def op_template(self, w=None):
from hedge.tools import count_subset
fld_cnt = count_subset(self.get_eh_subset())
if w is None:
from hedge.optemplate import make_sym_vector
w = make_sym_vector("w", fld_cnt + 2 * self.dimensions)
from hedge.tools import join_fields
return join_fields(MaxwellOperator.op_template(self, w[:fld_cnt]),
numpy.zeros((2 * self.dimensions, ),
dtype=object)) + self.pml_local_op(w)
def op_template(self, w=None):
from hedge.tools import count_subset
fld_cnt = count_subset(self.get_eh_subset())
if w is None:
from hedge.optemplate import make_vector_field
w = make_vector_field("w", fld_cnt+2*self.dimensions)
from hedge.tools import join_fields
return join_fields(
MaxwellOperator.op_template(self, w[:fld_cnt]),
numpy.zeros((2*self.dimensions,), dtype=object)
) + self.pml_local_op(w)
def test_efield_vs_gauss_law():
from hedge.mesh.generator import \
make_box_mesh, \
make_cylinder_mesh
from math import sqrt, pi
from pytools.arithmetic_container import \
ArithmeticList, join_fields
from random import seed
from pytools.stopwatch import Job
from pyrticle.units import SIUnitsWithNaturalConstants
units = SIUnitsWithNaturalConstants()
seed(0)
nparticles = 10000
beam_radius = 2.5 * units.MM
emittance = 5 * units.MM * units.MRAD
final_time = 0.1 * units.M / units.VACUUM_LIGHT_SPEED()
field_dump_interval = 1
tube_length = 20 * units.MM
# discretization setup ----------------------------------------------------
from pyrticle.geometry import make_cylinder_with_fine_core
mesh = make_cylinder_with_fine_core(
r=10 * beam_radius,
inner_r=1 * beam_radius,
min_z=0,
max_z=tube_length,
max_volume_inner=10 * units.MM**3,
max_volume_outer=100 * units.MM**3,
radial_subdiv=10,
)
from hedge.backends import guess_run_context
rcon = guess_run_context([])
discr = rcon.make_discretization(mesh, order=3)
from hedge.models.em import MaxwellOperator
max_op = MaxwellOperator(epsilon=units.EPSILON0, mu=units.MU0, flux_type=1)
from hedge.models.nd_calculus import DivergenceOperator
div_op = DivergenceOperator(discr.dimensions)
# particles setup ---------------------------------------------------------
from pyrticle.cloud import PicMethod
from pyrticle.deposition.shape import ShapeFunctionDepositor
from pyrticle.pusher import MonomialParticlePusher
method = PicMethod(discr, units, ShapeFunctionDepositor(),
MonomialParticlePusher(), 3, 3)
# particle ic ---------------------------------------------------------
cloud_charge = -1e-9 * units.C
electrons_per_particle = abs(cloud_charge / nparticles / units.EL_CHARGE)
el_energy = 10 * units.EL_REST_ENERGY()
el_lorentz_gamma = el_energy / units.EL_REST_ENERGY()
beta = (1 - 1 / el_lorentz_gamma**2)**0.5
gamma = 1 / sqrt(1 - beta**2)
from pyrticle.distribution import KVZIntervalBeam
beam = KVZIntervalBeam(units,
total_charge=cloud_charge,
p_charge=cloud_charge / nparticles,
p_mass=electrons_per_particle * units.EL_MASS,
radii=2 * [beam_radius],
emittances=2 * [5 * units.MM * units.MRAD],
z_length=tube_length,
z_pos=tube_length / 2,
beta=beta)
state = method.make_state()
method.add_particles(state, beam.generate_particles(), nparticles)
# field ic ----------------------------------------------------------------
from pyrticle.cloud import guess_shape_bandwidth
guess_shape_bandwidth(method, state, 2)
from pyrticle.cloud import compute_initial_condition
from hedge.data import ConstantGivenFunction
fields = compute_initial_condition(rcon,
discr,
method,
state,
maxwell_op=max_op,
potential_bc=ConstantGivenFunction())
# check against theory ----------------------------------------------------
q_per_unit_z = cloud_charge / beam.z_length
class TheoreticalEField:
shape = (3, )
def __call__(self, x, el):
r = la.norm(x[:2])
if r >= max(beam.radii):
xy_unit = x / r
xy_unit[2] = 0
return xy_unit * ((q_per_unit_z) /
(2 * pi * r * max_op.epsilon))
else:
return numpy.zeros((3, ))
def theory_indicator(x, el):
r = la.norm(x[:2])
if r >= max(beam.radii):
return 1
else:
return 0
from hedge.tools import join_fields, to_obj_array
e_theory = to_obj_array(
discr.interpolate_volume_function(TheoreticalEField()))
theory_ind = discr.interpolate_volume_function(theory_indicator)
e_field, h_field = max_op.split_eh(fields)
