def __init__(self, t0, y0, dt):
self.t = [t0]
self.y = [y0]
self.dt = dt
from hedge.timestep.runge_kutta import LSRK4TimeStepper
self.forward_stepper = LSRK4TimeStepper()
self.backward_stepper = LSRK4TimeStepper()
def __init__(self,
order,
startup_stepper=None,
dtype=numpy.float64,
rcon=None):
self.f_history = []
from pytools import match_precision
self.dtype = numpy.dtype(dtype)
self.scalar_dtype = match_precision(numpy.dtype(numpy.float64),
self.dtype)
self.coefficients = numpy.asarray(make_ab_coefficients(order),
dtype=self.scalar_dtype)
if startup_stepper is not None:
self.startup_stepper = startup_stepper
else:
from hedge.timestep.runge_kutta import LSRK4TimeStepper
self.startup_stepper = LSRK4TimeStepper(self.dtype)
from pytools.log import IntervalTimer, EventCounter
timer_factory = IntervalTimer
if rcon is not None:
timer_factory = rcon.make_timer
self.timer = timer_factory(
"t_ab", "Time spent doing algebra in Adams-Bashforth")
self.flop_counter = EventCounter(
"n_flops_ab", "Floating point operations performed in AB")
def __init__(self,
method,
large_dt,
substep_count,
order,
order_f2f=None,
order_s2f=None,
order_f2s=None,
order_s2s=None,
startup_stepper=None):
if isinstance(method, str):
from hedge.timestep.multirate_ab.methods import methods
self.method_name = method
method = methods[method]
else:
self.method_name = None
self.method = method
self.large_dt = large_dt
self.small_dt = large_dt / substep_count
self.substep_count = substep_count
from hedge.timestep.multirate_ab.methods import \
HIST_F2F, HIST_S2F, HIST_F2S, HIST_S2S
self.orders = {
HIST_F2F: order_f2f,
HIST_S2F: order_s2f,
HIST_F2S: order_f2s,
HIST_S2S: order_s2s,
}
for hn in HIST_NAMES:
if self.orders[hn] is None:
self.orders[hn] = order
self.max_order = max(self.orders.values())
# histories of rhs evaluations
self.histories = dict((hn, []) for hn in HIST_NAMES)
if startup_stepper is not None:
self.startup_stepper = startup_stepper
else:
self.startup_stepper = LSRK4TimeStepper()
self.startup_history = []
self.hist_is_fast = {
HIST_F2F: True,
HIST_S2F: self.method.s2f_hist_is_fast,
HIST_S2S: False,
HIST_F2S: False
}
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,
dir_tag=TAG_NONE,
neu_tag=TAG_NONE,
rad_tag=TAG_ALL,
flux_type_arg="upwind"):
from math import sin, cos, pi, exp, sqrt # noqa
from hedge.backends import guess_run_context
rcon = guess_run_context()
dim = 2
if dim == 1:
if rcon.is_head_rank:
from hedge.mesh.generator import make_uniform_1d_mesh
mesh = make_uniform_1d_mesh(-10, 10, 500)
elif dim == 2:
from hedge.mesh.generator import make_rect_mesh
if rcon.is_head_rank:
mesh = make_rect_mesh(a=(-1, -1), b=(1, 1), max_area=0.003)
elif dim == 3:
if rcon.is_head_rank:
from hedge.mesh.generator import make_ball_mesh
mesh = make_ball_mesh(max_volume=0.0005)
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=4)
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper()
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(discr, rcon, "fld")
source_center = np.array([0.7, 0.4])
source_width = 1 / 16
source_omega = 3
import hedge.optemplate as sym
sym_x = sym.nodes(2)
sym_source_center_dist = sym_x - source_center
from hedge.models.wave import VariableVelocityStrongWaveOperator
op = VariableVelocityStrongWaveOperator(
c=sym.If(sym.Comparison(np.dot(sym_x, sym_x), "<", 0.4**2), 1, 0.5),
dimensions=discr.dimensions,
source=sym.CFunction("sin")(source_omega * sym.ScalarParameter("t")) *
sym.CFunction("exp")(
-np.dot(sym_source_center_dist, sym_source_center_dist) /
source_width**2),
dirichlet_tag=dir_tag,
neumann_tag=neu_tag,
radiation_tag=rad_tag,
flux_type=flux_type_arg)
from hedge.tools import join_fields
fields = join_fields(
discr.volume_zeros(),
[discr.volume_zeros() for i in range(discr.dimensions)])
# {{{ diagnostics setup
from pytools.log import LogManager, \
add_general_quantities, \
add_simulation_quantities, \
add_run_info
if write_output:
log_file_name = "wave.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 pytools.log import IntervalTimer
vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(vis_timer)
stepper.add_instrumentation(logmgr)
from hedge.log import LpNorm
u_getter = lambda: fields[0]
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
rhs = op.bind(discr)
try:
from hedge.timestep.stability import \
approximate_rk4_relative_imag_stability_region
max_dt = (1 / discr.compile(op.max_eigenvalue_expr())() *
discr.dt_non_geometric_factor() *
discr.dt_geometric_factor() *
approximate_rk4_relative_imag_stability_region(stepper))
if flux_type_arg == "central":
max_dt *= 0.25
from hedge.timestep import times_and_steps
step_it = times_and_steps(final_time=3,
logmgr=logmgr,
max_dt_getter=lambda t: max_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", fields[0]),
("v", fields[1:]),
],
time=t,
step=step)
visf.close()
fields = stepper(fields, t, dt, rhs)
assert discr.norm(fields) < 1
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
def main(write_output=True):
from math import sin, exp, sqrt # noqa
from hedge.mesh.generator import make_rect_mesh
mesh = make_rect_mesh(a=(-0.5, -0.5), b=(0.5, 0.5), max_area=0.008)
from hedge.backends.jit import Discretization
discr = Discretization(mesh, order=4)
