def test_vortex_init(ctx_factory):
"""
Simple test to check that Vortex2D initializer
creates the expected solution field.
"""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
dim = 2
nel_1d = 4
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=[(0.0, ), (-5.0, )],
b=[(10.0, ), (5.0, )],
nelements_per_axis=(nel_1d, ) * dim)
order = 3
logger.info(f"Number of elements: {mesh.nelements}")
discr = EagerDGDiscretization(actx, mesh, order=order)
nodes = thaw(actx, discr.nodes())
# Init soln with Vortex
vortex = Vortex2D()
cv = vortex(nodes)
gamma = 1.4
p = 0.4 * (cv.energy - 0.5 * np.dot(cv.momentum, cv.momentum) / cv.mass)
exp_p = cv.mass**gamma
errmax = discr.norm(p - exp_p, np.inf)
logger.info(f"vortex_soln = {cv}")
logger.info(f"pressure = {p}")
assert errmax < 1e-15
def test_isentropic_vortex(actx_factory, order):
"""Advance the 2D isentropic vortex case in time with non-zero velocities
using an RK4 timestepping scheme. Check the advanced field values against
the exact/analytic expressions.
This tests all parts of the Euler module working together, with results
converging at the expected rates vs. the order.
"""
actx = actx_factory()
dim = 2
from pytools.convergence import EOCRecorder
eoc_rec = EOCRecorder()
for nel_1d in [16, 32, 64]:
from meshmode.mesh.generation import (
generate_regular_rect_mesh, )
mesh = generate_regular_rect_mesh(a=(-5.0, ) * dim,
b=(5.0, ) * dim,
nelements_per_axis=(nel_1d, ) * dim)
exittol = 1.0
t_final = 0.001
cfl = 1.0
vel = np.zeros(shape=(dim, ))
orig = np.zeros(shape=(dim, ))
vel[:dim] = 1.0
dt = .0001
initializer = Vortex2D(center=orig, velocity=vel)
casename = "Vortex"
boundaries = {BTAG_ALL: PrescribedBoundary(initializer)}
eos = IdealSingleGas()
t = 0
flowparams = {
"dim": dim,
"dt": dt,
"order": order,
"time": t,
"boundaries": boundaries,
"initializer": initializer,
"eos": eos,
"casename": casename,
"mesh": mesh,
"tfinal": t_final,
"exittol": exittol,
"cfl": cfl,
"constantcfl": False,
"nstatus": 0
}
maxerr = _euler_flow_stepper(actx, flowparams)
eoc_rec.add_data_point(1.0 / nel_1d, maxerr)
logger.info(f"Error for (dim,order) = ({dim},{order}):\n" f"{eoc_rec}")
assert (eoc_rec.order_estimate() >= order - 0.5
or eoc_rec.max_error() < 1e-11)
def test_idealsingle_vortex(ctx_factory):
r"""Test EOS with isentropic vortex.
Tests that the IdealSingleGas EOS returns the correct pressure (p) for the
Vortex2D solution field (i.e. $p = \rho^{\gamma}$).
"""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
dim = 2
nel_1d = 4
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=[(0.0, ), (-5.0, )],
b=[(10.0, ), (5.0, )],
nelements_per_axis=(nel_1d, ) * dim)
order = 3
logger.info(f"Number of elements {mesh.nelements}")
discr = EagerDGDiscretization(actx, mesh, order=order)
from meshmode.dof_array import thaw
nodes = thaw(actx, discr.nodes())
eos = IdealSingleGas()
# Init soln with Vortex
vortex = Vortex2D()
cv = vortex(nodes)
def inf_norm(x):
return actx.to_numpy(discr.norm(x, np.inf))
gamma = eos.gamma()
p = eos.pressure(cv)
exp_p = cv.mass**gamma
errmax = inf_norm(p - exp_p)
exp_ke = 0.5 * np.dot(cv.momentum, cv.momentum) / cv.mass
ke = eos.kinetic_energy(cv)
kerr = inf_norm(ke - exp_ke)
te = eos.total_energy(cv, p)
terr = inf_norm(te - cv.energy)
logger.info(f"vortex_soln = {cv}")
logger.info(f"pressure = {p}")
assert errmax < 1e-15
assert kerr < 1e-15
assert terr < 1e-15
def test_vortex_rhs(actx_factory, order):
"""Tests the inviscid rhs using the non-trivial
2D isentropic vortex case configured to yield
rhs = 0. Checks several different orders
and refinement levels to check error
behavior.
