def no_test_tri_mass_mat_gauss(self):
"""Check the integral of a Gaussian on a disk using the mass matrix"""
# This is a bad test, since it's never exact. The Gaussian has infinite support,
# and this *does* matter numerically.
from hedge.mesh.generator import make_disk_mesh
from hedge.discretization.local import TriangleDiscretization
from math import sqrt, exp, pi
sigma_squared = 1 / 219.3
mesh = make_disk_mesh()
discr = self.discr_class(
make_disk_mesh(), TriangleDiscretization(4), debug=self.discr_class.noninteractive_debug_flags()
)
f = discr.interpolate_volume_function(lambda x, el: exp(-x * x / (2 * sigma_squared)))
ones = discr.interpolate_volume_function(lambda x, el: 1)
# discr.visualize_vtk("gaussian.vtk", [("f", f)])
num_integral_1 = ones * (discr.mass_operator * f)
num_integral_2 = f * (discr.mass_operator * ones)
dim = 2
true_integral = (2 * pi) ** (dim / 2) * sqrt(sigma_squared) ** dim
err_1 = abs(num_integral_1 - true_integral)
err_2 = abs(num_integral_2 - true_integral)
self.assert_(err_1 < 1e-11)
self.assert_(err_2 < 1e-11)
def test_tri_diff_mat():
"""Check differentiation matrix along the coordinate axes on a disk
Uses sines as the function to differentiate.
"""
from hedge.mesh.generator import make_disk_mesh
from hedge.discretization.local import TriangleDiscretization
from math import sin, cos, sqrt
from hedge.optemplate import make_nabla
nabla = make_nabla(2)
for coord in [0, 1]:
mesh = make_disk_mesh()
discr = discr_class(make_disk_mesh(), TriangleDiscretization(4), debug=discr_class.noninteractive_debug_flags())
f = discr.interpolate_volume_function(lambda x, el: sin(3 * x[coord]))
df = discr.interpolate_volume_function(lambda x, el: 3 * cos(3 * x[coord]))
df_num = nabla[coord].apply(discr, f)
# discr.visualize_vtk("diff-err.vtk",
# [("f", f), ("df", df), ("df_num", df_num), ("error", error)])
linf_error = la.norm(df_num - df, numpy.Inf)
print linf_error
assert linf_error < 4e-5
def test_tri_diff_mat():
"""Check differentiation matrix along the coordinate axes on a disk
Uses sines as the function to differentiate.
"""
from hedge.mesh.generator import make_disk_mesh
from hedge.discretization.local import TriangleDiscretization
from math import sin, cos
from hedge.optemplate import make_nabla
nabla = make_nabla(2)
for coord in [0, 1]:
discr = discr_class(make_disk_mesh(),
TriangleDiscretization(4),
debug=discr_class.noninteractive_debug_flags())
f = discr.interpolate_volume_function(lambda x, el: sin(3 * x[coord]))
df = discr.interpolate_volume_function(
lambda x, el: 3 * cos(3 * x[coord]))
df_num = nabla[coord].apply(discr, f)
#discr.visualize_vtk("diff-err.vtk",
#[("f", f), ("df", df), ("df_num", df_num), ("error", error)])
linf_error = la.norm(df_num - df, numpy.Inf)
print linf_error
assert linf_error < 4e-5
def no_test_tri_mass_mat_gauss(self):
"""Check the integral of a Gaussian on a disk using the mass matrix"""
# This is a bad test, since it's never exact. The Gaussian has infinite support,
# and this *does* matter numerically.
from hedge.mesh.generator import make_disk_mesh
from hedge.discretization.local import TriangleDiscretization
from math import sqrt, exp, pi
sigma_squared = 1 / 219.3
discr = self.discr_class(
make_disk_mesh(),
TriangleDiscretization(4),
debug=self.discr_class.noninteractive_debug_flags())
f = discr.interpolate_volume_function(
lambda x, el: exp(-x * x / (2 * sigma_squared)))
ones = discr.interpolate_volume_function(lambda x, el: 1)
#discr.visualize_vtk("gaussian.vtk", [("f", f)])
num_integral_1 = ones * (discr.mass_operator * f)
num_integral_2 = f * (discr.mass_operator * ones)
dim = 2
true_integral = (2 * pi)**(dim / 2) * sqrt(sigma_squared)**dim
err_1 = abs(num_integral_1 - true_integral)
err_2 = abs(num_integral_2 - true_integral)
self.assert_(err_1 < 1e-11)
self.assert_(err_2 < 1e-11)
def test_projection():
"""Test whether projection between different orders works"""
from hedge.mesh.generator import make_disk_mesh
from hedge.discretization import Projector
from hedge.discretization.local import TriangleDiscretization
from math import sin, pi
from numpy import dot
a = numpy.array([1, 3])
def u_analytic(x, el):
return sin(dot(a, x))
mesh = make_disk_mesh(r=pi, max_area=0.5)
discr2 = discr_class(mesh,
TriangleDiscretization(2),
debug=discr_class.noninteractive_debug_flags())
discr5 = discr_class(mesh,
TriangleDiscretization(5),
debug=discr_class.noninteractive_debug_flags())
p2to5 = Projector(discr2, discr5)
p5to2 = Projector(discr5, discr2)
u2 = discr2.interpolate_volume_function(u_analytic)
u2_i = p5to2(p2to5(u2))
assert discr2.norm(u2 - u2_i) < 3e-15
def test_projection():
"""Test whether projection between different orders works"""
from hedge.mesh.generator import make_disk_mesh
from hedge.discretization import Projector
from hedge.discretization.local import TriangleDiscretization
from hedge.tools import EOCRecorder
from math import sin, pi, sqrt
from numpy import dot
a = numpy.array([1, 3])
def u_analytic(x, el):
return sin(dot(a, x))
mesh = make_disk_mesh(r=pi, max_area=0.5)
discr2 = discr_class(mesh, TriangleDiscretization(2), debug=discr_class.noninteractive_debug_flags())
discr5 = discr_class(mesh, TriangleDiscretization(5), debug=discr_class.noninteractive_debug_flags())
p2to5 = Projector(discr2, discr5)
p5to2 = Projector(discr5, discr2)
u2 = discr2.interpolate_volume_function(u_analytic)
u2_i = p5to2(p2to5(u2))
assert discr2.norm(u2 - u2_i) < 3e-15
def test_filter():
"""Exercise mode-based filtering."""
