0, )],
nelements_per_axis=(nel_1d, ) * dim)
order = 3
logger.info(f"Number of elements: {mesh.nelements}")
discr = EagerDGDiscretization(actx, mesh, order=order)
nodes = thaw(actx, discr.nodes())
# Init soln with Vortex
vortex = Vortex2D()
cv = vortex(nodes)
gamma = 1.4
p = 0.4 * (cv.energy - 0.5 * np.dot(cv.momentum, cv.momentum) / cv.mass)
exp_p = cv.mass**gamma
errmax = actx.to_numpy(discr.norm(p - exp_p, np.inf))
logger.info(f"vortex_soln = {cv}")
logger.info(f"pressure = {p}")
assert errmax < 1e-15
def test_external_call(ctx_factory):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
def double(queue, x):
return 2 * x
from meshmode.mesh.generation import generate_regular_rect_mesh
dims = 2
mesh = generate_regular_rect_mesh(a=(0, ) * dims,
b=(1, ) * dims,
n=(4, ) * dims)
discr = DGDiscretizationWithBoundaries(actx, mesh, order=1)
ones = sym.Ones(sym.DD_VOLUME)
op = (ones * 3 + sym.FunctionSymbol("double")(ones))
from grudge.function_registry import (base_function_registry,
register_external_function)
freg = register_external_function(base_function_registry,
"double",
implementation=double,
dd=sym.DD_VOLUME)
bound_op = bind(discr, op, function_registry=freg)
result = bound_op(actx, double=double)
assert actx.to_numpy(flatten(result) == 5).all()
def test_unregularized_off_surface_fmm_vs_direct(ctx_factory):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
nelements = 300
target_order = 8
fmm_order = 4
# {{{ geometry
mesh = make_curve_mesh(WobblyCircle.random(8, seed=30),
np.linspace(0, 1, nelements+1),
target_order)
from pytential.unregularized import UnregularizedLayerPotentialSource
from meshmode.discretization import Discretization
from meshmode.discretization.poly_element import \
InterpolatoryQuadratureSimplexGroupFactory
density_discr = Discretization(
actx, mesh, InterpolatoryQuadratureSimplexGroupFactory(target_order))
direct = UnregularizedLayerPotentialSource(
density_discr,
fmm_order=False,
)
fmm = direct.copy(
fmm_level_to_order=lambda kernel, kernel_args, tree, level: fmm_order)
sigma = density_discr.zeros(actx) + 1
fplot = FieldPlotter(np.zeros(2), extent=5, npoints=100)
from pytential.target import PointsTarget
ptarget = PointsTarget(fplot.points)
from pytential import GeometryCollection
places = GeometryCollection({
"unregularized_direct": direct,
"unregularized_fmm": fmm,
"targets": ptarget})
# }}}
# {{{ check
from sumpy.kernel import LaplaceKernel
op = sym.D(LaplaceKernel(2), sym.var("sigma"), qbx_forced_limit=None)
direct_fld_in_vol = bind(places, op,
auto_where=("unregularized_direct", "targets"))(
actx, sigma=sigma)
fmm_fld_in_vol = bind(places, op,
auto_where=("unregularized_fmm", "targets"))(actx, sigma=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)
assert linf_err < 5e-3
def test_target_association_failure(ctx_factory):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