restricted_e = join_fields(*[e_i * theory_ind for e_i in e_field])
def l2_error(field, true):
return discr.norm(field - true) / discr.norm(true)
outer_l2 = l2_error(restricted_e, e_theory)
assert outer_l2 < 0.08
if False:
visf = vis.make_file("e_comparison")
mesh_scalars, mesh_vectors = \
method.add_to_vis(vis, visf)
vis.add_data(visf, [
("e", restricted_e),
("e_theory", e_theory),
] + mesh_vectors + mesh_scalars)
visf.close()
def test_efield_vs_gauss_law():
from hedge.mesh.generator import \
make_box_mesh, \
make_cylinder_mesh
from math import sqrt, pi
from pytools.arithmetic_container import \
ArithmeticList, join_fields
from random import seed
from pytools.stopwatch import Job
from pyrticle.units import SIUnitsWithNaturalConstants
units = SIUnitsWithNaturalConstants()
seed(0)
nparticles = 10000
beam_radius = 2.5 * units.MM
emittance = 5 * units.MM * units.MRAD
final_time = 0.1*units.M/units.VACUUM_LIGHT_SPEED()
field_dump_interval = 1
tube_length = 20*units.MM
# discretization setup ----------------------------------------------------
from pyrticle.geometry import make_cylinder_with_fine_core
mesh = make_cylinder_with_fine_core(
r=10*beam_radius, inner_r=1*beam_radius,
min_z=0, max_z=tube_length,
max_volume_inner=10*units.MM**3,
max_volume_outer=100*units.MM**3,
radial_subdiv=10,
)
from hedge.backends import guess_run_context
rcon = guess_run_context([])
discr = rcon.make_discretization(mesh, order=3)
from hedge.models.em import MaxwellOperator
max_op = MaxwellOperator(
epsilon=units.EPSILON0,
mu=units.MU0,
flux_type=1)
from hedge.models.nd_calculus import DivergenceOperator
div_op = DivergenceOperator(discr.dimensions)
# particles setup ---------------------------------------------------------
from pyrticle.cloud import PicMethod
from pyrticle.deposition.shape import ShapeFunctionDepositor
from pyrticle.pusher import MonomialParticlePusher
method = PicMethod(discr, units,
ShapeFunctionDepositor(),
MonomialParticlePusher(),
3, 3)
# particle ic ---------------------------------------------------------
cloud_charge = -1e-9 * units.C
electrons_per_particle = abs(cloud_charge/nparticles/units.EL_CHARGE)
el_energy = 10*units.EL_REST_ENERGY()
el_lorentz_gamma = el_energy/units.EL_REST_ENERGY()
beta = (1-1/el_lorentz_gamma**2)**0.5
gamma = 1/sqrt(1-beta**2)
from pyrticle.distribution import KVZIntervalBeam
beam = KVZIntervalBeam(units, total_charge=cloud_charge,
p_charge=cloud_charge/nparticles,
p_mass=electrons_per_particle*units.EL_MASS,
radii=2*[beam_radius],
emittances=2*[5 * units.MM * units.MRAD],
z_length=tube_length,
z_pos=tube_length/2,
beta=beta)
state = method.make_state()
method.add_particles(state, beam.generate_particles(), nparticles)
# field ic ----------------------------------------------------------------
from pyrticle.cloud import guess_shape_bandwidth
guess_shape_bandwidth(method, state, 2)
from pyrticle.cloud import compute_initial_condition
from hedge.data import ConstantGivenFunction
fields = compute_initial_condition(
rcon,
discr, method, state, maxwell_op=max_op,
potential_bc=ConstantGivenFunction())
# check against theory ----------------------------------------------------
q_per_unit_z = cloud_charge/beam.z_length
class TheoreticalEField:
shape = (3,)
def __call__(self, x, el):
r = la.norm(x[:2])
if r >= max(beam.radii):
xy_unit = x/r
xy_unit[2] = 0
return xy_unit*((q_per_unit_z)
/
(2*pi*r*max_op.epsilon))
else:
return numpy.zeros((3,))
def theory_indicator(x, el):
r = la.norm(x[:2])
if r >= max(beam.radii):
return 1
else:
return 0
from hedge.tools import join_fields, to_obj_array
e_theory = to_obj_array(discr.interpolate_volume_function(TheoreticalEField()))
theory_ind = discr.interpolate_volume_function(theory_indicator)
e_field, h_field = max_op.split_eh(fields)
restricted_e = join_fields(*[e_i * theory_ind for e_i in e_field])
def l2_error(field, true):
return discr.norm(field-true)/discr.norm(true)
outer_l2 = l2_error(restricted_e, e_theory)
assert outer_l2 < 0.08
if False:
visf = vis.make_file("e_comparison")
mesh_scalars, mesh_vectors = \
method.add_to_vis(vis, visf)
vis.add_data(visf, [
("e", restricted_e),
("e_theory", e_theory),
]
+ mesh_vectors
+ mesh_scalars
)
visf.close()
def __init__(self, *args, **kwargs):
