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 __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)
class PICRunner(object):
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 add_instrumentation(self, logmgr):
from pytools.log import \
add_simulation_quantities, \
add_general_quantities, \
add_run_info, ETA
from pyrticle.log import add_particle_quantities, add_field_quantities, \
add_beam_quantities, add_currents
setup = self.setup
from pyrticle.log import StateObserver
self.observer = StateObserver(self.method, self.maxwell_op)
self.observer.set_fields_and_state(self.fields, self.state)
add_run_info(logmgr)
add_general_quantities(logmgr)
add_simulation_quantities(logmgr)
add_particle_quantities(logmgr, self.observer)
add_field_quantities(logmgr, self.observer)
if setup.beam_axis is not None and setup.beam_diag_axis is not None:
add_beam_quantities(logmgr, self.observer,
axis=setup.beam_diag_axis,
beam_axis=setup.beam_axis)
if setup.tube_length is not None:
from hedge.tools import unit_vector
add_currents(logmgr, self.observer,
unit_vector(self.method.dimensions_velocity, setup.beam_axis),
setup.tube_length)
self.method.add_instrumentation(logmgr, self.observer)
self.f_rhs_calculator.add_instrumentation(logmgr)
if hasattr(self.stepper, "add_instrumentation"):
self.stepper.add_instrumentation(logmgr)
mean_beta = self.method.mean_beta(self.state)
gamma = self.method.units.gamma_from_beta(mean_beta)
logmgr.set_constant("dt", self.dt)
logmgr.set_constant("beta", mean_beta)
logmgr.set_constant("gamma", gamma)
logmgr.set_constant("v", mean_beta*self.units.VACUUM_LIGHT_SPEED())
logmgr.set_constant("Q0", self.total_charge)
logmgr.set_constant("n_part_0", setup.nparticles)
logmgr.set_constant("pmass", setup.distribution.mean()[3][0])
logmgr.set_constant("chi", setup.chi)
logmgr.set_constant("phi_decay", setup.phi_decay)
logmgr.set_constant("shape_radius_setup", setup.shape_bandwidth)
logmgr.set_constant("shape_radius", self.method.depositor.shape_function.radius)
logmgr.set_constant("shape_exponent", self.method.depositor.shape_function.exponent)
from pytools.log import IntervalTimer
self.vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(self.vis_timer)
logmgr.add_quantity(ETA(self.nsteps))
logmgr.add_watches(setup.watch_vars)
def inner_run(self):
t = 0
setup = self.setup
setup.hook_startup(self)
vis_order = setup.vis_order
if vis_order is None:
vis_order = setup.element_order
if vis_order != setup.element_order:
vis_discr = self.rcon.make_discretization(self.discr.mesh,
order=vis_order, debug=setup.dg_debug)
from hedge.discretization import Projector
vis_proj = Projector(self.discr, vis_discr)
else:
vis_discr = self.discr
def vis_proj(f):
return f
from hedge.visualization import SiloVisualizer
vis = SiloVisualizer(vis_discr)
fields = self.fields
self.observer.set_fields_and_state(fields, self.state)
from hedge.tools import make_obj_array
from pyrticle.cloud import TimesteppablePicState
def visualize(observer):
sub_timer = self.vis_timer.start_sub_timer()
import os.path
visf = vis.make_file(os.path.join(
setup.output_path, setup.vis_pattern % step))
self.method.add_to_vis(vis, visf, observer.state, time=t, step=step)
vis.add_data(visf,
[(name, vis_proj(fld))
for name, fld in setup.hook_vis_quantities(observer)],
time=t, step=step)
setup.hook_visualize(self, vis, visf, observer)
visf.close()
sub_timer.stop().submit()
from hedge.timestep.multirate_ab import TwoRateAdamsBashforthTimeStepper
if not isinstance(self.stepper, TwoRateAdamsBashforthTimeStepper):
def rhs(t, fields_and_state):
fields, ts_state = fields_and_state
state_f = lambda: ts_state.state
fields_f = lambda: fields
fields_rhs = (
self.f_rhs_calculator(t, fields_f, state_f)
+ self.p2f_rhs_calculator(t, fields_f, state_f))
state_rhs = (
self.p_rhs_calculator(t, fields_f, state_f)
+ self.f2p_rhs_calculator(t, fields_f, state_f))
return make_obj_array([fields_rhs, state_rhs])
step_args = (self.dt, rhs)
else:
def add_unwrap(rhs):
def unwrapping_rhs(t, fields, ts_state):
return rhs(t, fields, lambda: ts_state().state)
return unwrapping_rhs
step_args = ((
add_unwrap(self.f_rhs_calculator),
add_unwrap(self.p2f_rhs_calculator),
add_unwrap(self.f2p_rhs_calculator),
add_unwrap(self.p_rhs_calculator),
),)
y = make_obj_array([
fields,
TimesteppablePicState(self.method, self.state)
])
del self.state
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
max_steps=self.nsteps,
logmgr=self.logmgr,
max_dt_getter=lambda t: self.dt)
for step, t, dt in step_it:
self.method.upkeep(y[1].state)
if step % setup.vis_interval == 0:
visualize(self.observer)
y = self.stepper(y, t, *step_args)
fields, ts_state = y
self.observer.set_fields_and_state(fields, ts_state.state)
setup.hook_after_step(self, self.observer)
finally:
vis.close()
self.discr.close()
self.logmgr.save()
setup.hook_when_done(self)
def run(self):
if self.setup.profile_output_filename is not None:
from cProfile import Profile
prof = Profile()
try:
prof.runcall(self.inner_run)
finally:
from lsprofcalltree import KCacheGrind
kg = KCacheGrind(prof)