from hedge.visualization import VtkVisualizer
vis = VtkVisualizer(discr, None, "fld")
source_center = np.array([0.1, 0.22])
source_width = 0.05
source_omega = 3
import hedge.optemplate as sym
sym_x = sym.nodes(2)
sym_source_center_dist = sym_x - source_center
from hedge.models.wave import StrongWaveOperator
from hedge.mesh import TAG_ALL, TAG_NONE
op = StrongWaveOperator(
-0.1,
discr.dimensions,
source_f=sym.CFunction("sin")(
source_omega * sym.ScalarParameter("t")) * sym.CFunction("exp")(
-np.dot(sym_source_center_dist, sym_source_center_dist) /
source_width**2),
dirichlet_tag=TAG_NONE,
neumann_tag=TAG_NONE,
radiation_tag=TAG_ALL,
flux_type="upwind")
from hedge.tools import join_fields
fields = join_fields(
discr.volume_zeros(),
[discr.volume_zeros() for i in range(discr.dimensions)])
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper()
dt = op.estimate_timestep(discr, stepper=stepper, fields=fields)
nsteps = int(10 / dt)
print "dt=%g nsteps=%d" % (dt, nsteps)
rhs = op.bind(discr)
for step in range(nsteps):
t = step * dt
if step % 10 == 0 and write_output:
print step, t, discr.norm(fields[0])
visf = vis.make_file("fld-%04d" % step)
vis.add_data(visf, [
("u", fields[0]),
("v", fields[1:]),
],
time=t,
step=step)
visf.close()
fields = stepper(fields, t, dt, rhs)
vis.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 main(write_output=True,
dir_tag=TAG_NONE,
neu_tag=TAG_NONE,
rad_tag=TAG_ALL,
flux_type_arg="upwind",
dtype=np.float64,
debug=[]):
from math import sin, cos, pi, exp, sqrt # noqa
from hedge.backends import guess_run_context
rcon = guess_run_context()
dim = 2
if dim == 1:
if rcon.is_head_rank:
from hedge.mesh.generator import make_uniform_1d_mesh
mesh = make_uniform_1d_mesh(-10, 10, 500)
elif dim == 2:
from hedge.mesh.generator import make_rect_mesh
if rcon.is_head_rank:
mesh = make_rect_mesh(a=(-0.5, -0.5), b=(0.5, 0.5), max_area=0.008)
elif dim == 3:
if rcon.is_head_rank:
from hedge.mesh.generator import make_ball_mesh
mesh = make_ball_mesh(max_volume=0.0005)
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()
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper(dtype=dtype)
from hedge.models.wave import StrongWaveOperator
from hedge.mesh import TAG_ALL, TAG_NONE # noqa
source_center = np.array([0.1, 0.22])
source_width = 0.05
source_omega = 3
import hedge.optemplate as sym
sym_x = sym.nodes(2)
sym_source_center_dist = sym_x - source_center
op = StrongWaveOperator(
-1,
dim,
source_f=sym.CFunction("sin")(
source_omega * sym.ScalarParameter("t")) * sym.CFunction("exp")(
-np.dot(sym_source_center_dist, sym_source_center_dist) /
source_width**2),
dirichlet_tag=dir_tag,
neumann_tag=neu_tag,
radiation_tag=rad_tag,
flux_type=flux_type_arg)
discr = rcon.make_discretization(mesh_data,
order=4,
debug=debug,
default_scalar_type=dtype,
tune_for=op.op_template())
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(discr, rcon, "fld")
from hedge.tools import join_fields
fields = join_fields(
discr.volume_zeros(dtype=dtype),
[discr.volume_zeros(dtype=dtype) for i in range(discr.dimensions)])
# {{{ diagnostics setup
from pytools.log import LogManager, \
add_general_quantities, \
add_simulation_quantities, \
add_run_info
if write_output:
log_file_name = "wave.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 pytools.log import IntervalTimer
vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(vis_timer)
stepper.add_instrumentation(logmgr)
from hedge.log import LpNorm
u_getter = lambda: fields[0]
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
rhs = op.bind(discr)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=4,
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:
visf = vis.make_file("fld-%04d" % step)
vis.add_data(visf, [
("u", discr.convert_volume(fields[0], kind="numpy")),
("v", discr.convert_volume(fields[1:], kind="numpy")),
],
time=t,
step=step)
visf.close()
fields = stepper(fields, t, dt, rhs)
assert discr.norm(fields) < 1
assert fields[0].dtype == dtype
finally:
if write_output:
vis.close()
logmgr.close()
discr.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 # 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
def main(write_output=True):
from hedge.timestep.runge_kutta import LSRK4TimeStepper
from math import sqrt, pi, exp
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
c = 1 / sqrt(mu * epsilon)
pml_width = 0.5
#mesh = make_mesh(a=np.array((-1,-1,-1)), b=np.array((1,1,1)),
#mesh = make_mesh(a=np.array((-3,-3)), b=np.array((3,3)),
mesh = make_mesh(
a=np.array((-1, -1)),
b=np.array((1, 1)),
#mesh = make_mesh(a=np.array((-2,-2)), b=np.array((2,2)),
pml_width=pml_width,
max_volume=0.01)
if rcon.is_head_rank:
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
class Current:
def volume_interpolant(self, t, discr):
from hedge.tools import make_obj_array
result = discr.volume_zeros(kind="numpy", dtype=np.float64)
omega = 6 * c
if omega * t > 2 * pi:
return make_obj_array([result, result, result])
x = make_obj_array(discr.nodes.T)
r = np.sqrt(np.dot(x, x))
idx = r < 0.3
result[idx] = (1+np.cos(pi*r/0.3))[idx] \
*np.sin(omega*t)**3
result = discr.convert_volume(result,
kind=discr.compute_kind,
dtype=discr.default_scalar_type)
return make_obj_array([-result, result, result])