self.add_decay = kwargs.pop("add_decay", True)
MaxwellOperator.__init__(self, *args, **kwargs)
def bind(self, discr, coefficients):
return MaxwellOperator.bind(self, discr,
sigma=coefficients.sigma,
sigma_prime=coefficients.sigma_prime,
tau=coefficients.tau)
def run_setup(units, casename, setup, discr, pusher, visualize=False):
from hedge.timestep.runge_kutta import LSRK4TimeStepper
from hedge.visualization import SiloVisualizer
from hedge.models.em import MaxwellOperator
vis = SiloVisualizer(discr)
from pyrticle.cloud import PicMethod
from pyrticle.deposition.shape import ShapeFunctionDepositor
method = PicMethod(discr,
units,
ShapeFunctionDepositor(),
pusher(),
3,
3,
debug=set(["verbose_vis"]))
e, h = setup.fields(discr)
b = units.MU0 * h
init_positions = setup.positions(0)
init_velocities = setup.velocities(0)
nparticles = len(init_positions)
state = method.make_state()
method.add_particles(
state,
zip(
init_positions,
init_velocities,
nparticles * [setup.charge],
nparticles * [units.EL_MASS],
), nparticles)
final_time = setup.final_time()
nsteps = setup.nsteps()
dt = final_time / nsteps
# timestepping ------------------------------------------------------------
from hedge.models.em import MaxwellOperator
max_op = MaxwellOperator(epsilon=units.EPSILON0, mu=units.MU0, flux_type=1)
fields = max_op.assemble_eh(e, h)
from pyrticle.cloud import \
FieldToParticleRhsCalculator, \
ParticleRhsCalculator
p_rhs_calculator = ParticleRhsCalculator(method, max_op)
f2p_rhs_calculator = FieldToParticleRhsCalculator(method, max_op)
def rhs(t, ts_state):
return (p_rhs_calculator(t, lambda: fields, lambda: ts_state.state) +
f2p_rhs_calculator(t, lambda: fields, lambda: ts_state.state))
stepper = LSRK4TimeStepper()
t = 0
bbox = discr.mesh.bounding_box()
z_period = bbox[1][2] - bbox[0][2]
def check_result():
from hedge.tools import cross
deriv_dt = 1e-12
dim = discr.dimensions
true_x = setup.positions(t)
true_v = setup.velocities(t)
true_f = [(p2 - p1) / (2 * deriv_dt) for p1, p2 in zip(
setup.momenta(t - deriv_dt), setup.momenta(t + deriv_dt))]
state = ts_state.state
from pyrticle.tools import NumberShiftableVector
vis_info = state.vis_listener.particle_vis_map
sim_x = state.positions
sim_v = method.velocities(state)
sim_f = NumberShiftableVector.unwrap(vis_info["mag_force"] +
vis_info["el_force"])
sim_el_f = NumberShiftableVector.unwrap(vis_info["el_force"])
sim_mag_f = NumberShiftableVector.unwrap(vis_info["mag_force"])
local_e = setup.e()
local_b = units.MU0 * setup.h()
x_err = 0
v_err = 0
f_err = 0
for i in range(len(state)):
#real_f = numpy.array(cross(sim_v, setup.charge*local_b)) + setup.charge*local_e
my_true_x = true_x[i]
my_true_x[2] = my_true_x[2] % z_period
if False and i == 0:
#print "particle %d" % i
print "pos:", la.norm(true_x[i] - sim_x[i]) / la.norm(
true_x[i])
#print "vel:", la.norm(true_v[i]-sim_v[i])/la.norm(true_v[i])
#print "force:", la.norm(true_f[i]-sim_f[i])/la.norm(true_f[i])
print "pos:", true_x[i], sim_x[i]
#print "vel:", true_v[i], sim_v[i]
#print "force:", true_f[i], sim_f[i]
#print "forces%d:..." % i, sim_el_f[i], sim_mag_f[i]
#print "acc%d:" % i, la.norm(a-sim_a)
#u = numpy.vstack((v, sim_v, f, sim_f, real_f))
#print "acc%d:\n%s" % (i, u)
#raw_input()
def rel_err(sim, true):
return la.norm(true - sim) / la.norm(true)
x_err = max(x_err, rel_err(sim_x[i], my_true_x))
v_err = max(v_err, rel_err(sim_v[i], true_v[i]))
f_err = max(f_err, rel_err(sim_f[i], true_f[i]))
return x_err, v_err, f_err
# make sure verbose-vis fields are filled
from pyrticle.cloud import TimesteppablePicState
ts_state = TimesteppablePicState(method, state)
del state
rhs(t, ts_state)
errors = (0, 0, 0)
for step in xrange(nsteps):
if step % int(setup.nsteps() / 300) == 0:
errors = tuple(
max(old_err, new_err)
for old_err, new_err in zip(errors, check_result()))
if visualize:
visf = vis.make_file("%s-%04d" % (casename, step))
method.add_to_vis(vis, visf, ts_state.state, time=t, step=step)
if True:
vis.add_data(visf, [
("e", e),
("h", h),
],
time=t,
step=step)
else:
vis.add_data(visf, [], time=t, step=step)
visf.close()
method.upkeep(ts_state.state)
ts_state = stepper(ts_state, t, dt, rhs)
t += dt
assert errors[0] < 2e-12, casename + "-pos"