"""
actx = actx_factory()
dim = 2
from pytools.convergence import EOCRecorder
eoc_rec = EOCRecorder()
from meshmode.mesh.generation import generate_regular_rect_mesh
for nel_1d in [16, 32, 64]:
mesh = generate_regular_rect_mesh(
a=(-5, ) * dim,
b=(5, ) * dim,
n=(nel_1d, ) * dim,
)
logger.info(f"Number of {dim}d elements: {mesh.nelements}")
discr = EagerDGDiscretization(actx, mesh, order=order)
nodes = thaw(actx, discr.nodes())
# Init soln with Vortex and expected RHS = 0
vortex = Vortex2D(center=[0, 0], velocity=[0, 0])
vortex_soln = vortex(0, nodes)
boundaries = {BTAG_ALL: PrescribedBoundary(vortex)}
inviscid_rhs = inviscid_operator(discr,
eos=IdealSingleGas(),
boundaries=boundaries,
q=vortex_soln,
t=0.0)
err_max = discr.norm(inviscid_rhs, np.inf)
eoc_rec.add_data_point(1.0 / nel_1d, err_max)
message = (f"Error for (dim,order) = ({dim},{order}):\n" f"{eoc_rec}")
logger.info(message)
assert (eoc_rec.order_estimate() >= order - 0.5
or eoc_rec.max_error() < 1e-11)
def test_analytic_comparison(actx_factory):
"""Quick test of state comparison routine."""
from mirgecom.initializers import Vortex2D
from mirgecom.simutil import compare_fluid_solutions, componentwise_norms
actx = actx_factory()
nel_1d = 4
dim = 2
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=(1.0, ) * dim,
b=(2.0, ) * dim,
nelements_per_axis=(nel_1d, ) * dim)
order = 2
discr = EagerDGDiscretization(actx, mesh, order=order)
nodes = thaw(discr.nodes(), actx)
zeros = discr.zeros(actx)
ones = zeros + 1.0
mass = ones
energy = ones
velocity = 2 * nodes
mom = mass * velocity
vortex_init = Vortex2D()
vortex_soln = vortex_init(x_vec=nodes, eos=IdealSingleGas())
cv = make_conserved(dim, mass=mass, energy=energy, momentum=mom)
resid = vortex_soln - cv
expected_errors = actx.to_numpy(
flatten(componentwise_norms(discr, resid, order=np.inf),
actx)).tolist()
errors = compare_fluid_solutions(discr, cv, cv)
assert max(errors) == 0
errors = compare_fluid_solutions(discr, cv, vortex_soln)
assert errors == expected_errors
def test_idealsingle_vortex(ctx_factory):
r"""
Tests that the IdealSingleGas EOS returns
the correct pressure (p) for the Vortex2D solution
field (i.e. :math:'p = \rho^{\gamma}').
"""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue)
dim = 2
nel_1d = 4
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=[(0.0, ), (-5.0, )],
b=[(10.0, ), (5.0, )],
n=(nel_1d, ) * dim)
order = 3
logger.info(f"Number of elements {mesh.nelements}")
discr = EagerDGDiscretization(actx, mesh, order=order)
nodes = thaw(actx, discr.nodes())
eos = IdealSingleGas()
# Init soln with Vortex
vortex = Vortex2D()
vortex_soln = vortex(0, nodes)
cv = split_conserved(dim, vortex_soln)
gamma = eos.gamma()
p = eos.pressure(cv)
exp_p = cv.mass**gamma
errmax = discr.norm(p - exp_p, np.inf)
logger.info(f"vortex_soln = {vortex_soln}")
logger.info(f"pressure = {p}")
assert errmax < 1e-15
def main(ctx_factory=cl.create_some_context,
use_logmgr=True,
use_leap=False,
use_profiling=False,
casename=None,
rst_filename=None,
actx_class=PyOpenCLArrayContext):
"""Drive the example."""
