Beispiel #1
0
def my_box_mesh(boundary_tagger):
    from hedge.mesh.generator import make_rect_mesh
    from math import pi
    return make_rect_mesh(
        b=(2*pi, 3), max_area=0.4,
        #periodicity=(True, False),
        # meshpy doesn't do periodic at the moment (5/2014)
        periodicity=(False, False),
        subdivisions=(5, 10),
        boundary_tagger=boundary_tagger,
        )
Beispiel #2
0
def my_box_mesh(boundary_tagger):
    from hedge.mesh.generator import make_rect_mesh
    from math import pi
    return make_rect_mesh(
        b=(2 * pi, 3),
        max_area=0.4,
        #periodicity=(True, False),
        # meshpy doesn't do periodic at the moment (5/2014)
        periodicity=(False, False),
        subdivisions=(5, 10),
        boundary_tagger=boundary_tagger,
    )
Beispiel #3
0
def main(write_output=True):
    from math import sin, exp, sqrt  # noqa

    from hedge.mesh.generator import make_rect_mesh
    mesh = make_rect_mesh(a=(-0.5, -0.5), b=(0.5, 0.5), max_area=0.008)

    from hedge.backends.jit import Discretization

    discr = Discretization(mesh, order=4)

    from hedge.visualization import VtkVisualizer
    vis = VtkVisualizer(discr, None, "fld")

    source_center = np.array([0.1, 0.22])
    source_width = 0.05
    source_omega = 3

    import hedge.optemplate as sym
    sym_x = sym.nodes(2)
    sym_source_center_dist = sym_x - source_center

    from hedge.models.wave import StrongWaveOperator
    from hedge.mesh import TAG_ALL, TAG_NONE
    op = StrongWaveOperator(
        -0.1,
        discr.dimensions,
        source_f=sym.CFunction("sin")(
            source_omega * sym.ScalarParameter("t")) * sym.CFunction("exp")(
                -np.dot(sym_source_center_dist, sym_source_center_dist) /
                source_width**2),
        dirichlet_tag=TAG_NONE,
        neumann_tag=TAG_NONE,
        radiation_tag=TAG_ALL,
        flux_type="upwind")

    from hedge.tools import join_fields
    fields = join_fields(
        discr.volume_zeros(),
        [discr.volume_zeros() for i in range(discr.dimensions)])

    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper()
    dt = op.estimate_timestep(discr, stepper=stepper, fields=fields)

    nsteps = int(10 / dt)
    print "dt=%g nsteps=%d" % (dt, nsteps)

    rhs = op.bind(discr)
    for step in range(nsteps):
        t = step * dt

        if step % 10 == 0 and write_output:
            print step, t, discr.norm(fields[0])
            visf = vis.make_file("fld-%04d" % step)

            vis.add_data(visf, [
                ("u", fields[0]),
                ("v", fields[1:]),
            ],
                         time=t,
                         step=step)
            visf.close()

        fields = stepper(fields, t, dt, rhs)

    vis.close()
Beispiel #4
0
def main(write_output=True,
         dir_tag=TAG_NONE,
         neu_tag=TAG_NONE,
         rad_tag=TAG_ALL,
         flux_type_arg="upwind"):
    from math import sin, cos, pi, exp, sqrt  # noqa

    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    dim = 2

    if dim == 1:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_uniform_1d_mesh
            mesh = make_uniform_1d_mesh(-10, 10, 500)
    elif dim == 2:
        from hedge.mesh.generator import make_rect_mesh
        if rcon.is_head_rank:
            mesh = make_rect_mesh(a=(-1, -1), b=(1, 1), max_area=0.003)
    elif dim == 3:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_ball_mesh
            mesh = make_ball_mesh(max_volume=0.0005)
    else:
        raise RuntimeError("bad number of dimensions")

    if rcon.is_head_rank:
        print "%d elements" % len(mesh.elements)
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    discr = rcon.make_discretization(mesh_data, order=4)

    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper()

    from hedge.visualization import VtkVisualizer
    if write_output:
        vis = VtkVisualizer(discr, rcon, "fld")

    source_center = np.array([0.7, 0.4])
    source_width = 1 / 16
    source_omega = 3

    import hedge.optemplate as sym
    sym_x = sym.nodes(2)
    sym_source_center_dist = sym_x - source_center

    from hedge.models.wave import VariableVelocityStrongWaveOperator
    op = VariableVelocityStrongWaveOperator(
        c=sym.If(sym.Comparison(np.dot(sym_x, sym_x), "<", 0.4**2), 1, 0.5),
        dimensions=discr.dimensions,
        source=sym.CFunction("sin")(source_omega * sym.ScalarParameter("t")) *
        sym.CFunction("exp")(
            -np.dot(sym_source_center_dist, sym_source_center_dist) /
            source_width**2),
        dirichlet_tag=dir_tag,
        neumann_tag=neu_tag,
        radiation_tag=rad_tag,
        flux_type=flux_type_arg)

    from hedge.tools import join_fields
    fields = join_fields(
        discr.volume_zeros(),
        [discr.volume_zeros() for i in range(discr.dimensions)])

    # {{{ diagnostics setup

    from pytools.log import LogManager, \
            add_general_quantities, \
            add_simulation_quantities, \
            add_run_info

    if write_output:
        log_file_name = "wave.dat"
    else:
        log_file_name = None

    logmgr = LogManager(log_file_name, "w", rcon.communicator)
    add_run_info(logmgr)
    add_general_quantities(logmgr)
    add_simulation_quantities(logmgr)
    discr.add_instrumentation(logmgr)

    from pytools.log import IntervalTimer
    vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
    logmgr.add_quantity(vis_timer)
    stepper.add_instrumentation(logmgr)

    from hedge.log import LpNorm
    u_getter = lambda: fields[0]
    logmgr.add_quantity(LpNorm(u_getter, discr, 1, name="l1_u"))
    logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))

    logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])

    # }}}

    # {{{ timestep loop

    rhs = op.bind(discr)
    try:
        from hedge.timestep.stability import \
                approximate_rk4_relative_imag_stability_region
        max_dt = (1 / discr.compile(op.max_eigenvalue_expr())() *
                  discr.dt_non_geometric_factor() *
                  discr.dt_geometric_factor() *
                  approximate_rk4_relative_imag_stability_region(stepper))
        if flux_type_arg == "central":
            max_dt *= 0.25

        from hedge.timestep import times_and_steps
        step_it = times_and_steps(final_time=3,
                                  logmgr=logmgr,
                                  max_dt_getter=lambda t: max_dt)

        for step, t, dt in step_it:
            if step % 10 == 0 and write_output:
                visf = vis.make_file("fld-%04d" % step)

                vis.add_data(visf, [
                    ("u", fields[0]),
                    ("v", fields[1:]),
                ],
                             time=t,
                             step=step)
                visf.close()

            fields = stepper(fields, t, dt, rhs)

        assert discr.norm(fields) < 1
    finally:
        if write_output:
            vis.close()

        logmgr.close()
        discr.close()
Beispiel #5
0
def run_convergence_test_advec(dtype, debug_output=False):
    """Test whether 2/3D advection actually converges"""

    from hedge.mesh.generator import make_ball_mesh, make_box_mesh, make_rect_mesh
    from hedge.timestep import RK4TimeStepper
    from hedge.tools import EOCRecorder
    from math import sin, pi, sqrt
    from hedge.models.advection import StrongAdvectionOperator
    from hedge.data import TimeDependentGivenFunction
    from hedge.visualization import SiloVisualizer

    from hedge.backends import guess_run_context
    rcon = guess_run_context(["mpi"])