from hedge.mesh.generator import make_disk_mesh
from hedge.discretization.local import TriangleDiscretization
from math import sin
mesh = make_disk_mesh(r=3.4, max_area=0.5)
discr = discr_class(mesh,
TriangleDiscretization(5),
debug=discr_class.noninteractive_debug_flags())
from hedge.optemplate.operators import FilterOperator
from hedge.discretization import ExponentialFilterResponseFunction
half_filter = FilterOperator(lambda mid, ldis: 0.5)
for eg in discr.element_groups:
fmat = half_filter.matrix(eg)
n, m = fmat.shape
assert la.norm(fmat - 0.5 * numpy.eye(n, m)) < 2e-15
from numpy import dot
def test_freq(n):
a = numpy.array([1, n])
def u_analytic(x, el):
return sin(dot(a, x))
exp_filter = FilterOperator(ExponentialFilterResponseFunction(0.9, 3)) \
.bind(discr)
u = discr.interpolate_volume_function(u_analytic)
filt_u = exp_filter(u)
int_error = abs(discr.integral(u) - discr.integral(filt_u))
l2_ratio = discr.norm(filt_u) / discr.norm(u)
assert int_error < 1e-14
assert 0.96 < l2_ratio < 0.99999
test_freq(3)
test_freq(5)
test_freq(9)
test_freq(17)
def test_filter():
"""Exercise mode-based filtering."""
from hedge.mesh.generator import make_disk_mesh
from hedge.discretization.local import TriangleDiscretization
from math import sin
mesh = make_disk_mesh(r=3.4, max_area=0.5)
discr = discr_class(mesh, TriangleDiscretization(5),
debug=discr_class.noninteractive_debug_flags())
from hedge.optemplate.operators import FilterOperator
from hedge.discretization import ExponentialFilterResponseFunction
half_filter = FilterOperator(lambda mid, ldis: 0.5)
for eg in discr.element_groups:
fmat = half_filter.matrix(eg)
n, m = fmat.shape
assert la.norm(fmat - 0.5*numpy.eye(n, m)) < 2e-15
from numpy import dot
def test_freq(n):
a = numpy.array([1, n])
def u_analytic(x, el):
return sin(dot(a, x))
exp_filter = FilterOperator(ExponentialFilterResponseFunction(0.9, 3)) \
.bind(discr)
u = discr.interpolate_volume_function(u_analytic)
filt_u = exp_filter(u)
int_error = abs(discr.integral(u) - discr.integral(filt_u))
l2_ratio = discr.norm(filt_u) / discr.norm(u)
assert int_error < 1e-14
assert 0.96 < l2_ratio < 0.99999
test_freq(3)
test_freq(5)
test_freq(9)
test_freq(17)
def main(write_output=True, flux_type_arg="upwind"):
from hedge.tools import mem_checkpoint
from math import sin, cos, pi, sqrt
from math import floor
from hedge.backends import guess_run_context
rcon = guess_run_context()
def f(x):
return sin(pi*x)
def u_analytic(x, el, t):
return f((-numpy.dot(v, x)/norm_v+t*norm_v))
def boundary_tagger(vertices, el, face_nr, all_v):
if numpy.dot(el.face_normals[face_nr], v) < 0:
return ["inflow"]
else:
return ["outflow"]
dim = 2
if dim == 1:
v = numpy.array([1])
if rcon.is_head_rank:
from hedge.mesh.generator import make_uniform_1d_mesh
mesh = make_uniform_1d_mesh(0, 2, 10, periodic=True)
elif dim == 2:
v = numpy.array([2,0])
if rcon.is_head_rank:
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(boundary_tagger=boundary_tagger)
elif dim == 3:
v = numpy.array([0,0,1])
if rcon.is_head_rank:
from hedge.mesh.generator import make_cylinder_mesh, make_ball_mesh, make_box_mesh
mesh = make_cylinder_mesh(max_volume=0.04, height=2, boundary_tagger=boundary_tagger,
periodic=False, radial_subdivisions=32)
else:
raise RuntimeError, "bad number of dimensions"
norm_v = la.norm(v)
if rcon.is_head_rank:
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
if dim != 1:
mesh_data = mesh_data.reordered_by("cuthill")
discr = rcon.make_discretization(mesh_data, order=4)
vis_discr = discr
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(vis_discr, rcon, "fld")
# operator setup ----------------------------------------------------------
from hedge.data import \
ConstantGivenFunction, \
TimeConstantGivenFunction, \
TimeDependentGivenFunction
from hedge.models.advection import StrongAdvectionOperator, WeakAdvectionOperator
op = WeakAdvectionOperator(v,
inflow_u=TimeDependentGivenFunction(u_analytic),
flux_type=flux_type_arg)
u = discr.interpolate_volume_function(lambda x, el: u_analytic(x, el, 0))
# timestep setup ----------------------------------------------------------
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper()
if rcon.is_head_rank:
print "%d elements" % len(discr.mesh.elements)
# diagnostics setup -------------------------------------------------------
from pytools.log import LogManager, \
add_general_quantities, \
add_simulation_quantities, \
add_run_info
if write_output:
log_file_name = "advection.dat"
else:
log_file_name = None
logmgr = LogManager(log_file_name, "w", rcon.communicator)
add_run_info(logmgr)
add_general_quantities(logmgr)
add_simulation_quantities(logmgr)
discr.add_instrumentation(logmgr)
stepper.add_instrumentation(logmgr)
from hedge.log import Integral, LpNorm
u_getter = lambda: u
logmgr.add_quantity(Integral(u_getter, discr, name="int_u"))
logmgr.add_quantity(LpNorm(u_getter, discr, p=1, name="l1_u"))
logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))
logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])
# timestep loop -----------------------------------------------------------
rhs = op.bind(discr)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=3, logmgr=logmgr,
max_dt_getter=lambda t: op.estimate_timestep(discr,
stepper=stepper, t=t, fields=u))
for step, t, dt in step_it:
if step % 5 == 0 and write_output:
visf = vis.make_file("fld-%04d" % step)
vis.add_data(visf, [
("u", discr.convert_volume(u, kind="numpy")),
], time=t, step=step)
visf.close()
u = stepper(u, t, dt, rhs)
true_u = discr.interpolate_volume_function(lambda x, el: u_analytic(x, el, t))