# {{{ generate circle
order = 5
nelements = 40
# Make the curve mesh.
curve_f = partial(ellipse, 1)
mesh = make_curve_mesh(curve_f, np.linspace(0, 1, nelements + 1), order)
from meshmode.discretization import Discretization
from meshmode.discretization.poly_element import \
InterpolatoryQuadratureSimplexGroupFactory
factory = InterpolatoryQuadratureSimplexGroupFactory(order)
discr = Discretization(actx, mesh, factory)
lpot_source = QBXLayerPotentialSource(
discr,
qbx_order=order, # not used in target association
fine_order=order)
places = GeometryCollection(lpot_source)
# }}}
# {{{ generate targets and check
close_circle = 0.999 * np.exp(
2j * np.pi * np.linspace(0, 1, 500, endpoint=False))
from pytential.target import PointsTarget
close_circle_target = (PointsTarget(
actx.from_numpy(np.array([close_circle.real, close_circle.imag]))))
targets = ((close_circle_target, 0), )
from pytential.qbx.target_assoc import (TargetAssociationCodeContainer,
associate_targets_to_qbx_centers,
QBXTargetAssociationFailedException
)
from pytential.qbx.utils import TreeCodeContainer
code_container = TargetAssociationCodeContainer(actx,
TreeCodeContainer(actx))
with pytest.raises(QBXTargetAssociationFailedException):
associate_targets_to_qbx_centers(places,
places.auto_source,
code_container.get_wrangler(actx),
targets,
target_association_tolerance=1e-10)
def main():
cl_ctx = cl.create_some_context()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
nel_1d = 16
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=(-0.5, -0.5),
b=(0.5, 0.5),
n=(nel_1d, nel_1d))
order = 3
# no deep meaning here, just a fudge factor
dt = 0.75 / (nel_1d * order**2)
print("%d elements" % mesh.nelements)
discr = DGDiscretization(actx, mesh, order=order)
fields = flat_obj_array(bump(actx, discr),
[discr.zeros(actx) for i in range(discr.dim)])
from meshmode.discretization.visualization import make_visualizer
vis = make_visualizer(actx, discr.volume_discr, discr.order + 3)
def rhs(t, w):
return wave_operator(actx, discr, c=1, w=w)
t = 0
t_final = 3
istep = 0
while t < t_final:
fields = rk4_step(fields, t, dt, rhs)
if istep % 10 == 0:
# FIXME: Maybe an integral function to go with the
# DOFArray would be nice?
assert len(fields[0]) == 1
print(istep, t, la.norm(actx.to_numpy(fields[0][0])))
vis.write_vtk_file("fld-wave-min-%04d.vtu" % istep, [
("u", fields[0]),
("v", fields[1:]),
])
t += dt
istep += 1
def test_block_builder(ctx_factory,
ambient_dim,
block_builder_type,
index_sparsity_factor,
op_type,
visualize=False):
"""Test that block builders and full matrix builders actually match."""
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
actx = PyOpenCLArrayContext(queue)
# prevent cache explosion
from sympy.core.cache import clear_cache
clear_cache()
if ambient_dim == 2:
case = extra.CurveTestCase(
name="ellipse",
target_order=7,
index_sparsity_factor=index_sparsity_factor,
op_type=op_type,
resolutions=[32],
curve_fn=partial(ellipse, 3.0),
)
def test_tangential_onb(ctx_factory):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
from meshmode.mesh.generation import generate_torus
mesh = generate_torus(5, 2, order=3)
discr = Discretization(
actx, mesh, InterpolatoryQuadratureSimplexGroupFactory(3))
tob = sym.tangential_onb(mesh.ambient_dim)
nvecs = tob.shape[1]
# make sure tangential_onb is mutually orthogonal and normalized
orth_check = bind(discr, sym.make_obj_array([
np.dot(tob[:, i], tob[:, j]) - (1 if i == j else 0)
for i in range(nvecs) for j in range(nvecs)])
)(actx)
from meshmode.dof_array import flatten
orth_check = flatten(orth_check)
for i, orth_i in enumerate(orth_check):
assert (cl.clmath.fabs(orth_i) < 1e-13).get().all()
# make sure tangential_onb is orthogonal to normal
orth_check = bind(discr, sym.make_obj_array([
np.dot(tob[:, i], sym.normal(mesh.ambient_dim).as_vector())
for i in range(nvecs)])
)(actx)
orth_check = flatten(orth_check)
for i, orth_i in enumerate(orth_check):
assert (cl.clmath.fabs(orth_i) < 1e-13).get().all()
def scalar_assignment_percent_of_total_mem_ops_table():
cl_ctx = cl.create_some_context()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
result2d = mem_ops_results(actx, 2)
result3d = mem_ops_results(actx, 3)
with open_output_file("scalar-assignments-mem-op-percentage.tex") as outf:
if not PAPER_OUTPUT:
print("==== Scalar Assigment % of Total Mem Ops ====", file=outf)