cl_ctx = ctx_factory()
if casename is None:
casename = "mirgecom"
from mpi4py import MPI
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
num_parts = comm.Get_size()
from mirgecom.simutil import global_reduce as _global_reduce
global_reduce = partial(_global_reduce, comm=comm)
logmgr = initialize_logmgr(use_logmgr,
filename=f"{casename}.sqlite",
mode="wu",
mpi_comm=comm)
if use_profiling:
queue = cl.CommandQueue(
cl_ctx, properties=cl.command_queue_properties.PROFILING_ENABLE)
else:
queue = cl.CommandQueue(cl_ctx)
actx = actx_class(queue,
allocator=cl_tools.MemoryPool(
cl_tools.ImmediateAllocator(queue)))
# timestepping control
current_step = 0
if use_leap:
from leap.rk import RK4MethodBuilder
timestepper = RK4MethodBuilder("state")
else:
timestepper = rk4_step
t_final = 0.01
current_cfl = 1.0
current_dt = .001
current_t = 0
constant_cfl = False
# some i/o frequencies
nrestart = 10
nstatus = 1
nviz = 10
nhealth = 10
dim = 2
if dim != 2:
raise ValueError("This example must be run with dim = 2.")
rst_path = "restart_data/"
rst_pattern = (rst_path + "{cname}-{step:04d}-{rank:04d}.pkl")
if rst_filename: # read the grid from restart data
rst_filename = f"{rst_filename}-{rank:04d}.pkl"
from mirgecom.restart import read_restart_data
restart_data = read_restart_data(actx, rst_filename)
local_mesh = restart_data["local_mesh"]
local_nelements = local_mesh.nelements
global_nelements = restart_data["global_nelements"]
assert restart_data["num_parts"] == num_parts
else: # generate the grid from scratch
nel_1d = 16
box_ll = -5.0
box_ur = 5.0
from meshmode.mesh.generation import generate_regular_rect_mesh
generate_mesh = partial(generate_regular_rect_mesh,
a=(box_ll, ) * dim,
b=(box_ur, ) * dim,
nelements_per_axis=(nel_1d, ) * dim)
local_mesh, global_nelements = generate_and_distribute_mesh(
comm, generate_mesh)
local_nelements = local_mesh.nelements
order = 3
discr = EagerDGDiscretization(actx,
local_mesh,
order=order,
mpi_communicator=comm)
nodes = thaw(discr.nodes(), actx)
vis_timer = None
if logmgr:
logmgr_add_device_name(logmgr, queue)
logmgr_add_device_memory_usage(logmgr, queue)
logmgr_add_many_discretization_quantities(logmgr, discr, dim,
extract_vars_for_logging,
units_for_logging)
vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(vis_timer)
logmgr.add_watches([
("step.max", "step = {value}, "),
("t_sim.max", "sim time: {value:1.6e} s\n"),
("min_pressure", "------- P (min, max) (Pa) = ({value:1.9e}, "),
("max_pressure", "{value:1.9e})\n"),
("t_step.max", "------- step walltime: {value:6g} s, "),
("t_log.max", "log walltime: {value:6g} s")
])
try:
logmgr.add_watches(
["memory_usage_python.max", "memory_usage_gpu.max"])
except KeyError:
pass
if use_profiling:
logmgr.add_watches(["multiply_time.max"])
# soln setup and init
eos = IdealSingleGas()
vel = np.zeros(shape=(dim, ))
orig = np.zeros(shape=(dim, ))
vel[:dim] = 1.0
initializer = Vortex2D(center=orig, velocity=vel)
gas_model = GasModel(eos=eos)
def boundary_solution(discr, btag, gas_model, state_minus, **kwargs):
actx = state_minus.array_context
bnd_discr = discr.discr_from_dd(btag)
nodes = thaw(bnd_discr.nodes(), actx)
return make_fluid_state(
initializer(x_vec=nodes, eos=gas_model.eos, **kwargs), gas_model)
boundaries = {
BTAG_ALL:
PrescribedFluidBoundary(boundary_state_func=boundary_solution)
}
if rst_filename:
current_t = restart_data["t"]
current_step = restart_data["step"]
current_cv = restart_data["cv"]
if logmgr:
from mirgecom.logging_quantities import logmgr_set_time
logmgr_set_time(logmgr, current_step, current_t)
else:
# Set the current state from time 0
current_cv = initializer(nodes)
