Example #1
0
    def sym_operator(self, w=None):
        from grudge.tools import count_subset
        fld_cnt = count_subset(self.get_eh_subset())
        if w is None:
            from grudge.symbolic import make_sym_vector
            w = make_sym_vector("w", fld_cnt + 2 * self.dimensions)

        from grudge.tools import join_fields
        return join_fields(MaxwellOperator.sym_operator(self, w[:fld_cnt]),
                           numpy.zeros((2 * self.dimensions, ),
                                       dtype=object)) + self.pml_local_op(w)
Example #2
0
def main(dims, write_output=True, order=4):
    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)
    actx = PyOpenCLArrayContext(queue)

    from meshmode.mesh.generation import generate_regular_rect_mesh
    mesh = generate_regular_rect_mesh(a=(0.0, ) * dims,
                                      b=(1.0, ) * dims,
                                      nelements_per_axis=(4, ) * dims)

    discr = DiscretizationCollection(actx, mesh, order=order)

    if 0:
        epsilon0 = 8.8541878176e-12  # C**2 / (N m**2)
        mu0 = 4 * np.pi * 1e-7  # N/A**2.
        epsilon = 1 * epsilon0
        mu = 1 * mu0
    else:
        epsilon = 1
        mu = 1

    from grudge.models.em import MaxwellOperator
    op = MaxwellOperator(epsilon, mu, flux_type=0.5, dimensions=dims)

    if dims == 3:
        sym_mode = get_rectangular_cavity_mode(1, (1, 2, 2))
        fields = bind(discr, sym_mode)(actx, t=0, epsilon=epsilon, mu=mu)
    else:
        sym_mode = get_rectangular_cavity_mode(1, (2, 3))
        fields = bind(discr, sym_mode)(actx, t=0)

    # FIXME
    #dt = op.estimate_rk4_timestep(discr, fields=fields)

    op.check_bc_coverage(mesh)

    # print(sym.pretty(op.sym_operator()))
    bound_op = bind(discr, op.sym_operator())

    def rhs(t, w):
        return bound_op(t=t, w=w)

    if mesh.dim == 2:
        dt = 0.004
    elif mesh.dim == 3:
        dt = 0.002

    dt_stepper = set_up_rk4("w", dt, fields, rhs)

    final_t = dt * STEPS
    nsteps = int(final_t / dt)

    print("dt=%g nsteps=%d" % (dt, nsteps))

    from grudge.shortcuts import make_visualizer
    vis = make_visualizer(discr)

    step = 0

    norm = bind(discr, sym.norm(2, sym.var("u")))

    from time import time
    t_last_step = time()

    e, h = op.split_eh(fields)

    if 1:
        vis.write_vtk_file("fld-cavities-%04d.vtu" % step, [
            ("e", e),
            ("h", h),
        ])

    for event in dt_stepper.run(t_end=final_t):
        if isinstance(event, dt_stepper.StateComputed):
            assert event.component_id == "w"

            step += 1

            print(step, event.t, norm(u=e[0]), norm(u=e[1]), norm(u=h[0]),
                  norm(u=h[1]),
                  time() - t_last_step)
            if step % 10 == 0:
                e, h = op.split_eh(event.state_component)
                vis.write_vtk_file("fld-cavities-%04d.vtu" % step, [
                    ("e", e),
                    ("h", h),
                ])
            t_last_step = time()
Example #3
0
def test_convergence_maxwell(ctx_factory, order):
    """Test whether 3D Maxwell's actually converges"""

    cl_ctx = ctx_factory()
    queue = cl.CommandQueue(cl_ctx)
    actx = PyOpenCLArrayContext(queue)

    from pytools.convergence import EOCRecorder
    eoc_rec = EOCRecorder()

    dims = 3
    ns = [4, 6, 8]
    for n in ns:
        from meshmode.mesh.generation import generate_regular_rect_mesh
        mesh = generate_regular_rect_mesh(a=(0.0, ) * dims,
                                          b=(1.0, ) * dims,
                                          n=(n, ) * dims)

        discr = DGDiscretizationWithBoundaries(actx, mesh, order=order)

        epsilon = 1
        mu = 1

        from grudge.models.em import get_rectangular_cavity_mode
        sym_mode = get_rectangular_cavity_mode(1, (1, 2, 2))

        analytic_sol = bind(discr, sym_mode)
        fields = analytic_sol(actx, t=0, epsilon=epsilon, mu=mu)

        from grudge.models.em import MaxwellOperator
        op = MaxwellOperator(epsilon, mu, flux_type=0.5, dimensions=dims)
        op.check_bc_coverage(mesh)
        bound_op = bind(discr, op.sym_operator())