order = 3
discr = rcon.make_discretization(mesh_data,
order=order,
debug=["cuda_no_plan"])
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(discr, rcon, "em-%d" % order)
from hedge.mesh import TAG_ALL, TAG_NONE
from hedge.data import GivenFunction, TimeHarmonicGivenFunction, TimeIntervalGivenFunction
from hedge.models.em import MaxwellOperator
from hedge.models.pml import \
AbarbanelGottliebPMLMaxwellOperator, \
AbarbanelGottliebPMLTMMaxwellOperator, \
AbarbanelGottliebPMLTEMaxwellOperator
op = AbarbanelGottliebPMLTEMaxwellOperator(epsilon,
mu,
flux_type=1,
current=Current(),
pec_tag=TAG_ALL,
absorb_tag=TAG_NONE,
add_decay=True)
fields = op.assemble_ehpq(discr=discr)
stepper = LSRK4TimeStepper()
if rcon.is_head_rank:
print "order %d" % order
print "#elements=", len(mesh.elements)
# 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"])
from hedge.log import LpNorm
class FieldIdxGetter:
def __init__(self, whole_getter, idx):
self.whole_getter = whole_getter
self.idx = idx
def __call__(self):
return self.whole_getter()[self.idx]
# timestep loop -------------------------------------------------------
t = 0
pml_coeff = op.coefficients_from_width(discr, width=pml_width)
rhs = op.bind(discr, pml_coeff)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=4 / c,
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, p, q = op.split_ehpq(fields)
visf = vis.make_file("em-%d-%04d" % (order, step))
#pml_rhs_e, pml_rhs_h, pml_rhs_p, pml_rhs_q = \
#op.split_ehpq(rhs(t, fields))
j = Current().volume_interpolant(t, discr)
vis.add_data(
visf,
[
("e", discr.convert_volume(e, "numpy")),
("h", discr.convert_volume(h, "numpy")),
("p", discr.convert_volume(p, "numpy")),
("q", discr.convert_volume(q, "numpy")),
("j", discr.convert_volume(j, "numpy")),
#("pml_rhs_e", pml_rhs_e),
#("pml_rhs_h", pml_rhs_h),
#("pml_rhs_p", pml_rhs_p),
#("pml_rhs_q", pml_rhs_q),
#("max_rhs_e", max_rhs_e),
#("max_rhs_h", max_rhs_h),
#("max_rhs_p", max_rhs_p),
#("max_rhs_q", max_rhs_q),
],
time=t,
step=step)
visf.close()
fields = stepper(fields, t, dt, rhs)
_, _, energies_data = logmgr.get_expr_dataset("W_el+W_mag")
energies = [value for tick_nbr, value in energies_data]
assert energies[-1] < max(energies) * 1e-2
finally:
logmgr.close()
if write_output:
vis.close()
def main(write_output=True,
flux_type_arg="upwind",
dtype=np.float64,
debug=[]):
from math import sin, cos, pi, exp, sqrt # noqa
from hedge.backends import guess_run_context
rcon = guess_run_context()
if rcon.is_head_rank:
from hedge.mesh.reader.gmsh import generate_gmsh
mesh = generate_gmsh(GEOMETRY,
2,
allow_internal_boundaries=True,
force_dimension=2)
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=4,
debug=debug,
default_scalar_type=dtype)
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper(dtype=dtype)
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(discr, rcon, "fld")
source_center = 0
source_width = 0.05
source_omega = 3
import hedge.optemplate as sym
sym_x = sym.nodes(2)
sym_source_center_dist = sym_x - source_center
from hedge.models.wave import StrongWaveOperator
op = StrongWaveOperator(
-1,
discr.dimensions,
source_f=sym.CFunction("sin")(
source_omega * sym.ScalarParameter("t")) * sym.CFunction("exp")(
-np.dot(sym_source_center_dist, sym_source_center_dist) /
source_width**2),
dirichlet_tag="boundary",
neumann_tag=TAG_NONE,
radiation_tag=TAG_NONE,
flux_type=flux_type_arg)
from hedge.tools import join_fields
fields = join_fields(
discr.volume_zeros(dtype=dtype),
[discr.volume_zeros(dtype=dtype) for i in range(discr.dimensions)])
# diagnostics setup -------------------------------------------------------
from pytools.log import LogManager, \
add_general_quantities, \
add_simulation_quantities, \
add_run_info
if write_output:
log_file_name = "wiggly.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)
logmgr.add_watches(["step.max", "t_sim.max", "t_step.max"])
# timestep loop -----------------------------------------------------------
rhs = op.bind(discr)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=4,
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:
visf = vis.make_file("fld-%04d" % step)
vis.add_data(visf, [
("u", fields[0]),
("v", fields[1:]),
],
time=t,
step=step)
visf.close()
fields = stepper(fields, t, dt, rhs)
assert discr.norm(fields) < 1
assert fields[0].dtype == dtype
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
def main(write_output=True,
flux_type_arg="central",
use_quadrature=True,
final_time=20):
from math import sin, cos, pi, sqrt
from hedge.backends import guess_run_context
rcon = guess_run_context()
# mesh setup --------------------------------------------------------------
if rcon.is_head_rank:
#from hedge.mesh.generator import make_disk_mesh
#mesh = make_disk_mesh()
from hedge.mesh.generator import make_rect_mesh
mesh = make_rect_mesh(a=(-1, -1), b=(1, 1), max_area=0.008)
if rcon.is_head_rank:
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
# space-time-dependent-velocity-field -------------------------------------
# simple vortex
class TimeDependentVField:
""" `TimeDependentVField` is a callable expecting `(x, t)` representing space and time
`x` is of the length of the spatial dimension and `t` is the time."""