    # note: x component must remain zero because x-periodicity is used
    v = numpy.array([0.0,0.9,0.3])

    def f(x):
        return sin(x)

    def u_analytic(x, el, t):
        return f((numpy.dot(-v[:dims],x)/la.norm(v[:dims])+t*la.norm(v[:dims])))

    def boundary_tagger(vertices, el, face_nr, points):
        face_normal = el.face_normals[face_nr]
        if numpy.dot(face_normal, v[:len(face_normal)]) < 0:
            return ["inflow"]
        else:
            return ["outflow"]

    for i_mesh, mesh in enumerate([
        # 2D semiperiodic
        make_rect_mesh(b=(2*pi,3), max_area=0.4,
            periodicity=(True, False),
            subdivisions=(5,10),
            boundary_tagger=boundary_tagger, 
            ),
        # 3D x-periodic
        make_box_mesh((0,0,0), (2*pi, 2, 2), max_volume=0.4,
            periodicity=(True, False, False),
            boundary_tagger=boundary_tagger, 
            ),
        # non-periodic
        make_ball_mesh(r=pi, 
            boundary_tagger=boundary_tagger, max_volume=0.7),
        ]):
        for flux_type in StrongAdvectionOperator.flux_types:
            for random_partition in [True, False]:
                eoc_rec = EOCRecorder()

                if random_partition:
                    # Distribute elements randomly across nodes.
                    # This is bad, efficiency-wise, but it puts stress
                    # on the parallel implementation, which is desired here.
                    # Another main point of this is to force the code to split
                    # a periodic face pair across nodes.
                    from random import choice
                    partition = [choice(rcon.ranks) for el in mesh.elements]
                else:
                    partition = None

                for order in [1,2,3,4]:
                    if rcon.is_head_rank:
                        mesh_data = rcon.distribute_mesh(mesh, partition)
                    else:
                        mesh_data = rcon.receive_mesh()

                    dims = mesh.points.shape[1]

                    discr = rcon.make_discretization(mesh_data, order=order,
                            default_scalar_type=dtype)

                    op = StrongAdvectionOperator(v[:dims], 
                            inflow_u=TimeDependentGivenFunction(u_analytic),
                            flux_type=flux_type)
                    if debug_output:
                        vis = SiloVisualizer(discr, rcon)

                    u = discr.interpolate_volume_function(
                            lambda x, el: u_analytic(x, el, 0))
                    ic = u.copy()

                    if debug_output and rcon.is_head_rank:
                        print "#elements=%d" % len(mesh.elements)

                    test_name = "test-%s-o%d-m%d-r%s" % (
                            flux_type, order, i_mesh, random_partition)

                    rhs = op.bind(discr)

                    stepper = RK4TimeStepper(dtype=dtype)
                    from hedge.timestep import times_and_steps
                    final_time = 1
                    step_it = times_and_steps(
                            final_time=final_time,
                            max_dt_getter=lambda t: op.estimate_timestep(discr,
                                stepper=stepper, t=t, fields=u))

                    for step, t, dt in step_it:
                        u = stepper(u, t, dt, rhs)

                    assert u.dtype == dtype

                    u_true = discr.interpolate_volume_function(
                            lambda x, el: u_analytic(x, el, final_time))
                    error = u-u_true
                    l2_error = discr.norm(error)

                    if debug_output:
                        visf = vis.make_file(test_name+"-final")
                        vis.add_data(visf, [
                            ("u", u),
                            ("u_true", u_true),
                            ("ic", ic)])
                        visf.close()

                    eoc_rec.add_data_point(order, l2_error)

                if debug_output and rcon.is_head_rank:
                    print "%s\n%s\n" % (flux_type.upper(), "-" * len(flux_type))
                    print eoc_rec.pretty_print(abscissa_label="Poly. Order", 
                            error_label="L2 Error")

                assert eoc_rec.estimate_order_of_convergence()[0,1] > 3
                assert eoc_rec.estimate_order_of_convergence(2)[-1,1] > 7
Beispiel #6
0
def main():
    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    from hedge.tools import to_obj_array

    if rcon.is_head_rank:
        from hedge.mesh.generator import make_rect_mesh
        mesh = make_rect_mesh((-5, -5), (5, 5), max_area=0.01)
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    for order in [1]:
        discr = rcon.make_discretization(mesh_data,
                                         order=order,
                                         default_scalar_type=numpy.float64)

        from hedge.visualization import SiloVisualizer, VtkVisualizer
        vis = VtkVisualizer(discr, rcon, "Sod2D-%d" % order)
        #vis = SiloVisualizer(discr, rcon)

        sod_field = Sod(gamma=1.4)
        fields = sod_field.volume_interpolant(0, discr)

        from hedge.models.gas_dynamics import GasDynamicsOperator
        from hedge.mesh import TAG_ALL
        op = GasDynamicsOperator(dimensions=2,
                                 gamma=sod_field.gamma,
                                 mu=0.0,
                                 prandtl=sod_field.prandtl,
                                 bc_inflow=sod_field,
                                 bc_outflow=sod_field,
                                 bc_noslip=sod_field,
                                 inflow_tag=TAG_ALL,
                                 source=None)

        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, sod_field.gamma, 2, op)

        # integrator setup---------------------------------------------------------
        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

        logmgr = LogManager("euler-%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"])

        # filter setup-------------------------------------------------------------
        from hedge.discretization import Filter, ExponentialFilterResponseFunction
        mode_filter = Filter(
            discr,
            ExponentialFilterResponseFunction(min_amplification=0.9, order=4))

        # timestep loop -------------------------------------------------------
        try:
            from hedge.timestep import times_and_steps
            step_it = times_and_steps(
                final_time=1.0,
                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 % 5 == 0:
                    #if False:
                    visf = vis.make_file("vortex-%d-%04d" % (order, step))

                    #true_fields = vortex.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", 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", op.rho(rhs_fields)),
                            #("rhs_e", op.e(rhs_fields)),
                            #("rhs_rho_u", op.rho_u(rhs_fields)),
                        ],
                        #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)
                # fields = limiter(fields)
                # fields = mode_filter(fields)

                assert not numpy.isnan(numpy.sum(fields[0]))
        finally:
            vis.close()
            logmgr.close()
            discr.close()

        # not solution, just to check against when making code changes
        true_fields = sod_field.volume_interpolant(t, discr)
        print discr.norm(fields - true_fields)
Beispiel #7
0
def main():
    from hedge.backends import guess_run_context

    rcon = guess_run_context()

    from hedge.tools import to_obj_array

    if rcon.is_head_rank:
        from hedge.mesh.generator import make_rect_mesh

        mesh = make_rect_mesh((-5, -5), (5, 5), max_area=0.01)
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    for order in [1]:
        discr = rcon.make_discretization(mesh_data, order=order, default_scalar_type=numpy.float64)

        from hedge.visualization import SiloVisualizer, VtkVisualizer

        vis = VtkVisualizer(discr, rcon, "Sod2D-%d" % order)
        # vis = SiloVisualizer(discr, rcon)

        sod_field = Sod(gamma=1.4)
        fields = sod_field.volume_interpolant(0, discr)

        from hedge.models.gas_dynamics import GasDynamicsOperator
        from hedge.mesh import TAG_ALL

        op = GasDynamicsOperator(
            dimensions=2,
            gamma=sod_field.gamma,
            mu=0.0,
            prandtl=sod_field.prandtl,
            bc_inflow=sod_field,
            bc_outflow=sod_field,
            bc_noslip=sod_field,
            inflow_tag=TAG_ALL,
            source=None,
        )

        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, sod_field.gamma, 2, op)

        # integrator setup---------------------------------------------------------
        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

        logmgr = LogManager("euler-%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"])

        # filter setup-------------------------------------------------------------
        from hedge.discretization import Filter, ExponentialFilterResponseFunction

        mode_filter = Filter(discr, ExponentialFilterResponseFunction(min_amplification=0.9, order=4))

        # timestep loop -------------------------------------------------------
        try:
            from hedge.timestep import times_and_steps

            step_it = times_and_steps(
                final_time=1.0,
                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 % 5 == 0:
                    # if False:
                    visf = vis.make_file("vortex-%d-%04d" % (order, step))

                    # true_fields = vortex.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", 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", op.rho(rhs_fields)),
                            # ("rhs_e", op.e(rhs_fields)),
                            # ("rhs_rho_u", op.rho_u(rhs_fields)),
                        ],
                        # 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)
                # fields = limiter(fields)
                # fields = mode_filter(fields)

                assert not numpy.isnan(numpy.sum(fields[0]))
        finally:
            vis.close()
            logmgr.close()
            discr.close()

        # not solution, just to check against when making code changes
        true_fields = sod_field.volume_interpolant(t, discr)
        print discr.norm(fields - true_fields)
Beispiel #8
0
def main(write_output=True,
         dir_tag=TAG_NONE,
         neu_tag=TAG_NONE,
         rad_tag=TAG_ALL,
         flux_type_arg="upwind",
         dtype=np.float64,
         debug=[]):
    from math import sin, cos, pi, exp, sqrt  # noqa