print discr.norm(u-true_u)
assert discr.norm(u-true_u) < 1e-2
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
def main(write_output=True):
from hedge.data import GivenFunction, ConstantGivenFunction
from hedge.backends import guess_run_context
rcon = guess_run_context()
dim = 2
def boundary_tagger(fvi, el, fn, points):
from math import atan2, pi
normal = el.face_normals[fn]
if -90/180*pi < atan2(normal[1], normal[0]) < 90/180*pi:
return ["neumann"]
else:
return ["dirichlet"]
if dim == 2:
if rcon.is_head_rank:
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(r=0.5, boundary_tagger=boundary_tagger,
max_area=1e-2)
elif dim == 3:
if rcon.is_head_rank:
from hedge.mesh.generator import make_ball_mesh
mesh = make_ball_mesh(max_volume=0.0001,
boundary_tagger=lambda fvi, el, fn, points:
["dirichlet"])
else:
raise RuntimeError, "bad number of dimensions"
if rcon.is_head_rank:
print "%d elements" % len(mesh.elements)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
discr = rcon.make_discretization(mesh_data, order=5,
debug=[])
def dirichlet_bc(x, el):
from math import sin
return sin(10*x[0])
def rhs_c(x, el):
if la.norm(x) < 0.1:
return 1000
else:
return 0
def my_diff_tensor():
result = numpy.eye(dim)
result[0,0] = 0.1
return result
try:
from hedge.models.poisson import PoissonOperator
from hedge.second_order import \
IPDGSecondDerivative, LDGSecondDerivative, \
StabilizedCentralSecondDerivative
from hedge.mesh import TAG_NONE, TAG_ALL
op = PoissonOperator(discr.dimensions,
diffusion_tensor=my_diff_tensor(),
#dirichlet_tag="dirichlet",
#neumann_tag="neumann",
dirichlet_tag=TAG_ALL,
neumann_tag=TAG_NONE,
#dirichlet_tag=TAG_ALL,
#neumann_tag=TAG_NONE,
dirichlet_bc=GivenFunction(dirichlet_bc),
neumann_bc=ConstantGivenFunction(-10),
scheme=StabilizedCentralSecondDerivative(),
#scheme=LDGSecondDerivative(),
#scheme=IPDGSecondDerivative(),
)
bound_op = op.bind(discr)
from hedge.iterative import parallel_cg
u = -parallel_cg(rcon, -bound_op,
bound_op.prepare_rhs(discr.interpolate_volume_function(rhs_c)),
debug=20, tol=5e-4,
dot=discr.nodewise_dot_product,
x=discr.volume_zeros())
if write_output:
from hedge.visualization import SiloVisualizer, VtkVisualizer
vis = VtkVisualizer(discr, rcon)
visf = vis.make_file("fld")
vis.add_data(visf, [ ("sol", discr.convert_volume(u, kind="numpy")), ])
visf.close()
finally:
discr.close()
def main(write_output=True):
from math import sin, cos, pi, exp, sqrt
from hedge.data import TimeConstantGivenFunction, \
ConstantGivenFunction
from hedge.backends import guess_run_context
rcon = guess_run_context()
dim = 2
def boundary_tagger(fvi, el, fn, all_v):
if el.face_normals[fn][0] > 0:
return ["dirichlet"]
else:
return ["neumann"]
if dim == 2:
if rcon.is_head_rank:
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(r=0.5, boundary_tagger=boundary_tagger)
elif dim == 3:
if rcon.is_head_rank:
from hedge.mesh.generator import make_ball_mesh
mesh = make_ball_mesh(max_volume=0.001)
else:
raise RuntimeError, "bad number of dimensions"
if rcon.is_head_rank:
print "%d elements" % len(mesh.elements)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
discr = rcon.make_discretization(mesh_data,
order=3,
debug=["cuda_no_plan"],
default_scalar_type=numpy.float64)
if write_output:
from hedge.visualization import VtkVisualizer
vis = VtkVisualizer(discr, rcon, "fld")
def u0(x, el):
if la.norm(x) < 0.2:
return 1
else:
return 0
def coeff(x, el):
if x[0] < 0:
return 0.25
else:
return 1
def dirichlet_bc(t, x):
return 0
def neumann_bc(t, x):
return 2
from hedge.models.diffusion import DiffusionOperator
op = DiffusionOperator(
discr.dimensions,
#coeff=coeff,
dirichlet_tag="dirichlet",
dirichlet_bc=TimeConstantGivenFunction(ConstantGivenFunction(0)),
neumann_tag="neumann",
neumann_bc=TimeConstantGivenFunction(ConstantGivenFunction(1)))
u = discr.interpolate_volume_function(u0)
# diagnostics setup -------------------------------------------------------
from pytools.log import LogManager, \
add_general_quantities, \
add_simulation_quantities, \
add_run_info
if write_output:
log_file_name = "heat.dat"
else:
log_file_name = None
logmgr = LogManager(log_file_name, "w", rcon.communicator)
add_run_info(logmgr)
add_general_quantities(logmgr)
add_simulation_quantities(logmgr)
discr.add_instrumentation(logmgr)
from hedge.log import LpNorm
u_getter = lambda: u
logmgr.add_quantity(LpNorm(u_getter, discr, 1, name="l1_u"))
logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))
logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])
# timestep loop -----------------------------------------------------------
from hedge.timestep.runge_kutta import LSRK4TimeStepper, ODE45TimeStepper
from hedge.timestep.dumka3 import Dumka3TimeStepper
#stepper = LSRK4TimeStepper()
stepper = Dumka3TimeStepper(
3,
rtol=1e-6,
rcon=rcon,
vector_primitive_factory=discr.get_vector_primitive_factory(),
dtype=discr.default_scalar_type)
#stepper = ODE45TimeStepper(rtol=1e-6, rcon=rcon,
#vector_primitive_factory=discr.get_vector_primitive_factory(),
#dtype=discr.default_scalar_type)
stepper.add_instrumentation(logmgr)
rhs = op.bind(discr)
try:
next_dt = op.estimate_timestep(discr,
stepper=LSRK4TimeStepper(),
t=0,
fields=u)
from hedge.timestep import times_and_steps
step_it = times_and_steps(final_time=0.1,
logmgr=logmgr,
max_dt_getter=lambda t: next_dt,
taken_dt_getter=lambda: taken_dt)
for step, t, dt in step_it:
if step % 10 == 0 and write_output:
visf = vis.make_file("fld-%04d" % step)
vis.add_data(visf, [
("u", discr.convert_volume(u, kind="numpy")),
