def main(write_output=True):
from hedge.backends import guess_run_context
rcon = guess_run_context(
#["cuda"]
)
gamma = 1.4
# at A=1 we have case of isentropic vortex, source terms
# arise for other values
densityA = 2.0
from hedge.tools import EOCRecorder, to_obj_array
eoc_rec = EOCRecorder()
if rcon.is_head_rank:
from hedge.mesh import \
make_rect_mesh, \
make_centered_regular_rect_mesh
refine = 1
mesh = make_centered_regular_rect_mesh((0,-5), (10,5), n=(9,9),
post_refine_factor=refine)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [4,5]:
discr = rcon.make_discretization(mesh_data, order=order,
debug=[#"cuda_no_plan",
#"print_op_code"
],
default_scalar_type=numpy.float64)
from hedge.visualization import SiloVisualizer, VtkVisualizer
#vis = VtkVisualizer(discr, rcon, "vortex-%d" % order)
vis = SiloVisualizer(discr, rcon)
vortex = Vortex(beta=5, gamma=gamma,
center=[5,0],
velocity=[1,0], densityA=densityA)
fields = vortex.volume_interpolant(0, discr)
sources=SourceTerms(beta=5, gamma=gamma,
center=[5,0],
velocity=[1,0], densityA=densityA)
from hedge.models.gas_dynamics import (
GasDynamicsOperator, GammaLawEOS)
from hedge.mesh import TAG_ALL
op = GasDynamicsOperator(dimensions=2,
mu=0.0, prandtl=0.72, spec_gas_const=287.1,
equation_of_state=GammaLawEOS(vortex.gamma),
bc_inflow=vortex, bc_outflow=vortex, bc_noslip=vortex,
inflow_tag=TAG_ALL, source=sources)
euler_ex = op.bind(discr)
max_eigval = [0]
def rhs(t, q):
ode_rhs, speed = euler_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)
# limiter setup -------------------------------------------------------
from hedge.models.gas_dynamics import SlopeLimiter1NEuler
limiter = SlopeLimiter1NEuler(discr, gamma, 2, op)
# time stepper --------------------------------------------------------
from hedge.timestep import SSPRK3TimeStepper, RK4TimeStepper
#stepper = SSPRK3TimeStepper(limiter=limiter)
#stepper = SSPRK3TimeStepper()
stepper = RK4TimeStepper()
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
if write_output:
log_file_name = "euler-%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)
logmgr.add_watches(["step.max", "t_sim.max", "t_step.max"])
# timestep loop -------------------------------------------------------
t = 0
#fields = limiter(fields)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=.1,
#max_steps=500,
logmgr=logmgr,
max_dt_getter=lambda t: 0.4*op.estimate_timestep(discr,
stepper=stepper, t=t, max_eigenvalue=max_eigval[0]))
for step, t, dt in step_it:
if step % 1 == 0 and write_output:
#if False:
visf = vis.make_file("vortex-%d-%04d" % (order, step))
true_fields = vortex.volume_interpolant(t, discr)
#rhs_fields = rhs(t, fields)
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")),
#("true_rho", discr.convert_volume(op.rho(true_fields), kind="numpy")),
#("true_e", discr.convert_volume(op.e(true_fields), kind="numpy")),
#("true_rho_u", discr.convert_volume(op.rho_u(true_fields), kind="numpy")),
#("true_u", discr.convert_volume(op.u(true_fields), kind="numpy")),
#("rhs_rho", discr.convert_volume(op.rho(rhs_fields), kind="numpy")),
#("rhs_e", discr.convert_volume(op.e(rhs_fields), kind="numpy")),
#("rhs_rho_u", discr.convert_volume(op.rho_u(rhs_fields), kind="numpy")),
],
expressions=[
#("diff_rho", "rho-true_rho"),
#("diff_e", "e-true_e"),
#("diff_rho_u", "rho_u-true_rho_u", DB_VARTYPE_VECTOR),
("p", "0.4*(e- 0.5*(rho_u*u))"),
],
time=t, step=step
)
visf.close()
fields = stepper(fields, t, dt, rhs)
true_fields = vortex.volume_interpolant(t, discr)
l2_error = discr.norm(fields-true_fields)
l2_error_rho = discr.norm(op.rho(fields)-op.rho(true_fields))
l2_error_e = discr.norm(op.e(fields)-op.e(true_fields))
l2_error_rhou = discr.norm(op.rho_u(fields)-op.rho_u(true_fields))
l2_error_u = discr.norm(op.u(fields)-op.u(true_fields))
eoc_rec.add_data_point(order, l2_error_rho)
print
print eoc_rec.pretty_print("P.Deg.", "L2 Error")
logmgr.set_constant("l2_error", l2_error)