    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    dim = 2

    if dim == 1:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_uniform_1d_mesh
            mesh = make_uniform_1d_mesh(-10, 10, 500)
    elif dim == 2:
        from hedge.mesh.generator import make_rect_mesh
        if rcon.is_head_rank:
            mesh = make_rect_mesh(a=(-0.5, -0.5), b=(0.5, 0.5), max_area=0.008)
    elif dim == 3:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_ball_mesh
            mesh = make_ball_mesh(max_volume=0.0005)
    else:
        raise RuntimeError("bad number of dimensions")

    if rcon.is_head_rank:
        print "%d elements" % len(mesh.elements)
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper(dtype=dtype)

    from hedge.models.wave import StrongWaveOperator
    from hedge.mesh import TAG_ALL, TAG_NONE  # noqa

    source_center = np.array([0.1, 0.22])
    source_width = 0.05
    source_omega = 3

    import hedge.optemplate as sym
    sym_x = sym.nodes(2)
    sym_source_center_dist = sym_x - source_center

    op = StrongWaveOperator(
        -1,
        dim,
        source_f=sym.CFunction("sin")(
            source_omega * sym.ScalarParameter("t")) * sym.CFunction("exp")(
                -np.dot(sym_source_center_dist, sym_source_center_dist) /
                source_width**2),
        dirichlet_tag=dir_tag,
        neumann_tag=neu_tag,
        radiation_tag=rad_tag,
        flux_type=flux_type_arg)

    discr = rcon.make_discretization(mesh_data,
                                     order=4,
                                     debug=debug,
                                     default_scalar_type=dtype,
                                     tune_for=op.op_template())

    from hedge.visualization import VtkVisualizer
    if write_output:
        vis = VtkVisualizer(discr, rcon, "fld")

    from hedge.tools import join_fields
    fields = join_fields(
        discr.volume_zeros(dtype=dtype),
        [discr.volume_zeros(dtype=dtype) for i in range(discr.dimensions)])

    # {{{ diagnostics setup

    from pytools.log import LogManager, \
            add_general_quantities, \
            add_simulation_quantities, \
            add_run_info

    if write_output:
        log_file_name = "wave.dat"
    else:
        log_file_name = None

    logmgr = LogManager(log_file_name, "w", rcon.communicator)
    add_run_info(logmgr)
    add_general_quantities(logmgr)
    add_simulation_quantities(logmgr)
    discr.add_instrumentation(logmgr)

    from pytools.log import IntervalTimer
    vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
    logmgr.add_quantity(vis_timer)
    stepper.add_instrumentation(logmgr)

    from hedge.log import LpNorm
    u_getter = lambda: fields[0]
    logmgr.add_quantity(LpNorm(u_getter, discr, 1, name="l1_u"))
    logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))

    logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])

    # }}}

    # {{{ timestep loop

    rhs = op.bind(discr)
    try:
        from hedge.timestep import times_and_steps
        step_it = times_and_steps(
            final_time=4,
            logmgr=logmgr,
            max_dt_getter=lambda t: op.estimate_timestep(
                discr, stepper=stepper, t=t, fields=fields))

        for step, t, dt in step_it:
            if step % 10 == 0 and write_output:
                visf = vis.make_file("fld-%04d" % step)

                vis.add_data(visf, [
                    ("u", discr.convert_volume(fields[0], kind="numpy")),
                    ("v", discr.convert_volume(fields[1:], kind="numpy")),
                ],
                             time=t,
                             step=step)
                visf.close()

            fields = stepper(fields, t, dt, rhs)

        assert discr.norm(fields) < 1
        assert fields[0].dtype == dtype

    finally:
        if write_output:
            vis.close()

        logmgr.close()
        discr.close()
Beispiel #9
0
def main(write_output=True, dtype=np.float32):
    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    from hedge.mesh.generator import make_rect_mesh
    if rcon.is_head_rank:
        h_fac = 1
        mesh = make_rect_mesh(a=(0, 0),
                              b=(1, 1),
                              max_area=h_fac**2 * 1e-4,
                              periodicity=(True, True),
                              subdivisions=(int(70 / h_fac), int(70 / h_fac)))

    from hedge.models.gas_dynamics.lbm import \
            D2Q9LBMMethod, LatticeBoltzmannOperator

    op = LatticeBoltzmannOperator(D2Q9LBMMethod(), lbm_delta_t=0.001, nu=1e-4)

    if rcon.is_head_rank:
        print "%d elements" % len(mesh.elements)
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    discr = rcon.make_discretization(mesh_data,
                                     order=3,
                                     default_scalar_type=dtype,
                                     debug=["cuda_no_plan"])
    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper(
        dtype=dtype,
        #vector_primitive_factory=discr.get_vector_primitive_factory()
    )

    from hedge.visualization import VtkVisualizer
    if write_output:
        vis = VtkVisualizer(discr, rcon, "fld")

    from hedge.data import CompiledExpressionData

    def ic_expr(t, x, fields):
        from hedge.optemplate import CFunction
        from pymbolic.primitives import IfPositive
        from pytools.obj_array import make_obj_array

        tanh = CFunction("tanh")
        sin = CFunction("sin")

        rho = 1
        u0 = 0.05
        w = 0.05
        delta = 0.05

        from hedge.optemplate.primitives import make_common_subexpression as cse
        u = cse(
            make_obj_array([
                IfPositive(x[1] - 1 / 2, u0 * tanh(4 * (3 / 4 - x[1]) / w),
                           u0 * tanh(4 * (x[1] - 1 / 4) / w)),
                u0 * delta * sin(2 * np.pi * (x[0] + 1 / 4))
            ]), "u")

        return make_obj_array([
            op.method.f_equilibrium(rho, alpha, u)
            for alpha in range(len(op.method))
        ])

    # timestep loop -----------------------------------------------------------
    stream_rhs = op.bind_rhs(discr)
    collision_update = op.bind(discr, op.collision_update)
    get_rho = op.bind(discr, op.rho)
    get_rho_u = op.bind(discr, op.rho_u)

    f_bar = CompiledExpressionData(ic_expr).volume_interpolant(0, discr)

    from hedge.discretization import ExponentialFilterResponseFunction
    from hedge.optemplate.operators import FilterOperator
    mode_filter = FilterOperator(
            ExponentialFilterResponseFunction(min_amplification=0.9, order=4))\
                    .bind(discr)

    final_time = 1000
    try:
        lbm_dt = op.lbm_delta_t
        dg_dt = op.estimate_timestep(discr, stepper=stepper)
        print dg_dt

        dg_steps_per_lbm_step = int(np.ceil(lbm_dt / dg_dt))
        dg_dt = lbm_dt / dg_steps_per_lbm_step

        lbm_steps = int(final_time // op.lbm_delta_t)
        for step in xrange(lbm_steps):
            t = step * lbm_dt

            if step % 100 == 0 and write_output:
                visf = vis.make_file("fld-%04d" % step)

                rho = get_rho(f_bar)
                rho_u = get_rho_u(f_bar)
                vis.add_data(
                    visf,
                    [("fbar%d" % i, discr.convert_volume(f_bar_i, "numpy"))
                     for i, f_bar_i in enumerate(f_bar)] + [
                         ("rho", discr.convert_volume(rho, "numpy")),
                         ("rho_u", discr.convert_volume(rho_u, "numpy")),
                     ],
                    time=t,
                    step=step)
                visf.close()

            print "step=%d, t=%f" % (step, t)

            f_bar = collision_update(f_bar)

            for substep in range(dg_steps_per_lbm_step):
                f_bar = stepper(f_bar, t + substep * dg_dt, dg_dt, stream_rhs)

            #f_bar = mode_filter(f_bar)

    finally:
        if write_output:
            vis.close()

        discr.close()
Beispiel #10
0
def main(write_output=True, \
        dir_tag=TAG_NONE, \
        neu_tag=TAG_NONE,\
        rad_tag=TAG_ALL,
        flux_type_arg="upwind"):
    from math import sin, cos, pi, exp, sqrt