],
time=t,
step=step)
visf.close()
u, t, taken_dt, next_dt = stepper(u, t, next_dt, rhs)
#u = stepper(u, t, dt, rhs)
assert discr.norm(u) < 1
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
def test_convergence_advec_2d():
"""Test whether 2D advection actually converges"""
import pyublas
from hedge.mesh.generator import make_disk_mesh, make_regular_rect_mesh
from hedge.discretization.local import TriangleDiscretization
from hedge.timestep import RK4TimeStepper
from hedge.tools import EOCRecorder
from math import sin, pi, sqrt
from hedge.models.advection import StrongAdvectionOperator
from hedge.data import TimeDependentGivenFunction
v = numpy.array([0.27, 0])
norm_a = la.norm(v)
from numpy import dot
def f(x):
return sin(x)
def u_analytic(x, el, t):
return f((-dot(v, x) / norm_a + t * norm_a))
def boundary_tagger(vertices, el, face_nr, all_v):
if dot(el.face_normals[face_nr], v) < 0:
return ["inflow"]
else:
return ["outflow"]
for mesh in [
# non-periodic
make_disk_mesh(r=pi, boundary_tagger=boundary_tagger, max_area=0.5),
# periodic
make_regular_rect_mesh(
a=(0, 0), b=(2 * pi, 1), n=(8, 4), periodicity=(True, False), boundary_tagger=boundary_tagger
),
]:
for flux_type in StrongAdvectionOperator.flux_types:
eoc_rec = EOCRecorder()
for order in [1, 2, 3, 4, 5, 6]:
discr = discr_class(mesh, TriangleDiscretization(order), debug=discr_class.noninteractive_debug_flags())
op = StrongAdvectionOperator(v, inflow_u=TimeDependentGivenFunction(u_analytic), flux_type=flux_type)
u = discr.interpolate_volume_function(lambda x, el: u_analytic(x, el, 0))
stepper = RK4TimeStepper()
dt = op.estimate_timestep(discr, stepper=stepper)
nsteps = int(1 / dt)
rhs = op.bind(discr)
for step in range(nsteps):
u = stepper(u, step * dt, dt, rhs)
u_true = discr.interpolate_volume_function(lambda x, el: u_analytic(x, el, nsteps * dt))
error = u - u_true
error_l2 = discr.norm(error)
eoc_rec.add_data_point(order, error_l2)
if False:
print "%s\n%s\n" % (flux_type.upper(), "-" * len(flux_type))
print eoc_rec.pretty_print(abscissa_label="Poly. Order", error_label="L2 Error")
assert eoc_rec.estimate_order_of_convergence()[0, 1] > 4
assert eoc_rec.estimate_order_of_convergence(2)[-1, 1] > 10
def test_2d_gauss_theorem():
"""Verify Gauss's theorem explicitly on a mesh"""
from hedge.mesh.generator import make_disk_mesh
from math import sin, cos, sqrt, exp, pi
from numpy import dot
mesh = make_disk_mesh()
order = 2
discr = discr_class(mesh, order=order, debug=discr_class.noninteractive_debug_flags())
ref_discr = discr_class(mesh, order=order)
from hedge.flux import make_normal, FluxScalarPlaceholder
normal = make_normal(discr.dimensions)
flux_f_ph = FluxScalarPlaceholder(0)
one_sided_x = flux_f_ph.int * normal[0]
one_sided_y = flux_f_ph.int * normal[1]
def f1(x, el):
return sin(3 * x[0]) + cos(3 * x[1])
def f2(x, el):
return sin(2 * x[0]) + cos(x[1])
from hedge.discretization import ones_on_volume
ones = ones_on_volume(discr)
f1_v = discr.interpolate_volume_function(f1)
f2_v = discr.interpolate_volume_function(f2)
from hedge.optemplate import BoundaryPair, Field, make_nabla, get_flux_operator
nabla = make_nabla(discr.dimensions)
diff_optp = nabla[0] * Field("f1") + nabla[1] * Field("f2")
divergence = nabla[0].apply(discr, f1_v) + nabla[1].apply(discr, f2_v)
int_div = discr.integral(divergence)
flux_optp = get_flux_operator(one_sided_x)(BoundaryPair(Field("f1"), Field("fz"))) + get_flux_operator(one_sided_y)(
BoundaryPair(Field("f2"), Field("fz"))
)
from hedge.mesh import TAG_ALL
bdry_val = discr.compile(flux_optp)(f1=f1_v, f2=f2_v, fz=discr.boundary_zeros(TAG_ALL))
ref_bdry_val = ref_discr.compile(flux_optp)(f1=f1_v, f2=f2_v, fz=discr.boundary_zeros(TAG_ALL))
boundary_int = dot(bdry_val, ones)
if False:
from hedge.visualization import SiloVisualizer
vis = SiloVisualizer(discr)
visf = vis.make_file("test")
from hedge.tools import make_obj_array
from hedge.mesh import TAG_ALL
vis.add_data(
visf,
[
("bdry", bdry_val),
("ref_bdry", ref_bdry_val),
("div", divergence),
("f", make_obj_array([f1_v, f2_v])),
("n", discr.volumize_boundary_field(discr.boundary_normals(TAG_ALL), TAG_ALL)),
],
expressions=[("bdiff", "bdry-ref_bdry")],
)
# print abs(boundary_int-int_div)
assert abs(boundary_int - int_div) < 5e-15
def main(write_output=True):
from hedge.data import GivenFunction, ConstantGivenFunction
from hedge.backends import guess_run_context
rcon = guess_run_context()
dim = 2
def boundary_tagger(fvi, el, fn, points):
from math import atan2, pi
normal = el.face_normals[fn]
if -90 / 180 * pi < atan2(normal[1], normal[0]) < 90 / 180 * pi:
return ["neumann"]
else:
return ["dirichlet"]
if dim == 2:
if rcon.is_head_rank:
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(r=0.5,
boundary_tagger=boundary_tagger,
max_area=1e-2)
elif dim == 3:
if rcon.is_head_rank:
from hedge.mesh.generator import make_ball_mesh
mesh = make_ball_mesh(
max_volume=0.0001,
boundary_tagger=lambda fvi, el, fn, points: ["dirichlet"])
else:
raise RuntimeError, "bad number of dimensions"
if rcon.is_head_rank:
print "%d elements" % len(mesh.elements)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
discr = rcon.make_discretization(mesh_data, order=5, debug=[])
def dirichlet_bc(x, el):
from math import sin
return sin(10 * x[0])
def rhs_c(x, el):
if la.norm(x) < 0.1:
return 1000
else:
return 0
def my_diff_tensor():
result = numpy.eye(dim)
result[0, 0] = 0.1
return result
try:
from hedge.models.poisson import PoissonOperator
from hedge.second_order import \
IPDGSecondDerivative, LDGSecondDerivative, \