logmgr.set_constant("l2_error_rho", l2_error_rho)
logmgr.set_constant("l2_error_e", l2_error_e)
logmgr.set_constant("l2_error_rhou", l2_error_rhou)
logmgr.set_constant("l2_error_u", l2_error_u)
logmgr.set_constant("refinement", refine)
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
def main():
from hedge.backends import guess_run_context
rcon = guess_run_context(
#["cuda"]
)
from hedge.tools import EOCRecorder, to_obj_array
eoc_rec = EOCRecorder()
def boundary_tagger(vertices, el, face_nr, all_v):
return ["inflow"]
if rcon.is_head_rank:
from hedge.mesh import make_rect_mesh, \
make_centered_regular_rect_mesh
#mesh = make_rect_mesh((0,0), (10,1), max_area=0.01)
refine = 1
mesh = make_centered_regular_rect_mesh(
(0, 0),
(10, 1),
n=(20, 4),
#periodicity=(True, False),
post_refine_factor=refine,
boundary_tagger=boundary_tagger)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [3]:
discr = rcon.make_discretization(mesh_data,
order=order,
default_scalar_type=numpy.float64)
from hedge.visualization import SiloVisualizer, VtkVisualizer
#vis = VtkVisualizer(discr, rcon, "shearflow-%d" % order)
vis = SiloVisualizer(discr, rcon)
shearflow = SteadyShearFlow()
fields = shearflow.volume_interpolant(0, discr)
gamma, mu, prandtl, spec_gas_const = shearflow.properties()
from hedge.models.gas_dynamics import GasDynamicsOperator
op = GasDynamicsOperator(dimensions=2,
gamma=gamma,
mu=mu,
prandtl=prandtl,
spec_gas_const=spec_gas_const,
bc_inflow=shearflow,
bc_outflow=shearflow,
bc_noslip=shearflow,
inflow_tag="inflow",
outflow_tag="outflow",
noslip_tag="noslip")
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
# needed to get first estimate of maximum eigenvalue
rhs(0, fields)
if rcon.is_head_rank:
print "---------------------------------------------"
print "order %d" % order
print "---------------------------------------------"
print "#elements=", len(mesh.elements)
from hedge.timestep import RK4TimeStepper
stepper = RK4TimeStepper()
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
logmgr = LogManager("navierstokes-cpu-%d-%d.dat" % (order, refine),
"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 -------------------------------------------------------
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=0.3,
#max_steps=500,
logmgr=logmgr,
max_dt_getter=lambda t: op.estimate_timestep(
discr, stepper=stepper, t=t, max_eigenvalue=max_eigval[0]))
for step, t, dt in step_it:
if step % 10 == 0:
#if False:
visf = vis.make_file("shearflow-%d-%04d" % (order, step))
#true_fields = shearflow.volume_interpolant(t, discr)
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")),
#("true_rho", discr.convert_volume(op.rho(true_fields), kind="numpy")),
#("true_e", discr.convert_volume(op.e(true_fields), kind="numpy")),
#("true_rho_u", discr.convert_volume(op.rho_u(true_fields), kind="numpy")),
#("true_u", discr.convert_volume(op.u(true_fields), kind="numpy")),
],
expressions=[
#("diff_rho", "rho-true_rho"),
#("diff_e", "e-true_e"),
#("diff_rho_u", "rho_u-true_rho_u", DB_VARTYPE_VECTOR),
("p", "0.4*(e- 0.5*(rho_u*u))"),
],
time=t,
step=step)
visf.close()
fields = stepper(fields, t, dt, rhs)
true_fields = shearflow.volume_interpolant(t, discr)
l2_error = discr.norm(op.u(fields) - op.u(true_fields))
eoc_rec.add_data_point(order, l2_error)
print
print eoc_rec.pretty_print("P.Deg.", "L2 Error")
logmgr.set_constant("l2_error", l2_error)
finally:
vis.close()
logmgr.save()
discr.close()
def run_setup(units, casename, setup, discr, pusher, visualize=False):
from hedge.timestep.runge_kutta import LSRK4TimeStepper
from hedge.visualization import SiloVisualizer
from hedge.models.em import MaxwellOperator
vis = SiloVisualizer(discr)
from pyrticle.cloud import PicMethod
from pyrticle.deposition.shape import ShapeFunctionDepositor
method = PicMethod(discr,
units,
ShapeFunctionDepositor(),
pusher(),
3,
3,
debug=set(["verbose_vis"]))
e, h = setup.fields(discr)
b = units.MU0 * h
init_positions = setup.positions(0)