assert errors[1] < 2e-13, casename + "-vel"
assert errors[2] < 2e-4, casename + "-acc"
vis.close()
def main(write_output=True, allow_features=None, flux_type_arg=1, bdry_flux_type_arg=None, extra_discr_args={}):
from hedge.mesh.generator import make_cylinder_mesh, make_box_mesh
from hedge.tools import EOCRecorder, to_obj_array
from math import sqrt, pi
from analytic_solutions import (
check_time_harmonic_solution,
RealPartAdapter,
SplitComplexAdapter,
CylindricalFieldAdapter,
CylindricalCavityMode,
RectangularWaveguideMode,
RectangularCavityMode,
)
from hedge.models.em import MaxwellOperator
from hedge.backends import guess_run_context
rcon = guess_run_context(allow_features)
epsilon0 = 8.8541878176e-12 # C**2 / (N m**2)
mu0 = 4 * pi * 1e-7 # N/A**2.
epsilon = 1 * epsilon0
mu = 1 * mu0
eoc_rec = EOCRecorder()
cylindrical = False
periodic = False
if cylindrical:
R = 1
d = 2
mode = CylindricalCavityMode(m=1, n=1, p=1, radius=R, height=d, epsilon=epsilon, mu=mu)
r_sol = CylindricalFieldAdapter(RealPartAdapter(mode))
c_sol = SplitComplexAdapter(CylindricalFieldAdapter(mode))
if rcon.is_head_rank:
mesh = make_cylinder_mesh(radius=R, height=d, max_volume=0.01)
else:
if periodic:
mode = RectangularWaveguideMode(epsilon, mu, (3, 2, 1))
periodicity = (False, False, True)
else:
periodicity = None
mode = RectangularCavityMode(epsilon, mu, (1, 2, 2))
if rcon.is_head_rank:
mesh = make_box_mesh(max_volume=0.001, periodicity=periodicity)
if rcon.is_head_rank:
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [4, 5, 6]:
# for order in [1,2,3,4,5,6]:
extra_discr_args.setdefault("debug", []).extend(["cuda_no_plan", "cuda_dump_kernels"])
op = MaxwellOperator(epsilon, mu, flux_type=flux_type_arg, bdry_flux_type=bdry_flux_type_arg)
discr = rcon.make_discretization(mesh_data, order=order, tune_for=op.op_template(), **extra_discr_args)
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(discr, rcon, "em-%d" % order)
mode.set_time(0)
def get_true_field():
return discr.convert_volume(
to_obj_array(mode(discr).real.astype(discr.default_scalar_type).copy()), kind=discr.compute_kind
)
fields = get_true_field()
if rcon.is_head_rank:
print "---------------------------------------------"
print "order %d" % order
print "---------------------------------------------"
print "#elements=", len(mesh.elements)
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper(dtype=discr.default_scalar_type, rcon=rcon)
# from hedge.timestep.dumka3 import Dumka3TimeStepper
# stepper = Dumka3TimeStepper(3, dtype=discr.default_scalar_type, rcon=rcon)
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, add_simulation_quantities, add_run_info
if write_output:
log_file_name = "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)
final_time = 0.5e-9
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 % 50 == 0 and write_output:
sub_timer = vis_timer.start_sub_timer()
e, h = op.split_eh(fields)
visf = vis.make_file("em-%d-%04d" % (order, step))
vis.add_data(
visf,
[("e", discr.convert_volume(e, kind="numpy")), ("h", discr.convert_volume(h, kind="numpy"))],
time=t,
step=step,
)
visf.close()
sub_timer.stop().submit()
fields = stepper(fields, t, dt, rhs)
mode.set_time(final_time)
eoc_rec.add_data_point(order, discr.norm(fields - get_true_field()))
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
if rcon.is_head_rank:
print
print eoc_rec.pretty_print("P.Deg.", "L2 Error")
assert eoc_rec.estimate_order_of_convergence()[0, 1] > 6
def __init__(self, *args, **kwargs):
self.add_decay = kwargs.pop("add_decay", True)
MaxwellOperator.__init__(self, *args, **kwargs)
def bind(self, discr, coefficients):
return MaxwellOperator.bind(self,
discr,
sigma=coefficients.sigma,
sigma_prime=coefficients.sigma_prime,
tau=coefficients.tau)
def main(write_output=True, allow_features=None):
from hedge.timestep import RK4TimeStepper
from hedge.mesh import make_ball_mesh, make_cylinder_mesh, make_box_mesh
from hedge.visualization import \
VtkVisualizer, \
SiloVisualizer, \
get_rank_partition
from math import sqrt, pi
from hedge.backends import guess_run_context
rcon = guess_run_context(allow_features)
epsilon0 = 8.8541878176e-12 # C**2 / (N m**2)
mu0 = 4 * pi * 1e-7 # N/A**2.