StabilizedCentralSecondDerivative
from hedge.mesh import TAG_NONE, TAG_ALL
op = PoissonOperator(
discr.dimensions,
diffusion_tensor=my_diff_tensor(),
#dirichlet_tag="dirichlet",
#neumann_tag="neumann",
dirichlet_tag=TAG_ALL,
neumann_tag=TAG_NONE,
#dirichlet_tag=TAG_ALL,
#neumann_tag=TAG_NONE,
dirichlet_bc=GivenFunction(dirichlet_bc),
neumann_bc=ConstantGivenFunction(-10),
scheme=StabilizedCentralSecondDerivative(),
#scheme=LDGSecondDerivative(),
#scheme=IPDGSecondDerivative(),
)
bound_op = op.bind(discr)
from hedge.iterative import parallel_cg
u = -parallel_cg(rcon,
-bound_op,
bound_op.prepare_rhs(
discr.interpolate_volume_function(rhs_c)),
debug=20,
tol=5e-4,
dot=discr.nodewise_dot_product,
x=discr.volume_zeros())
if write_output:
from hedge.visualization import SiloVisualizer, VtkVisualizer
vis = VtkVisualizer(discr, rcon)
visf = vis.make_file("fld")
vis.add_data(visf, [
("sol", discr.convert_volume(u, kind="numpy")),
])
visf.close()
finally:
discr.close()
def test_2d_gauss_theorem():
"""Verify Gauss's theorem explicitly on a mesh"""
from hedge.mesh.generator import make_disk_mesh
from math import sin, cos
from numpy import dot
mesh = make_disk_mesh()
order = 2
discr = discr_class(mesh,
order=order,
debug=discr_class.noninteractive_debug_flags())
ref_discr = discr_class(mesh, order=order)
from hedge.flux import make_normal, FluxScalarPlaceholder
normal = make_normal(discr.dimensions)
flux_f_ph = FluxScalarPlaceholder(0)
one_sided_x = flux_f_ph.int * normal[0]
one_sided_y = flux_f_ph.int * normal[1]
def f1(x, el):
return sin(3 * x[0]) + cos(3 * x[1])
def f2(x, el):
return sin(2 * x[0]) + cos(x[1])
from hedge.discretization import ones_on_volume
ones = ones_on_volume(discr)
f1_v = discr.interpolate_volume_function(f1)
f2_v = discr.interpolate_volume_function(f2)
from hedge.optemplate import BoundaryPair, Field, make_nabla, \
get_flux_operator
nabla = make_nabla(discr.dimensions)
divergence = nabla[0].apply(discr, f1_v) + nabla[1].apply(discr, f2_v)
int_div = discr.integral(divergence)
flux_optp = (
get_flux_operator(one_sided_x)(BoundaryPair(Field("f1"),
Field("fz"))) +
get_flux_operator(one_sided_y)(BoundaryPair(Field("f2"), Field("fz"))))
from hedge.mesh import TAG_ALL
bdry_val = discr.compile(flux_optp)(f1=f1_v,
f2=f2_v,
fz=discr.boundary_zeros(TAG_ALL))
ref_bdry_val = ref_discr.compile(flux_optp)(
f1=f1_v, f2=f2_v, fz=discr.boundary_zeros(TAG_ALL))
boundary_int = dot(bdry_val, ones)
if False:
from hedge.visualization import SiloVisualizer
vis = SiloVisualizer(discr)
visf = vis.make_file("test")
from hedge.tools import make_obj_array
from hedge.mesh import TAG_ALL
vis.add_data(visf, [
("bdry", bdry_val),
("ref_bdry", ref_bdry_val),
("div", divergence),
("f", make_obj_array([f1_v, f2_v])),
("n",
discr.volumize_boundary_field(discr.boundary_normals(TAG_ALL),
TAG_ALL)),
],
expressions=[("bdiff", "bdry-ref_bdry")])
#print abs(boundary_int-int_div)
assert abs(boundary_int - int_div) < 5e-15
def test_elliptic():
"""Test various properties of elliptic operators."""
from hedge.tools import unit_vector
def matrix_rep(op):
h, w = op.shape
mat = numpy.zeros(op.shape)
for j in range(w):
mat[:, j] = op(unit_vector(w, j))
return mat
def check_grad_mat():
import pyublas
if not pyublas.has_sparse_wrappers():
return
grad_mat = op.grad_matrix()
# print len(discr), grad_mat.nnz, type(grad_mat)
for i in range(10):
u = numpy.random.randn(len(discr))
mat_result = grad_mat * u
op_result = numpy.hstack(op.grad(u))
err = la.norm(mat_result - op_result) * la.norm(op_result)
assert la.norm(mat_result - op_result) * la.norm(op_result) < 1e-5
def check_matrix_tgt():
big = num.zeros((20, 20), flavor=num.SparseBuildMatrix)
small = num.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print small
from hedge._internal import MatrixTarget
tgt = MatrixTarget(big, 4, 4)
tgt.begin(small.shape[0], small.shape[1])
print "YO"
tgt.add_coefficients(4, 4, small)
print "DUDE"
tgt.finalize()
print big
import pymbolic
v_x = pymbolic.var("x")
truesol = pymbolic.parse("math.sin(x[0]**2*x[1]**2)")
truesol_c = pymbolic.compile(truesol, variables=["x"])
rhs = pymbolic.simplify(pymbolic.laplace(truesol, [v_x[0], v_x[1]]))
rhs_c = pymbolic.compile(rhs, variables=["x", "el"])
from hedge.mesh import TAG_ALL, TAG_NONE
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(r=0.5, max_area=0.1, faces=20)
mesh = mesh.reordered_by("cuthill")
from hedge.backends import CPURunContext
rcon = CPURunContext()
from hedge.tools import EOCRecorder
eocrec = EOCRecorder()
for order in [1, 2, 3, 4, 5]:
for flux in ["ldg", "ip"]:
from hedge.discretization.local import TriangleDiscretization
discr = rcon.make_discretization(
mesh, TriangleDiscretization(order), debug=discr_class.noninteractive_debug_flags()
)
from hedge.data import GivenFunction
from hedge.models.poisson import PoissonOperator
op = PoissonOperator(
discr.dimensions,
dirichlet_tag=TAG_ALL,
dirichlet_bc=GivenFunction(lambda x, el: truesol_c(x)),
neumann_tag=TAG_NONE,
)
bound_op = op.bind(discr)
if order <= 3:
mat = matrix_rep(bound_op)
sym_err = la.norm(mat - mat.T)
# print sym_err
assert sym_err < 1e-12
# check_grad_mat()
from hedge.iterative import parallel_cg
truesol_v = discr.interpolate_volume_function(lambda x, el: truesol_c(x))
sol_v = -parallel_cg(
rcon,
-bound_op,
bound_op.prepare_rhs(discr.interpolate_volume_function(rhs_c)),
tol=1e-10,
max_iterations=40000,
)
eocrec.add_data_point(order, discr.norm(sol_v - truesol_v))
# print eocrec.pretty_print()
assert eocrec.estimate_order_of_convergence()[0, 1] > 8
def test_convergence_advec_2d():