shape = (2, )
def __call__(self, pt, el, t):
x, y = pt
# Correction-Factor to make the speed zero on the on the boundary
#fac = (1-x**2)*(1-y**2)
fac = 1.
return numpy.array([-y * fac, x * fac]) * cos(pi * t)
class VField:
""" `VField` is a callable expecting `(x)` representing space
`x` is of the length of the spatial dimension."""
shape = (2, )
def __call__(self, pt, el):
x, y = pt
# Correction-Factor to make the speed zero on the on the boundary
#fac = (1-x**2)*(1-y**2)
fac = 1.
return numpy.array([-y * fac, x * fac])
# space-time-dependent State BC (optional)-----------------------------------
class TimeDependentBc_u:
""" space and time dependent BC for state u"""
def __call__(self, pt, el, t):
x, y = pt
if t <= 0.5:
if x > 0:
return 1
else:
return 0
else:
return 0
class Bc_u:
""" Only space dependent BC for state u"""
def __call__(seld, pt, el):
x, y = pt
if x > 0:
return 1
else:
return 0
# operator setup ----------------------------------------------------------
# In the operator setup it is possible to switch between a only space
# dependent velocity field `VField` or a time and space dependent
# `TimeDependentVField`.
# For `TimeDependentVField`: advec_v=TimeDependentGivenFunction(VField())
# For `VField`: advec_v=TimeConstantGivenFunction(GivenFunction(VField()))
# Same for the Bc_u Function! If you don't define Bc_u then the BC for u = 0.
from hedge.data import \
ConstantGivenFunction, \
TimeConstantGivenFunction, \
TimeDependentGivenFunction, \
GivenFunction
from hedge.models.advection import VariableCoefficientAdvectionOperator
op = VariableCoefficientAdvectionOperator(
mesh.dimensions,
#advec_v=TimeDependentGivenFunction(
# TimeDependentVField()),
advec_v=TimeConstantGivenFunction(GivenFunction(VField())),
#bc_u_f=TimeDependentGivenFunction(
# TimeDependentBc_u()),
bc_u_f=TimeConstantGivenFunction(GivenFunction(Bc_u())),
flux_type=flux_type_arg)
# discretization setup ----------------------------------------------------
order = 5
if use_quadrature:
quad_min_degrees = {"quad": 3 * order}
else:
quad_min_degrees = {}
discr = rcon.make_discretization(
mesh_data,
order=order,
default_scalar_type=numpy.float64,
debug=["cuda_no_plan"],
quad_min_degrees=quad_min_degrees,
tune_for=op.op_template(),
)
vis_discr = discr
# visualization setup -----------------------------------------------------
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(vis_discr, rcon, "fld")
# initial condition -------------------------------------------------------
if True:
def initial(pt, el):
# Gauss pulse
from math import exp
x = (pt - numpy.array([0.3, 0.5])) * 8
return exp(-numpy.dot(x, x))
else:
def initial(pt, el):
# Rectangle
x, y = pt
if abs(x) < 0.5 and abs(y) < 0.2:
return 2
else:
return 1
u = discr.interpolate_volume_function(initial)
# timestep setup ----------------------------------------------------------
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper(
vector_primitive_factory=discr.get_vector_primitive_factory())
if rcon.is_head_rank:
print "%d elements" % len(discr.mesh.elements)
# filter setup-------------------------------------------------------------
from hedge.discretization import ExponentialFilterResponseFunction
from hedge.optemplate.operators import FilterOperator
mode_filter = FilterOperator(
ExponentialFilterResponseFunction(min_amplification=0.9,order=4))\
.bind(discr)
# diagnostics setup -------------------------------------------------------
from pytools.log import LogManager, \
add_general_quantities, \
add_simulation_quantities, \
add_run_info
if write_output:
log_file_name = "space-dep.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"])
# Initialize v for data output:
v = op.advec_v.volume_interpolant(0, discr)
# 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=u))
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")),
("v", discr.convert_volume(v, kind="numpy"))],
time=t,
step=step)
visf.close()
u = stepper(u, t, dt, rhs)
