def estimate_timestep(self, discr,
stepper=None, stepper_class=None, stepper_args=None,
t=None, fields=None):
u"""Estimate the largest stable timestep, given a time stepper
`stepper_class`. If none is given, RK4 is assumed.
"""
rk4_dt = 0.2 \
* (discr.dt_non_geometric_factor()
* discr.dt_geometric_factor())**2
from hedge.timestep.stability import \
approximate_rk4_relative_imag_stability_region
return rk4_dt * approximate_rk4_relative_imag_stability_region(
stepper, stepper_class, stepper_args)
def estimate_timestep(self, discr,
stepper=None, stepper_class=None, stepper_args=None,
t=None, max_eigenvalue=None):
u"""Estimate the largest stable timestep, given a time stepper
`stepper_class`. If none is given, RK4 is assumed.
"""
dg_factor = (discr.dt_non_geometric_factor()
* discr.dt_geometric_factor())
# see JSH/TW, eq. (7.32)
rk4_dt = dg_factor / (max_eigenvalue + self.mu / dg_factor)
from hedge.timestep.stability import \
approximate_rk4_relative_imag_stability_region
return rk4_dt * approximate_rk4_relative_imag_stability_region(
stepper, stepper_class, stepper_args)
def estimate_timestep(self,
discr,
stepper=None,
stepper_class=None,
stepper_args=None,
t=None,
max_eigenvalue=None):
u"""Estimate the largest stable timestep, given a time stepper
`stepper_class`. If none is given, RK4 is assumed.
"""
dg_factor = (discr.dt_non_geometric_factor() *
discr.dt_geometric_factor())
# see JSH/TW, eq. (7.32)
rk4_dt = dg_factor / (max_eigenvalue + self.mu / dg_factor)
from hedge.timestep.stability import \
approximate_rk4_relative_imag_stability_region
return rk4_dt * approximate_rk4_relative_imag_stability_region(
stepper, stepper_class, stepper_args)
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,
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()