    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    dim = 2

    if dim == 1:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_uniform_1d_mesh
            mesh = make_uniform_1d_mesh(-10, 10, 500)
    elif dim == 2:
        from hedge.mesh.generator import make_rect_mesh
        if rcon.is_head_rank:
            mesh = make_rect_mesh(a=(-1,-1),b=(1,1),max_area=0.003)
    elif dim == 3:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_ball_mesh
            mesh = make_ball_mesh(max_volume=0.0005)
    else:
        raise RuntimeError, "bad number of dimensions"

    if rcon.is_head_rank:
        print "%d elements" % len(mesh.elements)
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    discr = rcon.make_discretization(mesh_data, order=4)

    from hedge.timestep import RK4TimeStepper
    stepper = RK4TimeStepper()

    from hedge.visualization import VtkVisualizer
    if write_output:
        vis = VtkVisualizer(discr, rcon, "fld")

    def source_u(x, el):
        x = x - numpy.array([0.7, 0.4])
        return exp(-numpy.dot(x, x)*256)

    def c_speed(x, el):
        if la.norm(x) < 0.4:
            return 1
        else:
            return 0.5

    from hedge.models.wave import VariableVelocityStrongWaveOperator
    from hedge.data import \
            TimeIntervalGivenFunction, \
            make_tdep_given
    from hedge.mesh import TAG_ALL, TAG_NONE
    op = VariableVelocityStrongWaveOperator(
            make_tdep_given(c_speed),
            discr.dimensions, 
            source=TimeIntervalGivenFunction(
                make_tdep_given(source_u),
                0, 0.1),
            dirichlet_tag=dir_tag,
            neumann_tag=neu_tag,
            radiation_tag=rad_tag,
            flux_type=flux_type_arg
            )

    from hedge.tools import join_fields
    fields = join_fields(discr.volume_zeros(),
            [discr.volume_zeros() for i in range(discr.dimensions)])

    # diagnostics setup -------------------------------------------------------
    from pytools.log import LogManager, \
            add_general_quantities, \
            add_simulation_quantities, \
            add_run_info

    if write_output:
        log_file_name = "wave.dat"
    else:
        log_file_name = None

    logmgr = LogManager(log_file_name, "w", rcon.communicator)
    add_run_info(logmgr)
    add_general_quantities(logmgr)
    add_simulation_quantities(logmgr)
    discr.add_instrumentation(logmgr)

    from pytools.log import IntervalTimer
    vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
    logmgr.add_quantity(vis_timer)
    stepper.add_instrumentation(logmgr)

    from hedge.log import Integral, LpNorm
    u_getter = lambda: fields[0]
    logmgr.add_quantity(LpNorm(u_getter, discr, 1, name="l1_u"))
    logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))

    logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])

    # timestep loop -----------------------------------------------------------
    rhs = op.bind(discr)
    try:
        dt = op.estimate_timestep(discr, stepper=stepper, fields=fields)
        if flux_type_arg == "central":
            dt *= 0.25

        from hedge.timestep import times_and_steps
        step_it = times_and_steps(final_time=3, logmgr=logmgr,
                max_dt_getter=lambda t: dt)

        for step, t, dt in step_it:
            if step % 10 == 0 and write_output:
                visf = vis.make_file("fld-%04d" % step)

                vis.add_data(visf,
                        [
                            ("u", fields[0]),
                            ("v", fields[1:]), 
                            ("c", op.c.volume_interpolant(0, discr)), 
                        ],
                        time=t,
                        step=step)
                visf.close()

            fields = stepper(fields, t, dt, rhs)

        assert discr.norm(fields) < 1
    finally:
        if write_output:
            vis.close()

        logmgr.close()
        discr.close()
Beispiel #11
0
def main(write_output=True):
    from math import sin, exp, sqrt

    from hedge.mesh.generator import make_rect_mesh
    mesh = make_rect_mesh(a=(-0.5,-0.5),b=(0.5,0.5),max_area=0.008)

    from hedge.backends.jit import Discretization

    discr = Discretization(mesh, order=4)

    from hedge.visualization import VtkVisualizer
    vis = VtkVisualizer(discr, None, "fld")

    def source_u(x, el):
        x = x - numpy.array([0.1,0.22])
        return exp(-numpy.dot(x, x)*128)

    from hedge.data import \
            make_tdep_given, \
            TimeHarmonicGivenFunction, \
            TimeIntervalGivenFunction

    from hedge.models.wave import StrongWaveOperator
    from hedge.mesh import TAG_ALL, TAG_NONE
    op = StrongWaveOperator(-1, discr.dimensions, 
            source_f=TimeIntervalGivenFunction(
                TimeHarmonicGivenFunction(
                    make_tdep_given(source_u), omega=10),
                0, 1),
            dirichlet_tag=TAG_NONE,
            neumann_tag=TAG_NONE,
            radiation_tag=TAG_ALL,
            flux_type="upwind")

    from hedge.tools import join_fields
    fields = join_fields(discr.volume_zeros(),
            [discr.volume_zeros() for i in range(discr.dimensions)])

    from hedge.timestep import RK4TimeStepper
    stepper = RK4TimeStepper()
    dt = op.estimate_timestep(discr, stepper=stepper, fields=fields)

    nsteps = int(1/dt)
    print "dt=%g nsteps=%d" % (dt, nsteps)

    rhs = op.bind(discr)
    for step in range(nsteps):
        t = step*dt

        if step % 50 == 0 and write_output:
            print step, t, discr.norm(fields[0])
            visf = vis.make_file("fld-%04d" % step)

            vis.add_data(visf,
                    [ ("u", fields[0]), ("v", fields[1:]), ],
                    time=t, step=step)
            visf.close()

        fields = stepper(fields, t, dt, rhs)

    vis.close()
Beispiel #12
0
def main(write_output=True,
        dir_tag=TAG_NONE, neu_tag=TAG_NONE, rad_tag=TAG_ALL,
        flux_type_arg="upwind", dtype=np.float64, debug=[]):
    from math import sin, cos, pi, exp, sqrt  # noqa

    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    dim = 2

    if dim == 1:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_uniform_1d_mesh
            mesh = make_uniform_1d_mesh(-10, 10, 500)
    elif dim == 2:
        from hedge.mesh.generator import make_rect_mesh
        if rcon.is_head_rank:
            mesh = make_rect_mesh(a=(-0.5, -0.5), b=(0.5, 0.5), max_area=0.008)
    elif dim == 3:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_ball_mesh
            mesh = make_ball_mesh(max_volume=0.0005)
    else:
        raise RuntimeError("bad number of dimensions")

    if rcon.is_head_rank:
        print "%d elements" % len(mesh.elements)
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper(dtype=dtype)

    from hedge.models.wave import StrongWaveOperator
    from hedge.mesh import TAG_ALL, TAG_NONE  # noqa

    source_center = np.array([0.1, 0.22])
    source_width = 0.05
    source_omega = 3

    import hedge.optemplate as sym
    sym_x = sym.nodes(2)
    sym_source_center_dist = sym_x - source_center

    op = StrongWaveOperator(-1, dim,
            source_f=
            sym.CFunction("sin")(source_omega*sym.ScalarParameter("t"))
            * sym.CFunction("exp")(
                -np.dot(sym_source_center_dist, sym_source_center_dist)
                / source_width**2),
            dirichlet_tag=dir_tag,
            neumann_tag=neu_tag,
            radiation_tag=rad_tag,
            flux_type=flux_type_arg
            )

    discr = rcon.make_discretization(mesh_data, order=4, debug=debug,
            default_scalar_type=dtype,
            tune_for=op.op_template())

    from hedge.visualization import VtkVisualizer
    if write_output:
        vis = VtkVisualizer(discr, rcon, "fld")

    from hedge.tools import join_fields
    fields = join_fields(discr.volume_zeros(dtype=dtype),
            [discr.volume_zeros(dtype=dtype) for i in range(discr.dimensions)])

    # {{{ diagnostics setup

    from pytools.log import LogManager, \
            add_general_quantities, \
            add_simulation_quantities, \
            add_run_info

    if write_output:
        log_file_name = "wave.dat"
    else:
        log_file_name = None

    logmgr = LogManager(log_file_name, "w", rcon.communicator)
    add_run_info(logmgr)
    add_general_quantities(logmgr)
    add_simulation_quantities(logmgr)
    discr.add_instrumentation(logmgr)

    from pytools.log import IntervalTimer
    vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
    logmgr.add_quantity(vis_timer)
    stepper.add_instrumentation(logmgr)

    from hedge.log import LpNorm
    u_getter = lambda: fields[0]
    logmgr.add_quantity(LpNorm(u_getter, discr, 1, name="l1_u"))
    logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))

    logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])