print(table(
"lr", ("Operator", r"\parbox{1in}{\centering \% Memory Ops. "
r"Due to Scalar Assignments}"),
(
("2D: Baseline", "%.1f" %
(100 * result2d["nonfused_bytes_total_by_scalar_assignments"]
/ result2d["nonfused_bytes_total"])),
("2D: Inlined", "%.1f" %
(100 * result2d["fused_bytes_total_by_scalar_assignments"] /
result2d["fused_bytes_total"])),
("3D: Baseline", "%.1f" %
(100 * result3d["nonfused_bytes_total_by_scalar_assignments"]
/ result3d["nonfused_bytes_total"])),
("3D: Inlined", "%.1f" %
(100 * result3d["fused_bytes_total_by_scalar_assignments"] /
result3d["fused_bytes_total"])),
)),
file=outf)
logger.info("Wrote '%s'", outf.name)
def problem_stats(order=3):
cl_ctx = cl.create_some_context()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
with open_output_file("grudge-problem-stats.txt") as outf:
_, dg_discr_2d = get_strong_wave_op_with_discr_direct(actx,
dims=2,
order=order)
print("Number of 2D elements:", dg_discr_2d.mesh.nelements, file=outf)
vol_discr_2d = dg_discr_2d.discr_from_dd("vol")
dofs_2d = {group.nunit_dofs for group in vol_discr_2d.groups}
from pytools import one
print("Number of DOFs per 2D element:", one(dofs_2d), file=outf)
_, dg_discr_3d = get_strong_wave_op_with_discr_direct(actx,
dims=3,
order=order)
print("Number of 3D elements:", dg_discr_3d.mesh.nelements, file=outf)
vol_discr_3d = dg_discr_3d.discr_from_dd("vol")
dofs_3d = {group.nunit_dofs for group in vol_discr_3d.groups}
from pytools import one
print("Number of DOFs per 3D element:", one(dofs_3d), file=outf)
logger.info("Wrote '%s'", outf.name)
def test_cost_model(ctx_factory, dim, use_target_specific_qbx):
"""Test that cost model gathering can execute successfully."""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
lpot_source = get_lpot_source(actx, dim).copy(
_use_target_specific_qbx=use_target_specific_qbx,
cost_model=CostModel())
places = GeometryCollection(lpot_source)
density_discr = places.get_discretization(places.auto_source.geometry)
sigma = get_density(actx, density_discr)
sigma_sym = sym.var("sigma")
k_sym = LaplaceKernel(lpot_source.ambient_dim)
sym_op_S = sym.S(k_sym, sigma_sym, qbx_forced_limit=+1)
op_S = bind(places, sym_op_S)
cost_S = op_S.get_modeled_cost(actx, sigma=sigma)
assert len(cost_S) == 1
sym_op_S_plus_D = (
sym.S(k_sym, sigma_sym, qbx_forced_limit=+1)
+ sym.D(k_sym, sigma_sym, qbx_forced_limit="avg"))
op_S_plus_D = bind(places, sym_op_S_plus_D)
cost_S_plus_D = op_S_plus_D.get_modeled_cost(actx, sigma=sigma)
assert len(cost_S_plus_D) == 2
def test_reversed_chained_connection(ctx_factory, ndim, mesh_name):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
actx = PyOpenCLArrayContext(queue)
def run(nelements, order):
discr = create_discretization(actx, ndim,
nelements=nelements,
order=order,
mesh_name=mesh_name)
threshold = 1.0
connections = []
conn = create_refined_connection(actx,
discr, threshold=threshold)
connections.append(conn)
if ndim == 2:
# NOTE: additional refinement makes the 3D meshes explode in size
conn = create_refined_connection(actx,
conn.to_discr, threshold=threshold)
connections.append(conn)
conn = create_refined_connection(actx,
conn.to_discr, threshold=threshold)
connections.append(conn)
from meshmode.discretization.connection import \
ChainedDiscretizationConnection
chained = ChainedDiscretizationConnection(connections)
from meshmode.discretization.connection import \
L2ProjectionInverseDiscretizationConnection
reverse = L2ProjectionInverseDiscretizationConnection(chained)
# create test vector
from_nodes = thaw(actx, chained.from_discr.nodes())
to_nodes = thaw(actx, chained.to_discr.nodes())
from_x = 0
to_x = 0
for d in range(ndim):
from_x += actx.np.cos(from_nodes[d]) ** (d + 1)
to_x += actx.np.cos(to_nodes[d]) ** (d + 1)
from_interp = reverse(to_x)
return (1.0 / nelements,
flat_norm(from_interp - from_x, np.inf) / flat_norm(from_x, np.inf))
from pytools.convergence import EOCRecorder
eoc = EOCRecorder()
order = 4
mesh_sizes = [16, 32, 48, 64, 96, 128]
for n in mesh_sizes:
h, error = run(n, order)
eoc.add_data_point(h, error)
print(eoc)
assert eoc.order_estimate() > (order + 1 - 0.5)
def test_chained_connection(ctx_factory, ndim, visualize=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
actx = PyOpenCLArrayContext(queue)
discr = create_discretization(actx, ndim, nelements=10)