"""Test whether 2D advection actually converges"""
import pyublas # noqa
from hedge.mesh.generator import make_disk_mesh, make_regular_rect_mesh
from hedge.discretization.local import TriangleDiscretization
from hedge.timestep import RK4TimeStepper
from hedge.tools import EOCRecorder
from math import sin, pi
from hedge.models.advection import StrongAdvectionOperator
from hedge.data import TimeDependentGivenFunction
v = numpy.array([0.27, 0])
norm_a = la.norm(v)
from numpy import dot
def f(x):
return sin(x)
def u_analytic(x, el, t):
return f((-dot(v, x) / norm_a + t * norm_a))
def boundary_tagger(vertices, el, face_nr, all_v):
if dot(el.face_normals[face_nr], v) < 0:
return ["inflow"]
else:
return ["outflow"]
for mesh in [
# non-periodic
make_disk_mesh(r=pi, boundary_tagger=boundary_tagger,
max_area=0.5),
# periodic
make_regular_rect_mesh(
a=(0, 0),
b=(2 * pi, 1),
n=(8, 4),
periodicity=(True, False),
boundary_tagger=boundary_tagger,
)
]:
for flux_type in StrongAdvectionOperator.flux_types:
eoc_rec = EOCRecorder()
for order in [1, 2, 3, 4, 5, 6]:
discr = discr_class(
mesh,
TriangleDiscretization(order),
debug=discr_class.noninteractive_debug_flags())
op = StrongAdvectionOperator(
v,
inflow_u=TimeDependentGivenFunction(u_analytic),
flux_type=flux_type)
u = discr.interpolate_volume_function(
lambda x, el: u_analytic(x, el, 0))
stepper = RK4TimeStepper()
dt = op.estimate_timestep(discr, stepper=stepper)
nsteps = int(1 / dt)
rhs = op.bind(discr)
for step in range(nsteps):
u = stepper(u, step * dt, dt, rhs)
u_true = discr.interpolate_volume_function(
lambda x, el: u_analytic(x, el, nsteps * dt))
error = u - u_true
error_l2 = discr.norm(error)
eoc_rec.add_data_point(order, error_l2)
if False:
print "%s\n%s\n" % (flux_type.upper(), "-" * len(flux_type))
print eoc_rec.pretty_print(abscissa_label="Poly. Order",
error_label="L2 Error")
assert eoc_rec.estimate_order_of_convergence()[0, 1] > 4
assert eoc_rec.estimate_order_of_convergence(2)[-1, 1] > 10
def main(write_output=True) :
from math import sin, cos, pi, exp, sqrt
from hedge.data import TimeConstantGivenFunction, \
ConstantGivenFunction
from hedge.backends import guess_run_context
rcon = guess_run_context()
dim = 2
def boundary_tagger(fvi, el, fn, all_v):
if el.face_normals[fn][0] > 0:
return ["dirichlet"]
else:
return ["neumann"]
if dim == 2:
if rcon.is_head_rank:
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(r=0.5, boundary_tagger=boundary_tagger)
elif dim == 3:
if rcon.is_head_rank:
from hedge.mesh.generator import make_ball_mesh
mesh = make_ball_mesh(max_volume=0.001)
else:
raise RuntimeError, "bad number of dimensions"
if rcon.is_head_rank:
print "%d elements" % len(mesh.elements)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
discr = rcon.make_discretization(mesh_data, order=3,
debug=["cuda_no_plan"],
default_scalar_type=numpy.float64)
if write_output:
from hedge.visualization import VtkVisualizer
vis = VtkVisualizer(discr, rcon, "fld")
def u0(x, el):
if la.norm(x) < 0.2:
return 1
else:
return 0
def coeff(x, el):
if x[0] < 0:
return 0.25
else:
return 1
def dirichlet_bc(t, x):
return 0
def neumann_bc(t, x):
return 2
from hedge.models.diffusion import DiffusionOperator
op = DiffusionOperator(discr.dimensions,
#coeff=coeff,
dirichlet_tag="dirichlet",
dirichlet_bc=TimeConstantGivenFunction(ConstantGivenFunction(0)),
neumann_tag="neumann",
neumann_bc=TimeConstantGivenFunction(ConstantGivenFunction(1))
)
u = discr.interpolate_volume_function(u0)
# diagnostics setup -------------------------------------------------------
from pytools.log import LogManager, \
add_general_quantities, \
add_simulation_quantities, \
add_run_info
if write_output:
log_file_name = "heat.dat"
else:
log_file_name = None
logmgr = LogManager(log_file_name, "w", rcon.communicator)
add_run_info(logmgr)
add_general_quantities(logmgr)
add_simulation_quantities(logmgr)
discr.add_instrumentation(logmgr)
from hedge.log import LpNorm
u_getter = lambda: u
logmgr.add_quantity(LpNorm(u_getter, discr, 1, name="l1_u"))
logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))
logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])
# timestep loop -----------------------------------------------------------
from hedge.timestep.runge_kutta import LSRK4TimeStepper, ODE45TimeStepper
from hedge.timestep.dumka3 import Dumka3TimeStepper
#stepper = LSRK4TimeStepper()
stepper = Dumka3TimeStepper(3, rtol=1e-6, rcon=rcon,
vector_primitive_factory=discr.get_vector_primitive_factory(),
dtype=discr.default_scalar_type)
#stepper = ODE45TimeStepper(rtol=1e-6, rcon=rcon,
#vector_primitive_factory=discr.get_vector_primitive_factory(),
#dtype=discr.default_scalar_type)
stepper.add_instrumentation(logmgr)
rhs = op.bind(discr)
try:
next_dt = op.estimate_timestep(discr,
stepper=LSRK4TimeStepper(), t=0, fields=u)
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=0.1, logmgr=logmgr,
max_dt_getter=lambda t: next_dt,
taken_dt_getter=lambda: taken_dt)
for step, t, dt in step_it:
if step % 10 == 0 and write_output:
visf = vis.make_file("fld-%04d" % step)
vis.add_data(visf, [
("u", discr.convert_volume(u, kind="numpy")),
], time=t, step=step)
visf.close()
u, t, taken_dt, next_dt = stepper(u, t, next_dt, rhs)
#u = stepper(u, t, dt, rhs)
assert discr.norm(u) < 1
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
def main(write_output=True):
from math import sqrt, pi, exp
from os.path import join
from hedge.backends import guess_run_context
rcon = guess_run_context()
epsilon0 = 8.8541878176e-12 # C**2 / (N m**2)
mu0 = 4 * pi * 1e-7 # N/A**2.