epsilon = 1 * epsilon0
mu = 1 * mu0
dims = 3
if rcon.is_head_rank:
if dims == 2:
from hedge.mesh import make_rect_mesh
mesh = make_rect_mesh(a=(-10.5, -1.5), b=(10.5, 1.5), max_area=0.1)
elif dims == 3:
from hedge.mesh import make_box_mesh
mesh = make_box_mesh(a=(-10.5, -1.5, -1.5),
b=(10.5, 1.5, 1.5),
max_volume=0.1)
if rcon.is_head_rank:
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
#for order in [1,2,3,4,5,6]:
discr = rcon.make_discretization(mesh_data, order=3)
if write_output:
vis = VtkVisualizer(discr, rcon, "dipole")
from analytic_solutions import DipoleFarField, SphericalFieldAdapter
from hedge.data import ITimeDependentGivenFunction
sph_dipole = DipoleFarField(
q=1, #C
d=1 / 39,
omega=2 * pi * 1e8,
epsilon=epsilon0,
mu=mu0,
)
cart_dipole = SphericalFieldAdapter(sph_dipole)
class PointDipoleSource(ITimeDependentGivenFunction):
def __init__(self):
from pyrticle.tools import CInfinityShapeFunction
sf = CInfinityShapeFunction(0.1 * sph_dipole.wavelength,
discr.dimensions)
self.num_sf = discr.interpolate_volume_function(
lambda x, el: sf(x))
self.vol_0 = discr.volume_zeros()
def volume_interpolant(self, t, discr):
from hedge.tools import make_obj_array
return make_obj_array([
self.vol_0, self.vol_0,
sph_dipole.source_modulation(t) * self.num_sf
])
from hedge.mesh import TAG_ALL, TAG_NONE
if dims == 2:
from hedge.models.em import TMMaxwellOperator as MaxwellOperator
else:
from hedge.models.em import MaxwellOperator
op = MaxwellOperator(
epsilon,
mu,
flux_type=1,
pec_tag=TAG_NONE,
absorb_tag=TAG_ALL,
current=PointDipoleSource(),
)
fields = op.assemble_eh(discr=discr)
if rcon.is_head_rank:
print "#elements=", len(mesh.elements)
stepper = RK4TimeStepper()
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
if write_output:
log_file_name = "dipole.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 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)
from pytools.log import PushLogQuantity
relerr_e_q = PushLogQuantity("relerr_e", "1",
"Relative error in masked E-field")
relerr_h_q = PushLogQuantity("relerr_h", "1",
"Relative error in masked H-field")
logmgr.add_quantity(relerr_e_q)
logmgr.add_quantity(relerr_h_q)
logmgr.add_watches([
"step.max", "t_sim.max", ("W_field", "W_el+W_mag"), "t_step.max",
"relerr_e", "relerr_h"
])
if write_output:
point_timeseries = [(open("b-x%d-vs-time.dat" % i,
"w"), open("b-x%d-vs-time-true.dat" % i,
"w"),
discr.get_point_evaluator(
numpy.array([i, 0, 0][:dims],
dtype=discr.default_scalar_type)))
for i in range(1, 5)]
# timestep loop -------------------------------------------------------
mask = discr.interpolate_volume_function(sph_dipole.far_field_mask)
def apply_mask(field):
from hedge.tools import log_shape
ls = log_shape(field)
result = discr.volume_empty(ls)
from pytools import indices_in_shape
for i in indices_in_shape(ls):
result[i] = mask * field[i]
return result
rhs = op.bind(discr)
t = 0
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=1e-8,
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 write_output and step % 10 == 0:
sub_timer = vis_timer.start_sub_timer()
e, h = op.split_eh(fields)
sph_dipole.set_time(t)
true_e, true_h = op.split_eh(
discr.interpolate_volume_function(cart_dipole))
visf = vis.make_file("dipole-%04d" % step)
mask_e = apply_mask(e)
mask_h = apply_mask(h)
mask_true_e = apply_mask(true_e)
mask_true_h = apply_mask(true_h)
from pyvisfile.silo import DB_VARTYPE_VECTOR
vis.add_data(visf, [("e", e), ("h", h), ("true_e", true_e),
("true_h", true_h), ("mask_e", mask_e),
("mask_h", mask_h),
("mask_true_e", mask_true_e),
("mask_true_h", mask_true_h)],
time=t,
step=step)
visf.close()
sub_timer.stop().submit()
from hedge.tools import relative_error
relerr_e_q.push_value(
relative_error(discr.norm(mask_e - mask_true_e),
discr.norm(mask_true_e)))
relerr_h_q.push_value(
relative_error(discr.norm(mask_h - mask_true_h),
discr.norm(mask_true_h)))
if write_output:
for outf_num, outf_true, evaluator in point_timeseries:
for outf, ev_h in zip([outf_num, outf_true],
[h, true_h]):
outf.write("%g\t%g\n" %
(t, op.mu * evaluator(ev_h[1])))
outf.flush()
fields = stepper(fields, t, dt, rhs)
finally:
if write_output:
vis.close()
logmgr.save()
discr.close()
def run_setup(units, casename, setup, discr, pusher, visualize=False):
from hedge.timestep.runge_kutta import LSRK4TimeStepper
from hedge.visualization import SiloVisualizer
from hedge.models.em import MaxwellOperator
vis = SiloVisualizer(discr)
from pyrticle.cloud import PicMethod
from pyrticle.deposition.shape import ShapeFunctionDepositor
method = PicMethod(discr, units,
ShapeFunctionDepositor(),
pusher(),
3, 3, debug=set(["verbose_vis"]))
e, h = setup.fields(discr)
b = units.MU0 * h
init_positions = setup.positions(0)
init_velocities = setup.velocities(0)
nparticles = len(init_positions)
state = method.make_state()
method.add_particles(state,
zip(init_positions, init_velocities,
nparticles * [setup.charge],
nparticles * [units.EL_MASS],
),
nparticles)
final_time = setup.final_time()
nsteps = setup.nsteps()
dt = final_time/nsteps
# timestepping ------------------------------------------------------------
from hedge.models.em import MaxwellOperator
max_op = MaxwellOperator(
epsilon=units.EPSILON0,
mu=units.MU0,
flux_type=1)
fields = max_op.assemble_eh(e, h)
from pyrticle.cloud import \
FieldToParticleRhsCalculator, \
ParticleRhsCalculator
p_rhs_calculator = ParticleRhsCalculator(method, max_op)
f2p_rhs_calculator = FieldToParticleRhsCalculator(method, max_op)
def rhs(t, ts_state):
return (p_rhs_calculator(t, lambda: fields, lambda: ts_state.state)
+ f2p_rhs_calculator(t, lambda: fields, lambda: ts_state.state))
stepper = LSRK4TimeStepper()
t = 0
bbox = discr.mesh.bounding_box()
z_period = bbox[1][2] - bbox[0][2]
def check_result():
from hedge.tools import cross
deriv_dt = 1e-12
dim = discr.dimensions
true_x = setup.positions(t)
true_v = setup.velocities(t)
true_f = [(p2-p1)/(2*deriv_dt)
for p1, p2 in zip(setup.momenta(t-deriv_dt), setup.momenta(t+deriv_dt))]
state = ts_state.state
from pyrticle.tools import NumberShiftableVector
vis_info = state.vis_listener.particle_vis_map
sim_x = state.positions
sim_v = method.velocities(state)
sim_f = NumberShiftableVector.unwrap(
vis_info["mag_force"] + vis_info["el_force"])
sim_el_f = NumberShiftableVector.unwrap(vis_info["el_force"])
sim_mag_f = NumberShiftableVector.unwrap(vis_info["mag_force"])
local_e = setup.e()
local_b = units.MU0 * setup.h()
x_err = 0
v_err = 0
f_err = 0
for i in range(len(state)):
#real_f = numpy.array(cross(sim_v, setup.charge*local_b)) + setup.charge*local_e
my_true_x = true_x[i]
my_true_x[2] = my_true_x[2] % z_period
if False and i == 0:
#print "particle %d" % i
print "pos:", la.norm(true_x[i]-sim_x[i])/la.norm(true_x[i])
#print "vel:", la.norm(true_v[i]-sim_v[i])/la.norm(true_v[i])
#print "force:", la.norm(true_f[i]-sim_f[i])/la.norm(true_f[i])
print "pos:", true_x[i], sim_x[i]
#print "vel:", true_v[i], sim_v[i]
#print "force:", true_f[i], sim_f[i]
#print "forces%d:..." % i, sim_el_f[i], sim_mag_f[i]
#print "acc%d:" % i, la.norm(a-sim_a)
#u = numpy.vstack((v, sim_v, f, sim_f, real_f))
#print "acc%d:\n%s" % (i, u)
#raw_input()
def rel_err(sim, true):
return la.norm(true-sim)/la.norm(true)
x_err = max(x_err, rel_err(sim_x[i], my_true_x))
v_err = max(v_err, rel_err(sim_v[i], true_v[i]))
f_err = max(f_err, rel_err(sim_f[i], true_f[i]))
return x_err, v_err, f_err
# make sure verbose-vis fields are filled
from pyrticle.cloud import TimesteppablePicState
ts_state = TimesteppablePicState(method, state)
del state
rhs(t, ts_state)
errors = (0, 0, 0)
for step in xrange(nsteps):
if step % int(setup.nsteps()/300) == 0:
errors = tuple(
max(old_err, new_err)
for old_err, new_err in zip(errors, check_result()))
if visualize:
visf = vis.make_file("%s-%04d" % (casename, step))
method.add_to_vis(vis, visf, ts_state.state, time=t, step=step)
if True:
vis.add_data(visf, [ ("e", e), ("h", h), ],