connections = []
conn = create_refined_connection(actx, discr, threshold=np.inf)
connections.append(conn)
conn = create_refined_connection(actx, conn.to_discr, threshold=np.inf)
connections.append(conn)
from meshmode.discretization.connection import \
ChainedDiscretizationConnection
chained = ChainedDiscretizationConnection(connections)
def f(x):
from functools import reduce
return 0.1 * reduce(lambda x, y: x * actx.np.sin(5 * y), x)
x = thaw(actx, connections[0].from_discr.nodes())
fx = f(x)
f1 = chained(fx)
f2 = connections[1](connections[0](fx))
assert flat_norm(f1-f2, np.inf) / flat_norm(f2) < 1e-11
def main():
cl_ctx = cl.create_some_context()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
from meshmode.mesh.generation import ( # noqa
generate_icosphere, generate_icosahedron, generate_torus)
#mesh = generate_icosphere(1, order=order)
mesh = generate_icosahedron(1, order=order)
#mesh = generate_torus(3, 1, order=order)
from meshmode.discretization import Discretization
from meshmode.discretization.poly_element import \
PolynomialWarpAndBlendGroupFactory
discr = Discretization(actx, mesh,
PolynomialWarpAndBlendGroupFactory(order))
from meshmode.discretization.visualization import make_visualizer
vis = make_visualizer(actx, discr, order)
vis.write_vtk_file("geometry.vtu", [
("f", thaw(actx,
discr.nodes()[0])),
])
from meshmode.discretization.visualization import \
write_nodal_adjacency_vtk_file
write_nodal_adjacency_vtk_file("adjacency.vtu", mesh)
def test_mean_curvature(ctx_factory,
discr_name,
resolutions,
discr_and_ref_mean_curvature_getter,
visualize=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
actx = PyOpenCLArrayContext(queue)
from pytools.convergence import EOCRecorder
eoc = EOCRecorder()
for r in resolutions:
discr, ref_mean_curvature = \
discr_and_ref_mean_curvature_getter(actx, r)
mean_curvature = bind(discr,
sym.mean_curvature(discr.ambient_dim))(actx)
h = 1.0 / r
from meshmode.dof_array import flat_norm
h_error = flat_norm(mean_curvature - ref_mean_curvature, np.inf)
eoc.add_data_point(h, h_error)
print(eoc)
order = min([g.order for g in discr.groups])
assert eoc.order_estimate() > order - 1.1
def test_geometry(ctx_factory):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
nelements = 30
order = 5
mesh = make_curve_mesh(partial(ellipse, 1),
np.linspace(0, 1, nelements+1),
order)
from meshmode.discretization import Discretization
from meshmode.discretization.poly_element import \
InterpolatoryQuadratureSimplexGroupFactory
discr = Discretization(actx, mesh,
InterpolatoryQuadratureSimplexGroupFactory(order))
import pytential.symbolic.primitives as prim
area_sym = prim.integral(2, 1, 1)
area = bind(discr, area_sym)(actx)
err = abs(area-2*np.pi)
print(err)
assert err < 1e-3
def test_function_symbol_array(ctx_factory, array_type):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
actx = PyOpenCLArrayContext(queue)
from meshmode.mesh.generation import generate_regular_rect_mesh
dim = 2
mesh = generate_regular_rect_mesh(a=(-0.5, ) * dim,
b=(0.5, ) * dim,
n=(8, ) * dim,
order=4)
discr = DGDiscretizationWithBoundaries(actx, mesh, order=4)
volume_discr = discr.discr_from_dd(sym.DD_VOLUME)
ndofs = sum(grp.ndofs for grp in volume_discr.groups)
import pyopencl.clrandom # noqa: F401
if array_type == "scalar":
sym_x = sym.var("x")
x = unflatten(actx, volume_discr,
cl.clrandom.rand(queue, ndofs, dtype=np.float))
elif array_type == "vector":
sym_x = sym.make_sym_array("x", dim)
x = make_obj_array([
unflatten(actx, volume_discr,
cl.clrandom.rand(queue, ndofs, dtype=np.float))
for _ in range(dim)
])
else:
raise ValueError("unknown array type")
norm = bind(discr, sym.norm(2, sym_x))(x=x)
assert isinstance(norm, float)
def test_bessel(ctx_factory):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
dims = 2
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=(0.1, ) * dims,
b=(1.0, ) * dims,
n=(8, ) * dims)
discr = DGDiscretizationWithBoundaries(actx, mesh, order=3)
nodes = sym.nodes(dims)
r = sym.cse(sym.sqrt(nodes[0]**2 + nodes[1]**2))
# https://dlmf.nist.gov/10.6.1
n = 3
bessel_zero = (sym.bessel_j(n + 1, r) + sym.bessel_j(n - 1, r) -
2 * n / r * sym.bessel_j(n, r))
z = bind(discr, sym.norm(2, bessel_zero))(actx)
assert z < 1e-15
def test_timing_data_gathering(ctx_factory):
"""Test that timing data gathering can execute succesfully."""