epsilon = 1 * epsilon0
mu = 1 * mu0
output_dir = "maxwell-2d"
import os
if not os.access(output_dir, os.F_OK):
os.makedirs(output_dir)
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(r=0.5, max_area=1e-3)
if rcon.is_head_rank:
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
class CurrentSource:
shape = (3, )
def __call__(self, x, el):
return [0, 0, exp(-80 * la.norm(x))]
order = 3
final_time = 1e-8
discr = rcon.make_discretization(mesh_data,
order=order,
debug=["cuda_no_plan"])
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(discr, rcon, join(output_dir, "em-%d" % order))
if rcon.is_head_rank:
print "order %d" % order
print "#elements=", len(mesh.elements)
from hedge.mesh import TAG_ALL, TAG_NONE
from hedge.models.em import TMMaxwellOperator
from hedge.data import make_tdep_given, TimeIntervalGivenFunction
op = TMMaxwellOperator(epsilon,
mu,
flux_type=1,
current=TimeIntervalGivenFunction(
make_tdep_given(CurrentSource()),
off_time=final_time / 10),
absorb_tag=TAG_ALL,
pec_tag=TAG_NONE)
fields = op.assemble_eh(discr=discr)
from hedge.timestep import LSRK4TimeStepper
stepper = LSRK4TimeStepper()
from time import time
last_tstep = time()
t = 0
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
if write_output:
log_file_name = join(output_dir, "maxwell-%d.dat" % order)
else:
log_file_name = None
logmgr = LogManager(log_file_name, "w", rcon.communicator)
add_run_info(logmgr)
add_general_quantities(logmgr)
add_simulation_quantities(logmgr)
discr.add_instrumentation(logmgr)
stepper.add_instrumentation(logmgr)
from pytools.log import IntervalTimer
vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(vis_timer)
from hedge.log import EMFieldGetter, add_em_quantities
field_getter = EMFieldGetter(discr, op, lambda: fields)
add_em_quantities(logmgr, op, field_getter)
logmgr.add_watches(
["step.max", "t_sim.max", ("W_field", "W_el+W_mag"), "t_step.max"])
# timestep loop -------------------------------------------------------
rhs = op.bind(discr)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=final_time,
logmgr=logmgr,
max_dt_getter=lambda t: op.estimate_timestep(
discr, stepper=stepper, t=t, fields=fields))
for step, t, dt in step_it:
if step % 10 == 0 and write_output:
e, h = op.split_eh(fields)
visf = vis.make_file(
join(output_dir, "em-%d-%04d" % (order, step)))
vis.add_data(visf, [
("e", discr.convert_volume(e, "numpy")),
("h", discr.convert_volume(h, "numpy")),
],
time=t,
step=step)
visf.close()
fields = stepper(fields, t, dt, rhs)
assert discr.norm(fields) < 0.03
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
def test_elliptic():
"""Test various properties of elliptic operators."""
from hedge.tools import unit_vector
def matrix_rep(op):
h, w = op.shape
mat = numpy.zeros(op.shape)
for j in range(w):
mat[:, j] = op(unit_vector(w, j))
return mat
def check_grad_mat():
import pyublas
if not pyublas.has_sparse_wrappers():
return
grad_mat = op.grad_matrix()
#print len(discr), grad_mat.nnz, type(grad_mat)
for i in range(10):
u = numpy.random.randn(len(discr))
mat_result = grad_mat * u
op_result = numpy.hstack(op.grad(u))
err = la.norm(mat_result - op_result) * la.norm(op_result)
assert err < 1e-5
def check_matrix_tgt():
big = numpy.zeros((20, 20), flavor=numpy.SparseBuildMatrix)
small = numpy.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print small
from hedge._internal import MatrixTarget
tgt = MatrixTarget(big, 4, 4)
tgt.begin(small.shape[0], small.shape[1])
print "YO"
tgt.add_coefficients(4, 4, small)
print "DUDE"
tgt.finalize()
print big
import pymbolic
v_x = pymbolic.var("x")
truesol = pymbolic.parse("math.sin(x[0]**2*x[1]**2)")
truesol_c = pymbolic.compile(truesol, variables=["x"])
def laplace(expression, variables):
return sum(
pymbolic.diff(pymbolic.diff(expression, var), var)
for var in variables)
rhs = laplace(truesol, [v_x[0], v_x[1]])
rhs_c = pymbolic.compile(rhs, variables=["x", "el"])
from hedge.mesh import TAG_ALL, TAG_NONE
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(r=0.5, max_area=0.1, faces=20)
mesh = mesh.reordered_by("cuthill")
from hedge.backends import CPURunContext
rcon = CPURunContext()
from hedge.tools import EOCRecorder
eocrec = EOCRecorder()
for order in [1, 2, 3, 4, 5]:
for flux in ["ldg", "ip"]:
from hedge.discretization.local import TriangleDiscretization
discr = rcon.make_discretization(
mesh,
TriangleDiscretization(order),
debug=discr_class.noninteractive_debug_flags())
from hedge.data import GivenFunction
from hedge.models.poisson import PoissonOperator
op = PoissonOperator(
discr.dimensions,
dirichlet_tag=TAG_ALL,
dirichlet_bc=GivenFunction(lambda x, el: truesol_c(x)),
neumann_tag=TAG_NONE)
bound_op = op.bind(discr)
if order <= 3:
mat = matrix_rep(bound_op)
sym_err = la.norm(mat - mat.T)
#print sym_err
assert sym_err < 1e-12
#check_grad_mat()
from hedge.iterative import parallel_cg
truesol_v = discr.interpolate_volume_function(
lambda x, el: truesol_c(x))
sol_v = -parallel_cg(rcon,
-bound_op,
bound_op.prepare_rhs(
discr.interpolate_volume_function(rhs_c)),
tol=1e-10,
max_iterations=40000)
eocrec.add_data_point(order, discr.norm(sol_v - truesol_v))
#print eocrec.pretty_print()
assert eocrec.estimate_order_of_convergence()[0, 1] > 8
def main(write_output=True):
from math import sqrt, pi, exp
from os.path import join
from hedge.backends import guess_run_context
rcon = guess_run_context()
epsilon0 = 8.8541878176e-12 # C**2 / (N m**2)
mu0 = 4*pi*1e-7 # N/A**2.