    # }}}

    # {{{ timestep loop

    rhs = op.bind(discr)
    try:
        from hedge.timestep import times_and_steps
        step_it = times_and_steps(
                final_time=4, logmgr=logmgr,
                max_dt_getter=lambda t: op.estimate_timestep(discr,
                    stepper=stepper, t=t, fields=fields))

        for step, t, dt in step_it:
            if step % 10 == 0 and write_output:
                visf = vis.make_file("fld-%04d" % step)

                vis.add_data(visf,
                        [
                            ("u", discr.convert_volume(fields[0], kind="numpy")),
                            ("v", discr.convert_volume(fields[1:], kind="numpy")),
                        ],
                        time=t,
                        step=step)
                visf.close()

            fields = stepper(fields, t, dt, rhs)

        assert discr.norm(fields) < 1
        assert fields[0].dtype == dtype

    finally:
        if write_output:
            vis.close()

        logmgr.close()
        discr.close()
Beispiel #13
0
def main(write_output=True, flux_type_arg="upwind", 
        #case = CenteredStationaryTestCase(),
        #case = OffCenterStationaryTestCase(),
        #case = OffCenterMigratingTestCase(),
        case = ExactTestCase(),
        ):
    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    order = 3
    if rcon.is_head_rank:
        if True:
            from hedge.mesh.generator import make_uniform_1d_mesh
            mesh = make_uniform_1d_mesh(case.a, case.b, 20, periodic=True)
        else:
            from hedge.mesh.generator import make_rect_mesh
            print (pi*2)/(11*5*2)
            mesh = make_rect_mesh((-pi, -1), (pi, 1),
                    periodicity=(True, True),
                    subdivisions=(11,5),
                    max_area=(pi*2)/(11*5*2)
                    )

    if rcon.is_head_rank:
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    discr = rcon.make_discretization(mesh_data, order=order,
            quad_min_degrees={"quad": 3*order})

    if write_output:
        from hedge.visualization import VtkVisualizer
        vis = VtkVisualizer(discr, rcon, "fld")

    # operator setup ----------------------------------------------------------
    from hedge.second_order import IPDGSecondDerivative

    from hedge.models.burgers import BurgersOperator
    op = BurgersOperator(mesh.dimensions,
            viscosity_scheme=IPDGSecondDerivative())

    if rcon.is_head_rank:
        print "%d elements" % len(discr.mesh.elements)

    # exact solution ----------------------------------------------------------
    import pymbolic
    var = pymbolic.var

    u = discr.interpolate_volume_function(lambda x, el: case.u0(x[0]))

    # diagnostics setup -------------------------------------------------------
    from pytools.log import LogManager, \
            add_general_quantities, \
            add_simulation_quantities, \
            add_run_info

    if write_output:
        log_file_name = "burgers.dat"
    else:
        log_file_name = None

    logmgr = LogManager(log_file_name, "w", rcon.communicator)
    add_run_info(logmgr)
    add_general_quantities(logmgr)
    add_simulation_quantities(logmgr)
    discr.add_instrumentation(logmgr)

    from hedge.log import LpNorm
    u_getter = lambda: u
    logmgr.add_quantity(LpNorm(u_getter, discr, p=1, name="l1_u"))

    logmgr.add_watches(["step.max", "t_sim.max", "l1_u", "t_step.max"])

    # timestep loop -----------------------------------------------------------
    rhs = op.bind(discr)

    from hedge.timestep.runge_kutta import ODE45TimeStepper, LSRK4TimeStepper
    stepper = ODE45TimeStepper()

    stepper.add_instrumentation(logmgr)

    try:
        from hedge.timestep import times_and_steps
        # for visc=0.01
        #stab_fac = 0.1 # RK4
        #stab_fac = 1.6 # dumka3(3), central
        #stab_fac = 3 # dumka3(4), central

        #stab_fac = 0.01 # RK4
        stab_fac = 0.2 # dumka3(3), central
        #stab_fac = 3 # dumka3(4), central

        dt = stab_fac*op.estimate_timestep(discr,
                stepper=LSRK4TimeStepper(), t=0, fields=u)

        step_it = times_and_steps(
                final_time=case.final_time, logmgr=logmgr, max_dt_getter=lambda t: dt)
        from hedge.optemplate import  InverseVandermondeOperator
        inv_vdm = InverseVandermondeOperator().bind(discr)

        for step, t, dt in step_it:
            if step % 3 == 0 and write_output:
                if hasattr(case, "u_exact"):
                    extra_fields = [
                            ("u_exact",
                                discr.interpolate_volume_function(
                                    lambda x, el: case.u_exact(x[0], t)))]
                else:
                    extra_fields = []

                visf = vis.make_file("fld-%04d" % step)
                vis.add_data(visf, [
                    ("u", u),
                    ] + extra_fields,
                    time=t,
                    step=step)
                visf.close()

            u = stepper(u, t, dt, rhs)

        if isinstance(case, ExactTestCase):
            assert discr.norm(u, 1) < 50

    finally:
        if write_output:
            vis.close()

        logmgr.save()
Beispiel #14
0
def main(write_output=True,
         flux_type_arg="central",
         use_quadrature=True,
         final_time=20):
    from math import sin, cos, pi, sqrt

    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    # mesh setup --------------------------------------------------------------
    if rcon.is_head_rank:
        #from hedge.mesh.generator import make_disk_mesh
        #mesh = make_disk_mesh()
        from hedge.mesh.generator import make_rect_mesh
        mesh = make_rect_mesh(a=(-1, -1), b=(1, 1), max_area=0.008)

    if rcon.is_head_rank:
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    # space-time-dependent-velocity-field -------------------------------------
    # simple vortex
    class TimeDependentVField:
        """ `TimeDependentVField` is a callable expecting `(x, t)` representing space and time

        `x` is of the length of the spatial dimension and `t` is the time."""
        shape = (2, )

        def __call__(self, pt, el, t):
            x, y = pt
            # Correction-Factor to make the speed zero on the on the boundary
            #fac = (1-x**2)*(1-y**2)
            fac = 1.
            return numpy.array([-y * fac, x * fac]) * cos(pi * t)

    class VField:
        """ `VField` is a callable expecting `(x)` representing space

        `x` is of the length of the spatial dimension."""
        shape = (2, )

        def __call__(self, pt, el):
            x, y = pt
            # Correction-Factor to make the speed zero on the on the boundary
            #fac = (1-x**2)*(1-y**2)
            fac = 1.
            return numpy.array([-y * fac, x * fac])

    # space-time-dependent State BC (optional)-----------------------------------
    class TimeDependentBc_u:
        """ space and time dependent BC for state u"""
        def __call__(self, pt, el, t):
            x, y = pt
            if t <= 0.5:
                if x > 0:
                    return 1
                else:
                    return 0
            else:
                return 0

    class Bc_u:
        """ Only space dependent BC for state u"""
        def __call__(seld, pt, el):
            x, y = pt
            if x > 0:
                return 1
            else:
                return 0

    # operator setup ----------------------------------------------------------
    # In the operator setup it is possible to switch between a only space
    # dependent velocity field `VField` or a time and space dependent
    # `TimeDependentVField`.
    # For `TimeDependentVField`: advec_v=TimeDependentGivenFunction(VField())
    # For `VField`: advec_v=TimeConstantGivenFunction(GivenFunction(VField()))
    # Same for the Bc_u Function! If you don't define Bc_u then the BC for u = 0.

    from hedge.data import \
            ConstantGivenFunction, \
            TimeConstantGivenFunction, \
            TimeDependentGivenFunction, \
            GivenFunction
    from hedge.models.advection import VariableCoefficientAdvectionOperator
    op = VariableCoefficientAdvectionOperator(
        mesh.dimensions,
        #advec_v=TimeDependentGivenFunction(
        #    TimeDependentVField()),
        advec_v=TimeConstantGivenFunction(GivenFunction(VField())),
        #bc_u_f=TimeDependentGivenFunction(
        #    TimeDependentBc_u()),
        bc_u_f=TimeConstantGivenFunction(GivenFunction(Bc_u())),
        flux_type=flux_type_arg)

    # discretization setup ----------------------------------------------------
    order = 5
    if use_quadrature:
        quad_min_degrees = {"quad": 3 * order}
    else:
        quad_min_degrees = {}

    discr = rcon.make_discretization(
        mesh_data,
        order=order,
        default_scalar_type=numpy.float64,
        debug=["cuda_no_plan"],
        quad_min_degrees=quad_min_degrees,
        tune_for=op.op_template(),
    )
    vis_discr = discr

    # visualization setup -----------------------------------------------------
    from hedge.visualization import VtkVisualizer
    if write_output:
        vis = VtkVisualizer(vis_discr, rcon, "fld")