pytest.importorskip("pyfmmlib")
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx,
properties=cl.command_queue_properties.PROFILING_ENABLE)
actx = PyOpenCLArrayContext(queue)
lpot_source = get_lpot_source(actx, 2)
places = GeometryCollection(lpot_source)
dofdesc = places.auto_source.to_stage1()
density_discr = places.get_discretization(dofdesc.geometry)
sigma = get_density(actx, density_discr)
sigma_sym = sym.var("sigma")
k_sym = LaplaceKernel(lpot_source.ambient_dim)
sym_op_S = sym.S(k_sym, sigma_sym, qbx_forced_limit=+1)
op_S = bind(places, sym_op_S)
timing_data = {}
op_S.eval(dict(sigma=sigma), timing_data=timing_data, array_context=actx)
assert timing_data
print(timing_data)
def simple_mpi_communication_entrypoint():
cl_ctx = cl.create_some_context()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
from meshmode.distributed import MPIMeshDistributor, get_partition_by_pymetis
from meshmode.mesh import BTAG_ALL
from mpi4py import MPI
comm = MPI.COMM_WORLD
num_parts = comm.Get_size()
mesh_dist = MPIMeshDistributor(comm)
if mesh_dist.is_mananger_rank():
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=(-1, ) * 2,
b=(1, ) * 2,
nelements_per_axis=(2, ) * 2)
part_per_element = get_partition_by_pymetis(mesh, num_parts)
local_mesh = mesh_dist.send_mesh_parts(mesh, part_per_element,
num_parts)
else:
local_mesh = mesh_dist.receive_mesh_part()
vol_discr = DiscretizationCollection(actx,
local_mesh,
order=5,
mpi_communicator=comm)
sym_x = sym.nodes(local_mesh.dim)
myfunc_symb = sym.sin(np.dot(sym_x, [2, 3]))
myfunc = bind(vol_discr, myfunc_symb)(actx)
sym_all_faces_func = sym.cse(
sym.project("vol", "all_faces")(sym.var("myfunc")))
sym_int_faces_func = sym.cse(
sym.project("vol", "int_faces")(sym.var("myfunc")))
sym_bdry_faces_func = sym.cse(
sym.project(BTAG_ALL,
"all_faces")(sym.project("vol",
BTAG_ALL)(sym.var("myfunc"))))
bound_face_swap = bind(
vol_discr,
sym.project("int_faces", "all_faces")(
sym.OppositeInteriorFaceSwap("int_faces")(sym_int_faces_func)) -
(sym_all_faces_func - sym_bdry_faces_func))
hopefully_zero = bound_face_swap(myfunc=myfunc)
error = actx.np.linalg.norm(hopefully_zero, ord=np.inf)
print(__file__)
with np.printoptions(threshold=100000000, suppress=True):
logger.debug(hopefully_zero)
logger.info("error: %.5e", error)
assert error < 1e-14
def op_test_data(ctx_factory):
"""Test fixtures for lazy tests."""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
eager_actx = PyOpenCLArrayContext(
queue,
allocator=cl_tools.MemoryPool(cl_tools.ImmediateAllocator(queue)))
lazy_actx = PytatoPyOpenCLArrayContext(
queue,
allocator=cl_tools.MemoryPool(cl_tools.ImmediateAllocator(queue)))
def get_discr(order):
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(
a=(-0.5,)*2,
b=(0.5,)*2,
nelements_per_axis=(4,)*2,
boundary_tag_to_face={
"x": ["-x", "+x"],
"y": ["-y", "+y"]
})
from grudge.eager import EagerDGDiscretization
return EagerDGDiscretization(eager_actx, mesh, order=order)
return eager_actx, lazy_actx, get_discr
def main(write_output=True):
cl_ctx = cl.create_some_context()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
from meshmode.mesh import BTAG_ALL
from meshmode.mesh.generation import generate_warped_rect_mesh
mesh = generate_warped_rect_mesh(dim=2, order=4, nelements_side=6)