time=t, step=step)
else:
vis.add_data(visf, [], time=t, step=step)
visf.close()
method.upkeep(ts_state.state)
ts_state = stepper(ts_state, t, dt, rhs)
t += dt
assert errors[0] < 2e-12, casename+"-pos"
assert errors[1] < 2e-13, casename+"-vel"
assert errors[2] < 2e-4, casename+"-acc"
vis.close()
def __init__(self):
from pyrticle.units import SIUnitsWithNaturalConstants
self.units = units = SIUnitsWithNaturalConstants()
ui = PICCPyUserInterface(units)
setup = self.setup = ui.gather()
from pytools.log import LogManager
import os.path
self.logmgr = LogManager(os.path.join(setup.output_path, "pic.dat"),
"w")
from hedge.backends import guess_run_context
self.rcon = guess_run_context([])
if self.rcon.is_head_rank:
mesh = self.rcon.distribute_mesh(setup.mesh)
else:
mesh = self.rcon.receive_mesh()
self.discr = discr = \
self.rcon.make_discretization(mesh,
order=setup.element_order,
debug=setup.dg_debug)
self.logmgr.set_constant("elements_total", len(setup.mesh.elements))
self.logmgr.set_constant("elements_local", len(mesh.elements))
self.logmgr.set_constant("element_order", setup.element_order)
# em operator ---------------------------------------------------------
maxwell_kwargs = {
"epsilon": units.EPSILON0,
"mu": units.MU0,
"flux_type": setup.maxwell_flux_type,
"bdry_flux_type": setup.maxwell_bdry_flux_type
}
if discr.dimensions == 3:
from hedge.models.em import MaxwellOperator
self.maxwell_op = MaxwellOperator(**maxwell_kwargs)
elif discr.dimensions == 2:
from hedge.models.em import TEMaxwellOperator
self.maxwell_op = TEMaxwellOperator(**maxwell_kwargs)
else:
raise ValueError, "invalid mesh dimension"
if setup.chi is not None:
from pyrticle.hyperbolic import ECleaningMaxwellOperator
self.maxwell_op = ECleaningMaxwellOperator(
self.maxwell_op, chi=setup.chi, phi_decay=setup.phi_decay)
if setup.phi_filter is not None:
from pyrticle.hyperbolic import PhiFilter
from hedge.discretization import Filter, ExponentialFilterResponseFunction
em_filters.append(
PhiFilter(
maxwell_op,
Filter(
discr,
ExponentialFilterResponseFunction(
*setup.phi_filter))))
# timestepping setup --------------------------------------------------
goal_dt = self.maxwell_op.estimate_timestep(discr) * setup.dt_scale
self.nsteps = int(setup.final_time / goal_dt) + 1
self.dt = setup.final_time / self.nsteps
self.stepper = setup.timestepper_maker(self.dt)
# particle setup ------------------------------------------------------
from pyrticle.cloud import PicMethod, PicState, \
optimize_shape_bandwidth, \
guess_shape_bandwidth
method = self.method = PicMethod(
discr,
units,
setup.depositor,
setup.pusher,
dimensions_pos=setup.dimensions_pos,
dimensions_velocity=setup.dimensions_velocity,
debug=setup.debug)
self.state = method.make_state()
method.add_particles(self.state,
setup.distribution.generate_particles(),
setup.nparticles)
self.total_charge = setup.nparticles * setup.distribution.mean()[2][0]
if isinstance(setup.shape_bandwidth, str):
if setup.shape_bandwidth == "optimize":
optimize_shape_bandwidth(
method, self.state,
setup.distribution.get_rho_interpolant(
discr, self.total_charge), setup.shape_exponent)
elif setup.shape_bandwidth == "guess":
guess_shape_bandwidth(method, self.state, setup.shape_exponent)
else:
raise ValueError, "invalid shape bandwidth setting '%s'" % (
setup.shape_bandwidth)
else:
from pyrticle._internal import PolynomialShapeFunction
method.depositor.set_shape_function(
self.state,
PolynomialShapeFunction(
float(setup.shape_bandwidth),
method.mesh_data.dimensions,
setup.shape_exponent,
))
# initial condition ---------------------------------------------------
if "no_ic" in setup.debug:
self.fields = self.maxwell_op.assemble_eh(discr=discr)
else:
from pyrticle.cloud import compute_initial_condition
self.fields = compute_initial_condition(
self.rcon,
discr,
method,
self.state,
maxwell_op=self.maxwell_op,
potential_bc=setup.potential_bc,
force_zero=False)
# rhs calculators -----------------------------------------------------
from pyrticle.cloud import \