        def rhs(t, w):
            return bound_op(t=t, w=w)

        dt = 0.002
        final_t = dt * 5
        nsteps = int(final_t / dt)

        from grudge.shortcuts import set_up_rk4
        dt_stepper = set_up_rk4("w", dt, fields, rhs)

        logger.info("dt %.5e nsteps %5d", dt, nsteps)

        norm = bind(discr, sym.norm(2, sym.var("u")))

        step = 0
        for event in dt_stepper.run(t_end=final_t):
            if isinstance(event, dt_stepper.StateComputed):
                assert event.component_id == "w"
                esc = event.state_component

                step += 1
                logger.debug("[%04d] t = %.5e", step, event.t)

        sol = analytic_sol(actx, mu=mu, epsilon=epsilon, t=step * dt)
        vals = [norm(u=(esc[i] - sol[i])) / norm(u=sol[i])
                for i in range(5)]  # noqa E501
        total_error = sum(vals)
        eoc_rec.add_data_point(1.0 / n, total_error)

    logger.info(
        "\n%s", eoc_rec.pretty_print(abscissa_label="h",
                                     error_label="L2 Error"))

    assert eoc_rec.order_estimate() > order
Example #4
0
def main(ctx_factory, dim=3, order=4, visualize=False):
    cl_ctx = ctx_factory()
    queue = cl.CommandQueue(cl_ctx)
    actx = PyOpenCLArrayContext(
        queue,
        allocator=cl_tools.MemoryPool(cl_tools.ImmediateAllocator(queue)),
        force_device_scalars=True,
    )

    from meshmode.mesh.generation import generate_regular_rect_mesh
    mesh = generate_regular_rect_mesh(a=(0.0, ) * dim,
                                      b=(1.0, ) * dim,
                                      nelements_per_axis=(4, ) * dim)

    dcoll = DiscretizationCollection(actx, mesh, order=order)

    if 0:
        epsilon0 = 8.8541878176e-12  # C**2 / (N m**2)
        mu0 = 4 * np.pi * 1e-7  # N/A**2.
        epsilon = 1 * epsilon0
        mu = 1 * mu0
    else:
        epsilon = 1
        mu = 1

    from grudge.models.em import MaxwellOperator

    maxwell_operator = MaxwellOperator(dcoll,
                                       epsilon,
                                       mu,
                                       flux_type=0.5,
                                       dimensions=dim)

    def cavity_mode(x, t=0):
        if dim == 3:
            return get_rectangular_cavity_mode(actx, x, t, 1, (1, 2, 2))
        else:
            return get_rectangular_cavity_mode(actx, x, t, 1, (2, 3))

    fields = cavity_mode(thaw(dcoll.nodes(), actx), t=0)

    maxwell_operator.check_bc_coverage(mesh)

    def rhs(t, w):
        return maxwell_operator.operator(t, w)

    dt = maxwell_operator.estimate_rk4_timestep(actx, dcoll, fields=fields)

    dt_stepper = set_up_rk4("w", dt, fields, rhs)

    target_steps = 60
    final_t = dt * target_steps
    nsteps = int(final_t / dt) + 1

    logger.info("dt = %g nsteps = %d", dt, nsteps)

    from grudge.shortcuts import make_visualizer
    vis = make_visualizer(dcoll)

    step = 0

    def norm(u):
        return op.norm(dcoll, u, 2)

    e, h = maxwell_operator.split_eh(fields)

    if visualize:
        vis.write_vtk_file(f"fld-cavities-{step:04d}.vtu", [
            ("e", e),
            ("h", h),
        ])

    for event in dt_stepper.run(t_end=final_t):
        if isinstance(event, dt_stepper.StateComputed):
            assert event.component_id == "w"

            step += 1
            e, h = maxwell_operator.split_eh(event.state_component)

            norm_e0 = actx.to_numpy(norm(u=e[0]))
            norm_e1 = actx.to_numpy(norm(u=e[1]))
            norm_h0 = actx.to_numpy(norm(u=h[0]))
            norm_h1 = actx.to_numpy(norm(u=h[1]))

            logger.info(
                "[%04d] t = %.5f |e0| = %.5e, |e1| = %.5e, |h0| = %.5e, |h1| = %.5e",
                step, event.t, norm_e0, norm_e1, norm_h0, norm_h1)

            if step % 10 == 0:
                if visualize:
                    vis.write_vtk_file(f"fld-cavities-{step:04d}.vtu", [
                        ("e", e),
                        ("h", h),
                    ])