discr = DiscretizationCollection(actx, mesh, order=4)
sym_op = sym.normal(BTAG_ALL, mesh.dim)
# sym_op = sym.nodes(mesh.dim, dd=BTAG_ALL)
print(sym.pretty(sym_op))
op = bind(discr, sym_op)
print()
print(op.eval_code)
vec = op(actx)
vis = shortcuts.make_visualizer(discr)
vis.write_vtk_file("geo.vtu", [])
bvis = shortcuts.make_boundary_visualizer(discr)
bvis.write_vtk_file("bgeo.vtu", [("normals", vec)])
def test_chained_batch_table(ctx_factory, ndim, visualize=False):
from meshmode.discretization.connection.chained import \
_build_element_lookup_table
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
actx = PyOpenCLArrayContext(queue)
discr = create_discretization(actx, ndim)
connections = []
conn = create_refined_connection(actx, discr)
connections.append(conn)
conn = create_refined_connection(actx, conn.to_discr)
connections.append(conn)
from meshmode.discretization.connection import ChainedDiscretizationConnection
chained = ChainedDiscretizationConnection(connections)
conn = chained.connections[0]
el_table = _build_element_lookup_table(actx, conn)
for igrp, grp in enumerate(conn.groups):
for ibatch, batch in enumerate(grp.batches):
ifrom = batch.from_element_indices.get(queue)
jfrom = el_table[igrp][batch.to_element_indices.get(queue)]
assert np.all(ifrom == jfrom)
assert np.min(el_table[igrp]) >= 0
def test_stepper_timing(ctx_factory, use_fusion):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(
cl_ctx, properties=cl.command_queue_properties.PROFILING_ENABLE)
actx = PyOpenCLArrayContext(queue)
dims = 3
sym_operator, discr = get_strong_wave_op_with_discr_direct(actx,
dims=dims,
order=3)
t_start = 0
dt = 0.04
t_end = 0.1
ic = flat_obj_array(discr.zeros(actx),
[discr.zeros(actx) for i in range(discr.dim)])
if not use_fusion:
bound_op = bind(discr,
sym_operator,
exec_mapper_factory=ExecutionMapperWithTiming)
stepper = RK4TimeStepper(discr,
"w",
bound_op,
1 + discr.dim,
get_strong_wave_component,
exec_mapper_factory=ExecutionMapperWithTiming)
else:
stepper = FusedRK4TimeStepper(
discr,
"w",
sym_operator,
1 + discr.dim,
get_strong_wave_component,
exec_mapper_factory=ExecutionMapperWithTiming)
step = 0
import time
t = time.time()
nsteps = int(np.ceil((t_end + 1e-9) / dt))
for (_, _, profile_data) in stepper.run(ic,
t_start,
dt,
t_end,
return_profile_data=True):
step += 1
tn = time.time()
logger.info("step %d/%d: %f", step, nsteps, tn - t)
t = tn
logger.info("fusion? %s", use_fusion)
for key, value in profile_data.items():
if isinstance(value, TimingFutureList):
print(key, value.elapsed())
def test_pulse(ctx_factory, dim):
"""
Test of Gaussian pulse generator.
If it looks, walks, and quacks like a Gaussian, then ...
"""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
nel_1d = 10
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=(-0.5, ) * dim,
b=(0.5, ) * dim,
nelements_per_axis=(nel_1d, ) * dim)
order = 1
print(f"Number of elements: {mesh.nelements}")
discr = EagerDGDiscretization(actx, mesh, order=order)
nodes = thaw(actx, discr.nodes())
print(f"DIM = {dim}, {len(nodes)}")
print(f"Nodes={nodes}")
tol = 1e-15
from mirgecom.initializers import make_pulse
amp = 1.0
w = .1
rms2 = w * w
r0 = np.zeros(dim)
r2 = np.dot(nodes, nodes) / rms2
pulse = make_pulse(amp=amp, r0=r0, w=w, r=nodes)
print(f"Pulse = {pulse}")