# We're feeding in a discontinuity through the BCs.
# Quadrature does not help with shock capturing--
# therefore we do need to filter here, regardless
# of whether quadrature is enabled.
u = mode_filter(u)
assert discr.norm(u) < 10
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()
def __init__(self, units):
from pyrticle.deposition.shape import \
ShapeFunctionDepositor, \
NormalizedShapeFunctionDepositor
from pyrticle.deposition.advective import \
AdvectiveDepositor
from pyrticle.deposition.grid import \
GridDepositor
from pyrticle.deposition.grid_find import \
GridFindDepositor
from pyrticle.deposition.grid_base import \
SingleBrickGenerator, \
FineCoreBrickGenerator
from pyrticle.pusher import \
MonomialParticlePusher, \
AverageParticlePusher
import pyrticle.geometry
import pyrticle.distribution
constants = {
"numpy": numpy,
"la": numpy.linalg,
"units": units,
"pyrticle": pyrticle,
"DepShape": ShapeFunctionDepositor,
"DepNormShape": NormalizedShapeFunctionDepositor,
"DepAdv": AdvectiveDepositor,
"DepGrid": GridDepositor,
"DepGridFind": GridFindDepositor,
"SingleBrickGenerator": SingleBrickGenerator,
"FineCoreBrickGenerator": FineCoreBrickGenerator,
"PushMonomial": MonomialParticlePusher,
"PushAverage": AverageParticlePusher,
}
import hedge.data
from hedge.timestep.runge_kutta import LSRK4TimeStepper
variables = {
"pusher":
None,
"depositor":
None,
"mesh":
None,
"dimensions_pos":
None,
"dimensions_velocity":
None,
"beam_axis":
None,
"beam_diag_axis":
None,
"tube_length":
None,
"element_order":
None,
"maxwell_flux_type":
"lf",
"maxwell_bdry_flux_type":
1,
"shape_exponent":
2,
"shape_bandwidth":
"optimize",
"chi":
None,
"phi_decay":
0,
"phi_filter":
None,
"potential_bc":
hedge.data.ConstantGivenFunction(),
"final_time":
None,
"nparticles":
20000,
"distribution":
None,
"vis_interval":
100,
"vis_pattern":
"pic-%04d",
"vis_order":
None,
"output_path":
".",
"debug":
set(["ic", "poisson", "shape_bw"]),
"dg_debug":
set(),
"profile_output_filename":
None,
"watch_vars": [
"step", "t_sim", ("W_field", "W_el+W_mag"), "t_step", "t_eta",
"n_part"
],
"hook_startup":
lambda runner: None,
"hook_after_step":
lambda runner, state: None,
"hook_when_done":
lambda runner: None,
"hook_vis_quantities":
lambda observer: [
("e", observer.e),
("h", observer.h),
("j", observer.method.deposit_j(observer.state)),
],
"hook_visualize":
lambda runner, vis, visf, observer: None,
"timestepper_maker":
lambda dt: LSRK4TimeStepper(),
"dt_scale":
1,
}
doc = {
"chi":
"relative speed of hyp. cleaning (None for no cleaning)",
"nparticles":
"how many particles",
"vis_interval":
"how often a visualization of the fields is written",
"max_volume_inner":
"max. tet volume in inner mesh [m^3]",
"max_volume_outer":
"max. tet volume in outer mesh [m^3]",
"shape_bandwidth":
"either 'optimize', 'guess' or a positive real number",
"phi_filter":
"a tuple (min_amp, order) or None, describing the filtering applied to phi in hypclean mode",
}
pytools.CPyUserInterface.__init__(self, variables, constants, doc)
stepper.add_instrumentation(logmgr)
try:
from hedge.timestep import times_and_steps
# for visc=0.01
#stab_fac = 0.1 # RK4
#stab_fac = 1.6 # dumka3(3), central
#stab_fac = 3 # dumka3(4), central
#stab_fac = 0.01 # RK4
stab_fac = 0.2 # dumka3(3), central
#stab_fac = 3 # dumka3(4), central
dt = stab_fac * op.estimate_timestep(
discr, stepper=LSRK4TimeStepper(), t=0, fields=u)
step_it = times_and_steps(final_time=case.final_time,
logmgr=logmgr,
max_dt_getter=lambda t: dt)
from hedge.optemplate import InverseVandermondeOperator
inv_vdm = InverseVandermondeOperator().bind(discr)
for step, t, dt in step_it:
if step % 3 == 0 and write_output:
if hasattr(case, "u_exact"):
extra_fields = [("u_exact",
discr.interpolate_volume_function(
lambda x, el: case.u_exact(x[0], t)))]
else:
extra_fields = []
def main(write_output=True, dtype=np.float32):
from hedge.backends import guess_run_context
rcon = guess_run_context()
from hedge.mesh.generator import make_rect_mesh
if rcon.is_head_rank:
h_fac = 1
mesh = make_rect_mesh(a=(0, 0),
b=(1, 1),
max_area=h_fac**2 * 1e-4,
periodicity=(True, True),
subdivisions=(int(70 / h_fac), int(70 / h_fac)))
from hedge.models.gas_dynamics.lbm import \
D2Q9LBMMethod, LatticeBoltzmannOperator
op = LatticeBoltzmannOperator(D2Q9LBMMethod(), lbm_delta_t=0.001, nu=1e-4)
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,
default_scalar_type=dtype,
debug=["cuda_no_plan"])
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper(
dtype=dtype,
#vector_primitive_factory=discr.get_vector_primitive_factory()
)
from hedge.visualization import VtkVisualizer