init_velocities = setup.velocities(0)
nparticles = len(init_positions)
state = method.make_state()
method.add_particles(
state,
zip(
init_positions,
init_velocities,
nparticles * [setup.charge],
nparticles * [units.EL_MASS],
), nparticles)
final_time = setup.final_time()
nsteps = setup.nsteps()
dt = final_time / nsteps
# timestepping ------------------------------------------------------------
from hedge.models.em import MaxwellOperator
max_op = MaxwellOperator(epsilon=units.EPSILON0, mu=units.MU0, flux_type=1)
fields = max_op.assemble_eh(e, h)
from pyrticle.cloud import \
FieldToParticleRhsCalculator, \
ParticleRhsCalculator
p_rhs_calculator = ParticleRhsCalculator(method, max_op)
f2p_rhs_calculator = FieldToParticleRhsCalculator(method, max_op)
def rhs(t, ts_state):
return (p_rhs_calculator(t, lambda: fields, lambda: ts_state.state) +
f2p_rhs_calculator(t, lambda: fields, lambda: ts_state.state))
stepper = LSRK4TimeStepper()
t = 0
bbox = discr.mesh.bounding_box()
z_period = bbox[1][2] - bbox[0][2]
def check_result():
from hedge.tools import cross
deriv_dt = 1e-12
dim = discr.dimensions
true_x = setup.positions(t)
true_v = setup.velocities(t)
true_f = [(p2 - p1) / (2 * deriv_dt) for p1, p2 in zip(
setup.momenta(t - deriv_dt), setup.momenta(t + deriv_dt))]
state = ts_state.state
from pyrticle.tools import NumberShiftableVector
vis_info = state.vis_listener.particle_vis_map
sim_x = state.positions
sim_v = method.velocities(state)
sim_f = NumberShiftableVector.unwrap(vis_info["mag_force"] +
vis_info["el_force"])
sim_el_f = NumberShiftableVector.unwrap(vis_info["el_force"])
sim_mag_f = NumberShiftableVector.unwrap(vis_info["mag_force"])
local_e = setup.e()
local_b = units.MU0 * setup.h()
x_err = 0
v_err = 0
f_err = 0
for i in range(len(state)):
#real_f = numpy.array(cross(sim_v, setup.charge*local_b)) + setup.charge*local_e
my_true_x = true_x[i]
my_true_x[2] = my_true_x[2] % z_period
if False and i == 0:
#print "particle %d" % i
print "pos:", la.norm(true_x[i] - sim_x[i]) / la.norm(
true_x[i])
#print "vel:", la.norm(true_v[i]-sim_v[i])/la.norm(true_v[i])
#print "force:", la.norm(true_f[i]-sim_f[i])/la.norm(true_f[i])
print "pos:", true_x[i], sim_x[i]
#print "vel:", true_v[i], sim_v[i]
#print "force:", true_f[i], sim_f[i]
#print "forces%d:..." % i, sim_el_f[i], sim_mag_f[i]
#print "acc%d:" % i, la.norm(a-sim_a)
#u = numpy.vstack((v, sim_v, f, sim_f, real_f))
#print "acc%d:\n%s" % (i, u)
#raw_input()
def rel_err(sim, true):
return la.norm(true - sim) / la.norm(true)
x_err = max(x_err, rel_err(sim_x[i], my_true_x))
v_err = max(v_err, rel_err(sim_v[i], true_v[i]))
f_err = max(f_err, rel_err(sim_f[i], true_f[i]))
return x_err, v_err, f_err
# make sure verbose-vis fields are filled
from pyrticle.cloud import TimesteppablePicState
ts_state = TimesteppablePicState(method, state)
del state
rhs(t, ts_state)
errors = (0, 0, 0)
for step in xrange(nsteps):
if step % int(setup.nsteps() / 300) == 0:
errors = tuple(
max(old_err, new_err)
for old_err, new_err in zip(errors, check_result()))
if visualize:
visf = vis.make_file("%s-%04d" % (casename, step))
method.add_to_vis(vis, visf, ts_state.state, time=t, step=step)
if True:
vis.add_data(visf, [
("e", e),
("h", h),
],
time=t,
step=step)
else:
vis.add_data(visf, [], time=t, step=step)
visf.close()
method.upkeep(ts_state.state)
ts_state = stepper(ts_state, t, dt, rhs)
t += dt
assert errors[0] < 2e-12, casename + "-pos"
assert errors[1] < 2e-13, casename + "-vel"
assert errors[2] < 2e-4, casename + "-acc"
vis.close()
def main():
from hedge.backends import guess_run_context
rcon = guess_run_context(["cuda"])
if rcon.is_head_rank:
mesh = make_boxmesh()
#from hedge.mesh import make_rect_mesh
#mesh = make_rect_mesh(
# boundary_tagger=lambda fvi, el, fn, all_v: ["inflow"])
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [3]:
from pytools import add_python_path_relative_to_script
add_python_path_relative_to_script("..")