current_state = make_fluid_state(current_cv, gas_model)
visualizer = make_visualizer(discr)
initname = initializer.__class__.__name__
eosname = eos.__class__.__name__
init_message = make_init_message(dim=dim,
order=order,
nelements=local_nelements,
global_nelements=global_nelements,
dt=current_dt,
t_final=t_final,
nstatus=nstatus,
nviz=nviz,
cfl=current_cfl,
constant_cfl=constant_cfl,
initname=initname,
eosname=eosname,
casename=casename)
if rank == 0:
logger.info(init_message)
def my_write_status(state, component_errors, cfl=None):
if cfl is None:
if constant_cfl:
cfl = current_cfl
else:
from grudge.op import nodal_max
from mirgecom.inviscid import get_inviscid_cfl
cfl = actx.to_numpy(
nodal_max(discr, "vol",
get_inviscid_cfl(discr, state, current_dt)))[()]
if rank == 0:
logger.info(f"------ {cfl=}\n"
"------- errors=" +
", ".join("%.3g" % en for en in component_errors))
def my_write_viz(step, t, state, dv=None, exact=None, resid=None):
if exact is None:
exact = initializer(x_vec=nodes, eos=eos, time=t)
if resid is None:
resid = state - exact
viz_fields = [("cv", state), ("dv", dv), ("exact", exact),
("residual", resid)]
from mirgecom.simutil import write_visfile
write_visfile(discr,
viz_fields,
visualizer,
vizname=casename,
step=step,
t=t,
overwrite=True,
vis_timer=vis_timer)
def my_write_restart(step, t, state):
rst_fname = rst_pattern.format(cname=casename, step=step, rank=rank)
if rst_fname != rst_filename:
rst_data = {
"local_mesh": local_mesh,
"cv": state,
"t": t,
"step": step,
"order": order,
"global_nelements": global_nelements,
"num_parts": num_parts
}
from mirgecom.restart import write_restart_file
write_restart_file(actx, rst_data, rst_fname, comm)
def my_health_check(pressure, component_errors):
health_error = False
from mirgecom.simutil import check_naninf_local, check_range_local
if check_naninf_local(discr, "vol", pressure) \
or check_range_local(discr, "vol", pressure, .2, 1.02):
health_error = True
logger.info(f"{rank=}: Invalid pressure data found.")
exittol = .1
if max(component_errors) > exittol:
health_error = True
if rank == 0:
logger.info("Solution diverged from exact soln.")
return health_error
def my_pre_step(step, t, dt, state):
fluid_state = make_fluid_state(state, gas_model)
cv = fluid_state.cv
dv = fluid_state.dv
try:
exact = None
component_errors = None
if logmgr:
logmgr.tick_before()
do_viz = check_step(step=step, interval=nviz)
do_restart = check_step(step=step, interval=nrestart)
do_health = check_step(step=step, interval=nhealth)
do_status = check_step(step=step, interval=nstatus)
if do_health:
exact = initializer(x_vec=nodes, eos=eos, time=t)
from mirgecom.simutil import compare_fluid_solutions
component_errors = compare_fluid_solutions(discr, cv, exact)
health_errors = global_reduce(my_health_check(
dv.pressure, component_errors),
op="lor")
if health_errors:
if rank == 0:
logger.info("Fluid solution failed health check.")
raise MyRuntimeError("Failed simulation health check.")
if do_restart:
my_write_restart(step=step, t=t, state=cv)
if do_status:
if component_errors is None:
if exact is None:
exact = initializer(x_vec=nodes, eos=eos, time=t)
from mirgecom.simutil import compare_fluid_solutions
component_errors = compare_fluid_solutions(
discr, cv, exact)
my_write_status(fluid_state, component_errors)
if do_viz:
if exact is None:
exact = initializer(x_vec=nodes, eos=eos, time=t)
resid = state - exact
my_write_viz(step=step,
t=t,
state=cv,
dv=dv,
exact=exact,
resid=resid)
except MyRuntimeError:
if rank == 0:
logger.info("Errors detected; attempting graceful exit.")