FieldRhsCalculator, \
FieldToParticleRhsCalculator, \
ParticleRhsCalculator, \
ParticleToFieldRhsCalculator
self.f_rhs_calculator = FieldRhsCalculator(self.method,
self.maxwell_op)
self.p_rhs_calculator = ParticleRhsCalculator(self.method,
self.maxwell_op)
self.f2p_rhs_calculator = FieldToParticleRhsCalculator(
self.method, self.maxwell_op)
self.p2f_rhs_calculator = ParticleToFieldRhsCalculator(
self.method, self.maxwell_op)
# instrumentation setup -----------------------------------------------
self.add_instrumentation(self.logmgr)
def main(write_output=True,
allow_features=None,
flux_type_arg=1,
bdry_flux_type_arg=None,
extra_discr_args={}):
from hedge.mesh.generator import make_cylinder_mesh, make_box_mesh
from hedge.tools import EOCRecorder, to_obj_array
from math import sqrt, pi # noqa
from analytic_solutions import ( # noqa
RealPartAdapter, SplitComplexAdapter, CylindricalFieldAdapter,
CylindricalCavityMode, RectangularWaveguideMode, RectangularCavityMode)
from hedge.models.em import MaxwellOperator
logging.basicConfig(level=logging.DEBUG)
from hedge.backends import guess_run_context
rcon = guess_run_context(allow_features)
epsilon0 = 8.8541878176e-12 # C**2 / (N m**2)
mu0 = 4 * pi * 1e-7 # N/A**2.
epsilon = 1 * epsilon0
mu = 1 * mu0
eoc_rec = EOCRecorder()
cylindrical = False
periodic = False
if cylindrical:
R = 1
d = 2
mode = CylindricalCavityMode(m=1,
n=1,
p=1,
radius=R,
height=d,
epsilon=epsilon,
mu=mu)
# r_sol = CylindricalFieldAdapter(RealPartAdapter(mode))
# c_sol = SplitComplexAdapter(CylindricalFieldAdapter(mode))
if rcon.is_head_rank:
mesh = make_cylinder_mesh(radius=R, height=d, max_volume=0.01)
else:
if periodic:
mode = RectangularWaveguideMode(epsilon, mu, (3, 2, 1))
periodicity = (False, False, True)
else:
periodicity = None
mode = RectangularCavityMode(epsilon, mu, (1, 2, 2))
if rcon.is_head_rank:
mesh = make_box_mesh(max_volume=0.001, periodicity=periodicity)
if rcon.is_head_rank:
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [4, 5, 6]:
#for order in [1,2,3,4,5,6]:
extra_discr_args.setdefault("debug", []).extend(
["cuda_no_plan", "cuda_dump_kernels"])
op = MaxwellOperator(epsilon,
mu,
flux_type=flux_type_arg,
bdry_flux_type=bdry_flux_type_arg)
discr = rcon.make_discretization(mesh_data,
order=order,
tune_for=op.op_template(),
**extra_discr_args)
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(discr, rcon, "em-%d" % order)
mode.set_time(0)
def get_true_field():
return discr.convert_volume(to_obj_array(
mode(discr).real.astype(discr.default_scalar_type).copy()),
kind=discr.compute_kind)
fields = get_true_field()
if rcon.is_head_rank:
print "---------------------------------------------"
print "order %d" % order
print "---------------------------------------------"
print "#elements=", len(mesh.elements)
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper(dtype=discr.default_scalar_type, rcon=rcon)
#from hedge.timestep.dumka3 import Dumka3TimeStepper
#stepper = Dumka3TimeStepper(3, dtype=discr.default_scalar_type, rcon=rcon)
# {{{ diagnostics setup
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
if write_output:
log_file_name = "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)
final_time = 0.5e-9
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 % 50 == 0 and write_output:
sub_timer = vis_timer.start_sub_timer()
e, h = op.split_eh(fields)
visf = vis.make_file("em-%d-%04d" % (order, step))
vis.add_data(visf, [
("e", discr.convert_volume(e, kind="numpy")),
("h", discr.convert_volume(h, kind="numpy")),
],
time=t,
step=step)
visf.close()
sub_timer.stop().submit()
fields = stepper(fields, t, dt, rhs)
mode.set_time(final_time)
eoc_rec.add_data_point(order,
discr.norm(fields - get_true_field()))
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
if rcon.is_head_rank:
print
print eoc_rec.pretty_print("P.Deg.", "L2 Error")
# }}}
assert eoc_rec.estimate_order_of_convergence()[0, 1] > 6