kg.output(open(self.setup.profile_output_filename, "w"))
else:
self.inner_run()
class PICRunner(object):
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 add_instrumentation(self, logmgr):
from pytools.log import \
add_simulation_quantities, \
add_general_quantities, \
add_run_info, ETA
from pyrticle.log import add_particle_quantities, add_field_quantities, \
add_beam_quantities, add_currents
setup = self.setup
from pyrticle.log import StateObserver
self.observer = StateObserver(self.method, self.maxwell_op)
self.observer.set_fields_and_state(self.fields, self.state)
add_run_info(logmgr)
add_general_quantities(logmgr)
add_simulation_quantities(logmgr)
add_particle_quantities(logmgr, self.observer)
add_field_quantities(logmgr, self.observer)
if setup.beam_axis is not None and setup.beam_diag_axis is not None:
add_beam_quantities(logmgr,
self.observer,
axis=setup.beam_diag_axis,
beam_axis=setup.beam_axis)
if setup.tube_length is not None:
from hedge.tools import unit_vector
add_currents(
logmgr, self.observer,
unit_vector(self.method.dimensions_velocity, setup.beam_axis),
setup.tube_length)
self.method.add_instrumentation(logmgr, self.observer)
self.f_rhs_calculator.add_instrumentation(logmgr)
if hasattr(self.stepper, "add_instrumentation"):
self.stepper.add_instrumentation(logmgr)
mean_beta = self.method.mean_beta(self.state)
gamma = self.method.units.gamma_from_beta(mean_beta)
logmgr.set_constant("dt", self.dt)
logmgr.set_constant("beta", mean_beta)
logmgr.set_constant("gamma", gamma)
logmgr.set_constant("v", mean_beta * self.units.VACUUM_LIGHT_SPEED())
logmgr.set_constant("Q0", self.total_charge)
logmgr.set_constant("n_part_0", setup.nparticles)
logmgr.set_constant("pmass", setup.distribution.mean()[3][0])
logmgr.set_constant("chi", setup.chi)
logmgr.set_constant("phi_decay", setup.phi_decay)
logmgr.set_constant("shape_radius_setup", setup.shape_bandwidth)
logmgr.set_constant("shape_radius",
self.method.depositor.shape_function.radius)
logmgr.set_constant("shape_exponent",
self.method.depositor.shape_function.exponent)
from pytools.log import IntervalTimer
self.vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(self.vis_timer)
logmgr.add_quantity(ETA(self.nsteps))
logmgr.add_watches(setup.watch_vars)
def inner_run(self):
t = 0
setup = self.setup
setup.hook_startup(self)
vis_order = setup.vis_order
if vis_order is None:
vis_order = setup.element_order
if vis_order != setup.element_order:
vis_discr = self.rcon.make_discretization(self.discr.mesh,
order=vis_order,
debug=setup.dg_debug)
from hedge.discretization import Projector
vis_proj = Projector(self.discr, vis_discr)
else:
vis_discr = self.discr
def vis_proj(f):
return f
from hedge.visualization import SiloVisualizer
vis = SiloVisualizer(vis_discr)
fields = self.fields
self.observer.set_fields_and_state(fields, self.state)
from hedge.tools import make_obj_array
from pyrticle.cloud import TimesteppablePicState
def visualize(observer):
sub_timer = self.vis_timer.start_sub_timer()
import os.path
visf = vis.make_file(
os.path.join(setup.output_path, setup.vis_pattern % step))
self.method.add_to_vis(vis,
visf,
observer.state,
time=t,
step=step)
vis.add_data(
visf, [(name, vis_proj(fld))
for name, fld in setup.hook_vis_quantities(observer)],
time=t,
step=step)
setup.hook_visualize(self, vis, visf, observer)
visf.close()
sub_timer.stop().submit()
from hedge.timestep.multirate_ab import TwoRateAdamsBashforthTimeStepper
if not isinstance(self.stepper, TwoRateAdamsBashforthTimeStepper):
def rhs(t, fields_and_state):
fields, ts_state = fields_and_state
state_f = lambda: ts_state.state
fields_f = lambda: fields
fields_rhs = (self.f_rhs_calculator(t, fields_f, state_f) +
self.p2f_rhs_calculator(t, fields_f, state_f))
state_rhs = (self.p_rhs_calculator(t, fields_f, state_f) +
self.f2p_rhs_calculator(t, fields_f, state_f))
return make_obj_array([fields_rhs, state_rhs])
step_args = (self.dt, rhs)
else:
def add_unwrap(rhs):
def unwrapping_rhs(t, fields, ts_state):
return rhs(t, fields, lambda: ts_state().state)
return unwrapping_rhs
step_args = ((
add_unwrap(self.f_rhs_calculator),
add_unwrap(self.p2f_rhs_calculator),
add_unwrap(self.f2p_rhs_calculator),
add_unwrap(self.p_rhs_calculator),
), )
y = make_obj_array(
[fields, TimesteppablePicState(self.method, self.state)])
del self.state
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(max_steps=self.nsteps,
logmgr=self.logmgr,
max_dt_getter=lambda t: self.dt)
for step, t, dt in step_it:
self.method.upkeep(y[1].state)
if step % setup.vis_interval == 0:
visualize(self.observer)
y = self.stepper(y, t, *step_args)
fields, ts_state = y
self.observer.set_fields_and_state(fields, ts_state.state)
setup.hook_after_step(self, self.observer)
finally:
vis.close()
self.discr.close()
self.logmgr.save()
setup.hook_when_done(self)
def run(self):
if self.setup.profile_output_filename is not None:
from cProfile import Profile
prof = Profile()
try:
prof.runcall(self.inner_run)
finally:
from lsprofcalltree import KCacheGrind
kg = KCacheGrind(prof)
kg.output(open(self.setup.profile_output_filename, "w"))
else:
self.inner_run()