# does it return the expected exponential?
pulse_check = actx.np.exp(-.5 * r2)
print(f"exact: {pulse_check}")
pulse_resid = pulse - pulse_check
print(f"pulse residual: {pulse_resid}")
assert (discr.norm(pulse_resid, np.inf) < tol)
# proper scaling with amplitude?
amp = 2.0
pulse = 0
pulse = make_pulse(amp=amp, r0=r0, w=w, r=nodes)
pulse_resid = pulse - (pulse_check + pulse_check)
assert (discr.norm(pulse_resid, np.inf) < tol)
# proper scaling with r?
amp = 1.0
rcheck = np.sqrt(2.0) * nodes
pulse = make_pulse(amp=amp, r0=r0, w=w, r=rcheck)
assert (discr.norm(pulse - (pulse_check * pulse_check), np.inf) < tol)
# proper scaling with w?
w = w / np.sqrt(2.0)
pulse = make_pulse(amp=amp, r0=r0, w=w, r=nodes)
assert (discr.norm(pulse - (pulse_check * pulse_check), np.inf) < tol)
def test_unregularized_with_ones_kernel(ctx_factory):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
nelements = 10
order = 8
mesh = make_curve_mesh(partial(ellipse, 1),
np.linspace(0, 1, nelements+1),
order)
from meshmode.discretization import Discretization
from meshmode.discretization.poly_element import \
InterpolatoryQuadratureSimplexGroupFactory
discr = Discretization(actx, mesh,
InterpolatoryQuadratureSimplexGroupFactory(order))
from pytential.unregularized import UnregularizedLayerPotentialSource
lpot_source = UnregularizedLayerPotentialSource(discr)
from pytential.target import PointsTarget
targets = PointsTarget(np.zeros((2, 1), dtype=float))
places = GeometryCollection({
sym.DEFAULT_SOURCE: lpot_source,
sym.DEFAULT_TARGET: lpot_source,
"target_non_self": targets})
from sumpy.kernel import one_kernel_2d
sigma_sym = sym.var("sigma")
op = sym.IntG(one_kernel_2d, sigma_sym, qbx_forced_limit=None)
sigma = discr.zeros(actx) + 1
result_self = bind(places, op,
auto_where=places.auto_where)(
actx, sigma=sigma)
result_nonself = bind(places, op,
auto_where=(places.auto_source, "target_non_self"))(
actx, sigma=sigma)
from meshmode.dof_array import flatten
assert np.allclose(actx.to_numpy(flatten(result_self)), 2 * np.pi)
assert np.allclose(actx.to_numpy(result_nonself), 2 * np.pi)
def _visualize_refinement(actx: PyOpenCLArrayContext,
discr,
niter,
stage_nr,
stage_name,
flags,
visualize=False):
if not visualize:
return
if stage_nr not in (1, 2):
raise ValueError("unexpected stage number")
flags = flags.get()
logger.info("for stage %s: splitting %d/%d stage-%d elements", stage_name,
np.sum(flags), discr.mesh.nelements, stage_nr)
from meshmode.discretization.visualization import make_visualizer
vis = make_visualizer(actx, discr, 3)
assert len(flags) == discr.mesh.nelements
flags = flags.astype(bool)
nodes_flags_template = discr.zeros(actx)
nodes_flags = []
for grp in discr.groups:
meg = grp.mesh_el_group
nodes_flags_grp = actx.to_numpy(nodes_flags_template[grp.index])
nodes_flags_grp[flags[meg.element_nr_base:meg.nelements +
meg.element_nr_base]] = 1
nodes_flags.append(actx.from_numpy(nodes_flags_grp))
nodes_flags = DOFArray(actx, tuple(nodes_flags))
vis_data = [
("refine_flags", nodes_flags),
]
if 0:
from pytential import sym, bind
bdry_normals = bind(discr, sym.normal(
discr.ambient_dim))(actx).as_vector(dtype=object)
vis_data.append(("bdry_normals", bdry_normals), )
vis.write_vtk_file(f"refinement-{stage_name}-{niter:03d}.vtu", vis_data)
def test_cost_model_order_varying_by_level(ctx_factory):
"""For FMM order varying by level, this checks to ensure that the costs are
different. The varying-level case should have larger cost.