    # initial condition -------------------------------------------------------
    if True:

        def initial(pt, el):
            # Gauss pulse
            from math import exp
            x = (pt - numpy.array([0.3, 0.5])) * 8
            return exp(-numpy.dot(x, x))
    else:

        def initial(pt, el):
            # Rectangle
            x, y = pt
            if abs(x) < 0.5 and abs(y) < 0.2:
                return 2
            else:
                return 1

    u = discr.interpolate_volume_function(initial)

    # timestep setup ----------------------------------------------------------
    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper(
        vector_primitive_factory=discr.get_vector_primitive_factory())

    if rcon.is_head_rank:
        print "%d elements" % len(discr.mesh.elements)

    # filter setup-------------------------------------------------------------
    from hedge.discretization import ExponentialFilterResponseFunction
    from hedge.optemplate.operators import FilterOperator
    mode_filter = FilterOperator(
            ExponentialFilterResponseFunction(min_amplification=0.9,order=4))\
                    .bind(discr)

    # diagnostics setup -------------------------------------------------------
    from pytools.log import LogManager, \
            add_general_quantities, \
            add_simulation_quantities, \
            add_run_info

    if write_output:
        log_file_name = "space-dep.dat"
    else:
        log_file_name = None

    logmgr = LogManager(log_file_name, "w", rcon.communicator)
    add_run_info(logmgr)
    add_general_quantities(logmgr)
    add_simulation_quantities(logmgr)
    discr.add_instrumentation(logmgr)

    stepper.add_instrumentation(logmgr)

    from hedge.log import Integral, LpNorm
    u_getter = lambda: u
    logmgr.add_quantity(Integral(u_getter, discr, name="int_u"))
    logmgr.add_quantity(LpNorm(u_getter, discr, p=1, name="l1_u"))
    logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))

    logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])

    # Initialize v for data output:
    v = op.advec_v.volume_interpolant(0, discr)

    # timestep loop -----------------------------------------------------------
    rhs = op.bind(discr)
    try:
        from hedge.timestep import times_and_steps
        step_it = times_and_steps(final_time=final_time,
                                  logmgr=logmgr,
                                  max_dt_getter=lambda t: op.estimate_timestep(
                                      discr, stepper=stepper, t=t, fields=u))

        for step, t, dt in step_it:
            if step % 10 == 0 and write_output:
                visf = vis.make_file("fld-%04d" % step)
                vis.add_data(visf,
                             [("u", discr.convert_volume(u, kind="numpy")),
                              ("v", discr.convert_volume(v, kind="numpy"))],
                             time=t,
                             step=step)
                visf.close()

            u = stepper(u, t, dt, rhs)

            # We're feeding in a discontinuity through the BCs.
            # Quadrature does not help with shock capturing--
            # therefore we do need to filter here, regardless
            # of whether quadrature is enabled.
            u = mode_filter(u)

        assert discr.norm(u) < 10

    finally:
        if write_output:
            vis.close()

        logmgr.close()
        discr.close()
Beispiel #15
0
    def test_cuda_volume_quadrature():
        from hedge.mesh.generator import make_rect_mesh
        mesh = make_rect_mesh(a=(-1,-1),b=(1,1),max_area=0.08)

        from hedge.backends import guess_run_context
        cpu_rcon = guess_run_context(['jit'])
        gpu_rcon = guess_run_context(['cuda'])

        order = 4
        quad_min_degrees = {"quad": 3*order}

        cpu_discr, gpu_discr = [
                rcon.make_discretization(mesh, order=order,
                    default_scalar_type=numpy.float64, 
                    debug=["cuda_no_plan", "cuda_no_microblock", ],
                    quad_min_degrees=quad_min_degrees
                    )
                for rcon in [cpu_rcon, gpu_rcon]]

        from math import sin, cos
        def f(x, el):
            return sin(x[0])*cos(x[1])

        cpu_field, gpu_field = [
                discr.interpolate_volume_function(f)
                for discr in [cpu_discr, gpu_discr]]

        def make_optemplate():
            from hedge.optemplate.operators import QuadratureGridUpsampler
            from hedge.optemplate import Field, make_stiffness_t

            u = Field("u")
            qu = QuadratureGridUpsampler("quad")(u)

            return make_stiffness_t(2)[0](Field("intercept")(qu))

        saved_vectors = []
        def intercept(x):
            saved_vectors.append(x)
            return x

        for discr in [cpu_discr, gpu_discr]:
            discr.add_function("intercept", intercept)

        opt = make_optemplate()
        cpu_bound, gpu_bound = [discr.compile(make_optemplate())
                for discr in [cpu_discr, gpu_discr]]

        cpu_result = cpu_bound(u=cpu_field)
        gpu_result = gpu_bound(u=gpu_field)

        cpu_ivec, gpu_ivec = saved_vectors
        gpu_ivec_on_host = gpu_ivec.get()[gpu_discr._gpu_volume_embedding("quad")]
        ierr = cpu_ivec-gpu_ivec_on_host
        assert la.norm(ierr) < 5e-15

        gpu_result_on_host = gpu_discr.convert_volume(gpu_result, kind="numpy")
        err = cpu_result-gpu_result_on_host
        assert la.norm(err) < 2e-14

        cpu_discr.close()
        gpu_discr.close()
Beispiel #16
0
def main(write_output=True, flux_type_arg="central", use_quadrature=True,
        final_time=20):
    from math import sin, cos, pi, sqrt

    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    # mesh setup --------------------------------------------------------------
    if rcon.is_head_rank:
        #from hedge.mesh.generator import make_disk_mesh
        #mesh = make_disk_mesh()
        from hedge.mesh.generator import make_rect_mesh
        mesh = make_rect_mesh(a=(-1,-1),b=(1,1),max_area=0.008)

    if rcon.is_head_rank:
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    # space-time-dependent-velocity-field -------------------------------------
    # simple vortex
    class TimeDependentVField:
        """ `TimeDependentVField` is a callable expecting `(x, t)` representing space and time

        `x` is of the length of the spatial dimension and `t` is the time."""
        shape = (2,)

        def __call__(self, pt, el, t):
            x, y = pt
            # Correction-Factor to make the speed zero on the on the boundary
            #fac = (1-x**2)*(1-y**2)
            fac = 1.
            return numpy.array([-y*fac, x*fac]) * cos(pi*t)

    class VField:
        """ `VField` is a callable expecting `(x)` representing space

        `x` is of the length of the spatial dimension."""
        shape = (2,)

        def __call__(self, pt, el):
            x, y = pt
            # Correction-Factor to make the speed zero on the on the boundary
            #fac = (1-x**2)*(1-y**2)
            fac = 1.
            return numpy.array([-y*fac, x*fac])

    # space-time-dependent State BC (optional)-----------------------------------
    class TimeDependentBc_u:
        """ space and time dependent BC for state u"""
        def __call__(self, pt, el, t):
            x, y = pt
            if t <= 0.5:
                if x > 0:
                    return 1
                else:
                    return 0
            else:
                return 0

    class Bc_u:
        """ Only space dependent BC for state u"""
        def __call__(seld, pt, el):
            x, y = pt
            if x > 0:
                return 1
            else:
                return 0


    # operator setup ----------------------------------------------------------
    # In the operator setup it is possible to switch between a only space
    # dependent velocity field `VField` or a time and space dependent
    # `TimeDependentVField`.
    # For `TimeDependentVField`: advec_v=TimeDependentGivenFunction(VField())
    # For `VField`: advec_v=TimeConstantGivenFunction(GivenFunction(VField()))
    # Same for the Bc_u Function! If you don't define Bc_u then the BC for u = 0.

    from hedge.data import \
            ConstantGivenFunction, \
            TimeConstantGivenFunction, \
            TimeDependentGivenFunction, \
            GivenFunction
    from hedge.models.advection import VariableCoefficientAdvectionOperator
    op = VariableCoefficientAdvectionOperator(mesh.dimensions,
        #advec_v=TimeDependentGivenFunction(
        #    TimeDependentVField()),
        advec_v=TimeConstantGivenFunction(
            GivenFunction(VField())),
        #bc_u_f=TimeDependentGivenFunction(
        #    TimeDependentBc_u()),
        bc_u_f=TimeConstantGivenFunction(
            GivenFunction(Bc_u())),
        flux_type=flux_type_arg)

    # discretization setup ----------------------------------------------------
    order = 5
    if use_quadrature:
        quad_min_degrees = {"quad": 3*order}
    else:
        quad_min_degrees = {}

    discr = rcon.make_discretization(mesh_data, order=order,
            default_scalar_type=numpy.float64, 
            debug=["cuda_no_plan"],
            quad_min_degrees=quad_min_degrees,
            tune_for=op.op_template(),