my_write_viz(step=step, t=t, state=cv)
my_write_restart(step=step, t=t, state=cv)
raise
dt = get_sim_timestep(discr, fluid_state, t, dt, current_cfl, t_final,
constant_cfl)
return state, dt
def my_post_step(step, t, dt, state):
# Logmgr needs to know about EOS, dt, dim?
# imo this is a design/scope flaw
if logmgr:
set_dt(logmgr, dt)
set_sim_state(logmgr, dim, state, eos)
logmgr.tick_after()
return state, dt
def my_rhs(t, state):
fluid_state = make_fluid_state(state, gas_model)
return euler_operator(discr,
state=fluid_state,
time=t,
boundaries=boundaries,
gas_model=gas_model)
current_dt = get_sim_timestep(discr, current_state, current_t, current_dt,
current_cfl, t_final, constant_cfl)
current_step, current_t, current_cv = \
advance_state(rhs=my_rhs, timestepper=timestepper,
pre_step_callback=my_pre_step,
post_step_callback=my_post_step, dt=current_dt,
state=current_state.cv, t=current_t, t_final=t_final)
# Dump the final data
if rank == 0:
logger.info("Checkpointing final state ...")
current_state = make_fluid_state(current_cv, gas_model)
final_dv = current_state.dv
final_exact = initializer(x_vec=nodes, eos=eos, time=current_t)
final_resid = current_state.cv - final_exact
my_write_viz(step=current_step,
t=current_t,
state=current_state.cv,
dv=final_dv,
exact=final_exact,
resid=final_resid)
my_write_restart(step=current_step, t=current_t, state=current_state.cv)
if logmgr:
logmgr.close()
elif use_profiling:
print(actx.tabulate_profiling_data())
finish_tol = 1e-16
assert np.abs(current_t - t_final) < finish_tol
def main(ctx_factory=cl.create_some_context,
use_profiling=False,
use_logmgr=False,
use_leap=False):
"""Drive the example."""
from mpi4py import MPI
comm = MPI.COMM_WORLD
logmgr = initialize_logmgr(use_logmgr,
filename="vortex.sqlite",
mode="wu",
mpi_comm=comm)
cl_ctx = ctx_factory()
if use_profiling:
queue = cl.CommandQueue(
cl_ctx, properties=cl.command_queue_properties.PROFILING_ENABLE)
actx = PyOpenCLProfilingArrayContext(
queue,
allocator=cl_tools.MemoryPool(cl_tools.ImmediateAllocator(queue)),
logmgr=logmgr)
else:
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue,
allocator=cl_tools.MemoryPool(
cl_tools.ImmediateAllocator(queue)))
dim = 2
nel_1d = 16
order = 3
exittol = .1
t_final = 0.1
current_cfl = 1.0
vel = np.zeros(shape=(dim, ))
orig = np.zeros(shape=(dim, ))
vel[:dim] = 1.0
current_dt = .001
current_t = 0
eos = IdealSingleGas()
initializer = Vortex2D(center=orig, velocity=vel)
casename = "vortex"
boundaries = {BTAG_ALL: PrescribedBoundary(initializer)}
constant_cfl = False
nstatus = 10
nviz = 10
rank = 0
checkpoint_t = current_t
current_step = 0
if use_leap:
from leap.rk import RK4MethodBuilder
timestepper = RK4MethodBuilder("state")
else:
timestepper = rk4_step
box_ll = -5.0
box_ur = 5.0
rank = comm.Get_rank()
if dim != 2:
raise ValueError("This example must be run with dim = 2.")
