Esempio n. 1
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()
Esempio n. 2
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()
Esempio n. 3
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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()
Esempio n. 4
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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()
Esempio n. 5
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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()
Esempio n. 6
0
def main(write_output=True,
         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()

    if rcon.is_head_rank:
        from hedge.mesh.reader.gmsh import generate_gmsh
        mesh = generate_gmsh(GEOMETRY,
                             2,
                             allow_internal_boundaries=True,
                             force_dimension=2)

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

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

    source_center = 0
    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
    op = StrongWaveOperator(
        -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="boundary",
        neumann_tag=TAG_NONE,
        radiation_tag=TAG_NONE,
        flux_type=flux_type_arg)

    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 = "wiggly.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)

    logmgr.add_watches(["step.max", "t_sim.max", "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", fields[0]),
                    ("v", fields[1:]),
                ],
                             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()
Esempio n. 7
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def main(write_output=True, 
        flux_type_arg="upwind", dtype=numpy.float64, debug=[]):
    from pytools.stopwatch import Job
    from math import sin, cos, pi, exp, sqrt

    from hedge.backends import guess_run_context
    rcon = guess_run_context()

    if rcon.is_head_rank:
        from hedge.mesh.reader.gmsh import generate_gmsh
        mesh = generate_gmsh(GEOMETRY, 2,
                allow_internal_boundaries=True)

        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, debug=debug,
            default_scalar_type=dtype)
    from hedge.timestep import RK4TimeStepper
    stepper = RK4TimeStepper(dtype=dtype)

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

    def source_u(x, el):
        return exp(-numpy.dot(x, x)*128)

    from hedge.models.wave import StrongWaveOperator
    from hedge.mesh import TAG_ALL, TAG_NONE
    from hedge.data import \
            make_tdep_given, \
            TimeHarmonicGivenFunction, \
            TimeIntervalGivenFunction

    op = StrongWaveOperator(-1, discr.dimensions, 
            source_f=TimeIntervalGivenFunction(
                TimeHarmonicGivenFunction(
                    make_tdep_given(source_u), omega=10),
                0, 1),
            dirichlet_tag="boundary",
            neumann_tag=TAG_NONE,
            radiation_tag=TAG_NONE,
            flux_type=flux_type_arg
            )

    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 = "wiggly.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)

    logmgr.add_watches(["step.max", "t_sim.max", "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", fields[0]),
                            ("v", fields[1:]), 
                        ],
                        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()
Esempio n. 8
0
def main(write_output=True,
        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()

    if rcon.is_head_rank:
        from hedge.mesh.reader.gmsh import generate_gmsh
        mesh = generate_gmsh(GEOMETRY, 2,
                allow_internal_boundaries=True,
                force_dimension=2)

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

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

    source_center = 0
    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
    op = StrongWaveOperator(-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="boundary",
            neumann_tag=TAG_NONE,
            radiation_tag=TAG_NONE,
            flux_type=flux_type_arg
            )

    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 = "wiggly.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)

    logmgr.add_watches(["step.max", "t_sim.max", "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", fields[0]),
                            ("v", fields[1:]),
                        ],
                        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()