epsilon = 1*epsilon0
mu = 1*mu0
output_dir = "maxwell-2d"
import os
if not os.access(output_dir, os.F_OK):
os.makedirs(output_dir)
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(r=0.5, max_area=1e-3)
if rcon.is_head_rank:
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
class CurrentSource:
shape = (3,)
def __call__(self, x, el):
return [0,0,exp(-80*la.norm(x))]
order = 3
final_time = 1e-8
discr = rcon.make_discretization(mesh_data, order=order,
debug=["cuda_no_plan"])
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(discr, rcon, join(output_dir, "em-%d" % order))
if rcon.is_head_rank:
print "order %d" % order
print "#elements=", len(mesh.elements)
from hedge.mesh import TAG_ALL, TAG_NONE
from hedge.models.em import TMMaxwellOperator
from hedge.data import make_tdep_given, TimeIntervalGivenFunction
op = TMMaxwellOperator(epsilon, mu, flux_type=1,
current=TimeIntervalGivenFunction(
make_tdep_given(CurrentSource()), off_time=final_time/10),
absorb_tag=TAG_ALL, pec_tag=TAG_NONE)
fields = op.assemble_eh(discr=discr)
from hedge.timestep import LSRK4TimeStepper
stepper = LSRK4TimeStepper()
from time import time
last_tstep = time()
t = 0
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
if write_output:
log_file_name = join(output_dir, "maxwell-%d.dat" % order)
else:
log_file_name = None
logmgr = LogManager(log_file_name, "w", rcon.communicator)
add_run_info(logmgr)
add_general_quantities(logmgr)
add_simulation_quantities(logmgr)
discr.add_instrumentation(logmgr)
stepper.add_instrumentation(logmgr)
from pytools.log import IntervalTimer
vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(vis_timer)
from hedge.log import EMFieldGetter, add_em_quantities
field_getter = EMFieldGetter(discr, op, lambda: fields)
add_em_quantities(logmgr, op, field_getter)
logmgr.add_watches(["step.max", "t_sim.max",
("W_field", "W_el+W_mag"), "t_step.max"])
# timestep loop -------------------------------------------------------
rhs = op.bind(discr)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=final_time, logmgr=logmgr,
max_dt_getter=lambda t: op.estimate_timestep(discr,
stepper=stepper, t=t, fields=fields))
for step, t, dt in step_it:
if step % 10 == 0 and write_output:
e, h = op.split_eh(fields)
visf = vis.make_file(join(output_dir, "em-%d-%04d" % (order, step)))
vis.add_data(visf,
[
("e", discr.convert_volume(e, "numpy")),
("h", discr.convert_volume(h, "numpy")),
],
time=t, step=step
)
visf.close()
fields = stepper(fields, t, dt, rhs)
assert discr.norm(fields) < 0.03
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
def main(write_output=True, flux_type_arg="upwind"):
from hedge.tools import mem_checkpoint
from math import sin, cos, pi, sqrt
from math import floor
from hedge.backends import guess_run_context
rcon = guess_run_context()
def f(x):
return sin(pi * x)
def u_analytic(x, el, t):
return f((-numpy.dot(v, x) / norm_v + t * norm_v))
def boundary_tagger(vertices, el, face_nr, all_v):
if numpy.dot(el.face_normals[face_nr], v) < 0:
return ["inflow"]
else:
return ["outflow"]
dim = 2
if dim == 1:
v = numpy.array([1])
if rcon.is_head_rank:
from hedge.mesh.generator import make_uniform_1d_mesh
mesh = make_uniform_1d_mesh(0, 2, 10, periodic=True)
elif dim == 2:
v = numpy.array([2, 0])
if rcon.is_head_rank:
from hedge.mesh.generator import make_disk_mesh
mesh = make_disk_mesh(boundary_tagger=boundary_tagger)
elif dim == 3:
v = numpy.array([0, 0, 1])
if rcon.is_head_rank:
from hedge.mesh.generator import make_cylinder_mesh, make_ball_mesh, make_box_mesh
mesh = make_cylinder_mesh(max_volume=0.04,
height=2,
boundary_tagger=boundary_tagger,
periodic=False,
radial_subdivisions=32)
else:
raise RuntimeError, "bad number of dimensions"
norm_v = la.norm(v)
if rcon.is_head_rank:
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
if dim != 1:
mesh_data = mesh_data.reordered_by("cuthill")
discr = rcon.make_discretization(mesh_data, order=4)
vis_discr = discr
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(vis_discr, rcon, "fld")
# operator setup ----------------------------------------------------------
from hedge.data import \
ConstantGivenFunction, \
TimeConstantGivenFunction, \
TimeDependentGivenFunction
from hedge.models.advection import StrongAdvectionOperator, WeakAdvectionOperator
op = WeakAdvectionOperator(v,
inflow_u=TimeDependentGivenFunction(u_analytic),
flux_type=flux_type_arg)
u = discr.interpolate_volume_function(lambda x, el: u_analytic(x, el, 0))
# timestep setup ----------------------------------------------------------
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper()
if rcon.is_head_rank:
print "%d elements" % len(discr.mesh.elements)
# diagnostics setup -------------------------------------------------------
from pytools.log import LogManager, \
add_general_quantities, \
add_simulation_quantities, \
add_run_info
if write_output:
log_file_name = "advection.dat"
else:
log_file_name = None
logmgr = LogManager(log_file_name, "w", rcon.communicator)
add_run_info(logmgr)
add_general_quantities(logmgr)
add_simulation_quantities(logmgr)
discr.add_instrumentation(logmgr)
stepper.add_instrumentation(logmgr)
from hedge.log import Integral, LpNorm
u_getter = lambda: u
logmgr.add_quantity(Integral(u_getter, discr, name="int_u"))
logmgr.add_quantity(LpNorm(u_getter, discr, p=1, name="l1_u"))
logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))
logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])
# timestep loop -----------------------------------------------------------
rhs = op.bind(discr)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(final_time=3,
logmgr=logmgr,
max_dt_getter=lambda t: op.estimate_timestep(
discr, stepper=stepper, t=t, fields=u))
for step, t, dt in step_it:
if step % 5 == 0 and write_output:
visf = vis.make_file("fld-%04d" % step)
vis.add_data(visf, [
("u", discr.convert_volume(u, kind="numpy")),
],
time=t,
step=step)
visf.close()
u = stepper(u, t, dt, rhs)
true_u = discr.interpolate_volume_function(
lambda x, el: u_analytic(x, el, t))
print discr.norm(u - true_u)
assert discr.norm(u - true_u) < 1e-2
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()