from gas_dynamics_initials import UniformMachFlow
box = UniformMachFlow(angle_of_attack=0)
from hedge.models.gas_dynamics import GasDynamicsOperator
op = GasDynamicsOperator(dimensions=3,
gamma=box.gamma, mu=box.mu,
prandtl=box.prandtl, spec_gas_const=box.spec_gas_const,
bc_inflow=box, bc_outflow=box, bc_noslip=box,
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",
#"print_op_code",
"cuda_no_plan_el_local",
],
default_scalar_type=numpy.float32,
tune_for=op.op_template())
from hedge.visualization import SiloVisualizer, VtkVisualizer # noqa
#vis = VtkVisualizer(discr, rcon, "shearflow-%d" % order)
vis = SiloVisualizer(discr, rcon)
fields = box.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)
from hedge.timestep import RK4TimeStepper
stepper = RK4TimeStepper()
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
logmgr = LogManager("navierstokes-%d.dat" % order, "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"])
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())
# timestep loop -------------------------------------------------------
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=200,
#max_steps=500,
logmgr=logmgr,
max_dt_getter=lambda t: op.estimate_timestep(discr,
stepper=stepper, t=t, max_eigenvalue=max_eigval[0]))
for step, t, dt in step_it:
if step % 200 == 0:
#if False:
visf = vis.make_file("box-%d-%06d" % (order, step))
#rhs_fields = rhs(t, fields)
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")),
# ("rhs_rho", discr.convert_volume(
# op.rho(rhs_fields), kind="numpy")),
# ("rhs_e", discr.convert_volume(
# op.e(rhs_fields), kind="numpy")),
# ("rhs_rho_u", discr.convert_volume(
# op.rho_u(rhs_fields), kind="numpy")),
],
expressions=[
("p", "(0.4)*(e- 0.5*(rho_u*u))"),
],
time=t, step=step
)
visf.close()
fields = stepper(fields, t, dt, rhs)
finally:
vis.close()
logmgr.save()
discr.close()
def optimize_shape_bandwidth(method, state, analytic_rho, exponent):
discr = method.discretization
rec = method.depositor
adv_radius = method.mesh_data.advisable_particle_radius()
radii = [adv_radius * 2**i for i in numpy.linspace(-4, 2, 50)]
def set_radius(r):
method.depositor.set_shape_function(
state,
method.get_shape_function_class()(
r,
method.mesh_data.dimensions,
exponent,
))
tried_radii = []
l1_errors = []
debug = "shape_bw" in method.debug
visualize = set(["shape_bw", "vis_files"]) <= method.debug
if visualize:
from hedge.visualization import SiloVisualizer
vis = SiloVisualizer(discr)
import sys
if debug:
sys.stdout.write("optimizing shape bw (%d attempts): " % len(radii))
for step, radius in enumerate(radii):
if debug:
sys.stdout.write("%d." % step)
sys.stdout.flush()
try:
try:
method.set_ignore_core_warnings(True)
set_radius(radius)
except RuntimeError, re:
if "particle mass is zero" in str(re):
continue
else:
raise
finally:
method.set_ignore_core_warnings(False)
state.derived_quantity_cache.clear()
try:
try:
method.set_ignore_core_warnings(True)
rec_rho = method.deposit_rho(state)
except RuntimeError, re:
if "particle mass is zero" in str(re):
continue
else:
raise
finally:
method.set_ignore_core_warnings(False)
tried_radii.append(radius)
l1_errors.append(discr.integral(numpy.abs(rec_rho - analytic_rho)))
if visualize:
visf = vis.make_file("bwopt-%04d" % step)
method.add_to_vis(vis, visf, state, time=radius, step=step)
vis.add_data(
visf,
[
("rho", rec_rho),
#("j", method.deposit_j(state)),
("rho_analytic", analytic_rho),
],
expressions=[("rho_diff", "rho-rho_analytic")],
time=radius,
step=step)
try:
rec.visualize_grid_quantities
except AttributeError:
pass
else:
rec.visualize_grid_quantities(visf, [
("rho_grid", rec.deposit_grid_rho(state)),
("j_grid",
rec.deposit_grid_j(state, method.velocities(state))),
("rho_resid",
rec.remap_residual(rec.deposit_grid_rho(state))),
])
visf.close()
if debug:
sys.stdout.write("\n")
sys.stdout.flush()
if visualize:
vis.close()
from pytools import argmin
min_idx = argmin(l1_errors)
min_rad = tried_radii[min_idx]
min_l1_error = l1_errors[min_idx]
rel_l1_error = abs(min_l1_error / discr.integral(analytic_rho))
if rel_l1_error > 0.1:
from warnings import warn
warn("Charge density is very poorly resolved (rel L1 error=%g)" %
rel_l1_error)
def is_local_minimum(list, i):
if i == 0:
return False
elif i == len(list) - 1:
return False
else:
return list[i] < list[i - 1] and list[i] < list[i + 1]
local_minima = [
idx for idx in range(len(tried_radii))
if is_local_minimum(l1_errors, idx)
]
chosen_idx = max(local_minima)
chosen_rad = tried_radii[chosen_idx]
if "shape_bw" in method.debug:
chosen_l1_error = l1_errors[chosen_idx]
print "radius: guessed optimum=%g, found optimum=%g, chosen=%g" % (
adv_radius, min_rad, chosen_rad)
print "radius: optimum l1 error=%g, chosen l1 error=%g" % (
min_l1_error, chosen_l1_error)
set_radius(chosen_rad)
state.derived_quantity_cache.clear()
if set(["interactive", "shape_bw"]) < method.debug:
from pylab import semilogx, show
semilogx(tried_radii, l1_errors)
show()
def main():
from hedge.backends import guess_run_context
rcon = guess_run_context(
#["cuda"]
)
from hedge.tools import EOCRecorder, to_obj_array
eoc_rec = EOCRecorder()
def boundary_tagger(vertices, el, face_nr, all_v):
return ["inflow"]
if rcon.is_head_rank:
from hedge.mesh import make_rect_mesh, \
make_centered_regular_rect_mesh
#mesh = make_rect_mesh((0,0), (10,1), max_area=0.01)
refine = 1
mesh = make_centered_regular_rect_mesh((0,0), (10,1), n=(20,4),
#periodicity=(True, False),
post_refine_factor=refine,
boundary_tagger=boundary_tagger)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [3]:
discr = rcon.make_discretization(mesh_data, order=order,
default_scalar_type=numpy.float64)
from hedge.visualization import SiloVisualizer, VtkVisualizer
#vis = VtkVisualizer(discr, rcon, "shearflow-%d" % order)
vis = SiloVisualizer(discr, rcon)
shearflow = SteadyShearFlow()
fields = shearflow.volume_interpolant(0, discr)
gamma, mu, prandtl, spec_gas_const = shearflow.properties()
from hedge.models.gas_dynamics import GasDynamicsOperator
op = GasDynamicsOperator(dimensions=2, gamma=gamma, mu=mu,
prandtl=prandtl, spec_gas_const=spec_gas_const,
bc_inflow=shearflow, bc_outflow=shearflow, bc_noslip=shearflow,
inflow_tag="inflow", outflow_tag="outflow", noslip_tag="noslip")
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
# needed to get first estimate of maximum eigenvalue
rhs(0, fields)
if rcon.is_head_rank:
print "---------------------------------------------"
print "order %d" % order
print "---------------------------------------------"
print "#elements=", len(mesh.elements)
from hedge.timestep import RK4TimeStepper
stepper = RK4TimeStepper()
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
logmgr = LogManager("navierstokes-cpu-%d-%d.dat" % (order, refine),
"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 -------------------------------------------------------
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=0.3,
#max_steps=500,
logmgr=logmgr,
max_dt_getter=lambda t: op.estimate_timestep(discr,
stepper=stepper, t=t, max_eigenvalue=max_eigval[0]))
for step, t, dt in step_it:
if step % 10 == 0:
#if False:
visf = vis.make_file("shearflow-%d-%04d" % (order, step))
#true_fields = shearflow.volume_interpolant(t, discr)
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")),
#("true_rho", discr.convert_volume(op.rho(true_fields), kind="numpy")),
#("true_e", discr.convert_volume(op.e(true_fields), kind="numpy")),
#("true_rho_u", discr.convert_volume(op.rho_u(true_fields), kind="numpy")),
#("true_u", discr.convert_volume(op.u(true_fields), kind="numpy")),
],
expressions=[
#("diff_rho", "rho-true_rho"),
#("diff_e", "e-true_e"),
#("diff_rho_u", "rho_u-true_rho_u", DB_VARTYPE_VECTOR),
("p", "0.4*(e- 0.5*(rho_u*u))"),
],
time=t, step=step
)
visf.close()
fields = stepper(fields, t, dt, rhs)
true_fields = shearflow.volume_interpolant(t, discr)
l2_error = discr.norm(op.u(fields)-op.u(true_fields))
eoc_rec.add_data_point(order, l2_error)
print
print eoc_rec.pretty_print("P.Deg.", "L2 Error")
logmgr.set_constant("l2_error", l2_error)
finally:
vis.close()
logmgr.save()
discr.close()
def main():
from hedge.backends import guess_run_context
rcon = guess_run_context( ["cuda", "mpi"])
if rcon.is_head_rank:
mesh = make_wingmesh()
#from hedge.mesh import make_rect_mesh
#mesh = make_rect_mesh(
# boundary_tagger=lambda fvi, el, fn, all_v: ["inflow"])
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [3]:
from pytools import add_python_path_relative_to_script
add_python_path_relative_to_script("..")