if write_output:
vis = VtkVisualizer(discr, rcon, "fld")
from hedge.data import CompiledExpressionData
def ic_expr(t, x, fields):
from hedge.optemplate import CFunction
from pymbolic.primitives import IfPositive
from pytools.obj_array import make_obj_array
tanh = CFunction("tanh")
sin = CFunction("sin")
rho = 1
u0 = 0.05
w = 0.05
delta = 0.05
from hedge.optemplate.primitives import make_common_subexpression as cse
u = cse(
make_obj_array([
IfPositive(x[1] - 1 / 2, u0 * tanh(4 * (3 / 4 - x[1]) / w),
u0 * tanh(4 * (x[1] - 1 / 4) / w)),
u0 * delta * sin(2 * np.pi * (x[0] + 1 / 4))
]), "u")
return make_obj_array([
op.method.f_equilibrium(rho, alpha, u)
for alpha in range(len(op.method))
])
# timestep loop -----------------------------------------------------------
stream_rhs = op.bind_rhs(discr)
collision_update = op.bind(discr, op.collision_update)
get_rho = op.bind(discr, op.rho)
get_rho_u = op.bind(discr, op.rho_u)
f_bar = CompiledExpressionData(ic_expr).volume_interpolant(0, discr)
from hedge.discretization import ExponentialFilterResponseFunction
from hedge.optemplate.operators import FilterOperator
mode_filter = FilterOperator(
ExponentialFilterResponseFunction(min_amplification=0.9, order=4))\
.bind(discr)
final_time = 1000
try:
lbm_dt = op.lbm_delta_t
dg_dt = op.estimate_timestep(discr, stepper=stepper)
print dg_dt
dg_steps_per_lbm_step = int(np.ceil(lbm_dt / dg_dt))
dg_dt = lbm_dt / dg_steps_per_lbm_step
lbm_steps = int(final_time // op.lbm_delta_t)
for step in xrange(lbm_steps):
t = step * lbm_dt
if step % 100 == 0 and write_output:
visf = vis.make_file("fld-%04d" % step)
rho = get_rho(f_bar)
rho_u = get_rho_u(f_bar)
vis.add_data(
visf,
[("fbar%d" % i, discr.convert_volume(f_bar_i, "numpy"))
for i, f_bar_i in enumerate(f_bar)] + [
("rho", discr.convert_volume(rho, "numpy")),
("rho_u", discr.convert_volume(rho_u, "numpy")),
],
time=t,
step=step)
visf.close()
print "step=%d, t=%f" % (step, t)
f_bar = collision_update(f_bar)
for substep in range(dg_steps_per_lbm_step):
f_bar = stepper(f_bar, t + substep * dg_dt, dg_dt, stream_rhs)
#f_bar = mode_filter(f_bar)
finally:
if write_output:
vis.close()
discr.close()
def main(write_output=True, allow_features=None, flux_type_arg=1,
bdry_flux_type_arg=None, extra_discr_args={}):
from math import sqrt, pi
from hedge.models.em import TEMaxwellOperator
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.
c = 1/sqrt(mu0*epsilon0)
materials = {"vacuum" : (epsilon0, mu0),
"dielectric" : (2*epsilon0, mu0)}
output_dir = "2d_cavity"
import os
if not os.access(output_dir, os.F_OK):
os.makedirs(output_dir)
# should no tag raise an error or default to free space?
def eps_val(x, el):
for key in materials.keys():
if el in material_elements[key]:
return materials[key][0]
raise ValueError, "Element does not belong to any material"
def mu_val(x, el):
for key in materials.keys():
if el in material_elements[key]:
return materials[key][1]
raise ValueError, "Element does not belong to any material"
# geometry of cavity
d = 100e-3
a = 150e-3
# analytical frequency and transverse wavenumbers of resonance
f0 = 9.0335649907522321e8
h = 2*pi*f0/c
l = -h*sqrt(2)
# substitute the following and change materials for a homogeneous cavity
#h = pi/a
#l =-h
def initial_val(discr):
# the initial solution for the TE_10-like mode
def initial_Hz(x, el):
from math import cos, sin
if el in material_elements["vacuum"]:
return h*cos(h*x[0])
else:
return -l*sin(h*d)/sin(l*(a-d))*cos(l*(a-x[0]))
from hedge.tools import make_obj_array
result_zero = discr.volume_zeros(kind="numpy", dtype=numpy.float64)
H_z = make_tdep_given(initial_Hz).volume_interpolant(0, discr)
return make_obj_array([result_zero, result_zero, H_z])
if rcon.is_head_rank:
from hedge.mesh.reader.gmsh import generate_gmsh
mesh = generate_gmsh(CAVITY_GEOMETRY, 2, force_dimension=2)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
# Work out which elements belong to each material
material_elements = {}
for key in materials.keys():
material_elements[key] = set(mesh_data.tag_to_elements[key])
order = 3
#extra_discr_args.setdefault("debug", []).append("cuda_no_plan")
#extra_discr_args.setdefault("debug", []).append("dump_optemplate_stages")
from hedge.data import make_tdep_given
from hedge.mesh import TAG_ALL
op = TEMaxwellOperator(epsilon=make_tdep_given(eps_val), mu=make_tdep_given(mu_val), \
flux_type=flux_type_arg, \
bdry_flux_type=bdry_flux_type_arg, dimensions=2, pec_tag=TAG_ALL)
# op = TEMaxwellOperator(epsilon=epsilon0, mu=mu0,
# flux_type=flux_type_arg, \
# bdry_flux_type=bdry_flux_type_arg, dimensions=2, pec_tag=TAG_ALL)
discr = rcon.make_discretization(mesh_data, order=order,