            )
    vis_discr = discr

    # visualization setup -----------------------------------------------------
    from hedge.visualization import VtkVisualizer
    if write_output:
        vis = VtkVisualizer(vis_discr, rcon, "fld")

    # initial condition -------------------------------------------------------
    if True:
        def initial(pt, el):
            # Gauss pulse
            from math import exp
            x = (pt-numpy.array([0.3, 0.5]))*8
            return exp(-numpy.dot(x, x))
    else:
        def initial(pt, el):
            # Rectangle
            x, y = pt
            if abs(x) < 0.5 and abs(y) < 0.2:
                return 2
            else:
                return 1

    u = discr.interpolate_volume_function(initial)

    # timestep setup ----------------------------------------------------------
    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper(
            vector_primitive_factory=discr.get_vector_primitive_factory())

    if rcon.is_head_rank:
        print "%d elements" % len(discr.mesh.elements)

    # filter setup-------------------------------------------------------------
    from hedge.discretization import ExponentialFilterResponseFunction
    from hedge.optemplate.operators import FilterOperator
    mode_filter = FilterOperator(
            ExponentialFilterResponseFunction(min_amplification=0.9,order=4))\
                    .bind(discr)

    # diagnostics setup -------------------------------------------------------
    from pytools.log import LogManager, \
            add_general_quantities, \
            add_simulation_quantities, \
            add_run_info

    if write_output:
        log_file_name = "space-dep.dat"
    else:
        log_file_name = None

    logmgr = LogManager(log_file_name, "w", rcon.communicator)
    add_run_info(logmgr)
    add_general_quantities(logmgr)
    add_simulation_quantities(logmgr)
    discr.add_instrumentation(logmgr)

    stepper.add_instrumentation(logmgr)

    from hedge.log import Integral, LpNorm
    u_getter = lambda: u
    logmgr.add_quantity(Integral(u_getter, discr, name="int_u"))
    logmgr.add_quantity(LpNorm(u_getter, discr, p=1, name="l1_u"))
    logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))

    logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])

    # Initialize v for data output:
    v = op.advec_v.volume_interpolant(0, discr)

    # timestep loop -----------------------------------------------------------
    rhs = op.bind(discr)
    try:
        from hedge.timestep import times_and_steps
        step_it = times_and_steps(
                final_time=final_time, logmgr=logmgr,
                max_dt_getter=lambda t: op.estimate_timestep(discr,
                    stepper=stepper, t=t, fields=u))

        for step, t, dt in step_it:
            if step % 10 == 0 and write_output:
                visf = vis.make_file("fld-%04d" % step)
                vis.add_data(visf, [ 
                    ("u", discr.convert_volume(u, kind="numpy")), 
                    ("v", discr.convert_volume(v, kind="numpy"))
                    ], time=t, step=step)
                visf.close()

            u = stepper(u, t, dt, rhs)

            # We're feeding in a discontinuity through the BCs.
            # Quadrature does not help with shock capturing--
            # therefore we do need to filter here, regardless
            # of whether quadrature is enabled.
            u = mode_filter(u)

        assert discr.norm(u) < 10

    finally:
        if write_output:
            vis.close()

        logmgr.close()
        discr.close()
Beispiel #17
0
    #case = OffCenterMigratingTestCase(),
    case=ExactTestCase(),
):
    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    order = 3
    if rcon.is_head_rank:
        if True:
            from hedge.mesh.generator import make_uniform_1d_mesh
            mesh = make_uniform_1d_mesh(case.a, case.b, 20, periodic=True)
        else:
            from hedge.mesh.generator import make_rect_mesh
            print(pi * 2) / (11 * 5 * 2)
            mesh = make_rect_mesh((-pi, -1), (pi, 1),
                                  periodicity=(True, True),
                                  subdivisions=(11, 5),
                                  max_area=(pi * 2) / (11 * 5 * 2))

    if rcon.is_head_rank:
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    discr = rcon.make_discretization(mesh_data,
                                     order=order,
                                     quad_min_degrees={"quad": 3 * order})

    if write_output:
        from hedge.visualization import VtkVisualizer
        vis = VtkVisualizer(discr, rcon, "fld")
def main(write_output=True,
        dir_tag=TAG_NONE,
        neu_tag=TAG_NONE,
        rad_tag=TAG_ALL,
        flux_type_arg="upwind"):
    from math import sin, cos, pi, exp, sqrt  # noqa

    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    dim = 2

    if dim == 1:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_uniform_1d_mesh
            mesh = make_uniform_1d_mesh(-10, 10, 500)
    elif dim == 2:
        from hedge.mesh.generator import make_rect_mesh
        if rcon.is_head_rank:
            mesh = make_rect_mesh(a=(-1, -1), b=(1, 1), max_area=0.003)
    elif dim == 3:
        if rcon.is_head_rank:
            from hedge.mesh.generator import make_ball_mesh
            mesh = make_ball_mesh(max_volume=0.0005)
    else:
        raise RuntimeError("bad number of dimensions")

    if rcon.is_head_rank:
        print "%d elements" % len(mesh.elements)
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    discr = rcon.make_discretization(mesh_data, order=4)

    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper()

    from hedge.visualization import VtkVisualizer
    if write_output:
        vis = VtkVisualizer(discr, rcon, "fld")

    source_center = np.array([0.7, 0.4])
    source_width = 1/16
    source_omega = 3

    import hedge.optemplate as sym
    sym_x = sym.nodes(2)
    sym_source_center_dist = sym_x - source_center

    from hedge.models.wave import VariableVelocityStrongWaveOperator
    op = VariableVelocityStrongWaveOperator(
            c=sym.If(sym.Comparison(
                np.dot(sym_x, sym_x), "<", 0.4**2),
                1, 0.5),
            dimensions=discr.dimensions,
            source=
            sym.CFunction("sin")(source_omega*sym.ScalarParameter("t"))
            * sym.CFunction("exp")(
                -np.dot(sym_source_center_dist, sym_source_center_dist)
                / source_width**2),
            dirichlet_tag=dir_tag,
            neumann_tag=neu_tag,
            radiation_tag=rad_tag,
            flux_type=flux_type_arg
            )

    from hedge.tools import join_fields
    fields = join_fields(discr.volume_zeros(),
            [discr.volume_zeros() for i in range(discr.dimensions)])

    # {{{ diagnostics setup

    from pytools.log import LogManager, \
            add_general_quantities, \
            add_simulation_quantities, \
            add_run_info

    if write_output:
        log_file_name = "wave.dat"
    else:
        log_file_name = None

    logmgr = LogManager(log_file_name, "w", rcon.communicator)
    add_run_info(logmgr)
    add_general_quantities(logmgr)
    add_simulation_quantities(logmgr)
    discr.add_instrumentation(logmgr)

    from pytools.log import IntervalTimer
    vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
    logmgr.add_quantity(vis_timer)
    stepper.add_instrumentation(logmgr)

    from hedge.log import LpNorm
    u_getter = lambda: fields[0]
    logmgr.add_quantity(LpNorm(u_getter, discr, 1, name="l1_u"))
    logmgr.add_quantity(LpNorm(u_getter, discr, name="l2_u"))

    logmgr.add_watches(["step.max", "t_sim.max", "l2_u", "t_step.max"])