from gas_dynamics_initials import UniformMachFlow
wing = UniformMachFlow(angle_of_attack=0)
from hedge.models.gas_dynamics import GasDynamicsOperator
op = GasDynamicsOperator(dimensions=3,
gamma=wing.gamma, mu=wing.mu,
prandtl=wing.prandtl, spec_gas_const=wing.spec_gas_const,
bc_inflow=wing, bc_outflow=wing, bc_noslip=wing,
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",
#"print_op_code"
"cuda_no_metis",
],
default_scalar_type=numpy.float64,
tune_for=op.op_template())
from hedge.visualization import SiloVisualizer, VtkVisualizer
#vis = VtkVisualizer(discr, rcon, "shearflow-%d" % order)
vis = SiloVisualizer(discr, rcon)
fields = wing.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)
from hedge.timestep import RK4TimeStepper
stepper = RK4TimeStepper()
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
logmgr = LogManager("navierstokes-%d.dat" % order, "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 -------------------------------------------------------
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=200,
#max_steps=500,
logmgr=logmgr,
max_dt_getter=lambda t: 0.6 * op.estimate_timestep(discr,
stepper=stepper, t=t, max_eigenvalue=max_eigval[0]))
for step, t, dt in step_it:
if step % 200 == 0:
#if False:
visf = vis.make_file("wing-%d-%06d" % (order, step))
#rhs_fields = rhs(t, fields)
from pyvisfile.silo import DB_VARTYPE_VECTOR
from hedge.discretization import ones_on_boundary
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")),
#("rhs_rho", discr.convert_volume(op.rho(rhs_fields), kind="numpy")),
#("rhs_e", discr.convert_volume(op.e(rhs_fields), kind="numpy")),
#("rhs_rho_u", discr.convert_volume(op.rho_u(rhs_fields), kind="numpy")),
],
expressions=[
("p", "(0.4)*(e- 0.5*(rho_u*u))"),
],
time=t, step=step
)
visf.close()
fields = stepper(fields, t, dt, rhs)
t += dt
finally:
vis.close()
logmgr.save()
discr.close()
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_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():
from hedge.backends import guess_run_context
rcon = guess_run_context(["cuda"])
if rcon.is_head_rank:
mesh = make_boxmesh()
#from hedge.mesh import make_rect_mesh
#mesh = make_rect_mesh(
# boundary_tagger=lambda fvi, el, fn, all_v: ["inflow"])
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [3]:
from pytools import add_python_path_relative_to_script
add_python_path_relative_to_script("..")
from gas_dynamics_initials import UniformMachFlow
box = UniformMachFlow(angle_of_attack=0)
from hedge.models.gas_dynamics import GasDynamicsOperator
op = GasDynamicsOperator(dimensions=3,
gamma=box.gamma,
mu=box.mu,
prandtl=box.prandtl,
spec_gas_const=box.spec_gas_const,
bc_inflow=box,
bc_outflow=box,
bc_noslip=box,
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",
#"print_op_code",
"cuda_no_plan_el_local",
],
default_scalar_type=numpy.float32,
tune_for=op.op_template())
from hedge.visualization import SiloVisualizer, VtkVisualizer # noqa
#vis = VtkVisualizer(discr, rcon, "shearflow-%d" % order)
vis = SiloVisualizer(discr, rcon)
fields = box.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)
from hedge.timestep import RK4TimeStepper
stepper = RK4TimeStepper()
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
logmgr = LogManager("navierstokes-%d.dat" % order, "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"])
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())
# timestep loop -------------------------------------------------------
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=200,
#max_steps=500,
logmgr=logmgr,
max_dt_getter=lambda t: op.estimate_timestep(
discr, stepper=stepper, t=t, max_eigenvalue=max_eigval[0]))
for step, t, dt in step_it:
if step % 200 == 0:
#if False:
visf = vis.make_file("box-%d-%06d" % (order, step))
#rhs_fields = rhs(t, fields)
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")),
# ("rhs_rho", discr.convert_volume(
# op.rho(rhs_fields), kind="numpy")),
# ("rhs_e", discr.convert_volume(
# op.e(rhs_fields), kind="numpy")),
# ("rhs_rho_u", discr.convert_volume(
# op.rho_u(rhs_fields), kind="numpy")),
],
expressions=[
("p", "(0.4)*(e- 0.5*(rho_u*u))"),
],
time=t,
step=step)
visf.close()
fields = stepper(fields, t, dt, rhs)