tune_for=op.op_template(),
**extra_discr_args)
# create the initial solution
fields = initial_val(discr)
from hedge.visualization import VtkVisualizer
if write_output:
from os.path import join
vis = VtkVisualizer(discr, rcon, join(output_dir, "cav-%d" % order))
# monitor the solution at a point to find the resonant frequency
try:
point_getter = discr.get_point_evaluator(numpy.array([75e-3, 25e-3, 0])) #[0.25, 0.25, 0.25]))
except RuntimeError:
point_getter = None
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:
from os.path import join
log_file_name = join(output_dir, "cavity-%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 = 10e-9
if point_getter is not None:
from os.path import join
pointfile = open(join(output_dir, "point.txt"), "wt")
done_dt = False
try:
from hedge.timestep import times_and_steps
from os.path import join
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:
sub_timer = vis_timer.start_sub_timer()
e, h = op.split_eh(fields)
visf = vis.make_file(join(output_dir, "cav-%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)
if point_getter is not None:
val = point_getter(fields)
#print val
if not done_dt:
pointfile.write("#%g\n" % dt)
done_dt = True
pointfile.write("%g\n" %val[0])
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
if point_getter is not None:
pointfile.close()
def test_kv_with_no_charge():
from random import seed
seed(0)
from pyrticle.units import SIUnitsWithNaturalConstants
units = SIUnitsWithNaturalConstants()
# discretization setup ----------------------------------------------------
from hedge.mesh import make_cylinder_mesh
from hedge.backends import guess_run_context
rcon = guess_run_context([])
tube_length = 100 * units.MM
mesh = make_cylinder_mesh(radius=25 * units.MM,
height=tube_length,
periodic=True)
discr = rcon.make_discretization(mesh, order=3)
dt = discr.dt_factor(units.VACUUM_LIGHT_SPEED()) / 2
final_time = 1 * units.M / units.VACUUM_LIGHT_SPEED()
nsteps = int(final_time / dt) + 1
dt = final_time / nsteps
# 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)
nparticles = 10000
cloud_charge = 1e-9 * units.C
electrons_per_particle = cloud_charge / nparticles / units.EL_CHARGE
el_energy = 5.2e6 * units.EV
gamma = el_energy / units.EL_REST_ENERGY()
beta = (1 - 1 / gamma**2)**0.5
from pyrticle.distribution import KVZIntervalBeam
beam = KVZIntervalBeam(units,
total_charge=0,
p_charge=0,
p_mass=electrons_per_particle * units.EL_MASS,
radii=2 * [2.5 * units.MM],
emittances=2 * [5 * units.MM * units.MRAD],
z_length=5 * units.MM,
z_pos=10 * units.MM,
beta=beta)
state = method.make_state()
method.add_particles(state, beam.generate_particles(), nparticles)
# diagnostics setup -------------------------------------------------------
from pytools.log import LogManager
from pyrticle.log import add_beam_quantities, StateObserver
observer = StateObserver(method, None)
logmgr = LogManager(mode="w")
add_beam_quantities(logmgr, observer, axis=0, beam_axis=2)
from pyrticle.distribution import KVPredictedRadius
logmgr.add_quantity(
KVPredictedRadius(dt,
beam_v=beta * units.VACUUM_LIGHT_SPEED(),
predictor=beam.get_rms_predictor(axis=0),
suffix="x_rms"))
logmgr.add_quantity(
KVPredictedRadius(dt,
beam_v=beta * units.VACUUM_LIGHT_SPEED(),
predictor=beam.get_total_predictor(axis=0),
suffix="x_total"))
# timestep loop -----------------------------------------------------------
vel = method.velocities(state)
from hedge.tools import join_fields
def rhs(t, y):
return join_fields([
vel,
0 * vel,
0, # drecon
])
from hedge.timestep.runge_kutta import LSRK4TimeStepper
stepper = LSRK4TimeStepper()
t = 0
from pyrticle.cloud import TimesteppablePicState
ts_state = TimesteppablePicState(method, state)
for step in xrange(nsteps):
observer.set_fields_and_state(None, ts_state.state)
logmgr.tick()
ts_state = stepper(ts_state, t, dt, rhs)
method.upkeep(ts_state.state)
t += dt
logmgr.tick()
_, _, err_table = logmgr.get_expr_dataset(
"(rx_rms-rx_rms_theory)/rx_rms_theory")
rel_max_rms_error = max(err for step, err in err_table)
assert rel_max_rms_error < 0.01
def main():
import logging
logging.basicConfig(level=logging.INFO)
from hedge.backends import guess_run_context
rcon = guess_run_context()
if rcon.is_head_rank:
if True:
mesh = make_squaremesh()
else:
from hedge.mesh import make_rect_mesh
mesh = make_rect_mesh(
boundary_tagger=lambda fvi, el, fn, all_v: ["inflow"],
max_area=0.1)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
from pytools import add_python_path_relative_to_script
add_python_path_relative_to_script(".")