from meshmode.mesh.generation import generate_regular_rect_mesh
generate_mesh = partial(generate_regular_rect_mesh,
a=(box_ll, ) * dim,
b=(box_ur, ) * dim,
nelements_per_axis=(nel_1d, ) * dim)
local_mesh, global_nelements = generate_and_distribute_mesh(
comm, generate_mesh)
local_nelements = local_mesh.nelements
discr = EagerDGDiscretization(actx,
local_mesh,
order=order,
mpi_communicator=comm)
nodes = thaw(actx, discr.nodes())
current_state = initializer(nodes)
vis_timer = None
if logmgr:
logmgr_add_device_name(logmgr, queue)
logmgr_add_device_memory_usage(logmgr, queue)
logmgr_add_many_discretization_quantities(logmgr, discr, dim,
extract_vars_for_logging,
units_for_logging)
logmgr.add_watches([
"step.max", "t_step.max", "t_log.max", "min_temperature",
"L2_norm_momentum1"
])
try:
logmgr.add_watches(
["memory_usage_python.max", "memory_usage_gpu.max"])
except KeyError:
pass
if use_profiling:
logmgr.add_watches(["multiply_time.max"])
vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(vis_timer)
visualizer = make_visualizer(discr)
initname = initializer.__class__.__name__
eosname = eos.__class__.__name__
init_message = make_init_message(dim=dim,
order=order,
nelements=local_nelements,
global_nelements=global_nelements,
dt=current_dt,
t_final=t_final,
nstatus=nstatus,
nviz=nviz,
cfl=current_cfl,
constant_cfl=constant_cfl,
initname=initname,
eosname=eosname,
casename=casename)
if rank == 0:
logger.info(init_message)
get_timestep = partial(inviscid_sim_timestep,
discr=discr,
t=current_t,
dt=current_dt,
cfl=current_cfl,
eos=eos,
t_final=t_final,
constant_cfl=constant_cfl)
def my_rhs(t, state):
return euler_operator(discr,
cv=state,
t=t,
boundaries=boundaries,
eos=eos)
def my_checkpoint(step, t, dt, state):
return sim_checkpoint(discr,
visualizer,
eos,
cv=state,
exact_soln=initializer,
vizname=casename,
step=step,
t=t,
dt=dt,
nstatus=nstatus,
nviz=nviz,
exittol=exittol,
constant_cfl=constant_cfl,
comm=comm,
vis_timer=vis_timer)
try:
(current_step, current_t, current_state) = \
advance_state(rhs=my_rhs, timestepper=timestepper,
checkpoint=my_checkpoint,
get_timestep=get_timestep, state=current_state,
t=current_t, t_final=t_final, logmgr=logmgr,
eos=eos, dim=dim)
except ExactSolutionMismatch as ex:
current_step = ex.step
current_t = ex.t
current_state = ex.state
# if current_t != checkpoint_t:
if rank == 0:
logger.info("Checkpointing final state ...")
my_checkpoint(current_step,
t=current_t,
dt=(current_t - checkpoint_t),
state=current_state)
if current_t - t_final < 0:
raise ValueError("Simulation exited abnormally")
if logmgr:
logmgr.close()
elif use_profiling:
print(actx.tabulate_profiling_data())
def test_vortex_rhs(actx_factory, order, use_overintegration):
"""Test the inviscid rhs using the non-trivial 2D isentropic vortex.
The case is configured to yield rhs = 0. Checks several different orders
and refinement levels to check error behavior.
"""
actx = actx_factory()
dim = 2
from pytools.convergence import EOCRecorder
eoc_rec = EOCRecorder()
from meshmode.mesh.generation import generate_regular_rect_mesh
for nel_1d in [32, 48, 64]:
mesh = generate_regular_rect_mesh(
a=(-5,) * dim, b=(5,) * dim, nelements_per_axis=(nel_1d,) * dim,
)
logger.info(
f"Number of {dim}d elements: {mesh.nelements}"
)
from grudge.dof_desc import DISCR_TAG_BASE, DISCR_TAG_QUAD
from meshmode.discretization.poly_element import \
default_simplex_group_factory, QuadratureSimplexGroupFactory
discr = EagerDGDiscretization(
actx, mesh,
discr_tag_to_group_factory={
DISCR_TAG_BASE: default_simplex_group_factory(
base_dim=dim, order=order),
DISCR_TAG_QUAD: QuadratureSimplexGroupFactory(2*order + 1)
}
)
if use_overintegration:
quadrature_tag = DISCR_TAG_QUAD
else:
quadrature_tag = None
nodes = thaw(discr.nodes(), actx)
# Init soln with Vortex and expected RHS = 0
vortex = Vortex2D(center=[0, 0], velocity=[0, 0])
vortex_soln = vortex(nodes)
gas_model = GasModel(eos=IdealSingleGas())
fluid_state = make_fluid_state(vortex_soln, gas_model)
def _vortex_boundary(discr, btag, gas_model, state_minus, **kwargs):
actx = state_minus.array_context
bnd_discr = discr.discr_from_dd(btag)
nodes = thaw(bnd_discr.nodes(), actx)
return make_fluid_state(vortex(x_vec=nodes, **kwargs), gas_model)
boundaries = {
BTAG_ALL: PrescribedFluidBoundary(boundary_state_func=_vortex_boundary)
}
inviscid_rhs = euler_operator(
discr, state=fluid_state, gas_model=gas_model, boundaries=boundaries,
time=0.0, quadrature_tag=quadrature_tag)
err_max = max_component_norm(discr, inviscid_rhs, np.inf)
eoc_rec.add_data_point(1.0 / nel_1d, err_max)
logger.info(
f"Error for (dim,order) = ({dim},{order}):\n"
f"{eoc_rec}"
)
assert (
eoc_rec.order_estimate() >= order - 0.5
or eoc_rec.max_error() < 1e-11
)
def main(ctx_factory=cl.create_some_context):
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue,
allocator=cl_tools.MemoryPool(
cl_tools.ImmediateAllocator(queue)))
dim = 2
nel_1d = 16
order = 3
exittol = .09
t_final = 0.1
current_cfl = 1.0
vel = np.zeros(shape=(dim, ))
orig = np.zeros(shape=(dim, ))
vel[:dim] = 1.0
current_dt = .001
current_t = 0
eos = IdealSingleGas()
initializer = Vortex2D(center=orig, velocity=vel)
casename = "vortex"
boundaries = {BTAG_ALL: PrescribedBoundary(initializer)}
constant_cfl = False
nstatus = 10
nviz = 10
rank = 0
checkpoint_t = current_t
current_step = 0
timestepper = rk4_step
box_ll = -5.0
box_ur = 5.0
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
from meshmode.mesh.generation import generate_regular_rect_mesh
generate_grid = partial(generate_regular_rect_mesh,
a=(box_ll, ) * dim,
b=(box_ur, ) * dim,
n=(nel_1d, ) * dim)
local_mesh, global_nelements = create_parallel_grid(comm, generate_grid)
local_nelements = local_mesh.nelements
discr = EagerDGDiscretization(actx,
local_mesh,
order=order,
mpi_communicator=comm)
nodes = thaw(actx, discr.nodes())
current_state = initializer(0, nodes)
visualizer = make_visualizer(
discr, discr.order + 3 if discr.dim == 2 else discr.order)
initname = initializer.__class__.__name__
eosname = eos.__class__.__name__
init_message = make_init_message(dim=dim,
order=order,
nelements=local_nelements,
global_nelements=global_nelements,
dt=current_dt,
t_final=t_final,
nstatus=nstatus,
nviz=nviz,
cfl=current_cfl,
constant_cfl=constant_cfl,
initname=initname,
eosname=eosname,
casename=casename)
if rank == 0:
logger.info(init_message)
get_timestep = partial(inviscid_sim_timestep,
discr=discr,
t=current_t,
dt=current_dt,
cfl=current_cfl,
eos=eos,
t_final=t_final,
constant_cfl=constant_cfl)
def my_rhs(t, state):
return inviscid_operator(discr,
q=state,
t=t,
boundaries=boundaries,
eos=eos)
def my_checkpoint(step, t, dt, state):
return sim_checkpoint(discr,
visualizer,
eos,
q=state,
exact_soln=initializer,
vizname=casename,
step=step,
t=t,
dt=dt,
nstatus=nstatus,
nviz=nviz,
exittol=exittol,
constant_cfl=constant_cfl,
comm=comm)
try:
(current_step, current_t, current_state) = \
advance_state(rhs=my_rhs, timestepper=timestepper,
checkpoint=my_checkpoint,
get_timestep=get_timestep, state=current_state,
t=current_t, t_final=t_final)
except ExactSolutionMismatch as ex:
current_step = ex.step
current_t = ex.t
current_state = ex.state
# if current_t != checkpoint_t:
if rank == 0:
logger.info("Checkpointing final state ...")
my_checkpoint(current_step,
t=current_t,
dt=(current_t - checkpoint_t),
state=current_state)
if current_t - t_final < 0:
raise ValueError("Simulation exited abnormally")