finally:
vis.close()
logmgr.save()
discr.close()
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()
def main():
from hedge.backends import guess_run_context
rcon = guess_run_context()
if rcon.is_head_rank:
mesh = make_nacamesh()
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 [4]:
from gas_dynamics_initials import UniformMachFlow
uniform_flow = UniformMachFlow()
from hedge.models.gas_dynamics import GasDynamicsOperator, GammaLawEOS
op = GasDynamicsOperator(
dimensions=2,
equation_of_state=GammaLawEOS(uniform_flow.gamma),
prandtl=uniform_flow.prandtl,
spec_gas_const=uniform_flow.spec_gas_const,
mu=uniform_flow.mu,
bc_inflow=uniform_flow,
bc_outflow=uniform_flow,
bc_noslip=uniform_flow,
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_optemplate_stages",
# "dump_dataflow_graph",
# "print_op_code"
],
default_scalar_type=numpy.float32,
tune_for=op.op_template(),
)
from hedge.visualization import SiloVisualizer, VtkVisualizer
# vis = VtkVisualizer(discr, rcon, "shearflow-%d" % order)
vis = SiloVisualizer(discr, rcon)
fields = uniform_flow.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)
from hedge.timestep.runge_kutta import ODE23TimeStepper, LSRK4TimeStepper
stepper = ODE23TimeStepper(
dtype=discr.default_scalar_type, rtol=1e-6, vector_primitive_factory=discr.get_vector_primitive_factory()
)
# stepper = LSRK4TimeStepper(dtype=discr.default_scalar_type)
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, add_simulation_quantities, add_run_info
logmgr = LogManager("cns-naca-%d.dat" % order, "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 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())
# filter setup-------------------------------------------------------------
from hedge.discretization import Filter, ExponentialFilterResponseFunction
mode_filter = Filter(discr, ExponentialFilterResponseFunction(min_amplification=0.9, order=4))
# timestep loop -------------------------------------------------------
logmgr.add_watches(["step.max", "t_sim.max", "t_step.max"])
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=200,
# 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 % 10 == 0:
visf = vis.make_file("naca-%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")),
# ("true_rho", op.rho(true_fields)),
# ("true_e", op.e(true_fields)),
# ("true_rho_u", op.rho_u(true_fields)),
# ("true_u", op.u(true_fields)),
# ("rhs_rho", discr.convert_volume(op.rho(rhs_fields), kind="numpy")),
# ("rhs_e", discr.convert_volume(op.e(rhs_fields), kind="numpy")),
# ("rhs_rho_u", discr.convert_volume(op.rho_u(rhs_fields), kind="numpy")),
],
expressions=[
# ("diff_rho", "rho-true_rho"),
# ("diff_e", "e-true_e"),
# ("diff_rho_u", "rho_u-true_rho_u", DB_VARTYPE_VECTOR),
("p", "(0.4)*(e- 0.5*(rho_u*u))")
],
time=t,
step=step,
)
visf.close()
fields, t, taken_dt, next_dt = stepper(fields, t, dt, rhs)
fields = mode_filter(fields)
finally:
vis.close()
logmgr.save()
discr.close()
def optimize_shape_bandwidth(method, state, analytic_rho, exponent):
discr = method.discretization
rec = method.depositor
adv_radius = method.mesh_data.advisable_particle_radius()
radii = [adv_radius*2**i
for i in numpy.linspace(-4, 2, 50)]
def set_radius(r):
method.depositor.set_shape_function(
state,
method.get_shape_function_class()
(r, method.mesh_data.dimensions, exponent,))
tried_radii = []
l1_errors = []
debug = "shape_bw" in method.debug
visualize = set(["shape_bw", "vis_files"]) <= method.debug
if visualize:
from hedge.visualization import SiloVisualizer
vis = SiloVisualizer(discr)
import sys
if debug:
sys.stdout.write("optimizing shape bw (%d attempts): " % len(radii))
for step, radius in enumerate(radii):
if debug:
sys.stdout.write("%d." % step)
sys.stdout.flush()
try:
try:
method.set_ignore_core_warnings(True)
set_radius(radius)
except RuntimeError, re:
if "particle mass is zero" in str(re):
continue
else:
raise
finally:
method.set_ignore_core_warnings(False)
state.derived_quantity_cache.clear()
try:
try:
method.set_ignore_core_warnings(True)
rec_rho = method.deposit_rho(state)
except RuntimeError, re:
if "particle mass is zero" in str(re):
continue
else:
raise
finally:
method.set_ignore_core_warnings(False)
tried_radii.append(radius)