"""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
# {{{ constant level to order
def level_to_order_constant(kernel, kernel_args, tree, level):
return 1
lpot_source = get_lpot_source(actx, 2).copy(
cost_model=QBXCostModel(),
fmm_level_to_order=level_to_order_constant)
places = GeometryCollection(lpot_source)
density_discr = places.get_discretization(places.auto_source.geometry)
sigma_sym = sym.var("sigma")
k_sym = LaplaceKernel(2)
sym_op = sym.S(k_sym, sigma_sym, qbx_forced_limit=+1)
sigma = get_density(actx, density_discr)
cost_constant, metadata = bind(places, sym_op).cost_per_stage(
"constant_one", sigma=sigma)
cost_constant = one(cost_constant.values())
metadata = one(metadata.values())
# }}}
# {{{ varying level to order
def level_to_order_varying(kernel, kernel_args, tree, level):
return metadata["nlevels"] - level
lpot_source = get_lpot_source(actx, 2).copy(
cost_model=QBXCostModel(),
fmm_level_to_order=level_to_order_varying)
places = GeometryCollection(lpot_source)
density_discr = places.get_discretization(places.auto_source.geometry)
sigma = get_density(actx, density_discr)
cost_varying, _ = bind(lpot_source, sym_op).cost_per_stage(
"constant_one", sigma=sigma)
cost_varying = one(cost_varying.values())
# }}}
assert sum(cost_varying.values()) > sum(cost_constant.values())
def test_stepper_mem_ops(ctx_factory, use_fusion):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
dims = 2
sym_operator, discr = get_strong_wave_op_with_discr_direct(actx,
dims=dims,
order=3)
t_start = 0
dt = 0.04
t_end = 0.2
ic = flat_obj_array(discr.zeros(actx),
[discr.zeros(actx) for i in range(discr.dim)])
if not use_fusion:
bound_op = bind(discr,
sym_operator,
exec_mapper_factory=ExecutionMapperWithMemOpCounting)
stepper = RK4TimeStepper(
discr,
"w",
bound_op,
1 + discr.dim,
get_strong_wave_component,
exec_mapper_factory=ExecutionMapperWithMemOpCounting)
else:
stepper = FusedRK4TimeStepper(
discr,
"w",
sym_operator,
1 + discr.dim,
get_strong_wave_component,
exec_mapper_factory=ExecutionMapperWithMemOpCounting)
step = 0
nsteps = int(np.ceil((t_end + 1e-9) / dt))
for (_, _, profile_data) in stepper.run(ic,
t_start,
dt,
t_end,
return_profile_data=True):
step += 1
logger.info("step %d/%d", step, nsteps)
logger.info("using fusion? %s", use_fusion)
logger.info("bytes read: %d", profile_data["bytes_read"])
logger.info("bytes written: %d", profile_data["bytes_written"])
logger.info("bytes total: %d",
profile_data["bytes_read"] + profile_data["bytes_written"])
def _acf():
"""A tiny undocumented function to pass to tests that take an ``actx_factory``
argument when running them from the command line.
"""
import pyopencl as cl
from meshmode.array_context import PyOpenCLArrayContext
context = cl._csc()
queue = cl.CommandQueue(context)
return PyOpenCLArrayContext(queue)
def main():
cl_ctx = cl.create_some_context()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
dim = 2
nel_1d = 16
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(
a=(-0.5,)*dim,
b=(0.5,)*dim,
n=(nel_1d,)*dim)
order = 3
if dim == 2:
# no deep meaning here, just a fudge factor
dt = 0.75/(nel_1d*order**2)
elif dim == 3:
# no deep meaning here, just a fudge factor
dt = 0.45/(nel_1d*order**2)
else:
raise ValueError("don't have a stable time step guesstimate")
print("%d elements" % mesh.nelements)
discr = EagerDGDiscretization(actx, mesh, order=order)
fields = flat_obj_array(
bump(discr, actx),
[discr.zeros(actx) for i in range(discr.dim)]
)
vis = make_visualizer(discr, order+3 if dim == 2 else order)
def rhs(t, w):
return wave_operator(discr, c=1, w=w)
t = 0
t_final = 3
istep = 0
while t < t_final:
fields = rk4_step(fields, t, dt, rhs)
if istep % 10 == 0:
print(f"step: {istep} t: {t} L2: {discr.norm(fields[0])} "
f"sol max: {discr.nodal_max('vol', fields[0])}")
vis.write_vtk_file("fld-wave-eager-%04d.vtu" % istep,
[
("u", fields[0]),
("v", fields[1:]),
])
t += dt
istep += 1