            # NOTE: These are here to ensure the solution is bounded for the
            # time interval specified
            assert norm_e0 < 0.5
            assert norm_e1 < 0.5
            assert norm_h0 < 0.5
            assert norm_h1 < 0.5
Example #5
0
def main(write_output=True, allow_features=None):
    from grudge.timestep import RK4TimeStepper
    from grudge.mesh import make_ball_mesh, make_cylinder_mesh, make_box_mesh
    from grudge.visualization import \
            VtkVisualizer, \
            SiloVisualizer, \
            get_rank_partition
    from math import sqrt, pi

    from grudge.backends import guess_run_context
    rcon = guess_run_context(allow_features)

    epsilon0 = 8.8541878176e-12  # C**2 / (N m**2)
    mu0 = 4 * pi * 1e-7  # N/A**2.
    epsilon = 1 * epsilon0
    mu = 1 * mu0

    dims = 3

    if rcon.is_head_rank:
        if dims == 2:
            from grudge.mesh import make_rect_mesh
            mesh = make_rect_mesh(a=(-10.5, -1.5), b=(10.5, 1.5), max_area=0.1)
        elif dims == 3:
            from grudge.mesh import make_box_mesh
            mesh = make_box_mesh(a=(-10.5, -1.5, -1.5),
                                 b=(10.5, 1.5, 1.5),
                                 max_volume=0.1)

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

    #for order in [1,2,3,4,5,6]:
    discr = rcon.make_discretization(mesh_data, order=3)

    if write_output:
        vis = VtkVisualizer(discr, rcon, "dipole")

    from analytic_solutions import DipoleFarField, SphericalFieldAdapter
    from grudge.data import ITimeDependentGivenFunction

    sph_dipole = DipoleFarField(
        q=1,  #C
        d=1 / 39,
        omega=2 * pi * 1e8,
        epsilon=epsilon0,
        mu=mu0,
    )
    cart_dipole = SphericalFieldAdapter(sph_dipole)

    class PointDipoleSource(ITimeDependentGivenFunction):
        def __init__(self):
            from pyrticle.tools import CInfinityShapeFunction
            sf = CInfinityShapeFunction(0.1 * sph_dipole.wavelength,
                                        discr.dimensions)
            self.num_sf = discr.interpolate_volume_function(
                lambda x, el: sf(x))
            self.vol_0 = discr.volume_zeros()

        def volume_interpolant(self, t, discr):
            from grudge.tools import make_obj_array
            return make_obj_array([
                self.vol_0, self.vol_0,
                sph_dipole.source_modulation(t) * self.num_sf
            ])

    from grudge.mesh import BTAG_ALL, BTAG_NONE
    if dims == 2:
        from grudge.models.em import TMMaxwellOperator as MaxwellOperator
    else:
        from grudge.models.em import MaxwellOperator

    op = MaxwellOperator(
        epsilon,
        mu,
        flux_type=1,
        pec_tag=BTAG_NONE,
        absorb_tag=BTAG_ALL,
        current=PointDipoleSource(),
    )

    fields = op.assemble_eh(discr=discr)

    if rcon.is_head_rank:
        print("#elements=", len(mesh.elements))

    stepper = RK4TimeStepper()

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

    if write_output:
        log_file_name = "dipole.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 pytools.log import IntervalTimer
    vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
    logmgr.add_quantity(vis_timer)

    from grudge.log import EMFieldGetter, add_em_quantities
    field_getter = EMFieldGetter(discr, op, lambda: fields)
    add_em_quantities(logmgr, op, field_getter)

    from pytools.log import PushLogQuantity
    relerr_e_q = PushLogQuantity("relerr_e", "1",
                                 "Relative error in masked E-field")
    relerr_h_q = PushLogQuantity("relerr_h", "1",
                                 "Relative error in masked H-field")
    logmgr.add_quantity(relerr_e_q)
    logmgr.add_quantity(relerr_h_q)

    logmgr.add_watches([
        "step.max", "t_sim.max", ("W_field", "W_el+W_mag"), "t_step.max",
        "relerr_e", "relerr_h"
    ])

    if write_output:
        point_timeseries = [(open("b-x%d-vs-time.dat" % i,
                                  "w"), open("b-x%d-vs-time-true.dat" % i,
                                             "w"),
                             discr.get_point_evaluator(
                                 numpy.array([i, 0, 0][:dims],
                                             dtype=discr.default_scalar_type)))
                            for i in range(1, 5)]