for order in [3]:
from gas_dynamics_initials import UniformMachFlow
square = UniformMachFlow(gaussian_pulse_at=numpy.array([-2, 2]),
pulse_magnitude=0.003)
from hedge.models.gas_dynamics import (GasDynamicsOperator,
GammaLawEOS)
op = GasDynamicsOperator(dimensions=2,
equation_of_state=GammaLawEOS(square.gamma),
mu=square.mu,
prandtl=square.prandtl,
spec_gas_const=square.spec_gas_const,
bc_inflow=square,
bc_outflow=square,
bc_noslip=square,
inflow_tag="inflow",
outflow_tag="outflow",
noslip_tag="noslip")
discr = rcon.make_discretization(
mesh_data,
order=order,
debug=[
"cuda_no_plan",
"cuda_dump_kernels",
#"dump_dataflow_graph",
#"dump_optemplate_stages",
#"dump_dataflow_graph",
#"dump_op_code"
#"cuda_no_plan_el_local"
],
default_scalar_type=numpy.float64,
tune_for=op.op_template(),
quad_min_degrees={
"gasdyn_vol": 3 * order,
"gasdyn_face": 3 * order,
})
from hedge.visualization import SiloVisualizer, VtkVisualizer
#vis = VtkVisualizer(discr, rcon, "shearflow-%d" % order)
vis = SiloVisualizer(discr, rcon)
from hedge.timestep.runge_kutta import (LSRK4TimeStepper,
ODE23TimeStepper,
ODE45TimeStepper)
from hedge.timestep.dumka3 import Dumka3TimeStepper
#stepper = LSRK4TimeStepper(dtype=discr.default_scalar_type,
#vector_primitive_factory=discr.get_vector_primitive_factory())
stepper = ODE23TimeStepper(
dtype=discr.default_scalar_type,
rtol=1e-6,
vector_primitive_factory=discr.get_vector_primitive_factory())
# Dumka works kind of poorly
#stepper = Dumka3TimeStepper(dtype=discr.default_scalar_type,
#rtol=1e-7, pol_index=2,
#vector_primitive_factory=discr.get_vector_primitive_factory())
#from hedge.timestep.dumka3 import Dumka3TimeStepper
#stepper = Dumka3TimeStepper(3, rtol=1e-7)
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
logmgr = LogManager("cns-square-sp-%d.dat" % order, "w",
rcon.communicator)
add_run_info(logmgr)
add_general_quantities(logmgr)
discr.add_instrumentation(logmgr)
stepper.add_instrumentation(logmgr)
from pytools.log import LogQuantity
class ChangeSinceLastStep(LogQuantity):
"""Records the change of a variable between a time step and the previous
one"""
def __init__(self, name="change"):
LogQuantity.__init__(self, name, "1",
"Change since last time step")
self.old_fields = 0
def __call__(self):
result = discr.norm(fields - self.old_fields)
self.old_fields = fields
return result
#logmgr.add_quantity(ChangeSinceLastStep())
add_simulation_quantities(logmgr)
logmgr.add_watches(["step.max", "t_sim.max", "t_step.max"])
# filter setup ------------------------------------------------------------
from hedge.discretization import Filter, ExponentialFilterResponseFunction
mode_filter = Filter(
discr,
ExponentialFilterResponseFunction(min_amplification=0.95, order=6))
# timestep loop -------------------------------------------------------
fields = square.volume_interpolant(0, discr)
navierstokes_ex = op.bind(discr)
max_eigval = [0]
def rhs(t, q):
ode_rhs, speed = navierstokes_ex(t, q)
max_eigval[0] = speed
return ode_rhs
rhs(0, fields)
if rcon.is_head_rank:
print "---------------------------------------------"
print "order %d" % order
print "---------------------------------------------"
print "#elements=", len(mesh.elements)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=1000,
#max_steps=500,
logmgr=logmgr,
max_dt_getter=lambda t: next_dt,
taken_dt_getter=lambda: taken_dt)
model_stepper = LSRK4TimeStepper()
next_dt = op.estimate_timestep(discr,
stepper=model_stepper,
t=0,
max_eigenvalue=max_eigval[0])
for step, t, dt in step_it:
#if (step % 10000 == 0): #and step < 950000) or (step % 500 == 0 and step > 950000):
#if False:
if step % 5 == 0:
visf = vis.make_file("square-%d-%06d" % (order, step))
#from pyvisfile.silo import DB_VARTYPE_VECTOR
vis.add_data(visf, [
("rho",
discr.convert_volume(op.rho(fields), kind="numpy")),
("e", discr.convert_volume(op.e(fields),
kind="numpy")),
("rho_u",
discr.convert_volume(op.rho_u(fields), kind="numpy")),
("u", discr.convert_volume(op.u(fields),
kind="numpy")),
],
expressions=[
("p", "(0.4)*(e- 0.5*(rho_u*u))"),
],
time=t,
step=step)
visf.close()
if stepper.adaptive:
fields, t, taken_dt, next_dt = stepper(fields, t, dt, rhs)
else:
taken_dt = dt
fields = stepper(fields, t, dt, rhs)
dt = op.estimate_timestep(discr,
stepper=model_stepper,
t=0,
max_eigenvalue=max_eigval[0])
#fields = mode_filter(fields)
finally:
vis.close()
logmgr.save()
discr.close()