l1_errors.append(discr.integral(numpy.abs(rec_rho-analytic_rho)))
if visualize:
visf = vis.make_file("bwopt-%04d" % step)
method.add_to_vis(vis, visf, state, time=radius, step=step)
vis.add_data(visf, [
("rho", rec_rho),
#("j", method.deposit_j(state)),
("rho_analytic", analytic_rho),
],
expressions=[("rho_diff", "rho-rho_analytic")],
time=radius, step=step)
try:
rec.visualize_grid_quantities
except AttributeError:
pass
else:
rec.visualize_grid_quantities(visf, [
("rho_grid", rec.deposit_grid_rho(state)),
("j_grid", rec.deposit_grid_j(state, method.velocities(state))),
("rho_resid", rec.remap_residual(rec.deposit_grid_rho(state))),
])
visf.close()
if debug:
sys.stdout.write("\n")
sys.stdout.flush()
if visualize:
vis.close()
from pytools import argmin
min_idx = argmin(l1_errors)
min_rad = tried_radii[min_idx]
min_l1_error = l1_errors[min_idx]
rel_l1_error = abs(min_l1_error / discr.integral(analytic_rho))
if rel_l1_error > 0.1:
from warnings import warn
warn("Charge density is very poorly resolved (rel L1 error=%g)" % rel_l1_error)
def is_local_minimum(list, i):
if i == 0:
return False
elif i == len(list)-1:
return False
else:
return list[i] < list[i-1] and list[i] < list[i+1]
local_minima = [idx for idx in range(len(tried_radii))
if is_local_minimum(l1_errors, idx)]
chosen_idx = max(local_minima)
chosen_rad = tried_radii[chosen_idx]
if "shape_bw" in method.debug:
chosen_l1_error = l1_errors[chosen_idx]
print "radius: guessed optimum=%g, found optimum=%g, chosen=%g" % (
adv_radius, min_rad, chosen_rad)
print "radius: optimum l1 error=%g, chosen l1 error=%g" % (
min_l1_error, chosen_l1_error)
set_radius(chosen_rad)
state.derived_quantity_cache.clear()
if set(["interactive", "shape_bw"]) < method.debug:
from pylab import semilogx, show
semilogx(tried_radii, l1_errors)
show()
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 main():
from hedge.backends import guess_run_context
rcon = guess_run_context(["cuda", "mpi"])
if rcon.is_head_rank:
mesh = make_wingmesh()
#from hedge.mesh import make_rect_mesh
#mesh = make_rect_mesh(
# boundary_tagger=lambda fvi, el, fn, all_v: ["inflow"])
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [3]:
from pytools import add_python_path_relative_to_script
add_python_path_relative_to_script("..")
from gas_dynamics_initials import UniformMachFlow
wing = UniformMachFlow(angle_of_attack=0)
from hedge.models.gas_dynamics import GasDynamicsOperator
op = GasDynamicsOperator(dimensions=3,
gamma=wing.gamma,
mu=wing.mu,
prandtl=wing.prandtl,
spec_gas_const=wing.spec_gas_const,
bc_inflow=wing,
bc_outflow=wing,
bc_noslip=wing,
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",
#"print_op_code"
"cuda_no_metis",
],
default_scalar_type=numpy.float64,
tune_for=op.op_template())
from hedge.visualization import SiloVisualizer, VtkVisualizer
#vis = VtkVisualizer(discr, rcon, "shearflow-%d" % order)
vis = SiloVisualizer(discr, rcon)
fields = wing.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)
from hedge.timestep import RK4TimeStepper
stepper = RK4TimeStepper()
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
logmgr = LogManager("navierstokes-%d.dat" % order, "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 -------------------------------------------------------
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=200,
#max_steps=500,
logmgr=logmgr,
max_dt_getter=lambda t: 0.6 * op.estimate_timestep(
discr, stepper=stepper, t=t, max_eigenvalue=max_eigval[0]))
for step, t, dt in step_it:
if step % 200 == 0:
#if False:
visf = vis.make_file("wing-%d-%06d" % (order, step))
#rhs_fields = rhs(t, fields)
from pyvisfile.silo import DB_VARTYPE_VECTOR
from hedge.discretization import ones_on_boundary
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")),
#("rhs_rho", discr.convert_volume(op.rho(rhs_fields), kind="numpy")),
#("rhs_e", discr.convert_volume(op.e(rhs_fields), kind="numpy")),
#("rhs_rho_u", discr.convert_volume(op.rho_u(rhs_fields), kind="numpy")),
],
expressions=[
("p", "(0.4)*(e- 0.5*(rho_u*u))"),
],
time=t,
step=step)
visf.close()
fields = stepper(fields, t, dt, rhs)
t += dt
finally:
vis.close()
logmgr.save()
discr.close()
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()