    # }}}

    # {{{ timestep loop

    rhs = op.bind(discr)
    try:
        from hedge.timestep.stability import \
                approximate_rk4_relative_imag_stability_region
        max_dt = (
                1/discr.compile(op.max_eigenvalue_expr())()
                * discr.dt_non_geometric_factor()
                * discr.dt_geometric_factor()
                * approximate_rk4_relative_imag_stability_region(stepper))
        if flux_type_arg == "central":
            max_dt *= 0.25

        from hedge.timestep import times_and_steps
        step_it = times_and_steps(final_time=3, logmgr=logmgr,
                max_dt_getter=lambda t: max_dt)

        for step, t, dt in step_it:
            if step % 10 == 0 and write_output:
                visf = vis.make_file("fld-%04d" % step)

                vis.add_data(visf,
                        [
                            ("u", fields[0]),
                            ("v", fields[1:]),
                        ],
                        time=t,
                        step=step)
                visf.close()

            fields = stepper(fields, t, dt, rhs)

        assert discr.norm(fields) < 1
    finally:
        if write_output:
            vis.close()

        logmgr.close()
        discr.close()
Beispiel #19
0
def main(write_output=True):
    from math import sin, exp, sqrt  # noqa

    from hedge.mesh.generator import make_rect_mesh
    mesh = make_rect_mesh(a=(-0.5, -0.5), b=(0.5, 0.5), max_area=0.008)

    from hedge.backends.jit import Discretization

    discr = Discretization(mesh, order=4)

    from hedge.visualization import VtkVisualizer
    vis = VtkVisualizer(discr, None, "fld")

    source_center = np.array([0.1, 0.22])
    source_width = 0.05
    source_omega = 3

    import hedge.optemplate as sym
    sym_x = sym.nodes(2)
    sym_source_center_dist = sym_x - source_center

    from hedge.models.wave import StrongWaveOperator
    from hedge.mesh import TAG_ALL, TAG_NONE
    op = StrongWaveOperator(-0.1, discr.dimensions,
            source_f=
            sym.CFunction("sin")(source_omega*sym.ScalarParameter("t"))
            * sym.CFunction("exp")(
                -np.dot(sym_source_center_dist, sym_source_center_dist)
                / source_width**2),
            dirichlet_tag=TAG_NONE,
            neumann_tag=TAG_NONE,
            radiation_tag=TAG_ALL,
            flux_type="upwind")

    from hedge.tools import join_fields
    fields = join_fields(discr.volume_zeros(),
            [discr.volume_zeros() for i in range(discr.dimensions)])

    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper()
    dt = op.estimate_timestep(discr, stepper=stepper, fields=fields)

    nsteps = int(10/dt)
    print "dt=%g nsteps=%d" % (dt, nsteps)

    rhs = op.bind(discr)
    for step in range(nsteps):
        t = step*dt

        if step % 10 == 0 and write_output:
            print step, t, discr.norm(fields[0])
            visf = vis.make_file("fld-%04d" % step)

            vis.add_data(visf,
                    [("u", fields[0]), ("v", fields[1:]), ],
                    time=t, step=step)
            visf.close()

        fields = stepper(fields, t, dt, rhs)

    vis.close()
Beispiel #20
0
def main(write_output=True, dtype=np.float32):
    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    from hedge.mesh.generator import make_rect_mesh
    if rcon.is_head_rank:
        h_fac = 1
        mesh = make_rect_mesh(a=(0,0),b=(1,1), max_area=h_fac**2*1e-4,
                periodicity=(True,True),
                subdivisions=(int(70/h_fac), int(70/h_fac)))

    from hedge.models.gas_dynamics.lbm import \
            D2Q9LBMMethod, LatticeBoltzmannOperator

    op = LatticeBoltzmannOperator(
            D2Q9LBMMethod(), lbm_delta_t=0.001, nu=1e-4)

    if rcon.is_head_rank:
        print "%d elements" % len(mesh.elements)
        mesh_data = rcon.distribute_mesh(mesh)
    else:
        mesh_data = rcon.receive_mesh()

    discr = rcon.make_discretization(mesh_data, order=3,
            default_scalar_type=dtype,
            debug=["cuda_no_plan"])
    from hedge.timestep.runge_kutta import LSRK4TimeStepper
    stepper = LSRK4TimeStepper(dtype=dtype,
            #vector_primitive_factory=discr.get_vector_primitive_factory()
            )

    from hedge.visualization import VtkVisualizer
    if write_output:
        vis = VtkVisualizer(discr, rcon, "fld")

    from hedge.data import CompiledExpressionData
    def ic_expr(t, x, fields):
        from hedge.optemplate import CFunction
        from pymbolic.primitives import IfPositive
        from pytools.obj_array import make_obj_array

        tanh = CFunction("tanh")
        sin = CFunction("sin")

        rho = 1
        u0 = 0.05
        w = 0.05
        delta = 0.05

        from hedge.optemplate.primitives import make_common_subexpression as cse
        u = cse(make_obj_array([
            IfPositive(x[1]-1/2,
                u0*tanh(4*(3/4-x[1])/w),
                u0*tanh(4*(x[1]-1/4)/w)),
            u0*delta*sin(2*np.pi*(x[0]+1/4))]),
            "u")

        return make_obj_array([
            op.method.f_equilibrium(rho, alpha, u)
            for alpha in range(len(op.method))
            ])


    # timestep loop -----------------------------------------------------------
    stream_rhs = op.bind_rhs(discr)
    collision_update = op.bind(discr, op.collision_update)
    get_rho = op.bind(discr, op.rho)
    get_rho_u = op.bind(discr, op.rho_u)


    f_bar = CompiledExpressionData(ic_expr).volume_interpolant(0, discr)

    from hedge.discretization import ExponentialFilterResponseFunction
    from hedge.optemplate.operators import FilterOperator
    mode_filter = FilterOperator(
            ExponentialFilterResponseFunction(min_amplification=0.9, order=4))\
                    .bind(discr)

    final_time = 1000
    try:
        lbm_dt = op.lbm_delta_t
        dg_dt = op.estimate_timestep(discr, stepper=stepper)
        print dg_dt

        dg_steps_per_lbm_step = int(np.ceil(lbm_dt / dg_dt))
        dg_dt = lbm_dt / dg_steps_per_lbm_step

        lbm_steps = int(final_time // op.lbm_delta_t)
        for step in xrange(lbm_steps):
            t = step*lbm_dt

            if step % 100 == 0 and write_output:
                visf = vis.make_file("fld-%04d" % step)

                rho = get_rho(f_bar)
                rho_u = get_rho_u(f_bar)
                vis.add_data(visf,
                        [ ("fbar%d" %i, 
                            discr.convert_volume(f_bar_i, "numpy")) for i, f_bar_i in enumerate(f_bar)]+
                        [
                            ("rho", discr.convert_volume(rho, "numpy")),
                            ("rho_u", discr.convert_volume(rho_u, "numpy")),
                        ],
                        time=t,
                        step=step)
                visf.close()

            print "step=%d, t=%f" % (step, t)

            f_bar = collision_update(f_bar)

            for substep in range(dg_steps_per_lbm_step):
                f_bar = stepper(f_bar, t + substep*dg_dt, dg_dt, stream_rhs)

            #f_bar = mode_filter(f_bar)

    finally:
        if write_output:
            vis.close()

        discr.close()
Beispiel #21
0
    def test_cuda_volume_quadrature():
        from hedge.mesh.generator import make_rect_mesh
        mesh = make_rect_mesh(a=(-1, -1), b=(1, 1), max_area=0.08)

        from hedge.backends import guess_run_context
        cpu_rcon = guess_run_context(['jit'])
        gpu_rcon = guess_run_context(['cuda'])

        order = 4
        quad_min_degrees = {"quad": 3 * order}

        cpu_discr, gpu_discr = [
            rcon.make_discretization(mesh,
                                     order=order,
                                     default_scalar_type=numpy.float64,
                                     debug=[
                                         "cuda_no_plan",
                                         "cuda_no_microblock",
                                     ],
                                     quad_min_degrees=quad_min_degrees)
            for rcon in [cpu_rcon, gpu_rcon]
        ]

        from math import sin, cos

        def f(x, el):
            return sin(x[0]) * cos(x[1])

        cpu_field, gpu_field = [
            discr.interpolate_volume_function(f)
            for discr in [cpu_discr, gpu_discr]
        ]

        def make_optemplate():
            from hedge.optemplate.operators import QuadratureGridUpsampler
            from hedge.optemplate import Field, make_stiffness_t

            u = Field("u")
            qu = QuadratureGridUpsampler("quad")(u)

            return make_stiffness_t(2)[0](Field("intercept")(qu))

        saved_vectors = []

        def intercept(x):
            saved_vectors.append(x)
            return x

        for discr in [cpu_discr, gpu_discr]:
            discr.add_function("intercept", intercept)

        opt = make_optemplate()
        cpu_bound, gpu_bound = [
            discr.compile(make_optemplate())
            for discr in [cpu_discr, gpu_discr]
        ]

        cpu_result = cpu_bound(u=cpu_field)
        gpu_result = gpu_bound(u=gpu_field)

        cpu_ivec, gpu_ivec = saved_vectors
        gpu_ivec_on_host = gpu_ivec.get()[gpu_discr._gpu_volume_embedding(
            "quad")]
        ierr = cpu_ivec - gpu_ivec_on_host
        assert la.norm(ierr) < 5e-15

        gpu_result_on_host = gpu_discr.convert_volume(gpu_result, kind="numpy")
        err = cpu_result - gpu_result_on_host
        assert la.norm(err) < 2e-14

        cpu_discr.close()
        gpu_discr.close()