    # timestep loop -------------------------------------------------------
    mask = discr.interpolate_volume_function(sph_dipole.far_field_mask)

    def apply_mask(field):
        from grudge.tools import log_shape
        ls = log_shape(field)
        result = discr.volume_empty(ls)
        from pytools import indices_in_shape
        for i in indices_in_shape(ls):
            result[i] = mask * field[i]

        return result

    rhs = op.bind(discr)

    t = 0
    try:
        from grudge.timestep import times_and_steps
        step_it = times_and_steps(
            final_time=1e-8,
            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 write_output and step % 10 == 0:
                sub_timer = vis_timer.start_sub_timer()
                e, h = op.split_eh(fields)
                sph_dipole.set_time(t)
                true_e, true_h = op.split_eh(
                    discr.interpolate_volume_function(cart_dipole))
                visf = vis.make_file("dipole-%04d" % step)

                mask_e = apply_mask(e)
                mask_h = apply_mask(h)
                mask_true_e = apply_mask(true_e)
                mask_true_h = apply_mask(true_h)

                from pyvisfile.silo import DB_VARTYPE_VECTOR
                vis.add_data(visf, [("e", e), ("h", h), ("true_e", true_e),
                                    ("true_h", true_h), ("mask_e", mask_e),
                                    ("mask_h", mask_h),
                                    ("mask_true_e", mask_true_e),
                                    ("mask_true_h", mask_true_h)],
                             time=t,
                             step=step)
                visf.close()
                sub_timer.stop().submit()

                from grudge.tools import relative_error
                relerr_e_q.push_value(
                    relative_error(discr.norm(mask_e - mask_true_e),
                                   discr.norm(mask_true_e)))
                relerr_h_q.push_value(
                    relative_error(discr.norm(mask_h - mask_true_h),
                                   discr.norm(mask_true_h)))

                if write_output:
                    for outf_num, outf_true, evaluator in point_timeseries:
                        for outf, ev_h in zip([outf_num, outf_true],
                                              [h, true_h]):
                            outf.write("%g\t%g\n" %
                                       (t, op.mu * evaluator(ev_h[1])))
                            outf.flush()

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

    finally:
        if write_output:
            vis.close()

        logmgr.save()
        discr.close()
Example #6
0
 def __init__(self, *args, **kwargs):
     self.add_decay = kwargs.pop("add_decay", True)
     MaxwellOperator.__init__(self, *args, **kwargs)
Example #7
0
 def bind(self, discr, coefficients):
     return MaxwellOperator.bind(self,
                                 discr,
                                 sigma=coefficients.sigma,
                                 sigma_prime=coefficients.sigma_prime,
                                 tau=coefficients.tau)
Example #8
0
def test_convergence_maxwell(actx_factory, order):
    """Test whether 3D Maxwell's actually converges"""

    actx = actx_factory()

    from pytools.convergence import EOCRecorder
    eoc_rec = EOCRecorder()

    dims = 3
    ns = [4, 6, 8]
    for n in ns:
        mesh = mgen.generate_regular_rect_mesh(a=(0.0, ) * dims,
                                               b=(1.0, ) * dims,
                                               nelements_per_axis=(n, ) * dims)

        dcoll = DiscretizationCollection(actx, mesh, order=order)

        epsilon = 1
        mu = 1

        from grudge.models.em import get_rectangular_cavity_mode

        def analytic_sol(x, t=0):
            return get_rectangular_cavity_mode(actx, x, t, 1, (1, 2, 2))

        nodes = thaw(dcoll.nodes(), actx)
        fields = analytic_sol(nodes, t=0)

        from grudge.models.em import MaxwellOperator

        maxwell_operator = MaxwellOperator(dcoll,
                                           epsilon,
                                           mu,
                                           flux_type=0.5,
                                           dimensions=dims)
        maxwell_operator.check_bc_coverage(mesh)

        def rhs(t, w):
            return maxwell_operator.operator(t, w)

        dt = maxwell_operator.estimate_rk4_timestep(actx, dcoll)
        final_t = dt * 5
        nsteps = int(final_t / dt)

        from grudge.shortcuts import set_up_rk4
        dt_stepper = set_up_rk4("w", dt, fields, rhs)

        logger.info("dt %.5e nsteps %5d", dt, nsteps)

        step = 0
        for event in dt_stepper.run(t_end=final_t):
            if isinstance(event, dt_stepper.StateComputed):
                assert event.component_id == "w"
                esc = event.state_component

                step += 1
                logger.debug("[%04d] t = %.5e", step, event.t)

        sol = analytic_sol(nodes, t=step * dt)
        total_error = op.norm(dcoll, esc - sol, 2)
        eoc_rec.add_data_point(1.0 / n, actx.to_numpy(total_error))

    logger.info(
        "\n%s", eoc_rec.pretty_print(abscissa_label="h",
                                     error_label="L2 Error"))

    assert eoc_rec.order_estimate() > order